commit 633409476b3f3d75e6013d504a3b761ec6e1ee2a
Author: Tobias Kurze <it@t-kurze.de>
Date:   Mon Aug 16 20:00:17 2021 +0200

    added geopy

diff --git a/.gitignore b/.gitignore
new file mode 100644
index 0000000..7675100
--- /dev/null
+++ b/.gitignore
@@ -0,0 +1,4 @@
+__pycache__/
+__pycache__/*
+besser_tanken/__pycache__
+merged.feather
\ No newline at end of file
diff --git a/.gitmodules b/.gitmodules
new file mode 100644
index 0000000..65f8575
--- /dev/null
+++ b/.gitmodules
@@ -0,0 +1,3 @@
+[submodule "tankerkoenig-data"]
+	path = tankerkoenig-data
+	url = https://tankerkoenig@dev.azure.com/tankerkoenig/tankerkoenig-data/_git/tankerkoenig-data
diff --git a/.idea/.gitignore b/.idea/.gitignore
new file mode 100644
index 0000000..26d3352
--- /dev/null
+++ b/.idea/.gitignore
@@ -0,0 +1,3 @@
+# Default ignored files
+/shelf/
+/workspace.xml
diff --git a/.idea/besser_tanken.iml b/.idea/besser_tanken.iml
new file mode 100644
index 0000000..d0876a7
--- /dev/null
+++ b/.idea/besser_tanken.iml
@@ -0,0 +1,8 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<module type="PYTHON_MODULE" version="4">
+  <component name="NewModuleRootManager">
+    <content url="file://$MODULE_DIR$" />
+    <orderEntry type="inheritedJdk" />
+    <orderEntry type="sourceFolder" forTests="false" />
+  </component>
+</module>
\ No newline at end of file
diff --git a/.idea/csv-plugin.xml b/.idea/csv-plugin.xml
new file mode 100644
index 0000000..b04f5cc
--- /dev/null
+++ b/.idea/csv-plugin.xml
@@ -0,0 +1,16 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="CsvFileAttributes">
+    <option name="attributeMap">
+      <map>
+        <entry key="/tankerkoenig-data/stations/2021/02/2021-02-07-stations.csv">
+          <value>
+            <Attribute>
+              <option name="separator" value="," />
+            </Attribute>
+          </value>
+        </entry>
+      </map>
+    </option>
+  </component>
+</project>
\ No newline at end of file
diff --git a/.idea/inspectionProfiles/Project_Default.xml b/.idea/inspectionProfiles/Project_Default.xml
new file mode 100644
index 0000000..ee88431
--- /dev/null
+++ b/.idea/inspectionProfiles/Project_Default.xml
@@ -0,0 +1,62 @@
+<component name="InspectionProjectProfileManager">
+  <profile version="1.0">
+    <option name="myName" value="Project Default" />
+    <inspection_tool class="PyPackageRequirementsInspection" enabled="true" level="WARNING" enabled_by_default="true">
+      <option name="ignoredPackages">
+        <value>
+          <list size="42">
+            <item index="0" class="java.lang.String" itemvalue="cffi" />
+            <item index="1" class="java.lang.String" itemvalue="numpy" />
+            <item index="2" class="java.lang.String" itemvalue="requests" />
+            <item index="3" class="java.lang.String" itemvalue="markupsafe" />
+            <item index="4" class="java.lang.String" itemvalue="pyrsistent" />
+            <item index="5" class="java.lang.String" itemvalue="certifi" />
+            <item index="6" class="java.lang.String" itemvalue="lxml" />
+            <item index="7" class="java.lang.String" itemvalue="urllib3" />
+            <item index="8" class="java.lang.String" itemvalue="itsdangerous" />
+            <item index="9" class="java.lang.String" itemvalue="jsonschema" />
+            <item index="10" class="java.lang.String" itemvalue="pynacl" />
+            <item index="11" class="java.lang.String" itemvalue="flask-restx" />
+            <item index="12" class="java.lang.String" itemvalue="werkzeug" />
+            <item index="13" class="java.lang.String" itemvalue="six" />
+            <item index="14" class="java.lang.String" itemvalue="aniso8601" />
+            <item index="15" class="java.lang.String" itemvalue="flask-jwt-extended" />
+            <item index="16" class="java.lang.String" itemvalue="cryptography" />
+            <item index="17" class="java.lang.String" itemvalue="click" />
+            <item index="18" class="java.lang.String" itemvalue="attrs" />
+            <item index="19" class="java.lang.String" itemvalue="bcrypt" />
+            <item index="20" class="java.lang.String" itemvalue="jinja2" />
+            <item index="21" class="java.lang.String" itemvalue="pandas" />
+            <item index="22" class="java.lang.String" itemvalue="paramiko" />
+            <item index="23" class="java.lang.String" itemvalue="user-agents" />
+            <item index="24" class="java.lang.String" itemvalue="flask" />
+            <item index="25" class="java.lang.String" itemvalue="pyjwt" />
+            <item index="26" class="java.lang.String" itemvalue="idna" />
+            <item index="27" class="java.lang.String" itemvalue="blinker" />
+            <item index="28" class="java.lang.String" itemvalue="flask-cors" />
+            <item index="29" class="java.lang.String" itemvalue="flask-httpauth" />
+            <item index="30" class="java.lang.String" itemvalue="flask-sitemap" />
+            <item index="31" class="java.lang.String" itemvalue="mariadb" />
+            <item index="32" class="java.lang.String" itemvalue="tqdm" />
+            <item index="33" class="java.lang.String" itemvalue="protobuf" />
+            <item index="34" class="java.lang.String" itemvalue="tabulate" />
+            <item index="35" class="java.lang.String" itemvalue="pytimeparse" />
+            <item index="36" class="java.lang.String" itemvalue="sqlite3-to-mysql" />
+            <item index="37" class="java.lang.String" itemvalue="packaging" />
+            <item index="38" class="java.lang.String" itemvalue="mysql-connector-python" />
+            <item index="39" class="java.lang.String" itemvalue="sqlalchemy" />
+            <item index="40" class="java.lang.String" itemvalue="simplejson" />
+            <item index="41" class="java.lang.String" itemvalue="unittest" />
+          </list>
+        </value>
+      </option>
+    </inspection_tool>
+    <inspection_tool class="PyPep8Inspection" enabled="true" level="WEAK WARNING" enabled_by_default="true">
+      <option name="ignoredErrors">
+        <list>
+          <option value="E402" />
+        </list>
+      </option>
+    </inspection_tool>
+  </profile>
+</component>
\ No newline at end of file
diff --git a/.idea/inspectionProfiles/profiles_settings.xml b/.idea/inspectionProfiles/profiles_settings.xml
new file mode 100644
index 0000000..105ce2d
--- /dev/null
+++ b/.idea/inspectionProfiles/profiles_settings.xml
@@ -0,0 +1,6 @@
+<component name="InspectionProjectProfileManager">
+  <settings>
+    <option name="USE_PROJECT_PROFILE" value="false" />
+    <version value="1.0" />
+  </settings>
+</component>
\ No newline at end of file
diff --git a/.idea/misc.xml b/.idea/misc.xml
new file mode 100644
index 0000000..7d35dc4
--- /dev/null
+++ b/.idea/misc.xml
@@ -0,0 +1,4 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="ProjectRootManager" version="2" project-jdk-name="Poetry (besser_tanken)" project-jdk-type="Python SDK" />
+</project>
\ No newline at end of file
diff --git a/.idea/modules.xml b/.idea/modules.xml
new file mode 100644
index 0000000..8b8d2b1
--- /dev/null
+++ b/.idea/modules.xml
@@ -0,0 +1,8 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="ProjectModuleManager">
+    <modules>
+      <module fileurl="file://$PROJECT_DIR$/.idea/besser_tanken.iml" filepath="$PROJECT_DIR$/.idea/besser_tanken.iml" />
+    </modules>
+  </component>
+</project>
\ No newline at end of file
diff --git a/.idea/vcs.xml b/.idea/vcs.xml
new file mode 100644
index 0000000..2b95f36
--- /dev/null
+++ b/.idea/vcs.xml
@@ -0,0 +1,7 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="VcsDirectoryMappings">
+    <mapping directory="$PROJECT_DIR$" vcs="Git" />
+    <mapping directory="$PROJECT_DIR$/tankerkoenig-data" vcs="Git" />
+  </component>
+</project>
\ No newline at end of file
diff --git a/.ipynb_checkpoints/feather_test-checkpoint.ipynb b/.ipynb_checkpoints/feather_test-checkpoint.ipynb
new file mode 100644
index 0000000..64aa28e
--- /dev/null
+++ b/.ipynb_checkpoints/feather_test-checkpoint.ipynb
@@ -0,0 +1,1948 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "abc85460",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import os\n",
+    "import matplotlib.pyplot as plt\n",
+    "import seaborn as sns\n",
+    "import pandas as pd\n",
+    "import earthpy as et\n",
+    "import numpy as np\n",
+    "import feather\n",
+    "from besser_tanken.config import stations_dir\n",
+    "from besser_tanken.data_loader import load_prices_from, load_stations\n",
+    "from besser_tanken.data_tools import group_prices"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "1b7ebdd6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Handle date time conversions between pandas and matplotlib\n",
+    "from pandas.plotting import register_matplotlib_converters\n",
+    "register_matplotlib_converters()\n",
+    "\n",
+    "# Use white grid plot background from seaborn\n",
+    "sns.set(font_scale=1.5, style=\"whitegrid\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "c1384e22",
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "NameError",
+     "evalue": "name 'feather' is not defined",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
+      "\u001b[0;32m/tmp/ipykernel_277834/1413196281.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mdf\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfeather\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread_dataframe\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34mf\"{stations_dir}/2021/01/2021-01-01-stations.csv\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
+      "\u001b[0;31mNameError\u001b[0m: name 'feather' is not defined"
+     ]
+    }
+   ],
+   "source": [
+    "df = feather.read_dataframe(f\"{stations_dir}/2021/01/2021-01-01-stations.csv\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "4d1b7811",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2021-08-12 14:54:15.450 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-02-prices.csv\n",
+      "2021-08-12 14:54:15.450 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-06-prices.csv\n",
+      "2021-08-12 14:54:15.450 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-07-prices.csv\n",
+      "2021-08-12 14:54:15.451 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-05-prices.csv\n",
+      "2021-08-12 14:54:15.451 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-01-prices.csv\n",
+      "2021-08-12 14:54:15.451 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-03-prices.csv\n",
+      "2021-08-12 14:54:15.452 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-04-prices.csv\n",
+      "2021-08-12 14:54:15.664 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-08-prices.csv\n",
+      "2021-08-12 14:54:15.671 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-09-prices.csv\n",
+      "2021-08-12 14:54:15.769 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-11-prices.csv\n",
+      "2021-08-12 14:54:15.917 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-15-prices.csv\n",
+      "2021-08-12 14:54:15.929 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-10-prices.csv\n",
+      "2021-08-12 14:54:15.936 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-13-prices.csv\n",
+      "2021-08-12 14:54:15.964 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-14-prices.csv\n",
+      "2021-08-12 14:54:16.341 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-12-prices.csv\n",
+      "2021-08-12 14:54:16.405 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-16-prices.csv\n",
+      "2021-08-12 14:54:30.998 | INFO     | besser_tanken.data_loader:load_prices:70 - got 267833 prices\n",
+      "2021-08-12 14:54:31.918 | INFO     | besser_tanken.data_loader:load_prices:70 - got 256623 prices\n",
+      "2021-08-12 14:54:31.952 | INFO     | besser_tanken.data_loader:load_prices:70 - got 267574 prices\n",
+      "2021-08-12 14:54:32.854 | INFO     | besser_tanken.data_loader:load_prices:70 - got 287410 prices\n",
+      "2021-08-12 14:54:33.028 | INFO     | besser_tanken.data_loader:load_prices:70 - got 297538 prices\n",
+      "2021-08-12 14:54:33.040 | INFO     | besser_tanken.data_loader:load_prices:70 - got 290865 prices\n",
+      "2021-08-12 14:54:33.231 | INFO     | besser_tanken.data_loader:load_prices:70 - got 280439 prices\n",
+      "2021-08-12 14:54:33.661 | INFO     | besser_tanken.data_loader:load_prices:70 - got 273987 prices\n",
+      "2021-08-12 14:54:33.953 | INFO     | besser_tanken.data_loader:load_prices:70 - got 285397 prices\n",
+      "2021-08-12 14:54:34.125 | INFO     | besser_tanken.data_loader:load_prices:70 - got 291143 prices\n",
+      "2021-08-12 14:54:34.326 | INFO     | besser_tanken.data_loader:load_prices:70 - got 283593 prices\n",
+      "2021-08-12 14:54:34.506 | INFO     | besser_tanken.data_loader:load_prices:70 - got 283024 prices\n",
+      "2021-08-12 14:54:34.567 | INFO     | besser_tanken.data_loader:load_prices:70 - got 294324 prices\n",
+      "2021-08-12 14:54:34.613 | INFO     | besser_tanken.data_loader:load_prices:70 - got 297991 prices\n",
+      "2021-08-12 14:54:34.672 | INFO     | besser_tanken.data_loader:load_prices:70 - got 299993 prices\n",
+      "2021-08-12 14:54:34.965 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-17-prices.csv\n",
+      "2021-08-12 14:54:35.315 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-18-prices.csv\n",
+      "2021-08-12 14:54:35.322 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-19-prices.csv\n",
+      "2021-08-12 14:54:35.537 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-20-prices.csv\n",
+      "2021-08-12 14:54:35.551 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-21-prices.csv\n",
+      "2021-08-12 14:54:35.828 | INFO     | besser_tanken.data_loader:load_prices:70 - got 295394 prices\n",
+      "2021-08-12 14:54:35.902 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-22-prices.csv\n",
+      "2021-08-12 14:54:36.065 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-23-prices.csv\n",
+      "2021-08-12 14:54:36.394 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-24-prices.csv\n",
+      "2021-08-12 14:54:36.574 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-26-prices.csv\n",
+      "2021-08-12 14:54:36.956 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-25-prices.csv\n",
+      "2021-08-12 14:54:37.181 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-27-prices.csv\n",
+      "2021-08-12 14:54:37.269 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-28-prices.csv\n",
+      "2021-08-12 14:54:37.825 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-01-prices.csv\n",
+      "2021-08-12 14:54:38.064 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-29-prices.csv\n",
+      "2021-08-12 14:54:38.189 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-30-prices.csv\n",
+      "2021-08-12 14:54:40.552 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-02-prices.csv\n",
+      "2021-08-12 14:54:48.819 | INFO     | besser_tanken.data_loader:load_prices:70 - got 254847 prices\n",
+      "2021-08-12 14:54:49.651 | INFO     | besser_tanken.data_loader:load_prices:70 - got 259956 prices\n",
+      "2021-08-12 14:54:50.729 | INFO     | besser_tanken.data_loader:load_prices:70 - got 304068 prices\n",
+      "2021-08-12 14:54:51.511 | INFO     | besser_tanken.data_loader:load_prices:70 - got 302116 prices\n",
+      "2021-08-12 14:54:52.112 | INFO     | besser_tanken.data_loader:load_prices:70 - got 274800 prices\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2021-08-12 14:54:52.657 | INFO     | besser_tanken.data_loader:load_prices:70 - got 268463 prices\n",
+      "2021-08-12 14:54:52.745 | INFO     | besser_tanken.data_loader:load_prices:70 - got 300758 prices\n",
+      "2021-08-12 14:54:52.782 | INFO     | besser_tanken.data_loader:load_prices:70 - got 279674 prices\n",
+      "2021-08-12 14:54:52.811 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-03-prices.csv\n",
+      "2021-08-12 14:54:53.726 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-05-prices.csv\n",
+      "2021-08-12 14:54:54.025 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-04-prices.csv\n",
+      "2021-08-12 14:54:54.126 | INFO     | besser_tanken.data_loader:load_prices:70 - got 295627 prices\n",
+      "2021-08-12 14:54:54.546 | INFO     | besser_tanken.data_loader:load_prices:70 - got 281698 prices\n",
+      "2021-08-12 14:54:54.772 | INFO     | besser_tanken.data_loader:load_prices:70 - got 295088 prices\n",
+      "2021-08-12 14:54:55.054 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-06-prices.csv\n",
+      "2021-08-12 14:54:55.235 | INFO     | besser_tanken.data_loader:load_prices:70 - got 272618 prices\n",
+      "2021-08-12 14:54:55.821 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-07-prices.csv\n",
+      "2021-08-12 14:54:55.924 | INFO     | besser_tanken.data_loader:load_prices:70 - got 291122 prices\n",
+      "2021-08-12 14:54:55.974 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-08-prices.csv\n",
+      "2021-08-12 14:54:56.432 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-09-prices.csv\n",
+      "2021-08-12 14:54:56.479 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-10-prices.csv\n",
+      "2021-08-12 14:54:56.743 | INFO     | besser_tanken.data_loader:load_prices:70 - got 293853 prices\n",
+      "2021-08-12 14:54:57.040 | INFO     | besser_tanken.data_loader:load_prices:70 - got 294534 prices\n",
+      "2021-08-12 14:54:57.117 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-11-prices.csv\n",
+      "2021-08-12 14:54:57.742 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-12-prices.csv\n",
+      "2021-08-12 14:54:57.894 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-13-prices.csv\n",
+      "2021-08-12 14:54:57.959 | INFO     | besser_tanken.data_loader:load_prices:70 - got 304781 prices\n",
+      "2021-08-12 14:54:58.335 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-14-prices.csv\n",
+      "2021-08-12 14:54:58.351 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-15-prices.csv\n",
+      "2021-08-12 14:55:01.215 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-16-prices.csv\n",
+      "2021-08-12 14:55:01.553 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-17-prices.csv\n",
+      "2021-08-12 14:55:02.137 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-18-prices.csv\n",
+      "2021-08-12 14:55:06.184 | INFO     | besser_tanken.data_loader:load_prices:70 - got 266473 prices\n",
+      "2021-08-12 14:55:06.439 | INFO     | besser_tanken.data_loader:load_prices:70 - got 296438 prices\n",
+      "2021-08-12 14:55:09.035 | INFO     | besser_tanken.data_loader:load_prices:70 - got 295515 prices\n",
+      "2021-08-12 14:55:09.500 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-19-prices.csv\n",
+      "2021-08-12 14:55:10.830 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-20-prices.csv\n",
+      "2021-08-12 14:55:11.346 | INFO     | besser_tanken.data_loader:load_prices:70 - got 268331 prices\n",
+      "2021-08-12 14:55:11.614 | INFO     | besser_tanken.data_loader:load_prices:70 - got 295646 prices\n",
+      "2021-08-12 14:55:12.213 | INFO     | besser_tanken.data_loader:load_prices:70 - got 295127 prices\n",
+      "2021-08-12 14:55:13.951 | INFO     | besser_tanken.data_loader:load_prices:70 - got 295290 prices\n",
+      "2021-08-12 14:55:14.032 | INFO     | besser_tanken.data_loader:load_prices:70 - got 291843 prices\n",
+      "2021-08-12 14:55:14.208 | INFO     | besser_tanken.data_loader:load_prices:70 - got 283770 prices\n",
+      "2021-08-12 14:55:14.241 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-21-prices.csv\n",
+      "2021-08-12 14:55:14.549 | INFO     | besser_tanken.data_loader:load_prices:70 - got 291819 prices\n",
+      "2021-08-12 14:55:15.975 | INFO     | besser_tanken.data_loader:load_prices:70 - got 296929 prices\n",
+      "2021-08-12 14:55:16.400 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-22-prices.csv\n",
+      "2021-08-12 14:55:16.414 | INFO     | besser_tanken.data_loader:load_prices:70 - got 274498 prices\n",
+      "2021-08-12 14:55:16.442 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-23-prices.csv\n",
+      "2021-08-12 14:55:16.458 | INFO     | besser_tanken.data_loader:load_prices:70 - got 295861 prices\n",
+      "2021-08-12 14:55:16.458 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-25-prices.csv\n",
+      "2021-08-12 14:55:16.569 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-24-prices.csv\n",
+      "2021-08-12 14:55:16.752 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-26-prices.csv\n",
+      "2021-08-12 14:55:16.937 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-27-prices.csv\n",
+      "2021-08-12 14:55:17.835 | INFO     | besser_tanken.data_loader:load_prices:70 - got 285905 prices\n",
+      "2021-08-12 14:55:17.961 | INFO     | besser_tanken.data_loader:load_prices:70 - got 267248 prices\n",
+      "2021-08-12 14:55:18.088 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-28-prices.csv\n",
+      "2021-08-12 14:55:18.588 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-29-prices.csv\n",
+      "2021-08-12 14:55:18.915 | INFO     | besser_tanken.data_loader:load_prices:70 - got 298455 prices\n",
+      "2021-08-12 14:55:19.720 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-31-prices.csv\n",
+      "2021-08-12 14:55:20.110 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-30-prices.csv\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2021-08-12 14:55:21.651 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-02-prices.csv\n",
+      "2021-08-12 14:55:21.961 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-01-prices.csv\n",
+      "2021-08-12 14:55:23.426 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-03-prices.csv\n",
+      "2021-08-12 14:55:24.026 | INFO     | besser_tanken.data_loader:load_prices:70 - got 282465 prices\n",
+      "2021-08-12 14:55:24.126 | INFO     | besser_tanken.data_loader:load_prices:70 - got 272819 prices\n",
+      "2021-08-12 14:55:28.195 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-04-prices.csv\n",
+      "2021-08-12 14:55:28.421 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-05-prices.csv\n",
+      "2021-08-12 14:55:30.258 | INFO     | besser_tanken.data_loader:load_prices:70 - got 297022 prices\n",
+      "2021-08-12 14:55:30.904 | INFO     | besser_tanken.data_loader:load_prices:70 - got 270551 prices\n",
+      "2021-08-12 14:55:31.102 | INFO     | besser_tanken.data_loader:load_prices:70 - got 299097 prices\n",
+      "2021-08-12 14:55:31.142 | INFO     | besser_tanken.data_loader:load_prices:70 - got 265410 prices\n",
+      "2021-08-12 14:55:31.820 | INFO     | besser_tanken.data_loader:load_prices:70 - got 271525 prices\n",
+      "2021-08-12 14:55:32.881 | INFO     | besser_tanken.data_loader:load_prices:70 - got 305490 prices\n",
+      "2021-08-12 14:55:33.143 | INFO     | besser_tanken.data_loader:load_prices:70 - got 257397 prices\n",
+      "2021-08-12 14:55:34.151 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-07-prices.csv\n",
+      "2021-08-12 14:55:34.214 | INFO     | besser_tanken.data_loader:load_prices:70 - got 278182 prices\n",
+      "2021-08-12 14:55:34.437 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-06-prices.csv\n",
+      "2021-08-12 14:55:34.438 | INFO     | besser_tanken.data_loader:load_prices:70 - got 285401 prices\n",
+      "2021-08-12 14:55:34.879 | INFO     | besser_tanken.data_loader:load_prices:70 - got 274174 prices\n",
+      "2021-08-12 14:55:34.918 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-08-prices.csv\n",
+      "2021-08-12 14:55:35.307 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-09-prices.csv\n",
+      "2021-08-12 14:55:35.578 | INFO     | besser_tanken.data_loader:load_prices:70 - got 244857 prices\n",
+      "2021-08-12 14:55:35.640 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-10-prices.csv\n",
+      "2021-08-12 14:55:36.181 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-12-prices.csv\n",
+      "2021-08-12 14:55:36.321 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-11-prices.csv\n",
+      "2021-08-12 14:55:36.518 | INFO     | besser_tanken.data_loader:load_prices:70 - got 260542 prices\n",
+      "2021-08-12 14:55:36.796 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-13-prices.csv\n",
+      "2021-08-12 14:55:36.820 | INFO     | besser_tanken.data_loader:load_prices:70 - got 279312 prices\n",
+      "2021-08-12 14:55:37.396 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-14-prices.csv\n",
+      "2021-08-12 14:55:37.540 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-15-prices.csv\n",
+      "2021-08-12 14:55:38.592 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-16-prices.csv\n",
+      "2021-08-12 14:55:39.974 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-17-prices.csv\n",
+      "2021-08-12 14:55:40.192 | INFO     | besser_tanken.data_loader:load_prices:70 - got 257142 prices\n",
+      "2021-08-12 14:55:41.408 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-18-prices.csv\n",
+      "2021-08-12 14:55:42.548 | INFO     | besser_tanken.data_loader:load_prices:70 - got 279636 prices\n",
+      "2021-08-12 14:55:43.937 | INFO     | besser_tanken.data_loader:load_prices:70 - got 294651 prices\n",
+      "2021-08-12 14:55:44.635 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-19-prices.csv\n",
+      "2021-08-12 14:55:46.691 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-20-prices.csv\n",
+      "2021-08-12 14:55:47.484 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-21-prices.csv\n",
+      "2021-08-12 14:55:49.553 | INFO     | besser_tanken.data_loader:load_prices:70 - got 291819 prices\n",
+      "2021-08-12 14:55:49.555 | INFO     | besser_tanken.data_loader:load_prices:70 - got 293143 prices\n",
+      "2021-08-12 14:55:49.943 | INFO     | besser_tanken.data_loader:load_prices:70 - got 278188 prices\n",
+      "2021-08-12 14:55:50.902 | INFO     | besser_tanken.data_loader:load_prices:70 - got 267935 prices\n",
+      "2021-08-12 14:55:51.096 | INFO     | besser_tanken.data_loader:load_prices:70 - got 291029 prices\n",
+      "2021-08-12 14:55:52.656 | INFO     | besser_tanken.data_loader:load_prices:70 - got 295469 prices\n",
+      "2021-08-12 14:55:53.060 | INFO     | besser_tanken.data_loader:load_prices:70 - got 267150 prices\n",
+      "2021-08-12 14:55:53.243 | INFO     | besser_tanken.data_loader:load_prices:70 - got 291697 prices\n",
+      "2021-08-12 14:55:53.299 | INFO     | besser_tanken.data_loader:load_prices:70 - got 277281 prices\n",
+      "2021-08-12 14:55:53.423 | INFO     | besser_tanken.data_loader:load_prices:70 - got 293111 prices\n",
+      "2021-08-12 14:55:53.451 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-22-prices.csv\n",
+      "2021-08-12 14:55:53.654 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-25-prices.csv\n",
+      "2021-08-12 14:55:53.679 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-24-prices.csv\n",
+      "2021-08-12 14:55:53.845 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-23-prices.csv\n",
+      "2021-08-12 14:55:53.857 | INFO     | besser_tanken.data_loader:load_prices:70 - got 296425 prices\n",
+      "2021-08-12 14:55:53.976 | INFO     | besser_tanken.data_loader:load_prices:70 - got 294834 prices\n",
+      "2021-08-12 14:55:55.681 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-26-prices.csv\n",
+      "2021-08-12 14:55:56.449 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-28-prices.csv\n",
+      "2021-08-12 14:55:56.624 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-27-prices.csv\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2021-08-12 14:55:56.718 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-29-prices.csv\n",
+      "2021-08-12 14:55:56.920 | INFO     | besser_tanken.data_loader:load_prices:70 - got 286600 prices\n",
+      "2021-08-12 14:55:57.612 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-30-prices.csv\n",
+      "2021-08-12 14:55:58.799 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-31-prices.csv\n",
+      "2021-08-12 14:55:59.506 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-01-prices.csv\n",
+      "2021-08-12 14:55:59.625 | INFO     | besser_tanken.data_loader:load_prices:70 - got 292261 prices\n",
+      "2021-08-12 14:55:59.861 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-02-prices.csv\n",
+      "2021-08-12 14:56:00.676 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-03-prices.csv\n",
+      "2021-08-12 14:56:01.950 | INFO     | besser_tanken.data_loader:load_prices:70 - got 292338 prices\n",
+      "2021-08-12 14:56:03.371 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-04-prices.csv\n",
+      "2021-08-12 14:56:03.849 | INFO     | besser_tanken.data_loader:load_prices:70 - got 288069 prices\n",
+      "2021-08-12 14:56:06.027 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-05-prices.csv\n",
+      "2021-08-12 14:56:07.359 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-06-prices.csv\n",
+      "2021-08-12 14:56:10.541 | INFO     | besser_tanken.data_loader:load_prices:70 - got 265136 prices\n",
+      "2021-08-12 14:56:10.717 | INFO     | besser_tanken.data_loader:load_prices:70 - got 300483 prices\n",
+      "2021-08-12 14:56:10.784 | INFO     | besser_tanken.data_loader:load_prices:70 - got 258369 prices\n",
+      "2021-08-12 14:56:12.295 | INFO     | besser_tanken.data_loader:load_prices:70 - got 295133 prices\n",
+      "2021-08-12 14:56:13.796 | INFO     | besser_tanken.data_loader:load_prices:70 - got 292843 prices\n",
+      "2021-08-12 14:56:14.298 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-07-prices.csv\n",
+      "2021-08-12 14:56:14.627 | INFO     | besser_tanken.data_loader:load_prices:70 - got 281149 prices\n",
+      "2021-08-12 14:56:14.962 | INFO     | besser_tanken.data_loader:load_prices:70 - got 290998 prices\n",
+      "2021-08-12 14:56:15.006 | INFO     | besser_tanken.data_loader:load_prices:70 - got 295802 prices\n",
+      "2021-08-12 14:56:15.415 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-08-prices.csv\n",
+      "2021-08-12 14:56:15.538 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-09-prices.csv\n",
+      "2021-08-12 14:56:15.770 | INFO     | besser_tanken.data_loader:load_prices:70 - got 301491 prices\n",
+      "2021-08-12 14:56:16.567 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-10-prices.csv\n",
+      "2021-08-12 14:56:17.202 | INFO     | besser_tanken.data_loader:load_prices:70 - got 269334 prices\n",
+      "2021-08-12 14:56:17.330 | INFO     | besser_tanken.data_loader:load_prices:70 - got 296274 prices\n",
+      "2021-08-12 14:56:17.720 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-12-prices.csv\n",
+      "2021-08-12 14:56:17.887 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-13-prices.csv\n",
+      "2021-08-12 14:56:17.958 | INFO     | besser_tanken.data_loader:load_prices:70 - got 293349 prices\n",
+      "2021-08-12 14:56:18.057 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-11-prices.csv\n",
+      "2021-08-12 14:56:18.137 | INFO     | besser_tanken.data_loader:load_prices:70 - got 290786 prices\n",
+      "2021-08-12 14:56:18.451 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-14-prices.csv\n",
+      "2021-08-12 14:56:19.732 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-16-prices.csv\n",
+      "2021-08-12 14:56:19.751 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-15-prices.csv\n",
+      "2021-08-12 14:56:20.259 | INFO     | besser_tanken.data_loader:load_prices:70 - got 285679 prices\n",
+      "2021-08-12 14:56:21.224 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-17-prices.csv\n",
+      "2021-08-12 14:56:22.485 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-18-prices.csv\n",
+      "2021-08-12 14:56:23.505 | INFO     | besser_tanken.data_loader:load_prices:70 - got 266559 prices\n",
+      "2021-08-12 14:56:23.601 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-19-prices.csv\n",
+      "2021-08-12 14:56:24.136 | INFO     | besser_tanken.data_loader:load_prices:70 - got 320138 prices\n",
+      "2021-08-12 14:56:24.419 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-20-prices.csv\n",
+      "2021-08-12 14:56:27.567 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-21-prices.csv\n",
+      "2021-08-12 14:56:28.468 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-22-prices.csv\n",
+      "2021-08-12 14:56:30.811 | INFO     | besser_tanken.data_loader:load_prices:70 - got 285353 prices\n",
+      "2021-08-12 14:56:31.603 | INFO     | besser_tanken.data_loader:load_prices:70 - got 312960 prices\n",
+      "2021-08-12 14:56:32.009 | INFO     | besser_tanken.data_loader:load_prices:70 - got 291564 prices\n",
+      "2021-08-12 14:56:33.464 | INFO     | besser_tanken.data_loader:load_prices:70 - got 303852 prices\n",
+      "2021-08-12 14:56:34.063 | INFO     | besser_tanken.data_loader:load_prices:70 - got 299186 prices\n",
+      "2021-08-12 14:56:35.077 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-24-prices.csv\n",
+      "2021-08-12 14:56:35.160 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-23-prices.csv\n",
+      "2021-08-12 14:56:35.470 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-25-prices.csv\n",
+      "2021-08-12 14:56:37.739 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-27-prices.csv\n",
+      "2021-08-12 14:56:37.931 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-26-prices.csv\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2021-08-12 14:56:38.078 | INFO     | besser_tanken.data_loader:load_prices:70 - got 322374 prices\n",
+      "2021-08-12 14:56:38.118 | INFO     | besser_tanken.data_loader:load_prices:70 - got 280736 prices\n",
+      "2021-08-12 14:56:38.265 | INFO     | besser_tanken.data_loader:load_prices:70 - got 308485 prices\n",
+      "2021-08-12 14:56:38.529 | INFO     | besser_tanken.data_loader:load_prices:70 - got 305624 prices\n",
+      "2021-08-12 14:56:39.474 | INFO     | besser_tanken.data_loader:load_prices:70 - got 299061 prices\n",
+      "2021-08-12 14:56:40.019 | INFO     | besser_tanken.data_loader:load_prices:70 - got 286031 prices\n",
+      "2021-08-12 14:56:40.725 | INFO     | besser_tanken.data_loader:load_prices:70 - got 297799 prices\n",
+      "2021-08-12 14:56:42.114 | INFO     | besser_tanken.data_loader:load_prices:70 - got 299713 prices\n",
+      "2021-08-12 14:56:42.177 | INFO     | besser_tanken.data_loader:load_prices:70 - got 302117 prices\n",
+      "2021-08-12 14:56:42.242 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-03-prices.csv\n",
+      "2021-08-12 14:56:44.122 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-28-prices.csv\n",
+      "2021-08-12 14:56:44.294 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-02-prices.csv\n",
+      "2021-08-12 14:56:44.355 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-04-prices.csv\n",
+      "2021-08-12 14:56:44.421 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-01-prices.csv\n",
+      "2021-08-12 14:56:44.595 | INFO     | besser_tanken.data_loader:load_prices:70 - got 251823 prices\n",
+      "2021-08-12 14:56:45.036 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-05-prices.csv\n",
+      "2021-08-12 14:56:46.790 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-07-prices.csv\n",
+      "2021-08-12 14:56:46.835 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-06-prices.csv\n",
+      "2021-08-12 14:56:46.856 | INFO     | besser_tanken.data_loader:load_prices:70 - got 302751 prices\n",
+      "2021-08-12 14:56:47.949 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-08-prices.csv\n",
+      "2021-08-12 14:56:50.465 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-09-prices.csv\n",
+      "2021-08-12 14:56:52.903 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-10-prices.csv\n",
+      "2021-08-12 14:56:53.022 | INFO     | besser_tanken.data_loader:load_prices:70 - got 281441 prices\n",
+      "2021-08-12 14:56:53.755 | INFO     | besser_tanken.data_loader:load_prices:70 - got 298778 prices\n",
+      "2021-08-12 14:56:54.436 | INFO     | besser_tanken.data_loader:load_prices:70 - got 292382 prices\n",
+      "2021-08-12 14:56:54.476 | INFO     | besser_tanken.data_loader:load_prices:70 - got 299860 prices\n",
+      "2021-08-12 14:56:55.540 | INFO     | besser_tanken.data_loader:load_prices:70 - got 301929 prices\n",
+      "2021-08-12 14:56:57.613 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-11-prices.csv\n",
+      "2021-08-12 14:56:58.301 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-14-prices.csv\n",
+      "2021-08-12 14:56:58.459 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-12-prices.csv\n",
+      "2021-08-12 14:56:58.642 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-13-prices.csv\n",
+      "2021-08-12 14:56:59.772 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-15-prices.csv\n",
+      "2021-08-12 14:57:01.157 | INFO     | besser_tanken.data_loader:load_prices:70 - got 267923 prices\n",
+      "2021-08-12 14:57:02.583 | INFO     | besser_tanken.data_loader:load_prices:70 - got 314743 prices\n",
+      "2021-08-12 14:57:02.933 | INFO     | besser_tanken.data_loader:load_prices:70 - got 298276 prices\n",
+      "2021-08-12 14:57:03.389 | INFO     | besser_tanken.data_loader:load_prices:70 - got 300006 prices\n",
+      "2021-08-12 14:57:04.820 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-16-prices.csv\n",
+      "2021-08-12 14:57:05.572 | INFO     | besser_tanken.data_loader:load_prices:70 - got 270202 prices\n",
+      "2021-08-12 14:57:05.958 | INFO     | besser_tanken.data_loader:load_prices:70 - got 294123 prices\n",
+      "2021-08-12 14:57:06.661 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-18-prices.csv\n",
+      "2021-08-12 14:57:06.743 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-19-prices.csv\n",
+      "2021-08-12 14:57:06.820 | INFO     | besser_tanken.data_loader:load_prices:70 - got 287711 prices\n",
+      "2021-08-12 14:57:06.909 | INFO     | besser_tanken.data_loader:load_prices:70 - got 297457 prices\n",
+      "2021-08-12 14:57:07.578 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-17-prices.csv\n",
+      "2021-08-12 14:57:08.018 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-20-prices.csv\n",
+      "2021-08-12 14:57:09.147 | INFO     | besser_tanken.data_loader:load_prices:70 - got 299724 prices\n",
+      "2021-08-12 14:57:09.237 | INFO     | besser_tanken.data_loader:load_prices:70 - got 300856 prices\n",
+      "2021-08-12 14:57:09.985 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-21-prices.csv\n",
+      "2021-08-12 14:57:10.950 | INFO     | besser_tanken.data_loader:load_prices:70 - got 270065 prices\n",
+      "2021-08-12 14:57:11.247 | INFO     | besser_tanken.data_loader:load_prices:70 - got 303379 prices\n",
+      "2021-08-12 14:57:11.354 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-22-prices.csv\n",
+      "2021-08-12 14:57:11.770 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-23-prices.csv\n",
+      "2021-08-12 14:57:12.733 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-25-prices.csv\n",
+      "2021-08-12 14:57:13.299 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-24-prices.csv\n",
+      "2021-08-12 14:57:14.402 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-26-prices.csv\n",
+      "2021-08-12 14:57:15.460 | INFO     | besser_tanken.data_loader:load_prices:70 - got 274465 prices\n",
+      "2021-08-12 14:57:15.595 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-27-prices.csv\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2021-08-12 14:57:16.569 | INFO     | besser_tanken.data_loader:load_prices:70 - got 302240 prices\n",
+      "2021-08-12 14:57:16.967 | INFO     | besser_tanken.data_loader:load_prices:70 - got 303081 prices\n",
+      "2021-08-12 14:57:18.744 | INFO     | besser_tanken.data_loader:load_prices:70 - got 300843 prices\n",
+      "2021-08-12 14:57:20.310 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-28-prices.csv\n",
+      "2021-08-12 14:57:21.070 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-30-prices.csv\n",
+      "2021-08-12 14:57:21.158 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-29-prices.csv\n",
+      "2021-08-12 14:57:22.092 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-31-prices.csv\n",
+      "2021-08-12 14:57:23.771 | INFO     | besser_tanken.data_loader:load_prices:70 - got 303397 prices\n",
+      "2021-08-12 14:57:24.841 | INFO     | besser_tanken.data_loader:load_prices:70 - got 289836 prices\n",
+      "2021-08-12 14:57:25.797 | INFO     | besser_tanken.data_loader:load_prices:70 - got 305209 prices\n",
+      "2021-08-12 14:57:25.863 | INFO     | besser_tanken.data_loader:load_prices:70 - got 309499 prices\n",
+      "2021-08-12 14:57:26.278 | INFO     | besser_tanken.data_loader:load_prices:70 - got 300025 prices\n",
+      "2021-08-12 14:57:28.340 | INFO     | besser_tanken.data_loader:load_prices:70 - got 267630 prices\n",
+      "2021-08-12 14:57:28.514 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-01-prices.csv\n",
+      "2021-08-12 14:57:29.012 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-02-prices.csv\n",
+      "2021-08-12 14:57:29.784 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-03-prices.csv\n",
+      "2021-08-12 14:57:30.148 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-04-prices.csv\n",
+      "2021-08-12 14:57:30.349 | INFO     | besser_tanken.data_loader:load_prices:70 - got 278406 prices\n",
+      "2021-08-12 14:57:30.450 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-05-prices.csv\n",
+      "2021-08-12 14:57:30.466 | INFO     | besser_tanken.data_loader:load_prices:70 - got 307740 prices\n",
+      "2021-08-12 14:57:30.479 | INFO     | besser_tanken.data_loader:load_prices:70 - got 284813 prices\n",
+      "2021-08-12 14:57:31.503 | INFO     | besser_tanken.data_loader:load_prices:70 - got 281674 prices\n",
+      "2021-08-12 14:57:31.682 | INFO     | besser_tanken.data_loader:load_prices:70 - got 279638 prices\n",
+      "2021-08-12 14:57:31.770 | INFO     | besser_tanken.data_loader:load_prices:70 - got 257995 prices\n",
+      "2021-08-12 14:57:34.898 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-06-prices.csv\n",
+      "2021-08-12 14:57:36.742 | INFO     | besser_tanken.data_loader:load_prices:70 - got 243278 prices\n",
+      "2021-08-12 14:57:37.615 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-07-prices.csv\n",
+      "2021-08-12 14:57:38.020 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-10-prices.csv\n",
+      "2021-08-12 14:57:38.151 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-08-prices.csv\n",
+      "2021-08-12 14:57:38.359 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-11-prices.csv\n",
+      "2021-08-12 14:57:38.632 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-12-prices.csv\n",
+      "2021-08-12 14:57:38.674 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-09-prices.csv\n",
+      "2021-08-12 14:57:39.595 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-13-prices.csv\n",
+      "2021-08-12 14:57:40.003 | INFO     | besser_tanken.data_loader:load_prices:70 - got 307644 prices\n",
+      "2021-08-12 14:57:40.639 | INFO     | besser_tanken.data_loader:load_prices:70 - got 310474 prices\n",
+      "2021-08-12 14:57:42.529 | INFO     | besser_tanken.data_loader:load_prices:70 - got 312526 prices\n",
+      "2021-08-12 14:57:43.801 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-14-prices.csv\n",
+      "2021-08-12 14:57:45.486 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-15-prices.csv\n",
+      "2021-08-12 14:57:46.504 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-16-prices.csv\n",
+      "2021-08-12 14:57:46.733 | INFO     | besser_tanken.data_loader:load_prices:70 - got 269837 prices\n",
+      "2021-08-12 14:57:47.588 | INFO     | besser_tanken.data_loader:load_prices:70 - got 256287 prices\n",
+      "2021-08-12 14:57:49.306 | INFO     | besser_tanken.data_loader:load_prices:70 - got 311357 prices\n",
+      "2021-08-12 14:57:49.584 | INFO     | besser_tanken.data_loader:load_prices:70 - got 274141 prices\n",
+      "2021-08-12 14:57:50.459 | INFO     | besser_tanken.data_loader:load_prices:70 - got 268407 prices\n",
+      "2021-08-12 14:57:51.005 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-18-prices.csv\n",
+      "2021-08-12 14:57:51.256 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-17-prices.csv\n",
+      "2021-08-12 14:57:53.426 | INFO     | besser_tanken.data_loader:load_prices:70 - got 261957 prices\n",
+      "2021-08-12 14:57:53.561 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-19-prices.csv\n",
+      "2021-08-12 14:57:53.882 | INFO     | besser_tanken.data_loader:load_prices:70 - got 317049 prices\n",
+      "2021-08-12 14:57:53.994 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-20-prices.csv\n",
+      "2021-08-12 14:57:54.237 | INFO     | besser_tanken.data_loader:load_prices:70 - got 279637 prices\n",
+      "2021-08-12 14:57:55.421 | INFO     | besser_tanken.data_loader:load_prices:70 - got 293932 prices\n",
+      "2021-08-12 14:57:55.668 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-21-prices.csv\n",
+      "2021-08-12 14:57:56.042 | INFO     | besser_tanken.data_loader:load_prices:70 - got 317581 prices\n",
+      "2021-08-12 14:57:56.147 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-22-prices.csv\n",
+      "2021-08-12 14:57:57.335 | INFO     | besser_tanken.data_loader:load_prices:70 - got 315661 prices\n",
+      "2021-08-12 14:57:58.179 | INFO     | besser_tanken.data_loader:load_prices:70 - got 338501 prices\n",
+      "2021-08-12 14:57:58.486 | INFO     | besser_tanken.data_loader:load_prices:70 - got 308348 prices\n",
+      "2021-08-12 14:57:58.646 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-23-prices.csv\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2021-08-12 14:57:58.764 | INFO     | besser_tanken.data_loader:load_prices:70 - got 269150 prices\n",
+      "2021-08-12 14:57:58.781 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-24-prices.csv\n",
+      "2021-08-12 14:57:59.108 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-25-prices.csv\n",
+      "2021-08-12 14:58:00.443 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-26-prices.csv\n",
+      "2021-08-12 14:58:01.096 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-27-prices.csv\n",
+      "2021-08-12 14:58:02.025 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-28-prices.csv\n",
+      "2021-08-12 14:58:02.478 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-30-prices.csv\n",
+      "2021-08-12 14:58:02.643 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-29-prices.csv\n",
+      "2021-08-12 14:58:02.947 | INFO     | besser_tanken.data_loader:load_prices:70 - got 314120 prices\n",
+      "2021-08-12 14:58:04.351 | INFO     | besser_tanken.data_loader:load_prices:70 - got 307809 prices\n",
+      "2021-08-12 14:58:04.725 | INFO     | besser_tanken.data_loader:load_prices:70 - got 231764 prices\n",
+      "2021-08-12 14:58:06.030 | INFO     | besser_tanken.data_loader:load_prices:70 - got 245486 prices\n",
+      "2021-08-12 14:58:07.390 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-01-prices.csv\n",
+      "2021-08-12 14:58:08.017 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-02-prices.csv\n",
+      "2021-08-12 14:58:08.660 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-03-prices.csv\n",
+      "2021-08-12 14:58:09.468 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-04-prices.csv\n",
+      "2021-08-12 14:58:13.118 | INFO     | besser_tanken.data_loader:load_prices:70 - got 311389 prices\n",
+      "2021-08-12 14:58:13.294 | INFO     | besser_tanken.data_loader:load_prices:70 - got 319437 prices\n",
+      "2021-08-12 14:58:14.389 | INFO     | besser_tanken.data_loader:load_prices:70 - got 311989 prices\n",
+      "2021-08-12 14:58:14.811 | INFO     | besser_tanken.data_loader:load_prices:70 - got 247493 prices\n",
+      "2021-08-12 14:58:16.005 | INFO     | besser_tanken.data_loader:load_prices:70 - got 266464 prices\n",
+      "2021-08-12 14:58:16.215 | INFO     | besser_tanken.data_loader:load_prices:70 - got 277334 prices\n",
+      "2021-08-12 14:58:16.334 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-06-prices.csv\n",
+      "2021-08-12 14:58:16.467 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-05-prices.csv\n",
+      "2021-08-12 14:58:16.477 | INFO     | besser_tanken.data_loader:load_prices:70 - got 317099 prices\n",
+      "2021-08-12 14:58:18.111 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-08-prices.csv\n",
+      "2021-08-12 14:58:18.136 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-07-prices.csv\n",
+      "2021-08-12 14:58:18.296 | INFO     | besser_tanken.data_loader:load_prices:70 - got 316090 prices\n",
+      "2021-08-12 14:58:18.353 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-09-prices.csv\n",
+      "2021-08-12 14:58:18.499 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-10-prices.csv\n",
+      "2021-08-12 14:58:20.181 | INFO     | besser_tanken.data_loader:load_prices:70 - got 323020 prices\n",
+      "2021-08-12 14:58:20.319 | INFO     | besser_tanken.data_loader:load_prices:70 - got 320842 prices\n",
+      "2021-08-12 14:58:23.099 | INFO     | besser_tanken.data_loader:load_prices:70 - got 295191 prices\n",
+      "2021-08-12 14:58:24.631 | INFO     | besser_tanken.data_loader:load_prices:70 - got 320951 prices\n",
+      "2021-08-12 14:58:24.753 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-11-prices.csv\n",
+      "2021-08-12 14:58:24.788 | INFO     | besser_tanken.data_loader:load_prices:70 - got 281559 prices\n",
+      "2021-08-12 14:58:25.271 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-12-prices.csv\n",
+      "2021-08-12 14:58:25.592 | INFO     | besser_tanken.data_loader:load_prices:70 - got 268206 prices\n",
+      "2021-08-12 14:58:26.433 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-14-prices.csv\n",
+      "2021-08-12 14:58:26.652 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-13-prices.csv\n",
+      "2021-08-12 14:58:27.396 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-15-prices.csv\n",
+      "2021-08-12 14:58:27.564 | INFO     | besser_tanken.data_loader:load_prices:70 - got 316110 prices\n",
+      "2021-08-12 14:58:27.898 | INFO     | besser_tanken.data_loader:load_prices:70 - got 310422 prices\n",
+      "2021-08-12 14:58:28.063 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-16-prices.csv\n",
+      "2021-08-12 14:58:28.567 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-17-prices.csv\n",
+      "2021-08-12 14:58:28.934 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-18-prices.csv\n",
+      "2021-08-12 14:58:30.981 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-20-prices.csv\n",
+      "2021-08-12 14:58:30.988 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-19-prices.csv\n",
+      "2021-08-12 14:58:35.858 | INFO     | besser_tanken.data_loader:load_prices:70 - got 314216 prices\n",
+      "2021-08-12 14:58:36.657 | INFO     | besser_tanken.data_loader:load_prices:70 - got 300563 prices\n",
+      "2021-08-12 14:58:36.883 | INFO     | besser_tanken.data_loader:load_prices:70 - got 311043 prices\n",
+      "2021-08-12 14:58:37.566 | INFO     | besser_tanken.data_loader:load_prices:70 - got 303829 prices\n",
+      "2021-08-12 14:58:37.826 | INFO     | besser_tanken.data_loader:load_prices:70 - got 279529 prices\n",
+      "2021-08-12 14:58:40.451 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-22-prices.csv\n",
+      "2021-08-12 14:58:40.478 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-21-prices.csv\n",
+      "2021-08-12 14:58:40.676 | INFO     | besser_tanken.data_loader:load_prices:70 - got 322838 prices\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2021-08-12 14:58:41.478 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-23-prices.csv\n",
+      "2021-08-12 14:58:41.515 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-24-prices.csv\n",
+      "2021-08-12 14:58:41.617 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-25-prices.csv\n",
+      "2021-08-12 14:58:42.738 | INFO     | besser_tanken.data_loader:load_prices:70 - got 318446 prices\n",
+      "2021-08-12 14:58:43.053 | INFO     | besser_tanken.data_loader:load_prices:70 - got 320776 prices\n",
+      "2021-08-12 14:58:44.436 | INFO     | besser_tanken.data_loader:load_prices:70 - got 281255 prices\n",
+      "2021-08-12 14:58:44.672 | INFO     | besser_tanken.data_loader:load_prices:70 - got 300333 prices\n",
+      "2021-08-12 14:58:44.679 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-26-prices.csv\n",
+      "2021-08-12 14:58:45.118 | INFO     | besser_tanken.data_loader:load_prices:70 - got 323364 prices\n",
+      "2021-08-12 14:58:45.662 | INFO     | besser_tanken.data_loader:load_prices:70 - got 295663 prices\n",
+      "2021-08-12 14:58:45.885 | INFO     | besser_tanken.data_loader:load_prices:70 - got 312171 prices\n",
+      "2021-08-12 14:58:46.903 | INFO     | besser_tanken.data_loader:load_prices:70 - got 322048 prices\n",
+      "2021-08-12 14:58:46.985 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-27-prices.csv\n",
+      "2021-08-12 14:58:47.569 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-28-prices.csv\n",
+      "2021-08-12 14:58:47.802 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-29-prices.csv\n",
+      "2021-08-12 14:58:48.437 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-30-prices.csv\n",
+      "2021-08-12 14:58:48.982 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-31-prices.csv\n",
+      "2021-08-12 14:58:49.653 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-01-prices.csv\n",
+      "2021-08-12 14:58:49.703 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-02-prices.csv\n",
+      "2021-08-12 14:58:49.763 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-03-prices.csv\n",
+      "2021-08-12 14:58:51.189 | INFO     | besser_tanken.data_loader:load_prices:70 - got 321281 prices\n",
+      "2021-08-12 14:58:51.727 | INFO     | besser_tanken.data_loader:load_prices:70 - got 323562 prices\n",
+      "2021-08-12 14:58:54.747 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-04-prices.csv\n",
+      "2021-08-12 14:58:55.570 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-05-prices.csv\n",
+      "2021-08-12 14:58:58.161 | INFO     | besser_tanken.data_loader:load_prices:70 - got 273299 prices\n",
+      "2021-08-12 14:58:58.252 | INFO     | besser_tanken.data_loader:load_prices:70 - got 295898 prices\n",
+      "2021-08-12 14:58:58.744 | INFO     | besser_tanken.data_loader:load_prices:70 - got 283712 prices\n",
+      "2021-08-12 14:58:59.410 | INFO     | besser_tanken.data_loader:load_prices:70 - got 311513 prices\n",
+      "2021-08-12 14:59:01.014 | INFO     | besser_tanken.data_loader:load_prices:70 - got 311840 prices\n",
+      "2021-08-12 14:59:01.422 | INFO     | besser_tanken.data_loader:load_prices:70 - got 309601 prices\n",
+      "2021-08-12 14:59:01.754 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-06-prices.csv\n",
+      "2021-08-12 14:59:02.402 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-07-prices.csv\n",
+      "2021-08-12 14:59:02.559 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-09-prices.csv\n",
+      "2021-08-12 14:59:02.695 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-08-prices.csv\n",
+      "2021-08-12 14:59:03.288 | INFO     | besser_tanken.data_loader:load_prices:70 - got 306849 prices\n",
+      "2021-08-12 14:59:03.415 | INFO     | besser_tanken.data_loader:load_prices:70 - got 311428 prices\n",
+      "2021-08-12 14:59:03.706 | INFO     | besser_tanken.data_loader:load_prices:70 - got 292252 prices\n",
+      "2021-08-12 14:59:04.457 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-10-prices.csv\n",
+      "2021-08-12 14:59:04.582 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-11-prices.csv\n",
+      "2021-08-12 14:59:04.633 | INFO     | besser_tanken.data_loader:load_prices:70 - got 272179 prices\n",
+      "2021-08-12 14:59:05.357 | INFO     | besser_tanken.data_loader:load_prices:70 - got 297145 prices\n",
+      "2021-08-12 14:59:07.128 | INFO     | besser_tanken.data_loader:load_prices:70 - got 310321 prices\n",
+      "2021-08-12 14:59:10.776 | INFO     | besser_tanken.data_loader:load_prices:70 - got 296089 prices\n",
+      "2021-08-12 14:59:11.201 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-13-prices.csv\n",
+      "2021-08-12 14:59:11.267 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-14-prices.csv\n",
+      "2021-08-12 14:59:11.376 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-12-prices.csv\n",
+      "2021-08-12 14:59:11.830 | INFO     | besser_tanken.data_loader:load_prices:70 - got 305627 prices\n",
+      "2021-08-12 14:59:11.946 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-15-prices.csv\n",
+      "2021-08-12 14:59:12.810 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-16-prices.csv\n",
+      "2021-08-12 14:59:13.874 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-17-prices.csv\n",
+      "2021-08-12 14:59:14.596 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-18-prices.csv\n",
+      "2021-08-12 14:59:15.772 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-19-prices.csv\n",
+      "2021-08-12 14:59:15.855 | INFO     | besser_tanken.data_loader:load_prices:70 - got 315296 prices\n",
+      "2021-08-12 14:59:16.417 | INFO     | besser_tanken.data_loader:load_prices:70 - got 284582 prices\n",
+      "2021-08-12 14:59:19.259 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-20-prices.csv\n",
+      "2021-08-12 14:59:20.797 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-21-prices.csv\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2021-08-12 14:59:22.061 | INFO     | besser_tanken.data_loader:load_prices:70 - got 280524 prices\n",
+      "2021-08-12 14:59:22.229 | INFO     | besser_tanken.data_loader:load_prices:70 - got 301502 prices\n",
+      "2021-08-12 14:59:23.325 | INFO     | besser_tanken.data_loader:load_prices:70 - got 329611 prices\n",
+      "2021-08-12 14:59:24.570 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-22-prices.csv\n",
+      "2021-08-12 14:59:25.013 | INFO     | besser_tanken.data_loader:load_prices:70 - got 324502 prices\n",
+      "2021-08-12 14:59:25.092 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-23-prices.csv\n",
+      "2021-08-12 14:59:26.697 | INFO     | besser_tanken.data_loader:load_prices:70 - got 278483 prices\n",
+      "2021-08-12 14:59:26.781 | INFO     | besser_tanken.data_loader:load_prices:70 - got 326345 prices\n",
+      "2021-08-12 14:59:27.309 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-24-prices.csv\n",
+      "2021-08-12 14:59:27.370 | INFO     | besser_tanken.data_loader:load_prices:70 - got 318813 prices\n",
+      "2021-08-12 14:59:27.956 | INFO     | besser_tanken.data_loader:load_prices:70 - got 286250 prices\n",
+      "2021-08-12 14:59:29.661 | INFO     | besser_tanken.data_loader:load_prices:70 - got 326330 prices\n",
+      "2021-08-12 14:59:29.788 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-25-prices.csv\n",
+      "2021-08-12 14:59:30.479 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-26-prices.csv\n",
+      "2021-08-12 14:59:30.576 | INFO     | besser_tanken.data_loader:load_prices:70 - got 320353 prices\n",
+      "2021-08-12 14:59:31.068 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-27-prices.csv\n",
+      "2021-08-12 14:59:31.805 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-29-prices.csv\n",
+      "2021-08-12 14:59:31.858 | INFO     | besser_tanken.data_loader:load_prices:70 - got 318714 prices\n",
+      "2021-08-12 14:59:31.960 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-28-prices.csv\n",
+      "2021-08-12 14:59:32.562 | INFO     | besser_tanken.data_loader:load_prices:70 - got 291300 prices\n",
+      "2021-08-12 14:59:33.087 | INFO     | besser_tanken.data_loader:load_prices:70 - got 322612 prices\n",
+      "2021-08-12 14:59:33.306 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-30-prices.csv\n",
+      "2021-08-12 14:59:34.033 | INFO     | besser_tanken.data_loader:load_prices:70 - got 318015 prices\n",
+      "2021-08-12 14:59:34.734 | INFO     | besser_tanken.data_loader:load_prices:70 - got 278580 prices\n",
+      "2021-08-12 14:59:35.338 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-01-prices.csv\n",
+      "2021-08-12 14:59:36.013 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-02-prices.csv\n",
+      "2021-08-12 14:59:36.785 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-03-prices.csv\n",
+      "2021-08-12 14:59:38.639 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-04-prices.csv\n",
+      "2021-08-12 14:59:38.919 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-05-prices.csv\n",
+      "2021-08-12 14:59:39.381 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-06-prices.csv\n",
+      "2021-08-12 14:59:41.434 | INFO     | besser_tanken.data_loader:load_prices:70 - got 320304 prices\n",
+      "2021-08-12 14:59:43.846 | INFO     | besser_tanken.data_loader:load_prices:70 - got 311422 prices\n",
+      "2021-08-12 14:59:45.731 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-07-prices.csv\n",
+      "2021-08-12 14:59:46.590 | INFO     | besser_tanken.data_loader:load_prices:70 - got 313682 prices\n",
+      "2021-08-12 14:59:48.577 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-08-prices.csv\n",
+      "2021-08-12 14:59:49.006 | INFO     | besser_tanken.data_loader:load_prices:70 - got 329516 prices\n",
+      "2021-08-12 14:59:49.219 | INFO     | besser_tanken.data_loader:load_prices:70 - got 303649 prices\n",
+      "2021-08-12 14:59:49.968 | INFO     | besser_tanken.data_loader:load_prices:70 - got 293388 prices\n",
+      "2021-08-12 14:59:50.861 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-09-prices.csv\n",
+      "2021-08-12 14:59:51.313 | INFO     | besser_tanken.data_loader:load_prices:70 - got 318168 prices\n",
+      "2021-08-12 14:59:52.141 | INFO     | besser_tanken.data_loader:load_prices:70 - got 319096 prices\n",
+      "2021-08-12 14:59:52.903 | INFO     | besser_tanken.data_loader:load_prices:70 - got 311116 prices\n",
+      "2021-08-12 14:59:57.409 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-11-prices.csv\n",
+      "2021-08-12 14:59:57.419 | INFO     | besser_tanken.data_loader:load_prices:70 - got 320103 prices\n",
+      "2021-08-12 14:59:57.466 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-10-prices.csv\n",
+      "2021-08-12 14:59:58.224 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-12-prices.csv\n",
+      "2021-08-12 14:59:58.778 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-13-prices.csv\n",
+      "2021-08-12 14:59:58.941 | INFO     | besser_tanken.data_loader:load_prices:70 - got 291670 prices\n",
+      "2021-08-12 14:59:59.089 | INFO     | besser_tanken.data_loader:load_prices:70 - got 322544 prices\n",
+      "2021-08-12 14:59:59.675 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-14-prices.csv\n",
+      "2021-08-12 15:00:00.012 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-15-prices.csv\n",
+      "2021-08-12 15:00:00.249 | INFO     | besser_tanken.data_loader:load_prices:70 - got 324591 prices\n",
+      "2021-08-12 15:00:00.690 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-16-prices.csv\n",
+      "2021-08-12 15:00:00.871 | INFO     | besser_tanken.data_loader:load_prices:70 - got 302137 prices\n",
+      "2021-08-12 15:00:02.287 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-17-prices.csv\n",
+      "2021-08-12 15:00:02.470 | INFO     | besser_tanken.data_loader:load_prices:70 - got 323030 prices\n",
+      "2021-08-12 15:00:03.132 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-18-prices.csv\n",
+      "2021-08-12 15:00:04.115 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-19-prices.csv\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2021-08-12 15:00:05.017 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-20-prices.csv\n",
+      "2021-08-12 15:00:05.341 | INFO     | besser_tanken.data_loader:load_prices:70 - got 322967 prices\n",
+      "2021-08-12 15:00:06.068 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-21-prices.csv\n"
+     ]
+    }
+   ],
+   "source": [
+    "#data = load_prices_from(2020,11,1)\n",
+    "#df = load_prices_from(2020,11,1)\n",
+    "#df = pd.DataFrame(data)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "4625073c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df.e5 = df['e5'].astype(float)\n",
+    "df.e10 = df['e10'].astype(float)\n",
+    "df.diesel = df['diesel'].astype(float)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "8d98c145",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df[\"date_time\"] = pd.to_datetime(df.date, infer_datetime_format=True, utc=True)\n",
+    "df[\"hour\"] = df.date_time.dt.hour\n",
+    "df[\"month\"] = df.date_time.dt.month\n",
+    "df[\"quarter\"] = df.date_time.dt.quarter\n",
+    "df[\"year\"] = df.date_time.dt.year\n",
+    "df[\"day\"] = df.date_time.dt.day\n",
+    "df[\"week\"] = df.date_time.dt.isocalendar().week\n",
+    "df[\"weekday\"] = df.date_time.dt.weekday\n",
+    "df[\"season\"] = np.where(df[\"month\"].isin([3,4,5]),\"spring\",\n",
+    "   np.where(df[\"month\"].isin([6,7,8]),\"summer\",\n",
+    "   np.where(df[\"month\"].isin([9,10,11]),\"fall\",\n",
+    "   np.where(df[\"month\"].isin([12,1,2]),\"winter\",\"None\"))))\n",
+    "#buehl[\"weekday_name\"] = np.where(df[\"weekday\"].isin([0]),\"mon\",\n",
+    "#   np.where(df[\"weekday\"].isin([1]),\"tue\",\n",
+    "#   np.where(df[\"weekday\"].isin([2]),\"wed\",\n",
+    "#   np.where(df[\"weekday\"].isin([3]),\"thu\",\n",
+    "#   np.where(df[\"weekday\"].isin([4]),\"fri\",            \n",
+    "#   np.where(df[\"weekday\"].isin([5]),\"sat\",            \n",
+    "#   np.where(df[\"weekday\"].isin([6]),\"sun\",\"None\")))))))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "ee8153a0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#df[\"date_time\"] = pd.to_datetime(df.date)\n",
+    "#df[\"month\"] = df[\"date_time\"].dt.month"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d4419141",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "7babd7db",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df.info()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "add38d92",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "grouped_by_station = df.groupby('station_uuid').mean()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "919a8bbf",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "grouped_by_station['diesel'].plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "928c0449",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "grouped_by_station['diesel'].nlargest(20).plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "0b67b964",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "grouped_by_station['diesel'].nsmallest(20).plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "4d9f5349",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "stations = load_stations()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "3fcabf92",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "stations_df = pd.DataFrame(stations)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "493ce272",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "merged = pd.merge(df, stations_df, how=\"outer\", left_on=[\"station_uuid\"],right_on=[\"uuid\"])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "005e93e4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "merged.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "476b5d9e",
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "NameError",
+     "evalue": "name 'merged' is not defined",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
+      "\u001b[0;32m/tmp/ipykernel_326572/2217073540.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mplz_grouped\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmerged\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgroupby\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'post_code'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmean\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
+      "\u001b[0;31mNameError\u001b[0m: name 'merged' is not defined"
+     ]
+    }
+   ],
+   "source": [
+    "plz_grouped = merged.groupby('post_code').mean()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 196,
+   "id": "9ce5a1c0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#prices = group_prices(data)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 123,
+   "id": "4221f111",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "buehl_stations = filter(lambda s: s['post_code'] in ['77815'], stations)\n",
+    "buehl_station = list(buehl_stations)[0]\n",
+    "#buehl = prices[buehl_station['uuid']]\n",
+    "buehl = df[df[\"station_uuid\"] == buehl_station['uuid']]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 127,
+   "id": "5c01f16f",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'uuid': 'e95c2523-8d12-4132-98b3-0aa6a2ce454d', 'name': 'ZG Raiffeisen Tankstelle Bühl', 'brand': 'ZG Raiffeisen Energie', 'street': 'Hurststraße', 'house_number': '24', 'post_code': '77815', 'city': 'Bühl Vimbuch', 'latitude': '48.7133', 'longitude': '8.12091', 'first_active': '2014-03-18 16:45:31+01', 'openingtimes_json': '{}'}\n"
+     ]
+    }
+   ],
+   "source": [
+    "#buehl_station = next(buehl_stations)\n",
+    "print(buehl_station)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 128,
+   "id": "c5371e50",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "buehl= pd.DataFrame(buehl)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 129,
+   "id": "c4a16376",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "9581        2020-11-01 06:06:05+0100\n",
+       "22918       2020-11-01 07:31:06+0100\n",
+       "23793       2020-11-01 07:36:05+0100\n",
+       "26755       2020-11-01 07:56:07+0100\n",
+       "33824       2020-11-01 08:31:06+0100\n",
+       "                      ...           \n",
+       "49842510    2021-03-31 19:01:05+0200\n",
+       "49853848    2021-03-31 19:26:08+0200\n",
+       "49862771    2021-03-31 20:01:05+0200\n",
+       "49867661    2021-03-31 20:11:05+0200\n",
+       "49892392    2021-03-31 23:51:05+0200\n",
+       "Name: date, Length: 3533, dtype: object"
+      ]
+     },
+     "execution_count": 129,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "buehl[\"date\"] "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 139,
+   "id": "adbd26b4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "buehl[\"date_time\"] = pd.to_datetime(buehl.date, infer_datetime_format=True, utc=True)\n",
+    "#buehl[\"date_time\"] = pd.to_datetime(buehl.date)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "6950f7b6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#buehl[\"date_time\"] = pd.to_datetime(buehl.date, format='%Y-%m-%d %H:%M:%S%z')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 140,
+   "id": "e0b8a829",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "9581       2020-11-01 05:06:05+00:00\n",
+       "22918      2020-11-01 06:31:06+00:00\n",
+       "23793      2020-11-01 06:36:05+00:00\n",
+       "26755      2020-11-01 06:56:07+00:00\n",
+       "33824      2020-11-01 07:31:06+00:00\n",
+       "                      ...           \n",
+       "49842510   2021-03-31 17:01:05+00:00\n",
+       "49853848   2021-03-31 17:26:08+00:00\n",
+       "49862771   2021-03-31 18:01:05+00:00\n",
+       "49867661   2021-03-31 18:11:05+00:00\n",
+       "49892392   2021-03-31 21:51:05+00:00\n",
+       "Name: date, Length: 3533, dtype: datetime64[ns, UTC]"
+      ]
+     },
+     "execution_count": 140,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "buehl.date_time"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "id": "ce8e2387",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "9581        2020-11-01 06:06:05+0100\n",
+       "22918       2020-11-01 07:31:06+0100\n",
+       "23793       2020-11-01 07:36:05+0100\n",
+       "26755       2020-11-01 07:56:07+0100\n",
+       "33824       2020-11-01 08:31:06+0100\n",
+       "                      ...           \n",
+       "49842510    2021-03-31 19:01:05+0200\n",
+       "49853848    2021-03-31 19:26:08+0200\n",
+       "49862771    2021-03-31 20:01:05+0200\n",
+       "49867661    2021-03-31 20:11:05+0200\n",
+       "49892392    2021-03-31 23:51:05+0200\n",
+       "Name: date, Length: 3533, dtype: object"
+      ]
+     },
+     "execution_count": 33,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "buehl.date"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 133,
+   "id": "3f5c3044",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "d = pd.to_datetime(buehl.iloc[0].date)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 134,
+   "id": "3609750b",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Timestamp('2020-11-01 06:06:05+0100', tz='pytz.FixedOffset(60)')"
+      ]
+     },
+     "execution_count": 134,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "d"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 135,
+   "id": "69d3322e",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "11"
+      ]
+     },
+     "execution_count": 135,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "d.month"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 141,
+   "id": "cd27f6c5",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "DatetimeIndex(['2020-11-01 05:06:05+00:00', '2020-11-01 06:31:06+00:00',\n",
+       "               '2020-11-01 06:36:05+00:00', '2020-11-01 06:56:07+00:00',\n",
+       "               '2020-11-01 07:31:06+00:00', '2020-11-01 08:01:06+00:00',\n",
+       "               '2020-11-01 12:26:08+00:00', '2020-11-01 13:21:12+00:00',\n",
+       "               '2020-11-01 14:31:06+00:00', '2020-11-01 14:46:09+00:00',\n",
+       "               ...\n",
+       "               '2021-03-31 14:51:06+00:00', '2021-03-31 15:56:06+00:00',\n",
+       "               '2021-03-31 16:01:07+00:00', '2021-03-31 16:11:06+00:00',\n",
+       "               '2021-03-31 16:41:07+00:00', '2021-03-31 17:01:05+00:00',\n",
+       "               '2021-03-31 17:26:08+00:00', '2021-03-31 18:01:05+00:00',\n",
+       "               '2021-03-31 18:11:05+00:00', '2021-03-31 21:51:05+00:00'],\n",
+       "              dtype='datetime64[ns, UTC]', name='date_time', length=3533, freq=None)"
+      ]
+     },
+     "execution_count": 141,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "pd.DatetimeIndex(buehl['date_time'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 164,
+   "id": "e56eda9b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "buehl[\"hour\"] = buehl.date_time.dt.hour\n",
+    "buehl[\"month\"] = buehl.date_time.dt.month\n",
+    "buehl[\"quarter\"] = buehl.date_time.dt.quarter\n",
+    "buehl[\"year\"] = buehl.date_time.dt.year\n",
+    "buehl[\"day\"] = buehl.date_time.dt.day\n",
+    "buehl[\"week\"] = buehl.date_time.dt.isocalendar().week\n",
+    "buehl[\"weekday\"] = buehl.date_time.dt.weekday\n",
+    "buehl[\"season\"] = np.where(buehl[\"month\"].isin([3,4,5]),\"spring\",\n",
+    "   np.where(buehl[\"month\"].isin([6,7,8]),\"summer\",\n",
+    "   np.where(buehl[\"month\"].isin([9,10,11]),\"fall\",\n",
+    "   np.where(buehl[\"month\"].isin([12,1,2]),\"winter\",\"None\"))))\n",
+    "buehl[\"weekday_name\"] = np.where(buehl[\"weekday\"].isin([0]),\"mon\",\n",
+    "   np.where(buehl[\"weekday\"].isin([1]),\"tue\",\n",
+    "   np.where(buehl[\"weekday\"].isin([2]),\"wed\",\n",
+    "   np.where(buehl[\"weekday\"].isin([3]),\"thu\",\n",
+    "   np.where(buehl[\"weekday\"].isin([4]),\"fri\",            \n",
+    "   np.where(buehl[\"weekday\"].isin([5]),\"sat\",            \n",
+    "   np.where(buehl[\"weekday\"].isin([6]),\"sun\",\"None\")))))))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 143,
+   "id": "ff6450d2",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Index(['date', 'station_uuid', 'diesel', 'e5', 'e10', 'dieselchange',\n",
+       "       'e5change', 'e10change', 'date_time', 'month', 'quarter', 'year', 'day',\n",
+       "       'week', 'weekday', 'season', 'weekday_name'],\n",
+       "      dtype='object')"
+      ]
+     },
+     "execution_count": 143,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "buehl.columns"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 144,
+   "id": "65deae4d",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "Int64Index: 3533 entries, 9581 to 49892392\n",
+      "Data columns (total 17 columns):\n",
+      " #   Column        Non-Null Count  Dtype              \n",
+      "---  ------        --------------  -----              \n",
+      " 0   date          3533 non-null   object             \n",
+      " 1   station_uuid  3533 non-null   object             \n",
+      " 2   diesel        3533 non-null   object             \n",
+      " 3   e5            3533 non-null   object             \n",
+      " 4   e10           3533 non-null   object             \n",
+      " 5   dieselchange  3533 non-null   object             \n",
+      " 6   e5change      3533 non-null   object             \n",
+      " 7   e10change     3533 non-null   object             \n",
+      " 8   date_time     3533 non-null   datetime64[ns, UTC]\n",
+      " 9   month         3533 non-null   int64              \n",
+      " 10  quarter       3533 non-null   int64              \n",
+      " 11  year          3533 non-null   int64              \n",
+      " 12  day           3533 non-null   int64              \n",
+      " 13  week          3533 non-null   UInt32             \n",
+      " 14  weekday       3533 non-null   int64              \n",
+      " 15  season        3533 non-null   object             \n",
+      " 16  weekday_name  3533 non-null   object             \n",
+      "dtypes: UInt32(1), datetime64[ns, UTC](1), int64(5), object(10)\n",
+      "memory usage: 486.5+ KB\n"
+     ]
+    }
+   ],
+   "source": [
+    "buehl.info()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 145,
+   "id": "26cae1bf",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>date</th>\n",
+       "      <th>station_uuid</th>\n",
+       "      <th>diesel</th>\n",
+       "      <th>e5</th>\n",
+       "      <th>e10</th>\n",
+       "      <th>dieselchange</th>\n",
+       "      <th>e5change</th>\n",
+       "      <th>e10change</th>\n",
+       "      <th>date_time</th>\n",
+       "      <th>month</th>\n",
+       "      <th>quarter</th>\n",
+       "      <th>year</th>\n",
+       "      <th>day</th>\n",
+       "      <th>week</th>\n",
+       "      <th>weekday</th>\n",
+       "      <th>season</th>\n",
+       "      <th>weekday_name</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>9581</th>\n",
+       "      <td>2020-11-01 06:06:05+0100</td>\n",
+       "      <td>e95c2523-8d12-4132-98b3-0aa6a2ce454d</td>\n",
+       "      <td>1.079</td>\n",
+       "      <td>1.279</td>\n",
+       "      <td>1.239</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2020-11-01 05:06:05+00:00</td>\n",
+       "      <td>11</td>\n",
+       "      <td>4</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>1</td>\n",
+       "      <td>44</td>\n",
+       "      <td>6</td>\n",
+       "      <td>fall</td>\n",
+       "      <td>sun</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22918</th>\n",
+       "      <td>2020-11-01 07:31:06+0100</td>\n",
+       "      <td>e95c2523-8d12-4132-98b3-0aa6a2ce454d</td>\n",
+       "      <td>1.049</td>\n",
+       "      <td>1.249</td>\n",
+       "      <td>1.209</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2020-11-01 06:31:06+00:00</td>\n",
+       "      <td>11</td>\n",
+       "      <td>4</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>1</td>\n",
+       "      <td>44</td>\n",
+       "      <td>6</td>\n",
+       "      <td>fall</td>\n",
+       "      <td>sun</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23793</th>\n",
+       "      <td>2020-11-01 07:36:05+0100</td>\n",
+       "      <td>e95c2523-8d12-4132-98b3-0aa6a2ce454d</td>\n",
+       "      <td>1.099</td>\n",
+       "      <td>1.309</td>\n",
+       "      <td>1.269</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2020-11-01 06:36:05+00:00</td>\n",
+       "      <td>11</td>\n",
+       "      <td>4</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>1</td>\n",
+       "      <td>44</td>\n",
+       "      <td>6</td>\n",
+       "      <td>fall</td>\n",
+       "      <td>sun</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26755</th>\n",
+       "      <td>2020-11-01 07:56:07+0100</td>\n",
+       "      <td>e95c2523-8d12-4132-98b3-0aa6a2ce454d</td>\n",
+       "      <td>1.079</td>\n",
+       "      <td>1.279</td>\n",
+       "      <td>1.239</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2020-11-01 06:56:07+00:00</td>\n",
+       "      <td>11</td>\n",
+       "      <td>4</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>1</td>\n",
+       "      <td>44</td>\n",
+       "      <td>6</td>\n",
+       "      <td>fall</td>\n",
+       "      <td>sun</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>33824</th>\n",
+       "      <td>2020-11-01 08:31:06+0100</td>\n",
+       "      <td>e95c2523-8d12-4132-98b3-0aa6a2ce454d</td>\n",
+       "      <td>1.049</td>\n",
+       "      <td>1.249</td>\n",
+       "      <td>1.209</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2020-11-01 07:31:06+00:00</td>\n",
+       "      <td>11</td>\n",
+       "      <td>4</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>1</td>\n",
+       "      <td>44</td>\n",
+       "      <td>6</td>\n",
+       "      <td>fall</td>\n",
+       "      <td>sun</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1569576</th>\n",
+       "      <td>2020-11-14 14:21:07+0100</td>\n",
+       "      <td>e95c2523-8d12-4132-98b3-0aa6a2ce454d</td>\n",
+       "      <td>0.999</td>\n",
+       "      <td>1.179</td>\n",
+       "      <td>1.139</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2020-11-14 13:21:07+00:00</td>\n",
+       "      <td>11</td>\n",
+       "      <td>4</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>14</td>\n",
+       "      <td>46</td>\n",
+       "      <td>5</td>\n",
+       "      <td>fall</td>\n",
+       "      <td>sat</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1610045</th>\n",
+       "      <td>2020-11-14 16:26:09+0100</td>\n",
+       "      <td>e95c2523-8d12-4132-98b3-0aa6a2ce454d</td>\n",
+       "      <td>1.039</td>\n",
+       "      <td>1.219</td>\n",
+       "      <td>1.179</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2020-11-14 15:26:09+00:00</td>\n",
+       "      <td>11</td>\n",
+       "      <td>4</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>14</td>\n",
+       "      <td>46</td>\n",
+       "      <td>5</td>\n",
+       "      <td>fall</td>\n",
+       "      <td>sat</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1616416</th>\n",
+       "      <td>2020-11-14 16:51:06+0100</td>\n",
+       "      <td>e95c2523-8d12-4132-98b3-0aa6a2ce454d</td>\n",
+       "      <td>0.999</td>\n",
+       "      <td>1.179</td>\n",
+       "      <td>1.139</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2020-11-14 15:51:06+00:00</td>\n",
+       "      <td>11</td>\n",
+       "      <td>4</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>14</td>\n",
+       "      <td>46</td>\n",
+       "      <td>5</td>\n",
+       "      <td>fall</td>\n",
+       "      <td>sat</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1690582</th>\n",
+       "      <td>2020-11-14 21:46:09+0100</td>\n",
+       "      <td>e95c2523-8d12-4132-98b3-0aa6a2ce454d</td>\n",
+       "      <td>1.009</td>\n",
+       "      <td>1.199</td>\n",
+       "      <td>1.159</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2020-11-14 20:46:09+00:00</td>\n",
+       "      <td>11</td>\n",
+       "      <td>4</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>14</td>\n",
+       "      <td>46</td>\n",
+       "      <td>5</td>\n",
+       "      <td>fall</td>\n",
+       "      <td>sat</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1701588</th>\n",
+       "      <td>2020-11-14 23:51:07+0100</td>\n",
+       "      <td>e95c2523-8d12-4132-98b3-0aa6a2ce454d</td>\n",
+       "      <td>1.059</td>\n",
+       "      <td>1.239</td>\n",
+       "      <td>1.189</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2020-11-14 22:51:07+00:00</td>\n",
+       "      <td>11</td>\n",
+       "      <td>4</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>14</td>\n",
+       "      <td>46</td>\n",
+       "      <td>5</td>\n",
+       "      <td>fall</td>\n",
+       "      <td>sat</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>100 rows × 17 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                             date                          station_uuid  \\\n",
+       "9581     2020-11-01 06:06:05+0100  e95c2523-8d12-4132-98b3-0aa6a2ce454d   \n",
+       "22918    2020-11-01 07:31:06+0100  e95c2523-8d12-4132-98b3-0aa6a2ce454d   \n",
+       "23793    2020-11-01 07:36:05+0100  e95c2523-8d12-4132-98b3-0aa6a2ce454d   \n",
+       "26755    2020-11-01 07:56:07+0100  e95c2523-8d12-4132-98b3-0aa6a2ce454d   \n",
+       "33824    2020-11-01 08:31:06+0100  e95c2523-8d12-4132-98b3-0aa6a2ce454d   \n",
+       "...                           ...                                   ...   \n",
+       "1569576  2020-11-14 14:21:07+0100  e95c2523-8d12-4132-98b3-0aa6a2ce454d   \n",
+       "1610045  2020-11-14 16:26:09+0100  e95c2523-8d12-4132-98b3-0aa6a2ce454d   \n",
+       "1616416  2020-11-14 16:51:06+0100  e95c2523-8d12-4132-98b3-0aa6a2ce454d   \n",
+       "1690582  2020-11-14 21:46:09+0100  e95c2523-8d12-4132-98b3-0aa6a2ce454d   \n",
+       "1701588  2020-11-14 23:51:07+0100  e95c2523-8d12-4132-98b3-0aa6a2ce454d   \n",
+       "\n",
+       "        diesel     e5    e10 dieselchange e5change e10change  \\\n",
+       "9581     1.079  1.279  1.239            1        1         1   \n",
+       "22918    1.049  1.249  1.209            1        1         1   \n",
+       "23793    1.099  1.309  1.269            1        1         1   \n",
+       "26755    1.079  1.279  1.239            1        1         1   \n",
+       "33824    1.049  1.249  1.209            1        1         1   \n",
+       "...        ...    ...    ...          ...      ...       ...   \n",
+       "1569576  0.999  1.179  1.139            1        1         1   \n",
+       "1610045  1.039  1.219  1.179            1        1         1   \n",
+       "1616416  0.999  1.179  1.139            1        1         1   \n",
+       "1690582  1.009  1.199  1.159            1        1         1   \n",
+       "1701588  1.059  1.239  1.189            1        1         1   \n",
+       "\n",
+       "                        date_time  month  quarter  year  day  week  weekday  \\\n",
+       "9581    2020-11-01 05:06:05+00:00     11        4  2020    1    44        6   \n",
+       "22918   2020-11-01 06:31:06+00:00     11        4  2020    1    44        6   \n",
+       "23793   2020-11-01 06:36:05+00:00     11        4  2020    1    44        6   \n",
+       "26755   2020-11-01 06:56:07+00:00     11        4  2020    1    44        6   \n",
+       "33824   2020-11-01 07:31:06+00:00     11        4  2020    1    44        6   \n",
+       "...                           ...    ...      ...   ...  ...   ...      ...   \n",
+       "1569576 2020-11-14 13:21:07+00:00     11        4  2020   14    46        5   \n",
+       "1610045 2020-11-14 15:26:09+00:00     11        4  2020   14    46        5   \n",
+       "1616416 2020-11-14 15:51:06+00:00     11        4  2020   14    46        5   \n",
+       "1690582 2020-11-14 20:46:09+00:00     11        4  2020   14    46        5   \n",
+       "1701588 2020-11-14 22:51:07+00:00     11        4  2020   14    46        5   \n",
+       "\n",
+       "        season weekday_name  \n",
+       "9581      fall          sun  \n",
+       "22918     fall          sun  \n",
+       "23793     fall          sun  \n",
+       "26755     fall          sun  \n",
+       "33824     fall          sun  \n",
+       "...        ...          ...  \n",
+       "1569576   fall          sat  \n",
+       "1610045   fall          sat  \n",
+       "1616416   fall          sat  \n",
+       "1690582   fall          sat  \n",
+       "1701588   fall          sat  \n",
+       "\n",
+       "[100 rows x 17 columns]"
+      ]
+     },
+     "execution_count": 145,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "buehl.head(100)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 146,
+   "id": "f5f30288",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "buehl.e5 = buehl['e5'].astype(float)\n",
+    "buehl.e10 = buehl['e10'].astype(float)\n",
+    "buehl.diesel = buehl['diesel'].astype(float)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 153,
+   "id": "9bcf07be",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>diesel</th>\n",
+       "      <th>e5</th>\n",
+       "      <th>e10</th>\n",
+       "      <th>month</th>\n",
+       "      <th>quarter</th>\n",
+       "      <th>year</th>\n",
+       "      <th>day</th>\n",
+       "      <th>week</th>\n",
+       "      <th>weekday</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>weekday_name</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>fri</th>\n",
+       "      <td>1.204121</td>\n",
+       "      <td>1.377952</td>\n",
+       "      <td>1.337810</td>\n",
+       "      <td>5.415323</td>\n",
+       "      <td>2.137097</td>\n",
+       "      <td>2020.669355</td>\n",
+       "      <td>14.941532</td>\n",
+       "      <td>22.881048</td>\n",
+       "      <td>4.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>mon</th>\n",
+       "      <td>1.212656</td>\n",
+       "      <td>1.390277</td>\n",
+       "      <td>1.350161</td>\n",
+       "      <td>5.365571</td>\n",
+       "      <td>2.102515</td>\n",
+       "      <td>2020.680851</td>\n",
+       "      <td>14.715667</td>\n",
+       "      <td>21.692456</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>sat</th>\n",
+       "      <td>1.216235</td>\n",
+       "      <td>1.391703</td>\n",
+       "      <td>1.351557</td>\n",
+       "      <td>5.380457</td>\n",
+       "      <td>2.118503</td>\n",
+       "      <td>2020.675676</td>\n",
+       "      <td>15.588358</td>\n",
+       "      <td>23.378378</td>\n",
+       "      <td>5.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>sun</th>\n",
+       "      <td>1.207577</td>\n",
+       "      <td>1.384637</td>\n",
+       "      <td>1.344506</td>\n",
+       "      <td>5.528090</td>\n",
+       "      <td>2.187266</td>\n",
+       "      <td>2020.653558</td>\n",
+       "      <td>15.988764</td>\n",
+       "      <td>23.747191</td>\n",
+       "      <td>6.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>thu</th>\n",
+       "      <td>1.210599</td>\n",
+       "      <td>1.384385</td>\n",
+       "      <td>1.344142</td>\n",
+       "      <td>5.844130</td>\n",
+       "      <td>2.269231</td>\n",
+       "      <td>2020.641700</td>\n",
+       "      <td>14.556680</td>\n",
+       "      <td>23.352227</td>\n",
+       "      <td>3.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                diesel        e5       e10     month   quarter         year  \\\n",
+       "weekday_name                                                                  \n",
+       "fri           1.204121  1.377952  1.337810  5.415323  2.137097  2020.669355   \n",
+       "mon           1.212656  1.390277  1.350161  5.365571  2.102515  2020.680851   \n",
+       "sat           1.216235  1.391703  1.351557  5.380457  2.118503  2020.675676   \n",
+       "sun           1.207577  1.384637  1.344506  5.528090  2.187266  2020.653558   \n",
+       "thu           1.210599  1.384385  1.344142  5.844130  2.269231  2020.641700   \n",
+       "\n",
+       "                    day       week  weekday  \n",
+       "weekday_name                                 \n",
+       "fri           14.941532  22.881048      4.0  \n",
+       "mon           14.715667  21.692456      0.0  \n",
+       "sat           15.588358  23.378378      5.0  \n",
+       "sun           15.988764  23.747191      6.0  \n",
+       "thu           14.556680  23.352227      3.0  "
+      ]
+     },
+     "execution_count": 153,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "weekday_groups = buehl.groupby(\"weekday_name\").mean()\n",
+    "weekday_num_groups = buehl.groupby(\"weekday\").mean()\n",
+    "weekday_groups.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 151,
+   "id": "92c12366",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot:xlabel='weekday_name'>"
+      ]
+     },
+     "execution_count": 151,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "weekday_groups[['diesel', 'e5', 'e10']].plot.bar()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 162,
+   "id": "4f808aa0",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot:xlabel='weekday'>"
+      ]
+     },
+     "execution_count": 162,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "weekday_num_groups[['diesel', 'e5', 'e10']].plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 166,
+   "id": "04dedef5",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot:xlabel='hour'>"
+      ]
+     },
+     "execution_count": 166,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "buehl.groupby([\"hour\"]).mean()[['e5', 'e10','diesel']].plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 169,
+   "id": "44318715",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot:xlabel='weekday,hour'>"
+      ]
+     },
+     "execution_count": 169,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYAAAAEZCAYAAACervI0AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjQuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8rg+JYAAAACXBIWXMAAAsTAAALEwEAmpwYAADwwklEQVR4nOy9d5wkV3ku/JxKnXvyzM7O5tXuKguxyiIjMAiERJYByyLYl2DAgAPX5uM6cHEAc69swBgQQWCuwBYgkggSkhGKaCUkrcKuNsfJ09PTqcI55/vjhKrq7pmd7pndHXnn/f2k2enprj5dXXWe93neRDjnHMu2bMu2bMt2yplxshewbMu2bMu2bCfHlgFg2ZZt2ZbtFLVlAFi2ZVu2ZTtFbRkAlm3Zlm3ZTlFbBoBlW7ZlW7ZT1KyTvYD5GmMM5XIZtm2DEHKyl7Nsy7Zsy/asMM45fN9HJpOBYcR9/mcNAJTLZezcufNkL2PZlm3Zlu1ZaZs3b0Yul4s99qwBANu2AYgP4ThOy6/fvn07zj777MVe1pKy5c/47Lf/7p8PWP6MJ9o8z8POnTv1Hhq1Zw0AKNnHcRwkEom2jtHu655NtvwZn/323/3zAcuf8WRYM+l8OQi8bMu2bMt2itoyACzbsi3bsp2itgwAy7Zsy7Zsp6gtA8CyLduyLdspassAsGzLtmzLdorasyYLaNmWbdlOrBWLRYyOjsL3/UU9rmVZeOqppxb1mEvNTsRntG0b/f39yOfzbR9jGQCWbdmWrcGKxSJGRkYwNDSEVCq1qNX35XIZmUxm0Y63EPMDhkOjMxjqy8KxzUU77vH+jJxzVKtVHD58GADaBoFlCWjZlm3ZGmx0dBRDQ0NIp9P/rVuv+AFFQDm8gJ7spbRkhBCk02kMDQ1hdHS07eMsA8CyLduyNZjv+0ilUid7Gcfd1DxEzk7uOtq1VCq1IIluGQCWrW2bLNbw7dt3YHmq6H9Pm8vz55xjYroKyhp3zoAyTBZrS/K6KFd9lKvhhskh1siW4FrnYwtlZ6cEAExMVzFVCk72Mv7b2QPbj+Kbtz2NsUL1ZC9l2U6wuR7FZNFFtdZ4X5WrPiamawjo0nOrJ4s1FGZc/btmAM9SAFionRIAcOMPnsD37ps82cv4b2d+wGI/l+3UMV73M2rKm2Zs6W2qnMc3e/XPJbjUE2KnBAAwxlFxlzepxTbl4Xn+syuAtmwLN7WJNvOcl/KmyrXoI3/nz24JaKF2SqSBJhwTPl2aX3DNC5CwzWdlpoW/DACnrGkG0OS2WsoMABwxCNCfI7LWQ4cO4aUvfWnTl3/pS1/CC17wguO5Qm2ci5Uax3FvODUAwDbhB0vvYqzUfFz/Nz/Dh9+yFZecPXiyl9OyKenHW5aATj3T2nmTPy1hr5ojvuZwrY3Pfc1rXoPnPe95scdOP/3047i6uE0Wa6jUAqweyB37yW3aqQEAS5QBlKo+qi7F6GTlZC+lLQtUDMBf+gDAGMc9jx7BZeethGk8+9jWUjMtATWJAqiUSr4EGUC9ZKXlqiZrPeuss3D11VefiGU1NT9gxz2+dkrEABQDWGqRfipB6dkSRP2nb23D3b89rH8P5PqfDUU0O/ZP4R+/+RCe3DNxspfy38LmJQEtsfsNEOsdHRnBn/3Zn+HSSy/FCy67AH/0B2/F7T+/renzK5UKPM87wasUxnlzgF1MOzUAwBEl3ktto9VB1CW2rtns/sePYvvucf27Lzf+ZwMDqLoiXbFSW9y+Nothe49M4zdPDp/sZbRmc6RPLuUg8MTEGD70vnfgoYcewnXXXYcPfuhP0d3Ti0/89V/iu9/9buy5N9xwA84//3yce+65ePOb34zf/OY3J3i1vCnALqadGhKQ7PHh+nRR+30s1BQA+M8CDxoQ6w0iUpr6t/ssCAIrlrIUwfb7/7Ubj+8ex4VnrjjZS5m3Kc90zhjAEkSAr9/4BRCD4Pvf/z7y+TzGClW86OVX46//8kP4zGc+g2uuuQaGYeB5z3seXvayl6G/vx/79+/HjTfeiLe//e342te+hgsuuOCErFWkrIrzebySRE4NAJAMwPUocumTvJiIhQCw9DaleuOcI6A8BlaaATwLAEwHrJcgWPkBW5LrqrdfPnQAv3jwAABx7fo+g2UZsK24kOB6FIxxWKYB224UGSilMM32HbGXXbQGL7lgTcuv45zj3l/fhRe95OUIggCTk5MoTFcxXfZxwUWX4DcP3Iu9e/di48aNuPHGG2OvvfLKK/GqV70Kn/70p3HzzTe3vfbW1it/AjheUatTAwAiDGAp2YmOAUwVa7BtE9mU3fJrKWtcaxgDWPoA5i9hBhBQBu9ZIKM1tTmc/OOtX7dqExMTKJdm8OMf3IIf/+CWps+Zmppq+vjAwABe9apX4Tvf+Q6q1eoJ6ZMUsiwOLDOA9i3hiI/peksLAE50Hv3//uqDWLMihw+8+fyWXxs0qfp9NhWCqQ12Ka41oOxZwaJeckHoeRdmahgr1JDPOBjojtPq/cNFeD5DNmVhsDfbcJyT1Q6ayuv1it95Fa590+tgGgamZKqlYRAM9mawadOmWV8/ODgIxhiKxeKJAYA5Um0Xy+YFAKOjo7jpppvw6KOPYvv27ahUKrjppptw8cUXH/O1H/3oR/G9732v4fHzzjsP3/nOd1pfcRsWlYCWkqkL0j9BPVMKJRe5Gaet1wZN1vpsagWxlCUgSoW8thQ189lsrh46YWrlCVzQPKyruwupdBqcA5deehks08DwRBkzFR+EAKet6pzz9QcPHoRpmujo6Dgh610yALB371586Utfwtq1a7FlyxY88sgjLb1JKpXCX//1X8ce6+7ubukYC7FQAlpaDeGUhHKismgWojWrtQZRBrCEN9V60xLQEpRamoHrUrdnYxqoYZi49PIX4e67bsfePXuxadPGSEsLIRH19PRgcnKyYX/av38/fvzjH+OCCy5AMpk8IeuNSUDHyeYFAGeddRbuv/9+dHV14fbbb8f73ve+1t7Esk5qQcVSZQAnOgjsB6ztOEiztfrPojRWbwmDlT63S3Bts9nchWBLEwDAgevf9T48/ttteNOb3oA3v/nN6OkdRG3qCB55eg/27tmFO++8E5/61Kdw8OBBXHLJJejv78eBAwd04PfP//zPT+h6Iz+Oi80LALLZRh2vVaOUolqtLsqxWrWlGgQO6wBOzLoCShfAABq91GcXA1jYWis1Hz9/YD9e8/yNMBa5kvjZVg8Stfo9nnM+Z3XtyTQOju6eXnzmc1/FD/7z67jtttswPj6Oro481m04DR/4wAcBAJdffjluvvlmfPOb38TMzAzy+Twuv/xy/NEf/dGcMYJFX+8cDfcWy05IELhcLmPr1q2oVqvo7OzENddcgw9/+MNIJBIn4u2XMANozKyhVHjp6WTrmTrHsoVJQGKNQRMG8GyIAajP3e4m++CTI7jxB0/gvE19WL9ycTVgnU31LABSZbPp0xyhx7rE9n+91q7uHnzs//s4ko6FkZEJdLIpTNAcegd6AQCvfvWr8epXv/okrlTYXDLbYtlxB4C+vj68613vwhlnnAHGGO6880587Wtfw+7du/HlL3/5eL89gCXMAILGTfV7/7UbP7t/H770Fy9b1PdiTAQa2wXBEKzC16eCabwq9QimvaXfyG6hDKAmK4mj06QWy+aSAu/adhC5jIOtpw8s+vsuxDjn6DTK8Hiu4XETFDnDxTRLH9ciplaNA0gTFxwk3FTlPwj4kpOsTsSwmuMOAB/5yEdiv7/61a/GwMAAbrzxRtxzzz24/PLLWzre9u3bW15DMDOJPqOI3XsPYFuqeZ7vybA9e0sAgEKxhG3btgEAntgxhZHJCh566KG2bhx1nHpTzfDKNW/W58xlRyZFP5RSpaZfv7K6Cy9PPY6bxs7Gtm0nrsK6nfUfHRbf+8jYRFuv37VnBgDw2Pan4RYWNwWwXBYT1R59fDsGu5zY+r7+o2F0Ziyg3Luo73kssywL5XJ51r9zr4YOo4opaqNcDr97yoAU8ZE3KiixBMrlStMU9rmOfbzMpxw5owYOoFargQUEnDGACACoVmug/uKB1UI/owKkWs0Fp7P3I/K89u5p4CTVAbzjHe/AjTfeiPvuu69lADj77LNblo6Gb/k03pLZhdH+P8bWrSeuneuxbLi6B0ABtpPA1q1bAQC/2vkwOC/jvOecD9tqbVPdtm2bPk69las+8O3DoIzM+py5LLN/EvjpKAzD0q9/8La7xN9SybaO2Y7N9Rmjtv9oEZZlYKhPxJzu2rENQBmZbL6tte6a2gFgGoOr1mLr1tUtv34uM3/6CwABTtu0BeXxvbH1kdt+jkQqfcLOr7Knnnpqzlz9WtUHmJhJG32e51NUposAAINwJFMpWGa8Gvhk1QHU3AB+SdTVOokEMkkbpaLYpAnhcJwEMm0USTazRfmMUwUAgJNwkEnNnr7tOA7OO++8Wf/uuu6sjvNJaQbX29sL27YxPT19Qt6PECBteEsvBsAaK2mVRLHYa41KIO1QymaFYIQJWYTTpddg7fO3PIov3xpe9AuVgNT3cTwkIF0P0iRFteYGupHd0jJe91P+xjkICWWVpdSBV7VUiK9L/DSW2lojwfTjuayTAgDDw8Pwff+E1QIQO4EECZZkDCBNXARBeIOrPPV21/q1Hz2B/+8L9zY8HkvfbCMQ2iwLiDCxRu6fnHa5c1nNpbHOn/4Cz6sGgOPQTXSubLCaR5cmAMyyOzEe9q0xsLSK28QGX9fETscAll7aKgGHAfbsAYADBw7gwIED+nfXdVEqlRqe9/nPfx4AGqbtHC8zrARsQpccA2BeBX/VeQs20T36MbUJtLvWw2Ml7BsuNjweRDbudjbBZhlLhC9dBuDTeM2Dt8DW1TX5fVSqi78ZNzu3gOi/5AdMB6CXkvE5GICBaGD1BC9sDuM8ygDif2v22Mk0zoEOo4J+s7g0gsBq0969ezcA4NZbb8W2bduQz+fxtre9DQBw/fXXAwB++ctfAgDGxsbw2te+Fq9+9auxYcMGnQV033334corr8SFF164mJ9lViN2Ag6WHgOAV0WCBMggBEklUdTaBADPZyhV/Ibsi2j2TjsyiAIQxjgo4zANEjKAYOkxALHeSOtqP8DFzi4c9s5t63g1T2YBHUcG4PsMUQXale+5NBmA+lkPAGIzBZYgAxD5PyAgelMlEhXIUlsr5zDBYILheA4znDcA3HDDDbHfb7lFdNMbGhrSAFBv+XweL3rRi3DPPffge9/7HhhjWLduHT760Y/iuuuuW8CyWzNiO7ARwF1iNxKnYj0GjUpAC2MArk8RSO836YRfb9S7bOfYAWV4e/YuPOatQUAZCAwYEMchwdJjAJQyUBYCYI93GK/L3otv0vZkxxMRA/ACinSEk6uNvybbKy92AdrCLJROosY41wCw5FIrtTzVOBbeAAddQmuNxSuOYy3wvAFgx44dx3yO8vyV5fN5fOpTn2p9VYtshp0AIUDguyd7KTGjvthMTFBQymCaBlytVbcHVsrTL1f9OAAsggR0hn0EMywFP2AwCGBCHpMtPQAIKIs3IwvEd2+0yVYUAFRqi+tEcM6xAuPosUvwgvOASLJHFKhdnyKVWELNeyNB1Cjb5JxrUCCEL6m5wCE7ITLIGq7NIBzB0lmqjlcQ/DcMAp9oI7ZIG6Xe0gIALrNoLMIaetW0ywBUEHmmEt+U/SaZRq1YEDBJSSn8gMIPGCzFAJYgAPgBjwOdYllz5FPPZepYiy0BUcbxwuRTeG36Nw29gKIy4JKUgRDKPcpYvQS0pLzqKGjF5SqCpdW6QscryPHNTjo1AMASAMCWGANgMvvHAm1IU2w3BqA2qlIlvtHFJKA2AIBSCoswWITBD8R/FpHHpEtvc6Ksru2FDFS3C1YqBrDYM4WDgMECizkB9e8JYOkFgiObUnR/4iyeBrqE9tS6IDCXMQFhhCw1sII+j8sAsEAzJANgbTKAv//6b/Cl7z++mEsCAHCpnVuERtoVSwbQZsBaeZGlOq06CBg6jTIypNZWS+RAylUWKIKAIaBMS0AmD7SOvVQsCBgo42H2kwQAkwd6ulkrdrxiAAHjMAmDTWhDFlDUCagsNQCI6PzRDYoDOgtoyQWBZY0CIWGefZStLKH9vw5VlwFgQUZsIazyoD0A2HtkGrsOFRZxRcIYbWQAOgbQNgMQry81kYDemb0LV6e3tRcElgDVjAHYhLbVZO2xXWP4p3/fdlw8nIZpZSw81+1IYDVdB7C4GzGVQGqBon4qWNTrX3IMQFq9Rs1Y6FUbZInl1tdtqtHrLhqwLpfL+Od//me8853vxEUXXYQtW7bgi1/591m/g4cffhi/+7u/i/POOw+XX345PvGJT6BarS54qUT/exkAFmQqBoA2A4BVN0CxfBxSHWm4qXo+jXms7TIAle9ezwD8gCJNXGRJra1jq1RPCww+FQxAxQBs0t6m+siOMdz18KFFP7eUhdKD+qwq06rdtaqUTNejsZqKhVpAGUwi5DXPi28wSzoGEGmiFsupiWQBGWTpMYDov+MxgDBgPTU1hc997nPYvXs3Tj9dtI6hjDe9b5566ilcf/31cF0XH/3oR/GGN7wB3/72t/HRj350YWtFJL6yFOoAns1mLAIABMchGZdJr9SWDCAaBGzHS+ecRySgxhiARagoiGsnBhCRq4KAwTcITMkAogymFVMe1Xihio7s4rUGj8pRridbX/AoALS+VtenSDgmXI+iUguQz7Q3WrPeAsphyhs98D1EEyvdWAxgidWwRCzGABpklSUEAKhjAAjPdpQB9Pf34+6770Z/fz+eeuopXHPNNQCas5nPfOYz6OzsxDe+8Q3d+2fVqlX42Mc+hvvuuw+XXnppe2uNZFMtM4AFmgoCG8xvWf9ljKPmUZSqXlva8ZymGQBtmNZV81r3+CgLe7CX6yUgKoKNNgna8oBpXcA6GgMQElD7ssp4YWF0ud6iHrrnUwSUw1ZsBa2vNaAMAeXozotRgPWB4HsfO4JPfOWBtteqmBT14seNMYA2rgcA+P5/7cLju8fbeu3cNksMoK4X0JKaCyzXOTw6hr/9m4/jhS94Hp7/O6/E69/xPvzkjrsALhbrOA76+/sbXl7PZkqlEu69915cc801scZvV199NdLpNG677bYFLvX4M4BTAwBkDKCdzU9txJw3ZtYAwHTJbVsS0GmgYHJYy+K0awCaSUCSAbSpgfMgTFn1A4Yg4LCIBDC051WrTW3xASA8D64vtHW11nauAdejSBEXL3UeBQFrOLdP7J3AA08Mt3UdBJTBkBsmq2OoUc25XQno5l/sxO0PHjj2E1u1SA+duLTOm3rVS8E45xibmMTb3vsRPPboI3jLW96GD73vPejr6cZH//ZT+NltP5zz9fWfZceOHQiCAGeffXbsccdxsHnzZjz11FPtrxXLDGDRTElADoKWpZXojVevVXPO8Z5/+CV+fM/e9hamgsDSg456pu1V6x4DAMDgkNbPAQCwQBWtMVEHQCmsKANoJ7Aqz+3YcWUALFaz0A4A1rwAZ9qHcWHtXgyahQYGsJAisSCyNlbXVK/mUZiy+rfdILDrBZguHb/0Z0LidaqcLe1K4M/eeBMIIfjyjd/Au/7gD/GGq1+NL3zqb3H5RVvxlS9/AWwOylL/p7GxMQBi6FW99fX1YXR0tP2lRqS04zkV+JSIAaggsNOG/h29qesBwPUoZioeRiYrba0rLASjelzjOmsMp1nDqPorWz6eHwWA+joAP4BFWFvnAIjULBAKnzLYAQ8loHZjAHLjPJ4A4PqCncQyllpkK65HkSDi86eIj3JdQ7hqZFpYq7EBysIYAAvqJaAAz8/sRsG3UXVPa+m4QChdTS9SkH3msbsw86io9vc9FzUwMBAQy4FpCF/S9QKMIfwcFDaOOPFthlKKabP9AUK5816C3Lkvavl1nDHc/qt7ceUVLwKlASYnp8Cmp1GFj8sv2op7HtyGvXv3YuPGjU1fXy8B1Wo1AMLjrzfHcfTf27IYqi4DwIJMAYBNglhgbT4WZQD1npSSMNrNDVfN1Cww+L6IATzX2YvLEjtxs3dFy8dTDICQxkrgQHqXbQNARK6qBQyBxcIgcJsMoOoeLwkoHgT2AxrGANqIV7g+hQMFAN6sDKCd60C01ZCN9powgOdZT2DSyGCf+/yWj60Atng8GcCsfyBi41pCBGBqahIzpTK+/f0f49vf/3HT50xMTM4OAHUbcTIpYkKe1wiwnufpv7djqnGd+GUZABZkxBI9Fp02ZgJU52AA1QXOieUs3JRqVGyiNgLYhMFzWz+mAoCObKJhTcqDbzcGEGMAsg7AiWyq7TAABcaLzgAChlXmBCgMeD7V8Q+gTQnIpXAkA0gSr+Hc6uugjSphypiW0uq7qta8ADahSJm0rcpwdX5nYwA1N0DCMec9ejR37ou05z1x+BCyRg0et0A6VyKbFl7woaNT6MMEiJ0E92s4TLsxONQVe4+TNRFMyTtXv+IKvPBlVyGRToGUJ2AZABjFFMvgtNNmZ1r1DEBJP0oKitrY2FjTQPJ8LVoHsCwBLdAIMcCIBQetzwSIVmBOl+OelErNq9fb572uWHGSCAI7cqOifuv00afCa+jJOdg/Uoo16aLSu7RJAK+dFNNI0VpARS1AOpIG2g6rqMrzNzFd0y2mF8Mo43h9+kHUuAPPfzG8gGqd3SJUF8vN11w/0ACQIn5DMdhCGEAQcM2k6ucq1DwKmwRIwm8rCKxAw/Uoal4Qaw5Yrvq4/m9+hg+/5bm49JzW5UZlpL5XJZczdg0hbBGVb78EGpl2dnQgk06Bc44LLrgAqVwe5vRhWJYJUA/jNIdcPj/r6+sZwObNm2FZFrZv346Xv/zl+nHP87Bz505cddVVba81mk21nAW0CMZMS0hArTKAOYLAC2UAUBKQzKxxfZGnD7TXtiKgHFentuFN9AcIKI+BXVReCNo4tgIAU2cB0VgaaH0V63ys5gVwbBOMcRRmFqCX1pkfiGB3gvhNYgBBQ9O1Y68zZABZK2iQgKoL6BMUsDCdth4AXE8Al9MuAMxx7RZKLmoexaHRxoFNx7JosRdBXZaK+rfU+I0l1GPHNA285PmX4Wd33o0D+/eHE8IMsdbpwtScvYvqGUAul8Oll16KW2+9NTYA/tZbb0WlUsErXvGKttcaz/xZZgALNm7YbWXAqBsv4ZgolmYBgDYbhBEeplH6gZKAFANofZP2KUePOYMuNglAMJOkbCEcDTC20xU1ZACyFQTl4aYKilKLXjXnHDU3wLrBDuw5Mo2xQhU9HSn99x/9eg/GC1Vc/+qzWl6rqlFwSIAZXxSuResAZtpIA7VlDCBvB5isNs/XL7UxLSwIGNKqrXaTILDFAzhkYQwAAIolD/1daf27kjbrY0Xzseh21DhJSwKD3FSX0lxgzjn++A+vx28eeQx/8D/eide+7o3YuKITxXIV25/Yju079+DnvxBB7m9+85soFosYHxc1FA/edzcmxkfRnU/ive99rz7mhz70IVx77bX4vd/7PbzxjW/E8PAwvvrVr+Lyyy/HZZddtqC1Rn5p+zjHslMHAExbSEBtMoCB7nSDF1VbYBAYjAJGPAvIlp4mbwMAVMGTzWoAOEpVH72dYlNlfrjGdrqiagAgDL4fILDNeCuIFhmAHzAwDqzqzwoAmKri9LXh3+97/CiOTpTbAgAqwYlAbN5erA6g9b5FtUgWUMYMcLAhCNw+A6A0KgHVSUs1DyYobPhtpYFGnZ16+VJd1zNtZAhFGYD4PXxc/2KIrWWpNYTr6+nGt/71M7jh6/+J22//Gb4zMYGuzg5sWr8Wf/COd2q28pWvfAWHDx/Wr7v313fh3l/fBQAxADjrrLPw1a9+FZ/+9Kfxd3/3d8hms3jTm96Ed7/73Qtb6DIDWFzjpi2zgFoHAIMAfZ0pFOqzgGrqxg/a0rANHq1OFRJQVm5U7bStCCiHTSgMLrJWoqmgUXmhPttkXsbCDSjwPfi+pRmABTrnrF0/YLCtuNqoNqDVK3IAGjOBimUP0zNuw2jL+ZgvGYAB0b/FW2AQ2PXCGEDG9BvmAqtYRltZQJGKakKbZG6ZgM19VNtICohWk0/Pwl5nmhQ3HtN4vIWC8lZjvXUiDGDJ7P9ynb093fjIhz4MO9uJdOkwzGwHWLmAaZbW+250uNWRsZKO+2wc6mg47AUXXICbb7459lhUEmprqTgxDOCUiQHAtNvLAnIDJBMWOrKJxhhA5AZrq0+8jAGYhMP3A6FVS68a1GuZOvuUawaRIl4sOB2VgNpiACw8b9T3dWsIYO5CsB37J/Gmv/gxhifiN4SSJ3rySaQSZlMA8ALWlvQhGqzJtheqc2kkXtHqNeD6VAfnU4Yfk/wo4/qzt5UFFFANpITHX08j6YXUbT1GEpOA6hhAZQEAwAGNAAShfxqLDUgAWFIMICarRNtDEwDGrIVr8V5HJ+iznKBzdsoAADHbywKq1gKkEhbyGWfWIDDQnvenGAAgbnYvEgS2ud9ya4Foz5u04cVaQscCjO1MxYrIE8z3QSMMxZpDVjk4UkJAWUM7bSVppJIWejtTsVRQzrk+1/Wsa15LlV61Lb9vP3pe20hZjQaBk4jXAUTrStrLAgpfT+okoKgMyNvICnPnxQDaiAFEPf3IxKpoIzjEGEDjZhZQhpHJygkGhzpZRa+LAITMOhg+uv4Ttd7GOMvxed9TBgBg2XCM9hhAyjGRT1s6nU5ZtENjO6mgJAoAgQAA5Wm207ZCSUAAkCZerCMoj2w0bXVFjTAAFvh6njFxknM2WFPn5fBYPNtEncekY6GvMx0DANF9VWzShZk2YiGBiAEoZuLFWkG0fg2ISmDxmgTcWCVw9DtqpxVElEkZoLrhoB8wnSYMACb1WnYIFANIJcyGIsbaQiSgSJ8aABEJiOt0TyKzgAjhoE066dZki/V2254v3CKbKiEAMWbtXhr9XCeMAdS9z/F621MHAEwbCdIGA3ADvAE/xWmHReVglAXUFsAAOOcwEN7Q1PNiUkM7UoUfRADAcGdnAG0BQPhZaeBrSclw0jAJRzBLhbUCocN16YYKPJOOid7OVEwCip7jdgDApwyGGrPo+bFCMJNw+F5r31XNC5AwZCEd82JST1QGbMcJYJHvxY4AgOsFWs4DgARpPRCsAKCvqzGBIRoEbtW7bHi6ZgBcTwMDMQAQWEZzaUx50ieUAcQGwCAOAAYRc4GbLIdxwJLxvRO23rphNfw4BYJPGQDgC4gBdPMppCojABBLBa0sAAAoiwMAC3x4PtPphu2krAYMWgLqcmh8Q6JRqcFv+aYnEQbAA19XBhtJkVoYzBJXUG2p6xlA1QuwxTqC1L3/ht6OJAozrq4liG5W7TQyozTU/APPjbWCAOLa+nxMALPMgmI1WQkdFlkBIk24rSygSHaWRaiu5q558TUniN/yWEjXC2BbBrpyicY2JvJYlPGW4yzxRmVoCAJzEKGrGwYck6BaaxwZqjzphWyorcsi8U1VVQYTEBBiwCDiXNS8IH5sxtBPJpAg/omTgOoBYJkBLMy4Ycd6AT25d2Jec2yrbgAHPqxABDFjDMALkHQE1W0VAILIJgWIVsCeF2hP1SFBy+X/QYQBdDhBfCxkBAAsBK23Lq6XgCSLMByRZjrbphpKQOXYRV1zA2yyh0EOPIyBjJoLIHTuhTKAIAjCFsu+G46vNC251taOGa0DMJkPA0zLQIrJ9OSTbcUAWOx7oVBKmmoDoSxBgrYYQNIx0ZFJNLSDiG76rcYBGrzRqAQEhGW/xIBtCqioZwHq8mtXUpks1rD3SBG0lYEDKl0VwttXE8CUBGQZIuZ3cKSE4YmwwaOBQMeUTlxR2yxsZZHtlAEAmLbWf3cdKuDPP/trPPjk8DFfVnED2NyD4QoPNppPXXOpzrNvNQMkiOR/A0Kj931fU+h2YgB+EDKIvBXEp4LxeNZOq+0QogDAaSMDoLOkliqNuVz1Y4FIkVsvzlmfLTZ+JQNFM1baCgJHdHXuu/B8UVFrJrNyra0ds+YGsBGA2KK5V4qEMpCSgHo6UijXgpZv1Gh9hk0oArkp1VxaBwB+yw5BzQuQcCzks05DQ7hoj6uW4wCzMACms4DEtkKIAZNw2CZpmFGtNtJ2hixNFmu6fUiz+MKcCwcAYsQDq0QwFtskWLcyj3TC0kpBtLaBkMYBN5QyTExXF3+DXmYAi2vctGBBNFl7cs8EgNDjBIDhiTKe3jfZ8LpazYPFfcAtg4DFvNOqG6A7n4RBWtd/gyDM/wakVx3xTIVc1ZrHxyjVzlfO8mNrIjGtufWhKEYEQFhdDAAAuASA+x4/gh37w/NYqvq6PiIqA9W8QBdXdRiCXY1pABDH6s4n2wOAyKZKfQ+B78MkXIMVD1r7rnzPE4Pbc10AgCTxtbfvegHOd/biNdXv6ulxrVicAbCIBBRoMAcEA6i2GGSueRQvsh7BanoA5VoQy36KykmtFoNxqPRPebHVSUC6boMQcM6RSTuouEHMW+dtxgCKZRcT0zU4tti6WgEQJU+pHFau1yMYAOcMlmnAsQ193KjcZTTJaKq4ASaL7nGY2bwcBF5U46boCEp9F0/JjT66mf+/n+/A39z4QAOSM51/zZE1/ZiWWnUDdFtV5JJGwwjGYxllcQDggRcr0GprcEtkk69PA4168E4bwfBoxhKngd64jERaHl6s/QvffQy33LlLP7dU8bFeFs9E+85UIx0203QaQMgApkseLJNgsDfTlgREoxu872lAMBKiA6Wqg7jn0SP42f37jnk81TvJzHYDiLeErroU66xx9Nf2SWmoteuARdhKQwwgygDgtzwW0vUoLmK/xWDhMQBxZlV1A3RkRQfPVhmA7qFDjMjvCIfBRCQgcIZsygbniBXQsQhrmM0Y4xifrsaAo1Tx4VgGBmRbi5YkIGUy5TOeBUT0LmsYBIyJv4espnlNg/q9nYl4c9pyEHiRTQGA52pPPyrnTBZrmKl4sXREP2AwWficFWlaxwB8vGr8q3hBagdKLUpAfiCKlZQXxalfBwCtZwFFWwmk6toWGzwqNbTOAGIAEPgabIyE7N/je/ADhqkZN7Zpl6s+1g/mYZkGjkQZgBsgKQGAlKeQSzsxBpDPOE2Dl/Ox6KbKAk/PQjCSGbl+8fsPf70Ht/5qzzGPxxUASAYgJCDxHq4nYkTh4y3q6ZHvzEYIAG49AJCgZS9TsYgEE3p2PXvtk5to6zEAxLV+6cgwDhgEGhiIIQAg6ZgwTRI7N/PJAipVPEwV3RjzoYzDsgyYZhtZOVytXMYA5AxgyIC1mglsRjJ+RLaesGaN7RSItNNi/RiLlf83GsZuLqadMgDADQEAk5NFjE83BhvVRrP38LR+rOoGSJLwou1NxQGAeTU4rIYes9JWFpAJBm7KaULUj1Xo2hBBYMY4Pvx//wv3PHpkHgcNb5Qkd1Gqhil+KouHG+31RIoCAFgQxgCUVx34UgsNzyXnHKWqh45sAoO9mZgEVPUCpExxzKA4jr6uVCwGkM8k0JlNtMUAYpO1qA/mxQFAgdfkdG1emTuqCMvKKgAIJaCqG50W1jgr4FhGZ2EAVbdeAmo9DdRzPRhgsGUCQz177e8S4N1ODACA3ujDuSXCWyZGyAA4Y1JfN2JyzbwAQJ7L6OtUyxVDvkd7MYA4AyAqa4nLDV8dmwnNXzMA0oQByF9b7YV1zJXqc0xixXaLbacOAMihMIGUdNJJK6Z9qptjz5Gifqzqhjo1APQm/AYAAICs2fqNHygGYMmpQTSIDQRRElCh5OKZgwUtW81pSgIiBhxW0y2hGeMwOAWHAW4nWm6LzTmPVS2DBrouQOvq1ItIOOJcup7Y0LIpG6v6szEJyPWoZgBBcQJ9nVEAEAygM5eQ2nVrNxeNVdd6OtdegRUCAYwT09V5fW88iEtASRLKa9E+QUnit14MRuMAEK8DkJ/bspFsoyMo88T5NH0FAPEallzaQSphtSUBxbT++iCwAgZCtFetZBW9tmNIQJQxHadoCgCEgJD5xwBUhhKXcg8hkWI2mQWkqoPVeEsmAWGuGIDamF2fLu4mreWpZQawKKYYgAMxBemsDT16o2KM65tj75GQAVRqfowBdNq+1lEpZSByY0gbfltpoCYYuMws4c0AwKcNm+qcJjdlM52HRcXrZiq+TDmlYIYJYjoiC6iFGACrq1kAC3TrYiLTQEF9LeGoTVtJC9m0jaG+LIYnyjr1tuqKNseAYADRdhDTJQ85CQAAUJhpcYOKxEII8xG44tyFYCUC5F7AUPPoMVNi1feigsBpw9ebZtWjSBrR6usWYwAaAAhssEgaKNUT18x0BxwS6KZz8z62YpQ1Abz1ElDO9JBLW20HgfVGr+QKLgUWCQyEGNqrNg3SEgMoVwO96YUBWeGBG4bw2OtBRT2n6Zr1wyTy/5ARfO7fvoxzX/QqQDKAV19xMT7/uc8KUCMKADSehZ+Dq88TTuRbDCPg+NjffQavfNPvLbeCWBSTOeA2CbBpdSe680l9Q5Rrvr7I9tRJQIkIAOQtVwNFNI0xCbf9OgBLbHKEBdqDJ6atA7UT0/MHANVLxsx1wwyqADgqblgJyw0LxHZazgIKGIcFBkZk81ga6IH2KghMqB+r5p0uha0osikHQ30ZUMYxMin06FqEXdGZSfR2iDGWlZqvGUBHVgJAqbU+ONEYgA0KzxXrMKUERFh8rXN57ZRxmDLAbUoJqDNBNQDUvABJQzGAxnnBxzIdA7ATTYLAAWBYMJNppM0g1oZkXsdWWWWBC4cEOubFGAfxq7hsx2dwfuJg6/2AIvKE+H0WBmCEXnUjAxA/Z/Pgy1WRCGCZBEwCtHqu8tDrQeXIWAljU83Hi4YzdmXAN9bOgujPwjnTEhCTGaAqNbtZXyMeef/FjQPwOX5bPJsXAIyOjuLTn/40fu/3fg/nn38+tmzZggceeKDlN6OU4qqrrsKWLVvwta99reXXL8RUFpBDKM5Y162bu3HOtc68bjCPkcmK9uLqASBneJipeKCUxeShBFoP/gWUi2HgkgEQ6usmbUY6Jwp/vECnqtY382pmesRktgtEtoSuVIOwG6ZhgVjOnN07m641EK0VmBkFK/F6HQSmfuzmK5RcfR6zKRtDfaLt8yEZBxCVrj6InQA4w4qkeO7YVBWlaigBzfezR43RaMZTAM8V6zJkHQChPiamQ1CZC7yjLRkMJw1iJ5G3w1iQ6y0sBqCAlDgpWQgWpoEmTQZiOyB2CimDoir75/zbdx+bnxwUiSkNpKmuYq95AXKkCpP56Ldm2pOACJ+FAdRlAYkPCTOSWQNEGEATz5YxjnItQDZlw4rEDpgGAKJ/RgGg6gWYLnuxNujhmhVrEQxFhIIjWUA6pVWs9bs/+RXe/o4/kKAmzABrEgPgkHjU9J5q23OPvOykM4C9e/fiS1/6EkZGRrBly5a23+zmm2/GoUOH2n79QkwDAAKcvq4b+UwCVF5oyrs+f4sY4qxkoGgQmNhJpElNBDnLXgwAbFZD1aXzqixWphmABADwQOfqm6kcEgaNS0DleTAAJQFllVQhgElnHBkWDDvRckuMgIpKWqbZih/GADQDCDBWqOp7f7oU9iLKpG0M9YvNV2UC1VwfFvdhd4t5tD22YAZ7j0yDc2DD1P1I//Y/AKDlcZG8rr+OV4sHgS1QzUSAYwFAuMET24GRTCNrBRoAotdBxgxaBwAJVsRJxQvBPIqkyWFYDgwniaQhsoBuf/AAfnTPXjy1d+6YEGUchIUb4UCa6mtIyG+yYND0WpeAdGGU2uDDDTpsrxxKQSqwyqF0dSkjESGd1G9u5ZoPzoFMyoYR2eQ1AzBDAFDtHBgLi7RGp6qNsp4Cp0jnTz3TILL/g3MYhMBxEiCGGFdKIgyANmnSZpkGLJM0AECx7GL/8AyCFrvP6gXLdz3pMYCzzjoL999/P37+85/jXe96V1tvVCgU8M///M945zvf2dbrF2wSANI2w+lrBQMAgGIplHXO39wHIMwEqtYim3xXP5IynW6qWJOFTOJmt6jYoOqHhc9lahIUcQQAmDwcXG6kcroSeDwiAR3LC1DFWmZOBCvTxEO1FsCn8tgSAOwWs4B0vEIxAE412CgAMHiA0akKVvXn9HrLWgKykUvbSDqm1vkD14MBDqdvNQAgDwEMu+W575zeAb5/GwCg0CIDiKVWEqrz+NVabUJj8wnmYm/ROc2Gk4SREHKMigW5HtVpoB0ObekaABACqZNqKARLmBTEckCcJBIyCHzPY2JKlZIGZ113JDgNAL3JQF/nlVro2KQNr42W0PI61AOQ1AYthvCEQeA4AwBUaqV42DbDYGts7T4FAZBKWDEvXzlYSqIxjJAdqA2/M5cA47xhvgSPbKiPPLodv/fu9+Nlr7gCV77lnbj52/8ht1mxVhUD+NK/fT4WBB4eHcWnPvm/cOmll+Lss8/GVVddhV/8/DYBGLYJN2DwfR+f/exncfXVV+PySy7AG656Kd507bW4+9e/jq3n4Ycfxtvf/nY897nPxXOe8xxcf/312L59e+M5JkuAAWSzWXR1dS3ojW644QasWrUKV1999YKO066pIPA7r9ws9WUJAGVPV5uuW5lHZy6BPREGkCA+QAjMXC9sKgFgRlT+JeSNb1K35SIgtamq9gI2wo3GTOd0N1AlVQSUHzPDxIhIQACQIq5mAKIXjg3TSbQcBFZtK7glzpnBaUMMwCYUw+NlnLaqA4AI3CoJKG0GIISgpyOFCSlpUV/coHbPkFhrUAQhYQzGDipglSKSjtGQCvrXX74f37l956zrZTEACHQGk2IANiiOjkcAQK6zWPbw9r/5WaySueZRJGQ6JrESMBIZpIgXYwAqXTNrtp4MoKQ0M5GKxQAE8xASkOGkkECAgyMz2HmgAACYKM7NitzIugGg2wkTGKLSZho1lKteS/n0jQxA/FBavaaBShthDAaJpFbK11sKAOplFcphmCLQaxpEb/x0FgmIc67/lk5ayKcdlKrxhoeci1YOz+zZg//xwY9gqjCNd1z/dlzzipfhs5/7LG7/5Z2xzwaIGACTMYCxiUn83ns/jCce/y2uu+46/MVf/AX6+/vxv//6L/Gz234Ixzbh+RT/8i//gi984Qt4/vOfjz/+yEfxprdcj+6ePjy07VF93HvvvRfXXXcdPM/DBz7wAXzwgx/E8PAw3va2t2HXrl2RcxoGrI8XAzghIyF37NiBb3/727jppptaHu+3WMZlEDghMzYUA5guuZguuSAEyKcdbFjZgb2HRSqokoCIk4KZycMc2QdANCjLZxydxgiIFEAR9MzMaz0BFcPADcsGIyYsQmFLD95I5WDDFwygUNUX+nTJRSZlNz2eqCuQm4mSgGRQ0lf98A0TpiMkoFYqFxVYwbDEWkHhBQFghs3g1FjL1QM5OJaB6ZIL2zKwwRrF+L/+AVL/4waR6ik9V+7VABuwct0gTgqsNIHu/CrNAAyvBE59DGRJDAAo43hkx+jcC44AgINwHrDhJMGJAZtQHBkvI5uyUZKBZwA4Ml7C+HQNOw8UsGWtYFFRT5o4CRiJNBIoYaYsNk3P9WHJjTZjBa0XgqmpcMlUrBCs5gZIGIIBGE4SNnzdoMwyDUxOzw0A0SE2ANBpi6IqIC5tJngNjIuMt2zamfOY/7X3fty5914EAYXBPBDTBqc+Am7C2eGgJjO7iGmDmBY4Z+C+C2I5YDDEvIsdJjhj8GmYGZTYaWqAAISWzjiQfNqETxmCgCG50wKlYrrbK/3n40UbLhWykgzUKgZgGQZs2wDnAliUXKRiAJ+/8esghOBr//JPSPWuQqdRwStf/2a85jVXqy8k/G5UGijh+OyNYu/67Be+hrM2r4FpGnjLW96Ct133dnzli5/DG17/WnAO3HXXXXjjG9+IP/mTP0GxKuoDMkkbUzOuOD+2gb/6q7/C8573PHzhC1/Q7/WGN7wBr3zlK/G5z30O/+f//B/Ew77Hqw74BGUBfeITn8AVV1yBCy644ES8XXOTEpCastSREXKGYgDZlAPTNLB+ZR4HRorw5TjClBHAcFIw03mdTjc1U4ulMQKtBwDV2ELDsgHDEgCgGEAyCxMMtZqLiekq1qxQssrsUogfhGmDlpSAMoaHSi1AILOAiGWD2A6cVoPAMl5BTAvcELOAlcxCbEcDGCB6z3fkEiiUXMxUPKxKlQFG4Q7vQU9nEhOFqvD4ZAotcZKw8j0IpkUqqDiHHEQ23xvI0FgGVKFMNRjOZtHxlTYJtLRGTFt3hR2ZKOvzWpItClSQdCoSc1DZOJwQENOGkUzD4a7eNAMvfG6atMEAohIQoVBysWoFoSQgm4u1bRjqwOqBbCyI3cxqdRJQ3hSMzPVpPH4l04WLbQ2GCY0jsk01cfKiD6nNTDkszZqL6jhy5EVhcZR8faRgS7EEkTkktrVoWiYHB6UU9z34EF764hdioK9HH3vjxtPwvMsvC988sg7GOQjnuP1X9+JFl18MTgNMTE5iUv53wUWXYGJiHEcPHwQAZLM5PProoxgZGREARIh2Nr2A4umnn8b+/fvxqle9Sh9jcnISvu9j69atePDBB2Oyk/q4x0sCOu4M4Kc//SkeeeQR3HbbbYtyvLhO1oIZJjgxcOTgfuzZtk2PMHxy5x4cnvCRsBi2bdsG4lUQUI6f3vkA9h8q4zmGD48BRydnkA48ZO0AO3YfxGSHFSsSSxEPjz2xA3Tm4LyWs2tvGSvAMDE5hQwMWGAaAI5MTCMNYHR0AgE10ZEU77Pt0SdRmUw1PV7FDT3dJ/YeQieAnOlh74EjSPJJdICh6voIpoqwSYCDh49i27b5BVePTnrIEoZKzUOGE9EYjVBwAA8//AhyxNRrnxw5AJsEOHB4DEmHYA0R77H/8YfgV87BRLGG+x54CI70mnfvP4QkHJDhAzD5+QBE3xvVuygVFLBvzMa2bSIeMFEUG+zoxIx+rN6qpRn9bzsCrI8/9TQyMDRbSRoCRHbt2Y9t2QIe2y1koWf2Hsa2bWJj3HGoigQJwIiFhx9+GOmZCognnnfvAw/Dq8wA8iuxaAUTU7Ovq5n5bhUgwHixBAcUQSCuw8nCDAzTRalqojA+iRQoTFCs6+U4MOrh4HB1zvc5OOZqAOCmA14eA7AWd9/7EA6MuVoCIq44V7/Z9jhW9YYMwLKshsHmF/Sfgwv6z0G54qEjmABNdcKoFlBkaSTzeUwWahi0CqCpTnA7BXAGa2YELJmHb6UxUgjQmTFhEKBWrqDXnMEI7UAmm0TSDn3R0WkftknQlbVQ9RimShR9HRbKNQbXZxjotFEulxFIFluuVFB1GQiAWq2KIODy8SoCX2zzfsBRmC6g5rpYPbRSZwFxEFQqFaxaLWJRnlsD46LFO2MMnhegWihgplTGt7//Y3z7+z9uer7Hx0awItOP33/HH+IvP/oRXHnlldi4aQsuuugSvO6aVyPZuRqVqosdO3YAAP7kT/6k6XEMw0C5UtGzlpV05Xk+yuXmrN3zvJauuagdVwBwXRf/+I//iOuuuw6r5QleqJ199tlIJBItv27btm0wnCQGervRu3UrOOdwvvsj5Dr7YRSnsKIP2Lp1K1ZvqOA/7/kFkBxANj+F9ARFuqMbA5vOwPjOO7G6w4CT6sDAik4UtkearxEPA4NrsHXr2nmtZ8LfB2sHQ//gIKoTT8OC6DnPDRtrNpyG8R13wK26ANK45LyN+O2ex9G3YhW2bl3X9HjjhSoe+4kA2fMveR723vVZdCQYaL4LGzaswvRvKDK5DnStHMLYgcfQ2dWDrVvP16/3fArLNHSALWo79k9i9F6GTC4Pw58QrZXBwImFrRdcgGfuSmgv+3kXPwePH34MhZkanFQCXTUAPtCXBM5eswG/euJRDKzahAR5CACw+cyzUaITqDzzG2zesBJPHtiNnkQIrOu6HTx6wMDWrVsBAPc9fRcAoOpxPPe5z20qKf72V9uACgAiNns1d+G85zwXex/4d9gVsdYzNq3G04d3oaOrD1u3noP9xWcATMGws/r9KsZh7HsogJlIYevWrZiYfhKFw48DANas3wwLe/X7Zi0K5pn6tfOxR39+F8CAgaE1mD7wMDil2Lp1K4yf346kSdDR1YPUuo2YeOZXSJAAb37lhbjlzl34zZPDc76PuXMUh+++HQDgdK9AnyU2tZVrToNvF1H7rUpgcAFwDK3ZgK1nDOjXP/XUU8hkmsuZrseAAEgkEvCrIqPGshMgEuwTyRTMZAacc/iVKZgsQCKTwUhhGpZlIwjCtucGOBw7gUwmBB9emIbj2Mhk0iCmj6lSGY6TQMVzYZnQ6yKmD8i/1XwPlsmRyWTgBBTjxRlYlo2MZPpVNwjTOU1TZCtJnT2TycCSnQJs24YV+dymaSKQMaSrX3EFLnvJq9DRmUPCFufz6HgZqYSJc845B+MzwNYLL8Ltt9+O2267Df9193344a3fxXdu/iY+8JH/iauvfi0cR3zO//k//yc2b97c9PymUim4hSlZsSwesyxz1u/DcRycd955Tf8GiH14Nsf5uALAt771LUxNTeE1r3mNTv8cHhY9+Kenp3Ho0CEMDAzAtpvr2otthuVoCYgQgnxWNBsrzLhYtzIPAOjvSqO3I4mn903C9SlSJIDhJIUEBKA/TTExU4tlCAGtS0CqXYFpWYBhC08VFDCFTANAb6obhjoBzN0b3/PF6zkxQQwTRjKNnOvjUM0PJRzLArFkKwiZRz4xXcW3f7ETP39gP973hvPwsosbAUwFgYlpagnIAgOTg7/V+gkBujuS6Mg62He0CNMwkDN9wAf8iSPo3SQC3odGZ7R3athJWPle0PI0+vOWPMcR7dpyUSy5ugXARFH8zZMSXTrZeO2o1Eo4KdhuOGSHWA5gOXrSVm9HEhkZBwBCiW2yGJWAxPdMZAqskUiDMCErTZdc0ScoBRA7AYd7rWcBqQC1jKUwFjaZs1KBqAOQmWLXvngtVvZldZvsgDItd9SbigFw04aV6YBdVhlsbiwITDhFAn5rtQAxLUbkzwQ0IltE0kCNZAa0XBCZY7J1Q32LZRqTXbj+roGw6Ev05QnbNIi/RSUgDlOeC/UzYPHjdnXkkUwkcODgIbn68O/79u0DADC3AiYTM5iUgHo688ik0+Cc48KtW9HZ061jcbsOFdCZTaCzM4XJ8jQY5ejs7sRrXvMaXPyCK2EiwIc/8If4xle/iCtfdbV2hPP5PC677LKmp5dSFllbvNhuse24xgCOHDmCSqWCq6++Gi996Uvx0pe+FG9961sBAJ///Ofx0pe+FAcOHDieS4gZsRMaACp7HkVn2kSx7KFYdtGZDVnFGet78OS+SX2jEBUDANCbpOIm8ijSRqBbIaRNv6UAYKD66Vu2yM4hTMwDthxRHAXoTXJFbxrppBUbR1lvXiAkJNVczkhmkTFFDEBVAhsyBkAA+L6HPYen8Yd/dwd+8eB+MM5xsG5ur16rylgyBVhZkGmlqjLYsmGDojufhGUa6JTAWqp6SBtizd7kEfR0SAAYK4W59TIGAAD9CVee43ATzRkiSDklN+WJmfBvswJiJEPJJmF6rQBARwNCd0cKmaStg8AqsycaA1BpoIbchFU/oRTxMFGs6QwgK9cDm9Vk/yOGw2OleTVvU036dEGddAyqLoUJATwKHF510SAAoKcjCc7nnpamAIBYCRjpPAxPfLcTxSoqdU0OM4bbEgDEtH6ZUx9ENq0oKzNSWQAczK3AIGExmJrYRupaLDdU+5rxTV4EfjmC4gQweUAXZwUsBENDZg9F8+9Fvr6JSy++ELf/8i6MjI3LlFWC3bt349cyTZN7NfiTh/VrGBNB95e+8Pn42Z134+DB/TqLicuahkJhUq6ZYKowpd+TcY5MJo1169bB81z4lOGss87C6tWr8ZWvfAXVamMq7+TkZNhqI3rOnw0xALWZr1mzBoCIbF988cWx50xMTODjH/84Xv/61+MlL3kJVqxYsZhLmNOInQDzXdSO7MLw//sbnJ27Co/PrMNMxddtBwDg9HVduPu3h8EYQ8LxYSRSMNMiYNjteCjM1FBzA6TMAFa+B/74IXTYrRUBsQgDIKYFCxQUBmA5MKQH4iCAZRroyCTQkUk0bHiFGRd/c+P9+Mhbt2oGoILdZjKDdFkVglFkwEAsG4YEF+q5uO2+fSAE+Nc/fyn+/LO/blpBCYiaBQtUBFFNCyZhMDkDlwyAmDYsEk5H68gm4AcMY1NVpAbFMblbQY8j/n1oNAQAw0nC6hD1F92m8FK7nACQH7UnIV7z9P5JPK9zCBMzATpzoktoYcbFyt5sw3qjNQoOKgIYQWQltA2biBuvRzIANd5RAcB0ydPedc2jSBEfhi02ftVPKEl8jE5WdCzDzHXDnDwKgOOB7cP4x28+hGtftgW/+/K5CycJpyLALBkGp2KqmOsFMHmgs4CAsPlgtwTSiemqPuf1prKXiJ2Ame4Ar83AMgmmii68gKLHDAPlGcPDTLmF4HVsMxJbVRBEvFYS+pXEcgDTBq2VYBpZscFzwJ6lw6bq7hkt9lKPK2ZAS1OgZbHRmmAhA0iE26ZlklgxGBetEPHeP3gn7n3gN/j9P/pTvPbqq0BYgJu//2Ocdtpp2LFjB5yBdfCnRiLrEZ/rQ+9/Dx7c9jDe/Z4/xGtf90accfomTE5O4oHfPIy9u3bgzrvuhGEQ/P5b3oCLL74ImzdvBreyOLT/GfzkJz/B69/4ZlDKQYiBv/3bv8Uf/uEf4qqrrsI111yD/v5+DA8P45577sGaNWvwyb/7+xg7aTzni2fzBoDPf/7zAIDdu3cDAG699VZs27YN+Xweb3vb2wAA119/PQDgl7/8JQBgy5YtDZXDSgravHkzrrjiioWtvkUz7AS476F28EkAQJdVw6GjwjPqM6ZR3fc4UuvOwZnrhEc6WXRh93ownBSMtMhv77B8UT1cdpE0ApjZfvgTR5C3KUZbAgBZQ2DZsj1DBQyGyPqQEpBDAvTkkzAMgo6s05D58tiuMdEpdO8EBnoyIthphQwgibE6BuCIGxKAV6vi1789jEvOGsSKngxyaXtWLzCgDA5hMExLTlbzdWUxIG5yGzX0dqZQeuJu9MvgnBcwJLkLGBbAAtiVMTi2icOjJawnaqJYyAByvKTPMQCYuR6kUEXSMfHE7glccPoAihWKy88dwD2PHZk9E0inVqZhkxlYEGBFCIFhO7Bl0VlPRwrppKVrE2KjKGdc9Ham4HoUnQhgJhQDEACQtUTrC10MmOsGAUcCAT7zrW1gjGM0Um08mxFGwUwDRGrQYOL7YlzMH45KQFwCQE9e/D45Ry2AYgBKvuRuBT05G5PFGkyDIG2EANCTCGYF/6am1YmQAfiUwYyV1qp/EpjJDGh5GqaRlVk10AzArAcAFu/JL5q+iYAsYxwJXgEtFUCsBHjgwjIE+6CMx+QwyzTizdnkP7dsOg1f+tw/4+//8VP44ldvwkBfL97//vdjbGwMO3bsADHM8LsAEFAKmEB//wC+9a+fwQ1f+w/cfvvP8B/f+X/o7OzEunXr8f53vBXcq8EwCK55/Zux7cF7cM8998DzPAwOrsQHP/hBvPl3fw/jRZGSfemll+Ib3/wWvvCvn8c3vvENVCoV9Pf34/zzz8e1117b0LgOWAIM4IYbboj9fssttwAAhoaGNAAsdSO2Ax64cA+JIqIOy9UFUYOHfomRR5/E2g9/HetX5pFwTDGUg3kgsgIUhomszBw5Ol5GgogUUSOZRtb3saeNGIBh2ZIBMDAEMOwkDEtJQHGveqRuQ3nmYAEAMD5dQ3depBEqBmAkM0jyQ6IOQHYDVWADAIeOTqFEc3jR1lUAgGzambUi1KcMKRlDgGnDIi4sLuoCAEhZpYy+zhQmfvEF9HSsBSCCUg6rIrFiPdwjzyCYPILejiQOj5WwxVJppAmYOQEAjjeNVCKJDtsDDAt29yBYpYjT13Vj+54JHJXVu2eu78Y9jx2ZXQLhqrhKSkCE6kJAwxaFcAnHBN91L87xnsKPaxsBiBYfqYSJqksxWRSAVvMCOAbVzEkBQE+KY2SqghyJV18niYfASiGfTcSkpNlMMIDIpsOo7vNjsEC2gpDxAU8xF/G7SgX9yg+fwOhUBX/2tgt0EL/mBcggHr8aynJMFmvIpmyR3pzOg1WK6E7SYxaW1Z1gsfZIoVJAGVK6C3RcwDCSWdByAUm4qLIkCLguIjYIR8CjABBKQJwxBDOTsA0LfsDAAdi0BmI6sDr64E8cgknCHjyWGWUABmpeeD1H+xRdcMFW3PzFG+BzC5ZpIDkgFIv3v//9Yv2Gicfu+jEOBD0gam2Gid6eHvzph/4YRrYbPR0p+AHF+PAYus0SWODDNCz87tvegY/+6R9jeqaE0UKAge408hlRI4GiiMclYKJ3cB3+9GN/h1UDYUBZmetREMLxt3/553BynQgKwyefAaj0pblMef5z2apVq+Z1rONhxEqAlqfhT4r3z5DIDN6gBFYrI5geg93Zjy1ruvDErhEYYDCclPBkUjmkIG7Co+NlJHK+bA+QQYb6MQ/yWBYyACFLqLRKwwo9Pof4yEm635FNYOeBqdgxdh0qABAZQGtX5OEg0Bu8kczC5rUIA2AwbFvHF2yIkYCq/UU+48QGtkSNqpoFM5SrBNiIC9ewRRC4P2+DlguwM736tRatwelfC29knwgEd56GI+NlJOxABLwNGbRO50FnxvHJ916L1EP7EFRyMDMdcI/uxtmbevDvP3saT+8Xn/+M9WKznQ0ACKOAIUDQIWEbDMjza4OiJ5/EzCO/wMbSOMpVsQEUyx7WrMhjx/4pHXMQcwuoPm+qo2hXgmHPVAW9JIwBAEBfhuOt116AH9+zd04PXRtnAgAkcIMGODRaggEGAtZUAspnHFgmwWSxBs457tp2EFMzLm4ZegZvfOlmve5uI4DpJGFkZAJDhuLJacEAEsSH3dEPt1LEpn4bNz45jNHJCvq70/NYc9imQMcAAiZOMQfqQ4vETgCGhQQ8lFgCJgk7bJqzxQBMAlYrgVUKSJIOVAI5ZQxcdPaV8qNlcFR9xRoiAWKT6KpjgxAdtyCRxj8EDCDxzReArmA2wONxDcOAwSItoCPBbB64MIgdmyUcORQsS/zDDygYs1DzKDgXs8hX9+di2XdqcrE6v7EDLrKdOu2gIbw/f+ooaEkEbVI8DMJYvtj8vBGR1nfGum4dKFMBOiOdR4KJ16huloIBZNCRoNh3dOaYveWV6X41pgXDdkQaKKEw7IgEBIq+jgQOfvGPsdF7GsVyWLLPGMfuQ6JqdrxQFTEA+XoAMFNZWLQKP6Co1ETWimk7MCRA2KB4/nOGdMZENmXPKgOoLCLDsmBYNiwSVgYDQCKVQk/GxEXrZF8jVwEJhxlUYKZzsLoH4UcCwQni6zYYAGDlexEUx3Haqk6YfglmOgcz0wlansZZG3rAOXDHgyLGtLo/h1zanjUITLjQ/ImdDOsAVGzEEd1QezpSwrvkNV0tXa76WDcoNstJCS6TxRocI9BrVQygI0ExWQxz7VXx3Sff+VxccMYAunKJeTWxMzUDkGmQjGLf0aIOLgsJSFx/XDIAwyDoyicxMV3DyGQFUzMuOrIOvvnTp/Hk3gkAql25igGoBIYAU8WaTm6wOgRQn782DUIIbv7F/ByzaF8dQKQqMo6mEpD4lYCYlp6pG22x3BgDCCUgWhXXkUmgB9oTzrTTIP4WtoGoZwDR4+luoJH1qSBwvREJCgbCWQAgBkCM2Hp1V1QA3PdgmJFZwnIbUBXOYoiN+ByuJ2YddGYdeD7D6FSc2Yu9nguGpRrqHada4FMKAIidAHfFyTaSGTgsBABSEwUxrmz3cPq6bq3vKgpupvMaKADA5r6Qh5IZ5C3RY3/f0XCi2FymBpcTM9xUHQQwnYSWgGwSYCAVwB87iF7/qOxeGrYtqLoBDCKkAD8Qnm7IADIwuDhmcaYGk3CYEXCxSYAXbw1rM3JSAmqmNfq+aAct5CqZBUSY9loNy0Z3xkSeiHPIa+IcOAhAOIORzMLpWSkZgDiXSp9WZuV7RGYHAFqZgZHKw8x0gHtVbBrMwDIN7DgwhXzaRDJhiUDwbADAKBgx5ewDWQcgW4GYUgLqySdAZyZhUZFlNFYQ18WaFTkQEmYd7R8uImGEwKr6CeWlhKWuEdV+Q11fXfkkCiVvzolVouKTiviEJeU0FmD/0SI6k9JLbcIAAKA7n8TEdFWzoj+/7kL0d6XwT/++DZQy3UrCcEQQGBD9gGYqYt6CAx9GMgvipJDgNbzy0nW446GDsbnNsy9cnWi1QanNPPJ4vRkGiAzYRj3n+g6bOgWUMw14Jok4VZwKt1p68mZkYzTrYgBAWA0ctrAON1XdHbTJWsXnYRqoRE5+HABEp1C5rMCDSYgu3lL3kRGJZdiWIToMSNm5O59EVy6hhzaFn1ExABJpUrcMAAs2tfkRO4nk6jP1rFTLAFhVbFpRBjCQk7RTA0BOV4EaYLCkxmok0kjKtJV6mWY2022ADVMAQJQBaAkoQK8jbgLFVlTgc5fU/89Y34PxQhWuL9JATTuUgADR7bFYEpuSGZGAzlufx6bVnXo92bQtvJMmLSIoFUAjGIDMAgLVm6oIyHkIiuPis7kV5FOGTgE1khnY3SvhF0bQmxfrSzQAQK9+PasWJQMQG5fhz2DLWrHB9uTEe3ZkE7O2xlC6umE5ohVENDYiW2Gs7THBqQ+T+TDAdHO4rlwSHZkEJqWnPDxRgc0D/Z0QJwUYFnKmeG8HAWA6Mt1R5JGL4yTAGJ+z1XJAxaAdIQHJa5MF2He0iLUD8v0iacFRAOjpSGKyWMPT+yaRdEycua4b175sC0anqjg8VtJtrIkdxgDyprh2xGfyRHZbKgdWncEbXrIJtmXgWz+bDwuIbEZEb1F6IHyz4jxCTBAeNnVTE+aMOgmISQBgtbJ+HzMCFpoBEAIYppipAbGNmzJFFAjZgN5YdQO7cFONtYGOrrWpBCQZAKIMIFJLwJkGKgVyQBjMBiAAQM0SsQ2YpoFUQlzPfjRlVS8rBKtlAFgEU4G8xNAmmNlOnRs9kIVuAuVJBpBJ2fibtz9XvE61bE53gFWKyGecSB67qHo0gio6cwns2D8/AFBpoMS0YNpClnAIBbESOiCYMikGk3KjkZ1I1ab3zKECHNvEczb3oVQVhTw2oTAdGayU6Yop4qFckkzHDIPAb3rR+tiNqvqVNEsHpH6YsWRYToQBKF1dNgWTHjwArMxQpIkEgFQWds9KgFH022KjTRqNAMDdCphbAa0UYaY7YGY6xfuXhAwEAD2yWEwMjG8usZCIrGKCyUIucU6J7SBtA688L6+fnyKeBgA1iGaq6GL/cBEEDAYPNCsjhMBM55AxZNWrlFlUfQCthUACYM5AcEAFs0Ik84Qwiv3DRaztlZKT7YAQA8RJao8YEIHgiekant4/ic1rumQfKwGY+4/OSIkygGEnBDgRA1mixpkGsLiobzFSOdBqCV35JF520Rrc89jhY89g5hGvGCQ2NL2p9w9oBgCgjgGwhjRQDQCGqJFRm7z2xlX6sWGEsQSTwJ88imBaNApslICiG3k8S6nBSCgvRWUj9X6KsXDOwzUBMGX6MWMsjAFEjm9ZJvxAsLOk3PjtSGxAmZKAomyloWHSItkpBQAq1zo5tBlmKgfUSiDgWJEWJ98ZWI9gekxrjyrrQsUAzHQHWLWEnqyle8AbUgJitQq2rOmKtRKey3QMwBAAEGMARKSDvvGF65CTKYuKrSgGsPvQNDaszKO/S2z0R8fLsBGRKhJhvnpJVoES09Z/Z35cPlGdINUYx6hFM5YMO4wBEJ0FZIP5HoLpcf2agTRFWm44ZjKr2z53MQGQKYM2AAAA+IVRsGoZRioXAkAlAgC5CAA0YQBqgD03TM34UsTTchUxHSDwQCoF/ZooAHRkE+jOJzE5U8P+o0Wd50+csE7ETOeQ4mJjd0ggZUBxvpkrjqOmmakOnM2MykE7XNYnAAJsK7UAq3ok4ChJz06CeTXQ8jTGfvQ59KZFX/+9h6dx+joRf1jVn4VhEOwfLqLmBWLimpMU0kUqq1lkWIORgpnKglWFdHf2hl4ElGP/0RnMz1QaqDAj8v+GZxqG3Nmi/wGEczl6UfxOGYNpCCZlJDPC21dyivL2VWTVMDWoWKYB7tfAqjOg1ZKcGxyRgOqK12KfodlaAVgk4uFLBhAtXAtHYMqYAfflZwhbXkffyjZll1IOpBxxHVuWGPoeYwDyuNGA9TIDWARTVDq5aouQFzhDyvDQlxJfXGqDSF30RvcBiACAkoAyHQA4VmR57CYyEhlwv4Ytq/M4PFaODd+ezXiEAahNNarhEycJ7rsIZoRXrZp2Tcu2CLsPFXDa6k70dopN9MhYCTYJYNalKyaJj0q5qt9LFxwF8TXm0mIDalYLoDOWbAkAUlc3lNdqOeCBLyQcWQTUk/CQMaMSkKhizfgCIBNGKKsAIQCIc89hpvMwZfYKLRdwzsYevPKydThjtfguOnNihnC9tyraVvBYYDVFvHCttgOAwy+ELaWTxNcppvmMg658AlPFGvYdKSKflJuPHQKAkcrr+JGSsgzLATHtUALKSwCYgwH4qs12JA1UVS0Pdjn63ALCCWFeFTOP3oGZR3+JQXZEfDccOF3KY45tYmVvBvuOFmWb6jB91UznYVPxGRNR5yWVBZNdbjfKWQ67DxcAzJF7HpFTojGAcNNqYsQU6Z9SVhEbq2IF4aZKGUcCHgAuMq6IoeUi3S9OMQBiaHCw9MR2gmB6DGBU1gI0SkCxTX+WeAUgGI2eB0wIYAi2o2oVdGDZMEWRoZxEp6ae5Ywa/LED+v5R3j4AzQAMQmDJ2IA+vWqF82AAC60POKUAwO7oE0GvoS0wUqKytz/F0J2QwzHWCwBwh0UcgMlZsjoGkO0Ur0n64ahIyQAAYMtKsaHNJw6ger4Q09Syik0iaZyWA+a7Wlbh1SIAjumyh8OjguJvWt2JXpkTfmS8LPrxNDAAD25VbELEsvTfeR0DyEkG0KwWINq3yDQlWBEaBi4tG2ABgulR2L2irmAgRdEve1cZyawMOCZh1QqwTAMJ+LriGYAuBlPnXmUBAQAtT8O2TLz39eehMxPGAIDGFtkBDWcfqM0vRbww/iPPrz81rF+TJh6OjJX1eejOJ1GYcbH3aBHr+qQWHwEAM5WDHYiNPkFEqqX4nGmpXUcloLkYgOixBCOMAVjSyx3IRwFLxK24V0PpqfvF5yehHKRmFwDA2hV5HBieAZXxApW9ZKY7YHjCM9bOi4wBUMkABrrTyCQt7D40Ddu2m7YqEBZuOoSQmJyjNud6i+rqelNVEiK43DRFRa/IgCKCvZimlmdN1T5C96AK4wq2IaWgTCfAGYLieKwaOLZRHkMCEoNuDCkBhQyAEENKVuJ4THvqsoCTSQCQMQCbUHFfTA2DM6YBwLaMGBjYZh0A8BAAyDFiANVqdUG91E4pAMicdTnWfuCLMFNZHRi77iWrcPEGsVk6/WthZrt0HIDXMwCZ6dGT8MJmZhEAWNdtwSDzDASrfvqGBWLaWm8Mb3jRt0jr6oyiJ8UxPePitzvHAAAbV3WiR2bVFMsebFDtSao1J4mvPSgSiQE0MgAVA5idARimBdNxdDdQQweBxWuDqREkBjcAAC7ckMbrLxPzfs1kBoQQWLke0JkJ9HYmtXSizMx1A8SAJwHASOWFV51Ig5anY+s58s3/haHDotNlfS2AqlkQskojA1A/gwgAJImHkcky+pM+Dv/z27GSDYMyjh37p7C2V0oxEbAy0jkdP0oaVH8OI5HRDCCVsJB0zGPGAEyZoaS+NxsUfV0pJEz5nakmdE4S3thBeMOiEj8jq6aH+rI6fgMAawfzGJ4soyplvygDYJUiunKJiPOSEgygWgbnDIQQbFzVid2HC+jv78fhw4dRqVRm9zJJXAICo2LDbmZy04561YgCgJRNBC+QoCgDvUQW9lkKACTLJIYpi/44LAkAJJESBW61CiwjUg0cjVuQYzAAADAkAKg0UINoCUjJQKpVMwxRYY5AMBc1pcyUyfw8cCUgiXWnnPg5susZgJTKwjK7RuOco1Kp4PDhw+jv72/+GeZhJ2Qi2FIxQgwQ6RkrADhz0IE77KEAAiOVhTOwTmcCqawLQ7YBUB5pl1kLawRkHQAAJLiLNSvyeGrfJO57/CjuefQI3n7VmbpyM2p6aEnk5gfCzZTYQgKiMxNQrRRWpCnufvQwpkseTlvdiVX9OZgGQS7toFSpiWIvqzEIHB2Ioo7P/PhGn51LAorULJiWA5NwEa+w4l41pz6cnlUiddGbQcq04RIDRMZQRKbPBM5c3wNnrx+LARDDhJntgjuiGEBe/6TlQnQxqB14EqlBAqCvIRVUyypGKAGpFNjoWv2pYRgyAyZFPASUY3VHTcR4gmEAGQSUYVW3A+yHjp0AgJnKg3hlEHARzI7UCCgGAAgWUJgjBqCb7EWCwBahWDeY1wCtpSsnpQOcxHLg+DMAcjhjXXfsmGtX5MA5UK1UACeMXZjZTtB9j6E7nwTK4bVrpnIAOFitDDOVw4ahDvz4nr1IZ7IYGBANHX0/zgpL00Uk4cKc8sBqJVC3hmleQM0si7qD4UYHiAc+aLmAGTYJDoIZoyqv8Rqm2RSKUynZ7bWGiuWJLLvJKlitAuaWMcmmUDQDOFy8LyFEdO6slTHFCignANMvw5yoggceWK2Mml1E1aWoFtIolatIBiUYYyUQ0xb3FQDiTMFMTTSsN5iZBOUEHiMYIT7sgg/mVsFqJUyxAmrTKVQ9CsstwrYt0WesOoNpNonCWAKeFyCFGmyDw7ATYO4RmJlhuJSgNm1gcjT0vSs1H6Wqj+p0CgYhqLoBrNoUDGcSRnIMtDiOCncwVYyfV9u2MTAwgHw+X7/8edspxQCiZsjmbrRaBK1Mw0jnQAwTiYH18MYPgQe+iAGYlg4gqrTEnBH2gCFOUleHUreMLWu78NudY/jk1x7Efz1yCL9+9EjzBdAwBhAFAO2p2g6YV0MwMwmnX1SqiulYHn7nkrX4+/c9T6eY9XYmdYvjqGQAYiBjBlpWIJYtKLslWmJELWGbsC0DpSYSUDRjSck+DglgRCUgaVZHL8xMB2i5CFYrw0imtcdm5noQzEzgj699jshCiXjVQJgJBEQAQBaD6fNTLQCc6XqMRgbAQwCIbtp1YBVMjeiB9FmZ098ju5BmeLiJr+hUUkyEraRzAOdIEU9kAenMq5ABACJOMZcEFGgJKLzGNABIgNaSoATLxOBG2D1DIJUpvPUVp+PVz1sfO6YqZNMyj5KAst1gtTL6cmasvkWnr0oZ6LRVnfADhoMjM8jn8zjttNNwxhlnxP574pd3IXPHDThjyyYMTD6FxB2fxU13jiFz+w1YObOn4flnnHEGThvoQOaOG/CzHz2A7966DZk7bsDK0h5k7rgB/3HrI6gZPTAzg/j0LYeQevi76HnmFzjjjDOwmk8gc8cN+NL3dmLyobuR/a9/1cdcjSlk7rgBHekM1niHkbnjBmzZuA5rnRoyd9yAiZESPnXLIaxauxFPPTWCzB03YF3Sx+mnrUfmjhuQueMGrCjsaLrenqdvA73vFmz/yY+R/dW/xd7vy9/bASe/Eg/vB9zbv4K+A7/Gaf15ZO64AXf+9EE8vB/4xi9HUPnVf6D7qZ9g87pVyNxxA1bRMZz/nHNwztlnxd6rZvbi07ccQjK/EmeccQYOTSeRveMG9E09gzO2bEbmjhvw4I9+gU2bt8TP6WmnLWjzB05hAFDFMawyIxpVyQ3HWbFejDAc3S8yEZzQezdsMRO2w6xFJKCUTgFktQpevHU1ztvUiz9561b0dCRnlYM4i2yqZjMGkBAeH6NIrBCyyqu39uJ/vesS/NEbnxPrH9LTkdJTr3Q6ISEwEilkrUg7ZCXZ2I7eYPT7EjJrQzglARHD0rQ9QYJIEDgCAPk+mOkO0PI0aHVG1yOIv3WDlgrgrpLW6gGgR/9bbUwCTAr6cbMss6xksVk9AwhkZg0iEpB4r0a2IjKTCPK2LMxx5JzcICyGGsjJgGM0CCyvlQ7bE0PnZ2EA3fnkvCQgYgq5gxETNijWrggZQD0AZM64DGa2C0FpCte+bAs2ruqMHXOgJwPHNsM5xnLdloxfDaQCPcvaSCQlA4DOfNOB4ENx2S1qSpKBYcGUNSyDaSFbqPuo3tR10JWgmj2rwH+KeLrBIiA9ebku5ahdcloWAxkKI5XVEo6ZFH87fYUDXp2WIzuzui1HtyWus/FCtc6JaXS4mq03wV048PU5jGXWVcXMbke2CbG7hdw5mCjL0ZsMSYhaCyvfCxADQWGk6XsN9oj9Q8181ll3tg0YJjgILEJjMtFi2SkLAIadALEc0EoRrFLU3n1ySHQvdQ89LTr8OXH5xsx0IkeqePvviE05GgNgtTLO2tCDT7z7crzwuauweU2XbtjWYDoGEO8+qC42AQAirdIZEF7eQJrigsjUJmW9nalIz/vIppdII2v5kYEoasNONEhAtFZGPmU1BQA9/9c0Y2Bl2uHxlFn5HrFpV6aFrBAFgFwPwBn8yaPyM9YBgGxNQOxkqF1nOkArYXW1IQGAV4pIOEZDR1A/ULn1lpaoAFHDII4dGXuY75UgKTakDkt8dssT3nBPRxJJ2TXTqAsCA0B/isKR1eBAIwPoOgYDoNE5C4BstMewcVVHCACK0cnrMHP6JbBy3aAzzdONTYNgzUA2lqYMhPGrvkRkHKSd0skQigGs7M0ilTB1JlAzI4yCgcgWDzYMAgykxXrVfVRv6h7pcMJhNArwU8RHpebr7DnilkIGmBI/3/k769Cf5vrcA4CRFtcWrc6AzkzCzHaJOg3ZlqNTthcfK1S1jClmWoTKtz739etNZZBgNaQtFpkFEcbVyhUFAMIBIE4SMEzkrACligCABFwxQMi0YHX0wp8FAFb0yFRumYmmZoVYtgNCCLhhwgJbBoDFNjOd1xKQYgRWvgdWvhe1Q0+DuVWt/+vXZDtFZ0O1qdqJMAe8Fi+j37S6E0fHy83bLMvsBczCAMSGIwJQiRUCAKIbYdR6O5JimAwaASBtBHokIolUwyoJyC+MYPQH/4L9//T72GrtbJoFFI0BRNfawACIATPXDUMyAFYrw0iFY+zUDe9NiIEbjQxAAICavQAIwGWVGR0zMSsSAKiP/ixplIAYl0VqZsxr18wqylZy3TASaWRM8fmyslKWV6aQSVpYO5jX9RL1WUAA0J9msODHOoVGGUBnXqSqek2qqwFZCUzCegrLSeCc1Q5W9ec0QKt15859EbqvuB521wqYuW7Q8nRYS1JnawfzjQxAboq9TggAggGoTVRcu4ZBsH5lx5wMQDWwi57PgYRgOrMBgGoIl7d8JGWBoPq+s3aAR58Zw3TJFeDtlvX9qK4FWikKRhlhGKYGrxJoaUqDnJUTP7NSyhudrIDLFE0VXA7rQpozADOZhcWquOT07jDLK8YAPDEsCHJqm5x+ljV9lKs+aj6HzTytDtidAwimmgNAOmmjI+tgWAKAKrxU95eYwkePXaDXhp3SAGCk86DlImi5GLtwE6tPR+3gDjCvqj0vZWamE7RUAPOrIHZCePBSb4/e/ACweY24EJuygLosIGVRCUiZ3bVCZMNUmt+UcQkoDgBJ4seCwOI5onWDe2QXDn7hAyg/dS9ACPqMYtOGcJw2xgCAKAOQMZJslwjmZvKSAZTqJCBZ7DUbAOQUAIQ3uZXtAsB1mwjFAABgME0bJaAgbFQX9fajn12vP9cDI5lBRrasyEBsYkGpgDddsQVXPW+DTpc1mkhAr3lul0hrjDAAHnjg1Ic7sg/d8tKZrWupqgTW0pxlI+vIwiUJ0Or7TKzYgM6Lr5LnqRsAjwfHI7Z2RT6sVLfjDGBLH8HvPHcAkM3yjGScAQAiu2zPkelZ+xgRLnotAaEHfcl6lW7aXAIS3XTFlLp6Ceii0/K4f/sw7v7tYXTJlGx1jg3JAGhlBqw6owFL/C1ce1Ca0hs/MW0Y6TxstwjHMkQbdRqXQaGcl9kYQDIr5i94lbARoPyek8RDqeqj5voSAORnT2aRMcSEQT/gsJirnUOrc0AH8ZvZip6MLkbU4C/Xxg1rmQEcDzPTedDSFFitpD0OAEiuOh20NAl//FCjBJTtRFAugLk1fUEo9I/Sf0AE1ADgmSZxAKWjNmiSdpQBQHQLTedlNkwcAIKZKRz84h+j35jSm7zRAABeJAgcjwEUH/kFiGlh9Xs+CzPbKSZDNWEAfBawClMrZQ678uAzHQANEEyPa+oPQPf9VwBAZokBqJseABJDor1x7eDT4hjlyVDOSAYNm2t0fGUUDEndWoGQASiPNCkrZVmliNe+YC0uOGMgnCHt1AWBAeQwI89n3EMsPXUfDt/4pxgcvhvA7MVgKl6hvhfDskHkueaBJ3LLm6QpKm8+mEUGijIAzU5SOcCwwCsF9OcMWSFM5AZFdC0AAJy2qgOuR3Vn0XozZKsNIATWDJuR56Y5AwAEQKYNDynDF5liiRSIaeP0lSmsHshi75GirspXRYCmDlJLBhCRgKLsJcoAxDnqAS1Nor87jZHJSsyJif2cNQYgrttgZjIiAYnvN21SlCo+qBd3DoxkBiniYWyqChNUtBBJhABAy9O6uLTeBnsymgFE4xWAuC5sgyLpLH7S5ikPAGozijKA5CoRB6DlQpMYQBe4WwGtTMfYgWgHEWcAmZSNVf1Z7DxQaHxznQZaFwOoYwBWrkf2nxF9iKJW278d/thBdFQOwdYeXxwAEtxrZAB2AqxWQvmpe5HZconQ7VNZpImYDVuf9x1jAGZUP43TaKXhq02AUz8WAzCSGRA7AW9CZEYZDTGAPvn68CZ3+lbDSKRRO/AkmFeF4c4gufoMAKIeoykAyD5FRhMAaJCAkhlZeRr2WwKgwZb5tYbXETsJYtoIZDWxESkEA4CxH31OVJn74vuaLQ6gMpaM6GbEJQD4XgzAomZmBQDMFgc4a0MPzt8ovgMScVKsbCdoaQrcq+rrmhgmjFQGrBrKlxeeuQL93Wn8400P6U0paoQzcJWLr+oqZiYBmUo9mxnJLHKGjw6bhi3Wk2nAq+I9rxNFmL0pCQByoyemJQfLT4NVSzomIP5mgzhJBDMTIt4UA4BuBDMCAEanKrGkC/Xa6M9608Hx4kQYBJbnrMOhmKl4GgD032Xg2AsYUqoPlgQAu0vE7tQ1440eQO3Q0/r9VvRkMF6oimlwGgDE2pxEAs8/Z0C3F1lMO6UBwEiH2RZRz8XpXxsp7okDgMqmCKaGYxuYkcjoRmBR27ymCzsPTjVsqpoBGOacEpDyipWsEjX36C4AQCooNpWASCIFm7thO10z9ILdo7vB3AqyZ79APJbMIcFrzTuCsghbia41klUUX2t4LqMMQBWD+ZMCAOoZgJHOw0ikY9lAxDCRWHU6agef0sFjBQDdtofpshujxmp2ATFnk4DCNFmSSMu24Cr7pKJBPZgRrI37npD6onNuCYGRzomWA4hsAFLvVXOObV94xbMBgF8XBCamDSKlCsUAmlk9Axj/2Zcx/O1P6jhJwjZxyRbxnFj9Qq5bMF6vFottmalcjE3k0g7+6l2XgDKG//XF+xoC7UT2WhIvFmsPiuM6lXo2M5IZ9GY4zlxp6PNsJNJgbhnnnNaLN79sM567Nuy7pV+Xyok5vZzFnAO1dn/soDgvEQAwc90IZiYw0JUWoznrGcAxJSDxXXIa1quo6zVnM5SqPrh0DkIGkIYje0Sl6maJWJ0CANS84bHbvoCj//7Xuv38ip40GAdGpypgKl4RWauJxdf/gVMcAKIZBYpyAmLTSa7cJP7dJAYAiEKimCyQyjZ46IAIBBdmXIwX4jIAYYEY+VCfBaTrAEIGAECmVsaP7x4VVaGkWkBnKu6RAeLmspgbyRCKb4JmphOpdWeL56aycJhYY0MtgG5cV7fWukrgMIgbvXnjHqGZ79HHq48BEEKw8vc/iY5LXxt7PLXmTPgTh7UMlFx1OgDR3pjzsHc/EObWGyrbo85T1WCV65apsmnYEgAMr6RrLmhJAADza7F4jP4cqRAA1OdwelfByvdi4HV/AqdvDYhKVZ1lMlh00po+j6qjZODFACxqRlrIObQ0Cc45Sk/eg8qubZj69X/q53DfFd9XNGtLpo+yCAMAgNSG81HZtS3WHmP1QA4fe8fFODpRxk/u2RuumXHdvwgIgZXOTMwaAA7PWRa8VoLFPO0Zi8C5YF5ve8UZ2LpOPh4N9qbz8Cdl3KjuejJSOXhjB/TnU2blusEqRQx0ijkXritjW/US0CwMIPo+OjNPxvsyVoBy1W9IEDCTWVhUfNdJzQDCIDAgki6Y78I9shs88DD63U+DuRWskKmgR8fLYdp1dI2zBPwXaqc2AEQuMqNOu0zITaZZGiggbrDo35z+NfDGDoTZBtLCQHBdHIAz+MTEP93zRRyshn9TQUp9USmvOp0HrRTBZfYQZ1T3zQmKE3jbyzbK18clIIOHedehxy6OnT3reeFkpVQOluxvU5+1FJeAIjeMPJ7V2Y/Oy16HzOmXynMUnsuoBASEgCbWEQcAQEg+ZoQ1AEByjfD4Zx4VI0ft3iEYqRwyRKx3fDrUVWMxAEIiPYDqwE960UYiA5PW0Jk2AK8Cp28tgBAA6Mxk08CmEalQVp/D7h7Emvf/G1LrzoGZ7QIrF5DPOJgo1vDNnz6FD/3f/xKzYevWGi2oI9KLn0sCIsSAletCMDOJoDAi0pizXSj8+j9R3b8dgAAuow64rGwX6MwUuFeLOTadl70OxDAxdfd/xJ5/5voeDHSncXA0lIdU6mrNMPF3v/ocpqjYBIPixKwBYH3OpExKAjeUgBLpWOxMZbrFMsFSOQSFMfnv+HuYqZyWXs06BgAAg7LRo2qJ/pN99+Onz9wVYYRzMwCgLgEgkULGFKmeCOoloAzMoAqARxiABLRUFiSRRlAYhXt4J8ACdFx6DfypEYz9+F+xdoX4vHuPhNldv5k+gG8++j0Q025o3bJYtgwA6t913ktytQSAOglINYQD4h5sYmgzeODBG9kfe/76lXlYJmkoCDM4xYxl4oFDj+Dp4iH9eLQXEBBhALJ7KauKi92fPCooKDEQzEygK23EXi/WLi6+rOxdX++xZ89+YfjcVBaGXwHAG9NWeUSTbBYDIAa6X/xWLU1Eb16jbjOPFXs589M0E4MbQSwH3she0GQehp2AmelAUmr2E4UoAxDDasJN1YmvVbVcUACQTIOA40sfELMfnL5VAAgCCQDe6AE4/Wsb1hTLR3cagczMdIJWiujO2rj9wQP49i92YtfBAh7eEWaCBAGDSXiYTmvamgHwwIvFMBqOnxUat9KRB17/J7C7VmD01hvAaQDuuQ0Aa2a7ROuGynTMebFyXchf8AqUtv8K3vih2GuG+rI4HAEAFWMZcww8cnQ79tYm9XrnCgADQiNntYoAAEdcm0RKQMpYpSgaB0akJMEGZFfWVFwCinrq6jsV/xbXWa8jr30pud4//DjuP/hwRAKaPQ1UWawPVCKNFPFE23TVrkMH2rMgnCGBIMIA5OckBHZHP4LCCGoHnwJA0HnZ69B52WtRfupeJIMZDPVlsGP/lAaA3xYP4Ff77gexrFlTfhdqpzQAqCpDGJb+opQlh7bA7h5suPkFaMg2TZGbSElGtcM7Y8+3LROr+nM4OBKvESCcIpD5336ku6K66Y36GIC8uVQcQOn/yTVngM5MgGva2AQASA0chr6p0hvOQ/acF4qqZ/W5klkQFsBB0JAJpHRpISkcu4hGVWQCiKWBAvUMYH4AQEwbiSFxfllGgkymA7ZsBxFjAHpTDYfAAxEGIGsVnD4h9egq7mmhzZrZLhFvKU2BuRUE06P6uVGLOg9NJaJsJ8AZVnWIa+UPrjkbubSN+7YfjaxV5XtHGUAkC2gWCQiALgZzD+0UHW5XbkLn894AOjMJf+KIYAB1AKs8ZH9qtMGx6bzkGhDbwdSvvh17fKgvi8PjpUi/fiEBBbK7ZxBJUjoWAxBZOxxGrRhhAJkGBlB/nBgbaBIDEAeyYuCgwKDDiI+V9BmFR/0Gh6DeYgwgch6NVBYp4qFQ8mAqx6guBpQ23LBXWDLcV6yuAfgSAJz+NTCTGSTXnCnWNTWMLWu7sePAlJaAAs71WtX9vdh2SgOALjbJ5BvS7YxECqvf81mkN54fe5yYlgaOqOdn5ntFM7MjzzS8z8q+DA7XzVo1ONU3ka+KwkC0h233DIkApawCNlRvfA0Au0HsBFLrzwOrlfVIS6MJA8gZNbCIR5U5/RL0v+YDsc+sPKm04TXUAvBoELhJDKCZqZhKtBAMCCUtYidjgdVjWXK1uFFoJgREXisi4ZiYmI7HACxQGGZc84/KKav+8P+iQ+bUqxtd6d9mKgcz0wVamtLacjMGYByLAUimeN2LV+KfP/IivOb5G3HhmSvwmydHdItiPWchKk/NQwICVJBzErXDO5Ec2gRimHqd3tgBcL+RAWgPmQUNAXgz04H8c65AeccDYBG5YWVfFq5H9TkOKINBGKi8nvy6Y8xl6lwbfk1fm2ayUQIy6gEgIvuYszAAK9sZu56VBJQIpuHYpo6D+YzCp34o/RizOTFWmEEV7QOVzCLBa/B8qocFhQxAfL4U8RskIEAWgxVGUTu0U2/8dtcKsa6pYWxZ24XCjIvCtKwIBhNrNe0GaXmx7NQGAHkxHYu61pvKBIp1syQEiaHNDQwAEF7U8ERZj6dTM1E1A5AAoCoKARFQXPeRm2B39sfWqDRS9+geOAPrdeqkbq9gzcIAZrnQlalzkSFuIwPgzWMAcwKAAtdZGECzTXMuU3EAllYMoBOsPI3ejmQdA6AxBqBjKtFgaDIT5ljLc+RPHZXrzstgaQHe6OwAEPVEm8UyrIzwtjvMGtasEBvYJWcPolz1sX23KGqjvjivFUJxdGZUnF9VB0DnBgAr1w3uVeGN7NO1Ek7PEEAMeKP7wXy3gZlENfL62BYgs6sY1Z8bAFb1ie9POTBBIOYYU+W8IMzAOnYMIJISHGEA3KtpJ6MZAwiZuqm7+er3VPdw5LOp9yKWAzozhYHulG5BHbCggQHsHN/TtOW1unZjfaCSGdg0nAYX/bt6foq44TzsqNTWOSAKBf2azmSL9gnaIuOF09MCEAPO4LMAMM1lADgeJrwHckzPpd5MeXPXZwglhzYjmBpuaNmwsjcLyjhGpmSzJxlIC2Q3Tw0Ac3l8qnldeRqcUXgje5EY3Kg3VH9qWHQQj2qnOgbgzurp6OdKTypv+Q0zAYhmAPGsEm5YmKo2r042Mx0AMRrOkaUZQGs5zak1Z6Lj4tfAW3G6Pj5zK+jP25gohABAtaxSl/Z5DKrvTwoGYEgAoKUpeKP7QZyUBtnY54t4pc1iGYoBRKt1z9/SB8c2cd/jAmwUA/hJaQ/+8e5/jWcB+d6sawZCDxfgOiuKWDbsnpWCAXiNEpB1DABwZNNBb3iPfmxlHQBQxuISUFS+nCcDAAAiYwDhKE1xb7BmElAqLAprYOqzAIDqCRTMTKC/Kw2LiP5Ffh0A7K+M42N3fApPje1qsl4pY0acFSOZhUXF9VYPAOrzpYmHjCVmRUedJOXMASGjFX2C+uBPDWPdYB6ObcKUKd2B3BeoZesJgottpzQAEMOEEZk8NV9TgFHvxSZkHMA9HJeBhuRNpKZOqewPKjdlTxWpzAkAYU8Uf/wwuO8KAJAbqj95FJCZL8qUl5UhtTk3EyC82LuTQZMgsLggv/zIf2Db2A798LbCXvzRjz6GUiSIp8zuHoTV2d/0hiWW0zIDIKaNnit+H1y2LlDfwWCOYzwiAYXTy8K+R+r1zUyBZBCRgCzZ78kd2Qenf03Tatxo/KjZsdX6VDYRACQdC1tP78cDTwyLAShyrRUWYMYrxbOAAi/WtqLeopu5uu4AwOkT2WisiQQk0kdl+maT82919MFIZuFGAKCnI4mEY4YMgDIYhINq5yUEgGMxabMpAwgBgHM+SwxAyYlx+QeArgaOBoD155Fxkv7uNEyI/kU+C+AxX98PJSqu9alaoeH1StKpZwBGUAMBi1Rbh61AAKDDDpAxvIa4oiWLwayuFbptBSBkoGBqBKZpYNPqTpFmi9AxDExrmQEsxO7e9yC2FZ5o+rf+q/4InZe9tunfZjOziQQEiGwVEKNBBlrZJy6M8CYSueo6BsACRAe2NzNREZkFLU+jsvth/X7KE2TVmQaZRxcmESCZnHvDVVS606EoVeskIEbBYOBX+x7A4+OhpzTlV+CzADNeIwB0Pu+NGPr9TzZ+DumZNduAWjG12QykfEwWa7pvjWYAdl0W0CwAqFJO/cKo7txoZrsAzuAe2aXTQhteJ73S2TKZDCclqlRLhdjjl5w9iInpGnYdKoBKuYeSMNgXywKa43pQbTXs3lWx/jhO/1oEhVFRxV7HsggxtLPTjAEQQpBYsT7GAAyDYGVvRjsvqnq5PQkoElitB4CaGO4CzhpiAAps6/V/YHYGAIRxkoGuNCwiACCgigFI50uuv+xVGl6vGUCsEaCSeTwdA9BjWOXzO5wAacNvAAC7ox8ghpZ/lIngsHBATl/bpZs3BtIZCAzjuAHAKTER7L5DD2N/8UDTv6VP29ry8WaTgAwnCad/LWqHnkZp+90oPXUvel7+duTzfcim7JBGawZgAGDwqA9Y9jG9dDOdR+nJX4NVS0isOh1296BkMWLcH8x6AAjXN1u+s36uvLC7EwF+O1wEYxyG9PKI7P0SsAC+6gWPkP67TXKUDTsBzCLzpNad07IEVG8KhHsSPhjjKMzU0NOR0rKKZdUHgedmAGABjLQsZFPeGQua6v9AyMia6f/6OZnOhoZt52wU77H78DSYjAHobA/LFm0WGD1mEFh5vKp9uTI15IZVis1jE7lu0JmJhiwg/foVGzD9mx+DR2SSob6s7g7qy0prWidfis97DAko2shNSUARBhDWADSXgJoxAHUemsl0Vq4blZlJ9HelUAIDNwQD4OBaElXrLzUBgDAGEJeAACHzOCQQo0fVuMtECpDzJZKsEQCIZaP/6g8isfK02ON254DoaFoTA6WG75UAIO81apowliWg9i1tJeGxxUPQ2RgAACSGNqG2fztGb/2/qOx8EOWn7wchBEN9WRyRAODLJmDai5IeyVyUX7xvF1i1hPyFr8LKt/6VvvBUHIAb8U0u2hBtNglEmZqPsLnfxuGxMh58MqwKJYwiMExQzuAxCpUGq24ej7ZWpNJ35bvR+7K3t/SaelObRIescVBZKrQhtbIxCBw1YoVjMtUxo/KKqgyuN7UZzVXLYGW7QOsYQE9HEpZpYGSiDCavyQAcjDNQ1f0x8OdsBSHeN4nul16HjoteHXs8ClhzxSZmk+ASgxsBGsAbC+sBhvqyGJksww8YqM4CUhls0iEghvbwDxQO4+9+9Tnh2ETXbCfCluRNJCA2CwAYyTRAjKYMwMr3YuXv/29kz7y88W+5HnDqYyDLYYIiIBYYZ+Ccg1sKAIQT05QBpFRrj7gEBAgAsAkFoq1X5Dk4ayiJniRtAABAFF+qzB9l6vdgahib14QMwD8BDOCUAICknYC7iADg9K4CiNHU68id+2KkN12AgTf8Oax8L9wjQjIRqaAhjTbAwORNJLw/Z84bHgB6Xv4ODL7tb9D78nc0NDUDAN4kK0dfhMcAAEB4N4N5YKA7jf+4Y6fOjDBAQWXpv89C+qwAwG0RABbDlJShitzGZSBYedUNvX/mYFc6JbGJnNCsBgAQujCxHBC7uSet1kjLdQWABkF/VwrDkxXwIB7sU0kBKiA6Vx0AAHRecnUDQFmd/bGhQg1ryjZnr8rU7Am3LhDMODA8URbyJRiojIv4TKzdTOd1Wu+TY8/gkaPbMTzT2P5Yp4Im6oPA5QgDiDMJYpjInHkZUhvOa7rm5KrTm2akKXm026zCJBxBZGC9L//tyfTQ5hJQI8uLSkAJEjQ4bUYyjcE8aSoBzWZWJBW0pyOF3rxssBcBADCquwAspp0SAJBaZAaQWLEB6z78NQEEdZYc2owVb/qfyGy5CImVmzQADPVlMV6oouYFumEZJQoAvIb2xU3fd2AdUmvPanhc5dY3y/RRN9ix5CVAUHReK+P1Lz4NOw8U8NiucZGyyhkClfdNA91LXW1czSSg422GkxR1EExWA0sGEJ1eBhxbAgLCc6TagahN0sz3xvT1qBFCYKRyczIAswkDAETnx5HIkBIlpfnyHFf3PS7XPPf10HxdBpxeIQPVd1sFAEt2Em0WAwDEZkScVCwOsKo/zARSWUBKAvJkinBU/qn4AoyLbthiWpmSgaJpoICIATRrA6Fs4JoPNfXy5zIrLxy0VDCNs9d1wE6F3xXLdcPMdsGT10vJbwQAp2+1aO8QbRkjASxvy1kATj0AZEGrJdnuYn4AYNc1invVpeL782U8yJfn+ngUg50aAGAnwWRRxWJZfYuDZpZYeRqCwghopajT6Y6Ol3U5PTWVBBSIAqQmF/58LJSAmgCAKrmfI2dfmZnKgVVn8NIL16Arl8B3bt+pG5Yp70mBFRDS/1YloMUyM9MBy5uBZRqYkLUAKrNGxUMMOapvrjRYtQmp829YjijCm8X7V2blupvq0np92U4hbfjxbpoD3WkhAVEVA1AMQFwPYz/4ZxA7gcTghjnffzaz5bqbMQCrU7Xcnm1wi4HEivUNDAAAjoyVRB0AYWAqBsACwDBjx6vILpmFWhMAkPdNmAaaAXFSqO75rQaA+iBwu6bSLoPpUfR3OOB2eA0kzrwUq9/3eZ2B14wBpDddgLUf/lpdGqj4vrscNQ6yrtYimQFzZb+j5PwAwEikYGY69Mxg0fmThAAgHcXj0Q5iXkHg0dFR3HTTTXj00Uexfft2VCoV3HTTTbj44ouP+dqvf/3ruO2227Bv3z6Uy2UMDg7ihS98Id7znvegu7sxdet4WFLStGrgwp6HFLJYpoI97tHdGOoTN/ORsTL6u1OSRocMoP+1H27L4wMi/XWaSUCKAcxHAkpl4U8egWObuOr5G3DTT57CkfEyLDAEJGQA6lgKAGongQEAQipg1SJ6OpK62yqNDK8BgPz5L0di5aamqZzK1DmKbmJdL7i2KcOLWv/VH5w7V1/KVLQ8DSOSAz7QncZMxUetKhupSQAwVm5AZeU5WHXBi5DZcvGsXvqxTMlCzXT+7JnPg905EOvJ1PD6FRsw8/DPwRkFMUxkUzY6swkcGi1h1UAOtpKAeHg9RGsAqpIBTNcau+OqwKpiAMS00PX8N2Hyjq/DL4zE5kEv1Ix0HsRyEBRGwWmgq5cBoa8blqOdl2YAIK6Z+jRmNdvYh1MLYDpxR9BIZhGM7gOh85eAAMDqXKGr0TkNQExLA0BATjID2Lt3L770pS9hZGQEW7ZsOfYLIvbkk09i06ZNePe7342Pf/zjuOKKK/C9730Pb3nLW1CrNW+Tu9iWssSNUPNPzPspS6zYCIDAPfIMBnvDVFAq00B1DIAFsDv7dYVxqzYXA1BaL7FsEfxqUvGozExm9WCQy89dCQC497Ejkq0oAIik0LGTzQBElk1vZyqsBq7r+27le5DZdMGcxwkZQAgAHRdeidT6c+d8nd09qFtgNzOrSTEYAN36d7Ig60JUtkcyi8q5VyF3zova3vyBMG7RjAEQ02pIQ6y3xIr14IGH6r7t+rGh/iz2HS1qRqhjANSH1dmnZScglICmZ5GAODFizk7HhVfC6V8Df/zQMVNJWzFCCKzOfvjTYwIAIjEAFaD2gtkBoJkZMlaXswIkSNAgARrJDIJpOb60BQCwuwZ0LQpoAG5aCBRDVLv0cQgEzwsAzjrrLNx///34+c9/jne9610tvcE//MM/4G//9m9x/fXX441vfCP+7M/+DJ/85Cexd+9e3HXXXe2suWVLSS20GpxYADASKdi9Q3CP7EIqYaGnI4nDYyU9CETrqAvcQM25GIDc3Ihp45O/+hd847e3zL7elAAAzjlW9mUx1JfFfY8flWuVEpAqoiGG9lBORgwAEBJQUCqgpyMZSkA03vp6PqYDk3PIOR71cd/BbXMCaOP6RCwhWgwGCAYAAMUZWRmus6kab/CbH/8BfvbMf837PQFRNd152WuRWt88aHosS2+6EHb3IEa//xl4cmLeeZv6sOtQAZPTNcleode86p2fitXSVKWjNd1EArK7V4Klu2KMjJgWel/xPwAcu5agVbM6+kIGEA0CKwCQP5vFAGYzNUfaIbQhzmIkMzq20xID6FqBoCiaOnIJAFy1r1AxgOMgAc0LALLZLLq6Ggst2rWVK4V3OTPTeIEcD0tKBlCt02JPhCVWboJ7dBc456Kz4liprg5ABlYXYDoLyGiUI0IJyMLwzBiOzIzMehwzlQOnvp6De9FZK7DvaBEmoXUpq7agqPJCPxlZQIBgPqxSRG/OxnihBs45WP3w73mYzgKaY/N56PBj+D/3fhmHi8OzPqfedDuIukDwih6pf/N4ul8zR+C+A9vwm8OPzvs9AcH2ul/8tlkD2McyM5nBims/BmKYGP5/n0BQKuDCMwfAOXD/9mGY4GBy59DXQ0ReUY5WMwbQedlrUbzsHQ2PJ1efjq4XvRXZc17Y8LeFmN3RLwb3yFRmZepcKwCo+jVQNab1GCYAwEfSoA1yVbzfUWsMAODwpyVYRZsu9q5C1/PfrCuJF9NOWBB4cnISY2NjeOihh/CJT3wClmXhwgsvPCHvnZJfUu0EMwAASAyeBlqeRlAcw+nrurHzwBR2HihICUg8Z6EMwHBSMLPdYE7jBadnv5oWPObPuVmrDA1WEzLQRWeKC84Ej0hAgZ4NrBjASZOA8gL4VqQ8BJShWPY0TX6ksB+Pj4QzV8fLk3jfjz6GkdJYw3EUA5gLAJREUGiia8+6Ptk6PKiTgLJpB5mkBYOogp/ZGUDFr2pJ5USa3bUCA2/6CwTFcRS3/RQbhzrQ05HE47tHRSsIxQCaZNdVvNljAMQwZ01J7rr8dei48MrF+xAQabFqBkJghtudV8cAAKA8z/NspnJYmQc6UqSx4V6s2rkVAJC1AJPD4CzQNSGAKATresGbWuqeO187IZXA5XIZl156qf59xYoV+Kd/+iesW7eu5WNt37792E+qszFXDK14YueToEdOLAiYxQB5AE/9+udY370FScfAzb94Gn+VZai4LpAQF+FDDz00Z6DyWGY891owJ4Vt27bFHk+MTSINYHRiElWnhgk22fAcZfbwKLIAtm97EDQ/AMo4Uo4BCxRl1bnSq6JUJTA5MDVdAAAcOnoY24LmxzweptZvjU0hB8Ad2wMgiV/d9zDKklXevPMuOHszuHZIbCh7yocwVp7AXQ/fjdMy8epeu+gjncjisV37AfNI0/d8Zkqk8z769ONwD5WaPqeZdTgpjOzdgeGD/wB7fA+Kl/w+YCWQSxFY5fjG//QzO3BGbkPs+yl5FZjMmPU7O96WT3VgdNfj2JvdhHV9Jh6dlpWztRpgAKVKqWFthbKoGh4rTsy67hP1eezJErIAvMlhTDsJQO7PTz+zA/yoh9HJ0CF44OEH0e0cuzFkphbAqE3DCGoYm5rGgchnsY+OQHGAHXsPgE7OT7cnfg2dAPY+cg/MmTFUggBqe96zfy+2TbfH5o5lJwQAkskkvvrVr8J1XTz99NP4+c9/jlJp/jdR1M4++2wkEq1lCYyWJ/CVg9/F4OohbN3QeuuHhRinPvY++A0MJRnOvfRCFPle/Ostj8EiDE46DVBxHs47/7wFZyht27YNW7fGP1/RnML4jjuwYuUq8IkjMBNWw3OUVfc5OPrb72LL+tVIrTsHAHDxM9tgPsNgp1MAfDDCke/shhdU4KQcwAXy3R2zHnOxLfoZvbE+HNp2M85d2wU8XEVn3xqkk08DPmAlHDgJRz83OGQAR4GVa1Zh67r6tW4FXnntnO+7e/sRYALoHxrA1hbahxx6uBfG4ccB6eVvyQPZM7Zi/eMPgu+QcwGk1rtq7SpgEnrNPvVBd1FQk5+w81tvR59ZDzozidO3bgVNDWP7rl8DAJxUEnBnQCyjYW30wP8DAFS5i+c+97kNjk2z6/R4We1IB4789nsgnCGZywFMBN5XrV2Nreu24kfFXwFS/l+/eQNO61l3zGOOHr4Xtf1TCFiAFUOr0R35LJXdBoYfvRUAcNZzngu7e+W813rw0e8gzUtARw41VgQgmPXA4ApsPbP98+W67qyO8wmRgEzTxGWXXYYXv/jFeM973oO/+qu/wl/+5V/izjvvPBFvj7TKAjoJEhAxbTg9Q/DlqL3fuXgt1q7IwYgE0oCFxwGUPXxkeyxoqGmoISSgWjB7HEQFQWk1BOeLzlwBEwwskgUEJQHRkxwEltlPeYib+sh4SQfKfE5Ri0hTao3VoD05pSbjIjNea46L1TEAGAZ6r3wPjHQe5R0PABCBYJMwMABsFglIST8nQwJSZveshD95BJwznLepD0lbXLRUFa/VrZlzjopfhW2IGNGJTryoNztSra/iWEBcAkrINPFm/YCamZHMiJoFRhskoGgMgDSRZOeyxMrNqB15BqBxCaiZNLhYdlIKwc477zwMDg7ihz/84Ql5v6TKAjrBaaDK7O6VemCLaRp47xvOg0UYiBW9IBdnE71z7734/lM/07/rXiuWCc75nACgWiGwahi8u/ScQfTmHTjpMG2Pmg6IZWv992QFgY1EWpTpV6bQnU/g6HhZT9SinMU+qwL/dhMBqvJYM01aX89lva/4A6z+Hzcgf/4VyGy6AJVdD4NTHyt6MrFsGqAZAIg1+9Rf1CLGVszpXgkeeKAzk0jYJs7dICSSgAgAqF+zR30wzjCQFRtvsUkm0Ik0I53Xm3QQAYBoFlB3Unymsj+/79ZMZvWQ9oYYQGQC3nwLwZQlhzaBVYrwJg7HM5YWsYtBvZ20SmDXdU9YFpBlmDCJedK8Ebt7EH5hRHunZ6zthAGuqymBxUN5j3ooeuEMV93vXmZAzOWt1weBAcAyDWQTBDxy82QufjV6Xvb2hlzqE22EEFh50fN9sDcbAwCfUbgxAFggA5DXTssMIN+jA3zpLReDuxVU923XDCAg0Wsgfh6rEc//ZLEAu0dIGCod9GUXiOI41ZXGZ0EsNVatc0VOFL41qwY+kUYI0T27gib3mxd46E53AmihFiC6ydczAJl2zYmp51HP19Rkt2BqWHcJiK71eNiiAsCBAwdw4EDYdtl13aZa/+23347JyUmcdVZjX5vjZQ6xTx4D6Fkp0tCmRXMsNf4uKvosVq8iN/Dg0zDbJwQAOcGJBbrJVL0RywEx7ZgEBABgNEafSd8Q0huec9LTQAGRChrMTIie9eNl3U8/YLSOAYh/V9q8BhQDaDb8Zr6WWn8uiJ1EeceDAgCOyQCiAHDy2CsA+BOCwZ69vhOAmFerTGWDASFoDSoG0CQV9ESb1SFbQjQBW4/66JIMYP4SUETmaZCAJAC0Uc3s9K3WjedopKhzseThZjbvIPDnP/95AMDu3bsBALfeeiu2bduGfD6Pt73tbQCA66+/HgDwy1/+EgAwNjaG1772tXjlK1+JjRs3wrIsPPHEE/jBD36AoaEhXHfddYv5WeY0x7D1TXyiLXoT2d0rAZmrTiPj9LxFKvNWm3HRLSFpJUS/mkQaPFL67wYurCb6pGpwxuoAgNNAV34C4Ubln2QGAIgiOG/v4xhcnUFhxoVveoAhAMCjPhhjMAxDs4FamxKQen2z4Tce9VH2KuhKHaMfvuUgvfF8VHY+iBVXvEM0BMTsLDC66Z8sBmDmukHsJPxJkR2lnZeI1+9TH45MYFBrHtQMYP5ps8fL7M5+VIF4zC2Swpxx0rBNe94MIDbZrK4QTA2T58do7d7MiGEisXIjavufiDGA4yn/zRsAbrjhhtjvt9wiKkqHhoY0ANRbZ2cnrrrqKjzwwAP44Q9/CN/3MTg4iGuvvRbvfe97T1gvIEAAwIluBaFMAYA3eQRpbNVSUHSe6mLpfGoznnFL6M/0wEiksfYjN2G4NAY8Jp5TC1xkZglQGaksaDXutYk+KvELknMeVgKfZAZAS1NY2S3qHdyaB6QRW1vKSIYMoE0JSLHHZgzgJzt/iR/uuB1fvvofj5nKm9lyMcpP3wc+thfdOVs3+gIaJaDKEpCACCFCwpyQ6bH62g0ZgEd9lV0ZSkBLigFICUh+NwYx9H3iUg+OaSNrp9uSgJq17DaSWfA2EyyTQ5tR2/+EbAEtHlvMTsb1Nu9V7tix45jPUZ6/smw2i49//OOtr+o4mGAAJwcAzHRON1oDAC43p6gQo7y/+w8+jAcP/RYfuLSxWnI+pjbjGTf04gkhMS/CnYMJWdkuMVRcNgIT66Ux+uxTP0b7TzYAgDMMZsTZNCEya6jsr+MGLlJ2MswCatMJqM3BAMYrk5hxS3ADVycczGbJNWIYuDe8Fy957iD2RtLzPOoDYewvtunPd3M6Hmb3rNRtzTmNzzAA4h6quseyThZZJ7MkGICluoLKSzhjp+DJ2IVHfTimg4yTnnc7iFi1b5OGe2YyA96mapNYKeMAEgDq793FtlOiHTSgGMDJkYCAeCYQIgzAJGGLBQB4fORp3HPgIZ0a2Kq58jhFNy7jROWFuTKBcs95KYKpYZR3Phg+2EQCigPKyZWAAKDHEZulSVgMWNVnrVElAbUbAxCvK3sVMBb/bjQ7mMcmbea6QEwbfmEEJuFzpvsthRgAIJIYgukx0adGxVg40112ox6qqgJOOyl0JHIo1tqr91lMi8YACCFIWgl41NNOjGPayDgtMIBItW+zKX6dz38jausvaWutiaFNAKDvt7SdOq4xgFMKAE5mTrLdvVLTaKWjUnCk5USpaE8SDt62pxqVgKIWlZjmat+cOf0SWF0rULjnuzq7Q8QAoscKNABk7NRJZgBCRjRrBXTlErBA4UcCaOqzuloCap8BmMQAB2/wFEMAOHaAmBADVqdoUIZZOlQqq3hVEBkjaFcC8qg/7x43s5ndMwRwJtoVs5ABZGwhI0bjV+oeS1tJdCRzmHZPPgPQcwEIgWPYcEwHHvW15JawnJYAwIzl+jcCQPb0SxH0bWxrrVa2C86KDWAyIy9tp/57poGeaHPIyQaAQdCZCTCvpmMAlHPdqVTd/JWIp9mqcc5DCaguXTHqRczFAIhhovOy18Ib3oPqnt8KsOJM02dxLF+vN+tkQBmdNbPoeJtqhU2LExjszcAkTE/WAiIMYAESkKqf6E6LhoilOnBV19V8AAAQxWEqLTjWo75JDCAvB5C0CwB/8Yt/wC1P3tbWa5XpJIbJI2H8ilGk5bUb3aAUU0naSeSTuSUhAZnpPPpf/ycg3StgmRZs2chQAVerMQBi2Tr7Z7FmF0Rt6O1/D2eTqPzN2KlFSxBpZqcOACxAAqp41QUHkFU+tT95NBIEZg0MoNaCnFBvDExLR8W6YGVcs5/7POTOeSHMXA8K9343wlbiEpCi/Vk5EONkNYQz0nnAtBDMTGJlbxYmWKzro/qsCgjacQI8GfTuzwiwqY8DtCIBAcIjDQqj4CzQFdYmMZpmAWWdNFJWEpU2YwDDpVEcKBxu67XKnO5BAIA/cSRWaZ2S125UDqz4VSRMB5ZhojORP+mFYMqyp18KapiwDauBAbQaAwAik83ayPY5lhHDRCDv17SdOq5B4FMGABKGg1rgttTPXdmn7vkCvvjQtxb0/lEvSscAeFQCinuo5RYuRmVRL7xBAorGAI4BhMS00XHhlagdeBL+uNg86vPVFaPIysKXk1oMJmsBBntFdW0zBhBNA201vqJAoy8tAcCdDQDmyQC6BkSHynJR12ekm3h6Fb+KtJ1C2k61FQOgMhV2qlpo+bVRM5IZmJlOwQAYlUF2phmAR6N1ADXNavPJHMp+9aRVMdebz3wJALYEgJABZJw0qn6tIb4zm6lAcDMJaDEsCgDLQeBFMMewwcHnzICZzUZK49hXONT0b9967PvYNbHvmMdQ1aD+5NFILjXTN4vaUBciAfmR1IO5gsDz0ewzp4sgVvnp+8Vao+8TCQLnJAM4qXGAfA9ocQIr+4QEFGMAOgYgfoproLW1KlbWlxHxhvqNvhK0xgBUVoo/eUTHANJOumkaaNpOIe2k2pKAFHBNLYIMY/cOwR3ZD1CqE0DrnRdAFIKpa7pTylf11+LJsoAGUgKyY8WSjukgK9Oi5+t4ibbPZF6jVtsxtR8sB4EXyRw5LKWdIOCMV8ZIebzBc/Soj+8/9TP8+sBvjnkMw0nCzPXEdFTKmabRIQMQN3o7ElAUAOZkAPMAQbtrBezeVSjvEABAwXVA0mfxGABwcjOBNAPoyYj5xTEGUJM/XV2s1KoMpM5XX2Y2BqC+s/kxALtTzFkICqN6LnTaTjbNAgoZQOsAoJjeVG26LeYbtdS6c+EN70YwM65TgtNaAgqvO7VmAOhIivkKzeYCnAzzWQDbsJszABnQnn8tQBbESSyohfux1kogM5aWJaCFmwKAVrV8n/pwAxc+9RsCWupimapOz+tYds9K+OOHY6l0jmnDNEyt0WsJqA0AULQx52SaZAHNLwgctfSmC3QX0wBAUga8PBrowF9WtppohwHsmtiHrz/ynwvenMx8D4KZSQz2ppEwAW5FAcATQVzqoivVCaD1QLACjO5UJ0xixALsquIYmH+jOEsCADjTFZ8ZOz0nALQjCap1U0ab1i+0Ymk5V7m840GdEJCWw4aiQeCqX9PSUEdCMIBmk8FOhgUsgG0qCciLxABsXRg5X8fLTOUXNLd5Pmu15FqXJaBFMAUArbaDiG7E9dOkQgAozOtYydVnwD26C+5BUVQXcArLMMUFGXgIaKA36nZueMUAetPdmPHKMcaiNhdCyLwBILMpnNgWgCNthWxFxwAWwAAeOPQIfrzzDoxXJlt+bdSsXDdAAyRoFRee0Qs7FVZn1iR4c87RJT3SVgFAna+klUDWycSqgaMOxXwZgJnM6CAijcYAmkpASaTtZFsxgOjnLDRxUtR5mY85/Wth5ntRO/BkLEcdiMuLFb+qWW2nPN8TlSksBfOoiAEICSjQ605Yc0tAXuDhn+75Io7OjOrHOi97Lfpe8/7jtlafBpG1LgPAgs0hEgBavJGintNIaTz2N3WxzJcBdF58FcxMJwr3fQ+AYAC2YcMxbHgsiEkTbcUAJHj0ZLrBOIvJBn5EspnvZp0Y2iSybCAkIFX4E715FpIFpLytPVMHjvHMuc3K9Yp1TY+BMBpLrXQDV88F6JS9elqVgFQL6ZSdRDaRiV0T0WO1ItspFhAHgPBGV8wibaeQsdMLigEAwGTdNVrxqnjX9/8M2448Nq9jEUKQ2XRBLCW4KQAENe0o9Ga60ZXswKPDT7W89uNhAY0zAHUfiBiAuI6b3XdHZkbwwKFH8Fjkc9jdg0ivP++4rVXIVQIAKGcLruWYzU4dAFASUIs3f2kuAJAXy+Q8NVYjkUbXi35X9xKnUQZAvRg4tSUBaQYg8tWjkoTPfBjEQMZOzfscEMNE+rTnimODw1YBtFgMoH0JSJ3bPZMLAwC7W85TnRoGWFAXA3B14F91fVwIA6iX19SxCCHzZgBAvDgJEHJKtLWy2vB1ENirtCyVxRhALQ4Ak7UCqkEN+1tIEU3LSWj1DCDWCiKSBWQQA1tXnoNHh59cEplAPgtgxQrB4llAQHMQV4B/IovaVMDakZXiUQl3Me2UA4BWB4KU5pCA1N986s9bssmd+2I4A+vBIbw8K0JJozR/oRIQEA8EezSAbdpIWImW5Bql/VJwWJEUOn8RgsAaABbKAFSG1dQwOI23rnYDT2/gqltnq960AsyUlUQ2kY0xAPWd9aS6WgIAlQlUv5kGsoeRWmPKTiJtp0A5a7kvfFTqm6yTKdsZcp9cdzaIndCglbAcGMTQMQDGmYwBhNr4BUPnoha4eGL0mZbWfjxMedWOacFnQVgJLOsAgOaOl3KkTuRsA5Wyast963jNBDj1AKBVBiC//IFsH0bKzRkAMH8ZiBgmeq98NxIbnwMOxBmA7FRpGmZ7WUAsDgDR9Duf+nAMC0krMe8YAABkNl+E3ivfA5ZIibUaAqzUTZ9LiHzohUpA9d4ta4H2GnYCZq4b/pQoslOBVYMYkgFICUhq0q18/ujzFQOIxgDUd9aX6WnpO9OZQBEJCAhZnO6pI4PAQOvAFWUnhWrzBIZWAMCwHKTWn6trQpREoeoX3MADR1jdDgBn92+BY9rzlprma0+OPoO/vP0fW6o/Cb1qESNS35djisyglJ3E9tEdDbUAJRn0P5FVzVEJCDh+LaFPOQBoVQJS3t7GrjWNQWC/dQAAgOTK09D3hj8HAOlVC0qq2ElvqqtNCUhsmKEEFAcA27SRtJyWaiGIYSJ//hUiXhEto6+XgNooVy95ZRjEwIxbaggUfuXhb+Pv7/78vI9ldw3qKmvloWadNFzq6u+8XQZQ9WuwDAuWaSEnGYACLLXJ9qW7ZXuB+W1IKgbAiAAqHV+R36HuqbMQAJDH6E/3YKpOAipLgGl1U+u48FWw1opBTpoRsrCPlVhzCACO5eDcFWfioSOPLTjbK2o/3XUXnpn4/9t77/ioqvz//zW9l/QOgUACJIFgpAiuUgRRQcUC2FFWV3dxf7q6ll1Z/aq7ttXdtbLrWj92BRULiAtYEAIYpfeahIT0SabX8/vjzjlz75RkJgxhkPt8PHho7txyzi3nfd71HEoogMAb8AVrAXFjAdXY6CB7deWl2Na8G29s/khwHNUA+jOcNSSsRAGQFJQSBSSQ9MEEZIdMIkVxWhG63bYwO33og0xEAACh0Dm5VMYGVTqbzNSlH5cTOFMXqQF4AiETUKIzYCAYlkZnfMFMYAkkbHDqiw/A7nFgaHoxgEgzUH1XIw52HIn7XIq0XOYDoCYgvVIHl9fN6gDplTrIpXL2DButzTjcGT3Bj4/L54YmOEAblDr4Ar5QcTmWJMblCMSfDBbUACRSpgUCoVBegQ8geI8TfSecXhdkUhmydBkR7yedvCQqADTFlTCeM4frg1TONMLwNvM5M38k2h2dCfkbesLt8+DnRq6MdiJJZl6/l0sEk1IB4IBCpmCx/OcPPRcXlU7F8n1r8NW+b9lxdBLY/xpASFiJJqDjhJaBpbOieGcjNo8DeqUOOXou0oTvCLZ7HCwTNnyG1Ru0bINQA+DalqlNh93rTHjGRM0HRqUeCplCEK/OTEAyFYuKSejcfh9kwQ/eE/ByNkqZHDKpDHKpPOEMa5/fB5fPjfKcUkglUhzsFA72XS4rrB573MJKkZ4Hv70LfoeV2dX1Sh1nAvKHTDgahZq9A6//9AFe2vRmr+d2+lxshm4Ilr6ggwLVLliSWJxrBitMWQAk8EvAyhMAUUxASr4GkHj+glauhlljing/qaDqy6yWDvhUI6TmP77fgs8Z+RWQQIIf+2AGimYG/Llpu2Dlu7jbzXwA3L22e+xQyYQLulw36jKUZZZgxb5v2DYbTwNIphbTEzRngZmARCfw8aNWqODyutBm78CNH9+FPW0Hej3G5rZzAkDHrSrUbA+ZgWxeB9I0ZugUmggnW2/QmR5fA3DwSg4ESCBhf4WX+CCTSCGXyWFU6iN8AJwJqK8agJ99PNQERF9OlUyRsAZAC2+lqc0oMuZFRALRtser4suDkUB+Wwezq+uVWrj8HpYRq5IroZGrmKA9ZmuNq169i7fQC3V6U7OAI6JMRPwVJZU5xQgo1WwSAEQ6gbUKDXTKvpmAXF6u3ekaEzqdwkg1WlzO5XMnnBwZene5doc0gJDZio9ZbUShMTdhZ39DdxOuW3JHxLuxvv4nKIIlv8MTHnvCGzao2tx2JgwoUqkUg8xFgqgpairy+L39VlHY6w9q3MF+iiagJKCRq+H0ufFz0w44vE4c6qzv9Ribxw69UsuWuOP7AeweB3RKLdI05oRNQNE0AJfPBQkkyNCksfPTa8ajAnoDPijl3EBiUAnDFbkZuwIqufI4TEAylpji9fuYX0UpVyZcDI5+VHqVFoPSBwgcwf6An/3eZo8viUiRlhdqK9UAVFQD4NrGaQAaVvSr1dERV+SOy+uO0ADocU6vCxq5GgalXrA9HgpufBzS7IECW29PJqC++AA0cjXMahN8AZ/AhMSvfGlJMFOXtpFzUsqZOZOaMDXyyFWyTGojrAlG0Wxu2gFfwIf6rka2ze3z4KfGbThrABeSGm+GMyGEs6vzNACbxxEhAADArDHC7nWGMrx51+gK64Mv4MfWY7uSrhmEayuiCSgJaORqOL1ObGvZDSA+u73NY4depYNWqYFeqYswAXECwNgHARCcRclkUErl8AQ4DUAtV7EKm3aPAx6/F3d/9Ves2Lem93MSH1NpDSq9MA/A74NSxkUBeYOLpSfWXmHIqsfvgSIYo6yWqdgg+7dvn8N72z7t9Xw2NzcA6ZU6DE4bgG63De1ObrDnf3Btjva42keL7QGh0Eq9QsslgtEoHpkK2qAJqNPVBX/AD7ff0+vsig6kANhATzUUWvyMlsSItmZwLCQyeTAbnOfs42kASpkCcqmMJwAS8wG4fC5o5CqkB53ffDMQXxiERwj1Bp3xy2WhsGCA7wSOLJFgVAk1UpfPjU93rewx0mtnMHSUH39PzT/nFo+HSqaM2wTkJwEQEMGgaotiAgJ4JSyC5jFqBQAi8yl+atyGR799Frvb9sfVjnjhF64DRBNQUlArOPV/R8teAPHZ7akPAABy9JmRAkChQZranHDJXV9wbVUFLzGFJtHQwlQ2jwPNtla4fW40WVt7Oh0A7iURCgC+CYhzKqmCM1lXL2sCRJ7by8xVnkBQAwheSylXwh0sK7CzdR92t4ZMay6vC1/sWQVfWEVD6oTUK3UoNhcBAKtbz68hH68JSKpUQ6bnNCe/hKuvrw6uBezyuTlfhUwOtVwNp9eFVntIsPTmXHX5IjUAem8dPu6Z0Xck0fBdn9/HatQDPB8AL55eLeeKjiWqATi8LqgVnAYACCc8Dl7VzvBBrTe8fPOlNCQAYjmBAcCoMqCb5x/5uWk73t76Mfa2H4x6jQAJYFdwUOXH3//YuBUGlR4jsobCoNLHvei8L9hGBU/bsnljaQDc/aKzfavHjkJjrmAbhWp8PzftiKsd8RLKAxBNQElDI1fjkKWefbz8D+KHuk14vub1CJui1ROS/jm6TEEugN1LNQBT3NnAlGg+ACoA+HVJaP2ReASMj4RMQEalXvDBeQLe4ADIDWSJJm4xH0Dwg/cEncAAl0jj8XnQ7bbC4/cKBu1NR7fijc0f4bsjGwTnozNlvVKLTB03cFM/Cn9W12qPP8xPEVy4xCcB5EF/BwFBt9sGdXCA1Sg4AdDCEwC9Ddour4sVwjMo9ZBJpGzyQE1A3CIo8oRMQEDItKaUUydwSAOgA6lEwkVbOTwJZjB73dAo1Cz8lf++2zwOFBi4QS3R6Ba+CYhfrIytBhZlkRSDSge7x8FMn1TriHXt+q5GJpj5juoWWxsGmPIhk8qCZs7Q/X625jW8/tMHUb9DD2tzKLKGEMK+Fz40X8Ti6kIgEIDd40ChMS9qe6l2ubkHAUAIwe7W/QmND16/aAJKOmpeyd1BaUWCAlnfH96I745swJ/+9yQaurjF22klUDrry9Znos3ejkAgAF/AD5fPDX1QACRacTGaD8DhdUIrVwuyEo/ZOAEQj5PZS/w8DYD74KiKzUUBKdjHmagfgFYnDPkAvMwHoJJzTmA6WLc7LczERAXm8r1rBB8AHSh1Si3MahMkkEQIAL1Sh7YEColRM5Af3OBE+9rl6maaj1bOmYCEAqDn58aFgQbLG0ilSNOY0eHg2kqFtkQigV6pTVgDCLf18n0A/GiavpSEpqYrWgQv3ASUa8jmksT6LAAUzCRI26yWqyCVRg4rxqBZhS6nSa8Zy3S6q5Wb/aepTYJZd6ezi5X0MKoMggnbT43b8OW+NVi2++vINvMil5Q8s080DcAUXMfA4rLC7nWAgCDfmAOpRBpTABy2NMTsy6ajW/CX1U9jV2v82dDegNAEJAqAJEBjufMM2ShJL0YH74NodXSgyJQPl8+NB1Y9hW63jc1A6Iw8S5sBPwmg09XFoih0Ci3Sg2WGEzED8TUA+hJaPTZoFBpBXZJGpgH0rqb7Aj6o5CETEHdObnDzBktBhDSARE1APtZWKgDoy6mUcclldFD1B/ywBO22LUEBcKTrKHbyPgCbx8HyCORSGUxqAytYRtX6wWkDEkr0EWgAUhlPAFjZ/4c0gJAm15sAcPJMQACQoTEzf4XTF6p9o1fq+qYByKJHAfFNKX0pCe0M+gDUCjU0crXgHbJ7uRBmk8oQYdboDeYDoCZB3mp20cw/AGBUC30ndFYfS/jsbNmHDG0aStIHsn0JIehwdTGNhm/mdHpd7J69s/UTbGj4WdhmlncjZ5orAIEwoFAfgMXVzb4fo8oAo0ofUwAAsbUAul5IeC2xngjPAxBNQEmAfqiV2cOQpjbC6rbB5+cKcLXZO1CRXYbfj78RDq8TBzuOsIdPTUDUVNHm6GBRFNQEBCSWDMYPpaMDaZfLCk3wY5VKpJwGEBQAXW5rhB09HC8J2eX1YbVNqMmGCohENIBAIABCCOTBGZ8n4GMCBeBMQJwGEJpVtwW1gVZ7OwaZi2BQ6rB8b8iRbfPYoVNqIQ0uiJKmMTEBSgVAcVoROhydcTus5cFIIB84DYD2ldMAQiYgt9+DZlsrm0n2NGv3+X3wBXyC2Xi6Nk2gAdDqlwZVHwRAWGRKyAcgFAA63rKQ8ZgSCCEsDBQI3t/ghCcQ4Gr2cNqXse8+gKDgouYVm8cOXSwBoKKrg3HPlkYeRXNAE0Kwq3UfRmQNhUltZPvavQ54/V62roNRqWMChWqP11ddjsFpA/BK7XtR2xyPBqCQKaBX6mBxdfFMlTqY1caIvAmXzw2tQoM0tQmbj+2MOJfL68JPjdsEbYwHn98blgcgCoDjRh1U4ytyythLZHF3w+5xwOlzIUuXjmJzIQCgvqspFKpIBUCwxk6bo0OgHdBzhZfc7YloGkCX28rMCTqFBnaPA022FsiC1S17U9U5AcCdKzx0MNIElEANFUFbg6UgeD4ALgzUKxQAwZl7i60NBcZcTC05G5satzAtgYbXUtJ5ZpVuly2Ye5HJNK54YCYgCQT+Dovbyp49NeXUdTViUFoRa0ss+HWAKFQDIIQIlkDUhdUJigcaXRUtCihcA3B4nVh9cB3mf/wHNFqbezyv2+fm6vLIeQIg+H6GHPBUACRuApJJpJBKpFBK5Wx22uGwID1YhiQco4pqAMGkKuYDiHy2TdZmdLmtGJ41FCa1Ad1uKwKBAHs/0nkagNPngtfvZaVEcvXZmDjwTG72zjMPMRMQb1YNRNcAAM4M1OWysnfDoNJxwiiKANDI1RiVNwJbj+2MiGr6sXEbM9/EKwACJAA/CQjyADy9TP76ymklALJ1GVDLVSjPLhXM2luDg1WmNh0GlR4mtRH13Y1sZhghAOydrAyEVqEN2VgTMgHxfQDcC+kP+NkHq1Nq0e7sRKezC0OC5RJ6e4F8vCggOnjQ0DxqslHJqACI36HIb6tCqkCABODyupgPgIaBtjrakRPMl2hzdMAX8KPN2YlsfQamDzkHhBCsq/sRAKeZ0PsKBAUAzwdgVOkFGhefd7Z+grVHNka0U5GRD6nWCL9cATnPB+D1e6FmGkCorMIAcwGkEmmcAkCoAXj8Xtg8dhYFBOC4fABSiRRyqZznA3BFCICj3ceweNP/wel1YW9b9OgZCl34iLYtTW1i99cenBToFNqog1pvcCGK3LOnpUEAoN3ZiYzgZCgcAxMAVAMI+gCiXHtn0P4/InsozGojCCGwemxsIkC/XapVWD121rcMrRl5Bq7MBn8BF28UjRvgkhijQQUjdTIbmAYgNJfRCLHReeWwe53Y33FY8Pu6+lqkaUwYYCqIWwCEhBWXaS+TSEUTUDI4e+AYvDTrbzCo9Ez973R2sZkrTecvNOaioauJPXwal69RcA7aNkcH7N5QFItCpoBBqUuoHEQ0DYBeA+AEwIFgLZzy7KEAehcAXl4UEF8D8Af88JMA5wNQJB4FJKxbFBlCx4WBck7ggaYC6BQatNo70OHgZsnZukxkatORpjHhaPcx7vhgDgUlTWOG1WOH1+9Ft9sKk9qALC33PPiRQIQQfLXvW6wNChI+UoUKA/+//4LoTJwJSBaatauYDyC0LVuXCZ1Sy3ISokEzPwUagNYMgBtgCAnNsqkPwBfw47ma1wQLiMSCRgEBnDnCR/xcfoLPLSiqplVq4Av4MDqvHAqZAnW85Kie2k3blqlLR0fQOU+1V51Swwa6hCJUeG1WyBTwBXzw+r3oclljagC0ZEq32wZCCBtIowmfRmszFDIF8vTZzCHb5bIyDYb63PghuVQDSNOYkWfIZudhbQ4OqkoZN6um61tHiwICeAKAZwUwRblXbp8nOKksAwDsbTvEfrN7HNjctAMTis5EhjYtbgHAN1dx/z1xq4KdVgJAKpGyQYevAdAZJhUARcZ8NHQ3sTKwBt5MNVObjlaeCSh0vsSygQWzap4A0PJmk/TjGJFVytra2znDNQCH18leKKVMzsIhE/EB0Lbyo1WcXpegFITX70WLvQ1ZugxkatPR5uhgjtbs4H3NN+SwWVk0ExDtY7fbBoNKjwxtpAbgCri5RK6gOSAciVTG1VGRypmwAzgtBQA08tCsOluXEZy121mb7lrxiKD0gIvNpPkmIK5dDd1Nwd9Cz8zt9+CTXSvw/ZGNcdW+odEeABUAvqgJVROKzsRFpVNx98TfoNCQK8iOjQYt70DbnalN45zzrm7Bu2tWG+EP+BMqNEdDgmmbAc7XQ0BiagAyqQx6pQ7dbivcAQ98AR/UchUz7/DpdFqQrjFDIpHApKIhmd1sAA1FAQUDHdw2tDstMKr0UMoUyNZlQiqRhmkAdBLDFX9TyITtD8cUtPfbPDYuDDcoLH0BnyAaiysTwpUJD9cmNx3dAl/Ah4kDzhSYOHuDr60AQS1L9AEkF5PKAIlEgk5XF1rtHVDJlGygLzTlweVz47DlKJdQxJv9ZWrT0G7vYKo+X6DE+4CB8HoqPA0gOEDRZDAAGJoxCDKprMcZBCEEXuKDSh7pA6CzBwXPB+BOIBEsVluZAAjOojx+L7J06cjQpaPN0cns/dk6rpBeniEHTcFZmS2KCQjgtJxutxVGlUGgcVG6vEKnX6z2ymVyNujz28ifVXMCQMeeZZ2lEfVdjdh8LBTNQQdjjcAExLW1IajNaHlRQACwZMeXAIQJbT22VcoXAH4mOGlVVwAYllWCG0ZfAYVMgSJTfq8CIBSTH9QAgtoUp72GItjMmtAAGy80SYm2GeDqKgFgQjsaNBvY7ucG0IHmQk4bCEvm6nB2MTu/OUwD0Cm1vHInociiDkcnE8xyqQw5ukyhAPBHzqr57Q/HrDbC5XOjzd4JvYILVgi1JXSvXD4XVMFEPeq3o9RZjkIlU6IkfSDSNaa4AjkAoQkIgKDiarI5bQWAVCqFWWUM+gDakalLZ2Vhi0xcNMnu1v3QK3VsOwA2u7UHS8nSFyhblyEILeyNkAYQ2wQEcIJFo1AjXW3qUQPwBXwgIMyppVaoIIEkKADoy69gH08iGkAo6kPGSukCYMvV8R1p2boMZGnT0WZvR4u9DVKJlA0K+YZsWD12FmIrFADcB9/m6ITVbWezu0xtOosoAoAuHzdY9PQx0UJafMFN/5/+VwIJMrXpgtBNakbgD67RnMBmtQkSiQRHmQbACVvaH3nQfBE+sEWDiwKiJiAlvAEfC/3N02dHPabIlI8Op6UX34WwNj8tVtfqaA/TALj7nkgkEI1cAsDeBzrYpsfQAABOAFh5AoAGXIQLn06nhc3yTUH/Wpe7G53OLqQHt9PzAQiWEbEwwQxwod5NPBMQP3kNCA38sZzANBmsobuJmYBDCWJ8ARAKEdYptYIaSzaPA3oVN34wDTd4nzucFrTECAsNmYCon0XepwWX4uG0FQAAV/TJ4uJ8AFna0GyryJgPgJst0YdPoaWa2xzczICSo8+E1WNnZXx7w8cLpeMPqtowAUAHgTSNGZ0ui+AcrfZ2XPvR73Gg4wirxUNNQFKJFGqFCg6Pk6mPSpkCUokUKpkysSggXtkKfgw1bTe/ngo1Adm9ThyxHEWGNo1FMVHn3IGOwyAgUU1AdV1HQUDYx52lTRckg3V5Q4NqR4xBi5qAVDz7LksECw7W6Roz5DK5wAREY/tpIiDAEwA8zUEulcGsNrL9QpE23AAxt2IWisz5cc2qOXNKaDbqI340WpshgQS5htgCILydAKcF0qJ8dN0L2m4awNAapr2GBrX4cwF8AT8zW9H3IR4NwEA1AJ9QAPAnNoQQbqAPvg9cnogcFpeVEww8AROqzCrUAICgtmlrQYBw5iV+/SIgNPD3JgCOdh9j9Z9MUe6Vy+dmZlWdUgs7TyjbeFUEqHCimuu/N72FRav/HjXBi2rsfBPQSdUAWlpa8Pe//x3XXXcdRo8ejbKyMmzYsKHX4wKBAJYsWYJbb70V5557LqqqqjBz5kwsXrwYHs+JkWiJkKYxo8PZhTZ7BzKDdmqAc/rSF4A/SwVCM6k6y1FolXx7MmfmiFcLiBYFBIRUdjo40kGAsyEKB7xDnfXw+L3cf4MrcvEHPa2cix1nJiBavC3BktCxHNYhE1BodpylzWD3aHfrfmb/B8Ccc/vaOUcZ3wmsCzrT6aIhNMKDalyULl8otC+Wyc0bNKvIpDI24+MnggFAtp5rl16pYzNiep2j1mb2fJwxyhtkaNJY9BgV2mWZJXhw8p24sHQyzCpjXCYgb4QT2IcmazMydekxzRMDggIg3BH82Z7/4TfL7oPH54lwAvPNaQ6vEzKpDCqZMuqsNp42h2bS3Pt2zNYKlVwVMxEMCNYDctvg4JmAwq/t8Drh9nvYQC+RSIIhmd2CJDCA8yvolFq0Ozph9dgFGkC+IQcev5cNuN5wDUDasw+A3he33xNFAwh9h3wNgG9OBIR+Lr6JkxCCAx1H0OnswuqDP0Rc2xfmBFZKFSc3D+DQoUN4+eWX0dzcjLKysrhP7nQ68ac//QmdnZ2YN28e/vSnP6GyshL/+te/cMstt/S50ckiTW1Ci60NVo9dMFABITMQf5YKhGZSjbbmMA2ArhcQnwBgUl4iHFSZBqAI1wBM6AjTAGhmYafTwlRE/oxGq1ALTUDSkM0+kUzgWMJKGeYD0Cm10Co17B7ZvU4mGAFOSMokUiYA+MKVqsmHLVyJbhr9kalLg8PrDNWF8VqZ4InlB6CVFLm2UdNPMAw0OCDSCCO9Ugu714lAIMBMQL6Aj5XgYE7gsBLH/MGGChWpRIrybG6BG5PaAGswIigWhBC28AfAPTtfgNMA8oPaUjQytGnQyNUCU5XNY8fSncth9zrRaG3hLWTPF86cOc0WLGJIawxxM+z4BYAv4OX5LYIagLUFGUHHbSyoCcjmd0AqkTJNhj+gUm2AP9CbVZymbnEKBQDA1bw6bOFWdRNqANx3Q01TvgCdBAlNP70JACA0BuiUWsgkUhbBRAhhTmD6O98HwDdzMgHgsMDi6ka32wapRIpPd62MiPCJEFZyxcktBVFeXo6amhqsXLkSv/71r+M+uUKhwLvvvov3338ft912G+bMmYPHHnsMv/vd77B+/fq4tIgTSZrGxGZKmTwTEAAUBs1AVP2j0P0IIYIZbI4ucsWwnvAF/JBKpJBKpYJBO9wHQF/kNI0JTq9LsHgHXZym09kVMgHxNYBg8pCXZwICOC0jMQ2An0YfRQBQP0hwUOXfyyyeYJVLZcjWZ2Jf+2EAkdpVOi+SipqA6HOgmkGXz9ZrXgQ/SoXOzmhIqFQqxfCsIajI4SYyrO6S14F2RycbYKh5xelzQSKRRAwU/MEmev37YIx6D+WK/TzBCvA1gBb23KMhkUgiHMGf71nFolMarc1weLm1JVSCAAbOnGbnheBKJBKY1caEslS5LHChM7XV0cHCY2NhVOkRIAF0eLpgUhmgkiuhU2gE2cC0HXxfgkltQF1XI/wkEOFjMKr07D5khGkAAJgfwBPuWJULJy/hGFR6FipKxwCpRAqj2sCEpTfAVRFgWrtCKAD4gQ56pQ4KmQLtTguOBAXWpcOno93ZiW8O1QiuzffZcW0+ySYgvV6PtLTYtr1YKJVKnHHGGRHbp02bBgA4cKD3FblOJGk8h1KWTigAYmkAZrURsmD5Ar4A0Cq5Gj6xHDvh+ASx1CG7OnUolmYMRmVOGYZlDQHAm0HwZktU2HQ4LSyuX6BNKDWCKCA60HAaQCKZwCGHNd9fEbJdcx8RHezNGiOz+4drVnmGHDZQ0Rr6FP7sjpqABqcPAAAc7DzCRYx4rRhkLoRSpkBHjEJxtHQ17SsAQUjo/5tyFyYNOotrA6+Mc7ujEyNzhkMCCTOvUBU/fGabEUUD4MOclz3MrH1h4X5KmQIWrxUun7tHDQAAEwCEcNVOv9y7GmfkVQDgBACtYCoIYNClo9XRDofXIdBeyzIH48ejW+JeXYtmL9M2A1z2arqm5zGCPtM2TycTkGa1cLnKkAAIvQsmtTEiB4BiUOnZjJmfg5CmMUElUzKHergTmO93iYZMKmOTEAPPD2hQ6pnPKDxAQBfUJgkhIIQITEBUw+1wWpjGMrPsPAzNGISPd60QZBBHtFUm/2XlAbS1cQNXX4RKMuEPONQkQKEzz3AnsFQqZS+aLkw4hJeL7gnhR8TTAIIvU7rWjEWT7mAvIf0g+HbvFmYC6mImIJVAm+AEgIclwVANoK8+gPAw0JBAAUICQCqRsnhwvgkIgGBgi6YBUGiIn1ltRIY2DQeCtZm8xIdsfaYgczgcvo06pAFEn+nRNlA7cp4hG7n6LDar7HBYBCG5obbSkEOhVkQJxa/H9gPwBSvAvQcewn3ovQuAPFg9dlhc3Xhv2zK4fR5cO+oyZGrT0WhthpNXwZSSqU1npbC1vHf3shEXwO3z4PM9q3q8JkWQCMabEPSmAdBn2untZiYWLhAjJCRDJqDQuaiw4LYLTUD0nIDw/ZFIJIJIIDYJCov/j+UEBhDVD8g380QTAHQpVx/xwxvwRYQ6dwY1ABqBNr3kHLQ5OliCJNC/eQDy3ndJPv/9739hMBhw9tlnJ3zs9u3b+3zd2tpawd/HXJwJRQopDu7cj0O82ZI74IFGqoanzRlxnNrPvTzdbV2C3xReGepsDRH7R6OppQkIENTW1rLMQplEhq2boycPtXssAICfdm2Gu8GGAAkwDaDZ2oode7is04P7DsJZzw06DosN3U4rdu/jVkDbt2cvulTtcNmcsHitrJ0BEsA37RtRbhiCHFUmwtlj48oO7N29hw2sAFB36AgULQSdXu4DdnXY2TlVwXt07OBR2Oss7BhvV8iEtXf7bsgkMva3w8K1WyVVYsvPm9n2DIkRO5v24rsf1wIAupssUPhkqGuNfq+9Pi/aW9tRW1sLr5MTjIcPHIb3aGSy01EXN0P8YTunhlubu6AnGuxrPojvN/6ATQ2bMco0LOI6bU7uOAXkUdvQ4eEGsi27t8LfGD0yzObj2tPU0Ihaay26Oizst/bDLaiN0l6K08HN1v/y1VNodrej2lSO5v2N0BE1Dhw7BKNCD/iIoG1WG3f+JmsLzEQv+K1MPwhf7F6FIlcmNLJIjYaP1W6F2qtAbW0tWt0hB72t1drju3/Mxb2vBAQ+uxe1tbUIOPxodrWw4/a07oNKqsT2LdtC17OENISGfXXoPhy6pqOTuw9qqQo7tgjHBrVPgUNt9aitrUV9ewOkkODnn7gqobZu7rj9e/bBoow+aZMEleTWo82o7eLa53N4YPF2C/p+tO4oajtq0dbNjSc1tRsgCVoJ2ptaUesI3hNnAE2uFrR0tSFNbkRtbS1cwWTTNT9/jwojl/G/x0q/t73oVLXCaumGzWmPa1xJlH4XAIsXL8a6devw8MMPw2Aw9H5AGBUVFVCpIhec6I3a2lpUV1cLtnU4LHiz4VNk6TNw5plnRhxz1pnjozq11nu3of7IMQwZWILqstA5d2+pw4G99Rg9enTUmuh8Nm7cCbX3GGuT/NAb0CjUEW2kOL0u/LfuI5hz01A9rBqt9nYEDgRYka/8AQVAEzCqYiRzru3aUocde/djQPEA4BgwqnIU8g05+KFmK7rb7OxaK/Z9g00HtqMwrxAXjoy8vuOwnx2vkiuBIx8AAIaXDUdlzjAESAAWgxPnlZzNZk3rfdtwrK4N54w9m1X8BAB1iwFfrVkLlVyFsWeOFVzHXUewum0D0rVmwX04srMF721bBk2uHmgAxo8ci5bdFuxpPxhxvwgh8O9/BQX5BaiurMbXjg2oczahqnwkBpgLIvqWZ23GWw3L4DdIgDbgzPIzoGrW4pNdX6FZ1wU/ArjmrMvZPaUU2drwztHPYdTooz4zh9eJl+s+RFpeBqqHRX+mrfZ24DAwuHgwqgdXY8fPh/Bz9y4oZQqcO+5XgvsWTolrKN7/dDla3B24euSluGTYdEgkEmzGPnx3ZAOy9VlIUwrvo6k9A58eW821P6dQ8Ft2Vx7uXvEo6tStuHrkpTGvCwCvN32CrMwsVFdXc07W+qUAgNHDRqE6vzLmcW2ODrzR8AkAYHDBIFSP4vp88EA9zjjjDEgkEqxZ+yOySIagba66AFa1cQL6V2PPZtoHABzd3Y4Nlq3INmRGPId9245iz64VGFU1Cju2HoLCqmT71GzYjt22gxhdWYVsfeSkB+C+88NHjmLUsEpU5AwDAGzYuAMdx7pRXV3N1WOqB0aUDsPovAr4GqRY0fI9BpeVYNcubkJWXjoC1YWjAQA7Nx/Gvn1HEPAHcO6Qs1BdWY1AIID/O7oMMMtRPZprm/2wD2gGqipHIteQjR837UZjY2vMsaE33G53zIlzvwqAL7/8Ev/85z8xd+5czJ07tz8vHRWT2gAJJIIcAD6xIhpokbJw/0COPhO+gA8dLkuEUzkcvg8A4FRSbRRnIkWjUEMtVzETEJ39D88cgnX1tcz0pAqLAvLyUtdDxduUsHkdcPs8cPvceH/bMgCx7dUxw0CD55NKpLii/ELBMReVTkVl9rCIQYw6N8PvHRBS4Y08tR4AStIHAgCr8Z6ty0C6Ng2dDdwqbPznxF/7lfYViL5KFdcOTkWnjrkMbRoGmPIRIAF8unslhmcNjRj8gZApIpr9H+AcwwqpvMclC8NrvlDHZJ4+u8fBH+Ay2edVXoxicxHOyK9g2/MNOXB6XThma414rzN5NvJw82WRKR/jikZj5f7vMK/i4h4nMOGhq5SeksCAkA8AAM8EZILbz4WtahUadATLQAj7amR95n8z/HNGMz/lG3JACMExe6vALMhvdywfANe2SBOQXhFK9oowAfGWcqVLrvLNh+kaM/uWaA6EVCrFAFMBi34DIs1Vv4hEsB9++AH33HMPJk+ejAcffLC/LtsjMqkM2boMFBhze9+ZBx3cwz8ilgtgawMhBD81bo8ZBsj3AQCcnS/WYEJJ15iZE5jmG1AnMV03QBkWBQSE7NB0oBmZOxwOjxOLVj2Fl2vfhcvn7rEqpCAMNEomcDQGpRXh3EHjI7anqU3cwvdh9n/aPwAwqoWa4eA0zhG8rXk31FIVtEoN0jUm+AK+CMdleAw18wHEiPag9etp1E+GxswGfLfPjfOHnBP1OIVMAVOwXEU0uPj1nitt+vxCWy+1R+f1Yv+n579sxAWCwR8A8o3csc221oi2GdUGNgjqlJHx+mMLRsHhdfZaaI4/mPL9H7HqAFGUvAWJzMwJLMxD6IwS6kn3Cd8OhHwA0RzQuTQ029YWrIYr/N64NvXuA+D7GXRKLdw+N3x+X0SlWP5Srs6AO7iN5wPgCSmaAwFw614c7qxnpuCIMNDgGhwngn4RAFu2bMHChQtRWVmJf/zjH5DJZL0f1E88OPlOXFV5SULH0A+UH0UEgKmSzbY2bDq6BY9//wI2hq1MRPFFmZFoekiiATjB09jNObWO2Vohk0gxNGMQ+xsI1wC489GZPX3pxxedgXt/9Vu02NuxoeFnXDB0MgaZC2OuDEXDSBVSOZuVcG2O/fHEQiKRoNCYxwYAPuFlfikGlR7ZOm41NpOCfvBmAJGhoOGDqooJgOgagEwqg1ahgTfgg0llYFUoZRIpTGojxhZUxexLoSmvR02P1pSPRbQoIADIN8YOAe0NvvM43AkslUhDk5coju3SzBIAwN72nqPz+O8uTaiSS+WCgTIWdB9T2KBucXYhEFz7IXygp07gaBoGrd8VTQMICYAeNIAYEwMA+NXAsbi5+mpBdjOLGgtq0IDQCQxw8f9UA+BHutHQYZVchRye2WmQuQh2r5NVJeYvuUn/6/V7E6rYGi9JFQB1dXWoq6sTbDtw4ABuueUWFBQUYPHixVCre57l9jeZunRBRm88jMgair+ddy+GZBQLz6Xl6gk129uwfB+3+lUDz7vPJ1wDUEoVgqSdaIzKHYG6rqNosbWhxdaGTF0GU+ubgwIgWlIZHYT4s/cz8ivw+LT7cPmIC3Flxczgyku9aQAyVrceEIavJsLCcTdgwRnzIrYrZAqcWzw+YlYLAIODZiCTXCgA2sMEQHgEhV6pjYheCofO3OiHLpfJMXXw2ZhbMVMg8ML548RbcXP1VTF/N6kMPWYD+6LkAQBAnr53DSAWGdo0Juj5oa8Uar4M114BLlEsTW3Cnl7WGghfDwBAr0lgFGreo8su8jWAbpc1GE5qFhxDE7DMUTQAOqvO0WVF/GZQ6aGRq3HMSgVA6B0YnVeO80p+FWFS4mNSGzFtyK8i2gIEB/koUUBA0AQUTQMI9muAKV9g4qMLE9Hw0PCyFfQ7850ALSDuL/jFF18EEIrd//TTT1FbWwuj0Yhrr70WADB//nwAwOrVnKPJZrNhwYIF6O7uxoIFC/DNN98IzllWVoZhw4Ydbx/6HYlEEjH4A9wAmalNR+3RrTjSxSUuNcVYucnHi1UHgEuGTxeEu0VjbOEo/N+WJdh4dDOa7W3I1WfCoNJDJpWhy22FDFIWfw8INQAJJILfAK7MxNzKWQDAFrsIt6lzbQ0PS5MHM1hjD6o9kd+Dye13426Iur0kbSBq6n+CUU5tvtxAFl4OIjyG+vyhk1CRU9ajTV2n1AL2dsFM79dnxh7YKb1NHExqIw7xbLvhRPgAghoVNeP0BalEijx9Nuq6jkZNUKNVQaMJAIlEgtLMwT0uNkMIEfgA6IIlsdYBCIdqd3Qwp1p0m6OTragXLgCkEiluGH0l03aF/UnH3867lw2i4f3J1Weh2d4KmUQmEObDs4ZieNbQuNrMR9+DAOAv5er0uyGXygUauVnDFRHkm38ATiBIJBIc6qzH2MIq3iQmFB4MhNb1TiZxC4B//etfgr+XLFkCACgoKGACIByLxYKmJs62+vTTT0f8vnDhwlNSAPREji4T21v2QClTYICpQFCSlg+/oBYAlpjU47n1WRhoLsTGhs1otrVhcNEZkEqkSFOb0OboEGgUAM8H4LZCIZP3OEMzBWud272OCPs8HVRlvBfSyVsRrD8oCSaEUROQWW2ERCKJMAGFawBGlR7GXj50PTMjJDcvxaTmNIBoQhUQOtcBoCp3BMaZR2JQ0OfRV/INOZwAiOKfoAmP0UxAAJcUtqHhZ1icXTBrTFGd7AAE5hSFTNGr/Z9iDGbY8ssrFBnz8MORTcx8Fc3WP2PopJjnjDYZo+Tos3CkqwHZukxBm/uKYJYfrCJAB3l+SWhXwA29Uiu4d3KpDL8ffyNK0oXtVcqVKDDkssmCL+CDLKhtAyFfmyfghRaJWSt6I+47smfPnl73oTN/SmFhYVzH/ZLI1mcCLXtwTvF4KKRyrDm0Lvqs2u9L2PQEcI66j3Z8CQLC7IhpGk4AKCTRBUCXq7vXmQO/7nqkAODMVbQPyigOwBNNaWYJJg+agCEBbqYnk8pgVkWWMPCF1X2Ph9CSn0kWACoD/IRbgSs8oRDgpfwH76dZY8KkzLE9miXigfoQomkARab84IzdHPXY0ozBAIC97YcwLGsI7v/6cVxZfhGboPjCCgsCnK28Mie+idwZ+RXoaO9gg5tEIsFFZVOxeNNbWFu3CUDv0USJkGvIwqbGLTCrjX02WfIJCQA7XD43V2GXFzFFS0I7/e6ogQ4TB4yJet7itCLsbNkLIDjT5wvY4ETrRGQDn9bloE8EdBZz4dDJyDNkw+VzR40E8QX8kPVhRjKucDQIOGcQLUBHZ0yxNACXz93rbL2n0gX8mvUAv0ZJ/0URK2UK3Db2OpgVITNZutaMDqewHES4uSoewn0AyYKVD47pW0m8rfFAfQjRNICxBVV4fuajgmJnfAalFUEhlWNP2wG8u/VTtNrbBUtbhmtYAHDzmVdjfFFkyZdonFVUjQtzhJFVZw8cC6NKj3V1P0ICCbtvySBHlwl/wI9j1laBD6Cv0EGdmoDCw4tppjDVAOJlkLmIWwzJZRUsuAOEwtXDTbjJQBQASWZ6ya/wt/PuRaEpL6IgFZ/wPIB4KTLls4GfFqCjMyaFRHg+/gDQ2+ynp7LA0UJWZVJZr8luJ5poy+xFG6B6g5mAND3nbiQK9enEcgTz14RIJjSMNTyfAuBm3D0JOoVMgcHpA/FD3Y9YffAHSCQS5pzk2ix0XCcDpUyB6UPOBcDds+PVgPjQb6XT1ZWU+0zDhu3BKKBwAUDXl3DF0ABiMSiN8wscstQLqtkCQFVeOZ6esSipmhFFFABJRq1QM5tkaHHqSD9A+KAaLxKJBOMLR0MmkbKwU/piyMNMQDKpjIU/9mauMfUgACJC6MLyAU4WdH1mfnhc+NJ/8UCLfdEImWRBI11i1QM6EYMpwBXQe2jynajKLe/T8WWZg9HhtMCkNmDGkElotDazcsThMerJYvqQc6CQyqPa/4+HXEMoOigZbZZJZdDI1UEfgJvlAFB0CqoBeBIUAAMggQT72g9FfG9SiRSFweKUyeak1AI6XaAheY1J1AAA4PLyCzGucDQz8dBIimgvuFahhjsOE5Beya17Gi1uPbyt/KUwTybUxNbp7GI2bf4C9vFy9oAxUMlUvWZvJwrTAGJkA4f7AJLJiOzSvh+bNRTLdn+Na0ddBqVMgeX71qChqxGD0wcyH0CyhZZZbcR1VZcn/V6ka8xQSOURg+rxoKOz/B5MQG6/JyETkE6pRZEpH3vaDkCj0CTFXBUPogZwAqEhedFNQH3TAAAu7Iwf+UAHv3AnMBDyA/Sm/kolUphUhug+AN7C5QCnsvenAzgWNIO70RrKtQitXRC/cDVrTBHx3snAoNRDIpHA4urGzpZ9ePWn96OW/U2mySMZjM6rwJPT/4RzisexkEUWox5IXMOKlxlDJ2FqSeIFIntCKpGyDP1kmdr01M4fQwDYvA54iDeq478nyjIHY2/bIXj83qSbBWMhCoATDFeSNpoJqO8aQDixnMBASADEM2M3xyhd4A0IbZIKmeKEDACJQn0sfA2rLz6AE4VUKoVRZcDu1v14Yu2LWLHvG+xq3c9+T6W28pFIJCgOxtXn6DOhkquYADhRZqsTSU7QDJRMDSCWANArtcwkmYgGAADDMofA6XPhYMeRfguwEAXACSbPkI1mW6tg5gcgIjPxeAg5gaObgID4Xv5YpQs4bSUkrCYOGIOpg5M7U+sL6RozVHIVjnaHBABbwD4FNBSA8wPsbN0HlUwJhUyBjUc3s9/Ck9ZSEalEioGmArYim9efmkKrJ3KDGkCy3omQAHBF1JgSFI5LwAcAAGVZXCkOi6u73yZYogA4weQbcuAnAbQE63xQwgfV40EjV0MjV0e189P6QvG8/LHKQfjDTEATBlTj4mHTjqPFyUEikSDfkB1DA0gNs0q6xgSlTIF7zr4No3JHYFPDFjZDDE+wS1WKzYU4YmkIrmEcmQeQ6tBIoGQJWr1Cy3MCR5qA2H4JCoAsbXoooEPUAH4ZRAsFpYuBJ+shSyQS3DXxFowxR9Zi1yYoAGg5CD7H46840eQbctDYHekDSJVZ9Q2jr8TDU+7CkIxijC0YhXZnJw50HAEQmWCXqgw0F8LhdaLV0dEnJ/vJhkYCJUto6VU6VgwuQgAo+AIgMROQRCJBWbAgn2gC+oUQLRSUptMnc5Y6Mne4IEmKwnwAcZibzGoDKwfBJzwzMZUoMOaizdEJT7AyI7NRp8gMtcCYywrZnZk/ElKJlJmBwhPsUpXiYIz64c76lNOw4oFqAMmaxOgUWnj9Xrj90fMAQv+fmAYAcI5goP/eX1EAnGAMKj0MKj32tIVK7J6oDNBohDSA3q9lZtnAQj9AMh3WySbfkAMCgiYbJ2BT2UatV+lQnj0UGxs2A4jMr0hVikz5kECCI5aGlL6/scjWZWJ41hAMCavB01f4Zp6IPIDjFADDMrn1PUQN4BfE1METsbFhM1t0pD/D/5gTOE4TEBBZDiK1TUBcKCh1BJ+oRKVkMaagCo3WZjR0N6X0feWjlquQZ8jGgc463oI7qeFkjwe5VIb/N+UujMwdnpTz6QUCILoPQAJJrws8RWOguQBquSrm+hXJRhQA/cDMsvOglCvx0c4vAfRvKF0iYaChzFWhAPAG+i8uOVFCJjZOAPgCPkgkJ6ZuSjKga+Zub96T0vc1nOr8SvzcuB372g8BSF0B2x/oehAAtCS0Wqrsk29HJpXhnrNvwyXDph93O+NBFAD9gFGlxwVDJ2F9XS0aupr6WQMImoDi+GBj1QNKZsRSslHJldxKaTwBkMqz6kxtOkwqAw521KX0fQ3nshEXwKDSYeWB7wCcWj6AZMM37YSHgdKS0GpZ32fwFTllbGJzohEFQD8xs+w8qIJawMnQAOJR2fUqXdRyEKk+qBYYQ5FAqeywBrgBYnD6QBzoOAyfP3m5ICcanVKLqyovYRFip4rmciLoSQOgv6ul/WPCOV5EAdBPGFV6TCo+Cz8e3QKXl1tIQt4PayMnYgKKVQ4i1WeqeYYcNFqbWXhtKgsAAChJH4gG6zHYPPaUvq/hTB40AYODi9WcKoLrRKBX9CwAcvRZSFMkr6T1iUQUAP1IZe4wePxe7A5GBPXHR0SdwPHO4E1qA9rDa+yn+Ey1wJDLisJ5U1xbATgBQAjBgc66lBdWfKRSKW4ffyOuG3V5hOnjdIJOqoDoAuAPE27G+dknP1M+HkQB0I8MzxwCCSTYcmwngP6xo2brMnFh6RRU5cVXGrg8uwxbju1ibQRSOwwUCDmCm2wtEbXUU5GSYF6A2+dO+baGU2DMxaxh553sZpxUpFIpWxdAHSXSR6OInpWfiogCoB/Rq3QYaC7AjuDSb/0xU5VKpZg/+kpk6zLi2n9e5cUoNObh+Q1voMvVHTSrpHa4Ym4w0afZ1gpfwJ/ys2qz2sgWZUnl+yoSG+oHiKYBnEqIAqCfGZFdCpfPDSA1IylUciX+v7NugsPjwIsb/w9+EgABSenaLxnaNMgkUhyztXKhlSl4X8MpSeO0gFOhrSKRiAJApE+U8xbqSNXZ30BzIa6smImfm7bjSLAMcCoPVDKpDNm6TByztZ4STmAgZAZKZd+KSGz0Si0kEskp8a71hCgA+hnqBwBSe1A9Z+A4AMC6uh8BpK6wouToM5kJSH4KZKlSAZDK74BIbHRKHdRyVcoX8usNUQD0M9QPAKT2oJquNWNIejHW1/8EILXbCgC5+mzOBHSKFFgbnM6FU55qTmARjnxDNnKC6wycyogC4CRA12tN9YFqTMEotDk6AKS+AMjRZ8LpdaHDaTkl1HK9UocxBaOSVqBMpH+5onwmHp36x5PdjONGFAAngbMHjEFJ2kC2+EOqMrawiv1/qgur3GAoaJuj45SZVf/x7Fsxfcg5J7sZIn1ALpVB+QvIhRAFwElgSEYxHpt+X9QY4lSiwJiLgmC1zVNBA6CkeltFRFIFUQCI9MiYwlEAUn8JwGxdJnOunwomIBGRVEAUACI9MqHoTMikMmRo0k52U3pEKVMgXWsGIAoAEZF4Eb8UkR4pTivEG7OfOSXsnbn6LLQ7OkUTkIhInIgagEivnAqDP8Bb+zXFzVUiIqmCKABEfjHQmkCiCUhEJD7i+lJaWlrw5ptvYsuWLdi+fTscDgfefPNNjBs3rtdj165diy+//BLbtm3D/v37kZeXh9WrVx93w0VEwqECINVDVkVEUoW4NIBDhw7h5ZdfRnNzM8rKyhK6wOeff47PP/8cOp0OOTk5fWqkiEg8UBPQqbRguYjIySQuAVBeXo6amhqsXLkSv/71rxO6wJ133ona2lq89957GDFiRJ8aKSISD3n6LGgVmpRPsBMRSRXiMgHp9fo+X0Cc9Yv0F2qFGi/N+ttpvVqViEgiiN4ykV8UmhTPrhYRSSVOOQGwffv2Ph9bW1ubxJakJmIfT31+6f0DxD6mCqecAKioqIBKlfgqPLW1taiurj4BLUodxD6e+vzS+weIfexv3G53zImzmAcgIiIicpoiCgARERGR0xRRAIiIiIicpiRVANTV1aGuri6ZpxQREREROUHE7QR+8cUXAQAHDhwAAHz66aeora2F0WjEtddeCwCYP38+AAhKPezevZv9ffjwYVitVnauMWPGYMyYMXFdnxACAPB4PPE2OQK3293nY08VxD6e+vzS+weIfexP6JhJx1A+EhJtaxRilYAoKChgA/yUKVMACAXA0qVLcf/990c9duHChbj99tvjuTysViv27t0b174iIiIiIkJKS0thMBgE2+IWACebQCAAu90OhUIBiURyspsjIiIickpACIHX64VOp4NUKrT6nzICQEREREQkuYhRQCIiIiKnKaIAEBERETlNEQWAiIiIyGmKKABERERETlNEASAiIiJymiIKABEREZHTFFEAiIiIiJympLQAWLx4MWbNmhU1hflk8I9//ANz5szp8/Gp1p94+eGHHzB69Gh0dHT0uN8vvX/AqdvHrq4ujB49Gt9++22fjk+1fovfYu/valyQFKW7u5uMGTOGfPLJJxG//e9//yOXXnopqaioIOeeey557rnniNfrTcp1GxoayMiRI0lpaSnZuXOn4LfW1lZSWVlJ1qxZk/B5Y/XnnXfeIb///e/JpEmTSGlpKbn33nuPp/mEEEJefPFFcuutt5IJEyaQ0tJS8uyzz8bcd//+/eSmm24iVVVVZMyYMeSee+4h7e3tEftdeuml5PHHH495nmj96+joIC+//DK56qqryLhx40h1dTWZM2cO+fLLL4+rf4nes2XLlpHLL7+cjBo1iowZM4Zcc801ZMuWLQn1j5DofQwEAmTRokVk5syZpLq6mlRVVZFZs2aRN954g3g8nj71L5H7tm7dOnLfffeR6dOnk5EjR5KpU6eSBx54gLS0tETs+9e//pVcfvnlCbcn1rs7efJkUlpaGvHvqaeeSvgahBBSU1MT9Xz034svvsj2PRHfIv3tscceI5MmTSLl5eXknHPOIXfeeWef+kNI/N/i66+/TubOnUvGjRtHKioqyLRp08ijjz7ap28xEVJ2RbCPPvoIhBBccMEFgu3ffvstfve732H8+PFYtGgR9u7dixdeeAGdnZ1YtGjRcV/3iSeeiEiXpmRmZmLq1Kl49dVXMWnSpITOG6s/L7/8Mmw2GyorK9Ha2trXZgv45z//iczMTAwfPhzff/99zP2OHTuGa665BkajEXfeeSccDgdeffVV7N27Fx988AEUCgXbd86cOXjyySdx++23Q6vVxtW/zZs345///CfOOecc3HbbbZDL5fjqq69wxx134ODBg/jd737Xp/4lcs/+8Y9/4L///S8uvvhizJ07Fw6HA7t37444rrf+xepjIBDAjh07cPbZZ6OwsBAymQybN2/G3/72N2zfvh1PPvlkwv1L5L499dRT6OrqwowZM1BcXIz6+nq89dZbWLNmDT799FNkZGSwfefOnYs33ngDmzZtirsIY6x+U8rLy3HDDTcItpWWlibcZwAoKSmJer+WLVuGtWvXYuLEiWzbifgWu7u7cc0116C7uxtXXnklcnNz0draik2bNvWpP0D83+LOnTsxdOhQzJgxAzqdDocOHcIHH3yA77//Hp988gnU6tBa1/G8q3GTFDFyApg5cya57777IrZfeOGFZPbs2cTn87FtzzzzDBk2bBg5dOjQcV2zpqaGlJeXk2eeeSaqBkAIIStWrCBlZWWkoaEhoXPH6k9DQwMJBAKEEEKqq6uTogHU19cTQgjp6urqcdbx4IMPkqqqKnLs2DG27YcffiClpaXkww8/FOzb1tZGhg8fTj7++OOo54rWv7q6uoj7FAgEyPXXX09GjhxJnE5nol0jhMR/z2pra0lZWRlZuXJlr+fsrX+ExH6G0XjkkUdIWVlZ1BlcbyRy3zZu3Ej8fr9g340bN8Z87on0obdjJk+eTG677baEztUXpk2bRqZPnx6xPdnf4qJFi8iUKVNIR0dHn9saTrzfYjS++uorUlpaSpYvXy7YHs+7Gi8p6QOor6/H3r17cdZZZwm279+/H/v378fcuXMhk8nY9quvvhqBQAArV67s8zX9fj/++te/4tprr8XAgQNj7jdhwgQAwoqnvRGrPwBXTTXZxe0KCwvj2m/lypWYMmUKcnJy2LYJEyaguLgYy5cvF+ybkZGBsrIyrFq1KuI8sfpXVFSEgoICwTaJRILzzjsPLpcLR48ejbdLAuK9Z2+++SYqKysxbdo0VkwwFj31D+j5GUYjPz8fhBBYrda49ueTyH0bM2ZMhMY6ZswYmM1mVrqdz4QJE7B69eq4bd/x9Nvj8cDpdMZ1vkTZunUrjhw5glmzZkX8lsxvsbu7Gx9//DEWLFiAtLQ0uN3u4yo9T4n3W4xGfn4+AES8Q729q4mQkgLg559/BsCpl3x27twJgFsYnk9OTg5yc3PZ733hvffeQ3NzM37729/2uJ/BYMCAAQPw008/xX3uWP05mTQ3N6O9vT3iXgLAyJEjsWvXrojt5eXlUfudaP/a2toAAGlpaYk0OWHWr1+PyspKPPPMM6iursYZZ5yBKVOmYNmyZVH3j9U/oPc+er1edHR0oKmpCV9//TVeffVVFBUVHdcAEE68981ut8Nut0fdr7y8HBaLBQcPHozrmr31+4cffkBVVRWqqqpw3nnn4f3334/rvPFCn1U0AZDMb/HHH3+Ex+NBZmYm5s+fj1GjRqGqqgo33XRTvy5y1dHRgdbWVvz444949NFHIZfLo5rrenpXEyElfQD05Qz/eKjdNisrK+KYrKwstLS09Ol6FosFzz77LG6//XYYjcZe9y8qKsL+/fvjPn+s/pxM6L2KdS/b29vh9/sFmlZRURHa2tpgsVhgNpvZ9kT6Z7FY8OGHH2Ls2LFIT08/zl7EpqurCxaLBV988QVkMhnuvvtumM1mvP322/jjH/8IjUaDadOmCY6J1T+g9z6uXbsWt956K/u7oqICjz32mOD+HQ+J3Lc33ngDXq83qs2+qKgIALewU0lJSa/X7anfpaWlOPPMM1FcXIzOzk588MEH+Mtf/oKuri7ccsst8XSrR/x+P5YvX46RI0fG1MqT9S3SQX7RokWoqKjAM888g5aWFjz//PO44YYb8Nlnn0Gv1/exJ/Fht9sFmklubi6efvppFBcXR+zb07uaCCkpACwWC1QqFVQqlWC7y+UCACiVyohjVCpVn9XQZ599Funp6Zg3b15c+xuNRuzZsyfu88fqz8mErlYU614C3P3W6XRsOxWOnZ2dgpcu3v4FAgHcfffdsFqteOCBB463Cz3icDhY2z744AOMGjUKADBt2jRMmzYNL7zwQoQAiNU/ep6e+jhq1Ci89tprsFqtqKmpwa5du1gbjpdE7tumTZvwwgsvYObMmRg7dmzE7/w+xkNP/V68eLHg78suuwxXX301XnzxRVx11VURi48kyvr169HW1obf/OY3MfdJ1rdIzYNZWVl4+eWXmVlt0KBBuOWWW7BkyZIIZ3eyUavVeO211+B2u7F7926sXLkSNpst6r49vauJkJImICD68mXUEx7NNud2uwWe8njZu3cv3nvvPdx3332Qy+OTh4SQhO328dpc+wv6AcS6lwAi7iftQ7S+x9O/Rx55BGvXrsVjjz0Wc4W5ZEH7V1hYyAZ/gBN4559/Pnbv3h3hE+ipf/zfo5Geno4JEybg/PPPx4MPPoipU6fixhtvTEpkV7z37cCBA1i4cCHKysrwyCOP9HjORN7feN9dmUyGG264AU6nk5lajofPPvsMMpkMF154YY9tS8a3SN/1GTNmCHwq5557LkwmU1LMLb0hk8kwYcIETJ48Gbfddhseeugh/PnPf8aaNWsi9u3tXY2XlBQAZrMZHo+Hzfgp1FwR7aNqbW1FdnZ2wtd65plnMGLECJSUlKChoQENDQ1sdtTS0oKmpqaIY7q7uxOyX8fqz8mE3qtY9zIjIyPCfNHd3Q0g0gYdT/+ef/55vPPOO/jjH/+ImTNnHm/ze8VsNkOpVCIzMzPit8zMTBBCImZXsfpHz5fIM5wxYwYcDsdxO+rivW9NTU1YsGABDAYD/vOf/8QMD+zq6gIQv/8l0X7n5uYKrtNXXC4Xvv76a5x11llRnyElWd8iHVuiXSs9PZ29G/3JqFGjkJeXh88++yzit57e1URISQEwePBgAEBDQ4Ng+/DhwwEA27dvF2xvbm7GsWPH2O+J0NTUhG3btmHq1KnsH41FvuWWW3DFFVdEHNPQ0BCX/ZQSqz8nk5ycHKSnp0fcS4CLvIh2LxsaGpCZmQmTySTY3lv/3n77bTz33HOYP38+FixYkITW945UKsXw4cPR3Nwc8duxY8cgk8ki+hGrf0Diz5AOMH2JAqLEe986Oztx0003wePx4JVXXulxwKTtp/3pjUT7XV9fDwDH7d9ZvXo17HZ7VOcvn2R9i9QpHP6+BAIBtLa2nlB/VU+43e6o71BP72oipKQAGD16NIDIgX7o0KEYPHgw3n//ffj9frb93XffhVQqxfTp0xO+1v33348XXnhB8O+6665jvz322GOC/a1WK+rq6lgbj6c/J5vp06dj9erVgpd+/fr1OHz4MGbMmBGx/44dO6L2u6f+ffnll3j00Ucxa9Ys3HfffUlsfe/MmDEDTU1N+OGHH9g2m82G5cuXY/To0REmrlj9A2L30WKxCN5FyocffgggMmItXuK9bw6HA7fccguam5vxn//8p8cQZoDro9lsjlsA9NTvQCAg2OZ2u/HKK69Ap9OhqqoqrvPH4rPPPovqqOeTzG+xpKQEpaWl+Oyzz5gJFOCeg81mizv8ty+43e6otv7//e9/6OjoiBqB1dO7mggp6QQuKipCaWkp1q1bh0svvVTw2z333IPbbrsNCxYswIUXXoi9e/fi7bffxty5czFo0CC234YNG3D99ddj4cKFuP3222Nea/z48RHbqHo1bty4iJnwunXrAABTpkxJSn9Wr16N3bt3A+Ds8Xv27MGLL74IALjkkktYPPjSpUuZQLrssst6vN4nn3yCxsZG9iJv2rSJnfO6665jzrlbb70VK1aswPXXX49rr70WDocDr7zyCoYNG4ZLLrlEcM729nbs2bMH119/fdz927p1K+655x6YzWacddZZEeGXEydOZLPVeJ9XIvfsqquuwocffojbb78d8+fPh9FoxJIlS2C1WvGHP/wh7v711MfVq1fjpZdewrRp0zBgwAA4nU6sXbsWa9euxaRJkwQDR7x9TOS+3X333di6dSsuv/xyHDhwQBD7n5mZKcieBbj3d8qUKXHbjnvq9+LFi3H++eejoKAAFosFH3/8MQ4fPoyHHnpIEDyQyLMFOOHy/fffY/r06YLzhJPsb/G+++7DzTffjKuvvhqXXHIJWltb8cYbb2DEiBG4+OKL2X7J/hZbW1sxe/ZsXHDBBSgpKYFcLseOHTuwbNkyFBQURLyTvb2riZCSAgDgIgpeeOEFeDweQaTK5MmT8fzzz+P555/HI488gvT0dNx2220R8fs0AiNamOPxsGLFCowZMybhkM5Y/Vm5ciU+/vhj9vfOnTtZPkN1dTUbzBLpz5IlS7Bx40b294YNG7BhwwYAwMUXX8wEQF5eHt566y08/vjjePrpp6FQKDBp0iTcf//9EdFBK1euhEqliqllRevf/v37WXz8n/70p4hj3nzzTTaQJdK/eO+ZRqPBm2++iSeffBJvvfUWXC4XysvL8dprr6G6ujqh/sXqY0VFBUaOHIkVK1agra0NUqkUgwYNwr333ss0SUq8fUzkvlFBuGTJEixZskSw39ixYwUC4MCBA9i7d2/CEVjR+l1aWorBgwfj008/RUdHB5RKJcrLy3Hfffdh8uTJfeo3ZcWKFfB6vb36ipL9LU6cOBGLFy/Gc889h7///e/QarWYNWsW7r77bsF+yf4WzWYzZs2ahQ0bNuCzzz6D1+tFXl4e5s2bh9/+9rcR5qd43tW4Oe5c4hNEV1cXOfPMM/uc7vzUU0+Rc845h7jd7qS1qa2tjVRWVpJVq1YlfOzx9ueOO+7oUyGvZDF79mzy2GOPxfw9FZ9XIvTWP0JO/T7+7W9/I7Nnz074uFTst/gt9vyuxkvKCgBCCHnppZfIzJkzWd2XRLjyyivJe++9l9T2PPPMM+SKK67o8/HH05+JEyeS77//vs/XPh7Wrl1Lqqqqeq1rk2rPK17i7R8hp24fLRYLqaqqIt98802fjk+1fovfYuI1pqIhISTFAtRFRERERPqFlIwCEhERERE58YgCQEREROQ0RRQAIiIiIqcpogAQEREROU0RBYCIiIjIaYooAER+0SxduhRlZWUs+aYvPPfccygrKztptZwaGhpQVlaG55577qRcX+SXiygARERERE5TRAEgIiIicpoiCgAREZE+4/f7T9iC8CInHlEAiCSNo0ePoqysDM8++6xg+4IFC1BWVobXX39dsP3KK68UrFvb0tKCBx98EJMmTUJFRQXOPvtsLFq0CO3t7RHXslqteOqppzBt2jRUVFRg/Pjx+MMf/sDq0ffGSy+9xFbOomWNA4EA/v3vf2PKlCmorKzEzJkzYy4gf+DAATz00EO46KKLMHr0aIwaNQqXXXYZKwNNef3111FWViYoSU3xeDwYN25cQlUd16xZg8svvxyVlZU4++yz8cQTT8Dn80Xst2nTJtx4442orq7GyJEjMXv27Ii2AVwlzfCidQBXtKysrAxLly5l26g/Zd26dXjhhRdw3nnnYeTIkVi+fHnc7RdJLVK2GqjIqUdBQQGKiopQU1OD3//+9wC4Qa62thZSqRQ1NTWYP38+AK4u/44dOzB37lwAQGNjI+bOnQuv14srrrgCAwYMwJEjR/Duu+9iw4YNWLJkCatiarVaMW/ePDQ2NuLyyy/H0KFD0drainfeeQdXXnkllixZwiqChuP3+/Hwww/jvffew1133SVYvPyxxx7Dm2++iTFjxmD+/Plob2/Hww8/zBZS57Nx40b8+OOPmDRpEgoLC+F0OrFixQo88MAD6OjoYOvYXnLJJXj66aexZMmSiNLMX3/9NSwWC6688sq47u+3336Ld955B/PmzcPll1+OVatW4dVXX4XJZBIsSL969WosXLgQmZmZuPHGG6HX6/HFF1/ggQceQENDA+688864rhcLKnTmzJkDnU4nKMMucoqRlIpCIiJB/vznP5Py8nLicDgIIYRs3LiRlJaWkrvvvpuMHj2aeL1eQgghq1atIqWlpWTFihWEEEJuvfVWMn78eNLU1CQ439atW8nw4cPJs88+y7Y98sgjpLKykuzatUuwb0NDAxk9ejS599572bYlS5aQ0tJSUlNTQ5xOJ/ntb39LysvLIypBHjhwgJSVlZHrr7+e+Hw+tn379u2krKyMlJaWkvr6erbdbrdH9N3v95Nrr72WnHHGGcTj8bDtf/jDH0hFRQXp7OwU7D9//nwyZswY4nK5Yt5PQgipr68npaWlZNSoUYI2BAIBctFFF5GJEyeybT6fj0yaNIlUV1eTY8eOse1ut5vMnTuXDBs2jBw6dIhtnzx5Mrn22msjrllTU0NKS0vJkiVL2DZ6L6dPn86er8ipjWgCEkkq48ePh9frxY8//ggAqKmpQUZGBq6//nrY7XZs27YNAGdikEgkGDduHKxWK7755htMmTIFSqUSHR0d7F9BQQEGDBjATCiEEHz22WcYM2YMsrOzBftqNBpUVVVh7dq1Ee3q6urCjTfeiHXr1uGll16KWAxk1apVIITgxhtvFKyFXF5eHjFzByBYc9ftdqOzsxMWiwUTJ06EzWbDwYMH2e9z5syBx+MRrO3a0NCA9evXY9asWWwB+96YOnWqoPY9vX+tra1sgfsdO3YwzSgnJ4ftq1Qq8etf/xqBQOC41ym+6qqroNFojuscIqmBaAISSSp0hbWamhr86le/Qk1NDcaNG4fy8nKYTCbU1NRg9OjRqKmpwbBhw2A2m7F161YEAgF89NFH+Oijj6Kel5phOjo6YLFYsHbt2pjL9EmlkfOa++67Dw6HA2+99RbOPPPMiN+p7yDaUoklJSURQsVut+P555/H8uXL0dTUFHEMfxHxcePGobi4GB999BGzty9duhSEkLjNPwCimqLMZjMAbhUtnU7HchWGDBkSse/QoUMBIG4/SSxEk88vB1EAiCSVzMxMDBkyBDU1NXA6ndiyZQsWLVoEqVSKMWPGYP369Zg3bx727NnD/AEkWJH84osvxuzZs6Oel86S6b4TJkzAzTffHHe7LrzwQixduhQvvfQSXnjhhYj1gBPlrrvuwjfffIM5c+ZgzJgxMJvNkMlk+Pbbb/H6669HrJc7Z84cPPnkk9i+fTtGjBiBjz/+GBUVFRg2bFjc1+RrJuGQJFd1j7bOMeV4751I6iAKAJGkM378eLzzzjtYs2YNvF4vm6mfddZZeOKJJ/Ddd9+BEMK0hQEDBkAikcDr9WLChAk9njs9PR1GoxE2m63XffnMmjULZ511Fu655x785je/weLFiwVmDDq7PnjwIAYMGCA4lr/OLsDN7r/55htccsklePjhhwW/0XVqw5k9ezb+8Y9/4KOPPsLUqVPR2NgocEAnC2oi2r9/f8RvdBtfkzCbzbBYLBH7Hq+WIHJqIPoARJLO+PHjEQgE8PzzzyM/P58NqOPHj4fH48F//vMfyOVyZopJS0vDueeei6+//hqbN2+OOB8hBB0dHQA4886sWbOwdetWrFixIur1o4WNAsBFF12Ep59+GrW1tbj55puZ3RwAWyj9tddeE8x+d+zYETGoUxNT+Ky7paUlaqglwAmu8847D59//jnefvttaDQazJo1K+q+x0N5eTny8/OxdOlStLa2su1erxevvPIKJBIJpk6dyrYXFxfj0KFDaG5uZts8Hg/efvvtpLdNJPUQNQCRpDN27FhIpVIcOHAAl112Gds+ZMgQZGVlYf/+/aiqqoJer2e/PfTQQ7j66qtx7bXX4pJLLsGIESMQCARQX1+PVatW4dJLL8Xtt98OALjzzjvx008/4Y477sAFF1yAUaNGQaFQoLGxEd999x3Ky8vx+OOPR23bjBkzIJfLcccdd2DBggX473//C71ej5KSElxzzTV46623cMMNN2D69Olob2/H22+/jWHDhrFF5wFAr9dj4sSJWLZsGdRqNSorK3H06FG8//77KCwsjDqjBoC5c+di+fLlWLNmDWbPni3oP2Xp0qW4//77sXDhQtbfRJDJZFi0aBEWLlyIK664goVqLl++HJs3b8att96K4uJitv8111yDL774AvPnz8e8efPg9Xrx6aefik7e0wRRAIgkHZPJhOHDh2PHjh0YN26c4Ldx48bh888/Z+YfSl5eHpYsWYKXX34Zq1evxrJly6BSqZCXl4fJkycLEsYMBgPeffddvPrqq1ixYgVWrVoFmUyG3NxcVFdX9+pYPe+88/D888/j9ttvx0033YRXXnkFBoMBf/7zn5GZmYkPPvgATz75JIqLi/GXv/wFR44cEQgAAHjqqafw9NNPY/Xq1fj4449RXFyMO++8E3K5HPfff3/U644fPx4DBw7EkSNHcMUVV0Tdh2ol/AieRJkyZQpef/11vPTSS3jllVfg9XpRUlKCRx99NOLeVFdX4/HHH8fixYvx1FNPITs7G1dddRUqKiqYj0bkl4u4JrCISD9y0UUXwe/3xzRfLVy4EHv37sUXX3wBhULRz60TOd0QfQAiIv3E+vXrsX//fsyZMyfq7z6fDzU1NbjrrrvEwV+kXxA1ABGRE8z69etRX1+Pf//733A4HPj666+j2v9FRPob0QcgInKCefHFF1FbW4uSkhI88cQT4uAvkjKIGoCIiIjIaYroAxARERE5TREFgIiIiMhpiigARERERE5TRAEgIiIicpoiCgARERGR0xRRAIiIiIicpvz//+dHu7ZURwMAAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "buehl.groupby([\"weekday\", \"hour\"]).mean()[['e5', 'e10','diesel']].plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 161,
+   "id": "c0f2a72f",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot:xlabel='year,week'>"
+      ]
+     },
+     "execution_count": 161,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "buehl.groupby([\"year\",\"week\"]).mean()[['e5', 'e10','diesel']].plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 156,
+   "id": "3508a896",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot:xlabel='date', ylabel='diesel'>"
+      ]
+     },
+     "execution_count": 156,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sns.lineplot(x=\"date\", y=\"diesel\",\n",
+    "             data=buehl)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 88,
+   "id": "1cb4ef0b",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot:xlabel='date', ylabel='e5'>"
+      ]
+     },
+     "execution_count": 88,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sns.lineplot(x=\"date\", y=\"e5\", \n",
+    "             data=buehl[0:100])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 89,
+   "id": "05af38ea",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAABCQAAAJfCAYAAACnowcxAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjQuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8rg+JYAAAACXBIWXMAAAsTAAALEwEAmpwYAAEAAElEQVR4nOydeXgUZda3716zJwSyAEECKMimiCiCoriLIqOijqLIgPrigowyLojfzLwqvsIoiIgCyqBDEAUVHRQRERHZRQJGWYWwRLYkhABJOkkn3f390XSll+o1nXQHzj3XXKSrnrWqOuacOuf8NDabzYYgCIIgCIIgCIIgCEIjoo30AgRBEARBEARBEARBOPsQh4QgCIIgCIIgCIIgCI2OOCQEQRAEQRAEQRAEQWh0xCEhCIIgCIIgCIIgCEKjIw4JQRAEQRAEQRAEQRAaHX2kF3AmYrVaqaiowGAwoNFoIr0cQRAEQRAEQRAEIYzYbDZqampISEhAq5X3/KEiDokGoKKigt9//z3SyxAEQRAEQRAEQRAakE6dOpGUlBTpZTRZxCHRABgMBsD+cBqNxgivRp2tW7dGegmCIAiCIAiCIAhe6d69e6SX4BWz2czvv/+u2H5CaIhDogFwpGkYjUZiYmIivBpBEARBEARBEISmR1OwpSRFv35IsosgCIIgCIIgCIIgCI2OOCQEQRAEQRAEQRAEQWh0xCEhCIIgCIIgCIIgCEKjIw4JQRAEQRAEQRAEQRAaHXFICIIgCIIgCIIgCILQ6IjKhiAIgiAIgiAIQiOh1WrRarXYbDZRaPDDjh07Gn1Og8FARkYGycnJjT732Yg4JARBEARBEARBEBoBo9FIWloa8fHx6HQ6cUj4ISEhoVHns9lsVFZWcujQIQBxSjQCkrIhCIIgCIIgCILQwOh0Olq3bk1ycjJ6vV6cEVGIRqMhPj6erKwsioqKIr2cswJxSAiCIAiCIAiCIDQCMTExkV6CEABxcXHU1NREehlnBeKQEARBEARBEARBaGA0Go1ERTQR5D41HuKQEARBEARBEARBEASh0RGHhCAIgiAIgiAIgiAIjY44JARBEARBEARBEISw8eWXX3LxxRezadOmSC9FiHLEISEIgiAIgiAIgiAIQqMjDglBEARBEARBEARBEBodcUgIgiAIgiAIgiAIgtDo6CM5eVFRETk5OeTl5bF161ZMJhM5OTlcdtllAfXPz8/n1VdfZfPmzRgMBq655hrGjh1L8+bNlTbTpk3j7bff9jrGRx99RK9evQCw2Wx88MEHLFiwgEOHDpGens4dd9zBY489hsFgqN9mBUEQBEEQBEEQopCamhrmzZvH0qVLKSgoQK/Xc8455zBo0CDuvfdepd3hw4eZPn06GzZsoKysjMzMTG644QYefvhh4uLifM5RXV3NBx98wLfffkthYSF6vZ6WLVvSt29fxowZ09BbFKKUiDok9u3bx6xZs8jOzub8889ny5YtAfc9evQo999/P8nJyYwZMwaTycT777/P77//zieffKI4EG644Qbatm3r0X/KlCmYTCYuuOAC5diECROYM2cOAwYMYPjw4eTn5/Puu+9y5MgRJkyYUP8NC4IgCIIgCIIgRBE1NTWMGjWKTZs20adPH2655RaMRiN79uxhxYoVikPi8OHDPPDAA5SXl3P33XfTtm1bcnNz+eCDD8jLy2PmzJno9d7Ny4kTJ7Jo0SJuvfVW7r//fiwWCwUFBfz888+NtVUhComoQ6Jbt25s2LCB1NRUli9fzqhRowLuO3PmTKqrq5k7dy6ZmZkAXHjhhYwYMYJFixZx1113AdC5c2c6d+7s0vfIkSMcPXqUu+++G6PRCEBhYSEffvghgwcPdnE+tGvXjvHjxzNs2DC6dOlS3y0LgiAIgiAIgiBEDfPmzWPTpk2MGDGC0aNHu5yzWq3Kz++88w6lpaW89dZb9OvXD4A///nPtGzZkrlz57J48WJuv/12r/P88MMPXHHFFbz88ssNsg+haRLRGhKJiYmkpqaG1HfZsmVce+21ijMC4PLLL6ddu3Z88803PvsuXrwYm83GoEGDlGN5eXlYLBYGDhzo0vaWW24BYMmSJSGtUxAEQRAEQRAEIVr55ptvSE5OZuTIkR7ntFq7uWi1Wvnxxx/p3Lmz4oxw8OCDD6LValmxYoXPeRITE8nPz2fPnj3hW7zQ5IlohESoFBYWUlJSQvfu3T3OXXjhhaxdu9Zn/6+++opWrVpx6aWXKsfMZjMAsbGxLm0duVDbt2+v77KjhqrqWn4/VEnLVCPJ8bqg+1usNgpP1NC6uVE5dqCoGoNe43IsUI6X12LUa0iM9VxLdY2VExUWMps1bg2PI8fNpKcY0Os0PtsVnqjhaKn92YkxaOnYOhad1rXPgaJqjpfXEqPXEGvUUl5lJSVeR0qCjmYJrl9Bm83GniNV2GzQJi2G+Bgtx07VkBCrw6DTUHSyhtREPfsKq6mptaJBQ3amkeQ4HXuOVFFlttG1bZyyhoPHqslqYUSj8b0PX5SW11JQXE1irI5aqw2DTkNyvI6jpTVkNjOQnmKg0mxlz+Eq2qQZKT5ZQ7vMGIx6+3/Ajp2q4XBJDTZsaNDQIllPy1QDhSdqaJ6op6zSQnqKQbnusUYtGg3KtTFVWzFVW0hLdn0GTNUW9hVWo9Vo6NAyhhiDf/9qdY2VkxUWMk4/T0dLzbRIMmDQa5S1JsTqqKy2otGAudamPHsnKmrRaTWcrLDQuoUBrcZ+P5LjdcSqzO245wkqz7Ua5ZUWaiw2YgwaKqut6HUaKs3W0+u2H7faIDVRz8mKWmw2qK61EaPX0CqE750gCIIgCALAH3/8QadOnYiJifHaprS0FJPJRIcOHTzOpaSkkJaWxqFDh3zO88wzz/CPf/yDP//5z7Rp04ZLLrmEq666iquuukpxfAhnH03SIVFUVARAenq6x7n09HRKSkqwWCzodJ6GwO7du9m1axcPP/ywi5HWvn17ADZv3swll1yiHN+0aZPLnMGwdevWoPs0Bht/L2fJphMAvHhfm6D7L9tykp92lfPErZmkJRuotdj4YHlxyOO99eVRNBr43yGefResLmHv0Wr+eW8WWm3oRnUwnDJZeHdpERd1iOf2Ps19tp2xpNDl89Cr0zivdZ1Ty2KtuzZquF+vn3dXKPcmKU7H03e04u3FhaQm6ji3ZSyb9lSg04KlLnqO9BQ9l52fyOKN9n6Hjydy08XN2HmwkvmrSri1dzMuOS8xgJ2r8/53RZRVWr2ef/G+Nry+8DBWW92xTlmx3Nc/DYC3Fxd69OnRPp68fSb0Oqi12McoLa/l3aV13zPHtZn5TSGnTBaPa/X24kJM1fZ1tcuIYfj1nr8P3Jm38hgFxWZevK8N5VUWZn5TxIXt4hl8eXNlzGYJOk5UWJQ+f78nC71Ow5uLjirHbro4hb6dk5j+dSFZLQz8z02ZHnO99eVRtFr4572BfScmfXEEgLgYLZXV3q+3+/2H0L53giAIgiAIjcnVV1/N4sWLWbNmDZs3b+ann37iv//9Lz179mTmzJmqIgIVFRURWKkds9lMbm5uxOY/W2iSDonq6moApf6DMw7PXlVVFQkJCR7nv/rqKwCXdA2w17Po0aMHM2fOJC0tjd69e5Ofn89LL72EwWCgqqoq6HV2797dp6cxUhysyIfTRm8oHC6xRwRUVFlJSwabzU+HAPA2xoEi+722WKGxHKeOt9KHTu8zGMwW141YvduVqhSdrFF+LqusM4pLyy0UFNddC2eKT9ZSWFrX78jxmtN9apXz9cGXM8KB1e3+OdbqjX2F9vO1dVukosqi2vaUSf24yclo31/ke766ddXdU4fRf/i46312dkYAWG02wNUZduxU3TU9VFKDN4K9/87r8ob7/RcEQRAEQagPbdu2Zf/+/ZjNZlX7CiA1NZWEhAT27t3rce7UqVMcO3aMTp06+Z0rJSWFgQMHMnDgQGw2G2+99RZz5sxh5cqV3HDDDR7t1ey5xsJoNNKjRw+v56urq6P2BXRToknGxjiMfEeahTMOZ4V76gXYw+EXL15Mp06dPApdgl0i9Pzzz2fcuHFcd911PPbYYwwYMIAuXboQHx8f5l1EDoO+nrfdPVChAQMXHCkTte4Wb5TiHsRhDYe35jS16nb56XPRdX00fh4Kq8r9bOxb7Him3FNsAqEeGTCCIAiCIAhRxc0338ypU6f497//7XHOdvpvWa1Wy1VXXcXOnTs90uM/+OADrFYr1157rdc5LBYLZWVlLsc0Go1ik508ebK+2xCaKBGNkCgqKiInJ4e8vDzy8vIA2LFjB5dddpnPfhkZGUrbL774gs2bN2MwGLjmmmuorKykRYsWqukaubm5Sm7TJZdcoqRjOI97ww03UFRUxNGjR2nRogWxsbEcPnyYXr16hWPLUYGxng6JxrTF7MaiLeoMbm+4G6pBG9k+2vtyytQ2sbfmaltpbIeE5fQzpQ++jIqH40kQBEEQBKGpct9997Fq1Sr+/e9/s23bNvr27YvRaCQ/P58DBw4wc+ZMAEaNGsWGDRt4+umnufvuuznnnHPYvHkzy5Yt4+KLL+bWW2/1OofJZOLGG2/kqquuonPnzqSmpnL48GE+++wzkpOT6d+/f2NtV4gyIuqQ2LdvH7NmzSI7O5usrCzVECA1MjMzadasGTk5ObRq1YoxY8ZgMpl4//33qaysdKkB4cwXX3wBqEdPAEyYMIE5c+YwYMAAHn74YfLz85k5cyYWi4W+ffuGtskoxBCKBRYhHG+vI+GQCMXmdO9jC2OEhMWHxW6JNoeNn4undlnqc61CiVhwRJz4i5BQi/aoT5FQQRAEQRCEaMJgMDB9+nTmzp3L0qVLefvttzEajbRt25Y//elPSrvWrVuTk5PDjBkzWLJkCWVlZWRmZjJixAgefvhh9HrvpmVsbCz33XcfGzduZOPGjZhMJtLS0rjqqqt48MEHVWsDCmcHEXVIdOvWjQ0bNpCamsrkyZN57733VNsVFBQA9vwmB2lpaezZs4c33nhDUdvQ6/W8/vrrLlKgDmpqavjqq6+IiYnh+uuv58cff3Q5X1hYyIcffsjgwYOZMGECYJe3Wb9+PXv27AkoJ6qpYAxAjSAQGsME1p1eamM6JBTDOAxGZ9Bv/X1M6esaNJWUFgdqqSyNHiFhdURIBH+fJUJCEARBEIQziZiYGB5++GEefvhhn+2ysrJ45ZVX/I73pz/9ycWZYTAYGD16dL3XKZx5RNQhkZiYyPTp0wG7ugXA2rVrMZlMJCcnM3ToUACGDx8O4KJtW1JSgsFg4Omnn2bo0KGYTCZmz56N0WhUVcT48ssvqa6u5r777qOystLjfF5eHhaLhZKSEj766CNqampYvHgx+/fvB2DlypVnTNpGfSMkFDu9EQzIplZDwn2VQRc19LHNphQh4c9eV9uKrZHTTupTQ0IcEoIgCIIgCIJQfyKusjF16lSXz6tWrWLVqlVkZWUpDgl3CgsLKS0t5aGHHmLXrl1MnjwZg8HA1Vdfjdls5ueff/boM23aNDQaDU8++SQTJ070OO8okLl37142btyIXq+nZ8+efPDBBzzwwANs3749DLuNDkIpanmiolaRPTS4v1H2YQufNNWyamsZN/dqpjgX8vZVoEHDhe3jWbfDtbjN7sOVHDtVS9/OSUCdsfjbfhOtUtWr/qpRVWPl280nuOniZsSejgg5dqqG978r5oaeKfTs4Fmxd+Pv5STH62iWYHfYFJ2oYX9RNe0yXJVSVv52ig4tY2ib7qmgcrysljcXHSHWqKVv50QOH/euwOCg0mxl2eYT3HxJM5/tfBW1zD/qQ2UiBF/Fr/tNWK02LlK5ToFgqrbyTe4JBlyconpevail67HtBSY+WXNc+XyiopZmCfZfWXn7fEtAOe7/gIubEaMSEfTSxweVtJHdh6v4YHkRB4rUVVXmfF9MZqqrDJV7ysakzw9zVfdkLj43gY9XHePgseAVWgRBEARBEAThbCPiDoldu3YBsHz5ckaNGkVOTo5HUUvnyAhAiYDo2rUrzz33nMu51157jaVLl2KxWJTClhs3bqSoqIj//ve/NGvWTHUd7du3B+DPf/4zI0eOVI6vXr3aZc5giFYZGH+SjGr8d0Op8nPN6bfxNlz/VeObTSfYebCKjq1j6dwmDoAv1tvHurB9PMu2uFbUnbeyBEBxSDjeRK/bUc6NPZsFvN71O8rYkm8iJV7P1RckAzB/VQmmaiuLNpSqOiSWnJZCffTmDOXYf5YX8+J9bVzarfztFCt/w+M4QN4+k102ssKi7NMfq7aeYsteE+kphrAGndTnJf7n6+yOgFAdEgA/7Sqnd0f1/oEUtXR2RgB8sf44I67POP2z67V13+u60/e/Wbye/qfvvzPuGSPenBEAB0vMHHSTgHWXoC2vsrJk0wk6tIwh/0jw3y9BEARBEATBk4oK3y+hGhKz2Uxubm7E5j9biLhDIhQc0p5qOrkOSdCqqioSEhKwWCy88sorDB48WFXq00G3bt3o0aMHM2fOJC0tjd69e5Ofn89LL72EwWCgqqoq6HV2795dWU80kXLwBHz3o992zoRacFCriVxRylCpz0rrU8Oy6VyhwNF4yW1Qu07hzMpRxm+g1Aqtl/oiYaxhKgiCIAiCcNaTkBD6y7H6YjQa6dGjh9fz1dXVUfsCuinRJGU/HUb+H3/8wUMPPeQi++l4aB1KGgsWLKCgoICMjAwuueQSLBaL4qhwZ/Lkydx///2MGzdOOdanTx+aN29OTY3/0PumQn1lP4NBdzpNw1f9A1+ENWIgSvP+HesKlzHrK2KlsQnmktdLkcTLRA11y6WGhCAIgiAIgiDUnyYp+5mRYQ/bnjZtGhkZGS6ynwDNmzdHp9NhNpuZMmUKFouF7du3c/fddxMbG8vcuXMxmUysWbOGrl270rx5cwAmTpxIcXExN998My1btuTo0aN88803xMfHc+WVVzbMRYgAzkUtbTZbg0oY6hWVjAabImAC3mUj2/N162qYiSPpngjm0Qq6AKgPGjpSwdu+oscVJAiCIAiCIAjRT5OQ/XQnMzOTmJgYzGYzc+fOVWQ+L7zwQkaMGMF5550H2NM2Tp06BdhVORwOCwcPPfQQt9xyC1OmTCEvL4/ly5czevRonnjiCaVNbGwsX3zxhSIteibgLPtptUEIqodAndHny/hzFKUMNkLCarN5DYsPmSgNkXA4hMJlRGsaLC6gYWmAAIlGT9kQBEEQBEEQBCFwIi77GQgFBQUAtG3b1mc7h2Hn+DcuLo7WrVsTExPDM888o7TLyclh06ZNaDQahgwZAtTJjg4cOFBpZ7VaOXDgAEBU1oIIFecICasN6icC6ptQUzYsVtDqwvumO1ATsrHfcoc7ZSOaCCpCogldAI3GS4pJ09mCIAiCIAiCIESciBe1nD59OlDnEFi7di0mk4nk5GRF9nP48OFAndpGYWEh1dXVxMbGMmzYMIYOHYrJZGL27NkkJydTUmJXajAYDBiNRjIzM7n++uuVOZcvX45Wq6WmpgaDwS7n55D9fOedd7j44oupqalh8eLFitxnfn5+A1+JxsO5hoRVJUSi1mZBr6lzU9RYa7HavMfTW3yE2telbARnqdVabJ7yovWgvkU1zbVWdFqNEvHhjVBenDu6hN0eD2IttRabIsvqTL3qOhBctEZ9ilo6nkGbzcYpk4WKasvp+e2OjppaG9owF35QW26tn03U1NqUZ6SqxkpCjLZBU6bCgc1mo6LaSpxR6/f5FwRBEARBEIRgiLhDYurUqS6fV61axapVq8jKylIcEu44JDhHjx7N+vXrmTx5MgaDgauvvpqkpCTmzZunyH62b9+eLVu2YDKZiI+PV8ZwFLV0jOWQ/dy0aRPLly9Hr9fTs2dPRowYwaxZs0KS/YxWDHrXlA1nfjv1O0uKVvE/be+muTGFo1XHmHPwv9AeKB7g0tbRdcHqY17nqouQCG6N4VTlqLXYeGXBoZD7F52sYfrXhYC61Ge9cURI0FBREr4HzdtXwRfrS3ni1kzSkg0u51b+dsr/6GFadH3HOVpq5tf9JtbtKHc5/tXGUrbkm+o1tjvLtpykusbzoX5vqfffE3uPVpGzwvW7ctPFKYrEbbSy4tdTrN5WBjTQ8y8IgiAIgiCctUTcIbFr1y7AHrUwatQocnJyPFQ2HJERDhyyn23btuXhhx92OedwcDhkP4cMGcIPP/zA3/72N/76178SFxdHUlISOp0Oq9WqyHn279+frKwszGYzkyZNokuXLuTl5fHSSy+h1+tDkv2MZhmYizrE88tekz1CwonfK/YDUGI+QXNjCoeqCr0PcrrrgSKz1yZ1b/+DMzaV+hRB9VLHXBva3A6OHm9YhZVQr1G42HnQ/mwXnajxcEhs2evfkA/Xqus7zuHjNWwrqPQ4Hm5nhINfArg2zuwrrPY4tr+oOuodEjsPel5TQRAEQRCExqCioiJic5vNZnJzcyM2/9lCxB0SoeCo5+BIs3DG4axwyH7279+ff/zjH0yePJk77rgDgOzsbJ566ilef/11RSY0JiaGd999l6eeeopRo0YBdu3ZZ599lpkzZ7pEVwRK9+7do7b2xM+7f+SXvaaorVsQTdKVDY2vopahOCnCee3qG6DfmPexsZ/ls+cJFQRBEARBCI2ZM2fy3nvvKen5F198MSNHjuTRRx8NqL/DVgsnzz//PBs3bvR46e2O0WikR48eXs9XV1dH9QvopoLWf5OGw2w28/rrr9OvXz+eeuopALZt2+a3n0P2c+LEiVxwwQX069ePV155hYqKCoqLi2nRogU6nb0GQlFRETt37iQlJQWj0UjLli254YYb0Ovtvpjs7GzAbvitXr2a2tpa9Ho9LVq04IEHHuCOO+6gtLRUaXem4EgF95e378ugbEiDLFzGpd2gr99g3q6BmrMgFANe45Sy4Tl36DSa2oavRTaq1a5yP86SkgeRiq4RBEEQBEEQhPoQ0QiJ559/nmXLljFs2DBMJhMff/wxkyZNomfPnvTs2dNrv6VLlwL2P8Kff/55CgsLycnJYffu3Rw5coQuXboAYDKZuPfeezGZTNx///20bNmS7du385///IekpCTS09M599xzAZgwYQJz5sxhwIABDB8+nPz8fObMmcOOHTuwWq307du34S9II+KQLfSmbBDQm+0GtIGUZZ0FhpbPopaR3n4ABn20+CNsqhNGt0ciXKuzhXEsQRAEQRCEhmL9+vXKi2NBgAg6JH799Ve+/vprxo0bx/Dhw1m+fDkff/wxLVq0YNKkScybN09p6yz7aTabmTZtGhkZGZSVlXH99deTmZlJz549ldCf//mf/wFg5cqVHDp0iHfffZerr75aGe/kyZN8/fXXPPzww2i1WgoLC/nwww8ZPHgwEyZMUNplZWUxceJEzjnnHK644opGuCqNh/Z0bIzVT7HJSNnD4ZpXo9E0rk8jFJWNMEdIhDMyokkZuZF23kQS8UgIgiAIgtAEiNZ0diFyRMwhsXTpUgwGAydOnGD69OmKrGZ6ejqbNm1ixowZPPbYY4Cr7Ofu3bspKytj5MiRzJ4920X2EyApKYnbbrsNgPJye7X9119/nR07dpCWlsbu3bv59ttvAbj//vsByMvLw2KxsH//fv7v//6P8847j7KyMj799FMALr300jPOk+cvQqKOyFh54SxqGerc6ufqTqo1q1fKhs3WIDUXAnXIhDqz7+sVzEAhLsC5u9sNaEgbPZqCd6JoKYIgCIIgnKVs2bKFyZMns2fPHjIyMhg2bJhHG7UaEkePHuWdd95h3bp1lJeXk52dzYMPPsiAAXUKfzU1Nbz77rt8+eWXHDlyhPj4eDp06MATTzzh8uJ48+bNTJs2jby8PKxWKxdddBHPPPMM3bt3b9jNCyETMYfEjh07aN++PTNmzHA57qghMXfuXMUh4YyjkGVGRgYffvghEydOVGQ/jUYjqampGI1GAHr16oVWq6W4uJgPPviAiooK5fzAgQNp3bq1y5jnnXceq1evZsGCBcTFxXHppZeyf//+M0ry04EjQmLhuuMMuLgZ2RkxHCoxc7LCLoe6v6iaTolwymTxOkZJWS1bNxxXPWex2li/s5zj5XX9q2usLioIv+x1rZq750idkonNZsNUbaH4ZK1y7NvNJ6gyWzm/TRyd28R5XdfOg5WKckRouCmPHKryciY8OCIa1AzcA0WeygyNSWPVYAhHDYRochAIgiAIgiCcTezevZtRo0aRmprKo48+Sm1tLe+++y7Nmzf32a+4uJi//OUvGAwGhgwZQkpKCitXruSFF17AbDYzZMgQAN5++21mz57NfffdR8eOHSkrK+O3335j27ZtikNi3bp1jBw5kh49evDXv/4Vm83GggULGDp0KJ999hnnnXdeg18HIXgi5pAoLi4mMzOTr776yuX4nj17GDhwIGPGjFGOOVdAzc7ORqPRsHnzZm6//XZmz54NwN69e7n55ps5duyY0vbcc8/l5Zdf5rXXXuPUqVPKvPfccw8vvvii0q59+/YAnHPOOYwfP145vnr1ar777ruQHRLRXHXVESFx5HgNHywv5sX72jDr2yKMHWvQpcKGneX0zqxl/c4yDG3Vx/gm94TX8YtO1LD8l5Mux77++QS/7q+TSvzvhlKX8x/+UHfvbDb4bK2rs2P9TnvEy5a9Jl68r43XueevKvF6LhDcDVsXKUnnc2EygH0Z/e7XMBBCjbJoCN9DoCtRi24ICw3qUIkeD4g4YwRBEARBiCQzZ84E4IMPPlAECK699lruuecen/2mT5+OVqvl448/JinJLoV+991388QTT/D2229z6623otVqWbFiBbfffjtPPvmk0tcxdkVFBVarlX/+85/06dOHqVOnKm1uvvlm7rzzTqZOncrEiRMBqK2txWq1+pUUFdnPxiFiDomqqioMBoPHcUdekUO+053mzZtz8803s3DhQjp06MB1111HYWEh48ePx2AwePRr2bIlPXr04KqrrqJ169Zs2rSJuXPnkpKSwtNPPw1At27d6NGjBzNnziQtLY3evXuTn5/PSy+9hMFgoKoqtLft0Sz7ufvwGr9tLBZ3KyfwRHWLinxHWaX3aAt3bEG2Dyce2w6C+kQUqAmC1NZnMcHOr3IskHoUPld4BhvK0bS1aFqLIAiCIAjBseqXw/yw+XCkl8E1F7fmqotaB93PYrGwfv16rr32WsUZAdChQwf69u3LmjXqdofNZmPFihUMGDCA2tpaSkvrXlZefvnlrFu3jqKiIs4991yaNWvG9u3bKSsro2XLlh5jbd++nT/++IMnn3zSxR40Go1ccsklbNq0SZEQ1ev1aLVav5KiIvvZOETMIREbG0tFRQWTJk0iLy+PrVu3YjKZlKKSvgz5l19+maqqKiZMmKC0NxgMpKWlKZEQALm5uTzyyCMMGjSIhQsXUlBQQEJCAm3atOG9997jjjvuoEOHDgBMmzaNJ598knHjxin9ExISSE1NJS7Oe3pAU0WvC8Byrod17U9O1B/hfOMb7FBWH4tvkJQNpYaEyloibWkG8gj4qiER6Dxh2Kfa9Ttr6jxG+jkRBEEQBOGspbS0lKqqKtq29Qyrzs7O9uqQKC0tVer2OWr3qbUB+Otf/8rjjz/O1VdfTdeuXbnyyisZNGiQkoaxf/9+AJ555hnVcbSOfHUh6oiYQyI9PZ2CggI2btxIdnY2559/Plu2bOHEiRMALt41d5KSkvjf//1fcnNziY2N5e6778ZgMPDWW29hMBioqanBYDCwYMECYmNjWbFiBTfeeCP33XcfZWVlzJ07F4CFCxfy7LPPApCZmcmFF17Ili1buOyyy7jyyispLCxk7ty5qpEcTR291o+ppnEYc6FZOmqGdDBOhnDUFAgVf8ojDtRXGLwJ7EifUUu1iHQofmD+iDBVtax3UUtbBHRG64cmTEU6bCKzIQiCIAhNlqsuCi0yoaljPf1H96BBg7jllltU23Ts2BGwiwx89913rFixgrVr1/Lxxx/z73//m5dffpk777xTsR3GjRtHp06dGmcDQliImEOic+fObNy4kRUrVpCVlcXy5csZNWqUorbRuXNnn/1nzpxJTU0NX331FZmZmZw6dYq33nqLqqoqFi1axF133UVJSQkxMTEsX77cJSSnS5cuPPjggyxfvlxxSKhJf+7Zs4e5c+dy6NAhduzYQZcuXRroajQ+uoAiJAjZxvEVZRAI4bIrbbbgjVRfyiMN6SBQj5Bo2q++g6ohUd+5mvalEgRBEARBaJKkpqYSGxtLQUGBx7kDBw747Oew0S677DLVNs42XLNmzRg8eDCDBw/GZDLxwAMP8NZbb3HnnXdyzjnnAJCcnMzll19en+0IjUzEYlccuULfffedy/HVq1dz8cUXk5mZCcDhw4cVJ4Uzy5Yt49prr1XaTZ48Gb1eT5s2bfjmm28AaNeuHcePH2fHjh0ufX/88UcAlzwlh/TnwIEDAbvH7vXXXyc1NRWAJUuWhGPbUUNAKRv1QDVCIgiz02aL3Pve+vhS6iX7iadhHoqR3diGeTQ7AhpSJSSath3N90AQBEEQhDMbnU5H3759WbFihYsYwN69e1m/fr3Pftdccw3Lli1TUi6ccbbVnH8GiI+Pp127dkq9iG7dunHOOefw/vvvU1lZiTvHj6srAwqRJ2IREj169GDAgAFMmjSJ4uJipcrpsWPHmDJlitJu7NixbNy4kV27dinHXn/9dUpKSqiqquKjjz7i+++/Z82aNbz88sts2rSJtWvXAnD//ffz+eef88gjjzB06FBatWrFzz//zOLFi0lOTiY9PV0Z8+OPPwbsDpH8/HwWL17Mjh07eOONNxg9ejTbt29vjMvSaHh1SDgZNp4pG/7Dwm02GxqNpt4REo2Nc4pIY6/dVw2JSBua9Z2/Mdcf6WslCIIgCIJwtvLII4+wbt06RowYwd13301tbS0LFiygQ4cO7N6922u/0aNHs2nTJoYOHcrgwYNp164dJ06cYNu2bezcuZOVK1cCMHDgQC699FK6d+9Os2bN2Lp1K0uWLOH+++8H7M6N8ePHM3LkSAYNGsTtt99ORkYGR48eZe3atbRt25bXX3+9MS6FECQRc0gAvPbaa7z55pssWrRI8Xo988wz9OrVy2e/tLQ0AFatWsW6devo1q0bs2bN4qqrruLAgQOUlJRgsVjo0KEDCxcuVOY4duwYGRkZ3HrrrXz99df85S9/Uca86KKLWLduHR9++CFxcXH07NmTefPmKUUyQ5X+jFa81pAI0xvl+teQCKzd1gMmRR70hp4prNtR5tHmna8LfY5RVmlh1rd19/eTNd49qK8sOKT8vGTTCc8GQV6///vkEDW19s3m7qng/DaxLudPmoJXGnG/dNU1Nl786CAAV3ZL4kBRNTf2bMYHy4sYc1srl7ZVNVYmflpX5TmQqJYp/z3i9Zy/ax8K2wtM/hudZYgvRhAEQRCESNKpUyfefvtt3njjDWbMmEFmZiaPPPIIx44d8+mQSE9PJycnh/fee4/vvvuOkpISmjVrRseOHXn88ceVdg888AArVqxg3bp1mM1mWrduzZNPPslDDz2ktOnbty/z58/nnXfeYe7cuZhMJjIyMujZsyf33ntvg+5fCJ2IOiRiYmIYO3YsY8eOVWpIdOvWzaWNowClMxdccAFgT9O48cYbPcYEu6xoQkICHTp04K233lLOl5SUMHjwYNq2bcuDDz6oHH/yySdZu3Yte/bs4YUXXgiL9Gc0y8CElLKhwa/l44ihqL/KRmAJHl87OQW+23LS47xGo6HS7LtKZWl5LadCMPxz93hqFwd7VR3OCAeHSsxBr8MdhzPHEXlxykk+dfU2u8Nm/c4yLFbYX+Qqk1tYWqM6li+qaupvDgfjrPom1/M+w1lulJ/VmxcEQRAEIRro1asX8+bN8zj+6KOPKj9v3rzZ43xaWhovvPCC6piOKPphw4YxbNgwj/Nmsxmzue7v53bt2nmNhHCM9Y9//MPlszfMZjO5ubk+2wj1J6IOiVBxOB2cHz4Hjjyi2NhYj3Mmk4lHHnmEyspKZs+eTXx8vMv5adOm8dRTTynSnzqdjuHDh/Pzzz+rzuWP7t27+5QvjSTrf/pZ/YRzykYoRS1PeyTU0h6CsZn8GaiBpoZEUq0jYrhtWe0aWd2cFl66Rl52NBhUMooasg5JND1aUbQUQRAEQRCEsOFc1LKxMRqN9OjRw+v56urqqH4B3VSIqCCr2Wzm9ddfp1+/fjz11FMAbNu2zW8/hyToxIkTueCCC+jXrx+vvPIKFRUVFBcX06JFC3Q6HQD5+fk8/vjjXHLJJfTq1YutW7fy7LPPKpq1zmv56KOPKCwsxGAw0LJlS5544gmeffZZjhw5QnZ2dng3H2F0/mQ/cRhcoZk6qsZakAqQvgw+xzl/BnNtABKe4TQso9EwVLtGDvUOrZ+qj9FkdNehvqh6PK4RI1wOk+i8T4IgCIIgCILgm4hGSDz//PMsW7aMYcOGYTKZ+Pjjj5k0aRI9e/akZ8+eXvstXboUsL/9fv755yksLCQnJ4fdu3dz5MgRRZ7z4MGDDBkyBKPRSKtWrdi9ezetW7fm1VdfpWfPni5OiTFjxrBixQruuusuunbtSl5eHlOnTuXYsWMUFxfTt2/fhr0YjUwgDolQcNhFanKVwUZI+Gpvtdm9af4iICwW/7OG1ZaLQsNQNVrltKPGnwpFMMoo9SGoZ8PbcbVnIVJSLY1OFD54giAIgiAIguCHiEVI/Prrr3z99dc888wzPPfcc/Tr1w+AFi1aMGnSJJe2BQUFiq6t2Wxm2rRpZGRkUFFRwfXXX8/f/vY3pkyZwoYNGzhw4AADBgwAYNasWZhMJvr06cPvv//OSy+9xNdff01KSgpvvPGGMn5eXp5Sw2L8+PEMGTKEiRMnMmLECD766CNSU1MZNGhQI12Z6MHTvgvc6LGqRSYEW9QykAgJPxEQtQE4JMJpy9V7qDCsJZC0C8cxD7+UW9uofPMeJWuKkmUAUXqfBEEQBEEQBMEPEXNILF26FIPBwIkTJ5g+fTrffPMNYK+0umnTJmbMmKG0HT58OMOHDwdg9+7dlJWV8cADDxATE8OwYcOYO3cuv//+OwBJSUncdtttgL1oSkZGBl999RU9e/YkNjaWZcuW0b59e1auXMmCBQuUdgD79u3jn//8Jx999BFz5sxh9erV2Gw2brnlFhITExvr0kQJp9+Na0KzdNwjJPz4F1Rn99XecdZfykZNQBES4bTmosEydF2DaoTE6fujiZaUjSDTeQI9ron2EIkoX54gCIIgCIIgNCQRS9nYsWMH7du3d3E8QF0Niblz5/LYY4959HMUl8zIyODDDz9k4sSJTJ48GYPBgNFoJDU1FaPRqLR1tN+yZQtbtmxxGeuf//wn99xzj9KmS5cufPnll3z55Zfo9Xo6deoEQG1tbRh3Hp2ohbtvyfddeVaNrQdMdMqKY+uBSpfjO/6opPhk4NfRX4RErQX+OOZf+eT3Q8Gro9SH+hrw4bD/D5XUuKiGFKlcd28REsfLXds25pv3aIguier5fBBFSxEEQRAEQRCEgImYQ6K4uJjMzEy++uorl+N79uxh4MCBjBkzRjm2YsUK5efs7Gw0Gg2bN2/m9ttvZ/bs2QDs3buXm2++mWPHjilt27dvrzginBU17r33XrZs2aLIgbZv3x6AVq1a8eWXXyrt5s+fT25uLkVFRSHtsSlVXd1WUOlxbM32MvRZTgcCkP38Yn0pUOpxPBhnBDhqSHif7LWFhwMax5/kp2OuM403/nuEWy5p5vW8uzSogy9/KnVr11g1JAKfx9uSzsDbGDhn9eYFQRAEQThT8SfN2ZCI7GfjEDGHRFVVFQaDweO4QybTId/pTvPmzbn55ptZuHAhHTp04LrrrqOwsJDx48djMBhc+g0ZMoQffviBv/3tb/z1r38lLi6Ojz76SHEUVFXZ357379+frKwsJkyYQExMDF26dCEvL48pU6ag1+uVdsESzbKfubm5PDu4Fa9/fgSA42UOh0F0xJCrGZ0ZzQwUnagJ/1xROlZDYglUZaMxFhMk3otaeh7zV7SzfuuInqsTPSsRBEEQBEEIHyL7eeYTsRoSsbGx1NR4GpcOh4IvQ/7ll1/mqquuYsKECVx//fXcf//9dOrUiWuuucYlEqJ///784x//4KeffuKOO+5gwIAB/Pjjj4rEqOMBj4mJ4d133yUlJYVRo0Zx7bXXMnbsWEaNGkVKSorLmGcSMYa6219nuLmbNjYvPzcsNmweBmZ8TAM9rmehR8KhPqL1c0mjKXpEWUu0rCkM64gO958gCIIgCIIgRIaIOSTS09M5fPgwkyZN4oEHHqBnz56cf/75rFq1CrDXiPBGUlISM2bM4D//+Q8XXHABsbGx/Pjjj2zatImsrCyXtnfccQdDhw6lR48eJCYmcuDAAfbs2QPY0z8cdOzYkc8//5w///nPpKWlYbPZmDt3LsePH6dt27YNcAUij3P9AK03GdAIWUyNqeAYTqM7Wmxl8B0d4FAf8RdB4K9oaLgI5h54i0xorPSSaOQs3rogCIIgCILQhImYQ6Jz584cOHCAWbNmUVhYyPnnnw9Afn6+ct4XR48eZcyYMZw6dYqnn36a+++/n+PHj1NcXOwSeVFaWsp7771HUVER3bp1A+xKHenp6Zx77rkuY/7tb3/js88+49prr+X//b//R1ZWFjabjZKSknBuPWpwNkZ1ys/R8c7WXkOikeZqpHmiidrTpTX8qVBEpZEfxJIaMmUjmoim9BFBEARBEARBCJSIOSQGDBiAxWLhySefZNmyZTz88MMArF69mosvvpjMzEwADh8+rDgpnJk5cybV1dXMnTuXYcOGcfz4cQwGAyUlJSxatEhpl5GRwerVq1m5ciXjxo0D7Eoew4YNQ+sUr56Xl8fy5csZNWoU48eP54477uDUqVM0a9aMpUuXUlxc3JCXIyI4Sz56jZCIkKFjozHf+oZvomi039WwWKIt/8E//lZ8FotsRNliBEEQBEEQBCEwIuaQ6NGjBwMGDGD69Om8/vrrrFmzBoBjx47xzDPPKO3Gjh3LLbfc4tJ3xowZLFy4kPbt2/P999/z0EMPMX/+fP7xj3/Qrl07vvnmGwAKCgq4//77WbhwIZ9++qmiyNG+fXuGDx/uMubf//53wG6k//vf/2bw4MHs37+fF154AbPZzPfff99QlyIqiLY3yY0qNxlFxlxjraX2dC6GDd8xMY2VshEOouk+NjZn8dYFQRAEQRCEJkzEVDYAXnvtNd58800WLVpEaaldbvCZZ56hV69ePvtlZmZiNpv5/fffef311+nWrRuzZs3iqquuYtOmTaxduxaw15pIS0vjww8/5OTJk6SlpQEwYsQIjEajy5gZGRn8/vvvzJw5k/j4ePr06cPbb7+N1WqPbd++fXu4tx9V5B8JTUmkoViwumHTZF786CBDr0njvFaxZ2NNSyqq6uRQHWv+dvNJj3aNZeQHNM3pRsGsabuKnK0gCIIgCILQ+Bw+fJhbb71V9dy0adO44oorGnlFQjQQUYdETEwMY8eOZezYsUq6hKPOg4O5c+d69OvYsSMAEydO9Hio09PTKSkpwWKxkJqayowZM5RzO3bs4Pbbb0ev99z2Pffcw5o1a5g4cSIDBw5Ujs+fPx+AoqKioPfXFGRgUhJ0nKywsPOgF4eE8+tzTVMxtwPjwx+O8eJ9bcKsstHErpHTck+ZLJFbRxD07JDAT7+XexxXu/T7CtXlg8NBNN3qaFqLIAiCIAiCL2655Rb69u3rcqxTp06qbSsqKhpjSaqYzWZyc3MjNv/ZQkQdEqHikAZ1j3KAOrnQqqqqoHRr+/fvT1ZWFhMmTCAmJoYuXbqQl5fHlClT0Ov1VFUFH0HQvXt3n/KlkcTx5Xrw+nSmLDrqo2X0WDoNtZJojpDolBXL74caLnolau5uAAtxNDEaoiy/qB5EW6qUIAiCIAhCQ9OlSxeXF8C+CMaeCzdGo5EePXp4PV9dXd0kXkBHOxF1SBQVFZGTk0NeXh55eXmAPYrhsssu89nPYeT/8ccfPPTQQ2zevBmDwcA111yjPLSxsbEu87z11lusXLkSgEmTJrF3715GjhxJcnKyMubMmTMZPnw4o0aNUvr269eP7du3Ex8fH7Z9RxMasYjk7XKUEOh98NbubL6NZ/PeBUEQBEGIDo4ePco777zDunXrKC8vJzs7mwcffJABAwZ4tK2srESv12MwGCKwUiGaiKhDYt++fcyaNYvs7GyysrLYu3dvQP0yMjIAe65RRkYGY8aMwWQy8f777wPQvHlzdDodACaTiXvvvReTycSNN97IggUL6NixIx988AGbN2/mo48+Usb97LPPKCkpoV+/fnTs2JGKigo+//xzamtryc7ODvPuowNtxMqanpmE3bnRCJZmNLikgqoh4e302exZOou3LgiCIAhC5CkuLuYvf/kLBoOBIUOGkJKSwsqVKxWBgD/96U9K2xkzZjB58mQ0Gg3du3fnr3/9q98agsKZS0QdEt26dWPDhg2kpqYyefJk3nvvvYD6ZWZmEhMTg9lsZu7cuYpE6IUXXsiIESM477zzlLYrV67k0KFDvPvuu2RmZrJgwQJuu+02unbtyvvvv88ff/zBOeecQ2FhIR9++CGDBw9mwoQJSn+tVsv8+fPJysoK7+ajBK2fCAlNNNWNaKClRNEOGx2brensX1lnlDgeomMVdqJpLYIgCIIgBEfl9jVUblsV6WUQ1+0q4rr2C6nv9OnT0Wq1fPzxxyQlJQFw991388QTT/D2229z6623otFo6Nu3L9dccw3p6en88ccf5OTk8NhjjzFz5kwuvvjicG5HaCJE1CGRmJgYULuCggIA2rZt67OdI/3AOQ2hvNxe/K5FixYubR2KG47Ujry8PCwWi0s+U1VVFVu2bAHgyJEjAa21qRFchMSZafaE8816fUcK5xWOhsiHYAg4ZaOe/cNGFH0dzuroEEEQBEEQIorNZmPFihUMGDCA2tpaRT0R4PLLL2fdunUcOHCA9u3b884777j0vemmm7jzzjuZNm0aH3zwQWMvXYgCIl7Ucvr06QBs3rwZgLVr12IymUhOTmbo0KEADB8+HIAVK1YAUFhYSHV1NbGxsQwbNoyhQ4diMpmYPXs2ycnJlJTUSUb26tULjUbD6NGjufDCCwFYsGABv//+O126dCE9PR2wV1EF+OSTTzh06BBlZWV8/vnniiNi586dDXwlIoPWn9WqdVJeCMrCtYHeDLWhFvW0gqEGaqKzKKg3rNb6GYYWS/gMy0CWYrNFh+MikOvmr43V6vN02LEG6ASwWm1ovXzRrFaotdjCXtzSarXfWH8RUIIgCIIgRJ64rv1CjkyIBkpLSykrK+PTTz/l008/9dqmffv2HsfT09MZMGAAn3/+OZWVlcTFxTX0coUoI+IOialTp7p8XrVqFatWrSIrK0txSLjjkOAcPXo069evZ/LkyRgMBq6++mqSkpKYN28eFosFnU7HueeeS0pKCkeOHFGcC7/88gtgL6DpwPEF2bhxIytXriQuLo4+ffowYsQI/v73v4ck+9kU8Gew6DMOhjSuof1W9OmHqN5+Gdby1OA6a6zEXboMgOrfe2I9kXn6eEhL8Us4Xy6XltdPOtNc67qY+ixtyaYTftv85/tiup4T+V/8Hywv5tKOviOmjpTWUFVj9Xq/fvq9HF0j1kSxBOgAeXn+Ibu8rArb/6hk+4JD9V6L+zV5ef4hWqYaePTmzHqP7cwveyu4qEPkql0LgiAIghB9WE+/FRo0aBC33HKLahvnlHp3MjMzsVqtlJeXi0PiLCTiDoldu3YBsHz5ckaNGkVOTo6HyoYjMsKBQ/azbdu2PPzwwy7nHA4OZ9nPSZMmMWfOHK666ipat27Npk2bmDt3Lg8++KDSr1u3bvTo0YM9e/bw4osv0rt3b/Lz83nppZcwGAwhyX42BRmYhjLgtIkn7D/ozcF31tRZehqDU3+JSj9jOXaqFlsAN7iy2rcXIFAnwdnA0dKasI+5vaBSHBKCIAiCILiQmpqq2F3+1BLVOHToEDqdTqk94UxFRUW91xcqZrOZ3NzciM1/thBxh0QoOGQ/HWkWzjicFY7aELm5uTz66KN89tlndOnSBYDrr7+exMRE3n77be644w46dOgA2FU7nnrqKcaNGweATqdj+PDh/Pzzz6pz+aN79+7KWqMNx5dLo9Gg10Ft/V7se6feUQ0N74WQ9Pvo5aIO8ZRXWtlzpM4hGK771SJJT0lZrfK5WYKOExUN9UU4Q5AMEEEQBEEQ3NDpdFxzzTUsW7aMESNG0K5dO5fzpaWlpKamKv86U1BQwNKlS+nZs6divznjcHREAqPRSI8ePbyer66ubhIvoKOdiDokzGYzU6dOZdGiRZw4cQKAbdu2+fWsOWQ/J06cyLhx40hJSWHAgAGMGTOG4uJiWrRooch+LliwgObNm/Puu++yYcMGTCYTWVlZ9OvXD5vNxi+//EKHDh0wm8189NFHFBYWYjAYaNGiBffccw+PPfYYV1555Rld9VWn1VAbxtoFTY2zd+dRhsqNaEj790y672fSXgRBEARBaHqMHj2aTZs2MXToUAYPHky7du04ceIE27ZtY+fOnXz99de8+eabHDp0iN69e5OWlsbBgwf57LPPABgzZkyEdyBEiog6JJ5//nmWLVvGsGHDMJlMfPzxx0yaNImePXvSs2dPr/2WLl0K2Cu6Pv/88xQWFpKTk8Pu3bs5cuSIEgkBcODAAYqLizl06BCPPPIICQkJ/PHHH4pyh8VifyM6ZswYVqxYwV133UXXrl3Jy8tj6tSpHDt2jOLiYvr27duAVyKy6HUaqmsCMWlCMXvqaSo5WaSBhPSHhFhz0YsGj4KPEtEiCIIgCIIQXaSnp5OTk8N7773Hd999R0lJCc2aNaNjx448/vjjAPTt25fPPvuM+fPnU15eTlJSEn379mXkyJGce+65Ed6BECki5pD49ddf+frrrxk3bhzDhw9n+fLlfPzxx7Ro0YJJkyYxb948pa2z7KfZbGbatGlkZGRQVlbG9ddfT2ZmJj179uTRRx8F4H/+538Au7Nh37592Gw2nn32WXr37q2M+eqrrwLQpUsX8vLyWL58OaNHj+aJJ54AYMiQITRr1oz//Oc/pKamMmjQoEa5LpFArzu747AbzNERBs4m4zvQrYbtkpxJ17aR9nJ2/6YQBEEQBMEXaWlpvPDCC17PDxgwgAEDBjTiioSmQMQcEkuXLsVgMHDixAmmT59Ofn4+YPeubdq0iRkzZvDYY48BrrKfu3fvpqysjJEjRzJ79mwX2U+ApKQkbrvtNgDWrFnDyZMniY2N5bHHHuOee+6hTZs25ObmsnjxYq688kq6d++uaN7u27ePf/7zn3Tu3JmamhpWr16NzWbjlltuITHRtwJAUya6HRJSQ+JsRuNmAtujJcJzw6LZERUsjbaTaP5VIQiCIAiCIDQ5IuaQ2LFjB+3bt2fGjBkux7dt2wbA3LlzFYeEM47ikhkZGXz44YdMnDhRkf00Go2kpqZiNBoBWL9+PYmJibzwwgu88sorzJ49G4D4+HiGDx+u5Co5xuzSpQtffvklX375JXq9nk6dOgFQW1vrvowzCr02QCtDjBEhArg/duJAEgRBEARBEIQzg4g5JIqLi8nMzOSrr75yOb5nzx4GDhzoUtjEWfYzOzsbjUbD5s2buf322xUnw969e7n55ps5duyY0vbAgQNYLBbGjx/PnXfeyWWXXcaWLVv44IMP+OOPP5RKru3btwegVatWfPnll0r/+fPnk5ubS1FRUUh7bCpVV/W6BhjUZjcjNZrgrMdWzQ0cOeHkAGoEJ4gYuNGB3IfoR3ySgiAIgiA0JiL7eeYTMYdEVVUVBoPB47hDJtMh3+lO8+bNufnmm1m4cCEdOnTguuuuo7CwkPHjx2MwGFz6mUwmKisruffee/nHP/4BwI033ohGo2H27Nns3LmTzp07079/f7KyspgwYQIxMTFKXYkpU6ag1+upqqpSXYs/moLsJwSTstFwFmNasp4nbm3JyYpapnx1sFHmbLwZ6kN0r66hcS9oqeFsvyLq2MSbIwiCIAjCGYjIfp75RMwhERsbS0VFBZMmTSIvL4+tW7diMpmYMGECgE9D/uWXX6aqqooJEyYo7Q0GA2lpaZw6dcplDoD9+/dzww03UFxcTExMDK1btwbsRnnnzp2JiYnh3Xff5cknn2TUqFFK/+TkZAwGg6om7plEwCkbjUEULUWIUsJke4sNLwiCIAiCIAiRJWIOifT0dAoKCti4cSPZ2dmcf/75bNmyhRMnTgD2GhHeSEpK4n//93/Jzc0lNjaWu+++G4PBwFtvvYXBYKCmpgaDwUB6ejpg914NGjSIli1bUlVVxddffw3Ya0zcf//9AHTs2JF+/fqRn5/PZZddxtVXX01BQQEff/wxBw8e9LqWMwFdFBW1dC9i2BhEs2EaxUsLO9726n68oa6JezSGIAiCIAiCIAgNizZSE3fu3JmjR4+yYsUKli1bxsMPPwygqG107tzZZ/+ZM2dSU1PDp59+yujRo7nvvvsAeyrIokWLAOjWrRsATz75JH/961/585//zLBhwxQ5mry8PGW8wsJCPvzwQwYPHkxOTg4PPvgg11xzDQC7d+9mx44dYdx9dNGwKhvRb1KfSWoLTRqV2yA+gsCQJ1gQBEEQBEFoikTMITFgwABqa2v57rvvXI6vXr2aiy++mMzMTAAOHz6sOCmcWbZsGddee63SbvLkyej1etq0acM333wDwLXXXovBYOCzzz5z6btw4UIArFarciwvLw+LxcLAgQMBu2Nj6tSpSsHLJUuWhGPbUUmDpmwEOXRE3lKLNdd00IQvosUj8kKeA79oJIxEEARBEARBCCMRS9no0aMHAwYMYNKkSRQXFysVVI8dO8aUKVOUdmPHjmXjxo3s2rVLOfb6669TUlJCVVUVH330Ed9//z1r1qzh5ZdfZtOmTaxduxaAzMxMRo4cyTvvvENVVRU9e/Zk8+bNfP/992g0Gvr166eM+d577wGwdu1adu7cyeeff87Ro0f597//zZAhQ9i+fXtjXJaI0LAREvXDWaWjoQzGqLZDo3px4UV1qyqPpkS0qCCXRBAEQRAEQWiCRMwhAfDaa6/x5ptvsmjRIkpLSwF45pln6NWrl89+aWlpAKxatYp169bRrVs3Zs2axVVXXcWBAwcoKSnBYrGg0+kYPXo0ycnJvPPOOyxfvhywv+W76aab+H//7/8pY1544YX89ttvzJkzh6SkJPr06cPbb7/NoUOHAEKW/mwKBCr7qdE0nCkYFxOxYB15Mx7FaFDxSYTrfsl9FwRBEARBEISIElGHRExMDGPHjmXs2LEsX76cUaNGKXUfHMydO9ej3wUXXADY0zRuvPFGjzHBnnKRkJCARqNh+PDhXH311Rw+fJiioiK+/fZbLBYLZrNZ6ffPf/6TrVu3smfPHsaOHUvv3r3Jz8/npZdewmAwhCT92VRkYNQiJLpnx/FraThGD8zqu6dfC6B+NQO0GrCKkRk89QyQ0WrBKfupHqjfvIYqankmPSpn0l4EQRAEQRAcOKLoI4HZbCY3Nzdi858tRNQhESoOp4OzQ8FBdXU1gIdUZ7t27WjXrh0At99+O//zP//Do48+yqeffqrkRU+bNo2nnnqKcePGAaDT6Rg+fDg///yz6lz+6N69u0/50kji/OVSqyHRtW0cv/4S+vjNk/ScsATWNs6oJTHudJiGBtAEbl6NHtSSaV8dBeCfQ9rw4kfBK6Kc9RES9dz/he3i+WWvyeN4386JrN9ZHvgyAlnH2X6vBEEQBEEQziISEhIiNrfRaKRHjx5ez1dXVzeZF9DRTEQdEkVFReTk5JCXl6coXuzYsYPLLrvMZz+HJOiOHTv44osv2Lx5MwaDgWuuuYbKykpatGiBTleXh2C1Wpk9ezYff/wxxcXFtGvXjp49e7Jq1Sr27dtHhw4dlHFvuOEGioqKOHr0KC1atCA2NpbDhw/7TSNpyjSE7Geo8p2evXxboGd6jb2mYH97uwXhuDdqY5z1DiRBEARBEIQmiMlkYs6cOWzdupVt27Zx6tQpXnzxRf70pz+pts/Ly2PatGls376dxMREbr75Zp5++mni4uIaeeVCQxJRh8S+ffuYNWsW2dnZZGVlsXfv3oD6ZWZm0qxZM3JycmjVqhVjxozBZDLx/vvvU1lZySWXXOLSfsqUKbz33nvcc889dO/ene+//54FCxYAUF5e9wZ3woQJzJkzhwEDBvDwww+Tn5/PzJkzsVgs9O3bN3wbjzICL2oZuCWoGJL1NUr99A+HP8J2tlu4DXyPwslZfqe8crY/woIgCIIgRD8nTpxg1qxZtGzZkk6dOrFp0yavbXft2sWjjz7Keeedx/PPP8/Ro0d5//33OXjwIDNnzmzEVQsNTUQdEt26dWPDhg2kpqYyefJkRenCnYKCAgDatm2rHEtLS2PPnj288cYbdO/eHQC9Xs/rr7+uSIEC7Ny5kw8++IBhw4YpRSzvuOMOevfujclkUmQ9CwsL+fDDDxk8eDATJkwA7JEV69evZ8+ePXTq1Cn8FyBKUEvZCJ+B438g51KZwb5VD8dbeLHl6keo0TDuqN+Hhns2xYgXBEEQBEFoPNLS0vj2229JT09n165dDBkyxGvbt99+m5SUFObOnaukbbRp04a///3vrF+//ox+WXy2EVGHRGJiItOnTwdg8+bNgF1202QykZyczNChQwEYPnw4ACtWrFD6lpSUYDAYePrppxk6dCgmk4nZs2djNBpdFDH++c9/UlNTg8Vi4dNPP+XYsWN89dVXmEz2nPf8/Hwuuugi8vLysFgslJSU8NFHH1FTU8PixYvZv38/ACtXrjxj0zYaQvYzdEeBe0exGs9mPJ4GeRwEQRAEQRCikqNHj/LOO++wbt06ysvLyc7O5sEHH2TAgAGAvSZDenq633HKy8v56aefeOCBB1xqSNx22228+uqrfPPNN+KQOIOIeFHLqVOnunxetWoVq1atIisrS3FIuFNYWEhpaSkPPfQQu3btYvLkyRgMBq6++mrMZjM///yz0jYhIQGdTseyZcv45JNPiIuLo2vXrgwdOpSXXnqJ7du3c9FFFylFK/fu3cvGjRvR6/X07NmTDz74gAceeIDt27c33EWIMGqyn6oOhSCcDEH5I5yMzKAjJIJrrj69GLkNQtD3JsD7EL7bdebceHmGBUEQBEGIJMXFxfzlL3/BYDAwZMgQUlJSWLlyJS+88AJms9lrnQg19uzZQ21tLV27dnU5bjQa6dKlCzt27Aj38oUIEnGHxK5duwAU2c+cnByPopbOkRGAEgHRtWtXnnvuOZdzr732GkuXLsVisaDT6TAajZxzzjl8++23Lu0qKyt56aWXlLEcqRt//vOfGTlypNJu9erVLnMGQ1OpuqoWIWGzQXaGkeB3bUfj5llo08LIwRIzKfE6Tpr8yW+oW1fnZ8VRUOymdnKGp2w0BUPTqxMpSO+S6lZVi1qG56K4j9K0C6Q2gQdFEARBEIQzlunTp6PVavn4449JSkoC4O677+aJJ57g7bff5tZbb0Wr1QY01rFjxwB7ioe77Gfz5s359ddfG0UOVGQ/G4eIOyRCwSHtaTQaPc45ZDarqqpISEigqqrKZzvHWN26daNHjx7MnDmTtLQ0evfuTX5+Pi+99BIGg4Gqqqqg19kUZT/Tkw0cP/3zA9ekM3lfXZ+Hbkwn1pbI24sLlWOXdkzAaNCydnuZy/jKiBob11+UTJ/zk7DabGg0GixWGxM/Pay0tan1UzlweZdELu2UwLyVxzhQZOaq7kl+6xc8d2drpiw6Qk2tfZbRg1qi18Kin0opOVXruQCBfl2T6Ns5EZ1Ww8TPDvvv4I0wOA4aM4GnKTh/BEEQBEE481h7cBOrCzZGehlc2bY3V7S5xH9DN2w2GytWrGDAgAHU1tZSWlqqnLv88stZt24dBw4cUF4A+8NhdxmNRg/Zz/j4eKqrqxtFDlRkPxuHJumQcBj5jjQLZxwOhtjYWOVfX+2cHQbTpk3jqaeeYty4cQDodDqGDx/Ozz//rDrGmYJzhIRer1E9DpAQqyPVYHA5ZtRr0PtxdibE6k6PZR/P4KtmRV2z09itxDijFo1Gg1GvIdZgnzAhRiXXxI34GK3LcElxWox6LcnxOo6ddkjYxCPhQoxBQ0Ks/2vrIGyBBYGmbITrdp1Bt72xtnLWK9IIgiAIguBBaWkpZWVlfPrpp3z66ade2wTqkHDYcd5sOMd54cwgog6JoqIicnJyyMvLIy8vD4AdO3Z4pGy4k5GRobT94osv2Lx5MwaDgWuuuYbKykpatGiBTmc3qNLT09m0aRP79u1j6tSpbNiwAZPJpIzh+BcgNTWV3r17c+jQIUpKSmjZsiUtW7bk8OHDZ2xBSwCds4PAhncLU8UYCcQ8CcaGCcS41Z2O6KhPiL1GU7cusbFcCVvqQkPkQMi9UkeuiyAIgiA0Wa5oc0lIkQnRgtVqBWDQoEHccsstqm3OO++8gMdLS0sD6lI3nCkuLnax34SmT0QdEvv27WPWrFlkZ2eTlZXF3r17A+qXmZlJs2bNyMnJoVWrVowZMwaTycT7779PZWUll1xS94Xu0qULn376KYMHD+a8887jkUceISEhgR9++IE//viDLl26KG3HjBnDihUruOuuu+jatSt5eXn83//9H8AZXclVTfZTjeBsnoZLyHd2oIRq82rQSGSEF4KW8fTSPNhbo3Y33O+vzUu7UJC7LwiCIAiCUH9SU1OVFAp/L5YD4dxzz0Wv17N9+3aXYphms5kdO3YwaNCges8hRA+BVRZpILp168aGDRtYtmwZ119/vdd2BQUFFBQUuBxLS0vDbDbzxhtvMGzYMB599FFGjhyJ2WwmMzNTaXf11Vcr7RcsWMCIESO4++67OXXqFK1bt1bygvLy8pTCmuPHj2fIkCG8+uqrtGnTBjjDHRLO0flhV7mwBRch4T6gxrOzY71hi5AIfZgzkwgonQSMzSY3TAW5JIIgCIIgRAqdTsc111zDsmXL2L9/v8d555oSgZCUlETv3r1ZsmSJS/HKRYsWYTKZFBlR4cwgohESiYmJTJ8+HYDNmzcDsHbtWkwmE8nJyYrs5/DhwwFXtY2SkhIMBgNPP/00Q4cOxWQyMXv2bIxGo4sixp49ewC7U+PFF1+kU6dOrFq1ik2bNjFlyhSl2qtj/vz8fD766CNqampYvHgxR44cAWDDhg20a9eu4S5GBNGrpmzUz8TRuAzpe6xgUyYcER1Wa2DGsGvRTHsPraRs1OG2/2gXmzjbb1ckcVfPEQRBEARBABg9ejSbNm1i6NChDB48mHbt2nHixAm2bdvGzp07+frrrwGYP38+5eXlSjrGqlWrFNvt4YcfVsYbNWoUI0aM4IEHHuDuu+/m6NGjfPDBB1x11VVcfvnljb9BocGIeFHLqVOnunxetWoVq1atIisrS3FIuFNYWEhpaSkPPfQQu3btYvLkyRgMBq6++mrMZjM///yz0nb9+vUkJiZy0003sXDhQmpra9FoNFx22WVcc801SjtH0ZSdO3fyww8/oNfr6dmzJ6+//jp/+9vf2L59ewPsPjpQlf1UaRdSioPGy2Bem/s3eBw1JCxWW/DW8+n2zhESYuG6Eimbc+Vvp/y2sQH5R4JXvFEdS+67IAiCIAhCWEhPTycnJ4f33nuP7777jpKSEpo1a0bHjh15/PHHlXZz585VXviC/YWz46Wzs0OiS5cuzJgxg7fffpsJEyaQmJjIn//8Z/72t7813qaERiHiDoldu3YBKOkSOTk5HrlHzpERgOJF69q1K88995zLuddee42lS5disVjQ6XQcOHAAi8XCkiVLuPfee7nsssvYsmULH3zwAU8//bQSoeGo+vrEE08wcOBAZbz58+e7zBkMTUUGxqWGRADG6N39mvPpmtPioAFYr0HZfQFEZzgkjEPxR9RNo1EUA4JZX+vmBg4frwlxVu9c2C6eX/ebwj5uINTXLm9IB4ba2HaHlHgTnBHniiAIgiAIkSYtLY0XXnjBZxtHpEQg9OzZk9mzZ7scs9lsLmkcDYnZbCY3N7dR5jqbibhDIhQckp1Go9HjnEPGs6qqioSEBEwmE5WVldx777384x//AODGG29Eo9Ewe/Zsdu7cSefOnenfvz9ZWVlMmDCBmJgYunTpQl5eHlOmTEGv1yt6uMHQvXt3F1nRaML5y6UWIeGLbm3j+ZTjAbevn8qGr86B6kR6jq/R1B12ljJsnxnDvsJqr0ONHJDJsi0nWLej3OeUg3o346uNJwJbHzDoslRVh4TzDlMTdZSWWwIeM1DqL+XYuCEVTSFrIDFWS3mVNdLLCDsi+ykIgiAIQmPiKJYZCYxGo1JvUI3q6uom8wI6momoQ8JsNjN16lQWLVrEiRMnANi2bZvf6qwOI//VV1/l6aefJiUlhQEDBjBmzBjFWREbG8u0adPYsGEDYI90cEQ7OJObm0vnzp0xGo3cdNNNzJ07l1GjRgGg1Wp57rnnmDVrFvHx8eHadtShLvupJvEZijHiv6ilz9MqxqfjkM1WD5UNjT3CwmMtYbO3gluY19ZNwP7zqhLbAHOFs6al+zhNwdEhCIIgCIIgCGcSEXVIPP/88yxbtoxhw4ZhMpn4+OOPmTRpEj179qRnz55e+/3444+A3THx/PPPU1hYSE5ODrt37yY9PZ0WLVqg0+m44YYb2LhxIxs3buTZZ58lPT0dgClTplBeXk5ZWRmnTtnz1idMmMCcOXMYMGAAHTp0YM+ePXz//ffs2LGD0tJSsrOzG/6CRAi9itZKOI3JYBwZARmFLo1CSxnxprIRLinQYI3bSBrD7jsO2inj1SNR/2upOrTofnrg8gxLFIMgCIIgCILQRIiYQ+LXX3/l66+/Zty4cQwfPpzly5fz8ccf06JFCyZNmsS8efNU+5nNZv7zn/+g1+vp1q0b999/P2DPMXr00UdJT0+nS5cuAHTu3JlbbrmFjRs30q1bN/r27cuRI0c4evQo1113HcuXL6d58+YUFhby4YcfMnjwYCZMmKDM9eGHHzJ+/HjgzJb9dKmcHybDWClOGUi6v8eral8nXU+HavhrNHU1JKLBMI3oy/ko2H8wNJTBHdZho8jBJAiCIAiCIAjRisq78cZh6dKlGAwG7r77bpfj/fv3Jzc316WIZEFBAQUFBQDs3r2bsrIyLrroIn744QcKCwsBuOaaa4iNjaW4uNhFm/baa6/FYDDw2WefAbB48WJsNhsWiwWNRkOfPn3Iy8vDYrG4FLMEuO666wBo1qwZV1xxRfgvQlSjkrIRkqUTrpgDtZFDb+nsJ3F9u1yvJbmMH44OzlcvEAWSUIjmChIe0RsqxwTcw3wEQRAEQRAEoUkQsQiJHTt20L59e+bMmQNAfn4+AEePHsVmszF9+nRefPFFAIYPHw7Y1TYc8pw33ngje/bsYdiwYQwdOhSTyUR1dTVGo5HbbrtNmSczM5ORI0fyzjvvUFNTwy+//EJcXBw//PAD9913H9nZ2fz2228AzJw5kx9//JHzzjuPsrIyxYnRrl07dDpdY1yWqCFSUd924zbwYpUhq2w4p2w4TRcpWy6gfTSU5d9Amw7HsFb3upBhXGvDucoaP0DCeS/ijxAEQRAEQRCaChFzSBQXF5OZmcnUqVNdjq9evRqAb775RnFIOJOdnY1GoyE/P58PP/yQiRMnMnnyZLRaLTabDb1e76G+MXr0aJKTk/nPf/5DYWEhiYmJPPXUUzzyyCNAneRnTEwMq1evZsGCBcTFxXHuueeyb98+TKbIyDFGAp2z/IQHnidSE3WUmXwrPyTHezpztE5FJV1GdbPkYo0a3PUsHGkXNpX2CbFaKtzUDdScK84OCdfGKscaAU0Ei0hEs+yn+z2yqRwLffAwjaNKBO+neCQEQRAEISqx2WzYbLaI/t0nBIbU5Go8IuaQqKqqwmAwsGvXLpfjf/zxB9dffz2jR49Wjq1YsUL5uXnz5tx8880sXLiQDh068OKLL1JYWMj48ePJz89XVDac0Wg0DB8+nOPHj/Puu+8yb948OnfurJzv1q0bPXr0YMuWLfz973+nd+/e5Ofn89JLL2EwGEKS/ASalAzMQzekc6jEzJF4HUcCkPZ95OYMik/WckF2HCt/O+W13aUdE+h6TpzH8YdvyuDI8Rq+2ljqctz91/P5bWLJ3et9He7t/3JtOjsPVbIiT31Njvba0/8hcPyHwcGZ8Kvn8i6JfmVJmwpWlf8YNAl/hCAIgiAIggrV1dXExsZGehlNhoqKAAyTBqCqqgqz2Uxubm5E5j+biJhDIjY2lpqaGo/jDoeCQ9pTjZdffpmqqiomTJigFKH805/+RNu2bVm/fr1qH5vNxuLFi+nUqZOLM8LBtGnTeOqppxg3bhwAOp2O4cOH8/PPPytpIsHSvXt3n/uIJO5frnPSYzgnPYZFR+2f/YWzt0o10irV6LMNQItkvaoXuHVzIynxOr7aaJ/NgXtbo96HB1lliRnNDOh0Gq8OCedam+ApI6nmDTXqNZhrI2++BuJL1+s0pCcbgho3mh3A0RTFEs1EQ9qRIAiCIAi+sVgsHD58mLS0NOLj49HpdBIt4YeEhIRGnc9ms1FZWcnx48dp3749ycnJXttWV1c3qRfQ0UrEHBLp6ekcPnyYSZMmkZeXx9atWzGZTIwdOxaAjIwMr32TkpK4//77iYmJ4bfffuPw4cPk5uaSkZHhIc/566+/8sUXX7By5UoOHz5MUlISY8aM4amnnnJpm5mZyZw5c/i///s/li9fzsmTJ/n+++8pLi4+CwtaquPNSaH2i9RRgLEhjF3FmYB6ukAgv9dd0j6ciGbjPBCPhIZQUijqt+mG/O+o1T1lw9aQlR/CR0RlXKP6IRYEQRCEsxuz2czRo0eVdHNxSPjGPRW/MTAYDGRmZvp0RgjhI2IOic6dO/PTTz8xa9YssrOzOf/889myZYtS3FItisGZxYsXs2LFCrp27YrFYsFqtbJ161alAKaDf//732zevJlmzZoBcPfdd/Pll19y++2389lnn3HuuecqbceMGcOKFSu466676Nq1K6tXr2b//v0hR0icLfg2gLyfU5wCPrqrnvLze9vXacc557n9vV0O5b8TYUsrcBoo0MKXwa43ms1XtZSNhlqx/D0gCIIgCEJjYLVasXpU7hbU6NGjR6SXIDQwEZP9HDBgABaLhSeffJJly5bx8MMPA/ailhdffDGZmZkAHD58WHFSODNmzBhyc3OZP38+Xbt25eTJk2i1Wu655x6XdsOHD2fZsmUUFxdzySWXMHbsWObNm0dtbS2zZs1S2uXl5bF8+XJGjRrF+PHjueeee7BYLMTGxrJu3TqKi4sb8GpEE0HpXPjF9ziBWIDqkp1gd4SoSWEGEyFhtdlcHSIqC9Y2IUtVQwjyoPW82d5mC8eLerUxwhUA0JCBBI2vsuH0czR7mARBEARBEATBiYhFSPTo0YMBAwYwffp0KioqlIIlx44dY8qUKUq7sWPHsnHjRpfilzNmzCA/P58ePXqg0+nYsmULJpOJl19+mXPOOcdlnosvvpgffviBEydOMGjQIMAu49mxY0cXR4ejFoXNZmPOnDksXryYHTt28Oyzz/Lqq6/y/fffc++99zbY9Yg+Ai8mGGqoWVjsfLWUDZ9zalz+VVNxCGrAaOSMipBw/WwjutcbDcj1EQRBEARBEJoKEXNIALz22mu8+eabLFq0iNJSu9rCM888Q69evXz2O//88/n+++/5/vvvAXtuUYsWLTyiIxx89dVXGAwGBgwYANidDseOHXNJC0lPTwdg1qxZGI1Gevbsybx585RCKtu3b6/fZqMcm83G1rLdWGx2Cc/yWhN7Kg4E1K9Ytx80KWDTgaEKbcJJNNZaewPHv0Gg0TiZVBbX/gcrj2LSmFGCe2w2dGkHsRxrDUCttZblpT+iTWmO9aT9nrobaAcrCzFhBjRs2l1B/tEqtM2KsFYkY7N5FoTUagBDNfrM/RRVxwGeMqaqaGsxZO+g9tC52Mzxbiet6NIOg00LNg3Li//A2LEIc34PsNbvaxmIP0KbdBxdaiE1BZ3r/0Zdo0HbrBBrRTOoCW8RV6vVRrWxBH2bg9QePpfjZbWELcIx7iQaiw2bKSVMA0aO1VvLqK6x0fWcOE45yfDWWmys/O0UZZUWBl7aDKNei9Vq4+tNJ8jOiCE5Tke7zBj2FVZRWFpDl3PiSEmwP38HiqqJNfoOoqsyW9l9uIoL2sWz/Y9K1u8o484rmtMsQc/vhyrJbGZQxhMEQRAEQRAEdyL6l2JMTAxjx45l7NixSrpEt27dXNrMnTvXo9+1117Ltddeq3x+/PHH2blzp9d53njjDZfPX375JYWFhYwZM0Y5NmjQIJYtW8aECRMYOHCgcnz+/PkAFBUVBbc5mpbs556KApYUrVI+rz6uJnHjabnuMx1ir3EjhnPaUlPQlZjOP6ONq4BKDehBayqFFupzejOc9dQZVPoqV1nQeYcWQxzAAGzAtvLdGDtspcZgBtqy+ngue6r2EXP+Pio3DlAdf96hr8BgH+O7X04CENd7M9bqWDhwg+o6YzpvRBtXwQd/7KMnd3lZuSuG9lvRtziKPv2Qx1r0LQ9gaFsX9ZN7EnSpYGi3nZq9F6qOF2gqSiDtYrpsBMByMg1o47+DD2xYiOm0Baspkeqt/eo1lufYUJyxGgOgiani0zXh+5Wl67IOHSj3JqypDo0cVbO/qJr9RdW8eF8bZn1b97tq1dZTrNleBoBBp+HW3qls2lNB7un/A7x4XxvmfH8MgJVbT/H8XVkAfLDcnqaWnuL9mn+x4Ti7DlbRMtXAJ6tLAHhz0VFevK8NH/1YQkKslmcHtw7/hgVBEARBOCsQ2c0zn7Pu1VV+fj4vv/wyvXr14rbbblOO9+/fn6ysLCZMmEBMTAxdunQhLy+PKVOmoNfrqaqqCnqupiT7WWWt9ttHzWCrttoLfqY0s3CsADQxptONrYAmJCtP4+z48FMvU1m33r6OCkulartA0MZUuRTojDFoqK6xf1b2FQQao49nRq9eKFVj8H4fArVxg0mF0eiCj2Bxx6F7oYlRufb1H1xBYwj+OxhNNFYpkhonidryqrpwkrJKu6Ovstp7iEmV2XvNFjVOVtjHrLGof8kqqqRglyAIgiAIoeMvcj6SiOxneIioQ6KoqIicnBzy8vLIy8sDYMeOHVx22WUB9c/Pz+fVV19l/fr1WK1WJdqiefPmSpuDBw9y3XXXefTNzc1lzZo1XHXVVYA9WmPmzJkMHz6cUaNGKe369evH9u3biY93D7kX7Pi29n2KNHqxdGxOJ/yJPLqfD7qg4+lRPH9qaEJYZwAWrSbIkW02jdQcOE04HQZqQzWGP8Kn4s3pBWiCLWXs48J4U8pRV0cRBEEQBEEQBFci6pDYt2+fIvuZlZXF3r17A+579OhR7r//fpKTkzn33HM5evQoP/zwA7///juffPIJBoNrLYCbb76ZvLw8Tpw4wahRo0hPT/eQFv3ss88oKSmhX79+dOzYkYqKCj7//HNqa2vJzs4Oy57PNGwePwSOopYR2AxBnAkdNTuqQd5s27x5Y3wYfwEMq9Fogi4y6lu2NZA569XdJ2eSWdsYe3Gfw/neaNz+DZRAZHQ9isOeSTdOEARBEARBaDAi6pDo1q0bGzZsIDU1lcmTJ/Pee+8F3HfmzJlUV1czd+5cXnrpJSoqKnjllVcYMWIEixYt4q67XPP8t27dSmlpKf/5z3+46KKLPMYrLCzkww8/ZPDgwYriBoBWq2X+/PlkZWWFvM8zBd/RCupmS2jGbjB9HG29m02hjAbORlWoFnco/Vz7OK8nIMM/wBoS3uYLJ2KUuhEJj4QKDSNj6zqxSKsLgiAIgiAIgRBs8G5YSUxMJDU11W+7goICCgoKXI4tW7aMa6+9lszMTOXY5ZdfTrt27fjmm2+UY9bTfxkfOnSI1157ja5du6rOkZeXh8VicSloWVVVxZYtWwA4cuRI4BtrgoSW6gD+LSDv5zUBhEj4LCFhczKnTzesb8qG2oT2dYYwbgQM8qBXWc81ajRNTxU1UkSJPyLoiBZf7ZWUDbfjkrIhCIIgCIIgBELEi1pOnz4dgM2bNwOwdu1aTCYTycnJDB06FIDhw4cDsGLFCsAezVBSUsLJkyeZPn06+/fvp6ysjOnTpxMbG8uvv/6qjD9jxgzAHso+evRoNBoN55xzDrfccgsXXHAB119/PQBms73I4CeffMKhQ4coKyvj888/VxwRvlQ8zma8xSfYAkzIUMO1qoGf/uF42+s0hNpsDWJwe03Z8P450K0GGyFRf9nPevb3QX3TSSKF2j1ojK0EMkd4a2WoeySsTfO2CYIgCIIgCI1MxB0SU6dOdfm8atUqVq1aRVZWluKQcMchwbl69WpWr16tOpbFYkGn05Gfn698BruBU1BQwMyZM0lLS1McEu3btwdg48aNrFy5kri4OPr06cOIESP4+9//HpLs55mGWsqGw2DUar2lbHgfz2HM+BbS8FNh4vQEep19LDVjKz5GG3C1/3ijluNO/cy1FuJjtDhrXxj1/gOLvFyOOrzWinA9Hmusm8ug829Jxsdog/YPuN+7YGzJhBgtRr36jEZD04qd0AdwfQMlKU5HabnF5VgkbHTnHTlqi4Q1Y8NbhIR4JARBEARBEIQAiLhDYteuXQAsX76cUaNGkZOT46Gy4YiMcFBdbTcPp02bxo033uhyburUqUyfPp2qqioSEhL45JNPPOYsLCxk4MCBnHPOOcqxbt260aNHD/bs2cOLL75I7969yc/P56WXXsJgMIQk+3k2ycC0bm7kgotSWKd1N06CV9m4pkcyqwLo7nzqovYJXgd96MYM3vryqPeBnPjL9enM+b6Ybm3j6HJOHHuOVHF+VhzvOGUMXdE1id8PVXL4eI3Xcc5vE8cas5aKgGZ14rSj4u5+zTHoNGS1MPL65/Yonc5t4igoVpcLBbikYwJXdk1SLWo57No0clYcA+CiDvHsOn08MVZHyxQD+wvV5Uad+6nx0I0ZxMRY2XDA89yV3ZJZtbXMa1+Abm3jsNlg+x91kqFGvQZzrW+D9spuSaze5ntsd1ITdSTF6SgoNqs6Uc5tGcsF7bSsyDvlc5yEWC2d28SRu6fu7v7lujS+WF/KKZPdCTHw0lS+yT3hcl0DifYw6jW0bxmDqcrKH8e832tveEyhWtQy2KKn3s95K2op/ghBEARBEMJBbm5upJcgNDARd0iEQkxMDFCXZuGMw1kRGxvrtX9mZiYDBw7kk08+obKykri4OMDu4HjqqacYN24cADqdjuHDh/Pzzz+rzuWP7t27K2uNNsL95dZpNfTrmsT6PYG/CfZmFnVpE8eqQ/affY5lsykRFHExWq9jNk/095jXzWLQaXj4xgzl8yXnJXoYkgadhqu6JzN/VYnXEeOMWpol6qjw6sfybhRmZxjp1rZOZva8VjHsOVKNRgPXX5TM8l9cDebURPvb+EvOSyAlQU+NxfOqtU2vew5v79Ocf+2x/xxr0AF2Q7jXeQms31nu0u+cdO/Pb/fsOFIT9VRb1b8bBp0GvU5Drcp6AAb1bkav8xIBePnjg1htMKh3Kr3OS2DHH5UsWF3i9f57i8rwxmO3ZJLZzMDS3BMUFJu5+oJkHLFVN/RM4bstJ9Fo4Kpuyfy6z8SxU7VK33NbxVByqpYTFRZu7d2MS06v2eGQuLRjAu0zY+nQMoZf9poAyGxmYPh16fzw60l+3FoWcOrJny5LpXu2/d4vXHec3/abgtqnpwyuJ/WJkPCl4uGMREgIgiAIghAOevXqFekleKW6uvqsegHdUETUIVFUVEROTg55eXnk5eUBsGPHDo8ICXcyMuwG45w5c3j33XfZs2cPrVq1YsWKFRQXF9OiRQt0Op3S3mw2M3XqVBYtWsSpU6fo3Lkz5513HlarlVOnTikOidTUVHr37s2hQ4coKSmhZcuWtGzZksOHD0f1l6GxUDMxHAaQ+1tXm9v50GcKTPZTo/JTuAhWRtOBb2dKCOvA99ttxzr9povUcx3B4HspTndNY19LQ0qIhgOf11/tmKYuLSkQn0RQ9y5YTo8d7DV2dqZ46yoREoIgCIIgCEIoRNQhsW/fPmbNmkV2djZZWVns3bs3oH6ZmZkYjUa2bt1Kjx49XJQ2fv31V7p06eLS/vnnn2fZsmUMGzaM7OxsvvjiCz7//HO0Wi0pKSlKuzFjxrBixQruuusuunbtSl5eHv/3f/8HQN++fcOw47MQH1ZYQxifIQ0ZUCfXRoGs3fdbca+mnfceGg0ajX9LT82o9bdeb+cDujQhGp/Oc3pdn5exG9LeDURVImhsAToknG9eCFUwG8Lp4fMpVmpIuMl+ikNCEARBEARBCICIyn5269aNDRs2sGzZMqW4pBpqsp8333wzMTExTJ06VZHyXL9+Pfv372fAgAFKu9WrV/P111/zzDPP8Nxzz3HPPfcwfvx4ABISEpTUjry8PKWOxfjx4xkyZAivvvoqbdq0AcQhAahaO17tDi/F7gIZ1jU+wk9RS/cJQyIUJZAGQlMfCdbTQwRlNWsaOkgiIBx7Vuoc+Hl+grXV63NFXQtDBjeJs9ZMQ0hyuuMrpcJxzYKN+AlFHURSNgRBEARBEIRAiGiERGJiYkiyn2CPZvjxxx8ZNmwYRqORsrIynnzySTp37sxtt92mtPvXv/6FRqPh+PHjfPLJJxQUFDB//nx0Oh3l5eUUFRWRkZGhzJ+fn89HH31ETU0NixcvVmQ/N2zYQLt27Rr6kjRB1A0P5aivCAmvQwZmzNibuefMN07Mf0AREr7STbyqbKiNUzen2ryB7Nn7tcanpVzfffpamqqhH+BlaUgJzSB9DoEPFlD0Qpg9Es6nTl+0sMp+OlJSJGVDEARBEARBCIGIF7UMRfYToFWrVnz44YdMnDiRdevWYbPZGDRoEOPGjcNoNLq0jY2N5ZNPPqGsrIzk5GSuuOIK+vXrx9///nd27NhBRkaGUrRy586d/PDDD+j1enr27Mnrr7/O3/72N7Zv3x7+zTcx7HnwNo6ZS0mPaa4cA19GcZ1lYrVZOV5zkjRjKlablWM1J5RztdZajlTb1RzincYqwGQfQ2OlxFzX3h1l/kaqQRCIEyC0+hl43YM3h0R9xjxRYSH3aEXI41psFv6oCkzBxNeaLFab+yE74TJsgwoa8VWnI7Rpf9lrIm+ff80VbT1j1jwLmtYtuLzSyr7CKr+XYufBStKT6/7T4Fzg0x3nCBBnNu8JWl9GEARBEARBOAuJuEMiFNlPBx07dmT27Nk8/vjj7Ny5k9dff121Xa9evZg9e7bLsT177DIDRUVFALRv3x6AJ554goEDByrt5s+f79IuGJpS1dXADC0bv5zawbLiddzb+hay41t7fVWtdnTt8S2sK93Cg+fcybay3fx04lc0MVfSvVU6XxX+wO8Vdu3IDrGtlT4nNDVoU47RrF0J/y7Y7zqHzXOeQNUMXAigLoNHl3o7Pnw4cLwsx19Ry0Bmu6BdvMvxWgtYvahgOPfzxuaTO1hxbEO91gRgsbr+683QdRDsfQ4uicXzSEWV1W+/9pmxbMl3VcVwPCdfbSwNaO5g6zuck2Z0kQf9Za+rI8B5uIMlZuZ8f4xLOibgC1/qMV6vutuJn34vV28nCIIgCIIQBCL7eeYTcYdEQ1NVVYXBYPA47pDjdMiE9u/fn6ysLCZMmEBMTAxdunQhLy+PKVOmoNfrqaryqt/olTNR9vPo6SiG0ppTZNPaJZ3AGUVlw8lwPFxld+qUWyooqLSnwgy7MYW2Cam8sfcPpd0f1a7Onz9dnsS6EzvBorIgN8O00SLF61HU8qnbWvL2hgOBz1UXhhK0I+TJP7UkIVaLRqPhuTtbE2Nwv1H+ql16Hrr2wmRW/HoKmw1O1pzybFAvHIUOgu95Y88Ulm05GbaVtM+MYV9hNXqdXfpz58Eql8fNIRfq4MJ28Xy+7rjLGMHWa/CVsnFhu3g6to5l4ek5ruyWROc2ccz6tu77UlVTt8DEWPVwixPl3iMegsVfrQ9BEARBEIT6EM1KhyL7GR4iWtSyMYiNjaWmpsbjuMMR4XAYxMTE8O6775KSksKoUaO49tprGTt2LKNGjSIlJYX4+HiPMQRn1GU/1bDZ7KH+APFGPTqtBivOb6Bde+t0Vrfzni01HkcalkDMTG8riY/R+o508Kp4oQnaIZGSoMOo1yrz6gJ5Be/nEhr0LtUfgluQc0+VroHePTVfj+u6QsexrpQEu3SwTqshxmC/hs7T6gO4lmpNErw4CkA9ZSPOaD+YHK9z2WN6ssGjvXMxSRuo3p5wfkOUSBbxSAiCIAiCIAghENEIiaKiInJycsjLyyMvLw+AHTt2eKRsqLFmzRqWLFnCb7/9xu+//45Op1Ntl5KSwrZt23jggQfYunUrJpOJnJwcrFa7gZuRkaG0bdmyJb1796akpITy8nLatm1LYmIipaWlZGdnh2HHTRv1LH8vuf8aDfYqCk46GI4CeNiw2OzXX6fxvG/uto3FZlHae23nNHbwNEzKhs+1eDvlR3IyrAUXA6C+Ywbd3y1Awpuhq3Y43EZx7elUFr3OyREU5BzB1oTwV9RS4/WDHav/zJKG8UhIjIQgCIIgCIIQAhGNkNi3bx+zZs2isLCQrKysoPouXryYxYsXk5CQ4DMtIj09ndLSUo4cOcL555+vHHc4QDp37gxAbW0tI0aM4NNPP+X222/nhRdeIDs7m3HjxmG1Ws8C2c/QTE9vsps2lZ+csZyOeNAG8AjW2ixYVRwSzkPX601tQOEOro3qX9TSR+FEH8eDrSFRb4eCXwO5HhESKn3rY9b6kpoMJrLE0dRRz0Kvq1tpsOsLVjVD1YHhNITzcBo876/FOULCpn7/w+uPUFfZEARBEARBEIRAiKhDolu3bmzYsIFly5Zx/fXXe21XUFBAQUGBy7ExY8aQm5vL/PnzSUpK8tr33nvvBWDo0KE8/PDDgN358Pnnn3PxxReTmZkJwLJly/jtt9945ZVXeP7557nvvvt44403SE5ORqfTcemll9Z3u1FOIBaFmkakr7gJV0PF2axzpGyoGe3utRdqbRYfKRuRsYQCsjN9Bkj4VyVxPxKKyob/GgYRtCQDLKSqelTlcNikJk+vyxEhodNqnOQtg5tEzcHgawhnB4ZnOpJ/B4clgPWF03ngWI7IfAqCIAiCIAihENGUjcTERKZPnw7A5s2bAVi7di0mk4nk5GRF9nP48OGAq9pGaWkpCxcuBMBkMmG1WpWxLr30UsWB0KdPHwYMGMCkSZPo378/AK+++iqHDx9mwoQJyniO+X/99Veqq6spKyvj888/p7q6GovFwqZNm7jyyisb6lI0CVTD5IPoVeeOsKlHPHihNpCUDceb2qaeshHCvMo8jSZ52nDjOIxlf8US1Y5bw2Rp10VIOFI26qIlgp0i6AgJfzVGvURLOHBO2Qjm2gWKVzeaOCQEQRAEQRCEEIi4ysbUqVNdPq9atYpVq1aRlZWlOCTU2L59u0dfx+cnnnjCJaLhtdde48033+Szzz4DwGKx8N5777lUbTWbzWi1WtauXctnn31GXFwcffr0YdiwYfzv//4v27dvP2MdEtvK9rCnosB/Q8Bhkqwr3cKG0l84WVt++qh6ysY6SuhtNROjNbqcczgY5h9awuPthqj2BdDaoMB02NO4N1RhI471pb8AsLtiP1c078nWst0B7iN0fjz2M+1sF/htd7xGXfEhZOlOe1mOsI13urPr+MF2D8KADnJk36dVLGBf9RNCWYbikNBqMJ++8MGnbISvvVqEjHsETN6+OtnRymorG3Z5ym/uL6wOblFOuO/fMfuC1d6lQgVBEARBEATBGxF3SOzatQuA5cuXM2rUKHJycjyKWjpHRjgYPHgwgwcPBuDxxx9n586dqu3ArqAxduxYevXqxahRo3jppZc85mjfvj1Wq5V//etfXHTRRcrxyZMnA/YCnMHSVGRgFheuDKyhrS6yoay2wvWcF9lPgOLq47SJa1lnONtQUjDKLSYqre6Sqvbe7SvN/BEbwx9VRz2W0qzzdtplXcTW0yqLhdUlHlEXQ65qEdi+gjQaN5zIo3lSW5djRr2G2/qk8uma4x7tE60tqDz9c5s0I3odYFPPlrKWpfpYpgY0dVdWq4UubeIoPOGpIhMKfTsncbS0hp7nuirKdGgZw96j1Wg10DErlvhY50Kkzh6Nuus/8NJmHuMb9RoG9GrGlz+V2ps7ddVq7GH/Hn4GLx4A9xSBmy5OoUf7eFb86kWGNAjPiKPppR0T0esq6H1+Ij/+Zh/XJQUpgCG1QXok1FJsLumYwMFjZi7rlEjxqbp73SkrltJyNS3chiOrhdHlc7BFOwVBEARBEIIhNzc30ksQGpiIOySihVtvvZV33nmH559/nn/+85+0bduWtWvX8tFHHwFQVeVuNPune/fuPgtuRpJgvtxdKqrZkRDjEtngjtpbep3NhsXJwHJW2Qgkm6HPyUoOxqpfv5bN9STGuj6+LpKMGh3nt4nzPonXnt7wViUD7rqiOd2z7Ub8p3g6JNomN2PUfW3cunsxVG1ar4au/bj9ZFKcjqfvaAXA24s9HTaBU7ePpDgdw65N92jhfmzrAZPS01314e5+zenW1lMi95ZLmtG7UyKA4pBwptd5Cfy8u87J5a+IpMVq49xWMeQfqeb+q1vQsXWg9/r0+G7FId3OAnaZ1AeuSXdpH3zKhv82f+7XnE9OO7LU7n28Uavcg2OnagFomWo4LefauA4Jd9nYgGRkBUEQBEEQQsQ5oj3aqK6ubjIvoKOZM17286effmLYsGEuxxyflyxZwrnnngvY1TjeeustRo8ezYgRIwC7AT1o0CC+/PJL4uM9jayzBicjzFGMMpAumtMWq3u6RbgKUeo0rq9nXSRGG7igQkMW0wxE2jNSxTx9E9ya1OohBFoPwxJgCRKNRl1twpdjQW3qOjWJIItaBvIYujjtfC/I3TESaXeAOCQEQRAEQRCE+hBRh4RD9jM7O5usrCz27t0bcN/FixezZMkSunbtSkxMDLW1tT7b/+UvfwFgzpw5PPLII5x77rmKwoaDefPmYTKZuOGGGzjnnHMoLi7myy+/BKBdu3bBbe4Mwtnk8OaQ8DBLNM5SnOpKHMHO7Xpcg07j6oQK1lisDzZN4EU5g16VzwiJ02NGoz+iXvipYulGrcU5ysb7k6WU3Qjm4VNp66/IpjcCSdnQePlZta37OiLsD/DiBxYEQRAEQRCEgIioQ8Ih+5mamsrkyZN57733Au47ZswYxo8fj8Fg4IorrqC01DMM3JnevXsDdofEFVdc4RGFkZeXx/Llyxk9ejRPPPGEcry4uJgNGzbQqVOnIHZ2ZmLD5jVlw90ysgHa00H97jobHmUC3A443pL7jBTQaCIaIRGcRyDIyAEvU4VeILLhcL7O9Vmfe4qGv6EsVvenysu4XgqBBrIW1QiOMKRs+BxCzRmidjBSHim3aSVCQhAEQRAEQagPES1JlpiYSGqq9yJ+DgoKCigocFWByMzMxGAwBDWfrzoQDtnPgQMHKseOHz/Onj17AMjPzw9qrjMJZ5dCbbApG6ilF4RLntHdCRLauBpNAP3cmlidIiT8GeLqo3ufU62wIdhtVaUOh6raRgg0kj2ptiX3+hNqeLO7LdYAK39ofA7vpZP3ccIi++kzXcT3St0jJMJx++oTWSQOCUEQBEEQBKE+RLyo5fTp04E6h8DatWsxmUwkJycrsp/Dhw8HXNU2nFU1TCYTVqtVGevSSy91kf0EeOqpp6ipsVeof+aZZ7jhhhvo0KGDMofZbAbsERTdunWjuLiYBQsWYD2tJbh9+/aw770p4j1lw9M5oHX62bmNzQZmWwDKECq5/3Xzqbf33SB8WG0WAvfn1S2sxlqLXuMrzj0wR0X43o837Jt21ZIIp+s6uNROcKwmQEvbYgls3Zq6pA2PNTiwup13ntpms1Fjq/Wo3WG2uj6/tTaLqjMhEBUKq5NDwK+Mqv/hgqY+T0B911NpthJnPHulOqprrOh1GnHsCIIgCIJw1hJxh8TUqVNdPq9atYpVq1aRlZWlOAvU2L59u0dfx+cnnnhCcUg4oigczgiwF9OcN28eGRkZyhzt27cH4Ntvv+Wzzz4jJSWF/v37065dOyZPnhyS7Ge0s/nkdr4rXue3neNP5aPVxzhSXeyzrcO4K9eCw2D/5PBSOiZks7viAACHqgpdx7d6j7rQWC2g8zRY9poOstd00OWYzSmdxH3MuBgtlvbr+deepT7XHyg2azXgGaGjMVYSe9GP/GtP3bGd5fu49bTB+ta+udTaLBjOVR83Vmv2aZRq6izjurUAMReu4v1iEy1PpfGXc2536fOvPf8GoHNiB25rea3fvQVDKKkxgRRk9Ddq8yQ9RSf9O7Wcr+XG0l/JS9kIuuu8Rjr8a8+/oT3EtQcYyurjuawv/QWSAAaQFKdTridaMHbMYGtqEVtPB1AZ2mZTU9BFGU8tQsI9ksfi9Kj6ryHhPUImZIIYK5zT/rK3gv9uKOXWS5txScdEj/MvfmT/fj9/V2tiz0Cnxdwfisk/Uk3r5gZGDrDXM1r8cymbdlfworsqTxNj9rIi/jhmbvL7EARBEASh4Ym4Q2LXrl0ALF++nFGjRpGTk+NR38E5MsLB4MGDGTx4MACPP/64S8SEMxdffLEyh4OdO3dy5513KnUlAPr3709WVhZms5k333yTLl26kJeXx0svvYRerw9J9jPaZWB+PbXLfyPqjKSCyiMhz+VwRgCU1px0PWmp9jlvoDg7JHBzSIy6JZN3DnmrMxK8maWtMQGeRpQmrky1fa3Vgk6j9ZvykqSp8h4VolIoVFlPrF2K82j1Ma9j7yzfy22E0SHhofsZOt6KRqrdmVt7N+Oi9gl89OPpvQbgwNFoYMupnfaf9eYAZrHj/B25/+o0zmsVw1Kn7C1dqqujUt/yAKN6XuMxvy9qnephOO8lkNohgYx/Y88Ulm056fV8fZwM9elbVmn/LpSW+y5IXFFlOSMdEvlH7L/3Dh+vc6xtcpK+bcr8ccz9OyYIgiAIoZGbmxvpJQgNTMQdEpGgc+fO9O3blw0bNijHYmJiePfdd3nqqacYNWoUAEajkWeffZaZM2eGJPvZvXt3YmJiwrbucBLMlzuwEguRl33wtYbEOB9pEgEZ1RqfH/2e0ARovGlsPtNUQlV7aCj8XrpgjWk/HokYg4ZLznN1BAUcaeElrMDXc+N8rmPrWB8z1dEsIbhfq94KdDqW6xzNH+z912rh8i5JrNlehqlavSBtfaItbDaINWioqgl+EJvbv4IgCIIgCO706tUr0kvwSnV1ddS/gG4KRNQhUVRURE5ODnl5eeTl5QGwY8cOjwgJNdasWcOSJUv47bff+P3339EFqD83a9YsJk2aRLNmzaiocH0blZ2dzXXXXcepU6c4fvw4mZmZ1NTUcPz4cbKzs4Pf4FlEMA6JYAyQYF7AO0dINLSR46roEXyfUNBovBRXrFcRgMYxBwOVs/T2OdBxPMdVqyHhVu/Ei3KMzeYZiRJsAchAnC61TvUwXKRdlWOetTYCvedqiiH1Q8VjFGIEh+NSWgNX0BUEQRAEQRDOMCLqkNi3bx+zZs0iOzubrKws9u7dG3DfxYsXs2TJErp27UpMTAy1tb7DfsEu4Tljxgzi4+Mxm80eCh9jxoxhxYoV3HXXXXTt2pW8vDxee+01APr27Rvc5poAgeb/B9KqPpX66zt33RpCtWwCWbubYRq0lGfgO/GmshHsOA2F6/JCX09gARJuBSedC3sGcAucVTZsKsf94T6FleCesUCmcYmQcFqYo9ilqvxogOM7xvPpGAhgjV772rwXDvXfOcD5o1HvVhAEQRAEQQgLEU3M7datGxs2bGDZsmVcf/31XtupyX6OGTOG3Nxc5s+fT1JSkte+x48fV36ePHky3bt3Jzs7G5PJRL9+/ZRzeXl5Sh2L8ePHM2TIEF588UVatGiBRqOhU6dO9dhp0yYQc8CKLWCnREM5Lxo1bSQEGynQ9XmvIaEJWX7S+1yeRm84Cd6B4tvxo7rOgN/Q143lfP00XpwMNjwdENZwREi4UeulqKVaykaw1DlkvA8SzPdRVW7W1/X3NVYI8wuCIAiCIAhnFhGNkEhMTAxZ9rO0tJSFCxcCvmU/n3rqKeLi4mjVqhWLFi3i5ptvZuPGjeh0OkaPHq2M55j/jz/+YMGCBZSVlfH5559TUVGBzWZj5cqV3HvvvQ14NZo2NrtLIsTe6maLxusZL2sI1bAJZBK3Ni57Dbc17zFX3TR1b8jVCyEGixYbFkIzeu01LQPsqNJMTaW1ToHDyzMR5Do1Hj+g8krey3Nj8zwVbIREIDfHEkRRS41HiITv8cOfsuGK369cAPOKP8ITm83mM1JKEARBEAThTCHiRS0bWvbz+uuv58svv2T16tXYbDZ+/vlnWrRoQUpKCq1bt1b6ms32quC5ubl88803xMXF0adPH5599lkeffRRtm/fHpb9Rgu1NotPRQZnNIqR6B2rzRawQ8KzXXgsEpuTsWjWath8cjuphmTax3uTnrOb1NqkkqDnyjPvQ9ccLMdbBb6+ACwvZ+GK/Io/KKouoTpWDzRzLWrpNFRt4uGA1+COt+iAgLH4l94MbCHqT5fN5masG00cMB2muTGFk81/gWNe9FMBXcYBbFojHLXfo5O15fZhjNUutTP26X5F26wZu+M3uc6NWoREkCkbfhwx4FZDwrmdkrLhWUPC8R0KtDZHILUcgqXWYuPX/SYMel8pRr7mtU9sFYeEB2EUsAk7a7afIj3ZwPlt4iK9FEEQBEEQzgAi7pBoaNnPYcOGkZSUxMsvv8y3335LRkYGDzzwAKdOnXJp1759e8CeCjJw4EDl+Pz58wF7Ac5gieaqq6tLNvlvpHDa+Kku99qimSE58AiFWleZT2+9rEGmptvcLJvvitcBMPa8h332M7YPxNnkOnaJ9RTG8/Ko3NiK8sq6mPtOrWM5ENhy/c7z2ZFv7T9kAgcGnJb9tJspjktdVF2Cuc3mgEevtpiJ0RmVz7rThvn1F6WEtFr9KT9SsBqXf1xw9zWA0+5VrTEb1s4rme/wvySB8bxyoLVnU20txnY77O6Eo61cbl9M158ottRNcES3j5hO4CG4qFLUsr4pGy2S9JRXuUq/dmsbz/qd5R7t66JFvI8XaIBCIKkTvriiSyJrd7h+/7/PO4m51oa5NjSPgqOXv2sarYZ5gxKlHonjZbUs/8X+384X7/Pm6BUEQRCE8CGyn2c+EXdINDTl5eVMnjyZkSNHkpGR4bVd//79ycrKYsKECcTExNClSxfy8vKYMmUKer2eqqqqoOeOZtnPr77+IeC2yt/FPsrhx2qNWAONkLBa/DcCqs7piaZqT0Btoa4eQmKthXJ9AKorGhvYAvur32CwUWuDDiYze+ONLuecDarenZI44MVG9xZBkmau5Zix7qvo7W22XudU0PH0v2ar/2KuLmt1e+OvwcbAS5txacdELz18o7HUgo9LrZYKcn6bWHYd9PJ98hGNo1FRBNHEmNTtNo3rPj2iEjCrz+/Wx/2eBV/M1E58jJbn7rQ7TiZ8esilTZs0o1N7z3usVan043jk/DkB3YtaJsfrOGVy+/45DTHw0mZ8/fMJ5fONPVO4vEsStRabh0OirNL/99hn1oGobHglWoNGaizRujJBEAThTEVkP898znjZzxkzZmAwGLj00ksZOXIkW7Zsoby8HIPBwOeff65EWcTExPDGG28wcuRIRo0aBdj/mP/Tn/7EmjVriI+PD9Oumy6qCopOhJqyEa6idkqIe+A9Am5Za7MbXwaVtTobkd4MMF8JLe5vwDWoXxOdVqMcrztdv2unwdagL2LVHBIe0RB4qkc4sIUqS6p1f8a8rcIXNhcnm81mCzplQ20anzOr1pDw/nz5S3eoS9nwrrahVssjENRqHGg07tfaRzHN0/9KyoYnUldDEARBEISzhYiqbDhkPwsLC8nKygqq7+LFi1m8eDEJCQleoxCKioqYM2cOffr04S9/+Qvl5eX85S9/oXXr1sTGxrJr1y5OnjwJQG1tLa+88gomk4nbb7+dESNGcOWVV7Jo0SKOHz9OdnZ2vffbVPHMYPfEFoTKRsCRFAG1cm5vNxa1gXYMwRLXq+wx8Lfm6u1cHBLYQKNRHVOnBW19JBdU0GKtV8FDf0UttcrgapawyvXwVV5E1Tnhrfil69t7j6kCiIxx72PFGvCzq6zDMZbaQR/tnefXqJxXjHk/1ryz7KmfqQNq4M954f4s+a4hYf/X3x4EQRAEQRCEM5eIRkg4ZD9TU1OZPHky7733XsB9x4wZw/jx4zEYDFxxxRWUlpZ6tCkpKaGmpobPP/8csOcgOech/ec//8FgMPDMM8+wbNkyfvvtN/71r39x++23K22GDBnC5s2blSKZZyOB2quhF7X0MXcwNSQCLPTn3CNYDCpdAg059+avcd6jr4gFnVYT9tfJWk3wyeourf2pPAQpwqHm7gkJrVvKhtvF14bghbGGECGhGkWA91AjlxoSp9s4+6DcVTaCfZOutm/na1Nfd1co/f0+0lFYS6GhEReNIAiCIAhnCxGX/QyEgoICANq2bascy8zM9NuvTZs23HPPPSxcuJCJEycSFxdHVVUVM2bMoLKykhdeeIF27doBdtlPjUbDzTffrPSvqqpSill6SwlpqgQlKee70qBTs0AjJLwMH+Bxr/OfNhYDDvsJIR3AoGI9BW4UeouQsLn8rNGot9TrNA0Qym2rZ4SEbxwRHWrSlb6iBlRTOFTvlzcvj+8aEoFYue59rKf/FwzKLAHmRahGSKiESASa7uB+b33VowgIZ+eZWjpKCL9W/EZWnY3WeZTu+Sz0DQmCIAiC0MBEvKjl9OnTAbtDAGDt2rWYTCaSk5MV2c/hw4cDrmobzqoaJpMJq9WqjHXppZdy6aWXkpSURGlpKeeeey4ajYbx48dz9OhRdDodKSkpXHPNNYqjwSH7+frrr9OxY0fKysr4/PPPKS4uVubr379/A1+N6MZXlLuNwBUIPA0Q7/2C+QNYqSHRgAnYajUkrC5vmL0WkfC6S62qkadeQ8IScD5KYGg19ash4a93oBkmSoSEz3vnP6qgbmL3CAn3+QJYmFsfmy3wtCSniQI5VHfO6aRVcUh4T5ryW9TSx/iB9AhENtSzv1PdDR8tFdlPPz6ecNWYaUrYolVmQxAEQRAEIcxE3CExdepUl8+rVq1i1apVZGVlKQ4JNbZv3+7R1/H5iSeeUFIsDhw4wNGjR3n++ed5+OGH6dq1Ky+99BLHjh1j4sSJ/L//9/8Au+ynzWZj+fLlfPLJJ8TFxdGnTx969erFJ598EpLs55mCwxGRbznhtY226hS2xMAMh0Kra7X+6YcXqc8b0Gh1VFgqgSD+jA8hQiLe4mk9BZJF8ea+HK/nnF9a+4uQqLG47q6+ppq/GhLltSbe2f+RymKuAeL8jn/sVC3GTrl8Zyvmu9OCKa0M/TF22sZi8zEW74GR2X/GqLdfBYNew87yvawq3wL0xmioG8ugqcVD18HL2jVuDgn3PRZo/Uu9/rdqnsvnjSd+Y33pL377ucx7+t+AoocMVUzbN49Kq12BJNl4JZDglrJxejwVZ4WvFZSUeVdjmfxFnSxMMBEOqhESgXdXsDg5HFZvO8Xh4zXcc2UL5di0xYUu7S/tmMDAS1NDmCl0luaeYMOucu69qgWd23h/7tftKONAUTVD+qfVaz7HJflkTQktUw1c1S3Z5Xx5lYVJn9vv2wPXpnFuy1ivY326poRMlTEAth4wsWZ7GY8MyAgsas6pyZFSM61S7Qoxh4+bmb+qhMduyeS3/Sb/4wiCIAiCIJwm4g6JXbt2AbB8+XJGjRpFTk6Oh8qGc2SEg8GDBysKGY8//rhLxIQzJpOJkydP8vTTTzNy5EgAbrzxRp588kk+/vhjHnvsMZo3b86tt97KO++8Q2xsLDNnzqRt27asXbuW1157DSAk2c9oloEJ6A3xaQIJUteX7MfW4sLQF6RCsMb27qrDQOApG3/u1xyjJpaFFf7bXlhWza9JMfQ7WcnyFq6pRvV9gevuYtCoDHrLJc2Ij9FSXRNYysAjAzI4dsrTCHU3jP3ZIDvL96oe1zUrxmZLCUg1Vdes2OXziaSd6GKOKZ9/PbmLK86/hFqrjT7nJzFl36dYsXFdz2S6Zhv4t/22kqKv4rjKjpy5rkcy3+edAm2d6+Kmi1NokaQHJ59ipabM/8LdCNYZAcGlNeiaH1WcEQCm1F1w+GLXdBflJ/u+Wzev89j07ZxIrFHLD7+e8jpXTa1ahI+vHbgSvCKH98HrpEvrjn2fd0q9sRM/765odIfEhl12J+qiDaV0vsu7Q2LZlpNhnXd7QSXbCyo9nAm7D9U9J0eOm306JLYVVLJNZQyAheuOY7PZnwFdcP4IVm8r48/97I6jVVtPccpkYX9hNUs2nfA/kCAIgiAEiHP9P+HMJOIOiYYmNtb+h9qtt97qcnzQoEEsXbqU3377jf79+5Oens6MGTN47rnnGDFiBGCvcfGPf/yDsWPHhiT72b17d68KIJHm6yU/BtzWFsCbMxvBFasMlKDeuDreGge4jOwMIwn6WNjjv60OG6k1FvQq1lt9VQJci1ra33q7j9i7k90J4lkDQH3uVs2NtGpu9Dju6TypXw2J0PDIn0Cv09C/u6vB1LdzIrXWOqeKRuu9GKSDjq1j7UatUw2Jvp2T6r3iUAnHpfVVf8P5rfZNFzcDcHFIuONPpSWo9QaS9eLjdp2FmRg+cU5NCebaREqkRO1RklsqCIIghJtevXpFegleqa6ujuoX0E2FiDokioqKyMnJIS8vj7y8PAB27NjhESGhxpo1a1iyZAm//fYbv//+u9eik3Fx9rdZ9913H8ePHycpKYnOnTtz4403AiiynwA9evTg1ltv5YsvvqC0tJTmzZuzb98+AKX45dlIoH9kNoRDIhjqpA1d12Gz2VTDkYORcHRkdKtFX1hdHArBm6Bal3X4XlMo6hCuuEVIoH5tAltNYM6q4LE7Hmw2m8sz5e35Urvm7ikbEaNe1+d0TRS1MQJ8dIOuIRFMykaYahyIY8KO8++RoOqMhuFRD+UeBFUYWRAEQRAEwQsRdUjs27ePWbNmkZ2dTVZWFnv3qoeHq7F48WKWLFlC165diYmJobZWPUc6Lc2ey3vTTTdx3nnnUVZWxldffcWLL74IQPPmzZW2Y8aMYcWKFdx111107dqVvLw8Zs6cCUCfPn1C3GXTJ9C/dwMtahkoNk1wb2wdjohA6z6Gslq19dR33y4iChpO15BQH9P9rWTQSiR+5g+sR8PiXHfBn6tG4y0cxilCwptDqjHQ1G0maBxdVGtIBLyA4Ob029yPykYwNEU/REM6XYP6NeJ07euzIkfMkf13WHA3VDXYRrxLgiAIgiAEScAKiQ1Bt27d2LBhA8uWLeP666/32q6goECR/nQwZswYcnNzmT9/PklJ3kOyR40aBdhTN+6++24efPBB5s2bh06nQ6vVctFFFwGQl5en1LEYP348Q4YM4bnnniMhIQGNRkNysmf+7dmCNcC/UyMdIeH4g9pDicDbukJQTWiIv8E1bm9GT8cHqLb1F3LvDxuue/ZMDnFr73dv9Tf0PUZwpCXY7IlAylqCWUKUREio+SO8XTFvzhX1GhLBzV9fGsKdo9SQaICxmyIuzrcgfqnUyyHqViQ1qK4qqUSCIAiCIAjBEtEIicTExJBlP0tLS1m4cCHgXfYT7HUcbr/9dt59911KSkro2rUrP/74IzU1NWRlZZGYmOgy/9GjR/n0008pLi5mwYIFGI1GKioq+P7777n33nsb+IpEJ4EIQ9rQhN0hEfxopyMkAhzH5vEO3vfI3uRE65vD7a6y4etyO/wRdW/e6x+dYfG5AT8Oi5Bmde+lUf3k7jwJai6nopY2bGFLLwgWVTst6KgFT49EqLc9nFchkLECenqakEeiIZ+jYGpIOK8iDP6IsEWLNaFbKQiCIAhClBDxopYNLfsJMH78eFq0aMHixYv54osvSEhIAOD2229X2pjNZgBWr17Nf//7X1JSUujfvz+33XYbw4YNY/t2/zKBZyqBKCkAHK4q9t8oSIL58//30yobgUZIVFmrSSTB47jNZqOk5gRpxkAq+duUopY2m43jNSeCWLEd9ygFu8qG8+e6HTlqSIQaKKFWfFRFydSlvb/xgibAtVsDSNlwPlprraXMYlfP0KWU+OnXONTHH+HYvXMh06AjJIJ1fvhp73It65uyofgjxIyF0B0L4ciSCHQMCYQQBEEQBCHcRNwh0dCynwBGo5GDBw9SWGjXszeZTNx77708+uijSpv27dsD8NxzzzFw4EDl+Pz58wF7Ac5gOVOqrgYS/H5Sa+WnolWNPq/LGiwmQCWSwaYeCZF7Yjs3ZlzhcXzzye0sP7ae+7NupU1cS/sQPt6Ntk23K6nkndrFsuJ1Qa4aOleY2R1/Wo1FY6NteoyPlA37vxe0C0z1xSP022ajsLrOWNdobCTG+src8m6ptM+MpdZe8EKhRZLrr5TEWC0WQsPmVq2vmVXDKZ2nQkdKvL2g7ddFq9hZvhdtUm8XqdGIGryqD03dwVijdwsv3qilAog1eN6fUHfUIlnPsVO1pJ3+N2DU5Eudfs7OMHKgyKysq0WynpJTtaprF9Rx/qoGc3/DUbsn0CGkRIQgCILQ2Ijs55lPxB0SjcWoUaO45557OHr0KIsWLcJsNlNTU4PRaJdG7N+/P1lZWUyYMIGYmBi6dOlCXl4eU6ZMQa/XU1VV5WcGT6JZ9nPJksCdB7V6g+rxPidM9DlVyZttW1AVqNZmkDiMnjZVNQw/coJKrZbJ2S189jG42+CoG6UajcbFYNee/vlItd2YPVFTpjgknHlh3zH+e353tpuPMnpQJi2SjC79/BGvi8VksT9Pjx08TnZVLReWV/Ov7BZkZ8RwQbt4qizVTuuvW6NOq+HZwa2INYZm6NmwUWOtUT5fdn4CnbJifbRX58aLU+jdIoF1bnVoW6a6So0+eVsr3tjne03urh7HZ/f7lmbRUOB2c+NiNKQm2n+N7TMdBOCmvgZWnnDag817GkzPU1VsSfa+//qi7EWlGOTw69Jp3UL9uwV2o/7eQS1pnqTya9rH123c3a1Zt6OMH7eWeaiyZDYzcOulqWwrMLE096RHXw0axt7VmuW/nCR3T4X3SXB9W/7ANemYa2288d8jANxwUQobdpVTVundHaVESIiRC7ipbARxTcITISE3QRAEQYhORPbzzOeseX11/vnnc8UVV3DnnXcye/Zstm3bxrhx45TzMTExvPvuu6SkpDBq1CiuvfZaxo4dy6hRo0hJSSE+PrA30mciFq263yrZYqV5jd3gUBddrR/OfyPHWa0kWmw0q/X/vl3v9se1DRtWt7ftybUWnK06na3O9PX3x3myxUq6zl57pFmi87UJ7I/6RF1dmkgLs30/SafzJnSKioJ9rBit0WNNCbE6dNo6o90Xao4Y5yNxMdqQCtLFGu39/M1v0IUe4+2esmEFdBrXJ01t9ARj4H7WtJogogRCwNelTYrXYdT7/hXsHnGicXs+1IgxaDGejkzwmN8GSXE67/E+GogzatFrXQvEqqee1B3V6zT/n703j7OiutOHn7pr7yt0NzR0N7Iom4gogktciSZqFHRETTIDIXGSYDI6WTW/mYmOb3QSGTUkphVXRnGJQjQEF1CxkR2UBmnWpqHZer+93L77rXr/qFv7qapTd+lusB4/0reqzl5Vp873Od8FOV6pLw4GyPU6DB9QTvX3q45kSQGjbGZlis8TrYaEXjl02W3YsGHDhg0bNjQYVA2JtrY2LF++HPX19aivrwcA7Nu3T2OyQcJnn32GNWvWYM+ePTh48CCcTrJI/Otf/xqrVq0iXjtw4ACOHTuG6upqAEB1dTWuvfZa9Pb2oqurC+Xl5YhGo+jq6hLTfBUR05ddRDhoHU1YAcOJK2ArChhEQoKQjuNkdvocEHcoNSbkgro6BKnc8aK8PBrId621ZSoLcaS41FcLrmqtAz1HnWL6wdw5VdXNMoCTcSDOyR1WShAEZAejFPKNhPdMM7JGPiS0ZAXNWNPF/dSvgy5fqoml8LUUsBkJAOooG8Zp5ffVmJAwq9Uopg+pQFVWy/XZsGHDhg0bNmwoMaiERFNTE5YtW4bq6mpUVlbiyJEj5pkSWL16NdasWYNJkybB6/UiFiPvdM6fPx+zZ89WnOM4Dr/5zW8Qi8XEKBsAH0r0448/xu23345Jkyahvr4ev//97wFAU8aZDiuCitEestEOajqQTPku9aKYA1gVJSEQHMJS3MlxiIqUAGdap6SKz8lkRLrVOI2nfqEkgRRJNlKEdijU/jSSkyBS8c6vzqXXKxbK+C4cABfjRARR2TkZuSL+VZZodF8yZGkkq8DCJYrby9DxESLUJhupQhky1ggUz7j4Dp594DjOsuaR0ocE/agY+ZCgjQCUqoaErSJhw4YNGzZs2EgWg0pITJ48GVu2bEFxcTGWLFmCZ599lpiuubkZAFBVVSWeu//++/Hf//3fcLvduOyyy+Dz+Yh5q6urMX36dMW5DRs2IBaLIT8/H6WlvD+C+vp6rFu3Dj/5yU9w7733AgDmzp2Luro6dHV1YcKECSn390xFXE9DIkknbLQglUkjQLpVq3BeQ4KcURCwhJ1ylijiao9SWX8bCYmc6pcj0TI9AcVMcCE5tbTiPE+/3hSg7j6jHmeB7GHByLQdOGhNNkgFawTBQZR4TXxaGiIVZ5zCEOgNhaVoGiCMqUlORnmok/LMYyRo7wnLSeZX1GUnyRMakQlmDi9FYtFWbbBhw4YNGzZsDBIGlZDIy8vD008/DQD4/PPPAQAbN25EIBBAQUGBGPZzwYIFAJTRNnw+H95++20AfNQMlmXFsi6++GIx7Od9990Hr9eL6dOnY/jw4Th9+jRefPFF8ZoAof7jx4/jjTfeQF9fH1auXIn+/n5wHIf169fjzjvvzNBIDG3EKVbHmbDYkMOahoSWkFBHbBDPyzQkhHMkaUDvTDJCo3wHX0lySHULXZA0JJIDyWRDUVrSduuZ9wCgNi/hADihb46hJzMbakik0kAKkNqUinaJJEDSpbcaHlbTXhOzDP2LFGN75vER1EjmtZKTAlayG6VlzUIVJW4SvSYFOaGtIGHDhg0bNmzYSBaDHmXjqaeeUhzX1dWhrq4OlZWVIiFBQkNDgyavcHzvvfeKhMS3vvUtvPPOO/i///s/9Pb2Ii8vD9FoFBMmTFCUH4lEAPChZd577z1kZ2dj1qxZ+MUvfoEf/vCHaGhoSEt/z0ToaUgAWtOHdIIDEE1IVDFG6WTPCG7Vovnl43/DbSO+rjjHAHCE/WKrHUI/OA5geR8F2vCh0s+s418Aw/KxzbcbrZFOcByHxsBxitYBrkCPrvMCTjWejmgYYJSmIadD7djs2wUAOBY4pSnj6aOv4dphs3Bu3hgCIcEB8YjyWIYTwRa8enI15gy/FBcWTtK9q4IJjPr6590N2NW7DzU5lQCAo4GTOiVI2Nj1Oabmj0ehOx9xjkWE400yOiI+DPeWyOoEnOongGB4z7IxVRIO/bEgsW5zt5zWsbN7Lw74mxBgQ6j2jgJQqTI+ERumOHCPPqi43Bw8rVX9N3kBvujZh6bACeRx5wJwIBAmS6QWFR4sl0HysSJgb3MADplD1JOdEcRZTnTUCgB//HuLYbN2HenH37b4MHF0NrxuBn3BOO762jC4LKolsCyHP/2jFV19MVw1tQBXTS0Qrx04GURPfxwf1ffI+kVXvj8UR1Eu/ef1r5914roLCsXjdbt6cPtlxtGEBKRispGa6ZUW4aiypFCE1Y0ItO94EMc7wphzQWFSjnVt2LBhw4YNG2cHBp2QOHDgAABg3bp1WLx4MZYvX65xainXjBAwb948zJs3DwDw4x//GPv37yemu/3223H77beLx5988gl++MMf4q677lKkGzNmDADeFOTGG28Uz7/++usAeAecVjG0w8DQLwBvauvFqxX5xiVEQ5aepgv6QtiVbx5usTchYBzO8Zik5FEejsGjWoX3xPz4pHObeDytL4RjWW44/e3ijp9gCMCChaOvDXAC7u6TQME4APpOLTf6vqBqlxyuUC9A6A9JF8IZCwNup0KwW37iHcPy+2L9+FvLR/jVuO8TJQ0mQDZvAoBXT64GAKxt34QLCydp2iNAHbVEwNqOTQCA9oh+HUW5TgQjynOrWtZhwei5OOBvUpy7p+qfxGOOAYqD/eh0A9lxFkGnQzEujmgQcDrg6GrW1Plh+0bd9qQb6zo2i787I91gcvKBSJF4juQH4spZUWwjDGmQDSHHmS0ee10MJo7OxswJudrEkPXT1QzgenT38+RaXpYD/pDZdrl1J5hqJILF8IKwTmF//awLADBtjBS5aG9zEOfXSMddfcbRT/62hX++9h2XiKa9zQFMG0MeFz00toTFutbv6VUQEq992qlJTzs+a3Z04+4rh1G3Y29zENfKCIkvjwVx+2V0eVMx2aApQ5FO9ruiSDuHbdjbqzj+ZHcvvnFREbGsNzbw43v11EK4B30lYsOGDRs2hip27tw52E2wkWF85ZYBq1evhtvtxje+8Q3F+SuvvBKVlZV49NFH4fV6MXHiRNTX1+OJJ56Ay+VCKBSyXNeUKVPg9XrT1fS04r33NlCle+xwG9q85mQALxjSSzN3tvaaEhJWd+2KonHcf7wLHxVrQ7TKVY2v9vXjpRFFCpMAh8zDnmTeYaDqn8KWolPWFr0REx1rpmjbTdKQUNqqm/ig0DlPK+iQ4CTYEQgEhzoeitKsnoGL4zAiHMXoUAzbCrMVaYV7IkThOK8/jP25XnDgEOUyG97TFKThko1hdbkH206TkigzMgyD+VdQ7JyrHtCLJ+Thk92SsCjcgaJcp0hakMtRtUf/EgBg/MgsHDwZQpzWBkAoNw0+DFI1k6AB6dlNX1us5zHLR000JEFcOAiKD3EV50UzT/BpbA0JGzZs2LBBxowZMwa7CboIh8NDfAP6zMBZH/YTAHbt2oUnnngC9fX1CAaDGDZsGPr6+lBcXCym8Xq9+N///V/cc889WLx4MQB+8f+tb30Ln332GXJytELumQxr4f3MgyMOlB14sstWp6oPggGIPOwnoIzGwSjsKtK3YHbKBktRKif+I8IhXkrS14OakFDVYVqqjkAhlJsuUx09VXiFDwlGSwSRXJCyIpmTSMMNtu07TVQVcvviOpoo5gXqO2SVQ+1g1cp4kNTsBYE9zhKNVBQ4E/0oOinjxFr13QFYI0fk78tAakhYzUNjimGRu7Jhw4YNGzZsnGWgXF5lBkLYz9bWVlRWVlrKu3r1aqxevRq5ubmGWgi7d+/Gd77zHbS0tOCaa64BALAsi7vvvhsdHR1iulgshkceeQSBQAC33norFi5ciCuuuALvvPMOurq6UF1dnVwnzwboEBKMzDI+E2vKZMskLYEdsj6IbZbZsTtEZ5LqsJhSW9IVZcOp0zMGUp+Fv5JQnSwhoT1jJeynvoZEkoKyTqmi804j4YphNAlIyQUnrA4ZaZIJHyfU4NSaBfSOSmOcgfaCuhqF5g35nRWTCFE40vwFcCXKi8WF90k/LWlMhjqclD4qkjF9SZagMfQhYfKaiuZD1JoUxuWon2qaYWBtRsKGDRs2bNj4SmNQCQkh7OeHH36I6667zlLe+++/Hzt37sTrr7+O/HytfwMBf/zjH5Gbm4s333wTvb29yMnJwRtvvIH+/n4888wzYroPP/wQe/bswSOPPIL/+Z//wa9//WssW7YMF154ITiOE51knj1IrwBgvh+aTJnpg0JDgksI/4xDXGE7RcFfpiGhkSpk/gpSaIvDkA+QbesjDRoSBAmCM7lOA0ELIamdVcI5Kg2JxP+MsgOyMpRtk98j3fEbEFmIMTw0akjcAiEhJy8YTvWE6jRB0xTGhGKUa/cQ+iEI7GrVfXJZeqpCAwdNWFSTB5rWZMMotK8e1HJ5MmYUVq4p0tEls1w2zTDYfIQNGzZs2LDx1cagEhJ5eXkKswk9NDc3o7lZ6aiuvLwcbrfbNO/nn3+Oyy+/HPF4HJs3b8acOXNQVVWFmTNn4r333lOkYxhG4VsiFAqJziyNTELORFhaLjvIfZeXkZkdaMJOukFqXSELgANaDQm+BqXwynKsVKuROnsK3dXzIcEQyk09CoRao4BTnDNVqzd1aplZaUIu9AheJpT3TwuhbfIIMHq7yENlX15vFK1oSMjJCz0NCchSAFqBURv1UzpDI1wqTDZM0qf7yUmuPGUjzYRjapONJL6sagLCUOCXNTs9JhuZM+0wQyr+aGzYsGHDhg0bZz4G3anl008/DYAnBABg48aNCAQCKCgoEMNyLliwAIAy2oY8qkYgEADLsmJZF198sajREIlE4PV6sWbNGsRiMdx8880AgKysLLS3t6OtrQ1lZWVi2M8//OEPGD9+PPr6+rBy5Uq0t7eL9V155ZWZHIohC111ai79YeNUxRPakhwcOrrposkGJ+z4S4SEwk5b047ke+wwyKr2zeDglOetQp2LU5WVfLnJm2yQzD30Vfa1GhLKqzJyJfFTMNmQP5uDa7JBILaYuEK402ufQEiwHIsYF4fHoU/CKsgLzvhNEciCZMMtshxHdFwpEhKCyYbsGsdxiMmaGI1LV2Px9N+faIwTiQGng0EkxvL95fj+k0KEhqMscrz65LOehkQoysLrkpM3adCQoM4npYzGOLicdCZQgOwdoR5+47kjmbuoZ1YSjXFwOvnrLicDluPE3zZs2LBhw4aNsweDTkg89dRTiuO6ujrU1dWhsrJSJCRIaGho0OQVju+9916RkBgzZgx27dqFw4cPo7S0FJdeeikikQh2794NACIhMWbMGHAch3Xr1uHNN99EdnY2Zs2ahRkzZuDNN99MKuzn2QKOYnH9ZXYGFolpjE0vJyS8LAeG48Axkm+BWKKu7T1firuFDMMgGA/hj02vALkejAhHpaal0BY9HxIkSAIDn8eq7wat0KCKsiG7TtqN19eQ4HC4vxlb0WWpPQBwOtyuOceAwXttG7C794Bu/UddMdSwSpMNDhz+5/Bz/IGbv8fr2RYAEpnzl6OvWW5juuGe8R7+53DiYCKQDeCFduCK+AxcWjJdV5KLc3Gpfwn8dMx3kO3URqiRa0jEnSEw2X3ggrw5W2GOE9kz38dOADsT7XBVjoUjMElRhvDKFeXyn4bPnG9j/WHhub8BdXv7ULe3T7efxfkMsme+j08BlHtnoKd/OJ7/sA2Lvl6Gtbt6sGmfX0x74IQUuejdrT68u9WnWy4N3tniwztbfDi/Jge7jwbE8zleB+bOLsGr6zsMcvP4/duncdnEPGyUtVOOEx0RPPzaCfznXaPw2FsnEYpwuGxSPjY29OFrkyXTwRyPNN/sOx4UQ1wCwJVT8vHpl9oxfPZ95TdG/p7+dsUJ8fe3LilWjBXHAUtXt6Czl48kc+nEPHT3x9HQHMSPvlkupluy6jSyvQ78OHFu20E/QlG+kmc/aMN/3TUKvYE4/vdvpzF3djGmjcnFhr29+Kiej84ytSYHe2Tjuv9ECO/v7CGOk4AtB/zYckAayx99sxzlRUpSjUSGHD4Vwiuy+3XdBQU43h7BgZPSM/Mv1w5DdZkXD792EpdPysd1srCpcvx2xQlcPD4XN14saWN+1tCLdbt68Zs7KuFOEEkPvXYCY8q9+Odrhov5Lhybi29dYqzF+eaGTjQcD+K3d4/SXFu3qwefNfThisn5uHYauX02bNiwYcPGVx2DTkgcOMALIOvWrcPixYuxfPlyTZQNuWaEgHnz5mHevHkAgB//+McKjQk57r77bvz2t7/Fbbfdht/97ndobGzEX/7yF1HzQQjnedNNN+HPf/4zsrKyUFtbi6qqKmzcuBG///3vFems4KwJA6Pr1NIYDzR14NExw5Ku1qp/A9Fkg5BN2IG/sDeIQrmBe6KO3oQ3vl19BzFGZvzhj0kLcHm5KRES8vY5HEA8jkj5BDDokjm1VPuQ4GE16gJJDVyhISG7HGe1hIQeAcKCxQF/k6W2GIFhoCEjSAgygLmhVqJMCuJnIPZa584uxnv95Gvbu7/EpSXTTTUk5OiN+RWExH23VCAUYcFCOUc58rswZyIvJJ1fk4P3G5XluEY0wdmkIiQSf2edm4dhBS6sCkokHEcRnvH8sV7UHU20M/sogOE43sFrn23ZTxby0w05GQEAgTCLFl+EOv9mk3YKmgyhCP9j20E+/clOqY7hRdKndc8xZXv0yA419J7ejQ1KMiPOciIZAQDbD/UjGhM0vqRS+oJx9AWl52nHIakdQrL2Xv5+7zoSwLQxuQoCaY9qXI+2hukbLcujJiRIJhst3VHF8aZ9fgTCyrlo3/EQqobzDq037uvTJSQAfkzkhIRwj0NRFm4XrxHDccCRFmWfPm/sNyUkGo4Hda99lrhXGxv6bELChg0bNpLEzp07B7sJNjKMQSckMo277roLLS0teP755/H2228DAKZMmYJFixahtrYWubm5AIDhw4fjL3/5C375y19i4cKFAHgfF//xH/+BX/3qV0mF/ZwyZYphBJDBxAfvfUadlknSFX8hlWe7gQK/6B0rCFiCSnPiKpsQtByyUKAMGGJ0Dhpc09WPj0tyidfkhER02Dnwth5CvGAEmFiXKBmIZiPisfIvLTRhPzWGDzKTB4JGih4BwnKcJpRqKtB3aqmE04L71EF1kCPDiBI3oENICLBCSKjlt6JcF5ALdEXUghGDgoSmg54JgeZ84tDhYDChMhs4LL/GmZqCuNIdtiNNsORkUh7uhgLC/dBRPNKURe+vQcfviaorMdUjIr9s6BODNCac8lLMosdJs9Qk8oFksqFuGcmkJ85K2l5D3g2FbWViw4YNG0ljxowZg90EXYTD4bNnA3oQMaiERFtbG5YvX476+nrU19cDAPbt26fRkCDhs88+w5o1a7Bnzx4cPHjQ0Onk3LlzcfjwYezcuROBQADBYFD0WTF69Ggx3bRp03DTTTdh1apV8Pl8KCkpQVMTvwtcU1OTQk/PTjDI7DorE2tMvfaygk29TBphGAZORsehp0nj3AYrZIXJBpN4BdXaCZooG+mDmqKQfhEW/TpOFTlwumOTDHQJCTUhYmEgzO4RX2/mYUQimRFMcS5meN2wLA4wDApB1CQygCMOxE0IBzOvs4MkOFrlI6xAIA6UPkH0QSvjm4fY5KEW1uXXrQrq6vTp9u1B4qhJJIWmj4RBI/kwsQqbJ7Bhw4YNGzYGH4NKSDQ1NWHZsmWorq5GZWUljhw5Qp139erVWLNmDSZNmgSv14tYjLxwb21txT/90z8hPz8f3/ve91BYWIgdO3bg3XffRXFxMfLy8sS0999/Pz7++GPcfvvtmDRpEurr61FbWwsAmDVrVmqdHWLQdyJotZwzA4Qlr+KcsE52MA7RYaORgrpZv10GkoDCqaUQwUQVtULSkBBOp09DQiE4mRSnryHBwsWkb/rQdwKopU/SqSEx2ISElIaMmAUTHVI9dJExJEHRMD0zlDSerMESIZHkQ6H3Xmm8uNASEjrn1doeamFdftWq0C7OO4lC0q15wBLaQ2qi+h6QtCjicbU/HHoMeY0KGzZs2LBh4yuEQSUkJk+ejC1btqC4uBhLlizBs88+S0wnhPysqqoSz91///347//+b7jdblx22WXw+XzEvO+88w56e3uxYsUKjB8/HgCQn5+Pd999Fz09PYhGo3C73aivr8e6devwk5/8BPfeey8A4Prrr8eHH34oRv34qmKwSAcT7XBdGCn/CyYQSoMNqS6HIrKGfgNMCQkD2U0e9lMgJBg2jkQAAAUkDYnkVtAktW9lWWY79GQNCRbswJhsqCQRzsIuOzNEpA6jZkj3gpyI5NeDvh7GWEMiMeYuJyMKrkZEJeNgk3wK5bUNDqyYbDAWVTmEcZfv9Kfj0dMrQ31PtRoSUvsFXxLk8glzg2J+TD9IBAmJpKCpP84mPy8OOM6QZtqwYcOGDRuDgUElJPLy8pIO++nz+USfEEZhPwWnmWvWrMHIkSOxa9curFq1CjU1NWhpaRFNPYT6W1pa8Ne//hXt7e1444034PF40N/fj48++gh33nlnJodjYJGGFWemBYy0mimQCuOkBa3oQ4KRfEhwjHLBG5MJNaloSCidWiZeQUHwZ5SaEIIeh6QokZpNN59fR3AiFB3XCe/JcpxuKNVkoO9DQqvhQRtylap1AyAoGApNog08OU2MYLKhL1uTNCTM31I+lKXgPMAgoYNCQ4LTPRhUWNJ6sDixCb1MgwWBstwkTTbk7Y8YEhL6dScbDtYMZJON5OqPseYaEmbz5dB5Qm3YsGHDho2vLgbdqWWmw35eeumlWL16NZYtWwaO4zB69GjcdNNNWLt2LX7wgx/AkQhUH4nwHtI3bNiAv/3tbygsLMSVV16JW265Bf/8z/+MhoaGtPV5KCAdu8dnirkGAOzpO6g6o2y94EPCAQdanPyqeV3wMILHpXwBp4yQMBk/Q0JCvgyWa0g4oVkhC+YdglDbH9f36K4Gy7EEgV5ZhY+TyjvYf5RYBglf9h2ibgcNjgZPki+oo4RYKJPm+RyIZ/hEqFX3GgcO/lgATQFy/8lRNvpR7uWj10TZGA73N2Ni/jk4GVKGjWSy+g01JBhnHOB4DQnxXOJnU+AEhnmU0QXcNV8icuAigCP7DuE4Dg1+KZRHyNUNJqcXXKAA7+3oJgqjA4VWVdQGI1j3IcH/PdEhRdmQR9xIFt39ZDNEM5MNOd7a2Ek8H4tz6OjVli/X9qjb20vZUgn9IeOb3NQawodfcJhaLTmJ/sf2biycMxxZbpkDYYqbEGc5tPcY39fDpwmRQGTQm6atEr9msIkPGzZs2LBhQx+DTkhkOuznbbfdhtbWVjzzzDMIhUJoampCU1MTfvrTn2Lx4sViujFjxgAAfvnLX+LGG28Uz7/++usAeAecVjGUva7mdLdQhyHQdQ6Y5lWWN84i7JQaNd5ZjE9x1HI5VOEeGeVidLo/gp35XtR4h2N3jA+J0MUqw9z1ueidOJaoXd/LUBiTFu2xkhrg6DZERkwG03YcrEZDgoewQH7z1PvUbWgNd8LtUL3i8YiCpOjlpAX7mrY6TRlWw4ymG5qwpeDHZHpfCNsKsw3zZlNIwCPD9IJqsvi4Y4vuNQ4cXj3xd3TH+ojXSeO/8vRa/Grc9wEA6zu34fOeBuS6svFBuzJyjnvEUZQVXW3aPrnKvPC8vXnqfeS7lFFinAU+uKsOIHpMGSpUQGPgOD5s3yj1jWGRNWUTgttuwNaDAxPyUw87D5uEOUkzdh8NYN6lJQCSF26ffZ/8zVErJqkfc3l9eq/Aul09xPNCzsbTYTSaCPPJ4GRnFCc7o4pwoq3dUbyzxYf5V5RaKotlgec+bDdM8+r6DuJ5yVCKfG9sAsGGDRs2hg7ssJ9nPwadkBgIjBo1CjNnzsScOXNQVFSE9evXY+nSpSgpKcFdd90FALjyyitRWVmJRx99FF6vFxMnTkR9fT2eeOIJuFwuhEIhy/UO5bCf2xpeAzzAL4924Pc1/G7riHAU/3bch1+PK6MqI1I+Ad0XXQ00rxDPLTzVjRdHFmnSXtITwNZC49CpleEYjuR4AAA/OtGF0vOUApHv+gd4FuHICwD40Jpf7+pHi8eJJ6ukxWw8pxgAeXdR3HhTrThrwix25gPFzjw4AOjRCeGRUxEvKAdzYoNhX7JYDo8dbsOO/Cy8Va70P1IoIyvY3BL4bngQAOBqBeKqOHYOVTt7Y/SCHcuxIukysyeIbYXZvFPLROedHCf6zLAiNBW48jTtmOoPYU9eFnUZNHAyTrGtk/0h7M3LEm/bmJA5kTAiYh6hwjtsAgqjrehxOzG3rReX9Ibw3MgiHE48hwAwPhBBn5NBi9ctnvvZsU68XZaPo9l8upJoHOf7Q1hfTA71agQ9MoKRhaDVQ0+UzxtmyTvyeVnGJJrDAVx9fgH+vq2br1O2M90X0wrxjFt/HozotOFMQzqiN2QSauUBTt1eiub3BHSi5wxS17v99NFk0gLlNKu9nMQ4cByna2oyRNzZ2LBhw8YZCTvs59mPMzLsJ8uyWLVqFdauXYt9+/ahra0NDocDtbW1+N73vgePRxImli9fjsceewwVFRXYvn07vF4vxo0bh1mzZuH3v/89vvnNb6KwsBBerxe1tbVYsGCBQnPi8ssvR0NDA3JyjIXpMw2SE8fkwcj+Fc/pLLxiNLbsmjNq22iyszl1yfQq15JwziRMJzgdnwlS4Q6q1aVRyEk1ySDAxXGICRoSonM5pcaEFXAyAw0HwW+EQ+ZDQ89XBGm80+nM0ghyfxfy8KfUUTZohkymQSJqo6jboVOn5lwyQozBNbXjVSMka3rCMEp7ffPoO/rXHWkMAzuYGOJ8hKZ9SfARaTdJSBmqx2qgmpdeQiL5CC02bNiwYcPGVxlnZNjPYDCIBx98EBdccAHuvPNOvP/++2hubsZTTz2FLVu24KWXXhLTvvXWW8jNzcWtt96KiooKhEIhrF27Fps3bwYA7N+/XyRA3nrrLXR2duLyyy/H+PHj0d/fj5UrVyIWi6G6ujrt/R9MCOstueCsJ0Qbxppg1GfIhcQpVmoO9SrQZFWo1naQ/DqYC8witSFK5y6xSuPABHxO2nUnKZ28dXJh0MUBMVXUBbUPCSvgZPmEe6sU8iWncFaiOaTTmaUxOG37LSz4qVrpcGl3nOmrUCAZWcRIMGTAZFwwczCMUohijNvEGdwAZ0r05tABzZizFm5Mum8hyYxJeZ2ijPQ1Jy3QvIMUnUilD6Lj4jSWzXKpEfw2bNiwYcPGVxVnRNhPNdxuN1577TVceOGFAIA9e/agr68P8+bNw9KlS7F161aRZAiHwxg3bhx++tOfivm/853v4LrrrsPJkycRj/OCWGtrK1555RXMmzcPjz76qJjW4XDg9ddfR2VlZbq6fZaBTgyLUyTTLuZIy0KtY0lN0VYkQ0EQFz1KmmlIMFQrfqMmyIkfTrYn7YJESKjD76nDX9KAk9EYDtlZZTv4Y1I0B2VqCQMleMoJI4XMTCktUD0GTpe+fY6sHFKdtO0whgEhwZibbGi9P1gDo+IUTUsxICQGjqgafFgiitIs/Wt5W87wOrkQvbIHh6pQmzpkvBWc6q/edQvgSSpbRcKGDRs2bNiwikFdQebl5aG4uNg0XXNzM5qbm8Vjj8cjkhFyzJkzBwDQ2Ch5eh8zZgy+/PJLRX6Hw4FwmHfYde655wIA6uvrEY/HFQ4tQ6EQvvjiCwDA6dOnrXRtyINjGDCccqffyu4zYEYXKEFjsqHVkKBrhyi0M4IRiaFOh/JYICQS0VZMw8RZ1JAgwanTMRcHxNUaEsJF1rqNNcdxErEh05DgZGULtVlxXjmQgqeoyaM6pgFVJBmHZGZgpIVBut/qdElpSBhco/EhIZSQ7PPoYJRq5owq1C2pVXoYKFOeoQAr/GC6hWuNiYZm2kxeu2CwNCe0GhKZrU+cZXUqSkojbaipndiwYcOGDRtnCAbdqeXTTz8NAPj8888BABs3bkQgEEBBQYEY9nPBggUAlNE25FE1jh49ir6+PrzwAu/ssKurS0y3aNEi1NXV4c4778Rtt90Gj8eDNWvWoKOjAzU1NSgt5Z0hCmE/33zzTZw8eRJ9fX1YuXKlSETs378/U0MwqEhFsOYIyza98mgMAtQ2/2bRMvTqolkXiiYbCUKCcbhA2UoqQddoXOX9VJtshNUaEom/XDKEBOTkA6c4K7RD+E0KLylvhxzmfgbSA7kPDHEcLNROk44jmGyQ25La9WRAQ0ikriHBqHxImAhjRiYbXyVCwor0meaHw9SHREoaEkk1Ke0YqGboEjNJaUik1BQbNmzYsGHjK4tBJySeeuopxXFdXR3q6upQWVkpEhIkNDQ0aPL+7W9/AwBFRIyLL74Yr7/+Ou6//36FSciECROwfPly8VgI+7lt2zasX78e2dnZmDVrFhYuXIj/9//+X1JhP4cqGtoOoc7lh0wsB2DdhwQHUHvxctJsVmsqkLYhs4WfhPqEMyJRYMWzWELQZxIO+ZhQH1+OXhmCY80UzAYcHJAVZxFyOhQpiD4khCM2jtqjb9BVKiAaBJeIDKEw2UhU4Xc5sJ/tRlVPA06GtM/3Fz0NOBo8qTnv6T4JZHuU5zK0Gt/euw+AXEMiNf8dGjhMXakCANgMcTBGwj8TD4MJ+IjXeqN+vHZqDbqjvYm05AgXnZFuvHXqA8wuuYBch9oNDAOsPL1Ot025CKNbduyqaAKT24MoW4EVJ/+hm+9sA0VEWdS+14p/uXZ42utu61ZGmFELzw6GkWlaabH/RBAHT2mjpaz9ohu7mgKEHJmH0Nqm1hDe39mDSaONQ/oqMiXQ4ovgjQ2dWHDtcJzsiuLNDZ2K6xv29uKj+l7MOjdPPHeiI4K/ftaFubMlTc3frjihW+XRtjDe29GNOy4vgc8fx7p6KXzq9kN+fG2yFFEpEFY+JC+sbUNzewRXTsnH1ecXmvdPhU37+nCqK4LbL+M3Ubr8MSz/qB3fm1OGghx+Hnvt0w6MHZGFmROkPr69qQvlRS5cPklq2+eN/WhoDuA7Vw9PtDWOlz7qwHmVWbhmmvW22Tj7cLIzgne3+jB3djEqipXf++7+GF5a146F1w1HYW5qYsTR1jBe+kgK3/vbu0elVJ4aL65rw4xxeTi/5uxyTH+moLElhA8/78GdXytFcR7/rATCLJZ90Io7vzYM5UVukxJsfFUw6ITEgQMHAADr1q3D4sWLsXz5ck2UDblmhIB58+Zh3rx54nFtbS2eeOIJPPzww5g/f74i7fnnn4/nn38ep06dQltbGz744AM4nU7RfwTA+7OYNm0aDh8+jN/+9reYOXMmGhsb8dBDD8HtdicV9nOohoHZ6tst/qaTs/SYCgI5wAHfPd2NLJZD76x/ATreAwDc1t6LR/IsLs5lK+2FvdpJK7X9WEZRB5tdCCCgaxpxXn8Y13f6gRE1AGcuFBtG2QCHe0/4cDjbA2aUpAfigOTBQu1DguFY9OiEh9SDs6sZGDFF0R7eZEOJD9s3EfPrnSeN+00dfuwsoBAiLOJwghCRR9kQkBdj4XfpPwU0Ph44pzbKBjEdxZuSbs6C4QBHz2mAMKy7+w6KZAQAOPvatYkAbOveg+5YH95r0wlTq+LeGDA4EjguHg+PxNDukcZotKtLQUi4q/j5uzXcYdqfswk0vhZafFF098eIs6fTQUdqJIOq4R40toR1r7+9qYt4fuM++pDCmcLq7d3o7I2hotj6IvWj+l74/HHsOhLA+i97idcBYMsBPzwu/qHf2xxEa3cUhwgEDQmfH+5Ha3cUJzojWLerB31B6SZ+XN+rICQOq8psbudJw0+/7EuKkPjwC578uP0y/nj7QT+6++PYczSAyyblAwAOnAzhwMmQgpDYczSAPYCCkHh3q5Lo9PnjaOuOoq07ahMSNgAADceld0NNSHx+uB/d/fy7duXUAp0S6LBmB5l0TxeOtUVwrK3LJiQGCdsP+tHaHUWLLyoSEo2nQ/D546j7shf/dHkpVTk7d+7MZDNtDAEMOiGRDqxZswZPPvkk5s+fryEjBNTU1KCmpgYAcOutt+IHP/gBfvjDH+Kvf/2rqLK8dOlS3HfffXjggQcAAE6nEwsWLMD27dtFkw4rmDJlCrxeb3KdyiDaD/Vhfec2/iCFjW3S7i4DYHI/P1a+okogIafkxa1VpBYmS+IMouSkiOWXA5CIBBofEpJqeqIilweI6w/HRb1BjIjEEaLWvlCaGsjh4IDiWBzDokGFcCfPJ2pIiERCEk4tGUYUnESBniMZ2lgDSdvFk1WMfNaBPkeGpCwn/x5xkO7h5P4wthbqkyA0hBXHmEfZoLG3z4zJBv01XYUeE5qEVRMSquSFMRbtyrWoTjkZuu8p4vJJ+fisQSLyqoZ7RMEwFdCq9OulG1bgRmu33oyWWbgcDKJDLs6GYJrGH8mfw8sn5WPT/j6N3w71PMYmtLQcA2A5xN9Xs3crs2PsYAamHhs2Mgo7Vu5ZjXRNTzNmzEhPQRlAOBweshvQZxIGlZBoa2vD8uXLUV9fj/r6egDAvn37NBoSarAsi1WrVmHt2rXYtWsXfD4fcnNzUVFRgUgkAo/Ho0n//PPP47XXXkN7eztqamowffp01NXVoampCeeccw4AoKysDHPmzEFbWxtaWlpQWlqKrKwsnDp1aki/DFbhdpB3heldQfIgudNL66dFNpORytU1MUnqA8ckTDXMkjnoNCQMrinXy2Tv8hKRIPhOSMLJmiyf5DA0dUJCz7dHquUa15mog+Frkv41ykNjJ6Q12SCByi9JmgUDBtYdzZLKMALLcUofEiSHnhwnOozV62HcLDrNIEHdH6cjPTMUrYUSx5EXZGlqBrlOk+tOukd+QCGMEUm4pgxsJGqcOBhGZYxoVG/m5qxM8wTCe5uOemxOw4YV2I+LDVoIzwpp48N+jmzIMaiERFNTE5YtW4bq6mpUVlbiyJEjVPmCwSAefPBBjB8/Hn6/H1VVVZg+fTqWLl2Kbdu24aWXXlKkf+KJJ/Dss89i/vz5mDJlCj766CO88QZvj+/3S2qqjz76KF5++WXccMMN+P73v4/GxkbU1tYiHo9j9uzZaev3YMPtTI/NViYFUKEGAaSd3qTW9GoHcLLCjB36JRZ/gg+JFPquiCbCEH+K5YumFkkTEok6hXOyyBvJQu18FADAZPbjIo+yQR32M0mTDTXdxMgvDiAYA1clZN0k62BVHJwmhCTUnmb0yhl6SwuGIRES6Smb9n3kCYmBHRuz6pxp2pGkJQqsQCAVFFMkNSHBienNIBG/1tpnBZl2cilpSKSjtKH3/toYZAzBOd3GGQijx8h+xGzIMKiExOTJk7FlyxYUFxdjyZIlCqeTcgghO6uqqgAAbrcbjz/+OB555BHU1NTg1VdfRWFhIaqqqrB06VJs3bpV1LLYv38/XnzxRfzzP/8zfvOb3wAA5s6di5kzZyIQCIjOLFtbW/HKK69g3rx5ePTRRwHwmhWbN2/G4cOHMWHChIyOxUDCTWk3bwYO2hU/1a40dQUyQsJCQzkKZX2pOE5xhhfAOOiOTGJ1nIqGhO41RjZ6Kh8SyQg1HCNFaUiF2FCD3H4m5d18mjrl+/DmGhIUIGlIDBENUpqgn6ZlmLw4LMsp3i2W0UZboRmOoWiyoXHYifRpSFCbbOjcw0yuw8zali6ThnTKK0JRArEVl0nZtHcsnoTJRmbvQ2ZX2+IuYxrqseUCGzZsZBIKbWxbQ8IGAYNKSOTl5SUV9jMSiWDJkiXo7e3FokWLsH79egCAy8V3Z9OmTSIh8Z//+Z+IRqOIx+P461//io6ODvz9739HIMB7E29sbMQFF1yA+vp6xONxdHZ2YsWKFYhGo1i9ejWOHj0KAFi/fv1ZY7bhdmROQ4J295oGcnLDUqhJg6SK3WBV+42V0mWpKIQvRvVXDqWGgUxdnpPql8J1Sq21Cg6MhtgAwamlVRA1JJDZj4tDQRjR1Ucnl2jvULICZNqdWoLOmSagL5SYvTfqgDKsKvwrB/5+x02aMRRNNhhoCRmnc2AJCXADHw7S7A1PzqRtYCCMq9zhJ217hTxOh6juZlCRsr5kYNaszGtIMOmrx5YMbKgxQPPE0J2NbKQD9tRigxaD7tQymbCf3d3dOH36NABgyZIlmusCiQAAubm5cDqd+PDDD/Hmm28iOzsbkyZNwne+8x089NBDaGhowAUXXCA6rTxy5Ai2bdsGl8uF6dOn48UXX8R3v/tdNDQ0pKnHgw+PzGSDyvGfxfNpg5kPCZUDSOl8cj4ktCXJmiImY1LWAmF0D+T1JwiJxBgk59RSZrIh8yER4FJz6ucg9Z9Jq26MtvjE3/TXwSAu/rJWRzzDCzYGQLcO+3PQ36Q49uvcU19UG21ADlah7cPhVOyU4nqnW6lBojc2aiJjKIBssjHAPiQAtPdonVeyGZRWj7UZv9+Z9F+RLDgOiMRYMVRmXOYEWe81U5MJgnaFPxin/gIc77A2F1rS1MvwB5JxpK8eW2iwYcNGRkEwTx5oc0YbQxuDTkgkE/Zz1KhRYj45Fi5ciD179uCRRx4Rz3k8HowePRoffPCBIm0wGMRDDz2EtrY2ABBNN+644w7cc889YroNG/hweUI6KxiqXlePB09LB1TzATkRv3RMj1NLryoGHu+7kE5t19XXBpRIoYNOOcy910sTonSG4WC6uosVjgQTj4Jp/dy4fNFEgtBevd1sWSfVYT+TmbY5aDUtOA44EbcWPlQNL1GYIhsYODgOrKxjuTEW/QahOvUgkEycXA0/DYKVh3GiJyF0R3SkjVGhKLrzlNFysuMsjmdJxN7E/nBad3ryYnEwHHDYQyai2iM+xfF7oUPEdE2BE4b1jB2RJe5AO/K7UNe3XXG9R0VI5MTIvRyKPiQABl19yjC+NWVe7DkaSLlk2oVUnOXQH9Lew7YecnjhgYDXPQBhKJLAX9a0ir/lJhvqe6gHIYr3p1/2mfoKEUqPxTnFcTphR9mwcdZjCJKbctgC7xCC/FYksZljh/08+zHohES6UFtbi02bNuHhhx9Gfn6+eD4UCmmibgAQw3GGw3y89smTJ2PatGmora3FsGHDMHPmTDQ2NuKhhx6C2+1GKEQXp1yOoRr2M7f9MHDyHwBS+56w4DQFJKWbwHH4eXMXVg/LU12R75LprzDVn5wOh/5urdJkQ3aeQssXAGLDxwIAwsETQPyoSWqI0QkA4MfHu1Aci0Mp4umNWKIlLj6sJc2H9dqufnxUkqsoQWv6wcLLuFAYjWuETSP8+mgHAg4H8uIs1hdr43lz0I7dA00d+NPoYvS5nLi8O4DLuwPIjnP4r7HDAQAX9IVwQ6cfsZHT8FnwELYU6scJJzmcTHWpcWtbH7yl0twgmCUI5V7aHcBUfxhVoSj2JAiJOZ1+XNAXQp5MYDq/L4SbOvyoI4xLMvjl0Q7kxVn8bxVdfG4AiFOOxsyeII5ku9Hh4af+q6YU4EgrPwfCZU7k5UXo3vAZvUHsLNAPyZoMfnJzBXz+GF75pIMqPcMAoYiSDJhSnY3W7ii2HfTr5KID7To3nkZLllnn5mHLAWW7XU4gZlE5pbzIjZOdqYc+TQfysh3wB/lB8vmljsjHzR+i66AVY7RUBRWa3GdSlA0bNs5G2K/G4EOYnxTrbWjPmWEom8zbYT/Tg7OCkFizZg2efPJJzJ8/H/Pnz1dcy8rKEs0x5BCICDlhsHTpUtx333144IEHAABOpxMLFizA9u3biWWcqRAWMlmUq2U9O/ZYmqb70mgc+XFWW4vFlZaQ39r6XBgDwWSD0mrfkwMEzdsiR1XYbKdPZoQi/HB5wI+0/r0SwjIWqiQTjmEkTQvB9CNBHeTHWUuERFGMRRFRJ0ZohNZko0B2T0eGYyiKKftQHYqiKMYixLiQFzN+FuUfMAYAl4ZIMflx5XiprSNGh6IYE1IK6flxFqWqthbEWKQzkmJJovxM7GPnsCyKYyw6EjyMw8FYdBhLh9x0SuIJlOa7xB1tGjDQEgIMAxTkpH63aKemdJpmlBZoP9fZHif6gtZmvKG0a1ic54I/qP22xmVtdFHamKgjc1hCEkNiVkWmrHJYjoODYdIaZWMIPRI2bKQP9nM9tGHfHxsyDCoh0dbWhuXLl6O+vh719fUAgH379mlMNtRgWRarVq3C2rVrsWvXLvh8PuTm5qKiogKRSEShEeH1enHy5EnccsstaG5uRm5uLiZPnow77rgDAFBWViamLSsrw5w5c9DW1oaWlhaUlpYiKysLp06dGtLsnFUk52NBC96RXeomGzFhp0dzhcSpmtdlvFusNIWQl2bkBUF7JV26igzhl1Sj4LjMqEuCZofaoahca0ER9lNTV3qgbqLCqzJpxSucMtB+UZfFydRYzL5ldN86rWEjp70inSMU6lRFMqGFQCQZXR8IpONZYFWj7c5Q0620lWGUqv98/nT5kKDrYDpvobovyZeTlmLSAq3pHA+5Dwlavx9WRmcgXq1MET9cYgJPZ5QNGzYGC5l0xWS/GUMBic0wAmFs3x8bcgwqIdHU1IRly5ahuroalZWVOHLkCFW+YDCIBx98EOPHj4ff70dVVRWmT5+OpUuXYtu2bXjppZfEtD09PYhGo6iursbdd9+Nvr4+vPHGG7j33nsBABMnThTTPvroo3j55Zdxww034Pvf/z4aGxtRW1uLeDyO2bNnp7XvgwlHQgBMdTIgaUgkE2WDZJau9iFBhM5ls4gAQg0KMwM9Ww7d3MaVUKukqTxcShoSAnEiUgmmRahbxAEQIoJI9yX1TwC552SDF6FeslNS4Yf5DXMkyk8nmUIicACI4UsN22xQDnX9ML4bA2Wea0lDQietOuynnp+UlGGhrbyGBKc9mQZQa0ikcRhYApGQzGJ+KPkccOiQ0XLShDaMp7Jbxm+X+r4kNSImY58xDQkWcDrSE2WD4zgwGXZIbMOGDRtE2BOPDRkGlZCYPHkytmzZguLiYixZsgTPPvssMV1zczMAoKqqCgDgdrvx+OOP45FHHkFNTQ1effVVFBYWoqqqCkuXLsXWrVtFLYvvfe972LFjB8rLy0Vzjnnz5uGKK66Ay+XCtGnTAACtra145ZVXMG/ePDz66KMAeE2MzZs34/Dhw5gwYUJGx2IgoRdGzeraNpYm8VDQkNCWlNxspd6tlYOkhSCcFzUNzDNSgLbtRBpBNNGQdhCNTDb4hJqSGIJTSyQWoZStI4LUNcb63ZKWweatIRE8afmWyd4FIw0PTvcZTR4ODmANChw4QiL1mjSERIakMUstJWpIpAe0vUun8H9WakjoqEjI+2riZUc6pnSCnBZQ3IpM8T5sQkVC0pBIvizxe2cLBjbOQgwh7vUrC071F0jOh4SNsx+DSkjk5eXh6aefBgB8/jkftWDjxo0IBAIoKCgQw34uWLAAgBRtIxKJYMmSJejt7cWiRYuwfv16AIDLxXdn06ZNIiFx5ZVX4l/+5V/wwgsvIBwOY+rUqVi3bh1isRjy8vLgSGy/1NfXIx6Po7OzEytWrEA0GsXq1avFEKLr168/a8w2xN39FFdtcaJTS+tTjF74RCZJo2Aai2qiyQavUkBdD035VswK5Ht6Qt/FHUSKL6tDlUYgHxTXSB6G0gJylA097Q05aJrCEHc80yt2aD6chIYZ1ZhuIWjACIk0lBFX+ThxZ2glaIU7YRiGKHynxUSFUqinTUeDdPVloDQkGCZ5gUA+brRFcKQVLy0yMCSZMqUQuJq0EBIJRsKKQ1AbNgQM1DfKxlkAxXp+8JphY+hi0J1aPvXUU4rjuro61NXVobKyUiQk1Oju7sbp03zoyiVLlmiuCySCgJ///OcoLCzEG2+8gZUrV2LMmDGoqakRCQwAotPKI0eOYNu2bXC5XJg+fTpefPFFfPe730VDQ0Mq3RxScFjcEdVT044TVkLJzDP6JhbGiyS9bLQyAKcgIPT8WOhVbtLTFNd3EjHB17M/clo3rZHJhrDQlAgSwewh+Qbq71jqa8wYmT9kN20GTCJUSGE/JV8fes8lLQy8N2iuq4kiyoJSQrKmIOblSgXzKtv0efV0a9QaEs7Bt9ggmmyky1557a5uxbGDIavOf/hFT3oqRPocZB44YT1iVDIwM0kCpPuhDoPa5ZeO9QTu4+1KZ5h+QnjVdEAwa5Dj3W0+YrvW7+mFx8Xgkz29iMaMe+8PxrHlgB/XnF8AB6WfDIB/Dj5v7MeJDr7/nzf241uXFJu22YaNoYhMPqU2zTYEQNgD01GMs/EVx6ATEgcOHAAArFu3DosXL8by5cs1Ti0FzQgBo0aNEvPJsXDhQuzZswePPPKI4rzD4cC//uu/4l//9V8BADt27MB3vvMd0Y8EAIwZMwYAcMcdd+Cee+4Rz2/YsAEA74DTKoZqGJi2cKf428NxGB+I4FCOB7e29yFSNgG3th3H38ry8d3T3QCAApVn+4n+MPbleXG1ayTUn5PiqHJR+DVfPwoSUQPuaO3Fm+UF4rWb2vuweng+FpzmF+3XdfVjV36WeD086gJcv+8gYpE+wJEPEjgwKInGMS4QwZwuPiTeTWwpXndS3C9GO0nq7RRZpV4YALH8MkRLigH4DBJK5TAEEVhYVNaHThjUxWlyA4IDS6XJBv8FSO0roCYz5rb1AkwJOEYrEIhtIsnxFppBWlsbZfewLMojZlFNAICBg+PAMoxIcEgUlVYFXPyQMlKkBlJ6PUzoD+NgrldRln7LMoMruwNiGwBgRAnvBJihuSE6SeKcxdiT4O/pZRPz8VlDn7VMFpLeckkxnvuwPdkidHGsTRUZggHKC91o7VZGZTGLgHHDjEJ8srsX4SjFs1OZhbq9yrGaM70Qb23sMsxXXqRt10DA4WDAmkRFueb8Ahxpade9PuvcPPQGkni2LOfQB8sBTkGp0EQrYf2eXupyV2/3Yf+JEGrKvRg3Iss8g6w97241+KYACEc5ZHnMR8EWCGyc1bCf70GH8S2gv0E7d+5MtSk2hjgGnZBIF2pra7Fp0yY8/PDDyM8nC68A0NnZiZ/97GeoqqrC9773PfH85MmTMW3aNNTW1mLYsGGYOXMmGhsb8dBDD8HtdiMUsr6rNGXKFEVY0aGC5u6TwPFV4n72olPd4jXfhbdj1vu/w6xeKaalU7W8u629F3ktHPonXYgIgEn+MBryvLittRde1Qrnm539AIBw5TRceLJeQUhc3hPE5T1SPcOicVSGojiZxYd05Lx5uCLogKunH9FhUpmXdgewqYjfUe++4QEUv/87fF/Wh5HQX9zpOlkk+GAAgKl9IezJ15ZH463ff/HdYE9vAaLGi0c5RLMB0aklhX8FnTmdAyf6npBCWio1JlLBtV39mNPF399osQuAlgCgMdmggbyP6vCcJDx8pMN8dzbxz2x/DBvz3YgMHw9071ZeBxAtrYETfsU5/4w7gO6PxLSsNxfR4ecAXKtuff95pB05LIdfjyvTTaOEsgdulkPUYCd1fCCMQznm883YoFI4dTsZFOc5QSNKcQCunJKPT79UCsYxTnvvz+sPo8/pwBEH8J93jsJvVyhJtf+YX4n23hg+a+hDUa4T3f3mgqdVMmHUMC++e80w/N/HHXx+0EdtsAIGwI++WQ4AWLW5C/VNAdM8k6uyMevcfERjHD6ql0b/2mkFimMBXrcDs8/Lw+b9fvHcMFUo0OI8JyIxDv0ybYEffbNcM/ZyTKnOxqnOqEIrQY47v1aKT/f04rQvqsjz5bEgqss8WnImAZcDkEci/qfLS/DXz5TkSWmBfvje80Zl4YYZRXhjQ6duGhKcScTLHQy5RTDBiVsIZQvQkQhWzVxsYsKGFZwpz4ttijR0kFJYZmBIm8yHw+EhuwF9JuGMD/u5b98+dHV1IRKJYOrUqZg7d64ibX9/P55//nnU19dj9+7d6O3tRXZ2Nt566y3k5CjVxJcsWYJvf/vbeOCBB8Rzs2bNQklJCaLRgd9hyhQcFGEWldCZ1BkGYIzDZUpFpKhOa8V2nDIxryygMtmgdvhoriGRqCXJcpQ+JGhK0EaN4MTuiWYOaYxUoTBfcJKnEqPQlVba4JClpvXPQXsf1eVJ5hlSKsEEQV+JwEFdIy2slpaMiQcHjvp9EeB2adPHVBoSjM5vRRodEtAIlkw2hF1tVQFOJyn14EH9ilg1qVOXZTU7H2XB4D1lAJeTUZ3jj43a6nIygEzzw/K9tuA/R450iyCZEr6E6CFWLXFoxoO2zZkLAm3Dhg0bxrDpIhtyJLGXkD4IYT9bW1tRWVlJnU8I++nz+TB79mzE43GMGDECe/fuVZhbAIDP58Of//xnHD58WFzgfPe738W4ceM05T722GNob2/HN77xDSxcuBDf+MY3sGXLFjQ2NqK6ujq1zg4hpGpbqp5EaHask596BN8O2jbrCzrW+8cwZLHMSJiiKNWyirlWQ8L8FXWo/krQakgIfjNSeQJIeTmHMbeZamA5+TCme/ks+afQr8CpvqRKw1GQfOpizcZE/V5l8uNthZSQC6dcYtBibDImGxIjQfuaWHJqKfgCUT07rgxoSCQD3VjsBs1T95/0TCRD8hgJsAwIhIROewQ4HNo8pMRG9zMVp43pdJ+QqfdOCttprQY9AkNOVNCSOBnzcWzDxhDAmaLJ8VWANiwz7InHhgKDSkgIYT8//PBDXHfdddT53G43XnvtNTz44IP44IMPMG3aNLz//vtYvHgxNm/ejK1bt4ppy8rK8Omnn+LCCy9EXx+vZiz4i5Cjvr5e9GPx5JNP4te//jWefPJJzJ07F4FAAFOmTEm9w0MEqTu7UuZ3EM+qclBqSCj1FYzT6NZFLRxyip1BhoOF/SI6DQnT+VZxL+S/Oe1lUyhrkzvtdMjSpPoNIOY3GXMrZA85v1ZDIj3Qlib0T94jiZDQPqEcADgcpkJ9JrUBkkmvBcXOK8PALRc0WX6UogSTDaHEdDrXS05DQvbsMExmTDZSKVI17JZIUMItS/caz0EYM6EtekPpZBhdEsPsnPqaZaEiGU0hg0oyFS1DMC2xGolFrzUcRRrLhdqwYYS0qFqmoQwbQxZGfsDtaceGHINKSOTl5aG4uNg0XXNzM5qbm8Vjj8eDwsJC3HPPPaisrERtbS2ysrIwZ84cAEBjY6Mi7TPPPIM1a9aITi1JEMKO3njjjeI5lmVx7NgxABiSviCShUMUx2m/BLpLZMOrCtDu2KhnqiQ+VkaCoVbkV9SeNptDifCwlkfIIYbrtOBDQp2SN9ngFGnUx6mA5tbQCBx0dcmESk4wP0kN2vHSh5MzedZp7A8sNljTvgws3MQmMYQKdaAQTjn+E0Iy2TBQOFGk4//SqkjQJVOUrcqTjI8B+trokandaavys1wzS++6S8fMRY9scjjofHVQaUiYlqLEmbLIZZLUkOB0VCTkxVCbbNgaEjbOYtjP9dABSUHChg05Bt2p5dNPPw1AIgQ2btyIQCCAgoICMeznggULAEjRNvx+PxYtWoTe3l4sWrQI69evBwAcPHgQAG/SIeCll17CihUrMH36dJFU+OKLL+BMGBLfcsstAKSwn3/+859x4YUXIhqNYvXq1WK4TznJcaYjbSYbwi4Z1eonNZMN0gymv5NIKypzmjN6ULfetIqUv4SChgS9KQDJh4SkIaH0ITFQ0Gsbf46+JUQ9kjTtzqiFYRIX5hQimYgX1ero1jUkzJo/4BoShCgpxGTyiliBkNDRkLBAdFDVnQwjoUKmnFpahRCSlHYHnlJBIilCImbgWJHsQ0L5Vw0HSUOCkNZork7Wh0QyMKoiYz4kEl1Pl4aEIg21DwkLhdqwkQFkVDa1n+uhA9m9SFr7zcZZjUEnJJ566inFcV1dHerq6lBZWSkSEmp0d3fj9OnTAHhHlGr4fD7x9/79+wHwJMQXX3wBAHjzzTfx5ptvApAICcGMY8eOHVi3bh1cLhemT5+OhQsXYtmyZUmF/RyqoBFy5YjnFAMyH/wu1SwilMYaSvRSHpeBF6+ySBynvW4xWoezm/cO7+pt0RapU4aR3wV9XQ8GfS4nPkevYgu1NMrv/ObG1atGbUlOjkOcke2kMw5iG1l3NhxRgTSTmyJoy3RQKTHxtbgSlZWHY2j1uvBh5CjQeVRZSyLsZyY0LSvCUbR4yV7zraprqyHXFGnzuBArqACHHgslaJETZyEfdQ3pJPvl1KgnSMfCaEZgLFlofEaYfIzVhE1FOCZGoEkf+DqC560GRZRAvl2yvjsZB1gAh/ubtQl1NHcUZcn4xhyvA4GwyRgSCvO4GERi2sHU05DIy86AV8skXqiYdbcbmmo8Kgej6lFQXychElVG5VAj2+PQkAuFOfwYluSRlxDlxW4FkUByhArQac+U5LuA02GDlEpwnPXbYfQqyq+lU3gSCQmLi3J9HxKy35SSmC0Q2DibYT/eQwcciZGwYUOGQSckDhw4AACi/4bly5dromwImhECRo0aJeYTUFtbiyeeeAIPP/ww5s+fL55/7LHH8NhjjwHgI3jceuutePTRRzFv3jxF/iuvvBKVlZWIRCJ4/PHHMXHiRNTX1+Ohhx6Cy+VKKuznUA0D0xuVwsYFJs5Bzr61AADWpTVLCUz8OqLDxwKn3gYAXNXVjxxxRaTVqQ2PnArvqT3aShMrnx8f70JhjEXfjPnI3/mGIkmsoBy3tbViRl8I3vP/CTGpBjjCUphB4Vy8gA+z13fhHcj/nCeY/BfMBQI+CLLhL492oNvlxLOjigEAkfLz0FN5CZjjf5fpD+jjuq5+jA5FMV4VKlE+n072h3C+P4yaYBSPjuHjk/ZPuRGMOwukmbf//JuRv/NNbUGy9giLeXXIVTnmtvVieCSONxKhVAtjcdzV0oMR4Rj+t7pU2V6Zaq7Zgn1ifxj7cvln4Zo+Fpd0KEP16eX9TksvGrPdCDsYjAzHFGlpvz+jQ1F8vdOP5iw31pbmEes8keVGYOy3wB34PwDA9N4g5nT1I+B04E+jS8R0/um3AX0bAAA3t/eBAdDicWFbYTZKIzGMDscSNFtiJxZA76x/Adeyhj8rrtY50YcEK5NuZ4Yc2JaVeNA4DkGZ2cJdLT3odzpwLMuNekLYWDnk4Tq/d7JbPO+UPZxF0Ti+d6ob/33OcN1yGA74xdEOhB0OvFZRgHaP/vQ+rS+E+vwsjbaTHHKC7VvtfXh3eD6fngEWfX04uv1xbIQbPbGgJi/pfv/rN8rgD8Zx2hfF6GEezfUffbMc63b1oL4pgJJ8F66eWoCuvhg+2SORoepyb7u0BNVlXvzv33iC+p8uL8GuIwEcOhUiR9kAUFnqwZ1fK8XrdVI4yUsn5mHTPmlenFCZhYMnpTn/ugsK0dEbxa4jynCe08/JwRdHAqbP9/k1Odh9lM9bWuBCZ29MMs8yyHfeqCzsP5FoRyKqkYDvXj0MhTnaeyw8tlNrcjDngkKTlgHBiD4Z8e2rSjGixKNxBDp9bC5GlHgwoTIL5cVudPtjYijYSaOzcfMlxXgzEa6zMMeJRV8vw6kubXhQI00zYQ6cM70I2w7y4YXLi9y4+8pSrNnRjQMnDb7JFBOOcO/4uozaYV7WQIIq7Cd1m9Nj/mbDhg0bJNCSvWbYuXNnqk2xMcQx6IREOrBmzRo8+eSTmD9/voKMsAKv14tnnnkG9913HxYvXgyA9z/xi1/8ArW1tZoQoTSYMmXKkPQ90RHoAo69Dg5ArHi0eF4Q8AWw7myEqy8CE5IW6jP6tItA+dovPHq6ISFRlRBUfcPHapKw3nx4elsxIRBBrzdXt/1CfTEPn4ZLpI0VVCBaMRFM0xYxbUmMRZ5Mu4HNygebN1xTlh6cACYFtAtpec6rfAGMDitV1uMl1YmXi+CpQkH8yFqgWJ0ntB5U2ixF0Ti63bx4fEmv8l4wAKb5w8R9erZ4NAA/OJNdfIAXVgVC4lo/C6dKO4T15oGkZTEsGsewqGrb1+CLQxr7CYEIxgej6NYYrStTs9mSoDW5P4KSGIuSGKGdCR6rIhLD2GAU7w7jSY7ZPQkhWhVdJV5UCa6VpP2SuC5wcAyD4rhEZAC8Iz/hYJqf39FtkZECejoWhVGp3VUhifhyyiKXjAlGkUvYGq2JOnDUzYrllcZYACzO7Y8YEhIVkRjqAUN2iuGkRk7xh/Hu8HyxntHDvBg9DNhyTGfnWyYRCY/1iGIPUAyMH5mtTQ8gP9uJ0cM8qG8KoKbMi6k1Odi4r0+bMIHpY3MwtUY5L48o8SDb4+AJiURiktA7fqSSJCrIUT5vI4rdCkLi8kn5WLdLq5FTrKMhoEZhrlT+rHPz8I/t3TL2UT/fuaOyRUJCbf0ydkQWogRTC4HoGD3Mo+kXCUaLQuFekRxUnjeKvzb9HH7+FQiJq6YWINvjEMe9MtGO00peUxcjit047YuK7XI7GVQUu9Hii+KcCi8Kc124dGK+SEiMKHHjdBf/3lSWunGyU0keTxuTg/omJZEEAOePkRESdE1LK/Ssv0zzcRzcTkZz71PxIWFTEjbORgw1MvErCaJdocE1HcyYMSMdrckIwuHwkN2APpMwqIREW1sbli9fjvr6etTX1wPgtRjUGhJqsCyLVatWYe3atdi1axd8Ph9yc3NRUVGBSCQCj0fafVu6dCn+9Kc/KfI/8MADeOCBBwAAK1asEB/0cePGYd68eXj11VfR2tqKkpISdHR0oKur66wK+6k0A0if7hS/e6qnmmvRUNYAkoo9eTbTV64nIMkvltz2mVh+MqFHOa2GhFtlskFjwEFKI4rdnPgPbat0zlmze0/1KSM59+RkTwK5cvNaOcJvkg8Jof4Y6b4z+m2kUUnXO5fK5Ow2ea7T4dTUDDT3XNNMdSZO/zLJxImB0gxEryXaOcK8tWQfCKbZdOsWumakss/oHuickpVF7SqD4llwakJ4GiRWaaZYfQcciQlM/myofVbIx13eT5GEopijHLJCBiPKRrLFspzeGt96gdL3Jrm22LCRKtIZolcL+8EebEiO2uXnlNds2AAGmZBoamrCsmXLUF1djcrKShw5coQqXzAYxIMPPojx48fD7/ejqqoK06dPx9KlS7Ft2za89NJLYto5c+agqqoKAHDq1Ck8+eSTuOOOO7BhwwYEAgFMnTpVTPvoo4/i5Zdfxg033IAf/OAHaGxsxLJly8BxHGbPnp3Wvg8mGJmfA07+NVDPDUKoTsWCT1ES4ZwOaFY8lF8mwYkmaW+Q1B658CVfJCtCfloWmY3Tiw7ZiH1idH7LIWhIKHc4rTiClMMptoODbOObCKUQpJ/SilBLHAUL2hOG3vh1r0jUjGFduiSaBNFkg3DVeBhkz5jFW+e2mF7uo0Lt50UPhuqUhGHhoLwXZu8NdRd0itHwFRZeU0PHi2r5mqJcovAszKUm+RVvvCqtkcCrHGtKcEJeuhw0i0KXiuWkiWRk5vhSkVgGYUw5g2SKcZGThKRnVqd7imAxtCYbaRSeBCLKKuHBcdo82mP6smzYOFthP99DFPZ9sUHAoIb9nDx5MrZs2YIPP/wQ1113nW46ddhPt9uNxx9/HO3t7aipqcFbb72F3//+91i8eDE2b96MrVu3imnPO+883HLLLbjllltw1VVXAeAdWLa0tOD6668XtSlaW1vxyiuvYN68eXjqqadw11134ec//znKysoAACUlkm36mQ5GvuAjmAmI6awulPhcOhfTNwNp98UZxQn1Ypl4JGbhSIlMIScaLGtI6EgZDMNomGO1yUayL6zg6JOT1ZAsyCSLXr361VkZcpIAZNoDi1svapt+OYEgOAyNG9x3qyNKlpPlpALFrr3OeVcaXjeyHKZ6myjGOFlhH9AKWmb18dFXlUQpUbMhmTamS0NCjB7BH1txaqgJ7qJDGgEWNCQoQBMxQw058a2bhnCOpCEhET9yDQjhmrV2SfXINST002Vq7czpEuvm+TR7B5zaZINT/NUvC0m1wYYNGzasgKiNak88NmQYVA2JvLy8pMJ+RiIRLFmyRBP20+Xiu7Np0yaF2ccrr7yC3t5edHR0AABWrlwJjuMQj0v27vX19YjH4+jt7cUbb7yBvr4+rFy5Er29vEO1Dz74AFOmTMnQSAwslKrlBiKuoCEhF0cIUopyR92sLCPQrSaFNrAaMkGgRAwICd0qrK3eFamJkyrtMtyYwHGAgYPjRGeKVrQKSFeFxSz9bj3F9jJfsk5+4Z5Y+/JoBEaDRDR9MdrPlfLrPzeOhE5NzEjKNanX6qMn142h4CaU5h5mJhtiwdZJRxoNCUaRQr/xZhYbRtAlGlQ788QnWJU5WbVhozp08yT+0izKrGpuKaZnyqw0j4CakDCCZkwoQnvKIWpIEPyQkF4/vd8C9LpnpByoyJ+hRbNIBlgsn+W0eTikuOC3BQMbg4Y0Mqcq2I/14EPmG1x+dhBaYmOoY9CdWmYi7OfRo0cVxy+88AJOnjwpHh86dAgA8Pbbb+N3v/sdAJ7kAIC9e/diw4YNyM7OxqxZs/D4449j7ty5aGhoSK6DQxBsqF86MNCQIK9mDBVpCed0yiaB8rskUCjSPpGxcEEUSLhUvVqYaUgYED0Ukqm4GGcccLEcIhS7jUZwMNKomd0LeR1Of7txAhMwqr/Kawaq6ppjLSlm5ZNmOOSixpBKQ0KWTCAH4gbCVTo+sUpSgSJ9NAS4PYS8tCYb+uloSmiP6HsqFO+vLufGoSl0FIAqCokrgj53D95v+xK9jhwAvLNdlmNxKHAEgJcvndRARvvzWOQonKU+xDsrie1wjWjEQTAAxoi5fM5TgCMbYGVOSQn3XuuvQgckoZkkkLrD6GZaIY6JibB9NHACcEaBuOQ3SShPEOy7Ij1wlp5U9p9h4ShqA+uroLrPJKeWZjAla1xh7OrZDzA5AMfPT448H1hXPgAXOAD9sSA2dO1AwDEC8udE6UNCSX/RQp6y8bR+xI6NDX2YUp2DUcM8lgkiI2hIBY7D3uYgJo3OVmhvqHH4VAgcx8FR3Aq2uwzgHEI0Z03Z6nt7vCOM3CyJ6jzREcakKqVj2I7eKMJRDiNL3Nh1JACW43DuqGzkJfJ1+WPoD8UxepjSYff+E0HkZTnhcgKFuS4cbw9jQqXkwDYSY3GkJSw6QyX1a2SpGzleqX1HWkIYXuhGfiJUr88fw4a9fbhicr7oUDYW53DgJD9uvcE4fP44aspSdybe1hNFnOV4Z7wZhs8fw9HWMMqL3RhZknx9x9rCKMx1oihXf2nf1BpCab4bHjeDfc28c+fjHRE4HMCVUwrEsabB7qYASvJcmFKdg87eKIIRDqMIEZTSgRZfBIdPh5DjdaK9J4oLzslFeZEbh0+HEGc5dPTEkJvlwAXn5KKpNYRhBe4MUh1KNDQHML4yG27ZPLn/RBAMwztzJjkX5jgOu5oCqC7zIhBike1hUFqgDOvd1RfD9kN+XDutkIoUJs0h4SiLbQf9CEc5XDOtQJwvm9vD6OyNYdzILORnO4nvWl8wjqrhXpzoCCPH6+RDMCegfl85jsOXx4I41RXBjHG5GFbgRmdfDM3tvGwViXH4rKEX51RkaeY+luWw5YAfI0s9qCnz4mRnBL2BOCIxFk4Hg8lV5DnDxtmFQSck0hX2EwAWLlyIPXv24JFHHtHNf+jQIdx00034/ve/j1/84hfi+TFjxgAA7r77btxzzz3i+Q0b+LCBbW1tlvs2VL2uskc2SQeMkZ29VmQnT4lKQS6eUww2u0iRIjz6Qri7mmEM/Qk3PHKqJpWmuYlZTrP7qfid/CcqVD2TOq1xPQyC476G7MN1mivaHWNGEf7RQRAfaHokEBLCujW1D7U2d3jUBfC0at9Ja6XIrmlU9enyWQej+zzJCZMpYQc25sQxXoi4opEOyWLd9gLpQ6qn9TEsoopMIpRo2f2+9DPLih2A1cIT6Ir0aM4xHKdpt14v9vQdwvq+OjjLzwOC48TU3nO340RuH070AnADcF8FRLOw1bcbdV074CyZhnjXCHze2I9vXVKsqku6n8I88Km/Dp6xQJBASDjyfHCPPoTjAFwVDGItY8B4+3HIuxGec8oROTzdsB+iKYEVQTiRVCCDJlVlY+tBPpKRd9Jm7HGFANxArPO8UdnYsJePZhGKh/FWywfwTChGZJ/WEbRQzzstH8EztgvB3lIgygv1rlEH4R5xFOH9FwEYadpmp1pANuiuWotB7zF2jzqED9pPwJF3Mdg+Pkyxd9JWtAHAyRvAccBLx1fBHw+AHXEMaLtKDFEqL7K9V4qqoR5b/oADwxD4dVkhHb0x6GHLAT+2HPDjt3eP0k2TDNRaDLuPBrBqsw9fn16ISyfm6+ar29sHR1E7vON3IXpyLGInx2s1JHS0L57/UEkwv/lZF357d44i759WtwIAfvqtCryz1QcA2Lzfj3tvqgAA/PHdFgBQjEdrd1QRRndshReNLWH8bO4IUcBZva0bu48G8KNvlqO8SCl4RWIsXlnfgcpSD35wfZl4fvnHHSjKdeK+W0YAAJ5K1N3lj2HBtXy0rPV7evFZQx++fVUp3trYhXCUS8u9evofrZp+ZgpCv1Kt78V17WAY4L/u0i/j5Y86kJflwIgSDw6dUhJxXzT24z/upK+/ozeGtzZ2YWSpB0tXp2e8OI4jkr+17ynX4Jv3+/H/5lfilU86FOen1uTg5Y86kJvlwA+/oYwclwkcawvjzc+6MHNCHr55UREAoLNXeh9yvA788jbtHNvdH8c7W3wYPdyD4wmhXT12f/w7/1w4HAxVCOf6pgD+tkU5h/x9mw9fHuOJp8JcJy4ez0cae2EtPxfkZzvws7kjdd+13949Cs8l5g2hfaT3teF4EG9v4jcoNu/n58uVm6Q54b2d3Ylfvbj7Sn6+F+adbQf9+PCLHrGOZR8o7zXDlIBh7LCfZzsGnZBIF2pra7Fp0yY8/PDDyM/X/5j//e9/BwDcfPPNivOTJ0/GtGnTUFtbi2HDhmHmzJlobGzEQw89BLfbjVDIIOa5DoZq2M9ToSPAiQZeDdzQaaFW18pJkHMYxQ8GvV/7kSZNdMQkoP5vJi0zICTGSAtuoV0iXaLRHqAQDhgkukUnuPmn34Zo+bnEphJ3+gmO2eQ5QuMuR2jc5ZomSRAciqoMbJI02RA/8LIV6p0tPXi9gvCRMx0SbU2x4WMRKxwBV89pZUrjTXJqMASbhXh2EYAg3W6toTYG/zAQNQsTKUbHnXjs8GnFOajSC4L49Z1SmFwjnxMCRkbIwtDYCLDFJNowo/O7MqwvYPFpBRLRQEOCMDfIyawIG9VcZ1Rp1CYecgTjiXCWnhAY2fTKZPUr0jGOODgAfbHEeRcpDC8Ph0wxSVsvoa9OWR/c4cQ5niBivMpQkemLsqHMVC3bzXV4VaF8VeVXlnrERWF/jG+fQzVeYlmJsWhLaLEwjHS3Hd5E2Fun8XOi1w6auUb6q5NOaIOOzRXHAf54oo8G4yKzvLRmsqFzfqAhTMn+ED/n9wXJBKUcTOK+Cc8ox3FEL/apgJWRmkaEDcDvwsrR2cenj8akMroS5yJR7UaHEFm6U0YuxRP1d/drx6O9R0rX08+XGwxzCEdtVXBjB638RX+IFe+RHPEk1UZDkfRFUbMC1qCz/aGBaZPQ926/NJ7ykLyBMLkdwvPd6tN+R9UQnnEz9BPmkG5/XHNdjr6gdI70rpEgPCcdsveVVPapLnLfONUPszmvP8TaYT+/Ajjjw37u27cPXV1diEQimDp1KubOnUvM09TUhKeeegoffPABGIbB/fffj3nz5uEHP/iBmGbJkiX49re/LYYEBYBZs2ahpKQE0aj5pHGmwCHTiuAUyzKdyV2xQ0+4IP+TyirPIK+8ZWqTDY6Yyhwc0mMfTGo2Y+Sbw1DtP9EnUe/aqSt0WoEgBHGwGGXDYi16Z0gyh7UoG/qCvdFomkNLLIhXTLJbHSca+VgZEUZkzSwLVekO66mox4jEtFCmMA8x6sZyDpC0s+jKZMTm0Tl1lD1XYjt0aERCeWIdVjqu5QatZDOFaHKUhJ+TVOsmJU52PiGNjzDe8r4Zk1BSGzTvd7KOQ9IEibRLwgZNIGgZ4XuhLMCqw0zSWKfybST5ARF/kUgj0URROhc30PKSa+zYFAQ9FENKOXA0yeLx5O8CSdeQeq4zqXYgnCZKWlkSHBRzixUlRup+kL5RAxS6gNRG0rzLJ1b8MX3GbOeXXw0MapQNIexna2srKivJ9r0kCGE/fT4fZs+ejXg8jhEjRmDv3r0KcwsBe/fuxe23346DBw+CZVlcd911uO6669DS0qJI99hjj6G9vR3f+MY3sHDhQnzjG9/Ali1b0NjYiOrq6pT7O1TAMDorON2XXrrgIMwMdAraVC2juibffSUnNdInVmtTCGVaazdnlp7auFyeRUsOMQyj6GjShATBh0TSc3yaFvLWZDgL95+U30CiJy2I5PUAIDiVTJ7I0JaQ3HXj9NSiiOVKDN9SIw0qFZzC54eRBVNlIPoTMGyEDpTCacp6OeYpKH27JEsqMgYZ1btM4qHAZVJWlEyEEcMpVp0mydtA0t4h+aUwc7LKWZFwBgFqfw8094PjBO0TVsyrjLIh/E1+JZ+KDCD0QSl0Jb5ppLpEPkK6GosL30BteuKzPYTv8VBBTEYc0IT7TSQ0PZWsZgVtfVaSDrTwKimfcppzRhCfeQtpk4HG3G4IQO/bpZveZiS+EhhUDQkh7GdxcTGWLFmCZ599liqf2+3Ga6+9BqfTiQULFmDatGl48cUX8dxzz2Hp0qXYunWrqGURj8fxy1/+ErNnz0ZJSQmOHDmCBx98ECNHKm266uvrsW7dOvzkJz/BvffeK57PysrCqlWrzpoIG4BSQ0IldpnnNbiW+pRhTiQAktmCbPpPnDBvQdJTs0HZxLWRsENEkNCMfAOIjLGww8U4FOYGhloFBtekHStrOxCpQ19gs6KlkZyGBB3UJhvkcrXbvmrhJ9nnX55PKWjp7i+YglpATjNvIZdBGfVJFcR5SPXgcqwj6XvqYJQCeVILGb1ddsNoERaKJ+yoUeXTPG9a6kwZKjO5colpNB2kyGNWvmjPRR4Jw+gjDDmdnslGuuRXaiHOrByOIzRAX2DXFpB4dxyShkQSm9/G6VPoKsFCUPab7j2KJbS4h6A8dcbCiOTRA5WGRCo+i1K4v0TNHsXvgRBkpbUVqQ16EL5NNN03Mk3RtkT1HaDYdk6HwE8sw2QJQ9r8ISHtLrFsDEkMqoZEXl4eiouLTdM1NzejuVlyiOjxeFBYWIh77rkHlZWVqK2tRVZWFubMmQMAaGxsFNN+9tlnOHz4MO6991588MEHuOCCC1BRUaGpQwg7euONN4rnWJbFsWPHAGBI+oJIFoxiG5Eig2yicZitelLZlaReQPMVa8N+6jdLvxRrdRMzGI6DBQ0JaFfZDJIXzpRlyzUkYDhI9KKG+flkwiKS0st9SKg1JHTLptIskY26sIjWtJl4g3XrooVpKFTrygv0sLpFIUtNdBwotoG+PCcjaUgo3haaGKc6cDCMYueJsyKmmai2pEuoVUfZSC8kDSgtiaBTIY2GhPqYgjs2c2ppNgC0hIR8sUqsy0A7yjLSdM/kfERS4T9ZpXaRbpQNasKRQJxbaI4aAokgF6SMNEBI7Ywlbixph9eWT5KD0ZjqgmKwY7KXMFXh1kpu00BwA/CgkAhmlkKCtjJMtElJ7xbNvU72lpltZ+rVLNVHV7H9vn81MOhOLZ9++mkAEiGwceNGBAIBFBQUiGE/FyxYAECKluH3+7Fo0SL09vZi0aJFWL9+PQDg4MGDAHiTDgGbN29GXl4ePv74Y3R3d+OLL77AhRdeiJtuugm/+c1vkJ3Ne8EXwn7++c9/xoUXXohoNIrVq1eL4T7lJMeZDkYWcUEZnlLvtZcREkQhREqVysRhaAYh3yEXZWq1SErDtyp37NPBDJNro+uLGqKGhEi2qHZFDb8t+n2Romzw/xl/oswEN+PLpMQkQdVKVxwEDYlkbK+JdaockFqV1dXJUiGQFBoSFqmhZPxGpFsVUq15obc7Dcg0JBycasubzJPT7HY5HJIQ5GAYibS0BPJzRXxtk7jZjOp5M2wJxe6SXh56DQmKNCn0M9n3wWh8FAth2eLfIU0OpuUMIh9hLDNR6XALbI9ASKioN4tTI1GuS2FuEJ9xAkli5HhUqSFhQEjobMbaMIagdeKysBVJ8xTIfUjEWcBFHzk0JZCeUfmbMBCCLEkbiGZHX0hDk9bqqyhPTkVIWCs+bWYxtOXYFhtfDQw6IfHUU08pjuvq6lBXV4fKykqRkFCju7sbp0/zHu+XLFmiue7z+cTfx44dQzwex5/+9Cc4HA787ne/w8GDB/Hiiy+iq6tLJESEsJ87duzAunXr4HK5MH36dCxcuBDLli1LKuznUIWwWMhilYIA53TrZRB/GkV5SBl69fONEH95ErOT6O5RELadNPGvyZyuufCnlk7MqjESOmg0DIRdTnMNCTqBgh+jXdEWdHIhFKe0etPJTDhtNK7mtBH5WF2m7q48RYQLMAzciewuYyMNTT5XIp9bXE0bZSAUYXbdshQof55Tq1svfZwB1offQ25wNj7t3KFNx0nphTwet7T6XXV6HY4FT+HCwkkY7ikBALhKT8PVF5UymviQ8NQ0INgxEmC1ny8HwyiEm+2+PdpO6MKYWooRVo4MMaUx1KSNflsYxUJMq/DAJf5IF7xuh+jVnWEAHyE0qxzZHrqWJ+VDQn1CL6EOjARi+bshvy2CLXsoEW3BObwZp0vaED9xIdQKoVZfrz//owXtPXTe7s3AyT69HAfsOOTHR/W9AICNDX3o6Y/hy2NBuJy8EHn5JJ3IYYJTS6iEfwKp9pc1rWlpOw1au/n3+Zn32/DzeSOQl+WU+YkAghEWL6xtw+2XlaK8yK24JkAgJEgq56RbJ4QcTAUsx+Hh106my02SiEA4jhfXtWP+FaUYVmC0zgF8/hiK8zKzNBdJHieTViHvzc+ksX9vZzdunllMnfdEh37UJDOY9WFlGp4JI3zweTc27+ejajW1hsGyHBwOBvVHlBGa3t7YiaoyL0YP86D2vTYML3SJYxSRRaL5orEf08fmauqhvVefNfRpztEQ0/LyX/qoHUdbw+Jxi490f7QvLJEkTNN7ZPuQ+Gpg0AmJAwcOAADWrVuHxYsXY/ny5ZooG4JmhIBRo0aJ+QTU1tbiiSeewMMPP4z58+eL5wOBAILBIO6880489NBD4nmGYfD8889j//79OO+883DllVeisrISkUgEjz/+OCZOnIj6+no89NBDcLlcSYX9HKphYDwnTuHm9j5MCETAjfcgcN51cPa1ITj+KgBA38zvIOvwBgQm8iYwXFaBmFcxv6gmG9adBTa3VHHOf8E8cO4sAEDv7AUo2PySeC1UdRGymiWhJnDuNfCe2EVutGxmuyCWjZ6uflxSdA5YAGxOMQITrkZkxGQx7by2XowK0Swek5voSE4WjYofrgjtaOELwTgUO9+0u4aaa4nx62R57aE+pz7RYdo63a+M9nySCh2EKkkaEvoIVc1APL8MoOARZ4Qd6I/04pKKEQotH4U2EKNcFXMApoed6Iv04EpfAMj2pH03JlnSIJm8tOj3sOjhuvBB+0Z0Rro11zVhgRngO1cNEw8P9h8FAGz27cKtFdeK56dfIAtdSVADGlOuNJlz5PaA7SvVpAMAToiYywB1XVrSRJmY8MzqqJr0B+k8t5ktwqz4kKC1HQaAC8fm4orJ+Vi6OhG7nmHQIbtHk6uz8eUhZZ5Z5+aj6aB52UYEoW4egS/WTaHRSVLAaOdQabIhJQyqQux5xjQgDPDhTWMSYX39hYX6hesgXWQEoO4xh9XblcTRl8f4eVrY0dYIGoxAqOcpSQABAABJREFUWAuklKp8goaEQBIk18bkse94EBePzxOPGQZoPB1Ce08Mn+7pxR1XlEr29PL7KnuPBYwp96KpNYzKUprNB+sQwpSmW/7Zf4Lv72cNfbh1Vonmen62Uwx9uP2QH1+fXpTeBiQgmBLQRIFIFjsP91siJNSwMvakOUKev7k9ebKDBgIZISAc45DtYbD1oPL8nmNB7DkWxLgR/Fq4vSeGHkKIzXe2+oiEBC3E0JtGRDaMvytyMgKASJTKYea7w+U0fr7Emd/Cvd65cyd9YhtnJAadkEgH1qxZgyeffBLz589XkBEA75QSAG666SbF+W9961t4/vnnsXPnTpx33nnwer145plncN9992Hx4sUAeF8Vv/jFL1BbW4ucnBzL7ZoyZcqQ9D3R6/Ahdy+/4PEBCNfMVFyPlVTBP/PbxLwOANFhY+HuaISkjs8jWn4u4FDq6kUrzhN/xwuVjkRjJVWAjJCAOwux/DK4+oylSLZyKr5+qA7BIgdCAMAwCJ8zW0rAMJjZa51AIiFSfh48rfuTXqEI8s74gOzDqLMYYBhGTC+F/SQGWiXXZXDNwSjvS2yAQ96RjESM/A2orxkRQKSeBCddr7hnRnoaLjhwfVc/+kc6EYGO4Y9DrYPKwAkGX+/iBem4QjvB+FlhOA4cw1BEpJBpLxmWqNdGc+iZQQht1IOe5ouL4NlLb7dPXne2x8h0jMGYci+CqnN6kEw2dJOQYWLzQlrEkVzF0BISNHdV7r1eoyChyn/pxDzFWKt9aFw6MR9fHlIulIcXuXDUtBV02jqFOU70BKQ3Qc+HxISRWTh4SjY/6xRtFEqQ5PzQqCz5WOdmOTD7vHx09qWPYLAM+WuSivAr8yGhUFXnlH9Nm2Mi2KUCUhQC6SL/RxAs5c8ZKX2OV2ZumgFkynme3IyMhMIciZDIJIT+WXIhMYR3p4dy20hIdtlltZ9mqVkVt25UfIwwD0trJEZ7EkBxnlNMQWxNEmGJZ8yYQZl64BEOh4fsBvSZhEElJNra2rB8+XLU19ejvr4eALBv3z6NhoQaLMti1apVWLt2LXbt2gWfz4fc3FxUVFQgEonA45HYc4FI0DP/6O2V2L9x48Zh3rx5ePXVV9Ha2oqSkhJ0dHSgq6vrrAr7aRhLjgri6oF01no5VLDSZgOVb9munXw3nKpaxXlKDYkkISwu02eyoUwVZwxsqykHJQXfg6bQkg6y8Sbs/pELIX8sDdPJkkrjwIBTETo6zijMWmQK62+mjAiREzAmg2NGdbg4IJpEd9wpeg6neN14GDx8kq16aveD4+jnN+V9I2ldEDR8DO8RB4Ax9F6ve0VH6LCg2KRNQlOWzARBnkaPvNLTRBGQTChB3a7I6iKZBww0krFzF8w3AEj9cQhhPzklySH8HQICmxjhKXFMei9JrTQiBzLVr0wNl2mIxwF6GAUNCcbg+y9iCDw7ZiC1cCi3OtkhTeVWkPKqv71G/pmIhARh10aeisDTq+qzhjPgUbSRBgwqIdHU1IRly5ahuroalZWVOHLkCFW+YDCIBx98EOPHj4ff70dVVRWmT5+OpUuXYtu2bXjppZfEtOPHjwcAzJ49G3PnzhXPnzhxAn/84x9RUiKpzz366KN4+eWXccMNN+AHP/gBGhsbsWzZMnAch9mzZTvwZzgUC4Kk+AiB3VRqSCRbjs5F5WEycfVIl3TqsdoHq/Ojonw9DQl5uXKTjRTqFeBAGjUkdLKSZERR+CKmt9IGaxoS+rnVFxioP59CWxW0FkFDItOgEaiTcWQph94r6OQ4RElvC2P8vrg0Cx3D2k3bp5vTgJDQ3wVMbbDIG7zapZfZ7iOVU8vEZKBYDKrKVTv1Vb9rDMMoFpp6j5NV56m0acRyk3xVUgolaADSYnqgQYqyYQang9EKB7omGxZ3VAdEQyJxLL8m1CUTlMX6CWUJ5zKlyZBpomOAFRM1YGXtMOsqp/qrvJg5CdFKycTn4CwUXtO92aceN6PbGTXQVNOtkzK8GrUGF2ULbJzZGNSwn5MnT8aWLVvw4Ycf4rrrrtNNpw776Xa78fjjj6O9vR01NTV466238Pvf/x6LFy/G5s2bsXXrVjHtpZdeCgDo6enBLbfcIv7f2toKhmEwa9YsAEBrayteeeUVzJs3D0899RTuuusu/PznP0dZWRkAKIiLMx5Mqrc9XVtMpGmGXKhZXAhlEUZpJQFCXrt++ToiNeVuNPmS+TaJFGVDRUgkq/Kn0ZBI5eYlBCBN5wg7w0L9hFKMNkDVZcuFPEHQSUVDQ1G8TiQThe8OCnMI2o+m2e5BsrCiXWF23a1aKejfWXU+4Zf5G2vFP4L2cTXSkNAKN3SVGC7BqcNQUptsUHTf0GRD7ShAVbHaGSC19glFGiMSQ6shYQbyuBtqh+hdouiLqH1mnjRj4DjIJHW6PApv+aL3WJnJhny+Uj0aSbcxDSCNs4ZAIaQlRlDglH9JZaWCjGtIUKTN5HOpMB1JQs4cajDzZXC2IN3PpcZkwyBtNKb/HuqdM9WQsNifoaDpZSPzGFQNiby8vKTCfkYiESxZskQT9tPl4ruzadMm0exj2DDeoVpDQwN+/OMfY/bs2di9ezfeffdd3H333aIpRn19PeLxOHp7e/HGG2+gr68PK1euFE06PvjgA0yZMiXDIzJAUKxUk/j8ibOZckFlecqwksGCdEGz8y6mSJpb4XR+U4BCQ0KgSxiCM8VkwDAOReaYQYcHaqFu6fYbaUhQFKTn18Fog0WRh0JDQhR0TNpDO740O9fKBiTzdJDzuJLsg6AhQdNymjCeUn0a9QBdSBoSSS7/GfI1Ixt4xSmSSrqcwKSSQ/mrxiYbZNJIdD+jJhFSUYqiUEtS90vPh4QE48lXvWhW5NQZFn3SRRqtobBbzcGYrCXBqfgUCN8HTlOevMzUdiDTIwSoTTaI5LSJgKO9ZvL2cFxSJluD5UNioB5FhYaESdp0kFpJwUKFZNJq8IRXK/fRCiFvXYCX/ZadF9qnqdug/AiJkCBkUNST5gfa5iO+Ghh0p5aZCPt59OhRzTmPx4OPPvoIH330EdxuN26//Xb8x3/8h3g9EuGdDu7duxcbNmxAdnY2Zs2ahccffxxz585FQ0NDsl0cckjVtlrc22ZUqsIWizVz/meKVLbJhCJos6irIrDBtG3R7bUYu52Dj004fWMcCt8AxrXpX1MLdKmYbAh73zT320ibgbVAipAICSsCrXFNSj5fKFWx/idpFens2qfrW2yVkLCSWkjbHw8iB9qQgmrTCzXiOvotbgsrekv3T6MeQL9Dr1sG3wi9A7NDRZEK7RQzDQnjywrIHTuqy1WbbKgLZhiGapFIpSGhKpyURXzXVaSUud28cMOsaEgorzkYM2FyaK1ou/2SQ83ufjrnmizpM5DQkOj2x1CUKy3n0rGAT9eIBcJxRGKsWGAgrHXeSHpnySQFp3tNkQ7W5+GeQAz7j6fHGbYa4ahAIOkksDKBpACB5DMzK4vGOLT4+KgsvYHMO9uUg7Nw96wSWbQIR1lE4xzysqw7ijZCr8xxqRXyqydAniNYjkNrdxQuB4PhhTrhZAn1WNGQIDlbFcY4GGbFUKf0a2KIz9ZZoKRjI40YdEIiXWE/AWDhwoXYs2cPHnnkEfGcw+HA5Zdfjjlz5qCsrAzHjh3D888/j3feeQdz587FRRddBAAYM2YMAODuu+/GPffcI+bfsGEDAN4Bp1UMVa+r7tNHIQbhovz4VUTiaPEkJmeHcuITl71GW1oyxPJ5MxjSlyM27By4+lrBelShj6w44jQwSVF48VZeIbe1pAqeln1gc1Mz2VGUbjLmG31fYGPsVCKt0mRjQiCMFq8LDqtfXYJTS5q1EUVR0vkoaTHHLy7ImghGBIq6TunMuQH+Y3YOm41mZxiFMfMFk5C7KhTFRgAjhDCsDGRbuVKLAVg22QBLF1aPSay3TMdZ9tsq9Wb6VicKfOHku/jVuO/rXdaeTxRMCvkJAFaWb6SdrOGFbkATSp1DRZEbhxXnlD0syXOhKyHklRbwn7Waci+UXolo1T509ouNssuaQ1rsjyiRHC2rbep1y+OAihL98Ibq8VNXy7fDfJ4YU+7FwZPSu1td5sGxNmW4PJrPxITKLGw54BcjpjAqwtocyraOr8zCflWKUaV81KosWVSW0cM8aPFFwRrZOssaMRScWj7zfhvGVvB92XUkQJVHDOkHQE3iLP+4Az+4vky6Kvh5SmHFn65dyfc/78HnRwJieS9/1IHbLuW/p+oIHHLii7j7Tdk2LglG4om/tVjLYAHr9/Catvp+XAYGws44/27qD+LrdR1oSoR/rG8K4JsXFcHrHlQLbyIy5ftk6d9b4A+x+O3do3TTHD5FJq9ITiAFtMlC71IulwEAPn8ccZZTmm0B2NjQJ4blfPAOKYqd2RCoNSQaTydPxH2ypxfXTisEad9M73kXwxhT3iyWs8N+fhUw6IREulBbW4tNmzbh4YcfRn6+tOM3cuRIPP/884q03/zmN3HjjTfi8ccfx+uvvw6A92cxbdo01NbWYtiwYZg5cyYaGxvx0EMPwe12IxSy/sIO1bCf/n1htNVby/PDln7EYmH0T/5GIuQnoPmMUkwu3Vf/GziXsMjWpg9OuBKhqhngsrS7ttSQzYLh0dPhPf6FNon4y7jN4dEXIjp8HNjsQtUVuomUvAusp7bJC+5HAydlJ6VFwIT+MG7o7MdVvgAcAgfklcZJb9N4Zk8QzDAnygIxtHldibRakqAyFMXJLDfYrAKTXumQN6U1cPnbESk/F+7Wg2B0KIexgSgac9zEkYnll6H7/JsROr0ViDchO87iJ8e70FcpfWxvaelEL4CvcYWYdfQwimIsfNf9HAwbA5pXKMrLi8XhdzkRHDMLPcMnYdpny1B1tAPFMbnZkbKVqn1n6N9rlZQTj4mner72I7g7jgAR7bOnzm2mMQMA8fwyoFUbD1xB0yneP2WpF/cEsb0wW7ctarA6K4mCHCcA/R1ddQQUo7eE9G5UlnowvM+FTlkVC64bjurCLBySc8Kqh/2H3ywTbV1Hlnhw3y0VKMxx4uNGpABlHeodrUsm5BEXXOpzd19ZigmV2bLrSk0cMjiMKvVg0mj5PVM/p6rBJrRDYderMz/MOjcPY0dkIRBike11oDDHqSmSJsrGnOmFuHRiPnITu4pSSFQ9cUtVi4wB/PdbRyA3y4H9MkbpvlsqRC2A3Cwn7r2pHLE4h9J8N/6w8pRxVbK6xPdbJ/GYci/uvnIYvjjSjzU7uvUKTBnBSBJhRBJgVFE2AH5XV4DA0ZppIXndjCJdUa4T3f3p3xFv647KQgFqITclEEBcTnAG184A0ITbzCQ5IdeQMBrDxpaw4jgW5+DV2YBPqT0p3kgj0ioV+EPm7+ZpX0RzjgN9n6z2nZS8uV1qg4IIIf8kpwXQ2k23mUJqS1NLGJhGNg0xLYcyHQM77OdXAWcFIbFmzRo8+eSTmD9/PubPn2+avry8HDfeeCPefPNNBINBZGfzi76lS5fivvvuwwMPPAAAcDqdWLBgAbZv3y6adJwNUPsloIGHBbJYDn05JQDXKBSkSmU+iXNemeYDUVZ3gMsmCMRJRtngXHSEkK56PMMQyAhA3njDlhGlTuO+KO3NnWLqwhgLB4AcmWTEenPBcNKzGc8qhDPUoyivKBYHxzAojcZFQoIEj6AO680FEDRsI7HdibGO5w2Hs7cFzmAPMV1OYlVEMtngXF5wWXmAwwXEeY2GkhiLYOKZzYmz4i68AwyKBGLB5QEH7W5ybpyD3wVwriywecMBQEZGJMAofwij6zDdUVe/R7L7klOMeN4woIuQzbhUWTrZc+wk3zeHrIlGOkQlKi0Sq4teNruIr4966jA3OGF1xle9C5SfLdxx/fvhcTngkQ2RXH2dHsZb58J7mZftgD/IJsgZbRa1oKtui6SIYfx8FeQqBTityYayRPV1tb26vskGg7JCN0Ca5nTykopyOhjimOg+BwYPiLwcAepxHFYgSUimnwczQVeGvGwn3C4GRbnpVddWIy3+Chj5t0I6LZq7mNThcioHrqzQLRIS6Rb69ezaFddkzSGq44t/Tei8IUpY6JFgA+XPRNKQAFIR3dM1vKlqOGQyOowZ9MIS09ZvRUNCD3K/MlbmE3XbLfuoMLluXTvOho1BJiTa2tqwfPly1NfXo76e37Lft2+fxmRDDZZlsWrVKqxduxa7du2Cz+dDbm4uKioqEIlE4PEoBZO2tjb88Y9/xKZNm9DZ2Yny8nIMHz4cLMuit7dXJCTKysowZ84ctLW1oaWlBaWlpcjKysKpU6eGNDtnGamGfFStHqQFttUZ1sosaEXx18hpp7RM5mC+sKGBccsIE7OBnj3HMGBlxA4jM9kgZ+NMnXhyAMA4TAVs8aoJYaVrvk8IH0DiY0w1AwhwJdoUz8AXTq3HQYqyQRx9jYTIqUwxUmysWQw8GJAmpoObmVWboHdDU7qe8zGNsDJQFqTSREZsiKTqz4jpSa+eZhdUR7uA9hbphegzc97GKObq1KChl2h2ek3UdoUOirv9KcSwdZiooCs0JIaItJpSMxjV2EEpkAg7oLRVDISjT45wIH4LCM5wjTQkMuV8MtMY7LCf0n0eGqJiqkK5kZ+RTINN8SFMRzvl5L18LM1KVmtIpKStIXzP5Btpmh8U5STZFhtnD9JCSHz55Zfo6enBRRddZMlEoampCcuWLUN1dTUqKytx5MgR80wAgsEgHnzwQYwfPx5+vx9VVVWYPn06li5dim3btuGll14S0wYCAdx5550IBAL49re/jYqKCjQ0NOC1114DABQWSttCjz76KF5++WXccMMN+P73v4/GxkbU1tYiHo9j9uzZ1P0a8kgp7Kds4acRyCx+XSxNPElqSKh3CRV/U5j4KNsuhZgzV2gTFv3yCZlTRcdIph08IUHvItE8pd5Wq4OqTaK5CVV4Vh6CnkjSzjiN8pl6PtehgtTvkarfekQRk/CrwVh4/vVIIIWGBGlBoAOro6h2WGhWLhUhkcr7l4LwqipI9ltdpoqoMhDajMJ+mvATujBbmOlF2RBgppZtBTQaEnp5qJ+1FO5pMtOCOaGTWaEt3YKTXEASCQmTKtTXTU0mUoFBeWSTDW0GUUPCRPgaqjKNnsmG5YhKSYLWqeVAYaiabNCA5CqC42j0hHmkg1STazjpjSVpjNSEBHU0nkT0GioyHMJzTblGNWjLEOHPbGQYlgiJ559/Htu3b0dtba147mc/+xnWrFkDABg9ejRWrFghhto0w+TJk7FlyxYUFxdjyZIlePbZZ4npmpubAQBVVVUAALfbjccffxyPPPIIampq8Oqrr6KwsBBVVVVYunQptm7dKmpZrF69GidPnsQzzzyDq666CgBw7NgxvPnmm4jFYmhvb8fo0aPR2tqKV155BfPmzcOjjz4KgNfE2Lx5Mw4fPowJEyZYGaqhjRTfbrX3AVoVZC0spJcvVMwWugMye8mEP8NuUOysq2BNQ0IpiJIScQzDa0jQDrdJ+/QXT4ysPcLvRBsI4j3NsAlpXBA0JDJxb8lbuYrxIlWrCcmq3uUzIzpSB6PzO1Mwe4Rod0b4svRK4yjTDSyEVliNokHjf0FbiDKGhvRGydsjvFzkCVEtUKcyjto+mHfC9FlIG6mkXgAb12UWztBsvk0XUhTFNGfkatiWNSQSf5VOn9P73tHw6kb0oDydqckG8Y0ZwjAgNNMJucnGUJhVjcxyaDCYJhtkDQmO3mTDqlYC4ZxCQ8JCcckSEnEWcOlYshGDwZlpSJiVY+MrBUuExD/+8Q9MmzZNPN68eTP+8Y9/4MYbb8S5556Lv/zlL3juuefw61//mqq8vLw8PP300wCAzz//HACwceNGBAIBFBQUiGE/FyxYAECKthGJRLBkyRL09vZi0aJFWL9+Pd8ZF9+dTZs2iYTEypUrAQAfffQR2tra0NzcLDqyBICsrCwAQH19PeLxODo7O7FixQpEo1GsXr1aDCG6fv36s8ZsI5WdH072JVPvAHMZ1JDgiKKX2ZIShl93TtYGyzvGGZg1JQ0J2Tg65FE2kvv68hoSDtM+SgJEcho00vNA2LWQ3xLdVPI0yta6UtLqMYHurpVZPq2ISAXKZDS7ZtQk0wDBilPLAVfNNBGAzUwHSGrl0rpLRkOZEXpieF/DZGYKG4QoGypCLY2CTVJFUdsRG487Daz0VXw2daqjJZ5SRTpMNuRQaEgIn5AhND8ofUgoVSI4wqCT1fn5hArhawj10Qx6QuNAUSdC/Wr/MmbI1LuQqtlDpsJ+0iBlHxJp2L9T+JCQFajrryVxH2OqymnbHGM5uJwMSHtgSfAR0tQvO2WbbHx1YYmQOHnyJObNmycef/TRRxg+fDgef/xxMAwDn8+Hjz/+mJqQAICnnnpKcVxXV4e6ujpUVlaKhIQa3d3dOH36NABgyZIlmusCiQAAc+bMwRdffIG3334bb7/9NvLz8zF+/Hg0NTXh6quvxvDhvKM7wWnlkSNHsG3bNrhcLkyfPh0vvvgivvvd76KhoYG6T0MeKQt38r072WEmfUgk6dRST2Ga0VxK/otrOadJMPKuaI8sqRPCOBE36SlbwxHEW/12JzkWhHiGpJIkkw36ouVPrFG4UH0Y5SFfcxA/sfJTGglRmdJU08QEFN2UaytZ0ZaQXw/Fw7rp1Bl0/YeooN6f5DgOW3z1ijQ7uiWv1Gs7NiHHmYUtvnq0R3yKdGta63BLxTWo79WGelajNdyBU6F2TMkfj6ePvkbXWFmr3WN3wZHVT7yqVitnNAfAyWArGj31cBSXgPVVJNIrB004dBhI0e7Kw+Bi06WyOX0NCUeOn1gG74A0PYu7ZAQScVFKqVLiyO0xTmdUBME+hFGUp1ys7+j+Eh2BfgAjQXpbjgVO4Z3+tWByZ4DrL0q6XUbo6NWPVmMFTJYfXCgPp32Sp/wvjvSjstSNghzjJV4kxmHtrh7Rgaf8Vq3bpbwf3f0xhYr454392HHIj+9/vQw06AtKjnWFUIV7jgbwrZnF4rPc1h0VwxsKnxF/kMXKTV0YXuiSNCRMHuv2nhia28OYfZ42WteJjjDaemKYfk4OXvu0E5WlHlw51SyyFB1YlsObn3XC6WBw88xiRXhaQOZsNA2IxFjUfdmHq6YWaJyT9gXj2HHIj6umFijeP0FoNXK5IoRPluN4ewTBCIsLzslFnOWwaR95zrGKk50EZ/EWhog0njsbyfO3HLE4h/V7evG1KfnwuJT3KBCmW8eS6uY4eqKh7ktNfGtDNLaEcN4o3t9dU2sI/iCr0JAgRQTadzyIAye0EQI1GhKUgx6Lc4BbeYvae6N4e1OXInRoc3uEiljgAPT0x7BR9jxtPaB9ts4gXScbKcASIREMBhU+IrZs2YJLL71UnPDGjh0r+magxYED/CJz3bp1WLx4MZYvX65xailoRggYNWqUmE+OhQsXYs+ePXjkkUfEc4sWLUJBQQF+//vfo7e3F93d3fj8888xf/58/Pa3vxXTjRkzBgBwxx134J577hHPb9iwAQDvGNMqhmoYGFdHE5IPqsnItzNk/wKxggprJWXMh4Q+4cLIf6WwNojnlgIU3xOyAEffF07u+4HYXloNCa3PAl39EjOnlrpXBKlV+qDf0MsiiDhqgtJi+aruIE55HJjs1wrC8YIRQiM0bZrkD+PCviCdioVO04wuqokO8w1bJU0SKygHAk2ydpErpb/75hRDOj7U6zu3UbfFbOGi157emB91XTsU5/zxgPg7wkbx19MfEPOeDrfjr6fI19R46fjfAAD98SBCrPL5uu6CQsXxHVeU4q0vpDAozuJ2xU0X3rw7Li8BAFw7rRD+YBwVxR74/P2JNIm0iR+vnPw74AS845sR3HaDIs2U6myU5rtQnOfCqFIPLp8szcIzJ+ShKNeJDYljV8UxXDvsKkV+NTQ+JFQJGVVo39Q2nqw/aeaRL5QN8k743HId6rrkVWZN3ixLoEz/UccWAMDo8lE43qrWNAFeP8Wboeacsw/9e4ag/yjZ2DmL2hBrycOGvdIHqbM3hpc/6sC9N5UbFhOLc9jY0IfyIj5iiXyYTnYqQwG+XteJi8fnicfvbuWJwwMnQ8jNsrbJ0RuQyInNB/pQWSo5Iu/qi2F4oVvxfO8+ys8VwwsTYatNnuVlH/DrtUsm5GmIv+c+bAcAVJd5cfBUCAdPhdJGSBw4GcL+hAB4wTk5GD9SGWq5OI+85E6G8Kv7sg+fNfQhP9uJS87NU2hMrdrchSMtYYwbkYXRw6U1u6Qhof/5fOWTDs251+o6AQAXnJOL/SesR+DSw4pPOzXnrExTXx7TtmVjg/nCbMchPz5r6APD8PO6HO/v7KaqW1fDilbbgOSEAjwhkuPVvk+v13Xit3ePAgC8/BF/jy6bKL2PR1q066k3NqjGV9gMSjLKhkDCyNOHIhz2HA1o0h5ro9jo4LRtFMhKBRhg586ddI20ccbCEiFRXl6OgwcPAuC1JQ4fPiyaUwBAb2+vJsLFQKG2thabNm3Cww8/jPx8pbhdUVGBadOm4Wtf+xpGjhyJHTt24P/+7/9QWFiIn/3sZwB4fxbTpk1DbW0thg0bhpkzZ6KxsREPPfQQ3G43QiEty2iGKVOmWHLyOVAINrlxeod5On2otgqFs5QhNjXl0MDCF9ss6oS8dhPZUR+yMIzGsq5Tk0bf2SHhnIwcIOaSO8DUaQKtyYZxRfI26SQgaEhUxIB7Tyh3vEtjLH6qOieAcynnD4nQYfDPLT2Jc2k237BwP+TQmCypn/8kyyWmNHimHRwHVuW01MrjHKfQbKLlgPTSpbovGOHUcdKNS4yx2l2+i8blKo4njc5GWZMb4j6wDgM1biRv1lde5MY9N5QTF6wuI5uBxKXbLysVT33/euWu8jcvKgLHcdjQKJ0ThEQ9mDkW45s0eBoSwu6d+U5Z6m00fz7JV7591TCs+LgHze3ksN65eTGY77cOBgg60ylAGQ6SjGiMIxKSqapYs6xKxVwQmgyKpXUIynJK2jiZMqwgrqM2X5rvQmdfLK1mVIJASxr/qHhNeV7SkNBvSDhq/D2Ixw0vi6TRQCCqI9SbQTBZIJmMJFsmkFhTpvxc0edP1vxa3UTqJlvoGo2mCAcOYfWnXQdD2WQ+HA4P2Q3oMwmWZo6rr74aK1asQDweR319PTwej+goEgAOHTqEyspK6vLSEfZz37596OrqQiQSwdSpUzF37lxF2p07d+KHP/wh3nrrLUycOBFr1qzBiy++CI/Hg2XLlmHu3Lk455xzAAB//OMfcffdd+OBBx4Q80+fPh0lJSWIRinfmjMBKYX9ZDSzV9KlZcxUzEg4YMQ/SgHOWi/odA3oyRGxUdqTqfsJYPTKNsqgD91dcpEoSEOAbbUVolEYg5SgP7imtEeKhIPpBrJBtBg5HJzW/MXK5rSVZ5963SLYhqfpXmkWeSbFsiQ/JoRzxsWYt13onp6jL7pS6OrQWAiZ1KOdqpOfSJIjJPi/erbW6fwACDbxujbpOu0fKg5TLUPRH4PvD2X3VLOtLqz6HqCBOhqM8NPIYSGtWjwrc7A80KDtE0CjC0dRH0UauYaEWRr9eowTDKQLgGSFf5LPklTL5DNncFlLgNnekB7U99AqH0E7Rmbt4J8187IG5w22MdCwtNW4ePFizJgxAytWrMChQ4fw4IMPihE1QqEQ1q5da0omyCGE/WxtbbVEZAhhP30+H2bPno14PI4RI0Zg7969CnMLAHjjjTdQVlaGiRMnIhQK4Q9/+ANycnLgcrnAcRx27dolpn3hhRdw8uRJXHHFFVi4cCFuv/127NmzB4cOHUJ1dTV1+4Y8ktphFmdwWTnqacLqVJwZDQla4ZVL0w4ijYYETQ5SSxgHvYaEHgQNCVpQiGE6pxNkj6JN6fo8p7pkMyepLORIJNDde0utXIu5BF8XlDKKNj/NuyUIfGbJEveeg67CQVJgLZJcadn9tFCE02CFTzt1WRWONelV9aRTeExFQyJutuOYhmaaRxwmXzDd3R+yK2G6Z4X6iRKJehOKLgPjwRNnBALR4N5kzHFgGiGvm5PNi0QMECMh+sFxGJkcpEY4DOSQkx2fmoOwmk0bUn/m6Ful99mxGu6XVsvJLEKRHDS9YFn6qCQ2zn5Y0pAoLCzEyy+/DL/fD6/XC7dbqVL6yiuvoKKC3o8AbdhPNdxuN1577TU4nU4sWLAA06ZNw4svvojnnntOE/azs7MT8YSO2bJly+DxeHDNNdeIfimEa6SwnwAwbNgw1NbWoqamhrpfQx1yIdd6ZujOdpbnlUHxISHtBaVJz8Ow48IOMdXkTFSQsBAdQ68NsnbQINldbdEHA8elYeWq3vLPkIYEJ7Vb/UQYtkfdDo60yDEmJMwJD3oNCUCt9UAPaxoSxu8sI6ZLL6wSDPTCfXqeJbVTuWSg32YGpBHV+JBQ50rja5JMUSIhoau1IO63JdUmRVGJv7pVMeTRJRshnAFQvOxGHyDK4oS/BjfaSNcgFaFC6+uEPzI22VC2Sw9GAmsmBCGl6cnAPlny2vTukyB4GpGVKRMOKXbbyrAlbS6UoVvDIfXnytrem87mlkVSibbNZpo+aph1Jc6mNxqUjTMbSUmmeXl5GjIiKysL5513HoqKiiyVU1xcbJquubkZzc3N4rHH40FhYSHuueceVFZWora2FllZWZgzZw4AoLFRMsStqalBa2sr3n//fTz33HP41a9+BbfbLZpgTJw4EYAU9vPGG28U87Isi927dwPgbYTOGqS0UpUtjtXCtuWZOEVCQlf/kX6PPx3LUaPaRH8HFNUQkzCMiQBLoyHBwNqrnuTzYRD2M1mQS8qQhoTV55dROrXUtFbvOaSWw8xJGA7SnTUmVHRLzojJRrqhNcEwWXARBfjMwVBDgrIMvUWk+FZZ3NXiHddJaVKZ65KxVXYmlMP0TTbSB4f4CqeXuBpooTLdoKblKG9v5jQkpGMjoUc4RSuIDmYIQaWGhPKvBgPUTIGgMSSezNqScQ0J+hJS5SMy8TwP5JxhtsTQZiBft+pDgjq9mckGe4YSwjYyAkMNiVOnTiVV6MiRI6nTPv300wCAzz/nPWxv3LgRgUAABQUFYthPwXGmoNXg9/uxaNEi9Pb2YtGiRVi/fj0AiA43g0HJ8+63v/1trFy5Ej/72c9QXl6OtrY2bN++HdFoFFdccQWmTJkCQAr7+eqrr6K5uRnRaBSrV68Ww30ePnw4maEYmkh32M+BgEKCSkVnIJ1q9OYg7mwbCJeExCYVGO1bycq18OU1VdvVNdkw1ZtOug0cUUMiXZ8yivJIfJjJOBntd+sUaVCpkYZEauNAI2wK99ysJuVIKvY9rTdMkdtafpYyBLFx1wXCVT+RIHQ4DaZUWmHebBFploMUZSNdSMlkYwD05oW+6ldFfhbPVMKBodSQsGrrbRqh1dK3iw5qHxI0Qg+1/GSQMBOPpbxIUvm6ZhKy30lbbFD0R3ReCv0xNPchYdYQ83akC0nfQ2FPTf9ScsVymdG80YMuIWF2D9UR12g1JCx0Tu2njYQ4R0canpmztA2rMCQkrrnmmqQWNfv27aNO+9RTTymO6+rqUFdXh8rKSpGQUKO7uxunT58GACxZskRz3efzib/POecc/Nd//Rd+/etfIxwO45FHHoHb7YbH48Gf/vQnMZ0Q9nP37t3YvHkzXC4Xpk+fjl/+8pf43e9+l1TYz6GL1DQk2OxiwHcCrJv3Pl8Y481e8lw5lkriPLmmaWL5ZXD1tcFKm+WCIuvN009HXaIWWQ4pGoRRy/JcfB8LFduEejkI5x0OQwE2njcMwyPt6PC44OY4xAvK4Ax2K9IUxOMW9QANPPQBYlnq8WMT95PNykc8txTOgA9w0FmFFSTGR/8ZkpkvJPP86vXfIetr4sOYxwJ+mYDJZhdqsnFON+RaJ2xuKQpc/LOWJ9xrhxO5cRb9GmmVr6ckGker14VsHb1ieYsL3HzkoOGRGNo90pgWxVj4XdpILnJtibKINuKEGbLjLOCWxiaeUwSgB6wJmSkSEqqdmJQFP0L2whz955QcOURbSEG2Ez5CSgDwuhiEoX10ChL15mU7xZ15vXB+AEBrIadHupQVunGyM0JwaqlML6hhF+c54fObuMK3CMMoIjrIcvMd1wsJyaTRyciwAhdau6Nwu/TIUulnUZ4Dgr7j2b4/Z3Uj0/AuE5TALFdEqptRzg/Cr32E8JKmmgYq6Do5Rea1J1idiBsDCc03mpWd1yNHUmws7Tuld28GwmRDzJVuRgKpE11WuqQ3LZtN11qTDbpKV2/vxr9cO5w6vZHmIMBH7onGKMo6u6dpGwkYSguLFy9O6y4LCQcOHAAArFu3DosXL8by5cs1jjEFzQgBo0aNEvMJqK2txRNPPIGHH34Y8+fPF8/H43G88MILuP322/HII48AAH79619j3bp1yMrKEtMJYT8PHz6M//zP/0xL2M+hGgbG2XMaVqNuM7Ifgck3IFpxHth8PnTdhKn/jHnBExhXcJ6lMiMjp4CJhcHEQogVjSam8V98N5x9bVYN66Q6Rl0Azp0N+D9T9MMB4aOsnelua+2Fc8xlKC4eq1tFmVcK4dd/yb8gxrJg2Dh+lJWNPpmcNLXgXJTuWYNJ/WGER05FZMQkRchQOYQPuZvlcEV3AKNCUXjPyZKcRKqa2j/lJkSH1eCbgS5MRQiuPKC//FxE2g4CfRsAAN853YNJ/WH4DYiB8nAM32npwbvDeaE3ml2AH6IUiEcQmDAZ4aoZ8LTuBxMJgM0pBtN/CGCBmCcHvbPni2MYGz4W/um3ITp8HMDGEPadQNax7XD62xErHIlw9UWIFY5EwcbnAACsNxfBc68F687GeRyHefDLniEV6SEnDkQTC17oCo+aJl5aOHounAaORKPDxsLd0Yjg2MsQKx4NzpurebZ+3JuNHv8pxHOKESutQXDc15DVtCWR/xxEys8Fl10g5osOGwv/tFswy+VB9d6PMKk/gm4AbE4JvuP34plC3jzMf8FcsN58MK3/AADMcY/GVE8RKrOOAuA1tPzTbwMTDSJWUg00fiK26cryy9A3swb/sn8NHk9EjJzjGYPZOSF8DJ6cnVQ8FT2Tp8Pdsh9c+yGxzHtO+LC9MBsAEM8qRP/51yLmbwTQrhmlq7v6keXMQjcXxcksNzwsi0XVdyDIAjj5FlinWyxXjsXHuxB0OrA7lw99Gik/F0zPEVFrhhT1wgrUTi0nV2XjhkllOqnJTjBJa6hZ5+XhWAu5jNHDvZhxzTCNf4hZ5+ahKM+FiaOyEGOBb11SjPNGZWny33VlKSJRDnlZJgSf0D6dMfr2VcPQ4ovA41IK9vL+3H5ZCbI8/PVFc8rQ0RtLlKnED64vQyDMYmcsC8fIkS6JKM5z4tZZxRhW4KI2wRg/Mkt3bO67pQLLWxwIcjD2gUCJW2YVY9qYHDQcD+I4MYQnJ6YbU+HCMwnlz2Sey9svK8FbG7sU535wfRk+2d2LiaOzMKzAjeI8F1q7IwAYvLq+AwBw2aR8OB1A3Zd9luvUIM0+JMSiTLW+dITIVMyBoPYhwf/1urVtkfxLUAq9RhoSGTYlUphsiH9TF8L1QFMEp7OWsNKWdJErcl+3C64djtXbfeK8RYuknVrKNEU015IrUlM2ALhdDJ3ArdOColwnuvv1yWW999XrNmbBNUQVZRObWsPE/HooynUZtt8M8y4twcpNXeDAR0y0cXbDkJD4yU9+MlDtSAlr1qzBk08+ifnz5yvICICPsnHixAm88MILpuUsXboU9913nxj2U3CauX37dtGkwwqmTJkCr9drOV+mEW45gpObAdabn0RuBnC6ES0bL57h8odhfP6wJIpiEK6+yDAJ58lBrLTGYsGyyZhhECseDfgT5SU+QQ4wSpFFNq9f3BeCbyR9tBhHTjHibl7gK0j8LxbrcGBKPz+JB86/2bAcYVf52q5+XNUdAAD4ZB8cBkA8qwDOUC8AIDLqfACAK6sAYwAIgWmj5eeKhIRQN5xKny9yjIjEMDwahzPxIY0DKKyaBQDiTmKk8nwxvauJ99ESyS5AvHCErLMMXzcAOJyIDR8LHNsOAAiOu4I/liEw8XpEKyQSa7zsmvozyxEIFSaxGokVSiZicqJImTihPp5XCndHIziXF7Fh5yiuCSutfM6BklAUfTOuR2z4OYpioqU1iIyerjkHdxYcAKb0y+YJhoFr+HlAZA+fruxcfru8lb8cr5yGMUXVCHnKRMIsOny8tKWeaFcZ64SLcSJWUgXu/NuAlnfgYVlcWHUtov52oOUdAIC3+hKw7lyEz5nNR95geXOzPNlqg/XmITJyCrimk/yNhnKsq0JRjJx+Fz5pehcAcH1nPwomFCEa6eeHSGcpMjrMLyT3JAgJ1pODeHYRgJBhPlqod2Qum5RvKOjTakgYOaN0ORicU6EVph0OBpNG8++72wlcOJas6XVuZbZu2STo7TrleB3EdsjHdEq1pFmUl+1EXrZTTAXZr8pSXrNr72kHiVfSBcMwuOAcc402OVxORndsinJd/GOeJkUOj8uBCZXZ2Nus3VWXY/o5uQizUsflY1413INmFZlBem7zs7XPXWWpB9+5WvkNLMhR3v85FxRi33Hj9pmhIMeJ3kActOZQRm9dlptBKJoQzGThsI2gH5nBOJ8RHDoRH2KE6CxDXkNCViSp/IxqSlCULQyHUVIhTbbHgWCEQOya+l0xb4e6ETXlXsyckIc1O7opM9PXNXNCHrYd9IPjOI0ATxToU7hHHJRRIyaOysbuowFrZcjy62p8JZBJ85505OfAobrMg2Nt1uUngNeuE0y6ZsyYkVQZA4FwODxkN6DPJFiKspFutLW1Yfny5aivr0d9fT0A3tzDLHQoy7JYtWoV1q5di127dsHn8yE3NxcVFRWIRCLwePhFVyQSwR//+Edce+21+MUvfiE6rszJyUE0GsWJEyeQk5ODkpISAEBxcTFmzpyJkydPorOzExUVFaioqMCpU6eG9MtgGaLa9VmqB6Uxptb+doAhR7VIAg4zEwdKSNEelJDUaZO/X5yOVoYcLkHTwURKcCZaFE/1+TFa/aovyQkVIR+b2E1xmI+/tqUk/wzqVCb9sxAuU14NhdsCxQGnn0CxMpD7OkjWUSUDqMxslOXQbkhx6r9pVgM2WxTT+pAwRma1A9Ww7CeDIr161IYmBqBdMi0CpXkAJ1ZP60chpSBVKT5S2m+DiUaDwdDywphASJDLHwgwDNkBJImQEAVqWkJiMDUkZOWbRj1IQ33E+UN1StEm0++bbkVpgb62DT1oSCXJ4a1m7yHl+kmZ0+mbJFltFav5MkGUWVmDmBRk4yuCpAmJ/v5+9PX1gSXM6rROLZuamrBs2TJUV1ejsrISR44cocoXDAbx4IMPYvz48fD7/aiqqsL06dOxdOlSbNu2DS+99BIAIBQKwefz4d1331XkF8wvrr32Wnzzm9/EE088AQC4//778fHHH+P222/HpEmTUF9fj//v//v/AACzZ8+matuZgJTMcDJswpMWaNqobbMDauFq8MdE+CYoiAeKvlCV7dDXkBDgSlQbN/k6uRKEVmwABAlRoJUTKsJuHssTJxwFIWFMfqhWKdT3U4/IkBctl14S7TYcNhmpILZDvz2MgpBQagYZ10K+zoA81gJow36qf6eqIWFVtZ5ESAxVcVyAZcVemlXkEHbamAn/DVSO/WQzv7wNRqEQ5aBNR0LaoiEzgso5k7TJC4ErTV5DIqkWCHUzWpIIQJzAi5M0JEjvgRC5w5CQkNeZpvdEEdVG3kbCOVVGEekwk9YrQugzx3GmNy1ZPoJaQYJiLJIuQwbx806oIt3LWU7VpmTKJz03RvVZOS/VkRpVTe8EM7X5EhwMHbDaOLtgmZD4xz/+gb/85S+K0Jpq0Dq1nDx5MrZs2YLi4mIsWbIEzz77LDGdEPKzqqoKAOB2u/H444/jkUceQU1NDV599VUUFhaiqqoKS5cuxdatW3HJJZcgOzsbl19+ObZs2YLf/OY3KCvjbY5ffPFF7Ny5E1OnTsX3vvc9AHzYz3Xr1uEnP/kJ7r33XgDA/PnzsX37dpw4ceKsIiSSilIgfMjS35okYNJ+A8d7giDGJDQk0rMoTu9XTV9DIgVQaEhIJhvGW0dp05AwhKq3pF37BCFB5ziTsCqBcEp4JjhlWloNCYOvs5EDTjFXkv5R+EKke+VIMqC3hkQg+esQqrNQljLfwM4cZs+wAKNWZdp/khrpDlmpLd9S8oxD7O9ADLNMaNcTRMna29pBS0lDIvmsqoL4djlMwjkbPVOkwEWmhITlC+bQi7IRI7AJln1IGJpsyMulKs4SWIJkqS9Apt4AuigbKVeTNh8T6nTJTLdWNSTUdZOqTN2cwXhOMc2ve2CamtgGOXR1QS1/eyiQhoUrB4FcHGIfLxsZgSVCYt26dfjZz36GmpoazJ8/H6+//jpuuukmxONxrFu3Dueeey6uuuoq6vLy8vKSCvsZiUSwZMkSTdhPl4vvzqZNm3DJJZfA7Xajra0NU6dOxd13363oR319Pfbt2ydG1xDqb2xsxIoVK8Swn0I0jy1btqCmpsbKcA1dpBSecQhpSOju1ljXkEipV+nWkFB/qNNRNoXQLmhIxEwJiYSGRMoNM9j5VwvCjuQ0JLRCP+Gh0WhI6CdVli1oPBgt+i0OEjG8qQSNpoCOhoSZuqTuVU451hJZI5iPGJEv5N+qZqYFZsWlw2RjoGc660KJefqhvIwbrLbJnw35mNPe78HUkNBmZwyjlRgSbvLfDOksPVLSkGDIcwfRh4Twl2J3nwO9yUa6nkV5u4jlD/ILKRA0HEVTMs3HpkFBgsrsRvgGE5+ZDPQxnbc4aZMNi+Va/T7TEATCO5gGfZ+US7BxZsASIfH8889j7NixWLlyJfr7+/H666/jtttuw+zZs3Hw4EHcdddd+OEPf2ipAZkI+3n06FHxdyQSEX1EqBGNRnHo0CFMnz5ddFq5f/9+fPLJJ2LYzz/84Q/493//dzQ0NFjq15CGSeg+47zpa0bGYORDIgHeh0S6OpNukw2DWpKtyoIPCVOTjYTga5bOFBb6QvSBYcGHhNbyhWBcoOoP0WcHUR/TYBwIBIMmlyX7Yn0NCQUJYfpsS9cP+I/KznK8xgkbB+DUpD8Ng2hDDAOHXJOKYdDtYrCp6wv0x1Nz5qdGfyyA5uBpVGVLTlW3+OrF38eCpzR59vYdRrG7ABXeYdjvb0JXtBtlHh0nqAD2+5twUagNlVll6Ij40BQ4gSn545Ht5B1MchyHg/1HMT63GqdC7WgMNBPLiXNxNPYfx4S8Gs01X6QHYTaKiiyyU+B9fY0o9w5DiadQc+1MD1kpRhWq2od4h7mZJ8kpnRoxRxCOPB9Yf7HivCO3B2zPcEW9ANAS7gCHYsAdQjirD0A+WBh7+reqiOQo6ATbzzuQTtWuWuo+Bwbq+BRaNLWE9S/KmnKiI6I+RYTeVNXii5IvUIBhyIJlKj4khHTqHXR/MC5LI10zcoZ64GQQY8q9mig3avQF4/h4dy+xfOFnbyCO5vYwqoYrnZ0rPiuGtQANx4MYlq/8HsZZDlv2+4lpa8q9YDkO2w/2i1ES4nEO4aj1+WPrAT++ONJvmEZ9bxpPh+BxMRit6vOxNoNnU4ZojMORFvJ35zTFcydoNPH3g8Gprgjqm3hHk5/t7cMVk/IV88qRVqmu1u4oyouU5q7+UByf7ulFR6+2brWZUDJLzJOdEZQVuVGS50KXXzsXNZ6W2qcX8WjHoX6U5uuv+eRlAMCBk/RRBH3+GA5SpO8JxHG8PYKRJebmwrrgJPMrG2c/LBESBw4cwI9+9CN4vV4Eg/wELviQmDBhAu644w48++yzuO666yyVCaQe9hMAFi5ciD179ojhPQFgzJgx+OKLLxAIBJCTw3sif+yxx3D06FF88cUXaGtrE9MBwL333osbb7xRzP/6668DgJjOCoaq11VHfxcKAUtvOcdIxg5DHgZ+F4QPj6ghwWnT0GJifxhHs9zp20pIUMrquyJugHFAuPpieI/tAOfNoy6WdWcDYHBBXxifF/Ce32f1BFAV4j92F/TxH5fz/SFsLMpBjcM4+kqlMxeIAefHtZ7/rcF83ITII3LSIVTDzw/hURfA3XUM8bzhuvkv6wlgVVkB8h18vyMV5yHr2HZl5BYVsUA0szC8x7T7kMozcsHowt6geG8E5Cem51lx6V67Ew5Ur/bxCyo2txjoFJqoryExoT+CD0qBczk+6kEXpMWgPx6Q5QPAOMDEwgBywLD0YdhC464AfLymmXwHZUNX+sN1rWpZBwD41bjvAwCOBU7h087thnnWd26zXM8rJ97Fr8Z9H883vw0AOOg/im+P4qPlHOhvwjstH+PK0osN697QuRNbu3dj/shvoCanUnHt2ea/iv1QEwzBeAjvtn6CUk8Rvl91u6ZcOrV1mVA0yARGRWJheoEq8gbj4FA6eR+s+aIn41jJR/AOiyC4/euK886iNsROjQOg1JB4r20DSrlvIWvyZnR6wsDRG9DjbFXkdTiUAnNuFj2hH2Vj8J63Hay/EMA5aflUzBiXi/oQ4OBYuFh1xA0l5AKyGvI5QhBsjNrHJf4jYd2uHsM2G4H3ISHTWuGENhE0JBLn6E02lMfPr20jXlu5SRnGVY7XPu3EtDE5mDubvLElYMmq07p1C83detCPrQf9+O3do4wbroNonMObGzqRn+3E5Crpe7FpXx8+2aO919sO+jFneiHqj/TjvZ3d4vnDp83JANKjIC9DH8p783+f8GFv1X1+va7TtD6hzs8bjUkQIwgaTUKrnn1fegYiMQ4HT4XEiEjRGKe4b39Z06pp91/WtKI/JCX62uR81O2VQvkqTDaSWFcK4/KLeSM010JRVhxPANi4Tz+E8Aefk9/JUJRFoxFRaYKn3tWJk62C8E6d6kqerCwrcvPLYs4O+/lVgCVCgmVZFBUVAQCysnhhpK9PeiHOOeccUYAfaNTW1mLTpk14+OGHkZ8vCVR33XUXPvnkE/z7v/87fvrTnyI7OxsrVqwQyQLBweWVV16JyspKPProo/B6vZg4cSLq6+vxxBNPwOVyiemsYKiG/Yz6WnB8g8VMNI4Dhwoo7N6FsJ+ka745v6Cq5l9O8xO+b4K15ulB+Hipo3/ITfHCo6cjXDOTukzfdT/nd7wZBmNyR+Gxw0rHsY8dlj7OFaWT8Njh3eifcrFhRMAiJguPHW5DuLIiOSGCalWeWES4s+C74UE4e/iPIOd0i/2PjpwM38jJhqVc6ByOSw4fR9/FbsQAxItHw3fDg8S6tASdmV6wXj55Eq3wwhB+3dHWhzva+uAbJ6XLghOPHW5DqGoUhP07h8Mh3jMfAM4jE+7IOtjw3fAgKt//HR473IbgmLEIAQjrmDSER89Q5I2WTdCWTYAwpsyOzxNnjLxnpB8hNvkFlhV0RLrF3/0x/q70xYwXy91R/htp1ka1GmyM43dzO2V1KtIbljb0UJjjUizu5cJtXmEIAZPIcCw40X+NbhoHX8i3LinEWp24ztq3nAPjke5NRYkL7cI1DvjPO6U2x1kOTgsqEoIDTSbbr25G0rh5ZjHyO/Kwsys1rTnSNKx3Tnw0M/HQqXZAjcwyUm2Gzy9pSJA0MC6flI/PGrRCHmmn2gxy0oRErshB2x+hnL6g0uNnT79+ZCyO49BtcF0XST5XVu/NjRcXKfOrCujqsz72cpB8SMgRCEsTBQ3RJScjCnOcuGZaoYKQEG71wuuGi5oYycAo7K2AaIw/cW5lFg6cDOHi8bnYfsj4e2TkVwWQhxa2jlTyqvH9rw9HQY4kdwzlSId22M/0wBIhUV5ejlOneFXYrKwslJaWYu/evbjhhhsAAEeOHEF2Nn3s9WTDfgLAyy+/jPfeew9Hjx5FX18fYrEYxo8fjzlz5ijSXXTRRbjiiivw6aef4pNPPgEAlJaW4r777sMf/vAH5ObyC3qv14s//elP+N73vofFixeL+b/+9a9jx44donbFWYFkvHKJhMRQ0pDQm1hV/SOo50thP7nE2RT6lSYNCcE3A2voAyMJnwSJ+20ejYLCBCEdSAjphiKruik08boM6zS6pqlMeZhUoeqykwGj+mtWZwrPiZhLzYZZK2eAnqAhBTPNA45yjtGENjU15TEf5SF9H6zaLVvKYIE0UBXLMAQ1tQSskBEkpPqlkPtyYSBozyV3l2kJCTky9TxxhANSXVbDfholIznN1Ot/MvdNXrwZIaFoqEFlej4TjErnzQis37mkn9VkHxKdClPV7DJbOsirtTpMGh/TkO6Rw5Ha55/0yOg6q0zUQ+ffxjhNKnOUMwVrcDUEbWa1jxkbZy8sERIXXnghNm/ejH/7t38DAFxzzTV4+eWX4fV6wXEcVqxYgauvvpq6vGTDfgJAQ0MDxo8fj3PPPRd//etfUVVVhZaWFtx9993429/+Jmpw+Hw+bNiwARUVFSKB8u///u+IJ2JKVVdXi2X++c9/Rk9PD66//nqMHDkSbW1t+Mc//gGGYRTpznRIu7ZWTDYSwuxQ4CPMJl2KSVnjQ2II9EuMXmGgIZHSF8503BJ/aR+LJMkBjnFQ7Owp1Swz6mFLz6klcSCIqwTzsuWnRD8LJvt9jOZHxpGuBflAmQcIfgXSFvPcAsQ6TWUNWkJCCdbEuSyd5/Ghu5SzHiWEo38QTUwPlOVqU5B/p450hf3kCQn+/6Q1JAjnzASaTNlyKzUkON26iGE/DQvWvxQn7ECncxZREhLGaWmHVY9Y0ESskGsEceb1pxNWH5FkQ83SQog+ZSbMA9aJG03bZeSPg0ntq0TSZNAjpBwy4T1VpLbETP93WLZvaOMshyVC4q677sK6desQCoWQlZWF+++/H7t378af/vQnAMD48ePxq1/9iro82rCfJPzP//wP6uvrsWDBAkybNg0vvvgi6urq8JOf/ATr168XtTbKysqwYcMGlJWVYd++fbj11lvhcDiwYcMGDB8+HGPHjgVADvsJ8E4x165di0mTJlG3beiDdgdYBmF3ncat8SCDM/IhIWpI8NBELVClH0g4ElRwXNX+9O3J0dLXZg9GiuND8dFSf8o5wi86qLQekk5rtJ1o1Cb9MTfvCaOqR6cdmvao82hBfu5T1BTCwL85XMK5X0qxzpMFZZXJakiYL46taUgMtg8JNRQRLijG0kr7Nc4ejSJRqLbnGdmWXLpHLF0Ldo7ju6SibS22hfJc0jXQg+QAkgS5UMlynDmBYtBykkq83iuaVEhKK/4uKAdYV0PCMPS0uZo+GZmbU+VjovZOZk4YWoOZyYaiXRaXt5poYFBqSKQyhKRbpncbacP2ZlqpM51PjNgOZuh9u2xkBpYIicmTJ+P8888Xj0tKSvDOO+9g//79cDqdGDt2LBwWzAHy8ugc8zU3897Lq6qqxHONjY245557UFlZidraWmRlZWHkSN5Tt9yvhcfjQVlZmaK8Y8eOYe3atbjvvvvE9gphP+UOLUOhEBobGzVlnvFIRkMiEQpQCLU4tEGnIQHoCGaDpC0hxJRX+5AQkJSGhEKWTcPXSpEsyY+E/EtjNY9VlUqqtWBiQaQJ+2mSOWUfEiYgjRPtLTKZh2OWB5KuYmG8B0xDQqp5QOojt8G4r4KwYL4TqCIkTDQk9EglVePOGqTrmTIjfozCaKaKNClISCYbKZVF0N7S42IJmglpA2esDSGHXCBLBE1IGkSTjeSL00AoPk6xZJK3xKgNuhoSRmVzXFIaEskIpg5Gpb1CodFhFnI25WBeJksH+XtglbfRWHBxXPo0JIjPv7GWBxWxm8mQFWl8gaTVD2NH2fiKwBIhccUVV+Dmm2/GrbfeiokTJ4rnzzvvvKQb8PTTTwOQCIGNGzciEAigoKBADPu5YMECAFK0Db/fj0WLFqG3txd33XUX/v73v6OjowNr1qyBw+FAaakUyq25uRk/+9nPcM011yAa5b29Pvfcc7jooovEcgGIYT+XLVuGadOmoa+vDytXrhTDi+7fvz/pPg45qMIPUkHUkEjNwdCAQC0EktTmVYSE8tMxOMKNM9HOuKr+1PQl6HfNRZjO/smMj7xMCtJSUwWNNoJB7UZ91/MhQahLKaukuN1gmt3CKsNi4XqEBIlAoSlPSiWpWw/EW8RxLMA4BslkI9EGM0KCUkvHsg+JM3yVZrirSwjxaaW/2pSUGhJMZh/cdJpsOJCYj5IlUHS0IYzOZYJo5MCphFj9ukjpDMs2SCM4BJRDT4MlmflF0EogER9ayCV0g1Q6RWl29mVl8CYbAzNXqO39adpLMntQpE1xnhOjbJhoFyRTF+lxETUkmNTedysmGwLSoSmYyrc0ExoSg6H8aGNwYImQGD16NF5++WUsX74c48ePx9y5c3HzzTdj2DByDHUaPPX/s/flcVKUZ/7fqu6es+ce5mC4bxiQQ0RBFBEkKF4Qg1kTWRKNZhfdVfe3SYyJG3aTEBOPJW4MC6tEgkSIMSjGg5CAKOESdDRcynAMwzAHc0/3dE8f9fujuu63qt6q7p6egfr6kemqet/nfd633qp6n+d9jtWrFce7d+/G7t27UVFRISok1GhraxMVBb/+9a81148cOYIbb7wRAJCTk4Pi4mJs3LgRbW1tAIAbbrgBzz77LNLS0sQ6QtrP3bt346233kJmZiauueYa3HLLLXj++edtpf3sqxB3T60s8DxCise+tAim+MJorvF/BLHrDV/fiYzriXHF6gmLcX6YOV1hs5dBZSERW0SY7J6Yg2LMKCwdhICgysCgKssKMnHNmXTNQsO4b3wKTrqytDCbCR5hl8die+5Y11y9tIigE/UTh0A0iPcaP8SXSmZje9PfAOgvYk/6ajAqewhO+WsB8KlJX7/wZ6Kg9VnH5zjcflRxTm4h8Vrde6j2nwMA3FY6FxNyRipSJX7QfAgcOHSEuzAkcyBcDIO3Gt5X0DvS8TkGZpSA4zic8J0GAHQE27C+5Y/4ysAvwevmAze/1bALQzIH4opcZfqgM/7z2Fz3DgCgyJOP+4dqU5ECfKrL9edeR2tImYZwYs5oLCqdAwDoiYYQMbAAEVxx5Pig5RAy2HRcV2Qebd3FApDvTMuEdvXtkh+zeRfxSfiwdM3g/eEqqYGroAE9J6ab8sO4Ivis43PkY6hpWRpwkVD8LhukcwbfztauCN491K45//sP9VNm0uCPe1sVx28dbMVXry9GoMe4Xy//pQkcgNqL+ulZNvyVT5E4Y0y2Jv3g+3+nt3o90xjExp1N+PrcAWjtCuO3Oy8iGuXw1euLUNcSwpv7WzV1hNc8yTXkeG23mN5xxphsxRz8a1UHpo/yYv+JTrz/907Mm5yL0w1BzByXg0IvOTC1uoUzDdI343xzj61sD3beqZEo0B2M4kebajFlRBamj5KyQNW19OCtA62485pC5GVL/RBXA7Ef//tuI/zBKJbPG4BhpelxpY2U0137bgO+Nlcrq/zhby14/+8duPfGYuw2mBOfnPJp0mWqn5fP6wLISo+t43iTVtt8/++7WpmDlNqVYaQsK9095qYwSdlvkvGSDPRz3bsDSlhSSGzevBlnz57FH//4R2zbtg1PPfUUnnnmGVx77bW48847MW/ePIWQT4MTJ04AAHbs2IEVK1Zgw4YNmiwbgmWEgEGDBuHEiROIRCLYv38/gsEgjh8/ju3bt+NrX/sa7rpLWigVFBSISgshhsS8efM06TiFtJ89PT149tlnxbSfK1eutJ32s6+mgWF6upEPwMpCxjfpVqTXHEIk317+7F6F+q0oE8SFK8aCVmpUslPZYnRfPIG5LcrFw9VdIWRGIpjoC1K/8f/5XAsa0tzACH3Lj+DgqUg/97HsssV+W/pKSLRFawUrxgN2v3QiixT3m+N0joHAiJlANILgEEkY4jSWFUDXFXeAS5dc0UgL/Hvr23E4JwOFZTngAIQLyUKKoARku9s0rJohmpkPGLyy5rsH4VigCUGVa4cgBM5r8YMFMHVAIcL0zeKGVh+iDHDlwDJsR/KVuGJaxV7cRvmk4zi+VDJbPNYTWv9wYTu+O+p+8bg2UK9b9u3G3ZpzckWHoIwAgG0NOzEhZyQQkQSxv7VKz/GRzpPwMNpP++GO47ipZDZCnGTldrjtCNq5II50nsTVBVeI9Y90ntQoJLY17BR/N4faiP0AgIbgRY0yAgD+3vmFqJBoD3Xp1gekMS0JhtGYzvdFUNjQKCTGVGTg3TPScV6WCwtvFIQRaVwHpBWiS3ZL0kZLyggzpA2LKZBcBlaDMtrvNn6Ir+bHp5AQhbfuNjAxKwm7nyvaGBIswyDSixsRrV0R7PhEq/hQ45yBIkKNA58bp0IUYDSUJy8EwXEc/nasU0xFuf3jdpyqJ6fzFZ5fknWCoIwQeBtY6FFcP1HbLSpM/lLFP0vnmnrwwEKl+7EIg2/xp2dspp6M85X6ySk/mtolZcKRmm7UtYRw4nw3po+WfyOV9YQ0nPtOdGJYqXKdbgeC1UBXIIrth8nz6mJHGBc7wjhcrT9Ptu7TKp3ULhvvHW7HndcU8NdYpUr1S9Py8J5O+7T4THUvvRks/MGo+CwcqTG/12ZPcjyJhBL5HVZn2Th06FDCaDvom7CkkAD4rBSPPPIIHnnkERw4cABbt27F9u3b8f777yM3NxcLFy7Ef/7nfyaDVw1cLhdmzZoFAJg7dy5mzZqFpUuXoqioyFK2D4BP+/m///u/eOSRR8S0n2lpafj3f/93rFmzxlbaz4kTJ2oUH30BkYAPZ/9qXk4OLt2LwOg5yWEo4dAqJBiOiwmQsZecJWm4d+BiXVjYrP0gjgtEMaGDX8BrP4lkDAmGMSQYRqtBX8IFg5UKCREmn6x4PzqigsiCUsh2mxYsJISypKZcHgTG6rxTZIvB0MBK0+byw1Hc2OpHO8M7OHBp5FTJ4dwyDX3ayRnNzDWcLJmMG4+facaPRgxQXoiNRTrHYWGzD/4SFlactNI4YGGzD10VybHGyQtF0O6RdtfE+AwpjCER4egctK3yGDWha7R7L1c6GNUTrBRcFNZTLsYsbbCVchTuKAyQZnNrTP26SEtjMKIsQ1POw7iVAfYSPI3kYx1FNGHzVLAf4a2zEjNGAFkYSYXJtNFtz892oc2XnFhWiUx7KpjX03hL0NLVo2Voo2fzBibitstjVwgpISNRpTuCHn/hBN1iuc7daJzsvGpIz4vQNbXLxthBmXErJIhtMbAU48WsjLpPWemsqCQyQ1JcNmLHV15prohOFYLBYJ/dgO5PiGvVOGPGDPz0pz/Fnj178F//9V+IRqP4/e9/T12/sbERTz/9NO6991489thjAHgrBhq8/PLL+OpXv4prrrkGkyZNwoIFC/DWW2+htLQU27ZtU5SNRqNYt24dHnjgAQC8m8jbb7+toTlq1CgsWbIEFRUVcLvdKCwsxMWLF9HS0nKJpf00N1Hv19BYSGiXgZoifSCGRHLatU6TtoYmkn3CWyDVsesvbcUihrItmiwbCUnTmoznlLFI1lo/GDFUaHLRF6JvmykOBFgVDMyCViYihkQ4RoNGiUCvkIhfGUUVsNMC5GMlnzOcyQyiml8WYjjErcuN1Y8y/BMZj1U4rctGany49cc0qfyYKSQM3H30ylJluKDx4mP0aRlmnjZvPWmQs+uKSbqRKKc4z6j+CkhU3AuFgE1xv6zR1o6ucI9YlWQfj+WBHqJR5XeWaqqZdFT9DkhVDAdG9uNSFVUcKGHZQkKNvXv34o033sD27dvh9/uRn59PXff06dNYt24dhg4dioqKCpw6dYq67tGjRzF69GgsXLgQ2dnZOH36NLZs2QKfzyfGihDw3HPPYe3atViwYAG2b9+OvLw8PProo2BZVkwPCgCrVq3Cyy+/jIULF+Jb3/oWqqursW7dOnAch5kzZ1Lz1udxqUSJSeBLiusLQ6J3X3rhfnFyEdIsmF68SxwLmXhE2MyyYS+GBG1bNOMVj0KCFOuFXl1kp0QqLQ1ooOaONqVmMmGWDUOA1XgcphYSNt9/8gWpZCHhMm2TVtHAUpSjDwRqD1bqG45jnN+YZCnMODBxx5AgBnsmWUjYox4XjHqUzBS/ZpStPHOC5U0C9RH6FhJJ0IknYpjlChSlQoJglaRqL1EKCbmAbaZ+tArSUkbPQiIZ81Y9RInIMKtWnFjhOpFdlFtI9IWNBwfJhy2FRHV1Nd544w1s27YN9fX1cLlcuP7667F48WLccMMN1HQqKyuxb98+FBQU4JlnnsHatWuJ5dRpP4PBIH74wx9q0oayLIt169YhO1sKpNPQ0ID169dj2bJlWLJkCbZv345//Md/xOuvv46f//znWLBgAViWRUNDAzZu3IglS5Zg1apVAPi0n3/+859RX1+PwsJCK0PUt2Ej7WffgvWdY/Gbp/P169uCWCJ22SnKWW3GrkAE2ZeGsgnOxj1XFqewkFCl/TS1AKGwYDB2DTIZAAPpIO4nl9Hpnx5LludGct4tGoWEmFIzhQoJSgsJqyNipujgKBUhWrpyhQT/2x37Jhi5n7gpLSRo3qWmY8Ep/sQNpVWEEvFG8U/Fd5RjePPWeGa9ntCrOcfKbMJ7C0kyOks0jEZFcNlIhBm9RFPHQsKgTrLHizHYwVZaSPB/IxGTLBsx2ElVSuRP9pvGosUKUm4hwQnfPr5NU+sHmPdTa2BMz3hypppVa04H/RWWFBIbN27E1q1bceTIEXAchwkTJuAb3/gGbr31VlsCu9frtZX2s6mpCYsXL8bNN9+MkSNHwu1248iRI3jjjTcAKH2NduzYIab7FNxJdu3aheLiYnz00Uf49NNPMWXKFFRVVSESiaCjowObN28W0352dPABhd577z1MnDjRch/7JGzvNvcRJOCtZ9j1lNmopc5CItaQxfJ2d+bMY0horthJVQvAMC6EUEKkHfuoW7VCSNJzJGRFYYgWEjaUGRTQEyb7isJOzQU5bW/vgjaGhNVdHtO0n5aoyelK/Arjx8aUDWGD2BMu0CkkKLlQHKnvX6J3xJRjqXLZMBJSqCysjOonFnIVKAPeW4SxmfaTWldti3p8ICSmEJEMwU6AmfDFcap7asCnaCGRsJ1+IwuJ1C3mXKx+vAd53wXhXeOyofNtj0S5hPQrqTEkrFhIJCGsUpTjxHTxQIJiSMShSEmshQQj0uyvoooDa7CkkPjxj3+M4uJifOMb38DixYsxevTouBmwk/YzPz8ft912G/bv348333wToVAIhYWFKCgoQEtLi8JK49ixY2AYBhs2bBDPbd++Xfx99OhRTJkyBT09sSi1R47ggw8+ENN+Pv3001i8eDGOHlWmZOvPYBTLmssDjLCC6yOCFRlk3nrHG1/ZoiHiZYfqq6Weo3E3as6PFQdhBclkbedpn1Mqgw9jjkQCyZ1VSbKQUN2T84EGFHry0EbI6pAonPGfN7xOKzxfDLZaajcY1U93Vx+4iCaDTBe6NCM9xPgMgoVEIKqfucDNmiskusJ+dEfMM1JpHjUVT62hDpS7VAFXYzjf3YCBGSWGwqO6hwoLCdnF9lCXPYWEJ6AopYcIp5TUEiU3Nkf5aPpxvV1IBliU55KNcFh/oNQCUyJhRpmDUiNh9Oy3+/l7b8dlI0TQyARDHNGNIRgyVqq1dlkJSyyBdmecle3Qq9Hhl+Z/m4/no6M7goisf3qthCIczjbSZ1LRg5z+eYPMLMGQDZcNAvNdAb7PaqPTpLhsRAGXTIozm2ttvoipkkfjspEqhYTsrxND4vKAJYXE2rVrMXv2bLAJVPXZSfvp9Xrx5JNPwufzYdq0aQD4AJllZWV49tlnMWzYMLFsU1MThg4divfee09Bo7u7G1OmTEFjI5+abvjw4QCAe+65Rwx+CQAffPCBSP+SQez+hUrGmBTsm4h4+YVqJG+gYblwfoX4m+Y9WdwTxsW0uMOq2EcKLSRCpWOhcV3QRZz86DmNyuBl+fTBw0OuOJs0/5JFcvhUauE8PqtFuGAQ0i8cQSTb2Oor4uXrRfLKdcsYs01p5SC/H4Sxy45E4XOp38l2ByxBPhtc/CqPwlAELR6lEKym+Ea9xXRBNrC57h3D67QuGz2cvoKBhDcb9Pv2cu1WS7QE/PfpDfinoV/VnGdj8a0Ptn4GgOyewVLEwP7VmU1UfJgpcTbUvoHvjLyPeG3j+W24oWiGmKZUrwXFkc47rTsawOChPpwjXiW/PYLRHmRO3WXQtoS3G9TpXK2vrD1uBqGYgD6yPAPdkQAuRDqRzTBIQxRWgmrKQXo6mzu0wmsyLRL0EDaQrIw+hzmZLDq77dv6m42kxkLCABda+OedLqilssyfDrYRiwkpQAGgoY2nv+uzDowZqM0gI8CuUE9tJ2hQUN71vcf5TGE1jUGcaQzKypDHp7kjjN/8pYmSCyP+JAaNbsXre1vioi3gb8f4frpYBsfOSYrLZFhIAMr7NKo8Aycv6CuED530YbhJKlW1wq9ySCb2HDNO00zmJj5QLBMdXGKwJH1df/31yeLDFjIyMrB+/XoEg0EcP34c27dvR1eX8sEJBAJIS0vT1BXScQaD/IuxsrISkydPxpo1a1BcXIwZM2aguroaK1euhMfjQSBgvuujRl9OA8Pc8BC4NOupTPsCwkXD0H79PyGama9bpu2GfwHnkV68TMzIVV9IYvDwuVb0sEB4VELZRduNj8jcFPShbwnBn+8pHZc4pmSIZObDd8XtyDzxF4s17aqtY2Nh8KHJd2XhO2cuIjt3EPyAfaUMhUlBuHgEP5+yCgAAPYOnIVw8QjzWrVc01HQexpfIiM6S6TtnmhFigJB83qrGKzB8JjJO71VSJ5GNVQuWVyL9whFr7ALoKRmDtMbPTXk2w9SObny5sRM/GFUSF53eQMRmLAc5GDC9FriLZCEhLKwFHkZnD9Mto4d4zKtJVcMcH+GipCeMRpWiuKb7golCQkVfdo/U4zx2ZBjnmukZ61FZrvzzIv05eqZbaV1jNELTRmbj2vFeMCyDX75ZDwD4xvwByM924bk3+ON5k/Pgj/KpoWe1+/F3r7W04v98SyleeLsBAPmVSkqnaTc+S1mBB/WtyrG669pCvLbHXPAzmkpGCpJv31wKXyAq9tEOrqvMwQdHOqn4MuQz9uq3m/YzO4OFLxBFTqYLnd38fTnfLCkXmjsl5VFS3hy0Lj0Wp0dGmvKbKMSKSNa+SzL3c/SUDLlZLrhYBi0y6xSWYfDvS8pR29yD372vfOF8aVqepZSg6ueYjbnz3DI9H7/cVm9Y18xiRv58jSrPwPwpechKd+HPn5jzRxrq268uwJv7rVkHqmlyHHDo0CHbNBz0D6RwOzh+uFwuzJo1CwAwd+5czJo1C0uXLkVRURHmzp0LgFdaCO4YcgiKCEExAQDPP/88HnnkETz++OMi/eXLl+PgwYNEGmaYOHGign5fQn9/uM2ERS7Da3idhHSOQ3oEsP/q1OElXsVP7IsatdEnGoTzKwDWBTu74LZAqfouDEcRoo2ZoAvzGBKAaj4xjOn8ItYjID6PDZLFinY80jkO6ZzxvOXc6veQfrQIAOA8+jtuRrBbT428SJT4ceqtzRKG48TYImagtZDoK+AI/ApTzMhBymw0aLON8O3EYldwHKI6Jt8RLsIHb7Sh6NAKjkYuAEZ8miPdk5hZWVbgQVGuB4EeaRyHliifW5YFuJiEmxeOxpSK9OOTly1ZvpDeAInIspGX7UK7L4LsdO3ADsjzUNEwCjRqZPrucTMoyadrgwwOWQS+pav0ELgU+uJ26cdaIEEI/Kg3FvLzqTRpN3LZ0IOc30TF2NCD1flb6HUrFAlG0JuL+dkECzMGyM5wwe3S1snNshafpzBH+XUURtBFQcbM5UnepXyvCwzDoMBLGdCYQNru+1HMssHw/ZPHBuxrCAaDfXoDur8gpQqJxsZGbNiwAVVVVaiqqgLAx3xQu2yQ8PLLL+Odd97BmTNn4PP5UF5ejjlz5qC0tBTbtm0TFRKZmZmora3FTTfdhKamJqSnp2PUqFG48847AQAlJdLuRklJCW666SY0Njaivr4eRUVFyMjIQF1dXZ9+GByYg1H/UOda7k1m9KC70OpjtmsU2SWMwBHTWdK2aRepGru4NBKxv4RxMiVrdxGgo6agHn9atx97sGmdbhksAFrZIf4sDbFdoLip0IFkISEoCKS/JBjPgTBHL20J9FkOiDLk9gR69mayymVDFciSnop5WUuWLRRFjR41+TxhYv/bfcVYScBkBazB54rW/cNuGst4s+2YPcpqxZZRcUHOFhQLLpZBWCdaJ6ld4b2il/5SnqkiGdZViXDZ0IP8nZmobBp6sMqflbHUm88kRYVwKmIUsZUScvKCBYFeu1rezK5LBayu9BKZNlhBywkicVkgpQqJ06dPY926dRg6dCgqKipw6tQp6rpHjx7F6NGjsXDhQmRnZ+P06dPYsmULfD4f2traxHKlpaUIh8O47rrrMG7cODGV5w9+8AMAwPjx48Wyq1atwssvv4yFCxfi/vvvR3V1NdasWYNIJIKZM2cmrN8OUgBxB7CPCPUkpCiGBKNY4iL5L39x559mJSIISHZdNlL7ISPtQnIxA33qtJ8mMSR0Gja9npRZlSCienett55elgMilI1ZsQzQR++pJIwX3JzqrwSz4QhHLWz/CulaNe1KEAJCsjaGRV3FyEIiXmHOiqsKTUkzgdsOv0JqRoUgkySFhPDOI1WjVUhEDR4pI6Er2e8Hza02uBUcxwvegvDNWkyfKoyBnsCebAsJ2vtuNcYIByW/gsIlWWGWk5kSWs/agGR1JfARJtxPqxwqn2NpXtHQMVNasDbeEUawbUgrvkdME7A7uESQUoVEZWUl9u3bh4KCAjzzzDNYu3YtsVxNTQ0AYMiQIQB485gf/vCH8HqVJuwsy2LdunXIzs4Wz33jG9/AK6+8ApfLhaVLlwIAvva1r+HKK69EKBTC5MmTAQANDQ3YuHEjlixZglWrVgEAotEo9u7di5MnT2LMmP4ZANIBD60Yp37T9gdFRZJ5pCYfJx+9aCEhWcak6P4Sbd8Zur7rZf9IEHRsISyV1i/Xp1V/pmDFxIrmSITLBtOLuc3IAnRM8ady3ZDDTGBQZ5Qw5EGkyYn/qhGfhYS6PbmFhL16+mUSC9NdTkHA5YRnzJyDeNRdVgVFiX1tPdoMGUZWR8YKGyryhjAiwXHK17HZmPJKCf43wVLfkI4lC4kUSmx2BH55l/T6lyhYtpCwwI6+hYR+HZKFhNURYHQOaPpqFlxTaX1h99mPH3KXDQeXB1KqkPB6vXjhhRcAAIcPHwYA7NmzB36/H7m5uWLaz+XLlwOQsm00NTVh8eLFuPnmmzFy5Ei43W4cOXIEb7zxBgClr1FZWRmWLVuGl156CcFgEJMmTcKOHTvQ3d2NvLw8MWNIVVUVIpEImpubsWnTJoRCIbz11ls4c+YMAGDXrl2O20Y/RpIs3BMME2EwSTxqRUfaz6PNhYT4hbEiyNntvJEJem+A9PWnEyOUQptwMvbb9Cttfr1PTHmL6K29Eiu78glRSMRNgR5klw3hr4GFhMmcs+KyQbOjF4kFtUz42GhzjsZHzooLSJwuG3x7sXKwaFbPKZ96q15YtDCiS20hYTBOicxWIAQDFMABhv3VsGVyP6NRSXFgqIwhumxINIhVLChGkgnLWVg4HZeNJL0EkxrUUlchod8oSQFjZBFEAsMwktWT6ny8YJUaCWt8kSxC452clPs3Dvo/Uh7UcvXq1Yrj3bt3Y/fu3aioqBAVEmrk5+fjtttuw/79+/Hmm28iFAqhsLAQBQUFaGlpwQ033KAo///+3/9DVlYWfv/73+MPf/gDCgoKwLKsGGcCgBi08tSpUzhw4ADcbjemTp2K9evX495778XRo0cT23EHvQq3WpBTvTf7xPtO52NCG1wvAQxYK25z0IQYEgzNV0ZcffdH8VlnRGl3w4kWEpSDbnO4EjbMvWrVkXiYyTyH2qQMJG1hckR+AGjuaaNqz5owHx9IlgxvN+zGHWU34u+dXwCQZlmNvw6fdX6B8d4RuvQ+aT+O0/5zKM8wz4jS3NOGLXXvYlQ2b+0oxgQhuHtsrnsHXpt7+2olARcN6177sCW+AM9yel1hPz7tOIGZBVOIwkFLpBmu4lpELg4C622Fq/g8QudHASEpGKy5QkI1HhSBVViGQQScQhCkFl4sDr/RziathUSHX/95MHTZsKM8sfB6fenPjfAH5RlbjLF+RyOKc82DbBJtlkyIh2Q77WcaggYl7UF3e0QlIFod83Z/BH+VpS+VXDaSAxv6EgUOftGFz8+Ts+zpzecgyS8jBlJKWzufS+E+yOvSPF4ffeEzvC5X+Fm+J8mwkEAfWZ87SDpSrpA4ceIEAGDHjh1YsWIFNmzYoAlqKVhGCPB6vXjyySfh8/kwbdo0AHyAzLKyMjz77LMYNmyYojzLsvD5fKiv59PhNDc3Y8GCBXjiiSfEMsOHDwcALF26FA888IB4/oMPPhDpW4UTdbXv4NaLXfgwPwu5LL/wq0QO3oH8nlp/5fnH3giXz3ruan2YmcvH97YPjJiF9LrPAAC+SbciNGAkIt5iBEbymWqCQ66Ep+kkesonGtIJFQ1DxDsAgdE20wBTuSIkxqXGP2EhMo//BdHsQlv144bhCkG65qu8GZ6LpxVXo1mFCOcNRPfYG6WTrjSECgYjMNwspo2y3WDFJKTVfYaeIfz70tWp9z7T4Vd1uiIQwvkMwkK7nyqO1DBTlu24uNfwuoD/q3ktEewkFCe6TmvOdUcDeLXubelErPu/i537e+cXGENIBQoA7zV9CAD43HfWtO29rZ+gI9yFw+1KBT8b6NSsRvyRAIJpLlQE6CLeKxBR1pG7qbg7lCkhu6PWhDn1LqCc9p8a3seZ7vMYllWBgQQFzXbf20gbAXRfHAR3+Wm4ChoR7SpA5GKFWMbMZUNQSAgWEmluBkIOMFLKyusn5mBQURo+PNoJj1uirRdgMV60x1KHklyDLO+mE2AW9NMaLa24Y2Q71tqlVpRwKMlzo7GdPEfrWkKoawkRr6nIpARZ6axCwQLI5hDDoCjHrUgvCgBfva4I3T1RbN3XCkA5X68Z68W+E12WeJg6Itu8UAzDStM1ypcRZek4Va//DNMEelRAdS/+dLBNt6hAOjfLpVCinW3kn8g5E3Pw/t+Vz+P4QZl464CSZoTjMKg4DbUXtdn8Crwuwrzj+xUFhx6Z8kOvq1cMy8KnZ/wAgIY2fj4OLk7DrPE52PwBn4I0K51FbpYL00d7caSmWxFzZkQZXfYsRtUWoL/Mu/OaAnEO6dECgAmDM5Hvdff7zIAOzJFyhUQ8yMjIwPr16xEMBnH8+HFs374dXV3kl+Hdd9+N6667Do2NjXjvvfcQiUQUqTwrKysxefJkrFmzBsXFxZgxYwaqq6uxcuVKeDweBAJkDakRnLSffQeTu4KY3BVER4UbEQDZUApTdtYDweHXJIQ3EUkOahn1FqF14fcV5zpmS8q3aFY+Oq570JyQJwMds78VByeCQsKCnaLNMQgXDkHnrG/Yqps0EKx0egZPRc/gqcpyrAudM5dr6nZdfa/lJrmMHOW9jcPN4K6GDkzvDOB7o4x2xLVP1NSOAD7OpVvY6D2PZpvB959vxf9VFFC1YQQ7VuH/VNuCgcEwfjjS3FIglaCxxkhG1H4A6IkqhTNpnMnt6UeYMIYR//H2TGN9ITvu4fj+UbnxMEIZaxyJxn7gFWeDitNwPHZt9gStQuLGK/IAAGMqMhXnSekWSW9Zq3NBUDqQ3C5oLSRo6JNg1WRdXdxOvAGPO34fEg4chpem43QSLB2M8J0vD8SPNtUCAH50zyAAwOmGAD440gkGwOzKHLwhExoLvC6MHZQZU2Lw54UxW3ZjMbLSWcsKCSHlJY0rTkVRGs41BRWBPgfkegwVEnr3tDDHjZZOrSKJA3SVA2oIc/G6yhyi4mLsoEy8//dOeDOkzmVnaFNoRqIcrq/Mwab3mzXX5kzMJQruQhrZyiGSAoBheAXkbpUSZOygDIWSAACun5iL0QOl7/F3vjxQRptBKCw9wJlp2ptTnOvGxQ7l+DEMMG1ktqatq0Zn46DKMmPsoEwYJSsX7tuNk/n3V192mXfSfiYGl1Taz8rKSjzxxBMoKioS3TGqq6vxhz/8AXv27EFNTQ2ys7NRWVmJ1tZWfPvb38bvf/978SP2y1/+Evfccw8ef/xxsZ2pU6eisLAQoRCFlttBv0XfNgkzsIHtjxCCWlKNutxjuj+CwDeTQCdo3WbtjRejK4ozhF9aCPFISP7trgQ8Zb3msmGDVTt1UgErWSHkSIR/slW7pyhjM9aJOj2jjAiXyCAEUL7Femd+xiwkSAK/hXuUrFiCLhcDhDgi/UR8wizveBvSUh7bmeN2nyc1+srnXf7EqbsmjA8pWwvDxPeOoKnJiDxIjJmNvh5LRnok2lsq9FevPO1wRAx0xHq03S5+HNyyaKmsjjso6b4Y8SYoJGy5QKmgu7lgTs1a4w76PS65tJ8ulwtbt24VFRKvvfYaXnvtNSxYsAD33HMPOjs7sXnzZtTW1iIajeL06dMYMYL3j33ppZdw/vx5XHfddRg1ahQ6OzuxdetWuN1uzJkzJylj4KCX0Ycd03RjRfSVlUqiIPTHKJKTRnLpn2Ogn/aTv5rMlm1dj5cloT5hFeWylB6RzEivKSRs1qFw5085SEEt1SDtiidm7JVUhPGy4rxlXsO4NMdodyjt0gLUAilDLEOG8C2y2hdZHAgo76eV1yQxu0ECbrI7JuWTLDCS7bIRLy1eqKavz4n/ULRlRIfrO+KXXMGgUUgQyidKQUSrzNAWM74BelRdRmlPKGE2n8XPoQmdSFRf+NerKzxnbtnrTC88FYm0oUKCNV+h0LYDTluW5jnrp0s+B3GgX6T9JOGpp57SnJsyZQoefvhhnD17Vjy3aNEiPPTQQ4pUoF/+8pdx4403wu/3iy4epLSfAFBcXIw1a9Zo4lI46O9Qvu0StcsRH2wKkf0MYlDLvqYRSgasrgQSBLsjS7MfbVxC/6orAbe7t54Q1sb7IJrA9pMJu+4YycjLQvMOsKfkUbtVyH7HayGhtr5QKQhI7dsgawqGoLazpJBIUhxVl6iQ0F5LhPCaCKWGAPVuu2XSnAVLk34pgJlrJKQ9HiauPtDeV3Uxs+dGT9Gh1x5nQctkqpCgHBA+0KWO6tXQQkJ63vj2yOVJbBhxJio5DPgn88UYurRZQZ98HBwkFSlP+0mDmpoaAMCQIXxk7mAwiFAopKlfW8v7wpWUSD68AwcOVCgjACAnJwduN9/1kSNHApDSfi5atEgsF41G8emnn4ptOrh0wfWJt5+xhcQlI76LQS2TH0Mi9UgR37bHi0IhQSU5cRoe3H1C6UcHOyJrtJ9MURrlK3kRGX8H1UoNmh1EO62q+5jImWe84KZ9V8u3De1ZSEjGSAm0kEgABH1PhDDPEvEaT4TrkACty4Z1GonQR3BIbL/igcKIlMpCQroYTw9oum/VgoWWrhL0z0XiXDb0bAL1BXpBISF32dCjQVRIGFlIuCgsJKw83zZeNX3kcXDQi0h5UMsXXngBAHD48GEAwJ49e+D3+5Gbmyum/Vy+fDkAKdtGU1MTFi9ejJtvvhnl5eVgWRaHDh3C7t27AQArVqwQ6f/iF7/A2bNncc0116C8vBwXL17Etm3b0NHRgaKiIlFZIQS4fOWVV1BTU4NQKIS33npLTPd58uTJJI+Eg94Bo/rbh6D7Bu6DvMYDIYZCPxJQ7YIYk6EvfGnjYIHKQoK0WLHQhl2/00S5TNihw2nE7b4Jqh0rCmt+juOsC1FqAZCCFVILERNlplZpIPudxPeOyKvptq3susxEngZiUEuO/1/ekhULhOQpJPQtJBLxfCQyBEgiXDYSMp8MBNre/kwysh8072ExrgTi+7TRvEtIri12Y0jojStncE0NWpcNM0SMzOt0eBHaVigkGLLNGYlPo/EWXTYMOkC0xNApp3HZ0CcrlekPH1MHCUXKFRKrV69WHO/evRu7d+9GRUWFqJBQIz8/H7fddhv27t2riDuRlZWFJ554ApMnTxbPzZs3D7/73e+wZcsWtLW1ITMzE4MGDQLDMLjnnnvEckLaz08//RR79+6F2+3G1KlT8Z3vfAc//elPbaX9dNB3wSktNfuG9YHeh1Pu1NnPEM3MAwBw7nTtOY9RxgVyXyMZeQnjrTcg3LIseVjwXrmPfBu6rgc65z16/vW0PMuKqYXNRAR9zAtFAFK6UQN4ohxCFu28i0IRNKRb+zx6ovq7XH0JNAoJDhzebfxAce5oV7XiuNpfg1HZQy21rU45SrUwJfB7trsOh9uO4nPfGbSHOvHgsLsV1+VCoovjEFW0FN9ENI4hQduCtkRWulLSlgsaGR4GgRAXqylZSDAAmB4/3C7GchrPMGWWDavITOOp5GW7xBSD6gaMUmWaIZGvT7UCx45KkVavYyjc6Vx3sXwmhd6EoFAq9LoJQS215Qtz3Djf3BO3oojmvoYjHAbkeXBOngHD1GXDIiMWHiPaOAhmCo6sdNaqPkLMcMEAyM92oc0g3S5pXhuxfqGVf25JWUgMQTnWA/I8/XE56yDJSLlC4sSJEwCAHTt2YMWKFdiwYYMmy4ZgGSHA6/XiySefRCQSwf79+xVpP9WYP38+5s+fLx43NzdjyZIlGDJkCL75zW+K54W0nydPnsSTTz6ZkLSfThqYPghG8wNAH1FIyJgIDJmGnvLK2FH/fXP7x81HqGg4IgWDxHOBEbMQ8RYjVDLGEq3Oq+5BxFucaBaTCpZx4WsX2lEUigBjhbM0hurx49u1rcgPR8CNJlyM7TB/63wr/lyYjTOZaXBHOeS5MmGWT0g9Gx872wyM0rsKVHYFcFVHAC0eSdlRHgzhurZubCnNFc89XNOC54cU6pHB3fXtGBCK4LMcutShAHBlRzdG+XuwuYxOkZUViWK8L4gbWv046rWWsrmix56A1dug3dGt6jhheP2zjs8xMmtIXLzIn4SJXQH83au9t3pWFJ91fo764EVDukO6QxgcDGFPfpZo0UH71GVEosgiFDZy2aC1GFl0VR4+QxqaAEwblYW04hxUDpHScn5j/gDkZ0vPyz8vKhOFA7VCgouG8M2bBqDDb01yHVmWgSM13YZl7p1bjLcOtprS8rilNIHlBWm4ZmwOygo8+Px8vaIcyzC4d24xygo8+MXrFyzxK6dhhruvK8LmD7QpFNVQU7KT9jMiUwSNKs/AsNI0eFws3jnUZokOqW1WFePCCOMHZ+LYOeX9zM1yocMfQUVRGm69Kh/hKIfff9iimCsPLCxBmltqvLzAg9tm5GP0QC09Ufki43XB1DwMK0nDwMI0USjW9IMlW8w8uFByr6bRGXMA/mFOMc439+CVXRfFcwAwvDQdoTCH2uYeXDEsCzdckYtOf0Rf0DewkNCDOjWrMBfV74Tbry4AYL5y+8b8AejsjmD84ExUXyDLGHp89gjPW6EH940sQVO7/pebpCyimes1TfqpT2mtSNQWJ1+fW4zyAg/S3CwGFnpQ10LmW/0uPXToEF2DDvotUq6QiAculwuzZs0CAMydOxezZs3C0qVLFWk/5fD7/XjwwQfR3d2NF198EVlZWYrrzz//PB555BEx7afL5cLy5ctx8OBB0aXDCiZOnIj0dGuL2t7C5ftwk9/CdgPvJBQc/zEPFY9A94SF0vn+rEp2eRAqG6c8x7oQKhtPSUC6L+GiYQljqzcxyccvYMRlvbhtksRGGQbDAiFlu3LEVggju0Pwt3XjTGYaxvqD4PLN55q6RGEogk5iSR6ZUQ7j/D3YmysJXFM6g5jWGVAoJOQCPWlorugKojHNOEOCwpSY4/CVxk4cyU4zrCPHeF8QX2nsRMDiM6ewgOnjoLOQoEH87yU5BRcHFPeEcTHNrVtGjqiB2wYH/trVHd1oVef3o3zuxvuCOJNF+H4nID7FpOGZONfoRpMPKMv34MphSoXZ0BJlu7lZLuRmKee+fFwGFqZhYKE1HmhcNkaWZxgKHjdNycOfP2lHbpYLzR2CwoQXjn0BsnA6spxeoSjHgDw3mtrDVILrgDzjpa0gCBFdNmK/p43MxuFqn2lbckuTAq8Lsyfk4nitsaJHDY4jW1fxAQvpZticiTkaBcKkYVnYc7QT4wZloLwwTeRRrpAYWKh8P7IsgytH8fHZ1O8KUuaUnEyXWF7v1lw5MhsHv9COZbmsbaNX7qjyDJyMCexZ6SxGD5TmkDA/K4dk4rOzfv730EwUet0o9LrRqLbSEerpN6d7beqIbIVCQi+DufCsmiko5c+53ifETPD3ZriQk8n/r1fealBLAS6j1Ki0J1XnRsme/xFlGfoKCdXxlVdeqc9MihEMBp0N6AQgpQqJxsZGbNiwAVVVVaiqqgIAHDt2TGMhQcLLL7+Md955B2fOnIHP50N5eTnmzJmD0tJSbNu2TVRI1NbWYt68eZr6ixYtwrp163D99deL50pKSnDTTTehsbER9fX1KCoqQkZGBurq6vr0w+DABvqgkM9EYyZ3rEro6scuG5c9CPdMWHpq41H3HhiZMCfsGXOgdKBWm/GSjjhOc4Xthd4qDPPjeF6SaOWbctCk/aTtUbwzWAiQakRFVyFhUEu+KJesMPgoH7Q864mCGpcNQimzNqKQnj+rY6gIYknkiA4kVwCrlEg7r8mOeUBjhWJWQox7QFBIWBkEDuRsJVbfH1GO3C8rbhAkyxFhrtgNmKm+l4LQrEfNaupKZV19HgUllGEvGMk1Qa60stV1XesJ5QWhHb0YCYkIMmtm0cZSaOhIY0vDm8uANoktmvclLZzl7uWHlCokTp8+jXXr1mHo0KGoqKhQxIMww9GjRzF69GgsXLgQ2dnZOH36NLZs2QKfz4e2tjZN+YEDB+LChQtYtmwZKit5U/hx45Q7t6tWrcLLL7+MhQsX4v7770d1dTXWrFmDSCSCmTNnxtVXB30bfSLtZ0whAbVCoh+7bDgggNaxNBFt6EEj1AgLB+uLfcbookQ4bi9+wUTdcj2LAoYd9IG3BzXosmxQ0oqPFcoYEmQYWUggJvAzkDKmSMJEYu+WUkFAN0Ojsh1xq9yIVvMcr9Cx+xohCkAWaZEEFkkItsOVOajCwZg0LlwmxZDgLL0wOGLsDvKOtLFwR7pqJUgpqagYADVB98LMqiZZaT+pMnDIyskFcKtBLQH9x0AbU4NM3M4ekl4MGLPZqB43Yr+IVhPmzBkrxPQUKKSS9vrm4PJCShUSlZWV2LdvHwoKCvDMM89g7dq1xHKktJ8//OEPNWk/WZbFunXrNGk+AaCurg7/+Z//ibvvvltzDQAaGhqwceNGLFmyBKtWrQLAp/3cu3cvTp48iTFjrPm7O+hf6Avh6IRda04dWFD8cKSeRwdWQbpngkIimWb+ZgoJmYVEbFXAyVd0FigTLSSgXWHHmwGjN2c/faQBHslaWLEch2iCJTsqlw1KKTdRNj4c9MdQb94YtS2/Is5vPalPr10dnozTfprzBgjKFEbiyxIE1SEHMPbtrEhBLW1bSMgqalWdiQWN1YC5hYTyr/y8ldcyB34c3S6lxYkVRQLAK6hITFuJxUsqKyokLHGjrS+AFAeCjpB5ESMejbwcpfkvU0JQ0iXByuOYqCwbgJGFhDUeaN5ZQAIsJEjnSMoIUpoNowoxOBYSlx9SqpDwer1xp/0cOXIk3G43jhw5gjfeeAOA0tfotddeAwBUVFSAZVn84Q9/gNstdfuOO+4AAFRVVSESiaC5uRmbNm0S036eOXMGALBr1y7HbeOSAFm47xMxJBwLCQ0SlcaxT4GRCe0pg46FBNVUU/JtuvgnlOPM9CU6dMzbIiy8TOokBElqJBlkE2UNxoCJ28rHWLlljKhB2+IufRyWCPEoJMwgdzex7LIh/hKeCHv3IELYkbV6O11ENwHxl3WmKEDlfkApKGoUEhZ5iUb5/npcLMKyIABEFg2I6+nKrAhlJNN9UVS3+SLRumwkz0LC6L4a3nOZFQhJcaFX187sVI+HGNRSYzlh3DYJdsMQae47oWOk20bDmZHChfyuICs5dfURBm1fvqveyxcpD2oZT9rP/fv3480330QoFEJhYSEKCgrQ0tKCG264QSxbXc2nKjt//jx+8IMfaGgJCgkhaOWpU6dw4MABMe3n+vXrce+99+Lo0aOJ6K6DVKMvv+X0FBJ9meckIR7//z4Fo5VpUt2ETEyWFTEkYuxQ1DMtIXNHiUfY1EWSdTjavTY6BOPNeacDlgMiCX4UqATgqHnGkJP+GlwINsXFizj3jMy1dfiVx2EAgKZgq/i7yielKJVipMT+6jx3DMcp3zuyYrXd9Sjw5MLNunGg9TNFPY7jcLTzJC72tOF8oCF2DuiJ6ke957gotXsHADQFW9AV8aM7EsS5bj47BcPwFOTdCUZ6wOY2I9pRZEozTBCA1HOjNdSBaHoH4NNanQLG1grJSldJYzVAayGhcdmw+Kw1xzKfeNwMumVxz4l0DB67njCnk/aTnqFkuGyoWRaUgHr09OY0zWvbiEejGBIK5QPhpC5dnfeAEa/qa2bjYCV+ta7LhmULCTpFI82cMLL0IVtDkArq0zfqm924Jw76L1KukIgn7afP58O0adMA8AEyy8rK8Oyzz2LYsGFi2ccffxx+vx833XQTSkpKcPbsWbz44otoa2vDb37zG7Hc8OHDAQBLly7FAw88IJ7/4IMPRPpW4URd7cNgGBSGImIqwmK316RC8hEuGAwA6FFloIhk5sMDIJqZR00rWF6J9AtHEsmeAxsgfW+Dw65C1tH3EE1P4pwz+Zb3lFci7QKvZBWtrmUuG6HSscioOYRQ4VAtaaOFdcloZJzeh3DRcKD+rIIVVrb6MFug2dU7kHjrz8saXphOsMsGhU26q/Uc2KwMjdAvR4SLYNP5P8XFi+hOYVBGT+ZVKxY2170t/v6oU0pZKincOPEXkRdohRvh+JXzbyHHnY2y9GJ84TurqNcSbMFfWg6qucN7jR/qcB6zkBCFFfPZ/tK517X8MqwmSOfW+r8gfdx5ZJ9cgIstxkqyq0Zn408H2wAAI8vSce5iD6aOyEb1BSmLwNqzW/iUvgekrE9y9wS5wJKf7UKbL4IJg/lsOhlpynlbYpL5Ii/bhXZV2kghbSUATBmejT9/0g5vhnGmHRroBbUcVJyGM7IsCiPK0tHaFUZrl7F2xe0yV2wYWfQAwPFabdrH7AwWzUYpjGQgC4+c5lrlkCycbexBVrq5EnVkWTp2yI7NdvGTFUNiZDmfonbcIClT0/jBmThe2610SyFaSJBpThmRje0ft2svcPqCstZCQtuevE0rwzG8jJyRz+ztoLaQoFUUCM9AVjqryUozeEAazjX1GLvFkdohlBtSko78bDc+OeWnoqGHyzcz4OWDlCsk4kFGRgbWr1+PYDCI48ePY/v27ejq6lKUGThwIF588UXFuVtuuQWLFi3C008/jVdffRUAH89i8uTJWLNmDYqLizFjxgxUV1dj5cqV8Hg8CATIOYKN4KT97DuQlvWiLR2+c1bKU95RYi8VWSIRzRmA1oXf15zvHr8A3WNuANz0c8k/+Q74J9+RQO4c2IN2SRIcciWCQ5Lt/mW8FAqVjEbbnBXIf/9X4iqCkzlFhIuGEeeiGSIFg6V69foc2VU4RLLNd37jQ+wt0QveNPmhCL57thmPjyrRLcMmgQ/jYJASBmYMQG1sxz8eTO4MoCrH/P2q11W9e6FWlvgi2lSLHMMoY0hAXwEgzM+h3T34p/NteH1AjuJ6Z9gHD6NdMgUi2rUBB966QA9cAqIWkepf7OGtRP5xfhGe2dJKKCHhqtFeUSFx740DxPOv7Wkhlr9tRgG2HWhFbpYbLTHLAMFCggPwyB3livJpsnSr/3RLKUrzPUS6P7i7QhTof7SpVjy/eGYBmtrD+PAoL5FfOyEHV4/1ovqCcry/9aUSrHtPuWFkJhirXTYKvC786+08/4JCgmGAr99QDA68pYKcNzXUwjQx44UxS8Qd8gF5HtQ00aWcN7KQkGPGGC+mjczWKFFIKFelBO2tOMxlBR7Ut0oWRhVFafjRPYMU5e++jv8W/HFvbL4y8mdC5thE6OZ1lTmoHJJJVEgYKwhV7oqUwVNpPnjlBeT01MJ7a8qILKJQT5UYi3DjhGrf+fJAzbWF0/Kx7r1GoquHgEiUQ4HXhdauCG6Zno+3P2rTlHG7GJTkeVCSR372SZg2Mhu3X12gOd+XXeadtJ+JwSWV9rOyshJPPPEEioqKxLSfarz99tt49NFH4fF4UFVVhe7ubmRm8lrXX/7yl7jnnnvw+OOPi+WnTp2KwsJChEL65pcO+gNI+1/q630UDGNJGeGgD6Evmx0Ku4SiSTudq4zdHiVCIdGHR9My3AS3FjWS4QhCFdQS+ubXVuE2ClxmcmwEsx1nQDnPzPrNxLTWorAKrSuJSx1wGEAgSicwElrk+bIp5XEMG3uEe0F7Bn63HgCiMimF1qXAqJSeYMwQnHXcLkZDzI63lOSyob0mb5MmpaKcnt4xYE+YT1hQS9U1GmWEHZCoMgxd3+XCvUt1T90G91gZuJNRnOPPaLmSW1NoCdLHPBDHXCeGRCIguhHq0FQrv0i8E2NIGPBIkwgsEuXi/kaQ6JvFKXFw6eKSS/vpcrmwdetWokIiEAjgF7/4BbKyshCJRBAKhdDR0SEqJF566SWcP38e1113HUaNGoXOzk5s3boVbrcbc+bMSVi/HaQAan2EAweXMqhWRAqbocTEkDAo3xvKBOKC2EJ9QQDtK4qPZFhq0ArAveHDq47vQC5DBq2lh7q+XvdJe9rqoi5GKxkFiQoJ+htnN6Ay77BhNR+MfWSk8X2Xm+3rCWRq2JlKvCCrv7NrWJeCNv83MXNcbXFBVkgk906R+mImzNpuSxUjwQi0Sit5MbWQ7aJUoJBiNhCbN1CSGN4ljW+G4WkZP/bvvcCnXjwHtUKO3mVDv03xsTZUSEDzoGkTahj3m3TVUUhcvugXaT9JeOqppzTnpkyZgocffhhnz54l1lm3bh3S0tJw44034r333oPL5UJeHu+XT0r7CQDFxcVYs2aNIi6Fg/6ImEaiL+9YOyCgv3+c+vB8Ey0keNhN+0lbTi5c2w5a2oeH0ypoZjabhPkf5cyjDXJM4iwkqKHTnP5GJt3YSJkpzWJIKON1kNpliQoJsvWkUfwNOX3bd5hhAdhP+2kVGR6e44gdCwmbU8luMD6zqWtFoKaBpAzg/5KERzM5i2RJYCnLhpGFRJKeZTV/pC6qrR2oaFmw6JArXRj1SQKPAnlD/RBlwEtG54rUZvzjLikkyNdpHkGrij3JQsLau0Vd2qw6ib7dbCMO+j+SExqcEl6vFwUFBablampqUFNTIx4Hg0FNrAgAqK3lffxKSiSf3JYW3r+srq4O//d//4fvfve7CAaDCIVCmD59OjIyeN9WIe3nokWLxLrRaBSffvqp2KYDBw56CzpbD/0NfVqAji3KxRgSyaEv2V5Y2TU2pmjWYrzoK7ctGTEkIpSWBYmC4cJXs4LVK6e9QGMhwcnakGJIGPPCyI45KBfNLsKSiWQhoa6nuc7JW7J3k4UsG70FwUJC7rKRpOQyAIyEcXMp2Gxk1C4biRpJ9c64HFazJVhum9Sm8O5N0kShIcuydEozuYWHmq6hi4nSP4M/paBrXk1zjaIpOW0trcQPuJ41j8Zlg2QhYYGenKbZXdPM9wR8r/SyjTi49JHyoJYvvPACAODw4cMAgD179sDv9yM3N1dM+7l8+XIAUraNpqYmLF68GDfffDPKy8vBsiwOHTqE3bt3AwBWrFgh0v/FL36Bc+fOobW1FQMHDsThw4exc+dOAMB3v/tdsZyQ9vOVV15BTU0NQqEQ3nrrLTHd58mTJ5M1BA56Awxj6BvowMFlh9gqQtpBBpLhsiFALlybPoeGwoi1p7ivKBfsIBm8R0x27oHExpAwul3ydazRXSXd9SjlPJDHSDFiiNRbrcsGbQwJzoQ/KX6IfVP+WJYNool24r906Z6Yy4aMtGAhoSdwsgxvGWDHNUIv9oCakp2ealw2dHbRrdIDozqWwVS4Y6y/2+QgBtIUlGwJfpFIig5zYZg2XIVcIaOJeWGgrREtJMCQrSEIJxmG0Y1BY+XR0XtHapqM43EUnmVdCwm1ywahsSjplW/kshG7Zuo9odENWrSoIBR3XDYuX6RcIbF69WrF8e7du7F7925UVFSICgk18vPzcdttt2Hv3r2KuBNZWVl44oknMHnyZPHctddei7Vr1+LkyZNwuVz4wx/+gJKSErS3t6OyslIsJ6T9/PTTT7F371643W5MnToV3/nOd/DTn/7UVtpPB30JZjac/VlsuQQRM43mXPGneEst+vK8iikkYqsCl9JiXR8W1wsCyUTcSVujKd9A4zhDdxFpcZt8UO0uJqHdxlCbaRnaqRAvhDY6XQz+7s1AaTBMXVe++D3jP2/aBicqJowVEnJLCU5VnhRDgjSeVhQ6e1o/xqzCqUR3ECMwABrdQJMrgp5oCGmsFMk+GW4cnphk6WYZuNKAQA8nCkl6KSRzs/hUoHbmEgOyuT/Np9o0y4a+HsIWNEEtCWXMlETxWkiQrFUEhRGta41VpLmVdEnjnp7GGioUSHU1MSQMHg3BeoJlpTkqr22n5x4dLYq6GwKb6vFVxxLxuO2PvxBYVW0lwrK8okE9VqSx1nNbMW3T5L6lCWPPSDzKq5i9hUjXkzRVHfQDpFwhceIEny98x44dWLFiBTZs2KDJsiFYRgjwer148sknEYlEsH//fkXaTzVuvvlmrF27Fl/5ylfw4x//GADwve99Dzt27FCUE9J+njx5Ek8++WRC0n46aWD6FzquvhcuX7N5QQdJRySvHN0jr0Vw8LRUsxIfeuHj2nnVPWCDWhc2U8QWEYODYdzY4sPV7d3AUHOGhbgGD59rwdkM+nReo/3STrKwEHm4pgXPDykUzw8KhFCb4UGUdaP92m9h7KktOJEtZZiRm/hnRqIY7e/BdW1+/GowT4MBsKSxA6+X5Ep1ZMuefz3Xgi+y0vB2kddQMUG6MjgQwjkL/TUDVQwJEyGmpCeMxjTyZzwnHMHShg58kJ+Fz7OtZenh3Om6QdS+dqEdr5TnUdNiAPxLTQt+KbvPlqDjmsCCFeM07GutIlYluWzoDbxa5iFZIZMUEnoNj8oegqYecgpNNd1gtAeZLmupp7n0bDR6+GfqXHc9RmYPFq9FweHWq/JRRkgleM+cIoRiZg7/MKdI47N924x8nKoP4vqJufjNRf7cwivz4HYxuGlKHkZXZIABcOJ8AGUFabhyVDamjsgm8njnNYU4UuNHfrZWHTl/Si68Gcrz8vSBDMPg+om5+PRMN26bkS/1jXD/bpmerz0Zwz9cX4QT5wM4XO0DAHx5ViHSPAzcLINhpek43RBUCGx6j9z00dn46Asf8ZrKQMLQWkEPRu4vk4dnofpCAF0B/mbNn5KLHZ90YMaYbBz4nOdJ3eTtVxdg/OBMZHgYVA7JNG7cAEuvK4KLBdp9EVQU8fMpzc1i/pRcjBukpOvNYDGmIgOfn5fWy1+/oRiZaSzqW0MoznPj42pt6koAyM10YUxFBoKhKMoLPTgdS7/6pWl5hhY2C6bmIzvDhfGDMzGiLB352W6MHig9S+keBpOHZ6HqtB85mS50dvMKsqIcN0aUpWNwcRre/3unWJ7j+D5/csqP3Uc6FNYFU0ZkY+/xLjR3KhWnV43x4mJHWJxjAreZaSzmTc7F+MHKcfrq9UXE+XD71QV4c38rAGD84ExMHZGFYaXpCIaimDnOK6bABYAHF5ZqUuACwLzJeXCxDPad4NcE1473YvzgTNx1baEipa+R0q7Q68INk3IxeXiWeO7u64qw+QN+fTx6YAbmXpGLrHQWn5zyY+rILLT5wpgxxovsDFZKUSrr453XFCCP8B4AgAF5biyeWYhj57px1WgvscyhQ4f0GXZwSSDlCol44HK5MGvWLADA3LlzMWvWLCxdulSR9nPz5s2ora3FSy+9ZErv+eefxyOPPCKm/XS5XFi+fDkOHjwounRYwcSJE5Ge3jfTNV52D7faplIFDkC0YDAiBYOJ1x30MhgGgdFzUs1FApB8jUS4aJiteoJAzgBY0MIvpDoo6gmuFxXBMCoMdrTFngtBuQB8qbkL7xV5xXVKRY+y/vSOAGozPIjklCKaMwBj/D1KhYTMeH9aZwC3XeQXXSXBMBrT3QAHjOhWBhmUr/PLeiIo6+nGOzIeSOBcSkHuZycb8Waxl0ohMb2jGx/l2hcA5JDz/u9nmvGLYUXi8Y+qm/DHkhxdhcSXmn0Y3R1ChOm2rpBgXcQd/rRoVKFYogEDYGAPveWDBqxHTMk5raMbSxs78c6gQdidId1nmiwdZhYSwml5rzlGWZ4luGyQSRlLn5zKSYUmhaka4QEjgZ5jMb7UpvMcpuss7MdUSHNzbIV2nl45yosrR8XqxhQS14zNAQBcOyFHLDcgj38WbptRoMvjsNJ0DCslz73ZE3I152aM8eLYuW5RGE33sPi3xeWKMmqTbo7j68khjIbHxWDsoEyMHZSJU/UBtPkiKCvwYECeB2MrMnHuIt+OXiYGOa4YlqWvkKAwkTCPIaHvsjGwMA03X5mPn71WB4Afu9kTcsFxnKiQkM+B6yfmYNpIXkl009R844ZNMGEw+V1Gun8Mw+CeOcXwByP4+R8uAAAKvPz76b4FJQiEoroKCZbl6wLAkRqpzMxxOcTyArLSWdw0JS/224X5U5TKUoZhsHhmIRbPLMSfP2nHnqOdAMOfX3bjAABQKCSiHIf8bDdumJSL3X+XvojDStPhdjF4+LYybPmwGUdruiULCBeD268uEBUS8vt/XaV2nNSKHAHTRmbj5IUAjtZ0o3JIpvisLpiaj56wUnNYmu9Bab72e5SRxmLB1DxRISHc/4lDs5DmZrDp/ebYuBBZiF1jcMMkJd/jB2fC7QLCEeDqsV4MLOS/kUK5eZOlcZ8/OQ+fnPIrZvMUgtJSeCYEegJNEq688kp9hlOMYDDobEAnAClVSDQ2NmLDhg2oqqpCVRW/w3Hs2DGNhQQJL7/8Mt555x2cOXMGPp8P5eXlmDNnDkpLS7Ft2zbMnTsXPT09eOqppxAIBHDttddqaIwdOxZr1qwRlRclJSW46aab0NjYiPr6ehQVFSEjIwN1dXV9+mFwQAPHDsyBAyUoVuEE0BuWG6146ChEdExkrZC1kjpTKEqynkjFG0TJu7IjZvzEw6+Ry0Yix8FunAoWdG4JHCMp0MzdobXjy0EV1NKSWwX9xLPnYsHIfqkUEpdAtCS9Z53Kx9xQ2NIWo4lxYVRCohP7QYzrYUzfLEAobXwEvfZ7E3rWVbRPe7JSDhtvS/HgdH7L3UbMYnPE9e7VoW3lXanLF6P/zqCBoDSjdYkygxiLxDInDi5FpFQhcfr0aaxbtw5Dhw5FRUWFIh6EGY4ePYrRo0dj4cKFyM7OxunTp7Flyxb4fD60tbUBAAKBgKmrxdatW0WFxKpVq/Dyyy9j4cKFuP/++1FdXY01a9YgEolg5syZtvvpoA8g0U6jDhxQoQ9POKuOpTGYuREYkTTP6KG8ElHxyMqFMHlsCEIbUh0bkLUr9NeKYiNRkAvJpFuTTJaIweCgFdxN6Vi4RlQoEVw2tO4V5u43tDEkxKscf1ZhIUE5mzhwplYP8qs0GUPUkPf5klRI6JyPmGetleqavuIYvWLaepRKDoD8XJrNBz0hnqZ9NVJ99/WUK7R9SFYcATErhkEZ+W2S/3ZZUFLHo1ARFKAaChZI6rWvUMbZYNHlYoAwZ8qKfvYRFcTrfXid5KDXkFKFRGVlJfbt24eCggI888wzWLt2LbGckPJzyJAhAHjzmB/+8IfwepVmeizLYt26dcjO5k2DMjMz8atf/UpDb926dfjkk09w7bXX4v777wcANDQ0YOPGjViyZAlWrVoFgE/7uXfvXpw8eRJjxoxJTKcdpAS9FaTNgQMF+vSkS7aFhH0IAlVYtWrSU0Koa8tBUqBY2Q8VdtjZFCzzzfik4cgO10ZBGRNrIaEPFgyiKtFaKG8lHaqQMtQ0hoRGkSU4VtizkDBSCnCyfwH6jCFyyO8PyWWjv0IdEFCNMMFlwxp9mSIn9pMkAGuUZUYxZ9QKCQJTZmwaBW7k+enTHxMFdC0kKKXgpCkkhB8GN0NvPrlkQSU5ExOJeK3TeNIk1Vl8iFshwdLVpb3PUl+t8+Lg0kNKFRJerzfutJ8jR46E2+3GkSNH8MYbbwCQfI08Hg/mz5+vaVdo89vf/jYmTZoEAKiqqkIkEkFzczM2bdokpv08c+YMAGDXrl2O20a/Bo2xngMHiYX5XkIKYXMVYEUY1DQZ+6tHQs2RejNUYQlBoMIQRpyodjHTUCpMW/XpJBvysdb2izM2TY+zbWJ9zo6liHl8B1JZN8Oih4uAAQMGUUVpFurFOrm38ttsGkNCp768OCntp149K3EhbFlIyIWLS9BCQg80LhuGBpGyk1bSYtJYSBiVoYshYa99q20lG3oKBdousEnSSNBYSOhB4bIh0DNpxw6EV4HGZSMBQ8Lo/KaFkE3ETOFAS1t8/mzw4uDSQ8qDWsaT9nP//v148803EQqFUFhYiIKCArS0tOCGG24wbPPcuXNgGAZXXXWVeE4IWnnq1CkcOHBATPu5fv163HvvvTh69Gh8HXWQWpi+8ZxXooMkoE+r/knbgub8uiiXc2T7C0EopNv717psGNMnwZbXv2wnXOA5FXdSHkOD1L51MZYOHUwE2YQWGR0+NOVk6VWtjFtU4SqjbFf+V31Pu6P6rplCHV/Yj1y3F3riiJ4iqyMsBTKkTc3pC/sRjBoF/+TgC0uB+6I27qTCZSPGlz/Cj4NcGRKKhhHmwposHp1hH7yuLIVwEYqGEeLCyLKY8YMEX7gb6a40uCmVOGqQhB5fuBudkXbVWdL91Fd1ya+I5vGythIhzJNImNFNlF9+X4B+DAO6+slO/WjHgkie2tOKIssqBM40KUYTQFtpIWGdoovynW6VdH+a2w6Sh5QrJOJJ++nz+TBtGp8WsLGxEWVlZXj22WcxbNgw3fa++OILdHR04P7771c8kMOHDwcALF26FA888IB4/oMPPhDpO+i/CBeNQFr9UTF6fsRbnGKOHDhIMUip6SiqWbWQkLdS1sPbPFQEQ+TCKj7KVdkZaNwI1CWsxrzgiUhUXMLiMwW7jvXp+lk9TBeFgquCjXY7WQ6dvjM2avJgIVm3nM7Qj5yuhjxjSCQaBlgGIQaaTqjnYEOQnK6ZA9ATu5e/q3sbA9IKMSttkC7PaoRZBi+d+wMl9xJ2XNxreL0nGsK5QIPEpy0pWGsxIig25BYSvzn3R7SE2vHdUfeL5zrCPvz6zO8wq2AqriuSLD9fOb8NDcFmRVkAON51GuO8wy1x9z9nXsGorCH48sAFluoZ4Tfn/ogutx9w3wiE+XmVnaFVeNAKOIKxRbwCcFlBGs429qA8lmY1K107m8ZWZODEeevp4wX0J5lNN4aB7PfIMv3MP8mzkODp2nnaBhfL3mM6O/ssw8+peATsqKgkU11IhIUEwV3JClwuurrUQS0vXUMuBzaQcoVEPMjIyMD69esRDAZx/PhxbN++HV1dXYZ1tm3bBgC47bbbFOcrKysxefJkrFmzBsXFxZgxYwaqq6uxcuVKeDwe0+CYJDhpYPoOfBNvQWDENeAy+RRFdlMlOnBgDf1pGUmH4LCr0V4+GXm7f22pXsRbjDFdF/FvZ5sxIESOTKcercmdAWwpzSVeJykIgoOnIvPsYcU5kqApp/NAbSvWDipQXJBbcLgoF03+8TchVDgU+HwzAGBWmx/XtfkRZhj8tjxPNz0nLVKhECGBzkJCKtiQrt9vI1pXd3Tjw/wshBmt77cVeSUgK9zU0wLoKCREBY5gfk8Y70TFZuiJKhVydmJIKK2F9F02WkJqiwLAH+4GAFT7axQKCT3FzvnuBssKCQA46a+xXEfYiSa5vHRFeKsSxhUGF07Dv9xWJqaVNAXxfvJ/aQQoo1s/ZmAGrhqdjeJcXoGYl+XGgzeXwNcdxcZdfO7Uu2YXwReI4L/fqKfjV4X+FNRSDyzL4JE7yuALRFGUo3/fkh1Dwupj/JXZhYr0p3qxGF0sg2gkPkdNaU4qqSTEQkL+245CQnTZMGuHjriVGBKHDh2ioumg/6JfKyRcLhdmzZoFAJg7dy5mzZqFpUuXoqioSMycIQfHcXjrrbcwZswYjBs3TnP9+eefxyOPPILHH39cpL98+XIcPHhQdOmwgokTJyI93Vr+997CZfdwu9MQyS1LNRcOHPQd2N3GychFNKvAcrWItxiurou6yggSNDtQBtcAIJw/GFApJEiCJSOLLlBM4kdhmk/nshHOq0A0p0Q8LusJo0DIHZ8ECYHh6GKUcAle3NOQY2Xjyxis/o2ULAXifZGWt6LLBvV4Mgo3EAC60gjNhmSiYjOo6diLISHNUatBLYXgnBHKdq26lMSjuBF89SNGTTL8xUIDoRYgv+Lk5wSlh1n8BsBYiI1ynKiMEFBekAbIXpMeF4P8bPtLbksm9n146zk/2438bOMyNPfDDuySLc71qNx6yN8ElwsIRey5Q0i0+b/aGBLxjwkp5a0VmAVeJbVjBGkczSv05Rh+wWDQ2YBOAFKqkGhsbMSGDRtQVVWFqqoqAMCxY8c0LhskvPzyy3jnnXdw5swZ+Hw+lJeXY86cOSgtLcW2bds0ConTp0/jP/7jP3D+/Hm43W7cfPPNWLJkCb71rW+JZQoKCjBjxgycP38ezc3NKCsrQ1lZGerq6vr0w+AgEei7H3AH/Rj9zjnSnF9aP3o1Kc6KL7nOgk+Z6pBQDVzC036KgrWlOqpLdniIk0YyZh7Ti3yQ3HBEhQQlDQ5AmJIBa3t68UFNxV6WDX16ZooT4RmmVYRYVZjYiYkhQNiFjUQM+mDDXMgoroOZ4oIvq9+mofIkBejvqxm9tKFxQ7CAs5yZRXmslwmDn7vGwYbNkMxAj/Fm2RBcaaKJnu/9bZnkIClIqULi9OnTWLduHYYOHYqKigqcOnWKuu7Ro0cxevRoLFy4ENnZ2Th9+jS2bNkCn8+HtrY2RdkjR45g2bJlSEvjfcD+9V//FZ2dnaivV5rOPfroo/jrX/+Ku+66CxMmTEBVVRV+8pOfAABmzpwZX2cd9Gk470MHDujAUoqDjFqQt5QyUaChpmnWqLYEaYdej45kiktHJ9VItPVDokCXntWERuwvqY/UcUEYaC0kLAa1NK9pAypCnA0LCaVaRmVxQckpvYWEtZ5byTCihqiQMMymYUyfVqgjKST0lDlGLUYpMn84oEfyXTas3S81P3rzS3RpsM6aRFuwyEvCGCgV+tYboHs2rceQ6KOfMQe9jJQqJCorK7Fv3z4UFBTgmWeewdq1a4nlamp4P8QhQ4YA4M1jfvjDH8Lr9SrKsSyLdevWITtbsgeLRCL4zne+g6uvvhofffQRpk+frghaKaCqqgo7duzAww8/jIceeggAcPfdd+PgwYOora11FBKXOvqgsOHgUkA/+9RSsGvbnJY1t5Aw3fgkpOPkwemc14khoSMwk7JsmKV4kwpaNGu3OI6WlTNJAG2bCusGg3tqqKKS3yOToJZGJNQOOXpV1W0QFRIJ+k4kwmVDoY7QKDhMBPZY+7SWDL1qIRF7TRgKPbQWEiYTVnLZMCdlNKR9zUKivyNZLhsCXatPsW6QTtVpwaUhHv2UXgyJRCBeCwm36E6VGIVEPLw4uPSQUoWE1+vFCy+8AAA4fJj3+92zZw/8fj9yc3PFtJ/Lly8HIGXbaGpqwuLFi3HzzTdj5MiRcLvdOHLkCN544w0ASl+jDz/8ECdPnsTXvvY1/OUvf8GCBQsQjUbBqmzChParq6uxadMmhEIhvPXWW7hw4QIAYN++fYbZOxw4cOBAg373oU2gy4aGtJXBIC94FDEkKIVDq1lBYtQN2ybC1i63FWg7YtS1VE492vSsNNdk8TFtxJDQpo6ljSFBQtJiSBjQ1VMuGAksZnwKJGkVDVb7bUfBIsAt7sIaFDJVSNDxSxL+9HaODS0k+tiGRh9jxzL6msuGnoWEeqq4XXQWBEYQaCfDSiRehYSL5tkE/benv89TB4lFyoNarl69WnG8e/du7N69GxUVFaJCQo38/Hzcdttt2L9/P958802EQiEUFhaioKAALS0tuOGGG8Sye/fuhdfrxbvvvgsA+OlPf4rnnnsOt956K5544glkZvKRc4WglcePH8fOnTvhdrsxdepU/OIXv8Bjjz2Go0ePJqH3DvoOnDejg2Sg32kkTEFr6hkSd2FjSMDqw7xtbQlSDT3rCvEM64LAObVVgEUhzKoLiF0LiVS82ZQWKHY5kFb9ktsGf87T1Qjk5FNRiKgGan/wLLGswKfYKuH+JEohcaDtM8WxXKC9EGhCa6gdE3JGGbapCLKnKkOqE4gEkeHig2z/rZXfgPFFuqn4PddtLTOEnoBe469DINqDMd5hunUFoSdsEEOCYejuhNn7gpT2U9dlox/FkOjvSFpQy9jfhMWQUJWjin9iAmFOJisGEOk3LVhqlw1rEXkcCwkHQB9QSJw4cQIAsGPHDqxYsQIbNmzQBLUULCMEeL1ePPnkk/D5fJg2bRoAPkBmWVkZnn32WYUlw9mzZxGJRPDpp5/i61//Oq6++mp8/PHHWL9+PVpaWkQLjeHDhwMAHnroISxatEis/+qrr4r0rcKJutqP4OgjHCQDDItQ0TCEC4f1etM9A0YjNGCkYZlQ0TB4ms+Ix9GsfFO66sWif+w8Yrn9bAcA4HBuJhb1eBFN9xLLCQgMmQamNab4JTyPkYxcBIfNADo/AEBeXPHChLJyz5ArASiF0LsaO/Db8nzxOC8UQbvHJWatCAy/Gt72PehysyK1WlX6ypuau9DNsviwIAsAEM4tV/Ei4Y6mTjG16FhfECeyydmXpnd046NcKb3cpK4APvNmiATTo1EEZduHN7X4cFyHloCR3SHNudJg2DAdp1UMCYRQkyFlGfhKYwd+MzAfgKSc8EQ5hFTbfjd09OCLTCUfc1p96GGUomRA5ZtNm4oVAKazxfgb/OJxQ4RPDf6l5i68VyTNSSqXjQR9KOoCyvUEJ3Nx2FDLW3qaKSRYMBjbw+JEGl9XLjCTFAJ/ubgPi0rnIMxFcLzrtCV+E+Wy8bu6twEA3x11v27dGWO9OHG+GxOHZumWGT84A/lMju71DA+L8kIPbpgkpQy+/eoC7PikHTmZkuvYsNJ0FOa4ccMVUrkRpRkozfdjkqr9gYVpyExj0d2j7dvYigxdXqaPykZ2hvTMDitJx5nGIK6rzMEHRzoVZQcXp+GacV40toXgC0YxaVgWzjb2YHgp/4yPG5ShyeYxeXgW0j08/atGZ+PgFz5cNdr4XdsbmDnOa1vQ9GayGFjowaDitITyZCYAjyxLx8Rh2nmn/ubNn5yHrftaUFGk5O/mK/Pxp4/aNPfICr40LQ/bDrSitEBLY0RZOq4g8EfC6IEZGDdIOS/jtZC4YVIuGttCGFGmP98FDBmQhhljjOfhnIk5aKCkd9llBrwMkXKFRDzIyMjA+vXrEQwGcfz4cWzfvh1dXV2KMn6/H93d3fjqV7+KH/7whwCABQsWgGEYvPjiizh+/DjGjRuHOXPmoKKiAqtWrUJ6ejrGjx+PqqoqPPfcc3C73QgEApb5c9J+9ic4GgkHSQDDoOuqe1LStO/Kr5iW6brqHngaP4f38GvoGTAKYM0/CSxYhbgRHG6cFSnKsOic9U2kn94nnusePQeBkdei4N2fSucmLAT26Fuidcz5Z7BdzUBsDa/j1as4al34fXANR4FOpUJijL9HUeP2i534bXk+Ihk5aF24AggH8c1jf8IvhxSK5dSm//NaeSFXUEjAnabL14iApBSY0+pXKCRuaPFhVyEf9+iuxk6U9oTxp2Je2Fp4sQufZ6UhyLJgACxo9mHbgByxnYpgWNFOdjgKX8zRV+Ajk7CbdU1HN96I0RnQE0ZTmnTfHz3bjOeGFhF6ob+rdk17t6iQWHGuBYNlfAl1ljZ04JXyPEW9MoJwd3OzDwCwP1dapE7sCqIqRzp2U25xBismITfoAfCF5tr0jm6lQkJ1ncspAWSKDIDfWc1hMzHj4kX8pdAkdyGAAe5cNIU7TMvZcQdgAFwVdOFEWhQcONPAk8EoP+ftxMGw6qYVT6yNQq8b/3p7uWGZGWOzMTQrT/c6yzJ4cGGp4tyo8gyMKlcKPplpLP7lNmU68JJ8D/7pFmVdAEj3sPjuXQMBAP/1aq3CKiI7Qz8+zq0zChTHy+cPEH/Pm5yHH22qBcDPgfsW8GmDK4dI5eW8fPX6Yg39xTOld9Siqwqw6KoCTZlU4EvT8m3XTXOzeGCh9h7ECyH4KKvjD3HvjQOI59XC+6DiNDx0qzaN/NCSdPwzYe5YwZAB6VixiJyifpkOfyR87QbtXJH3206MitJ8Dx6+jcybGt+8qcS0TFlBmub500NfznTopP1MDC6ptJ+VlZV44oknUFRUJKb9zMjgP0D19fW48cYb0dzcjNLSUnFyHzp0COPGjUN6ejrWrFmD5cuXY8WKFWI7s2fPxtGjR5GVRaeVdNBf4SgkHFye4GLCBnVMBjCWQta5BVFPlvbTLKAjeVeYUUiNehRooj8odsM5sku6fVcDY4gWFIxy158EtZiTKMtWl8G9pg00SUtPHf+BdM2oHsfIYkYI1hbUt4bR3QpU01CXYgnpPThwlhbytO5NRpYXetYGDMMq6CszdWjpCVYOdgJOWo3IbyeNqTX6jo+EA+sQlEguizEqkpX1o7dxqfTDwaWJSy7tp8vlwtatW0WFREEBry0+fPgwli1bhrKyMhw9ehSbN28GAHR0SLsXr732GpqbmzF79myMHj0aPp8Pr7/+OsLhMIYOHZrAnjvoc3D0EQ4uW8RWZ7Rm2RYjjrliwgynyLJBY9+gvsgoSpDj2jGaZ5lmEUZys7DEmwVaVmJBqLOBmPkAK84ZdMbI5cFOEFC5xYJGsDdkiGZUGVE5JLlsUAYthL4wraahvm/0Ci99sLSlDbqj5y7BymYEB6USgKTgEFJ82rFesCrHCDzbSS1IR/8S/GBfgl3qaxAsJFwWrQP0LCr6Gy6Vfji4NNEv0n6S8NRTT2nOTZkyBQ8//DDOnpXMc12xHFLf/OY38U//9E/i+c7OTmzbtk3c7WhoaMDGjRuxZMkSrFq1SizHsixeffVVVFRUWO6fg/4EZzXg4DKFsDij9hO3tqgRPzIUaT8F2PbVZ0gCP8FCQvVbGYOCP6vpJTVLZiKtPi9WrsVDV65AUHfLjmWI26CKoFQhKlAMmJQrY9RKEo8lgZTciJpnjSKFwBwHzpKQTR/czcBCQtdlQ8YJxylokKoI1209WxYFuGRbMHCOhYQDGxBiTVrN4nGpBF109BEO+jJSnvaTBjU1NQCAIUN4x7pgMIhQKKSpX1vL++KVlEi+S0Kwyo8++ohIU3APqaqqQiQSUQS0DAQC+PjjjwFATP/pwIEDB5cUBP/wJO06Ci4bHEV8ClMo0vPJThvt+FMIkIZWDYyyDC30LSRUO/OG7g7q7AmJgVEMBjsZ94xdNmLWDUS3GLpRFVRZQmkjBYgcSrsKddvGx6Rx4DjO0jygLWukJNDNsiF314DS8oFUR7BaoFVIcAZWL7R1HQsJelx6Pep7EC0kLErml4ogn6zsJQ4cJAIpD2opZLk4fJhPQ7Vnzx74/X7k5uaKaT+XL18OQMq20dTUhMWLF+Pmm29GeXk5WJbFoUOHsHv3bgBQxICYO3cunn76aXz44YdYtmwZZs2ahT179qCqqgojRozA1KlTAUhpP7ds2YLz58+js7MTr7/+uqiIOH78eJJHwkFKcQkucBw4oIIQy4DWQsLiokaMIZGQ5PJyhYR+sD/lsXm7GoUEY1+UYjQ/KMuToHLZSBSMXDaMlDt6TLgM+DSKIWEE+T1hVe9n2qCWfIAQUEl71DEkrFhIJCKGhM5zyTBKlYSZy4ZwXc9lQ31eTsN6DAlrKXOt4pKMIXGZLUE4zlo8lkRAiCFh3ULi0hDkLxXFioNLEylXSKxevVpxvHv3buzevRsVFRWiQkKN/Px83Hbbbdi7d68i7kRWVhaeeOIJTJ48WTw3cuRI/Nd//Rd+/OMfY//+/di/fz8APgOGEEcCkCwpDhw4gF27diEzMxPXXHMNvvGNb+AHP/iBrbSfDhw4cNDXEfXwgX8jmfpR65VgxHpsyDz7kCDYcWnmWQmyYyvGHM6Ce4dJBgDSWlIjNHOCObucsD7NnHDEgCHT6qTiRLhlfaOUqxXl9ZAZ1RfojOr5dKLBKeipXSGMXDYoO6RulVohoYo7YgTB9uFCLB0qyc/8WNcpDOgJa87rwdNRD2Sapy7kolE8U70ek3LHaK69GkuVqQYLBu6OeiCnAK+cfwsPDl1q2IY7FlRWL+Dk2427FcfycvIsG2817MIpXy3+ZYS0PuuOBPDL0xtxe+lcjM8ZKVkwMAzfr5wxWFByrSF/VlDtO4dx3hEAgDP+89hc9w4eHHo38j36qUATibICD843a9PpXkroDPvwwpnf4cvlN2FUdmJjqPnC3XjhzO8wJLMcZ7rPi+fnFV+D6fkTE9qWHN5Y+lWvQVYUEi4VQT4hewIOHCQJKVdInDhxAgCwY8cOrFixAhs2bNBk2RAsIwR4vV48+eSTiEQi2L9/vyLtJwllZWW46qqrcP3112PgwIH46KOP8Nvf/harV6/Gv/3bvwHg41lMnjwZJ0+exI9+9CPMmDED1dXVWLlyJTwej620n04amP6Ey2x7woGDGKI5JeiasgSh4hF0FWKLs45r74fL16Jb7MvREvyBbRTLhwtluexiz1vH1cvw74deQZebAUYBw3OH4x/qz2Bk0WCEAPSUjgXQKmubRV4ognaPC1xWEXwVk3i+qzfFrjPwT1wE+A/IqpgoLBRckd8DPaVjwaV3AuCF0YfPtRLLAQBcxjnoaYXw4p4wMmRle4pGAD114nE4vwKIRgAYZ1eQY26LDxXBEEqDkkJFa9Fg7V14a1MnBvToK2iMLCSMdt4lSxNGjCHBAOgZMBpM80kq3rhYfZoulfdEcTYD6InNFz1XH/n9G+sLwhuJ4lBuJrEsdYDQaAhhLoKP249pLrWGyGlD1bu2nWGf+Fs+j7NdmfBFulGUlh+7RsbfO5WpUeWWGRmslKb2SKd27Jt72gAAh9qPxBQSkoVEmIvg445jCVFIpLNpCEZ74GGkpetnHZ8DAM4H6ntNIbFkVhGOn+vGnz9pj5vWV2YX4vcfttiPm5MkNAb5d/vh9mMJV0h0hn2IIqpQRgDA31o+SapC4toJOSjwulE5RPm8PrCwxNCN4xIxkOjXLhuHDh1KNQsOkoyUKyTigcvlwqxZswDwrhmzZs3C0qVLFWk/Dx06hG9/+9t47bXXMH78eADA/Pnz4fV68T//8z9YvHgxRozgF+LPP/88HnnkETz++OMi/eXLl+PgwYOiS4cVTJw4Eenp6eYFUwDn4VaCNuWhAweXIkJl4yyUjlk8ZOQinJGrWyqHM/+8RDNyUBSOoCjMqx0i+UMwuf4EAoVACEAkpwRyhQTHsBgeCOETjwvRzDz0DOZd7hCLTxEFEM0qBPxydm24bMhEZY51wzf1y+A+fwWCQiI3om9hwKXnAAjELV6M8/dALsYHxs4FPntFPO6a8mVkHX0HAFkoimbkAr4mRLxS7vqMKIeJvh4EdRamw7t7qBUmAqZ1Bgyzfxi6bFCuj9nYaEazCuCb8BWkb5cCTxeGImjx8DuegwMhnMtQKoQYivsPAFlRZcd1FRKy34OCYdzU4sNn3nRRkaGkQQc7mS/UgxeRKRDk5OTCO3+Nzt3BHk+xukkSruMKzJlAFOW4ce2EnIQoJMoKzC1oUgFX7LmJcAbWYDYR1qHponxW7cLFMpg0LEtzfmCh8T3oz4K8HP3ZQuLKK69MNQu6CAaDzgZ0ApBShURjYyM2bNiAqqoqVFVVAQCOHTumsZAg4eWXX8Y777yDM2fOwOfzoby8HHPmzEFpaSm2bdsmKiQ2b96MgoICPP/88zhw4AAikQiuuOIK3HXXXeA4Dp988omokCgoKMCMGTNw/vx5NDc3o6ysDGVlZairq+vTD4MDBw4c9BooF2dGgSJFM3610GNGWuXCYNSuAKJLh6oPwk62FENCQYGSOTpo+SPT5Xf35byryjHac4ojYpYIoRxZoHNbDNootGlUR8oEQbpm3hofQ0L/ujy+hFqZYkVsVc8SvbW7FQsS2rK2skYwynFXKCQU8SSU52iF+agFyxt1qaSl/STNodg8d/YUEguX4OJDnX2JHnpKDsGtyEFycKkoVhxcmkipQuL06dNYt24dhg4dioqKCkU8CDMcPXoUo0ePxsKFC5GdnY3Tp09jy5Yt8Pl8aGtrE8udP38eFy9exKeffor7778fmZmZeP311/GDH/wAABCJSC/GRx99FH/9619x1113YcKECaiqqsJPfvITAMDMmTMT02kHfRTOasaBAzokYlEjaADUi13DfBdKZ169xZVaAUFQSOgJSpyijPJXorJsWAJj0l+bC0y9Wi7OXvBJQ4WEmHFBOyJUigxolQN6FhlEBQC1Ak2lpKLMzgHou+FQu2wQpGlS0D+G42QKLOU1PcFRVEAIfygl96hCwWEGFS9ifpPECkBGSpVUW03YRV8VESULicQrJPQsJNgkW0hc7rhUYmE4uDSRUoVEZWUl9u3bh4KCAjzzzDNYu3YtsRwp7ecPf/hDTdpPlmWxbt06ZGdLwdPa29vBcRy+973v4dZbbwUALF26FNdey/szCm4cVVVV2LFjBx5++GE89NBDAIC7774bBw8eRG1traOQuNTRP9cyDhz0OvR29O0R03nw9J5HMwsJorRIWuQq1Q1SCX1rCNp+mxp5UFGR2pR2uNXDYkxJnoHBqKycpovjrKf91Bi5kLkkcWCY0EM2N1gx6KhWOSRXBsQzM9W7h3rCNEnJQGutowfSY0DK6KEObKqwkIAk5BkJ7HpBLdVQlrP2gRSVGVYjsZpAUkhISFZq0d5GX7PwYJE8hYSehYTLsZBIKhwDCQd9GSlVSHi93rjTfo4cORJutxtHjhzBG2+8AUDpaxQKhcCyLP7jP/4DX3zxBcrLy3Hw4EH4fD4wDINhw4Yp2q+ursamTZsQCoXw1ltviWk/9+3bJ5Z1cCmij60GHDjos6AUzAVTasNSqlSDQgpSHcUAp1BI6LgkaIIYWAhqadA1q28I228URUWj6AwwXGEaC/vk825O/5ouLcrrRF0R1VySEreKrMl4lN9dtbJADGpJ04qqrr7LBt05Ej96ILlskKqyHBBlhOv6MSTktdXKCVpLAlsxJGJVkmUhoWnoUkAfFxLliq5EQc9CwnHZSC4ulfSlDi5NpDyoZTxpP/fv348333wToVAIhYWFKCgoQEtLC2644QZF+UmTJqGsrAxvvPEGLl68iJKSEkyaNAmfffYZvvjiC0ydOlUMWnn8+HHs3LkTbrcbU6dOxS9+8Qs89thjOHr0aFL678CBAwf9Cgm1kNBx2RDTBkK1HUqOqaAQ2xl9JQaxAiQFCCmopVUwmh92CUDlskEqZxBDgmjlYcyai+MsxUggwUq3jaaSfBwFwT7KcMprUFpkqO+0trQRL3G4bOjRpBzLdlmGDAFNwRaUZRTrt8MolSh6QS0FxUJzTxv2t1aJ2TYEHOk8ifFeZYadxmAz0lgpOKiVGVHjr0N3hM9KFozqBwOv9p3DsKwKS4EMhb4ky5ogEAmiqacFgzPLk9NAL8MX7kZbuBMVGSWW64oWNQQLCY7jUO0/h5FZg20JuS2xrCxqNAabLdNy0P/BcRxO+c9hhM355ODSQMoVEvGk/fT5fJg2bRoAPkBmWVkZnn32WYUlw/Dhw/Hxxx/jN7/5DbKypOi6X/3qV8V6QjkAeOihh7Bo0SKx3KuvvqooZwVO1NW+jWh6DthgJwAgkl2UYm4cOOjbGNIdQlOaC9QCHk3AwgyLafoYlmg7cZWfw/k0BvlsFjRiqUzgiWQXAdEI2GCXjAnjoJZclM+sMQm5OAGt4KgHPZlJFK71yqkUMNe1deMvhdlwM26CM4RyjGe1dePdYt6VMZJTAlxsQGjAaADVmpqk35O7gjZiSJB7OsYXxOfZUpYpsuUFxRwBrygBpDGTt+mS0U2PKoWnEe58Pl0LBdTz1WVBIXFdmx/vFXk159UWEgN6wmhK0y679nRqNzxert2K7466X3GuMBRBQzp52RaV7Tpz4aDm+rlAPc4F6kVTfAFvNexCgUeZLWf9uT/iW0O+Ip2gVAAEokH8ru5t03I1/jq8duE9XJM/GXOKr6IjLmOD7JISP/5w4c+oDdTjsRHL4WHNl8f52S7DdJE0yE7n78eMMdr5Ey821L6BjnCXZh7RwEghUdVxAu81fYibS67HFbljLNNuDrURz0fsBHdNIiYPz0LVab95wX6G6aOyzQv1Ij7uOIY/N/0Ni0rmYGLuaGIZJzPgpY+UKyTiQUZGBtavX49gMIjjx49j+/bt6OrqUpT5h3/4B+zcuROPPfYY/uVf/gWZmZnYtGmTqCwIBHhN/pw5c1BRUYFVq1YhPT0d48ePR1VVFZ577jm43W6xnBU4aT/7NtrnPpxqFhw46Df45/OtAICOMvsL8O4Rs5B56m8QxAfOo8wHr90yV5sykF02rgoA15xsRHtpOsLqRa2MZsd1DwIA8v/8CyJ/Cl2AzEgDACqZXLyGC8R6Bhxr4I4J1xGGQeuXHgcO/tKgPoObWrpwU4sPbYMI5swM8LOTjQgxgCfGr6iQyC5A68Lvw910EmjXV0gI+EZdG8b6e2KJTSX87GQj/mdQAWpj6TTbbnwEqNlk0ktgUXMXPs9OB+dOR+vC7wO7yGPuDUfR5SYFHpXgjvVN4C0w8noAx2PXpLuWLkvd+bOTjeiamgMOyjWBHuQctC78Ptijbyj5EQJKEiTfua1+zG3143ujlDvR8j6srG5CbYYb6yoKqPghoawnjIdqW+DhgM4rlSoUhRm8QapGIXtGtisTvki3tq5AwoaITxufoivWblu40xJ9Ek/CKCQiqGVTTwsAPsaBh2J5/Mgd8VtSpHtY/OieQXHTIaEjTDf3STAaTYFuJ8GyhwZqpVhfxeKZhVg8szDVbCQUyZpr8aAzxM8jo/nUlzMdOmk/E4N+m/YTAFwuF2bNmoVIJIJnn30Wn3/+OZ544gkUFRWJaT8HDRqEmTNnYteuXdi5cycAIDMzE//wD/+ADRs2iAEw09PTsWbNGixfvhwrVqwQ25g9ezaOHj2qsK5w4MCBg8sX1oI7WhMTTGoZuTCI9fSVGHotalslxWtgKTsjCEjkcRIE6DAD0xgQnLq/jLoMf8JjxBdlEEajWA8Kci6P4lhXhaQyN9GLz8FSDKpLVOLEFFkyxYBHppDQWpvQ77iqLSTcqnnjjUTR6XZZcmnRZAexKDOr4zgwUN5rRVBLnawYeoK6vL9Es3yDOBR6oFVVCvTsOkYlK6OGlFki8XET+h2SGGXzEooA4iAREOPiODPjcka/Tfspx6uvvora2loAQG5uLrZt2yYqJF577TUcOXIEd9xxB4qLixEMBrFr1y5s3LgRADB06FCRzmuvvYbm5mbMnj0bo0ePhs/nw+uvv45wOKwo58CBAweXLZLp4ylqBswXJnrCjCaGBGucZQOQBEVOJcoZ1dHnyxjCbn9EZxyVcQLIMTPEY4tBLQ1H1eCikify2KnpUCmkGEZXSDeykGDkCglDnQNHH9RSdexWaVBcHLmcIU3ZPLYTm0NtuaAcKyUnUcqglmJtRq6QILhAWBBIJWUW3egItNWZTUzrGY1hAgToZGaW6G9IpnDoCJ4O5HCiRjgA+knaTyO0tbXhl7/8Je677z48//zzCIfD6OyUzAAXLVqEhx56SJEKdMWKFbj++uvBcRxGjhwJAGhoaMDGjRuxZMkSrFq1SizLsixeffVVVFRUxNFTBw4cOLhEEE/6S0bcCrFSi7o1+b/SJXPzYI3wzGhFKz1zfatQWEhAnyQX40PDpOLYqkCnf04QmM0p2rOQsTx0srgenthBmBBBxGMkiHJRUPOrmidulX2DYKVhZcTjNUxX79QrlBqM8lhelkY2ZxXJbo0tJBINOxYScgWJ/LfpK8UC2Ngc0MsCcTkhmSoDRyHhQAnBqtDB5YyUOnJ5vV4UFJj7U9bU1KCmpkY8DgaDYqyI1atXY9CgQbjjjjsAAH6/H5WVlWLZiRMnKpQRAG+Z0dPTA4/HAza2e1ZVVYVIJKIIaBkIBPDxxx8DgJj+04EDBw4uZ9AuGox3yE2oGEhUkkjKaM6B47RRuolZNtSRGjhzriwqYvRoCQqJKBU9ZfhJOws2q7VMudKMnUl9mzomeTXBOiHCCCzoKSTU1htxWEioTogWEhaGk1HqDywPhbFgrKQmDwiocLfQ4Zc1s5CgY1FVh65WYtOCJm5/1XHZkEB3L+2JkLZSyjq4ZJHIODAO+i9SHtTyhRdeAAAcPnwYALBnzx74/X7k5uaKaT+XL18OQMq20dTUhMWLF2PmzJnYvn07li1bhqeffhoAkJeXh2XLlon0a2pq8G//9m+48cYbUVxcjC+++AKbN2+G1+tFaWmpWE5I+7llyxacP38enZ2deP3110VFxPHjx5M4Cg4cOHDQT0BrZm3LtYO+jr4bgblCQh7fgZEdGSskEqO/d5usuRS8GI4hAyOOrS7taGNI0JSgdxehu99C3ARJTJQpJKIGPbXkdqAcT42FROyalVmQeAsJJfTTflK4bMhjSJAsJChoSMQYTR0jCOWsvCL0Ylok0txbsBpxLCSSrTRwBE8HEqS4Q868uJyRcoXE6tWrFce7d+/G7t27UVFRISok1MjPz8dtt92G119/HSzLYtOmTRgwYAAAXnlRWChFxc3JyUFxcTE2btyI9vZ2DBw4ELfccgv++Mc/4pZbbhHLCWk/Dxw4gF27diEzMxPXXHMNvvGNb+AHP/iBrbSfDhw4cHDpgXbH2bqowLGxTBKi8K9doDCEX0btckQLCeWhkJ7RRShiV/TRD+JoDEb+Q+GyoeqXKQeJiXmhrWBsISGUoaWrV44UQ0JYsMhjMyiCWmr8bKLUUi+rUUgo6wk8WHPZUN4lq2P9Ys0fqOsfbPtMdsS32x7qRCCqTQEKACFOyqfybuOHmusv124Vf9cHL6Iu0IjSdCk9dmtPO95p/ABfHrgAHzZ/xJ+M0gnykssGvcpGYQcT6JB+x1KcnvWdw2l/Le4sm6e1kqKEK0kuG8FoD16/8GfcXHI98j05OND6GeqDF3F72VyxjD8SwNYLO3Bb2VzkuONLy7jz4n4UePLE45+ffFEc838cdCfKMop1637cfhTbm/4Gr4vPgMQYxNP4sOUw9rd+inxPDpp6WgEA3x56N/I85HTO7zZ+gOFZg8AlKUbHia7TOOU/h5tLrk8o3W31O3G0i89UdHvpjRifMyKh9EmIcBH84cKfcX3hdN37dbGnFRvOvYGitHwUePJwLMbjv4/8puh+BADvXzyIfW1VeGjYPch2SwH6dzTtxaH2I/iX4V/Hpx0n8GnH52gJtWNM9jAsLp+Pdxs/RFUHvxlbkVGCrw+6HQCfDWNb/U5cV3QlBmcaZ5rxR7qx9cJfcFXBJHzU9nd8acBsFKbloSvsxxv1f8GdZfMlhab94XJwCSDlCokTJ04AAHbs2IEVK1Zgw4YNmiwbgmWEAK/XixkzZmDLli147733MHjwYNTW1mLevHmabBgFBQX49a9/LR43NzdjyZIlGDJkCL75zW+K5ysrKzF58mScPHkSP/rRjzBjxgxUV1dj5cqV8Hg8ttJ+OmlgHDhwcMmBerFPWmRo63Ze9TWw3fxiNlQ2DoGOegRGzNKlKrpsWLDUuLu+HVlRDhhF5mNAKIIbW3yY4pbSNmpdDxgsbuxASY+xsELD1aKmTgwPRmX8AMO7eSs9eewEThXUUpO5g7CjJKanTFGkMGIcD+hkHTHkUXKjKe+JYHpHN6al8S6ebKANSONLkSxOBgdCMRKcoWXLg7Wt+N9BMbdRTwYAv3hNnZqQFXb15QoQTwYAKVXdA7WtWCvQg8plw8ZqW6404BuU/Ta4xUJMiA9bDuvSlqfY01NayPFWwy7cXnqjePx+80c4F6jHaX8tznTXxRj2K7V6uvwJ1iYWYkjIOu/qqJd+t9cDHuC4/ywA3nXFTcMEAcI7hZR1JB580XUWNd0X8GHLIdxaegN2Nu8HANwOSSHxWccJnAvU46O2v2NuMV2mOT0cUCinlGP3btMHWD54sW7d7U1/AyClZmV6ujVl5OrGEBcWlREAUBto0FVIVHWcQFXHCYxOKyVejxdb6/8CAAlXSAjKCAD4c9OeXlFIXOxpxWl/LXxhP74xZAmxzF+a9iHEhVEfvIj64EXxvD8SgFemeNjXVgUA+Lj9GGYXSekzD7UfAQB81vEFdjUfFM9/7jsDAKIyAgDOB6RN2cZgC84F6rG/9VNThURLTzvOBepx7gL/zL7ffBCLy+fjcPtR1AYa8EnHcSqXjUOHDhm246D/I+UKCTsIBoP4+c9/jmXLlmHw4MHU9fx+Px588EF0d3fjxRdf1Cgvnn/+eTzyyCN4/PHHAfBpRZcvX46DBw+KLh1WMHHiRKSnp1uu1xtwHm4HDhzYA22QQINyMqEuXDQUwFD+gHWhe9w8Q7rRjBwAIR0uOICQVWNqFy9wtWquSL79C1p8CBWz6NJjmWFwdYe5YprG/eO69m5wrBttsnKj/T2K+upxltO7vtUHDCOPwMSuID7LybCcZcOu/kLPTkXTZuzUaH8QX2Sla8rpU2CQxgF3NXYiODANfijjYrgISplZbTHFAhcFGP1lzvBACCP8PTiVlQakeyFXSKinrzCr5Kcj3gFonfogCt79KQBgRCCEvFAE7R6Xok6ioKSnP3bJMrc3i61A26rksmHFZ0MnqCU9BVMIghHJhSUesDqxKThZzBtSbJxkIBH0jQRHtSKPWL8fZzHRKAmTBnOrAbuWQPFCaDVK8cSr5wpp/hG+FhpceeWVutdSjWAw6GxAJwApVUg0NjZiw4YNqKqqQlUVr8E7duyYxkJCjU2bNqG1tRW33347amtrEYlEcN999wHgXT7mz5+P0tJSeDwenDt3Ds8++yw+++wznD9/HtFoFGPHjkVtbS1GjRqloFtSUoKbbroJjY2NqK+vR1FRETIyMlBXV9enHwYHDhw46DVQL4L03S6oYVBV33FA42lPqEwRKUHTtkWXDUultYsyTQwJAs+kgJVmLi2Jhq7LhkooFgUuFctUESk0qUalY5fhHOEQNWlBip2hnlHKY8Gtx4xfuduIelbaC0uqD11ekqWQSJCgbieoJafzOxkgBfmMB1KwTOX4ceCk3WE7SppegcWguDr862VJIZXre2PQ+4hnBPQURlbupLFSkz5mjKYM0VBOoEfLnYNLESnNsnH69GmsW7cODQ0NltJq1tXVwe/344477sC8efOwYMECnDt3DgAfFHPevHliVo6Ghga0trYiPT0dHMfhrrvuQl5eHh588EG89tprCrqrVq3CU089hYkTJ+IHP/gBFixYgDVr1uDixYuYOXNm4jruwIEDB/0WlEslgqWCdVDu6cvNEjT6CCtLOyPpNtGfS7KESxGhQUPC+KLxKk9PUWAXiRIljPhRWEgY9Y9iJ1ZfIaEEKwrR9GATvMJWKjQMLCQSmsVCAslCQt5FyxYSNl025NBQiGPMJdPxxO7guxneYoakkFD/7g8WEkY09IRUeVyORI9vMqHuT7LvjxUkjhftPaPJNEOTFUNdgsSxZCXkaCQuZ6TUQqKyshL79u1DQUEBnnnmGaxdu5ZYTlAuDBkyBABw1113iVYUPp8PK1euxIwZM7Bz505cccUVePDBB1FWVgYAmD59OoYPH469e/fiP//zP3H33XcjGo1iyZIl+M1vfoO77roLAK+42LhxI5YsWYJVq1YBAKLRKPbu3YuTJ09izJgxSR0LBw4cOOgXiCuGRLLYMNJIxAfJ5YDSVUVdL952dc8xhq2kdHHHaHkjcsMwplYDnOhUA+I9cBkJxBbSfrJqKwxGHUMidt5kWOlUBvagnvK9aSHBQRVbgdA4tUJCEL4tKAuV89lo3sePRFtI6LlsRDkOrtgQ9FlhjMCWEa961xR9N0zrzPUpoT/190W/ff0YMnrn6ftiHNiVng6Ny4YDB0CKFRJer9dW2s+xY8di7NixAICVK1di+PDhuO+++7Bz504MGDAA8+fPF9v4zW9+g02bNmHq1KnIyMjAG2+8IV6TZ86oqqpCJBJBc3MzNm3ahFAohLfeegtnzpwBAOzatctx23DgwMFlD2JwQgIkYUMe2S9+cd2697iJyb5CzjGgblERYwpO8UdTmyNeNW9BvEZY9HMGfaCiSQ1JIUGzQ2a5TVnfSDEkpDGwbyGh5kBy2aCfu6x86iMBViiK+ozuY5QsIUq9w69pl3rq8/xZCWop75LROyievicrhoSLxkLChtWIHVilb9XNSG/8FRYSBvMo9QoAJWjiJCQTtmJIJEChZqSQkGzvaCwkzL8A0jevb917B72LlAe1tJP2U8CJEyewefNmbNiwQbfM8eN8lNiPP/4YH3/8sW45IWjlqVOncODAAbjdbkydOhXr16/Hvffei6NHj9J2yYEDBw4uXVBnt+B3BeNaYnCcRWmYsCNO5NfGop/SZYN+Aa/aOTI3iVA1ZGwhQUVDTi5+EjwdDiCl/RRdQ2jpKH7oc8AaMWfBQkK9uFeTpXXZ6DULCQP6XZEAusJ+tIbaE9q+XEjpicYymdh4wrvCfPDQ1lCHKIi3hNpR4MkVrQmiXBStoQ4UevLAMIzKvUEC7RgHIkG4GRfcrLTs9YW7kelKl6VI5CkHI1IQ8+5IAD3RkCJzRDDSA5Zh4YnR6omGwIFDOsunfolwEXSEulCQlgdAUryoLSR6oiGksR5Fn9SWOmoEoz1gwIj1BLSHOpHOpiHDZRJI3YB8OEoXsNFIqRGMkgPAUyskdN75wWgPuiMBuBgXQtEwvO4shLkw2kKdKPDkyuYjmR/h3lhFqlw2hHZ8Yb9uXI14eJFn2SE9wTQuG90RbZBnjuPgi3SLWT4oQkiIZx11xOWNlCsk7KT9FPDjH/8Y8+fPx/Tp01FbWwsAmDFjhqLMz372M/zsZz/DU089hZdeegkAwLIsFixYgP/6r/8Syw0fPhwAsHTpUjzwwAPi+Q8++ACA0prCgQMHDi5f0Cok+HKJik1gxEe4cCjcHfXgPFkG5eMDrWWIWN5mYDZGIbnLt9gJqQxNgsNRtUfNGT1IY5Uf5he4QwMhHM+WZ9kw55OJ8MIGE9YKO3lhfeEm6i0GomYLa/LOdFrTF0CZpIQSXEPM57NEJ/ExJOhwoPsUDpw5ldC2wXEKl43T/lpCETqXKSHd4Oe+M6gPXgQHDr+tfRPXFk7D7MJpAICP2v6Onc0HcPfAmzEsqwIXgk061NSKJPKYrz79W5SlF+MfB98JgE+N+D9nXsGM/Elimk2Xvw1wAe82fYjJeeMAAL88vREA8PDwryPLlQEA+O/TG+B1ZWHF8HsAAL8+8yoC0SC+O+p+AMCfm/aiquM4vj30boUiQ2158fqFP2PZ4DtUfBuP33+f2oB0Ng2PjFgmnjvaWY1tDTsBQORBD0bUN53/E+GsdjxZX7MujT83/Q3T8iZozgsCLguWTw+rI33oPTH/fUp/49EIQj2zcdFDqnftu6NBfNr5OSbnjtVc03fZ0HfaAICOUBd+ffZVw3aPdlYbXOXpyNO9CjjQ9hl2NR/At4Z8BYVpeVTj5+7in222O7EKVAf9CylXSNjFu+++i48//hjvvPMOVfm7774b1113HRobG/Hee+8hEokoUnlWVlZi8uTJWLNmDYqLizFjxgxUV1dj5cqV8Hg8CATM072p4aSBceDAwSUHaglWsJBIzp6xnGr3mLkIDp6KaFY+mKBPWZCkGNB3vtcvwhIUAkQkpo8coFQ4uIw/1x0zvwF3Sw2YNiGfvFR3Vpsff8vPsr20tqiKUegZhDbLeyJ47GwzikMRvFfkFa+ps3Go21RcFXdwpbPFIf1d3VDJaHgaThhyKykYlL10dV0EUCIek9J+kqCXZcM/6TYwn9OtV/Qgp2dX4ZVM2JlfgWhQdGWoD0hKh4YgL/QK1hTyHduo0s+Kmon64EXxt7C7e9JXIyok2JAfcHmIdbsjAVEhAQBdESlFbCAaVJQ95eeDrAu79npCmVzJIgW1NIfaCqE2UE9Ryxz6Sh8l2GCn5decvH8cwwIgKwpTrQBQgyZLRLJR211PVEjoMWM2hh1hn+F1AKgNNOheM6IuzP2OcBcK0/I0pdWWHgwAV3c7/4IN6iXdBg4dOmTCsYP+jn6pkAgGg/j5z3+OZcuWYfDgwVR1hg0bhmHDhgEA7rzzTnzrW9/Ct7/9bfz+978XH5Dnn38ejzzyCB5//HEAgMvlwvLly3Hw4EGF8oIWEydORHq6iflciuA83A4cOLAFapeNRKzcDH0WpJ8si2h2oeY0DYy80RVHJgoBNT0a71pSOUPXCXVUQ1ntSHYh3G3aXWuAQ1ZE34pAkO3iTUmZE46g0+2K8U/uRUlIJYRYnSNC5hZVbAYB1iNuyOoy+jEZAMnawQrHcicfcX4mEIlKI+oCa5rSM+aJk3BwHDl+gp4LDaOywlCPQFwxJBIkCwv9EXixkh7Rlhm+Bb5TFVRQGhNjdvucQkItUPfa+MksrXTcBfXce/Tmm74Njra8sQufuWWe4KZEN37mLht9OYZfMBh0NqATgJSm/WxsbMTTTz+Ne++9F4899hgA4NixY6b1Nm3ahNbWVtx+++2ora3F2bNnxcCXu3fvRm1tLUIhyZ8sGo1i3bp1uPHGGzFp0iTcdtttKC8vx2effYbTp0+L5UpKSnDTTTdh0KBBcLvdKC4uRkZGBurq6jB06NDEdt6BAwcO+iUSoJBIhCm7LvnELBjtW0gkpj0j43dGXkg8qf6c967LBq1iJzEwsGRRnzPpoBSrwrggo/qrB3lvFfEtEiDNq/cWE3Xv6IRACqHaFkOctHtu+M7g/6idfBKqkDC4Fg9dSzFYkm75YpV+gmLwiOCoBNq+glQHtQR4hSEZ5Pugy7PwDFHMMZpn0eiSmMqTYvikN1nqx9pB6pBSC4nTp09j3bp1GDp0KCoqKnDqFJ3PY11dHfx+P+644w7NtT179mDevHl4++23MXLkSADAc889h7Vr1+Luu+/GxIkT8Ze//AWbN28GAHR1SSZCq1atwssvv4yFCxfi/vvvR3V1NdasWYNIJIKZM2cmoMcOHDhw0M9BHSSQsIhK4FpbXxyjaUSnjFFMBjbBFhJUay+DQpouKHf45V0xGhFR0DbetrSMpIhVBD6sxHSwSFoBl60xkN8ESzklyPRSvl437oFd9gQBivRMa3dY1S0lT4BPlHDMGfTPShmzujRIoEOZxRqc7Dddub6AlAW1lBsA6lhI6PGiN4bW5on5XCVfiyrqW7Ew6Wv33kHvIqUKicrKSuzbtw8FBQV45plnsHbtWmK5mpoaAMCQIUMAAHfddZcY+NLn82HlypWYMWMGdu7ciSuuuAIPPvggysrKAPBZNtavX49ly5bhiSeeAAAsXrwYM2bMgN/vF4NZNjQ0YOPGjViyZAlWrVoFgLes2Lt3L06ePIkxY8YkbyAcOHDgoI+DY1gwXBT0Al5ydj0SJH+aF1c3RKmQiBdGo8Ypfqg4pwgiSrpEY/ZvxTWAZOlhVFpfrWRgxmtBUDQLRsoQfpHL0bWpEJXlCiLKLC3UPBAymdhFop5QO3Q4QMy6IN+VVfdOFNg59T1VuVbZ4EFqUwmj1Ic0sMKLlRgS/RGc7G+CdZ9JRV8QkvUVEmSYKdJo3hykEnrZPpRllG2YBdiUt5X6kXaQSqRUIeH1evHCCy8AAA4fPgyAt3Dw+/3Izc0V034K7hhCto2xY8di7Fg+wMvKlSsxfPhw3Hfffdi5cycGDBiA+fPni208+eSTCIVCiEQi+P3vf4+LFy9i27Zt8Pv5gETV1dWYMmUKqqqqEIlE0NzcjE2bNiEUCuGtt97CmTNnAAC7du3q0z5MDhw4cJBUsC4gYsGAlSEJlFYjoXEUfgvUF2ga1KVCayGhpWSthEJANgn4qAymwMYucNprBpBiSCQQDEO3m2/QKPESYTxM+aa06DFzNzBMLyqnI69jgw8jaCgkbAWvT4jlOEQZfXVMIliwYh3AQCnkaNuPhyNlXZrUh2QqaiUJxdvAgjl9PEi+S4geKC0k+pjLRl9QSOi5bOjdS6s8m31l5HQZMIb01e5XGgsJAst6ZR1cXkh5UMvVq1crjnfv3o3du3ejoqJCVEjo4cSJE9i8eTM2bNBPB5SdnQ2Xy4Xt27djy5YtyMzMxIQJE/D1r38dK1euxNGjRzFlyhQxaOWpU6dw4MABuN1uTJ06FevXr8e9996Lo0ePxt9ZBw4cOOin4BgXGIRMliMSiC4bCYXeYiyxEOlRxpBgND9MyqnPC8HfCAU0fTNe2RszYMKHVdhTbNhtXV9xZBX0FhJ00FVIJGHvuzcsJKy0EWTtcRQ1COio5k2tGlE/J4kUaDvCkkuvPbIcdd14XDasoKb7AoLRHqSzaUltRw35GGiEVI4Ts8YkUiiN18IFILls9A7k7SbaZYNK8UfQHNDcmajaZUMz+S9VGyAH8SLlCokTJ/iUXDt27MCKFSuwYcMG0R1DgGAZocaPf/xjzJ8/H9OnT0dtLR9dfMaMGYoyaWlpGDx4MN577z3F+e7ubqxcuRKNjY0AILpuLF26FA888IBY7oMPPgAAsZwVOFFXHThwcKnAf8VtyPjifXAuysxBwiIqTgFhakc3CsJSBoCrQulojnajLC1Lp10Gw7t7MLUzAIwiF/FNvAVo36W9IDc4UF9SKSS6R16LzOo9GhKTI5k4GO7EVe1Squhw/iAAvNI7OGgK0ms/kTUZc7UAh2B5JdB5UsFQqHAoesrG80du+dgzCIyajbSmL2KHDHpKx4Np3qfgJ1w4BFd+FsD+vExM7+gGAPSUjsGErgYMDYTwmVf/fi5q6gQA3Nzsw5pBkgAzp9WH9wuyAQBRTyYi3mIAvNVh1JUGf+Ui5Bz+PUqCYcxnizR0b7nYidMZaQiMuBFMy/uKa4FhM8BEQmCaSQGu+RsUHHY10LgNAJAZiWJwIIRpnQEM7Q7hTKYHo/yyrFiyxXxJTxiNaW7Ma/EhMOxqZJzZj5lt3WhxuzDAm4kRnT2Y3MXPm8DwmQCqxbqdbp4OScTpHjkbmdUfAgCWNnbgt+X5AIAMeXaTBLhYqK1OQoVDAJin8BNwXasfHxToPDdGbSZVhuBkMSTI1/l/pTJGbjjxvG3UcUIu9rTFRVl49VFZSPSSQgIAdl08gC+VzKYqmx1NjIKAU91HOe5o6sTWktyEtCNHYyx1bDzQ8tv7AnUm7Tc3hsTEjCYoJLgowLBUenCWaCFJpispL/TpOpkBL32kXCFhF++++y4+/vhjvPOOcV7vQCCAtDStJlhIxxkM8vmjKysrMXnyZKxZswbFxcWYMWMGqqursXLlSng8HgQCAQ0NMzhpPx04cHCpIFQyGqGS0fQVGF6AJ+4vWVgx3d3IC8WtseOREQ8erWuBb2Im9JIxP3i+TVFHjfCAUaJCggHQPfoGZH6xS8OtjGOFrWnrwu/zpyIhAGcU5fM4F75/RrkQDhUNBcArDrpHzVYoJEIFgwHw5f2T70Dw7F+B0ClRPOma8TWJ76JhQPi8yFgkr1zRDpfhlR3EBABPJvJVPPknLMSynb8EAHzmzeDLaXoOzO4Ioqd0DIY1fK44f3OzDzc384Jw603/DtbfCtT+EQDQOf2ryM0ZCHb8TXjs2J8RHDwUfgD+cfORdXwHAOD6tm5cj260jyoB15EBICzS7h4Xc7ncfUzoJnyVtyD7yNtimYh3ABDbI3ADWFEr3Wn12Mvv22M1LeLv9knTkXFmP8Z092DMuRb4JmTggbo2vk8AesrGAk2SQkJQBozq7kGHW6mcCoy+XlRIVPp6kBaNoodlUVw4DsAFgYKpTPuzk404kZWG9QPzidcjuaUIR4Jwt58HOA6h8olA135jojJc0RUQFRLyXWkjqCM5JBocgChFDAnxPAdwSY7umcYIS2OpnWRnW+itLB4AEOLC5oVicCeh22qS13QERIVEX7OQSFWWDfk4WLWQiJqm8DXvE4myNBYULhu6QS2ttSmgL7vMO2k/E4OUKiQaGxuxYcMGVFVVoaqqCgCf9lNtIaFGMBjEz3/+cyxbtgyDBw9GJBLB/fffDwA4cOCAGHMC4M2FPv/8czHmhBpyhcEvf/lL3HPPPXj88cfFc1OnTkVhYaEijagDBw4cODCBaFGQpAVdUmJIaGHoHEDsmln7ZmEfZddVAqMVc3TDRadC8IuV14+QZtISA/nSmBGd4SksZAxXp/xFFoz4WzTXt3KLdRbzGq405RjiEU3Twg4+y+jfSz0YL9gZGR3rz5U8DgZDSYEfc/MdTDPozV0+CaTSzFt5Xc2P8fV4BFpBjJPELlncgziePaosG4LbSi/EeLDWlwS1mYIYEuFoElw2eslAQt6q3pjox5AwpqlWspDoG2W8MbpFGoUEVd5PJ6ylg36a9nPTpk1obW3F7bffjtraWmzduhV1dXUAeIuI2tpalJaWwuPxoKiINxe9/fbbMXu2ZKLW3NyMp556CiUlJeK5l156CefPn8d1112HUaNGobOzE1u3boXb7cacOXMS2HMHDhw4uLShdnGQg3pNZ7iY0aFiccXIQC6M0wnxEgjlra5YuaiyKzHBWE98A4TiOjvIVI1Kwrcg5BPN4DnOXApllI1KwhwNJ/ploqReiqzQj7F+dgsVDc1909+hN0M0VlWZ6JPSGJ9yTc4rfqzNNbmxNW1NSVRIkrDAGceQEC19ZPzI55ZWIUHbrLakWmSWT32zXWerbem1bc9lI3mCHN1zTEOH/FtbLnF9iRAdrKzBStrKxEI+G3UUEnpOTpyJhYRNpQ8nPosGFhKc/EkljF/Kgqo66OvoF2k/1airq4Pf78cdd9yhubZnzx7MmzcPb7/9NkaOHIlRo3gn4vLyckX5bdt4/9Px43nfXFLaTwAoLi7GmjVrMGzYMLvddODAgYPLD6zWZcMsk4ElJHRhQ/JrNT9DJmXPQkLcgWcY/bImC00SXTILWgsJYjFwsVSvRlBpJEQrBspdLx0GFEJ9PDtoegoJjf7BWEFhzUKCh8LUmtpCQr+PDAOFm0WUsSYky0eC5YAIBUuK1KVxuRXoW0gIwr7cokT4qVYS8Gk/jRqi45FUjFO1adtCglPVp6jamzEkrCBR72z5+BlnaUgcEmEhEU2gxYYVKJRhptmWVHVNbCTsPsdWYqEoW5RgmM7ZwWWNZIdBN4TX60VBQYFpuZqaGtTU1IjHd911F371q1/hV7/6Fa6//noMGTIEjz76KADgiiuuwK9+9SuUlZUBAGbNmgWAj5ng9/vR09MDjuPw6quvYuDAgZg8eTIAiGk/Fy1aJLYTjUbx6aefApBiTThw4MCBAwrEFBJMHAs6e2th+ytow91vagWISTkzm3PZaY2Pf4JMreV0hT7rirZWs3VI+Qup6uvu8oluGgrqStpUjFFaSJjcN4bMCRFRwd1ExiftTrOhgoiTKX84DhGLz5Z8fhuHpqPjB4DobmEGQ4UE0UIiHgsgOo7UiKouKd0MEq+MUZSJw2XDKmdW2kic4EjpspFIC4kExJDoC6KzdQsJnWeNMK/12zTiw0ihZMdmqW8p4RykBikPavnCCy8AAA4fPgyAt3Dw+/3Izc0V034KMSGEbBtjx47F2LFjceLECezZs0eR9nPAgAGYP3++4hgAPvroI0ydOhUMwyAnJwcdHR147rnnwLL8YkVI+/nKK6+gpqYGoVAIb731lpju8+RJeeRzBw4cOHBgCGJQSwHxL/J0BbykrW0S5bKho5EQ5XhWtzmFtYJOOxrFgPo3oBDSRdsD3e02OgsJrQ0Dzfa7ucsGa1LOFCzlvos6XofOsRVOWCgtJIysH8RiZldl1iIRi8+R2kKCBmJrHFmMod1BNrIwIAW1lNXk2xaej5jIw3EcGEY7olysvD49qZz2nGRmznGcom/Wghuqd4npd5bjfX0lMgYDkDhxnNZSLhH8CzSMgloK88cM6vtuxYKFtg1SWRplmB5ts7lKN8YEhZ3KfcqYNkdsi2Rpxml+OLgckXKFxOrVqxXHu3fvxu7du1FRUSEqJPQgT/v50UcfEcuwLIvZs2cjIyMDhw8fRltbG3w+H1wulyJ+hJD289NPP8XevXvhdrsxdepUfOc738FPf/pTW2k/HThw4OByBef28D+MXBDMqdhoOZ4lvaw9UTHAKP+aUrBmIcGxqs+wO03GiUoodrnJeSeVDMTKeqiYkGJI6NGjcLmQs8mqxs3UQkKn2WgPgCy4QrIMVzaEFZpMEjTlBL9sucWP5t6poHb6iFfYZCNBiSrHwWXRyJWV8U5b0xWr0xXxEwWjtxt3U9G5eHI7sVEOwO4Wfv32cfsxDHUVYGzhBHGs9tfvwXtNezAtbwIAvvdnMz149tRv8ODQuzX0XruwHUyPHwM727FwygqAYXDSd1a8vr1pD451nsJXK24GALSE2vHUyf9DJpuB7kzpmXnp3Ou42NMqHv/u/J/w3VH3K9r6wncWo7OHisdPnfw/LCqZo3D56ImGsLX+LwCAC8EmPFv9Gw3PXWE//t7JZ+F5p/EDVHWcwL2DbsfbDbtx2l+L+4Z8GatP/xa3lc4V6xzvOo1x3uGyUeRx0lcDMxzpPIlbS29QnCt496fAqBJNWfUd7wh1YTfTqilnDolSM6uv5EyEhcTPq19UHMuf2bVnt6A11AEA+ObgJRiQXmhIy91wwhYPX/jO4s36v+LOsvl47cJ7imuLy+ZjjHcY/vvUBgSjUq6oR0YsQzorvP8lnt9vPohrCiZr2tB7n9R012FYVgUA4L2zf9JcV8dDIY35sS5tTD+ShcTBs9vx11ANvjvqfoSiYbSFOxV1XC1nFceH2o/iqvxJ2NtapaF/iO1AuPFDLKRMSevg0kLKFRInTvAP+44dO7BixQps2LBBk2VDsIyQQ532U3DRmDFjhqLcwIED8eKLypdTQ0MDFi1ahKeffhqvvvoqACnt58mTJ/Hkk08mJO2nkwbGgQMHly3SsgEA0bSs5NDXle4SZCIREzYFwZ4osJLWzqbNKwuEc8uADikdZSS7GOiKkWYIZVvrqXoYziszYEHrsmGwf23SklIjEc3IkZ03pqzVZkgQM1WEAtTuDuQmbLpsqC0kCKUiuaWGTStjSBgWlYoZDJeruwNg8kWOytw5+oVJ/Mh/Uyp38sJRdAppTuPYvT7eWQ3kZWrOq3dQD7X/HWMLJ4jHbbGm22JCpDA+YS6CrrBfM7sEJUJTTgYWCjTbjorXP24/FmtXWa87Kq3xOHAKZYScV/mu9OG2owqFBADsa1MKWoGI0t03xIVR4MlFa6gDgzP4Z7Q+eFFRpi7Ab4B91smn220JtQMADrZ9Jpb5qO3vMoWEhEPtRzTn4oF6fGsD9Qmh05uQP3qCMgIA2kKdpgoJ1/lPgQHWRaVq3zmEuQiOEwT7Q+1HMMY7TKGMAPi5Iigk6KBnJSc96Z+ELoi/abJkGEFUR8jq/zVUEzvHoTuilZPcTV8AhRmKc2e663TbqOo4TlRIHDp0yDrDDvoVUq6QsAN12k+rKC0txaJFi7BlyxZ0d3cjM5P/SD7//PN45JFHxLSfLpcLy5cvx8GDB0WXDiuYOHGiIq1oX4LzcDtw4KA3QBbkE7E8TYLLhsKuWC2CxhNDwsBKROUKYGxmbs4DQ/ilLURVir9uKW0bDGJIWLtfYlBLTk7fxryxG9RSbZ0S+6ugZmIhkfi0n7ISnJoZCtpxPnbxVNd3V1Gel6w+zBVC5jxxhBrCFRvWNuASEnSStRm+jVE83fFYntFD7V5hdw7QumIkLZsLCRTDFta8rmnHWrBx05bXjf0g/00xXvp0zJ4KuxoJM2s5rcsJ6Zul7hvHwHRiXXnllVQspgLBYNDZgE4AUqqQaGxsxIYNG1BVVYWqKl6rfOzYMY2FhBrqtJ+RSAT33XcfAN7lY/78+WLaT5/PhxdffBFVVVX47LPP0N7ejlWrVqG8vBzRaBQdHR2iQqKgoAAzZszA+fPn0dzcjLKyMpSVlaGurq5PPwwOHDhw0NdAXCxZTonZSy4bNAIvddpPE2GDkj1OES9ARcJgXKyKvWLP9e4N5SJUzZOwEDVXaBgvzuONvK2f9tOMD5VALHjuWJiSSsEzQQoJxVy1Ntd7R4S1BvVwukwC9cmvmgpWHKfbUTuZHqJcVGn1YgJOpx1JWKOno4ZC2ZVEIZ7EvWkdC7ET+jrUCglaiAo0SwFE5XEjzGF3iM0yYVitr3cOMHeFYwys5BxcXkipQuL06dNYt24dhg4dioqKCpw6pTVtIsFK2s/W1lb86le/Qnl5OcaNG4f9+/cDAM6dOweXy4W8vDyx7qOPPoq//vWvuOuuuzBhwgRUVVXhJz/5CQBg5syZCeixAwcOHDhICJK+4E3OIl+7Y2QUNC1R5h4qKFw2zGJI0GRRkO+MqU9p/Y7lfOjt8kXlliOU8SjIrFG6bKjL6bhsWIG6ZZq7aR740r5CIn7YfyZoa7pi90GvZ9Z6LMxta2K1nnClDhZolDmEph3DZ0NRTHvd7u54vDB6BJlYyFGSJQktX72ZZZPK9c2+TQiAWNpi2hqKztu3kNCvK7hsKK9HKdNJm91DSpU9aDPzOLi8kFKFRGVlJfbt24eCggI888wzWLt2LbGckPJzyJAhAPi0n4IVhc/nw8qVKzFjxgzs3LkTV1xxBR588EExpoTb7cYHH3yAkpISHDt2DHfeeSeam5vxpz/9CdOnT0dGBu/bVFVVhR07duDhhx/GQw89BAC4++67cfDgQdTW1joKCQcOHDiwgURHfTdFwhUVKheEeNs3y47RyzC3DbF7/+KjLO4wcnEK3nr3w9RlQ82PoCChHw8NRRrvF0OBT9pxZHSyXhjzE9+zmIwnWd0Lt45NjJiFQh5UNPafAXH9S3YCpFodAY4zZMKqhYR+mkf578TeJSvUBIUEmU489iAJAMfZ+jaEVXVoXXakrDD23l1UFhIUrh+k81oLCWtjTqPgE9sisKieor28QnDQR5FShYTX640r7ScArFy5EsOHD8d9992HnTt3atJ+rl69GufOncM111yDSIQPT/4///M/YBgG3/3ud8VyQvvV1dXYtGmTmPbzwgU+IMy+ffswbNiwJI2EAwcOHFxi6Jcmu0ZLo3hiSNBDWGRqDdStgdYo11RtQBlDQsOpaNVgWJEvRygj7KEp034m0kLCrB5dDANDGLgM6DZres3+WMQbQyIZooNagHaZmnir6htTt3lNp4aNOAjkHWKlZQSFEwT/Rx6SxKIwahdaQdPgXRJ7lvuagKlrR0DBqF2XDbFtwnyms26Jw0LCpKrG0od6XhuR17MqIsSQ6HMzxEFfQMqDWsaT9vPEiRPYvHkzNmzYoFvm2muvxauvvoqNGzeio4OPrjtq1Cj87Gc/w+jRo8VyQtDK48ePY+fOnWLaz1/84hd47LHHcPToUSJ9Bw4cOHBgFSneLaNpTr1Io44hYbaCNXEFYGR/NQHlaBapWspMVD9XqJl4y1CY8yqX0WrRndYFQUWTFLPBxnTQjyGhvg+JjyGh1yLLcaJLimUKcbivKJyB7Iyl9Soi2oVMHSqohSMhqKWeyb+lyAmiOxJpR9d6b9S86rcr/TES9qxbuEhgdeaPXWGvJp0sDtCmzQXI7x7xTG9bysnbFv+17kYSVh3TjoY0XwkKCYp7R2UhYSM+CgAxhbEAdRpQg5oCAeIVkhKcNH/ijWHh4NJEyhUSdtN+AsCPf/xjzJ8/H9OnT0dtbS0AbdrPW2+9FbfeeisAiC4bX/va1xTKCAAYPnw4AOChhx7CokWLxPNCWtDGxkbLfXOirjpw4OByRSbLZxialiel8AsXDgUAhAaMoqIRGjAKGWcOJJ65GF+H23lFczRbSP0mLY0iQ68CUI0r8ypjZ7QLq1DJGDCt51CRJqWOI0UVDxUPR2FHA58WTbVAG5U9BIfbj2J4dwgAUBKjNbkzgJ4KZTDlEVmDsLf1E4zulrI+hQoGw9N6Tjyu9AWxPy8TFRnklJTBwVMVx1M6AziWnY6yHn7p3VMyGvkhKQ1pT/kEZH6xG/mhCHIyi4g0wTC4ur0bfxqQA68rSzzHD4jBYpdhMDlnNLZ3VPF9Z6S0kIPCvAA7yRe0ZSEhppvVUUhwLpP0egyD9EgUQReL8mAIUzoDOJ6djvIeSUQpzSiW2kvPBhv0AQCmt3fjo7xMMByHypxRONJ5Epxbas/F8UqJEiYddYwyg5eRwHM6ncWVxROQ1vg5IjklYLs7DEoTuhT7e2VHN05mWkkvGEMcksPxbHLGMbX/uphlQ62ME4JaqpSGRixFuYhuUFRbLhsUyjmGQmXCqX+YsCJTLSpaIpe1o2ni8MJgbfrLkmAYUZdSTDCizgdxjfBjq1GmUrKSDCsc4R8bCl6thYQ1RaIVlw2O0zvQp24FesFUqeN7qP4qL3IKnoWfZAshFXSs5ORwMgNe+ki5QsIu3n33XXz88cd45513EkJvzpw5qKiowKpVq5Ceno7x48ejqqoKzz33HNxuNwIBbX5dMzhpPx04cHC5wsO68d1R9yvORfLK0brw+9Q0wkXDEsyVhJsGzMJNA2ahdRTgar+guR4aMxffxVzpBGGnJ1w8At8pHqE8GSvXPWIWAqOuA1hesP5WQSxFdSSkKD48axB+dpJXeLcCyPPk8OM2rAdBt1JoHJRZpigLAF1X36soM8bfg5+dbETrKK3ywDdhIXpUConJXUFMPtmIthseRmtGDlztF/C9vevF64GRs+Fp+Bz/72w9uq5aoLNuZHBdezeua+9G6yieZy7Wb9E6g7Sdx7owteQqTC25CkyoG5xHUkhkXX0ffrbzl+AYFj6DhXdw8FSkn/uY/11eifQLRwAA7Tc+ot8uAKgELZIAtfL0RXGH1A1gyslGXuE0///h0WgIaaxHLN8+919R8O5PAQB3NXXirqZOBIaPwK2lc3Fr6Q0AAN8VtwPte8ByHFaevoju4TOx0lUNAFja0EFiQ4EOF4NQ+QS0lvNKPjZgTSEBQJw/PxtWrLnm4jhEDNPOJkNYVCkkxGCmZEsilwUeIlxUXyFBTUUCtYWEoh1CHQPLDT0qgL46QrGzriPI/md1I54cWQIAKA+GiGXk+NnJRvyuNBe1mWoxwYBnBgYuG8qzGZEoAi7p7nz9Qjs2lueZ8tXbEOdd7NmwatdkzRBKayGRH4oYBHg1J17IudHChBVE1c9cooxXiJZIJAsJTUYmcwb6cqZDJ+1nYhBvRq240NjYiKeffhr33nsvHnvsMQC8FYMZgsEgfv7zn2PZsmUYPHgwIpEI7r+fX/geOGC+m/b4449j+vTpinPp6elYs2YNotEoVqxYgRtvvBGPPvooJk6ciNzcXGRlZdnooQMHDhw4uKwgLMBYt6iMUBWgo+O2sYNtBtZlEORR8EnQLgs4lwduSBkQdOuq2wIA0V2EsDBlJWFHrowQ2uR/cESrE7GcRRcZ6nIxum6odm5ixeTKCH3mlAtt0WVDOMFK4yk6uhiszeOVG8wWfGZuHMlQSETVMSRMVAgspzxDCpon0o7yghhJSLfTl0S5HVilQrKQ0Es/msh7xEDLqxF1IwFZXY9kyJ8s8O8Ie3NAKJEZsZYZQuu6JrumM4+ULhv8bxenn5NCNzaGjA4py4c2qCRl38SKNC4beiVJ494f4005SDT6ZdrPTZs2obW1Fbfffjtqa2uxdetW1NXVAQACgQBqa2tRWloKj0e5YAgGgwCAtDTyQu+1115Dc3MzZs+ejdGjR8Pn8+H1119HOBzG0KFD4+ipAwcOHDjou4gjaKIudGilMtinQSwJcQwM+TNRZsggKBuMLSQMliBi+kdOrMsQF/KSYEbMImF7uBNxn1Q7gbF+iEK1xYCb2t5Z5NFkerMku3abYDiOKv6A2n9dTyEhCmiqs0YIcxHo2ajaUkhQm7ZrBUt1CWsN0995ewoJHbsnjtMofIyUMoLwS9Nn/UCTyVFMcBwh4TJFU8Ls9Bi4IOi1F891ASz0lW56sSjkcCkie/Btqi191EpBPZh5GJHmPfkdYN1CwsGlj36R9lONuro6+P1+3HHHHZpre/bswbx58/D2229j5MiRimuvv/46AGD8+PEa5UdDQwM2btyIJUuWYNWqVeJ5lmXx6quvoqKiwmr3HDhw4MBBf0JC1kX2gw4mG0bBLQWhn2yNYNYXghApWkiE9emyBgI5rbAuX/AS2bQrYCdAMNeZA6zAKOOSmVGrrpHIxcmSWQQCkoUEp/Obpi2a8hoLCdFlQ8VHrBirMffWR5gL65axI/haddngQJ4CkmBnTRBU9kQnhoSeHpRIT++EVMfSPWf0FRKaGMHqYzNm4oZNC4kYo55YByKckVKXUF/HOscs0Krwm+X0R4Qm0wrpLaqOhWJdIaDTJ51gl2bnjCzgHFw+SHnaTxrU1NQAAIYMGQIAuOuuu8TAl5s3b8aZM2fw5S9/Gc899xyuuOIKPPjggygrK1PQqKurwx//+EcAgMulNaOtqqpCJBJRBLQMBAL4+OOPAUBM/+nAgQMHDi4xiOuhBCyGTQMwpnDxZbiYprGQ0CFLqsOoYkhYhVwhYcSTQnFBGnP6uPi2qlmgyaj+ciwLWBgea0bjWhAtSCwh8cKiWhgS3IK0QoskoNFyIygk9EzMrUIdgFMPtOkbpSCDVhUTRlk2aHjUqHt0S1kZOWOXDfWzYO62kEiQLCRoZoEwmu6ooJCw67ph3rJcnhcVcOCgFwlFf7wlQi6KXtMq2vSCYqqvK85RxJBw4ADoA0EtX3jhBQDA4cOHAfAWDn6/H7m5uWLaz+XLlwOQsm2MHTsWY8eOxYkTJ7Bnzx5F2s8BAwZg/vz5ijY2btyIV199FYWFhaivr0d9fT2CwSBeeOEF/PM//zMAKe3nli1bcP78eXR2duL1118XFRHHjx9P0gg4cODAgYPUIoFKArO0jCnUR9BYSJCEf9MUkUSXDVUMCauKDkV5AyWPGV3adjWkk2Ehoe+yIZ4yGGuNkG5xTO1E21DsrFuQI2g50xPy9QQ5tcuGoYVEbO6Rd2mtC0V2dpITkXJUKi/Vo9kd16enOta5sbZjSBCtQsjKOfE46TKqPaWUUMaqhYSRFQyNhYRAgeWsW0bpPacST+qglhYHX+f+El02iNVVVk6OgYQDpDioJQCsXr0aq1evxkcffQQA2L17N1avXo2XXnrJtK487acRfv3rX+OLL75AfX09AN5aoqenB6tXrxbLCGk/Dxw4gJ/85CdYt24dRo8eje9/n48IbyftpwMHDhw4SCzEYId9FFzMMkBfEE6lhYT+7p4o3MqFZMEEO+ZaoSsAk9wrhPgQieiugT6CE3bU3emSEsRWE2oLCR2BL43OspOnQV5isQbXjYbLfu/oQHbWkc7ubN5PT4tSxlErJP4aOMWfU9WXLCTIDgwkSMJj/EoBQCu4mdEwa4FWDtxcx2eT6wp3i+d8kW48dfL/sL+1ioqG8f3QUUgQ3QUMLCR0XDaqfefwbuOHyrLWWIkbZIsEGpcNntOMmIWEOuaJWYtk9xWye8Mb9X8VzwtXWehbRlkJyqngSVWNtk9mFj1k9ySShQaJKweXO1JuIXHixAkAwI4dO7BixQps2LBBdMcQIFhGyKFO+ym4aMyYMUNRLhKJoKioCHPnzsWPf/xjAMD3vvc97NixQ1SCAHw8i8mTJ+PkyZP40Y9+hBkzZqC6uhorV66Ex+OxlfbTSQPjwIEDB/HBN+lWRNOkLEeB4TMBAOHCobp1/GPnISyk2bSCBJiSBodOBxvoRGD4NeQCKQxqGRgmfVt9lTcjmlWAnIObYmfUDgWAb+qX+b9X3I6MMwcRyR8EAOia9hV4D/8ewUGTNXUERDPz0D3yWvQMnBgrIpXpvOprYH3Npvz6x96IcOFQMOFg7Ix0f77c0IG8cBTc0CwEBk9DqGQ0InnlSK9TfXcJ4x0qGq44Dg6ciHD+IPjHzUc4XxsvKpxbDncHby3pm3SrKd/BQVOAaBjBIcpUdaKQIQgdCuUP/9dlMAXvbrHp/gISbYIlTFzU7dEimYt3R4IEoUXrssFnYDGgbaSA03nW06JR9OjENqE3bSf/1rZt7X3THu4Uf9d08/NxV/NBVOaMEs+Xpw/AxZ5WYv3FjR14p8gLTpXBRz0Wc1p9AGIWEqrnh8ZCQn1XXrvwnrYsB3y1vh1pUWtKHtuw6GohVgMf3PPLjZ346fB0DM4oM63D1xOEf3rXlPZwJwLRIDJdGSK/LCGwKG3bAv/q32oFhFULCXIqW3VrsdME3u24bBw6dMhyHQf9CylXSNiBOu2nETZv3oza2loqi4vnn38ejzzyCB5//HEAfKyJ5cuX4+DBg6JLhxVMnDgR6el6MZ5TC+fhduDAQX9AT8UViuNozgD4r7jdsE5w+NWG1zXQCaRnCy4PuicsSASlxEMmiPQMnqq8JuxuygSQUMkY/lxGLrrHzZOdH43Whd/X1FXTC4yeIz8h/goXDf3/7b15fBX1vf//mrPkZD0hEEggQNgEAggiEkFBVFARUBRpVVRKLS63oF+VFsWv9VdqgRZxQesti2iNwhWrqN/igqLxxkaogBhUFiUgAQIJCdnPPjO/P86ZObOfOUtyWN7Px6PlzMxnm+XE837NewG66AtKAt6QqGOrP6I6Nrol+JLABQbuoZMjjgUAgewC2JqOw99VnvBaeJ68fSQvNCTn5B50lSjcBHLlYoYWrmFTNPcLBq04sobhazP4sd45wMOtezQy0tk0n3Utj44YvxRBjxMTVTY0DEUth3bhslgVxpaRaWPkNq73VrjQ48dP6dq/28wYUrIz1nkTHl6ffJ2xIp0jYBBScGmzBz+lp6Am3djLrK/bD0Anh4TBUo1ySKjbAhe1emXbwfHbR5AwEzqgBRd6x+9kOfT0+MGkmzvHsPFvPmRDa20WGD/jkdcR2cfFtNBm0Ew/DEWrbeQ2SkaNGhW5UZLwer30AjoBJDVko7a2FitWrMBdd92FRx55BACwb9++iP2UZT+PHDki5pkoKyvDsWPH4Pf74fP58MILL2DGjBn46aefcN9996G4uBjvv/8+WltbsWLFCpw+fVocNycnB8XFxcjLy4PNZkP37t2Rn5+P6upqKvtJEARxjkIuozDMIWG6r3Gj6Mc10zWaYaM6N0nbKMtz6hH2kFCPK+wyEiTUiQwT621zpnhI8JpSg4aHhGS/NrxuE71Sh6rqD5J2pt31TRvVifnLIzUEw4k8tdEOy9G5FlGGuoRDNiKj/EZFSgUcN3ov9U10Y5Q7ophPr/JERHGLDz/vXNT5QqTPrHq/qspGlM+rXmstzwwzIRsEASTZQ+Lw4cNYu3YtCgsLUVBQoCrFqYfZsp9du3ZFQ0MDXn/9dbz++uuqtmvXrsXx48fx3HPPAQAefvhhfP7555g5cyaGDBmCiooKLFmyBAAwduzYOM6UIAiCOPM5n38oCT8cYzG+TZifcYWqGJkr7RMCI/UU4RMmSAhvPYWQDXVWCJvBI9jeb5ASmVgw1hwSQCjGXrkvtEcadhLpPXM4Hl/LKNQWF5RPkwXhQihmDTdpQIZR8sJEXW7pHH5OW5AwLiQk3ykGb/HRrdEihGyY8STRbdNeHhLanjiR+ykru5h9BoyevWg8JIxCNvTCQXQ+i/qcvF/iyn6qJ9MM2Yh7fuJcJKmCxNChQ7F9+3bk5OTgmWeewZo1azTbGZX9bGtrw+LFi1FcXIzS0lJZ2c+UlBS8+OKLWLJkCfLy8jB37lxYLBaUlJRgz549WLFiBfLy8gAEy35u3boVDzzwAObPnw8AuPXWW7Fjxw4cO3aMBAmCIAji3KXdPSRiRxQH4nTnjjmbu05OgWjhJG89leOa8ZCIxiU+EpEqasQ8Ls9HVf1D32BXGi1BLDr7NddicEzXQ0KxbeV5sDrJGs8UpKfi5/2R26v6618L5XfG3DUwIUjE3jVxmEpqGfYUMe//Iemv45oRaRRe8reivUM2ohZZdJprz6UO/FEnhyWIJAsSmZmZcZX9BIDFixejb9+++M1vfoPS0lJV2U+Hw4GTJ0/ilVdeQf/+/dHW1oZPP/0Ue/fulbUT5q+srMSGDRvg9/uxefNmsezn9u3b0adPn/a7GARBEESSSIzBe3YThyBhavhEeEjEvYgYuyVIkBAucXhg6SQAoqykkeBrqj1adHMIHgXxlP3klG9bkXgPCb2El6qQDcW6tMbXmFm2RvVRXvFvfEhDSfQ8JAQ0QzYU5yEr9RqNABRFyIZe8FF7iT7KMIXgXJHhIH8mzK8u2FJL+Ap6E0QI/xEECQCcXsUf3Zn1QjZC+xRzGyV/1ZtBa49myEYEDwkmiUmeiTOLpCe1lJbeBII5IMrKylBQUCAKEnocOHAAGzduRElJiW6bbdu2ITMzEzU1Nfjtb3+Ln3/+GVarFRaLBW63G2lpaQAgJq3cv38/SktLYbPZMHLkSDz99NN45JFHsHfv3jjPlCAIgjgjod9E8XlImEArltg0TNhcSQoJD9lQj9vRZ9Zej7zgUWB2/NaAS7UvGLIhvyJuNpjENBoPCRenXx1NL5Gfct3SVnrhJXpj6womglBilPAyCnFUmsiy0d+i2UZ6Xix41PsaYWWssDFWNPtPyxvz4T4BAB7Wi1SrAy2BNnhYL/SwcFyoexweEpK+HtYLH+ePotSmMcq1N2lcK57n4WI9SLHYxfsnfEsZABzHitdDaN/GumFlLMHqGAAa/M1iiVYfp06I3xxohYs1rtzXEGgGEK7I4+P8SLEokpHqPCM+zo8AF4Cb88IruXbCfXErrkMrq/4OaiE8Z3qBItJnluVZuFgP2jRudFOgVb5WRd6TRn8LeJ6Dw+oAx3PItKUrhyDOQZIuSMRa9hMA/vznP2PSpEm45JJLcOzYMQDqsp9HjhwBy7L47W9/i1tuuQULFizA7t278eqrr2LBggWih0bfvsHM2fPnz8fUqVPF/m+++SaAYAJOgiAI4tyDtweF6UDn3hHbcqlZCZkzkC0vL2k2TwGXkg6Lz9wPyFiISzhoJ3hr8Ic4m91DfVBZlpCxGIgq8v2cIwsWr7YBB0l+B96aAjajC6wRSpVyjkxYvK26x9MtQSOmr9unWnuuX/vNdirLoaOnsHcAAH+nSURBVIufxfFU7coI0pACC8/rvk1VLzYA5U9ArXAFhucQjd+GEI5iNofEQVeVap+WQSsYcLJ4/gju7O83fI2uWb2RaVUbNHpvhZWCh08WVqOe7T+Ne2Tbp5QlN7WMxoA3YkKQStdR4wYSLJI754sQssEAaLBweLnqbd022WzQ8GR4IMAAKw+/jl90n4x/nvjYcGxbWz3gMK7gIa5DxxNFunvlYXXut9jhVeNtb6zAwMw+6J7aVdxX0XwAW079W9y+FPLvRZW3BisPv45HB8wNjtFQgbLTOwEAj/Sbg3pfI1479p7YXus+trFuvHJ0k+5Ka7x1+KIh6LUteAS9dHgDHu7/K1k7a+Nxzf4/tBzEcXcNGgMtssVbPC3wcwHsbJJXhKjxRi7BDABvV2/Bg/3ugsXdrDoW/C6G796b1R8GP6SqxznQelj8vK3hW9Xx1Uc2yraFa02c2yRdkIiVjz/+GLt378ZHH31k2M7lcsHtduO2227DH/7wBwDAtddeC4ZhsG7dOuzfvx+DBw/GhAkTUFBQgGXLlsHhcKCoqAgVFRV47rnnYLPZ4PEYq5laUBkYgiCI5NN45QOARd+o4h2ZaBp3H7j0TsbjTJgvK50ZK01X/BZcSthIirQ+Kc1jfw2G1Tc6Gq96EPFVtGin1IkhQ9mf0zPqrlxmVzRfehfYrDzVMWViyOZx9+oLEordzePuCRqHWlhtwWsd8IFL74TmsXNg8Rv/Dmgedy8Q0C8R3tmagUeO1KOLP/SmkWHw+M+nUWtnMMAdvqeP/lwHl8UCB88jneVg5YE2KwOkdFKN+X8P18Ef8kiw8jye6tdV1eYPh06JooUR0ha/O1KPdJbDKz3Ucxoh3A2t2X5R04x/5jkjjqGX30E9rlwiGNjmxY8Z8pKdDf5mdE7JBhQanq6HhMbuW2qa8U6eU3NdB9vUJWn1Vyjs5CBXJNRtmgP6wpYS4c25w5ICb+iN/OzqRnzROQNVOkKWHr3dfuT5gs+nVJw55jkZsa8gFkXr7dM8dg78x7cDOC0KONGHEcjFOYERLR5UZKXqjnfK1yATJKrc1bLjPCMRwTRO7GBbWFBjeRZtJr0NjGgLhIv72gUPCQ2hyeI6DaQB3b1+nFAIQY0BtdDK+FwRq7AY4eaCfyt5VutvXPtmWNm1a1c7jk6cCZyVgoTX68Xy5csxe/Zs9OrVy7BtampQnps2bZps/4033oh169Zh165dGDx4MBwOB1avXo2HHnoI8+bNAwCkpKTg97//PVatWoX09OhdhoYNGwaHQ7uedbKhLzdBEOcLvAmvBi6zS+Rx0iIbU2ZQCh9m1hdeQ7Zx3LwjM7ZFCbR3gsqUGNbHMGBzdP5brxByuIzORgPJ12JPBewar/BCsNndwxs2Bzib8X/PI40HAN38rGTLgiyWhzMgNxJyAhxyFG7qjgAPVjU9g3ROnQBSSYZGm0h3Oddv5J6tRgzV4IUEgOqeDs6skamfHUIZzy9t18/tVwkSgLappJtDQmNfvi8QXlUUCfn0zoFTHNfUX6Kw7jieRxd7J3g4LwR5rVOAQ543IAoSZr/Vwrkq++hdL6kIEK7kEV3IBpvdA1x9FsCFQ0fYGASJ7t4AjikEGEH883OsVhcVFoUgy4ORJLXUzwcifI5l3crxpGPYOcOsHQCANNbswxK5nZ3j4bdEeloi55BINKNGjWq3sePF6/XSC+gEkFRBora2FiUlJaioqEBFRQUAYN++faqQDSUbNmxAQ0MDbrzxRhw7dgwsy+I3v/kNgGAOikmTJiEvLw92u10MtdDLR7F//37x84ABAzBjxgysX78eNTU16Ny5M+rq6nD69GkUFhYm4pQJgiAI4syl3ZNaJvZHKx9TBYxkhaUo5mXUGeij6x/vepTDRbueMDaOB2s1zh1hMTk0p2H4CxjleNCrHKI1lK7gobFPeMK0xIhIuR7MaA1GiS/NwIGDRfG9VYaeMIp/9dA7rmdoM3y4U3yJKeV/H2J5k29UOYY1OZ5FEUvDhSQJJTzPayZkZHlzwocePC/PCZJilGcEwao2Zv8MtHeemmjynhCEkqQKEocPH8batWtRWFiIgoICHDp0yFS/6upquFwuTJ8+XXWsvLwcEydOxIcffoj+/fvjiiuuwN69e3HvvfdiwIABYrvly5ejrq4OgwcPFvctW7YMr732GiZPnox77rkHlZWVWLt2LXiep7KfBEEQxHlAO4VsaEaJJwCL+Z8xjMm3pO2HMnD+zMrXEc9q7DwPLyQ5JDTamM1EYWTYyN9S87Is/lpvsEOtVPui8ZAQvDK4oFSiuzZtNMQGsaiP/ljRJHLkeV71Zp9BbPdTeg2l3ihm1mM2bwigviqC0S9c31g8DbTvXXA8v45QoOyj8pBgjIU05fMQr4cEwMtEDbuJa9rRf0XiFdCino+EjvOCpAoSQ4cOxfbt25GTk4NnnnkGa9as0WxXVRWM0erdO5hwbObMmaIXRVtbGxYvXozi4mKUlpZi+PDhuO+++5Cfnw8AmDVrFtatW4fq6mosWLAAAHDixAnU1dUBAMaNGwcAqKmpwRtvvIEZM2Zg2bJlAACPx4NPP/0UJ0+eROfORm6gBEEQBHEO0N4eEgn+bcmbzL0BAEi6IKEkymutujex3yujt8mxzGBXCBFaxqnVpGHBG4VsyNrJ0TYctb0+9Mt+qtsK3gaxGGJaxpTynbbWGAGDZ9UCi0wg4MCp3uzriQORRAPpcVlYhQmDnhGvU/wEYvA0MJrXrMeFVRWyoe1dwovBHPJZY1m3cj6Zh4RhyEbswpP+eNIz1kFnSe2bRYI410mqIJGZmSlWufjmm2BG2fLycrhcLjidTjHMYs6cOQDC1TYGDRqEQYMGAQAWL16Mvn374je/+Q1KS0vRtWtXTJo0SZwjLy8P9957L1566SX4/X6MGTMGb731FgBg4sSJYihGRUUFWJZFc3MzNm7ciJaWFmzatAnNzcFsslu2bMGwYcPa+YoQBEEQRBJp97f2Cf7RykQhSMRpLCScqEM22hetO292dbaQ4S0tkajEanIwfTnCOKml3pOrNZbeG3/NkA3BQ4JXriuSGAGZB4eyVziHhIYgYfCsWhmLTFDhNMIHYv0WMzqfdUM2JAZsuH0czzQfe8iG1gqFNRkJPPL2iko8YMTSm1K0xanY1q1EKv7YjEI2hFAZs0JfgjwN9M69vQQJEjrOD5Ke1HLlypWy7bKyMpSVlaGgoEA374PAgQMHsHHjRpSUlBi2e+CBB+B0OrFhwwZ8/vnn4HkeWVlZePHFF8U2Pl8wa+wPP/yAL7/8EmlpaRgzZgxWrFiBm2++GXv37o3xDAmCIAjiPEf0kEh0yIZ5QYLhQsbCGRIpwScxZCPRP/EFwymc1FKNWQ+JzTVfoMGvLi0YHD/8eW9LJWqYcPUBrWCjRn8zKpoPqPaf1Cl1aOQlUla/E/3S5VViDI0lntWsWhMIJQ1sCrTiYFuV5hhGuQisAKQ1F1oCrcj0tAHW8Or1n6zIb9y1Pv/QctCwHyCpsiG5z8fckatzBOeSr9hsLgYrD7ChrgGN75Nw9c0KBeqkluHr0GyTlALmeYCRn+trR9/DoMw+pubRY+2Rf6IwPVzeWOuZ/q75R1ijEWKFfpZWTIjz7+/3zT/he3+tan+zvwWldV/HNbYeLYG2dhmXOLNIuiBx4EDwPxRbt27FvHnzUFJSokpqKXhGKPnzn/+MSZMm4ZJLLsGxY8cAAMXFxap2DMNgzpw5mDNnDn766SdMmzYNt956K6zW8Be6b9++AIIhHvfee6+4/8svvwQAMTlmNFDWVYIgCCLZePpcCsarXUbQVXQt7Cf3yfYFnHnw9h4d1Rz+3H7wd+6tezyQ0wucIwOe/pdHNW4kAk51KVAlw1s8yAmwaLtwJjJ3vQVf3uCIfdobNj0HXFqOzD5k0zohkNMLjurvdHqZD9no5/LhUHoKxjZqlyG8oa5VVdLTwgYAqxX9XfqlS/UQvB/yfQGwDIOLWjwo7ZyhatPX7UM/tx+fKY5J0RMjAMgM/H2th2SXQCscYWvdNs1hDruOaQ+vMYbwhrwp0IKPastkxwzzXXhawKfn6B4HgHdOfILru12h2m+Ui8Dq9wG28HWo9zch2+sDk2IFQkazbsiG4WoUgoTk3MyE0GhliVl/fHOEGeUI8wRM5mKw8hzY0DPBapyccB0CMFllQ8MHRxBLTtslgoRivUCwVOuOxvh+9/t4P36SlJLV8n74MPQMjoc96pCNSGVqI/FB7f9q7t/eUIFTvtOax+Ll7ROfIHuX+UpUxNlJ0gWJWPn444+xe/dufPTRR1H1+9e//gUAuOGGG2T7hw4dihEjRmDVqlXIzc1FcXExKisrsXjxYtjtdng8xvXHtaCynwRBEESycQ+eqHvMW3gJvIWXyPa1XPabqOdoveQ2w+O8PQ1NV/2fqMeNSIRSnAAwqyZo4DaMLkDTxIcTv4YYaL7iv0KfggaHq+gaeAtHw1Z/xECQMM+91Y2qfU0T5iH7f18CAAzUEB2EHADjdUQMJWMaXdjeKT3UN0iBN4C7TjajwWZRCRJ2nsd9x4PrMhIkjAiWtdXLZxC/34fWG2npPi8X9k3gYexvwEiCTxie1/WIiTY3hbKCBhC8tsq548WMoSsVPrTWFf1coaSWnDmPBun8rMb1FUWSKPKXSOEYRlPcEcNtTI0aO8b3QB4qc9XpNuzOSkWjXd97wh/BU0RrvkFtXhzQKKcrxcNFL2Kaxc16qOznecBZWfbT6/Vi+fLlmD17Nnr16gWWZTF37lwAwNdffy3mnJDO88ILL6C8vBwnTpyA3W7H5s2b0aNHDzid4bryL7zwAmbNmoVFixaJ+0aOHInOnTvD7/eDIAiCIAgi4YTe8kZVxjTKiA9eI3wgngG1RjMqL2kUD28WrVKL4noSYB1qGfLRVFmQH5RUrIC+8aptLEd3Msprq3eVIt1hMzk59BBDNmIx0xXuFWaTQ8ryXGh5SBjk6TADD+3nPCxItK8kEemZZvjo7pNeMtd4adcqG5RD4rygvep7mUIo+1lTU4OCggLT/TZs2ICGhgbceOONOHbsGP7+97+juroaQLAyxrFjx0QBweVy4bbbbsPWrVsxZswY8DyPIUOG4NVXX8X9998vG/eVV17B8ePHMX78ePz617/GzJkz8d133+Gnn34Sk18SBEEQBEFEj/qHddgOEzLU6f8si/tneYScFUZiglF72T6DRdoSYlfory4RGTm01h/ruDzChrCxYamdJFAPbbFH3SaWyx2tIKEdshHLzPKyn2YFCem3xchDgtMNOVGGaEC1rSVSiQJHO9vKyjOSCiu8QsQxE77RboknqTQnESdnRdlPJdXV1XC5XJg+fbrqWHl5OSZOnIgPP/wQ/fv3xxdffIHjx49j9erVKC0tBcMweP755/H666/jlVdewdGjR9GrVy/Nsp8AkJubi1WrVqFPnz6JOm2CIAiCIM43DK3MyIJE3GU/I3hIRGt4S4134aPRGAnxkIh7hOjHl4YiyA1YPqIhZua6aIZsGOWm0Dik8pDgEyBImBhAel7xeKgor4/ZpJbSflrBCIyoG5j1DOBVW8YhG+1riCuvi7Q6jNazFen7wcXwHUy21EBix/lB0st+mqGqqgoA0Lt3MGHWzJkzxbCOjRs34ueff8Ytt9yC5557DsOHD8d9992H/Px8AEBrazCRV3Z2Nj7++GOMGjUKPXr0QG5uLgAgNTUVQLjs59SpU8V5OY7Dnj17AATDRAiCIAiCIBKOGUEiTiKHbESHUc4ALSNOmecgFpRvtKVouewnAiPD3NgglQoZ0noNilYGBq/mejT2qXNImO8rn9d8W2Ub4XmI7TbLZzMdsiGZizPykDBdGlOxrVpZeH9HoCw5qrwuQa8I86vR8xQxQqt0rapNu4ZsEOcDSU9q+d///d8AgG+++QZA0MPB5XLB6XSKZT+FnBBCtY1BgwZh0KBBOHDgAMrLy2VlP7t27YpJkyaJ26NGjYLFYsHjjz+OxsZGXHHFFfj888/x6quvYsaMGejatSuAcNnP9evXo6qqCn6/H5s3bxbLfR48GLnkEUEQBEEQhDZGP61DOSQMwyritLgjekjIk+RFHE5zn/45WhNgWRitTcsgTcT4sco4QVuS1x1XbBdlUkvtkqrKNjrJBSLcA6nxacrQlTQJiwPR32hVUkvTHhLhuYwEqXhySGheRj45HhJa10UaaqVVlUMKHymHhGb3yN8ryiFBxEvSBYmVK1fKtsvKylBWVoaCggJRkNBDWvZz586dmm369++PP/3pT/jjH/8IAHj22WcBALfeequ4DwiX/dyzZw+2bdsGm82GkSNHYuHChVi6dGlMZT8JgiAIgiAiYsJDgktzKvZE+UNdZ+xsP4smuxU5LI9qACmc1Mo0yNkgaXYs1Q4A8BslnYxqsXqT6o9vbSfXbum4P7uPi5+Pe2qRY1fekzD/bN4BhCqYRutlcdh1XKNlaCyNfWaTWkaCl/Q05yEhT9wZHCP2+yAY+rEktTQSk8ysieM57GySV0v4Md2G3h51UnsePI65TxqXqE0A0u/MXw++LDtWZQ1eI+l516cYm3XlDbsNj8fqDdKeURUkSJwfJF2QOHDgAABg69atmDdvHkpKSlRVNgTPCCnKsp9CiEZxcbGqbX5+PsaOHYsrrrgCPXr0wM6dO/H6668jOzsbCxYsABAu+3nw4EE8+eSTCSn7SWVgCIIgCCLxtBTfCS4lLdnLSBwmBAnXhfJy5VH/TleMPetEE7JYDg6Ox3GHDcO4dAxrakIfqQGmmGNgmxc/hkoACqPZOB4BS3D9LdbgXqlhc/+xBjTZEhMuwhj4jw9v8aLR1ga3hcG2UDnSqMfX2JfCAyPRCbvRqDpm9hYYnb2WwdUcaNVtr/UWfGSLB7uyUiVtdPoarCO4Fuk8ERpHObYWvryBoc7yDI1G1SAmnm4Ty8YKa8z1BVDo8WOXU/43QTjOmcghoVcSk+F5+Lv0ASAvh7un+UfD8WyM1bSwoofRPThqY4PioZDUsp1UAVOCRHuKBjywa9eu9hufOCNIuiARC8qyn0bs2rUL999/P95++20UFRUBACZNmoTMzEz87W9/w80334x+/foBAF588UU89NBDYtlPq9WKOXPmYMeOHWJIRzQMGzYMDkfkGunJgL7cBEEQxNlKoHPvZC8hofAmBAnenqrcE90kCu+C4W3h3Fg9fAGwGekY2SrPlyVdza0nm8AyTFiQCBlABV4/jqSlqNoDQFaAlQsc8WJg9abyPK493YYau9WUIJHnDaDGIf8ZrDf8xXqChEkj0DBkI0pDUhjLwXHwhsrEdvarcwtEuw7AXL4AWXsNj4pozobNypOPZ6J4xdBWb1iQCO0b2eJBi4boFW/ZT2EO3poCqSDBgzcsQQsARZn98V2LsWgRee7I627vRK/JEiSybVloCrSAB49Ro0YlfPxE4fV66QV0Akhq2c/a2lqsWLECd911Fx555BEAwL59+yL227BhA06ePIl169aJ+SQmTpwIIFi6U1r2c/369UhNTcWKFStQXFyMQYMGYdOmTbj66qvB8zy+/fZbcdycnBwUFxcjLy8PNpsN3bt3R35+Pqqrq6nsJ0EQBEEQ7USo7GE7JrWMVPZTy7SRV5iQhy9YJPuV+9qLaBMtGqGZlFPHrtI7L7OGmNHb66gdXcQx1fuk23FX2TDTXppzQhATYjD+1eU3jXJoqJ9B6fzytkH0PC7MpB3RyyHR3kIAELlySUesIdlJLYnzg6QKEocPH8batWtRU1ODgoIC0/2qq6vBstpuUDU1NZg4caJYmaOmpgatra2orKzE4MGDxXaBQNA1SzrOww8/jDVr1mDChAl44oknMHr0aCxZsgR1dXUYO3ZsLKdIEARBEARhjCBEtKcgEQMWhdGrVeZRFsffznaJUZWNaNEy9vQM1HgFiWhDNowQlmhkjCciZCP6JzGem68QJIzKnko/i8kltWcPl/2MvDa9ORkeqgeDBx/xWYzkQWGGaAS49hInzOWQSPwXPxE5SYizh6SGbAwdOhTbt29HTk4OnnnmGaxZs0aznVbZzwMHDmDPnj1YsWIFAKC+vh5PPvkkbrnlFlx99dViTokLLrgAO3fuxIoVK5CRkYGbbroJALB582YAEMM4KioqsHXrVjzwwAOYP38+gGDiyx07duDYsWMkSBAEQRAE0T4IxoulI9556qH+4W+UNNDoTX17mRBmjDzzHhLme+sKEmZDNgyaGeVL0J40tKYIHhKxIAvBMHFq0pVHY0DqrU+4nmbLU0rHYQ3KfpoSJHTaaN17M6tLxDc54hgdYKsnWw5I9vxEx5BUQSIzMzPmsp89evTA3r17cdVVV8HtdqOxsREAMHDgQFnZz9mzZ+P999/Hfffdh8mTJwMA3nzzTVRUVGD8+PEYNmyYbP7Kykps2LBBLPt54sQJAMD27dvRp0+f9rsYBEEQBEGcuxgZryZySGgMGNdyNBah2qN8C69VFlLWS2EUJlpeSWjIRhRvdfXuiplkiYDxmtgoBYnwG3Ht0AXlMTkRykLKFmrGiFevK5Y32owiqWXE8pTKORkGAY2LLB43ca85PQ8J2UjCKiPnkEiEN0/0QVbtO58e7Vr2sz1LeBBnDElPahlP2c+2tjaMGjUKbrcbTmew9JIQiiHQr18/vPPOO3j++efxxRdfAACOHDmCuXPn4oEHHhDbCUkr9+/fj9LSUrHs59NPP41HHnkEe/fujfdUCYIgCIIgNIghh0QH/E6PFMMOyI2Yds2BgQSHbEQxvtXrAjRylOsZsWbmCo8RrSARnDOSh4RmCEOEsaPNIQFG/bE50IYeZvpqcNBTjRxffoQcEtqfjTwkvJx2YlUf58dxTy0sYFDtqdWej+dVF4PneTT6W3TXCAAMm8Bkrjp4rJYOCNmIPLJZASkaGL8ndFIkSJwPJF2QiLXsZ9euXTF37lwUFRWB4ziUlpZi8+bN2L59O+bOnStr269fP7zwwgvYt28fbrrpJjz66KOYMWOGrE3fvn0BAPPnz8fUqVPF/W+++SaAYALOaKGsqwRBEASRXHgwYLO6JXsZhvAx5ZCI/EOdTesEq7tRtd+XX4SUk5GTiEvftAc/q6sqyAQJW0rEMc3SzRdAbYryZ6qJkA2T9oum2KLz1jv1xF6gT65qv5aHRBdfAPWKdaezHE7breJ2ri+AulCbaEpDjmp2ozpUGcToSuhdA3+Et/r93OGKclotGZ4PV4SBdpnQ909+hsED5L/DIyGMuLutErvbKnF5irkqOuEcEcCwNi/2ZMkr0bhDIVBftR3Q7P/Jqa9Mrk3tIXHYdcywn+P4d0CM5WcFnAHzz0a7BXuZGVgUDxI4bcAD2K3geZ4qA54HJF2QiJUFCxbItqdNm4a8vDysW7cO5eXluPzyy6Mab8KECSgoKMCyZcvgcDhQVFSEiooKPPfcc7DZbPB4PFGvkcp+EgRBEERyabzusWQvIUSiQzYi03zFfyFnyzLVfk/fMaYECaO38OHTCTdiU50ATkVdPhIAlh6sBQPAZWFg44EUnseiAXIhyVyeQLNeC8Y5M6Sj2XWG1HInv72mGX/r1Vm2L4sNCxdWnscgl08iSMg9e42YWduCF3vmADD2utC7TFpeBFIubQ7/1jUj7EjfnivXE52rvcLgZ3067eR31ypJajm81YuWUy34V9cs8XgkASb6lQlr6JhynN19LNI5wGVws9s7kayp4XmuHRURKvt5PpBUQaK2thYlJSWoqKhARUUFgGDZT6WHhBaPPfYY3n33Xc1j27ZtkwkSHMdh3bp1KCkpARAME0lNTcWUKVPENg6HA6tWrcKcOXMwb948cf+4ceOwd+9epKfHp3ISBEEQBJEEEmCUtD/tI0jonrvWPAYu74BQbUB9TGoQKY2XaIwlYUUZnJG7fgKTWmpOo+kXAJuOca2VfFHznCX7LIoIgGg8JKSVToxKiXZIQkVle8V6osoroAyJMJhcJkgojinvaUKug1Z12ChDmeLBwTNwdVDYgp4gF4n2WJ1YQeWs+PtNxEtSBQmh7GdhYSEKCgpw6NChqPqnpaVh8eLFsn2LFi1CU1OTbN9zzz2HNWvW4Nprr8Unn3yC7OxsPPzww7BYLGKiSwB4++23UV9fj3HjxuGCCy5AW1sbNm3ahEAggMLCwthPlCAIgiAIQg/RQyKKH99xJHsz+yNfltRSp037prE0ni0etMt+amdG1BMktGLnI3leMOBlFpyfM+8hIR0rFg+JWOZR7pOenVHOCaNKGSrhShUSoX8GMq8MiYdEcJz2Kj+pXE/HeEiYQUwu206aRbIECeL84qwo+6mHzWbD9OnTxe2TJ0+CZVl07hx2laupqcGrr76K2bNnY8aMGfjkk0/wq1/9Cps2bcLy5ctx7bXXwmKxoKamBm+88QZmzJiBZcvC7o0WiwVvvvkmCgoK4j9hgiAIgiAIJR39FtCkJ4ZhyIbGfr6d/ccTW/bTXMgGwIihAUo0PSQizMsoPCT8UYRsSMc3utR6SS1jmccIqSdDfCEbcjiTN9EaViKk/yQUBhpJLTvQBD8b/ANiCdEiCCntmw45ApmZmcjJyYnYrqqqClVVVeK21+uF3x/MXsuyLFpbWwFALCE6btw4se3WrVvh9/sxa9YscR/DMLj99ttx/Phx7NmzBwBQUVEBlmVlCS09Hg92794NAGL5T4IgCIIgiETS3tUp1JizIPQqGki35YZx+1omZkY3uwKrpk2p3TveuyNPDirfjiaHhNA/1jVFldXBhKCgldQyfKx9PHikxq8QstGe8oAFao8NUzkkzhG3AfKQIDqCpCe1FESEb775BgBQXl4Ol8sFp9Mplv2cM2cOgHC1jVOnTmHLli0IBAIYMWIE/H4/bDYbAoEArrvuOowePVocf9++fXA4HPjoo49QV1cHACgtLUX37t0BAHv37sVFF10klv186623cPz4cbS0tGDTpk2iELF///52vhIEQRAEQZyfxGLIx2EGxBCyoTuU5HN7GyamckiYXIReSILZvdEgHcGi2I46ZCMkFMQSnhB7msnI41kVo0cnSMhn4wxDNsIoQzaM2saKMncK0LE5JCJ63CRwPs0cEiYGJkGCiJekCxIrV66UbZeVlaGsrAwFBQWiIKHE6XSisLAQtbW1cLvdsNlsSEtLQ0tLC9ra2mRtT506BZZlZfN88skn4mehnKdQ9vPrr7/GF198gbS0NIwZMwa//vWv8cQTT8RU9pMgCIIgCCIiZ0TIhnoNUi8Chpcb+2FDSN8cUSYdjJdEXiV19gdtwYOJIulkcAzjfcrjJ7ynohr/hMPcT3etOxyvIGHl5eEUVh4ICOESksFP+5rg4bzm51JM5jbpNaLt5RLGbOiHEQygWuBnddsj9mu1JuZptbB+wNox5lqEfKy6tDFa3yaCME/SBYkDB4K1gbdu3Yp58+ahpKREVWVD8IwQcDqd+OCDD1RjLV++XFX20+PxoF+/fvjXv/4la8txHIqKiuD1Bv9gDh06FCNGjMDBgwfxxz/+EcXFxaisrMTixYtht9tjKvtJZWAIgiAIggAAtpNBLiombLq7Bk1E+oHPAAAtl9wG3poCW+OxiOO3XPxLoPkLAEDrxTPB+NzBzyNnggkojEOTAsjkBg92ZqUEu4DH0LZwOUbpm9nBbV7sz3CIxkt2gMOVDW0YJSkj2XrxL5D5zT9NzStwS00z3slzittmQlvMmoFaxqoyR8XNtc0mR4uAUtiJYyifJXgNGmzack8XXwC+/CGYUrsPu5xp8oPR5EzV2PfbY6exsncXAMAvaprR3RvAC72Dedukd+aTU+VoY93mJ1MsbK+/BgDQw+NHdapdd13hsp/aqScTYSZrXbJjnpOGfe480YhPOmfGNe+dJ4IJ+iN5/MTyLI1pcmF7drB64OzqRuzOSsV3Wak616vjE0Rc1OKBg+NRHyqNu2vXrg5fA9GxJF2QSCR333031q1bJyv7mZqaKoZjSBGECIfDIe578cUX8dBDD2HRokUAAKvVijlz5mDHjh2aY0Ri2LBhsvHPJOjLTRAEQRAdiIExzVvDxqW376WiIBHI7QcAYHN6qodT+I0Hug0QBQl/t4Hifn/eQCjRitHXsnvSOR79XD4cSk8BA4XHQ6gDA2CQyxcUJJiwYTi5Xu6xymZ21ZjBmNEtHpkgES85fhYN9uBZaIcFyPcNbQ0LOZc0u7FTaeBroVW9Q/aZT4iPu/Rp4lKzxM9XNrjguXAsnCf3qvpEY6BrLbG7L+wtMrzVAzsPFLV6sS/TIQ9LYSxRJbXU8kxxBlhcX9+KdQXyXHOykI3Qd0ovrCARJSOD3zPz4/T2+DGszYctXfTbFDe58XW2/rPUy+PHsLbgs6cMhZEywCUVCM1f7yGtPlGQGOzyIZXj8V1WKliTfxfMMqO2GZu6yb+/mQEWrTpimsANp1rwaecMcXvUqFFxrKJ98Xq99AI6ASRVkKitrUVJSQkqKipQUVEBIJjzQekhEQmWZXHTTTfhxx9/hMVikZX97Nq1K77++mv89re/xddffw2WZTF8+HDcddddAIBu3bqJbXNyclBcXIzjx4+jvr4e+fn5yM/PR3V19Rn9ZSAIgiAI4izG0sE/x0wn0WQ0Psm3GR6SuosGhlsijEMzOSRMHtP0kFD0jiVxpJmY/0S8c5ZWQOEZhYGnc62NymmaheF58AwTfnPPCOsJL8gCJu5KFAwfeb2RklomwkMi2mdAEAq1jHvTc0qupc3gMnJATIqBUrywiWtWt010fohEJqYlzh2SKkgcPnwYa9euRWFhIQoKCnDo0KGYxnnzzTdx7FjQnZHjOFnZz+7du8PlcmH37t2YO3cu0tLSsGnTJjzyyCMAgKKiIrHtww8/jM8//xwzZ87EkCFDUFFRgSVLlgAAxo4dG+tpEgRBEARB6MLHJEi0f1JLMEZJ7eSVIyKtKBHGsLkzNtdKO2RDvi01RuMxzIyqUcSK3htxo5Kf0UzNRWlQS6+VhbFEJ0hozKU3u6zUaIQpEpLUEohKTBNaGmUeMZuoEoBuyVkgeC1i+VYp+wiih9Y9j6ekp9azblqQIFXivCKpZT+HDh2K7du345NPPsGkSZN022mV/RRKfTY2NuKFF17Ab37zG/G4tOznzz//DAC44oorcP/99+NXv/oV/ud//gc8zyM1NRUjRowAECz7KeSxeOqpp3D77bdj6dKl6Nkz6CZJggRBEARBEO2CJdHpHyNh/te++CJcYVxoZ/dvXw8JM2OYziGhlcBS6SERRdiBIYz8Y6I9JBhe4Qug5yERZw4JQH/t8oSnDLioQjbUmDFQlB4SqtKjiXjkonwEhPui5W1gek7JZ6PEndJgkmimUyZZtWncKzNlXyMR6/U/V0qmEuZJqodEZmZmzGU/b775ZkybNg0HDhxAWloa/v3vfwMIejxIy37u378f3bp1w/vvvw+Hw4ELL7wQW7duhc/ng9VqhcvlQmZmpjh/ZWUlNmzYAL/fj82bN4tlP7dv344+ffq0+zUhCIIgCOL8IjYPiTjQCtnQNGLD7+HVRy2S/aHkgoaCQQe98jRpzGgbjHL/gvZYcbu8CZQIEtrpHUPNohkyyiWockjEWdOD4bWzf0o9bTrMQyKKJ0G4v4G4QjbCnw09JHQ3zKMrSISGTHjIRgeWTCXOHpKe1DLWsp9XXnklSktLceLECdjtdqSlBZPDTJ8+XdbW5/OhX79+uPPOO7Fx40Zs2rQJffv2xZVXXokvvvgCP/30E0aOHCkmrdy/fz9KS0ths9kwcuRIPP3003jkkUewd686ORBBEARBEETcxCJIxGEpxJLsT9Uj5NVhumpEIqyMOD0kpG99NT0kFONHMnjNzq8cJhGXQvb2WWlQ6uaQiHF86dA67S2S0f2cHx7WfNlP7fEiEzGHRELylkT3EIghG3HMLRN3omhrenzFKdkNQiuSk0OCXCTON5IasgEEy34eOHAAL730EgCgpKQEBw4ckJX6/Pzzz2XbTqcTTz/9NHr16oXrrrsO33//PdauXQtA/R+Tvn37Yv/+/bjrrrvw+eef4/vvv8e//vUvMfFlbW2t2A4A5s+fj2+//RY7d+7E2rVr0dLSImtHEARBEAQRC8rkg/6c3sEPluh/jnGOjMiNFLCZucEPZpNaWmzo5QkAADLZ4Fv4PG9wu0soCUMPrx9d/MGI+TwmTd+UYBgEnN2jXrMUvbEdnNJDQJveoXMBgG6+gOp4usIKZwBwdhOVNSIgXfdpuzUmd/h0Vp2iURiHSw2XmDT0kLCaF770VnhBqLKDMENPjx8A0MkfXl+l6yh8vF937D6e4Bhshn4pCoYPVtpQkiG5Dk42uMqcUDvhORQQntV4sPAA68wz3V64J/3d6up8wj3sHmFd0lChQo/+deQZRhwzJcoQGWmFjhQu2Le3OzyXIKgMckVfZTAShRrXRkl+6BplazwDxLlH0j0kYuXjjz/G7t278dFHHxm2u/3221FaWopHHnkEDz74INLS0rBhwwaxRIvHE6yRPWHCBBQUFGDZsmVwOBwoKipCRUUFnnvuOdhsNrFdNFAZGIIgCIIgBJquegBgw8ZI66hfwuJtVbVrvPKBiN4AXGYumi6fC96eJrZ9/HAdGACBAdp9Wi65HRZvm6Eg0Tb0egRyeoLxe5G+7xNcX38Sl7S4kRsy9n5T3YgWmwX5VicerDqN7r4AGAAPVp2Gs/9INF39ECxtp+H8T4liZAYtxbNg8bbhia9WgwWDJpsFHMOgs1/f6Fj4cx2W98kVx5Ayqb4Vw1u9yGQ5eHqPQmqVuqR5gceP46l2AMC1p1sxobENHBh4LAx2ZqchM8Did1Wn0WizoCWnAEAABR4/bqtphgVA88Uz4fzP65oGepcAUB/6Jd3VF8DsE02a5xBLQs+Lm934JlRm9NGf6+Dg5CvgATxxuA5+CwO221AA1QCEUAcGvu5DANQBAJrG3Qsm4AV38lMAcmP4D4dO4YdMBwa3+RDI6gbXsKkAz8N3chuABtW6Zp1sQpPNKnonXNXgQlGbDw6btnAzstmN3aHzeKDqNFxWBr2sndB82a2ioa98mQgE73S+j8XgNi/2ZzgwttGFS5vd6Cp5Vka4WBS4GlAYMqT7efz4r2On8feeweT2F2b1xzs4JRt3SKsX19W34rlCbTFk3tHT6OJn8ad+oTK1Fhu8vUfhhu1f4l9ds1TtZ51sQjrL4aMumTieahfv9KyTTTiaakdWgEOLzQIHxyPPF8Apuw3dfQFc2OpBm9UCC4DvMh3Y0kUpKgHufpdhwqGvZMfuP9aAqlQbPszNAg9gXCADfaobUdC5CEWHv8O3WQ58mBte5+0nm5DG8vg5zY7PQ6U0LeAx+0QjmkPlNx08j3lHTyPL0Rl/Cd3GbD+LX51oQr6fxVed0mXnnBVg0aIo3ZnrC2BaXSv+0aOTbL9Wudw7TjZjad9c6MEAuLTZg+wAh15eFrt2qb/XxLnFWSlIeL1eLF++HLNnz0avXr0M206YMAF/+MMf8Mwzz+Dmm28GABQWFuKhhx7C008/jYyM4JfT4XBg9erVeOihhzBv3jwAQEpKCn7/+99j1apVSE9P151Dj2HDhsHhcETdryOgLzdBEARBdCx8iuK3hC0FnK2zul2q2vDRgsvqJtt2ht6Wqs3I8LhsahbAaQkAoWwQjkxwmV2FHrAiaBhK53CyHAJOO3q4gsYtm56DHq4GtFms4FPSwXEab4AZBrA5wNkcyGaD0enZGm/9lXQOSNoo7NZufhbdQgaqK/S2XWnaFngDOG23wm21wMqHz6UyLShSdPWzSOV45PtYtIRCZ2w8HzZ8bfq/41gmXAazi59FVz+LOrs6Qaky/MGMPNFJct45Ae3rlMHxAMfDyzAKAYsB58iEIEhwIc8Y/qR65gyOR3Fz8KWbN6sb2OygFwvbkAmw6icphYd4bThHJizeVvTwBVCX1QmAPEwj28+KzyQAFIS8UgKZgDuC14EQAtLf5cP+DAcskD+HwbUw6K/wICiUeMFwzu5AQC5I5PkCSOW0vQkyYEMv4c28n0WT3QqkpAMSTwTZGnkew1u9obXwoXULawP6h4SSbhIRpUfoGmRwPDJC38M0xdhiuERKhsqVvY/HL+Y/4QDYM3Ix6EQtXD07I4OxyzxVgOCzPNDtC4VBBG0ehg+uL1eyrl7eAAKpdgDh69nDFwDnUP8t0np+c/2s6Gkhxal4dnlE9uYQwsCKXD7wAPqPGmXYPpl4vV56AZ0AkhqyUVtbixUrVuCuu+4Sy3Du27cvYr8NGzbg5MmTWLduHQYNGoRBgwZh4sSJAIBXXnkFx44dg98f/EIdPXoUu3btQpcuXeBwOJCZmYnc3FxUVweV5MLCQnHcAQMGYMaMGSgoKIDNZkPnzp1RV1eH06dPy9oRBEEQBEGcvZjJdGAMb02RbIT6GnheJKLsp6qmh0ZWP6OKDRHLLYbWL12r0VXhYFwFQdouWiKtVTatRIxgoJ8jJJpEk6bayuaNI2eCloeEieltURXQDMJDPz+G1jmL4oDJnBCxVIhQfjfEMXTmFHKb8IziWbVYNRNUAurKGpEaMRr7wuvVXpOZqhq8PG9spGVQgsvzhKR6SBw+fBhr165FYWEhCgoKcOjQIVP9qqurwbLa7n01NTWYOHEiPvzwQ/Tv3x81NTVobGzEjTfeiPz8fHg8Hnz66adYv349MjMz0b9/f7HvsmXL8Nprr2Hy5Mm45557UFlZibVr14LneSr7SRAEQRDEuYGBcWVaOLDaJZ1CJrfFwPRPQIJBU54GWsYOrz6oWSoylKhTNo+ByMIBsIJHIMI1iyWpZeSSowZmG8NoXodElP3UX4P2fLGOY+aNqSXSldR65hhzAhEj/hvyHIrUXtDkYkjIyCmWaYkwhnCcBxN+PhkGvMUGuyJ3h1aVHHOJJYX+JoUYk+dtphWJEOcfSRUkhg4diu3btyMnJwfPPPMM1qxZo9muqqoKANC7dzD508yZM3HgwAHs2bMHK1asAADU19fjySefxC233IKrr74a+fn5AIBLLrkEr776qmy8IUOG4I477oDD4YAl9B/PmpoavPHGG5gxYwaWLVsGAKJ4cfLkSXTurHapJAiCIAiCODeIzgyQekgIifzav+ynMumkxLzhtVoo24Vfz2oaagblULUMKY7hVR4SWm/IldUeojEI9TDykNBNahnFPTBjOEYaj4d2NROVUKCTQyIiEUQurefRqJSldH+0goTw5MRSmUVPsNL7PokeEoDkGjCAxQabSm0JPRGSSfTXqHyOoHmNNT0kIo4Y7kuCA6EkqYJEZmYm/vu//xsA8M033wAAysvL4XK54HQ6xbKfc+bMAQCx0sagQYPQo0cP7N27F1dddRXcbjcaGxsBAAMHDsSkSZPEOaqqqrBgwQJcffXVyM3NxU8//YSNGzeiU6dOsFrDcX4VFRVgWRbNzc3YuHEjWlpasGnTJjQ3NwMAtmzZgmHDhrXr9SAIgiAIgmh3dN4cqzAwrniph4TwztmoekciPCSUQ5o0/sJve/WPSbd4gxZSOEDXRV7ZLloiXi1D7UfbLz66kA0TSO6prveF5nOlvMKxhWxEfqZ0hBkTIS2M4l/t9mZnNEbpIRE+dx1BQpifgfweWKywserkp+r+0agmWoKEyTgOjd1mRDESLM4/kp7UcuXKlbLtsrIylJWVoaCgQBQk9Ghra8OoUaPgdrvhdDoBAIGAPJFSVlYWcnNz8frrr6OpqQndunXD6NGj8dVXX+GGG24Q2/l8wRI0P/zwA7788kukpaVhzJgxWLFiBW6++Wbs3bs3EadLEARBEARx1sPbpCEbyhwS2n4K8SMfQ0v+0DKMtQQJwTDScmWXex/oiyweC4MsldqgIQToGpz6RHrTLjuXRHlISIQC3swiI3koIHphQ9yVCOd+nbf7ugKRpAKO4PVjJGZJabEGnxOPJfrnXJVDQvyg5yEh9fJhwm2tNth82iuVPsWmPHSMhDadATS9iJRtTExOgsT5R9IFiQMHDgAAtm7dinnz5qGkpASXXnqprI3gGSGla9eumDt3LoqKisBxHEpLS7F582Zs374dc+fOFdvl5OTg73//O/7617/ilVdeQXV1NU6ePIlrr70W//f//l+xXd++fQEAs2bNwr333ivu//LLLwEEE3BGC2VdJQiCIAiio/AWDI/fE8Fsd0ZSTcJEUkvpujyFlyD1yE5x29dtIFJqf4w4pTIhntZS7RyPzn4Wnf0sDqYHw0qmn2rB/8vNQgarVbEjPGDn9HxkemsxuV5SijXC9VSWP9Rct+Tz5Dp1mVctLnD58BGC5RSlDGrz4kCGQ9+Lg4fumrko3owPsXTBZzgeoVV4ntROvQEo76FcVmAzusDaVg/3oIm64wgcSQveuwvbvPi0SwZGcVkAgtfu2vpWHE5LCZa8NVye+nnkwSAnoF9mVrkiwXuDSzGeq8YRNKl+zIi+ut7wVg8+65yOoa0+7HamRmwvDdnwd+kD+6mfwGZ1A19zQBVC5O9UALTJc/QxPNB24TRkfLdZ3pj1yTZ5awraht8I1H8s268p6Og4TWgLhNrPoYPlkKWoOOLuO5YqA54HJF2QiJUFCxbItqdNm4a8vDysW7cO5eXluPzyy2XHb731VowfPx61tbXYsmULWJYVvSKAYD6LESNGYNWqVcjNzUVxcTEqKyuxePFi2O12eDyeqNdIZT8JgiAIgugoXBdOi6N3lDEbEmOPCZX55K02/aEkO91F1wKMBak/fw3XoKvh7XUxUrauiLhC3WoEEqwAFh6px3+cqaIgMbTNh6Ft9Yqx5GN4e42E3ebAEwfq5O2iFHi0Wgs5JO440YQL27z4306RS8lnsRz+clD9MmxqXSsOZDjE0o/BSc15SLA6p9I29Hpk/PCRbF8ni/z3a4GivKaUltG3w9paL60YCUCe1PKGUy1ovuwBwKpleuhf42wW+NOhOrj7XQa+qR4M68PVDS6gwQVvj17w9hqFjO83a3dmLBjc5sX+DAf6un1BEQOAXS+8wCDdhTdvMOCr1F1nPOQEOPzpUB1Kc4LPRUQPidC/PAB/9yFo6j4kuOPQNtWVDHTuheZe48F8u17cxwDwFQxXCRL+rgMAHBRbNV7zu+BH+VcHrKbQo40yh4hR+NJFrV7cfKpF3G6cMB98mhOjqOznOU9SBYna2lqUlJSgoqICFRUVAIJlP5UeElo89thjePfddzWPbdu2TRQkKisr8c4776C8vBxVVVXIyMjA0KFD0dDQgPvvvx///Oc/xXJDL7zwAmbNmoVFixaJY40cORKdO3cWy4gSBEEQBEGc90iNEi74xpm3GPysVBpXoks4E7NXB6MIwogGraSW2pgtGhp5LovoZB95rXou80LOCrmhpxhRZ6kB3XljjOsPW84RE0gyRtNo9LUK52+xhd/cq9rxqjFlZTClopmJG66ZE4IX8opoheK0d3CB9vh6YSS8xaqZRBIMYzKpZaSZg2gJW7qCRBSXKECxGuctZ2XZT4G0tDQsXrxYtm/RokVoamoSt99++228/fbbuPbaazFr1iy0tLRg48aNOHbsGDiOw+HDh9GvXz8AwCuvvILjx49j/PjxGDBgAFpaWvDee+/BZrNhwoQJ8Z8wQRAEQRDEGY05q0CWt0As+xnNz0ohzMO8IKEM2TBTGjLC7AoMElDEgSAeKN3pDWEsANShBbbQGDJDT3H9eCguVAjdQIUIHi26TSIUk+Qluxleu43eXhsXypNgtYFhfQDD6FRoUOyxSEJoLBaJGCRZkw5aOTakRSzam3DpUHGPYTuVIGKx6QhZjOJO6VwFlaeNNnqeNlqoRBODvmy7CzzEmcpZUfZTD5vNhunTp4vbJ0+eBMuyshKdU6dOxfz585GRkSHuE0qDulwutLYG49G0yn4CQG5uLlatWoU+ffrEeJYEQRAEQRBnIwYGgpbbtmgMGvi+i40lgkSM1p7ZKhtaaL4w11pG6DzNJOPTG0LoG42vhcViBVgtQSLkIcHITUyZ3axj2LG6FyyyEGO8ZkYnX4N28lAlWm78gvAir+ZiAuk6GIvkPkd+WIyrZrS/sayaQec+CueiMvatNm0PCQUWnf3xeQHp5S2JvB4B8pA4f0l62U8zVFVVAQB69+4NIBivI4RQsCwLt9stKyE6btw4sW+PHj1kYgQQrLxhswVPvX///gDCZT+nTp0qtuM4Dnv27BHnJAiCIAiCOH8wMB8sGv4JsXhIRBGyoTR64vGQEIjsBxC/lSQYZUJ1BHMFJLTPzq71Blx2/UJ+BBrNogvZUObrMJjXwMvFjCCgtS5RShCfKXPCFS/1kGAsYTEoiksvbSdIPXFoX6YRrlEkoU0vZAMWm/Z3glF4SPA652PSQ0ILvYoqnIb3jp54ESAPifOWpCe1FESEb775BgBQXl4Ol8sFp9Mplv2cM2cOgHC1jVOnTmHLli0IBAIYMWIE/H4/bDYbAoEArrvuOowePVoc/+mnn8aRI0cwZswYdO/eHXV1dfjXv/6F5uZmdOnSRRQrhASX69evR1VVFfx+PzZv3iyW+zx48CAIgiAIgiDOTaI1BjRc9C1GSS0VvYXShfF4SMRhJvK6Vp2yXfxGkjBXNN7/Fka7eodm2AfPhUMjAF1xIKC519yCYskyIU1qaTQKa5DqUEyUqpEvIjik/sqCOSSUBrE+Wl4wlg4UJCQrCf6j6yEhaxXuZbGqxAwha4lxcI1wIHzDoj5fnUGj85AgQeJ8JemCxMqVK2XbZWVlKCsrQ0FBgShIKHE6nSgsLERtbS3cbjdsNhvS0tLQ0tKCtrY2WduJEyfif/7nf/DWW2+hsbERaWlp6NmzJxiGwaxZs8R2QtnPPXv2YNu2bbDZbBg5ciQWLlyIpUuXxlT2kyAIgiAI4kyGc2TB4m0Bl5oFNJ8Ab0sx1Y+3aVQRsxqEbKgGMJ9WMp3l4LJaVAajXWLtKF37U0M5CDJYbWPXETru1DkuEvJU0BtHiaZeoMgh4bJG9u1gdAQJoad8PQxaQ2OyoseJeiXZvBWnGC1ZInKIjdFd4nU8JLwWi7jONFZHUABgMfJ1CYlcDMeCS8uGxS+veqd8Di1+N4Cs0KItyAqV+BTutxFGIRupjDmTyWZiHj3cFiE8SBBBtC+YELaTHVA8kxZ1yEZKaN2ypJbgdfKJhHs7Wf3zcHCAV+OWpSi8aFI5HpmcfI05AVZXSFR9x7S8sIhzkqQLEgcOHAAAbN26FfPmzUNJSYmqyobgGSHgdDrxwQcfqMZavny5quznpEmTMGnSJLFNfX09ZsyYgd69e+Puu+8W9wtlPw8ePIgnn3wyIWU/qQwMQRAEQRBnIq0jpoNPyQRvd8DaWA1fj2Hw1+wH26lnuFHIGPd1uwAM6wfAwF5/GADg7XUxuJQ08CmZyNoRLCmoVWWjpfhOMJ4W1f7wHJFDNh48ehrVKTac7BVcW543gCsb2tDDFzaufflFsLgawbA+pFbtwvBWL3w1zRjZov37rWfOQMysqcTwVulxjXXYUuDtNRJXVlfAGeDwcZcMmdfExNNt+KxzhuSttXyMuccb8F5XJ4BwyMbJFP2f37NONMFrYWCzpIn7vD0uhKP6O3F7dnUjukvO3dt7FFAdvC9uq+BxwmNOdWPwDfWAUD9/Lr52HcLIFg84xrgEIwD89uhpHE5LwUe5mWLIg6xEqJgHxAowDH53pB4VmQ582iUckj3pdBu6+Flc2OZFo46BnWdzYtqpFmzumqU6Jr3WraNuha3hKDK/DVfZ83cdgLZhU2Gr/xmOEz8AAH53pB71diuQY8H0U63o7/bDZWWwJytVlD4eOVKP3VmpKO0cDus2Sgc5zNYNJ5q+RU2KFUfS9EW7h6uCNTL9XfqK3xWzNNuCq8vxs8LkAILP0MsFOWK7TJbHrJNN6OfywX9huD/PWGRXeHJdKy7onwswTDgEBvohITzD4LHDdfi4SyamNfjFKq7zj57G33oF8/NdeboNo9AJTe5aZIe+Dz9kpoIHkN/1QvyiZh+K2rz4PtOBC1u9GNLmRZPVigmNbaiz29Db4wfTuS/uOFGNBrsFWQEOfTx+HE5LwZDWcHi8t+dF4B3B52jXrl1RXUfi7CPpgkQiufvuu7Fu3TpZ2U8pLpcL9913H9xuN9atW4f0dHkd6BdffBEPPfSQWPbTarVizpw52LFjhxjSEQ3Dhg2Dw6HxBuEMgL7cBEEQBHH+4u8+VPzMOvMBAL6C4fJGIYHB03cM2JxesFf/AHv9YfjyiwCLRTaGtL0AZ09DoHNvnRWY95DoFODQKeDDydB2f7cPI1sVub3sqfAMugqWtnqkVu0CA2C0jhgBAGxOIS6p/kG+M7QUb/ehonELAN6eI+E8uhsTGl34rHM6fBIjOT30Vlcw8pRlDnt6A+I+wRi2GjiuD28LnhcrybPmHnilKEjwYDDE5UMgKw9oqQnOmd5JbBsu88hjsCv427UhdMwJK6bWt6onZYTEk/J19fYG4Am9pWYQFJx8PYaFBYlQuVdYbeDBINfP4uIWj0yQsMH4Pgjzj2tyawoS0ueDd2TCn18EICRI8DzAMPD1HAFb4zGxXa6fRa6fRbPFAgfPY1SLB190Cv7mt/E8uNQsdPO0YEKDSyZIAIC310g4ju5WPZWMhcGMUy34qEuGoSDRJeS14C0YblqQ8Of2g73ukFhlopsoNgW3B7j9qj7DQ89/g3SnxSK7h5c0u8EzFnCQl/oUzo3N6AJrWz2kRzoFONxW0wzOnoqm0N6e3rD4VeTyIieVQdfQmi5q8QYFCYsV3h7DMOrobgBAcXPwnlt44NbaZgBAvi/4vLi69seF++XXJkfxjPjyi8TPo0aNUp3/mYLX66UX0AkgqYJEbW0tSkpKUFFRgYqKCgDAvn37VB4SWjz22GN49913VfsZhpGV/RTw+Xx44IEHsG/fPgQCAdx2223YuXOnrE23bt1wzTXXoLa2FidPnkSXLl2QmpqK6urqM/rLQBAEQRAEkWiEBIEMFzJIImkHQiJGzdKDysGN4+Q1uyhyMegswtxgRu7gyjWZGFJ4A608c2kCQcEotJi5PLJqEYz8c8gQ14IVcnJo3AO9EACt/cK+8DVXj8fwbKiNVbxGhucWS44AoU/EZ0or7CR8DVmN9Sl78AwTPBfJsbDPAaPZR3850Z+rsEYxT0jUY8iTdoQDdxhZUIxFb3xF5RYtLLw814bc86JjM20Q5w5JFSQOHz6MtWvXorCwEAUFBTh06FBU/dPS0rB48WJxu6mpCUuWLJGV/QSC1TIeffRRfPXVV8jOztatmLFs2TK89tprmDx5MubOnYvKykqsWrUKLMti7Nix0Z8gQRAEQRDE2YpQsYAzlz8hbNCYEBuiyCEhmSCKtsbwmjka9MaPPK9eFQcGvFhpQDDeLGYMN1m1CKUgob8mloH+dY/h8ol3iZduhZB4SERtsEvnMDS847jnMkFCyOMhMaC1PFUkHiFAbBqKcm6zCEkdjTxoIs2pWm5In7LIzjuIWogym7o03C7a6iXmIXHjfCKpgsTQoUOxfft25OTk4JlnnsGaNWs02+mV/bTZbJg+fbrY7sknnwQgL/sJAE899RQ+/PBDXHnllfj5558xbNgw/O///q+sTU1NDd544w3MmDEDy5YtAxAUMrZt24aDBw9i4MCBiTlpgiAIgiCIswCVh4Tpjma8H4Q2UQyLqLvoY+QhoRQMTFilopGn4Vyh8pAwsz6ZYKLx5lqvkoZSFNJcpQ7SLox8l+aa+aBQxVusumEf5jBYVzyVFzQ8JGwGHhLBnaFnXnw85QkmTZ9dNIJE6HkTEk2G1xjluSvLe4r/r/CQEL97ijUqhS+tKSJsE0QsJFWQyMzMjKvsJwC89tpr8Hq9+Oqrr7Bt2zZMmTJFVvbzH//4BzZs2IChQ4eivLwcd9xxB7777jv4/X68//77oqBRUVEBlmVRX1+PDRs2iGU/f/75ZwDAF198QWEbBEEQBEGcP4geEoKpFIMLeULaKNomIixAy2DU6WvGCDUKVVAa9WbG42UeEhaNz0YhG9AJcYj+Wgv5LxhA5ZnBhJ6LYDLTkBdITHpEAjwkNMaQel6wGt4HWskdeaWHhKyeahTEIKQElF4cUY7BM4yO2MXIQ1ViDgkR+kqeAWHu6EaJ3IQcJM4rkp7UMtayn/n5+Th69CiWLl0KIJiAcvTo0ViyZIms7f79+wEAP/wQTE70j3/8Qzy2cOFCUZAQklYeOnQIX3/9tVj289VXX8Vdd92FvXv3xn+yBEEQBEEQZwm8pORiaI/iX72OoRAPMyEbCc8hYXYsjZCNOGLgBc8ATrE6hg8b9YLbPGfmnCWChCykQcznoechIXTSOJdI02ocl4dsKNoIz4XFJgolCX9jHpeHRPgaCk+wRWJQa3tIhMqnqp61KD0kYkCVQyIGAVAqsohnqROyoRrfRA4JBvLyrfJWpCIQsZF0QSLWsp/XX389AKCoqAgcx6G0tBSbN2/Ggw8+iJdfflls+5e//AUzZszAnDlzsGnTJgwePBiPPfYYtm7dKktq2bdvXwDAL3/5S9x7773i/i+//BJAMAFntFDWVYIgCIIgzlb8eYPgqP4eAWceAIDNClXjyBssaxfoVABb43Fxm7cHS1Z6e15kMPZAOE78gECowocZeluC5TMHusK5wHibA0xAmhtM34hjM3Nhba0LbkRIaskzDLj0HNWYkbJMZAdY2X4LIntIXNTigYXn8Y0zXOpT5iEhnSck9jC+Ns3jA0KVNfzdLpCVCjVevT5CZYThrZ5geVGJt4a39yikHtkRFE/EPBlhenrU1SE0CfUd2+jCtk7pyoNRr1lEco8HuXzY1ikdfdx+wGLXHdnWcBQAcCpUmtWqSGopZUyjC768gUip+RH9XT5Upgerb7DpOeBS1RVDApldYWs9pd7fqQfs9YdxUasXR9JS0MXPgk3rpBJjRja7jc+XYWQhM4zk/yyyZhaxvXwdvWRjaaGSnSLkkOAcmbB45ZVdAtmRv/NcZhfxM1UGPPdJuiARKwsWLJBtT5s2DXl5eVi3bh3Ky8vFsp8sy+LPf/4zZsyYgcGDB2sNBSCYz2LEiBFYtWoVcnNzUVxcjMrKSixevBh2ux0eT4SSRRpQ2U+CIAiCIM5W/HmD0HDto+Lbei6zi2xboOXS2ZCZJLYUNFz7mOHbbX9+ERquHagaS4m7/zikVf4bAFBgzcKSg7WQ9mic+AjMvpl1DZmMrK/fCG5YjH8CN177KLTyNVh1puLTuwBoQQbHY8nBWliAYLnF0L+AOgHgbSebMLjNhxQ+mKFgZm1LeEDdHBKhPaw8r8efq9rA+9vgGzoFPgD+fP3fvIHsHrA1VWuchHoj18+GzodB4+UTZdfCPXgS3IOC+4QcC9I39PfXeuHpOwaph7frrkV6fjfWteLiFg9e6tU5fJ15/YSqsnwVmh4hYTN8sMsnPjtsqnRWORavXOjpwzlkjYXznFzXigmNLjRedwtQ8S5+Ux30yA5k90DLmF8BDIPGiQ8DYNDps2cBAC2XzwXAAxyHzF1vwn66Cq3Dp4vXdEyTG8VNbvDZ3dE8Zg7spw6K61hysBYMgIbrFiFnyzLdKyI7J8EbhJGHbLSMu1dsDwAtxXci0Kkg4ncRAGwcTHutuC+YAIu7CY5j38r2cxm5hv0ar3wAvETQOZND5qnsZ2I458p+AsC2bdtEQWL16tU4cOAADhw4gH/+85+ydmVlZbjiiivE7RdeeAGzZs3CokWLxH0jR45E586d4febVHkJgiAIgiDOFZRGipbRIpSalLUzkdTPhAGkzPWg6qE1tw7S0Ac9D4TgQV43KaFNJ6yDkYoWin+FecMhGwhtA6marvQR1gdFWVAEhQ8LD/g0q4coZjCTcFFymlZhPq0ykYxctJGKBBbGoltqVGtdDMKCj5hHgWe1u6jWqxYulNU7lFdGa2XKPjZFKduwt0vozBgGvMUmeiCwEm8RwVMoPGHoWbVawNtCqojFKq6dCa3RHxqD13imDMUARh2yIT57snqg8nvGM4zGd1F7HuXzL9xvrSIsvD0VcDdprFP/FILHo69QQpzdnFNlPwFg0aJFaGoKPvw+nw+vvvoqAGDSpEm45JJLAAAffPABfvzxR2RnZ+P06dNimdBXXnkFx48fx/jx4zFgwAC0tLTgvffeg81mw4QJE+I9XYIgCIIgCCIaJAaYqQoO7VJCMtzPpjS6TIwsekiI2+rwBhV6ZT/F4zEYbVIDNOEIoovW3khdw60Ew1k4e8Zsydm4k3hqY2WCK2LEvCgROpg1ptWuDBpjRLl+RZUN6WTy+yJ/DhgtLxSdZyQoSKiPJTSpZXs8nsQZzVlR9lMPZdnPkydPgmVZUWDweDxobm4GEMxRsXXrVln/X/7yl5gyZQqee+45zbKfAJCbm4tVq1ahT58+MZ4lQRAEQRAEEQtKT4CI7Y0Omkjap24H2dt3tYeEIC7ojyf0EN7+h5NzGqw24nnrzBeX2GB09SKYnKKHhLJPdKaqKNYI15kz8JCQDh2FUW2MwkMCVvgBlYeE7sixzKl6pGL0EGDkTyEDHgzPg4dC/FJ4SGiJOXp3TSnIGSW11BuDUl8SSpJe9tMMVVVVAIDevXsDCMbrCCEULMvC7XbLSoiOGzcOQNCD4k9/+hOefPJJ3HLLLbj88sthtVqxYcMG7NmzBytWrEBeXjBRk1D2c+rUqeK8HMdhz5494pwEQRAEQRBEByI18OKoghEaLLZekrABq2INZip/iCEaYiWO0LZRqVCLcQ6JeDwkVONpDG/KG0VjjFiusLw8Z/BfMYcEF1B30JpeM4dEDKtRhnkwTFCQUMUj6PU3e1+MBLHYBAlemUMCCH5neE4mSITDaPQFCaOQDS2flcSKDOQicb6R9KSWgojwzTffAADKy8vhcrngdDrFsp9z5swBEK62cerUKWzZsgWBQAAjRoyA3++HzWZDIBDAddddh9GjRwMA7Ha7mEvio48+wjvvvAOGYdCpUycAwTAOAaHs5/r161FVVQW/34/NmzeL5T4PHgwnliEIgiAIgiA6gmiNE5OeDwbJElUGmuQtvfINMRcyHo1MSDHvgCKppfmQDY0xdYxWUzkbzFzSqMUfDQ8JPvpxBPFGDNkwuk8yM1irnd4VNv9MiRUpQuuI5CERrUdP8I4pRa5YPSQYhYcEAHBqUUfUI/TqvkD3BC2Ql62NfCUTJBQR5zRJFyRWrlwp2y4rK0NZWRkKCgpEQUKJ0+lEYWEhamtr4Xa7YbPZkJaWhpaWFrS1ybPjWiwWjBs3Dtdccw26deuGI0eO4Pnnn4fH48HOnTvFvBJC2c89e/Zg27ZtsNlsGDlyJBYuXIilS5fGVPaTIAiCIAiCiINojTPTto6GEahjKDESQcLOaRvYRiEbTGg2pX8CY+QhEaHKhu51MTz/4EFb00nN/bxh5ZFYQjZMIrnuQsiGTbjOhoKEbBDDcU3t12yrndRSd26Tz6vhtY4jZEM9Ea8h6gguO/Jz02wTYa/wDEftUWMICRbnG0kXJA4cOAAgmONh3rx5KCkpUVXZEDwjBJxOJz744APVWMuXL1eV/ezRowfWrVsnazdlyhRMnToVK1aswJtvvgkgXPbz4MGDePLJJxNS9pPKwBAEQRAEQUTGNfgaMKwPtoZjYLwt8PQbC/vpKnh7XYT0/Z+GWsmNHk+vizVGUhszXEo6LD4XwDBoHTkTjM8luvizaZ3AZneHt/co2JqVhnqQQE5P8fOtNc34Iicd2zqlAwDGtPpRb3NjfFoBXAOvAp+Sjozv5b9R/6se2G9pE9/XT0kdiM6N+9Df7dO/INKQDIaB+4Ir4e/cG87/lIT2WeAaPAlsVreI5y/CBudj2PC8rSNnItCpB3z5RfD2lf7+VoYohLebL70LtoZj8sMSY3h8gwt5vgCC79PNGKrhNRd6/Bjb6MLlfCd4e/YBl+pE2sEyzV6uomtkn1NO7kPLqF8ia9dboTVpXwvX0OuRtfN/NI+1jbgJ2V+uwr3HGnA01Q7kyMMahBAdqVzkHnw1HNXfhU5FLQq0jrhJJQp4+40Fw3MI5PSGvU6R1D+0bja7O3z5RUg5uU8+3sUzkfnN26p5/Ln9wAnVOxDy5uF5sFl5CGR1w3X1rejn9gE9g+O3DZ2C1EPlCHTpq74Qimt3/7EGHE6zCwfF/X08flzW6ML4Zj/QQzWIzu2PLqnlrl27jNsTZz1JFyQSyd13341169bJyn5qkZeXh6lTp+Ktt96C2+1GWlqwLM+LL76Ihx56SCz7abVaMWfOHOzYsUMM6YiGYcOGweFwxHYy7Qx9uQmCIAiCOFPw9hmt2ufvPlS+Q/Em19dzeORxe14EW93h0BYDf95AAICt/mcAAJfqRNtFNweHb64JtVJXPXD3uwxph75CNsthel2rKEjYYcGMUy3w9LbA3W8sLK31qjV056zo1Rj24M1KycL0ulbjhSs8JDz9L1Otydun2HgM1ZhqY1m4HsI1EDFIXsjm9AKb00s5uPhpan3w3LiUdJPJBaRVNoDpda3wdeuBtmFT4Di8XbcX78iUfW6Y/LhiWPX5evqOAZeqn8OOy+iMhsmPo/B/X0K/xia4O8srUQRCa5XmEuFTMsBmdIG1rV77GncfotrHZnVTX3PFuvmUdLRddDNSPpYLEgGnyvIPtk/NCo7Z+FlwGCBUwpaBu+gaXPX1egBAIxNu7x4yWXsNCvp4/Ojj8QszifstAG6sawVvTUGEJzoK5IrEqFGjEjZyovF6vfQCOgEkVZCora1FSUkJKioqUFFRAQDYt2+fykNCi8ceewzvvvuuaj/DMGLZTymHDx/GypUrsX37drhcLmRkZIDjODQ3N4uCRE5ODoqLi3H8+HHU19cjPz8f+fn5qK6uPqO/DARBEARBEOcdUac50EiQKd3HKI5Ju+pVe1C9hddaVAzu7IzcQ0I1YizhCFHlc4g2qaVuVgUTfU3uixq9Qczk2Qhdf/G8QglJlUk3haOCiBBLslFVotQIYxgtX5WvlFOPaSpkJab0pCb3RT8KcW6TVEHi8OHDWLt2LQoLC1FQUIBDhw5F7iQhLS0NixcvFrebmpqwZMkSseynwA8//IDZs2ejX79+uO+++5CRkYE33ngDDQ0NyM7OFts9/PDD+PzzzzFz5kwMGTIEFRUVWLJkCQBg7NixcZwpQRAEQRAEERemDOrI5TdlY8mMP0arZWiXTi4Do8SAyrlU8xh0iWjYJspgTBQ664n5niVAkdAyvE2LMtqVKFhG7SEBIBxiE1P+B7VHjvHSQjk/zFw3cZ3qdJcJh5QEIkaSKkgMHToU27dvR05ODp555hmsWbNGs51e2U+bzYbp06eL7Z588kkA4bKfQLAix8KFCzF27Fi88MILsFgsOHLkCJYuXYri4mKkpgZjrSoqKrB161Y88MADmD9/PgDg1ltvxY4dO3Ds2DESJAiCIAiCIJJKjG/bNQ+GBAaZh4RBGURez0NCSAxoMG1M5Uqji7M31y8ZHhImklJq9jXjeRLLuFpjG40hr7IR0PGQUHtUxEFEUUORlNIILU+g9hAkElk5g6pwnHckVZDIzMyMq+wnALz22mvwer346quvsG3bNkyZMkUs+wkACxcuxMGDB3HppZfi7bffRmVlJd5+O5gI5tFHHxXbCfNXVlZiw4YNYtnPEydOAAC2b9+OPn36tNOVIAiCIAiCIAyJybCXINUeDA01rZANbcNacIUP553Q6Kt6Ax5FyIB+g8hjKIlKj4it7Kdqb6weEu0WssFHN7ZCpNL1kGAS6SFhcoGyPCM6fXkt4c38ygiiI0h6UstYy37m5+fj6NGjWLp0KYBgAsrRo0eLIRYCdrsdVqsV77//PtavXy+2nThxIvr16ye2E5JW7t+/H6WlpWLZz6effhqPPPII9u7dm7BzJgiCIAiCIKJFadyaNZq13NaFMo5aHhJaQ0QK2YhySRGIGLKhl7vCwJhNbGnGSOtB0Ig3I0iY8pCIAc01RTe2kKtDuHZsqKvSgBJzSMQiSChzSET0fAg9uxYNQULXs8Qi2ZNsRSLSM5Hs9REdTdIFiVjLfl5//fUAgKKiInAch9LSUmzevBkPPvggXn75ZbGt1WpFSkoKWJbFnXfeiUsvvRS7d+/Gq6++igULFogeGn37BkvezJ8/H1OnThX7C2VBa2trE3zmBEEQBEEQRCQC2T1ga6pWm1op6Rqt5a3YrG6wCWUVJQYq58gKHs/uru6rYURzaZ20F2fmbbZCzLC41cnXVWgam7KJ5c19ruBe1i/u48HIRYhovB6i9ZDQuA4WvxtsVtfIUxmOF71xyqZ1gtXdGM1sAIA8b0BrIeKYAFDgDeCndAeyA4oQnrg8JBRDsTrhQSH4kGdEoEsf3TZdfMFz4VKdoUE1hDcN2NRsWD1NslK3+uuwyMqZco6M4H5rChjWBy49Bywnv6b+3H7anh3EeU3SBYlYWbBggWx72rRpyMvLw7p161BeXi6W/XS5XHC73bjtttvwhz/8AQBw7bXXgmEYrFu3Dvv378fgwYMxYcIEFBQUYNmyZXA4HCgqKkJFRQWee+452Gw2eDyeqNdIZWAIgiAIgiDio2X07bB4WmGvD5bv9HUdAM8FE8Cl56gbC5qC1Y6W4jvBOvMlpSPDhhib3R3NY+8G6+wm6asfsuHpeykCnQqQUfEeLH43Fh2uC46W1kXRUt636fK5yNy9SbbPSJBovnwuwAaCJSSN0DMqA+Ey9c3j7tHs4+4/Dt5eF6vWqgVvtctEDt12Ovu9vS9B+r5PjTtrGPHxvMVvuexuMCGBRoXFqnntfnekHpksB7ei0qywtkDX/mi9+Be4qrIcw6tqkedTChKMrH1UKMQfpRjQfNndcH71SniHPRVNl88Fly5P4g8EPTp+d6QeGSyHlot/KZZn5U3mkGgeNxf2usPwdxsg7mu86kF0Kn1B1q7piv8Cb3PAcXQ30n76X/AAuKxuaL7sN2Azu8LaUgM2uzsCXfqAS3Ui0Lk3GJ8rKJBYbfB36QN7/c/w9L4YDM/DcXS3ZHny9e3atUt3vcS5wVkrSGhx9913Y926ddi2bZsoSAhJK6dNmyZre+ONN2LdunXYtWsXBg8eDIfDgdWrV+Ohhx7CvHnzAAApKSn4/e9/j1WrViE9XUuFN2bYsGFwOBxxnlX7QF9ugiAIgiDOCmwOcJkOoD7o6cClZYN15uk0losO8kMK74nsfJ0RNMxrqx2B3L7iGNmskOTQ2HDmHVlQmesG3g9sVlAgiVmQkMzFZeYqjoSqMzgywKdmGo8vlLlMzYK17XSEtgbriTVfhioXQuRhxKb2VPD2VO1jOoJBrj8oMLgN1uHvdgFSju9Bj6Zq9QAJ9JBQev6wGsIDl9VNtS+0APFcGqXPt9m8FDYH/PmD5etxKJ4VhhHFQKUHjPC9FL97DCOOJz0vNqML7PU/g8voEtFjaNSoUebWngS8Xi+9gE4ASRUkamtrUVJSgoqKClRUVAAA9u3bpwrZ0OKxxx7Du+++q9rPMAyamsIPdteuwS/KG2+8gUcffRT19fXIy8sTK3E0NzeLbQcMGIAZM2Zg/fr1qKmpQefOnVFXV4fTp0+jsLAwrnMlCIIgCIIg4kA0Stsnxlx8ixxNtIKQOwBCrgHlcUYjR0D8Lut6HgQMZ+DuLzqARD5BcXTT7vVxGOIJMOKjmyuqrJYRtoOEc0jEX45VJZok5PqYC9kwg/zZizW0RpLXJd5ktcRZT1IFicOHD2Pt2rUoLCxEQUEBDh06FFX/tLQ0LF68WNxuamrCkiVL0LlzWEm84IILAASrd/zqV79Cfn4+9u7dK+aGkLZdtmwZXnvtNUyePBn33HMPKisrsXbtWvA8T2U/CYIgCIIgkoqQuNFMW8bwk2EfvQSWml2USS2VxiUDdRUFE0Z+JKNR77jh2vVDUtTjGCVOjGI9JtBO4thOiQ2jFYOU56XrCRK7h4SqEkk8gkSk9Rm1iYGYkngifM48w2g8s5TU8nwjqYLE0KFDsX37duTk5OCZZ57BmjVrNNtVVVUBAHr37g0g6B7j9/ths9kwffp0sd2TTz4JAKL3AxCssgEAgwcPxgMPPCDu37VrFw4cOCB6PtTU1OCNN97AjBkzsGzZMgCAx+PBp59+ipMnT8qEC4IgCIIgCCJZGBksBsdMG/lRvLEVcwcYrEdlcCbC4NLzkNBKzKjoY+r0BPHHpMEZzzmZCdlIENF6p0Tt8RCxQoYJzIog2p21P5vMIRHXHNHAG3hIkB5x3pFUQSIzM1OscvHNN98ACHoyuFwuOJ1OseznnDlzAISrbZw6dQpbtmwBALz22mvwer346quvsG3bNkyZMgWjR48W57DZgqe4Y8cOPPjggxgzZgx2794tVvfo378/AKCiogIsy6K5uRkbN25ES0sLNm3aJIZ0bNmyBcOGDWvPy0EQBEEQBEHoITVi9IjLmIm+c9hg1X8zrcpJkQgXdT0j1UzIRhSCS+QSlKrBo6edxAftuaIUDFTtI601EYKE0kMiiuujqxUkUJCQDRVJkIs0FqP+fpAicd6R9KSWK1eulG2XlZWhrKwMBQUFoiChxOl0Ij8/H0ePHsXSpUsBBMt7jh49GkuWLJG1HTVqFCwWC7p3746Kigp89tlncDqdSE9Px3XXXSfmmPD5glmJf/jhB3z55ZdIS0vDmDFjsGLFCtx8883Yu3dvok+dIAiCIAiCMI3w1j5GD4lIRJFjIYzSANV426saLhEx8zHkkIjm2ojaT5I8JNorr4DJ82H8QnpLpbeCXofgP+YFHCkRckhEhbbwIPP0iNveT8RYlEOCCJN0QULwVNi6dSvmzZuHkpISVVJLwTNCwOl04vrrrwcAFBUVgeM4lJaWYvPmzXjwwQfx8ssvi2379++PP/3pT1i+fLno7XD69Gnceuut+OMf/yi269u3LwBg1qxZuPfee8X9X375JYBgAs5ooayrBEEQBEEQicGfNxj8j1/A23N45MYxGciCVRmFgaQwQNn0zuBsDgRy+8PWUBXKF2HsIeEecAXSDpZFuVT5+fnyBiGl5gC8BRdG7mvq/ATxx1yIg1aSTU+fyEnqQ5Poz59AeIsNvm4DwfBGok0QS0iQ4O3yannS82wbOkVyJP6yn2xGFzDeNlXlCgBgM3NDpVojYSKHRCI9JOIN2TCRQ4IqA577JF2QiJUFCxbItqdNm4a8vDysW7cO5eXlYtlPAMjPz8eIESNwxRVXoEePHti5cydef/11ZGdni+MMHToUI0aMwKpVq5Cbm4vi4mJUVlZi8eLFsNvt8Hg8Ua+Ryn4SBEEQBEEkBi69Exqve8xUW15jK6KJKxptBi0jufDbUtA0Sf4bVS0AyLc9/S5TCRJ6VTT05m0beQvaIvSIKSTFajfXUEMAcg+eGHVf16CrkX7gc6jXGr9A0XjtwuB0rgbTfVinojRsaK3eHsPg63WRan88niL+3L5wF12reax53L2a+1XoenAkrsqG3EMiRm8OmSBhnEOCyn6e+5xzZT8BYNu2baIgsWjRImzatAlA2NtBYM2aNRg4cCBuuOEGAMALL7yAWbNmYdGiRWKbkSNHonPnzvD7/dGfIEEQBEEQBHFWoap6IDuodOEXDDIjIy9CDokY7MOYykvGkrTT0sGmghlRKF6i8IDRD5/Qfg4SF26RiDESmchSm4g5VPR7hvtRlY3znnOq7CcQFCCamprE7dOnT6NTp054/PHHZe2WL1+Ouro6uN1ucd8rr7yC48ePY/z48RgwYABaWlrw3nvvwWazYcKECTGcIUEQBEEQBNFxxG7ImjHyeUXOCN5MUr/2iJGP5y23mfUIZRmtZk2FBBmRcRn07YCeR4zi+vNxlP1M6POhlysioYlDE1hlg2GMBUDivOCsKPuph7Ls58mTJ8GyrKxEZyAQgMPhkLU7ceIE6uvrAQBM6AuqVfYTAHJzc7Fq1Sr06dMnllMkCIIgCIIgOgrRtmmnHBIxeUgouiTkjXA8HhJmiFaQSAzxeRiYnsV8U92KFzrPQVzJPeMXDeRnlsgwDemw8Y8riBDB0CTl94E430iqDJmZmYmcnJyI7aqqqlBVVSVue71eMYSCZVm0trYCgFhCdNy4cWLbPn36oKamBjt37hT3bd68GXzoi1BUVAQgXPZz6tSpYjuO47Bnzx5xToIgCIIgCOIsICYb30RIQywlGSPkkIiJOJJ2RvVG2nTIRoLecneEIBHNUvXWoydMxfS230Q52zhpP6En1jUb5ZCgkI3zjaQntRREhG+++QYAUF5eDpfLBafTKZb9nDNnDoBwtY1Tp05hy5YtCAQCGDFiBPx+P2w2GwKBAK677jqMHj1aHP+OO+7Apk2bcN999+HOO+9E9+7dsXr1agBB4WLYsGEAwmU/169fj6qqKvj9fmzevFks93nw4MF2vhIEQRAEQRBE+2EyUWRMHhJGoypzSETs0i7wGp/0G7e/kayJ6vq2x/zR5JBQzq9XxUIQe2J425/QkAVJqU+d/YmcI+b7Iz1nCtk470m6ILFy5UrZdllZGcrKylBQUCAKEkqcTicKCwtRW1sLt9sNm82GtLQ0tLS0oK1NnmO4X79+eOedd/D888/j/fffx6lTpxAIBDB8+HC89NJLYjuh7OeePXuwbds22Gw2jBw5EgsXLsTSpUtjKvtJEARBEARBdByCAcmlOsV9XKoTFk+LqkSnqm+oogTnyNBvpGugGhhmkTwkNNYMW4r+eAD4FIM16vZJD/5rT43cNtSGS0kzN3iEa2saZW4GmyO0HpPrMEM0iTr1PGIU6+SEaxuDJ0LU19oIvXCKBAo7su9HjONyjtD1sjnE55I4f0m6IHHgwAEAwNatWzFv3jyUlJSoqmwInhECTqcTH3zwgWqs5cuXa5b97NevH1544QUAwLPPPovVq1fjqaeeQmpq+A+yUPbz4MGDePLJJxNS9pPKwBAEQRAEQXQg9lS0jpiOQOdCcVfryJmw1f8M3pFp2JXL6oq2C2+Av9sA3TZKg5O3WE0sKihAtA6fDtaZh7SfvgAAePqOgS9vUPDYRTcj0KlA7OHvOgDenhfBl18kG6n5st8g9dBXcA8Yb2JeOd7C0eCtdnm5Sh18PUcAPA9fzxHg0rIjCgJ8SgZah0+HrakaqUd2yI61XvwLjUoKclpG3QYuzQlb88nQgMFr5iu4EODY4HpCNI27JygwmaBl9B2weJrApWaL+7j0Tmi78AZY2upx/7EdsBm9oVcKLSEDXHnfvb0vASx21f0yg/Rax42eQJCgkA3XoInw9r5YOnDwnygFKfegiWCz8hDI7YdATi8EsnvAn9sPtqZqVdtdu3bFsWLibCDpgkQiufvuu7Fu3TpZ2U8pPM9j8+bNGDhwIAYPHqw6/uKLL+Khhx4Sy35arVbMmTMHO3bsEEM6omHYsGFwOBzRn0gHQF9ugiAIgiDORfzdh8q2eUcG/D2G6rSW4yu40LiB0uATDFMTVTb8XfsD9lRxO9CpAGxIhPArDVmGgWvYFNVQrDMPbRfdbLxGPSwW+GTGpAFMuK3yeurh7zEUrDNPJUj4u10QsW+gaz8AAN9SE5xeEDAY9Zq5zK7gMruaWlOgS6HmfuE+9zn0lfEASgFK2FZ4WfCODHj6X2ZqTVpzmL4vJsaSbOh8jh1v71GAJNFpuMqMGWFOgtUOX6+Rwc+2FFEk86c5VU1HjRoVy1I7BK/XSy+gE0BSBYna2lqUlJSgoqICFRUVAIB9+/apPCS0eOyxx/Duu++q9jMMIyv7CQCVlZV45plnsG3bNrhcLvTu3Rvff/+9mD9CICcnB8XFxTh+/Djq6+uRn5+P/Px8VFdXn9FfBoIgCIIgCKIjUHpICD+lTYRsKBMfnovJ+0x5jBggXqMzpfKCdk4Lc54xHY9uyEiinjWdEJaOqY5CnKskVZA4fPgw1q5di8LCQhQUFODQoUNR9U9LS8PixYvF7aamJixZskRW9vPYsWO4/fbbkZKSgv79++O7776D3W7HXXfdhX/+858YMCDslvfwww/j888/x8yZMzFkyBBUVFRgyZIlAICxY8fGebYEQRAEQRDEWY2eh4QhegLEuSdI8NHkZ9DiTBMklPdMEJPiPc/2ot0FCZ1xzlCBhjg7SKqcNXToUGzfvh2ffPIJJk2apNtOr+ynzWbD9OnTxf8JlTCkZT/Xrl0Ll8uF1157DUePHsUll1yCd955B9nZ2Xj22WfFdhUVFWIei6eeegq33347li5dip49ewIgQYIgCIIgCOK8R5l0MQZBQii7yZ+DgkTchnpc5TM7AOHenQ2CRHt44CjGZLigcHSmeowQZwdJ/TZlZmbGVfYTAF577TV4vV589dVX2LZtG6ZMmSIr+/nNN99g2LBhqKqqQmNjI2644QakpaXh6quvxltvvYXW1lZkZmaK81dWVmLDhg1i2c8TJ04AALZv344+ffq0+zUhCIIgCIIgzkxUZSDNGKaqEprnbsgGb43PtBBc/2Mqn9kBiOuK8zzbjY4OneDZ0LwkSBCxk/RvU6xlP/Pz83H06FEsXboUQDAB5ejRo8UQCwGfz4fOnTvjX//6F+x2OyZPngwASE1Nhd/vx08//YSRI0eKSSv379+P0tJSsezn008/jUceeQR79+5N9KkTBEEQBEEQZxXKHBKhbQNxQTyievt/7gkS514OCQX8me0RoBLM2hsuJEgkquwrcV6SdEEi1rKf119/PQCgqKgIHMehtLQUmzdvxoMPPoiXX35ZbNu3b1/s3r0bpaWlshANwSOitrZWbAcA8+fPx9SpU8V2b775pqxdNFDWVYIgCIIgiHMHX/chsDeEw4gDOb0BAP4ufXT7eHpdjNSj34THyB8Me/1hcBmddfuctTAW8IwFgc69Y+rOZnQBAPjy1NXwOhJft4FIqf1RfUBS/eOMRBayoRZNfN2HxDSsL78IKSf3qfZzaZ1C45qrxBILVBnw3CfpgkSsLFiwQLY9bdo05OXlYd26dSgvLxfLft5+++0oLS3FI488ggcffBBpaWnYsGGDKBZ4PB4AwIQJE1BQUIBly5bB4XCgqKgIFRUVeO6552Cz2cR20UBlPwmCIAiCIM4dfL1GwlcwHDmfLgcAsDk90XDtQsPQDfeQ6+Auukb0ovD1vChYdvJMzUMQJ40TH4753Pg0JxquWZj0JIltI29Bm4aXhhCywZ+pIQpSTwWF10LDtY/GLKS0jbgJbcNvVO3nU7Pa/X6dyZUOqexnYjhry34CAMdx2LBhAzZu3IgjR44gLS0NALBlyxZRkJgwYQIWLVqEp59+GqWlpQCAlJQU3HzzzXjrrbeQkZEBAHA4HPjb3/6Gu+++G/PmzRPnuPbaa7Fz506kp6cn7LwJgiAIgiCIsxCGUecPiGR8M4z8bTXDAMy5KUYAAGxxvow7E/IzKO+ZgOghcYaG2xgJDvGIBnrXAzgz7hdxVnNWl/1cuHAhtm7dipkzZ2L27NlobW3FX//6V9TX18va7dmzBwBwww03oEePHvjPf/6Dd955BwBQWFgotnvppZfQ1NSE6667Dj169EBtbS0++OADMAwja0cQBEEQBEEQxHnGmR6ycS7mJSHOeZIqSAhlP3NycvDMM89gzZo1pvtu3rwZH3/8MdavX48RI0YAAE6ePIm//OUvGDBggNhuz549+OCDD7Bo0SKxWofX68WYMWPg9/vRv39/AOGynw888ADmz58v9vf5fPj0008xZEhsMVcEQRAEQRAEQZwDcEKFlDNUkDhTPTcIwoCkl/00Q1VVMHlQ797BBDlerxevvPIKJk2ahBEjRiAQCMDv94slRMeNGyf2/fjjj2G32/GLX/xC3PfDDz/A7XaD53nU1dWhW7duYpJLaUJLj8eDyspKAEBLS0scZ0oQBEEQBEEQxNkMAyGHxBkqSBDEWUjSg34EEUEQBMrLy+FyueB0OsWyn4Jng1Bt4+eff8YPP/wAq9WK2267DXv27AHLBsvOjB49GqNHjxbH3717N6xWK0pKSpCbm4uffvoJGzduxKBBg7B//37s27cP3bp1E8t+rl27FiNGjEBLSws2bdqEEydOAAiWAyUIgiAIgiAI4jyFO9NDNgji7CPpgsTKlStl22VlZSgrK0NBQYEoSChpbm4GECyryfM8rFYr8vPzEQgEsHv3buzZswfDhw8HADQ2NiI9PR1vvPEGmpqa0KNHD9xzzz24+uqrcfPNN6vKfpaVlWHz5s1IS0vDmDFjMGXKFLz44osxlf0kCIIgCIIgCOIcw0KhEQSRKJIuSBw4cAAAsHXrVsybNw8lJSWqKhuCZ4QAE4qPslqt+PTTT9G9e3cAQH19PSZNmoTVq1fjpZdeAgD4/X6MGDECq1atko1x9OhRAMHwDyBc9tPn8+HZZ58Vy34uXrw45rKfVAaGIAiCIAji3KPtwhsoXv8cwt3vMvi79o/Yrm3YFKQd+gqBnDM32b37gisR6FSQ7GUkjF27diV7CUQ7k3RBIhYcjmA5oYsvvlgUIwCgS5cuuOyyy8TwDwBITU2F3+9XjSEIEcJYDocDq1evxkMPPSSW/UxJScHvf/97rFq1Kqayn8OGDRPHP9OgLzdBEARBEERs+AouTPYSiATiGXilqXZ8WjZcQ69v38XEiaf/ZcleQkIZNWpUspegi9frpRfQCSCpgkRtbS1KSkpQUVGBiooKAMC+fftUHhJKunXrBiAoQLzxxhvYuHEjjhw5gvT0dDgcDjQ1NYlts7Oz8cMPP+Cuu+7C999/D5fLhZKSEnChGDBhLADIz89HcXEx6uvr0drait69eyMzMxMNDQ1U9pMgCIIgCIIgCIIgEkhSBYnDhw9j7dq1KCwsREFBAQ4dOmSqX15eHnJzc7F9+3aUlpZi5syZmD17NlpbW7Fu3TpkZWWJbbt27YqdO3fixIkTGDRoEHbv3g0AogAyePBgAEAgEMCvf/1r7N+/H3feeSd69+6Nf//731i0aBEAYOzYsYk8dYIgCIIgCIIgCII4r0lqitihQ4di+/bt+OSTTzBp0iTddlVVVWLpT4FBgwbh9OnTWLJkCZ544gn84he/wDXXXIPGxkZMmDBBbHfbbbcBAO68807MnTsXQFB82LRpEy6++GLk5eUBAD755BN89913+POf/4zHHnsMs2bNwrPPPgun0wmr1Sqr3EEQBEEQBEEQBEEQRHwk1UMiMzMzprKfAHD69GmkpKRg2bJlolixceNGOBwOMQcEAIwZMwaTJ0/GihUrRKFi6dKlqK6uxrJly8R2wvx79uyB1+sVy356vV6wLIudO3di/Pjx7XQlCIIgCIIgCIIgCOL8IulJLWMp+9na2or9+/dj9uzZ+PTTT/H8888DANLT0/Hoo4+q8j0sX74czz//PN5++20AAMuyWLNmjSxJis/ng8ViQXl5Od5++22x7Ofs2bPx//1//x/27t1LggRBEARBEARBEARBJIikCxKxlP2sqqoCz/N4//33kZ2djaVLl8JqteLll1/GU089hSFDhmD48OFie4fDgUcffRSjRo3CvHnzsHjxYtUcffv2Bcdx+Otf/4qLLrpI3P/MM88ACCbgJAiCIAiCIAiCIAgiMSRdkIgFl8sFAGhra8N7770nlv4cP348Jk2ahNWrV+Oll16Kasxp06bhpZdewmOPPYYnn3wSvXv3Rnl5OTZs2AAA8Hg8Ua+TysAQBEEQBEEQxJlJ44R5AJPUlHpEBHbt2pXsJRDtzFkpSDgcDgDAxRdfLIoRQLAM6GWXXSbmg4iGrl274u9//zsWLlyIX//61wCCOS7+8Ic/4NFHH0V6enrUYw4bNkxc65kGfbkJgiAIgiCI8xk+LTvZSyAiIA2xP9Pwer30AjoBnJWCRLdu3QAAubm5qmNdunRBc3NzTOOOHj0aW7duxY8//giXy4XBgweLoRp9+vSJeb0EQRAEQRAEQRAEQcg5KwWJvLw85ObmoqamRnWspqYGOTk5MY9ttVpRVFQkbn/11VcAgtU6CIIgCIIgCIIgCIJIDGdF0FRVVZVY2lNg8uTJ2L17NyorK8V9x44dQ3l5OS677LKEzHv69Gm8/PLLGDduHPr375+QMQmCIAiCIAiCIAiCOAM8JP77v/8bAERh4f3338euXbvgdDrFsp9z5swBIK+2cd999+Hjjz/Gr371K9x1112wWq1444034HA4MG/evKjnAIDbb78do0aNQmFhIU6dOoWNGzeC4zj86U9/ap+TJwiCIAiCIAiCIIjzlKQLEitXrpRtv/POOwCAgoICmVigpFu3bli/fj3+8pe/YPXq1eB5HhdffDEWLlyIwsLCmOYYOnQoPvroI9TU1CA7OxsTJkzA//k//wd5eXlxnSNBEARBEARBEARBEHIYnuf5ZC/iXEPIuEpVNgiCIAiCIAiCIGLjbKiycSbbfGcDZ0UOCYIgCIIgCIIgCIIgzi1IkCAIgiAIgiAIgiAIosMhQYIgCIIgCIIgCIIgiA6HBAmCIAiCIAiCIAiCIDocEiQIgiAIgiAIgiAIguhwSJAgCIIgCIIgCIIgCKLDIUGCIAiCIAiCIAiCIIgOhwQJgiAIgiAIgiAIgiA6HBIkCIIgCIIgCIIgCILocEiQIAiCIAiCIAiCIAiiwyFBgiAIgiAIgiAIgiCIDocECYIgCIIgCIIgCIIgOhwSJAiCIAiCIAiCIAiC6HBIkCAIgiAIgiAIgiAIosMhQYIgCIIgCIIgCIIgiA7HluwFnIvwPA8A8Pl8SV4JQRAEQRAEQRDE2YnX6032EnQRbD3B9iNigwSJdsDv9wMAfvzxxySvhCAIgiAIgiAI4uzk+++/T/YSIuL3+5GamprsZZy1MDxJOgmH4zi0tbXBbreDYZhkL4cgCIIgCIIgCIJIIDzPw+/3IyMjAxYLZUKIFRIkCIIgCIIgCIIgCILocEjKIQiCIAiCIAiCIAiiwyFBgiAIgiAIgiAIgiCIDocECYIgCIIgCIIgCIIgOhwSJAiCIAiCIAiCIAiC6HBIkCAIgiAIgiAIgiAIosMhQYIgCIIgCIIgCIIgiA6HBAmCIAiCIAiCIAiCIDocEiQIgiAIgiAIgiAIguhwbNF22LRpE5YuXYqWlpb2WA9BEARBEARBEARBEGcpdrsdTzzxBG677baIbRme5/loBr/iiitQU1MT8+IIgiAIgiAIgiAIgji3WblyJSZPnmzYJmpB4s0338S2bdsQCATQ2NgInucRCARQUVER12IJgiAIgiAIgiAIgjg36NKlC7766ivDNlELEnqMGDECHo8nEUMRBEEQBEEQBEEQBHGWU1paih49eugeT0hSS47jSIwgCIIgCIIgCIIgCEKkrKzM8HhCBInFixcnYhiCIAiCIAiCIAiCIM4Rfv75Z8PjcQsSX3zxBd588814hyEIgiAIgiAIgiAI4hzC5XIZHo9LkNi/fz/uu+++eIYgCIIgCIIgCIIgCOIcJD093fB4zILEiRMnMGPGjFi7EwRBEARBEARBEARxDtOnTx/D4zEJEs3NzZg8eTJYlo2lO0EQBEEQBEEQBEEQ5zjjx483PB61IOHz+XDNNddQVQ2CIAiCIAiCIAiCIDTJyclBQUGBYZuoBYlf/vKXaGxsjHVNBEEQBEEQBEEQBEGc4zz55JMR29iiHfTYsWMxLYYgCIIgCIIgCIIgiHMbu92Oxx9/HFOmTInYluF5nu+ANREEQRAEQRAEQRAEQYjEVfaTIAiCIAiCIAiCIAgiFkiQIAiCIAiCIAiCIAiiwyFBgiAIgiAIgiAIgiCIDocECYIgCIIgCIIgCIIgOhwSJAiCIAiCIAiCIAiC6HBIkCAIgiAIgiAIgiAIosMhQYIgCIIgCIIgCIIgiA6HBAmCIAiCIFRcffXVuOuuu5K9DIIgCIIgzmFIkCAIgiAIIuH84x//wKZNm5K9DIIgCIIgzmBIkCAIgiAIIuGUlJTg3XffTfYyCIIgCII4gyFBgiAIgiAIgiAIgiCIDseW7AUQBEEQBJE8Tpw4gb/85S/497//DZ7nUVxcjMcff1yz7Ycffoj/9//+H/bv34+6ujpkZGRg1KhRePDBBzF48GCx3aBBgwAAx48fFz8DwGeffYaePXsCAL777jusWrUKO3fuRFtbGwoKCnDTTTfhnnvugc1GP08IgiAI4nyA4XmeT/YiCIIgCILoeJqbm3HTTTfh5MmTuO2229C/f3/s2LED3377LTweDy644AK8/vrrYvtZs2ahU6dOGDZsGLp27Yqqqiq89dZb8Pl8ePfdd9GnTx8AwPvvv49ly5YhJycH999/v9j/mmuuQXp6Or744gvMnz8fhYWFuPHGG5GdnY1vv/0W77//Pq655hq88MILHX0pCIIgCIJIAiRIEARBEMR5yrPPPovVq1dj6dKluOWWW8T9S5YsQUlJCYqLi2WChMvlQnp6umyMyspKTJ8+HTNnzsQf//hHcf/VV1+NgoICWX8A8Hq9uPrqq9GnTx+89tprMm+If/zjH1i2bBlKSkpw6aWXJvhsCYIgCII406AcEgRBEARxnrJ161bk5ubipptuku2/5557NNsLYgTP82htbcXp06eRk5ODvn37Ys+ePabmLC8vR11dHWbMmIHm5macPn1a/N8VV1whtiEIgiAI4tyHgjQJgiAI4jzl6NGjuPDCC2G1WmX7u3XrBqfTqWq/d+9erFy5El9//TVcLpfsmJAbIhKVlZUAoJunAgDq6upMjUUQBEEQxNkNCRIEQRAEQUSkuroad9xxBzIzM/Ff//Vf6NevH9LS0sAwDJYuXaoSKPQQIkUXLlyIoqIizTbdunVL2LoJgiAIgjhzIUGCIAiCIM5TevXqhSNHjoBlWZmXRG1tLZqbm2VtP/30U7hcLvz973/HmDFjZMcaGxuRkpJiak4h8WVaWhouu+yy+E6AIAiCIIizGsohQRAEQRDnKRMnTkRdXR3ee+892f61a9eq2gqChTIX9ltvvYVTp06p2mdkZKCxsVG1f9y4cejSpQvWrl2redzj8aC1tdX8SRAEQRAEcdZCVTYIgiAI4jylqakJN910E2pqanDbbbdhwIAB+PrrrzXLflZVVeHGG29EVlYW7rzzTjidTnzzzTcoKyuD0+kEy7L4/PPPxbGfeOIJvP3227j//vvRv39/WCwWXHXVVUhPT8eXX36JefPmIT09HbfccgsKCwvR3NyMQ4cO4dNPP8Xf/vY3qrJBEARBEOcBJEgQBEEQxHlMdXU1/vKXv+Df//43AKC4uBiPP/445syZoyrbuWPHDjz77LPYv38/rFYrLr74Yvzud7/DU089hePHj8sEifr6evzxj3/Ef/7zHzQ3N4PneXz22Wdi8ssff/wRa9aswX/+8x80NDTA6XSid+/eGD9+PO644w506tSpQ68DQRAEQRAdDwkSBEEQBEEQBEEQBEF0OJRDgiAIgiAIgiAIgiCIDocECYIgCIIgCIIgCIIgOhwSJAiCIAiCIAiCIAiC6HBIkCAIgiAIgiAIgiAIosMhQYIgCIIgCIIgCIIgiA6HBAmCIAiCIAiCIAiCIDocEiQIgiAIgiAIgiAIguhwSJAgCIIgCIIgCIIgCKLDIUGCIAiCIAiCIAiCIIgOhwQJgiAIgiAIgiAIgiA6nP8fDY3+5g6rR/4AAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<Figure size 1152x720 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "buehl_melted = buehl.melt('date', var_name='cols',  value_name='vals', value_vars=[\"diesel\", \"e5\", \"e10\"])\n",
+    "sns.lineplot(x=\"date\", y=\"vals\", hue='cols', data=buehl_melted)\n",
+    "fig = plt.gcf()\n",
+    "fig.set_size_inches( 16, 10)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 75,
+   "id": "91c57d5a",
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "KeyError",
+     "evalue": "\"['station_uuid'] not found in axis\"",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
+      "\u001b[0;32m/tmp/ipykernel_236719/3331971858.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mb2\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mbuehl\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdrop\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'station_uuid'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m \u001b[0;31m#b2 = b2.melt('date', var_name='cols', value_name='vals')\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0;31m#g = sns.factorplot(x=\"date\", y=\"vals\", hue='cols', data=b2)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m~/.cache/pypoetry/virtualenvs/besser-tanken-XZndgdH5-py3.9/lib/python3.9/site-packages/pandas/util/_decorators.py\u001b[0m in \u001b[0;36mwrapper\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m    309\u001b[0m                     \u001b[0mstacklevel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mstacklevel\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    310\u001b[0m                 )\n\u001b[0;32m--> 311\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    312\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    313\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mwrapper\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m~/.cache/pypoetry/virtualenvs/besser-tanken-XZndgdH5-py3.9/lib/python3.9/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36mdrop\u001b[0;34m(self, labels, axis, index, columns, level, inplace, errors)\u001b[0m\n\u001b[1;32m   4899\u001b[0m                 \u001b[0mweight\u001b[0m  \u001b[0;36m1.0\u001b[0m     \u001b[0;36m0.8\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   4900\u001b[0m         \"\"\"\n\u001b[0;32m-> 4901\u001b[0;31m         return super().drop(\n\u001b[0m\u001b[1;32m   4902\u001b[0m             \u001b[0mlabels\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mlabels\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   4903\u001b[0m             \u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0maxis\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m~/.cache/pypoetry/virtualenvs/besser-tanken-XZndgdH5-py3.9/lib/python3.9/site-packages/pandas/core/generic.py\u001b[0m in \u001b[0;36mdrop\u001b[0;34m(self, labels, axis, index, columns, level, inplace, errors)\u001b[0m\n\u001b[1;32m   4145\u001b[0m         \u001b[0;32mfor\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlabels\u001b[0m \u001b[0;32min\u001b[0m \u001b[0maxes\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   4146\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mlabels\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 4147\u001b[0;31m                 \u001b[0mobj\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_drop_axis\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlabels\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlevel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mlevel\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0merrors\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0merrors\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   4148\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   4149\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0minplace\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m~/.cache/pypoetry/virtualenvs/besser-tanken-XZndgdH5-py3.9/lib/python3.9/site-packages/pandas/core/generic.py\u001b[0m in \u001b[0;36m_drop_axis\u001b[0;34m(self, labels, axis, level, errors)\u001b[0m\n\u001b[1;32m   4180\u001b[0m                 \u001b[0mnew_axis\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdrop\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlabels\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlevel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mlevel\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0merrors\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0merrors\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   4181\u001b[0m             \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 4182\u001b[0;31m                 \u001b[0mnew_axis\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdrop\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlabels\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0merrors\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0merrors\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   4183\u001b[0m             \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreindex\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m**\u001b[0m\u001b[0;34m{\u001b[0m\u001b[0maxis_name\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mnew_axis\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   4184\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m~/.cache/pypoetry/virtualenvs/besser-tanken-XZndgdH5-py3.9/lib/python3.9/site-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36mdrop\u001b[0;34m(self, labels, errors)\u001b[0m\n\u001b[1;32m   6016\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mmask\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0many\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   6017\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0merrors\u001b[0m \u001b[0;34m!=\u001b[0m \u001b[0;34m\"ignore\"\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 6018\u001b[0;31m                 \u001b[0;32mraise\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34mf\"{labels[mask]} not found in axis\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   6019\u001b[0m             \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mindexer\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m~\u001b[0m\u001b[0mmask\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   6020\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdelete\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mindexer\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;31mKeyError\u001b[0m: \"['station_uuid'] not found in axis\""
+     ]
+    }
+   ],
+   "source": [
+    "b2 = buehl.drop('station_uuid')\n",
+    "#b2 = b2.melt('date', var_name='cols', value_name='vals')\n",
+    "#g = sns.factorplot(x=\"date\", y=\"vals\", hue='cols', data=b2)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/.ipynb_checkpoints/sprit_preis_analyse-checkpoint.ipynb b/.ipynb_checkpoints/sprit_preis_analyse-checkpoint.ipynb
new file mode 100644
index 0000000..9176964
--- /dev/null
+++ b/.ipynb_checkpoints/sprit_preis_analyse-checkpoint.ipynb
@@ -0,0 +1,2244 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "abc85460",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import os\n",
+    "import matplotlib.pyplot as plt\n",
+    "import seaborn as sns\n",
+    "import pandas as pd\n",
+    "import earthpy as et\n",
+    "import numpy as np\n",
+    "from besser_tanken.data_loader import load_prices_from, load_stations\n",
+    "from besser_tanken.data_tools import group_prices"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "1b7ebdd6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Handle date time conversions between pandas and matplotlib\n",
+    "from pandas.plotting import register_matplotlib_converters\n",
+    "register_matplotlib_converters()\n",
+    "\n",
+    "# Use white grid plot background from seaborn\n",
+    "sns.set(font_scale=1.5, style=\"whitegrid\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "4d1b7811",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2021-08-12 15:59:25.359 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-01-prices.csv\n",
+      "2021-08-12 15:59:25.361 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-03-prices.csv\n",
+      "2021-08-12 15:59:25.361 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-07-prices.csv\n",
+      "2021-08-12 15:59:25.362 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-05-prices.csv\n",
+      "2021-08-12 15:59:25.365 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-02-prices.csv\n",
+      "2021-08-12 15:59:26.047 | INFO     | besser_tanken.data_loader:load_prices:70 - got 280439 prices\n",
+      "2021-08-12 15:59:26.122 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-08-prices.csv\n",
+      "2021-08-12 15:59:26.622 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-04-prices.csv\n",
+      "2021-08-12 15:59:26.788 | INFO     | besser_tanken.data_loader:load_prices:70 - got 297538 prices\n",
+      "2021-08-12 15:59:26.813 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-06-prices.csv\n",
+      "2021-08-12 15:59:27.424 | INFO     | besser_tanken.data_loader:load_prices:70 - got 267833 prices\n",
+      "2021-08-12 15:59:28.101 | INFO     | besser_tanken.data_loader:load_prices:70 - got 287410 prices\n",
+      "2021-08-12 15:59:28.101 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-15-prices.csv\n",
+      "2021-08-12 15:59:28.760 | INFO     | besser_tanken.data_loader:load_prices:70 - got 285397 prices\n",
+      "2021-08-12 15:59:28.761 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-10-prices.csv\n",
+      "2021-08-12 15:59:28.762 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-14-prices.csv\n",
+      "2021-08-12 15:59:28.763 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-11-prices.csv\n",
+      "2021-08-12 15:59:28.774 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-16-prices.csv\n",
+      "2021-08-12 15:59:28.790 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-13-prices.csv\n",
+      "2021-08-12 15:59:28.816 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-09-prices.csv\n",
+      "2021-08-12 15:59:29.576 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-12-prices.csv\n",
+      "2021-08-12 15:59:29.588 | INFO     | besser_tanken.data_loader:load_prices:70 - got 267574 prices\n",
+      "2021-08-12 15:59:30.132 | INFO     | besser_tanken.data_loader:load_prices:70 - got 291143 prices\n",
+      "2021-08-12 15:59:31.038 | INFO     | besser_tanken.data_loader:load_prices:70 - got 290865 prices\n",
+      "2021-08-12 15:59:32.167 | INFO     | besser_tanken.data_loader:load_prices:70 - got 273987 prices\n",
+      "2021-08-12 15:59:33.567 | INFO     | besser_tanken.data_loader:load_prices:70 - got 283024 prices\n",
+      "2021-08-12 15:59:33.747 | INFO     | besser_tanken.data_loader:load_prices:70 - got 299993 prices\n",
+      "2021-08-12 15:59:33.748 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-17-prices.csv\n",
+      "2021-08-12 15:59:34.414 | INFO     | besser_tanken.data_loader:load_prices:70 - got 256623 prices\n",
+      "2021-08-12 15:59:34.420 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-18-prices.csv\n",
+      "2021-08-12 15:59:34.517 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-19-prices.csv\n",
+      "2021-08-12 15:59:35.206 | INFO     | besser_tanken.data_loader:load_prices:70 - got 297991 prices\n",
+      "2021-08-12 15:59:36.630 | INFO     | besser_tanken.data_loader:load_prices:70 - got 294324 prices\n",
+      "2021-08-12 15:59:37.164 | INFO     | besser_tanken.data_loader:load_prices:70 - got 295394 prices\n",
+      "2021-08-12 15:59:37.347 | INFO     | besser_tanken.data_loader:load_prices:70 - got 283593 prices\n",
+      "2021-08-12 15:59:37.377 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-20-prices.csv\n",
+      "2021-08-12 15:59:37.969 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-21-prices.csv\n",
+      "2021-08-12 15:59:38.869 | INFO     | besser_tanken.data_loader:load_prices:70 - got 302116 prices\n",
+      "2021-08-12 15:59:39.689 | INFO     | besser_tanken.data_loader:load_prices:70 - got 254847 prices\n",
+      "2021-08-12 15:59:40.517 | INFO     | besser_tanken.data_loader:load_prices:70 - got 259956 prices\n",
+      "2021-08-12 15:59:40.579 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-22-prices.csv\n",
+      "2021-08-12 15:59:40.867 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-23-prices.csv\n",
+      "2021-08-12 15:59:41.107 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-24-prices.csv\n",
+      "2021-08-12 15:59:41.868 | INFO     | besser_tanken.data_loader:load_prices:70 - got 304068 prices\n",
+      "2021-08-12 15:59:41.979 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-25-prices.csv\n",
+      "2021-08-12 15:59:42.793 | INFO     | besser_tanken.data_loader:load_prices:70 - got 268463 prices\n",
+      "2021-08-12 15:59:42.838 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-27-prices.csv\n",
+      "2021-08-12 15:59:42.892 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-26-prices.csv\n",
+      "2021-08-12 15:59:43.057 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-28-prices.csv\n",
+      "2021-08-12 15:59:43.951 | INFO     | besser_tanken.data_loader:load_prices:70 - got 274800 prices\n",
+      "2021-08-12 15:59:44.701 | INFO     | besser_tanken.data_loader:load_prices:70 - got 295088 prices\n",
+      "2021-08-12 15:59:44.748 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-29-prices.csv\n",
+      "2021-08-12 15:59:45.456 | INFO     | besser_tanken.data_loader:load_prices:70 - got 300758 prices\n",
+      "2021-08-12 15:59:45.498 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-01-prices.csv\n",
+      "2021-08-12 15:59:45.557 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-02-prices.csv\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2021-08-12 15:59:46.235 | INFO     | besser_tanken.data_loader:load_prices:70 - got 279674 prices\n",
+      "2021-08-12 15:59:46.285 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-30-prices.csv\n",
+      "2021-08-12 15:59:47.138 | INFO     | besser_tanken.data_loader:load_prices:70 - got 291122 prices\n",
+      "2021-08-12 15:59:47.366 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-04-prices.csv\n",
+      "2021-08-12 15:59:48.286 | INFO     | besser_tanken.data_loader:load_prices:70 - got 281698 prices\n",
+      "2021-08-12 15:59:48.297 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-03-prices.csv\n",
+      "2021-08-12 15:59:48.658 | INFO     | besser_tanken.data_loader:load_prices:70 - got 295627 prices\n",
+      "2021-08-12 15:59:49.508 | INFO     | besser_tanken.data_loader:load_prices:70 - got 272618 prices\n",
+      "2021-08-12 15:59:49.520 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-05-prices.csv\n",
+      "2021-08-12 15:59:50.403 | INFO     | besser_tanken.data_loader:load_prices:70 - got 304781 prices\n",
+      "2021-08-12 15:59:51.238 | INFO     | besser_tanken.data_loader:load_prices:70 - got 293853 prices\n",
+      "2021-08-12 15:59:51.258 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-06-prices.csv\n",
+      "2021-08-12 15:59:52.050 | INFO     | besser_tanken.data_loader:load_prices:70 - got 294534 prices\n",
+      "2021-08-12 15:59:52.932 | INFO     | besser_tanken.data_loader:load_prices:70 - got 296438 prices\n",
+      "2021-08-12 15:59:53.087 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-08-prices.csv\n",
+      "2021-08-12 15:59:53.143 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-09-prices.csv\n",
+      "2021-08-12 15:59:53.820 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-07-prices.csv\n",
+      "2021-08-12 15:59:53.862 | INFO     | besser_tanken.data_loader:load_prices:70 - got 295515 prices\n",
+      "2021-08-12 15:59:53.984 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-10-prices.csv\n",
+      "2021-08-12 15:59:54.731 | INFO     | besser_tanken.data_loader:load_prices:70 - got 266473 prices\n",
+      "2021-08-12 15:59:55.889 | INFO     | besser_tanken.data_loader:load_prices:70 - got 268331 prices\n",
+      "2021-08-12 15:59:56.049 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-12-prices.csv\n",
+      "2021-08-12 15:59:56.181 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-11-prices.csv\n",
+      "2021-08-12 15:59:57.046 | INFO     | besser_tanken.data_loader:load_prices:70 - got 295127 prices\n",
+      "2021-08-12 15:59:57.211 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-13-prices.csv\n",
+      "2021-08-12 15:59:57.217 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-14-prices.csv\n",
+      "2021-08-12 15:59:57.243 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-16-prices.csv\n",
+      "2021-08-12 15:59:57.963 | INFO     | besser_tanken.data_loader:load_prices:70 - got 291819 prices\n",
+      "2021-08-12 15:59:58.721 | INFO     | besser_tanken.data_loader:load_prices:70 - got 295646 prices\n",
+      "2021-08-12 15:59:58.737 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-17-prices.csv\n",
+      "2021-08-12 15:59:58.792 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-15-prices.csv\n",
+      "2021-08-12 16:00:00.193 | INFO     | besser_tanken.data_loader:load_prices:70 - got 291843 prices\n",
+      "2021-08-12 16:00:00.223 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-18-prices.csv\n",
+      "2021-08-12 16:00:00.961 | INFO     | besser_tanken.data_loader:load_prices:70 - got 283770 prices\n",
+      "2021-08-12 16:00:01.561 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-19-prices.csv\n",
+      "2021-08-12 16:00:01.787 | INFO     | besser_tanken.data_loader:load_prices:70 - got 295290 prices\n",
+      "2021-08-12 16:00:02.847 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-20-prices.csv\n",
+      "2021-08-12 16:00:03.212 | INFO     | besser_tanken.data_loader:load_prices:70 - got 267248 prices\n",
+      "2021-08-12 16:00:03.945 | INFO     | besser_tanken.data_loader:load_prices:70 - got 274498 prices\n",
+      "2021-08-12 16:00:04.682 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-22-prices.csv\n",
+      "2021-08-12 16:00:05.344 | INFO     | besser_tanken.data_loader:load_prices:70 - got 285905 prices\n",
+      "2021-08-12 16:00:05.424 | INFO     | besser_tanken.data_loader:load_prices:70 - got 296929 prices\n",
+      "2021-08-12 16:00:06.191 | INFO     | besser_tanken.data_loader:load_prices:70 - got 298455 prices\n",
+      "2021-08-12 16:00:06.897 | INFO     | besser_tanken.data_loader:load_prices:70 - got 295861 prices\n",
+      "2021-08-12 16:00:07.369 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-21-prices.csv\n",
+      "2021-08-12 16:00:07.550 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-23-prices.csv\n",
+      "2021-08-12 16:00:07.933 | INFO     | besser_tanken.data_loader:load_prices:70 - got 282465 prices\n",
+      "2021-08-12 16:00:08.676 | INFO     | besser_tanken.data_loader:load_prices:70 - got 272819 prices\n",
+      "2021-08-12 16:00:08.733 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-24-prices.csv\n",
+      "2021-08-12 16:00:08.795 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-25-prices.csv\n",
+      "2021-08-12 16:00:09.550 | INFO     | besser_tanken.data_loader:load_prices:70 - got 305490 prices\n",
+      "2021-08-12 16:00:09.592 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-26-prices.csv\n",
+      "2021-08-12 16:00:09.729 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-27-prices.csv\n",
+      "2021-08-12 16:00:11.246 | INFO     | besser_tanken.data_loader:load_prices:70 - got 297022 prices\n",
+      "2021-08-12 16:00:12.092 | INFO     | besser_tanken.data_loader:load_prices:70 - got 299097 prices\n",
+      "2021-08-12 16:00:12.149 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-28-prices.csv\n",
+      "2021-08-12 16:00:12.218 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-29-prices.csv\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2021-08-12 16:00:13.005 | INFO     | besser_tanken.data_loader:load_prices:70 - got 278182 prices\n",
+      "2021-08-12 16:00:13.006 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-30-prices.csv\n",
+      "2021-08-12 16:00:13.686 | INFO     | besser_tanken.data_loader:load_prices:70 - got 271525 prices\n",
+      "2021-08-12 16:00:13.753 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-01-prices.csv\n",
+      "2021-08-12 16:00:13.758 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-31-prices.csv\n",
+      "2021-08-12 16:00:14.446 | INFO     | besser_tanken.data_loader:load_prices:70 - got 270551 prices\n",
+      "2021-08-12 16:00:14.641 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-02-prices.csv\n",
+      "2021-08-12 16:00:15.269 | INFO     | besser_tanken.data_loader:load_prices:70 - got 265410 prices\n",
+      "2021-08-12 16:00:15.614 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-03-prices.csv\n",
+      "2021-08-12 16:00:15.905 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-04-prices.csv\n",
+      "2021-08-12 16:00:16.564 | INFO     | besser_tanken.data_loader:load_prices:70 - got 274174 prices\n",
+      "2021-08-12 16:00:16.577 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-05-prices.csv\n",
+      "2021-08-12 16:00:17.438 | INFO     | besser_tanken.data_loader:load_prices:70 - got 285401 prices\n",
+      "2021-08-12 16:00:18.119 | INFO     | besser_tanken.data_loader:load_prices:70 - got 279312 prices\n",
+      "2021-08-12 16:00:18.131 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-06-prices.csv\n",
+      "2021-08-12 16:00:18.791 | INFO     | besser_tanken.data_loader:load_prices:70 - got 244857 prices\n",
+      "2021-08-12 16:00:18.816 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-07-prices.csv\n",
+      "2021-08-12 16:00:19.489 | INFO     | besser_tanken.data_loader:load_prices:70 - got 257397 prices\n",
+      "2021-08-12 16:00:19.489 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-08-prices.csv\n",
+      "2021-08-12 16:00:20.285 | INFO     | besser_tanken.data_loader:load_prices:70 - got 260542 prices\n",
+      "2021-08-12 16:00:20.898 | INFO     | besser_tanken.data_loader:load_prices:70 - got 257142 prices\n",
+      "2021-08-12 16:00:21.633 | INFO     | besser_tanken.data_loader:load_prices:70 - got 279636 prices\n",
+      "2021-08-12 16:00:21.674 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-10-prices.csv\n",
+      "2021-08-12 16:00:21.679 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-09-prices.csv\n",
+      "2021-08-12 16:00:22.628 | INFO     | besser_tanken.data_loader:load_prices:70 - got 294651 prices\n",
+      "2021-08-12 16:00:22.913 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-12-prices.csv\n",
+      "2021-08-12 16:00:23.548 | INFO     | besser_tanken.data_loader:load_prices:70 - got 293143 prices\n",
+      "2021-08-12 16:00:23.655 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-11-prices.csv\n",
+      "2021-08-12 16:00:24.986 | INFO     | besser_tanken.data_loader:load_prices:70 - got 291029 prices\n",
+      "2021-08-12 16:00:25.466 | INFO     | besser_tanken.data_loader:load_prices:70 - got 291819 prices\n",
+      "2021-08-12 16:00:25.568 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-14-prices.csv\n",
+      "2021-08-12 16:00:25.626 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-15-prices.csv\n",
+      "2021-08-12 16:00:25.657 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-13-prices.csv\n",
+      "2021-08-12 16:00:25.703 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-16-prices.csv\n",
+      "2021-08-12 16:00:26.577 | INFO     | besser_tanken.data_loader:load_prices:70 - got 278188 prices\n",
+      "2021-08-12 16:00:27.109 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-17-prices.csv\n",
+      "2021-08-12 16:00:27.296 | INFO     | besser_tanken.data_loader:load_prices:70 - got 267935 prices\n",
+      "2021-08-12 16:00:28.030 | INFO     | besser_tanken.data_loader:load_prices:70 - got 295469 prices\n",
+      "2021-08-12 16:00:28.783 | INFO     | besser_tanken.data_loader:load_prices:70 - got 294834 prices\n",
+      "2021-08-12 16:00:28.820 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-19-prices.csv\n",
+      "2021-08-12 16:00:29.014 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-20-prices.csv\n",
+      "2021-08-12 16:00:29.045 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-18-prices.csv\n",
+      "2021-08-12 16:00:29.894 | INFO     | besser_tanken.data_loader:load_prices:70 - got 291697 prices\n",
+      "2021-08-12 16:00:30.849 | INFO     | besser_tanken.data_loader:load_prices:70 - got 296425 prices\n",
+      "2021-08-12 16:00:30.855 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-21-prices.csv\n",
+      "2021-08-12 16:00:31.560 | INFO     | besser_tanken.data_loader:load_prices:70 - got 293111 prices\n",
+      "2021-08-12 16:00:31.719 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-22-prices.csv\n",
+      "2021-08-12 16:00:32.260 | INFO     | besser_tanken.data_loader:load_prices:70 - got 277281 prices\n",
+      "2021-08-12 16:00:32.351 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-24-prices.csv\n",
+      "2021-08-12 16:00:32.563 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-23-prices.csv\n",
+      "2021-08-12 16:00:33.060 | INFO     | besser_tanken.data_loader:load_prices:70 - got 267150 prices\n",
+      "2021-08-12 16:00:34.515 | INFO     | besser_tanken.data_loader:load_prices:70 - got 292338 prices\n",
+      "2021-08-12 16:00:34.935 | INFO     | besser_tanken.data_loader:load_prices:70 - got 292261 prices\n",
+      "2021-08-12 16:00:35.012 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-25-prices.csv\n",
+      "2021-08-12 16:00:35.701 | INFO     | besser_tanken.data_loader:load_prices:70 - got 286600 prices\n",
+      "2021-08-12 16:00:35.706 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-26-prices.csv\n",
+      "2021-08-12 16:00:35.897 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-27-prices.csv\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2021-08-12 16:00:36.577 | INFO     | besser_tanken.data_loader:load_prices:70 - got 288069 prices\n",
+      "2021-08-12 16:00:36.706 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-28-prices.csv\n",
+      "2021-08-12 16:00:37.495 | INFO     | besser_tanken.data_loader:load_prices:70 - got 300483 prices\n",
+      "2021-08-12 16:00:38.357 | INFO     | besser_tanken.data_loader:load_prices:70 - got 258369 prices\n",
+      "2021-08-12 16:00:39.012 | INFO     | besser_tanken.data_loader:load_prices:70 - got 265136 prices\n",
+      "2021-08-12 16:00:39.121 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-30-prices.csv\n",
+      "2021-08-12 16:00:39.183 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-29-prices.csv\n",
+      "2021-08-12 16:00:40.137 | INFO     | besser_tanken.data_loader:load_prices:70 - got 295133 prices\n",
+      "2021-08-12 16:00:40.650 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-01-prices.csv\n",
+      "2021-08-12 16:00:40.888 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-31-prices.csv\n",
+      "2021-08-12 16:00:41.146 | INFO     | besser_tanken.data_loader:load_prices:70 - got 290998 prices\n",
+      "2021-08-12 16:00:41.966 | INFO     | besser_tanken.data_loader:load_prices:70 - got 295802 prices\n",
+      "2021-08-12 16:00:42.229 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-03-prices.csv\n",
+      "2021-08-12 16:00:42.817 | INFO     | besser_tanken.data_loader:load_prices:70 - got 292843 prices\n",
+      "2021-08-12 16:00:42.953 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-02-prices.csv\n",
+      "2021-08-12 16:00:43.013 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-04-prices.csv\n",
+      "2021-08-12 16:00:43.774 | INFO     | besser_tanken.data_loader:load_prices:70 - got 281149 prices\n",
+      "2021-08-12 16:00:43.783 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-05-prices.csv\n",
+      "2021-08-12 16:00:43.834 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-06-prices.csv\n",
+      "2021-08-12 16:00:44.648 | INFO     | besser_tanken.data_loader:load_prices:70 - got 301491 prices\n",
+      "2021-08-12 16:00:45.410 | INFO     | besser_tanken.data_loader:load_prices:70 - got 296274 prices\n",
+      "2021-08-12 16:00:46.092 | INFO     | besser_tanken.data_loader:load_prices:70 - got 269334 prices\n",
+      "2021-08-12 16:00:46.272 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-08-prices.csv\n",
+      "2021-08-12 16:00:46.278 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-09-prices.csv\n",
+      "2021-08-12 16:00:46.288 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-07-prices.csv\n",
+      "2021-08-12 16:00:46.962 | INFO     | besser_tanken.data_loader:load_prices:70 - got 293349 prices\n",
+      "2021-08-12 16:00:47.761 | INFO     | besser_tanken.data_loader:load_prices:70 - got 290786 prices\n",
+      "2021-08-12 16:00:48.849 | INFO     | besser_tanken.data_loader:load_prices:70 - got 285679 prices\n",
+      "2021-08-12 16:00:49.719 | INFO     | besser_tanken.data_loader:load_prices:70 - got 320138 prices\n",
+      "2021-08-12 16:00:49.785 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-10-prices.csv\n",
+      "2021-08-12 16:00:50.415 | INFO     | besser_tanken.data_loader:load_prices:70 - got 266559 prices\n",
+      "2021-08-12 16:00:50.523 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-11-prices.csv\n",
+      "2021-08-12 16:00:51.386 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-13-prices.csv\n",
+      "2021-08-12 16:00:51.513 | INFO     | besser_tanken.data_loader:load_prices:70 - got 312960 prices\n",
+      "2021-08-12 16:00:51.899 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-14-prices.csv\n",
+      "2021-08-12 16:00:52.703 | INFO     | besser_tanken.data_loader:load_prices:70 - got 285353 prices\n",
+      "2021-08-12 16:00:52.814 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-12-prices.csv\n",
+      "2021-08-12 16:00:53.017 | INFO     | besser_tanken.data_loader:load_prices:70 - got 291564 prices\n",
+      "2021-08-12 16:00:54.838 | INFO     | besser_tanken.data_loader:load_prices:70 - got 303852 prices\n",
+      "2021-08-12 16:00:55.326 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-16-prices.csv\n",
+      "2021-08-12 16:00:55.985 | INFO     | besser_tanken.data_loader:load_prices:70 - got 308485 prices\n",
+      "2021-08-12 16:00:56.360 | INFO     | besser_tanken.data_loader:load_prices:70 - got 299186 prices\n",
+      "2021-08-12 16:00:56.379 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-17-prices.csv\n",
+      "2021-08-12 16:00:56.455 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-15-prices.csv\n",
+      "2021-08-12 16:00:57.139 | INFO     | besser_tanken.data_loader:load_prices:70 - got 280736 prices\n",
+      "2021-08-12 16:00:57.198 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-20-prices.csv\n",
+      "2021-08-12 16:00:57.218 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-19-prices.csv\n",
+      "2021-08-12 16:00:57.239 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-18-prices.csv\n",
+      "2021-08-12 16:00:57.607 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-21-prices.csv\n",
+      "2021-08-12 16:00:58.189 | INFO     | besser_tanken.data_loader:load_prices:70 - got 322374 prices\n",
+      "2021-08-12 16:00:58.332 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-22-prices.csv\n",
+      "2021-08-12 16:00:59.171 | INFO     | besser_tanken.data_loader:load_prices:70 - got 299061 prices\n",
+      "2021-08-12 16:00:59.913 | INFO     | besser_tanken.data_loader:load_prices:70 - got 302117 prices\n",
+      "2021-08-12 16:00:59.944 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-23-prices.csv\n",
+      "2021-08-12 16:01:00.683 | INFO     | besser_tanken.data_loader:load_prices:70 - got 305624 prices\n",
+      "2021-08-12 16:01:00.746 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-24-prices.csv\n",
+      "2021-08-12 16:01:01.147 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-25-prices.csv\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2021-08-12 16:01:01.860 | INFO     | besser_tanken.data_loader:load_prices:70 - got 286031 prices\n",
+      "2021-08-12 16:01:01.977 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-26-prices.csv\n",
+      "2021-08-12 16:01:02.594 | INFO     | besser_tanken.data_loader:load_prices:70 - got 299713 prices\n",
+      "2021-08-12 16:01:03.295 | INFO     | besser_tanken.data_loader:load_prices:70 - got 297799 prices\n",
+      "2021-08-12 16:01:03.939 | INFO     | besser_tanken.data_loader:load_prices:70 - got 251823 prices\n",
+      "2021-08-12 16:01:03.940 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-27-prices.csv\n",
+      "2021-08-12 16:01:04.009 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-28-prices.csv\n",
+      "2021-08-12 16:01:04.727 | INFO     | besser_tanken.data_loader:load_prices:70 - got 302751 prices\n",
+      "2021-08-12 16:01:05.625 | INFO     | besser_tanken.data_loader:load_prices:70 - got 299860 prices\n",
+      "2021-08-12 16:01:05.804 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-01-prices.csv\n",
+      "2021-08-12 16:01:06.844 | INFO     | besser_tanken.data_loader:load_prices:70 - got 292382 prices\n",
+      "2021-08-12 16:01:07.358 | INFO     | besser_tanken.data_loader:load_prices:70 - got 298778 prices\n",
+      "2021-08-12 16:01:07.492 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-02-prices.csv\n",
+      "2021-08-12 16:01:08.279 | INFO     | besser_tanken.data_loader:load_prices:70 - got 301929 prices\n",
+      "2021-08-12 16:01:08.521 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-03-prices.csv\n",
+      "2021-08-12 16:01:08.805 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-04-prices.csv\n",
+      "2021-08-12 16:01:09.540 | INFO     | besser_tanken.data_loader:load_prices:70 - got 281441 prices\n",
+      "2021-08-12 16:01:10.181 | INFO     | besser_tanken.data_loader:load_prices:70 - got 267923 prices\n",
+      "2021-08-12 16:01:10.195 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-05-prices.csv\n",
+      "2021-08-12 16:01:10.366 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-06-prices.csv\n",
+      "2021-08-12 16:01:10.376 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-07-prices.csv\n",
+      "2021-08-12 16:01:11.153 | INFO     | besser_tanken.data_loader:load_prices:70 - got 294123 prices\n",
+      "2021-08-12 16:01:11.353 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-08-prices.csv\n",
+      "2021-08-12 16:01:12.572 | INFO     | besser_tanken.data_loader:load_prices:70 - got 298276 prices\n",
+      "2021-08-12 16:01:13.050 | INFO     | besser_tanken.data_loader:load_prices:70 - got 314743 prices\n",
+      "2021-08-12 16:01:13.110 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-09-prices.csv\n",
+      "2021-08-12 16:01:13.140 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-10-prices.csv\n",
+      "2021-08-12 16:01:13.968 | INFO     | besser_tanken.data_loader:load_prices:70 - got 300006 prices\n",
+      "2021-08-12 16:01:15.074 | INFO     | besser_tanken.data_loader:load_prices:70 - got 300856 prices\n",
+      "2021-08-12 16:01:15.774 | INFO     | besser_tanken.data_loader:load_prices:70 - got 287711 prices\n",
+      "2021-08-12 16:01:15.780 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-11-prices.csv\n",
+      "2021-08-12 16:01:16.448 | INFO     | besser_tanken.data_loader:load_prices:70 - got 270202 prices\n",
+      "2021-08-12 16:01:16.494 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-12-prices.csv\n",
+      "2021-08-12 16:01:17.353 | INFO     | besser_tanken.data_loader:load_prices:70 - got 297457 prices\n",
+      "2021-08-12 16:01:17.375 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-13-prices.csv\n",
+      "2021-08-12 16:01:17.470 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-14-prices.csv\n",
+      "2021-08-12 16:01:18.265 | INFO     | besser_tanken.data_loader:load_prices:70 - got 299724 prices\n",
+      "2021-08-12 16:01:18.991 | INFO     | besser_tanken.data_loader:load_prices:70 - got 303379 prices\n",
+      "2021-08-12 16:01:18.991 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-15-prices.csv\n",
+      "2021-08-12 16:01:20.049 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-16-prices.csv\n",
+      "2021-08-12 16:01:20.574 | INFO     | besser_tanken.data_loader:load_prices:70 - got 303081 prices\n",
+      "2021-08-12 16:01:20.669 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-17-prices.csv\n",
+      "2021-08-12 16:01:20.729 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-18-prices.csv\n",
+      "2021-08-12 16:01:20.966 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-20-prices.csv\n",
+      "2021-08-12 16:01:21.533 | INFO     | besser_tanken.data_loader:load_prices:70 - got 302240 prices\n",
+      "2021-08-12 16:01:22.218 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-21-prices.csv\n",
+      "2021-08-12 16:01:22.314 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-22-prices.csv\n",
+      "2021-08-12 16:01:22.334 | INFO     | besser_tanken.data_loader:load_prices:70 - got 274465 prices\n",
+      "2021-08-12 16:01:22.344 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-19-prices.csv\n",
+      "2021-08-12 16:01:23.186 | INFO     | besser_tanken.data_loader:load_prices:70 - got 270065 prices\n",
+      "2021-08-12 16:01:23.924 | INFO     | besser_tanken.data_loader:load_prices:70 - got 300843 prices\n",
+      "2021-08-12 16:01:23.971 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-23-prices.csv\n",
+      "2021-08-12 16:01:24.714 | INFO     | besser_tanken.data_loader:load_prices:70 - got 303397 prices\n",
+      "2021-08-12 16:01:25.411 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-24-prices.csv\n",
+      "2021-08-12 16:01:25.546 | INFO     | besser_tanken.data_loader:load_prices:70 - got 300025 prices\n",
+      "2021-08-12 16:01:26.403 | INFO     | besser_tanken.data_loader:load_prices:70 - got 309499 prices\n",
+      "2021-08-12 16:01:27.154 | INFO     | besser_tanken.data_loader:load_prices:70 - got 289836 prices\n",
+      "2021-08-12 16:01:27.276 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-25-prices.csv\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2021-08-12 16:01:27.949 | INFO     | besser_tanken.data_loader:load_prices:70 - got 267630 prices\n",
+      "2021-08-12 16:01:27.960 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-26-prices.csv\n",
+      "2021-08-12 16:01:28.697 | INFO     | besser_tanken.data_loader:load_prices:70 - got 307740 prices\n",
+      "2021-08-12 16:01:28.820 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-27-prices.csv\n",
+      "2021-08-12 16:01:29.552 | INFO     | besser_tanken.data_loader:load_prices:70 - got 305209 prices\n",
+      "2021-08-12 16:01:30.462 | INFO     | besser_tanken.data_loader:load_prices:70 - got 284813 prices\n",
+      "2021-08-12 16:01:31.234 | INFO     | besser_tanken.data_loader:load_prices:70 - got 278406 prices\n",
+      "2021-08-12 16:01:31.295 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-28-prices.csv\n",
+      "2021-08-12 16:01:32.480 | INFO     | besser_tanken.data_loader:load_prices:70 - got 281674 prices\n",
+      "2021-08-12 16:01:32.575 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-30-prices.csv\n",
+      "2021-08-12 16:01:32.903 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-31-prices.csv\n",
+      "2021-08-12 16:01:33.186 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-29-prices.csv\n",
+      "2021-08-12 16:01:33.590 | INFO     | besser_tanken.data_loader:load_prices:70 - got 279638 prices\n",
+      "2021-08-12 16:01:34.234 | INFO     | besser_tanken.data_loader:load_prices:70 - got 257995 prices\n",
+      "2021-08-12 16:01:34.584 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-02-prices.csv\n",
+      "2021-08-12 16:01:34.731 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-01-prices.csv\n",
+      "2021-08-12 16:01:34.742 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-03-prices.csv\n",
+      "2021-08-12 16:01:35.410 | INFO     | besser_tanken.data_loader:load_prices:70 - got 243278 prices\n",
+      "2021-08-12 16:01:35.565 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-05-prices.csv\n",
+      "2021-08-12 16:01:35.814 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-04-prices.csv\n",
+      "2021-08-12 16:01:36.607 | INFO     | besser_tanken.data_loader:load_prices:70 - got 312526 prices\n",
+      "2021-08-12 16:01:37.362 | INFO     | besser_tanken.data_loader:load_prices:70 - got 307644 prices\n",
+      "2021-08-12 16:01:37.392 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-06-prices.csv\n",
+      "2021-08-12 16:01:38.148 | INFO     | besser_tanken.data_loader:load_prices:70 - got 310474 prices\n",
+      "2021-08-12 16:01:38.159 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-07-prices.csv\n",
+      "2021-08-12 16:01:38.956 | INFO     | besser_tanken.data_loader:load_prices:70 - got 269837 prices\n",
+      "2021-08-12 16:01:38.996 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-08-prices.csv\n",
+      "2021-08-12 16:01:39.408 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-09-prices.csv\n",
+      "2021-08-12 16:01:39.828 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-10-prices.csv\n",
+      "2021-08-12 16:01:40.022 | INFO     | besser_tanken.data_loader:load_prices:70 - got 311357 prices\n",
+      "2021-08-12 16:01:40.667 | INFO     | besser_tanken.data_loader:load_prices:70 - got 268407 prices\n",
+      "2021-08-12 16:01:41.286 | INFO     | besser_tanken.data_loader:load_prices:70 - got 274141 prices\n",
+      "2021-08-12 16:01:41.925 | INFO     | besser_tanken.data_loader:load_prices:70 - got 256287 prices\n",
+      "2021-08-12 16:01:42.050 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-11-prices.csv\n",
+      "2021-08-12 16:01:42.783 | INFO     | besser_tanken.data_loader:load_prices:70 - got 317049 prices\n",
+      "2021-08-12 16:01:43.572 | INFO     | besser_tanken.data_loader:load_prices:70 - got 317581 prices\n",
+      "2021-08-12 16:01:44.745 | INFO     | besser_tanken.data_loader:load_prices:70 - got 338501 prices\n",
+      "2021-08-12 16:01:44.745 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-12-prices.csv\n",
+      "2021-08-12 16:01:46.554 | INFO     | besser_tanken.data_loader:load_prices:70 - got 279637 prices\n",
+      "2021-08-12 16:01:46.589 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-13-prices.csv\n",
+      "2021-08-12 16:01:46.616 | INFO     | besser_tanken.data_loader:load_prices:70 - got 293932 prices\n",
+      "2021-08-12 16:01:46.632 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-15-prices.csv\n",
+      "2021-08-12 16:01:47.764 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-14-prices.csv\n",
+      "2021-08-12 16:01:47.779 | INFO     | besser_tanken.data_loader:load_prices:70 - got 261957 prices\n",
+      "2021-08-12 16:01:47.834 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-17-prices.csv\n",
+      "2021-08-12 16:01:47.865 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-16-prices.csv\n",
+      "2021-08-12 16:01:48.113 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-18-prices.csv\n",
+      "2021-08-12 16:01:49.270 | INFO     | besser_tanken.data_loader:load_prices:70 - got 308348 prices\n",
+      "2021-08-12 16:01:50.158 | INFO     | besser_tanken.data_loader:load_prices:70 - got 315661 prices\n",
+      "2021-08-12 16:01:50.322 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-19-prices.csv\n",
+      "2021-08-12 16:01:50.384 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-21-prices.csv\n",
+      "2021-08-12 16:01:51.215 | INFO     | besser_tanken.data_loader:load_prices:70 - got 314120 prices\n",
+      "2021-08-12 16:01:51.215 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-22-prices.csv\n",
+      "2021-08-12 16:01:51.963 | INFO     | besser_tanken.data_loader:load_prices:70 - got 307809 prices\n",
+      "2021-08-12 16:01:52.035 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-23-prices.csv\n",
+      "2021-08-12 16:01:52.608 | INFO     | besser_tanken.data_loader:load_prices:70 - got 245486 prices\n",
+      "2021-08-12 16:01:52.617 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-24-prices.csv\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2021-08-12 16:01:52.633 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-20-prices.csv\n",
+      "2021-08-12 16:01:56.004 | INFO     | besser_tanken.data_loader:load_prices:70 - got 269150 prices\n",
+      "2021-08-12 16:01:56.568 | INFO     | besser_tanken.data_loader:load_prices:70 - got 231764 prices\n",
+      "2021-08-12 16:01:56.830 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-25-prices.csv\n",
+      "2021-08-12 16:01:57.360 | INFO     | besser_tanken.data_loader:load_prices:70 - got 311389 prices\n",
+      "2021-08-12 16:01:57.361 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-26-prices.csv\n",
+      "2021-08-12 16:01:58.168 | INFO     | besser_tanken.data_loader:load_prices:70 - got 317099 prices\n",
+      "2021-08-12 16:01:58.442 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-27-prices.csv\n",
+      "2021-08-12 16:01:59.319 | INFO     | besser_tanken.data_loader:load_prices:70 - got 311989 prices\n",
+      "2021-08-12 16:01:59.454 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-28-prices.csv\n",
+      "2021-08-12 16:02:00.155 | INFO     | besser_tanken.data_loader:load_prices:70 - got 277334 prices\n",
+      "2021-08-12 16:02:01.213 | INFO     | besser_tanken.data_loader:load_prices:70 - got 319437 prices\n",
+      "2021-08-12 16:02:01.301 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-29-prices.csv\n",
+      "2021-08-12 16:02:01.817 | INFO     | besser_tanken.data_loader:load_prices:70 - got 266464 prices\n",
+      "2021-08-12 16:02:02.069 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-30-prices.csv\n",
+      "2021-08-12 16:02:02.101 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-01-prices.csv\n",
+      "2021-08-12 16:02:02.762 | INFO     | besser_tanken.data_loader:load_prices:70 - got 247493 prices\n",
+      "2021-08-12 16:02:02.869 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-02-prices.csv\n",
+      "2021-08-12 16:02:03.681 | INFO     | besser_tanken.data_loader:load_prices:70 - got 323020 prices\n",
+      "2021-08-12 16:02:03.830 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-04-prices.csv\n",
+      "2021-08-12 16:02:05.207 | INFO     | besser_tanken.data_loader:load_prices:70 - got 316090 prices\n",
+      "2021-08-12 16:02:05.607 | INFO     | besser_tanken.data_loader:load_prices:70 - got 320951 prices\n",
+      "2021-08-12 16:02:05.676 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-03-prices.csv\n",
+      "2021-08-12 16:02:06.640 | INFO     | besser_tanken.data_loader:load_prices:70 - got 320842 prices\n",
+      "2021-08-12 16:02:06.856 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-07-prices.csv\n",
+      "2021-08-12 16:02:07.601 | INFO     | besser_tanken.data_loader:load_prices:70 - got 295191 prices\n",
+      "2021-08-12 16:02:07.622 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-05-prices.csv\n",
+      "2021-08-12 16:02:08.326 | INFO     | besser_tanken.data_loader:load_prices:70 - got 281559 prices\n",
+      "2021-08-12 16:02:08.427 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-06-prices.csv\n",
+      "2021-08-12 16:02:08.445 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-08-prices.csv\n",
+      "2021-08-12 16:02:08.472 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-09-prices.csv\n",
+      "2021-08-12 16:02:08.487 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-10-prices.csv\n",
+      "2021-08-12 16:02:09.224 | INFO     | besser_tanken.data_loader:load_prices:70 - got 268206 prices\n",
+      "2021-08-12 16:02:09.973 | INFO     | besser_tanken.data_loader:load_prices:70 - got 310422 prices\n",
+      "2021-08-12 16:02:11.427 | INFO     | besser_tanken.data_loader:load_prices:70 - got 316110 prices\n",
+      "2021-08-12 16:02:12.142 | INFO     | besser_tanken.data_loader:load_prices:70 - got 303829 prices\n",
+      "2021-08-12 16:02:12.162 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-11-prices.csv\n",
+      "2021-08-12 16:02:13.061 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-12-prices.csv\n",
+      "2021-08-12 16:02:13.148 | INFO     | besser_tanken.data_loader:load_prices:70 - got 314216 prices\n",
+      "2021-08-12 16:02:13.976 | INFO     | besser_tanken.data_loader:load_prices:70 - got 300563 prices\n",
+      "2021-08-12 16:02:14.720 | INFO     | besser_tanken.data_loader:load_prices:70 - got 311043 prices\n",
+      "2021-08-12 16:02:14.736 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-13-prices.csv\n",
+      "2021-08-12 16:02:14.793 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-14-prices.csv\n",
+      "2021-08-12 16:02:15.473 | INFO     | besser_tanken.data_loader:load_prices:70 - got 279529 prices\n",
+      "2021-08-12 16:02:15.482 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-15-prices.csv\n",
+      "2021-08-12 16:02:16.273 | INFO     | besser_tanken.data_loader:load_prices:70 - got 322838 prices\n",
+      "2021-08-12 16:02:16.372 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-16-prices.csv\n",
+      "2021-08-12 16:02:17.402 | INFO     | besser_tanken.data_loader:load_prices:70 - got 320776 prices\n",
+      "2021-08-12 16:02:18.337 | INFO     | besser_tanken.data_loader:load_prices:70 - got 323364 prices\n",
+      "2021-08-12 16:02:18.493 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-17-prices.csv\n",
+      "2021-08-12 16:02:19.176 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-18-prices.csv\n",
+      "2021-08-12 16:02:19.582 | INFO     | besser_tanken.data_loader:load_prices:70 - got 300333 prices\n",
+      "2021-08-12 16:02:20.369 | INFO     | besser_tanken.data_loader:load_prices:70 - got 318446 prices\n",
+      "2021-08-12 16:02:20.369 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-19-prices.csv\n",
+      "2021-08-12 16:02:20.426 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-20-prices.csv\n",
+      "2021-08-12 16:02:20.554 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-21-prices.csv\n",
+      "2021-08-12 16:02:21.375 | INFO     | besser_tanken.data_loader:load_prices:70 - got 295663 prices\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2021-08-12 16:02:22.613 | INFO     | besser_tanken.data_loader:load_prices:70 - got 281255 prices\n",
+      "2021-08-12 16:02:23.462 | INFO     | besser_tanken.data_loader:load_prices:70 - got 312171 prices\n",
+      "2021-08-12 16:02:23.508 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-23-prices.csv\n",
+      "2021-08-12 16:02:24.555 | INFO     | besser_tanken.data_loader:load_prices:70 - got 322048 prices\n",
+      "2021-08-12 16:02:24.695 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-22-prices.csv\n",
+      "2021-08-12 16:02:24.770 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-24-prices.csv\n",
+      "2021-08-12 16:02:25.171 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-26-prices.csv\n",
+      "2021-08-12 16:02:25.478 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-25-prices.csv\n",
+      "2021-08-12 16:02:25.540 | INFO     | besser_tanken.data_loader:load_prices:70 - got 321281 prices\n",
+      "2021-08-12 16:02:25.613 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-27-prices.csv\n",
+      "2021-08-12 16:02:25.623 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-28-prices.csv\n",
+      "2021-08-12 16:02:26.399 | INFO     | besser_tanken.data_loader:load_prices:70 - got 323562 prices\n",
+      "2021-08-12 16:02:27.132 | INFO     | besser_tanken.data_loader:load_prices:70 - got 311513 prices\n",
+      "2021-08-12 16:02:28.004 | INFO     | besser_tanken.data_loader:load_prices:70 - got 273299 prices\n",
+      "2021-08-12 16:02:28.717 | INFO     | besser_tanken.data_loader:load_prices:70 - got 295898 prices\n",
+      "2021-08-12 16:02:28.826 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-30-prices.csv\n",
+      "2021-08-12 16:02:28.827 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-29-prices.csv\n",
+      "2021-08-12 16:02:30.714 | INFO     | besser_tanken.data_loader:load_prices:70 - got 283712 prices\n",
+      "2021-08-12 16:02:30.851 | INFO     | besser_tanken.data_loader:load_prices:70 - got 309601 prices\n",
+      "2021-08-12 16:02:31.319 | INFO     | besser_tanken.data_loader:load_prices:70 - got 311840 prices\n",
+      "2021-08-12 16:02:32.259 | INFO     | besser_tanken.data_loader:load_prices:70 - got 306849 prices\n",
+      "2021-08-12 16:02:32.476 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-31-prices.csv\n",
+      "2021-08-12 16:02:32.489 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-01-prices.csv\n",
+      "2021-08-12 16:02:32.772 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-02-prices.csv\n",
+      "2021-08-12 16:02:33.184 | INFO     | besser_tanken.data_loader:load_prices:70 - got 311428 prices\n",
+      "2021-08-12 16:02:33.596 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-03-prices.csv\n",
+      "2021-08-12 16:02:34.249 | INFO     | besser_tanken.data_loader:load_prices:70 - got 272179 prices\n",
+      "2021-08-12 16:02:35.080 | INFO     | besser_tanken.data_loader:load_prices:70 - got 292252 prices\n",
+      "2021-08-12 16:02:35.115 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-05-prices.csv\n",
+      "2021-08-12 16:02:36.436 | INFO     | besser_tanken.data_loader:load_prices:70 - got 297145 prices\n",
+      "2021-08-12 16:02:36.452 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-04-prices.csv\n",
+      "2021-08-12 16:02:37.630 | INFO     | besser_tanken.data_loader:load_prices:70 - got 305627 prices\n",
+      "2021-08-12 16:02:37.651 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-07-prices.csv\n",
+      "2021-08-12 16:02:37.656 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-08-prices.csv\n",
+      "2021-08-12 16:02:37.672 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-06-prices.csv\n",
+      "2021-08-12 16:02:37.748 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-09-prices.csv\n",
+      "2021-08-12 16:02:37.752 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-10-prices.csv\n",
+      "2021-08-12 16:02:37.763 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-11-prices.csv\n",
+      "2021-08-12 16:02:38.814 | INFO     | besser_tanken.data_loader:load_prices:70 - got 310321 prices\n",
+      "2021-08-12 16:02:38.830 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-12-prices.csv\n",
+      "2021-08-12 16:02:39.224 | INFO     | besser_tanken.data_loader:load_prices:70 - got 296089 prices\n",
+      "2021-08-12 16:02:39.932 | INFO     | besser_tanken.data_loader:load_prices:70 - got 284582 prices\n",
+      "2021-08-12 16:02:40.922 | INFO     | besser_tanken.data_loader:load_prices:70 - got 315296 prices\n",
+      "2021-08-12 16:02:41.848 | INFO     | besser_tanken.data_loader:load_prices:70 - got 301502 prices\n",
+      "2021-08-12 16:02:42.817 | INFO     | besser_tanken.data_loader:load_prices:70 - got 326345 prices\n",
+      "2021-08-12 16:02:43.591 | INFO     | besser_tanken.data_loader:load_prices:70 - got 280524 prices\n",
+      "2021-08-12 16:02:44.374 | INFO     | besser_tanken.data_loader:load_prices:70 - got 329611 prices\n",
+      "2021-08-12 16:02:44.375 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-13-prices.csv\n",
+      "2021-08-12 16:02:44.376 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-14-prices.csv\n",
+      "2021-08-12 16:02:45.098 | INFO     | besser_tanken.data_loader:load_prices:70 - got 318813 prices\n",
+      "2021-08-12 16:02:45.099 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-17-prices.csv\n",
+      "2021-08-12 16:02:45.876 | INFO     | besser_tanken.data_loader:load_prices:70 - got 324502 prices\n",
+      "2021-08-12 16:02:46.087 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-16-prices.csv\n",
+      "2021-08-12 16:02:46.660 | INFO     | besser_tanken.data_loader:load_prices:70 - got 286250 prices\n",
+      "2021-08-12 16:02:46.670 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-15-prices.csv\n",
+      "2021-08-12 16:02:48.679 | INFO     | besser_tanken.data_loader:load_prices:70 - got 278483 prices\n",
+      "2021-08-12 16:02:48.695 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-18-prices.csv\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2021-08-12 16:02:49.514 | INFO     | besser_tanken.data_loader:load_prices:70 - got 326330 prices\n",
+      "2021-08-12 16:02:49.566 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-19-prices.csv\n",
+      "2021-08-12 16:02:50.373 | INFO     | besser_tanken.data_loader:load_prices:70 - got 318714 prices\n",
+      "2021-08-12 16:02:51.179 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-21-prices.csv\n",
+      "2021-08-12 16:02:51.190 | INFO     | besser_tanken.data_loader:load_prices:70 - got 320353 prices\n",
+      "2021-08-12 16:02:51.267 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-20-prices.csv\n",
+      "2021-08-12 16:02:52.035 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-22-prices.csv\n",
+      "2021-08-12 16:02:52.060 | INFO     | besser_tanken.data_loader:load_prices:70 - got 322612 prices\n",
+      "2021-08-12 16:02:52.243 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-23-prices.csv\n",
+      "2021-08-12 16:02:52.330 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-24-prices.csv\n",
+      "2021-08-12 16:02:53.065 | INFO     | besser_tanken.data_loader:load_prices:70 - got 318015 prices\n",
+      "2021-08-12 16:02:54.040 | INFO     | besser_tanken.data_loader:load_prices:70 - got 291300 prices\n",
+      "2021-08-12 16:02:55.256 | INFO     | besser_tanken.data_loader:load_prices:70 - got 320304 prices\n",
+      "2021-08-12 16:02:55.264 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-25-prices.csv\n",
+      "2021-08-12 16:02:56.026 | INFO     | besser_tanken.data_loader:load_prices:70 - got 278580 prices\n",
+      "2021-08-12 16:02:56.045 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-26-prices.csv\n",
+      "2021-08-12 16:02:56.955 | INFO     | besser_tanken.data_loader:load_prices:70 - got 311422 prices\n",
+      "2021-08-12 16:02:57.001 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-29-prices.csv\n",
+      "2021-08-12 16:02:57.714 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-27-prices.csv\n",
+      "2021-08-12 16:02:57.800 | INFO     | besser_tanken.data_loader:load_prices:70 - got 313682 prices\n",
+      "2021-08-12 16:02:57.809 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-28-prices.csv\n",
+      "2021-08-12 16:02:58.642 | INFO     | besser_tanken.data_loader:load_prices:70 - got 329516 prices\n",
+      "2021-08-12 16:02:58.928 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-30-prices.csv\n",
+      "2021-08-12 16:02:58.964 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-01-prices.csv\n",
+      "2021-08-12 16:02:59.512 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-02-prices.csv\n",
+      "2021-08-12 16:03:00.087 | INFO     | besser_tanken.data_loader:load_prices:70 - got 318168 prices\n",
+      "2021-08-12 16:03:00.902 | INFO     | besser_tanken.data_loader:load_prices:70 - got 303649 prices\n",
+      "2021-08-12 16:03:00.944 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-04-prices.csv\n",
+      "2021-08-12 16:03:01.793 | INFO     | besser_tanken.data_loader:load_prices:70 - got 311116 prices\n",
+      "2021-08-12 16:03:01.802 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-03-prices.csv\n",
+      "2021-08-12 16:03:02.433 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-05-prices.csv\n",
+      "2021-08-12 16:03:02.567 | INFO     | besser_tanken.data_loader:load_prices:70 - got 293388 prices\n",
+      "2021-08-12 16:03:03.668 | INFO     | besser_tanken.data_loader:load_prices:70 - got 320103 prices\n",
+      "2021-08-12 16:03:03.714 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-06-prices.csv\n",
+      "2021-08-12 16:03:04.482 | INFO     | besser_tanken.data_loader:load_prices:70 - got 319096 prices\n",
+      "2021-08-12 16:03:05.239 | INFO     | besser_tanken.data_loader:load_prices:70 - got 324591 prices\n",
+      "2021-08-12 16:03:06.041 | INFO     | besser_tanken.data_loader:load_prices:70 - got 322544 prices\n",
+      "2021-08-12 16:03:06.048 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-07-prices.csv\n",
+      "2021-08-12 16:03:06.838 | INFO     | besser_tanken.data_loader:load_prices:70 - got 291670 prices\n",
+      "2021-08-12 16:03:06.863 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-08-prices.csv\n",
+      "2021-08-12 16:03:06.990 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-09-prices.csv\n",
+      "2021-08-12 16:03:07.731 | INFO     | besser_tanken.data_loader:load_prices:70 - got 302137 prices\n",
+      "2021-08-12 16:03:08.715 | INFO     | besser_tanken.data_loader:load_prices:70 - got 323030 prices\n",
+      "2021-08-12 16:03:09.935 | INFO     | besser_tanken.data_loader:load_prices:70 - got 322967 prices\n",
+      "2021-08-12 16:03:09.972 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-10-prices.csv\n",
+      "2021-08-12 16:03:10.013 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-11-prices.csv\n",
+      "2021-08-12 16:03:10.023 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-12-prices.csv\n",
+      "2021-08-12 16:03:11.123 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-13-prices.csv\n",
+      "2021-08-12 16:03:11.309 | INFO     | besser_tanken.data_loader:load_prices:70 - got 330284 prices\n",
+      "2021-08-12 16:03:12.204 | INFO     | besser_tanken.data_loader:load_prices:70 - got 333165 prices\n",
+      "2021-08-12 16:03:12.958 | INFO     | besser_tanken.data_loader:load_prices:70 - got 329352 prices\n",
+      "2021-08-12 16:03:13.239 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-14-prices.csv\n",
+      "2021-08-12 16:03:13.301 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-15-prices.csv\n",
+      "2021-08-12 16:03:13.399 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-16-prices.csv\n",
+      "2021-08-12 16:03:13.805 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-18-prices.csv\n",
+      "2021-08-12 16:03:14.620 | INFO     | besser_tanken.data_loader:load_prices:70 - got 295236 prices\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2021-08-12 16:03:15.292 | INFO     | besser_tanken.data_loader:load_prices:70 - got 304704 prices\n",
+      "2021-08-12 16:03:15.441 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-17-prices.csv\n",
+      "2021-08-12 16:03:16.184 | INFO     | besser_tanken.data_loader:load_prices:70 - got 328208 prices\n",
+      "2021-08-12 16:03:17.028 | INFO     | besser_tanken.data_loader:load_prices:70 - got 326770 prices\n",
+      "2021-08-12 16:03:17.029 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-21-prices.csv\n",
+      "2021-08-12 16:03:17.060 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-20-prices.csv\n",
+      "2021-08-12 16:03:17.132 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-19-prices.csv\n",
+      "2021-08-12 16:03:18.161 | INFO     | besser_tanken.data_loader:load_prices:70 - got 311586 prices\n",
+      "2021-08-12 16:03:19.294 | INFO     | besser_tanken.data_loader:load_prices:70 - got 328226 prices\n",
+      "2021-08-12 16:03:19.329 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-22-prices.csv\n",
+      "2021-08-12 16:03:20.862 | INFO     | besser_tanken.data_loader:load_prices:70 - got 327267 prices\n",
+      "2021-08-12 16:03:21.356 | INFO     | besser_tanken.data_loader:load_prices:70 - got 305533 prices\n",
+      "2021-08-12 16:03:21.698 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-23-prices.csv\n",
+      "2021-08-12 16:03:21.743 | INFO     | besser_tanken.data_loader:load_prices:70 - got 293467 prices\n",
+      "2021-08-12 16:03:21.793 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-24-prices.csv\n",
+      "2021-08-12 16:03:21.964 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-26-prices.csv\n",
+      "2021-08-12 16:03:22.578 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-25-prices.csv\n",
+      "2021-08-12 16:03:22.794 | INFO     | besser_tanken.data_loader:load_prices:70 - got 337510 prices\n",
+      "2021-08-12 16:03:23.865 | INFO     | besser_tanken.data_loader:load_prices:70 - got 331415 prices\n",
+      "2021-08-12 16:03:24.739 | INFO     | besser_tanken.data_loader:load_prices:70 - got 326963 prices\n",
+      "2021-08-12 16:03:24.744 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-27-prices.csv\n",
+      "2021-08-12 16:03:25.695 | INFO     | besser_tanken.data_loader:load_prices:70 - got 331360 prices\n",
+      "2021-08-12 16:03:26.767 | INFO     | besser_tanken.data_loader:load_prices:70 - got 325880 prices\n",
+      "2021-08-12 16:03:27.540 | INFO     | besser_tanken.data_loader:load_prices:70 - got 311321 prices\n",
+      "2021-08-12 16:03:27.540 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-28-prices.csv\n",
+      "2021-08-12 16:03:27.581 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-29-prices.csv\n",
+      "2021-08-12 16:03:29.187 | INFO     | besser_tanken.data_loader:load_prices:70 - got 294263 prices\n",
+      "2021-08-12 16:03:29.353 | INFO     | besser_tanken.data_loader:load_prices:70 - got 328661 prices\n",
+      "2021-08-12 16:03:30.682 | INFO     | besser_tanken.data_loader:load_prices:70 - got 328049 prices\n",
+      "2021-08-12 16:03:30.782 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/08/2021-08-01-prices.csv\n",
+      "2021-08-12 16:03:30.786 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-30-prices.csv\n",
+      "2021-08-12 16:03:30.808 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-31-prices.csv\n",
+      "2021-08-12 16:03:30.915 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/08/2021-08-02-prices.csv\n",
+      "2021-08-12 16:03:30.992 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/08/2021-08-03-prices.csv\n",
+      "2021-08-12 16:03:32.033 | INFO     | besser_tanken.data_loader:load_prices:70 - got 326698 prices\n",
+      "2021-08-12 16:03:32.796 | INFO     | besser_tanken.data_loader:load_prices:70 - got 328307 prices\n",
+      "2021-08-12 16:03:33.338 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/08/2021-08-06-prices.csv\n",
+      "2021-08-12 16:03:33.369 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/08/2021-08-04-prices.csv\n",
+      "2021-08-12 16:03:33.398 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/08/2021-08-05-prices.csv\n",
+      "2021-08-12 16:03:34.259 | INFO     | besser_tanken.data_loader:load_prices:70 - got 294359 prices\n",
+      "2021-08-12 16:03:34.446 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/08/2021-08-08-prices.csv\n",
+      "2021-08-12 16:03:34.471 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/08/2021-08-07-prices.csv\n",
+      "2021-08-12 16:03:35.586 | INFO     | besser_tanken.data_loader:load_prices:70 - got 330570 prices\n",
+      "2021-08-12 16:03:36.009 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/08/2021-08-09-prices.csv\n",
+      "2021-08-12 16:03:36.013 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/08/2021-08-10-prices.csv\n",
+      "2021-08-12 16:03:36.015 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/08/2021-08-11-prices.csv\n",
+      "2021-08-12 16:03:36.396 | INFO     | besser_tanken.data_loader:load_prices:70 - got 304848 prices\n",
+      "2021-08-12 16:03:37.584 | INFO     | besser_tanken.data_loader:load_prices:70 - got 322580 prices\n",
+      "2021-08-12 16:03:38.107 | INFO     | besser_tanken.data_loader:load_prices:70 - got 324433 prices\n",
+      "2021-08-12 16:03:38.967 | INFO     | besser_tanken.data_loader:load_prices:70 - got 320613 prices\n",
+      "2021-08-12 16:03:39.874 | INFO     | besser_tanken.data_loader:load_prices:70 - got 331188 prices\n",
+      "2021-08-12 16:03:40.655 | INFO     | besser_tanken.data_loader:load_prices:70 - got 327766 prices\n",
+      "2021-08-12 16:03:41.461 | INFO     | besser_tanken.data_loader:load_prices:70 - got 293810 prices\n",
+      "2021-08-12 16:03:42.209 | INFO     | besser_tanken.data_loader:load_prices:70 - got 309683 prices\n",
+      "2021-08-12 16:03:43.090 | INFO     | besser_tanken.data_loader:load_prices:70 - got 331244 prices\n",
+      "2021-08-12 16:03:43.882 | INFO     | besser_tanken.data_loader:load_prices:70 - got 314980 prices\n",
+      "2021-08-12 16:03:44.785 | INFO     | besser_tanken.data_loader:load_prices:70 - got 327550 prices\n"
+     ]
+    }
+   ],
+   "source": [
+    "#data = load_prices_from(2020,11,1)\n",
+    "df = load_prices_from(2020,11,1)\n",
+    "df = pd.DataFrame(df)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "f7431b46",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df.e5 = df['e5'].astype(float)\n",
+    "df.e10 = df['e10'].astype(float)\n",
+    "df.diesel = df['diesel'].astype(float)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "be19ae6b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df[\"date_time\"] = pd.to_datetime(df.date, infer_datetime_format=True, utc=True)\n",
+    "df[\"hour\"] = df.date_time.dt.hour\n",
+    "df[\"month\"] = df.date_time.dt.month\n",
+    "df[\"quarter\"] = df.date_time.dt.quarter\n",
+    "df[\"year\"] = df.date_time.dt.year\n",
+    "df[\"day\"] = df.date_time.dt.day\n",
+    "df[\"week\"] = df.date_time.dt.isocalendar().week\n",
+    "df[\"weekday\"] = df.date_time.dt.weekday\n",
+    "df[\"season\"] = np.where(df[\"month\"].isin([3,4,5]),\"spring\",\n",
+    "   np.where(df[\"month\"].isin([6,7,8]),\"summer\",\n",
+    "   np.where(df[\"month\"].isin([9,10,11]),\"fall\",\n",
+    "   np.where(df[\"month\"].isin([12,1,2]),\"winter\",\"None\"))))\n",
+    "#buehl[\"weekday_name\"] = np.where(df[\"weekday\"].isin([0]),\"mon\",\n",
+    "#   np.where(df[\"weekday\"].isin([1]),\"tue\",\n",
+    "#   np.where(df[\"weekday\"].isin([2]),\"wed\",\n",
+    "#   np.where(df[\"weekday\"].isin([3]),\"thu\",\n",
+    "#   np.where(df[\"weekday\"].isin([4]),\"fri\",            \n",
+    "#   np.where(df[\"weekday\"].isin([5]),\"sat\",            \n",
+    "#   np.where(df[\"weekday\"].isin([6]),\"sun\",\"None\")))))))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "ee8153a0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#df[\"date_time\"] = pd.to_datetime(df.date)\n",
+    "#df[\"month\"] = df[\"date_time\"].dt.month"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "d4419141",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>date</th>\n",
+       "      <th>station_uuid</th>\n",
+       "      <th>diesel</th>\n",
+       "      <th>e5</th>\n",
+       "      <th>e10</th>\n",
+       "      <th>dieselchange</th>\n",
+       "      <th>e5change</th>\n",
+       "      <th>e10change</th>\n",
+       "      <th>date_time</th>\n",
+       "      <th>hour</th>\n",
+       "      <th>month</th>\n",
+       "      <th>quarter</th>\n",
+       "      <th>year</th>\n",
+       "      <th>day</th>\n",
+       "      <th>week</th>\n",
+       "      <th>weekday</th>\n",
+       "      <th>season</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>2020-11-07 00:00:08+0100</td>\n",
+       "      <td>a1e15688-663a-42da-86b3-0501597bcab7</td>\n",
+       "      <td>0.968</td>\n",
+       "      <td>1.168</td>\n",
+       "      <td>1.118</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2020-11-06 23:00:08+00:00</td>\n",
+       "      <td>23</td>\n",
+       "      <td>11</td>\n",
+       "      <td>4</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>6</td>\n",
+       "      <td>45</td>\n",
+       "      <td>4</td>\n",
+       "      <td>fall</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2020-11-07 00:01:06+0100</td>\n",
+       "      <td>9bb515a4-c551-41b8-a8a1-e120f29474fd</td>\n",
+       "      <td>0.989</td>\n",
+       "      <td>1.139</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2020-11-06 23:01:06+00:00</td>\n",
+       "      <td>23</td>\n",
+       "      <td>11</td>\n",
+       "      <td>4</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>6</td>\n",
+       "      <td>45</td>\n",
+       "      <td>4</td>\n",
+       "      <td>fall</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2020-11-07 00:01:06+0100</td>\n",
+       "      <td>0d58c4ba-3267-404a-89d6-6ba15a8fc422</td>\n",
+       "      <td>1.069</td>\n",
+       "      <td>1.239</td>\n",
+       "      <td>1.189</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2020-11-06 23:01:06+00:00</td>\n",
+       "      <td>23</td>\n",
+       "      <td>11</td>\n",
+       "      <td>4</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>6</td>\n",
+       "      <td>45</td>\n",
+       "      <td>4</td>\n",
+       "      <td>fall</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2020-11-07 00:01:06+0100</td>\n",
+       "      <td>3e385667-56a9-46b4-96de-2adcfd7b5655</td>\n",
+       "      <td>1.029</td>\n",
+       "      <td>1.219</td>\n",
+       "      <td>1.169</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2020-11-06 23:01:06+00:00</td>\n",
+       "      <td>23</td>\n",
+       "      <td>11</td>\n",
+       "      <td>4</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>6</td>\n",
+       "      <td>45</td>\n",
+       "      <td>4</td>\n",
+       "      <td>fall</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2020-11-07 00:01:06+0100</td>\n",
+       "      <td>0055910e-f1e4-4b42-8489-ba2880ef434c</td>\n",
+       "      <td>0.999</td>\n",
+       "      <td>1.149</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2020-11-06 23:01:06+00:00</td>\n",
+       "      <td>23</td>\n",
+       "      <td>11</td>\n",
+       "      <td>4</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>6</td>\n",
+       "      <td>45</td>\n",
+       "      <td>4</td>\n",
+       "      <td>fall</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                       date                          station_uuid  diesel  \\\n",
+       "0  2020-11-07 00:00:08+0100  a1e15688-663a-42da-86b3-0501597bcab7   0.968   \n",
+       "1  2020-11-07 00:01:06+0100  9bb515a4-c551-41b8-a8a1-e120f29474fd   0.989   \n",
+       "2  2020-11-07 00:01:06+0100  0d58c4ba-3267-404a-89d6-6ba15a8fc422   1.069   \n",
+       "3  2020-11-07 00:01:06+0100  3e385667-56a9-46b4-96de-2adcfd7b5655   1.029   \n",
+       "4  2020-11-07 00:01:06+0100  0055910e-f1e4-4b42-8489-ba2880ef434c   0.999   \n",
+       "\n",
+       "      e5    e10 dieselchange e5change e10change                 date_time  \\\n",
+       "0  1.168  1.118            0        1         1 2020-11-06 23:00:08+00:00   \n",
+       "1  1.139  0.000            1        1         0 2020-11-06 23:01:06+00:00   \n",
+       "2  1.239  1.189            1        1         1 2020-11-06 23:01:06+00:00   \n",
+       "3  1.219  1.169            1        1         1 2020-11-06 23:01:06+00:00   \n",
+       "4  1.149  0.000            1        1         0 2020-11-06 23:01:06+00:00   \n",
+       "\n",
+       "   hour  month  quarter  year  day  week  weekday season  \n",
+       "0    23     11        4  2020    6    45        4   fall  \n",
+       "1    23     11        4  2020    6    45        4   fall  \n",
+       "2    23     11        4  2020    6    45        4   fall  \n",
+       "3    23     11        4  2020    6    45        4   fall  \n",
+       "4    23     11        4  2020    6    45        4   fall  "
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "7babd7db",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "RangeIndex: 84331855 entries, 0 to 84331854\n",
+      "Data columns (total 17 columns):\n",
+      " #   Column        Dtype              \n",
+      "---  ------        -----              \n",
+      " 0   date          object             \n",
+      " 1   station_uuid  object             \n",
+      " 2   diesel        float64            \n",
+      " 3   e5            float64            \n",
+      " 4   e10           float64            \n",
+      " 5   dieselchange  object             \n",
+      " 6   e5change      object             \n",
+      " 7   e10change     object             \n",
+      " 8   date_time     datetime64[ns, UTC]\n",
+      " 9   hour          int64              \n",
+      " 10  month         int64              \n",
+      " 11  quarter       int64              \n",
+      " 12  year          int64              \n",
+      " 13  day           int64              \n",
+      " 14  week          UInt32             \n",
+      " 15  weekday       int64              \n",
+      " 16  season        object             \n",
+      "dtypes: UInt32(1), datetime64[ns, UTC](1), float64(3), int64(6), object(6)\n",
+      "memory usage: 10.4+ GB\n"
+     ]
+    }
+   ],
+   "source": [
+    "df.info()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "4af40046",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "grouped_by_station = df.groupby('station_uuid').mean()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "2bdd5266",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot:xlabel='station_uuid'>"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "grouped_by_station['diesel'].plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "96f887f0",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot:xlabel='station_uuid'>"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "grouped_by_station['diesel'].nlargest(20).plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "a1eba9ac",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot:xlabel='station_uuid'>"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "grouped_by_station['diesel'].nsmallest(20).plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "4d9f5349",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2021-08-12 19:43:44.752 | INFO     | besser_tanken.data_loader:load_stations:126 - got 16361 stations\n"
+     ]
+    }
+   ],
+   "source": [
+    "stations = load_stations()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "96a6ec58",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "stations_df = pd.DataFrame(stations)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "9fb4bc73",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "merged = pd.merge(df, stations_df, how=\"outer\", left_on=[\"station_uuid\"],right_on=[\"uuid\"])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "1416d11a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "merged.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "cacc0a33",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "plz_grouped = merged.groupby('post_code').mean()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 196,
+   "id": "9ce5a1c0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#prices = group_prices(data)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 123,
+   "id": "4221f111",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "buehl_stations = filter(lambda s: s['post_code'] in ['77815'], stations)\n",
+    "buehl_station = list(buehl_stations)[0]\n",
+    "#buehl = prices[buehl_station['uuid']]\n",
+    "buehl = df[df[\"station_uuid\"] == buehl_station['uuid']]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 127,
+   "id": "5c01f16f",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'uuid': 'e95c2523-8d12-4132-98b3-0aa6a2ce454d', 'name': 'ZG Raiffeisen Tankstelle Bühl', 'brand': 'ZG Raiffeisen Energie', 'street': 'Hurststraße', 'house_number': '24', 'post_code': '77815', 'city': 'Bühl Vimbuch', 'latitude': '48.7133', 'longitude': '8.12091', 'first_active': '2014-03-18 16:45:31+01', 'openingtimes_json': '{}'}\n"
+     ]
+    }
+   ],
+   "source": [
+    "#buehl_station = next(buehl_stations)\n",
+    "print(buehl_station)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 128,
+   "id": "c5371e50",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "buehl= pd.DataFrame(buehl)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 129,
+   "id": "4e5d9d13",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "9581        2020-11-01 06:06:05+0100\n",
+       "22918       2020-11-01 07:31:06+0100\n",
+       "23793       2020-11-01 07:36:05+0100\n",
+       "26755       2020-11-01 07:56:07+0100\n",
+       "33824       2020-11-01 08:31:06+0100\n",
+       "                      ...           \n",
+       "49842510    2021-03-31 19:01:05+0200\n",
+       "49853848    2021-03-31 19:26:08+0200\n",
+       "49862771    2021-03-31 20:01:05+0200\n",
+       "49867661    2021-03-31 20:11:05+0200\n",
+       "49892392    2021-03-31 23:51:05+0200\n",
+       "Name: date, Length: 3533, dtype: object"
+      ]
+     },
+     "execution_count": 129,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "buehl[\"date\"] "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 139,
+   "id": "adbd26b4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "buehl[\"date_time\"] = pd.to_datetime(buehl.date, infer_datetime_format=True, utc=True)\n",
+    "#buehl[\"date_time\"] = pd.to_datetime(buehl.date)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "6950f7b6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#buehl[\"date_time\"] = pd.to_datetime(buehl.date, format='%Y-%m-%d %H:%M:%S%z')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 140,
+   "id": "e0b8a829",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "9581       2020-11-01 05:06:05+00:00\n",
+       "22918      2020-11-01 06:31:06+00:00\n",
+       "23793      2020-11-01 06:36:05+00:00\n",
+       "26755      2020-11-01 06:56:07+00:00\n",
+       "33824      2020-11-01 07:31:06+00:00\n",
+       "                      ...           \n",
+       "49842510   2021-03-31 17:01:05+00:00\n",
+       "49853848   2021-03-31 17:26:08+00:00\n",
+       "49862771   2021-03-31 18:01:05+00:00\n",
+       "49867661   2021-03-31 18:11:05+00:00\n",
+       "49892392   2021-03-31 21:51:05+00:00\n",
+       "Name: date, Length: 3533, dtype: datetime64[ns, UTC]"
+      ]
+     },
+     "execution_count": 140,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "buehl.date_time"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "id": "14208efd",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "9581        2020-11-01 06:06:05+0100\n",
+       "22918       2020-11-01 07:31:06+0100\n",
+       "23793       2020-11-01 07:36:05+0100\n",
+       "26755       2020-11-01 07:56:07+0100\n",
+       "33824       2020-11-01 08:31:06+0100\n",
+       "                      ...           \n",
+       "49842510    2021-03-31 19:01:05+0200\n",
+       "49853848    2021-03-31 19:26:08+0200\n",
+       "49862771    2021-03-31 20:01:05+0200\n",
+       "49867661    2021-03-31 20:11:05+0200\n",
+       "49892392    2021-03-31 23:51:05+0200\n",
+       "Name: date, Length: 3533, dtype: object"
+      ]
+     },
+     "execution_count": 33,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "buehl.date"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 133,
+   "id": "68462004",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "d = pd.to_datetime(buehl.iloc[0].date)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 134,
+   "id": "82cc374c",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Timestamp('2020-11-01 06:06:05+0100', tz='pytz.FixedOffset(60)')"
+      ]
+     },
+     "execution_count": 134,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "d"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 135,
+   "id": "734328c6",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "11"
+      ]
+     },
+     "execution_count": 135,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "d.month"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 141,
+   "id": "7ecdc34e",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "DatetimeIndex(['2020-11-01 05:06:05+00:00', '2020-11-01 06:31:06+00:00',\n",
+       "               '2020-11-01 06:36:05+00:00', '2020-11-01 06:56:07+00:00',\n",
+       "               '2020-11-01 07:31:06+00:00', '2020-11-01 08:01:06+00:00',\n",
+       "               '2020-11-01 12:26:08+00:00', '2020-11-01 13:21:12+00:00',\n",
+       "               '2020-11-01 14:31:06+00:00', '2020-11-01 14:46:09+00:00',\n",
+       "               ...\n",
+       "               '2021-03-31 14:51:06+00:00', '2021-03-31 15:56:06+00:00',\n",
+       "               '2021-03-31 16:01:07+00:00', '2021-03-31 16:11:06+00:00',\n",
+       "               '2021-03-31 16:41:07+00:00', '2021-03-31 17:01:05+00:00',\n",
+       "               '2021-03-31 17:26:08+00:00', '2021-03-31 18:01:05+00:00',\n",
+       "               '2021-03-31 18:11:05+00:00', '2021-03-31 21:51:05+00:00'],\n",
+       "              dtype='datetime64[ns, UTC]', name='date_time', length=3533, freq=None)"
+      ]
+     },
+     "execution_count": 141,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "pd.DatetimeIndex(buehl['date_time'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 164,
+   "id": "e56eda9b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "buehl[\"hour\"] = buehl.date_time.dt.hour\n",
+    "buehl[\"month\"] = buehl.date_time.dt.month\n",
+    "buehl[\"quarter\"] = buehl.date_time.dt.quarter\n",
+    "buehl[\"year\"] = buehl.date_time.dt.year\n",
+    "buehl[\"day\"] = buehl.date_time.dt.day\n",
+    "buehl[\"week\"] = buehl.date_time.dt.isocalendar().week\n",
+    "buehl[\"weekday\"] = buehl.date_time.dt.weekday\n",
+    "buehl[\"season\"] = np.where(buehl[\"month\"].isin([3,4,5]),\"spring\",\n",
+    "   np.where(buehl[\"month\"].isin([6,7,8]),\"summer\",\n",
+    "   np.where(buehl[\"month\"].isin([9,10,11]),\"fall\",\n",
+    "   np.where(buehl[\"month\"].isin([12,1,2]),\"winter\",\"None\"))))\n",
+    "buehl[\"weekday_name\"] = np.where(buehl[\"weekday\"].isin([0]),\"mon\",\n",
+    "   np.where(buehl[\"weekday\"].isin([1]),\"tue\",\n",
+    "   np.where(buehl[\"weekday\"].isin([2]),\"wed\",\n",
+    "   np.where(buehl[\"weekday\"].isin([3]),\"thu\",\n",
+    "   np.where(buehl[\"weekday\"].isin([4]),\"fri\",            \n",
+    "   np.where(buehl[\"weekday\"].isin([5]),\"sat\",            \n",
+    "   np.where(buehl[\"weekday\"].isin([6]),\"sun\",\"None\")))))))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 143,
+   "id": "ff6450d2",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Index(['date', 'station_uuid', 'diesel', 'e5', 'e10', 'dieselchange',\n",
+       "       'e5change', 'e10change', 'date_time', 'month', 'quarter', 'year', 'day',\n",
+       "       'week', 'weekday', 'season', 'weekday_name'],\n",
+       "      dtype='object')"
+      ]
+     },
+     "execution_count": 143,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "buehl.columns"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 144,
+   "id": "65deae4d",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "Int64Index: 3533 entries, 9581 to 49892392\n",
+      "Data columns (total 17 columns):\n",
+      " #   Column        Non-Null Count  Dtype              \n",
+      "---  ------        --------------  -----              \n",
+      " 0   date          3533 non-null   object             \n",
+      " 1   station_uuid  3533 non-null   object             \n",
+      " 2   diesel        3533 non-null   object             \n",
+      " 3   e5            3533 non-null   object             \n",
+      " 4   e10           3533 non-null   object             \n",
+      " 5   dieselchange  3533 non-null   object             \n",
+      " 6   e5change      3533 non-null   object             \n",
+      " 7   e10change     3533 non-null   object             \n",
+      " 8   date_time     3533 non-null   datetime64[ns, UTC]\n",
+      " 9   month         3533 non-null   int64              \n",
+      " 10  quarter       3533 non-null   int64              \n",
+      " 11  year          3533 non-null   int64              \n",
+      " 12  day           3533 non-null   int64              \n",
+      " 13  week          3533 non-null   UInt32             \n",
+      " 14  weekday       3533 non-null   int64              \n",
+      " 15  season        3533 non-null   object             \n",
+      " 16  weekday_name  3533 non-null   object             \n",
+      "dtypes: UInt32(1), datetime64[ns, UTC](1), int64(5), object(10)\n",
+      "memory usage: 486.5+ KB\n"
+     ]
+    }
+   ],
+   "source": [
+    "buehl.info()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 145,
+   "id": "26cae1bf",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>date</th>\n",
+       "      <th>station_uuid</th>\n",
+       "      <th>diesel</th>\n",
+       "      <th>e5</th>\n",
+       "      <th>e10</th>\n",
+       "      <th>dieselchange</th>\n",
+       "      <th>e5change</th>\n",
+       "      <th>e10change</th>\n",
+       "      <th>date_time</th>\n",
+       "      <th>month</th>\n",
+       "      <th>quarter</th>\n",
+       "      <th>year</th>\n",
+       "      <th>day</th>\n",
+       "      <th>week</th>\n",
+       "      <th>weekday</th>\n",
+       "      <th>season</th>\n",
+       "      <th>weekday_name</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>9581</th>\n",
+       "      <td>2020-11-01 06:06:05+0100</td>\n",
+       "      <td>e95c2523-8d12-4132-98b3-0aa6a2ce454d</td>\n",
+       "      <td>1.079</td>\n",
+       "      <td>1.279</td>\n",
+       "      <td>1.239</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2020-11-01 05:06:05+00:00</td>\n",
+       "      <td>11</td>\n",
+       "      <td>4</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>1</td>\n",
+       "      <td>44</td>\n",
+       "      <td>6</td>\n",
+       "      <td>fall</td>\n",
+       "      <td>sun</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22918</th>\n",
+       "      <td>2020-11-01 07:31:06+0100</td>\n",
+       "      <td>e95c2523-8d12-4132-98b3-0aa6a2ce454d</td>\n",
+       "      <td>1.049</td>\n",
+       "      <td>1.249</td>\n",
+       "      <td>1.209</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2020-11-01 06:31:06+00:00</td>\n",
+       "      <td>11</td>\n",
+       "      <td>4</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>1</td>\n",
+       "      <td>44</td>\n",
+       "      <td>6</td>\n",
+       "      <td>fall</td>\n",
+       "      <td>sun</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23793</th>\n",
+       "      <td>2020-11-01 07:36:05+0100</td>\n",
+       "      <td>e95c2523-8d12-4132-98b3-0aa6a2ce454d</td>\n",
+       "      <td>1.099</td>\n",
+       "      <td>1.309</td>\n",
+       "      <td>1.269</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2020-11-01 06:36:05+00:00</td>\n",
+       "      <td>11</td>\n",
+       "      <td>4</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>1</td>\n",
+       "      <td>44</td>\n",
+       "      <td>6</td>\n",
+       "      <td>fall</td>\n",
+       "      <td>sun</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26755</th>\n",
+       "      <td>2020-11-01 07:56:07+0100</td>\n",
+       "      <td>e95c2523-8d12-4132-98b3-0aa6a2ce454d</td>\n",
+       "      <td>1.079</td>\n",
+       "      <td>1.279</td>\n",
+       "      <td>1.239</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2020-11-01 06:56:07+00:00</td>\n",
+       "      <td>11</td>\n",
+       "      <td>4</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>1</td>\n",
+       "      <td>44</td>\n",
+       "      <td>6</td>\n",
+       "      <td>fall</td>\n",
+       "      <td>sun</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>33824</th>\n",
+       "      <td>2020-11-01 08:31:06+0100</td>\n",
+       "      <td>e95c2523-8d12-4132-98b3-0aa6a2ce454d</td>\n",
+       "      <td>1.049</td>\n",
+       "      <td>1.249</td>\n",
+       "      <td>1.209</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2020-11-01 07:31:06+00:00</td>\n",
+       "      <td>11</td>\n",
+       "      <td>4</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>1</td>\n",
+       "      <td>44</td>\n",
+       "      <td>6</td>\n",
+       "      <td>fall</td>\n",
+       "      <td>sun</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1569576</th>\n",
+       "      <td>2020-11-14 14:21:07+0100</td>\n",
+       "      <td>e95c2523-8d12-4132-98b3-0aa6a2ce454d</td>\n",
+       "      <td>0.999</td>\n",
+       "      <td>1.179</td>\n",
+       "      <td>1.139</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2020-11-14 13:21:07+00:00</td>\n",
+       "      <td>11</td>\n",
+       "      <td>4</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>14</td>\n",
+       "      <td>46</td>\n",
+       "      <td>5</td>\n",
+       "      <td>fall</td>\n",
+       "      <td>sat</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1610045</th>\n",
+       "      <td>2020-11-14 16:26:09+0100</td>\n",
+       "      <td>e95c2523-8d12-4132-98b3-0aa6a2ce454d</td>\n",
+       "      <td>1.039</td>\n",
+       "      <td>1.219</td>\n",
+       "      <td>1.179</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2020-11-14 15:26:09+00:00</td>\n",
+       "      <td>11</td>\n",
+       "      <td>4</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>14</td>\n",
+       "      <td>46</td>\n",
+       "      <td>5</td>\n",
+       "      <td>fall</td>\n",
+       "      <td>sat</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1616416</th>\n",
+       "      <td>2020-11-14 16:51:06+0100</td>\n",
+       "      <td>e95c2523-8d12-4132-98b3-0aa6a2ce454d</td>\n",
+       "      <td>0.999</td>\n",
+       "      <td>1.179</td>\n",
+       "      <td>1.139</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2020-11-14 15:51:06+00:00</td>\n",
+       "      <td>11</td>\n",
+       "      <td>4</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>14</td>\n",
+       "      <td>46</td>\n",
+       "      <td>5</td>\n",
+       "      <td>fall</td>\n",
+       "      <td>sat</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1690582</th>\n",
+       "      <td>2020-11-14 21:46:09+0100</td>\n",
+       "      <td>e95c2523-8d12-4132-98b3-0aa6a2ce454d</td>\n",
+       "      <td>1.009</td>\n",
+       "      <td>1.199</td>\n",
+       "      <td>1.159</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2020-11-14 20:46:09+00:00</td>\n",
+       "      <td>11</td>\n",
+       "      <td>4</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>14</td>\n",
+       "      <td>46</td>\n",
+       "      <td>5</td>\n",
+       "      <td>fall</td>\n",
+       "      <td>sat</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1701588</th>\n",
+       "      <td>2020-11-14 23:51:07+0100</td>\n",
+       "      <td>e95c2523-8d12-4132-98b3-0aa6a2ce454d</td>\n",
+       "      <td>1.059</td>\n",
+       "      <td>1.239</td>\n",
+       "      <td>1.189</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2020-11-14 22:51:07+00:00</td>\n",
+       "      <td>11</td>\n",
+       "      <td>4</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>14</td>\n",
+       "      <td>46</td>\n",
+       "      <td>5</td>\n",
+       "      <td>fall</td>\n",
+       "      <td>sat</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>100 rows × 17 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                             date                          station_uuid  \\\n",
+       "9581     2020-11-01 06:06:05+0100  e95c2523-8d12-4132-98b3-0aa6a2ce454d   \n",
+       "22918    2020-11-01 07:31:06+0100  e95c2523-8d12-4132-98b3-0aa6a2ce454d   \n",
+       "23793    2020-11-01 07:36:05+0100  e95c2523-8d12-4132-98b3-0aa6a2ce454d   \n",
+       "26755    2020-11-01 07:56:07+0100  e95c2523-8d12-4132-98b3-0aa6a2ce454d   \n",
+       "33824    2020-11-01 08:31:06+0100  e95c2523-8d12-4132-98b3-0aa6a2ce454d   \n",
+       "...                           ...                                   ...   \n",
+       "1569576  2020-11-14 14:21:07+0100  e95c2523-8d12-4132-98b3-0aa6a2ce454d   \n",
+       "1610045  2020-11-14 16:26:09+0100  e95c2523-8d12-4132-98b3-0aa6a2ce454d   \n",
+       "1616416  2020-11-14 16:51:06+0100  e95c2523-8d12-4132-98b3-0aa6a2ce454d   \n",
+       "1690582  2020-11-14 21:46:09+0100  e95c2523-8d12-4132-98b3-0aa6a2ce454d   \n",
+       "1701588  2020-11-14 23:51:07+0100  e95c2523-8d12-4132-98b3-0aa6a2ce454d   \n",
+       "\n",
+       "        diesel     e5    e10 dieselchange e5change e10change  \\\n",
+       "9581     1.079  1.279  1.239            1        1         1   \n",
+       "22918    1.049  1.249  1.209            1        1         1   \n",
+       "23793    1.099  1.309  1.269            1        1         1   \n",
+       "26755    1.079  1.279  1.239            1        1         1   \n",
+       "33824    1.049  1.249  1.209            1        1         1   \n",
+       "...        ...    ...    ...          ...      ...       ...   \n",
+       "1569576  0.999  1.179  1.139            1        1         1   \n",
+       "1610045  1.039  1.219  1.179            1        1         1   \n",
+       "1616416  0.999  1.179  1.139            1        1         1   \n",
+       "1690582  1.009  1.199  1.159            1        1         1   \n",
+       "1701588  1.059  1.239  1.189            1        1         1   \n",
+       "\n",
+       "                        date_time  month  quarter  year  day  week  weekday  \\\n",
+       "9581    2020-11-01 05:06:05+00:00     11        4  2020    1    44        6   \n",
+       "22918   2020-11-01 06:31:06+00:00     11        4  2020    1    44        6   \n",
+       "23793   2020-11-01 06:36:05+00:00     11        4  2020    1    44        6   \n",
+       "26755   2020-11-01 06:56:07+00:00     11        4  2020    1    44        6   \n",
+       "33824   2020-11-01 07:31:06+00:00     11        4  2020    1    44        6   \n",
+       "...                           ...    ...      ...   ...  ...   ...      ...   \n",
+       "1569576 2020-11-14 13:21:07+00:00     11        4  2020   14    46        5   \n",
+       "1610045 2020-11-14 15:26:09+00:00     11        4  2020   14    46        5   \n",
+       "1616416 2020-11-14 15:51:06+00:00     11        4  2020   14    46        5   \n",
+       "1690582 2020-11-14 20:46:09+00:00     11        4  2020   14    46        5   \n",
+       "1701588 2020-11-14 22:51:07+00:00     11        4  2020   14    46        5   \n",
+       "\n",
+       "        season weekday_name  \n",
+       "9581      fall          sun  \n",
+       "22918     fall          sun  \n",
+       "23793     fall          sun  \n",
+       "26755     fall          sun  \n",
+       "33824     fall          sun  \n",
+       "...        ...          ...  \n",
+       "1569576   fall          sat  \n",
+       "1610045   fall          sat  \n",
+       "1616416   fall          sat  \n",
+       "1690582   fall          sat  \n",
+       "1701588   fall          sat  \n",
+       "\n",
+       "[100 rows x 17 columns]"
+      ]
+     },
+     "execution_count": 145,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "buehl.head(100)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 146,
+   "id": "7b9e1c16",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "buehl.e5 = buehl['e5'].astype(float)\n",
+    "buehl.e10 = buehl['e10'].astype(float)\n",
+    "buehl.diesel = buehl['diesel'].astype(float)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 153,
+   "id": "586fc458",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>diesel</th>\n",
+       "      <th>e5</th>\n",
+       "      <th>e10</th>\n",
+       "      <th>month</th>\n",
+       "      <th>quarter</th>\n",
+       "      <th>year</th>\n",
+       "      <th>day</th>\n",
+       "      <th>week</th>\n",
+       "      <th>weekday</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>weekday_name</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>fri</th>\n",
+       "      <td>1.204121</td>\n",
+       "      <td>1.377952</td>\n",
+       "      <td>1.337810</td>\n",
+       "      <td>5.415323</td>\n",
+       "      <td>2.137097</td>\n",
+       "      <td>2020.669355</td>\n",
+       "      <td>14.941532</td>\n",
+       "      <td>22.881048</td>\n",
+       "      <td>4.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>mon</th>\n",
+       "      <td>1.212656</td>\n",
+       "      <td>1.390277</td>\n",
+       "      <td>1.350161</td>\n",
+       "      <td>5.365571</td>\n",
+       "      <td>2.102515</td>\n",
+       "      <td>2020.680851</td>\n",
+       "      <td>14.715667</td>\n",
+       "      <td>21.692456</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>sat</th>\n",
+       "      <td>1.216235</td>\n",
+       "      <td>1.391703</td>\n",
+       "      <td>1.351557</td>\n",
+       "      <td>5.380457</td>\n",
+       "      <td>2.118503</td>\n",
+       "      <td>2020.675676</td>\n",
+       "      <td>15.588358</td>\n",
+       "      <td>23.378378</td>\n",
+       "      <td>5.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>sun</th>\n",
+       "      <td>1.207577</td>\n",
+       "      <td>1.384637</td>\n",
+       "      <td>1.344506</td>\n",
+       "      <td>5.528090</td>\n",
+       "      <td>2.187266</td>\n",
+       "      <td>2020.653558</td>\n",
+       "      <td>15.988764</td>\n",
+       "      <td>23.747191</td>\n",
+       "      <td>6.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>thu</th>\n",
+       "      <td>1.210599</td>\n",
+       "      <td>1.384385</td>\n",
+       "      <td>1.344142</td>\n",
+       "      <td>5.844130</td>\n",
+       "      <td>2.269231</td>\n",
+       "      <td>2020.641700</td>\n",
+       "      <td>14.556680</td>\n",
+       "      <td>23.352227</td>\n",
+       "      <td>3.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                diesel        e5       e10     month   quarter         year  \\\n",
+       "weekday_name                                                                  \n",
+       "fri           1.204121  1.377952  1.337810  5.415323  2.137097  2020.669355   \n",
+       "mon           1.212656  1.390277  1.350161  5.365571  2.102515  2020.680851   \n",
+       "sat           1.216235  1.391703  1.351557  5.380457  2.118503  2020.675676   \n",
+       "sun           1.207577  1.384637  1.344506  5.528090  2.187266  2020.653558   \n",
+       "thu           1.210599  1.384385  1.344142  5.844130  2.269231  2020.641700   \n",
+       "\n",
+       "                    day       week  weekday  \n",
+       "weekday_name                                 \n",
+       "fri           14.941532  22.881048      4.0  \n",
+       "mon           14.715667  21.692456      0.0  \n",
+       "sat           15.588358  23.378378      5.0  \n",
+       "sun           15.988764  23.747191      6.0  \n",
+       "thu           14.556680  23.352227      3.0  "
+      ]
+     },
+     "execution_count": 153,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "weekday_groups = buehl.groupby(\"weekday_name\").mean()\n",
+    "weekday_num_groups = buehl.groupby(\"weekday\").mean()\n",
+    "weekday_groups.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 151,
+   "id": "af80903b",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot:xlabel='weekday_name'>"
+      ]
+     },
+     "execution_count": 151,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "weekday_groups[['diesel', 'e5', 'e10']].plot.bar()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 162,
+   "id": "a0e1b2a2",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot:xlabel='weekday'>"
+      ]
+     },
+     "execution_count": 162,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "weekday_num_groups[['diesel', 'e5', 'e10']].plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 166,
+   "id": "9c655a50",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot:xlabel='hour'>"
+      ]
+     },
+     "execution_count": 166,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "buehl.groupby([\"hour\"]).mean()[['e5', 'e10','diesel']].plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 169,
+   "id": "40b16b00",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot:xlabel='weekday,hour'>"
+      ]
+     },
+     "execution_count": 169,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "buehl.groupby([\"weekday\", \"hour\"]).mean()[['e5', 'e10','diesel']].plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 161,
+   "id": "4000c560",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot:xlabel='year,week'>"
+      ]
+     },
+     "execution_count": 161,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "buehl.groupby([\"year\",\"week\"]).mean()[['e5', 'e10','diesel']].plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 156,
+   "id": "3508a896",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot:xlabel='date', ylabel='diesel'>"
+      ]
+     },
+     "execution_count": 156,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sns.lineplot(x=\"date\", y=\"diesel\",\n",
+    "             data=buehl)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 88,
+   "id": "1cb4ef0b",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot:xlabel='date', ylabel='e5'>"
+      ]
+     },
+     "execution_count": 88,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sns.lineplot(x=\"date\", y=\"e5\", \n",
+    "             data=buehl[0:100])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 89,
+   "id": "05af38ea",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 1152x720 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "buehl_melted = buehl.melt('date', var_name='cols',  value_name='vals', value_vars=[\"diesel\", \"e5\", \"e10\"])\n",
+    "sns.lineplot(x=\"date\", y=\"vals\", hue='cols', data=buehl_melted)\n",
+    "fig = plt.gcf()\n",
+    "fig.set_size_inches( 16, 10)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 75,
+   "id": "91c57d5a",
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "KeyError",
+     "evalue": "\"['station_uuid'] not found in axis\"",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
+      "\u001b[0;32m/tmp/ipykernel_236719/3331971858.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mb2\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mbuehl\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdrop\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'station_uuid'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m \u001b[0;31m#b2 = b2.melt('date', var_name='cols', value_name='vals')\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0;31m#g = sns.factorplot(x=\"date\", y=\"vals\", hue='cols', data=b2)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m~/.cache/pypoetry/virtualenvs/besser-tanken-XZndgdH5-py3.9/lib/python3.9/site-packages/pandas/util/_decorators.py\u001b[0m in \u001b[0;36mwrapper\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m    309\u001b[0m                     \u001b[0mstacklevel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mstacklevel\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    310\u001b[0m                 )\n\u001b[0;32m--> 311\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    312\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    313\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mwrapper\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m~/.cache/pypoetry/virtualenvs/besser-tanken-XZndgdH5-py3.9/lib/python3.9/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36mdrop\u001b[0;34m(self, labels, axis, index, columns, level, inplace, errors)\u001b[0m\n\u001b[1;32m   4899\u001b[0m                 \u001b[0mweight\u001b[0m  \u001b[0;36m1.0\u001b[0m     \u001b[0;36m0.8\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   4900\u001b[0m         \"\"\"\n\u001b[0;32m-> 4901\u001b[0;31m         return super().drop(\n\u001b[0m\u001b[1;32m   4902\u001b[0m             \u001b[0mlabels\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mlabels\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   4903\u001b[0m             \u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0maxis\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m~/.cache/pypoetry/virtualenvs/besser-tanken-XZndgdH5-py3.9/lib/python3.9/site-packages/pandas/core/generic.py\u001b[0m in \u001b[0;36mdrop\u001b[0;34m(self, labels, axis, index, columns, level, inplace, errors)\u001b[0m\n\u001b[1;32m   4145\u001b[0m         \u001b[0;32mfor\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlabels\u001b[0m \u001b[0;32min\u001b[0m \u001b[0maxes\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   4146\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mlabels\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 4147\u001b[0;31m                 \u001b[0mobj\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_drop_axis\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlabels\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlevel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mlevel\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0merrors\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0merrors\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   4148\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   4149\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0minplace\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m~/.cache/pypoetry/virtualenvs/besser-tanken-XZndgdH5-py3.9/lib/python3.9/site-packages/pandas/core/generic.py\u001b[0m in \u001b[0;36m_drop_axis\u001b[0;34m(self, labels, axis, level, errors)\u001b[0m\n\u001b[1;32m   4180\u001b[0m                 \u001b[0mnew_axis\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdrop\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlabels\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlevel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mlevel\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0merrors\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0merrors\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   4181\u001b[0m             \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 4182\u001b[0;31m                 \u001b[0mnew_axis\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdrop\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlabels\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0merrors\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0merrors\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   4183\u001b[0m             \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreindex\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m**\u001b[0m\u001b[0;34m{\u001b[0m\u001b[0maxis_name\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mnew_axis\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   4184\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m~/.cache/pypoetry/virtualenvs/besser-tanken-XZndgdH5-py3.9/lib/python3.9/site-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36mdrop\u001b[0;34m(self, labels, errors)\u001b[0m\n\u001b[1;32m   6016\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mmask\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0many\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   6017\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0merrors\u001b[0m \u001b[0;34m!=\u001b[0m \u001b[0;34m\"ignore\"\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 6018\u001b[0;31m                 \u001b[0;32mraise\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34mf\"{labels[mask]} not found in axis\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   6019\u001b[0m             \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mindexer\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m~\u001b[0m\u001b[0mmask\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   6020\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdelete\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mindexer\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;31mKeyError\u001b[0m: \"['station_uuid'] not found in axis\""
+     ]
+    }
+   ],
+   "source": [
+    "b2 = buehl.drop('station_uuid')\n",
+    "#b2 = b2.melt('date', var_name='cols', value_name='vals')\n",
+    "#g = sns.factorplot(x=\"date\", y=\"vals\", hue='cols', data=b2)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/besser_tanken/__init__.py b/besser_tanken/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/besser_tanken/config.py b/besser_tanken/config.py
new file mode 100644
index 0000000..8871b35
--- /dev/null
+++ b/besser_tanken/config.py
@@ -0,0 +1,10 @@
+import os
+
+conf_dir = os.path.dirname(os.path.abspath(__file__))
+
+stations_dir = os.path.abspath(
+    os.path.join(conf_dir, os.pardir, "tankerkoenig-data", "stations"))
+prices_dir = os.path.abspath(
+    os.path.join(conf_dir, os.pardir, "tankerkoenig-data", "prices"))
+feather_dir = os.path.abspath(
+    os.path.join(conf_dir, os.pardir, "feather_data"))
diff --git a/besser_tanken/data_loader.py b/besser_tanken/data_loader.py
new file mode 100644
index 0000000..fda431d
--- /dev/null
+++ b/besser_tanken/data_loader.py
@@ -0,0 +1,130 @@
+import concurrent
+import csv
+import os
+import re
+from collections import defaultdict
+from concurrent.futures import ThreadPoolExecutor, as_completed
+from datetime import date, timedelta
+from glob import glob
+from threading import Thread, Lock
+
+from loguru import logger
+from besser_tanken.config import stations_dir, prices_dir
+from besser_tanken.data_tools import fix_date_time_strings
+
+files_re = re.compile(r"(\d\d\d\d)-(\d\d)-(\d\d)-(\S*).csv")
+
+prices_cache = dict()
+stations_cache = dict()
+
+
+def load_date_hierarchical_file(base_dir, year=None, month=None,
+                                day=None) -> str:
+    year_dirs = glob(f"{base_dir}/*/")
+    years = []
+    for y_d in year_dirs:
+        y = y_d[:-1].rsplit('/', maxsplit=1)[1]
+        years.append(int(y))
+    if year is None:
+        year = sorted(years)[-1]
+    if int(year) not in years:
+        raise ValueError(f"No file for year {year}!")
+    year_dir = f"{base_dir}/{year}"
+
+    month_dirs = glob(f"{year_dir}/*/")
+    months = []
+    for m_d in month_dirs:
+        m = m_d[:-1].rsplit('/', maxsplit=1)[1]
+        months.append(int(m))
+    if month is None:
+        month = sorted(months)[-1]
+    if int(month) not in months:
+        raise ValueError(f"No file found for month {month}!")
+    month_dir = f"{year_dir}/{month:02d}"
+
+    day_files = glob(f"{month_dir}/*.csv")
+    days = []
+    file_type = None
+    for d in day_files:
+        match = files_re.search(d)
+        if match:
+            days.append(int(match.group(3)))
+            file_type = match.group(4)
+    if day is None:
+        day = sorted(days)[-1]
+    if int(day) not in days or file_type is None:
+        raise ValueError(f"No file found for day {day}!")
+
+    return os.path.join(month_dir,
+                        f"{year}-{month:02d}-{day:02d}-{file_type}.csv")
+
+
+def load_prices(year=None, month=None, day=None) -> list:
+    file = load_date_hierarchical_file(prices_dir, year, month, day)
+    if file in prices_cache:
+        logger.info(f"returning prices from cache for file: {file}")
+        return prices_cache[file]
+    logger.info(f"loading prices file: {file}")
+    with open(file, newline='') as csv_file:
+        res = list(csv.DictReader(csv_file))
+        logger.info(f"got {len(res)} prices")
+        res = fix_date_time_strings(res)
+        prices_cache[file] = res
+        return res
+
+
+def load_prices_from(year=None, month=None, day=None, threading=True) -> list:
+    today = date.today()
+    start_date = date(year, month, day)
+    res = []
+
+    def _threaded_loading(y: int, m: int, d: int):
+        try:
+            return load_prices(y, m, d)
+        except ValueError:
+            return None  # ignore ValueError, just do nothing
+
+    if threading:
+        with ThreadPoolExecutor(max_workers=16) as executor:
+            futures = []
+            while start_date < today:
+                # Thread(target=_threaded_loading, args=(start_date.year,
+                #                                       start_date.month,
+                #                                       start_date.day,)).start()
+                futures.append(
+                    executor.submit(_threaded_loading, y=start_date.year,
+                                    m=start_date.month, d=start_date.day))
+                start_date = start_date + timedelta(days=1)
+
+            for future in as_completed(futures):
+                try:
+                    r = future.result()
+                    if r is not None:
+                        res.extend(r)
+                except TimeoutError:
+                    print("timeout occured")
+    else:
+        while start_date < today:
+            try:
+                res.extend(load_prices(start_date.year,
+                                       start_date.month,
+                                       start_date.day))
+
+                start_date = start_date + timedelta(days=1)
+            except ValueError:
+                return res
+    return res
+
+
+def load_stations(year=None, month=None, day=None) -> list:
+    file = load_date_hierarchical_file(stations_dir, year, month, day)
+    if file in stations_cache:
+        logger.info(f"returning stations from cache for file: {file}")
+        return stations_cache[file]
+    with open(file, newline='') as csv_file:
+        res = list(csv.DictReader(csv_file))
+        logger.info(f"got {len(res)} stations")
+        stations_cache[file] = res
+        return res
+
+    # stations_dir
diff --git a/besser_tanken/data_tools.py b/besser_tanken/data_tools.py
new file mode 100644
index 0000000..bb49ff3
--- /dev/null
+++ b/besser_tanken/data_tools.py
@@ -0,0 +1,43 @@
+from collections import defaultdict
+
+import feather
+import pandas
+
+from besser_tanken.config import stations_dir
+
+
+def group_prices(prices):
+    grouped_prices = defaultdict(list)
+    for p in prices:
+        grouped_prices[p['station_uuid']].append(p)
+    return grouped_prices
+
+
+def fix_date_time_strings(price_dict_list):
+    for p in price_dict_list:
+        try:
+            date_time_string, tz_string = p['date'].rsplit('+', maxsplit=1)
+            if ':' in tz_string:
+                tz_string.replace(':', '')
+            else:
+                tz_string_len = len(tz_string)
+                if tz_string_len < 4:
+                    tz_string += '0' * (4 - tz_string_len)
+            p['date'] = date_time_string + "+" + tz_string
+        except IndexError:
+            pass
+
+    return price_dict_list
+
+
+def convert_csv_to_feather(csv_file: str, feather_file: str = None):
+    path = 'my_data.feather'
+    df = pandas.read_csv(csv_file)
+    if feather_file is None:
+        feather_file = csv_file.rsplit('.', maxsplit=1)[0] + '.feather'
+    feather.write_dataframe(df, feather_file)
+    # df = feather.read_dataframe(path)
+
+
+if __name__ == '__main__':
+    convert_csv_to_feather(f"{stations_dir}/2021/01/2021-01-01-stations.csv")
diff --git a/besser_tanken/main.py b/besser_tanken/main.py
new file mode 100644
index 0000000..010ab76
--- /dev/null
+++ b/besser_tanken/main.py
@@ -0,0 +1,45 @@
+import csv
+import os
+import re
+from collections import defaultdict
+from datetime import date, timedelta, datetime
+from glob import glob
+from pprint import pprint
+from typing import Union
+from loguru import logger
+
+from besser_tanken.data_loader import load_stations, load_prices_from, \
+    load_prices
+from besser_tanken.data_tools import group_prices
+
+
+def _test_get_buehl_stations():
+    for s in load_stations():
+        if s['post_code'] in ['77815']:
+            yield s
+
+
+if __name__ == '__main__':
+    buehl_station = next(_test_get_buehl_stations())
+    print(buehl_station)
+    for p in load_prices():
+        # for p in load_prices_from(2021, 4, 1):
+        print(p['date'])
+        print(datetime.strptime(p['date'],
+                                '%Y-%m-%d %H:%M:%S%z'))
+    # exit()
+
+    print(p)
+    print(p['date'])
+    # if ":" == p['date'][-3]:
+    #    p['date'] = p['date'][:-3] + p['date'][-2:]
+    #    print(p['date'])
+    datetime_object = datetime.strptime(p['date'] + "00",
+                                        '%Y-%m-%d %H:%M:%S%z')
+    print(datetime_object)
+    exit()
+    prices = load_prices_from(2021, 4, 1)
+    # print(prices)
+    print(len(prices))
+    prices = group_prices(prices)
+    pprint(prices[buehl_station['uuid']])
diff --git a/besser_tanken/tests.py b/besser_tanken/tests.py
new file mode 100644
index 0000000..1874222
--- /dev/null
+++ b/besser_tanken/tests.py
@@ -0,0 +1,6 @@
+import pygeodb
+print(pygeodb.distance("42897", "50933")) # strings
+
+print(pygeodb.distance("77815", "78247")) # strings
+
+# https://pypi.org/project/pyGeoDb/
\ No newline at end of file
diff --git a/feather_test.ipynb b/feather_test.ipynb
new file mode 100644
index 0000000..95a77b5
--- /dev/null
+++ b/feather_test.ipynb
@@ -0,0 +1,642 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "abc85460",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import os\n",
+    "import matplotlib.pyplot as plt\n",
+    "import seaborn as sns\n",
+    "import pandas as pd\n",
+    "import earthpy as et\n",
+    "import numpy as np\n",
+    "import feather\n",
+    "from besser_tanken.config import stations_dir\n",
+    "#from besser_tanken.config import stations_dir, feather_dir\n",
+    "from besser_tanken.data_loader import load_prices_from, load_stations\n",
+    "from besser_tanken.data_tools import group_prices"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "1b7ebdd6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Handle date time conversions between pandas and matplotlib\n",
+    "from pandas.plotting import register_matplotlib_converters\n",
+    "register_matplotlib_converters()\n",
+    "\n",
+    "# Use white grid plot background from seaborn\n",
+    "sns.set(font_scale=1.5, style=\"whitegrid\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "fe34b881",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#df = feather.read_dataframe(f\"{stations_dir}/2021/01/2021-01-01-stations.feather\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "4d1b7811",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#data = load_prices_from(2020,11,1)\n",
+    "df = load_prices_from(2020,11,1)\n",
+    "df = pd.DataFrame(df)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "4625073c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df.e5 = df['e5'].astype(float)\n",
+    "df.e10 = df['e10'].astype(float)\n",
+    "df.diesel = df['diesel'].astype(float)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "8d98c145",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df[\"date_time\"] = pd.to_datetime(df.date, infer_datetime_format=True, utc=True)\n",
+    "df[\"hour\"] = df.date_time.dt.hour\n",
+    "df[\"month\"] = df.date_time.dt.month\n",
+    "df[\"quarter\"] = df.date_time.dt.quarter\n",
+    "df[\"year\"] = df.date_time.dt.year\n",
+    "df[\"day\"] = df.date_time.dt.day\n",
+    "df[\"week\"] = df.date_time.dt.isocalendar().week\n",
+    "df[\"weekday\"] = df.date_time.dt.weekday\n",
+    "df[\"season\"] = np.where(df[\"month\"].isin([3,4,5]),\"spring\",\n",
+    "   np.where(df[\"month\"].isin([6,7,8]),\"summer\",\n",
+    "   np.where(df[\"month\"].isin([9,10,11]),\"fall\",\n",
+    "   np.where(df[\"month\"].isin([12,1,2]),\"winter\",\"None\"))))\n",
+    "#buehl[\"weekday_name\"] = np.where(df[\"weekday\"].isin([0]),\"mon\",\n",
+    "#   np.where(df[\"weekday\"].isin([1]),\"tue\",\n",
+    "#   np.where(df[\"weekday\"].isin([2]),\"wed\",\n",
+    "#   np.where(df[\"weekday\"].isin([3]),\"thu\",\n",
+    "#   np.where(df[\"weekday\"].isin([4]),\"fri\",            \n",
+    "#   np.where(df[\"weekday\"].isin([5]),\"sat\",            \n",
+    "#   np.where(df[\"weekday\"].isin([6]),\"sun\",\"None\")))))))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "ee8153a0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#df[\"date_time\"] = pd.to_datetime(df.date)\n",
+    "#df[\"month\"] = df[\"date_time\"].dt.month"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d4419141",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "7babd7db",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df.info()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "add38d92",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "grouped_by_station = df.groupby('station_uuid').mean()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "919a8bbf",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "grouped_by_station['diesel'].plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "928c0449",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "grouped_by_station['diesel'].nlargest(20).plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "0b67b964",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "grouped_by_station['diesel'].nsmallest(20).plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "4d9f5349",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "stations = load_stations()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "3fcabf92",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "stations_df = pd.DataFrame(stations)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "493ce272",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "merged = pd.merge(df, stations_df[['uuid','post_code']], how=\"outer\", left_on=[\"station_uuid\"],right_on=[\"uuid\"])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "005e93e4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "merged.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "362a180b",
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "NameError",
+     "evalue": "name 'merged' is not defined",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
+      "\u001b[0;32m/tmp/ipykernel_305767/422759019.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0mfeather_file\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m\"merged.feather\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mfeather\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mwrite_dataframe\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmerged\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfeather_file\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
+      "\u001b[0;31mNameError\u001b[0m: name 'merged' is not defined"
+     ]
+    }
+   ],
+   "source": [
+    "feather_file = \"merged.feather\"\n",
+    "feather.write_dataframe(merged, feather_file)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "5fe90138",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "merged = feather.read_dataframe(feather_file)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "476b5d9e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "plz_grouped = merged.groupby('post_code').mean()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "a3a95cf9",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot:xlabel='post_code'>"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plz_grouped[['diesel','e5']].plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "9ce5a1c0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#prices = group_prices(data)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "4221f111",
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "NameError",
+     "evalue": "name 'stations' is not defined",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
+      "\u001b[0;32m/tmp/ipykernel_305767/2847671869.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mbuehl_stations\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfilter\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;32mlambda\u001b[0m \u001b[0ms\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0ms\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'post_code'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;32min\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m'77815'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstations\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m \u001b[0mbuehl_station\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mbuehl_stations\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0;31m#buehl = prices[buehl_station['uuid']]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m \u001b[0mbuehl\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdf\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mdf\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"station_uuid\"\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0mbuehl_station\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'uuid'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;31mNameError\u001b[0m: name 'stations' is not defined"
+     ]
+    }
+   ],
+   "source": [
+    "buehl_stations = filter(lambda s: s['post_code'] in ['77815'], stations)\n",
+    "buehl_station = list(buehl_stations)[0]\n",
+    "#buehl = prices[buehl_station['uuid']]\n",
+    "buehl = df[df[\"station_uuid\"] == buehl_station['uuid']]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "370d561c",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "5c01f16f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#buehl_station = next(buehl_stations)\n",
+    "print(buehl_station)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "c5371e50",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "buehl= pd.DataFrame(buehl)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "c4a16376",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "buehl[\"date\"] "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "adbd26b4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "buehl[\"date_time\"] = pd.to_datetime(buehl.date, infer_datetime_format=True, utc=True)\n",
+    "#buehl[\"date_time\"] = pd.to_datetime(buehl.date)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "6950f7b6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#buehl[\"date_time\"] = pd.to_datetime(buehl.date, format='%Y-%m-%d %H:%M:%S%z')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "e0b8a829",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "buehl.date_time"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "ce8e2387",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "buehl.date"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "3f5c3044",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "d = pd.to_datetime(buehl.iloc[0].date)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "3609750b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "d"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "69d3322e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "d.month"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "cd27f6c5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "pd.DatetimeIndex(buehl['date_time'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "e56eda9b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "buehl[\"hour\"] = buehl.date_time.dt.hour\n",
+    "buehl[\"month\"] = buehl.date_time.dt.month\n",
+    "buehl[\"quarter\"] = buehl.date_time.dt.quarter\n",
+    "buehl[\"year\"] = buehl.date_time.dt.year\n",
+    "buehl[\"day\"] = buehl.date_time.dt.day\n",
+    "buehl[\"week\"] = buehl.date_time.dt.isocalendar().week\n",
+    "buehl[\"weekday\"] = buehl.date_time.dt.weekday\n",
+    "buehl[\"season\"] = np.where(buehl[\"month\"].isin([3,4,5]),\"spring\",\n",
+    "   np.where(buehl[\"month\"].isin([6,7,8]),\"summer\",\n",
+    "   np.where(buehl[\"month\"].isin([9,10,11]),\"fall\",\n",
+    "   np.where(buehl[\"month\"].isin([12,1,2]),\"winter\",\"None\"))))\n",
+    "buehl[\"weekday_name\"] = np.where(buehl[\"weekday\"].isin([0]),\"mon\",\n",
+    "   np.where(buehl[\"weekday\"].isin([1]),\"tue\",\n",
+    "   np.where(buehl[\"weekday\"].isin([2]),\"wed\",\n",
+    "   np.where(buehl[\"weekday\"].isin([3]),\"thu\",\n",
+    "   np.where(buehl[\"weekday\"].isin([4]),\"fri\",            \n",
+    "   np.where(buehl[\"weekday\"].isin([5]),\"sat\",            \n",
+    "   np.where(buehl[\"weekday\"].isin([6]),\"sun\",\"None\")))))))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "ff6450d2",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "buehl.columns"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "65deae4d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "buehl.info()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "26cae1bf",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "buehl.head(100)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "f5f30288",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "buehl.e5 = buehl['e5'].astype(float)\n",
+    "buehl.e10 = buehl['e10'].astype(float)\n",
+    "buehl.diesel = buehl['diesel'].astype(float)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "9bcf07be",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "weekday_groups = buehl.groupby(\"weekday_name\").mean()\n",
+    "weekday_num_groups = buehl.groupby(\"weekday\").mean()\n",
+    "weekday_groups.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "92c12366",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "weekday_groups[['diesel', 'e5', 'e10']].plot.bar()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "4f808aa0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "weekday_num_groups[['diesel', 'e5', 'e10']].plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "04dedef5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "buehl.groupby([\"hour\"]).mean()[['e5', 'e10','diesel']].plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "44318715",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "buehl.groupby([\"weekday\", \"hour\"]).mean()[['e5', 'e10','diesel']].plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "c0f2a72f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "buehl.groupby([\"year\",\"week\"]).mean()[['e5', 'e10','diesel']].plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "3508a896",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "sns.lineplot(x=\"date\", y=\"diesel\",\n",
+    "             data=buehl)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "1cb4ef0b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "sns.lineplot(x=\"date\", y=\"e5\", \n",
+    "             data=buehl[0:100])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "05af38ea",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "buehl_melted = buehl.melt('date', var_name='cols',  value_name='vals', value_vars=[\"diesel\", \"e5\", \"e10\"])\n",
+    "sns.lineplot(x=\"date\", y=\"vals\", hue='cols', data=buehl_melted)\n",
+    "fig = plt.gcf()\n",
+    "fig.set_size_inches( 16, 10)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "91c57d5a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "b2 = buehl.drop('station_uuid')\n",
+    "#b2 = b2.melt('date', var_name='cols', value_name='vals')\n",
+    "#g = sns.factorplot(x=\"date\", y=\"vals\", hue='cols', data=b2)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/poetry.lock b/poetry.lock
new file mode 100644
index 0000000..3fb325f
--- /dev/null
+++ b/poetry.lock
@@ -0,0 +1,2214 @@
+[[package]]
+name = "affine"
+version = "2.3.0"
+description = "Matrices describing affine transformation of the plane."
+category = "main"
+optional = false
+python-versions = "*"
+
+[package.extras]
+test = ["pytest (>=3.0)", "pytest-cov", "pydocstyle", "coveralls"]
+
+[[package]]
+name = "appnope"
+version = "0.1.2"
+description = "Disable App Nap on macOS >= 10.9"
+category = "main"
+optional = false
+python-versions = "*"
+
+[[package]]
+name = "argon2-cffi"
+version = "20.1.0"
+description = "The secure Argon2 password hashing algorithm."
+category = "main"
+optional = false
+python-versions = "*"
+
+[package.dependencies]
+cffi = ">=1.0.0"
+six = "*"
+
+[package.extras]
+dev = ["coverage[toml] (>=5.0.2)", "hypothesis", "pytest", "sphinx", "wheel", "pre-commit"]
+docs = ["sphinx"]
+tests = ["coverage[toml] (>=5.0.2)", "hypothesis", "pytest"]
+
+[[package]]
+name = "attrs"
+version = "21.2.0"
+description = "Classes Without Boilerplate"
+category = "main"
+optional = false
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*"
+
+[package.extras]
+dev = ["coverage[toml] (>=5.0.2)", "hypothesis", "pympler", "pytest (>=4.3.0)", "six", "mypy", "pytest-mypy-plugins", "zope.interface", "furo", "sphinx", "sphinx-notfound-page", "pre-commit"]
+docs = ["furo", "sphinx", "zope.interface", "sphinx-notfound-page"]
+tests = ["coverage[toml] (>=5.0.2)", "hypothesis", "pympler", "pytest (>=4.3.0)", "six", "mypy", "pytest-mypy-plugins", "zope.interface"]
+tests_no_zope = ["coverage[toml] (>=5.0.2)", "hypothesis", "pympler", "pytest (>=4.3.0)", "six", "mypy", "pytest-mypy-plugins"]
+
+[[package]]
+name = "backcall"
+version = "0.2.0"
+description = "Specifications for callback functions passed in to an API"
+category = "main"
+optional = false
+python-versions = "*"
+
+[[package]]
+name = "bleach"
+version = "4.0.0"
+description = "An easy safelist-based HTML-sanitizing tool."
+category = "main"
+optional = false
+python-versions = ">=3.6"
+
+[package.dependencies]
+packaging = "*"
+six = ">=1.9.0"
+webencodings = "*"
+
+[[package]]
+name = "certifi"
+version = "2021.5.30"
+description = "Python package for providing Mozilla's CA Bundle."
+category = "main"
+optional = false
+python-versions = "*"
+
+[[package]]
+name = "cffi"
+version = "1.14.6"
+description = "Foreign Function Interface for Python calling C code."
+category = "main"
+optional = false
+python-versions = "*"
+
+[package.dependencies]
+pycparser = "*"
+
+[[package]]
+name = "charset-normalizer"
+version = "2.0.4"
+description = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet."
+category = "main"
+optional = false
+python-versions = ">=3.5.0"
+
+[package.extras]
+unicode_backport = ["unicodedata2"]
+
+[[package]]
+name = "click"
+version = "8.0.1"
+description = "Composable command line interface toolkit"
+category = "main"
+optional = false
+python-versions = ">=3.6"
+
+[package.dependencies]
+colorama = {version = "*", markers = "platform_system == \"Windows\""}
+
+[[package]]
+name = "click-plugins"
+version = "1.1.1"
+description = "An extension module for click to enable registering CLI commands via setuptools entry-points."
+category = "main"
+optional = false
+python-versions = "*"
+
+[package.dependencies]
+click = ">=4.0"
+
+[package.extras]
+dev = ["pytest (>=3.6)", "pytest-cov", "wheel", "coveralls"]
+
+[[package]]
+name = "cligj"
+version = "0.7.2"
+description = "Click params for commmand line interfaces to GeoJSON"
+category = "main"
+optional = false
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, <4"
+
+[package.dependencies]
+click = ">=4.0"
+
+[package.extras]
+test = ["pytest-cov"]
+
+[[package]]
+name = "colorama"
+version = "0.4.4"
+description = "Cross-platform colored terminal text."
+category = "main"
+optional = false
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*"
+
+[[package]]
+name = "cycler"
+version = "0.10.0"
+description = "Composable style cycles"
+category = "main"
+optional = false
+python-versions = "*"
+
+[package.dependencies]
+six = "*"
+
+[[package]]
+name = "debugpy"
+version = "1.4.1"
+description = "An implementation of the Debug Adapter Protocol for Python"
+category = "main"
+optional = false
+python-versions = ">=2.7,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*"
+
+[[package]]
+name = "decorator"
+version = "5.0.9"
+description = "Decorators for Humans"
+category = "main"
+optional = false
+python-versions = ">=3.5"
+
+[[package]]
+name = "defusedxml"
+version = "0.7.1"
+description = "XML bomb protection for Python stdlib modules"
+category = "main"
+optional = false
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*"
+
+[[package]]
+name = "earthpy"
+version = "0.9.2"
+description = "A set of helper functions to make working with spatial data in open source tools easier. This package is maintained by Earth Lab and was originally designed to support the earth analytics education program."
+category = "main"
+optional = false
+python-versions = "*"
+
+[package.dependencies]
+geopandas = "*"
+matplotlib = ">=2.0.0"
+numpy = ">=1.14.0"
+rasterio = "*"
+requests = "*"
+scikit-image = "*"
+
+[[package]]
+name = "entrypoints"
+version = "0.3"
+description = "Discover and load entry points from installed packages."
+category = "main"
+optional = false
+python-versions = ">=2.7"
+
+[[package]]
+name = "feather-format"
+version = "0.4.1"
+description = "Simple wrapper library to the Apache Arrow-based Feather File Format"
+category = "main"
+optional = false
+python-versions = "*"
+
+[package.dependencies]
+pyarrow = ">=0.4.0"
+
+[[package]]
+name = "fiona"
+version = "1.8.20"
+description = "Fiona reads and writes spatial data files"
+category = "main"
+optional = false
+python-versions = "*"
+
+[package.dependencies]
+attrs = ">=17"
+certifi = "*"
+click = ">=4.0"
+click-plugins = ">=1.0"
+cligj = ">=0.5"
+munch = "*"
+six = ">=1.7"
+
+[package.extras]
+all = ["pytest (>=3)", "boto3 (>=1.2.4)", "pytest-cov", "shapely", "mock"]
+calc = ["shapely"]
+s3 = ["boto3 (>=1.2.4)"]
+test = ["pytest (>=3)", "pytest-cov", "boto3 (>=1.2.4)", "mock"]
+
+[[package]]
+name = "geopandas"
+version = "0.9.0"
+description = "Geographic pandas extensions"
+category = "main"
+optional = false
+python-versions = ">=3.6"
+
+[package.dependencies]
+fiona = ">=1.8"
+pandas = ">=0.24.0"
+pyproj = ">=2.2.0"
+shapely = ">=1.6"
+
+[[package]]
+name = "idna"
+version = "3.2"
+description = "Internationalized Domain Names in Applications (IDNA)"
+category = "main"
+optional = false
+python-versions = ">=3.5"
+
+[[package]]
+name = "imageio"
+version = "2.9.0"
+description = "Library for reading and writing a wide range of image, video, scientific, and volumetric data formats."
+category = "main"
+optional = false
+python-versions = ">=3.5"
+
+[package.dependencies]
+numpy = "*"
+pillow = "*"
+
+[package.extras]
+ffmpeg = ["imageio-ffmpeg"]
+fits = ["astropy"]
+full = ["astropy", "gdal", "imageio-ffmpeg", "itk"]
+gdal = ["gdal"]
+itk = ["itk"]
+
+[[package]]
+name = "ipykernel"
+version = "6.2.0"
+description = "IPython Kernel for Jupyter"
+category = "main"
+optional = false
+python-versions = ">=3.7"
+
+[package.dependencies]
+appnope = {version = "*", markers = "platform_system == \"Darwin\""}
+debugpy = ">=1.0.0,<2.0"
+ipython = ">=7.23.1,<8.0"
+jupyter-client = "<8.0"
+matplotlib-inline = ">=0.1.0,<0.2.0"
+tornado = ">=4.2,<7.0"
+traitlets = ">=4.1.0,<6.0"
+
+[package.extras]
+test = ["pytest (!=5.3.4)", "pytest-cov", "flaky", "nose", "ipyparallel"]
+
+[[package]]
+name = "ipython"
+version = "7.26.0"
+description = "IPython: Productive Interactive Computing"
+category = "main"
+optional = false
+python-versions = ">=3.7"
+
+[package.dependencies]
+appnope = {version = "*", markers = "sys_platform == \"darwin\""}
+backcall = "*"
+colorama = {version = "*", markers = "sys_platform == \"win32\""}
+decorator = "*"
+jedi = ">=0.16"
+matplotlib-inline = "*"
+pexpect = {version = ">4.3", markers = "sys_platform != \"win32\""}
+pickleshare = "*"
+prompt-toolkit = ">=2.0.0,<3.0.0 || >3.0.0,<3.0.1 || >3.0.1,<3.1.0"
+pygments = "*"
+traitlets = ">=4.2"
+
+[package.extras]
+all = ["Sphinx (>=1.3)", "ipykernel", "ipyparallel", "ipywidgets", "nbconvert", "nbformat", "nose (>=0.10.1)", "notebook", "numpy (>=1.17)", "pygments", "qtconsole", "requests", "testpath"]
+doc = ["Sphinx (>=1.3)"]
+kernel = ["ipykernel"]
+nbconvert = ["nbconvert"]
+nbformat = ["nbformat"]
+notebook = ["notebook", "ipywidgets"]
+parallel = ["ipyparallel"]
+qtconsole = ["qtconsole"]
+test = ["nose (>=0.10.1)", "requests", "testpath", "pygments", "nbformat", "ipykernel", "numpy (>=1.17)"]
+
+[[package]]
+name = "ipython-genutils"
+version = "0.2.0"
+description = "Vestigial utilities from IPython"
+category = "main"
+optional = false
+python-versions = "*"
+
+[[package]]
+name = "ipywidgets"
+version = "7.6.3"
+description = "IPython HTML widgets for Jupyter"
+category = "main"
+optional = false
+python-versions = "*"
+
+[package.dependencies]
+ipykernel = ">=4.5.1"
+ipython = {version = ">=4.0.0", markers = "python_version >= \"3.3\""}
+jupyterlab-widgets = {version = ">=1.0.0", markers = "python_version >= \"3.6\""}
+nbformat = ">=4.2.0"
+traitlets = ">=4.3.1"
+widgetsnbextension = ">=3.5.0,<3.6.0"
+
+[package.extras]
+test = ["pytest (>=3.6.0)", "pytest-cov", "mock"]
+
+[[package]]
+name = "jedi"
+version = "0.18.0"
+description = "An autocompletion tool for Python that can be used for text editors."
+category = "main"
+optional = false
+python-versions = ">=3.6"
+
+[package.dependencies]
+parso = ">=0.8.0,<0.9.0"
+
+[package.extras]
+qa = ["flake8 (==3.8.3)", "mypy (==0.782)"]
+testing = ["Django (<3.1)", "colorama", "docopt", "pytest (<6.0.0)"]
+
+[[package]]
+name = "jinja2"
+version = "3.0.1"
+description = "A very fast and expressive template engine."
+category = "main"
+optional = false
+python-versions = ">=3.6"
+
+[package.dependencies]
+MarkupSafe = ">=2.0"
+
+[package.extras]
+i18n = ["Babel (>=2.7)"]
+
+[[package]]
+name = "jsonschema"
+version = "3.2.0"
+description = "An implementation of JSON Schema validation for Python"
+category = "main"
+optional = false
+python-versions = "*"
+
+[package.dependencies]
+attrs = ">=17.4.0"
+pyrsistent = ">=0.14.0"
+six = ">=1.11.0"
+
+[package.extras]
+format = ["idna", "jsonpointer (>1.13)", "rfc3987", "strict-rfc3339", "webcolors"]
+format_nongpl = ["idna", "jsonpointer (>1.13)", "webcolors", "rfc3986-validator (>0.1.0)", "rfc3339-validator"]
+
+[[package]]
+name = "jupyter"
+version = "1.0.0"
+description = "Jupyter metapackage. Install all the Jupyter components in one go."
+category = "main"
+optional = false
+python-versions = "*"
+
+[package.dependencies]
+ipykernel = "*"
+ipywidgets = "*"
+jupyter-console = "*"
+nbconvert = "*"
+notebook = "*"
+qtconsole = "*"
+
+[[package]]
+name = "jupyter-client"
+version = "6.2.0"
+description = "Jupyter protocol implementation and client libraries"
+category = "main"
+optional = false
+python-versions = ">=3.6.1"
+
+[package.dependencies]
+jupyter-core = ">=4.6.0"
+nest-asyncio = ">=1.5"
+python-dateutil = ">=2.1"
+pyzmq = ">=13"
+tornado = ">=4.1"
+traitlets = "*"
+
+[package.extras]
+doc = ["sphinx (>=1.3.6)", "sphinx-rtd-theme", "sphinxcontrib-github-alt"]
+test = ["async-generator", "ipykernel", "ipython", "mock", "pytest-asyncio", "pytest-timeout", "pytest", "mypy", "pre-commit", "jedi (<0.18)"]
+
+[[package]]
+name = "jupyter-console"
+version = "6.4.0"
+description = "Jupyter terminal console"
+category = "main"
+optional = false
+python-versions = ">=3.6"
+
+[package.dependencies]
+ipykernel = "*"
+ipython = "*"
+jupyter-client = "*"
+prompt-toolkit = ">=2.0.0,<3.0.0 || >3.0.0,<3.0.1 || >3.0.1,<3.1.0"
+pygments = "*"
+
+[package.extras]
+test = ["pexpect"]
+
+[[package]]
+name = "jupyter-contrib-core"
+version = "0.3.3"
+description = "Common utilities for jupyter-contrib projects."
+category = "main"
+optional = false
+python-versions = "*"
+
+[package.dependencies]
+jupyter-core = "*"
+notebook = ">=4.0"
+tornado = "*"
+traitlets = "*"
+
+[package.extras]
+testing_utils = ["nose", "mock"]
+
+[[package]]
+name = "jupyter-core"
+version = "4.7.1"
+description = "Jupyter core package. A base package on which Jupyter projects rely."
+category = "main"
+optional = false
+python-versions = ">=3.6"
+
+[package.dependencies]
+pywin32 = {version = ">=1.0", markers = "sys_platform == \"win32\""}
+traitlets = "*"
+
+[[package]]
+name = "jupyter-nbextensions-configurator"
+version = "0.4.1"
+description = "jupyter serverextension providing configuration interfaces for nbextensions."
+category = "main"
+optional = false
+python-versions = "*"
+
+[package.dependencies]
+jupyter_contrib_core = ">=0.3.3"
+jupyter_core = "*"
+notebook = ">=4.0"
+pyyaml = "*"
+tornado = "*"
+traitlets = "*"
+
+[package.extras]
+test = ["jupyter-contrib-core", "nose", "requests", "selenium", "mock"]
+
+[[package]]
+name = "jupyterlab-pygments"
+version = "0.1.2"
+description = "Pygments theme using JupyterLab CSS variables"
+category = "main"
+optional = false
+python-versions = "*"
+
+[package.dependencies]
+pygments = ">=2.4.1,<3"
+
+[[package]]
+name = "jupyterlab-widgets"
+version = "1.0.0"
+description = "A JupyterLab extension."
+category = "main"
+optional = false
+python-versions = ">=3.6"
+
+[[package]]
+name = "kiwisolver"
+version = "1.3.1"
+description = "A fast implementation of the Cassowary constraint solver"
+category = "main"
+optional = false
+python-versions = ">=3.6"
+
+[[package]]
+name = "loguru"
+version = "0.5.3"
+description = "Python logging made (stupidly) simple"
+category = "main"
+optional = false
+python-versions = ">=3.5"
+
+[package.dependencies]
+colorama = {version = ">=0.3.4", markers = "sys_platform == \"win32\""}
+win32-setctime = {version = ">=1.0.0", markers = "sys_platform == \"win32\""}
+
+[package.extras]
+dev = ["codecov (>=2.0.15)", "colorama (>=0.3.4)", "flake8 (>=3.7.7)", "tox (>=3.9.0)", "tox-travis (>=0.12)", "pytest (>=4.6.2)", "pytest-cov (>=2.7.1)", "Sphinx (>=2.2.1)", "sphinx-autobuild (>=0.7.1)", "sphinx-rtd-theme (>=0.4.3)", "black (>=19.10b0)", "isort (>=5.1.1)"]
+
+[[package]]
+name = "markupsafe"
+version = "2.0.1"
+description = "Safely add untrusted strings to HTML/XML markup."
+category = "main"
+optional = false
+python-versions = ">=3.6"
+
+[[package]]
+name = "matplotlib"
+version = "3.4.3"
+description = "Python plotting package"
+category = "main"
+optional = false
+python-versions = ">=3.7"
+
+[package.dependencies]
+cycler = ">=0.10"
+kiwisolver = ">=1.0.1"
+numpy = ">=1.16"
+pillow = ">=6.2.0"
+pyparsing = ">=2.2.1"
+python-dateutil = ">=2.7"
+
+[[package]]
+name = "matplotlib-inline"
+version = "0.1.2"
+description = "Inline Matplotlib backend for Jupyter"
+category = "main"
+optional = false
+python-versions = ">=3.5"
+
+[package.dependencies]
+traitlets = "*"
+
+[[package]]
+name = "mistune"
+version = "0.8.4"
+description = "The fastest markdown parser in pure Python"
+category = "main"
+optional = false
+python-versions = "*"
+
+[[package]]
+name = "munch"
+version = "2.5.0"
+description = "A dot-accessible dictionary (a la JavaScript objects)"
+category = "main"
+optional = false
+python-versions = "*"
+
+[package.dependencies]
+six = "*"
+
+[package.extras]
+testing = ["pytest", "coverage", "astroid (>=1.5.3,<1.6.0)", "pylint (>=1.7.2,<1.8.0)", "astroid (>=2.0)", "pylint (>=2.3.1,<2.4.0)"]
+yaml = ["PyYAML (>=5.1.0)"]
+
+[[package]]
+name = "nbclient"
+version = "0.5.4"
+description = "A client library for executing notebooks. Formerly nbconvert's ExecutePreprocessor."
+category = "main"
+optional = false
+python-versions = ">=3.6.1"
+
+[package.dependencies]
+jupyter-client = ">=6.1.5"
+nbformat = ">=5.0"
+nest-asyncio = "*"
+traitlets = ">=4.2"
+
+[package.extras]
+dev = ["codecov", "coverage", "ipython", "ipykernel", "ipywidgets", "pytest (>=4.1)", "pytest-cov (>=2.6.1)", "check-manifest", "flake8", "mypy", "tox", "bumpversion", "xmltodict", "pip (>=18.1)", "wheel (>=0.31.0)", "setuptools (>=38.6.0)", "twine (>=1.11.0)", "black"]
+sphinx = ["Sphinx (>=1.7)", "sphinx-book-theme", "mock", "moto", "myst-parser"]
+test = ["codecov", "coverage", "ipython", "ipykernel", "ipywidgets", "pytest (>=4.1)", "pytest-cov (>=2.6.1)", "check-manifest", "flake8", "mypy", "tox", "bumpversion", "xmltodict", "pip (>=18.1)", "wheel (>=0.31.0)", "setuptools (>=38.6.0)", "twine (>=1.11.0)", "black"]
+
+[[package]]
+name = "nbconvert"
+version = "6.1.0"
+description = "Converting Jupyter Notebooks"
+category = "main"
+optional = false
+python-versions = ">=3.7"
+
+[package.dependencies]
+bleach = "*"
+defusedxml = "*"
+entrypoints = ">=0.2.2"
+jinja2 = ">=2.4"
+jupyter-core = "*"
+jupyterlab-pygments = "*"
+mistune = ">=0.8.1,<2"
+nbclient = ">=0.5.0,<0.6.0"
+nbformat = ">=4.4"
+pandocfilters = ">=1.4.1"
+pygments = ">=2.4.1"
+testpath = "*"
+traitlets = ">=5.0"
+
+[package.extras]
+all = ["pytest", "pytest-cov", "pytest-dependency", "ipykernel", "ipywidgets (>=7)", "pyppeteer (==0.2.2)", "tornado (>=4.0)", "sphinx (>=1.5.1)", "sphinx-rtd-theme", "nbsphinx (>=0.2.12)", "ipython"]
+docs = ["sphinx (>=1.5.1)", "sphinx-rtd-theme", "nbsphinx (>=0.2.12)", "ipython"]
+serve = ["tornado (>=4.0)"]
+test = ["pytest", "pytest-cov", "pytest-dependency", "ipykernel", "ipywidgets (>=7)", "pyppeteer (==0.2.2)"]
+webpdf = ["pyppeteer (==0.2.2)"]
+
+[[package]]
+name = "nbformat"
+version = "5.1.3"
+description = "The Jupyter Notebook format"
+category = "main"
+optional = false
+python-versions = ">=3.5"
+
+[package.dependencies]
+ipython-genutils = "*"
+jsonschema = ">=2.4,<2.5.0 || >2.5.0"
+jupyter-core = "*"
+traitlets = ">=4.1"
+
+[package.extras]
+fast = ["fastjsonschema"]
+test = ["check-manifest", "fastjsonschema", "testpath", "pytest", "pytest-cov"]
+
+[[package]]
+name = "nest-asyncio"
+version = "1.5.1"
+description = "Patch asyncio to allow nested event loops"
+category = "main"
+optional = false
+python-versions = ">=3.5"
+
+[[package]]
+name = "networkx"
+version = "2.6.2"
+description = "Python package for creating and manipulating graphs and networks"
+category = "main"
+optional = false
+python-versions = ">=3.7"
+
+[package.extras]
+default = ["numpy (>=1.19)", "scipy (>=1.5,!=1.6.1)", "matplotlib (>=3.3)", "pandas (>=1.1)"]
+developer = ["black (==21.5b1)", "pre-commit (>=2.12)"]
+doc = ["sphinx (>=4.0,<5.0)", "pydata-sphinx-theme (>=0.6,<1.0)", "sphinx-gallery (>=0.9,<1.0)", "numpydoc (>=1.1)", "pillow (>=8.2)", "nb2plots (>=0.6)", "texext (>=0.6.6)"]
+extra = ["lxml (>=4.5)", "pygraphviz (>=1.7)", "pydot (>=1.4.1)"]
+test = ["pytest (>=6.2)", "pytest-cov (>=2.12)", "codecov (>=2.1)"]
+
+[[package]]
+name = "notebook"
+version = "6.4.3"
+description = "A web-based notebook environment for interactive computing"
+category = "main"
+optional = false
+python-versions = ">=3.6"
+
+[package.dependencies]
+argon2-cffi = "*"
+ipykernel = "*"
+ipython-genutils = "*"
+jinja2 = "*"
+jupyter-client = ">=5.3.4"
+jupyter-core = ">=4.6.1"
+nbconvert = "*"
+nbformat = "*"
+prometheus-client = "*"
+pyzmq = ">=17"
+Send2Trash = ">=1.5.0"
+terminado = ">=0.8.3"
+tornado = ">=6.1"
+traitlets = ">=4.2.1"
+
+[package.extras]
+docs = ["sphinx", "nbsphinx", "sphinxcontrib-github-alt", "sphinx-rtd-theme", "myst-parser"]
+json-logging = ["json-logging"]
+test = ["pytest", "coverage", "requests", "nbval", "selenium", "pytest-cov", "requests-unixsocket"]
+
+[[package]]
+name = "numpy"
+version = "1.21.1"
+description = "NumPy is the fundamental package for array computing with Python."
+category = "main"
+optional = false
+python-versions = ">=3.7"
+
+[[package]]
+name = "packaging"
+version = "21.0"
+description = "Core utilities for Python packages"
+category = "main"
+optional = false
+python-versions = ">=3.6"
+
+[package.dependencies]
+pyparsing = ">=2.0.2"
+
+[[package]]
+name = "pandas"
+version = "1.3.2"
+description = "Powerful data structures for data analysis, time series, and statistics"
+category = "main"
+optional = false
+python-versions = ">=3.7.1"
+
+[package.dependencies]
+numpy = ">=1.17.3"
+python-dateutil = ">=2.7.3"
+pytz = ">=2017.3"
+
+[package.extras]
+test = ["hypothesis (>=3.58)", "pytest (>=6.0)", "pytest-xdist"]
+
+[[package]]
+name = "pandocfilters"
+version = "1.4.3"
+description = "Utilities for writing pandoc filters in python"
+category = "main"
+optional = false
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
+
+[[package]]
+name = "parso"
+version = "0.8.2"
+description = "A Python Parser"
+category = "main"
+optional = false
+python-versions = ">=3.6"
+
+[package.extras]
+qa = ["flake8 (==3.8.3)", "mypy (==0.782)"]
+testing = ["docopt", "pytest (<6.0.0)"]
+
+[[package]]
+name = "pexpect"
+version = "4.8.0"
+description = "Pexpect allows easy control of interactive console applications."
+category = "main"
+optional = false
+python-versions = "*"
+
+[package.dependencies]
+ptyprocess = ">=0.5"
+
+[[package]]
+name = "pickleshare"
+version = "0.7.5"
+description = "Tiny 'shelve'-like database with concurrency support"
+category = "main"
+optional = false
+python-versions = "*"
+
+[[package]]
+name = "pillow"
+version = "8.3.1"
+description = "Python Imaging Library (Fork)"
+category = "main"
+optional = false
+python-versions = ">=3.6"
+
+[[package]]
+name = "prometheus-client"
+version = "0.11.0"
+description = "Python client for the Prometheus monitoring system."
+category = "main"
+optional = false
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
+
+[package.extras]
+twisted = ["twisted"]
+
+[[package]]
+name = "prompt-toolkit"
+version = "3.0.19"
+description = "Library for building powerful interactive command lines in Python"
+category = "main"
+optional = false
+python-versions = ">=3.6.1"
+
+[package.dependencies]
+wcwidth = "*"
+
+[[package]]
+name = "ptyprocess"
+version = "0.7.0"
+description = "Run a subprocess in a pseudo terminal"
+category = "main"
+optional = false
+python-versions = "*"
+
+[[package]]
+name = "py"
+version = "1.10.0"
+description = "library with cross-python path, ini-parsing, io, code, log facilities"
+category = "main"
+optional = false
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
+
+[[package]]
+name = "pyarrow"
+version = "5.0.0"
+description = "Python library for Apache Arrow"
+category = "main"
+optional = false
+python-versions = ">=3.6"
+
+[package.dependencies]
+numpy = ">=1.16.6"
+
+[[package]]
+name = "pycparser"
+version = "2.20"
+description = "C parser in Python"
+category = "main"
+optional = false
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
+
+[[package]]
+name = "pyGeoDb"
+version = "1.3"
+description = "distance calculation based on ZIP codes and map generation"
+category = "main"
+optional = false
+python-versions = "*"
+develop = false
+
+[package.source]
+type = "git"
+url = "https://github.com/tkurze/pyGeoDb.git"
+reference = "master"
+resolved_reference = "1407e4836ac58442e4fe0093af146edc82ddd037"
+
+[[package]]
+name = "pygments"
+version = "2.10.0"
+description = "Pygments is a syntax highlighting package written in Python."
+category = "main"
+optional = false
+python-versions = ">=3.5"
+
+[[package]]
+name = "pyparsing"
+version = "2.4.7"
+description = "Python parsing module"
+category = "main"
+optional = false
+python-versions = ">=2.6, !=3.0.*, !=3.1.*, !=3.2.*"
+
+[[package]]
+name = "pyproj"
+version = "3.1.0"
+description = "Python interface to PROJ (cartographic projections and coordinate transformations library)"
+category = "main"
+optional = false
+python-versions = ">=3.7"
+
+[package.dependencies]
+certifi = "*"
+
+[[package]]
+name = "pyrsistent"
+version = "0.18.0"
+description = "Persistent/Functional/Immutable data structures"
+category = "main"
+optional = false
+python-versions = ">=3.6"
+
+[[package]]
+name = "python-dateutil"
+version = "2.8.2"
+description = "Extensions to the standard Python datetime module"
+category = "main"
+optional = false
+python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,>=2.7"
+
+[package.dependencies]
+six = ">=1.5"
+
+[[package]]
+name = "pytz"
+version = "2021.1"
+description = "World timezone definitions, modern and historical"
+category = "main"
+optional = false
+python-versions = "*"
+
+[[package]]
+name = "pywavelets"
+version = "1.1.1"
+description = "PyWavelets, wavelet transform module"
+category = "main"
+optional = false
+python-versions = ">=3.5"
+
+[package.dependencies]
+numpy = ">=1.13.3"
+
+[[package]]
+name = "pywin32"
+version = "301"
+description = "Python for Window Extensions"
+category = "main"
+optional = false
+python-versions = "*"
+
+[[package]]
+name = "pywinpty"
+version = "1.1.3"
+description = "Pseudo terminal support for Windows from Python."
+category = "main"
+optional = false
+python-versions = ">=3.6"
+
+[[package]]
+name = "pyyaml"
+version = "5.4.1"
+description = "YAML parser and emitter for Python"
+category = "main"
+optional = false
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*"
+
+[[package]]
+name = "pyzmq"
+version = "22.2.1"
+description = "Python bindings for 0MQ"
+category = "main"
+optional = false
+python-versions = ">=3.6"
+
+[package.dependencies]
+cffi = {version = "*", markers = "implementation_name == \"pypy\""}
+py = {version = "*", markers = "implementation_name == \"pypy\""}
+
+[[package]]
+name = "qtconsole"
+version = "5.1.1"
+description = "Jupyter Qt console"
+category = "main"
+optional = false
+python-versions = ">= 3.6"
+
+[package.dependencies]
+ipykernel = ">=4.1"
+ipython-genutils = "*"
+jupyter-client = ">=4.1"
+jupyter-core = "*"
+pygments = "*"
+pyzmq = ">=17.1"
+qtpy = "*"
+traitlets = "*"
+
+[package.extras]
+doc = ["Sphinx (>=1.3)"]
+test = ["flaky", "pytest", "pytest-qt"]
+
+[[package]]
+name = "qtpy"
+version = "1.9.0"
+description = "Provides an abstraction layer on top of the various Qt bindings (PyQt5, PyQt4 and PySide) and additional custom QWidgets."
+category = "main"
+optional = false
+python-versions = "*"
+
+[[package]]
+name = "rasterio"
+version = "1.2.6"
+description = "Fast and direct raster I/O for use with Numpy and SciPy"
+category = "main"
+optional = false
+python-versions = ">=3.6"
+
+[package.dependencies]
+affine = "*"
+attrs = "*"
+certifi = "*"
+click = ">=4.0"
+click-plugins = "*"
+cligj = ">=0.5"
+numpy = "*"
+snuggs = ">=1.4.1"
+
+[package.extras]
+all = ["boto3 (>=1.2.4)", "pytest-cov (>=2.2.0)", "hypothesis", "shapely", "numpydoc", "ghp-import", "pytest (>=2.8.2)", "matplotlib", "packaging", "ipython (>=2.0)", "sphinx-rtd-theme", "sphinx"]
+docs = ["ghp-import", "numpydoc", "sphinx", "sphinx-rtd-theme"]
+ipython = ["ipython (>=2.0)"]
+plot = ["matplotlib"]
+s3 = ["boto3 (>=1.2.4)"]
+test = ["boto3 (>=1.2.4)", "hypothesis", "packaging", "pytest-cov (>=2.2.0)", "pytest (>=2.8.2)", "shapely"]
+
+[[package]]
+name = "requests"
+version = "2.26.0"
+description = "Python HTTP for Humans."
+category = "main"
+optional = false
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*"
+
+[package.dependencies]
+certifi = ">=2017.4.17"
+charset-normalizer = {version = ">=2.0.0,<2.1.0", markers = "python_version >= \"3\""}
+idna = {version = ">=2.5,<4", markers = "python_version >= \"3\""}
+urllib3 = ">=1.21.1,<1.27"
+
+[package.extras]
+socks = ["PySocks (>=1.5.6,!=1.5.7)", "win-inet-pton"]
+use_chardet_on_py3 = ["chardet (>=3.0.2,<5)"]
+
+[[package]]
+name = "scikit-image"
+version = "0.18.2"
+description = "Image processing in Python"
+category = "main"
+optional = false
+python-versions = ">=3.7"
+
+[package.dependencies]
+imageio = ">=2.3.0"
+matplotlib = ">=2.0.0,<3.0.0 || >3.0.0"
+networkx = ">=2.0"
+numpy = ">=1.16.5"
+pillow = ">=4.3.0,<7.1.0 || >7.1.0,<7.1.1 || >7.1.1"
+PyWavelets = ">=1.1.1"
+scipy = ">=1.0.1"
+tifffile = ">=2019.7.26"
+
+[package.extras]
+data = ["pooch (>=1.3.0)"]
+docs = ["sphinx (>=1.8,<=2.4.4)", "sphinx-gallery (>=0.7.0,!=0.8.0)", "numpydoc (>=1.0)", "sphinx-copybutton", "pytest-runner", "scikit-learn", "matplotlib (>=3.0.1)", "dask[array] (>=0.15.0,!=2.17.0)", "cloudpickle (>=0.2.1)", "pandas (>=0.23.0)", "seaborn (>=0.7.1)", "pooch (>=1.3.0)", "tifffile (>=2020.5.30)", "myst-parser", "ipywidgets", "plotly (>=4.10.0)"]
+optional = ["simpleitk", "astropy (>=3.1.2)", "qtpy", "pyamg", "dask[array] (>=1.0.0,!=2.17.0)", "cloudpickle (>=0.2.1)", "pooch (>=1.3.0)"]
+test = ["pytest (>=5.2.0)", "pytest-cov (>=2.7.0)", "pytest-localserver", "pytest-faulthandler", "flake8", "codecov", "pooch (>=1.3.0)"]
+
+[[package]]
+name = "scipy"
+version = "1.6.1"
+description = "SciPy: Scientific Library for Python"
+category = "main"
+optional = false
+python-versions = ">=3.7"
+
+[package.dependencies]
+numpy = ">=1.16.5"
+
+[[package]]
+name = "seaborn"
+version = "0.11.2"
+description = "seaborn: statistical data visualization"
+category = "main"
+optional = false
+python-versions = ">=3.6"
+
+[package.dependencies]
+matplotlib = ">=2.2"
+numpy = ">=1.15"
+pandas = ">=0.23"
+scipy = ">=1.0"
+
+[[package]]
+name = "send2trash"
+version = "1.8.0"
+description = "Send file to trash natively under Mac OS X, Windows and Linux."
+category = "main"
+optional = false
+python-versions = "*"
+
+[package.extras]
+nativelib = ["pyobjc-framework-cocoa", "pywin32"]
+objc = ["pyobjc-framework-cocoa"]
+win32 = ["pywin32"]
+
+[[package]]
+name = "shapely"
+version = "1.7.1"
+description = "Geometric objects, predicates, and operations"
+category = "main"
+optional = false
+python-versions = "*"
+
+[package.extras]
+all = ["numpy", "pytest", "pytest-cov"]
+test = ["pytest", "pytest-cov"]
+vectorized = ["numpy"]
+
+[[package]]
+name = "six"
+version = "1.16.0"
+description = "Python 2 and 3 compatibility utilities"
+category = "main"
+optional = false
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*"
+
+[[package]]
+name = "snuggs"
+version = "1.4.7"
+description = "Snuggs are s-expressions for Numpy"
+category = "main"
+optional = false
+python-versions = "*"
+
+[package.dependencies]
+numpy = "*"
+pyparsing = ">=2.1.6"
+
+[package.extras]
+test = ["pytest", "hypothesis"]
+
+[[package]]
+name = "terminado"
+version = "0.11.0"
+description = "Tornado websocket backend for the Xterm.js Javascript terminal emulator library."
+category = "main"
+optional = false
+python-versions = ">=3.6"
+
+[package.dependencies]
+ptyprocess = {version = "*", markers = "os_name != \"nt\""}
+pywinpty = {version = ">=1.1.0", markers = "os_name == \"nt\""}
+tornado = ">=4"
+
+[package.extras]
+test = ["pytest"]
+
+[[package]]
+name = "testpath"
+version = "0.5.0"
+description = "Test utilities for code working with files and commands"
+category = "main"
+optional = false
+python-versions = ">= 3.5"
+
+[package.extras]
+test = ["pytest", "pathlib2"]
+
+[[package]]
+name = "tifffile"
+version = "2021.8.8"
+description = "Read and write TIFF files"
+category = "main"
+optional = false
+python-versions = ">=3.7"
+
+[package.dependencies]
+numpy = ">=1.15.1"
+
+[package.extras]
+all = ["imagecodecs (>=2021.7.30)", "matplotlib (>=3.2)", "lxml"]
+
+[[package]]
+name = "tornado"
+version = "6.1"
+description = "Tornado is a Python web framework and asynchronous networking library, originally developed at FriendFeed."
+category = "main"
+optional = false
+python-versions = ">= 3.5"
+
+[[package]]
+name = "traitlets"
+version = "5.0.5"
+description = "Traitlets Python configuration system"
+category = "main"
+optional = false
+python-versions = ">=3.7"
+
+[package.dependencies]
+ipython-genutils = "*"
+
+[package.extras]
+test = ["pytest"]
+
+[[package]]
+name = "urllib3"
+version = "1.26.6"
+description = "HTTP library with thread-safe connection pooling, file post, and more."
+category = "main"
+optional = false
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, <4"
+
+[package.extras]
+brotli = ["brotlipy (>=0.6.0)"]
+secure = ["pyOpenSSL (>=0.14)", "cryptography (>=1.3.4)", "idna (>=2.0.0)", "certifi", "ipaddress"]
+socks = ["PySocks (>=1.5.6,!=1.5.7,<2.0)"]
+
+[[package]]
+name = "wcwidth"
+version = "0.2.5"
+description = "Measures the displayed width of unicode strings in a terminal"
+category = "main"
+optional = false
+python-versions = "*"
+
+[[package]]
+name = "webencodings"
+version = "0.5.1"
+description = "Character encoding aliases for legacy web content"
+category = "main"
+optional = false
+python-versions = "*"
+
+[[package]]
+name = "widgetsnbextension"
+version = "3.5.1"
+description = "IPython HTML widgets for Jupyter"
+category = "main"
+optional = false
+python-versions = "*"
+
+[package.dependencies]
+notebook = ">=4.4.1"
+
+[[package]]
+name = "win32-setctime"
+version = "1.0.3"
+description = "A small Python utility to set file creation time on Windows"
+category = "main"
+optional = false
+python-versions = ">=3.5"
+
+[package.extras]
+dev = ["pytest (>=4.6.2)", "black (>=19.3b0)"]
+
+[metadata]
+lock-version = "1.1"
+python-versions = "^3.9"
+content-hash = "29337bf3f996991f3f4f28f5b18a556caf6c30b45c601fc7f7c87de05056efdb"
+
+[metadata.files]
+affine = [
+    {file = "affine-2.3.0-py2.py3-none-any.whl", hash = "sha256:34b05b070d954c382e56f02c207a372d8a32621a87653cc30cdd31cd7f65799f"},
+    {file = "affine-2.3.0.tar.gz", hash = "sha256:2e045def1aa29e613c42e801a7e10e0b9bacfed1a7c6af0cadf8843530a15102"},
+]
+appnope = [
+    {file = "appnope-0.1.2-py2.py3-none-any.whl", hash = "sha256:93aa393e9d6c54c5cd570ccadd8edad61ea0c4b9ea7a01409020c9aa019eb442"},
+    {file = "appnope-0.1.2.tar.gz", hash = "sha256:dd83cd4b5b460958838f6eb3000c660b1f9caf2a5b1de4264e941512f603258a"},
+]
+argon2-cffi = [
+    {file = "argon2-cffi-20.1.0.tar.gz", hash = "sha256:d8029b2d3e4b4cea770e9e5a0104dd8fa185c1724a0f01528ae4826a6d25f97d"},
+    {file = "argon2_cffi-20.1.0-cp27-cp27m-macosx_10_6_intel.whl", hash = "sha256:6ea92c980586931a816d61e4faf6c192b4abce89aa767ff6581e6ddc985ed003"},
+    {file = "argon2_cffi-20.1.0-cp27-cp27m-manylinux1_x86_64.whl", hash = "sha256:05a8ac07c7026542377e38389638a8a1e9b78f1cd8439cd7493b39f08dd75fbf"},
+    {file = "argon2_cffi-20.1.0-cp27-cp27m-win32.whl", hash = "sha256:0bf066bc049332489bb2d75f69216416329d9dc65deee127152caeb16e5ce7d5"},
+    {file = "argon2_cffi-20.1.0-cp27-cp27m-win_amd64.whl", hash = "sha256:57358570592c46c420300ec94f2ff3b32cbccd10d38bdc12dc6979c4a8484fbc"},
+    {file = "argon2_cffi-20.1.0-cp27-cp27mu-manylinux1_x86_64.whl", hash = "sha256:7d455c802727710e9dfa69b74ccaab04568386ca17b0ad36350b622cd34606fe"},
+    {file = "argon2_cffi-20.1.0-cp35-abi3-manylinux1_x86_64.whl", hash = "sha256:b160416adc0f012fb1f12588a5e6954889510f82f698e23ed4f4fa57f12a0647"},
+    {file = "argon2_cffi-20.1.0-cp35-cp35m-win32.whl", hash = "sha256:9bee3212ba4f560af397b6d7146848c32a800652301843df06b9e8f68f0f7361"},
+    {file = "argon2_cffi-20.1.0-cp35-cp35m-win_amd64.whl", hash = "sha256:392c3c2ef91d12da510cfb6f9bae52512a4552573a9e27600bdb800e05905d2b"},
+    {file = "argon2_cffi-20.1.0-cp36-cp36m-win32.whl", hash = "sha256:ba7209b608945b889457f949cc04c8e762bed4fe3fec88ae9a6b7765ae82e496"},
+    {file = "argon2_cffi-20.1.0-cp36-cp36m-win_amd64.whl", hash = "sha256:da7f0445b71db6d3a72462e04f36544b0de871289b0bc8a7cc87c0f5ec7079fa"},
+    {file = "argon2_cffi-20.1.0-cp37-abi3-macosx_10_6_intel.whl", hash = "sha256:cc0e028b209a5483b6846053d5fd7165f460a1f14774d79e632e75e7ae64b82b"},
+    {file = "argon2_cffi-20.1.0-cp37-cp37m-win32.whl", hash = "sha256:18dee20e25e4be86680b178b35ccfc5d495ebd5792cd00781548d50880fee5c5"},
+    {file = "argon2_cffi-20.1.0-cp37-cp37m-win_amd64.whl", hash = "sha256:6678bb047373f52bcff02db8afab0d2a77d83bde61cfecea7c5c62e2335cb203"},
+    {file = "argon2_cffi-20.1.0-cp38-cp38-win32.whl", hash = "sha256:77e909cc756ef81d6abb60524d259d959bab384832f0c651ed7dcb6e5ccdbb78"},
+    {file = "argon2_cffi-20.1.0-cp38-cp38-win_amd64.whl", hash = "sha256:9dfd5197852530294ecb5795c97a823839258dfd5eb9420233c7cfedec2058f2"},
+    {file = "argon2_cffi-20.1.0-cp39-cp39-win32.whl", hash = "sha256:e2db6e85c057c16d0bd3b4d2b04f270a7467c147381e8fd73cbbe5bc719832be"},
+    {file = "argon2_cffi-20.1.0-cp39-cp39-win_amd64.whl", hash = "sha256:8a84934bd818e14a17943de8099d41160da4a336bcc699bb4c394bbb9b94bd32"},
+    {file = "argon2_cffi-20.1.0-pp36-pypy36_pp73-macosx_10_7_x86_64.whl", hash = "sha256:b94042e5dcaa5d08cf104a54bfae614be502c6f44c9c89ad1535b2ebdaacbd4c"},
+    {file = "argon2_cffi-20.1.0-pp36-pypy36_pp73-win32.whl", hash = "sha256:8282b84ceb46b5b75c3a882b28856b8cd7e647ac71995e71b6705ec06fc232c3"},
+    {file = "argon2_cffi-20.1.0-pp37-pypy37_pp73-macosx_10_7_x86_64.whl", hash = "sha256:3aa804c0e52f208973845e8b10c70d8957c9e5a666f702793256242e9167c4e0"},
+    {file = "argon2_cffi-20.1.0-pp37-pypy37_pp73-win_amd64.whl", hash = "sha256:36320372133a003374ef4275fbfce78b7ab581440dfca9f9471be3dd9a522428"},
+]
+attrs = [
+    {file = "attrs-21.2.0-py2.py3-none-any.whl", hash = "sha256:149e90d6d8ac20db7a955ad60cf0e6881a3f20d37096140088356da6c716b0b1"},
+    {file = "attrs-21.2.0.tar.gz", hash = "sha256:ef6aaac3ca6cd92904cdd0d83f629a15f18053ec84e6432106f7a4d04ae4f5fb"},
+]
+backcall = [
+    {file = "backcall-0.2.0-py2.py3-none-any.whl", hash = "sha256:fbbce6a29f263178a1f7915c1940bde0ec2b2a967566fe1c65c1dfb7422bd255"},
+    {file = "backcall-0.2.0.tar.gz", hash = "sha256:5cbdbf27be5e7cfadb448baf0aa95508f91f2bbc6c6437cd9cd06e2a4c215e1e"},
+]
+bleach = [
+    {file = "bleach-4.0.0-py2.py3-none-any.whl", hash = "sha256:c1685a132e6a9a38bf93752e5faab33a9517a6c0bb2f37b785e47bf253bdb51d"},
+    {file = "bleach-4.0.0.tar.gz", hash = "sha256:ffa9221c6ac29399cc50fcc33473366edd0cf8d5e2cbbbb63296dc327fb67cc8"},
+]
+certifi = [
+    {file = "certifi-2021.5.30-py2.py3-none-any.whl", hash = "sha256:50b1e4f8446b06f41be7dd6338db18e0990601dce795c2b1686458aa7e8fa7d8"},
+    {file = "certifi-2021.5.30.tar.gz", hash = "sha256:2bbf76fd432960138b3ef6dda3dde0544f27cbf8546c458e60baf371917ba9ee"},
+]
+cffi = [
+    {file = "cffi-1.14.6-cp27-cp27m-macosx_10_9_x86_64.whl", hash = "sha256:22b9c3c320171c108e903d61a3723b51e37aaa8c81255b5e7ce102775bd01e2c"},
+    {file = "cffi-1.14.6-cp27-cp27m-manylinux1_i686.whl", hash = "sha256:f0c5d1acbfca6ebdd6b1e3eded8d261affb6ddcf2186205518f1428b8569bb99"},
+    {file = "cffi-1.14.6-cp27-cp27m-manylinux1_x86_64.whl", hash = "sha256:99f27fefe34c37ba9875f224a8f36e31d744d8083e00f520f133cab79ad5e819"},
+    {file = "cffi-1.14.6-cp27-cp27m-win32.whl", hash = "sha256:55af55e32ae468e9946f741a5d51f9896da6b9bf0bbdd326843fec05c730eb20"},
+    {file = "cffi-1.14.6-cp27-cp27m-win_amd64.whl", hash = "sha256:7bcac9a2b4fdbed2c16fa5681356d7121ecabf041f18d97ed5b8e0dd38a80224"},
+    {file = "cffi-1.14.6-cp27-cp27mu-manylinux1_i686.whl", hash = "sha256:ed38b924ce794e505647f7c331b22a693bee1538fdf46b0222c4717b42f744e7"},
+    {file = "cffi-1.14.6-cp27-cp27mu-manylinux1_x86_64.whl", hash = "sha256:e22dcb48709fc51a7b58a927391b23ab37eb3737a98ac4338e2448bef8559b33"},
+    {file = "cffi-1.14.6-cp35-cp35m-macosx_10_9_x86_64.whl", hash = "sha256:aedb15f0a5a5949ecb129a82b72b19df97bbbca024081ed2ef88bd5c0a610534"},
+    {file = "cffi-1.14.6-cp35-cp35m-manylinux1_i686.whl", hash = "sha256:48916e459c54c4a70e52745639f1db524542140433599e13911b2f329834276a"},
+    {file = "cffi-1.14.6-cp35-cp35m-manylinux1_x86_64.whl", hash = "sha256:f627688813d0a4140153ff532537fbe4afea5a3dffce1f9deb7f91f848a832b5"},
+    {file = "cffi-1.14.6-cp35-cp35m-win32.whl", hash = "sha256:f0010c6f9d1a4011e429109fda55a225921e3206e7f62a0c22a35344bfd13cca"},
+    {file = "cffi-1.14.6-cp35-cp35m-win_amd64.whl", hash = "sha256:57e555a9feb4a8460415f1aac331a2dc833b1115284f7ded7278b54afc5bd218"},
+    {file = "cffi-1.14.6-cp36-cp36m-macosx_10_9_x86_64.whl", hash = "sha256:e8c6a99be100371dbb046880e7a282152aa5d6127ae01783e37662ef73850d8f"},
+    {file = "cffi-1.14.6-cp36-cp36m-manylinux1_i686.whl", hash = "sha256:19ca0dbdeda3b2615421d54bef8985f72af6e0c47082a8d26122adac81a95872"},
+    {file = "cffi-1.14.6-cp36-cp36m-manylinux1_x86_64.whl", hash = "sha256:d950695ae4381ecd856bcaf2b1e866720e4ab9a1498cba61c602e56630ca7195"},
+    {file = "cffi-1.14.6-cp36-cp36m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e9dc245e3ac69c92ee4c167fbdd7428ec1956d4e754223124991ef29eb57a09d"},
+    {file = "cffi-1.14.6-cp36-cp36m-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:a8661b2ce9694ca01c529bfa204dbb144b275a31685a075ce123f12331be790b"},
+    {file = "cffi-1.14.6-cp36-cp36m-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:b315d709717a99f4b27b59b021e6207c64620790ca3e0bde636a6c7f14618abb"},
+    {file = "cffi-1.14.6-cp36-cp36m-win32.whl", hash = "sha256:80b06212075346b5546b0417b9f2bf467fea3bfe7352f781ffc05a8ab24ba14a"},
+    {file = "cffi-1.14.6-cp36-cp36m-win_amd64.whl", hash = "sha256:a9da7010cec5a12193d1af9872a00888f396aba3dc79186604a09ea3ee7c029e"},
+    {file = "cffi-1.14.6-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:4373612d59c404baeb7cbd788a18b2b2a8331abcc84c3ba40051fcd18b17a4d5"},
+    {file = "cffi-1.14.6-cp37-cp37m-manylinux1_i686.whl", hash = "sha256:f10afb1004f102c7868ebfe91c28f4a712227fe4cb24974350ace1f90e1febbf"},
+    {file = "cffi-1.14.6-cp37-cp37m-manylinux1_x86_64.whl", hash = "sha256:fd4305f86f53dfd8cd3522269ed7fc34856a8ee3709a5e28b2836b2db9d4cd69"},
+    {file = "cffi-1.14.6-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:6d6169cb3c6c2ad50db5b868db6491a790300ade1ed5d1da29289d73bbe40b56"},
+    {file = "cffi-1.14.6-cp37-cp37m-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:5d4b68e216fc65e9fe4f524c177b54964af043dde734807586cf5435af84045c"},
+    {file = "cffi-1.14.6-cp37-cp37m-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:33791e8a2dc2953f28b8d8d300dde42dd929ac28f974c4b4c6272cb2955cb762"},
+    {file = "cffi-1.14.6-cp37-cp37m-win32.whl", hash = "sha256:0c0591bee64e438883b0c92a7bed78f6290d40bf02e54c5bf0978eaf36061771"},
+    {file = "cffi-1.14.6-cp37-cp37m-win_amd64.whl", hash = "sha256:8eb687582ed7cd8c4bdbff3df6c0da443eb89c3c72e6e5dcdd9c81729712791a"},
+    {file = "cffi-1.14.6-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:ba6f2b3f452e150945d58f4badd92310449876c4c954836cfb1803bdd7b422f0"},
+    {file = "cffi-1.14.6-cp38-cp38-manylinux1_i686.whl", hash = "sha256:64fda793737bc4037521d4899be780534b9aea552eb673b9833b01f945904c2e"},
+    {file = "cffi-1.14.6-cp38-cp38-manylinux1_x86_64.whl", hash = "sha256:9f3e33c28cd39d1b655ed1ba7247133b6f7fc16fa16887b120c0c670e35ce346"},
+    {file = "cffi-1.14.6-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:26bb2549b72708c833f5abe62b756176022a7b9a7f689b571e74c8478ead51dc"},
+    {file = "cffi-1.14.6-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:eb687a11f0a7a1839719edd80f41e459cc5366857ecbed383ff376c4e3cc6afd"},
+    {file = "cffi-1.14.6-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:d2ad4d668a5c0645d281dcd17aff2be3212bc109b33814bbb15c4939f44181cc"},
+    {file = "cffi-1.14.6-cp38-cp38-win32.whl", hash = "sha256:487d63e1454627c8e47dd230025780e91869cfba4c753a74fda196a1f6ad6548"},
+    {file = "cffi-1.14.6-cp38-cp38-win_amd64.whl", hash = "sha256:c33d18eb6e6bc36f09d793c0dc58b0211fccc6ae5149b808da4a62660678b156"},
+    {file = "cffi-1.14.6-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:06c54a68935738d206570b20da5ef2b6b6d92b38ef3ec45c5422c0ebaf338d4d"},
+    {file = "cffi-1.14.6-cp39-cp39-manylinux1_i686.whl", hash = "sha256:f174135f5609428cc6e1b9090f9268f5c8935fddb1b25ccb8255a2d50de6789e"},
+    {file = "cffi-1.14.6-cp39-cp39-manylinux1_x86_64.whl", hash = "sha256:f3ebe6e73c319340830a9b2825d32eb6d8475c1dac020b4f0aa774ee3b898d1c"},
+    {file = "cffi-1.14.6-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:3c8d896becff2fa653dc4438b54a5a25a971d1f4110b32bd3068db3722c80202"},
+    {file = "cffi-1.14.6-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:4922cd707b25e623b902c86188aca466d3620892db76c0bdd7b99a3d5e61d35f"},
+    {file = "cffi-1.14.6-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:c9e005e9bd57bc987764c32a1bee4364c44fdc11a3cc20a40b93b444984f2b87"},
+    {file = "cffi-1.14.6-cp39-cp39-win32.whl", hash = "sha256:eb9e2a346c5238a30a746893f23a9535e700f8192a68c07c0258e7ece6ff3728"},
+    {file = "cffi-1.14.6-cp39-cp39-win_amd64.whl", hash = "sha256:818014c754cd3dba7229c0f5884396264d51ffb87ec86e927ef0be140bfdb0d2"},
+    {file = "cffi-1.14.6.tar.gz", hash = "sha256:c9a875ce9d7fe32887784274dd533c57909b7b1dcadcc128a2ac21331a9765dd"},
+]
+charset-normalizer = [
+    {file = "charset-normalizer-2.0.4.tar.gz", hash = "sha256:f23667ebe1084be45f6ae0538e4a5a865206544097e4e8bbcacf42cd02a348f3"},
+    {file = "charset_normalizer-2.0.4-py3-none-any.whl", hash = "sha256:0c8911edd15d19223366a194a513099a302055a962bca2cec0f54b8b63175d8b"},
+]
+click = [
+    {file = "click-8.0.1-py3-none-any.whl", hash = "sha256:fba402a4a47334742d782209a7c79bc448911afe1149d07bdabdf480b3e2f4b6"},
+    {file = "click-8.0.1.tar.gz", hash = "sha256:8c04c11192119b1ef78ea049e0a6f0463e4c48ef00a30160c704337586f3ad7a"},
+]
+click-plugins = [
+    {file = "click-plugins-1.1.1.tar.gz", hash = "sha256:46ab999744a9d831159c3411bb0c79346d94a444df9a3a3742e9ed63645f264b"},
+    {file = "click_plugins-1.1.1-py2.py3-none-any.whl", hash = "sha256:5d262006d3222f5057fd81e1623d4443e41dcda5dc815c06b442aa3c02889fc8"},
+]
+cligj = [
+    {file = "cligj-0.7.2-py3-none-any.whl", hash = "sha256:c1ca117dbce1fe20a5809dc96f01e1c2840f6dcc939b3ddbb1111bf330ba82df"},
+    {file = "cligj-0.7.2.tar.gz", hash = "sha256:a4bc13d623356b373c2c27c53dbd9c68cae5d526270bfa71f6c6fa69669c6b27"},
+]
+colorama = [
+    {file = "colorama-0.4.4-py2.py3-none-any.whl", hash = "sha256:9f47eda37229f68eee03b24b9748937c7dc3868f906e8ba69fbcbdd3bc5dc3e2"},
+    {file = "colorama-0.4.4.tar.gz", hash = "sha256:5941b2b48a20143d2267e95b1c2a7603ce057ee39fd88e7329b0c292aa16869b"},
+]
+cycler = [
+    {file = "cycler-0.10.0-py2.py3-none-any.whl", hash = "sha256:1d8a5ae1ff6c5cf9b93e8811e581232ad8920aeec647c37316ceac982b08cb2d"},
+    {file = "cycler-0.10.0.tar.gz", hash = "sha256:cd7b2d1018258d7247a71425e9f26463dfb444d411c39569972f4ce586b0c9d8"},
+]
+debugpy = [
+    {file = "debugpy-1.4.1-cp27-cp27m-macosx_10_14_x86_64.whl", hash = "sha256:a2c5a1c49239707ed5bc8e97d8f9252fb392d9e13c79c7b477593d7dde4ae24a"},
+    {file = "debugpy-1.4.1-cp27-cp27m-manylinux1_i686.whl", hash = "sha256:ebc241351791595796864a960892e1cd58627064feda939d0377edd0730bbff2"},
+    {file = "debugpy-1.4.1-cp27-cp27m-manylinux1_x86_64.whl", hash = "sha256:939c94d516e6ed5433cc3ba12d9d0d8108499587158ae5f76f6db18d49e21b5b"},
+    {file = "debugpy-1.4.1-cp27-cp27m-manylinux2010_i686.whl", hash = "sha256:e47c42bc1a68ead3c39d9a658d3ccf311bc45dc84f3c90fa5cb7de1796243f47"},
+    {file = "debugpy-1.4.1-cp27-cp27m-manylinux2010_x86_64.whl", hash = "sha256:3756cd421be701d06490635372327ebd1ccb44b37d59682c994f6bd59e040a91"},
+    {file = "debugpy-1.4.1-cp27-cp27mu-manylinux1_i686.whl", hash = "sha256:a4368c79a2c4458d5a0540381a32f8fdc02b3c9ba9dd413a49b42929297b29b3"},
+    {file = "debugpy-1.4.1-cp27-cp27mu-manylinux1_x86_64.whl", hash = "sha256:c96e82d863db97d3eb498cc8e55773004724bdeaa58fb0eb7ee7d5a21d240d6a"},
+    {file = "debugpy-1.4.1-cp27-cp27mu-manylinux2010_i686.whl", hash = "sha256:71e67d352cabdc6a3f4dc3e39a1d2d1e76763a2102a276904e3495ede48a9832"},
+    {file = "debugpy-1.4.1-cp27-cp27mu-manylinux2010_x86_64.whl", hash = "sha256:959d39f3d724d25b7ab79278f032e33df03c6376d51b3517abaf2f8e83594ee0"},
+    {file = "debugpy-1.4.1-cp35-cp35m-macosx_10_14_x86_64.whl", hash = "sha256:9d559bd0e4c288487349e0723bc70ff06390638446ee8087d4d5711486119643"},
+    {file = "debugpy-1.4.1-cp35-cp35m-manylinux1_i686.whl", hash = "sha256:7376bd8f4272ab01342940bd020955f021e26954e1f0df91cfa8bf1fa4451b56"},
+    {file = "debugpy-1.4.1-cp35-cp35m-manylinux1_x86_64.whl", hash = "sha256:dea62527a4a2770a0d12ce46564636d892bba29baaf5dba5bfe98bb55bf17a11"},
+    {file = "debugpy-1.4.1-cp35-cp35m-manylinux2010_i686.whl", hash = "sha256:12cb415e7394c6738527cbc482935aa9414e9b4cc87dd040015d0e5cb8b4471a"},
+    {file = "debugpy-1.4.1-cp35-cp35m-manylinux2010_x86_64.whl", hash = "sha256:3a6dee475102d0169732162b735878e8787500719ccb4d54b1458afe992a4c4d"},
+    {file = "debugpy-1.4.1-cp35-cp35m-manylinux2014_i686.whl", hash = "sha256:7e12e94aa2c9a0017c0a84cd475063108d06e305360b69c933bde17a6a527f80"},
+    {file = "debugpy-1.4.1-cp35-cp35m-manylinux2014_x86_64.whl", hash = "sha256:2bfda2721046fb43a7074d475a12adcd55a65bfd23a1ff675427b09a01ba40cc"},
+    {file = "debugpy-1.4.1-cp35-cp35m-win32.whl", hash = "sha256:732ac8bb79694cb4127c08bfc6128274f3dee9e6fd2ddde7bf026a40efeb202d"},
+    {file = "debugpy-1.4.1-cp35-cp35m-win_amd64.whl", hash = "sha256:bad668e9edb21199017ab31f52a05e14506ad6566110560796d2a8f258e0b819"},
+    {file = "debugpy-1.4.1-cp36-cp36m-macosx_10_14_x86_64.whl", hash = "sha256:cd36e75c0f71a924f4b4cdb5f74b3321952cf636aadf70e0f85fd9cd2edfc1d0"},
+    {file = "debugpy-1.4.1-cp36-cp36m-manylinux1_i686.whl", hash = "sha256:eee2224ce547d2958ffc0d63cd280a9cc6377043f32ce370cfe4ca6be4e05476"},
+    {file = "debugpy-1.4.1-cp36-cp36m-manylinux1_x86_64.whl", hash = "sha256:e6711106aafc26ecb78e43c4be0a49bd0ae4a1f3e1aa502de151e38f4717b2a2"},
+    {file = "debugpy-1.4.1-cp36-cp36m-manylinux2010_i686.whl", hash = "sha256:768f393ffaa66a3b3ed92b06e21912a5df3e01f18fb531bcbba2f94cad1725a7"},
+    {file = "debugpy-1.4.1-cp36-cp36m-manylinux2010_x86_64.whl", hash = "sha256:ab37f189b1dd0d8420545c9f3d066bd1601a1ae85b26de38f5c1ccb96cf0b042"},
+    {file = "debugpy-1.4.1-cp36-cp36m-manylinux2014_i686.whl", hash = "sha256:00f9d14da52b87e98e26f5c3c8f1937cc496915b38f8ccb7b329336b21898678"},
+    {file = "debugpy-1.4.1-cp36-cp36m-manylinux2014_x86_64.whl", hash = "sha256:1bc8e835a48ef23280cbaf2b70a5a2b629b9ee79685b64d974bfb8d467f4aa67"},
+    {file = "debugpy-1.4.1-cp36-cp36m-win32.whl", hash = "sha256:309909b6c85f89aea3fa10fc256b52fef3c25fee4d00e1b5f5db1ace57203a2c"},
+    {file = "debugpy-1.4.1-cp36-cp36m-win_amd64.whl", hash = "sha256:67d496890d1cada5ce924cb30178684e7b82a36b80b8868beb148db54fd9e44c"},
+    {file = "debugpy-1.4.1-cp37-cp37m-macosx_10_14_x86_64.whl", hash = "sha256:595170ac17567773b546d40a0ff002dc350cfcd95c9233f65e79370954fb9a01"},
+    {file = "debugpy-1.4.1-cp37-cp37m-manylinux1_i686.whl", hash = "sha256:c5e771fcd12727f734caf2a10ff92966ae9857db0ccb6bebd1a4f776c54186a8"},
+    {file = "debugpy-1.4.1-cp37-cp37m-manylinux1_x86_64.whl", hash = "sha256:2d4c4ab934fbe1c7095d19b3d4246afe119396b49540ca5d5ad34ef01b27bd2a"},
+    {file = "debugpy-1.4.1-cp37-cp37m-manylinux2010_i686.whl", hash = "sha256:4655824321b36b353b12d1617a29c79320412f085ecabf54524603b4c0c791e8"},
+    {file = "debugpy-1.4.1-cp37-cp37m-manylinux2010_x86_64.whl", hash = "sha256:399b2c60c8e67a5d30c6e4522129e8be8d484e6064286f8ba3ce857a3927312a"},
+    {file = "debugpy-1.4.1-cp37-cp37m-manylinux2014_i686.whl", hash = "sha256:8e63585c372873cd88c2380c0b3c4815c724a9713f5b86d1b3a1f1ac30df079e"},
+    {file = "debugpy-1.4.1-cp37-cp37m-manylinux2014_x86_64.whl", hash = "sha256:52920ccb4acdbb2a9a42e0a4d60a7bbc4a34bf16fd23c674b280f8e9a8cacbd6"},
+    {file = "debugpy-1.4.1-cp37-cp37m-win32.whl", hash = "sha256:7b332ce0d1a46f0f4200d59ee78428f18301d1fb85d07402723b94e1de96951c"},
+    {file = "debugpy-1.4.1-cp37-cp37m-win_amd64.whl", hash = "sha256:a19def91a0a166877c2a26b611c1ad0473ce85b1df61ae5276197375d574228b"},
+    {file = "debugpy-1.4.1-cp38-cp38-macosx_10_14_x86_64.whl", hash = "sha256:9a0cd73d7a76222fbc9f9180612ccb4ad7d7f7e4f26e55ef1fbd459c0f2f5322"},
+    {file = "debugpy-1.4.1-cp38-cp38-manylinux1_i686.whl", hash = "sha256:86cd13162b752664e8ef048287a6973c8fba0a71f396b31cf36394880ec2a6bf"},
+    {file = "debugpy-1.4.1-cp38-cp38-manylinux1_x86_64.whl", hash = "sha256:89d53d57001e54a3854489e898c697aafb2d6bb81fca596da2400f3fd7fd397c"},
+    {file = "debugpy-1.4.1-cp38-cp38-manylinux2010_i686.whl", hash = "sha256:7b4e399790a301c83ad6b153452233695b2f15450d78956a6d297859eb44d185"},
+    {file = "debugpy-1.4.1-cp38-cp38-manylinux2010_x86_64.whl", hash = "sha256:fece69933d17e0918b73ddeb5e23bcf789edd2a6eb0d438b09c40d51e76b9c74"},
+    {file = "debugpy-1.4.1-cp38-cp38-manylinux2014_i686.whl", hash = "sha256:4e0d57a8c35b20b4e363db943b909aa83f12594e2f34070a1db5fa9b7213336b"},
+    {file = "debugpy-1.4.1-cp38-cp38-manylinux2014_x86_64.whl", hash = "sha256:f77406f33760e6f13a7ff0ac375d9c8856844b61cd95f7502b57116858f0cfe1"},
+    {file = "debugpy-1.4.1-cp38-cp38-win32.whl", hash = "sha256:3d92cb2e8b4f9591f6d6e17ccf8c1a55a58857949d9a5aae0ff37b64faaa3b80"},
+    {file = "debugpy-1.4.1-cp38-cp38-win_amd64.whl", hash = "sha256:ac2d1cdd3279806dab2119937c0769f11dee13166650aaa84b6700b30a845d10"},
+    {file = "debugpy-1.4.1-cp39-cp39-macosx_10_14_x86_64.whl", hash = "sha256:e7e049a4e8e362183a5a5b4ad058a1543211970819d0c11011c87c3a9dec2eaf"},
+    {file = "debugpy-1.4.1-cp39-cp39-manylinux1_i686.whl", hash = "sha256:cf6b26f26f97ef3033008db7b3df7233363407d7b6cacd4bc4f8e02ce8e11df4"},
+    {file = "debugpy-1.4.1-cp39-cp39-manylinux1_x86_64.whl", hash = "sha256:8a2be4e5d696ad39be6c6c37dc580993d04aad7d893fd6e449e1a055d7b5dddb"},
+    {file = "debugpy-1.4.1-cp39-cp39-manylinux2010_i686.whl", hash = "sha256:d89ab3bd51d6a3f13b093bc3881a827d8f6c9588d9a493bddb3b47f9d078fd1d"},
+    {file = "debugpy-1.4.1-cp39-cp39-manylinux2010_x86_64.whl", hash = "sha256:f20a07ac5fb0deee9be1ad1a9a124d858a8b79c66c7ec5e1767d78aa964f86c4"},
+    {file = "debugpy-1.4.1-cp39-cp39-manylinux2014_i686.whl", hash = "sha256:6bb62615b3ad3d7202b7b7eb85f3d000aa17a61303af5f11eab048c91a1f30a6"},
+    {file = "debugpy-1.4.1-cp39-cp39-manylinux2014_x86_64.whl", hash = "sha256:a9f582203af34c6978bffaba77425662e949251998276e9dece113862e753459"},
+    {file = "debugpy-1.4.1-cp39-cp39-win32.whl", hash = "sha256:129312b01ec46ab303a8c0667d559a0de0bed1a394cc128039b6f008f1c376b7"},
+    {file = "debugpy-1.4.1-cp39-cp39-win_amd64.whl", hash = "sha256:1762908202b0b0b481ec44125edb625d136d16c4991d3a7c1310c85672ffe5ba"},
+    {file = "debugpy-1.4.1-py2.py3-none-any.whl", hash = "sha256:84ff51b8b5c847d5421324ca419db1eec813a4dd2bbf19dbbbe132e2ab2b2fc6"},
+    {file = "debugpy-1.4.1.zip", hash = "sha256:889316de0b8ff3732927cb058cfbd3371e4cd0002ecc170d34c755ad289c867c"},
+]
+decorator = [
+    {file = "decorator-5.0.9-py3-none-any.whl", hash = "sha256:6e5c199c16f7a9f0e3a61a4a54b3d27e7dad0dbdde92b944426cb20914376323"},
+    {file = "decorator-5.0.9.tar.gz", hash = "sha256:72ecfba4320a893c53f9706bebb2d55c270c1e51a28789361aa93e4a21319ed5"},
+]
+defusedxml = [
+    {file = "defusedxml-0.7.1-py2.py3-none-any.whl", hash = "sha256:a352e7e428770286cc899e2542b6cdaedb2b4953ff269a210103ec58f6198a61"},
+    {file = "defusedxml-0.7.1.tar.gz", hash = "sha256:1bb3032db185915b62d7c6209c5a8792be6a32ab2fedacc84e01b52c51aa3e69"},
+]
+earthpy = [
+    {file = "earthpy-0.9.2.tar.gz", hash = "sha256:efe71076edcbfe2c179687e9a7fa315a6cf43b1a9690e23f75e72d92ca09d9ab"},
+]
+entrypoints = [
+    {file = "entrypoints-0.3-py2.py3-none-any.whl", hash = "sha256:589f874b313739ad35be6e0cd7efde2a4e9b6fea91edcc34e58ecbb8dbe56d19"},
+    {file = "entrypoints-0.3.tar.gz", hash = "sha256:c70dd71abe5a8c85e55e12c19bd91ccfeec11a6e99044204511f9ed547d48451"},
+]
+feather-format = [
+    {file = "feather-format-0.4.1.tar.gz", hash = "sha256:45f67e3745d394d4f160ca6d636bbfd4f8b68d01199dc1649b6e487d3e878903"},
+]
+fiona = [
+    {file = "Fiona-1.8.20-cp36-cp36m-macosx_10_9_x86_64.whl", hash = "sha256:02880556540e36ad6aac97687799d9b3093c354787a47bc0e73026c7fc15f1b3"},
+    {file = "Fiona-1.8.20-cp36-cp36m-manylinux_2_5_x86_64.manylinux1_x86_64.whl", hash = "sha256:3f668c471fa2f8c9c0a9ca83639cb2c8dcc93edc3d93d43dba2f9e8da38ad53e"},
+    {file = "Fiona-1.8.20-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:54f81039e913d0f88728ef23edf5a69038dec94dea54f4c799f972ba8e2a7d40"},
+    {file = "Fiona-1.8.20-cp37-cp37m-manylinux1_x86_64.whl", hash = "sha256:328340a448bed5c43d119f61f760368a04d13a302c59d2fccb051a3ff021f4b8"},
+    {file = "Fiona-1.8.20-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:03f910380dbe684730b59b817aa030e6e9a3ee79211b66c6db2d1c8fe6ea12de"},
+    {file = "Fiona-1.8.20-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.whl", hash = "sha256:bef100ebd82afb9a4d67096216e82611b82ca9341330e4805832d7ff8c9bc1f7"},
+    {file = "Fiona-1.8.20-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:5e1cef608c6de9039eaa65b395024096e3189ab0559a5a328c68c4690c3302ce"},
+    {file = "Fiona-1.8.20-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.whl", hash = "sha256:e72e4a5b84ec410be531d4fe4c1a5c87c6c0e92d01116c145c0f1b33f81c8080"},
+    {file = "Fiona-1.8.20.tar.gz", hash = "sha256:a70502d2857b82f749c09cb0dea3726787747933a2a1599b5ab787d74e3c143b"},
+]
+geopandas = [
+    {file = "geopandas-0.9.0-py2.py3-none-any.whl", hash = "sha256:79f6e557ba0dba76eec44f8351b1c6b42a17c38f5f08fef347e98fe4dae563c7"},
+    {file = "geopandas-0.9.0.tar.gz", hash = "sha256:63972ab4dc44c4029f340600dcb83264eb8132dd22b104da0b654bef7f42630a"},
+]
+idna = [
+    {file = "idna-3.2-py3-none-any.whl", hash = "sha256:14475042e284991034cb48e06f6851428fb14c4dc953acd9be9a5e95c7b6dd7a"},
+    {file = "idna-3.2.tar.gz", hash = "sha256:467fbad99067910785144ce333826c71fb0e63a425657295239737f7ecd125f3"},
+]
+imageio = [
+    {file = "imageio-2.9.0-py3-none-any.whl", hash = "sha256:3604d751f03002e8e0e7650aa71d8d9148144a87daf17cb1f3228e80747f2e6b"},
+    {file = "imageio-2.9.0.tar.gz", hash = "sha256:52ddbaeca2dccf53ba2d6dec5676ca7bc3b2403ef8b37f7da78b7654bb3e10f0"},
+]
+ipykernel = [
+    {file = "ipykernel-6.2.0-py3-none-any.whl", hash = "sha256:35cc31accec420e90c4b66ea7f4e7b067c769e31af3502e45326c6f1294d238d"},
+    {file = "ipykernel-6.2.0.tar.gz", hash = "sha256:4439459f171d77f35b7f7e72dace5d7c2dd10a5c9e2c22b173ad9048fbfe7656"},
+]
+ipython = [
+    {file = "ipython-7.26.0-py3-none-any.whl", hash = "sha256:892743b65c21ed72b806a3a602cca408520b3200b89d1924f4b3d2cdb3692362"},
+    {file = "ipython-7.26.0.tar.gz", hash = "sha256:0cff04bb042800129348701f7bd68a430a844e8fb193979c08f6c99f28bb735e"},
+]
+ipython-genutils = [
+    {file = "ipython_genutils-0.2.0-py2.py3-none-any.whl", hash = "sha256:72dd37233799e619666c9f639a9da83c34013a73e8bbc79a7a6348d93c61fab8"},
+    {file = "ipython_genutils-0.2.0.tar.gz", hash = "sha256:eb2e116e75ecef9d4d228fdc66af54269afa26ab4463042e33785b887c628ba8"},
+]
+ipywidgets = [
+    {file = "ipywidgets-7.6.3-py2.py3-none-any.whl", hash = "sha256:e6513cfdaf5878de30f32d57f6dc2474da395a2a2991b94d487406c0ab7f55ca"},
+    {file = "ipywidgets-7.6.3.tar.gz", hash = "sha256:9f1a43e620530f9e570e4a493677d25f08310118d315b00e25a18f12913c41f0"},
+]
+jedi = [
+    {file = "jedi-0.18.0-py2.py3-none-any.whl", hash = "sha256:18456d83f65f400ab0c2d3319e48520420ef43b23a086fdc05dff34132f0fb93"},
+    {file = "jedi-0.18.0.tar.gz", hash = "sha256:92550a404bad8afed881a137ec9a461fed49eca661414be45059329614ed0707"},
+]
+jinja2 = [
+    {file = "Jinja2-3.0.1-py3-none-any.whl", hash = "sha256:1f06f2da51e7b56b8f238affdd6b4e2c61e39598a378cc49345bc1bd42a978a4"},
+    {file = "Jinja2-3.0.1.tar.gz", hash = "sha256:703f484b47a6af502e743c9122595cc812b0271f661722403114f71a79d0f5a4"},
+]
+jsonschema = [
+    {file = "jsonschema-3.2.0-py2.py3-none-any.whl", hash = "sha256:4e5b3cf8216f577bee9ce139cbe72eca3ea4f292ec60928ff24758ce626cd163"},
+    {file = "jsonschema-3.2.0.tar.gz", hash = "sha256:c8a85b28d377cc7737e46e2d9f2b4f44ee3c0e1deac6bf46ddefc7187d30797a"},
+]
+jupyter = [
+    {file = "jupyter-1.0.0-py2.py3-none-any.whl", hash = "sha256:5b290f93b98ffbc21c0c7e749f054b3267782166d72fa5e3ed1ed4eaf34a2b78"},
+    {file = "jupyter-1.0.0.tar.gz", hash = "sha256:d9dc4b3318f310e34c82951ea5d6683f67bed7def4b259fafbfe4f1beb1d8e5f"},
+    {file = "jupyter-1.0.0.zip", hash = "sha256:3e1f86076bbb7c8c207829390305a2b1fe836d471ed54be66a3b8c41e7f46cc7"},
+]
+jupyter-client = [
+    {file = "jupyter_client-6.2.0-py3-none-any.whl", hash = "sha256:9715152067e3f7ea3b56f341c9a0f9715c8c7cc316ee0eb13c3c84f5ca0065f5"},
+    {file = "jupyter_client-6.2.0.tar.gz", hash = "sha256:e2ab61d79fbf8b56734a4c2499f19830fbd7f6fefb3e87868ef0545cb3c17eb9"},
+]
+jupyter-console = [
+    {file = "jupyter_console-6.4.0-py3-none-any.whl", hash = "sha256:7799c4ea951e0e96ba8260575423cb323ea5a03fcf5503560fa3e15748869e27"},
+    {file = "jupyter_console-6.4.0.tar.gz", hash = "sha256:242248e1685039cd8bff2c2ecb7ce6c1546eb50ee3b08519729e6e881aec19c7"},
+]
+jupyter-contrib-core = [
+    {file = "jupyter_contrib_core-0.3.3-py2.py3-none-any.whl", hash = "sha256:1ec81e275a8f5858d56b0c4c6cd85335aa8e915001b8657fe51c620c3cdde50f"},
+    {file = "jupyter_contrib_core-0.3.3.tar.gz", hash = "sha256:e65bc0e932ff31801003cef160a4665f2812efe26a53801925a634735e9a5794"},
+]
+jupyter-core = [
+    {file = "jupyter_core-4.7.1-py3-none-any.whl", hash = "sha256:8c6c0cac5c1b563622ad49321d5ec47017bd18b94facb381c6973a0486395f8e"},
+    {file = "jupyter_core-4.7.1.tar.gz", hash = "sha256:79025cb3225efcd36847d0840f3fc672c0abd7afd0de83ba8a1d3837619122b4"},
+]
+jupyter-nbextensions-configurator = [
+    {file = "jupyter_nbextensions_configurator-0.4.1.tar.gz", hash = "sha256:e5e86b5d9d898e1ffb30ebb08e4ad8696999f798fef3ff3262d7b999076e4e83"},
+]
+jupyterlab-pygments = [
+    {file = "jupyterlab_pygments-0.1.2-py2.py3-none-any.whl", hash = "sha256:abfb880fd1561987efaefcb2d2ac75145d2a5d0139b1876d5be806e32f630008"},
+    {file = "jupyterlab_pygments-0.1.2.tar.gz", hash = "sha256:cfcda0873626150932f438eccf0f8bf22bfa92345b814890ab360d666b254146"},
+]
+jupyterlab-widgets = [
+    {file = "jupyterlab_widgets-1.0.0-py3-none-any.whl", hash = "sha256:caeaf3e6103180e654e7d8d2b81b7d645e59e432487c1d35a41d6d3ee56b3fef"},
+    {file = "jupyterlab_widgets-1.0.0.tar.gz", hash = "sha256:5c1a29a84d3069208cb506b10609175b249b6486d6b1cbae8fcde2a11584fb78"},
+]
+kiwisolver = [
+    {file = "kiwisolver-1.3.1-cp36-cp36m-macosx_10_9_x86_64.whl", hash = "sha256:fd34fbbfbc40628200730bc1febe30631347103fc8d3d4fa012c21ab9c11eca9"},
+    {file = "kiwisolver-1.3.1-cp36-cp36m-manylinux1_i686.whl", hash = "sha256:d3155d828dec1d43283bd24d3d3e0d9c7c350cdfcc0bd06c0ad1209c1bbc36d0"},
+    {file = "kiwisolver-1.3.1-cp36-cp36m-manylinux1_x86_64.whl", hash = "sha256:5a7a7dbff17e66fac9142ae2ecafb719393aaee6a3768c9de2fd425c63b53e21"},
+    {file = "kiwisolver-1.3.1-cp36-cp36m-manylinux2014_aarch64.whl", hash = "sha256:f8d6f8db88049a699817fd9178782867bf22283e3813064302ac59f61d95be05"},
+    {file = "kiwisolver-1.3.1-cp36-cp36m-manylinux2014_ppc64le.whl", hash = "sha256:5f6ccd3dd0b9739edcf407514016108e2280769c73a85b9e59aa390046dbf08b"},
+    {file = "kiwisolver-1.3.1-cp36-cp36m-win32.whl", hash = "sha256:225e2e18f271e0ed8157d7f4518ffbf99b9450fca398d561eb5c4a87d0986dd9"},
+    {file = "kiwisolver-1.3.1-cp36-cp36m-win_amd64.whl", hash = "sha256:cf8b574c7b9aa060c62116d4181f3a1a4e821b2ec5cbfe3775809474113748d4"},
+    {file = "kiwisolver-1.3.1-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:232c9e11fd7ac3a470d65cd67e4359eee155ec57e822e5220322d7b2ac84fbf0"},
+    {file = "kiwisolver-1.3.1-cp37-cp37m-manylinux1_i686.whl", hash = "sha256:b38694dcdac990a743aa654037ff1188c7a9801ac3ccc548d3341014bc5ca278"},
+    {file = "kiwisolver-1.3.1-cp37-cp37m-manylinux1_x86_64.whl", hash = "sha256:ca3820eb7f7faf7f0aa88de0e54681bddcb46e485beb844fcecbcd1c8bd01689"},
+    {file = "kiwisolver-1.3.1-cp37-cp37m-manylinux2014_aarch64.whl", hash = "sha256:c8fd0f1ae9d92b42854b2979024d7597685ce4ada367172ed7c09edf2cef9cb8"},
+    {file = "kiwisolver-1.3.1-cp37-cp37m-manylinux2014_ppc64le.whl", hash = "sha256:1e1bc12fb773a7b2ffdeb8380609f4f8064777877b2225dec3da711b421fda31"},
+    {file = "kiwisolver-1.3.1-cp37-cp37m-win32.whl", hash = "sha256:72c99e39d005b793fb7d3d4e660aed6b6281b502e8c1eaf8ee8346023c8e03bc"},
+    {file = "kiwisolver-1.3.1-cp37-cp37m-win_amd64.whl", hash = "sha256:8be8d84b7d4f2ba4ffff3665bcd0211318aa632395a1a41553250484a871d454"},
+    {file = "kiwisolver-1.3.1-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:31dfd2ac56edc0ff9ac295193eeaea1c0c923c0355bf948fbd99ed6018010b72"},
+    {file = "kiwisolver-1.3.1-cp38-cp38-manylinux1_i686.whl", hash = "sha256:563c649cfdef27d081c84e72a03b48ea9408c16657500c312575ae9d9f7bc1c3"},
+    {file = "kiwisolver-1.3.1-cp38-cp38-manylinux1_x86_64.whl", hash = "sha256:78751b33595f7f9511952e7e60ce858c6d64db2e062afb325985ddbd34b5c131"},
+    {file = "kiwisolver-1.3.1-cp38-cp38-manylinux2014_aarch64.whl", hash = "sha256:a357fd4f15ee49b4a98b44ec23a34a95f1e00292a139d6015c11f55774ef10de"},
+    {file = "kiwisolver-1.3.1-cp38-cp38-manylinux2014_ppc64le.whl", hash = "sha256:5989db3b3b34b76c09253deeaf7fbc2707616f130e166996606c284395da3f18"},
+    {file = "kiwisolver-1.3.1-cp38-cp38-win32.whl", hash = "sha256:c08e95114951dc2090c4a630c2385bef681cacf12636fb0241accdc6b303fd81"},
+    {file = "kiwisolver-1.3.1-cp38-cp38-win_amd64.whl", hash = "sha256:44a62e24d9b01ba94ae7a4a6c3fb215dc4af1dde817e7498d901e229aaf50e4e"},
+    {file = "kiwisolver-1.3.1-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:50af681a36b2a1dee1d3c169ade9fdc59207d3c31e522519181e12f1b3ba7000"},
+    {file = "kiwisolver-1.3.1-cp39-cp39-manylinux1_i686.whl", hash = "sha256:a53d27d0c2a0ebd07e395e56a1fbdf75ffedc4a05943daf472af163413ce9598"},
+    {file = "kiwisolver-1.3.1-cp39-cp39-manylinux1_x86_64.whl", hash = "sha256:834ee27348c4aefc20b479335fd422a2c69db55f7d9ab61721ac8cd83eb78882"},
+    {file = "kiwisolver-1.3.1-cp39-cp39-manylinux2014_aarch64.whl", hash = "sha256:5c3e6455341008a054cccee8c5d24481bcfe1acdbc9add30aa95798e95c65621"},
+    {file = "kiwisolver-1.3.1-cp39-cp39-manylinux2014_ppc64le.whl", hash = "sha256:acef3d59d47dd85ecf909c359d0fd2c81ed33bdff70216d3956b463e12c38a54"},
+    {file = "kiwisolver-1.3.1-cp39-cp39-win32.whl", hash = "sha256:c5518d51a0735b1e6cee1fdce66359f8d2b59c3ca85dc2b0813a8aa86818a030"},
+    {file = "kiwisolver-1.3.1-cp39-cp39-win_amd64.whl", hash = "sha256:b9edd0110a77fc321ab090aaa1cfcaba1d8499850a12848b81be2222eab648f6"},
+    {file = "kiwisolver-1.3.1-pp36-pypy36_pp73-macosx_10_9_x86_64.whl", hash = "sha256:0cd53f403202159b44528498de18f9285b04482bab2a6fc3f5dd8dbb9352e30d"},
+    {file = "kiwisolver-1.3.1-pp36-pypy36_pp73-manylinux2010_x86_64.whl", hash = "sha256:33449715e0101e4d34f64990352bce4095c8bf13bed1b390773fc0a7295967b3"},
+    {file = "kiwisolver-1.3.1-pp36-pypy36_pp73-win32.whl", hash = "sha256:401a2e9afa8588589775fe34fc22d918ae839aaaf0c0e96441c0fdbce6d8ebe6"},
+    {file = "kiwisolver-1.3.1.tar.gz", hash = "sha256:950a199911a8d94683a6b10321f9345d5a3a8433ec58b217ace979e18f16e248"},
+]
+loguru = [
+    {file = "loguru-0.5.3-py3-none-any.whl", hash = "sha256:f8087ac396b5ee5f67c963b495d615ebbceac2796379599820e324419d53667c"},
+    {file = "loguru-0.5.3.tar.gz", hash = "sha256:b28e72ac7a98be3d28ad28570299a393dfcd32e5e3f6a353dec94675767b6319"},
+]
+markupsafe = [
+    {file = "MarkupSafe-2.0.1-cp36-cp36m-macosx_10_9_x86_64.whl", hash = "sha256:f9081981fe268bd86831e5c75f7de206ef275defcb82bc70740ae6dc507aee51"},
+    {file = "MarkupSafe-2.0.1-cp36-cp36m-manylinux1_i686.whl", hash = "sha256:0955295dd5eec6cb6cc2fe1698f4c6d84af2e92de33fbcac4111913cd100a6ff"},
+    {file = "MarkupSafe-2.0.1-cp36-cp36m-manylinux1_x86_64.whl", hash = "sha256:0446679737af14f45767963a1a9ef7620189912317d095f2d9ffa183a4d25d2b"},
+    {file = "MarkupSafe-2.0.1-cp36-cp36m-manylinux2010_i686.whl", hash = "sha256:f826e31d18b516f653fe296d967d700fddad5901ae07c622bb3705955e1faa94"},
+    {file = "MarkupSafe-2.0.1-cp36-cp36m-manylinux2010_x86_64.whl", hash = "sha256:fa130dd50c57d53368c9d59395cb5526eda596d3ffe36666cd81a44d56e48872"},
+    {file = "MarkupSafe-2.0.1-cp36-cp36m-manylinux2014_aarch64.whl", hash = "sha256:905fec760bd2fa1388bb5b489ee8ee5f7291d692638ea5f67982d968366bef9f"},
+    {file = "MarkupSafe-2.0.1-cp36-cp36m-win32.whl", hash = "sha256:6c4ca60fa24e85fe25b912b01e62cb969d69a23a5d5867682dd3e80b5b02581d"},
+    {file = "MarkupSafe-2.0.1-cp36-cp36m-win_amd64.whl", hash = "sha256:b2f4bf27480f5e5e8ce285a8c8fd176c0b03e93dcc6646477d4630e83440c6a9"},
+    {file = "MarkupSafe-2.0.1-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:0717a7390a68be14b8c793ba258e075c6f4ca819f15edfc2a3a027c823718567"},
+    {file = "MarkupSafe-2.0.1-cp37-cp37m-manylinux1_i686.whl", hash = "sha256:6557b31b5e2c9ddf0de32a691f2312a32f77cd7681d8af66c2692efdbef84c18"},
+    {file = "MarkupSafe-2.0.1-cp37-cp37m-manylinux1_x86_64.whl", hash = "sha256:49e3ceeabbfb9d66c3aef5af3a60cc43b85c33df25ce03d0031a608b0a8b2e3f"},
+    {file = "MarkupSafe-2.0.1-cp37-cp37m-manylinux2010_i686.whl", hash = "sha256:d7f9850398e85aba693bb640262d3611788b1f29a79f0c93c565694658f4071f"},
+    {file = "MarkupSafe-2.0.1-cp37-cp37m-manylinux2010_x86_64.whl", hash = "sha256:6a7fae0dd14cf60ad5ff42baa2e95727c3d81ded453457771d02b7d2b3f9c0c2"},
+    {file = "MarkupSafe-2.0.1-cp37-cp37m-manylinux2014_aarch64.whl", hash = "sha256:b7f2d075102dc8c794cbde1947378051c4e5180d52d276987b8d28a3bd58c17d"},
+    {file = "MarkupSafe-2.0.1-cp37-cp37m-win32.whl", hash = "sha256:a30e67a65b53ea0a5e62fe23682cfe22712e01f453b95233b25502f7c61cb415"},
+    {file = "MarkupSafe-2.0.1-cp37-cp37m-win_amd64.whl", hash = "sha256:611d1ad9a4288cf3e3c16014564df047fe08410e628f89805e475368bd304914"},
+    {file = "MarkupSafe-2.0.1-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:be98f628055368795d818ebf93da628541e10b75b41c559fdf36d104c5787066"},
+    {file = "MarkupSafe-2.0.1-cp38-cp38-manylinux1_i686.whl", hash = "sha256:1d609f577dc6e1aa17d746f8bd3c31aa4d258f4070d61b2aa5c4166c1539de35"},
+    {file = "MarkupSafe-2.0.1-cp38-cp38-manylinux1_x86_64.whl", hash = "sha256:7d91275b0245b1da4d4cfa07e0faedd5b0812efc15b702576d103293e252af1b"},
+    {file = "MarkupSafe-2.0.1-cp38-cp38-manylinux2010_i686.whl", hash = "sha256:01a9b8ea66f1658938f65b93a85ebe8bc016e6769611be228d797c9d998dd298"},
+    {file = "MarkupSafe-2.0.1-cp38-cp38-manylinux2010_x86_64.whl", hash = "sha256:47ab1e7b91c098ab893b828deafa1203de86d0bc6ab587b160f78fe6c4011f75"},
+    {file = "MarkupSafe-2.0.1-cp38-cp38-manylinux2014_aarch64.whl", hash = "sha256:97383d78eb34da7e1fa37dd273c20ad4320929af65d156e35a5e2d89566d9dfb"},
+    {file = "MarkupSafe-2.0.1-cp38-cp38-win32.whl", hash = "sha256:023cb26ec21ece8dc3907c0e8320058b2e0cb3c55cf9564da612bc325bed5e64"},
+    {file = "MarkupSafe-2.0.1-cp38-cp38-win_amd64.whl", hash = "sha256:984d76483eb32f1bcb536dc27e4ad56bba4baa70be32fa87152832cdd9db0833"},
+    {file = "MarkupSafe-2.0.1-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:2ef54abee730b502252bcdf31b10dacb0a416229b72c18b19e24a4509f273d26"},
+    {file = "MarkupSafe-2.0.1-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:3c112550557578c26af18a1ccc9e090bfe03832ae994343cfdacd287db6a6ae7"},
+    {file = "MarkupSafe-2.0.1-cp39-cp39-manylinux1_i686.whl", hash = "sha256:53edb4da6925ad13c07b6d26c2a852bd81e364f95301c66e930ab2aef5b5ddd8"},
+    {file = "MarkupSafe-2.0.1-cp39-cp39-manylinux1_x86_64.whl", hash = "sha256:f5653a225f31e113b152e56f154ccbe59eeb1c7487b39b9d9f9cdb58e6c79dc5"},
+    {file = "MarkupSafe-2.0.1-cp39-cp39-manylinux2010_i686.whl", hash = "sha256:4efca8f86c54b22348a5467704e3fec767b2db12fc39c6d963168ab1d3fc9135"},
+    {file = "MarkupSafe-2.0.1-cp39-cp39-manylinux2010_x86_64.whl", hash = "sha256:ab3ef638ace319fa26553db0624c4699e31a28bb2a835c5faca8f8acf6a5a902"},
+    {file = "MarkupSafe-2.0.1-cp39-cp39-manylinux2014_aarch64.whl", hash = "sha256:f8ba0e8349a38d3001fae7eadded3f6606f0da5d748ee53cc1dab1d6527b9509"},
+    {file = "MarkupSafe-2.0.1-cp39-cp39-win32.whl", hash = "sha256:10f82115e21dc0dfec9ab5c0223652f7197feb168c940f3ef61563fc2d6beb74"},
+    {file = "MarkupSafe-2.0.1-cp39-cp39-win_amd64.whl", hash = "sha256:693ce3f9e70a6cf7d2fb9e6c9d8b204b6b39897a2c4a1aa65728d5ac97dcc1d8"},
+    {file = "MarkupSafe-2.0.1.tar.gz", hash = "sha256:594c67807fb16238b30c44bdf74f36c02cdf22d1c8cda91ef8a0ed8dabf5620a"},
+]
+matplotlib = [
+    {file = "matplotlib-3.4.3-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:5c988bb43414c7c2b0a31bd5187b4d27fd625c080371b463a6d422047df78913"},
+    {file = "matplotlib-3.4.3-cp37-cp37m-manylinux1_i686.whl", hash = "sha256:f1c5efc278d996af8a251b2ce0b07bbeccb821f25c8c9846bdcb00ffc7f158aa"},
+    {file = "matplotlib-3.4.3-cp37-cp37m-manylinux1_x86_64.whl", hash = "sha256:eeb1859efe7754b1460e1d4991bbd4a60a56f366bc422ef3a9c5ae05f0bc70b5"},
+    {file = "matplotlib-3.4.3-cp37-cp37m-manylinux2014_aarch64.whl", hash = "sha256:844a7b0233e4ff7fba57e90b8799edaa40b9e31e300b8d5efc350937fa8b1bea"},
+    {file = "matplotlib-3.4.3-cp37-cp37m-win32.whl", hash = "sha256:85f0c9cf724715e75243a7b3087cf4a3de056b55e05d4d76cc58d610d62894f3"},
+    {file = "matplotlib-3.4.3-cp37-cp37m-win_amd64.whl", hash = "sha256:c70b6311dda3e27672f1bf48851a0de816d1ca6aaf3d49365fbdd8e959b33d2b"},
+    {file = "matplotlib-3.4.3-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:b884715a59fec9ad3b6048ecf3860f3b2ce965e676ef52593d6fa29abcf7d330"},
+    {file = "matplotlib-3.4.3-cp38-cp38-manylinux1_i686.whl", hash = "sha256:a78a3b51f29448c7f4d4575e561f6b0dbb8d01c13c2046ab6c5220eb25c06506"},
+    {file = "matplotlib-3.4.3-cp38-cp38-manylinux1_x86_64.whl", hash = "sha256:6a724e3a48a54b8b6e7c4ae38cd3d07084508fa47c410c8757e9db9791421838"},
+    {file = "matplotlib-3.4.3-cp38-cp38-manylinux2014_aarch64.whl", hash = "sha256:48e1e0859b54d5f2e29bb78ca179fd59b971c6ceb29977fb52735bfd280eb0f5"},
+    {file = "matplotlib-3.4.3-cp38-cp38-win32.whl", hash = "sha256:01c9de93a2ca0d128c9064f23709362e7fefb34910c7c9e0b8ab0de8258d5eda"},
+    {file = "matplotlib-3.4.3-cp38-cp38-win_amd64.whl", hash = "sha256:ebfb01a65c3f5d53a8c2a8133fec2b5221281c053d944ae81ff5822a68266617"},
+    {file = "matplotlib-3.4.3-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:b8b53f336a4688cfce615887505d7e41fd79b3594bf21dd300531a4f5b4f746a"},
+    {file = "matplotlib-3.4.3-cp39-cp39-manylinux1_i686.whl", hash = "sha256:fcd6f1954943c0c192bfbebbac263f839d7055409f1173f80d8b11a224d236da"},
+    {file = "matplotlib-3.4.3-cp39-cp39-manylinux1_x86_64.whl", hash = "sha256:6be8df61b1626e1a142c57e065405e869e9429b4a6dab4a324757d0dc4d42235"},
+    {file = "matplotlib-3.4.3-cp39-cp39-manylinux2014_aarch64.whl", hash = "sha256:41b6e307458988891fcdea2d8ecf84a8c92d53f84190aa32da65f9505546e684"},
+    {file = "matplotlib-3.4.3-cp39-cp39-win32.whl", hash = "sha256:f72657f1596199dc1e4e7a10f52a4784ead8a711f4e5b59bea95bdb97cf0e4fd"},
+    {file = "matplotlib-3.4.3-cp39-cp39-win_amd64.whl", hash = "sha256:f15edcb0629a0801738925fe27070480f446fcaa15de65946ff946ad99a59a40"},
+    {file = "matplotlib-3.4.3-pp37-pypy37_pp73-macosx_10_9_x86_64.whl", hash = "sha256:556965514b259204637c360d213de28d43a1f4aed1eca15596ce83f768c5a56f"},
+    {file = "matplotlib-3.4.3-pp37-pypy37_pp73-manylinux2010_x86_64.whl", hash = "sha256:54a026055d5f8614f184e588f6e29064019a0aa8448450214c0b60926d62d919"},
+    {file = "matplotlib-3.4.3.tar.gz", hash = "sha256:fc4f526dfdb31c9bd6b8ca06bf9fab663ca12f3ec9cdf4496fb44bc680140318"},
+]
+matplotlib-inline = [
+    {file = "matplotlib-inline-0.1.2.tar.gz", hash = "sha256:f41d5ff73c9f5385775d5c0bc13b424535c8402fe70ea8210f93e11f3683993e"},
+    {file = "matplotlib_inline-0.1.2-py3-none-any.whl", hash = "sha256:5cf1176f554abb4fa98cb362aa2b55c500147e4bdbb07e3fda359143e1da0811"},
+]
+mistune = [
+    {file = "mistune-0.8.4-py2.py3-none-any.whl", hash = "sha256:88a1051873018da288eee8538d476dffe1262495144b33ecb586c4ab266bb8d4"},
+    {file = "mistune-0.8.4.tar.gz", hash = "sha256:59a3429db53c50b5c6bcc8a07f8848cb00d7dc8bdb431a4ab41920d201d4756e"},
+]
+munch = [
+    {file = "munch-2.5.0-py2.py3-none-any.whl", hash = "sha256:6f44af89a2ce4ed04ff8de41f70b226b984db10a91dcc7b9ac2efc1c77022fdd"},
+    {file = "munch-2.5.0.tar.gz", hash = "sha256:2d735f6f24d4dba3417fa448cae40c6e896ec1fdab6cdb5e6510999758a4dbd2"},
+]
+nbclient = [
+    {file = "nbclient-0.5.4-py3-none-any.whl", hash = "sha256:95a300c6fbe73721736cf13972a46d8d666f78794b832866ed7197a504269e11"},
+    {file = "nbclient-0.5.4.tar.gz", hash = "sha256:6c8ad36a28edad4562580847f9f1636fe5316a51a323ed85a24a4ad37d4aefce"},
+]
+nbconvert = [
+    {file = "nbconvert-6.1.0-py3-none-any.whl", hash = "sha256:37cd92ff2ae6a268e62075ff8b16129e0be4939c4dfcee53dc77cc8a7e06c684"},
+    {file = "nbconvert-6.1.0.tar.gz", hash = "sha256:d22a8ff202644d31db254d24d52c3a96c82156623fcd7c7f987bba2612303ec9"},
+]
+nbformat = [
+    {file = "nbformat-5.1.3-py3-none-any.whl", hash = "sha256:eb8447edd7127d043361bc17f2f5a807626bc8e878c7709a1c647abda28a9171"},
+    {file = "nbformat-5.1.3.tar.gz", hash = "sha256:b516788ad70771c6250977c1374fcca6edebe6126fd2adb5a69aa5c2356fd1c8"},
+]
+nest-asyncio = [
+    {file = "nest_asyncio-1.5.1-py3-none-any.whl", hash = "sha256:76d6e972265063fe92a90b9cc4fb82616e07d586b346ed9d2c89a4187acea39c"},
+    {file = "nest_asyncio-1.5.1.tar.gz", hash = "sha256:afc5a1c515210a23c461932765691ad39e8eba6551c055ac8d5546e69250d0aa"},
+]
+networkx = [
+    {file = "networkx-2.6.2-py3-none-any.whl", hash = "sha256:5fcb7004be69e8fbdf07dcb502efa5c77cadcaad6982164134eeb9721f826c2e"},
+    {file = "networkx-2.6.2.tar.gz", hash = "sha256:2306f1950ce772c5a59a57f5486d59bb9cab98497c45fc49cbc45ac0dec119bb"},
+]
+notebook = [
+    {file = "notebook-6.4.3-py3-none-any.whl", hash = "sha256:b50eafa8208d5db966efd1caa4076b4dfc51815e02a805b32ecd717e9e6cc071"},
+    {file = "notebook-6.4.3.tar.gz", hash = "sha256:e6b6dfed36b00cf950f63c0d42e947c101d4258aec21624de62b9e0c11ed5c0d"},
+]
+numpy = [
+    {file = "numpy-1.21.1-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:38e8648f9449a549a7dfe8d8755a5979b45b3538520d1e735637ef28e8c2dc50"},
+    {file = "numpy-1.21.1-cp37-cp37m-manylinux_2_12_i686.manylinux2010_i686.whl", hash = "sha256:fd7d7409fa643a91d0a05c7554dd68aa9c9bb16e186f6ccfe40d6e003156e33a"},
+    {file = "numpy-1.21.1-cp37-cp37m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:a75b4498b1e93d8b700282dc8e655b8bd559c0904b3910b144646dbbbc03e062"},
+    {file = "numpy-1.21.1-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:1412aa0aec3e00bc23fbb8664d76552b4efde98fb71f60737c83efbac24112f1"},
+    {file = "numpy-1.21.1-cp37-cp37m-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:e46ceaff65609b5399163de5893d8f2a82d3c77d5e56d976c8b5fb01faa6b671"},
+    {file = "numpy-1.21.1-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.whl", hash = "sha256:c6a2324085dd52f96498419ba95b5777e40b6bcbc20088fddb9e8cbb58885e8e"},
+    {file = "numpy-1.21.1-cp37-cp37m-win32.whl", hash = "sha256:73101b2a1fef16602696d133db402a7e7586654682244344b8329cdcbbb82172"},
+    {file = "numpy-1.21.1-cp37-cp37m-win_amd64.whl", hash = "sha256:7a708a79c9a9d26904d1cca8d383bf869edf6f8e7650d85dbc77b041e8c5a0f8"},
+    {file = "numpy-1.21.1-cp38-cp38-macosx_10_9_universal2.whl", hash = "sha256:95b995d0c413f5d0428b3f880e8fe1660ff9396dcd1f9eedbc311f37b5652e16"},
+    {file = "numpy-1.21.1-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:635e6bd31c9fb3d475c8f44a089569070d10a9ef18ed13738b03049280281267"},
+    {file = "numpy-1.21.1-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:4a3d5fb89bfe21be2ef47c0614b9c9c707b7362386c9a3ff1feae63e0267ccb6"},
+    {file = "numpy-1.21.1-cp38-cp38-manylinux_2_12_i686.manylinux2010_i686.whl", hash = "sha256:8a326af80e86d0e9ce92bcc1e65c8ff88297de4fa14ee936cb2293d414c9ec63"},
+    {file = "numpy-1.21.1-cp38-cp38-manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:791492091744b0fe390a6ce85cc1bf5149968ac7d5f0477288f78c89b385d9af"},
+    {file = "numpy-1.21.1-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0318c465786c1f63ac05d7c4dbcecd4d2d7e13f0959b01b534ea1e92202235c5"},
+    {file = "numpy-1.21.1-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:9a513bd9c1551894ee3d31369f9b07460ef223694098cf27d399513415855b68"},
+    {file = "numpy-1.21.1-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.whl", hash = "sha256:91c6f5fc58df1e0a3cc0c3a717bb3308ff850abdaa6d2d802573ee2b11f674a8"},
+    {file = "numpy-1.21.1-cp38-cp38-win32.whl", hash = "sha256:978010b68e17150db8765355d1ccdd450f9fc916824e8c4e35ee620590e234cd"},
+    {file = "numpy-1.21.1-cp38-cp38-win_amd64.whl", hash = "sha256:9749a40a5b22333467f02fe11edc98f022133ee1bfa8ab99bda5e5437b831214"},
+    {file = "numpy-1.21.1-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:d7a4aeac3b94af92a9373d6e77b37691b86411f9745190d2c351f410ab3a791f"},
+    {file = "numpy-1.21.1-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:d9e7912a56108aba9b31df688a4c4f5cb0d9d3787386b87d504762b6754fbb1b"},
+    {file = "numpy-1.21.1-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:25b40b98ebdd272bc3020935427a4530b7d60dfbe1ab9381a39147834e985eac"},
+    {file = "numpy-1.21.1-cp39-cp39-manylinux_2_12_i686.manylinux2010_i686.whl", hash = "sha256:8a92c5aea763d14ba9d6475803fc7904bda7decc2a0a68153f587ad82941fec1"},
+    {file = "numpy-1.21.1-cp39-cp39-manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:05a0f648eb28bae4bcb204e6fd14603de2908de982e761a2fc78efe0f19e96e1"},
+    {file = "numpy-1.21.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f01f28075a92eede918b965e86e8f0ba7b7797a95aa8d35e1cc8821f5fc3ad6a"},
+    {file = "numpy-1.21.1-cp39-cp39-win32.whl", hash = "sha256:88c0b89ad1cc24a5efbb99ff9ab5db0f9a86e9cc50240177a571fbe9c2860ac2"},
+    {file = "numpy-1.21.1-cp39-cp39-win_amd64.whl", hash = "sha256:01721eefe70544d548425a07c80be8377096a54118070b8a62476866d5208e33"},
+    {file = "numpy-1.21.1-pp37-pypy37_pp73-manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:2d4d1de6e6fb3d28781c73fbde702ac97f03d79e4ffd6598b880b2d95d62ead4"},
+    {file = "numpy-1.21.1.zip", hash = "sha256:dff4af63638afcc57a3dfb9e4b26d434a7a602d225b42d746ea7fe2edf1342fd"},
+]
+packaging = [
+    {file = "packaging-21.0-py3-none-any.whl", hash = "sha256:c86254f9220d55e31cc94d69bade760f0847da8000def4dfe1c6b872fd14ff14"},
+    {file = "packaging-21.0.tar.gz", hash = "sha256:7dc96269f53a4ccec5c0670940a4281106dd0bb343f47b7471f779df49c2fbe7"},
+]
+pandas = [
+    {file = "pandas-1.3.2-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:ba7ceb8abc6dbdb1e34612d1173d61e4941f1a1eb7e6f703b2633134ae6a6c89"},
+    {file = "pandas-1.3.2-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:fcb71b1935249de80e3a808227189eee381d4d74a31760ced2df21eedc92a8e3"},
+    {file = "pandas-1.3.2-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:fa54dc1d3e5d004a09ab0b1751473698011ddf03e14f1f59b84ad9a6ac630975"},
+    {file = "pandas-1.3.2-cp37-cp37m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:34ced9ce5d5b17b556486da7256961b55b471d64a8990b56e67a84ebeb259416"},
+    {file = "pandas-1.3.2-cp37-cp37m-win32.whl", hash = "sha256:a56246de744baf646d1f3e050c4653d632bc9cd2e0605f41051fea59980e880a"},
+    {file = "pandas-1.3.2-cp37-cp37m-win_amd64.whl", hash = "sha256:53b17e4debba26b7446b1e4795c19f94f0c715e288e08145e44bdd2865e819b3"},
+    {file = "pandas-1.3.2-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:f07a9745ca075ae73a5ce116f5e58f691c0dc9de0bff163527858459df5c176f"},
+    {file = "pandas-1.3.2-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c9e8e0ce5284ebebe110efd652c164ed6eab77f5de4c3533abc756302ee77765"},
+    {file = "pandas-1.3.2-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:59a78d7066d1c921a77e3306aa0ebf6e55396c097d5dfcc4df8defe3dcecb735"},
+    {file = "pandas-1.3.2-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:132def05e73d292c949b02e7ef873debb77acc44a8b119d215921046f0c3a91d"},
+    {file = "pandas-1.3.2-cp38-cp38-win32.whl", hash = "sha256:69e1b2f5811f46827722fd641fdaeedb26002bd1e504eacc7a8ec36bdc25393e"},
+    {file = "pandas-1.3.2-cp38-cp38-win_amd64.whl", hash = "sha256:7996d311413379136baf0f3cf2a10e331697657c87ced3f17ac7c77f77fe34a3"},
+    {file = "pandas-1.3.2-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:1738154049062156429a5cf2fd79a69c9f3fa4f231346a7ec6fd156cd1a9a621"},
+    {file = "pandas-1.3.2-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:9cce01f6d655b4add966fcd36c32c5d1fe84628e200626b3f5e2f40db2d16a0f"},
+    {file = "pandas-1.3.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:1099e2a0cd3a01ec62cca183fc1555833a2d43764950ef8cb5948c8abfc51014"},
+    {file = "pandas-1.3.2-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:0cd5776be891331a3e6b425b5abeab9596abea18435c5982191356f9b24ae731"},
+    {file = "pandas-1.3.2-cp39-cp39-win32.whl", hash = "sha256:66a95361b81b4ba04b699ecd2416b0591f40cd1e24c60a8bfe0d19009cfa575a"},
+    {file = "pandas-1.3.2-cp39-cp39-win_amd64.whl", hash = "sha256:89f40e5d21814192802421df809f948247d39ffe171e45fe2ab4abf7bd4279d8"},
+    {file = "pandas-1.3.2.tar.gz", hash = "sha256:cbcb84d63867af3411fa063af3de64902665bb5b3d40b25b2059e40603594e87"},
+]
+pandocfilters = [
+    {file = "pandocfilters-1.4.3.tar.gz", hash = "sha256:bc63fbb50534b4b1f8ebe1860889289e8af94a23bff7445259592df25a3906eb"},
+]
+parso = [
+    {file = "parso-0.8.2-py2.py3-none-any.whl", hash = "sha256:a8c4922db71e4fdb90e0d0bc6e50f9b273d3397925e5e60a717e719201778d22"},
+    {file = "parso-0.8.2.tar.gz", hash = "sha256:12b83492c6239ce32ff5eed6d3639d6a536170723c6f3f1506869f1ace413398"},
+]
+pexpect = [
+    {file = "pexpect-4.8.0-py2.py3-none-any.whl", hash = "sha256:0b48a55dcb3c05f3329815901ea4fc1537514d6ba867a152b581d69ae3710937"},
+    {file = "pexpect-4.8.0.tar.gz", hash = "sha256:fc65a43959d153d0114afe13997d439c22823a27cefceb5ff35c2178c6784c0c"},
+]
+pickleshare = [
+    {file = "pickleshare-0.7.5-py2.py3-none-any.whl", hash = "sha256:9649af414d74d4df115d5d718f82acb59c9d418196b7b4290ed47a12ce62df56"},
+    {file = "pickleshare-0.7.5.tar.gz", hash = "sha256:87683d47965c1da65cdacaf31c8441d12b8044cdec9aca500cd78fc2c683afca"},
+]
+pillow = [
+    {file = "Pillow-8.3.1-1-cp36-cp36m-win_amd64.whl", hash = "sha256:fd7eef578f5b2200d066db1b50c4aa66410786201669fb76d5238b007918fb24"},
+    {file = "Pillow-8.3.1-1-cp37-cp37m-win_amd64.whl", hash = "sha256:75e09042a3b39e0ea61ce37e941221313d51a9c26b8e54e12b3ececccb71718a"},
+    {file = "Pillow-8.3.1-1-cp38-cp38-win_amd64.whl", hash = "sha256:c0e0550a404c69aab1e04ae89cca3e2a042b56ab043f7f729d984bf73ed2a093"},
+    {file = "Pillow-8.3.1-1-cp39-cp39-win_amd64.whl", hash = "sha256:479ab11cbd69612acefa8286481f65c5dece2002ffaa4f9db62682379ca3bb77"},
+    {file = "Pillow-8.3.1-1-pp37-pypy37_pp73-win_amd64.whl", hash = "sha256:f156d6ecfc747ee111c167f8faf5f4953761b5e66e91a4e6767e548d0f80129c"},
+    {file = "Pillow-8.3.1-cp36-cp36m-macosx_10_10_x86_64.whl", hash = "sha256:196560dba4da7a72c5e7085fccc5938ab4075fd37fe8b5468869724109812edd"},
+    {file = "Pillow-8.3.1-cp36-cp36m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:29c9569049d04aaacd690573a0398dbd8e0bf0255684fee512b413c2142ab723"},
+    {file = "Pillow-8.3.1-cp36-cp36m-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:c088a000dfdd88c184cc7271bfac8c5b82d9efa8637cd2b68183771e3cf56f04"},
+    {file = "Pillow-8.3.1-cp36-cp36m-manylinux_2_5_x86_64.manylinux1_x86_64.whl", hash = "sha256:fc214a6b75d2e0ea7745488da7da3c381f41790812988c7a92345978414fad37"},
+    {file = "Pillow-8.3.1-cp36-cp36m-win32.whl", hash = "sha256:a17ca41f45cf78c2216ebfab03add7cc350c305c38ff34ef4eef66b7d76c5229"},
+    {file = "Pillow-8.3.1-cp36-cp36m-win_amd64.whl", hash = "sha256:67b3666b544b953a2777cb3f5a922e991be73ab32635666ee72e05876b8a92de"},
+    {file = "Pillow-8.3.1-cp37-cp37m-macosx_10_10_x86_64.whl", hash = "sha256:ff04c373477723430dce2e9d024c708a047d44cf17166bf16e604b379bf0ca14"},
+    {file = "Pillow-8.3.1-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:9364c81b252d8348e9cc0cb63e856b8f7c1b340caba6ee7a7a65c968312f7dab"},
+    {file = "Pillow-8.3.1-cp37-cp37m-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:a2f381932dca2cf775811a008aa3027671ace723b7a38838045b1aee8669fdcf"},
+    {file = "Pillow-8.3.1-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.whl", hash = "sha256:d0da39795049a9afcaadec532e7b669b5ebbb2a9134576ebcc15dd5bdae33cc0"},
+    {file = "Pillow-8.3.1-cp37-cp37m-win32.whl", hash = "sha256:2b6dfa068a8b6137da34a4936f5a816aba0ecc967af2feeb32c4393ddd671cba"},
+    {file = "Pillow-8.3.1-cp37-cp37m-win_amd64.whl", hash = "sha256:a4eef1ff2d62676deabf076f963eda4da34b51bc0517c70239fafed1d5b51500"},
+    {file = "Pillow-8.3.1-cp38-cp38-macosx_10_10_x86_64.whl", hash = "sha256:660a87085925c61a0dcc80efb967512ac34dbb256ff7dd2b9b4ee8dbdab58cf4"},
+    {file = "Pillow-8.3.1-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:15a2808e269a1cf2131930183dcc0419bc77bb73eb54285dde2706ac9939fa8e"},
+    {file = "Pillow-8.3.1-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:969cc558cca859cadf24f890fc009e1bce7d7d0386ba7c0478641a60199adf79"},
+    {file = "Pillow-8.3.1-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:2ee77c14a0299d0541d26f3d8500bb57e081233e3fa915fa35abd02c51fa7fae"},
+    {file = "Pillow-8.3.1-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.whl", hash = "sha256:c11003197f908878164f0e6da15fce22373ac3fc320cda8c9d16e6bba105b844"},
+    {file = "Pillow-8.3.1-cp38-cp38-win32.whl", hash = "sha256:3f08bd8d785204149b5b33e3b5f0ebbfe2190ea58d1a051c578e29e39bfd2367"},
+    {file = "Pillow-8.3.1-cp38-cp38-win_amd64.whl", hash = "sha256:70af7d222df0ff81a2da601fab42decb009dc721545ed78549cb96e3a1c5f0c8"},
+    {file = "Pillow-8.3.1-cp39-cp39-macosx_10_10_x86_64.whl", hash = "sha256:37730f6e68bdc6a3f02d2079c34c532330d206429f3cee651aab6b66839a9f0e"},
+    {file = "Pillow-8.3.1-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:4bc3c7ef940eeb200ca65bd83005eb3aae8083d47e8fcbf5f0943baa50726856"},
+    {file = "Pillow-8.3.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c35d09db702f4185ba22bb33ef1751ad49c266534339a5cebeb5159d364f6f82"},
+    {file = "Pillow-8.3.1-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:0b2efa07f69dc395d95bb9ef3299f4ca29bcb2157dc615bae0b42c3c20668ffc"},
+    {file = "Pillow-8.3.1-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.whl", hash = "sha256:cc866706d56bd3a7dbf8bac8660c6f6462f2f2b8a49add2ba617bc0c54473d83"},
+    {file = "Pillow-8.3.1-cp39-cp39-win32.whl", hash = "sha256:9a211b663cf2314edbdb4cf897beeb5c9ee3810d1d53f0e423f06d6ebbf9cd5d"},
+    {file = "Pillow-8.3.1-cp39-cp39-win_amd64.whl", hash = "sha256:c2a5ff58751670292b406b9f06e07ed1446a4b13ffced6b6cab75b857485cbc8"},
+    {file = "Pillow-8.3.1-pp36-pypy36_pp73-macosx_10_10_x86_64.whl", hash = "sha256:c379425c2707078dfb6bfad2430728831d399dc95a7deeb92015eb4c92345eaf"},
+    {file = "Pillow-8.3.1-pp36-pypy36_pp73-manylinux_2_12_i686.manylinux2010_i686.whl", hash = "sha256:114f816e4f73f9ec06997b2fde81a92cbf0777c9e8f462005550eed6bae57e63"},
+    {file = "Pillow-8.3.1-pp36-pypy36_pp73-manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:8960a8a9f4598974e4c2aeb1bff9bdd5db03ee65fd1fce8adf3223721aa2a636"},
+    {file = "Pillow-8.3.1-pp37-pypy37_pp73-macosx_10_10_x86_64.whl", hash = "sha256:147bd9e71fb9dcf08357b4d530b5167941e222a6fd21f869c7911bac40b9994d"},
+    {file = "Pillow-8.3.1-pp37-pypy37_pp73-manylinux_2_12_i686.manylinux2010_i686.whl", hash = "sha256:1fd5066cd343b5db88c048d971994e56b296868766e461b82fa4e22498f34d77"},
+    {file = "Pillow-8.3.1-pp37-pypy37_pp73-manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:f4ebde71785f8bceb39dcd1e7f06bcc5d5c3cf48b9f69ab52636309387b097c8"},
+    {file = "Pillow-8.3.1-pp37-pypy37_pp73-win_amd64.whl", hash = "sha256:1c03e24be975e2afe70dfc5da6f187eea0b49a68bb2b69db0f30a61b7031cee4"},
+    {file = "Pillow-8.3.1.tar.gz", hash = "sha256:2cac53839bfc5cece8fdbe7f084d5e3ee61e1303cccc86511d351adcb9e2c792"},
+]
+prometheus-client = [
+    {file = "prometheus_client-0.11.0-py2.py3-none-any.whl", hash = "sha256:b014bc76815eb1399da8ce5fc84b7717a3e63652b0c0f8804092c9363acab1b2"},
+    {file = "prometheus_client-0.11.0.tar.gz", hash = "sha256:3a8baade6cb80bcfe43297e33e7623f3118d660d41387593758e2fb1ea173a86"},
+]
+prompt-toolkit = [
+    {file = "prompt_toolkit-3.0.19-py3-none-any.whl", hash = "sha256:7089d8d2938043508aa9420ec18ce0922885304cddae87fb96eebca942299f88"},
+    {file = "prompt_toolkit-3.0.19.tar.gz", hash = "sha256:08360ee3a3148bdb5163621709ee322ec34fc4375099afa4bbf751e9b7b7fa4f"},
+]
+ptyprocess = [
+    {file = "ptyprocess-0.7.0-py2.py3-none-any.whl", hash = "sha256:4b41f3967fce3af57cc7e94b888626c18bf37a083e3651ca8feeb66d492fef35"},
+    {file = "ptyprocess-0.7.0.tar.gz", hash = "sha256:5c5d0a3b48ceee0b48485e0c26037c0acd7d29765ca3fbb5cb3831d347423220"},
+]
+py = [
+    {file = "py-1.10.0-py2.py3-none-any.whl", hash = "sha256:3b80836aa6d1feeaa108e046da6423ab8f6ceda6468545ae8d02d9d58d18818a"},
+    {file = "py-1.10.0.tar.gz", hash = "sha256:21b81bda15b66ef5e1a777a21c4dcd9c20ad3efd0b3f817e7a809035269e1bd3"},
+]
+pyarrow = [
+    {file = "pyarrow-5.0.0-cp36-cp36m-macosx_10_13_x86_64.whl", hash = "sha256:e9ec80f4a77057498cf4c5965389e42e7f6a618b6859e6dd615e57505c9167a6"},
+    {file = "pyarrow-5.0.0-cp36-cp36m-macosx_10_9_x86_64.whl", hash = "sha256:b1453c2411b5062ba6bf6832dbc4df211ad625f678c623a2ee177aee158f199b"},
+    {file = "pyarrow-5.0.0-cp36-cp36m-manylinux2010_x86_64.whl", hash = "sha256:9e04d3621b9f2f23898eed0d044203f66c156d880f02c5534a7f9947ebb1a4af"},
+    {file = "pyarrow-5.0.0-cp36-cp36m-manylinux2014_aarch64.whl", hash = "sha256:64f30aa6b28b666a925d11c239344741850eb97c29d3aa0f7187918cf82494f7"},
+    {file = "pyarrow-5.0.0-cp36-cp36m-manylinux2014_x86_64.whl", hash = "sha256:99c8b0f7e2ce2541dd4c0c0101d9944bb8e592ae3295fe7a2f290ab99222666d"},
+    {file = "pyarrow-5.0.0-cp36-cp36m-win_amd64.whl", hash = "sha256:456a4488ae810a0569d1adf87dbc522bcc9a0e4a8d1809b934ca28c163d8edce"},
+    {file = "pyarrow-5.0.0-cp37-cp37m-macosx_10_13_x86_64.whl", hash = "sha256:c5493d2414d0d690a738aac8dd6d38518d1f9b870e52e24f89d8d7eb3afd4161"},
+    {file = "pyarrow-5.0.0-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:1832709281efefa4f199c639e9f429678286329860188e53beeda71750775923"},
+    {file = "pyarrow-5.0.0-cp37-cp37m-manylinux2010_x86_64.whl", hash = "sha256:b6387d2058d95fa48ccfedea810a768187affb62f4a3ef6595fa30bf9d1a65cf"},
+    {file = "pyarrow-5.0.0-cp37-cp37m-manylinux2014_aarch64.whl", hash = "sha256:bbe2e439bec2618c74a3bb259700c8a7353dc2ea0c5a62686b6cf04a50ab1e0d"},
+    {file = "pyarrow-5.0.0-cp37-cp37m-manylinux2014_x86_64.whl", hash = "sha256:5c0d1b68e67bb334a5af0cecdf9b6a702aaa4cc259c5cbb71b25bbed40fcedaf"},
+    {file = "pyarrow-5.0.0-cp37-cp37m-win_amd64.whl", hash = "sha256:6e937ce4a40ea0cc7896faff96adecadd4485beb53fbf510b46858e29b2e75ae"},
+    {file = "pyarrow-5.0.0-cp38-cp38-macosx_10_13_x86_64.whl", hash = "sha256:7560332e5846f0e7830b377c14c93624e24a17f91c98f0b25dafb0ca1ea6ba02"},
+    {file = "pyarrow-5.0.0-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:53e550dec60d1ab86cba3afa1719dc179a8bc9632a0e50d9fe91499cf0a7f2bc"},
+    {file = "pyarrow-5.0.0-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:2d26186ca9748a1fb89ae6c1fa04fb343a4279b53f118734ea8096f15d66c820"},
+    {file = "pyarrow-5.0.0-cp38-cp38-manylinux2010_x86_64.whl", hash = "sha256:7c4edd2bacee3eea6c8c28bddb02347f9d41a55ec9692c71c6de6e47c62a7f0d"},
+    {file = "pyarrow-5.0.0-cp38-cp38-manylinux2014_aarch64.whl", hash = "sha256:601b0aabd6fb066429e706282934d4d8d38f53bdb8d82da9576be49f07eedf5c"},
+    {file = "pyarrow-5.0.0-cp38-cp38-manylinux2014_x86_64.whl", hash = "sha256:ff21711f6ff3b0bc90abc8ca8169e676faeb2401ddc1a0bc1c7dc181708a3406"},
+    {file = "pyarrow-5.0.0-cp38-cp38-win_amd64.whl", hash = "sha256:ed135a99975380c27077f9d0e210aea8618ed9fadcec0e71f8a3190939557afe"},
+    {file = "pyarrow-5.0.0-cp39-cp39-macosx_10_13_universal2.whl", hash = "sha256:6e1f0e4374061116f40e541408a8a170c170d0a070b788717e18165ebfdd2a54"},
+    {file = "pyarrow-5.0.0-cp39-cp39-macosx_10_13_x86_64.whl", hash = "sha256:4341ac0f552dc04c450751e049976940c7f4f8f2dae03685cc465ebe0a61e231"},
+    {file = "pyarrow-5.0.0-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:c3fc856f107ca2fb3c9391d7ea33bbb33f3a1c2b4a0e2b41f7525c626214cc03"},
+    {file = "pyarrow-5.0.0-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:357605665fbefb573d40939b13a684c2490b6ed1ab4a5de8dd246db4ab02e5a4"},
+    {file = "pyarrow-5.0.0-cp39-cp39-manylinux2010_x86_64.whl", hash = "sha256:f4db312e9ba80e730cefcae0a05b63ea5befc7634c28df56682b628ad8e1c25c"},
+    {file = "pyarrow-5.0.0-cp39-cp39-manylinux2014_aarch64.whl", hash = "sha256:1d9485741e497ccc516cb0a0c8f56e22be55aea815be185c3f9a681323b0e614"},
+    {file = "pyarrow-5.0.0-cp39-cp39-manylinux2014_x86_64.whl", hash = "sha256:b3115df938b8d7a7372911a3cb3904196194bcea8bb48911b4b3eafee3ab8d90"},
+    {file = "pyarrow-5.0.0-cp39-cp39-win_amd64.whl", hash = "sha256:4d8adda1892ef4553c4804af7f67cce484f4d6371564e2d8374b8e2bc85293e2"},
+    {file = "pyarrow-5.0.0.tar.gz", hash = "sha256:24e64ea33eed07441cc0e80c949e3a1b48211a1add8953268391d250f4d39922"},
+]
+pycparser = [
+    {file = "pycparser-2.20-py2.py3-none-any.whl", hash = "sha256:7582ad22678f0fcd81102833f60ef8d0e57288b6b5fb00323d101be910e35705"},
+    {file = "pycparser-2.20.tar.gz", hash = "sha256:2d475327684562c3a96cc71adf7dc8c4f0565175cf86b6d7a404ff4c771f15f0"},
+]
+pyGeoDb = []
+pygments = [
+    {file = "Pygments-2.10.0-py3-none-any.whl", hash = "sha256:b8e67fe6af78f492b3c4b3e2970c0624cbf08beb1e493b2c99b9fa1b67a20380"},
+    {file = "Pygments-2.10.0.tar.gz", hash = "sha256:f398865f7eb6874156579fdf36bc840a03cab64d1cde9e93d68f46a425ec52c6"},
+]
+pyparsing = [
+    {file = "pyparsing-2.4.7-py2.py3-none-any.whl", hash = "sha256:ef9d7589ef3c200abe66653d3f1ab1033c3c419ae9b9bdb1240a85b024efc88b"},
+    {file = "pyparsing-2.4.7.tar.gz", hash = "sha256:c203ec8783bf771a155b207279b9bccb8dea02d8f0c9e5f8ead507bc3246ecc1"},
+]
+pyproj = [
+    {file = "pyproj-3.1.0-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:8eda240225971b5cd0bac2d399ed6222068f0598ee92d5f6e847bd2019d2c8b0"},
+    {file = "pyproj-3.1.0-cp37-cp37m-manylinux2010_x86_64.whl", hash = "sha256:ae237492767e0225f99b53a0fd7110fde2b7e7cabc105bbc243c151a7497de88"},
+    {file = "pyproj-3.1.0-cp37-cp37m-manylinux_2_12_i686.manylinux2010_i686.whl", hash = "sha256:b635e7e21fea5af74e90fc9e54d1a4c27078efdce6f214101c98dd93afae599a"},
+    {file = "pyproj-3.1.0-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:aa87df0982aa0f4477478899d9c930cc0f97cd6d8a4ce84c43ac88ccf86d1da7"},
+    {file = "pyproj-3.1.0-cp37-cp37m-win32.whl", hash = "sha256:10dad599b9f7ce2194996dc25f1000e0aa15754ecef9db46b624713959c67957"},
+    {file = "pyproj-3.1.0-cp37-cp37m-win_amd64.whl", hash = "sha256:a162ed199cd2ec392cffe20b2fa3381b68e7a166d55f3f060eceb8d517e4f46d"},
+    {file = "pyproj-3.1.0-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:1e88ebc4e08e661e9011b5c1ebfb32f0d311963a9824a6effb4168c7e07918b1"},
+    {file = "pyproj-3.1.0-cp38-cp38-manylinux2010_x86_64.whl", hash = "sha256:da88abc5e2f6a8fb07533855a57ca2a31845f58901a87f821b68b0db6b023978"},
+    {file = "pyproj-3.1.0-cp38-cp38-manylinux_2_12_i686.manylinux2010_i686.whl", hash = "sha256:911d773da9fa4d4f3f7580173858c391e3ee0b61acaf0be303baab323d2eae78"},
+    {file = "pyproj-3.1.0-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:5f8a8d982bde211e65dc2de1f8f36cf162f9cc7fcd8a7625046ea265284e5e65"},
+    {file = "pyproj-3.1.0-cp38-cp38-win32.whl", hash = "sha256:c4193e1069d165476b2d0f7d882b7712b3eab6e2e6fe2a0a78ef40de825a1f28"},
+    {file = "pyproj-3.1.0-cp38-cp38-win_amd64.whl", hash = "sha256:b6c74bbec679199746a3e02c0e0fad093c3652df96dd63e086a2fbf2afe9dc0e"},
+    {file = "pyproj-3.1.0-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:04c185102e659439c5bd428ac5473d36ef795fca8e225bbbe78e20643d804ec0"},
+    {file = "pyproj-3.1.0-cp39-cp39-manylinux2010_x86_64.whl", hash = "sha256:ebbba7707fe83a01e54bce8e3e7342feb0b3e0d74ff8c28df12f8bc59b76827c"},
+    {file = "pyproj-3.1.0-cp39-cp39-manylinux_2_12_i686.manylinux2010_i686.whl", hash = "sha256:9cc464a1c51baad28ffb7a233116e8d4ce4c560b32039fa986d0f992ac3c431f"},
+    {file = "pyproj-3.1.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:4f3ad09cf3352bf5664794042b28d98781362ec8d9774ad73f28a1a0101a27f1"},
+    {file = "pyproj-3.1.0-cp39-cp39-win32.whl", hash = "sha256:ae5534fa7a3b74f20534694d297fce6f7483890ff6ca404394ecf372f3c589d4"},
+    {file = "pyproj-3.1.0-cp39-cp39-win_amd64.whl", hash = "sha256:808f5992320e9631b2e45444028a65cd6ba3ee40229292934178ef07020a5ffd"},
+    {file = "pyproj-3.1.0.tar.gz", hash = "sha256:67b94f4e694ae33fc90dfb7da0e6b5ed5f671dd0acc2f6cf46e9c39d56e16e1a"},
+]
+pyrsistent = [
+    {file = "pyrsistent-0.18.0-cp36-cp36m-macosx_10_9_x86_64.whl", hash = "sha256:f4c8cabb46ff8e5d61f56a037974228e978f26bfefce4f61a4b1ac0ba7a2ab72"},
+    {file = "pyrsistent-0.18.0-cp36-cp36m-manylinux1_i686.whl", hash = "sha256:da6e5e818d18459fa46fac0a4a4e543507fe1110e808101277c5a2b5bab0cd2d"},
+    {file = "pyrsistent-0.18.0-cp36-cp36m-manylinux1_x86_64.whl", hash = "sha256:5e4395bbf841693eaebaa5bb5c8f5cdbb1d139e07c975c682ec4e4f8126e03d2"},
+    {file = "pyrsistent-0.18.0-cp36-cp36m-win32.whl", hash = "sha256:527be2bfa8dc80f6f8ddd65242ba476a6c4fb4e3aedbf281dfbac1b1ed4165b1"},
+    {file = "pyrsistent-0.18.0-cp36-cp36m-win_amd64.whl", hash = "sha256:2aaf19dc8ce517a8653746d98e962ef480ff34b6bc563fc067be6401ffb457c7"},
+    {file = "pyrsistent-0.18.0-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:58a70d93fb79dc585b21f9d72487b929a6fe58da0754fa4cb9f279bb92369396"},
+    {file = "pyrsistent-0.18.0-cp37-cp37m-manylinux1_i686.whl", hash = "sha256:4916c10896721e472ee12c95cdc2891ce5890898d2f9907b1b4ae0f53588b710"},
+    {file = "pyrsistent-0.18.0-cp37-cp37m-manylinux1_x86_64.whl", hash = "sha256:73ff61b1411e3fb0ba144b8f08d6749749775fe89688093e1efef9839d2dcc35"},
+    {file = "pyrsistent-0.18.0-cp37-cp37m-win32.whl", hash = "sha256:b29b869cf58412ca5738d23691e96d8aff535e17390128a1a52717c9a109da4f"},
+    {file = "pyrsistent-0.18.0-cp37-cp37m-win_amd64.whl", hash = "sha256:097b96f129dd36a8c9e33594e7ebb151b1515eb52cceb08474c10a5479e799f2"},
+    {file = "pyrsistent-0.18.0-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:772e94c2c6864f2cd2ffbe58bb3bdefbe2a32afa0acb1a77e472aac831f83427"},
+    {file = "pyrsistent-0.18.0-cp38-cp38-manylinux1_i686.whl", hash = "sha256:c1a9ff320fa699337e05edcaae79ef8c2880b52720bc031b219e5b5008ebbdef"},
+    {file = "pyrsistent-0.18.0-cp38-cp38-manylinux1_x86_64.whl", hash = "sha256:cd3caef37a415fd0dae6148a1b6957a8c5f275a62cca02e18474608cb263640c"},
+    {file = "pyrsistent-0.18.0-cp38-cp38-win32.whl", hash = "sha256:e79d94ca58fcafef6395f6352383fa1a76922268fa02caa2272fff501c2fdc78"},
+    {file = "pyrsistent-0.18.0-cp38-cp38-win_amd64.whl", hash = "sha256:a0c772d791c38bbc77be659af29bb14c38ced151433592e326361610250c605b"},
+    {file = "pyrsistent-0.18.0-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:d5ec194c9c573aafaceebf05fc400656722793dac57f254cd4741f3c27ae57b4"},
+    {file = "pyrsistent-0.18.0-cp39-cp39-manylinux1_i686.whl", hash = "sha256:6b5eed00e597b5b5773b4ca30bd48a5774ef1e96f2a45d105db5b4ebb4bca680"},
+    {file = "pyrsistent-0.18.0-cp39-cp39-manylinux1_x86_64.whl", hash = "sha256:48578680353f41dca1ca3dc48629fb77dfc745128b56fc01096b2530c13fd426"},
+    {file = "pyrsistent-0.18.0-cp39-cp39-win32.whl", hash = "sha256:f3ef98d7b76da5eb19c37fda834d50262ff9167c65658d1d8f974d2e4d90676b"},
+    {file = "pyrsistent-0.18.0-cp39-cp39-win_amd64.whl", hash = "sha256:404e1f1d254d314d55adb8d87f4f465c8693d6f902f67eb6ef5b4526dc58e6ea"},
+    {file = "pyrsistent-0.18.0.tar.gz", hash = "sha256:773c781216f8c2900b42a7b638d5b517bb134ae1acbebe4d1e8f1f41ea60eb4b"},
+]
+python-dateutil = [
+    {file = "python-dateutil-2.8.2.tar.gz", hash = "sha256:0123cacc1627ae19ddf3c27a5de5bd67ee4586fbdd6440d9748f8abb483d3e86"},
+    {file = "python_dateutil-2.8.2-py2.py3-none-any.whl", hash = "sha256:961d03dc3453ebbc59dbdea9e4e11c5651520a876d0f4db161e8674aae935da9"},
+]
+pytz = [
+    {file = "pytz-2021.1-py2.py3-none-any.whl", hash = "sha256:eb10ce3e7736052ed3623d49975ce333bcd712c7bb19a58b9e2089d4057d0798"},
+    {file = "pytz-2021.1.tar.gz", hash = "sha256:83a4a90894bf38e243cf052c8b58f381bfe9a7a483f6a9cab140bc7f702ac4da"},
+]
+pywavelets = [
+    {file = "PyWavelets-1.1.1-cp35-cp35m-macosx_10_6_intel.whl", hash = "sha256:35959c041ec014648575085a97b498eafbbaa824f86f6e4a59bfdef8a3fe6308"},
+    {file = "PyWavelets-1.1.1-cp35-cp35m-manylinux1_i686.whl", hash = "sha256:55e39ec848ceec13c9fa1598253ae9dd5c31d09dfd48059462860d2b908fb224"},
+    {file = "PyWavelets-1.1.1-cp35-cp35m-manylinux1_x86_64.whl", hash = "sha256:c06d2e340c7bf8b9ec71da2284beab8519a3908eab031f4ea126e8ccfc3fd567"},
+    {file = "PyWavelets-1.1.1-cp35-cp35m-win32.whl", hash = "sha256:be105382961745f88d8196bba5a69ee2c4455d87ad2a2e5d1eed6bd7fda4d3fd"},
+    {file = "PyWavelets-1.1.1-cp35-cp35m-win_amd64.whl", hash = "sha256:076ca8907001fdfe4205484f719d12b4a0262dfe6652fa1cfc3c5c362d14dc84"},
+    {file = "PyWavelets-1.1.1-cp36-cp36m-macosx_10_9_x86_64.whl", hash = "sha256:7947e51ca05489b85928af52a34fe67022ab5b81d4ae32a4109a99e883a0635e"},
+    {file = "PyWavelets-1.1.1-cp36-cp36m-manylinux1_i686.whl", hash = "sha256:9e2528823ccf5a0a1d23262dfefe5034dce89cd84e4e124dc553dfcdf63ebb92"},
+    {file = "PyWavelets-1.1.1-cp36-cp36m-manylinux1_x86_64.whl", hash = "sha256:80b924edbc012ded8aa8b91cb2fd6207fb1a9a3a377beb4049b8a07445cec6f0"},
+    {file = "PyWavelets-1.1.1-cp36-cp36m-manylinux2014_aarch64.whl", hash = "sha256:c2a799e79cee81a862216c47e5623c97b95f1abee8dd1f9eed736df23fb653fb"},
+    {file = "PyWavelets-1.1.1-cp36-cp36m-win32.whl", hash = "sha256:d510aef84d9852653d079c84f2f81a82d5d09815e625f35c95714e7364570ad4"},
+    {file = "PyWavelets-1.1.1-cp36-cp36m-win_amd64.whl", hash = "sha256:889d4c5c5205a9c90118c1980df526857929841df33e4cd1ff1eff77c6817a65"},
+    {file = "PyWavelets-1.1.1-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:68b5c33741d26c827074b3d8f0251de1c3019bb9567b8d303eb093c822ce28f1"},
+    {file = "PyWavelets-1.1.1-cp37-cp37m-manylinux1_i686.whl", hash = "sha256:18a51b3f9416a2ae6e9a35c4af32cf520dd7895f2b69714f4aa2f4342fca47f9"},
+    {file = "PyWavelets-1.1.1-cp37-cp37m-manylinux1_x86_64.whl", hash = "sha256:cfe79844526dd92e3ecc9490b5031fca5f8ab607e1e858feba232b1b788ff0ea"},
+    {file = "PyWavelets-1.1.1-cp37-cp37m-manylinux2014_aarch64.whl", hash = "sha256:2f7429eeb5bf9c7068002d0d7f094ed654c77a70ce5e6198737fd68ab85f8311"},
+    {file = "PyWavelets-1.1.1-cp37-cp37m-win32.whl", hash = "sha256:720dbcdd3d91c6dfead79c80bf8b00a1d8aa4e5d551dc528c6d5151e4efc3403"},
+    {file = "PyWavelets-1.1.1-cp37-cp37m-win_amd64.whl", hash = "sha256:bc5e87b72371da87c9bebc68e54882aada9c3114e640de180f62d5da95749cd3"},
+    {file = "PyWavelets-1.1.1-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:98b2669c5af842a70cfab33a7043fcb5e7535a690a00cd251b44c9be0be418e5"},
+    {file = "PyWavelets-1.1.1-cp38-cp38-manylinux1_i686.whl", hash = "sha256:e02a0558e0c2ac8b8bbe6a6ac18c136767ec56b96a321e0dfde2173adfa5a504"},
+    {file = "PyWavelets-1.1.1-cp38-cp38-manylinux1_x86_64.whl", hash = "sha256:6162dc0ae04669ea04b4b51420777b9ea2d30b0a9d02901b2a3b4d61d159c2e9"},
+    {file = "PyWavelets-1.1.1-cp38-cp38-manylinux2014_aarch64.whl", hash = "sha256:39c74740718e420d38c78ca4498568fa57976d78d5096277358e0fa9629a7aea"},
+    {file = "PyWavelets-1.1.1-cp38-cp38-win32.whl", hash = "sha256:79f5b54f9dc353e5ee47f0c3f02bebd2c899d49780633aa771fed43fa20b3149"},
+    {file = "PyWavelets-1.1.1-cp38-cp38-win_amd64.whl", hash = "sha256:935ff247b8b78bdf77647fee962b1cc208c51a7b229db30b9ba5f6da3e675178"},
+    {file = "PyWavelets-1.1.1-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:6ebfefebb5c6494a3af41ad8c60248a95da267a24b79ed143723d4502b1fe4d7"},
+    {file = "PyWavelets-1.1.1-cp39-cp39-manylinux1_i686.whl", hash = "sha256:6bc78fb9c42a716309b4ace56f51965d8b5662c3ba19d4591749f31773db1125"},
+    {file = "PyWavelets-1.1.1-cp39-cp39-manylinux1_x86_64.whl", hash = "sha256:411e17ca6ed8cf5e18a7ca5ee06a91c25800cc6c58c77986202abf98d749273a"},
+    {file = "PyWavelets-1.1.1-cp39-cp39-manylinux2014_aarch64.whl", hash = "sha256:83c5e3eb78ce111c2f0b45f46106cc697c3cb6c4e5f51308e1f81b512c70c8fb"},
+    {file = "PyWavelets-1.1.1-cp39-cp39-win32.whl", hash = "sha256:2b634a54241c190ee989a4af87669d377b37c91bcc9cf0efe33c10ff847f7841"},
+    {file = "PyWavelets-1.1.1-cp39-cp39-win_amd64.whl", hash = "sha256:732bab78435c48be5d6bc75486ef629d7c8f112e07b313bf1f1a2220ab437277"},
+    {file = "PyWavelets-1.1.1.tar.gz", hash = "sha256:1a64b40f6acb4ffbaccce0545d7fc641744f95351f62e4c6aaa40549326008c9"},
+]
+pywin32 = [
+    {file = "pywin32-301-cp35-cp35m-win32.whl", hash = "sha256:93367c96e3a76dfe5003d8291ae16454ca7d84bb24d721e0b74a07610b7be4a7"},
+    {file = "pywin32-301-cp35-cp35m-win_amd64.whl", hash = "sha256:9635df6998a70282bd36e7ac2a5cef9ead1627b0a63b17c731312c7a0daebb72"},
+    {file = "pywin32-301-cp36-cp36m-win32.whl", hash = "sha256:c866f04a182a8cb9b7855de065113bbd2e40524f570db73ef1ee99ff0a5cc2f0"},
+    {file = "pywin32-301-cp36-cp36m-win_amd64.whl", hash = "sha256:dafa18e95bf2a92f298fe9c582b0e205aca45c55f989937c52c454ce65b93c78"},
+    {file = "pywin32-301-cp37-cp37m-win32.whl", hash = "sha256:98f62a3f60aa64894a290fb7494bfa0bfa0a199e9e052e1ac293b2ad3cd2818b"},
+    {file = "pywin32-301-cp37-cp37m-win_amd64.whl", hash = "sha256:fb3b4933e0382ba49305cc6cd3fb18525df7fd96aa434de19ce0878133bf8e4a"},
+    {file = "pywin32-301-cp38-cp38-win32.whl", hash = "sha256:88981dd3cfb07432625b180f49bf4e179fb8cbb5704cd512e38dd63636af7a17"},
+    {file = "pywin32-301-cp38-cp38-win_amd64.whl", hash = "sha256:8c9d33968aa7fcddf44e47750e18f3d034c3e443a707688a008a2e52bbef7e96"},
+    {file = "pywin32-301-cp39-cp39-win32.whl", hash = "sha256:595d397df65f1b2e0beaca63a883ae6d8b6df1cdea85c16ae85f6d2e648133fe"},
+    {file = "pywin32-301-cp39-cp39-win_amd64.whl", hash = "sha256:87604a4087434cd814ad8973bd47d6524bd1fa9e971ce428e76b62a5e0860fdf"},
+]
+pywinpty = [
+    {file = "pywinpty-1.1.3-cp36-none-win_amd64.whl", hash = "sha256:81dc6f16d917b756e06fc58943e9750d59dbefc0ffd2086871d3fa5f33824446"},
+    {file = "pywinpty-1.1.3-cp37-none-win_amd64.whl", hash = "sha256:54557887e712ea3215ab0d9f089ed55a6cc8d826cd5d1e340d75300654c9663f"},
+    {file = "pywinpty-1.1.3-cp38-none-win_amd64.whl", hash = "sha256:f5e25197397f1fef0362caf3eb89f25441827a1e48bf15827c27021592fd2160"},
+    {file = "pywinpty-1.1.3-cp39-none-win_amd64.whl", hash = "sha256:b767276224f86b7560eb9173ba7956758cafcdfab97bb33837d42d2a0f1dbf67"},
+    {file = "pywinpty-1.1.3.tar.gz", hash = "sha256:3a1d57b338390333812a5eed31c93c7d8ba82b131078063703e731946d90c9f2"},
+]
+pyyaml = [
+    {file = "PyYAML-5.4.1-cp27-cp27m-macosx_10_9_x86_64.whl", hash = "sha256:3b2b1824fe7112845700f815ff6a489360226a5609b96ec2190a45e62a9fc922"},
+    {file = "PyYAML-5.4.1-cp27-cp27m-win32.whl", hash = "sha256:129def1b7c1bf22faffd67b8f3724645203b79d8f4cc81f674654d9902cb4393"},
+    {file = "PyYAML-5.4.1-cp27-cp27m-win_amd64.whl", hash = "sha256:4465124ef1b18d9ace298060f4eccc64b0850899ac4ac53294547536533800c8"},
+    {file = "PyYAML-5.4.1-cp27-cp27mu-manylinux1_x86_64.whl", hash = "sha256:bb4191dfc9306777bc594117aee052446b3fa88737cd13b7188d0e7aa8162185"},
+    {file = "PyYAML-5.4.1-cp36-cp36m-macosx_10_9_x86_64.whl", hash = "sha256:6c78645d400265a062508ae399b60b8c167bf003db364ecb26dcab2bda048253"},
+    {file = "PyYAML-5.4.1-cp36-cp36m-manylinux1_x86_64.whl", hash = "sha256:4e0583d24c881e14342eaf4ec5fbc97f934b999a6828693a99157fde912540cc"},
+    {file = "PyYAML-5.4.1-cp36-cp36m-manylinux2014_aarch64.whl", hash = "sha256:72a01f726a9c7851ca9bfad6fd09ca4e090a023c00945ea05ba1638c09dc3347"},
+    {file = "PyYAML-5.4.1-cp36-cp36m-manylinux2014_s390x.whl", hash = "sha256:895f61ef02e8fed38159bb70f7e100e00f471eae2bc838cd0f4ebb21e28f8541"},
+    {file = "PyYAML-5.4.1-cp36-cp36m-win32.whl", hash = "sha256:3bd0e463264cf257d1ffd2e40223b197271046d09dadf73a0fe82b9c1fc385a5"},
+    {file = "PyYAML-5.4.1-cp36-cp36m-win_amd64.whl", hash = "sha256:e4fac90784481d221a8e4b1162afa7c47ed953be40d31ab4629ae917510051df"},
+    {file = "PyYAML-5.4.1-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:5accb17103e43963b80e6f837831f38d314a0495500067cb25afab2e8d7a4018"},
+    {file = "PyYAML-5.4.1-cp37-cp37m-manylinux1_x86_64.whl", hash = "sha256:e1d4970ea66be07ae37a3c2e48b5ec63f7ba6804bdddfdbd3cfd954d25a82e63"},
+    {file = "PyYAML-5.4.1-cp37-cp37m-manylinux2014_aarch64.whl", hash = "sha256:cb333c16912324fd5f769fff6bc5de372e9e7a202247b48870bc251ed40239aa"},
+    {file = "PyYAML-5.4.1-cp37-cp37m-manylinux2014_s390x.whl", hash = "sha256:fe69978f3f768926cfa37b867e3843918e012cf83f680806599ddce33c2c68b0"},
+    {file = "PyYAML-5.4.1-cp37-cp37m-win32.whl", hash = "sha256:dd5de0646207f053eb0d6c74ae45ba98c3395a571a2891858e87df7c9b9bd51b"},
+    {file = "PyYAML-5.4.1-cp37-cp37m-win_amd64.whl", hash = "sha256:08682f6b72c722394747bddaf0aa62277e02557c0fd1c42cb853016a38f8dedf"},
+    {file = "PyYAML-5.4.1-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:d2d9808ea7b4af864f35ea216be506ecec180628aced0704e34aca0b040ffe46"},
+    {file = "PyYAML-5.4.1-cp38-cp38-manylinux1_x86_64.whl", hash = "sha256:8c1be557ee92a20f184922c7b6424e8ab6691788e6d86137c5d93c1a6ec1b8fb"},
+    {file = "PyYAML-5.4.1-cp38-cp38-manylinux2014_aarch64.whl", hash = "sha256:fd7f6999a8070df521b6384004ef42833b9bd62cfee11a09bda1079b4b704247"},
+    {file = "PyYAML-5.4.1-cp38-cp38-manylinux2014_s390x.whl", hash = "sha256:bfb51918d4ff3d77c1c856a9699f8492c612cde32fd3bcd344af9be34999bfdc"},
+    {file = "PyYAML-5.4.1-cp38-cp38-win32.whl", hash = "sha256:fa5ae20527d8e831e8230cbffd9f8fe952815b2b7dae6ffec25318803a7528fc"},
+    {file = "PyYAML-5.4.1-cp38-cp38-win_amd64.whl", hash = "sha256:0f5f5786c0e09baddcd8b4b45f20a7b5d61a7e7e99846e3c799b05c7c53fa696"},
+    {file = "PyYAML-5.4.1-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:294db365efa064d00b8d1ef65d8ea2c3426ac366c0c4368d930bf1c5fb497f77"},
+    {file = "PyYAML-5.4.1-cp39-cp39-manylinux1_x86_64.whl", hash = "sha256:74c1485f7707cf707a7aef42ef6322b8f97921bd89be2ab6317fd782c2d53183"},
+    {file = "PyYAML-5.4.1-cp39-cp39-manylinux2014_aarch64.whl", hash = "sha256:d483ad4e639292c90170eb6f7783ad19490e7a8defb3e46f97dfe4bacae89122"},
+    {file = "PyYAML-5.4.1-cp39-cp39-manylinux2014_s390x.whl", hash = "sha256:fdc842473cd33f45ff6bce46aea678a54e3d21f1b61a7750ce3c498eedfe25d6"},
+    {file = "PyYAML-5.4.1-cp39-cp39-win32.whl", hash = "sha256:49d4cdd9065b9b6e206d0595fee27a96b5dd22618e7520c33204a4a3239d5b10"},
+    {file = "PyYAML-5.4.1-cp39-cp39-win_amd64.whl", hash = "sha256:c20cfa2d49991c8b4147af39859b167664f2ad4561704ee74c1de03318e898db"},
+    {file = "PyYAML-5.4.1.tar.gz", hash = "sha256:607774cbba28732bfa802b54baa7484215f530991055bb562efbed5b2f20a45e"},
+]
+pyzmq = [
+    {file = "pyzmq-22.2.1-cp310-cp310-macosx_10_15_universal2.whl", hash = "sha256:d60a407663b7c2af781ab7f49d94a3d379dd148bb69ea8d9dd5bc69adf18097c"},
+    {file = "pyzmq-22.2.1-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:631f932fb1fa4b76f31adf976f8056519bc6208a3c24c184581c3dd5be15066e"},
+    {file = "pyzmq-22.2.1-cp310-cp310-manylinux_2_12_i686.manylinux2010_i686.whl", hash = "sha256:0471d634c7fe48ff7d3849798da6c16afc71676dd890b5ae08eb1efe735c6fec"},
+    {file = "pyzmq-22.2.1-cp310-cp310-manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:f520e9fee5d7a2e09b051d924f85b977c6b4e224e56c0551c3c241bbeeb0ad8d"},
+    {file = "pyzmq-22.2.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c1b6619ceb33a8907f1cb82ff8afc8a133e7a5f16df29528e919734718600426"},
+    {file = "pyzmq-22.2.1-cp310-cp310-win32.whl", hash = "sha256:31c5dfb6df5148789835128768c01bf6402eb753d06f524f12f6786caf96fb44"},
+    {file = "pyzmq-22.2.1-cp310-cp310-win_amd64.whl", hash = "sha256:4842a8263cbaba6fce401bbe4e2b125321c401a01714e42624dabc554bfc2629"},
+    {file = "pyzmq-22.2.1-cp36-cp36m-macosx_10_9_x86_64.whl", hash = "sha256:b921758f8b5098faa85f341bbdd5e36d5339de5e9032ca2b07d8c8e7bec5069b"},
+    {file = "pyzmq-22.2.1-cp36-cp36m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:240b83b3a8175b2f616f80092cbb019fcd5c18598f78ffc6aa0ae9034b300f14"},
+    {file = "pyzmq-22.2.1-cp36-cp36m-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:da7f7f3bb08bcf59a6b60b4e53dd8f08bb00c9e61045319d825a906dbb3c8fb7"},
+    {file = "pyzmq-22.2.1-cp36-cp36m-manylinux_2_5_x86_64.manylinux1_x86_64.whl", hash = "sha256:e66025b64c4724ba683d6d4a4e5ee23de12fe9ae683908f0c7f0f91b4a2fd94e"},
+    {file = "pyzmq-22.2.1-cp36-cp36m-win32.whl", hash = "sha256:50d007d5702171bc810c1e74498fa2c7bc5b50f9750697f7fd2a3e71a25aad91"},
+    {file = "pyzmq-22.2.1-cp36-cp36m-win_amd64.whl", hash = "sha256:b4a51c7d906dc263a0cc5590761e53e0a68f2c2fefe549cbef21c9ee5d2d98a4"},
+    {file = "pyzmq-22.2.1-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:93705cb90baa9d6f75e8448861a1efd3329006f79095ab18846bd1eaa342f7c3"},
+    {file = "pyzmq-22.2.1-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:620b0abb813958cb3ecb5144c177e26cde92fee6f43c4b9de6b329515532bf27"},
+    {file = "pyzmq-22.2.1-cp37-cp37m-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:2dd3896b3c952cf6c8013deda53c1df16bf962f355b5503d23521e0f6403ae3d"},
+    {file = "pyzmq-22.2.1-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.whl", hash = "sha256:6e9c030222893afa86881d7485d3e841969760a16004bd23e9a83cca28b42778"},
+    {file = "pyzmq-22.2.1-cp37-cp37m-win32.whl", hash = "sha256:262f470e7acde18b7217aac78d19d2e29ced91a5afbeb7d98521ebf26461aa7e"},
+    {file = "pyzmq-22.2.1-cp37-cp37m-win_amd64.whl", hash = "sha256:246f27b88722cfa729bb04881e94484e40b085720d728c1b05133b3f331b0b7b"},
+    {file = "pyzmq-22.2.1-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:0d17bac19e934e9f547a8811b7c2a32651a7840f38086b924e2e3dcb2fae5c3a"},
+    {file = "pyzmq-22.2.1-cp38-cp38-manylinux_2_12_i686.manylinux2010_i686.whl", hash = "sha256:5933d1f4087de6e52906f72d92e1e4dcc630d371860b92c55d7f7a4b815a664c"},
+    {file = "pyzmq-22.2.1-cp38-cp38-manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:ac4497e4b7d134ee53ce5532d9cc3b640d6e71806a55062984e0c99a2f88f465"},
+    {file = "pyzmq-22.2.1-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:66375a6094af72a6098ed4403b15b4db6bf00013c6febc1baa832e7abda827f4"},
+    {file = "pyzmq-22.2.1-cp38-cp38-win32.whl", hash = "sha256:b2c16d20bd0aef8e57bc9505fdd80ea0d6008020c3740accd96acf1b3d1b5347"},
+    {file = "pyzmq-22.2.1-cp38-cp38-win_amd64.whl", hash = "sha256:ff345d48940c834168f81fa1d4724675099f148f1ab6369748c4d712ed71bf7c"},
+    {file = "pyzmq-22.2.1-cp39-cp39-macosx_10_15_universal2.whl", hash = "sha256:f5c84c5de9a773bbf8b22c51e28380999ea72e5e85b4db8edf5e69a7a0d4d9f9"},
+    {file = "pyzmq-22.2.1-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:2534a036b777f957bd6b89b55fb2136775ca2659fb0f1c85036ba78d17d86fd5"},
+    {file = "pyzmq-22.2.1-cp39-cp39-manylinux_2_12_i686.manylinux2010_i686.whl", hash = "sha256:a649065413ba4eab92a783a7caa4de8ce14cf46ba8a2a09951426143f1298adb"},
+    {file = "pyzmq-22.2.1-cp39-cp39-manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:c9cb0bd3a3cb7ccad3caa1d7b0d18ba71ed3a4a3610028e506a4084371d4d223"},
+    {file = "pyzmq-22.2.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:b4428302c389fffc0c9c07a78cad5376636b9d096f332acfe66b321ae9ff2c63"},
+    {file = "pyzmq-22.2.1-cp39-cp39-win32.whl", hash = "sha256:6a5b4566f66d953601d0d47d4071897f550a265bafd52ebcad5ac7aad3838cbb"},
+    {file = "pyzmq-22.2.1-cp39-cp39-win_amd64.whl", hash = "sha256:89200ab6ef9081c72a04ed84c52a50b60dcb0655375aeedb40689bc7c934715e"},
+    {file = "pyzmq-22.2.1-pp37-pypy37_pp73-macosx_10_9_x86_64.whl", hash = "sha256:ed67df4eaa99a20d162d76655bda23160abdf8abf82a17f41dfd3962e608dbcc"},
+    {file = "pyzmq-22.2.1-pp37-pypy37_pp73-manylinux_2_12_i686.manylinux2010_i686.whl", hash = "sha256:021e22a8c58ab294bd4b96448a2ca4e716e1d76600192ff84c33d71edb1fbd37"},
+    {file = "pyzmq-22.2.1-pp37-pypy37_pp73-manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:200ac096cee5499964c90687306a7244b79ef891f773ed4cf15019fd1f3df330"},
+    {file = "pyzmq-22.2.1-pp37-pypy37_pp73-win_amd64.whl", hash = "sha256:b3f57bee62e36be5c97712de32237c5589caee0d1154c2ad01a888accfae20bc"},
+    {file = "pyzmq-22.2.1.tar.gz", hash = "sha256:6d18c76676771fd891ca8e0e68da0bbfb88e30129835c0ade748016adb3b6242"},
+]
+qtconsole = [
+    {file = "qtconsole-5.1.1-py3-none-any.whl", hash = "sha256:73994105b0369bb99f4164df4a131010f3c7b33a7b5169c37366358d8744675b"},
+    {file = "qtconsole-5.1.1.tar.gz", hash = "sha256:bbc34bca14f65535afcb401bc74b752bac955e5313001ba640383f7e5857dc49"},
+]
+qtpy = [
+    {file = "QtPy-1.9.0-py2.py3-none-any.whl", hash = "sha256:fa0b8363b363e89b2a6f49eddc162a04c0699ae95e109a6be3bb145a913190ea"},
+    {file = "QtPy-1.9.0.tar.gz", hash = "sha256:2db72c44b55d0fe1407be8fba35c838ad0d6d3bb81f23007886dc1fc0f459c8d"},
+]
+rasterio = [
+    {file = "rasterio-1.2.6-cp36-cp36m-macosx_10_9_x86_64.whl", hash = "sha256:fda220ca942ff7446458a1d532121a2a0bebffdcbe064e4719dcca348a2ed541"},
+    {file = "rasterio-1.2.6-cp36-cp36m-manylinux_2_5_x86_64.manylinux1_x86_64.whl", hash = "sha256:2134587770d258ed97f40e4f910b7250bd3d39cdba76f9dd1617ca73cd481ff5"},
+    {file = "rasterio-1.2.6-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:6154622ec5210f5768db6544502b89487cfac10b0be9a321af33cd64e8cbe0fa"},
+    {file = "rasterio-1.2.6-cp37-cp37m-manylinux1_x86_64.whl", hash = "sha256:bd06ed04197eb79b96240dc90354fe15e0fe9b531312830045c849e4db57a42f"},
+    {file = "rasterio-1.2.6-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:87129e50e835e2696c17d19c5e7f5d566d09f8895d9e405e2c7d78adc63ae626"},
+    {file = "rasterio-1.2.6-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.whl", hash = "sha256:da2ed05c025bbdc1df8bdd9d1237e96ca3030eadabdb67722674620e9732a54a"},
+    {file = "rasterio-1.2.6-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:294479e9d7caf64c95a90b2ed2ec13df6eba35f035f0c536a388e0160e9abf03"},
+    {file = "rasterio-1.2.6-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.whl", hash = "sha256:f55aa86bac58672ca47627a1dfecd56d35581beb49feae1f22818f97ff79abf8"},
+    {file = "rasterio-1.2.6.tar.gz", hash = "sha256:24975b97fe2fc3fd282d59640baab19de431448e1b23be6b85b68fecc1362f88"},
+]
+requests = [
+    {file = "requests-2.26.0-py2.py3-none-any.whl", hash = "sha256:6c1246513ecd5ecd4528a0906f910e8f0f9c6b8ec72030dc9fd154dc1a6efd24"},
+    {file = "requests-2.26.0.tar.gz", hash = "sha256:b8aa58f8cf793ffd8782d3d8cb19e66ef36f7aba4353eec859e74678b01b07a7"},
+]
+scikit-image = [
+    {file = "scikit-image-0.18.2.tar.gz", hash = "sha256:32ff472355fbf8ab40a8e9ed685906c6c51a863f1ea8737882d26be9221631f3"},
+    {file = "scikit_image-0.18.2-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:6f6d0e79a91c62360708111951abb3a774cefac865902ea797c3b72d8ece6382"},
+    {file = "scikit_image-0.18.2-cp37-cp37m-manylinux1_i686.whl", hash = "sha256:49a9b48bc428d2d56aaefbc042fd79c67ebc908a1cbf542e9c863c49339ca496"},
+    {file = "scikit_image-0.18.2-cp37-cp37m-manylinux1_x86_64.whl", hash = "sha256:32620792e989beb2c3eb67eae38b59291be412be59ad3485ee0f67cb7b37c16f"},
+    {file = "scikit_image-0.18.2-cp37-cp37m-manylinux2014_aarch64.whl", hash = "sha256:38efc3fd9023c7849175fc18b2cc96a08629da840b6100ec5038f487fba7d34e"},
+    {file = "scikit_image-0.18.2-cp37-cp37m-win32.whl", hash = "sha256:5510b133999a45b2c8ed4c1b659fa0a1cf4ca0db949353d0f54fc6290dac4d5a"},
+    {file = "scikit_image-0.18.2-cp37-cp37m-win_amd64.whl", hash = "sha256:b3aa7230d84b12d8a4a9f0b65ee895603d27fe85366bf2b57929ba1cce2e8987"},
+    {file = "scikit_image-0.18.2-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:b21d65dcee453539fe70b5903edd8429ad9fe46233b049dd622368bad435f39e"},
+    {file = "scikit_image-0.18.2-cp38-cp38-manylinux1_i686.whl", hash = "sha256:f61d65de826abe2f5f6c171c75d2bb93df56aa4a690d1bab5911412f49b9e768"},
+    {file = "scikit_image-0.18.2-cp38-cp38-manylinux1_x86_64.whl", hash = "sha256:a4fdba1bdd883a8028ddff0b8fe8d43c8dd43360bdab6e1f40599fa210613f1d"},
+    {file = "scikit_image-0.18.2-cp38-cp38-manylinux2014_aarch64.whl", hash = "sha256:8e62228a91b770fbe89d310e833f8797f14136b9635bb67d8b780f1b8cf237e6"},
+    {file = "scikit_image-0.18.2-cp38-cp38-win32.whl", hash = "sha256:f80d16ce57e05af8e282620a23e90bb8886e5efa6eedcacb4da1c15293ba5e9a"},
+    {file = "scikit_image-0.18.2-cp38-cp38-win_amd64.whl", hash = "sha256:6d576a8249114e6169ea1c2b05a22168745eedba90b06d5765368dbd59b27c7f"},
+    {file = "scikit_image-0.18.2-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:278b0034c509d8b31a9b117837b3d45957dd3408e062ad0f2b24edeb1a460e91"},
+    {file = "scikit_image-0.18.2-cp39-cp39-manylinux2010_i686.whl", hash = "sha256:f9648093a0865150fc4ac9eaf02256afbf471a43216b0b6ee6585a4d57674563"},
+    {file = "scikit_image-0.18.2-cp39-cp39-manylinux2010_x86_64.whl", hash = "sha256:2c7e91fb3df5cc58cb13c39094a32bb2e990ced30b08ee34bf0976ff8a1ba579"},
+    {file = "scikit_image-0.18.2-cp39-cp39-manylinux2014_aarch64.whl", hash = "sha256:4f42a36e34a3e659dd5e0fe9c0b07f797f9b66680224a7f2545a564484574d78"},
+    {file = "scikit_image-0.18.2-cp39-cp39-win32.whl", hash = "sha256:66ea3bc8f53efbaf751fdae472fe1cbc55ad5e4fadbf6d3a0a268dc7e34d83b6"},
+    {file = "scikit_image-0.18.2-cp39-cp39-win_amd64.whl", hash = "sha256:74f7c5920c0b893608ef0d159a61a15e87aa9f31d2707d1ed6621a65233646cd"},
+]
+scipy = [
+    {file = "scipy-1.6.1-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:a15a1f3fc0abff33e792d6049161b7795909b40b97c6cc2934ed54384017ab76"},
+    {file = "scipy-1.6.1-cp37-cp37m-manylinux1_i686.whl", hash = "sha256:e79570979ccdc3d165456dd62041d9556fb9733b86b4b6d818af7a0afc15f092"},
+    {file = "scipy-1.6.1-cp37-cp37m-manylinux1_x86_64.whl", hash = "sha256:a423533c55fec61456dedee7b6ee7dce0bb6bfa395424ea374d25afa262be261"},
+    {file = "scipy-1.6.1-cp37-cp37m-manylinux2014_aarch64.whl", hash = "sha256:33d6b7df40d197bdd3049d64e8e680227151673465e5d85723b3b8f6b15a6ced"},
+    {file = "scipy-1.6.1-cp37-cp37m-win32.whl", hash = "sha256:6725e3fbb47da428794f243864f2297462e9ee448297c93ed1dcbc44335feb78"},
+    {file = "scipy-1.6.1-cp37-cp37m-win_amd64.whl", hash = "sha256:5fa9c6530b1661f1370bcd332a1e62ca7881785cc0f80c0d559b636567fab63c"},
+    {file = "scipy-1.6.1-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:bd50daf727f7c195e26f27467c85ce653d41df4358a25b32434a50d8870fc519"},
+    {file = "scipy-1.6.1-cp38-cp38-manylinux1_i686.whl", hash = "sha256:f46dd15335e8a320b0fb4685f58b7471702234cba8bb3442b69a3e1dc329c345"},
+    {file = "scipy-1.6.1-cp38-cp38-manylinux1_x86_64.whl", hash = "sha256:0e5b0ccf63155d90da576edd2768b66fb276446c371b73841e3503be1d63fb5d"},
+    {file = "scipy-1.6.1-cp38-cp38-manylinux2014_aarch64.whl", hash = "sha256:2481efbb3740977e3c831edfd0bd9867be26387cacf24eb5e366a6a374d3d00d"},
+    {file = "scipy-1.6.1-cp38-cp38-win32.whl", hash = "sha256:68cb4c424112cd4be886b4d979c5497fba190714085f46b8ae67a5e4416c32b4"},
+    {file = "scipy-1.6.1-cp38-cp38-win_amd64.whl", hash = "sha256:5f331eeed0297232d2e6eea51b54e8278ed8bb10b099f69c44e2558c090d06bf"},
+    {file = "scipy-1.6.1-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:0c8a51d33556bf70367452d4d601d1742c0e806cd0194785914daf19775f0e67"},
+    {file = "scipy-1.6.1-cp39-cp39-manylinux1_i686.whl", hash = "sha256:83bf7c16245c15bc58ee76c5418e46ea1811edcc2e2b03041b804e46084ab627"},
+    {file = "scipy-1.6.1-cp39-cp39-manylinux1_x86_64.whl", hash = "sha256:794e768cc5f779736593046c9714e0f3a5940bc6dcc1dba885ad64cbfb28e9f0"},
+    {file = "scipy-1.6.1-cp39-cp39-manylinux2014_aarch64.whl", hash = "sha256:5da5471aed911fe7e52b86bf9ea32fb55ae93e2f0fac66c32e58897cfb02fa07"},
+    {file = "scipy-1.6.1-cp39-cp39-win32.whl", hash = "sha256:8e403a337749ed40af60e537cc4d4c03febddcc56cd26e774c9b1b600a70d3e4"},
+    {file = "scipy-1.6.1-cp39-cp39-win_amd64.whl", hash = "sha256:a5193a098ae9f29af283dcf0041f762601faf2e595c0db1da929875b7570353f"},
+    {file = "scipy-1.6.1.tar.gz", hash = "sha256:c4fceb864890b6168e79b0e714c585dbe2fd4222768ee90bc1aa0f8218691b11"},
+]
+seaborn = [
+    {file = "seaborn-0.11.2-py3-none-any.whl", hash = "sha256:85a6baa9b55f81a0623abddc4a26b334653ff4c6b18c418361de19dbba0ef283"},
+    {file = "seaborn-0.11.2.tar.gz", hash = "sha256:cf45e9286d40826864be0e3c066f98536982baf701a7caa386511792d61ff4f6"},
+]
+send2trash = [
+    {file = "Send2Trash-1.8.0-py3-none-any.whl", hash = "sha256:f20eaadfdb517eaca5ce077640cb261c7d2698385a6a0f072a4a5447fd49fa08"},
+    {file = "Send2Trash-1.8.0.tar.gz", hash = "sha256:d2c24762fd3759860a0aff155e45871447ea58d2be6bdd39b5c8f966a0c99c2d"},
+]
+shapely = [
+    {file = "Shapely-1.7.1-1-cp39-cp39-manylinux1_x86_64.whl", hash = "sha256:46da0ea527da9cf9503e66c18bab6981c5556859e518fe71578b47126e54ca93"},
+    {file = "Shapely-1.7.1-cp27-cp27mu-manylinux1_x86_64.whl", hash = "sha256:4c10f317e379cc404f8fc510cd9982d5d3e7ba13a9cfd39aa251d894c6366798"},
+    {file = "Shapely-1.7.1-cp35-cp35m-macosx_10_6_intel.whl", hash = "sha256:17df66e87d0fe0193910aeaa938c99f0b04f67b430edb8adae01e7be557b141b"},
+    {file = "Shapely-1.7.1-cp35-cp35m-manylinux1_x86_64.whl", hash = "sha256:da38ed3d65b8091447dc3717e5218cc336d20303b77b0634b261bc5c1aa2bae8"},
+    {file = "Shapely-1.7.1-cp35-cp35m-win32.whl", hash = "sha256:8e7659dd994792a0aad8fb80439f59055a21163e236faf2f9823beb63a380e19"},
+    {file = "Shapely-1.7.1-cp35-cp35m-win_amd64.whl", hash = "sha256:791477edb422692e7dc351c5ed6530eb0e949a31b45569946619a0d9cd5f53cb"},
+    {file = "Shapely-1.7.1-cp36-cp36m-macosx_10_9_x86_64.whl", hash = "sha256:e3afccf0437edc108eef1e2bb9cc4c7073e7705924eb4cd0bf7715cd1ef0ce1b"},
+    {file = "Shapely-1.7.1-cp36-cp36m-manylinux1_x86_64.whl", hash = "sha256:8f15b6ce67dcc05b61f19c689b60f3fe58550ba994290ff8332f711f5aaa9840"},
+    {file = "Shapely-1.7.1-cp36-cp36m-win32.whl", hash = "sha256:60e5b2282619249dbe8dc5266d781cc7d7fb1b27fa49f8241f2167672ad26719"},
+    {file = "Shapely-1.7.1-cp36-cp36m-win_amd64.whl", hash = "sha256:de618e67b64a51a0768d26a9963ecd7d338a2cf6e9e7582d2385f88ad005b3d1"},
+    {file = "Shapely-1.7.1-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:182716ffb500d114b5d1b75d7fd9d14b7d3414cef3c38c0490534cc9ce20981a"},
+    {file = "Shapely-1.7.1-cp37-cp37m-manylinux1_x86_64.whl", hash = "sha256:4f3c59f6dbf86a9fc293546de492f5e07344e045f9333f3a753f2dda903c45d1"},
+    {file = "Shapely-1.7.1-cp37-cp37m-win32.whl", hash = "sha256:6871acba8fbe744efa4f9f34e726d070bfbf9bffb356a8f6d64557846324232b"},
+    {file = "Shapely-1.7.1-cp37-cp37m-win_amd64.whl", hash = "sha256:35be1c5d869966569d3dfd4ec31832d7c780e9df760e1fe52131105685941891"},
+    {file = "Shapely-1.7.1-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:052eb5b9ba756808a7825e8a8020fb146ec489dd5c919e7d139014775411e688"},
+    {file = "Shapely-1.7.1-cp38-cp38-manylinux1_x86_64.whl", hash = "sha256:90a3e2ae0d6d7d50ff2370ba168fbd416a53e7d8448410758c5d6a5920646c1d"},
+    {file = "Shapely-1.7.1-cp38-cp38-win32.whl", hash = "sha256:a3774516c8a83abfd1ddffb8b6ec1b0935d7fe6ea0ff5c31a18bfdae567b4eba"},
+    {file = "Shapely-1.7.1-cp38-cp38-win_amd64.whl", hash = "sha256:6593026cd3f5daaea12bcc51ae5c979318070fefee210e7990cb8ac2364e79a1"},
+    {file = "Shapely-1.7.1-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:617bf046a6861d7c6b44d2d9cb9e2311548638e684c2cd071d8945f24a926263"},
+    {file = "Shapely-1.7.1-cp39-cp39-manylinux1_x86_64.whl", hash = "sha256:b40cc7bb089ae4aa9ddba1db900b4cd1bce3925d2a4b5837b639e49de054784f"},
+    {file = "Shapely-1.7.1-cp39-cp39-win32.whl", hash = "sha256:2df5260d0f2983309776cb41bfa85c464ec07018d88c0ecfca23d40bfadae2f1"},
+    {file = "Shapely-1.7.1-cp39-cp39-win_amd64.whl", hash = "sha256:a5c3a50d823c192f32615a2a6920e8c046b09e07a58eba220407335a9cd2e8ea"},
+    {file = "Shapely-1.7.1.tar.gz", hash = "sha256:1641724c1055459a7e2b8bbe47ba25bdc89554582e62aec23cb3f3ca25f9b129"},
+]
+six = [
+    {file = "six-1.16.0-py2.py3-none-any.whl", hash = "sha256:8abb2f1d86890a2dfb989f9a77cfcfd3e47c2a354b01111771326f8aa26e0254"},
+    {file = "six-1.16.0.tar.gz", hash = "sha256:1e61c37477a1626458e36f7b1d82aa5c9b094fa4802892072e49de9c60c4c926"},
+]
+snuggs = [
+    {file = "snuggs-1.4.7-py3-none-any.whl", hash = "sha256:988dde5d4db88e9d71c99457404773dabcc7a1c45971bfbe81900999942d9f07"},
+    {file = "snuggs-1.4.7.tar.gz", hash = "sha256:501cf113fe3892e14e2fee76da5cd0606b7e149c411c271898e6259ebde2617b"},
+]
+terminado = [
+    {file = "terminado-0.11.0-py3-none-any.whl", hash = "sha256:221eef83e6a504894842f7dccfa971ca2e98ec22a8a9118577e5257527674b42"},
+    {file = "terminado-0.11.0.tar.gz", hash = "sha256:1e01183885f64c1bba3cf89a5a995ad4acfed4e5f00aebcce1bf7f089b0825a1"},
+]
+testpath = [
+    {file = "testpath-0.5.0-py3-none-any.whl", hash = "sha256:8044f9a0bab6567fc644a3593164e872543bb44225b0e24846e2c89237937589"},
+    {file = "testpath-0.5.0.tar.gz", hash = "sha256:1acf7a0bcd3004ae8357409fc33751e16d37ccc650921da1094a86581ad1e417"},
+]
+tifffile = [
+    {file = "tifffile-2021.8.8-py3-none-any.whl", hash = "sha256:1309d1f5cc2ee2e8274916dc609922cb2364f947a9d09b388069c63180710dfd"},
+    {file = "tifffile-2021.8.8.tar.gz", hash = "sha256:8260f31c4700143e8374ff6cde5cef7fe54fc9b7313afe88329f407881901dc5"},
+]
+tornado = [
+    {file = "tornado-6.1-cp35-cp35m-macosx_10_9_x86_64.whl", hash = "sha256:d371e811d6b156d82aa5f9a4e08b58debf97c302a35714f6f45e35139c332e32"},
+    {file = "tornado-6.1-cp35-cp35m-manylinux1_i686.whl", hash = "sha256:0d321a39c36e5f2c4ff12b4ed58d41390460f798422c4504e09eb5678e09998c"},
+    {file = "tornado-6.1-cp35-cp35m-manylinux1_x86_64.whl", hash = "sha256:9de9e5188a782be6b1ce866e8a51bc76a0fbaa0e16613823fc38e4fc2556ad05"},
+    {file = "tornado-6.1-cp35-cp35m-manylinux2010_i686.whl", hash = "sha256:61b32d06ae8a036a6607805e6720ef00a3c98207038444ba7fd3d169cd998910"},
+    {file = "tornado-6.1-cp35-cp35m-manylinux2010_x86_64.whl", hash = "sha256:3e63498f680547ed24d2c71e6497f24bca791aca2fe116dbc2bd0ac7f191691b"},
+    {file = "tornado-6.1-cp35-cp35m-manylinux2014_aarch64.whl", hash = "sha256:6c77c9937962577a6a76917845d06af6ab9197702a42e1346d8ae2e76b5e3675"},
+    {file = "tornado-6.1-cp35-cp35m-win32.whl", hash = "sha256:6286efab1ed6e74b7028327365cf7346b1d777d63ab30e21a0f4d5b275fc17d5"},
+    {file = "tornado-6.1-cp35-cp35m-win_amd64.whl", hash = "sha256:fa2ba70284fa42c2a5ecb35e322e68823288a4251f9ba9cc77be04ae15eada68"},
+    {file = "tornado-6.1-cp36-cp36m-macosx_10_9_x86_64.whl", hash = "sha256:0a00ff4561e2929a2c37ce706cb8233b7907e0cdc22eab98888aca5dd3775feb"},
+    {file = "tornado-6.1-cp36-cp36m-manylinux1_i686.whl", hash = "sha256:748290bf9112b581c525e6e6d3820621ff020ed95af6f17fedef416b27ed564c"},
+    {file = "tornado-6.1-cp36-cp36m-manylinux1_x86_64.whl", hash = "sha256:e385b637ac3acaae8022e7e47dfa7b83d3620e432e3ecb9a3f7f58f150e50921"},
+    {file = "tornado-6.1-cp36-cp36m-manylinux2010_i686.whl", hash = "sha256:25ad220258349a12ae87ede08a7b04aca51237721f63b1808d39bdb4b2164558"},
+    {file = "tornado-6.1-cp36-cp36m-manylinux2010_x86_64.whl", hash = "sha256:65d98939f1a2e74b58839f8c4dab3b6b3c1ce84972ae712be02845e65391ac7c"},
+    {file = "tornado-6.1-cp36-cp36m-manylinux2014_aarch64.whl", hash = "sha256:e519d64089b0876c7b467274468709dadf11e41d65f63bba207e04217f47c085"},
+    {file = "tornado-6.1-cp36-cp36m-win32.whl", hash = "sha256:b87936fd2c317b6ee08a5741ea06b9d11a6074ef4cc42e031bc6403f82a32575"},
+    {file = "tornado-6.1-cp36-cp36m-win_amd64.whl", hash = "sha256:cc0ee35043162abbf717b7df924597ade8e5395e7b66d18270116f8745ceb795"},
+    {file = "tornado-6.1-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:7250a3fa399f08ec9cb3f7b1b987955d17e044f1ade821b32e5f435130250d7f"},
+    {file = "tornado-6.1-cp37-cp37m-manylinux1_i686.whl", hash = "sha256:ed3ad863b1b40cd1d4bd21e7498329ccaece75db5a5bf58cd3c9f130843e7102"},
+    {file = "tornado-6.1-cp37-cp37m-manylinux1_x86_64.whl", hash = "sha256:dcef026f608f678c118779cd6591c8af6e9b4155c44e0d1bc0c87c036fb8c8c4"},
+    {file = "tornado-6.1-cp37-cp37m-manylinux2010_i686.whl", hash = "sha256:70dec29e8ac485dbf57481baee40781c63e381bebea080991893cd297742b8fd"},
+    {file = "tornado-6.1-cp37-cp37m-manylinux2010_x86_64.whl", hash = "sha256:d3f7594930c423fd9f5d1a76bee85a2c36fd8b4b16921cae7e965f22575e9c01"},
+    {file = "tornado-6.1-cp37-cp37m-manylinux2014_aarch64.whl", hash = "sha256:3447475585bae2e77ecb832fc0300c3695516a47d46cefa0528181a34c5b9d3d"},
+    {file = "tornado-6.1-cp37-cp37m-win32.whl", hash = "sha256:e7229e60ac41a1202444497ddde70a48d33909e484f96eb0da9baf8dc68541df"},
+    {file = "tornado-6.1-cp37-cp37m-win_amd64.whl", hash = "sha256:cb5ec8eead331e3bb4ce8066cf06d2dfef1bfb1b2a73082dfe8a161301b76e37"},
+    {file = "tornado-6.1-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:20241b3cb4f425e971cb0a8e4ffc9b0a861530ae3c52f2b0434e6c1b57e9fd95"},
+    {file = "tornado-6.1-cp38-cp38-manylinux1_i686.whl", hash = "sha256:c77da1263aa361938476f04c4b6c8916001b90b2c2fdd92d8d535e1af48fba5a"},
+    {file = "tornado-6.1-cp38-cp38-manylinux1_x86_64.whl", hash = "sha256:fba85b6cd9c39be262fcd23865652920832b61583de2a2ca907dbd8e8a8c81e5"},
+    {file = "tornado-6.1-cp38-cp38-manylinux2010_i686.whl", hash = "sha256:1e8225a1070cd8eec59a996c43229fe8f95689cb16e552d130b9793cb570a288"},
+    {file = "tornado-6.1-cp38-cp38-manylinux2010_x86_64.whl", hash = "sha256:d14d30e7f46a0476efb0deb5b61343b1526f73ebb5ed84f23dc794bdb88f9d9f"},
+    {file = "tornado-6.1-cp38-cp38-manylinux2014_aarch64.whl", hash = "sha256:8f959b26f2634a091bb42241c3ed8d3cedb506e7c27b8dd5c7b9f745318ddbb6"},
+    {file = "tornado-6.1-cp38-cp38-win32.whl", hash = "sha256:34ca2dac9e4d7afb0bed4677512e36a52f09caa6fded70b4e3e1c89dbd92c326"},
+    {file = "tornado-6.1-cp38-cp38-win_amd64.whl", hash = "sha256:6196a5c39286cc37c024cd78834fb9345e464525d8991c21e908cc046d1cc02c"},
+    {file = "tornado-6.1-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:f0ba29bafd8e7e22920567ce0d232c26d4d47c8b5cf4ed7b562b5db39fa199c5"},
+    {file = "tornado-6.1-cp39-cp39-manylinux1_i686.whl", hash = "sha256:33892118b165401f291070100d6d09359ca74addda679b60390b09f8ef325ffe"},
+    {file = "tornado-6.1-cp39-cp39-manylinux1_x86_64.whl", hash = "sha256:7da13da6f985aab7f6f28debab00c67ff9cbacd588e8477034c0652ac141feea"},
+    {file = "tornado-6.1-cp39-cp39-manylinux2010_i686.whl", hash = "sha256:e0791ac58d91ac58f694d8d2957884df8e4e2f6687cdf367ef7eb7497f79eaa2"},
+    {file = "tornado-6.1-cp39-cp39-manylinux2010_x86_64.whl", hash = "sha256:66324e4e1beede9ac79e60f88de548da58b1f8ab4b2f1354d8375774f997e6c0"},
+    {file = "tornado-6.1-cp39-cp39-manylinux2014_aarch64.whl", hash = "sha256:a48900ecea1cbb71b8c71c620dee15b62f85f7c14189bdeee54966fbd9a0c5bd"},
+    {file = "tornado-6.1-cp39-cp39-win32.whl", hash = "sha256:d3d20ea5782ba63ed13bc2b8c291a053c8d807a8fa927d941bd718468f7b950c"},
+    {file = "tornado-6.1-cp39-cp39-win_amd64.whl", hash = "sha256:548430be2740e327b3fe0201abe471f314741efcb0067ec4f2d7dcfb4825f3e4"},
+    {file = "tornado-6.1.tar.gz", hash = "sha256:33c6e81d7bd55b468d2e793517c909b139960b6c790a60b7991b9b6b76fb9791"},
+]
+traitlets = [
+    {file = "traitlets-5.0.5-py3-none-any.whl", hash = "sha256:69ff3f9d5351f31a7ad80443c2674b7099df13cc41fc5fa6e2f6d3b0330b0426"},
+    {file = "traitlets-5.0.5.tar.gz", hash = "sha256:178f4ce988f69189f7e523337a3e11d91c786ded9360174a3d9ca83e79bc5396"},
+]
+urllib3 = [
+    {file = "urllib3-1.26.6-py2.py3-none-any.whl", hash = "sha256:39fb8672126159acb139a7718dd10806104dec1e2f0f6c88aab05d17df10c8d4"},
+    {file = "urllib3-1.26.6.tar.gz", hash = "sha256:f57b4c16c62fa2760b7e3d97c35b255512fb6b59a259730f36ba32ce9f8e342f"},
+]
+wcwidth = [
+    {file = "wcwidth-0.2.5-py2.py3-none-any.whl", hash = "sha256:beb4802a9cebb9144e99086eff703a642a13d6a0052920003a230f3294bbe784"},
+    {file = "wcwidth-0.2.5.tar.gz", hash = "sha256:c4d647b99872929fdb7bdcaa4fbe7f01413ed3d98077df798530e5b04f116c83"},
+]
+webencodings = [
+    {file = "webencodings-0.5.1-py2.py3-none-any.whl", hash = "sha256:a0af1213f3c2226497a97e2b3aa01a7e4bee4f403f95be16fc9acd2947514a78"},
+    {file = "webencodings-0.5.1.tar.gz", hash = "sha256:b36a1c245f2d304965eb4e0a82848379241dc04b865afcc4aab16748587e1923"},
+]
+widgetsnbextension = [
+    {file = "widgetsnbextension-3.5.1-py2.py3-none-any.whl", hash = "sha256:bd314f8ceb488571a5ffea6cc5b9fc6cba0adaf88a9d2386b93a489751938bcd"},
+    {file = "widgetsnbextension-3.5.1.tar.gz", hash = "sha256:079f87d87270bce047512400efd70238820751a11d2d8cb137a5a5bdbaf255c7"},
+]
+win32-setctime = [
+    {file = "win32_setctime-1.0.3-py3-none-any.whl", hash = "sha256:dc925662de0a6eb987f0b01f599c01a8236cb8c62831c22d9cada09ad958243e"},
+    {file = "win32_setctime-1.0.3.tar.gz", hash = "sha256:4e88556c32fdf47f64165a2180ba4552f8bb32c1103a2fafd05723a0bd42bd4b"},
+]
diff --git a/pyproject.toml b/pyproject.toml
new file mode 100644
index 0000000..7922c43
--- /dev/null
+++ b/pyproject.toml
@@ -0,0 +1,21 @@
+[tool.poetry]
+name = "besser_tanken"
+version = "0.1.0"
+description = ""
+authors = ["Tobias Kurze <it@t-kurze.de>"]
+
+[tool.poetry.dependencies]
+python = "^3.9"
+loguru = "^0.5.3"
+seaborn = "^0.11.1"
+earthpy = "^0.9.2"
+jupyter = "^1.0.0"
+jupyter_nbextensions_configurator = "^0.4.1"
+feather-format = "^0.4.1"
+pygeodb = {git = "https://github.com/tkurze/pyGeoDb.git"}
+
+[tool.poetry.dev-dependencies]
+
+[build-system]
+requires = ["poetry-core>=1.0.0"]
+build-backend = "poetry.core.masonry.api"
diff --git a/sprit_preis_analyse.ipynb b/sprit_preis_analyse.ipynb
new file mode 100644
index 0000000..9176964
--- /dev/null
+++ b/sprit_preis_analyse.ipynb
@@ -0,0 +1,2244 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "abc85460",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import os\n",
+    "import matplotlib.pyplot as plt\n",
+    "import seaborn as sns\n",
+    "import pandas as pd\n",
+    "import earthpy as et\n",
+    "import numpy as np\n",
+    "from besser_tanken.data_loader import load_prices_from, load_stations\n",
+    "from besser_tanken.data_tools import group_prices"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "1b7ebdd6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Handle date time conversions between pandas and matplotlib\n",
+    "from pandas.plotting import register_matplotlib_converters\n",
+    "register_matplotlib_converters()\n",
+    "\n",
+    "# Use white grid plot background from seaborn\n",
+    "sns.set(font_scale=1.5, style=\"whitegrid\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "4d1b7811",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2021-08-12 15:59:25.359 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-01-prices.csv\n",
+      "2021-08-12 15:59:25.361 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-03-prices.csv\n",
+      "2021-08-12 15:59:25.361 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-07-prices.csv\n",
+      "2021-08-12 15:59:25.362 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-05-prices.csv\n",
+      "2021-08-12 15:59:25.365 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-02-prices.csv\n",
+      "2021-08-12 15:59:26.047 | INFO     | besser_tanken.data_loader:load_prices:70 - got 280439 prices\n",
+      "2021-08-12 15:59:26.122 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-08-prices.csv\n",
+      "2021-08-12 15:59:26.622 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-04-prices.csv\n",
+      "2021-08-12 15:59:26.788 | INFO     | besser_tanken.data_loader:load_prices:70 - got 297538 prices\n",
+      "2021-08-12 15:59:26.813 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-06-prices.csv\n",
+      "2021-08-12 15:59:27.424 | INFO     | besser_tanken.data_loader:load_prices:70 - got 267833 prices\n",
+      "2021-08-12 15:59:28.101 | INFO     | besser_tanken.data_loader:load_prices:70 - got 287410 prices\n",
+      "2021-08-12 15:59:28.101 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-15-prices.csv\n",
+      "2021-08-12 15:59:28.760 | INFO     | besser_tanken.data_loader:load_prices:70 - got 285397 prices\n",
+      "2021-08-12 15:59:28.761 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-10-prices.csv\n",
+      "2021-08-12 15:59:28.762 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-14-prices.csv\n",
+      "2021-08-12 15:59:28.763 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-11-prices.csv\n",
+      "2021-08-12 15:59:28.774 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-16-prices.csv\n",
+      "2021-08-12 15:59:28.790 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-13-prices.csv\n",
+      "2021-08-12 15:59:28.816 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-09-prices.csv\n",
+      "2021-08-12 15:59:29.576 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-12-prices.csv\n",
+      "2021-08-12 15:59:29.588 | INFO     | besser_tanken.data_loader:load_prices:70 - got 267574 prices\n",
+      "2021-08-12 15:59:30.132 | INFO     | besser_tanken.data_loader:load_prices:70 - got 291143 prices\n",
+      "2021-08-12 15:59:31.038 | INFO     | besser_tanken.data_loader:load_prices:70 - got 290865 prices\n",
+      "2021-08-12 15:59:32.167 | INFO     | besser_tanken.data_loader:load_prices:70 - got 273987 prices\n",
+      "2021-08-12 15:59:33.567 | INFO     | besser_tanken.data_loader:load_prices:70 - got 283024 prices\n",
+      "2021-08-12 15:59:33.747 | INFO     | besser_tanken.data_loader:load_prices:70 - got 299993 prices\n",
+      "2021-08-12 15:59:33.748 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-17-prices.csv\n",
+      "2021-08-12 15:59:34.414 | INFO     | besser_tanken.data_loader:load_prices:70 - got 256623 prices\n",
+      "2021-08-12 15:59:34.420 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-18-prices.csv\n",
+      "2021-08-12 15:59:34.517 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-19-prices.csv\n",
+      "2021-08-12 15:59:35.206 | INFO     | besser_tanken.data_loader:load_prices:70 - got 297991 prices\n",
+      "2021-08-12 15:59:36.630 | INFO     | besser_tanken.data_loader:load_prices:70 - got 294324 prices\n",
+      "2021-08-12 15:59:37.164 | INFO     | besser_tanken.data_loader:load_prices:70 - got 295394 prices\n",
+      "2021-08-12 15:59:37.347 | INFO     | besser_tanken.data_loader:load_prices:70 - got 283593 prices\n",
+      "2021-08-12 15:59:37.377 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-20-prices.csv\n",
+      "2021-08-12 15:59:37.969 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-21-prices.csv\n",
+      "2021-08-12 15:59:38.869 | INFO     | besser_tanken.data_loader:load_prices:70 - got 302116 prices\n",
+      "2021-08-12 15:59:39.689 | INFO     | besser_tanken.data_loader:load_prices:70 - got 254847 prices\n",
+      "2021-08-12 15:59:40.517 | INFO     | besser_tanken.data_loader:load_prices:70 - got 259956 prices\n",
+      "2021-08-12 15:59:40.579 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-22-prices.csv\n",
+      "2021-08-12 15:59:40.867 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-23-prices.csv\n",
+      "2021-08-12 15:59:41.107 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-24-prices.csv\n",
+      "2021-08-12 15:59:41.868 | INFO     | besser_tanken.data_loader:load_prices:70 - got 304068 prices\n",
+      "2021-08-12 15:59:41.979 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-25-prices.csv\n",
+      "2021-08-12 15:59:42.793 | INFO     | besser_tanken.data_loader:load_prices:70 - got 268463 prices\n",
+      "2021-08-12 15:59:42.838 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-27-prices.csv\n",
+      "2021-08-12 15:59:42.892 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-26-prices.csv\n",
+      "2021-08-12 15:59:43.057 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-28-prices.csv\n",
+      "2021-08-12 15:59:43.951 | INFO     | besser_tanken.data_loader:load_prices:70 - got 274800 prices\n",
+      "2021-08-12 15:59:44.701 | INFO     | besser_tanken.data_loader:load_prices:70 - got 295088 prices\n",
+      "2021-08-12 15:59:44.748 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-29-prices.csv\n",
+      "2021-08-12 15:59:45.456 | INFO     | besser_tanken.data_loader:load_prices:70 - got 300758 prices\n",
+      "2021-08-12 15:59:45.498 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-01-prices.csv\n",
+      "2021-08-12 15:59:45.557 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-02-prices.csv\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2021-08-12 15:59:46.235 | INFO     | besser_tanken.data_loader:load_prices:70 - got 279674 prices\n",
+      "2021-08-12 15:59:46.285 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/11/2020-11-30-prices.csv\n",
+      "2021-08-12 15:59:47.138 | INFO     | besser_tanken.data_loader:load_prices:70 - got 291122 prices\n",
+      "2021-08-12 15:59:47.366 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-04-prices.csv\n",
+      "2021-08-12 15:59:48.286 | INFO     | besser_tanken.data_loader:load_prices:70 - got 281698 prices\n",
+      "2021-08-12 15:59:48.297 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-03-prices.csv\n",
+      "2021-08-12 15:59:48.658 | INFO     | besser_tanken.data_loader:load_prices:70 - got 295627 prices\n",
+      "2021-08-12 15:59:49.508 | INFO     | besser_tanken.data_loader:load_prices:70 - got 272618 prices\n",
+      "2021-08-12 15:59:49.520 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-05-prices.csv\n",
+      "2021-08-12 15:59:50.403 | INFO     | besser_tanken.data_loader:load_prices:70 - got 304781 prices\n",
+      "2021-08-12 15:59:51.238 | INFO     | besser_tanken.data_loader:load_prices:70 - got 293853 prices\n",
+      "2021-08-12 15:59:51.258 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-06-prices.csv\n",
+      "2021-08-12 15:59:52.050 | INFO     | besser_tanken.data_loader:load_prices:70 - got 294534 prices\n",
+      "2021-08-12 15:59:52.932 | INFO     | besser_tanken.data_loader:load_prices:70 - got 296438 prices\n",
+      "2021-08-12 15:59:53.087 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-08-prices.csv\n",
+      "2021-08-12 15:59:53.143 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-09-prices.csv\n",
+      "2021-08-12 15:59:53.820 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-07-prices.csv\n",
+      "2021-08-12 15:59:53.862 | INFO     | besser_tanken.data_loader:load_prices:70 - got 295515 prices\n",
+      "2021-08-12 15:59:53.984 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-10-prices.csv\n",
+      "2021-08-12 15:59:54.731 | INFO     | besser_tanken.data_loader:load_prices:70 - got 266473 prices\n",
+      "2021-08-12 15:59:55.889 | INFO     | besser_tanken.data_loader:load_prices:70 - got 268331 prices\n",
+      "2021-08-12 15:59:56.049 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-12-prices.csv\n",
+      "2021-08-12 15:59:56.181 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-11-prices.csv\n",
+      "2021-08-12 15:59:57.046 | INFO     | besser_tanken.data_loader:load_prices:70 - got 295127 prices\n",
+      "2021-08-12 15:59:57.211 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-13-prices.csv\n",
+      "2021-08-12 15:59:57.217 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-14-prices.csv\n",
+      "2021-08-12 15:59:57.243 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-16-prices.csv\n",
+      "2021-08-12 15:59:57.963 | INFO     | besser_tanken.data_loader:load_prices:70 - got 291819 prices\n",
+      "2021-08-12 15:59:58.721 | INFO     | besser_tanken.data_loader:load_prices:70 - got 295646 prices\n",
+      "2021-08-12 15:59:58.737 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-17-prices.csv\n",
+      "2021-08-12 15:59:58.792 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-15-prices.csv\n",
+      "2021-08-12 16:00:00.193 | INFO     | besser_tanken.data_loader:load_prices:70 - got 291843 prices\n",
+      "2021-08-12 16:00:00.223 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-18-prices.csv\n",
+      "2021-08-12 16:00:00.961 | INFO     | besser_tanken.data_loader:load_prices:70 - got 283770 prices\n",
+      "2021-08-12 16:00:01.561 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-19-prices.csv\n",
+      "2021-08-12 16:00:01.787 | INFO     | besser_tanken.data_loader:load_prices:70 - got 295290 prices\n",
+      "2021-08-12 16:00:02.847 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-20-prices.csv\n",
+      "2021-08-12 16:00:03.212 | INFO     | besser_tanken.data_loader:load_prices:70 - got 267248 prices\n",
+      "2021-08-12 16:00:03.945 | INFO     | besser_tanken.data_loader:load_prices:70 - got 274498 prices\n",
+      "2021-08-12 16:00:04.682 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-22-prices.csv\n",
+      "2021-08-12 16:00:05.344 | INFO     | besser_tanken.data_loader:load_prices:70 - got 285905 prices\n",
+      "2021-08-12 16:00:05.424 | INFO     | besser_tanken.data_loader:load_prices:70 - got 296929 prices\n",
+      "2021-08-12 16:00:06.191 | INFO     | besser_tanken.data_loader:load_prices:70 - got 298455 prices\n",
+      "2021-08-12 16:00:06.897 | INFO     | besser_tanken.data_loader:load_prices:70 - got 295861 prices\n",
+      "2021-08-12 16:00:07.369 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-21-prices.csv\n",
+      "2021-08-12 16:00:07.550 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-23-prices.csv\n",
+      "2021-08-12 16:00:07.933 | INFO     | besser_tanken.data_loader:load_prices:70 - got 282465 prices\n",
+      "2021-08-12 16:00:08.676 | INFO     | besser_tanken.data_loader:load_prices:70 - got 272819 prices\n",
+      "2021-08-12 16:00:08.733 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-24-prices.csv\n",
+      "2021-08-12 16:00:08.795 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-25-prices.csv\n",
+      "2021-08-12 16:00:09.550 | INFO     | besser_tanken.data_loader:load_prices:70 - got 305490 prices\n",
+      "2021-08-12 16:00:09.592 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-26-prices.csv\n",
+      "2021-08-12 16:00:09.729 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-27-prices.csv\n",
+      "2021-08-12 16:00:11.246 | INFO     | besser_tanken.data_loader:load_prices:70 - got 297022 prices\n",
+      "2021-08-12 16:00:12.092 | INFO     | besser_tanken.data_loader:load_prices:70 - got 299097 prices\n",
+      "2021-08-12 16:00:12.149 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-28-prices.csv\n",
+      "2021-08-12 16:00:12.218 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-29-prices.csv\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2021-08-12 16:00:13.005 | INFO     | besser_tanken.data_loader:load_prices:70 - got 278182 prices\n",
+      "2021-08-12 16:00:13.006 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-30-prices.csv\n",
+      "2021-08-12 16:00:13.686 | INFO     | besser_tanken.data_loader:load_prices:70 - got 271525 prices\n",
+      "2021-08-12 16:00:13.753 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-01-prices.csv\n",
+      "2021-08-12 16:00:13.758 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2020/12/2020-12-31-prices.csv\n",
+      "2021-08-12 16:00:14.446 | INFO     | besser_tanken.data_loader:load_prices:70 - got 270551 prices\n",
+      "2021-08-12 16:00:14.641 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-02-prices.csv\n",
+      "2021-08-12 16:00:15.269 | INFO     | besser_tanken.data_loader:load_prices:70 - got 265410 prices\n",
+      "2021-08-12 16:00:15.614 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-03-prices.csv\n",
+      "2021-08-12 16:00:15.905 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-04-prices.csv\n",
+      "2021-08-12 16:00:16.564 | INFO     | besser_tanken.data_loader:load_prices:70 - got 274174 prices\n",
+      "2021-08-12 16:00:16.577 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-05-prices.csv\n",
+      "2021-08-12 16:00:17.438 | INFO     | besser_tanken.data_loader:load_prices:70 - got 285401 prices\n",
+      "2021-08-12 16:00:18.119 | INFO     | besser_tanken.data_loader:load_prices:70 - got 279312 prices\n",
+      "2021-08-12 16:00:18.131 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-06-prices.csv\n",
+      "2021-08-12 16:00:18.791 | INFO     | besser_tanken.data_loader:load_prices:70 - got 244857 prices\n",
+      "2021-08-12 16:00:18.816 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-07-prices.csv\n",
+      "2021-08-12 16:00:19.489 | INFO     | besser_tanken.data_loader:load_prices:70 - got 257397 prices\n",
+      "2021-08-12 16:00:19.489 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-08-prices.csv\n",
+      "2021-08-12 16:00:20.285 | INFO     | besser_tanken.data_loader:load_prices:70 - got 260542 prices\n",
+      "2021-08-12 16:00:20.898 | INFO     | besser_tanken.data_loader:load_prices:70 - got 257142 prices\n",
+      "2021-08-12 16:00:21.633 | INFO     | besser_tanken.data_loader:load_prices:70 - got 279636 prices\n",
+      "2021-08-12 16:00:21.674 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-10-prices.csv\n",
+      "2021-08-12 16:00:21.679 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-09-prices.csv\n",
+      "2021-08-12 16:00:22.628 | INFO     | besser_tanken.data_loader:load_prices:70 - got 294651 prices\n",
+      "2021-08-12 16:00:22.913 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-12-prices.csv\n",
+      "2021-08-12 16:00:23.548 | INFO     | besser_tanken.data_loader:load_prices:70 - got 293143 prices\n",
+      "2021-08-12 16:00:23.655 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-11-prices.csv\n",
+      "2021-08-12 16:00:24.986 | INFO     | besser_tanken.data_loader:load_prices:70 - got 291029 prices\n",
+      "2021-08-12 16:00:25.466 | INFO     | besser_tanken.data_loader:load_prices:70 - got 291819 prices\n",
+      "2021-08-12 16:00:25.568 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-14-prices.csv\n",
+      "2021-08-12 16:00:25.626 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-15-prices.csv\n",
+      "2021-08-12 16:00:25.657 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-13-prices.csv\n",
+      "2021-08-12 16:00:25.703 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-16-prices.csv\n",
+      "2021-08-12 16:00:26.577 | INFO     | besser_tanken.data_loader:load_prices:70 - got 278188 prices\n",
+      "2021-08-12 16:00:27.109 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-17-prices.csv\n",
+      "2021-08-12 16:00:27.296 | INFO     | besser_tanken.data_loader:load_prices:70 - got 267935 prices\n",
+      "2021-08-12 16:00:28.030 | INFO     | besser_tanken.data_loader:load_prices:70 - got 295469 prices\n",
+      "2021-08-12 16:00:28.783 | INFO     | besser_tanken.data_loader:load_prices:70 - got 294834 prices\n",
+      "2021-08-12 16:00:28.820 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-19-prices.csv\n",
+      "2021-08-12 16:00:29.014 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-20-prices.csv\n",
+      "2021-08-12 16:00:29.045 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-18-prices.csv\n",
+      "2021-08-12 16:00:29.894 | INFO     | besser_tanken.data_loader:load_prices:70 - got 291697 prices\n",
+      "2021-08-12 16:00:30.849 | INFO     | besser_tanken.data_loader:load_prices:70 - got 296425 prices\n",
+      "2021-08-12 16:00:30.855 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-21-prices.csv\n",
+      "2021-08-12 16:00:31.560 | INFO     | besser_tanken.data_loader:load_prices:70 - got 293111 prices\n",
+      "2021-08-12 16:00:31.719 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-22-prices.csv\n",
+      "2021-08-12 16:00:32.260 | INFO     | besser_tanken.data_loader:load_prices:70 - got 277281 prices\n",
+      "2021-08-12 16:00:32.351 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-24-prices.csv\n",
+      "2021-08-12 16:00:32.563 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-23-prices.csv\n",
+      "2021-08-12 16:00:33.060 | INFO     | besser_tanken.data_loader:load_prices:70 - got 267150 prices\n",
+      "2021-08-12 16:00:34.515 | INFO     | besser_tanken.data_loader:load_prices:70 - got 292338 prices\n",
+      "2021-08-12 16:00:34.935 | INFO     | besser_tanken.data_loader:load_prices:70 - got 292261 prices\n",
+      "2021-08-12 16:00:35.012 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-25-prices.csv\n",
+      "2021-08-12 16:00:35.701 | INFO     | besser_tanken.data_loader:load_prices:70 - got 286600 prices\n",
+      "2021-08-12 16:00:35.706 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-26-prices.csv\n",
+      "2021-08-12 16:00:35.897 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-27-prices.csv\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2021-08-12 16:00:36.577 | INFO     | besser_tanken.data_loader:load_prices:70 - got 288069 prices\n",
+      "2021-08-12 16:00:36.706 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-28-prices.csv\n",
+      "2021-08-12 16:00:37.495 | INFO     | besser_tanken.data_loader:load_prices:70 - got 300483 prices\n",
+      "2021-08-12 16:00:38.357 | INFO     | besser_tanken.data_loader:load_prices:70 - got 258369 prices\n",
+      "2021-08-12 16:00:39.012 | INFO     | besser_tanken.data_loader:load_prices:70 - got 265136 prices\n",
+      "2021-08-12 16:00:39.121 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-30-prices.csv\n",
+      "2021-08-12 16:00:39.183 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-29-prices.csv\n",
+      "2021-08-12 16:00:40.137 | INFO     | besser_tanken.data_loader:load_prices:70 - got 295133 prices\n",
+      "2021-08-12 16:00:40.650 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-01-prices.csv\n",
+      "2021-08-12 16:00:40.888 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/01/2021-01-31-prices.csv\n",
+      "2021-08-12 16:00:41.146 | INFO     | besser_tanken.data_loader:load_prices:70 - got 290998 prices\n",
+      "2021-08-12 16:00:41.966 | INFO     | besser_tanken.data_loader:load_prices:70 - got 295802 prices\n",
+      "2021-08-12 16:00:42.229 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-03-prices.csv\n",
+      "2021-08-12 16:00:42.817 | INFO     | besser_tanken.data_loader:load_prices:70 - got 292843 prices\n",
+      "2021-08-12 16:00:42.953 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-02-prices.csv\n",
+      "2021-08-12 16:00:43.013 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-04-prices.csv\n",
+      "2021-08-12 16:00:43.774 | INFO     | besser_tanken.data_loader:load_prices:70 - got 281149 prices\n",
+      "2021-08-12 16:00:43.783 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-05-prices.csv\n",
+      "2021-08-12 16:00:43.834 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-06-prices.csv\n",
+      "2021-08-12 16:00:44.648 | INFO     | besser_tanken.data_loader:load_prices:70 - got 301491 prices\n",
+      "2021-08-12 16:00:45.410 | INFO     | besser_tanken.data_loader:load_prices:70 - got 296274 prices\n",
+      "2021-08-12 16:00:46.092 | INFO     | besser_tanken.data_loader:load_prices:70 - got 269334 prices\n",
+      "2021-08-12 16:00:46.272 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-08-prices.csv\n",
+      "2021-08-12 16:00:46.278 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-09-prices.csv\n",
+      "2021-08-12 16:00:46.288 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-07-prices.csv\n",
+      "2021-08-12 16:00:46.962 | INFO     | besser_tanken.data_loader:load_prices:70 - got 293349 prices\n",
+      "2021-08-12 16:00:47.761 | INFO     | besser_tanken.data_loader:load_prices:70 - got 290786 prices\n",
+      "2021-08-12 16:00:48.849 | INFO     | besser_tanken.data_loader:load_prices:70 - got 285679 prices\n",
+      "2021-08-12 16:00:49.719 | INFO     | besser_tanken.data_loader:load_prices:70 - got 320138 prices\n",
+      "2021-08-12 16:00:49.785 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-10-prices.csv\n",
+      "2021-08-12 16:00:50.415 | INFO     | besser_tanken.data_loader:load_prices:70 - got 266559 prices\n",
+      "2021-08-12 16:00:50.523 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-11-prices.csv\n",
+      "2021-08-12 16:00:51.386 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-13-prices.csv\n",
+      "2021-08-12 16:00:51.513 | INFO     | besser_tanken.data_loader:load_prices:70 - got 312960 prices\n",
+      "2021-08-12 16:00:51.899 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-14-prices.csv\n",
+      "2021-08-12 16:00:52.703 | INFO     | besser_tanken.data_loader:load_prices:70 - got 285353 prices\n",
+      "2021-08-12 16:00:52.814 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-12-prices.csv\n",
+      "2021-08-12 16:00:53.017 | INFO     | besser_tanken.data_loader:load_prices:70 - got 291564 prices\n",
+      "2021-08-12 16:00:54.838 | INFO     | besser_tanken.data_loader:load_prices:70 - got 303852 prices\n",
+      "2021-08-12 16:00:55.326 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-16-prices.csv\n",
+      "2021-08-12 16:00:55.985 | INFO     | besser_tanken.data_loader:load_prices:70 - got 308485 prices\n",
+      "2021-08-12 16:00:56.360 | INFO     | besser_tanken.data_loader:load_prices:70 - got 299186 prices\n",
+      "2021-08-12 16:00:56.379 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-17-prices.csv\n",
+      "2021-08-12 16:00:56.455 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-15-prices.csv\n",
+      "2021-08-12 16:00:57.139 | INFO     | besser_tanken.data_loader:load_prices:70 - got 280736 prices\n",
+      "2021-08-12 16:00:57.198 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-20-prices.csv\n",
+      "2021-08-12 16:00:57.218 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-19-prices.csv\n",
+      "2021-08-12 16:00:57.239 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-18-prices.csv\n",
+      "2021-08-12 16:00:57.607 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-21-prices.csv\n",
+      "2021-08-12 16:00:58.189 | INFO     | besser_tanken.data_loader:load_prices:70 - got 322374 prices\n",
+      "2021-08-12 16:00:58.332 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-22-prices.csv\n",
+      "2021-08-12 16:00:59.171 | INFO     | besser_tanken.data_loader:load_prices:70 - got 299061 prices\n",
+      "2021-08-12 16:00:59.913 | INFO     | besser_tanken.data_loader:load_prices:70 - got 302117 prices\n",
+      "2021-08-12 16:00:59.944 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-23-prices.csv\n",
+      "2021-08-12 16:01:00.683 | INFO     | besser_tanken.data_loader:load_prices:70 - got 305624 prices\n",
+      "2021-08-12 16:01:00.746 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-24-prices.csv\n",
+      "2021-08-12 16:01:01.147 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-25-prices.csv\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2021-08-12 16:01:01.860 | INFO     | besser_tanken.data_loader:load_prices:70 - got 286031 prices\n",
+      "2021-08-12 16:01:01.977 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-26-prices.csv\n",
+      "2021-08-12 16:01:02.594 | INFO     | besser_tanken.data_loader:load_prices:70 - got 299713 prices\n",
+      "2021-08-12 16:01:03.295 | INFO     | besser_tanken.data_loader:load_prices:70 - got 297799 prices\n",
+      "2021-08-12 16:01:03.939 | INFO     | besser_tanken.data_loader:load_prices:70 - got 251823 prices\n",
+      "2021-08-12 16:01:03.940 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-27-prices.csv\n",
+      "2021-08-12 16:01:04.009 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/02/2021-02-28-prices.csv\n",
+      "2021-08-12 16:01:04.727 | INFO     | besser_tanken.data_loader:load_prices:70 - got 302751 prices\n",
+      "2021-08-12 16:01:05.625 | INFO     | besser_tanken.data_loader:load_prices:70 - got 299860 prices\n",
+      "2021-08-12 16:01:05.804 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-01-prices.csv\n",
+      "2021-08-12 16:01:06.844 | INFO     | besser_tanken.data_loader:load_prices:70 - got 292382 prices\n",
+      "2021-08-12 16:01:07.358 | INFO     | besser_tanken.data_loader:load_prices:70 - got 298778 prices\n",
+      "2021-08-12 16:01:07.492 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-02-prices.csv\n",
+      "2021-08-12 16:01:08.279 | INFO     | besser_tanken.data_loader:load_prices:70 - got 301929 prices\n",
+      "2021-08-12 16:01:08.521 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-03-prices.csv\n",
+      "2021-08-12 16:01:08.805 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-04-prices.csv\n",
+      "2021-08-12 16:01:09.540 | INFO     | besser_tanken.data_loader:load_prices:70 - got 281441 prices\n",
+      "2021-08-12 16:01:10.181 | INFO     | besser_tanken.data_loader:load_prices:70 - got 267923 prices\n",
+      "2021-08-12 16:01:10.195 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-05-prices.csv\n",
+      "2021-08-12 16:01:10.366 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-06-prices.csv\n",
+      "2021-08-12 16:01:10.376 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-07-prices.csv\n",
+      "2021-08-12 16:01:11.153 | INFO     | besser_tanken.data_loader:load_prices:70 - got 294123 prices\n",
+      "2021-08-12 16:01:11.353 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-08-prices.csv\n",
+      "2021-08-12 16:01:12.572 | INFO     | besser_tanken.data_loader:load_prices:70 - got 298276 prices\n",
+      "2021-08-12 16:01:13.050 | INFO     | besser_tanken.data_loader:load_prices:70 - got 314743 prices\n",
+      "2021-08-12 16:01:13.110 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-09-prices.csv\n",
+      "2021-08-12 16:01:13.140 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-10-prices.csv\n",
+      "2021-08-12 16:01:13.968 | INFO     | besser_tanken.data_loader:load_prices:70 - got 300006 prices\n",
+      "2021-08-12 16:01:15.074 | INFO     | besser_tanken.data_loader:load_prices:70 - got 300856 prices\n",
+      "2021-08-12 16:01:15.774 | INFO     | besser_tanken.data_loader:load_prices:70 - got 287711 prices\n",
+      "2021-08-12 16:01:15.780 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-11-prices.csv\n",
+      "2021-08-12 16:01:16.448 | INFO     | besser_tanken.data_loader:load_prices:70 - got 270202 prices\n",
+      "2021-08-12 16:01:16.494 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-12-prices.csv\n",
+      "2021-08-12 16:01:17.353 | INFO     | besser_tanken.data_loader:load_prices:70 - got 297457 prices\n",
+      "2021-08-12 16:01:17.375 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-13-prices.csv\n",
+      "2021-08-12 16:01:17.470 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-14-prices.csv\n",
+      "2021-08-12 16:01:18.265 | INFO     | besser_tanken.data_loader:load_prices:70 - got 299724 prices\n",
+      "2021-08-12 16:01:18.991 | INFO     | besser_tanken.data_loader:load_prices:70 - got 303379 prices\n",
+      "2021-08-12 16:01:18.991 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-15-prices.csv\n",
+      "2021-08-12 16:01:20.049 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-16-prices.csv\n",
+      "2021-08-12 16:01:20.574 | INFO     | besser_tanken.data_loader:load_prices:70 - got 303081 prices\n",
+      "2021-08-12 16:01:20.669 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-17-prices.csv\n",
+      "2021-08-12 16:01:20.729 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-18-prices.csv\n",
+      "2021-08-12 16:01:20.966 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-20-prices.csv\n",
+      "2021-08-12 16:01:21.533 | INFO     | besser_tanken.data_loader:load_prices:70 - got 302240 prices\n",
+      "2021-08-12 16:01:22.218 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-21-prices.csv\n",
+      "2021-08-12 16:01:22.314 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-22-prices.csv\n",
+      "2021-08-12 16:01:22.334 | INFO     | besser_tanken.data_loader:load_prices:70 - got 274465 prices\n",
+      "2021-08-12 16:01:22.344 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-19-prices.csv\n",
+      "2021-08-12 16:01:23.186 | INFO     | besser_tanken.data_loader:load_prices:70 - got 270065 prices\n",
+      "2021-08-12 16:01:23.924 | INFO     | besser_tanken.data_loader:load_prices:70 - got 300843 prices\n",
+      "2021-08-12 16:01:23.971 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-23-prices.csv\n",
+      "2021-08-12 16:01:24.714 | INFO     | besser_tanken.data_loader:load_prices:70 - got 303397 prices\n",
+      "2021-08-12 16:01:25.411 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-24-prices.csv\n",
+      "2021-08-12 16:01:25.546 | INFO     | besser_tanken.data_loader:load_prices:70 - got 300025 prices\n",
+      "2021-08-12 16:01:26.403 | INFO     | besser_tanken.data_loader:load_prices:70 - got 309499 prices\n",
+      "2021-08-12 16:01:27.154 | INFO     | besser_tanken.data_loader:load_prices:70 - got 289836 prices\n",
+      "2021-08-12 16:01:27.276 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-25-prices.csv\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2021-08-12 16:01:27.949 | INFO     | besser_tanken.data_loader:load_prices:70 - got 267630 prices\n",
+      "2021-08-12 16:01:27.960 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-26-prices.csv\n",
+      "2021-08-12 16:01:28.697 | INFO     | besser_tanken.data_loader:load_prices:70 - got 307740 prices\n",
+      "2021-08-12 16:01:28.820 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-27-prices.csv\n",
+      "2021-08-12 16:01:29.552 | INFO     | besser_tanken.data_loader:load_prices:70 - got 305209 prices\n",
+      "2021-08-12 16:01:30.462 | INFO     | besser_tanken.data_loader:load_prices:70 - got 284813 prices\n",
+      "2021-08-12 16:01:31.234 | INFO     | besser_tanken.data_loader:load_prices:70 - got 278406 prices\n",
+      "2021-08-12 16:01:31.295 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-28-prices.csv\n",
+      "2021-08-12 16:01:32.480 | INFO     | besser_tanken.data_loader:load_prices:70 - got 281674 prices\n",
+      "2021-08-12 16:01:32.575 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-30-prices.csv\n",
+      "2021-08-12 16:01:32.903 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-31-prices.csv\n",
+      "2021-08-12 16:01:33.186 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/03/2021-03-29-prices.csv\n",
+      "2021-08-12 16:01:33.590 | INFO     | besser_tanken.data_loader:load_prices:70 - got 279638 prices\n",
+      "2021-08-12 16:01:34.234 | INFO     | besser_tanken.data_loader:load_prices:70 - got 257995 prices\n",
+      "2021-08-12 16:01:34.584 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-02-prices.csv\n",
+      "2021-08-12 16:01:34.731 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-01-prices.csv\n",
+      "2021-08-12 16:01:34.742 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-03-prices.csv\n",
+      "2021-08-12 16:01:35.410 | INFO     | besser_tanken.data_loader:load_prices:70 - got 243278 prices\n",
+      "2021-08-12 16:01:35.565 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-05-prices.csv\n",
+      "2021-08-12 16:01:35.814 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-04-prices.csv\n",
+      "2021-08-12 16:01:36.607 | INFO     | besser_tanken.data_loader:load_prices:70 - got 312526 prices\n",
+      "2021-08-12 16:01:37.362 | INFO     | besser_tanken.data_loader:load_prices:70 - got 307644 prices\n",
+      "2021-08-12 16:01:37.392 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-06-prices.csv\n",
+      "2021-08-12 16:01:38.148 | INFO     | besser_tanken.data_loader:load_prices:70 - got 310474 prices\n",
+      "2021-08-12 16:01:38.159 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-07-prices.csv\n",
+      "2021-08-12 16:01:38.956 | INFO     | besser_tanken.data_loader:load_prices:70 - got 269837 prices\n",
+      "2021-08-12 16:01:38.996 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-08-prices.csv\n",
+      "2021-08-12 16:01:39.408 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-09-prices.csv\n",
+      "2021-08-12 16:01:39.828 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-10-prices.csv\n",
+      "2021-08-12 16:01:40.022 | INFO     | besser_tanken.data_loader:load_prices:70 - got 311357 prices\n",
+      "2021-08-12 16:01:40.667 | INFO     | besser_tanken.data_loader:load_prices:70 - got 268407 prices\n",
+      "2021-08-12 16:01:41.286 | INFO     | besser_tanken.data_loader:load_prices:70 - got 274141 prices\n",
+      "2021-08-12 16:01:41.925 | INFO     | besser_tanken.data_loader:load_prices:70 - got 256287 prices\n",
+      "2021-08-12 16:01:42.050 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-11-prices.csv\n",
+      "2021-08-12 16:01:42.783 | INFO     | besser_tanken.data_loader:load_prices:70 - got 317049 prices\n",
+      "2021-08-12 16:01:43.572 | INFO     | besser_tanken.data_loader:load_prices:70 - got 317581 prices\n",
+      "2021-08-12 16:01:44.745 | INFO     | besser_tanken.data_loader:load_prices:70 - got 338501 prices\n",
+      "2021-08-12 16:01:44.745 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-12-prices.csv\n",
+      "2021-08-12 16:01:46.554 | INFO     | besser_tanken.data_loader:load_prices:70 - got 279637 prices\n",
+      "2021-08-12 16:01:46.589 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-13-prices.csv\n",
+      "2021-08-12 16:01:46.616 | INFO     | besser_tanken.data_loader:load_prices:70 - got 293932 prices\n",
+      "2021-08-12 16:01:46.632 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-15-prices.csv\n",
+      "2021-08-12 16:01:47.764 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-14-prices.csv\n",
+      "2021-08-12 16:01:47.779 | INFO     | besser_tanken.data_loader:load_prices:70 - got 261957 prices\n",
+      "2021-08-12 16:01:47.834 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-17-prices.csv\n",
+      "2021-08-12 16:01:47.865 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-16-prices.csv\n",
+      "2021-08-12 16:01:48.113 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-18-prices.csv\n",
+      "2021-08-12 16:01:49.270 | INFO     | besser_tanken.data_loader:load_prices:70 - got 308348 prices\n",
+      "2021-08-12 16:01:50.158 | INFO     | besser_tanken.data_loader:load_prices:70 - got 315661 prices\n",
+      "2021-08-12 16:01:50.322 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-19-prices.csv\n",
+      "2021-08-12 16:01:50.384 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-21-prices.csv\n",
+      "2021-08-12 16:01:51.215 | INFO     | besser_tanken.data_loader:load_prices:70 - got 314120 prices\n",
+      "2021-08-12 16:01:51.215 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-22-prices.csv\n",
+      "2021-08-12 16:01:51.963 | INFO     | besser_tanken.data_loader:load_prices:70 - got 307809 prices\n",
+      "2021-08-12 16:01:52.035 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-23-prices.csv\n",
+      "2021-08-12 16:01:52.608 | INFO     | besser_tanken.data_loader:load_prices:70 - got 245486 prices\n",
+      "2021-08-12 16:01:52.617 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-24-prices.csv\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2021-08-12 16:01:52.633 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-20-prices.csv\n",
+      "2021-08-12 16:01:56.004 | INFO     | besser_tanken.data_loader:load_prices:70 - got 269150 prices\n",
+      "2021-08-12 16:01:56.568 | INFO     | besser_tanken.data_loader:load_prices:70 - got 231764 prices\n",
+      "2021-08-12 16:01:56.830 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-25-prices.csv\n",
+      "2021-08-12 16:01:57.360 | INFO     | besser_tanken.data_loader:load_prices:70 - got 311389 prices\n",
+      "2021-08-12 16:01:57.361 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-26-prices.csv\n",
+      "2021-08-12 16:01:58.168 | INFO     | besser_tanken.data_loader:load_prices:70 - got 317099 prices\n",
+      "2021-08-12 16:01:58.442 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-27-prices.csv\n",
+      "2021-08-12 16:01:59.319 | INFO     | besser_tanken.data_loader:load_prices:70 - got 311989 prices\n",
+      "2021-08-12 16:01:59.454 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-28-prices.csv\n",
+      "2021-08-12 16:02:00.155 | INFO     | besser_tanken.data_loader:load_prices:70 - got 277334 prices\n",
+      "2021-08-12 16:02:01.213 | INFO     | besser_tanken.data_loader:load_prices:70 - got 319437 prices\n",
+      "2021-08-12 16:02:01.301 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-29-prices.csv\n",
+      "2021-08-12 16:02:01.817 | INFO     | besser_tanken.data_loader:load_prices:70 - got 266464 prices\n",
+      "2021-08-12 16:02:02.069 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/04/2021-04-30-prices.csv\n",
+      "2021-08-12 16:02:02.101 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-01-prices.csv\n",
+      "2021-08-12 16:02:02.762 | INFO     | besser_tanken.data_loader:load_prices:70 - got 247493 prices\n",
+      "2021-08-12 16:02:02.869 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-02-prices.csv\n",
+      "2021-08-12 16:02:03.681 | INFO     | besser_tanken.data_loader:load_prices:70 - got 323020 prices\n",
+      "2021-08-12 16:02:03.830 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-04-prices.csv\n",
+      "2021-08-12 16:02:05.207 | INFO     | besser_tanken.data_loader:load_prices:70 - got 316090 prices\n",
+      "2021-08-12 16:02:05.607 | INFO     | besser_tanken.data_loader:load_prices:70 - got 320951 prices\n",
+      "2021-08-12 16:02:05.676 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-03-prices.csv\n",
+      "2021-08-12 16:02:06.640 | INFO     | besser_tanken.data_loader:load_prices:70 - got 320842 prices\n",
+      "2021-08-12 16:02:06.856 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-07-prices.csv\n",
+      "2021-08-12 16:02:07.601 | INFO     | besser_tanken.data_loader:load_prices:70 - got 295191 prices\n",
+      "2021-08-12 16:02:07.622 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-05-prices.csv\n",
+      "2021-08-12 16:02:08.326 | INFO     | besser_tanken.data_loader:load_prices:70 - got 281559 prices\n",
+      "2021-08-12 16:02:08.427 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-06-prices.csv\n",
+      "2021-08-12 16:02:08.445 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-08-prices.csv\n",
+      "2021-08-12 16:02:08.472 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-09-prices.csv\n",
+      "2021-08-12 16:02:08.487 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-10-prices.csv\n",
+      "2021-08-12 16:02:09.224 | INFO     | besser_tanken.data_loader:load_prices:70 - got 268206 prices\n",
+      "2021-08-12 16:02:09.973 | INFO     | besser_tanken.data_loader:load_prices:70 - got 310422 prices\n",
+      "2021-08-12 16:02:11.427 | INFO     | besser_tanken.data_loader:load_prices:70 - got 316110 prices\n",
+      "2021-08-12 16:02:12.142 | INFO     | besser_tanken.data_loader:load_prices:70 - got 303829 prices\n",
+      "2021-08-12 16:02:12.162 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-11-prices.csv\n",
+      "2021-08-12 16:02:13.061 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-12-prices.csv\n",
+      "2021-08-12 16:02:13.148 | INFO     | besser_tanken.data_loader:load_prices:70 - got 314216 prices\n",
+      "2021-08-12 16:02:13.976 | INFO     | besser_tanken.data_loader:load_prices:70 - got 300563 prices\n",
+      "2021-08-12 16:02:14.720 | INFO     | besser_tanken.data_loader:load_prices:70 - got 311043 prices\n",
+      "2021-08-12 16:02:14.736 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-13-prices.csv\n",
+      "2021-08-12 16:02:14.793 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-14-prices.csv\n",
+      "2021-08-12 16:02:15.473 | INFO     | besser_tanken.data_loader:load_prices:70 - got 279529 prices\n",
+      "2021-08-12 16:02:15.482 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-15-prices.csv\n",
+      "2021-08-12 16:02:16.273 | INFO     | besser_tanken.data_loader:load_prices:70 - got 322838 prices\n",
+      "2021-08-12 16:02:16.372 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-16-prices.csv\n",
+      "2021-08-12 16:02:17.402 | INFO     | besser_tanken.data_loader:load_prices:70 - got 320776 prices\n",
+      "2021-08-12 16:02:18.337 | INFO     | besser_tanken.data_loader:load_prices:70 - got 323364 prices\n",
+      "2021-08-12 16:02:18.493 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-17-prices.csv\n",
+      "2021-08-12 16:02:19.176 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-18-prices.csv\n",
+      "2021-08-12 16:02:19.582 | INFO     | besser_tanken.data_loader:load_prices:70 - got 300333 prices\n",
+      "2021-08-12 16:02:20.369 | INFO     | besser_tanken.data_loader:load_prices:70 - got 318446 prices\n",
+      "2021-08-12 16:02:20.369 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-19-prices.csv\n",
+      "2021-08-12 16:02:20.426 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-20-prices.csv\n",
+      "2021-08-12 16:02:20.554 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-21-prices.csv\n",
+      "2021-08-12 16:02:21.375 | INFO     | besser_tanken.data_loader:load_prices:70 - got 295663 prices\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2021-08-12 16:02:22.613 | INFO     | besser_tanken.data_loader:load_prices:70 - got 281255 prices\n",
+      "2021-08-12 16:02:23.462 | INFO     | besser_tanken.data_loader:load_prices:70 - got 312171 prices\n",
+      "2021-08-12 16:02:23.508 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-23-prices.csv\n",
+      "2021-08-12 16:02:24.555 | INFO     | besser_tanken.data_loader:load_prices:70 - got 322048 prices\n",
+      "2021-08-12 16:02:24.695 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-22-prices.csv\n",
+      "2021-08-12 16:02:24.770 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-24-prices.csv\n",
+      "2021-08-12 16:02:25.171 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-26-prices.csv\n",
+      "2021-08-12 16:02:25.478 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-25-prices.csv\n",
+      "2021-08-12 16:02:25.540 | INFO     | besser_tanken.data_loader:load_prices:70 - got 321281 prices\n",
+      "2021-08-12 16:02:25.613 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-27-prices.csv\n",
+      "2021-08-12 16:02:25.623 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-28-prices.csv\n",
+      "2021-08-12 16:02:26.399 | INFO     | besser_tanken.data_loader:load_prices:70 - got 323562 prices\n",
+      "2021-08-12 16:02:27.132 | INFO     | besser_tanken.data_loader:load_prices:70 - got 311513 prices\n",
+      "2021-08-12 16:02:28.004 | INFO     | besser_tanken.data_loader:load_prices:70 - got 273299 prices\n",
+      "2021-08-12 16:02:28.717 | INFO     | besser_tanken.data_loader:load_prices:70 - got 295898 prices\n",
+      "2021-08-12 16:02:28.826 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-30-prices.csv\n",
+      "2021-08-12 16:02:28.827 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-29-prices.csv\n",
+      "2021-08-12 16:02:30.714 | INFO     | besser_tanken.data_loader:load_prices:70 - got 283712 prices\n",
+      "2021-08-12 16:02:30.851 | INFO     | besser_tanken.data_loader:load_prices:70 - got 309601 prices\n",
+      "2021-08-12 16:02:31.319 | INFO     | besser_tanken.data_loader:load_prices:70 - got 311840 prices\n",
+      "2021-08-12 16:02:32.259 | INFO     | besser_tanken.data_loader:load_prices:70 - got 306849 prices\n",
+      "2021-08-12 16:02:32.476 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/05/2021-05-31-prices.csv\n",
+      "2021-08-12 16:02:32.489 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-01-prices.csv\n",
+      "2021-08-12 16:02:32.772 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-02-prices.csv\n",
+      "2021-08-12 16:02:33.184 | INFO     | besser_tanken.data_loader:load_prices:70 - got 311428 prices\n",
+      "2021-08-12 16:02:33.596 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-03-prices.csv\n",
+      "2021-08-12 16:02:34.249 | INFO     | besser_tanken.data_loader:load_prices:70 - got 272179 prices\n",
+      "2021-08-12 16:02:35.080 | INFO     | besser_tanken.data_loader:load_prices:70 - got 292252 prices\n",
+      "2021-08-12 16:02:35.115 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-05-prices.csv\n",
+      "2021-08-12 16:02:36.436 | INFO     | besser_tanken.data_loader:load_prices:70 - got 297145 prices\n",
+      "2021-08-12 16:02:36.452 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-04-prices.csv\n",
+      "2021-08-12 16:02:37.630 | INFO     | besser_tanken.data_loader:load_prices:70 - got 305627 prices\n",
+      "2021-08-12 16:02:37.651 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-07-prices.csv\n",
+      "2021-08-12 16:02:37.656 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-08-prices.csv\n",
+      "2021-08-12 16:02:37.672 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-06-prices.csv\n",
+      "2021-08-12 16:02:37.748 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-09-prices.csv\n",
+      "2021-08-12 16:02:37.752 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-10-prices.csv\n",
+      "2021-08-12 16:02:37.763 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-11-prices.csv\n",
+      "2021-08-12 16:02:38.814 | INFO     | besser_tanken.data_loader:load_prices:70 - got 310321 prices\n",
+      "2021-08-12 16:02:38.830 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-12-prices.csv\n",
+      "2021-08-12 16:02:39.224 | INFO     | besser_tanken.data_loader:load_prices:70 - got 296089 prices\n",
+      "2021-08-12 16:02:39.932 | INFO     | besser_tanken.data_loader:load_prices:70 - got 284582 prices\n",
+      "2021-08-12 16:02:40.922 | INFO     | besser_tanken.data_loader:load_prices:70 - got 315296 prices\n",
+      "2021-08-12 16:02:41.848 | INFO     | besser_tanken.data_loader:load_prices:70 - got 301502 prices\n",
+      "2021-08-12 16:02:42.817 | INFO     | besser_tanken.data_loader:load_prices:70 - got 326345 prices\n",
+      "2021-08-12 16:02:43.591 | INFO     | besser_tanken.data_loader:load_prices:70 - got 280524 prices\n",
+      "2021-08-12 16:02:44.374 | INFO     | besser_tanken.data_loader:load_prices:70 - got 329611 prices\n",
+      "2021-08-12 16:02:44.375 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-13-prices.csv\n",
+      "2021-08-12 16:02:44.376 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-14-prices.csv\n",
+      "2021-08-12 16:02:45.098 | INFO     | besser_tanken.data_loader:load_prices:70 - got 318813 prices\n",
+      "2021-08-12 16:02:45.099 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-17-prices.csv\n",
+      "2021-08-12 16:02:45.876 | INFO     | besser_tanken.data_loader:load_prices:70 - got 324502 prices\n",
+      "2021-08-12 16:02:46.087 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-16-prices.csv\n",
+      "2021-08-12 16:02:46.660 | INFO     | besser_tanken.data_loader:load_prices:70 - got 286250 prices\n",
+      "2021-08-12 16:02:46.670 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-15-prices.csv\n",
+      "2021-08-12 16:02:48.679 | INFO     | besser_tanken.data_loader:load_prices:70 - got 278483 prices\n",
+      "2021-08-12 16:02:48.695 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-18-prices.csv\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2021-08-12 16:02:49.514 | INFO     | besser_tanken.data_loader:load_prices:70 - got 326330 prices\n",
+      "2021-08-12 16:02:49.566 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-19-prices.csv\n",
+      "2021-08-12 16:02:50.373 | INFO     | besser_tanken.data_loader:load_prices:70 - got 318714 prices\n",
+      "2021-08-12 16:02:51.179 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-21-prices.csv\n",
+      "2021-08-12 16:02:51.190 | INFO     | besser_tanken.data_loader:load_prices:70 - got 320353 prices\n",
+      "2021-08-12 16:02:51.267 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-20-prices.csv\n",
+      "2021-08-12 16:02:52.035 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-22-prices.csv\n",
+      "2021-08-12 16:02:52.060 | INFO     | besser_tanken.data_loader:load_prices:70 - got 322612 prices\n",
+      "2021-08-12 16:02:52.243 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-23-prices.csv\n",
+      "2021-08-12 16:02:52.330 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-24-prices.csv\n",
+      "2021-08-12 16:02:53.065 | INFO     | besser_tanken.data_loader:load_prices:70 - got 318015 prices\n",
+      "2021-08-12 16:02:54.040 | INFO     | besser_tanken.data_loader:load_prices:70 - got 291300 prices\n",
+      "2021-08-12 16:02:55.256 | INFO     | besser_tanken.data_loader:load_prices:70 - got 320304 prices\n",
+      "2021-08-12 16:02:55.264 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-25-prices.csv\n",
+      "2021-08-12 16:02:56.026 | INFO     | besser_tanken.data_loader:load_prices:70 - got 278580 prices\n",
+      "2021-08-12 16:02:56.045 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-26-prices.csv\n",
+      "2021-08-12 16:02:56.955 | INFO     | besser_tanken.data_loader:load_prices:70 - got 311422 prices\n",
+      "2021-08-12 16:02:57.001 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-29-prices.csv\n",
+      "2021-08-12 16:02:57.714 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-27-prices.csv\n",
+      "2021-08-12 16:02:57.800 | INFO     | besser_tanken.data_loader:load_prices:70 - got 313682 prices\n",
+      "2021-08-12 16:02:57.809 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-28-prices.csv\n",
+      "2021-08-12 16:02:58.642 | INFO     | besser_tanken.data_loader:load_prices:70 - got 329516 prices\n",
+      "2021-08-12 16:02:58.928 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/06/2021-06-30-prices.csv\n",
+      "2021-08-12 16:02:58.964 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-01-prices.csv\n",
+      "2021-08-12 16:02:59.512 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-02-prices.csv\n",
+      "2021-08-12 16:03:00.087 | INFO     | besser_tanken.data_loader:load_prices:70 - got 318168 prices\n",
+      "2021-08-12 16:03:00.902 | INFO     | besser_tanken.data_loader:load_prices:70 - got 303649 prices\n",
+      "2021-08-12 16:03:00.944 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-04-prices.csv\n",
+      "2021-08-12 16:03:01.793 | INFO     | besser_tanken.data_loader:load_prices:70 - got 311116 prices\n",
+      "2021-08-12 16:03:01.802 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-03-prices.csv\n",
+      "2021-08-12 16:03:02.433 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-05-prices.csv\n",
+      "2021-08-12 16:03:02.567 | INFO     | besser_tanken.data_loader:load_prices:70 - got 293388 prices\n",
+      "2021-08-12 16:03:03.668 | INFO     | besser_tanken.data_loader:load_prices:70 - got 320103 prices\n",
+      "2021-08-12 16:03:03.714 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-06-prices.csv\n",
+      "2021-08-12 16:03:04.482 | INFO     | besser_tanken.data_loader:load_prices:70 - got 319096 prices\n",
+      "2021-08-12 16:03:05.239 | INFO     | besser_tanken.data_loader:load_prices:70 - got 324591 prices\n",
+      "2021-08-12 16:03:06.041 | INFO     | besser_tanken.data_loader:load_prices:70 - got 322544 prices\n",
+      "2021-08-12 16:03:06.048 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-07-prices.csv\n",
+      "2021-08-12 16:03:06.838 | INFO     | besser_tanken.data_loader:load_prices:70 - got 291670 prices\n",
+      "2021-08-12 16:03:06.863 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-08-prices.csv\n",
+      "2021-08-12 16:03:06.990 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-09-prices.csv\n",
+      "2021-08-12 16:03:07.731 | INFO     | besser_tanken.data_loader:load_prices:70 - got 302137 prices\n",
+      "2021-08-12 16:03:08.715 | INFO     | besser_tanken.data_loader:load_prices:70 - got 323030 prices\n",
+      "2021-08-12 16:03:09.935 | INFO     | besser_tanken.data_loader:load_prices:70 - got 322967 prices\n",
+      "2021-08-12 16:03:09.972 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-10-prices.csv\n",
+      "2021-08-12 16:03:10.013 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-11-prices.csv\n",
+      "2021-08-12 16:03:10.023 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-12-prices.csv\n",
+      "2021-08-12 16:03:11.123 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-13-prices.csv\n",
+      "2021-08-12 16:03:11.309 | INFO     | besser_tanken.data_loader:load_prices:70 - got 330284 prices\n",
+      "2021-08-12 16:03:12.204 | INFO     | besser_tanken.data_loader:load_prices:70 - got 333165 prices\n",
+      "2021-08-12 16:03:12.958 | INFO     | besser_tanken.data_loader:load_prices:70 - got 329352 prices\n",
+      "2021-08-12 16:03:13.239 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-14-prices.csv\n",
+      "2021-08-12 16:03:13.301 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-15-prices.csv\n",
+      "2021-08-12 16:03:13.399 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-16-prices.csv\n",
+      "2021-08-12 16:03:13.805 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-18-prices.csv\n",
+      "2021-08-12 16:03:14.620 | INFO     | besser_tanken.data_loader:load_prices:70 - got 295236 prices\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2021-08-12 16:03:15.292 | INFO     | besser_tanken.data_loader:load_prices:70 - got 304704 prices\n",
+      "2021-08-12 16:03:15.441 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-17-prices.csv\n",
+      "2021-08-12 16:03:16.184 | INFO     | besser_tanken.data_loader:load_prices:70 - got 328208 prices\n",
+      "2021-08-12 16:03:17.028 | INFO     | besser_tanken.data_loader:load_prices:70 - got 326770 prices\n",
+      "2021-08-12 16:03:17.029 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-21-prices.csv\n",
+      "2021-08-12 16:03:17.060 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-20-prices.csv\n",
+      "2021-08-12 16:03:17.132 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-19-prices.csv\n",
+      "2021-08-12 16:03:18.161 | INFO     | besser_tanken.data_loader:load_prices:70 - got 311586 prices\n",
+      "2021-08-12 16:03:19.294 | INFO     | besser_tanken.data_loader:load_prices:70 - got 328226 prices\n",
+      "2021-08-12 16:03:19.329 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-22-prices.csv\n",
+      "2021-08-12 16:03:20.862 | INFO     | besser_tanken.data_loader:load_prices:70 - got 327267 prices\n",
+      "2021-08-12 16:03:21.356 | INFO     | besser_tanken.data_loader:load_prices:70 - got 305533 prices\n",
+      "2021-08-12 16:03:21.698 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-23-prices.csv\n",
+      "2021-08-12 16:03:21.743 | INFO     | besser_tanken.data_loader:load_prices:70 - got 293467 prices\n",
+      "2021-08-12 16:03:21.793 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-24-prices.csv\n",
+      "2021-08-12 16:03:21.964 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-26-prices.csv\n",
+      "2021-08-12 16:03:22.578 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-25-prices.csv\n",
+      "2021-08-12 16:03:22.794 | INFO     | besser_tanken.data_loader:load_prices:70 - got 337510 prices\n",
+      "2021-08-12 16:03:23.865 | INFO     | besser_tanken.data_loader:load_prices:70 - got 331415 prices\n",
+      "2021-08-12 16:03:24.739 | INFO     | besser_tanken.data_loader:load_prices:70 - got 326963 prices\n",
+      "2021-08-12 16:03:24.744 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-27-prices.csv\n",
+      "2021-08-12 16:03:25.695 | INFO     | besser_tanken.data_loader:load_prices:70 - got 331360 prices\n",
+      "2021-08-12 16:03:26.767 | INFO     | besser_tanken.data_loader:load_prices:70 - got 325880 prices\n",
+      "2021-08-12 16:03:27.540 | INFO     | besser_tanken.data_loader:load_prices:70 - got 311321 prices\n",
+      "2021-08-12 16:03:27.540 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-28-prices.csv\n",
+      "2021-08-12 16:03:27.581 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-29-prices.csv\n",
+      "2021-08-12 16:03:29.187 | INFO     | besser_tanken.data_loader:load_prices:70 - got 294263 prices\n",
+      "2021-08-12 16:03:29.353 | INFO     | besser_tanken.data_loader:load_prices:70 - got 328661 prices\n",
+      "2021-08-12 16:03:30.682 | INFO     | besser_tanken.data_loader:load_prices:70 - got 328049 prices\n",
+      "2021-08-12 16:03:30.782 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/08/2021-08-01-prices.csv\n",
+      "2021-08-12 16:03:30.786 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-30-prices.csv\n",
+      "2021-08-12 16:03:30.808 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/07/2021-07-31-prices.csv\n",
+      "2021-08-12 16:03:30.915 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/08/2021-08-02-prices.csv\n",
+      "2021-08-12 16:03:30.992 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/08/2021-08-03-prices.csv\n",
+      "2021-08-12 16:03:32.033 | INFO     | besser_tanken.data_loader:load_prices:70 - got 326698 prices\n",
+      "2021-08-12 16:03:32.796 | INFO     | besser_tanken.data_loader:load_prices:70 - got 328307 prices\n",
+      "2021-08-12 16:03:33.338 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/08/2021-08-06-prices.csv\n",
+      "2021-08-12 16:03:33.369 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/08/2021-08-04-prices.csv\n",
+      "2021-08-12 16:03:33.398 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/08/2021-08-05-prices.csv\n",
+      "2021-08-12 16:03:34.259 | INFO     | besser_tanken.data_loader:load_prices:70 - got 294359 prices\n",
+      "2021-08-12 16:03:34.446 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/08/2021-08-08-prices.csv\n",
+      "2021-08-12 16:03:34.471 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/08/2021-08-07-prices.csv\n",
+      "2021-08-12 16:03:35.586 | INFO     | besser_tanken.data_loader:load_prices:70 - got 330570 prices\n",
+      "2021-08-12 16:03:36.009 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/08/2021-08-09-prices.csv\n",
+      "2021-08-12 16:03:36.013 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/08/2021-08-10-prices.csv\n",
+      "2021-08-12 16:03:36.015 | INFO     | besser_tanken.data_loader:load_prices:67 - loading prices file: /home/tobias/projects/besser_tanken/tankerkoenig-data/prices/2021/08/2021-08-11-prices.csv\n",
+      "2021-08-12 16:03:36.396 | INFO     | besser_tanken.data_loader:load_prices:70 - got 304848 prices\n",
+      "2021-08-12 16:03:37.584 | INFO     | besser_tanken.data_loader:load_prices:70 - got 322580 prices\n",
+      "2021-08-12 16:03:38.107 | INFO     | besser_tanken.data_loader:load_prices:70 - got 324433 prices\n",
+      "2021-08-12 16:03:38.967 | INFO     | besser_tanken.data_loader:load_prices:70 - got 320613 prices\n",
+      "2021-08-12 16:03:39.874 | INFO     | besser_tanken.data_loader:load_prices:70 - got 331188 prices\n",
+      "2021-08-12 16:03:40.655 | INFO     | besser_tanken.data_loader:load_prices:70 - got 327766 prices\n",
+      "2021-08-12 16:03:41.461 | INFO     | besser_tanken.data_loader:load_prices:70 - got 293810 prices\n",
+      "2021-08-12 16:03:42.209 | INFO     | besser_tanken.data_loader:load_prices:70 - got 309683 prices\n",
+      "2021-08-12 16:03:43.090 | INFO     | besser_tanken.data_loader:load_prices:70 - got 331244 prices\n",
+      "2021-08-12 16:03:43.882 | INFO     | besser_tanken.data_loader:load_prices:70 - got 314980 prices\n",
+      "2021-08-12 16:03:44.785 | INFO     | besser_tanken.data_loader:load_prices:70 - got 327550 prices\n"
+     ]
+    }
+   ],
+   "source": [
+    "#data = load_prices_from(2020,11,1)\n",
+    "df = load_prices_from(2020,11,1)\n",
+    "df = pd.DataFrame(df)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "f7431b46",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df.e5 = df['e5'].astype(float)\n",
+    "df.e10 = df['e10'].astype(float)\n",
+    "df.diesel = df['diesel'].astype(float)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "be19ae6b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df[\"date_time\"] = pd.to_datetime(df.date, infer_datetime_format=True, utc=True)\n",
+    "df[\"hour\"] = df.date_time.dt.hour\n",
+    "df[\"month\"] = df.date_time.dt.month\n",
+    "df[\"quarter\"] = df.date_time.dt.quarter\n",
+    "df[\"year\"] = df.date_time.dt.year\n",
+    "df[\"day\"] = df.date_time.dt.day\n",
+    "df[\"week\"] = df.date_time.dt.isocalendar().week\n",
+    "df[\"weekday\"] = df.date_time.dt.weekday\n",
+    "df[\"season\"] = np.where(df[\"month\"].isin([3,4,5]),\"spring\",\n",
+    "   np.where(df[\"month\"].isin([6,7,8]),\"summer\",\n",
+    "   np.where(df[\"month\"].isin([9,10,11]),\"fall\",\n",
+    "   np.where(df[\"month\"].isin([12,1,2]),\"winter\",\"None\"))))\n",
+    "#buehl[\"weekday_name\"] = np.where(df[\"weekday\"].isin([0]),\"mon\",\n",
+    "#   np.where(df[\"weekday\"].isin([1]),\"tue\",\n",
+    "#   np.where(df[\"weekday\"].isin([2]),\"wed\",\n",
+    "#   np.where(df[\"weekday\"].isin([3]),\"thu\",\n",
+    "#   np.where(df[\"weekday\"].isin([4]),\"fri\",            \n",
+    "#   np.where(df[\"weekday\"].isin([5]),\"sat\",            \n",
+    "#   np.where(df[\"weekday\"].isin([6]),\"sun\",\"None\")))))))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "ee8153a0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#df[\"date_time\"] = pd.to_datetime(df.date)\n",
+    "#df[\"month\"] = df[\"date_time\"].dt.month"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "d4419141",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>date</th>\n",
+       "      <th>station_uuid</th>\n",
+       "      <th>diesel</th>\n",
+       "      <th>e5</th>\n",
+       "      <th>e10</th>\n",
+       "      <th>dieselchange</th>\n",
+       "      <th>e5change</th>\n",
+       "      <th>e10change</th>\n",
+       "      <th>date_time</th>\n",
+       "      <th>hour</th>\n",
+       "      <th>month</th>\n",
+       "      <th>quarter</th>\n",
+       "      <th>year</th>\n",
+       "      <th>day</th>\n",
+       "      <th>week</th>\n",
+       "      <th>weekday</th>\n",
+       "      <th>season</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>2020-11-07 00:00:08+0100</td>\n",
+       "      <td>a1e15688-663a-42da-86b3-0501597bcab7</td>\n",
+       "      <td>0.968</td>\n",
+       "      <td>1.168</td>\n",
+       "      <td>1.118</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2020-11-06 23:00:08+00:00</td>\n",
+       "      <td>23</td>\n",
+       "      <td>11</td>\n",
+       "      <td>4</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>6</td>\n",
+       "      <td>45</td>\n",
+       "      <td>4</td>\n",
+       "      <td>fall</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2020-11-07 00:01:06+0100</td>\n",
+       "      <td>9bb515a4-c551-41b8-a8a1-e120f29474fd</td>\n",
+       "      <td>0.989</td>\n",
+       "      <td>1.139</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2020-11-06 23:01:06+00:00</td>\n",
+       "      <td>23</td>\n",
+       "      <td>11</td>\n",
+       "      <td>4</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>6</td>\n",
+       "      <td>45</td>\n",
+       "      <td>4</td>\n",
+       "      <td>fall</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2020-11-07 00:01:06+0100</td>\n",
+       "      <td>0d58c4ba-3267-404a-89d6-6ba15a8fc422</td>\n",
+       "      <td>1.069</td>\n",
+       "      <td>1.239</td>\n",
+       "      <td>1.189</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2020-11-06 23:01:06+00:00</td>\n",
+       "      <td>23</td>\n",
+       "      <td>11</td>\n",
+       "      <td>4</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>6</td>\n",
+       "      <td>45</td>\n",
+       "      <td>4</td>\n",
+       "      <td>fall</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2020-11-07 00:01:06+0100</td>\n",
+       "      <td>3e385667-56a9-46b4-96de-2adcfd7b5655</td>\n",
+       "      <td>1.029</td>\n",
+       "      <td>1.219</td>\n",
+       "      <td>1.169</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2020-11-06 23:01:06+00:00</td>\n",
+       "      <td>23</td>\n",
+       "      <td>11</td>\n",
+       "      <td>4</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>6</td>\n",
+       "      <td>45</td>\n",
+       "      <td>4</td>\n",
+       "      <td>fall</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2020-11-07 00:01:06+0100</td>\n",
+       "      <td>0055910e-f1e4-4b42-8489-ba2880ef434c</td>\n",
+       "      <td>0.999</td>\n",
+       "      <td>1.149</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2020-11-06 23:01:06+00:00</td>\n",
+       "      <td>23</td>\n",
+       "      <td>11</td>\n",
+       "      <td>4</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>6</td>\n",
+       "      <td>45</td>\n",
+       "      <td>4</td>\n",
+       "      <td>fall</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                       date                          station_uuid  diesel  \\\n",
+       "0  2020-11-07 00:00:08+0100  a1e15688-663a-42da-86b3-0501597bcab7   0.968   \n",
+       "1  2020-11-07 00:01:06+0100  9bb515a4-c551-41b8-a8a1-e120f29474fd   0.989   \n",
+       "2  2020-11-07 00:01:06+0100  0d58c4ba-3267-404a-89d6-6ba15a8fc422   1.069   \n",
+       "3  2020-11-07 00:01:06+0100  3e385667-56a9-46b4-96de-2adcfd7b5655   1.029   \n",
+       "4  2020-11-07 00:01:06+0100  0055910e-f1e4-4b42-8489-ba2880ef434c   0.999   \n",
+       "\n",
+       "      e5    e10 dieselchange e5change e10change                 date_time  \\\n",
+       "0  1.168  1.118            0        1         1 2020-11-06 23:00:08+00:00   \n",
+       "1  1.139  0.000            1        1         0 2020-11-06 23:01:06+00:00   \n",
+       "2  1.239  1.189            1        1         1 2020-11-06 23:01:06+00:00   \n",
+       "3  1.219  1.169            1        1         1 2020-11-06 23:01:06+00:00   \n",
+       "4  1.149  0.000            1        1         0 2020-11-06 23:01:06+00:00   \n",
+       "\n",
+       "   hour  month  quarter  year  day  week  weekday season  \n",
+       "0    23     11        4  2020    6    45        4   fall  \n",
+       "1    23     11        4  2020    6    45        4   fall  \n",
+       "2    23     11        4  2020    6    45        4   fall  \n",
+       "3    23     11        4  2020    6    45        4   fall  \n",
+       "4    23     11        4  2020    6    45        4   fall  "
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "7babd7db",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "RangeIndex: 84331855 entries, 0 to 84331854\n",
+      "Data columns (total 17 columns):\n",
+      " #   Column        Dtype              \n",
+      "---  ------        -----              \n",
+      " 0   date          object             \n",
+      " 1   station_uuid  object             \n",
+      " 2   diesel        float64            \n",
+      " 3   e5            float64            \n",
+      " 4   e10           float64            \n",
+      " 5   dieselchange  object             \n",
+      " 6   e5change      object             \n",
+      " 7   e10change     object             \n",
+      " 8   date_time     datetime64[ns, UTC]\n",
+      " 9   hour          int64              \n",
+      " 10  month         int64              \n",
+      " 11  quarter       int64              \n",
+      " 12  year          int64              \n",
+      " 13  day           int64              \n",
+      " 14  week          UInt32             \n",
+      " 15  weekday       int64              \n",
+      " 16  season        object             \n",
+      "dtypes: UInt32(1), datetime64[ns, UTC](1), float64(3), int64(6), object(6)\n",
+      "memory usage: 10.4+ GB\n"
+     ]
+    }
+   ],
+   "source": [
+    "df.info()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "4af40046",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "grouped_by_station = df.groupby('station_uuid').mean()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "2bdd5266",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot:xlabel='station_uuid'>"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAApcAAAEZCAYAAADCPg6kAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjQuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8rg+JYAAAACXBIWXMAAAsTAAALEwEAmpwYAACBAElEQVR4nO3dd1wT5x8H8E/YW0ABFVERDSgIKhYXVcFF3dZVF9q60Tq61A61at3+3NbWjXXi3lpnXYjiQBQXoizZewVI7vdHvDNHEhIgLP2+X6++Kpe7557b33vWCRiGYUAIIYQQQogGaFV2BgghhBBCyMeDgktCCCGEEKIxFFwSQgghhBCNoeCSEEIIIYRoDAWXhBBCCCFEY3QqOwOEqCKRSJCdnQ1dXV0IBILKzg4hhFQLDMOgoKAAxsbG0NKisiRScSi4JFVednY2Xrx4UdnZIISQakkoFMLU1LSys0E+IRRckipPV1cXgPQGqaenV+LlQ0ND4eLioulskVKi41F10LGoWjR9PPLz8/HixQvuHkpIRaHgklR5bFW4np4e9PX1S5VGaZcj5YOOR9VBx6JqKY/jQc2JSEWjRhiEEEIIIURjKLgkhBBCCCEaQ8ElIYQQQgjRGAouCSGEEEKIxlBwSQghhBBCNIaCS0I+Mjl5BUjJyKvsbBBCCPlEUXBJyEfGb/lljP79fGVngxBCyCeKgktCPjLJ6VRqSQghpPJQcEkIIYQQQjSGgktCCCGEEKIxFFwSQsosOT0Xo38/h+iETKXziCUM8kSFFZgrQgghlYGCS0JImd18FIuUDBHO3HqjdJ7Ve+9j8M+nKy5ThBBCKgUFl4RUM8/fpiD4WXxlZ0MhhmGU/nbtQbTG1iMqECMzJ19j6ZVEcduoSUN+Pg3/M0+LnSc2KQtZuQUVkp/y9u+dt3j+NqWys6ERLyJTcfb2m8rOBiGVhoJLQirBvbB4hIYnyU1PSMnBsF/PIDYxS+myP6y7jvlbAlWu4/rDGKW/pWbkQSKRD5KevUlBakYeElJzAACvotMQFa+8qrs4WbkFePMuo1TLqvLTuusY/ttZlfOlZOTh1803NRaIBoa+Q98fTiAyrny2S1auqBABl15yf4vFEmw+EsIbw3Tikkv4bvU1ja+bYRiF54cqy/zvYsfJJ6Va57qDD/HDuuulWlYdR668xIvIVKW/v32XgfiUnFKlffV+NCYsvgiJhMGJ6+H4fu1/2HToEff7mVsRWHfgQanSJqQ6ouCSkAqQkpHHK/H6fWsg5my6KTff1fvRyMotwMSll3jTr92PxrX7qkv+CsUS7t/Ld9/j/s0wDG6GxEIsliAhJQe+v5/H1JVXeMs+eZ2MH9dfh+/v5zF20b9IzxJh5upr8Ft+We3tFAgE3L/nbLyBb1deQURseqkDVGVex6arNd/Rq6/w6GUSLgZFamS9tx+/AwC8jEqT+63P98fx52FpQCF+fxwYhsHRq6+QkpGH1fvuo8/3x0u97uDnCTh9M4IXtADAu+TsUqepjP+ZMPT78QQKCqXbseKfe9gQ8BC5KtrM3ngUiyNXXyn9Pb9AjDO3IooNXHPyCjBn0w3EJil/wWIxDMM754uz49RTfL/2P6W/T115BeP++Ffhb5uPhOCHtf9h56knCkuK1+5/gHfJ2RBLJNhyLFTu9z8Ph+BfNc7BNwkiHLj4HImpuXgakYyCQrHKZQipiii4JKSUxBIGi3cG8UoZ80SFSM8S8eZ7FZWG0b+fV+vhoszKPcFYuSdY5XyHr7xUOP3W43dYuusuDl15iaT0XADgBXwZ2fmYvfEGb5lfN9/i/X3/WQJEBeo/7NhSy2mrrpYoQK0ov/x5E31/KH2wp8iZW2/wIjIV/X86ifvPExAZn4ntJ59g+e57uHwvqmyJv4/HJBqslmcYBhsCHiIsgl8dffrmawDgzu3/HsTgfOBbDCljm9m955/hz8MhuPFIeal6cFgCQsOTsftMmMr09l14jgE/neQFvTGJWfhy1km8S9Jc0H36ZgSeR6bi8JVXGPbrGWw9zg8g2QD3RWRamdaz82Ii/jn7DOMX/4tZG27gy1mn8LacSv8JKU8UXBJSSlfuReL243e8Usbv1l7DyHnnePNFvg/iHiuoBpfFMAzSigSmJZWWoXj552+l1YFJaXl4GiHfru1i0Fu5abJV2m/jMjBvy22uZK46ePA8AceuhQMADl1+KVdFH/IqCeXRfPLJ62Ru/WwJXbaC0q6gJ3F4JtPGMCUjjwuSFB0PWf/bG4xJSy+WOa+FYuB84Fv8ulm+FB2AXOl2WWXmSPdDcSWgiWkfqqZDXiXit79uQaykpPPfO9L9lJXzYf9euhuJgkIJ/nuouKQ/IzsfN0NiS5x3Wcf/C1c4nb3O1HExKBI3H0nzUbSEUnZ7X0WnlTyDhFQyCi4JKaVckXwpXlR88VV5uaJCpe0Qj1x5hZPXX3N/j1lwHkt2BZUoT8pipaPvqyqT0nKx63TxnUQUYYOj2MTiS4MqqrOLOv4596HkKyM7HzNXX63wPBS3OxZuv4MfZdoYjv79PIb8fBp3Qt9h7YGHxaZ7JTgaMTLHQiyWYOG2O8W2KSwJTR9GsViC5Pcl5kWN++Nf7D774Vglpknnu/EoFsv87+Hhi0RkabDz1uKdQVi66y5SMzX/JSuZViEqrT3wAEv97+JO6Dt8OesUXiloakFIdaVT2Rkg5GNw6sZraGmpfrL8seMOHr3kl2AevfoKHdzqIvhZAm96cnoeboW802g+y1tFf3ry0YtE1LIwhK2Vicp5C8WarE5WPY8oX4zp/7sKoGRBx6IdJXuhAID4lBwEPY1D0NM4NK5XA0umeMJAr+S396G/nMbwHk7FzhMRmw77ujV402ITs3BMpjQvNTMPFqYG3N9bj4fi1M0ItGteR2HeD1588WGCzL5l93N8Sg4yc/Kxet99LJjQHsaGuqo3Rskxin/fRrWwsGq8CLHX/YsozbwYEFIVUMklIRrw19HH+PNwiMr5QsOTeX8npOZg+8knWLjtjlrrKdqe8+7TOJwPLL4KVZYmShZjk7KUpsN2eKkov/51C5OKdH4qLwzDcO0mg57G4fSN18XOr06HFFZOnvrDCak6hK+i0xEerV6HJ1b++447OXmF2Ho8tNhgeNqqq3LTJi69hLMyY5z+tJ7f6zsoLP59+tLt3Hv+uVqlkWwv/2X+d7Hn3DO8iEzD/SIvYQDAvI8kGYaBWM2XCLFEgm0nQuWuqfJU3PVXhQr9CSkzCi4JUZNEwmDLscc4/l84Tl5/zVXfKVJQKMaGgIdYf/AhVu+7X2yaAJAjKlTZJhMArz2nRMJgwbY72BDwUO1tUPYAu/9c/oGtSERsOiYuuYSjVxW3OatKBJCPkGSH8SnOzlNP0Of744hLzuaGHZLtlXz78TtsPvq42DRk97WivMj6Q53SymKSuKSgs5CoQIyLQZEKA5pLdyMxdcVlXueg6w8+dLJR1ORDkedvU7D3/DO56XHJ0naTsUlZ+OtoiFweUjLyMOy3s4rHa1WwnUp7l7+PgjccfIj0LBH2X3jO9VYPj0nHrtNPlQZ04xdfxLFr4XKdc9R9KbgXVvKxZsPepGDLsceIkR1q7P32KuuMR0h1RMElIWqKSczCieuvsfV4KP4+9phrx6jI7cfvcD7wLS7cUa9UMTO75G3KYhSMhVnaksmiVfXK5OVLg46wN8l4/jYFfb4/rjAfxXkQno1Bc05xw/VUpM1HVJcuA8DhK9JjO37xRUxZIe3UomjX9vn+uFyv5JJUgbOevVFj8PBiDi2vWvk9/9NPsfbAA7nmFgCwZv8DvI3LREzyh/Nu+T/35OYDgB+KGb7nh3XXse/Cc6W/L9t1D6duRCAxVfoiVnQfKhqv9YKCkniG92/5HfHgRSK2n3yCizJB9u3H73Do8ktuOCVlig5lVNz2yPp9q3zeVR37iNgMnLj+Gn/skK+pYPdRUSWpmSCkqqDgkpByoCzGK/rwYXvNlmY8O0UPMmW9aj/kS3N1b1eDpb1x7z9LKLZUrahz99MgyhdzgWp5UTZs0rM3KUqrQsUSRmUwUlTIK9WBuey4nM/K+BUadYNXtpQ2N69s33N/XoZOQqUZNilfwf5nGIY3hqoiYrHib9ffC4vHywpqzyhR89SRnU/V4QxT58WDkCqGOvQQoqayBmb/3Y+W6/TDDnRems4mirJTtJQjKj4TdjamH5Yp8VpU23v+WYk+QVhRbcsU9cq//fgdbj9+h9o1jRQus2BboMI2fUDJ952yWOjHdddxclW/EqZWcgz3/+rfmE/pOSPzg7LPiy7ZdbfYtFUFrSWx41TxXyf6sKrqf0wIKQ6VXBJSDhSVjCkqVIxOKFmVckndfRpXLukyzIferYoCy8dqlOZp8JnOiU3MUutTj2ybwKKUBZYAihnMmn9g1Qmey/INbXWDc3YMxeIGby9tiHP5nuoPAiQV0ya5pAoKJdw1Ve4vJxUc92kyuCWkqqCSS1KshIQE+Pv749GjRwgNDUVOTg78/f3Rpk0blcvOnj0bR48elZvu5uaGgwcPlkd2y1VJHgJbjst/Aq60in49hSU7cHRFi4zPLPYLKMV9ezu/HIaAEYslGPrrGYjyxTA31cfu+T4aTV9UIFb66UBlwU5x7VhTZAa7f/QiUWFVsJxSxiDBzxIwY/VVCACM7esCF4dapUtIxup9D+DuZFPsPF8vvICGdczKvC5A+gKjsPlBKQKzpCLDZZUltPt+7TWYGeuXeDl+Zy9CPj4UXJJiRUREYMuWLWjQoAEcHR3x4MGDEi1vaGiI33//nTfN0tJSk1msMJU1QPhPG64rnK6sGlCWXJY1tAkVOXyLOlIyRBC9b8OZlqn5vBUWE/wV3aXqxTsflvr1r1vFzFc6Rc9VdmiijYce4c9ZXTSyjvUHH2oknZKS3b+aKh29Vcov9pT0c49s1qlSnHzsKLgkxXJ2dkZgYCAsLCxw8eJFTJkypUTL6+jooF+/8m9f9imqzBIPletWI8L6aKoDS/HSUZJF8gvE0NPVLvE6ytudJ+XT5EIVdt9p8mWP1y6zHE9LrhMbRZfkI0dtLkmxTExMYGFhUaY0xGIxsrLKt21h9aHBJ1cpkqqIzh2pGXlqDfnzkYSW5e7nTYq/+12cjyZwrwzleIlsPynt8PMuufjPqBJS3VHJJSlX2dnZcHd3R25uLszNzdG/f39899130NcveTslUoQaD0G5WnFNPTiLCV4i4zM1tJLqoTS7tCTLlGUoIKKGyo7DK3v9hJQDCi5JubGyssK4cePQtGlTSCQSXLlyBTt37kR4eDi2bt1a4vRCQ0vfSSY4OLjUy7IS0sregYZhNDdweELih57NyrYvJiYawcEfOtdkZPIDP3X3y/Pn/IGlxYXKx0588UJ+QG9FHjx8AD0dzVSePA7ll5SW5HjfCryLuNQCpGQq36aHDx8q/e3t20gE63/odBUVpbotbHh4yb5wFBwcjFcx0vaF6emqP+1Y9Hix8vLy+PumnAuyc3L5bSIzMsr+4vE6IgImTLzGqsVTUvgd5t7EJGLj3qto62iqZAn1qXMeJiQkaiQdQqoSCi5Jufn+++95f/fu3Rs2NjbYtm0bbt68iQ4dOpQoPRcXl1KVeAYHB8Pd3b3YeW48ikFrJxsY6Cu/JN7GZQBnSv7JN1kCgRYAzQSY1lbWwIsIAPiwfXv5gY2tbT24uzfhppuamALxHzq8KFuuKEdHR+DfDw9BbR0doEBxsC1sIgQuqx6KqGXLljDQK+UtqEh+m7u4Asc+tAF0d3dXuU2svy+kIDm9+M9CtmjRAjikuNNHfTs7uLs34tZnZ2cHPCg+AGzUqBFwQ/3hiNzd3SE2jAOuJaNGjRpAbPH5dXR0BC7KBy0GBga8fVNQivFVS8LI0BCQeSkzNTUFEsrW4cre3h7urepJg8t9MaoXUKGmZU3g7Ydz5U28CG/iRRjY4zPUrmksnajmuVSUOteXjY018KL4ZkMtW7aSGyNXHSKRqEwv5YSUFrW5JBXqm2++AQDcvn27knPywYvIVCzzv4c/VbQT1ETtVXk1hSvu++UVTe12nVWkU4OqwFKVopvxTo1vU1fSwANy9v+XXNlZqLKUfs+8EqRnV63RGQhRhYJLUqFq1aoFXV1dtar2Kgr7eTxVw5po4lFTXkFFcQNl89Zfyq148rpqByFVqf/KmVtvyjX9e2GqS88ra9gsVTTZoUxTm6js3KmoPViFTl1CNIaCS1Kh4uLiUFBQUG3HuqxS1HgqFQ0ySvtA9j8Txvu7uBq6KhrXVC20jwghHzEKLolGREZGIjLywyfhRCKRwuGHNm3aBADw9PSssLxVJVWphK28fGpxU2mC6dKU4H0Mp45AE1vxKb69fIKbTKo36tBDVGIDQraH6/HjxxEcHAwzMzOMHDkSADBmzBgAwOXLlwEAiYmJGDBgAHr37o1GjRpxvcVv376Nnj174rPPPqvw7YhPyYGxoS5MDHX5P1TiU1sgKP2zkv3qSpVTCU0uyztoLy6vpQkU41MUf9u8tHkoqqqOc1kR46yWVEpG2drcllVqOXxRipDKRsElUWnt2rW8vw8fPgwAsLW15YLLoszMzNC5c2fcvHkTR48ehUQiQcOGDTF79mz4+vqWe54VGffHv7A008eueUW+O131nndqCXujfm9jluba4ikPXiojgKjUwqxSrPv6w7L3ciaaofCb5RWIzgXyMaLgkqikbMw8WWyJJcvMzAwrVqworyyVWkpG5ZYSVM3ypJLLzMmv7CxUGaUaRL2avtBUBenZdO4RUtVRm0tCPpaITw0U1JTOJ3SKlCtNnH9bj0vHbSzvU7mq9rgnpDqg4JIQddGzRi3qPpNL+/COiJVva1q0iWFFBgYVtaqqNO5iabHDfhFCPm4UXBLyHhVUVA/TVl1VOU90guqBzDWn5CdOaYLffRdUN08pS/oV4bWCFwOiWtU8moQoR8ElIeoqh7rR8u7VWxkxRlUIbMQaLuWLilf+TezSDUVUcrGJFRkwE0JI6VFwST5JeaJC9Pn+OP578OGbvyrjvHKImSq6LV9FBH6VH1pqfr/+uP660t9Ks0sj45QHq+Tj8TIqtbKzQEiloOCSfJISUqXjDO7/90NVY4UUuJVjSaU6gWNVCPwqRAVG7XEp2YhLzq64Faqhqo5z+am5F5ZQ2VkgpFLQUETkk/QhDhN8NF/NCXmpery+52/5JSlTV1xGS0fr8srSJ+HsrTc4W87fEycKlPPboCaS/xg6YRFSGhRckk8Se8tXJ7BMyxQhL7/q93L99a9bJV7mbVwm3mq6irYKPE8/kvcFnrx8cZnTqOjmsKmZlfv1m8pWFdofE1IZqFqcfPTScwpRUCjhTWNv+lpqRJejfz+H8YsvaiQvRVen6Y4nVYG6D9TyfO5+bNXCD55Xz+rV9KzyG/D8m0UXyi1tTZEwDLI08MEBClJJdUMll+SjlicqxOpjcQiJecibnvN+vL037zJw+maE0uULxRJoMv4TaaD0qSQq5VOMFb5GQCz+uB++c/++XaL5lQUjH0vMLRZLKv1rW+qQSBj4/n6+srNBSIWjkkvyURMVSIO5S3ejeNN/3/rhYX0r5B337zxRIU7fjMDle9L5Jy29VAG5/Li8iKz4HrIHL73g/X3y+usKzwOpOP1/OlnZWVCLhIFcrQkhnwIquSSfpFyRfAkiAwZ/HgnhAku3JrUQn5LD/V7VegSr45+zz5BfULEPt4BLL9Wa786TOHi3tlP4G8MwyMwpgJmxnlppnQ98y/v77O03ai33sXr8SnHnrtTMql/a9zGhDj3kU0Ull+STs+nQI4XTQ8OTcS8snvu7aFXroh1B5Zqv8nLw4gvVM1WCTYcf4cwt+SYJ+QVizFxzDSPmnuUF90R9e5V8zSc7twB9vj9ewbn5dF0Meqt6JkI+QlRyST5qKRnyvVWLK9XKyC6/DgiET5Qvxp+HQ9CzvT0Wbb+DuORsvI3LhJd7PYRHSz8T+C4pCzaWRngcnoTs3AK0dalTybkmn5KcvALoaJe+DCabvqVOPlEUXJKPmjrfoVbmVXSaxvJBlItLzsadJ3Hc31eCP3w16be/buO74a3wv733AQBj+7pUeP7Ip8lv+WUAQIPappWcE0KqH6oWJ0SJJbvuVnYWPgmqhnliA0sA2HYitLyzQwiPxseBJeQTQMElIYQQUoVJqMM5qWYouCSEEEKqsMoYr5aQsqDgkhBCCKnKKLYk1QwFl4QQQkgVRrElqW4ouCSEEEKqMPq2OKluKLgkhBBCqjCKLUl1Q8ElIYQQUoXl5BVUdhYIKREKLgkhVZK+njb379ZNbVC3ljH3d7+ODpWRJUIqhbGhbmVngZASoeCSEA0xNdIr9vd2zenThcr2UY+2Dbh/+w1yAwDMH9cWADDQqzHmjWuLv+Z0hZWFIQCgz+eNyjmnfH4DXSt0fdXdmF7NcGRZn3JJe6BXY4XTD/zRs1zWVxXUrmmseiZCqhAKLgmRYWxQ+i+i7l34BfdvOxsT7t9Hl/fB8RV9YW6qX6a8lUULoZXG0tons50l5dW6nsLpI3ycuH93/aw+ds3rAReHWji5qh/G9HbmfhOUYp2jezUrxVJ8zRvXKnMaH7vO7vxjq6ujBReHmhpfzwgfJ/w85jO56UYG1at0738zOlZ2FggpNxRcEvKejrYA+//oBa33Eczm2V3Qxrk2AGmp48xhreSWmeXbGoB8idyq6Z3w06jWOLa8D3S0taClJajQ8UT2LPgCP4505/4uTVCmyPShLWGiooS2NAQQoMtndgAALS0BLM0Mip2/JL1nFZV0TRzQnPv3vPclpLIc61vAuZHmA6PKoKdT+tv8yVX91J5XV/vDegSaOuEUrUdHG+2a1y2/FWhA18/qK/3NyEAHnVrWQxM7C7R3pdoM8nGi4JIQAAZ62lg29XPeNGsLQzSzlwYYNpZGXNApq7kDW6LFD3YM9XXweQtbaMs8cMUS9QOiL9o3VHteZWTjL3XWvOXnrirn6eqh/KEJAJNVVB8LIIC9jeIS3G8Ht8C+hV9AW9GOfs/GUlo9qKujBVsrE6Xz8dapINLp2d6e+7ds207WyukdsXSKJ6+dpypGCkq9rS2N1F6+vDSyraFynvH9XBCwuFeZ1qNoPxf3DtDEzlytdE2UtDec0L95iY5PRRrSVahw+slV/XDgj174QebFj5CPEQWXhAD4fUI7COtbACgaiH34S0tB0KPogaqMrZX6D0LjYqr46qj5QK1dU/3A5sAfPTXWrkvVdo7yqoWjy/vg5Kp+6N1BGuQZ6GlDW1tLZano7NGfYZZva9SsYYhV08u/WpE9+uoc539+95GbZqggcJVV1uYK3w2XL00vSp289+3oAAP90jcJUbBWlXP8b0YnhdNtrYzxWTMb7m9F1x0gbXe7eXYXjPRx4l5qvNwVN7soTtOGliVeBlD8UsIyNdbD5tldYF/XrNg0BBqrUyCkaqHgkhAou8kLuJIXgUCgpGRG/dLIfp0aqxUQDe/uyAW6LDsbU+7fS6d4Yu7YNirTcWyg/kPTUEOBhTq7Q0tLAJ33Jbrj+jfH3oVfqB3YmBnrwdPNFoC0B+3JVf1gU8LSQR3tkj/QFS1Rv7Yp729dHe0S56WsGtQuPnhRx5T3HagAaZBfnNZNbZT+Jnt5lKVa3MRID191c+T+Li6IEwgEGNrNkSuJnvFVK6z7vnPpV14COgqC3h9GuGPfwi9gYqgLWysTGOipOK8ptiQfKQouCYHqh6EAgFYZG5Jpawm4oLFTS+UlLMN6OPF6lq+e0QnLpnpyf1uaGeCzZrXLlBdlVPV4V6WGSfHLM0XKhbW1BGVeZ3FaOVnLTWvvWlf94KeYYLmetXy1fGkC15KSbb6gzsuNspI/Vvc2H3rq7y2ms1admsYK26dqmmxu1a06Z8m+uFQGLYGAV/o+ulczmBkrP78ptiQfKwouCVGiaACiq6BjREmqxVknV/UrUZurxnbmpQ7AVk3viPU/eJVgibL1OhLIlPZWBewLgWynnpJURXLBsIJFFKVjUaQjUml2xW8ypdKKSpQ1PSyN7Cks+wI18gunIjNqdLUVbtsv3bh/OzeqyTUpKM/OR86NaqrVlpllYkCPZPJxoDOZEID34FTWEca9qQ3cFZSElZaiYLW0inYmYR+YwvoWaFjHrFRRzjd9nFXPVIyBXo0rbXxItrMPux/KOi6mAIJiS6BYmgisbSzUr1pXZ3WlDZ7MTfiBckmSYddZmm9iF31h09TLirWlERwbSGsOGtczh5W5odJ5HerVwMxhLYtNz7lROQxPVc0DeEJYFFwSAsX3dAE+PBwFAmkV7vzx7XjzlObhydLkoM8H/ii+p29dNTsTyW5O/07Kv4JjaaZ6zM5ubRrwqlyBiuvAsHSKtBlBv8+l21CzBj+QKE2J87rvO2OJXweZREq2vFuTWmhUt0jPbQWnT3FnlOx4oIB655+qfa7uvlDZdIQ3Q/EzN6xT9raipeH6frxSU6MPHeYUbf9s38/g3Vr5yAirZ3bCj6PK3uO7rE1tCKmqKLgkBKULNspKV6f4zhPqGtylicp5xvZ1wfzxH9rLFe1Vy24/o2BaHQXVsI3rWchNU6hoKVQFDfZpbqqPk6v6wa2MvbFlY7eaNQzh4lD60io9Xe1iO6d8WKfyfVT0LFXn3aa0nYzkLwkVQarMv7u9H7JKWf6Wf/u54h8qUFnOxIZ1zFR31lGDzvvaiw6u0nE7KdQkHwsKLglRRo2AU9NBaWmS8+0p/wWaosno6WrD3elDT9/vhispdXkfDSyYIC2hXTixHa8zkTp4AWqJlqwa+spUoX8Yiog/j1uTWmptm6rgr6TBdkkDIiMDHUz8srnqGdWg7rnZu4O9ym9ha2p0glIToEzRZWnOa0N95S8WqoYsIqS6oeCSECh+cEqrxdnfq2OYVHpN3vdqbyG0luukAgCWNRR/Qaem+YfpApRvZwluPRpex/j+xQdju+f7YO5Y1b2mZateAXAD8qsi+5nQottWNFhVVMq52K8Dpg1pAQBo37yuRkrYgIr7vnVZj2dNJedmea2vBGuqqBURUukouCQEpW8LqKcrvYTKa2igqmpsX8WdfZwaWGJcPxdYmOqjlrlh9Q/KFQRv5qb60NPVVmPb+L+r277OwtQAK6apV23coI4ZjA10eJ1PmstU3ZelGQKb25bvmxb06mCvfGZFC+JD8DtzWCt8r2DA951zu2N4D347Urn9WsJ2zUYGump9trK4fVPR5+2HnFTz64WQ9yq5boKQKkJRyaUa93kDPR1s/7U7r7RJUxZNbI+4lJxSLVvasf7UfYwXVxrm0aw2/Od/+FrNLN/WCHuTghP/vS6XDj0l3Vb2uA7v4YTPmtkgV1SoxjKaybe6ySj75GFRBno62P++M1dyeh6ycwvUWq6bR338GxQpN53f5pb/m+oOPQoSea9OTWM0tbeEvp42r3NVzRqGCr99XpaOcoqw7ZLbutRBwKWXaO1kg+w86b5SdE6qe7Qb1a2B17HpAIBWjtZo3Ux+kPniNoXdZzWM9aCjrYVuLWvgyK0UNddOSNVFJZfkoyY7GHlxlJUqsaUbxT1YrSwMNTqsEMtNaIUebRuonrGIdd93LvWn/LhmACVcrnubBvhrTheFv3m62XLDvpRHhx51qqgB+U8lDuvuiMb1zLm/bSyN5NqXFpdbRftINihS2NRCwcSve5dgyKdiIpXBXYQYUyQtRYGTsYEO/GS+yqNMwzqKv0neUmilcrB8VtHctmteV+7rU+w81hbSc0T2s6UCAaCvgWp9p/dfqxLWt8DJVf3gUM9cI0McrZX5GtDvE9qVuC2p4/t90aCOGY4u7wPXhpX/LXpCNIFKLslHTVWp1ubZXXAlOEphg3qBQFDWMcVV+m54K/xv732NpmlfdLgbJYZ3d0RKpoj3+T+oEUwr4tHMBnVryX+x5oPyq+5T91vrqtQyN1TaLlJR7od0FeK/hzEqUi3+BGIY4Euvxjgf+AaxSdkf1qf0ZadkFAXz/Ts3Vqu0t7GSr+MsmNhems6PJyCWqJcjdc6nz1vYomlDS7gJrfD2XQY3ff74trj+MAY62lq4/zxBrfUBQK0aBkhKz1O+fq49tcwy5oZISsvl/nZ3skbwMwXrLMEFUtysPu0awrWJFTcuKyEfCyq5JB812ZKkZvby39q2tTLBSJ+mvIe50kCzHHi523E9s1X5YYQ7fldzXnUM6+FUJLAEhnWXtn/T19XMMEnVXXGlWw3qmGHTT968aW2ci297W/Q06txK8WdAy1otXHQ9nm511VqOLcH37dn0Q17YNIuE2EU7+Ci6RtixUm0VfCqTS19mW9u41JFrclG7pjEGdxFiQOfGWPg+sC2pVk7y1dXG7ztc8V5OihTd//K1B/753QdlUXy1uEAusPzfjI5lWh8hVQGVXJJPwk8jW+OzZja48SgWu848RVqmSOm8iyZ1QFR8JoByL7gEwA8EigthOykJRFjLp36O2KSsMuVlQOfGGNC5seoZPxUq2gnY2Zjy/h7QuTE+a1YbfssvK2yzWDRAc21ixf2mSGnGtVRklu9nqHs2DAcvvuDSrFvLmFdaCki/za20M4yK9yu2Ols2kPR0s4XnKtvSZbqMZHeVtoLvqzeuZ45549rCtXEtnA98y/uNPU66OtqoYfLhRUsgKP0xUPf9tImdmmPIElKFUXBJPhkG+jro6lEf/meeFjufmbEenBtJq0dL2waxJGQDjrIEs03tLdFUQelsRVBVssu2LXNrbAXkqapKrnqK64g0y7c1LN8P1yQQCJR+B95QX0fB0ELFH3FdXW0g70OHo5IOs1PcupZN/RwXr99TY0H10vdoVhvC+hZo2rBk52BljijQuim/RPPboS3hf+YpLJR8gYobHpNhQD27CVGOgktSrISEBPj7++PRo0cIDQ1FTk4O/P390aZNG7WWDw8Px+LFi3H//n3o6urCy8sLs2bNgqVl5QRBQCkDOHqOFEtVkNTU3hIH/ugJIwNdBAdXTnCpLIvGBu+rRxWM4zh1SAvsOPlEabABSEvneOuROcPYdfq0a4hubRrguso2mlJ1a5mge5sG6Pt5I4gKxKhnbYLHr5LgIVPtXnQcTbW9P5fNTfVhb6N+sFr0EmBjwo4tbfHfgxiYmeijbinaDmq6Z/iHdNWfd/rQFnCoZw77ujXQytFa+Yzviy4r5jtThFRfFFySYkVERGDLli1o0KABHB0d8eDBA7WXjYuLw4gRI2BmZoaZM2ciJycH27dvx4sXL3Dw4EHo6pby4VgC1eEh4KCk48THxsigfI93PWsTRCeo0SygSJTUyLYGfvumDVybyH/a0d3JhvdlI3WwnWVsLI2Q877UsY+nPbS1BEqrRqWlnR+qqLW0BPj2/UDorDYuH0Y+CFjcCwIFVb1FyQZY9WtL2xLXszZVMrdieu/b32opWd/QrkJMH9qSm0+TyhZ3qr9wVw/VozI0bWgJc1N93H78rkSlrQb6OrC2NMIYBV/SUmXDj17IyVU9VBYhVQ0Fl6RYzs7OCAwMhIWFBS5evIgpU6aovezmzZshEomwe/du2NhIH9Curq74+uuvcfz4cQwaNKi8si2vtCWP5VSqIsvEUBcBi3th8M+ny31d5aWyB0s/sqw3BAIBBvx0slTLe6joiFMSpkZ6mDP6Mzg3qok5m27wfqthrLgE9OcxHthyPFRumB5lVA81JX88OrW0RX0bUzSyVW80Ada3Q1rg1M3XvMHZeWsSCDQeWGrifOrZwR7/nH0GAzW+564K2w61oFCM1EyRwjacymhrCbDtl26lWm+D2vRZSFI9UW9xUiwTExNYWJSugfmFCxfg7e3NBZYA0L59ezRs2BBnz57VVBbLlbKesqRq0dXRLvXA8eWhvWtd1DCRDyT9Brlh0oDmsLGUdn5h310szAzw06jWXO/qspN/KRIIBCUOLAFp9flIn6ZyJZeafu/S9AtKp5bSDnBmCo5DaenqaMPagsaiJESVqnM3Jh+V+Ph4JCcnw8XFRe43V1dXhIWFVUxGNPQArO5fMSxvTeqbV3YW1FeJbSWMDXXRy7MRV5pG5xXg9r7HfNHONYSQ6ouqxUm5SEiQDjxsZWUl95uVlRWSk5MhFouhra1+lVVoaGiJ85GamgoAiIh4DSNxHACgoODDJ/KCg4OLXT72/afdYmNjERycLfd70eUb1dZHXr5EZbpF5RdK1M6TqjyUxzIuDQwR+jZX4XLzh9fD6xdPynX9JaUo/TdvpMcvOSWl3NfPys2VDuL95OlTJMZ8aHPa38MYIRECREeEIeaN5iPMN2/fb2tyssptLe2+yBO937YnT5AQXbb2tPOH10Ne6hsEB78BAEQn5QMAsrOzS5+/Auk11cxWp0KOt6bWIZtORZ2nhGgaBZekXIhE0nEk9fTkh2XR15dWU+Xl5cHYWP2vq7i4uHDLquvf0LtAVC4aNWoE9/e9enVPJAKQ5s/d3b3Y5fN0Y3Et9C7auTvB3fX9QNR7o7nfiy6vIjnl6xEVAgdjIVAjT5z3+VB7/tIuA6BlSwYShuFXPZcyreDg4BIvo7Zi8pSBKOB2KmpaWpbf+oswuHgJyMiCi7Oz3JiYXTuV33pTxZFAYCpq1qwJd/dWSucry7EwfL9tzgq2raxMI1OBCwkwNjYu07E60loCHW1B+bYJLuV1oAh3PDSUpkgkKtVLOSFlRcElKRdsEJifny/3Gxt4GhiUfsy+itLBtS42/ujF9bT9VGlpCaBVzdudVkDfLFLF6OpQyy9CKgMFl6RcWFtLx4pLTEyU+y0xMRE1a9YsUZV4aWliRLqqGlh286gPFyU9eEkxqneM/Ekor7EvCSEVg4JLUi5sbGxgaWmpsEomJCQETZs2VbBU+fkYe3tPG9qyUte/ekYnmBkr/hoNkaIYqWyowxMh1RPVGRCNiIyMRGRkJG9a9+7dcfnyZcTHx3PTbt++jTdv3sDHx6eis8jRorNeIxrbmcPakoZlIYQQwkcll0SlTZs2AZB+yhEAjh8/juDgYJiZmWHkyJEAgDFjxgAALl++zC03adIknDt3Dr6+vhg5ciRycnKwbds2ODk5oV+/fhWSd0UlRwsmtsfUFVcqZP2EVIaKKPGbNqQldp15itoKPptJCPm0UXBJVFq7di3v78OHDwMAbG1tueBSkTp16uCff/7B0qVLsWrVKujq6qJz586YM2eOwl7k5UrmYVulv3pB9YBlsuknbySl5VZ2NipdRVTHN7W3xNIpnuW/IkJItUPBJVHp+fPnKueRLbGU1aRJE2zbtk3TWSJEITsbU40Pi1M21OiSEPLpodZnhJBPROUFehVdIE0F4ISQykTBJSHkk0JxFyGElC8KLskngQIK8ilhe/E3rFOF2xcTQj5a1OaSkFL6eYxHZWeBEIWaO9TC6hmd0Mi2RmVnhRDyCaLgknzUyvNLH+2a1ym3tMnHoTIHUW9sZ155KyeEfNKoWpx8EqiDA6lMAjoBCSGfEAouyUetiZ0FAMDKvHp8SYZCkI8TfSubEPIpoWpx8lEb5N0EJoIUqiIklVJFTQWWhJBPEZVcko+alpYANua6lZ0NUoVUZBU1FViWDu02Qqo3Ci4JIaScUZvL0hFQQxFCqiWqFiefpKmD3WBfl4ZpIYQQQjSNgkvySerRtmFlZ4EQQgj5KFG1OCGElBNqO0gI+RRRcElIFUJN8z5OdFgJIZ8SCi4JIZ8E6rlNCCEVg4JLQqoQCoAIIYRUdxRcElIVUL0pIYSQjwQFl4QQUl6oJLpMGNqBhFRLFFwSQkh5o5LpEqHdRUj1RsElIYQQQgjRGAouCalCaCii8kP7lhBCKgYFl4SQT0Jl9MSnNoOEkE8RBZeEEFLOBNSKsEQoJCekeqPgkhBCSJVEQTkh1RMFl4QQQgghRGMouCSEEEIIIRpDwSUhhJST74e7o5WTNawtDCs7K4QQUmF0KjsDhBDysXJqaInfx7er7GwQQkiFopJLQqoU6sBQfqgPMiGEVAQKLgkhnxQaTJ0QQsoXBZeEEEIIIURjKLgkhBBCCCEaQ8ElIYQQQgjRGAouCSGEEEKIxlBwSQghhBBCNIaCS0KqEOrJXH4YGomIEEIqBAWXhJBPioDGEq366EWAkGqNgktCCCFVE70HEFItUXBJCCGEEEI0hoJLQgghhBCiMRRcEkIIIYQQjaHgkhBCCCGEaAwFl4RUIdR/gRBCSHVHwSUh5JNAo9sQQkjF0KnsDJCqLT8/H2vXrsXx48eRkZEBJycnzJw5E+3atSt2ufXr12PDhg1y02vVqoWbN2+WV3YJUYkGqieEkPJFwSUp1uzZs3HhwgX4+vqiQYMGOHr0KMaPH4/du3ejZcuWKpdfsGABDAwMuL9l/00IIYSQjw8Fl0SpkJAQnD59GnPmzMGYMWMAAP3790fv3r2xcuVK7NmzR2UaX3zxBczMzMo5px8PqrolhBBS3VGbS6LUuXPnoKuri8GDB3PT9PX1MWjQIAQHByMhIUFlGgzDICsrCwx92LlYAqqrJUQe3TYIqZYouCRKhYWFwd7eHsbGxrzprq6uYBgGYWFhKtPo3Lkz3N3d4e7ujjlz5iAtLa2cckuIeug9pxqgdy1CqjWqFidKJSYmwsbGRm66lZUVABRbcmlmZoZRo0bBzc0Nurq6CAwMxIEDB/D06VMEBARAT0+vxPkJDQ0t8TKs4ODgUi9bEWkWFEojHoaRlEtei6qIdVS19b99mw0ASEpOqvTtr0qq4r6IShIBALKys6tk/hTRVD5l06ku205IURRcEqXy8vKgq6srN11fXx8AIBKJlC47evRo3t8+Pj5o0qQJFixYgGPHjmHIkCElzo+Liwu37pIIDg6Gu7t7iZdTam80AGg0TVGBGDgYAy2BlmbzWlQ55L2kNH481JRc+Ba4k4paNWvB3V11Z7RPQWUdC1WM36QAFxJhYmxcJfPHo8FrijseGkpTJBKV6aWckNKianGilIGBAQoKCuSms0FlSQO9YcOGwdDQELdv39ZI/ggpDWreWo3QsSKkWqLgkihlZWWlsOo7MTERAGBtbV2i9LS0tGBjY4P09HSN5I8QQgghVQ8Fl0QpJycnREREIDs7mzf90aNH3O8lUVBQgHfv3sHCwkJjeSSEEEJI1ULBJVHKx8cHBQUFCAgI4Kbl5+fjyJEjaNWqFdfZJzY2FuHh4bxlU1JS5NLbtm0bRCIRPv/88/LNOCGEVJD/zeiIX772qOxsEFKlUIceopSbmxt8fHywcuVKJCYmon79+jh69ChiY2OxZMkSbr5Zs2YhKCgIz58/56Z5eXmhZ8+eEAqF0NPTw507d3D+/Hm4u7ujd+/elbE5hBCicU3sLNDErrJzQUjVQsElKdby5cuxZs0aHD9+HOnp6XB0dMTff/+tshdjnz59cP/+fZw7dw4FBQWwtbWFn58fJk6cCB0dOu2KokHmCSGEfCzoKU+Kpa+vj1mzZmHWrFlK59m9e7fctEWLFpVntj5e1JW53FD8TgghFYPaXBJCCCGEEI2h4JIQQgghhGgMBZeEEEIIIURjKLgkhBBCCCEaQ8ElIYQQQgjRGAouCakKqCczIYSQjwQFl4RUITQSUXmiCL66oGGjCKneKLgkhHxSBBTBVxt0pAipnii4JIQQQgghGkPBJSGEEEII0RgKLgkhhBBCiMZQcEkIIYQQQjSGgktCqgDqHEsIIeRjQcElIVUI9Y4tPzS8DSGEVAwKLgkhnxQaiYgQQsoXBZeEEEIIIURjKLgkhBBCCCEaQ8ElIYQQQgjRGAouCalCqM8JIYSQ6o6CS0KqAOpjUnGo13j1QYeKkOqJgktCqgB6iBJCCPlYUHBJSBVCJZjlj4Yiqj7oUBFSPVFwSQghhBBCNIaCS0IIIYQQojEUXBJCCCGEEI2h4JIQQgghhGgMBZeEEEIIIURjKLgkpApgaPDFckd7mBBCKgYFl4RUITRMDiGEkOqOgktCCCGEEKIxFFwSQgghhBCNoeCSEEIIIYRoDAWXhBBCCCFEYyi4JIQQQgghGkPBJSHk00DDPVUbDA0cRUi1RsElIVUKjUVU3gQ03lO1QceKkOqJgktCCCGEEKIxFFwSQgghhBCNoeCSEEIIIYRoDAWXhBBCCCFEYyi4JIQQQgghGkPBJSFVAI2SU/5oFxNCSMWg4JKQKoRGXil/tIsJIaR8UXBJCCGEEEI0hoJLUqz8/HysWLECnp6ecHV1xZAhQ3D79m21lo2Pj8f06dPRunVrtGrVCn5+foiKiirnHBNCCCGkMlFwSYo1e/Zs7Nq1C3379sUvv/wCLS0tjB8/Hg8ePCh2uezsbPj6+iI4OBiTJk3CtGnT8PTpU/j6+iI9Pb2Cck8IIYSQiqZT2RkgVVdISAhOnz6NOXPmYMyYMQCA/v37o3fv3li5ciX27NmjdNm9e/fi7du3OHLkCJo1awYA+Pzzz9GnTx/s3LkT06dPr4hNIIQQQkgFo5JLotS5c+egq6uLwYMHc9P09fUxaNAgBAcHIyEhQemy58+fR4sWLbjAEgAcHBzQrl07nD17tlzzTQghhJDKQ8ElUSosLAz29vYwNjbmTXd1dQXDMAgLC1O4nEQiwfPnz+Hi4iL3W/PmzfHmzRvk5uaWS54JIYQQUrmoWpwolZiYCBsbG7npVlZWAKC05DItLQ35+fncfEWXZRgGiYmJqF+/fonyExoaWqL5ZQUHB5d62aJ6tKoBXR2BRtOUSBjUNNWBt5uZRtMtarCnJeLTCsp1HeqojPWba0ngaGuAZrVFlb79VUlV3BdiCQPn+obo7KxbJfNXnoKDg9HOyQT2Nvqf3LaTjwcFl0SpvLw86Orqyk3X19cHAIhEIoXLsdP19PSULpuXl1fi/Li4uHDLl0RwcDDc3d1LvJwyGkyKZ+dn5ZOurPLKe0lo+niURPu2lbLaKqsyj4UqHhVwPVQ17PHQ1CERiURleiknpLSoWpwoZWBggIKCArnpbPCoLNBjp+fn5ytd1sDAQFPZJIQQQkgVQsElUcrKykph1XdiYiIAwNraWuFy5ubm0NPT4+YruqxAIFBYZU4IIYSQ6o+CS6KUk5MTIiIikJ2dzZv+6NEj7ndFtLS0IBQKFVbHhISEoEGDBjA0NNR8hgkhhBBS6Si4JEr5+PigoKAAAQEB3LT8/HwcOXIErVq14jr7xMbGIjw8nLdsjx498PDhQzx9+pSb9vr1awQGBsLHx6diNoAQQgghFY469BCl3Nzc4OPjg5UrV3K9u48ePYrY2FgsWbKEm2/WrFkICgrC8+fPuWnDhw9HQEAAJkyYgK+//hra2trYuXMnrKysuAHZCSGEEPLxoeCSFGv58uVYs2YNjh8/jvT0dDg6OuLvv/9W2cPUxMQEu3fvxuLFi7Fp0yZIJBK0adMGv/zyCywsLCoo94QQQgipaBRckmLp6+tj1qxZmDVrltJ5du/erXB67dq1sW7duvLKGiGEEEKqIAouSZXHMAwAxUMbqUvZmJykctDxqDroWFQtmjwe7D2TvYcSUlEEDJ11pIrLzMzEixcvKjsbhBBSLQmFQpiamlZ2NsgnhIJLUuVJJBJkZ2dDV1cXAoGgsrNDCCHVAsMwKCgogLGxMbS0aHAYUnEouCSEEEIIIRpDrzKEEEIIIURjKLgkhBBCCCEaQ8ElIYQQQgjRGAouCSGEEEKIxlBwSQghhBBCNIaCS0IIIYQQojEUXBJCCCGEEI2h4JIQUqzo6Gg4OjriyJEjcr8dOXIEPXr0gLOzM7y9vSshd+p59OgRhgwZAjc3Nzg6OiI6Opr3e1ZWFubMmYP27dvD0dER69evV5rWnTt34OjoiDt37qhc75EjRxSuTxFvb2/Mnj1b9caUgKI0CwoKsHTpUnTs2BGOjo5K18nmPSwsTKN5UmTUqFHo169fua+nMpXkHCuJ4q5PVdavXw9HR0eN5EPW1atX0adPH7i4uChNn72OLl68qLH1lkeapHTUGkQ9Pz8fa9euxfHjx5GRkQEnJyfMnDkT7dq14813//59rFixAk+fPoWJiQm++OILfP/99zA0NCxVeiVJEwBCQkKwYcMGPHjwAIWFhbCzs8OYMWPw5ZdfAgBSU1Nx+PBhXL58Ga9fv0ZhYSEcHBwwZswYfPHFF7y0Xr9+jf379yMkJARPnz6FSCTCpUuXUK9ePYX7KCAgANu3b0d0dDTq1q0LX19fjBgxQtWu5YSHh2Px4sW4f/8+dHV14eXlhVmzZsHS0pI3n0QiwbZt27Bv3z4kJiaiYcOGmDx5Mnr27Mmbb9KkSbhy5Qq0tbWhra2NOnXqoFOnTpg8eTIvzfXr12PDhg1K82VnZ4eYmBjUqVMHly9fVrkdWVlZ6NGjB5KSkrBx40Z07doVgPQG2KVLF4XL1KtXD5cuXeJNO3PmDHbs2IHXr19DR0cH2dnZKCgo4KUZHh6Ow4cP4+bNm4iMjISxsTFMTU3x+vVrODk54fjx47w0le1jY2Nj7NixA8ePH0dsbCzMzc3RunVrTJ06Ffb29tzy+fn5+O2333DmzBnk5+dDS0sL9erVwzfffIOhQ4dyX8AYNWoUgoKC5Lazbt262L59O+zt7ZGdnY1t27bh4cOHCAoKQkFBAQAoTXPjxo3YvXs30tLSwDAMbGxscP78ed518PjxY2zevBlPnz5FcnIyTE1N4eTkhClTpqBVq1a8vPTr1w/Pnj2DqakpMjMz4eHhgd27dwOA0oeBlpYWJBIJdx28evUKffr0QefOndG9e3eYmpoiNTWVdx0MHjwYb9++xb///ou8vDy4urpizpw5aNq0qVz6ly5dwrp16/DixQsIBAIwDAM7OzuMHDkSo0aN4r7OlJGRAT8/P9y9e1dhPkNCQqCvrw8AuHjxIn7++Wekp6cDALS1tWFlZYVRo0Zh9OjR0NXVBQCsXLkS27dvR+3atZGUlAQtLS00adIEU6dORadOnQAA7969w6FDh3D69GlERETA2NgYzs7O8PPz4+5doaGhWLduHR4+fIjs7GwAQGFhIQDg6dOn6N+/P168eIE5c+Zg4MCB2LhxI86dO4eEhASIxWIA0k/1TZ48Ga6urkqvGUXmz5+Ptm3bYu3atQgMDERGRgaXpiwjIyPk5OTAxMQEeXl5qFu3LmbOnIkuXbrwrgM9PT1kZGTwrjlZ169fx59//on79++DYRg0aNAAv/zyCzw9PbntLE7t2rWRlpYGGxsb5Ofnw8TEBKdOneLNI3vNisViGBoaIi0tTen2Dxs2jPt79uzZOHr0qNL19+/fH8eOHUOXLl2wZs0abNy4ESdPnkRCQgLq1KmDRo0aITIykndPaNu2Lc6fP4/nz58jLS0NBgYGyMjIUJj+zJkz8d9//3HPGkNDQyQnJ2Pq1KmwtbWFo6MjnJycFG7Hvn37ULt2beTl5SEvLw+Ojo6YNm0aPD095eaPjIxEt27dULt2baSmpsLIyAjOzs6YN28e6tevr3T7AeDXX39FQEAA6taty7tnTJgwAffu3cOJEycQExMDc3Nz1K5dG3Xr1sXz58/x5s0b3j1D1vLly7Ft2za56SYmJnB2dkZ4eDjS09NRo0YNJCUlYcGCBRg6dGix+Sxq/Pjx+O+//+Dr64tffvmFm37nzh34+voqPWdlnThxAocOHeLyY21tjTZt2nDHp6iEhASsXbsW165dQ3p6OmxsbNClSxfMmTOnRHlXV3nk78aNGzhz5gweP36MV69eKX2uh4SE4OjRo7hz5w53/rds2RIzZsxAgwYN1Mq/jjozzZ49GxcuXICvry8aNGiAo0ePYvz48di9ezdatmwJAAgLC8OYMWPQuHFjzJ49G3FxcdxDZvPmzSVOr6RpXrt2DVOmTIGHhwemT58OHR0dvHnzBu/evePmefjwIdasWYOOHTti8uTJ0NHRwfnz5zFjxgy8fv0aU6ZM4c27e/duODg4wMHBAU+fPlW6f/bv34958+bBx8cHX3/9Ne7du4cFCxZAJBLhm2++Ubl/4+LiMGLECJiZmWHmzJnIycnB9u3b8eLFCxw8eJB7AALA6tWr8ffff2Po0KFwcXHBpUuXMHPmTGhpacHHxwcAkJiYiOvXr0NHRweWlpaYNm0aIiIicPDgQVy/fh3Hjh2DgYEBAKBbt24Kb0Dz5s1Dbm4uLC0tuYejOjZu3IicnBylv/ft2xeenp7IzMzE8uXLwTAMlxfWnj17sGDBAnTu3Blffvklzpw5wwUSYWFh3E3j0KFDOHToELp3747hw4cjLi4Of/75JwBwD3Z19rGtrS2uXLmCIUOGoFmzZoiLi8OePXu4C7FmzZoAgMmTJ+PGjRuwsLCAt7c3QkNDERUVhfnz5yM+Ph4zZszg1mdgYID8/Hy0adMGtra2SE9PR2BgIL766iucOXMGubm52LhxI/T19bnA0sXFBWlpaXJphoWFYf369RAIBGjQoAHevXuHhIQEzJw5k3cdREVFQSwWY/DgwbCyskJmZiZOnjyJkSNHYsuWLejQoQMAaakC++A3MjKCtra23HHy9PRE3759ce/ePQQEBIBhGNSqVQsJCQncPHfv3oVEIsGvv/4KW1tbuevg7t27WLFiBfT09DBx4kRYWFhg7969GDVqFI4cOcI779jr19zcHAzDoFGjRggPD4e2tjb++OMPZGRkYOrUqZBIJJgwYQKePHkCAGjevDlCQ0PBMAzc3d0xdOhQ7nph02QDcHt7e7x58wZGRkZYuXIlXrx4geXLlwMAzp49C7FYDBcXF7Rv3x5isRivXr1CXFwcl8dLly5h69ataNGiBSIiItC/f388fPgQY8aMwbJly9CkSRN89dVXsLe3R/PmzXHr1i3o6upy18/+/fu5Esy8vDwMHz4cGRkZsLW1xbt376CrqwsDAwMu2Js7dy4AQCAQoG7dusjPz0diYiIAwMPDA4MGDeIdMyMjIwwaNAiNGjXCxIkTcefOHVy5cgW1atXCTz/9xM23atUq5OTkoFevXrx7iJubG548ecJdB1euXMGlS5cwa9YsXLhwgbsOAODgwYOYO3cuGjRoAF1dXeTn56N+/fqIi4vjbWefPn3w+eefA5C+yMbFxaGgoABaWloYNGgQateujadPn2Lfvn1y94Gi1+w///zD3c8dHBxgY2ODoKAg1K9fHxMnTkSLFi14yw8dOlSuwIJhGMyfPx+1atXC6dOnuZeQmTNn4vLlyxg0aBCaNWuGv//+G1evXkXz5s3x66+/cveEixcvom3bthg1ahQsLS1x7do1XLhwATo6Opg2bRpq164NANw1y77Q6+joYNWqVRCLxWAYRmkp7bNnzxAQEABAeh+fOHEiatWqhbNnz2LChAnYtm2b3DYtXboUgPT8njp1KrKyshASEoK0tDSVwSUbGMveM06cOAFfX18YGxtjxIgRaNCgAVJTU7F161a8fPkSrq6uSgN8ANw94uuvv+a9RJ47dw4mJibo1KkTatSogbt37+LYsWNYvnw5vL29YWVlVWxeWVevXsW9e/fUmrc4z549g42NDZef2NhYHDx4EFevXsWJEyd4+YmJicGwYcNgYmICX19fWFhYIC4uDhEREWXOR0Xm79SpUzhz5gyaNWsGGxsbpeveunUr7t+/Dx8fHzg6OiIxMRF79uxB//79cejQITg4OKjeAEaFR48eMUKhkNmxYwc3LS8vj+natSszfPhwbtq4ceOYzz//nMnKyuKmHTx4kBEKhcytW7dKnF5J0szIyGDatWvHLFy4sNhtiYyMZKKjo3nTJBIJ4+vry7i6ujK5ubnc9NTUVCYzM5NhGIbZsWMHIxQKmaioKLk0c3NzGQ8PD2by5Mm86d9//z3TsmVLJiMjo9g8MQzDzJs3j2nRogUTFxfHTbt58yYjFAqZgIAAblpcXBzj7OzMLFq0iJf/4cOHM15eXoxYLGYYhmFmzZrFjBo1ihk5ciTTt29fbt7z588zQqGQOXv2bLH5iY2NZYRCIfPzzz8zDMMwkydPZry8vFRux+vXrxlnZ2dm/fr1jFAoZP7991/ut6ioKN5xV5ZHhmEYHx8fZuDAgYxEIuHSXLFiBSMUCplRo0Zx8z1+/Jh3bsyaNYv56quvmGbNmjFubm68NIvbx0KhkFm6dClv/suXLzNCoZA5dOgQwzAfzlsnJycmNTWVYZgP522LFi2Yzp07c8sOHTpUZZoikYi5evUqIxQKGUdHR0YoFDKHDx9WmOa4ceOY9u3bM+np6QzDMEzfvn2Z7t27y10HiuTk5DDt27dnJkyYwDAMw4hEIqZ79+7M4sWLGaFQyCxatIjp27cvM3LkSG4ZdjrDSK+D58+fM0KhkJk5cybvOmCPc3p6usLr4PTp04xQKGRcXV256yA5OZlp3bo18+OPP/Ly2bNnT6ZHjx6MUChk1q9fzzAMw/zvf/9jnJycmDlz5jAuLi5MQkICl+aCBQsYoVDIdO7cmVm+fDkjFAoZHx8fuTQHDBjABAYGcucjm+aPP/7IODo6MsnJyUxkZCQjFAqZXr16FbsvX7x4wSQnJ3PpBQYGMiKRiPHx8WG8vLyYuXPnMs7OzkxqaiqTmJjI5ObmMocOHeLOMQ8PD26fDRkyhPH29maeP3/OXdNeXl7MrFmzuGv6888/Z4RCIbNlyxaGYRhm0aJFXFqy9wCGYZjCwkKmZ8+ezJQpU7j7wLp167jjxoqLi2McHR2ZNm3acNMkEgkzePBgRigUMkuWLOGmHz58mFsfex0wjPQ+2rx5c2blypVy13tqaipvO9nr/fDhw4yHhwczaNAgRigUMjNmzODlv2PHjoxQKGQiIyO5acVds6NHj2YYhmG2b9/OCIVCJiQkpNhjx7p79y4jFAoZb29vZvbs2YyXlxczfPhw3nmXmJjICIVC5ssvv+TOO4aRvyfI7qOmTZsyv//+O28fFX3WeHt7M23atJF71sgaOXIkM2DAAEYoFDJfffUVN10sFjMDBw6Uu1eePHmSadasGXf/KCn2HJG1fv16xtHRkXevZRjpc6GwsJBhGEbuniHLz8+PEQqFTFBQULHrZq8joVDIbN26Va38svcv9vwqeh3IXuulERoaqjA/33zzDTN48GClx62ilDV/cXFxTH5+PsMwxT/Xg4ODGZFIxJsWERHBuLi4MLNmzVIrryrbXJ47dw66uroYPHgwN01fXx+DBg1CcHAwEhISkJWVhVu3bqF///4wNjbm5uvXrx+MjIxw9uzZEqUHoERpnjx5EhkZGZg+fTq3LKOgtt/Ozk6uOFkgEKBr167Iy8tDTEwMN93c3BwmJiaqdg/u3LmDtLQ0DB8+nDd9xIgRyM7Oxn///acyjQsXLsDb25v3JtG+fXs0bNiQt50XL15EQUEBb10CgQDDhg1DTEwMQkJCEBISghMnTigsqq9bty4A6ZvfgAED4OrqijZt2mDWrFlISkri5mOrptRpAxUTE4P58+ejR48eXNV8YGBgscsEBQXh+PHjSqsTsrKyULNmTQgEAixZsgReXl5cqZtsKa6Liwt3brDbPXfuXJiamiI/P5+XprJ9zDZzqFWrFm9+9m+2NOXcuXMQCAQwNDSEmZkZgA/nbU5ODlf6FxMTg8jISACAv78/PDw8MG3aNERHR/PS1NPTw507dyAQCLjSE0VpstfBwIEDufWy+TMyMsLp06exdu1afPnll3B3d0eLFi0wfPhw7hgYGhrC0tISGRkZkEgkXF727NkDALh8+TJEIhGXLluSsW/fPri7u2PRokUKq1a9vb25NmOfffYZ3NzckJaWhho1agCQnmMLFiwAIC2lGzRoEC5evAhLS0u0bt0ap06dQqdOneDi4oIOHTrg1atX3Ntwr169AADDhw+HRCLhSoEvXbqE8+fPw9raGs2aNQMAiEQijBkzBoC0epAtBX716hVevXoFbW1t+Pr6AgCmTJmCzZs3QyKRICoqCgzDoFevXlxJ+MuXL+Ho6AhHR0cuXxMmTEDnzp3h5OSE3r17o3Pnzli7di23H/T09NCpUyfExMQgJiYGEokEHTt2xJdffont27fz7kP16tXjrqlHjx4hPT0dAwYMQEFBAVxcXJCeno5Lly6hVatWePz4MeLj4wEAOjo6yMnJkTsOeXl53LG7fv06Xr16hfv376Nly5YYMWIE75rOyspCVFQUOnbsCIZhkJqaym1rUFAQ1yyI3X9FHT9+HJ999hlat24NPz8/mJiY4NmzZ+jcuTNcXFy4+dauXcvbTnbd//vf/zB16lQuT0Xb57LX9dixY+Hk5ARHR0fs27cPderUkbtmAeDt27fIy8vjSm8yMzPl8nzv3j1MmzaNy2OnTp24czIpKQkzZ84EAK7JxIMHD9CmTRt07tyZ2+/seQfI3xNk6enpITk5GRKJBAD/WcO2A4yOjkZqairy8vLg5uYm1w737NmzCA0Nhbm5ObS0tGBhYcH9pqWlhS+++ALPnj3DlClT4O7ujtatW2PRokVo06YNAEAsFiM3N5db5uXLl5g6dSo8PDzg6uqKnj17okePHmjevDm6du2K/fv3y22HRCLB/v37YW5ujoKCAuTn53PnWJ06dRTWcsgaNWoU195x5MiRcHR0xKxZs4pdBpDen9u3b4+WLVtiypQpWLJkicJ7mr+/P/Ly8jB27Nhi0yssLMTKlSu5NL/99luu1L847DNStqlDeHg4bty4gSlTpsDAwAC5ublKa/MuXryICRMmwNPTEy4uLujatSs2btyo8B764MEDjBs3Dq1bt0bLli3Rv39/rtS6vPJnY2PDe4Yq06pVK+jp6fGmNWzYEE2aNEF4eLjK5QE1qsXDwsJgb2/PC/AAwNXVFQzDICwsDCYmJigsLOTdZADpBde0aVNeg3B10rO2tsbz58/VTvP27dto1KgRrl27hhUrViAuLg5mZmYYOnQoZs6cqfKCYG94shezutjq8qL5dHZ2hpaWFp4+fco9LBWJj49HcnKy3PKAdJ/cvHmT+5vd17LtANn5AODJkyc4duwY+vfvz1VHiMViJCYm4u3bt1i5ciW0tLRw/Phx9OrVC0OGDEFiYiL8/f3x+PFjHDlyBAYGBjh58iTq1KmDzz77TOX2P378GA8ePICLiwuioqIwaNAgnDhxAgDkAjxA+vBhq83nz5+PvLw8uXk8PDxw9uxZzJs3Dzdv3sRff/2FHTt2AAA6duwoNz/DMFi4cCG33QUFBbxjXtw+btmyJWJjY7Fjxw7Y29tz1eJLly6Fg4MD1+aNPS/j4+Mxd+5cfP3119DX1+cCAPZh+fjxY277CgsLkZ6ejgsXLuD69eto3Lix0jQBaXVSdHQ0L01l14GWlhaaNm2KJ0+eIDExEb1798bgwYORnZ2NgwcPYuzYsVi7di1CQkLw4sULTJkyBTNmzMCVK1fQtGlTDBw4EIsWLQLDMNwxYBgGfn5+3L+zsrJw8uRJnD9/Xm6/jRo1CitWrIBYLEbHjh2RlJSEp0+f4uXLlwgICMCvv/4KXV1dripaT08PN2/eRNeuXblAqUePHnBwcMCpU6eQlJTEVdWzD28bGxvUrl0bb9++BSC91sLCwuDs7IysrCwA0qCCbYdWWFiIe/fuoV27dtx1mZ2dDR0dHRQWFqJ169YQi8V48OABHjx4AH19fQwYMACHDx/mgm+Wnp4e6tevj2vXrgGQ3mxtbGxw9+5dPHjwAAC4h25iYiIMDQ25doGOjo5o164dDh06xAvW5syZw7UbZd63UXzz5g2ysrK4auuGDRvim2++QXh4OHbt2gUAWLNmDZYsWcLb/4cOHcLu3bvBMAyEQiF3rdWrVw9RUVG4d+8eV3V47tw5nD59GsbGxqhVqxaSk5NRp04drhmHg4MDrKyssHTpUhw7dgwdOnRAs2bNuJckPT09iMViTJ8+HS9fvsT+/fthamqKmzdvwsjICP/++y8AaQegq1evwt/fn9tOANi0aRNMTEwwaNAgrFixAoD0xcvOzo6rFmdf7GNiYuDu7g4DAwPcuHED4eHhOHPmDPfiyj6kY2Nj4ebmxl0LigKHc+fOIS8vD8OGDYO5uTkePnyII0eOQCAQYMKECbC2tgYALiB7/Pgxhg0bBmtra6xatQqPHz8GIA1SnZycePeEzMxMFBQUcM0mcnNzce7cOVy5cgWdO3fG7NmzuUDAwcEBy5cvx5IlS6Cjo4PExETMmzeP1/Y9Ly8Py5cvx7hx43D//n3e/mOx18WlS5cwfPhw2NraYvny5Xj+/DkA6f30119/RZMmTTBy5EisWLECdevWxYQJE5Ceno4tW7aAYRgMHjwYdevWxfr167mmDllZWcjPz8eDBw+4fWlpaYkWLVpALBbDzc0Nc+fOVXgPlTVp0iRkZ2fjyZMn0NXVRUFBAc6fPw8tLS3MmjUL5ubmSEtLg1gsxuvXr7nlUlNTMXHiRMTHx8Pf3x8SiQQjR47k7mmHDh3C2LFjoauri/nz5yvscyFr48aN0NHR4aUZGRmJQ4cOyQVXbH5iY2OxceNGAOA1Pbh16xYA6XXw5Zdfctvm7e2N+fPn847j0aNHYWRkhK+//hpGRkYIDAzEunXrkJWVxQuy//vvP/j5+cHGxgZjxoxBzZo18fz5c1y9epVX8Kbp/JUFwzBISkpS2E5YEZXBZWJiosK6efaNMSEhgbs4FbWZsLKywsOHD0uUHjufumm+ffsWcXFxmD17NsaNG8e1F9qyZQtEIhGvwW9RaWlpCAgIgIeHR6kOQmJiIvT09GBubs6bzk6TbaOmCPu7su1MTk6GWCyGtrY2EhMT5UrYZJdlSy/YE1AsFuPly5fcw5dd9scff+S1Be3YsSO++uorHD16FK1bt8bz588xbtw4hTe4ojp37owuXbqgd+/eGD16NGbNmoUmTZpgwYIFePDgAfdQ0NLSgqenJ6ysrHD69GmMHz8eBw8eRFJSEuzs7Hhp/vzzz0hKSuLerMeOHcuViClqyHzs2DFuu+/du4esrCzefipuH1tbW3OlY5MnT+amt2jRAv/88w93Q09MTETjxo3RrVs3HDhwgHvD1NGRXkJNmjTh9kfPnj2hra2Ny5cvIykpCQzDICcnB69fv8a///4rl6a7uzvOnDmD1atXY/Xq1bw01bkOLl++zHvLDA4Oxtu3bzFlyhTo6uriq6++QosWLbBx40bUqlULR48ehUAgwKJFi9ClSxeu89GlS5dw9+5d2NraYsyYMahXrx5iY2O5domyJfv//vsvtLW1IRaLsWrVKqxZswavXr3C9u3b0alTJ7Rs2RLPnj2Dh4cH0tPT4eTkxLUhHDlyJAIDA+Hl5YV27dohKysLQUFBiIqKAiDtxMe+kFlZWXFBTkJCAhITE9G2bVtcvHgR5ubmmD17NkxMTDB16lQAwHfffYfTp09z++3Nmzf49ddf8fvvv/PaaTEMg9WrV6NLly44cOAAGIbhOhFNmzYNoaGhvIbu33//PVq3bo3c3Fz4+PggLi4O9+7dQ4MGDfDvv//Czs4O4eHh+OKLL3Dx4kWFbbRbt26N0NBQ7u+oqCjo6urCysoKDg4OCAwMRHx8PHr16gVtbW0uuGzbti2GDBmCbdu24d69exAIBBg4cCDat2+Pd+/eYceOHYiKioJAIMDz588xaNAgtGnTBkuWLEFsbCxMTU3x+++/IzAwEPv27YNAIICJiQmvdJF92dfS0uJdBwDQuHFj7Nq1izsvDx8+jMzMTGhra2PSpEnIzc3Fhg0bcOnSJTg6OqJ169ZcqVxKSgr8/f2xfv16BAYGcgF5RESEwk4cs2bNgq+vLx4/fowbN27AysoKq1atwhdffAGBQCBXalKzZk3o6urip59+gra2Nnr37s399sMPP/BKGa2trXHkyBEwDMPrAJmSkgIAmD59OtcJs3nz5pgwYQJSU1Nx8uRJnDx5kndPGD58ONfuV1tbG506dcKAAQMQEhKCXbt24dGjRzh69CgsLS1Rq1Yt9OvXD6tXr0ZSUhI8PDzkarq2bt0KhmEwduxYpKam4saNG3Iv3qdPnwYAeHl5Ye7cudw5xrZ/7NevHzw8PLB161bMnz8f9vb2OHLkCHR1dblSrdq1a+PFixdYtGgRevTogT59+gCQ3nNlXyL19PRgaGiIpUuXcu3DR48ejRMnTii8B7M6dOiAI0eO4MmTJ5g6dSoaNmyIwMBAHDhwAE+fPkVAQAB69OjBa7NZo0YNHD16lDsHGzduzHX6GzBgAABgyJAh8PT0hIGBgVo1allZWTh16hSXplAoxKxZs3Dq1CkuTZZsfszNzTF37ly0bduW+519uZ0xYwY8PT0xceJEvHr1Cps3b0Z0dDQCAgK4woxVq1bxzrlhw4Zh7ty52LdvH2bOnMm9qM2fPx+1a9fG0aNHYWpqys2vqMZVk/krixMnTiA+Pp4r8VdFZbV4Xl6ewmJUtipPJBJxF0HRYlR2PtmLRJ302PnUTTMnJwfp6emYNm0aZsyYge7du2PJkiXw8fHBvn37uJtHURKJBD/88AMyMzPx66+/Kt4BKijbHjafslWOirC/K9tOdh3s/4ubLzAwkPdGrqWlBTs7O2zevBkzZsyAtrY2GIZBt27dkJKSwv1Xv359WFlZISgoCCdPngQA7qajioGBAfz9/ZGeno7x48cjNTWVe3lggwVAWpy/du1a3LhxA35+fpg2bRoOHz6ssNTB0NAQIpEIenp6WLp0KRYvXsxVCctW9QHSm8iqVaswYcIEaGtr4/vvv4e+vj7vRUGdfSwUCjFx4kRs3LgRs2bNwps3bzB9+nSuRIjd93Z2dvD09MSyZcuwevVqeHh4AABXymFgYIDFixdj7NixaNmyJUaPHo1ly5ZBS0sLWVlZmDBhglyabCeAwYMHy6WpznXA/iaRSJCWloavv/4arq6uqFOnDlq1aoX8/Hzs27cPgLTxv7KXhv/++w+6uro4ffo0fH194e3tjZEjR3JVic+ePQMgrUYMDg7mqqbZbdHV1cXNmzeRk5ODiRMncseQvQ7Y9bLNTfLy8pCTk4PU1FQA0hurpaUllixZgosXLyImJgbZ2dmIiYmBjo4O13M2IyMD9+7dw8aNGzFgwAB069aNy0dKSgp27drF7bdGjRpx18O4ceOwePFi7kXw/v37AKSlmwzDcC8IJiYmWL16NYyNjbk8P3nyBAUFBcjLy8PAgQMBSKujpk+fzp2vrVq1QosWLXjnR9EXVnadgDTYEQqFsLCwwOrVqwFIS8ACAgK40m8LCwtoa2vD29ub298mJiYIDQ2Ft7c3RowYwQWDzPuOIr/99hu6d++Ow4cPA5AGHw0bNsT8+fPRsGFDMAwj18OZvQ4sLS2564ANwHJzc3mlumxpbPv27TFu3DjufAWkPeplqwAvXryIzz77DF5eXjh16hQ3+oGLiwt++eUXbNy4Ea1btwYgbeIzZMgQAB+u2Q4dOiA6Opor5apXrx53b/r6669Ru3ZtzJkzB7a2tlixYgXv4Sz7kM/JycE///zD/c0GqWKxmOs5/+eff3Ln3YMHD5CVlQWBQMBV7creE+bPn49t27Zh/vz5cHFxQcOGDeHl5YUffvgBGzZsQFxcHPdyAEivzZSUFBQWFso9a2JjY7FlyxZ89913MDAw4DpqsbVCUVFR+Ouvv7gSc7ZWij1H2G1u3bo1+vfvj3Xr1oFhGGhpaSEzM5Pr4NmpUyd4eXnh8ePHyM3NhYODA1fwMGXKFGzfvp1XarZ582b07dsXQ4cOxdatW5Gdnc3bJmXYJkydOnWCj48PV6L67NkzHDt2DBs2bMDff//NBdhNmzbl1WT27dsXNWrUwH///cfd0x49egSRSAQzMzO1Cj2KNqfr3bs3l2ZRbH7Y86hoZ1B2Pzdv3hyrVq1Cjx49MGXKFMyePRtPnjzBlStXuHllz7msrCykpKRwL6XsOfzkyRPExMRgzJgxvMASgMJt02T+Sis8PBwLFiyAu7u72kOGqSy5NDAwUNgOh7349fX1uR2qqBpUJBLxdrg66bHzlSRNALy3VkAaIJ07dw6PHz/mhhORtXDhQty4cQMrV64s9VhfbHswRUQiEbc92dnZvF7U2trasLS05H5Xtp3sOopbFzuftrY2vv76a266QCCAsbExvLy84OXlhadPn+LChQtKh2hISUnBo0ePIBQK5Yq+JRIJLwjU1dWFubk5YmJisHr1ahgaGqJ9+/a8m7ts+x8A+PPPP6Grq8vl0cbGBjVr1uRKv9mqjsmTJyMkJAS//PIL95Zpbm4OPz8/nDx5El999ZVcmkOHDsWECROQm5sLoVDIO8fYfZyUlMRtg4GBATcMDyBtN+jr64uUlBS4ubmhXr16+Pbbb3Ho0CEMHz4cBgYGeP36NZ4+fcobAkgoFKJXr144d+4c5s2bh4KCAqxfvx7bt2/nPZBZjx8/xrFjxzBkyBAuzUePHgGQVr327NmTlyb7hiqb98LCQojFYu46OHr0KLZv384NecKqU6cOtm3bhoEDByI8PByGhoZcz11FYmJiYGNjI1flxJ4LbMAWGxsLALzew+y5yb5QNGnShJsmex0A4Howfvfdd3IjC4wePRonT57kjdxQt25d5ObmwsjICPr6+ggKCkL37t25oERWnTp1cPv2bfTo0QOAtN0Zm9bWrVt5827fvh2HDx/mzlm2Wn716tVYvHgxb95169ZhyZIlvPP73r17yM7OxoYNG/Dtt9/CyMgIW7ZswcGDB2FrawuRSIT58+dz84vFYq7JAwD4+PhwbSvNzc1hYGCAvLw8LFu2jOsBnJqaKteesFevXjh48CB3zSQnJ3O/ubu7c/+2tLSEiYkJsrKyEBwcDCcnJ64qXvYBlZiYyL20WVlZwc/PDwUFBYiJicGZM2cQERGBvXv3YsyYMbyXO/Ylgb3WhEIhXrx4gYiICO6e9fr1a6xevRrZ2dm4dOkSrK2tERcXhylTpnDNbq5fv4579+6BYRjExsaiUaNG3PnCNlWKiYmBg4MDjIyMuJeFH3/8EWfPnsXMmTPx5Zdf4tChQwgMDOR6sMfHx2Pr1q24efOmXDDNNqtgA+Fx48bh1KlTvPOuW7duuH//Pjc0mIuLC0aNGsVdv7LHgw3EZ82ahU6dOqFRo0a4ffs2V8qzcOFCiEQiODs7c8+alJQUiMViLFy4EPb29lzTGicnJ1haWiIzM5O711lZWcHe3h7h4eG8Nt8A0KxZM+7lVnbbXr16xas+PXfuHPfvtLQ0GBoawt7eHteuXePa32ZmZiIgIAAGBgZYuHAh1q1bxx1bJycn7uVIIpHwRi9g86jMsGHDsGLFCty+fZvbdwYGBti7dy+Cg4Pxzz//YOTIkQCktUHGxsa4fPkyXF1defdyRW0XFSk6XI6Ojg5sbW15tS8s9jzs1KkTunTpgj59+sDIyIjLj7L4om/fvliwYAHu37/Pa7e9Zs0aBAYGcseBxV7HbKk++zKriibzVxrsqAU1atTA2rVruRdEVVTOZWVlpbBqlz2prK2tuZNKUbuXxMRE7magbnrsfCVJE1DeKYNtsC1rw4YN2Lt3L3788Ue5g1ISVlZWKCgokBuaIT8/H2lpaVw+t2/fDk9PT+4/9u2U/V3ZdtasWZMr0rayspIruQM+lCi1bdsWSUlJiI6ORnR0NEQiEQoKChAdHY309HTuRu3h4YEdO3bI/de7d2/ExMQoLLVMT0/n5f/bb78FAEyYMAEFBQXo1q0bfvvtNyxbtgyTJk0CIA1GoqOjwTAMEhISsGvXLgwfPpyXR/ZEff78OdLT0xEVFYXAwECYmJjA09OTm48NbF69eiWX5tChQ/Htt9/i+fPnmD9/PrS0tHjbze7j33//ncv/H3/8AeBDiWPXrl3x7t07ue1jG/NbWVkhJiYG7dq14wVf7HFLT0/Hu3fvsHDhQmzbtg0SiQRz587F9u3bsWPHDq5aX09Pj7tBs2mybWYVpcnun9mzZ3N5e/XqFd69e4fExETo6upi9uzZqF+/vlx1Dzu8jb29PQoLC2FkZMTtT/YGl5WVhYKCAoWBcEmw14HsC4WVlRXi4uJ414FYLOYCJzawZEtuAen1cOrUKd6wTrGxsUhNTUWDBg1gYmKC5ORkDBs2TG5bAGkwkpqayt0T7O3tubZO3377LXbs2AELCwuYmJhAIpHA1dUVVlZWXFUxIC1V27BhA6+pS+PGjbFmzRrekD5paWkoKCjAzZs3kZ+fj+fPnyMpKQmjRo0CAOzdu5cXPD948IAXKGpra6NmzZpISkrC5s2bkZeXBx0dHTRp0oRrY2llZSVXVVanTh1IJBKF4ysWrf6SHRuU3b/scWCx41IC0uGlzpw5gz/++IMXYG/ZsgWAtDSLXUdubi6io6O58WTZB/rLly+5togNGzZEZmYm9u/fzysBNTU1VfgcYJs7sflUtI2y90VnZ2dIJBIcOnQIADBmzBh4eXnB09MTAwcOxNmzZzFkyBDuHs8GW8nJyYiOjub2g56eHvbv349Tp05h/PjxAKTVjOx5B0jvmyYmJrzSZwAwMzND+/btuVofQHqM2OcO+6wxMzPjneuDBg2Cp6cnLl++jLCwMKxdu5Y7n3V1ddG6dWts3LgRO3fuxOXLl7kgomHDhrx9VLRJFruPBQIBduzYgTVr1gCQluax93plTcDY68bBwQEXLlzg1RDWrFmTOx4ZGRl4+PAh75lQHC0tLdjY2Ch8FterV4+372THWV20aBEmT54MgUDAtacvev+SfT6UlZ2dHZydnXn5YfeJ7Ms0ID2H2bFgAek+GTlyJJ49e4Zp06Zh8+bN2LFjB3744QcAKPM9tqz5K43MzEyMHz8emZmZ2Lp1q9rDRQFqlFw6OTlh9+7dyM7O5hUzs6UtTk5OMDIygo6ODkJDQ9G9e3dunvz8fISFhfGCFXXSA6RvSuqm6ezsjFu3biE+Pp7Xfo+9wRW9kPbs2YP169djzJgxKnudqcJWUYSGhvIusNDQUEgkEu73/v3780oV2LdOGxsbWFpa8tpisUJCQnjjhDVt2hQBAQGIiIjgdephvxRy8eJFhV8m6NKlC8aPH88b84ztdSlr3rx5EAgECoNtExMTri0nAO7t+c2bNwCk7bDYajjWw4cP0aVLF4SEhCA5ORkFBQVYuXIlVq5cKZf+0KFDMX78eK6zS3p6Ou+4s9LS0uTSZKsUAfDag7Db/cMPP8DMzAxNmzblAl/2xsy2V5FIJKhduzbXcYhhGEyePJk7R52cnHDr1i25Zg7seQtIH9jnz59Hs2bN8OTJE3h6eqJBgwYQiUS8oIItXWTTLFqSL5tm/fr1oaOjA09PTy54nDt3LmrUqIGwsDCYm5vDzs4OGzZsQGJiIleCsmjRIu6Fh612Tk5OlhuUm/2qh1AohIODA+7cucMrRQYgN1Ya21FBtsSMPU/ZQOjly5dwcnJCUFAQ7zp48eIFRCIRdHR08Oeff0JHRwfp6em8YJJtU1i/fn189913aN++PW7duoV27drh5s2bSExMxOjRo6HI06dP4eDgwK0vNTUVzs7O3P52cHDg9gcgLRUwNjbGmTNnuJKGNm3aoFu3bli5ciW3Dz09PeHj44P09HQcOXKEG4B48eLFsLGxwYULFxAXF4e2bdti2rRpAKRBseyxLfpRhTVr1sDPzw9ZWVk4duwYN10oFHJNbRSV1ERFRUFbW5t7YWGPB8Dv7Z2SksKdd+w9UCgUcvuYtWPHDmzatAl3797F5MmT4enpCVdXV1haWmLbtm3Q0dHh9mdsbCyXp6tXr+Lq1atcOmzHHtljGRERwdtuNqDs168f3NzccPDgQd59iQ0S2Psi265Qtp2f7H3R3NwcAoEADRs2REREBObOnQtra2skJydj3rx5GDduHKZNm8a177x9+zYA6UDfbFti9m8jIyMMGzaMq6p88OABJBIJF5AyDAOJRKKwJ25eXh7vGo+KikLNmjV5zxp2/7DYkjx21AV/f3/4+/tzv8fHx+P27duYP38+2rVrx+13dtttbGxQq1YtudI49hnI1iaJxWIYGBhAIpHI3feLXtuOjo7Q1dVFRkYGGIZBdnY2F9TGx8dz55GJiUmxX3cqqqCgAO/evVPYISgrK4tXGnb27FloaWmhQ4cO6N+/P3bu3Ml19gXAu4cdOXIER44cwZYtW3idPdn7OquwsBAxMTEKn3tF5eXl8V6S2fuHbK0DIL2+8vPzuX0SFBSEtLQ0bNiwgdcZtuioAOzxefnyJdfTvyRKm7+SEolEmDRpEt68eYOdO3eiUaNGJVpeZcmlj48PCgoKeF3k8/PzceTIEa4HpampKdq1a4fjx4/zqluOHz+OnJwcbnBvddMDUOI0AXBvr4D0RhAQEAAjIyPe4LpnzpzBokWL0KdPH418aq1t27YwNzfH3r17edP37dsHIyMj7oS3s7ND+/btuf9kA83u3bvj8uXLvJPj9u3bePPmDW87u3TpAl1dXd66GIbBlStXYGFhgfXr12Pjxo1Ys2YNVq5ciSZNmsDW1hYbN25E//79YWRkBEBxaYBIJMKZM2fg7u7Oe1ixdHV1eflnbxIGBgZo27YtNm7cyP3HBtlCoRAbN26Erq4ujI2NefNs3LiRC2b19PS4PDZo0AACgQBOTk68edkOSPXr1+fSrFevHrd/hw0bxs1bdLsBoGfPnnj8+DEcHBzQvn17NG7cGLdv3+YCDXZAZXb7cnNzIRKJuHOHPQ5Xr17l3r7z8/Nx+PBhGBkZwczMDPXq1YOWlha3n9kG+Lt27eLeWvPz87m2c2yash1NiqbJ9jwOCgqCm5sb2rdvD2NjY66ZRZ06dbjzQEdHh/v99evXMDAwQFZWFt68ecOVynl7e3P7CZB2DrC1tYWxsTE6duyIgoICHDhwgMuPWCzGzp07AYALOGvUqAF3d3depxX2Onj69CmMjIzw119/oWvXrkhNTYW+vj43BA77AHZxcUHHjh3Rvn17+Pj4cPuM3U/W1tZ4+fIlBAIBEhIS0LhxY3To0IEr8R81ahS3HWxJKPvC07lzZzRp0gRWVlZIS0vjBUBshxaWi4sL7xpjFRQUyLVtAqSlka9evQIA7lxycHDgquGfPHmCxo0bA5BWq8oG6evWreNKUXV0dFCzZk306NGDq8IFpA/Bdu3aYf/+/ahRo4bC9uKnT59G69atuYe+bNvXGzducP+WHWCfbV7Brke2NLRdu3bcenR1dWFtbY3GjRtz21FYWMgtP3HiRO5rT126dMHGjRu54NHExAQmJiZYt24d1063Xbt2GDVqFLS0tODh4cGVAk6ePBk//vgjlw5Ltp12165dERYWhtq1a8Pa2hr5+fk4f/4877544sQJMAyDxMRE1KtXDyNGjEC3bt24j3E0btwY2dnZePHiBTw8PLgH8ciRI7Fx40ZYWlrCyMgIBgYGXMEGWzK4du1a7rwDpLUYOTk5vP2dkpKC2NhY3Lp1i0v75MmTiIyMhI2NTbHPGnd3dwwZMkTuvsjmy9XVFRs3bsTnn3+ON2/ecC/yssPTde/endfrGpCWKAsEAhQWFiIlJQXa2trw9PTEv//+i/j4eO5Ys0PYyDIxMUHbtm3x+vVrrtkSIA20X758yQXaOjo6qFGjBu+ZwCpaHQwA27Ztg0gkUtgsJzExkdcsLTExERKJhJvX29ubK/2ztLSUu39t3LiR2/esY8eO8a7fU6dOIT09nReAKrq2QkND8ezZM156bdq0gYWFBY4cOcIrfWRjGHafsAGy7LWVn58vFxs0a9YMtra22Llzp1yTF9llNZ2/khCLxZgxYwYePnyItWvXyn2gQB0qSy7d3Nzg4+ODlStXIjExEfXr18fRo0cRGxvLGx5j5syZ+OqrrzBq1CgMHjwYcXFx2LFjB/cAKWl6JUnTxcUF/fv3x19//YXk5GQ0a9YM165dw40bN/Djjz9yD9aQkBD89NNPMDc3R7t27bghc1gdOnTgqtIzMzO5T1uxVTV79uyBqakp6tatywUtBgYGmDZtGhYsWIDp06fD09OT+2wWW2KmyqRJk3Du3Dn4+vpi5MiRyMnJwbZt2+Dk5MRrPFu7dm34+vpi+/btEIlEaN68OS5evIiHDx9i9erVXElfdHQ0BgwYAH19fQgEAsTHx+Py5cs4ceIEzMzM8OzZM4wcORJeXl4wNDREVFQU9ylOtkT42bNnXG/ZN2/eIDMzE5s2bQIgLe1h38y6du2KkydPQigUonHjxnj48CEXdFhYWHBtPf78809ERUWhbdu2sLa2RmRkJPbv3899fUS2TcigQYMQEBCA3bt3o3v37rySnUGDBnHzHj58GP/99x9atmyJli1bcjcTsVgMiUTCS1PZPnZ0dIRYLMb69esRHR0NNzc3vHnzBnv27IGNjQ336VA3Nze4uroiJCQEXbt2Rdu2bbkhVBiGwffffw9tbW24uLjg5s2b0NPTw9q1a7Fr1y4umBcIBLC2tubSfPz4MWxsbLgH/urVq7FkyRJufjbNmTNnYujQofDx8YGzszMiIyORk5ODBg0awMLCAsHBwZgyZQoiIiJQWFiIhIQEWFlZISMjA71790ZCQgL+97//4dKlSzh16hQYhuHG9wwODuZuaM+fP4eJiQmWLFmCkydPomHDhggODubVAMTExGDPnj0QCoVcB4NNmzahUaNG3HXn7OyMBw8ecJ0mCgsLMXr0aBgZGSEtLQ0CgQARERHYvHkzTExMcP78eVhaWiInJweLFy/GqVOnIJFIEBQUBFNTU7x79w67d++GtrY2RowYgdOnT+Off/5BYGAg6tevj5CQEADSlyb2c6iAtBmEn58ftm/fDkA6VAs7bFBubi60tLQQGBgIGxsbrqc4IH2BPX78OBITE7npBw4cwM2bN7ltBqSlcGyVsJ2dHYyMjJCZmYlu3brByckJISEhvJLE8PBw7tgWFhYiOTkZkyZNgrm5OdcUQltbGzt37sTLly+hra0NPT09hIWFwc/Pj2vCkZubi6ysLCxYsAAWFhY4cOAAl89Tp04hPDwcBgYGXF4tLS1x48YNrFq1CufPn4euri5ycnIwd+5c7h4SHh6O2rVrY8OGDYiJiYGbmxtX0qajo4NLly7BwMAAL1++xIMHD7jOEfXr1+ceqllZWVi9ejV69OjBldZ07twZOjo63JeVrly5grdv38Lf3x8MwyA8PJz3GU9/f3+EhITA0tKSG6u1sLAQa9aswdGjR7mmA2fOnMG+ffvw5MkTbhxQ2RqRRo0aoX79+li2bBnOnz8PsViMtLQ0Lq/Ozs7o2rUrFi9ejMaNGyM4OBijR49GmzZtoK+vz3U0dHV1xaFDh7h7gra2NoKCglBYWAhzc3OsWLGCq+5nP2167Ngx1KlThxvRgH3W5OTkIC4uDsePH+eeNdbW1nLt4QoLC5GRkYHMzEykpqYiICAA+/fvR7169WBkZIRly5YhMjISDg4OePbsGTdqw9WrV5GSkoJ//vkHhoaG0NLS4oYoc3JywpUrV9CtWzfUqlULgwcPxj///AN9fX3k5ORg06ZNsLKywrt37xAWFsaV0u7YsQM5OTnYtWsXatasCbFYjE2bNiE5OZn3TPD29uaCc7ZE+Pjx47h//z7u3LmD8+fPQyAQ4NatW0hJSYGRkREX2GppaeH58+fYtWsX4uPjuRLKCxcuoLCwENHR0di/fz+aNGmCnJwc3v6ys7NT2J7QxMQEI0eORP/+/bmhiIRCIa/G08vLC1988QWEQiGMjIzw6tUrHD58GMbGxtyQbIC0lvGHH37AL7/8grFjx6Jr164IDw/Hvn370LlzZy54a9myJWrUqIHZs2dzn6s9fvy4XLMWbW1tzJs3D35+fujfvz8GDBiAWrVqcV8EYz/HrOn8Aeo/15cuXYrLly/Dy8sLaWlpvE8pGxsbq9WGU61vi4tEIqxZswYnT55Eeno6HB0dueoqWffu3cPKlSu574D37NkT3333HVcqUdL0SpJmfn4+Nm3ahGPHjiEpKQn16tXDmDFjeJ0/jhw5Uux3QP39/bli6uK+ha3om6oHDx7kPk1Zp04djBo1ihu8WR0vX77E0qVLERwcDF1dXXTu3Blz5sxR+G3xLVu24MCBA0hISIC9vT0mTpzIq8pmBy0+fPgwVwXJflvcz8+PG4z22bNnXHAnFosRFRWFmzdvwtzcvNh9NXXqVK5NYkZGBpYsWYIrV65wPWb79OmDWbNmoU2bNlw1z6lTp7B//368evUKmZmZMDMzg4eHB6Kjo1FYWMg7eQsLC7F//34cOnSIq95o2LAhnj59yvtmrKpvB7Pjv6nax9ra2ti0aROuXr2K2NhYGBsbo0OHDvjuu+941XEikQg//vgjLl++jIKCAggEAtja2mLixIlcI/WwsDBMmTIF7969471FsvP6+/tzaXp7eytsYA5IOwDIdhqYM2cOV4VdVI8ePRAaGoq4uDjo6+tzg68LBAJ06tQJ33zzDTw8PCAWi7Ft2zYcPnwYkZGRStsAmZqach8iYMeIVMTKygqJiYkwNTVFQUEB6tWrB3t7e7x69QpRUVHQ0tKCWCzmvkmura2NFi1aYOTIkdi/fz8ePnwIfX19dOvWDSNGjEC/fv14naz09fXRuXNnzJgxg1clk56eDl9fX7x48QISiYQLrJycnLBr1y5eG7QdO3Zg1apVvCDPwMAAbm5uMDIy4oLrgoICmJmZcdW2WlpacHNzw4wZM5RWwRe1ZcsWrFixAi9fvgSgeFgR1ueff46QkBAu2GQ/oQiA+8xn3759sWXLFrmOcSyBQAAzMzO0aNEC48ePx507d7Bjxw7uJUtfXx/5+fkQCATQ0tKCra0tevbsiTt37iAyMhJ6enq8e8jnn3/Ouw7YoG3t2rW4fv06Lly4AIlEgu7du2P69On4+++/ce7cOW4cPrYJCvDh/jlnzhycPXsWUVFRuH79OjZt2oQNGzagS5cuePr0KZKSkrjhwNhvh0dGRoJhGOjr66NPnz7csE/skGz5+fncuauvr4/PPvsMfn5+vNogQBrML1q0CIGBgWAYBgMHDsSoUaPQr18/bpBuNiiqW7cuDh8+zLWRNTY2RsOGDZGdnc27J9SpUwdBQUF4+/YtsrKyoKenB21tba6Di7W1Nby9vdGwYUMsXLhQ6fGXfdYUJZFI0KpVK0gkEkgkEtSqVQs9evTA1KlTIRaLsXjxYly6dAkCgQDe3t7o0aMH/Pz8uGu/VatW+Omnn2BgYID169fj1q1byMjI4K7T3Nxc1KlTB+PGjcO1a9dw+fJl7kMLpqamaNGiBTp37ozTp0/j8ePH0NbWRocOHWBjY8OrtpfF7k9AWip89+5dGBgYQCwWc+ddVlYW7t69y7WRNDMzQ3JyMubOnYvY2FgcOXIEubm58PT0hL29PTekWOPGjTF9+nScO3cOQUFBXHDk6Oio9Nvia9eu5cZuZtP87bffeMMgLlu2DLdv3+byY2VlhbZt28LPz09ueDxAGixv3boVERERMDc3R+/evTFjxgxe5+L79+9j2bJlePbsGczMzNC3b1+0a9cOY8eOlTvmd+/exYYNG7iX44YNG2LEiBFc7Ux55E/d5/qoUaO4IeqKsrW1Vfg98qLUCi4JIYQQQghRh3p9ygkhhBBCCFEDBZeEEEIIIURjKLgkhBBCCCEaQ8ElIYQQQgjRGAouCSGEEEKIxlBwSQghhBBCNIaCS0IIIYQQojEUXBJCPjmjRo2Ct7d3ZWejQhw5cgSOjo64c+eOWvN7e3tj1KhR5ZwrQsjHjIJLQkiVsn79ely8eLHM6ezcuVPpV40IIYSUH/pCDyGkSnF0dMSAAQOwdOnSMqXj7e0NW1tbuU+1AuA+tainp1emdVQHYrEYhYWF0NXV5b6tXZzi9hshhKhDp7IzQAghFe1TCCpZ2tra0NbWruxsEEI+IVQtTgipMCKRCOvXr0ePHj3g5uaG1q1bo0+fPli2bBmio6Ph6OgIADh69CgcHR25/1hnzpzBpEmT0LlzZ7i4uKBNmzbw8/PDs2fPeOtxdHRETEwMgoKCeOlER0cDUN7m8u7du/j666/h7u4OV1dXDBgwAAEBAXLzscvHx8fju+++w2effQY3NzeMHTsWERERJd4vxbWLVJRXR0dHzJ49W610lKX97t07TJ8+He7u7mjVqhUmTZqEyMjIEuedEEKKopJLQkiF+f3333H48GH0798fLVu2hFgsxps3b3Dnzh18++23WL58OX766Se0bt0aQ4YMkVv+n3/+gbm5OYYMGQIrKytERkbi4MGDGDZsGI4ePYqGDRsCAJYvX44lS5bAwsICkyZN4pa3tLRUmrfLly9j6tSpqFWrFr7++muYmJjg9OnT+PXXXxEdHY2ZM2fy5s/JycHIkSPh5uaGmTNnIjo6Gv7+/vDz88OpU6eqdGlhRkYGRowYgbi4OHz11VdwcHDA3bt34evri7y8vMrOHiGkmqPgkhBSYS5evIiOHTti2bJlCn/v168ffvrpJ9jZ2aFfv35yv2/duhVGRka8af3790e/fv2wc+dOzJ8/n0tn7dq1qFWrlsJ0ihKLxVi4cCGMjIwQEBAAGxsbAMDw4cPh6+uLv//+GwMGDOCCVwBITU3F2LFjMX78eG6apaUlVqxYgVu3buHzzz9Xud7KsnXrVsTExGDx4sUYOHAgAGDEiBH4448/4O/vX8m5I4RUd1QtTgipMCYmJnj16hVevHhRquXZwJJhGGRlZSElJQUWFhawt7dHSEhIqfP15MkTxMbGYuDAgVxgCUjbZo4bNw4SiQSXLl3iLaOlpQVfX1/etLZt2wIA3r59W+q8VISLFy+iVq1a6N+/P2+6bKBMCCGlRSWXhJAK8/PPP+Onn35Cnz59YGdnhzZt2sDLywve3t5q9WR++vQp1q5di6CgIOTk5PB+q1evXqnzxbbFbNy4sdxvTZo0AQBERUXxpltbW0NfX583zdzcHACQlpZW6rxUhKioKDRv3lyu6t7a2hpmZmaVlCtCyMeCgktCSIXp2rUrLl++jGvXruHu3bu4desWDh06hNatW2PHjh3F9uKOjY3FiBEjYGJigsmTJ6NRo0YwNDSEQCDA4sWL5YLN8lZcm8qSjvAmEAiU/lZYWKh2OmKxuETrJYSQ8kDBJSGkQpmbm6Nfv37o168fGIbBypUrsXXrVly6dAlffPGF0uX+/fdf5OTk4M8//+Sqn1lpaWllGl6ILfV89eqV3G/sNDs7u1Knr0qNGjUAAOnp6XK/RUdHQ1dXlzfN3NxcYelo0dJVZezs7PD27VuIxWJekJyQkICMjIwS5JwQQuRRm0tCSIUQi8VygYtAIECzZs0AfAisjIyMFAZObBBUtFTw4MGDSExMlJvf2NhY7eppZ2dn1K1bF0eOHOGlVVBQgG3btkEgEKBLly5qpVUabEehW7du8aafOnUKCQkJCud/+PAhcnNzuWnp6elqf5GoS5cuSEpKwrFjx3jTt2zZUrKME0KIAlRySQipENnZ2fD09IS3tzeaNWsGS0tLREdHY9++fahRowa8vLwAAC1atMDt27fx999/o27duhAIBOjVqxc6duwIQ0ND/PTTTxg5ciTMzMxw//59/Pfff6hfv75clbCbmxsOHTqENWvWwMHBAVpaWvDy8pLrbQ5IA9fffvsNU6dOxaBBgzBkyBAYGxvj7NmzePjwISZNmsTrKa5pjRo1Qvv27XHgwAEwDIOmTZsiLCwMFy9eRIMGDeSqxkeMGIEff/wRo0ePRr9+/ZCRkYGAgADUrVtXYaBd1Lhx43Dq1Cn89ttvePLkCRo3boygoCA8fPgQFhYW5bWZhJBPBAWXhJAKYWBggNGjR+P27du4ffs2srOzYW1tDW9vb0ycOJHrpT1v3jwsWLAAmzdvRnZ2NgCgV69eqF+/PrZs2YL//e9/2Lx5M7S1tdGqVSvs3r0bCxcuRExMDG99M2fORHp6Ovbu3YuMjAwwDINLly4pDC4B6WcPd+7ciT///BPbtm1DQUEBHBwcsGjRIgwePLh8dw6kY3MuXLgQJ0+exIkTJ+Du7g5/f3/Mnz9fbtv69u2LhIQE7NmzB0uWLIGdnR38/PygpaWFR48eqVxXjRo1sGfPHixdupQrvfTw8IC/vz/GjBlTDltHCPmU0LfFCSGEEEKIxlCbS0IIIYQQojFULU4IIeVALBYjJSVF5Xw1atQoU093Qgipaii4JISQcvDu3Tu1epj7+/ujTZs2FZAjQgipGNTmkhBCyoFIJEJwcLDK+ZydnblxLgkh5GNAwSUhhBBCCNEY6tBDCCGEEEI0hoJLQgghhBCiMRRcEkIIIYQQjaHgkhBCCCGEaAwFl4QQQgghRGP+D8NY1OpGp/fPAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "grouped_by_station['diesel'].plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "96f887f0",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot:xlabel='station_uuid'>"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "grouped_by_station['diesel'].nlargest(20).plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "a1eba9ac",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot:xlabel='station_uuid'>"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAlkAAAEZCAYAAACkSDC2AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjQuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8rg+JYAAAACXBIWXMAAAsTAAALEwEAmpwYAABsIklEQVR4nO3dd1xV5R/A8c8FLnsIMpyoqYALVMwV5lY05y9H5k5t2DDNRLPhLytLzU3uMs20VEzN3JplbhyIW9kCgoM9Ltx7fn/wuyeuoLkIx/f9evmKzj3juc895znf86yjURRFQQghhBBCPFRmpZ0AIYQQQognkQRZQgghhBAlQIIsIYQQQogSIEGWEEIIIUQJkCBLCCGEEKIEWJR2AoQozGAwkJmZiVarRaPRlHZyhBDisaAoCnl5edjZ2WFmJvUnjwoJssQjJTMzkwsXLpR2MoQQ4rHk5eWFg4NDaSdD/J8EWeKRotVqgYKCwtLS8r72ER4eTt26dR9msp4qkn8PRvLvwUj+3R+dTseFCxfUMlQ8GiTIEo8UYxOhpaUlVlZW972fB9lWSP49KMm/ByP5d/+km8WjRRpuhRBCCCFKgARZwkRSUhLTp09n4MCBNGjQAG9vbw4dOnTX21++fJlhw4bRoEEDGjduTFBQEDdu3CjBFAshhBCPJgmyhInIyEgWL17M1atX8fb2vqdtExMT6d+/P7GxsYwePZpXXnmFPXv2MGzYMPLy8kooxUIIIcSjSfpkCRN16tTh4MGDODs7s3PnTt5888273nbBggXk5uayYsUKPDw8APD19WXo0KFs2LCBXr16lVSyhRBCiEeO1GQJE/b29jg7O9/Xttu3b6dNmzZqgAXQvHlzqlatypYtWx5WEoUQQojHgtRkiYfi6tWrXL9+vdih176+vvz111+lkCohhCh5BoNCSkYuSTezyMrJf6B9eVUug73t/U1fIx49EmSJhyIpKQkANze3Ip+5ublx/fp19Ho95ubmd7W/8PDwB0pPaGjoA23/tJP8ezCSfw/mUcs/g0EhPUdPSoaelMx8UjP1pGQW/J2SqSc1Mx+94eEcy6+aLT2buTycnYlSJ0GWeChyc3MBip1A1DjnTU5ODnZ2dne1v7p16973XDmhoaH4+/vf17ZC8u9BSf49mNLKv/QsHbFX00m4lknSjSySbmaTdDOLpJtZJN/MRm9QTNYv42CFu7MNtT1scXe2xd3FFg8XW+ysH2wy0KoVHLGxuvdbc25u7gM/nIqHT4Is8VAYAyKdTlfkM2MAZm1t/a+mSQghbpWakUvM1XRir6YTm5iu/n0zPddkPRdHazxcbPHydKZF/Yq4Odvi4WyLu4sNbs62WGnvrlZePN0kyBIPhbu7OwDJyclFPktOTqZs2bJ33VQohBAPQlEUUtL/DqbU/yamk5b594OgjZUFnh4O+Pt4UNnDAc9yDlRwtcPN2QathZRX4sFJkCUeCg8PD1xcXIqtrg4LC6NWrVqlkCohxJNAURSyc/PJyMojMyePjKw8MrLzyMzWkZGdT0a2jszsgmVXr2cRezWdjOy/5+azs7bAs5wjTeuWLwim/h9QlXWyltfQiBIlQZa4LzExMQB4enqqyzp06MDGjRu5evWqOo3DgQMHiIqKYvjw4aWSTiHEoy8jS8fpiOucjrzB+cvXWX/kLzVoyvz/v1u6RJnQaMDWWoudjRZXJ2sC6leksof9/4MpR5wdrCSYEqVCgixRxDfffAMUvCIHYMOGDYSGhuLo6MiAAQMAGDJkCAC7d+9Wt3v99dfZunUrgwYNYsCAAWRlZbF06VJ8fHzo3r37v/slhBCPrJT0XE5HXCc84hrhl68TnZiGooDWwgwnWzNczfSUcbCmopsD9rYFwZO9zW3+a2uJjZUF5mYSRIlHjwRZoojZs2eb/P+6desAqFixohpkFad8+fL88MMPfPnll3z99ddotVpatWrFhAkTih11KIR4OlxPzSb88nXCI65zOuIasVczALCyNKdWFRcCOvpQ55myeHk6cyrshIzOFE8MCbJEEefPn//HdQrXYBVWs2ZNli5d+rCTJIR4TCiKwtUbWQU1VZevczriOgnXMwGwtbagdrWytGnkSd3qZalRqQwW5vLiEfHkkiBLCCGeIoqikJWTT3qWjrRMHelZOtIzdaRn5ZGepUOXp0dvUDAoCgbD//8pFPr77+V6k3UU9AaFmMR0rqVkA+Bgq6XOM2Xp/Fw16lYvS7UKTtKsJ54qEmQJIcQT4mzkDaIT09QAKuP/gZMaTGUVBFOGO/Qi11qYYWamwUyjUf9rbqbBzIy/lxX+/Ja/vas406t1DepUd8XTwwEzCarEU0yCLCGEeMydjrjOyq3nOHX5mrrMUmuOo21Bx3BHO0uqlHPEwc4SB1stDraWOPx/uYOtJQ52BcvsbbSYS/OdEA+NBFlCCPGYuhBzkx+2nOX4hWTKOFgxontdmtWrgKO9pcxILsQjQIIsIYR4zERcSWXl1nMcPpOIg60lQ7vUpnPzaljfxzvvhBAlR65IIYR4TEQnpvHjtnPsD0vAzkbLgE4+dA14BtsHfCmxEKJkSJAlhBCPuCvJGfy47Rx/nriCtaUFfdt70aNlDextJLgS4lEmQZYQQjyiEq9nsnrHefYcjUWrNec/rWrwn9Y1cbSTyX2FeBxIkCWEEI+Y5JvZ/LTzPDsPx2BupqFri+q82KYGzg7WpZ00IcQ9kCBLCCFKiaIo5OsN5OYZ0OXpyczO47e/Itl6MBpQCGxWld5ta1LWyaa0kyqEuA8SZAkhxEOQdDOLvcfiOHPhJn9cOEZunh7d///l6vTo8gzk5ulNluvy9Nw6L6i5mYZ2jT3p084Ld2fb0vkyQoiHQoIsIYS4T3n5eg6dTmTHoRiOX0gCwNbKDLvr17DUmmNlaY6lhTnWlhY42v3//7VmBZ/9/5/l//9Zac2wsjSndrWylCtrV8rfTAjxMEiQJYQQ9yg6IY3th6PZczSO9CwdrmVs6NvOm3aNPYmLPIu/v39pJ1EI8QiQIEsIIe5CVk4ef564wo5DMZyPuYmFuYYmdcvToXEV/Lzc1Bcfx0WWckKFEI8MCbKEEOI2FEXhTOQNdhyOZt/JeHJ1ejzLOTCsW11a+1fCyd6qtJMohHiESZAlhBC3uJmWw+6jsew4HMOV5AxsrMxp1bAS7Rt74uXpjEajKe0kCiEeAxJkCSEEkK83cOxcEjsOR3P4zFUMBoVaVV3o1aYBAX4V5L2AQoh7JqWGEOKppSgK56Ju8vuxWP48EU96lo4y9lb0eL467Rp7UtnDobSTKIR4jEmQJYR46sReTWfvsTj2Ho8j8XoWllpzmtYpR0v/SjT0dsfC3Ky0kyiEeAJIkCWEeCrcSMvhj+NX2HsslktxqZhpwLemG/06eNO0bnlsreVly0KIh0uCLCHEEysrJ4+D4QnsCY0j7GIyBgVqVHJiWLe6PN+gIi6O8i5AIUTJkSBLCPFEydcbOH4+id9D4zh4OhFdnh53F1t6t/WiZcNK0s9KCPGvkSBLCPFEUBSFH7ed57f9kaRl6nCwtaTts5Vp3bAyPlVl2gUhxL9PgiwhxBPh8OlEVu84T6NaHnRqVpUG3u5oLaQDuxCi9EiQJYR47OXl61m68TSVPeyZOLSxjA4UQjwSpCQSJnQ6HdOmTSMgIABfX1/69OnDgQMH7mrb/fv3M3DgQJo0acKzzz5L3759+e2330o4xULAhj8iSLieyfDu9STAEkI8MqQ0EibGjx/P999/T7du3Zg4cSJmZmaMGDGC48eP33G7PXv28Morr5Cfn8/bb7/NqFGjMDMzY/To0axZs+ZfSr14Gt1Iy+HnnedpUqccDb3dSzs5QgihkuZCoQoLC2Pz5s1MmDCBIUOGANCjRw+6dOnC9OnTWbly5W23XblyJW5ubnz//fdYWloC0KdPH9q2bcuGDRvo3bv3v/EVxFPo+81nyMtXeKVbndJOihBCmJCaLKHaunUrWq3WJCCysrKiV69ehIaGkpSUdNttMzIycHJyUgMsAEtLS5ycnLCysirRdIun1/noG+w+Gkv355+hgqt9aSdHCCFMSJAlVGfPnqVatWrY2dmZLPf19UVRFM6ePXvbbRs3bszFixeZNWsWMTExxMTEMGvWLKKionjllVdKOuniKWQwKCz65RTODlb0aedV2skRQogipLlQqJKTk/Hw8Ciy3M3NDeCONVmvv/46MTExLFiwgPnz5wNga2vLN998w3PPPVcyCRZPtd+PxXIhJoV3X2ogr8QRQjySJMgSqpycHLTaojcrY3Nfbm7ubbe1tLSkatWqBAYG0r59e/R6PT///DPvvvsuy5Ytw9fX957SEh4efm+Jv0VoaOgDbf+0e9TzLzfPwOJNiVQsq8VRk0RoaHJpJ8nEo55/jzrJP/GkkCBLqKytrcnLyyuy3Bhc3alv1eTJkzl16hRr167FzKygFbpTp0506dKFL774gtWrV99TWurWrXvffblCQ0Px9/e/r23F45F/328+Q0aOgUmvPod3FZfSTo6JxyH/HmWSf/cnNzf3gR9OxcMnfbKEys3NrdgmweTkgloCd/fih8frdDrWrl1Lq1at1AALQKvV0qJFC06dOkV+fn7JJFo8deKvZfDL3su0aVT5kQuwhBCiMAmyhMrHx4fIyEgyMzNNlp88eVL9vDgpKSnk5+ej1+uLfJafn09+fj6Kojz8BIun0rcbT6O10DD4hdqlnRQhhLgjCbKEKjAwkLy8PJPJQ3U6HSEhITRs2FDtFB8fH8/ly5fVdcqWLYujoyM7duwwaW7MzMxkz549eHl5FdvXS4h7dex8EodOJ9K7rRcujtalnRwhhLgj6ZMlVH5+fgQGBjJ9+nSSk5Px9PRk/fr1xMfHM2XKFHW9oKAgDh8+zPnz5wEwNzfnlVdeYdasWfTt25du3bphMBhYu3YtiYmJBAUFldZXEk+QfL2BJRtOUb6sHT1aVi/t5AghxD+SIEuYmDp1KrNmzWLDhg2kpqbi7e3NokWL/rEj6htvvEGlSpVYvnw5wcHB6HQ6vL29mTdvHu3bt/+XUi+eZL/tjyT2agYThzZGa2Fe2skRQoh/JEGWMGFlZUVQUNAda59WrFhR7PKuXbvStWvXkkqaeIqlZuTy47bz1Pdyo0mdcqWdHCGEuCvSJ0sI8cj7Yes5snPzGdG9LhqNprSTI4QQd0WCLCHEIy3iSirbDkbxwnPV8CznWNrJEUKIuyZBlhDikaUoBe8ntLex5OUO3qWdHCGEuCcSZAkhHll/hcVzOuI6AzvXwt7WsrSTI4QQ90SCLCHEIylHl8+3m05TrYIjHZpUKe3kCCHEPZMgSwjxSFq/5xLJN7MZ0aMe5mbS2V0I8fiRIEsI8chJupnF2j2XeM6vAvWqu5Z2coQQ4r5IkCWEeOQs+/UMKAqvdKlT2kkRQoj7JkGWEOKRcjriOn+euMKLbWri7mJb2skRQoj7JkGWEOKRoTcoLFp/CtcyNvyndY3STo4QQjwQCbKEEI+MHYeiiYhP5ZUudbC2lLd+CSEebxJkCSEeCXn5BlZuPUedZ8oSUL9CaSdHCCEemARZQohHwsmLyaRk5PKf1jXk/YRCiCeCBFlCiEfCnyeuYGdtQQMv99JOihBCPBQSZAkhSl1evp5D4Qk0rVcerYUUS0KIJ4OUZkKIUnf8fDKZOfm0qF+xtJMihBAPjQRZQohS9+eJKzjYavGr6VbaSRFCiIdGgiwhRKnKzdNz6HQCzepVwMJciiQhxJNDSjQhRKk6du4q2bl6Avxk2gYhxJNFgiwhRKnadyIeRztLfGvIi6CFEE8WCbKEEKUmR5fP4TOJNPetgLk0FQohnjBSqgkhSk3o2SRydHpayAzvQognkARZQohS8+eJK5RxsKLOM9JUKIR48kiQJYQoFdm5+Rw5e5XnfCtgbiav0RFCPHkkyBJClIojZxLR5cmoQiHEk0uCLCFEqdh3Mh4XRytqVytb2kkRQogSIUGWMKHT6Zg2bRoBAQH4+vrSp08fDhw4cNfbb9q0iV69elG/fn0aN27MgAEDCAsLK8EUi8dRVk4eR89e5Tm/iphJU6EQ4gllUdoJEI+W8ePHs337dgYNGkSVKlVYv349I0aMYMWKFTRo0OCO286cOZMlS5bQrVs3+vbtS1ZWFufOnSM5OflfSr14XBw+nUhevoEWfvKuQiHEk0uCLKEKCwtj8+bNTJgwgSFDhgDQo0cPunTpwvTp01m5cuVttz127BgLFy5k7ty5tG/f/l9KsXhc/XkiHlcna7yrOJd2UoQQosRIc6FQbd26Fa1WS+/evdVlVlZW9OrVi9DQUJKSkm677fLly6lXrx7t27fHYDCQmZn5byRZPIYysvM4dj6JgPrSVCiEeLJJkCVUZ8+epVq1atjZ2Zks9/X1RVEUzp49e9ttDxw4QL169ZgxYwb+/v40bNiQNm3asHHjxpJOtnjMHApPIF9vkFGFQognnjQXClVycjIeHh5Flru5uQHctiYrNTWVlJQUNm/ejLm5OWPHjqVMmTKsXLmS999/Hxsbm3tuQgwPD7/3L1BIaGjoA23/tCvJ/Nv8xzWc7MxJT44g9FpkiR2nNMn592Ak/8STQoIsocrJyUGr1RZZbmVlBUBubm6x22VlZQGQkpLCzz//jJ+fHwDt27enffv2BAcH33OQVbduXfW49yo0NBR/f//72laUbP6lZ+mIWL2V7s9Xp1GjOiVyjNIm59+Dkfy7P7m5uQ/8cCoePmkuFCpra2vy8vKKLDcGV7cLeozLK1WqpAZYAJaWlnTs2JFz585JHy0BwMFTCegNCi3qy6hCIcSTT4IsoXJzcyu2SdA4BYO7u3ux25UpUwZLS0tcXYu+f87V1RVFUcjIyHi4iRWPpT9PXKFcWVuqV3Iq7aQIIUSJkyBLqHx8fIiMjCxS63Ty5En18+KYmZlRq1Ytrl69WuSzxMREzM3NcXKSm+rTLjUjl5OXrtGifkU0GhlVKIR48kmQJVSBgYHk5eWxZs0adZlOpyMkJISGDRuqneLj4+O5fPlykW0TEhL466+/1GUZGRls2bKFBg0aYG1t/e98CfHIOnAqAYNBIUAmIBVCPCWk47tQ+fn5ERgYyPTp00lOTsbT05P169cTHx/PlClT1PWCgoI4fPgw58+fV5f169ePNWvW8PbbbzNkyBAcHR1Zt24d6enpjBkzpjS+jnjE7Dt5hYpudlSr4FjaSRFCiH+FBFnCxNSpU5k1axYbNmwgNTUVb29vFi1a9I+jfWxsbFi+fDlTp07lhx9+ICcnhzp16vDdd9/JSCHBzfQcTl26Ru+2XtJUKIR4akiQJUxYWVkRFBREUFDQbddZsWJFscvd3NyYNm1aSSVNPMYOnErAoCCjCoUQTxXpkyWEKHF/nrhCZQ97PMs5lHZShBDiXyNBlhCiRN1Iy+F0xHVa+MmoQiHE00WCLCFEifrrZDyKAgHSVCiEeMpIkCWEKFH7Tl6hanlHKntIU6EQ4ukiQZYQosRcS8nmTOQNAvwqlHZShBDiXydBlhCixPwVFg9IU6EQ4ukkQZYQosT8eeIKz1RwoqKbfWknRQgh/nUSZAkhSkTSjSzOR98koL40FQohnk4SZAkhSsS+kwVNhTIBqRDiaSVBlhCiROw7eYUalctQrqxdaSdFCCFKhQRZQoiHLvF6JhdjU2ghowqFEE8xCbKEEA+dsakwwE+aCoUQTy8JsoQQD92fJ67g7emMu4ttaSdFCCFKjQRZQoiHKj45g4grqTI3lhDiqSdBlhDiofrz5BUAnvOV/lhCiKebBFlCiIdq34l4alV1wc3ZprSTIoQQpUqCLCHEQxN7NZ2ohDSZgFQIIZAgSwjxEO07GY9GI02FQggBEmQJIR6ifSevULtaWco6SVOhEEJIkCWEeChSM3KJSUynce1ypZ0UIYR4JEiQJYR4KKIT0wCoVsGxlFMihBCPBgmyhBAPRVRCQZBVtbwEWUIIARJkCSEekuiEdBztLCnjYFXaSRFCiEeCBFlCiIciOiGNquUd0Wg0pZ0UIYR4JEiQJYR4YAaDQnRiGlWkqVAIIVQSZAkTOp2OadOmERAQgK+vL3369OHAgQP3vJ8RI0bg7e3N559/XgKpFI+aqzeyyNHppT+WEEIUIkGWMDF+/Hi+//57unXrxsSJEzEzM2PEiBEcP378rvfx+++/c/To0RJMpXjUSKd3IYQoSoIsoQoLC2Pz5s2MHTuWcePG0bdvX77//nvKly/P9OnT72ofOp2OKVOmMGzYsBJOrXiURCemodGAp4dDaSdFCCEeGRJkCdXWrVvRarX07t1bXWZlZUWvXr0IDQ0lKSnpH/exfPlycnJyJMh6ykQlpFHOxQ5rK4vSTooQQjwyJMgSqrNnz1KtWjXs7OxMlvv6+qIoCmfPnr3j9snJyXzzzTeMHj0aGxt5rcrTJDohjSrlpRZLCCEKkyBLqJKTk3F3dy+y3M3NDeAfa7JmzJhBtWrV6N69e4mkTzyadHl64pMzZGShEELcQur2hSonJwetVltkuZVVweSSubm5t902LCyMX375hRUrVjyUeZLCw8MfaPvQ0NAHTsPT7F7yL/6GDoMChuxrku//J/nwYCT/xJNCgiyhsra2Ji8vr8hyY3BlDLZupSgKn3/+OR06dKBRo0YPJS1169a97fH+SWhoKP7+/g8lHU+je82/lCMxQBJtnqtPJXdpMpTz78FI/t2f3NzcB344FQ+fBFlC5ebmVmyTYHJyMkCxTYkAO3bsICwsjNGjRxMXF2fyWUZGBnFxcbi6umJtbf3wEy1KXVRCGpYWZpR3tS/tpAghxCNFgiyh8vHxYcWKFWRmZpp0fj958qT6eXHi4+MxGAwMHjy4yGchISGEhISwePFinn/++ZJJuChV0QlpVC7ngLmZvE5HCCEKkyBLqAIDA/n2229Zs2YNQ4YMAQrmvQoJCaFhw4Z4eHgABUFVdnY21atXB6BNmzZUqlSpyP7efPNNWrduTa9evahTp86/9j3Evys6MY36XsXXcgohxNNMgiyh8vPzIzAwkOnTp5OcnIynpyfr168nPj6eKVOmqOsFBQVx+PBhzp8/D4Cnpyeenp7F7rNy5cq0a9fuX0m/+PelZuRyIy1XZnoXQohiSJAlTEydOpVZs2axYcMGUlNT8fb2ZtGiRdIRVRQrOrHgdToyfYMQQhQlQZYwYWVlRVBQEEFBQbddZ8WKFXe1L2NNl3hyyTsLhRDi9mQyUiHEfYtOSMfRzhJnh/ubbkMIIZ5kEmQJIe5bdEIaVcs7PpQJaIUQ4kkjQZYQ4r4YDArRiWnSH0sIIW5DgiwhxH1JuplFjk5PlXISZAkhRHEkyBJC3Je/O73Lq3SEEKI4EmQJIe6LMcjylJosIYQolgRZQoj7EpWQRrmytthYyUwwQghRHAmyhBD3xTiyUAghRPEkyBJC3DNdnp74a5kyslAIIe5AgiwhxD2LvZqOwaBITZYQQtyBBFlCiHumvrNQOr0LIcRtSZAlhLhnUQnpaC3MqOBqV9pJEUKIR5YEWUKIexYVn0plDwfMzaUIEUKI25ESUghxz6ITZWShEEL8EwmyhBD3JC1Tx420XAmyhBDiH0iQJYS4J9H/n+ldpm8QQog7kyBLCHFP/n5noQRZQghxJxJkCSHuSXRiGg62ljg7WJV2UoQQ4pEmQZYQ4p5ExRd0etdoNKWdFCGEeKRJkCWEuGsGg0J0YhpVyjuUdlKEEOKRJ0GWEOKuJd3MIkenp2p5p9JOihBCPPIkyBJC3LW/O71LTZYQQvwTCbKEEHfNOH2Dp7yzUAgh/pEEWUKIuxaVkEa5srbYWFmUdlKEEOKRJ0GWEOKuRSemUUVqsYQQ4q5IkCWEuCu6PD1XkjNlElIhhLhLUucvTOh0OmbPns2GDRtIS0vDx8eH0aNH06xZsztut337dn777TfCwsK4fv065cuXp3Xr1owcORIHB+kk/SSIvZqOwaDI63SEEOIuSZAlTIwfP57t27czaNAgqlSpwvr16xkxYgQrVqygQYMGt93uo48+wt3dne7du1OhQgXOnz/PihUr+PPPP1m3bh1WVjI7+OMuOlFepyOEEPdCgiyhCgsLY/PmzUyYMIEhQ4YA0KNHD7p06cL06dNZuXLlbbedM2cOTZo0MVlWt25dgoKC2Lx5M//5z39KMuniXxCVkI7WwowKrnalnRQhhHgsSJ8sodq6dStarZbevXury6ysrOjVqxehoaEkJSXddttbAyyAdu3aAXD58uWHn1jxr4tOSKOyhwPm5lJsCCHE3ZDSUqjOnj1LtWrVsLMzranw9fVFURTOnj17T/u7du0aAM7Ozg8tjaL0RCWkSVOhEELcA2kuFKrk5GQ8PDyKLHdzcwO4Y01WcRYvXoy5uTkdOnS457SEh4ff8zaFhYaGPtD2T7tb8y8rV8+NtBzM9WmSt3dB8ujBSP6JJ4UEWUKVk5ODVqststzYaT03N/eu97Vp0ybWrl3La6+9hqen5z2npW7duvfdWT40NBR/f//72lYUn3+nLl0DEghoVJuGPu6lk7DHhJx/D0by7/7k5uY+8MOpePikuVCorK2tycvLK7LcGFzdbdBz9OhRJk6cSKtWrRg1atRDTaMoHcZ3FlaRdxYKIcRdkyBLqNzc3IptEkxOTgbA3f2fazDOnTvHG2+8gbe3NzNnzsTc3Pyhp1P8+6IT03CwtcTF0bq0kyKEEI8NCbKEysfHh8jISDIzM02Wnzx5Uv38TmJiYhg+fDguLi4sXLgQW1vbEkur+HcZO71rNJrSTooQQjw2JMgSqsDAQPLy8lizZo26TKfTERISQsOGDdVO8fHx8UWmZUhOTuaVV15Bo9GwdOlSXFxc/tW0i5JjMCjEJKZJU6EQQtwj6fguVH5+fgQGBjJ9+nSSk5Px9PRk/fr1xMfHM2XKFHW9oKAgDh8+zPnz59Vlw4cPJzY2luHDhxMaGmoyOsjT0/OOs8WLR1vSzSyyc/UyfYMQQtwjCbKEialTpzJr1iw2bNhAamoq3t7eLFq06B9H+5w7dw6AJUuWFPmsZ8+eEmQ9xv7u9C5BlhBC3AsJsoQJKysrgoKCCAoKuu06K1asKLKscK2WeLJE/z/I8vSQ5kIhhLgX0idLCHFHUQlpeLjYYmtddA41IYQQtydBlhDijqIT5XU6QghxPyTIEkLcVl6+nivJmRJkCSHEfZAgSwhxW7FXMzAYFOn0LoQQ90GCLCHEbRlHFkpNlhBC3DsJsoQQtxWVkIbWwowKrnalnRQhhHjsSJAlhLit6IQ0Krs7YG4uRYUQQtwrKTmFELcVlSCv0xFCiPslQZYQoljpWTpupOVQtbxTaSdFCCEeSxJkCSGKJZ3ehRDiwUiQJYQoVrT6zkJpLhRCiPshQZYQolhRCWk42GpxcbQu7aQIIcRjSYIsIUSxCjq9O6LRaEo7KUII8ViSIEsIUYTBoBCTmEbVctIfSwgh7pcEWUKIIpJuZpGdq5fX6QghxAOQIEsIUYSx03vVChJkCSHE/ZIgSwhRRFRiQZDl6SEjC4UQ4n5JkCWEKCI6IR0PF1tsrbWlnRQhhHhsSZAlhCgiKiFVJiEVQogHJEGWEMJEvl7hSnKmdHoXQogHJEGWEMJEcloeBoMi0zcIIcQDkiBLCGEiKSUPkNfpCCHEg5IgSwhh4mpKHhbmZlR0sy/tpAghxGNNgiwhhImklDw8PRwwN5fiQQghHoSUokIIE1dT8qWpUAghHgIJsoQQqvQsHenZepm+QQghHgIJsoQJnU7HtGnTCAgIwNfXlz59+nDgwIG72vbq1auMGjWKRo0a0bBhQ0aOHElsbGwJp1g8TFH/f52OTN8ghBAPToIsYWL8+PF8//33dOvWjYkTJ2JmZsaIESM4fvz4HbfLzMxk0KBBhIaG8vrrr/POO+9w5swZBg0aRGpq6r+UevGg1HcWSpAlhBAPzKK0EyAeHWFhYWzevJkJEyYwZMgQAHr06EGXLl2YPn06K1euvO22P/74I9HR0YSEhFC7dm0AWrRoQdeuXVm2bBmjRo36N76CeEBRCWnYWJrh4mhd2kkRQojHntRkCdXWrVvRarX07t1bXWZlZUWvXr0IDQ0lKSnptttu27aN+vXrqwEWQPXq1WnWrBlbtmwp0XSLhyc6IQ33MhZoNJrSTooQQjz2pCZLqM6ePUu1atWws7MzWe7r64uiKJw9exZ3d/ci2xkMBs6fP0/fvn2LfFavXj3++usvsrOzsbGxKbG0AyiKws87L3D6wg3+uHAMg6JgMBT80///v0WWFfp/499Ps6iENBpWty3tZAghxBNBgiyhSk5OxsPDo8hyNzc3gNvWZKWkpKDT6dT1bt1WURSSk5Px9PS867SEh4ff9bpGBkVhz5Ek0rIMmCXGo9GAmUaDmRnq3wX/Bc3/l6t/a/5e52lWvZwVftXsCA0NLe2kPNYk/x6M5J94UkiQJVQ5OTlotdoiy62srADIzc0tdjvjcktLy9tum5OTc09pqVu3rrrtvXi2UUEB7e/vf8/bigKSfw9G8u/BSP7dn9zc3Pt6OBUlS/pkCZW1tTV5eXlFlhuDqNsFPcblOp3utttaW0tHaiGEEE8XCbKEys3NrdgmweTkZIBi+2MBlClTBktLS3W9W7fVaDTFNiUKIYQQTzIJsoTKx8eHyMhIMjMzTZafPHlS/bw4ZmZmeHl5FVtVHRYWRpUqVUq807sQQgjxqJEgS6gCAwPJy8tjzZo16jKdTkdISAgNGzZUO8XHx8dz+fJlk207duzIiRMnOHPmjLosIiKCgwcPEhgY+O98ASGEEOIRIh3fhcrPz4/AwECmT5+ujgZcv3498fHxTJkyRV0vKCiIw4cPc/78eXXZyy+/zJo1a3j11VcZOnQo5ubmLFu2DDc3N3ViUyGEEOJpIkGWMDF16lRmzZrFhg0bSE1Nxdvbm0WLFv3jaB97e3tWrFjBF198wTfffIPBYKBJkyZMnDgRZ2fnfyn1QgghxKNDgixhwsrKiqCgIIKCgm67zooVK4pdXq5cOebMmVNSSRNCCCEeKxJkiUeKohTMuF7cdBD34nZzeom7I/n3YCT/Hozk370zlpnGMlQ8GjSK/CLiEZKens6FCxdKOxlCCPFY8vLywsHBobSTIf5PgizxSDEYDGRmZqLVauUlxUIIcZcURSEvLw87OzvMzGTigEeFBFlCCCGEECVAwl0hhBBCiBIgQZYQQgghRAmQIEsIIYQQogRIkCWEEEIIUQIkyBJCCCGEKAESZAkhhBBClAAJsoQQQgghSoAEWaXg5MmT9OnTBz8/P7y9vYmLiyt2vfHjx9OmTZt73n9ERASDBw/G19cXb29v6tSpg7e394MmG4BDhw7h7e3NoUOHHsr+SktSUhJvvvkmjRs3xtvbm5CQkNJO0j3z9vZm7ty5pZ2MO1q4cCFt2rShVq1aDBw48I7rtmnThpEjR/5LKSsZc+fOVa+1wn+XxP4fZd7e3nz++ef3vf3tzoV7OZ+eBsayvmHDhmq5/KBl26N4HQ4cOPBf+b1///13unbtSt26dR/adXZX7y5MSkpi+fLlnDx5kvDwcLKysli+fDlNmjQpsm56ejrBwcFs27aN5ORkypYti7+/PzNmzHighI4YMYI//viDQYMGMXHixCLH/Oabb9i1axeJiYm4uroSEBDAm2++iYeHh7peWFgYISEhhIWFceHCBfLy8jh//vwDpete5eXlMWrUKOzt7Zk4cSJWVlbs3buXH374gbi4OCpUqMCgQYPo37+/yXbFpX337t107tyZnJwcfvnlF2rVqgUUBGfx8fEYDAaqVq1Kv379cHZ2RqfTMXv2bEJCQkhJSQHA0tKS5557jgkTJlC5cuW7/h7Xrl3Dz8+PnJwcRo8ezf79+7l8+TKpqam4u7vTpEkTmjRpwrp16zh9+jQA1atX56233qJly5Ym+0pKSmL27Nns3buX1NRUPDw8aNu2LRMmTAAKZoFfv349O3bs4MyZM1y/fl19P1edOnUYM2YMzZo1AyA7O5uQkBB27tzJxYsXyczMpGrVqvTp04fGjRszd+5cjh07xrVr11AUhRYtWtCxY0eeffZZNS3vv/8+J0+eJCcnB0VRKF++PN9++y3ffvst+/fv5/r163h4eFC1alX27t1bbP6EhYWRl5dHx44duXbtGsHBwWg0GubNm8f58+fRaDQoioLBYADAxsaG5s2bM27cOKpUqQIU3FDnzZt3x99h6dKlvP3222raFy9ezG+//abmkbW1NTVq1GDgwIF0795dnUV/8eLFTJ8+nfLly2Nvb09ERATm5uYoikJ+fr6av3Z2dkyYMIHIyEj++usvYmJisLa2xsrKiszMTNLT04GC86ht27bUrFmTP/74g6ioKNLT08nPz6d8+fKUL1+eY8eO4ePjA4CLiwtdu3ZVf2MAvV5PeHg4TZo0IScnB29vb9555x0CAgJMvnNcXBxt27a9Y77cDQuLguLPycmJnJwcMjMzH2h/v/32m/r34sWL1d/ut99+Y/fu3Zw6dYqoqKg77qN379589tln//gdP/zwQz777DMAPvvsM7Zs2cLNmzfR6/UAaDQaypYtS/369fniiy9wcnICCt4J+N1337Fq1SqSkpJQFAUzMzNq1KjBe++9R8uWLZk0aRKrVq2iXLly2NrakpiYiJmZGVWrVi1yHkHxZRPAlStX6NOnD+fOncPGxoaWLVsSFBRE2bJl1XwZPXo0lpaW+Pr6cvLkSfLy8tBqtSiKgqOjo8l3/uOPP5gxYwb/+c9/aNKkCW5ubgDMnDmTffv2ERcXR3Z2NhUrVuSFF17glVdewdbWVt0+PT2dGTNmsGPHDlJTU3FyciI5ORkfHx82bNhgcqyBAwdy+PDhIvneuXNnZs6cCcCBAwfYuHEjx44dIzExETc3N5o1a8Y777yjpq2wpKQk5syZY1KGdOjQgVdffRVHR0dOnjxJ37597+ndgxYWFpQtW5b33nsPe3t7qlevzpgxY0wegidMmKBeZ7/99hvVq1dX897BwYGjR4/e9fEKu9M5unjxYp5//vn72u/DdOjQIQYNGnTbz999913eeOMNAG7cuMHo0aOpVasWkyZNQqvVArBx40bWrl1b5P721ltvUbFixX9Mw10FWZGRkSxevJgqVarg7e3N8ePHi10vLS2N/v37k5aWRu/evSlXrhzJyckcOXLkbg5zW7///vttTwSDwcCwYcO4ePEi/fr1o1q1akRGRrJq1SoOHjzIr7/+iqWlJQB79+5lzZo1eHt7U7lyZSIiIh4oXfcjJiaGhIQEvvzyS3r27Mnq1av59NNPCQwMZOjQoRw9epRPP/20yAtSi0v7V199VeT1CTk5OZw8eZJu3bqxceNGJk+eTOPGjQEYM2YM27Ztw9bWFltbWxwdHUlMTOTEiRMMGjSIX375RS2M/8mqVavUY0dGRuLh4UHLli1xcnIiPj6e77//npCQEFq1asW4cePQ6/VcunSJxMREk/1cuXKFfv36YW9vz6BBg3B2diYxMZHIyEh1nezsbD744APq16+Pk5MT165d45lnnuHSpUtEREQwYsQIVqxYQYMGDYiNjWXy5Mk0a9aMIUOGYG9vz759+9SLxt3dnQEDBrBw4UKcnZ3Zu3cvTk5OvPjii2RlZfHSSy9x9epVAKpUqUJ8fDwJCQl0794dOzs7+vfvT7ly5Thz5gyrV68GYPTo0ZQvX97ke2m1WmbNmkVWVhYA4eHhLFiwgKZNm1KvXj01APTw8KBmzZocPnyYPXv28Ndff7Fu3TqqV69O+/bt8fT0BGDHjh3s2LGDF198kV27dpGbm0t2drZJwBoZGcny5cuxsrLC3d2dq1ev0qdPH+Lj4wkKCiI6OppRo0aRnJzM/Pnz0Wq1JCQk0LRpUy5evIiLiwvJyckA2NrakpWVRU5ODh999BE2NjZ07tyZXr16MXfuXBITE1EUBVdXV6pUqcLx48fZvn07f/75J+3btycwMJB9+/axb98+EhISAChbtix+fn5cunSJmJgYQkND1bSnpaWpx37ttddwdXVly5YtvPrqqyxdulQNogvr1q0bKSkpHDhwgLy8PCwsLLC2tqZjx47cuHGDa9euUadOHZydnbGxsWHGjBnUqFGDyMhIzM3NqVy5MpcvX8bNzY1z584B0KxZM5ycnNi7dy9lypSha9eu1KhRQz3m5cuXWbhwIQADBgzA19dX/azwA938+fOxsLAgPz+fVatWER4eTt26dYmLi8PW1pZWrVqp+X/48GGcnJy4fv06zz33HFAQhE6dOlXdX3p6OlOnTkWn06EoiroewIkTJ7h27Rrm5uZq8G5mZoa1tTV6vZ6cnBz1un7//ffZsWMHBoOBOnXq4ObmxuHDh4mMjOTSpUt4eHiwdu1aLC0tyc7Opnv37pQvXx6DwcD+/ftNziOj25Wru3btol69eowdO5aMjAyWL1/OmTNnWLt2LQDTpk1Tz7OjR49SpkwZUlJSeO655zh69GiRMvDw4cNYWFgwefJkNUA2Xlv169ene/fuWFtbc+7cORYuXMihQ4dYvnw5Go2G/Px8hg4dyrlz5xgwYAAuLi7MmjULgNTU1CLnFkCFChV49913TZYVvqlOmzaN1NRUAgMDqVq1KrGxsfzwww/s2bOHDRs2qMEkoJYtWVlZJmXId999x7Fjx1i5ciWfffYZNjY2ZGVlYW1tzaeffqpuv337dnbu3Mmnn36KtbU1UPDAPnHiRPr06WPyUG48lwcPHkydOnVM0u/h4UFOTo6a9w9Dt27dijwIGR+mSlv16tVNriOjjRs3sm/fPpPryFiB9O6776r3TCjIz1vvbz///DO///47GzduLDagNqHchfT0dOXGjRuKoijKjh07FC8vL+XgwYNF1vvoo4+UNm3aqOs+DLm5uUqHDh2UuXPnKl5eXspnn31m8vmJEycULy8v5YcffjBZvmLFCsXLy0s5cOCAuiw5OVnJzs5WFEVRPvvsM8XLy+uhpfNuHT58WPHy8lJ27NihZGdnK40bN1beeOMNk3Xee+89pUGDBsqYMWOU1q1b3zbtderUUWbMmKF4eXkpZ86cURRFUa5cuaJ4eXkpY8aMMVl+8uRJxcvLS3nttdcUb29v5fTp00pOTo7Srl07pWfPnkqtWrWUWbNm/WP6Dx48qHh5eSm1atUqcmyjmJgYpU6dOoqXl5eyZMmSO+7vlVdeUXr37q1+t+Lk5uYqoaGh6nf47rvvFEVR1HMiICBAefnllxVFUZTr168rFy5cKLKPnj17Kl5eXsoff/yhKIqieHt7K5999pny9ttvK7Vr11Z0Op2yefNmxcvLS1m3bp2Sn5+vKIqidOvWTXn22WcVLy8v5eeffzbZ57BhwxQvLy9lz549RY4XERGh1KlTR03j888/r/Ts2VPdb2hoqDJt2jTFx8dHiYyMVLZt26Z4eXkptWvXVoKCgorsb86cOYqXl5dy/vx5xdvbW/nwww8VLy8vZc6cOeo6d7pOX3vtNaVBgwaKwWBQgoKClAEDBii1atVS6tevr+Tk5CihoaHKwoULFS8vL/X8bN68ueLl5aW0atVK6dKli6IoippHAQEBio+Pj5rvX375peLl5aX4+Piov8/48eOVWrVqKbVr11a8vLyUDRs2qL9nQECA0r9/fzXtxmP369dPXabX65UXX3xR6datm0lexMbGKl5eXsrXX3+t1KlTR2natKni5eWldO7cuci6Rsbz4siRI4qXl5cyf/58NY3GdPv4+CivvvqqoiiK8tdffyleXl7KmjVrTPZjPP99fX2VnJyc2/5OAwcOVFq1aqV4eXkp8fHxJufTgAEDTLb59ttvFS8vL8XPz6/YfSqKogQFBSkDBw5U6tatq3h5eZmsl56ersycOVNp1KiRsmrVKsXLy0v55JNPFC8vLyUsLExdLzk5Wb12jb+RoijK7t27FS8vL2Xt2rXKgAEDlPHjxyutW7cuUi4piul5VHi/t5ZNXl5eSqNGjRSdTqeud/bsWfX8mDNnjtKhQwfl7bffVry8vJTJkycrqamp6jld3PHHjx+v+Pv7F5s/tzLmqfH7G8/b9evXm+RnkyZNlFq1aim5ubkm2w8YMOC255LR4cOHFb1eX2TZrddl4ePfWlYYr5vFixcrjRs3ViZPnqx4eXkpDRs2NFnPeF6lpqaqy4xlfeHfUlEKyjbjNVwcY96PGTOm2Py83W9/K+N1eOvxS8KAAQOKXDcPon379kqHDh1Mlq1fv77Y+1lxwsPD7+r+piiKclc1Wfb29v+4TlpaGuvXr2fChAk4OzuTm5uLRqNRa5Fudfz4cYKDgzlx4gR6vZ4qVarQv39/evfubbLe8uXLycnJYdiwYcX2P8nIyAAweWoAcHV1BVCj/sLL/klKSgoLFy5Uq6A1Gg0NGzZk7NixJhG6Tqdj/vz57N27l+joaPR6PbVr1+add96hadOmRfY7fvx41q9fD8Cbb76pLn/55ZfZuXMns2bNIjo6Gnd3dzIzM9UalVvTbmxiGjBggNq0BKbNS7/++isAPXr0AKBmzZpotVqSkpKoX78+tWvXBqBXr17MnDmTRo0asWXLFpMn1MTERD799FP279+PjY0NXbt2VSP/9u3bmxy7sNWrV+Po6Mj169dJS0sjIyNDPYdycnJYuHAhmzdv5sqVK+Tn59OoUSNSU1NRFAWtVmvylAoFTVENGzZk8uTJmJmZ8d133zF9+nTKlCkDQK1atfjjjz+4dOkS69atK/Z3q1y5MqdPn2bnzp0MHz4cKDi3jJ5//nn1ifbq1auYm5urnxlr7MqVK2eSLuN3srS0JCMjA1tbW8zMzPj9998ZN24cBoOBJUuWqHk5cuRIdb8NGzakYsWKLF68mO3bt9O8eXMA3N3duXz5sslxdDodf/75JwD/+c9/UBSF5s2b8/PPP5usd+TIERYuXMi5c+fUJgfjOVSxYkWys7M5duwYGzduZOrUqRw+fBhHR0esrKxo2LAhixYtws3NjczMTH777TccHBzU2qAdO3YQERGhXm9JSUnY2NgQGhpK3bp11afiKlWqsGXLFqZMmVLkvDhw4ADt27dn06ZNpKenc/z4cWrVqoWZmRn5+fkAxMfHs23bNoKDg4mMjMTBwYHr16/TokULbt68iZubm1p7tHPnTmrVqkVYWBhQ0ERmMBjQ6XTqi3KhoCZ88eLFnDlzRm3KMp477du3JyQkBDs7O3Q6HampqWRmZlKtWjXs7e2ZNGkS//3vfylXrhwtW7ZUm5Xr16/P4cOHmTlzJhcvXqRMmTJYWFioNbUNGzYkNjYWoEgtZ0JCAi+99BKRkZFkZ2fj4uICgL+/P1ZWVup6R48eZcqUKZw/f568vDwGDRqkNgMVXs/W1pa1a9fSp08ftZwwfj9jcy78XVZaW1szaNAgFEUhMzNT3ebcuXOEh4fz9ddf89JLLxX5/aCgdiczM5P69euTk5MDFFwX06dPV/PGyNPTk82bNzN//nzi4+Px8fGhYsWKbNiwgYiICGbOnMmCBQsAGDVqlHrOKoWay/bu3cvXX39t0q3D2FdmypQpdOnSpdgy2Fjzafz+x44dQ6PR0KlTJ8LCwti4cSPr1q1j7Nix3Lx5k0OHDtGiRQv1GOnp6cTExNCwYUP0ej0NGjRg7Nix1K1bV13H+H0TEhKYOXMmf/75J+np6ZiZmfHnn3+qzfiF8/5296lvv/2Wt956S+3GAQXN59nZ2Sb3X0VRyMjI4NtvvyU4OFjNhylTpqg1gUbGe8zp06fVMjU+Pp4lS5Ywc+ZMtm/fzp0Y8z4yMpKqVasyduzYIl09jLKysrCwsLjt/X7nzp38/PPPnDlzhpSUFMqVK0fPnj15/fXXTcpagJ9++onFixeTlJSEl5cX48ePL7K/e733FhYWFkZ0dLTJ71O4edh4z+zZsydffvllsfuoUKECUBD3/JO7CrLuxtGjR9HpdLi6ujJkyBAOHjyImZkZTZs2ZdKkSWqzBxS0rY8cORIPDw+GDBlC2bJlOX/+PL///rtJkJWcnMw333zDxx9/jI2NTbHHrVOnDra2tsyePRsnJyeeeeYZIiIimD17Nk2aNMHPz++ev0tsbCw7d+4kMDCQSpUqce3aNX766ScGDBjA5s2b1WaBjIwM1qxZQ5cuXejduzeZmZmsXbuW4cOHs2bNGrWPlFHfvn3x8PBgwYIFDB48mMTERLZt20ZGRgajR49W+0Vcu3aNxYsXc+nSpWKrdC9cuADAyJEj2blzp7q8ffv2ODg4MGXKFKpUqUJ0dDRdu3alRYsWrFixgqpVq3Lx4kX69u2rbuPr64uiKLi7u3P06FGys7OxsbEhJyeHwYMHk5CQwKBBg3Bzc2PDhg1s3boVKDgRb968aZKulJQU9Ho9u3fvVvtsrFixggULFuDq6sorr7zC77//zuHDh+natSu1atVi69atpKamMmjQIKKiotBqtbRp04ZJkyapNx9jXq9btw6DwUCrVq2oVasWx44dY8OGDVSuXBlFUfjrr79u+7t17NgRKChwRo8ezcyZM9VzxXjTycvLIzg4mFmzZpGbm8tLL71Eenq6WlAHBwfj4OCgVvXv27cPKCjMsrKysLKyokaNGmoftFdeeYW8vDxWrFgBYFJAQ0GTopubG/v27WP37t1YWFiQm5uLs7OzyXoTJ07k5MmTAGqQMHr0aAD1RhcSEsIHH3xAq1ateP/99zl27Bi//vorn376KampqYSEhNCwYUO+/PJLevTooTZ7FO5bk5eXpzYxnT59Wu3fY2xqOnPmDP7+/mqTlF6vx8nJiU6dOqmda9PT00lISODjjz9mw4YNhIWFqTfNQ4cOUb9+ffV49vb2ZGVl4erqqgYn169fZ+LEifTv35/OnTszZ84coCD4fPPNN7l27RqbN28GKBKMRkREoNfrqVevHgBubm7Ur1+fHTt24OPjw4gRI1i0aBEODg6cP3+ejIwMwsPDgYIHl9zcXE6ePEnDhg0xMzNDURSsrKz44IMPiI+P57ffflPz5NixY2qwXr58eZP+TQaDgTVr1ty2j1diYiLPPvssrVq1Ij4+Xm0+K3x+nD9/nmHDhuHi4kLZsmVxcXFh3bp1xe7v4sWLJCcn4+rqyjfffAMUNFeamZmZ3MAqVaqEVqslLy+Pjz76iO3bt5OWloaFhQUuLi7s2LGD4cOH4+7urm6Tm5tLZmam2qS3atUqABwcHGjVqhU3btzgyJEjDBo0iI0bN5qkKyEhgalTpzJgwAAsLCxYuXKlmk9NmjShTZs26oPT3r17+eqrrwBYsmQJWq2Wy5cv8/7779OvXz9q1qzJzp07ycnJYeTIkVStWpWGDRuqZXDnzp3p3LkzGRkZrF+/nnnz5mFra6vmqU6nw8LCQm1u7NGjhxrgQ8G5bQyy9u/frza5GQP3w4cP07dvX9avX4+Xl5f6HZOSkujTpw9arZZBgwZhY2PDl19+ycmTJwkJCeE///kPUBBAm5mZ8fnnnzN+/HiT5sKaNWuSn59Pv379mD9/PgCZmZn4+/uTnZ1NmTJl1AfaVq1akZWVhY2NDb6+voSFhanNdcaye9y4cUDBw59Op8PPz48mTZoQFBTEN998Q4MGDWjTps0dg6yIiAg173v27MmaNWsYOXIkK1asoGHDhibrzp49mylTpqDRaPDz82Ps2LFFAu7169dja2vL0KFDsbW15eDBg8yZM4eMjAyCgoLU9dasWcPHH3+Mv78/gwcPJjY2ljfeeAMnJyeTh5V7vfcWZjxPu3btqi57/fXXqVatGj/99JPa/aNwzAJ/39/i4+PVALe4bgy3emhBVkxMDAAfffQRdevWZcaMGSQlJTFv3jwGDx7Mpk2bsLe3R6/XM2nSJMqVK8f69etxcHBQ96Hc0uFvxowZVKtWje7du9/2uGXKlGHmzJl8+OGHDBkyRF3eunVrZs2aZXITuVve3t5s27bNpL9T9+7d6dSpE2vXrlWfEJycnNi9e7dJ9N6nTx86derEihUr+OKLL0z226BBA3Q6HQsWLKBx48bs378fS0tLFixYgLu7O6tWrVKfWlavXs3NmzeLBFkpKSmcOHECoEjHUB8fH+zt7ZkyZQp169YlOjqaYcOGUatWLRYvXoyLiwsXL140aUM2/m28qSQnJ+Pp6clPP/1EVFQU8+bNo3379gB07NiR1q1bAwVPz7cGWR07dlSfpDQaDVqtlpEjR1KpUiU2bNigto1/+OGHDBw4UO24m5yczHPPPceYMWO4dOkSCxYsIC4ujjVr1qg3iSVLlpCdnU2tWrX473//C8C2bdtwcHCga9eu/PDDD1hZWRX7uwUGBrJ7926cnJy4cOECp06dAgoKEnt7e/bs2aPmZfny5fnkk0+YP3++WuC5ubnxzjvvMG3aNJMAtVmzZpQrV46mTZtiZ2fHkSNH+P7779XzICgoiEOHDqlBVuF8z8zMVC/Q5ORkypUrx0svvcQPP/xAp06d1PXOnTvHxo0badSoEeXLl2fTpk20bduWS5cuER0dzfr16xkxYgRffPEF/fv356OPPgLg7NmzQEHQ89lnn9GsWTNatWrF7NmzCQ4OVp9ss7Oz1WNVq1aN/fv3YzAY1ODN3NxcfVpLSkqiS5cu/Pe//+Xjjz9Gp9Oh0+lYtWoVffv2JScnR+1AXLg/idGVK1eAgs66BoOBjIwMgoODadeuHa1btyY+Ph6dTsesWbNo27Yts2bNUoOatLQ0tXalW7dudO3aVb3JGgNCvV5P06ZNsbW1Zffu3eTl5bFjxw7Kli3LmjVr+Ouvv8jOzmbcuHH069ePt99+mx07dqi/R926dRk+fDjLli1Tr7GcnBx69eqFubk57777Lp06dcLS0pLq1atz+fJlBg4cyPfff49er6dPnz5q7eLy5cvp3LlzkTwA8PLyMhnxZWlpiaIo6jEB5syZg0ajYfDgwcyePZs1a9YwdOhQLl26VGR/xrK38FO3k5MTZmZmjBw5ko0bN1KxYkU1yMjNzVUDOyi4lm/cuIGjoyPDhg0z2feaNWuYPHlykfRv2rRJ/f9169bxwQcf8N///tfk5nb9+nU2bNig1v43a9aMXr16AX/XsmRkZGAwGBg/fjwDBw7k22+/5ZlnnuHs2bNkZGQwf/58dYT1mDFj2Lx5M0ePHlVr3I0PdVFRUSY3TXNzcxo1aqRe19WqVSMvL4958+Zx6dIl9SZpfIBKSkoCCoLtSZMm4eHhQe/evfH29iYjI4NffvmFgwcPFnmwnTVrFmZmZvzyyy84OjryzTffoCgK9erVY8aMGfTo0QMzMzOqV6/Op59+ytSpU03KkM6dO7Njxw7mzp1rUoM/aNAg6tevj8FgYM+ePfz6669UqFCBMWPGoNVqOXjwID/99BNQcL8qfI8cN24cnp6evPbaazg7O3P+/Hm+/fZb+vbtS25urtqacieRkZEmef+f//yHDh06MHPmTLU8MzMzIyAggPbt2+Pu7k50dDRLly5l6NChLFu2jEaNGqn7+/rrr01alfr168fHH3/MqlWr1MEPeXl5zJw5kzp16vD999+rHc9r1KjBRx99ZBJk3eu910iv17NlyxZ8fX1NWmKee+45rl69yk8//UTLli2LDdIK39/KlCnDxx9//I+1ZvAQp3AwPrW5ubmxePFiOnfuzJAhQ/j666+Jj49Xn8JOnz7NlStXGDJkiEmABRQZsfLLL78wYcKEfwyUXFxcqFu3LmPGjCE4OJi3336bgwcP8sEHH9zXd7G0tFRv1Hq9Xg12qlWrxpkzZ9T1zM3N1R/ZYDCQkpJCfn4+devWNVnvdnJycjA3N+fs2bP07NnTpFrY3t5ebe4obM6cObet1funYxm/U+ETs3Czg3E9KKhtLF++PO3atVM/W7RokdoMUZx58+axaNEitaajQ4cODB8+nMDAQL755hscHBzQaDRqIWPsFG4skDp27Mibb77J+PHjOX36NHv27FH3vWPHDrRardpkt2DBAvbv38/777+vVsHn5+cX+7sZbyK9e/emSZMm6k3DzMyMjIwMfv75Z27cuMGNGzews7NTL76PPvoIZ2dnrl27xv79+/Hz82PixIkEBwczdOhQjhw5gpubGz169KB9+/Y0aNBATW9xv13hfLe2tua7776jRo0auLu7Y2dnx5o1a/D39zcpMI2jF6dMmaJWUb/zzjtMnz4dKLiRzZo1i/T0dDp16qR+D2NnbQ8PD5ydndHr9SxYsIBXX30Vd3d3XFxccHFxISUlhWXLlhEbG0vt2rUxGAxoNBqys7PJysrCwcGB33//3eTcsLe3V/O5Xbt2dO3alTVr1piMtPz6669p2rSpup69vT0zZsxg2rRpNGjQQG3yzs7O5saNG+ooJa1Wi4uLC7Gxsfz000/qtR8bG6ueLzt27MDGxobZs2dja2urBmI2Njbk5uYyf/58hg0bphaI169fJy4ujl9//RWtVkunTp3QaDQm5UrNmjXx8vIiICCAixcv0rFjR6pXrw783ZE4KiqKyMhI+vXrR2RkJIGBgbz33nuYmZmh0WjYsGEDVatWBQo63N5uEInxtw8ODqZHjx7odDrKly+vlhl6vZ59+/bRunVrlixZwquvvkpmZiaXLl0qtjnGWPba29szdOhQAJydnXnrrbfIzMxUA3/jb2gwGGjXrh3BwcEmtQj5+fnqjc2oXbt2fPfdd8yYMUOt/ezYsSMRERHqv3r16qHRaNRawcK2bNlCVFQU4eHhTJs2TV1urCUw/nbvvPOOOsqrbdu2ahlXuObT0tISrVbL0aNH1XPBWAZXqlSJpUuXMnXqVLVGqfDgmS5dumBvb8/ChQsJDAxEp9Px008/qcGV8dw+d+4c0dHRjB07lpdffhl/f39atmzJzJkzKVeuHLGxsWrHfkVR2LFjB23atCE/P59du3apD6Vdu3YlOTnZJA3lypUrUoZs2bIFd3d39eHV6K233qJz58506dKFr7/+mmHDhhEfH4+LiwuBgYFMmjSJt956C6DYfG/VqhW9evWibdu2jBw5ku+//14deXk3ndIrVKhgMn2Qk5MTXbp0Mcn7ChUqsHTpUl566SXatGnD0KFDWbduHdbW1mr5ZFQ4wMrIyODGjRs0atSI7OxsNT/Dw8O5fv06/fr1MzkPe/bsWSRWuN9774EDB7h27ZpJQH63jPe3CRMmULFixbsejfzQarKMmRgYGGhSk2DskX/s2DEGDx6szglVs2bN2+5LURQ+//xzOnToYBINFyc2NpZBgwYxffp0NSBo164dFStWZPz48bz44osmIwjuhsFgYPny5fz444/ExcWpBQFQJMhYv3493377LZGRkWpTDhRUzRvduHFD3UfhNnNra2t0Oh2AWjgb5ebmFjmxLly4wOrVq2nZsiW7d+++p+9kbW2t3tiMxzQepzCdTkdycjIxMTGUL1+ejIwMHBwc1GO/9tprapPErYxVxDY2Nuh0Onbv3s0PP/zAgAED1P55iqIQExNDjRo11HOmS5cu6j6Sk5PV/kn79u0jICAAa2trYmNjsba2Ji8vj99++41Zs2bRt29f+vbtqz7dW1hYMG/ePNavX09CQoLJ71a2bFl+/PFHtm7dioeHBx999JGaH9OmTTO5ARj5+Pjg4eGBubk5W7ZsUQvQ9PR0/Pz80Gg0LF68mHbt2uHn56f2GylTpgzHjh0rsr/C+W5ubk7z5s2xsbFRh8nn5ubSqVMnrl+/rq535coVLCwsqFixIr/++iteXl74+PiofTwsLCzUY9067QcU9MmqXLky6enppKam0qFDBy5evIher8fDw4Pc3Fy1TwdAo0aNOH78uJp3mZmZTJw4kUmTJmFra8v+/fsZM2YM1tbWODo6mjzVFz63n3/+ebU5FVD7rLVu3RoPDw91WPXYsWNN0mswGEz6A9WpU4fTp0+jKAoJCQmYm5sTHBzMa6+9Rm5urklzmL+/P/v37yc7O5tu3bqxdOlS9bM//viDXbt2ERAQgLOzM0uWLGH79u3079+flStXMmLECJYuXcrYsWPJzMykZs2aWFlZcfnyZU6cOIGPj486mtTX15fvv/+eSpUqcePGDXQ6HY6OjmRkZBAQEEBUVBQpKSnqTSA5ORlra2v1ek5LS2PWrFmcPXtWPSeMtXxQUF7k5OSQmJiIVqtl6NChLFq0CEDto1aY8ToylpffffcdL7zwAp9//jlVq1bl2LFj6HQ6rly5gqIoaDQaPvroI9zc3DA3N+f333/n0KFDZGVlERkZSaVKldDr9eh0OszNzalZs6b68HzlyhXmzp1bbP/YwrWiUFCmLVq0SO13Vb16dfUBzPi7Ge8VhcsAKChDsrOzOXXqFC1btlTzxNh8FxERoTYF3q4MzsjI4Ny5c/j4+ODm5kbLli3ZunUrISEhhISEYG9vT5UqVYiIiFBbDIxTbNx6XhZ26NAhnnnmGW7cuEFaWho//vgjP/74o/q5cSQwwM2bN7lx4wbHjx/n7bffZsmSJfj5+WFnZ4elpSXLli3jypUrRERE8Mwzz9z2mK+88gpLly7lwIED6v2sa9euzJkz5x+nBYGCuRnNzc3vOjC4takMCvpbGgwGEhIS1AeQW3l4ePDCCy/w888/q82XUNCkPWvWLA4ePKiWXUbG2sT4+Hig6L1Qq9UWO73Q3dx7b7Vp0ybMzc1vW8t8J8b7W8uWLWnbti1du3bF1taWAQMG3HG7hxZkGZtCiutc7uLiclcdxIx27NhBWFgYo0ePLjJRZ0ZGBnFxcbi6umJtbU1ISAg6na5IhzxjFH7s2LF7DrIWLFjA7NmzefHFFxk1apRa9f7FF1+YNGlu2LCB8ePH065dO4YNG0bZsmUxNzdn4cKFaqdXKOhcXrgQNXJzczMJBIx0Oh0pKSlUrlxZ7RAMBc2ntWvXVgO9uLg4tckuKSnpjrVMbm5uJCcnY2lpqQ6VB9S/jTUYX3zxhTq0PiYmhs8//5wvv/xSPbaxyjY5ObnIsY2fubm5kZWVRZUqVdi0aZN6EhoLVmMHc+M5U7gzaOGhwKtWrcLX11ft12BtbU1UVBTjxo2jdevWfPLJJybfYd++fWrhVpiTkxO5ubnUqVPHZJg9QJMmTTh06BDjxo3jzz//5MKFC+pTmPFBwHgBGwuDzz//3KTKPSgoiK1bt3Lw4EGgoJP5tWvXiIuL49q1a+p6p0+fxs3NzaQG5erVq2RnZ2Nubo6DgwOfffaZ2owKqLV+x44d48qVK7z33nsm6bezs1Ofwr/++mu1H9uxY8eYO3euOu/WqFGjMBgMxRYuL774Ih06dKBmzZpERUUxbNgwbG1tcXNzw83NTS3gKlWqpPb3MHZyfeedd9BqteTm5qqDLhwcHHB0dESv16uBrIuLC5s2baJ69epqXyYoqKYfPnw4e/fuZdmyZdSrV4+JEycyb9489u7dq/ZvM3rjjTfIzMxkxowZzJgxw6TfnpWVFQaDgdTU1CIdjI8fP052djZdu3YlJCSE6dOn079/f1577TVWrlyp1qYZm4jh79oNYz+zZcuWAai/gXFqCigInMzMzNRA49VXX1XPy4CAAF544QVmzJhBVlYWMTExNG7cmE8++YTZs2ej0WjUvkqFnThxgjFjxnDt2jV++eUXKleurO4/Li4OBwcHnJycii17jX2A8vLySEtL4/jx42pgqygKLVu2ZNeuXaSkpHDo0CG1r9alS5fYu3cviYmJJCYmqtfj+fPn1d/SeM5Uq1bNJL1lypRR+4sa07By5UqioqJwdHRk0KBBODg4kJaWRnp6Orm5uWogmpOTY3KjvLWsuLUMXbduHXXr1r1tGbxgwQIOHTrE5s2b8fHxISkpie3btzNq1Ci8vb3JycmhevXqajDl5OSkDr6BgrmlCve9goKAacyYMWqajPkRGBjI4cOHMTc3Z+LEiSY1mDVr1qRnz55q2ocOHcpbb73F22+/zbRp02jcuDGHDh1iz549WFpaqvfJ+Ph4cnJy1P5xrq6uaLVak+kmjAHqrcHtrXQ6HXPmzKFatWpERUWp99SsrCwMBoM6rUjha+lBGKf8SEtLw8bGhrS0NAYMGIC9vT3vvPMOnp6eWFlZcfr0aaZPn25yXt2tu733FpaTk8OOHTto1qzZXQ+Cu53KlStTp04dk/vb7Ty0IMs4H0fhEXFQcCImJyernxsL7IsXLxY7mSmgTqQ5ePDgIp8Zn0KMk50ZJ128tYAyBieFg5S7tW3bNpo0aVKkXTctLc2kU/K2bduoXLky8+bNM7lxGjvrGk2bNk2tMTp37pzawbNwu2/hp5Hw8HC1X0zhdvqEhATOnTun9ikqPBHcq6++iqurq9pOfysfHx+OHDlCzZo1TaqXjR2qr169SpUqVfjggw9IS0tj+vTpJCQkqH00bj124Zu98dh//fUXUHAubNu2DXd3d/VGBQXNGUlJSWohVNw5891335GWlsaoUaN44YUX1ELe09OTpKQkkpOT8fPzY+bMmWpBbPwOERER+Pj4EBQUxLFjxwgODqZVq1aEh4eTmppaJKDVarXqBV6rVi3279+PhYWFWpNmZDyHjNsPHz6cbt26ERERweTJkwkMDAT+DsaMgcGtE/W9/vrrhIWFqU20MTExJCUlqZ2CX3vtNerVq8eYMWPUbU6dOkV+fj6rV69Go9GoT/zGKvaMjAyqV69OdHQ0bm5u6jVlrNKvW7cujo6Od7wO1q1bh4uLC87Ozmpfmb59+3LgwAHMzMzUvoO//PILycnJ2NnZkZGRwYIFC9Snu7CwMDXIMo5cvbXGND09nd27d6PT6bCzsyMzM5NatWrRvHlzddRcfHw8vr6+jBs3jkuXLqmjU6Gg8HZ3dzeZ3+7GjRvq37t27QIKakGM/ZSMLl++jK2tLRqNhg8//JAOHTrw4YcfYmZmhouLC+Hh4bi7u6MoCra2tly8eFE9111cXNSAqkePHnTp0oU33nhDHRlo7GBsMBjUbhHGc9LI+ERvHH22dOlSzp49S1JSEq+//rpa22M8nnGf06dPL9L0AgXn1ogRIxg7dize3t5otVqT6yg/Px+9Xk96ejrPPPMMPj4+vPjii6xbtw6NRsPChQtN5gcznruFRxcbGYOzqlWrqrW1AQEBxQbshWd5j46OxtXVFVdXV9LS0kz6cBbud2j8f2PfT/j7WjPe+KdNm0ZwcDAHDx7EYDDQr18/4PZlsHEOLOOD0fXr18nLy7vtpNhz584lJyeHDh06AAX9XW8tB4xzNRrT5OLigq2tLfv27cPKyoqVK1cWO+J62rRpfPHFF8TFxTFz5kz1HpiQkKAGpVOnTjWZz6l79+74+fmpffwSExPJy8szCYSM1/Q/zXeVk5PDzZs31fy/tVxq27atySSrQJHrBwp+TzMzsyKjZW8VGxuLubm5Ws4fPnyYlJQU5s2bZ9Ih/tYKFGN3iKioKJP18vLyiIuLM2nmvNt7b2G7d+8mMzPzvpoKi5OTk/OPAS48xD5Z1atXVztEFm6C+u2338jIyFA7+dauXZuKFSuybNkyk+HF8HfH9zZt2hAcHFzkHxR0aA8ODlZv0FWrVsVgMLBlyxaTfRmnMDAW+PfCOPN1YVu2bCkSQBpv8oXXPXnypEkHVih4omvevDnNmzc3mRyuadOmlClTBnt7e9avX6/eTFatWoWVlVWR402YMEENHKBgtJvxVQMTJkwodti8UWBgIHl5ebi7u3PixAnOnDmDTqcjJCSE2rVrc/z4cQIDA6lbty7Nmzene/fu3LhxQw3+JkyYwMyZM9Wn5lGjRqnHHjVqlMmxAwMD0ev1nD17Vv2+eXl5alX1/v37gYJaJGdnZ0JCQtRCtXnz5kRHRwMFs18bn+T8/f3Vp7g2bdqoTSTG79CwYUO1CUur1bJo0SKeffZZOnfurE43EB4eblJ4VK5cmdDQUMzMzPD29qZq1apcvXqVo0ePmty8jYGY8XeuUaMGzZs3VwtIYzP12LFj1aC4Y8eOBAcHqzctJycnKleuTF5eHhkZGej1ekaMGAHAxx9/zLVr10hJSSEgIEA9V5o3b67Omrx9+3b8/f3VgsjYz0av19OtWze1v4mxj0lhdnZ26ijbTz75RL2eatasScWKFQkODsbf359XX31V7fdibHrMyclh9erVeHp6smPHDpo0aaL+jrfW6hoZb1TG30ij0ZCZmUnt2rXVa8ZYRtjZ2ZGenq4GJ0lJSezatYsaNWrw/PPPk56ejrm5Oc8++yy2traMGTOGL7/8knnz5hEcHMznn3+uPtFbWFjg5eWFg4MDa9asAf5+2r98+TINGzZk/Pjx+Pn5MW3aNPWz1q1bs2vXLn777Te1H+L27dtJSEhAo9HQrFkztm3bBhQ0ybZo0YKWLVuyd+9edYoLKChrjPs0DkAA1P43GRkZap7p9Xq18/itzSfGpmRLS0s+//xz9XovPO2LsT9XRkYGlpaWBAQEsGvXLrVM3bt3L4qikJqaqk6waqztVxSFq1evYmVlha+vr1qzaGNjo+ars7Mzvr6+BAcHqw+7hZtxb20u0ul0RWoQQkND1SDOxsZGvU7q1KmjnoPGJr+OHTuqNQLGqSXg75osf39/ypQpg16v59lnn1VrmYwP2LeWwcYg1/jbVKpUqcj95Msvv8TCwgIrKys1P+vUqUPFihVZunSpyQ1Ur9ezcOFC9XyAgnPYysqKjIwMPvnkkyIBlrEM8ff3p379+moTsjHImj59utoXa9y4cQQHB6sPbNOmTeP9999X92UMDgvX9BsfqO/UzGjM+9GjR6PRaGjatKn6/Zs0aYKNjQ3BwcG88sorJtvEx8ebdElJTU3l119/pVGjRmpQV7iMNIqOjmbz5s00atRIvf6N10Th30in05k0sULBA6GLiwurV682qdVcv359kZawu733FrZp0yZsbGxMgvm7Udz3DA8P59y5c0Umey3OXddkGfvhGIdNb9iwgdDQUBwdHdWLY/z48YwYMYKXX36Z7t27k5yczPfff0/t2rXp1q0bUJA5n3zyCSNHjqRHjx707NkTV1dXdTbwefPm4enpWWybMBTcGAt3xu7ZsyfffvstEydOJDw8XB1Cv3btWry9vU067125ckW9GRifUo3fy8fHR123VatWBAcHM2HCBBo0aMCFCxfYtGlTkXbhVq1asX37dt58801atWpFXFwcq1evpkaNGmpNwp1YW1vzzjvv8Omnn5KRkUHnzp1xc3MjPDwcKysratasqe7nypUrat8bY8Fz4cIFdeh7kyZNqFWr1m3fg+jn50dgYCA7d+7EwcGBgQMHqjO+Ozs74+bmZjI6s0+fPqxcuZKxY8cyaNAgXF1d2bBhgzoruL+/v1oFPn/+fF544QV1yomLFy+qQ9ktLCz44Ycf2Lx5M1evXuWZZ57h888/59SpUzRo0IDGjRuzbds2evfuzYsvvsjly5dZtWoVrVq1UguzjIwMk07ws2bNYvPmzVhYWHDx4kUMBgNTpkzhr7/+Um9oUHABfvzxx7i4uGBlZUVqaip9+vRRn8yN1eUWFhbq6EutVsvAgQOxsLAgICCAyMhIdc63yZMnc/LkSerVq8eRI0f49ddfcXNz48CBA5w6dYqwsDA1WIyMjCQiIkJ9eqxUqRJnzpxh+PDhnD17Fmtra1JSUnBycmLTpk0cO3YMZ2dn3N3d2blzp3qO16pVi2effZYjR45w+fJl3n77bWJiYtTfuXz58vTu3RsbGxvGjx+vTlVh7Hg/YsQILCwsyMzM5OWXX+bll19W8/GLL74gPT2dqKgoFi5cqBZkrq6ujBo1ioiICPLy8rCysuLSpUv4+PjQokULjh07Rl5eHoMHD1abXws3ne3btw+9Xk9kZKR6HgBs3rxZvYby8/MxNzdn7ty5LF26VE2vmZkZY8aMoXbt2moH1vz8fOzt7Vm9ejU3btxg2bJlVKlShZYtW+Lu7k716tW5ePEi+fn5WFlZ0adPH06dOoWLi4taQBoMBrU598KFCzz//PM0adIEe3t7zp8/T3Z2NtnZ2dSvX1+dzR4KAqe//vqLtWvXYmVlxfTp07GxsaFSpUrk5eXRqVMn9WZ87tw5XFxcuHbtGvPnz1f7FTk5ObF9+3bi4uLUJqmWLVuSnp6OpaWlOjK28MPp6NGjOXDgAMHBweq8Qj/99JO6T+P5cejQId577z3Kli1LVlYWH3/8MQArV65Eo9Fgb2+vBkmtW7emZs2aXLx4kY8//pgtW7agKIqaLxMnTlRvQOPHjyciIoJTp05x48YNUlNTTZri+/Tpw7PPPoujoyOXLl3i4sWLVKxY0aQZRqvV0qdPHwICAoiNjeXChQtotVpmzJih9rvZuXMnZ86cYdu2berD1cqVK8nNzcXa2ppJkyZx4cIFnJ2d+eOPPwDT2rZnnnmG3bt30759e/z8/Lh586Y635FWq1UHkTg4OLB06VL8/f2pUqUKycnJ6sCKSpUqmdxTBgwYwFdffUWLFi3w9/fH0tKS48ePk5ycTI0aNdRz2DjHlo2NDWPHjmXt2rXqPHNJSUlcvXpVDVT69+9PSEgIr732GgMGDKB8+fIcOXKEPXv20KJFC7XFwFije+jQIXx8fDhz5gx79uzhwIEDVKpUifDwcC5cuMChQ4fUwL+4G/2uXbsoW7Yszs7OXLx4kZ9++gkXFxeTATTGvC/83Y2qVavG+PHj1Vey/fzzz2RkZJjk/bRp04iNjaVp06a4u7sTExOj9lssPKCiQYMGODk5qSNIjYNEbq3I0Gq1vPvuu3z88ccMHjyYTp06ERcXR0hIyAPfe1NSUvjzzz/p0KFDsYOS7qR169Z06tQJLy8vbG1t1fkY7ezs7uodjxrl1m96G7d7WWLFihVNIt4//viDuXPncv78eWxtbWnbti1jx44tMvfPkSNHmDdvnjqRYNWqVenfv786xPd2aSju3YVXr15l9uzZHDp0iKtXr1KmTBnatGnD6NGjTY57p/cYFZ54TKfTMXPmTHXSxNq1axMUFMTXX38NoA5hVRSFRYsW8dNPP6kX4KhRo9i6dSuHDx8utnO6MQ3GoesAP//8M3PnzlVrIVxdXZk0aRK7du1S9/NP72AyvrvQ+D6pF154gc2bN5u80zA3N5dZs2bxyy+/cPPmTbUzerNmzZg4cWKREzk+Pp7Jkydz4MABrK2t6dq1K88//zzDhw9n+fLlXLlyhQkTJtCjRw/Onz9PXFwcOTk5uLm50ahRIzQaDfv27SMtLY2aNWsycuRIAgIC+Oabb9i8eTNJSUk4OztTvnx50tLSiIuLo0yZMnTp0oV3331XfRL6p/e4Gau6dTod48aNK1KrWZiXlxc3b94kOTkZBwcH+vfvz82bN9m7dy/Xr1/HwcFBveEWx8nJiaysLNzd3dW+ZwkJCWr/iTZt2lCvXj1+/PFHzp07h5mZGVlZWbz22mv4+voye/ZsLl26dMd+CLdeU8ZzythpWKPRULFiReLi4nj99dfVObMOHDhgEigXVqZMGQ4ePGhStd6lSxe19qFws+79sLGxoWfPnvz4449UqFCBlJQUNQ+fe+45IiIiSExMxGAwYG5uro4ENPbJyc7OxmAwqCP1jB2cjQ9cZ8+eJSUlRe0jlpeXR2RkJOnp6djY2JCenq6+xgYKarVq167Nyy+/zIIFC4iNjS22/6ORra0teXl56hO0o6Mjnp6eXLlyRX0HY+PGjdXJVGNiYkhPT0ej0aDX63F2dsba2lr9jv/9739ZuHAh8fHxvPXWW7d9B6WZmRktW7akZs2aLFq0yGTSzSNHjjBx4kSio6MpU6YMo0ePVvdpXC8xMZE5c+bcdg4tDw8PNTiBgge02bNns3HjRrXWy9HRkbFjx5pMLfDcc8+h0WgwNzfn+vXraLVavL29efHFF4mJiWHVqlXq9oXz/Vbm5ubquV6pUiV1dKnR+PHj2bBhw22vhy+++IJly5YRFRWFlZUV+fn5JrUVCQkJvPnmm5w7dw69Xo9Go6FcuXI4OjqSlpamjoyFgnc87tmzh6tXr6o1e5cvXzaZegQKmrs++ugjjh8/rl4XlpaW1K5dm3HjxuHv7w8U1KgX19fWmKcffvihyUjhiIgIZs2aRVhYGNeuXcPd3Z1OnTrx9ttvq2Xd9OnTWbx4MZUrV+batWvq+2etra1JT09Xmw0rVqxIQEAAP/zwAxMmTDC57r29vXF1dSU/P5+MjAxcXFwICAjg7bffVgMsY97v3LmzyCvr2rRpg4+PD3379mX69OlERUVRpUoV3nvvPZNRkL/++iurV6/m0qVLpKen4+joSOPGjXnrrbeKDGw7duwYX331FefOncPR0ZFu3brRrFkzhg0bVuQ9yD/++CNLly5VJyOdMGECs2fPBu7/3rt69Wp1ap7CFS+FhYSEMGHCBJN7JsBXX33FgQMHTO5vTZs2ZeTIkXf1vt+7DrKEEEIIIcTde2h9soQQQgghxN8kyBJCCCGEKAESZAkhhBBClAAJsoQQQgghSoAEWUIIIYQQJUCCLCGEEEKIEiBBlhBCCCFECZAgSwjxxBs4cOBtJyF80oSEhODt7a3OHv5P2rRpo74iSwjxcEmQJYQoVXPnzmXnzp0PvJ9ly5YREhLyEFIkhBAPh8z4LoQoVd7e3iavtbpfbdq0oWLFiuqrNwrT6XQA6mt8nmR6vZ78/Hy0Wq36ct47uVO+CSEezF2/IFoIIR5XT0NwZWRubo65uXlpJ0MIgTQXCiFKUG5uLnPnzqVjx474+fnRqFEjunbtyldffUVcXJz64vn169fj7e2t/jP67bffeP3112nVqhV169alSZMmjBw5knPnzpkcx9vbmytXrnD48GGT/cTFxQG375N15MgRhg4dir+/P76+vvTs2ZM1a9YUWc+4/dWrVxkzZgzPPvssfn5+DBs2jMjIyHvOlzv1myourd7e3owfP/6u9nO7fSckJDBq1Cj8/f1p2LAhr7/+OjExMfecdiHE3ZOaLCFEifnvf//LunXr6NGjBw0aNECv1xMVFcWhQ4d4++23mTp1KuPGjaNRo0b06dOnyPY//PADZcqUoU+fPri5uRETE8PPP/9Mv379WL9+PVWrVgVg6tSpTJkyBWdnZ15//XV1excXl9umbffu3bz11lu4uroydOhQ7O3t2bx5Mx9++CFxcXGMHj3aZP2srCwGDBiAn58fo0ePJi4ujuXLlzNy5Eh+/fXXR7r2KC0tjf79+5OYmMhLL71E9erVOXLkCIMGDSInJ6e0kyfEE0uCLCFEidm5cyfPP/88X331VbGfd+/enXHjxlG5cmW6d+9e5PMlS5Zga2trsqxHjx50796dZcuWMWnSJHU/s2fPxtXVtdj93Eqv1zN58mRsbW1Zs2YNHh4eALz88ssMGjSIRYsW0bNnTzWIA7h58ybDhg1jxIgR6jIXFxemTZvG/v37adGixT8et7QsWbKEK1eu8MUXX/Diiy8C0L9/fz7//HOWL19eyqkT4sklzYVCiBJjb2/PpUuXuHDhwn1tbwywFEUhIyODGzdu4OzsTLVq1QgLC7vvdJ0+fZr4+HhefPFFNcCCgr5bw4cPx2AwsGvXLpNtzMzMGDRokMmypk2bAhAdHX3fafk37Ny5E1dXV3r06GGyvHDAKIR4+KQmSwhRYj744APGjRtH165dqVy5Mk2aNKF169a0adPmrka+nTlzhtmzZ3P48GGysrJMPqtUqdJ9p8vYV6tGjRpFPqtZsyYAsbGxJsvd3d2xsrIyWVamTBkAUlJS7jst/4bY2Fjq1atXpEnT3d0dR0fHUkqVEE8+CbKEECWmXbt27N69m71793LkyBH279/P2rVradSoEd99990dR/3Fx8fTv39/7O3teeONN3jmmWewsbFBo9HwxRdfFAm6Stqd+lzd60w4Go3mtp/l5+ff9X70ev09HVcI8e+SIEsIUaLKlClD9+7d6d69O4qiMH36dJYsWcKuXbvo1KnTbbfbsWMHWVlZzJ8/X22WM0pJSXmgaRmMtWCXLl0q8plxWeXKle97///EyckJgNTU1CKfxcXFodVqTZaVKVOm2NqyW2vbbqdy5cpER0ej1+tNgsWkpCTS0tLuIeVCiHshfbKEECVCr9cXuYFrNBpq164N/B1g2NraFhtAGIOBW2uJfv75Z5KTk4usb2dnd9fNdnXq1KFChQqEhISY7CsvL4+lS5ei0Who27btXe3rfhg71O/fv99k+a+//kpSUlKx6584cYLs7Gx1WWpq6l3PcN+2bVuuXbvGL7/8YrJ88eLF95ZwIcQ9kZosIUSJyMzMJCAggDZt2lC7dm1cXFyIi4tj1apVODk50bp1awDq16/PgQMHWLRoERUqVECj0fDCCy/w/PPPY2Njw7hx4xgwYACOjo4cO3aMP/74A09PzyJNZX5+fqxdu5ZZs2ZRvXp1zMzMaN26dZHRiVAQwH300Ue89dZb9OrViz59+mBnZ8eWLVs4ceIEr7/+usnIwoftmWeeoXnz5vz0008oikKtWrU4e/YsO3fupEqVKkWaDPv378/777/P4MGD6d69O2lpaaxZs4YKFSoUG3Deavjw4fz666989NFHnD59mho1anD48GFOnDiBs7NzSX1NIZ56EmQJIUqEtbU1gwcP5sCBAxw4cIDMzEzc3d1p06YNr732mjqq75NPPuHTTz9lwYIFZGZmAvDCCy/g6enJ4sWLmTFjBgsWLMDc3JyGDRuyYsUKJk+ezJUrV0yON3r0aFJTU/nxxx9JS0tDURR27dpVbJAFBa+TWbZsGfPnz2fp0qXk5eVRvXp1PvvsM3r37l2ymUPB3F6TJ09m06ZNbNy4EX9/f5YvX86kSZOKfLdu3bqRlJTEypUrmTJlCpUrV2bkyJGYmZlx8uTJfzyWk5MTK1eu5Msvv1Rrsxo3bszy5csZMmRICXw7IQTIuwuFEEIIIUqE9MkSQgghhCgB0lwohBAPgV6v58aNG/+4npOT01P1wmohnmYSZAkhxEOQkJBwVyMSly9fTpMmTf6FFAkhSpv0yRJCiIcgNzeX0NDQf1yvTp066jxZQognmwRZQgghhBAlQDq+CyGEEEKUAAmyhBBCCCFKgARZQgghhBAlQIIsIYQQQogSIEGWEEIIIUQJ+B8RNw4fVIJ3HQAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "grouped_by_station['diesel'].nsmallest(20).plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "4d9f5349",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2021-08-12 19:43:44.752 | INFO     | besser_tanken.data_loader:load_stations:126 - got 16361 stations\n"
+     ]
+    }
+   ],
+   "source": [
+    "stations = load_stations()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "96a6ec58",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "stations_df = pd.DataFrame(stations)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "9fb4bc73",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "merged = pd.merge(df, stations_df, how=\"outer\", left_on=[\"station_uuid\"],right_on=[\"uuid\"])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "1416d11a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "merged.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "cacc0a33",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "plz_grouped = merged.groupby('post_code').mean()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 196,
+   "id": "9ce5a1c0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#prices = group_prices(data)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 123,
+   "id": "4221f111",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "buehl_stations = filter(lambda s: s['post_code'] in ['77815'], stations)\n",
+    "buehl_station = list(buehl_stations)[0]\n",
+    "#buehl = prices[buehl_station['uuid']]\n",
+    "buehl = df[df[\"station_uuid\"] == buehl_station['uuid']]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 127,
+   "id": "5c01f16f",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'uuid': 'e95c2523-8d12-4132-98b3-0aa6a2ce454d', 'name': 'ZG Raiffeisen Tankstelle Bühl', 'brand': 'ZG Raiffeisen Energie', 'street': 'Hurststraße', 'house_number': '24', 'post_code': '77815', 'city': 'Bühl Vimbuch', 'latitude': '48.7133', 'longitude': '8.12091', 'first_active': '2014-03-18 16:45:31+01', 'openingtimes_json': '{}'}\n"
+     ]
+    }
+   ],
+   "source": [
+    "#buehl_station = next(buehl_stations)\n",
+    "print(buehl_station)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 128,
+   "id": "c5371e50",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "buehl= pd.DataFrame(buehl)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 129,
+   "id": "4e5d9d13",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "9581        2020-11-01 06:06:05+0100\n",
+       "22918       2020-11-01 07:31:06+0100\n",
+       "23793       2020-11-01 07:36:05+0100\n",
+       "26755       2020-11-01 07:56:07+0100\n",
+       "33824       2020-11-01 08:31:06+0100\n",
+       "                      ...           \n",
+       "49842510    2021-03-31 19:01:05+0200\n",
+       "49853848    2021-03-31 19:26:08+0200\n",
+       "49862771    2021-03-31 20:01:05+0200\n",
+       "49867661    2021-03-31 20:11:05+0200\n",
+       "49892392    2021-03-31 23:51:05+0200\n",
+       "Name: date, Length: 3533, dtype: object"
+      ]
+     },
+     "execution_count": 129,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "buehl[\"date\"] "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 139,
+   "id": "adbd26b4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "buehl[\"date_time\"] = pd.to_datetime(buehl.date, infer_datetime_format=True, utc=True)\n",
+    "#buehl[\"date_time\"] = pd.to_datetime(buehl.date)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "6950f7b6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#buehl[\"date_time\"] = pd.to_datetime(buehl.date, format='%Y-%m-%d %H:%M:%S%z')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 140,
+   "id": "e0b8a829",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "9581       2020-11-01 05:06:05+00:00\n",
+       "22918      2020-11-01 06:31:06+00:00\n",
+       "23793      2020-11-01 06:36:05+00:00\n",
+       "26755      2020-11-01 06:56:07+00:00\n",
+       "33824      2020-11-01 07:31:06+00:00\n",
+       "                      ...           \n",
+       "49842510   2021-03-31 17:01:05+00:00\n",
+       "49853848   2021-03-31 17:26:08+00:00\n",
+       "49862771   2021-03-31 18:01:05+00:00\n",
+       "49867661   2021-03-31 18:11:05+00:00\n",
+       "49892392   2021-03-31 21:51:05+00:00\n",
+       "Name: date, Length: 3533, dtype: datetime64[ns, UTC]"
+      ]
+     },
+     "execution_count": 140,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "buehl.date_time"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "id": "14208efd",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "9581        2020-11-01 06:06:05+0100\n",
+       "22918       2020-11-01 07:31:06+0100\n",
+       "23793       2020-11-01 07:36:05+0100\n",
+       "26755       2020-11-01 07:56:07+0100\n",
+       "33824       2020-11-01 08:31:06+0100\n",
+       "                      ...           \n",
+       "49842510    2021-03-31 19:01:05+0200\n",
+       "49853848    2021-03-31 19:26:08+0200\n",
+       "49862771    2021-03-31 20:01:05+0200\n",
+       "49867661    2021-03-31 20:11:05+0200\n",
+       "49892392    2021-03-31 23:51:05+0200\n",
+       "Name: date, Length: 3533, dtype: object"
+      ]
+     },
+     "execution_count": 33,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "buehl.date"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 133,
+   "id": "68462004",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "d = pd.to_datetime(buehl.iloc[0].date)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 134,
+   "id": "82cc374c",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Timestamp('2020-11-01 06:06:05+0100', tz='pytz.FixedOffset(60)')"
+      ]
+     },
+     "execution_count": 134,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "d"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 135,
+   "id": "734328c6",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "11"
+      ]
+     },
+     "execution_count": 135,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "d.month"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 141,
+   "id": "7ecdc34e",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "DatetimeIndex(['2020-11-01 05:06:05+00:00', '2020-11-01 06:31:06+00:00',\n",
+       "               '2020-11-01 06:36:05+00:00', '2020-11-01 06:56:07+00:00',\n",
+       "               '2020-11-01 07:31:06+00:00', '2020-11-01 08:01:06+00:00',\n",
+       "               '2020-11-01 12:26:08+00:00', '2020-11-01 13:21:12+00:00',\n",
+       "               '2020-11-01 14:31:06+00:00', '2020-11-01 14:46:09+00:00',\n",
+       "               ...\n",
+       "               '2021-03-31 14:51:06+00:00', '2021-03-31 15:56:06+00:00',\n",
+       "               '2021-03-31 16:01:07+00:00', '2021-03-31 16:11:06+00:00',\n",
+       "               '2021-03-31 16:41:07+00:00', '2021-03-31 17:01:05+00:00',\n",
+       "               '2021-03-31 17:26:08+00:00', '2021-03-31 18:01:05+00:00',\n",
+       "               '2021-03-31 18:11:05+00:00', '2021-03-31 21:51:05+00:00'],\n",
+       "              dtype='datetime64[ns, UTC]', name='date_time', length=3533, freq=None)"
+      ]
+     },
+     "execution_count": 141,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "pd.DatetimeIndex(buehl['date_time'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 164,
+   "id": "e56eda9b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "buehl[\"hour\"] = buehl.date_time.dt.hour\n",
+    "buehl[\"month\"] = buehl.date_time.dt.month\n",
+    "buehl[\"quarter\"] = buehl.date_time.dt.quarter\n",
+    "buehl[\"year\"] = buehl.date_time.dt.year\n",
+    "buehl[\"day\"] = buehl.date_time.dt.day\n",
+    "buehl[\"week\"] = buehl.date_time.dt.isocalendar().week\n",
+    "buehl[\"weekday\"] = buehl.date_time.dt.weekday\n",
+    "buehl[\"season\"] = np.where(buehl[\"month\"].isin([3,4,5]),\"spring\",\n",
+    "   np.where(buehl[\"month\"].isin([6,7,8]),\"summer\",\n",
+    "   np.where(buehl[\"month\"].isin([9,10,11]),\"fall\",\n",
+    "   np.where(buehl[\"month\"].isin([12,1,2]),\"winter\",\"None\"))))\n",
+    "buehl[\"weekday_name\"] = np.where(buehl[\"weekday\"].isin([0]),\"mon\",\n",
+    "   np.where(buehl[\"weekday\"].isin([1]),\"tue\",\n",
+    "   np.where(buehl[\"weekday\"].isin([2]),\"wed\",\n",
+    "   np.where(buehl[\"weekday\"].isin([3]),\"thu\",\n",
+    "   np.where(buehl[\"weekday\"].isin([4]),\"fri\",            \n",
+    "   np.where(buehl[\"weekday\"].isin([5]),\"sat\",            \n",
+    "   np.where(buehl[\"weekday\"].isin([6]),\"sun\",\"None\")))))))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 143,
+   "id": "ff6450d2",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Index(['date', 'station_uuid', 'diesel', 'e5', 'e10', 'dieselchange',\n",
+       "       'e5change', 'e10change', 'date_time', 'month', 'quarter', 'year', 'day',\n",
+       "       'week', 'weekday', 'season', 'weekday_name'],\n",
+       "      dtype='object')"
+      ]
+     },
+     "execution_count": 143,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "buehl.columns"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 144,
+   "id": "65deae4d",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "Int64Index: 3533 entries, 9581 to 49892392\n",
+      "Data columns (total 17 columns):\n",
+      " #   Column        Non-Null Count  Dtype              \n",
+      "---  ------        --------------  -----              \n",
+      " 0   date          3533 non-null   object             \n",
+      " 1   station_uuid  3533 non-null   object             \n",
+      " 2   diesel        3533 non-null   object             \n",
+      " 3   e5            3533 non-null   object             \n",
+      " 4   e10           3533 non-null   object             \n",
+      " 5   dieselchange  3533 non-null   object             \n",
+      " 6   e5change      3533 non-null   object             \n",
+      " 7   e10change     3533 non-null   object             \n",
+      " 8   date_time     3533 non-null   datetime64[ns, UTC]\n",
+      " 9   month         3533 non-null   int64              \n",
+      " 10  quarter       3533 non-null   int64              \n",
+      " 11  year          3533 non-null   int64              \n",
+      " 12  day           3533 non-null   int64              \n",
+      " 13  week          3533 non-null   UInt32             \n",
+      " 14  weekday       3533 non-null   int64              \n",
+      " 15  season        3533 non-null   object             \n",
+      " 16  weekday_name  3533 non-null   object             \n",
+      "dtypes: UInt32(1), datetime64[ns, UTC](1), int64(5), object(10)\n",
+      "memory usage: 486.5+ KB\n"
+     ]
+    }
+   ],
+   "source": [
+    "buehl.info()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 145,
+   "id": "26cae1bf",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>date</th>\n",
+       "      <th>station_uuid</th>\n",
+       "      <th>diesel</th>\n",
+       "      <th>e5</th>\n",
+       "      <th>e10</th>\n",
+       "      <th>dieselchange</th>\n",
+       "      <th>e5change</th>\n",
+       "      <th>e10change</th>\n",
+       "      <th>date_time</th>\n",
+       "      <th>month</th>\n",
+       "      <th>quarter</th>\n",
+       "      <th>year</th>\n",
+       "      <th>day</th>\n",
+       "      <th>week</th>\n",
+       "      <th>weekday</th>\n",
+       "      <th>season</th>\n",
+       "      <th>weekday_name</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>9581</th>\n",
+       "      <td>2020-11-01 06:06:05+0100</td>\n",
+       "      <td>e95c2523-8d12-4132-98b3-0aa6a2ce454d</td>\n",
+       "      <td>1.079</td>\n",
+       "      <td>1.279</td>\n",
+       "      <td>1.239</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2020-11-01 05:06:05+00:00</td>\n",
+       "      <td>11</td>\n",
+       "      <td>4</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>1</td>\n",
+       "      <td>44</td>\n",
+       "      <td>6</td>\n",
+       "      <td>fall</td>\n",
+       "      <td>sun</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22918</th>\n",
+       "      <td>2020-11-01 07:31:06+0100</td>\n",
+       "      <td>e95c2523-8d12-4132-98b3-0aa6a2ce454d</td>\n",
+       "      <td>1.049</td>\n",
+       "      <td>1.249</td>\n",
+       "      <td>1.209</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2020-11-01 06:31:06+00:00</td>\n",
+       "      <td>11</td>\n",
+       "      <td>4</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>1</td>\n",
+       "      <td>44</td>\n",
+       "      <td>6</td>\n",
+       "      <td>fall</td>\n",
+       "      <td>sun</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23793</th>\n",
+       "      <td>2020-11-01 07:36:05+0100</td>\n",
+       "      <td>e95c2523-8d12-4132-98b3-0aa6a2ce454d</td>\n",
+       "      <td>1.099</td>\n",
+       "      <td>1.309</td>\n",
+       "      <td>1.269</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2020-11-01 06:36:05+00:00</td>\n",
+       "      <td>11</td>\n",
+       "      <td>4</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>1</td>\n",
+       "      <td>44</td>\n",
+       "      <td>6</td>\n",
+       "      <td>fall</td>\n",
+       "      <td>sun</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26755</th>\n",
+       "      <td>2020-11-01 07:56:07+0100</td>\n",
+       "      <td>e95c2523-8d12-4132-98b3-0aa6a2ce454d</td>\n",
+       "      <td>1.079</td>\n",
+       "      <td>1.279</td>\n",
+       "      <td>1.239</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2020-11-01 06:56:07+00:00</td>\n",
+       "      <td>11</td>\n",
+       "      <td>4</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>1</td>\n",
+       "      <td>44</td>\n",
+       "      <td>6</td>\n",
+       "      <td>fall</td>\n",
+       "      <td>sun</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>33824</th>\n",
+       "      <td>2020-11-01 08:31:06+0100</td>\n",
+       "      <td>e95c2523-8d12-4132-98b3-0aa6a2ce454d</td>\n",
+       "      <td>1.049</td>\n",
+       "      <td>1.249</td>\n",
+       "      <td>1.209</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2020-11-01 07:31:06+00:00</td>\n",
+       "      <td>11</td>\n",
+       "      <td>4</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>1</td>\n",
+       "      <td>44</td>\n",
+       "      <td>6</td>\n",
+       "      <td>fall</td>\n",
+       "      <td>sun</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1569576</th>\n",
+       "      <td>2020-11-14 14:21:07+0100</td>\n",
+       "      <td>e95c2523-8d12-4132-98b3-0aa6a2ce454d</td>\n",
+       "      <td>0.999</td>\n",
+       "      <td>1.179</td>\n",
+       "      <td>1.139</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2020-11-14 13:21:07+00:00</td>\n",
+       "      <td>11</td>\n",
+       "      <td>4</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>14</td>\n",
+       "      <td>46</td>\n",
+       "      <td>5</td>\n",
+       "      <td>fall</td>\n",
+       "      <td>sat</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1610045</th>\n",
+       "      <td>2020-11-14 16:26:09+0100</td>\n",
+       "      <td>e95c2523-8d12-4132-98b3-0aa6a2ce454d</td>\n",
+       "      <td>1.039</td>\n",
+       "      <td>1.219</td>\n",
+       "      <td>1.179</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2020-11-14 15:26:09+00:00</td>\n",
+       "      <td>11</td>\n",
+       "      <td>4</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>14</td>\n",
+       "      <td>46</td>\n",
+       "      <td>5</td>\n",
+       "      <td>fall</td>\n",
+       "      <td>sat</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1616416</th>\n",
+       "      <td>2020-11-14 16:51:06+0100</td>\n",
+       "      <td>e95c2523-8d12-4132-98b3-0aa6a2ce454d</td>\n",
+       "      <td>0.999</td>\n",
+       "      <td>1.179</td>\n",
+       "      <td>1.139</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2020-11-14 15:51:06+00:00</td>\n",
+       "      <td>11</td>\n",
+       "      <td>4</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>14</td>\n",
+       "      <td>46</td>\n",
+       "      <td>5</td>\n",
+       "      <td>fall</td>\n",
+       "      <td>sat</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1690582</th>\n",
+       "      <td>2020-11-14 21:46:09+0100</td>\n",
+       "      <td>e95c2523-8d12-4132-98b3-0aa6a2ce454d</td>\n",
+       "      <td>1.009</td>\n",
+       "      <td>1.199</td>\n",
+       "      <td>1.159</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2020-11-14 20:46:09+00:00</td>\n",
+       "      <td>11</td>\n",
+       "      <td>4</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>14</td>\n",
+       "      <td>46</td>\n",
+       "      <td>5</td>\n",
+       "      <td>fall</td>\n",
+       "      <td>sat</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1701588</th>\n",
+       "      <td>2020-11-14 23:51:07+0100</td>\n",
+       "      <td>e95c2523-8d12-4132-98b3-0aa6a2ce454d</td>\n",
+       "      <td>1.059</td>\n",
+       "      <td>1.239</td>\n",
+       "      <td>1.189</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2020-11-14 22:51:07+00:00</td>\n",
+       "      <td>11</td>\n",
+       "      <td>4</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>14</td>\n",
+       "      <td>46</td>\n",
+       "      <td>5</td>\n",
+       "      <td>fall</td>\n",
+       "      <td>sat</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>100 rows × 17 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                             date                          station_uuid  \\\n",
+       "9581     2020-11-01 06:06:05+0100  e95c2523-8d12-4132-98b3-0aa6a2ce454d   \n",
+       "22918    2020-11-01 07:31:06+0100  e95c2523-8d12-4132-98b3-0aa6a2ce454d   \n",
+       "23793    2020-11-01 07:36:05+0100  e95c2523-8d12-4132-98b3-0aa6a2ce454d   \n",
+       "26755    2020-11-01 07:56:07+0100  e95c2523-8d12-4132-98b3-0aa6a2ce454d   \n",
+       "33824    2020-11-01 08:31:06+0100  e95c2523-8d12-4132-98b3-0aa6a2ce454d   \n",
+       "...                           ...                                   ...   \n",
+       "1569576  2020-11-14 14:21:07+0100  e95c2523-8d12-4132-98b3-0aa6a2ce454d   \n",
+       "1610045  2020-11-14 16:26:09+0100  e95c2523-8d12-4132-98b3-0aa6a2ce454d   \n",
+       "1616416  2020-11-14 16:51:06+0100  e95c2523-8d12-4132-98b3-0aa6a2ce454d   \n",
+       "1690582  2020-11-14 21:46:09+0100  e95c2523-8d12-4132-98b3-0aa6a2ce454d   \n",
+       "1701588  2020-11-14 23:51:07+0100  e95c2523-8d12-4132-98b3-0aa6a2ce454d   \n",
+       "\n",
+       "        diesel     e5    e10 dieselchange e5change e10change  \\\n",
+       "9581     1.079  1.279  1.239            1        1         1   \n",
+       "22918    1.049  1.249  1.209            1        1         1   \n",
+       "23793    1.099  1.309  1.269            1        1         1   \n",
+       "26755    1.079  1.279  1.239            1        1         1   \n",
+       "33824    1.049  1.249  1.209            1        1         1   \n",
+       "...        ...    ...    ...          ...      ...       ...   \n",
+       "1569576  0.999  1.179  1.139            1        1         1   \n",
+       "1610045  1.039  1.219  1.179            1        1         1   \n",
+       "1616416  0.999  1.179  1.139            1        1         1   \n",
+       "1690582  1.009  1.199  1.159            1        1         1   \n",
+       "1701588  1.059  1.239  1.189            1        1         1   \n",
+       "\n",
+       "                        date_time  month  quarter  year  day  week  weekday  \\\n",
+       "9581    2020-11-01 05:06:05+00:00     11        4  2020    1    44        6   \n",
+       "22918   2020-11-01 06:31:06+00:00     11        4  2020    1    44        6   \n",
+       "23793   2020-11-01 06:36:05+00:00     11        4  2020    1    44        6   \n",
+       "26755   2020-11-01 06:56:07+00:00     11        4  2020    1    44        6   \n",
+       "33824   2020-11-01 07:31:06+00:00     11        4  2020    1    44        6   \n",
+       "...                           ...    ...      ...   ...  ...   ...      ...   \n",
+       "1569576 2020-11-14 13:21:07+00:00     11        4  2020   14    46        5   \n",
+       "1610045 2020-11-14 15:26:09+00:00     11        4  2020   14    46        5   \n",
+       "1616416 2020-11-14 15:51:06+00:00     11        4  2020   14    46        5   \n",
+       "1690582 2020-11-14 20:46:09+00:00     11        4  2020   14    46        5   \n",
+       "1701588 2020-11-14 22:51:07+00:00     11        4  2020   14    46        5   \n",
+       "\n",
+       "        season weekday_name  \n",
+       "9581      fall          sun  \n",
+       "22918     fall          sun  \n",
+       "23793     fall          sun  \n",
+       "26755     fall          sun  \n",
+       "33824     fall          sun  \n",
+       "...        ...          ...  \n",
+       "1569576   fall          sat  \n",
+       "1610045   fall          sat  \n",
+       "1616416   fall          sat  \n",
+       "1690582   fall          sat  \n",
+       "1701588   fall          sat  \n",
+       "\n",
+       "[100 rows x 17 columns]"
+      ]
+     },
+     "execution_count": 145,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "buehl.head(100)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 146,
+   "id": "7b9e1c16",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "buehl.e5 = buehl['e5'].astype(float)\n",
+    "buehl.e10 = buehl['e10'].astype(float)\n",
+    "buehl.diesel = buehl['diesel'].astype(float)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 153,
+   "id": "586fc458",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>diesel</th>\n",
+       "      <th>e5</th>\n",
+       "      <th>e10</th>\n",
+       "      <th>month</th>\n",
+       "      <th>quarter</th>\n",
+       "      <th>year</th>\n",
+       "      <th>day</th>\n",
+       "      <th>week</th>\n",
+       "      <th>weekday</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>weekday_name</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>fri</th>\n",
+       "      <td>1.204121</td>\n",
+       "      <td>1.377952</td>\n",
+       "      <td>1.337810</td>\n",
+       "      <td>5.415323</td>\n",
+       "      <td>2.137097</td>\n",
+       "      <td>2020.669355</td>\n",
+       "      <td>14.941532</td>\n",
+       "      <td>22.881048</td>\n",
+       "      <td>4.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>mon</th>\n",
+       "      <td>1.212656</td>\n",
+       "      <td>1.390277</td>\n",
+       "      <td>1.350161</td>\n",
+       "      <td>5.365571</td>\n",
+       "      <td>2.102515</td>\n",
+       "      <td>2020.680851</td>\n",
+       "      <td>14.715667</td>\n",
+       "      <td>21.692456</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>sat</th>\n",
+       "      <td>1.216235</td>\n",
+       "      <td>1.391703</td>\n",
+       "      <td>1.351557</td>\n",
+       "      <td>5.380457</td>\n",
+       "      <td>2.118503</td>\n",
+       "      <td>2020.675676</td>\n",
+       "      <td>15.588358</td>\n",
+       "      <td>23.378378</td>\n",
+       "      <td>5.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>sun</th>\n",
+       "      <td>1.207577</td>\n",
+       "      <td>1.384637</td>\n",
+       "      <td>1.344506</td>\n",
+       "      <td>5.528090</td>\n",
+       "      <td>2.187266</td>\n",
+       "      <td>2020.653558</td>\n",
+       "      <td>15.988764</td>\n",
+       "      <td>23.747191</td>\n",
+       "      <td>6.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>thu</th>\n",
+       "      <td>1.210599</td>\n",
+       "      <td>1.384385</td>\n",
+       "      <td>1.344142</td>\n",
+       "      <td>5.844130</td>\n",
+       "      <td>2.269231</td>\n",
+       "      <td>2020.641700</td>\n",
+       "      <td>14.556680</td>\n",
+       "      <td>23.352227</td>\n",
+       "      <td>3.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                diesel        e5       e10     month   quarter         year  \\\n",
+       "weekday_name                                                                  \n",
+       "fri           1.204121  1.377952  1.337810  5.415323  2.137097  2020.669355   \n",
+       "mon           1.212656  1.390277  1.350161  5.365571  2.102515  2020.680851   \n",
+       "sat           1.216235  1.391703  1.351557  5.380457  2.118503  2020.675676   \n",
+       "sun           1.207577  1.384637  1.344506  5.528090  2.187266  2020.653558   \n",
+       "thu           1.210599  1.384385  1.344142  5.844130  2.269231  2020.641700   \n",
+       "\n",
+       "                    day       week  weekday  \n",
+       "weekday_name                                 \n",
+       "fri           14.941532  22.881048      4.0  \n",
+       "mon           14.715667  21.692456      0.0  \n",
+       "sat           15.588358  23.378378      5.0  \n",
+       "sun           15.988764  23.747191      6.0  \n",
+       "thu           14.556680  23.352227      3.0  "
+      ]
+     },
+     "execution_count": 153,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "weekday_groups = buehl.groupby(\"weekday_name\").mean()\n",
+    "weekday_num_groups = buehl.groupby(\"weekday\").mean()\n",
+    "weekday_groups.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 151,
+   "id": "af80903b",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot:xlabel='weekday_name'>"
+      ]
+     },
+     "execution_count": 151,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "weekday_groups[['diesel', 'e5', 'e10']].plot.bar()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 162,
+   "id": "a0e1b2a2",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot:xlabel='weekday'>"
+      ]
+     },
+     "execution_count": 162,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "weekday_num_groups[['diesel', 'e5', 'e10']].plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 166,
+   "id": "9c655a50",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot:xlabel='hour'>"
+      ]
+     },
+     "execution_count": 166,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "buehl.groupby([\"hour\"]).mean()[['e5', 'e10','diesel']].plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 169,
+   "id": "40b16b00",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot:xlabel='weekday,hour'>"
+      ]
+     },
+     "execution_count": 169,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "buehl.groupby([\"weekday\", \"hour\"]).mean()[['e5', 'e10','diesel']].plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 161,
+   "id": "4000c560",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot:xlabel='year,week'>"
+      ]
+     },
+     "execution_count": 161,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "buehl.groupby([\"year\",\"week\"]).mean()[['e5', 'e10','diesel']].plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 156,
+   "id": "3508a896",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot:xlabel='date', ylabel='diesel'>"
+      ]
+     },
+     "execution_count": 156,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sns.lineplot(x=\"date\", y=\"diesel\",\n",
+    "             data=buehl)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 88,
+   "id": "1cb4ef0b",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot:xlabel='date', ylabel='e5'>"
+      ]
+     },
+     "execution_count": 88,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sns.lineplot(x=\"date\", y=\"e5\", \n",
+    "             data=buehl[0:100])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 89,
+   "id": "05af38ea",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 1152x720 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "buehl_melted = buehl.melt('date', var_name='cols',  value_name='vals', value_vars=[\"diesel\", \"e5\", \"e10\"])\n",
+    "sns.lineplot(x=\"date\", y=\"vals\", hue='cols', data=buehl_melted)\n",
+    "fig = plt.gcf()\n",
+    "fig.set_size_inches( 16, 10)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 75,
+   "id": "91c57d5a",
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "KeyError",
+     "evalue": "\"['station_uuid'] not found in axis\"",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
+      "\u001b[0;32m/tmp/ipykernel_236719/3331971858.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mb2\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mbuehl\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdrop\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'station_uuid'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m \u001b[0;31m#b2 = b2.melt('date', var_name='cols', value_name='vals')\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0;31m#g = sns.factorplot(x=\"date\", y=\"vals\", hue='cols', data=b2)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m~/.cache/pypoetry/virtualenvs/besser-tanken-XZndgdH5-py3.9/lib/python3.9/site-packages/pandas/util/_decorators.py\u001b[0m in \u001b[0;36mwrapper\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m    309\u001b[0m                     \u001b[0mstacklevel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mstacklevel\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    310\u001b[0m                 )\n\u001b[0;32m--> 311\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    312\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    313\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mwrapper\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m~/.cache/pypoetry/virtualenvs/besser-tanken-XZndgdH5-py3.9/lib/python3.9/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36mdrop\u001b[0;34m(self, labels, axis, index, columns, level, inplace, errors)\u001b[0m\n\u001b[1;32m   4899\u001b[0m                 \u001b[0mweight\u001b[0m  \u001b[0;36m1.0\u001b[0m     \u001b[0;36m0.8\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   4900\u001b[0m         \"\"\"\n\u001b[0;32m-> 4901\u001b[0;31m         return super().drop(\n\u001b[0m\u001b[1;32m   4902\u001b[0m             \u001b[0mlabels\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mlabels\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   4903\u001b[0m             \u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0maxis\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m~/.cache/pypoetry/virtualenvs/besser-tanken-XZndgdH5-py3.9/lib/python3.9/site-packages/pandas/core/generic.py\u001b[0m in \u001b[0;36mdrop\u001b[0;34m(self, labels, axis, index, columns, level, inplace, errors)\u001b[0m\n\u001b[1;32m   4145\u001b[0m         \u001b[0;32mfor\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlabels\u001b[0m \u001b[0;32min\u001b[0m \u001b[0maxes\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   4146\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mlabels\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 4147\u001b[0;31m                 \u001b[0mobj\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_drop_axis\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlabels\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlevel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mlevel\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0merrors\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0merrors\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   4148\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   4149\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0minplace\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m~/.cache/pypoetry/virtualenvs/besser-tanken-XZndgdH5-py3.9/lib/python3.9/site-packages/pandas/core/generic.py\u001b[0m in \u001b[0;36m_drop_axis\u001b[0;34m(self, labels, axis, level, errors)\u001b[0m\n\u001b[1;32m   4180\u001b[0m                 \u001b[0mnew_axis\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdrop\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlabels\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlevel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mlevel\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0merrors\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0merrors\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   4181\u001b[0m             \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 4182\u001b[0;31m                 \u001b[0mnew_axis\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdrop\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlabels\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0merrors\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0merrors\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   4183\u001b[0m             \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreindex\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m**\u001b[0m\u001b[0;34m{\u001b[0m\u001b[0maxis_name\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mnew_axis\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   4184\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m~/.cache/pypoetry/virtualenvs/besser-tanken-XZndgdH5-py3.9/lib/python3.9/site-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36mdrop\u001b[0;34m(self, labels, errors)\u001b[0m\n\u001b[1;32m   6016\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mmask\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0many\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   6017\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0merrors\u001b[0m \u001b[0;34m!=\u001b[0m \u001b[0;34m\"ignore\"\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 6018\u001b[0;31m                 \u001b[0;32mraise\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34mf\"{labels[mask]} not found in axis\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   6019\u001b[0m             \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mindexer\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m~\u001b[0m\u001b[0mmask\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   6020\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdelete\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mindexer\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;31mKeyError\u001b[0m: \"['station_uuid'] not found in axis\""
+     ]
+    }
+   ],
+   "source": [
+    "b2 = buehl.drop('station_uuid')\n",
+    "#b2 = b2.melt('date', var_name='cols', value_name='vals')\n",
+    "#g = sns.factorplot(x=\"date\", y=\"vals\", hue='cols', data=b2)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/tankerkoenig-data b/tankerkoenig-data
new file mode 160000
index 0000000..afed4bb
--- /dev/null
+++ b/tankerkoenig-data
@@ -0,0 +1 @@
+Subproject commit afed4bbe40d221673f14e6007fcba6667433db7e