From fa7aeaaa885c603bbc484d8f123ff5f5f9b1d3da Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Alexander=20Ro=C3=9Fmann?=
<alexander.rossmann@reutlingen-university.de>
Date: Thu, 13 Jun 2024 10:40:26 +0000
Subject: [PATCH] Delete notebook_Random Forrest Regressor.ipynb
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.../notebook_Random Forrest Regressor.ipynb | 5129 -----------------
1 file changed, 5129 deletions(-)
delete mode 100644 Forecast/Sales Forecast for retail store/notebook_Random Forrest Regressor.ipynb
diff --git a/Forecast/Sales Forecast for retail store/notebook_Random Forrest Regressor.ipynb b/Forecast/Sales Forecast for retail store/notebook_Random Forrest Regressor.ipynb
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-{
- "cells": [
- {
- "attachments": {},
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# 1. Business Understanding"
- ]
- },
- {
- "attachments": {},
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Ein Einzelh\u00e4ndler braucht einen sehr hohen Umsatz und eine Just-in-time-Lieferung von Produkten, um erfolgreich zu sein. Dazu werden sehr genaue Prognosen ben\u00f6tigt, die genaue Aussagen dar\u00fcber erlauben, welche Filialen in welchen Abteilungen wie viel Umsatz pro Woche machen. Die Fragestellung lautet daher wie folgt: Wie hoch ist die w\u00f6chentliche Umsatzprognose f\u00fcr alle Filialen eines fiktiven Marktes, wenn wir die Daten der letzten drei Jahre, demographische Informationen (VPI, Arbeitslosigkeit, Temperatur, etc.) ber\u00fccksichtigen? Wie hoch ist dann der Wochenumsatz pro Abteilung in einer dieser Filialen?"
- ]
- },
- {
- "attachments": {},
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# 2. Daten und Datenverst\u00e4ndnis"
- ]
- },
- {
- "attachments": {},
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Die f\u00fcr das Notebook verwendeten Daten sind in drei Dateien unterteilt. Sie enthalten verschiedene Merkmale und die gemeinsamen Attributsspeicher. "
- ]
- },
- {
- "attachments": {},
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## 2.1. Import von relevanten Modulen"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 1,
- "metadata": {},
- "outputs": [],
- "source": [
- "import numpy as np\n",
- "import pandas as pd\n",
- "import matplotlib.pyplot as plt\n",
- "import seaborn as sns\n",
- "sns.set()"
- ]
- },
- {
- "attachments": {},
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## 2.2. Trainingsdaten einlesen"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 2,
- "metadata": {},
- "outputs": [],
- "source": [
- "walmart_features_data = pd.read_csv('https://storage.googleapis.com/ml-service-repository-datastorage/Sales_Forecast_for_retail_store_features.csv') \n",
- "walmart_train_data = pd.read_csv('https://storage.googleapis.com/ml-service-repository-datastorage/Sales_Forecast_for_retail_store_train.csv')\n",
- "walmart_stores_data = pd.read_csv('https://storage.googleapis.com/ml-service-repository-datastorage/Sales_Forecast_for_retail_store_stores.csv')"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 3,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/html": [
- "<div>\n",
- "<style scoped>\n",
- " .dataframe tbody tr th:only-of-type {\n",
- " vertical-align: middle;\n",
- " }\n",
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- " .dataframe tbody tr th {\n",
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- " }\n",
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- "</style>\n",
- "<table border=\"1\" class=\"dataframe\">\n",
- " <thead>\n",
- " <tr style=\"text-align: right;\">\n",
- " <th></th>\n",
- " <th>Store</th>\n",
- " <th>Dept</th>\n",
- " <th>Date</th>\n",
- " <th>Weekly_Sales</th>\n",
- " <th>IsHoliday</th>\n",
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- " </thead>\n",
- " <tbody>\n",
- " <tr>\n",
- " <th>0</th>\n",
- " <td>1</td>\n",
- " <td>1</td>\n",
- " <td>2010-02-05</td>\n",
- " <td>24924.50</td>\n",
- " <td>False</td>\n",
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- " <tr>\n",
- " <th>1</th>\n",
- " <td>1</td>\n",
- " <td>1</td>\n",
- " <td>2010-02-12</td>\n",
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- " <td>True</td>\n",
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- " <th>2</th>\n",
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- " <td>41595.55</td>\n",
- " <td>False</td>\n",
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- " <th>3</th>\n",
- " <td>1</td>\n",
- " <td>1</td>\n",
- " <td>2010-02-26</td>\n",
- " <td>19403.54</td>\n",
- " <td>False</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>4</th>\n",
- " <td>1</td>\n",
- " <td>1</td>\n",
- " <td>2010-03-05</td>\n",
- " <td>21827.90</td>\n",
- " <td>False</td>\n",
- " </tr>\n",
- " </tbody>\n",
- "</table>\n",
- "</div>"
- ],
- "text/plain": [
- " Store Dept Date Weekly_Sales IsHoliday\n",
- "0 1 1 2010-02-05 24924.50 False\n",
- "1 1 1 2010-02-12 46039.49 True\n",
- "2 1 1 2010-02-19 41595.55 False\n",
- "3 1 1 2010-02-26 19403.54 False\n",
- "4 1 1 2010-03-05 21827.90 False"
- ]
- },
- "execution_count": 3,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "walmart_train_data.head(5)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 4,
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "<class 'pandas.core.frame.DataFrame'>\n",
- "RangeIndex: 421570 entries, 0 to 421569\n",
- "Data columns (total 5 columns):\n",
- " # Column Non-Null Count Dtype \n",
- "--- ------ -------------- ----- \n",
- " 0 Store 421570 non-null int64 \n",
- " 1 Dept 421570 non-null int64 \n",
- " 2 Date 421570 non-null object \n",
- " 3 Weekly_Sales 421570 non-null float64\n",
- " 4 IsHoliday 421570 non-null bool \n",
- "dtypes: bool(1), float64(1), int64(2), object(1)\n",
- "memory usage: 13.3+ MB\n"
- ]
- }
- ],
- "source": [
- "walmart_train_data.info()"
- ]
- },
- {
- "attachments": {},
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Daten beschreiben: Wir haben einen Datensatz mit 421.570 Eintr\u00e4gen. Jede Zeile enth\u00e4lt die Werte \"Store\", \"Dept\", \"Date\", \"Weekly_Sales\" und \"IsHoliday\". Diese Tabelle enth\u00e4lt also bereits den Wert, der f\u00fcr unsere Betrachtung relevant ist: \"W\u00f6chentliche_Ums\u00e4tze\". Wir werden eine Prognose f\u00fcr diesen Wert erstellen und nun nach Merkmalen suchen, die diesen Wert beeinflussen. Das Format dieser Werte ist ein boolescher Wert, eine Gleitkommazahl, zwei Ganzzahlen und ein Objekt."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 5,
- "metadata": {},
- "outputs": [
- {
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- "<table border=\"1\" class=\"dataframe\">\n",
- " <thead>\n",
- " <tr style=\"text-align: right;\">\n",
- " <th></th>\n",
- " <th>Store</th>\n",
- " <th>Dept</th>\n",
- " <th>Date</th>\n",
- " <th>Weekly_Sales</th>\n",
- " <th>IsHoliday</th>\n",
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- " <th>count</th>\n",
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- " <tr>\n",
- " <th>unique</th>\n",
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- " <td>NaN</td>\n",
- " <td>143</td>\n",
- " <td>NaN</td>\n",
- " <td>2</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>top</th>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>2011-12-23</td>\n",
- " <td>NaN</td>\n",
- " <td>False</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>freq</th>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>3027</td>\n",
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- " <tr>\n",
- " <th>mean</th>\n",
- " <td>22.200546</td>\n",
- " <td>44.260317</td>\n",
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- " <td>15981.258123</td>\n",
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- " <tr>\n",
- " <th>std</th>\n",
- " <td>12.785297</td>\n",
- " <td>30.492054</td>\n",
- " <td>NaN</td>\n",
- " <td>22711.183519</td>\n",
- " <td>NaN</td>\n",
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- " <tr>\n",
- " <th>min</th>\n",
- " <td>1.000000</td>\n",
- " <td>1.000000</td>\n",
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- " <td>-4988.940000</td>\n",
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- " <tr>\n",
- " <th>25%</th>\n",
- " <td>11.000000</td>\n",
- " <td>18.000000</td>\n",
- " <td>NaN</td>\n",
- " <td>2079.650000</td>\n",
- " <td>NaN</td>\n",
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- " <tr>\n",
- " <th>50%</th>\n",
- " <td>22.000000</td>\n",
- " <td>37.000000</td>\n",
- " <td>NaN</td>\n",
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- " <th>75%</th>\n",
- " <td>33.000000</td>\n",
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- " <td>20205.852500</td>\n",
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- " <tr>\n",
- " <th>max</th>\n",
- " <td>45.000000</td>\n",
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- " <td>NaN</td>\n",
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- " <td>NaN</td>\n",
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- "</div>"
- ],
- "text/plain": [
- " Store Dept Date Weekly_Sales IsHoliday\n",
- "count 421570.000000 421570.000000 421570 421570.000000 421570\n",
- "unique NaN NaN 143 NaN 2\n",
- "top NaN NaN 2011-12-23 NaN False\n",
- "freq NaN NaN 3027 NaN 391909\n",
- "mean 22.200546 44.260317 NaN 15981.258123 NaN\n",
- "std 12.785297 30.492054 NaN 22711.183519 NaN\n",
- "min 1.000000 1.000000 NaN -4988.940000 NaN\n",
- "25% 11.000000 18.000000 NaN 2079.650000 NaN\n",
- "50% 22.000000 37.000000 NaN 7612.030000 NaN\n",
- "75% 33.000000 74.000000 NaN 20205.852500 NaN\n",
- "max 45.000000 99.000000 NaN 693099.360000 NaN"
- ]
- },
- "execution_count": 5,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "walmart_train_data.describe(include='all')"
- ]
- },
- {
- "cell_type": "raw",
- "metadata": {},
- "source": [
- "describe data: We have included corresponding values for all rows in the table. It is interesting that \"Weekly_Sales\" takes a negative value in the minimum. The maximum value is 693,099, which is quite high. The \"Store\" value ranks from 1 to 45, so this will be the \"store number\" specification, since we already know that there are 45 stores. The \"Dept\" value ranks from 1 to 99, so I'm guessing that this is the name of the department within the stores, and thus there are 99 different departments. December 23rd seems to be a high frequency day."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 6,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "Index(['Store', 'Dept', 'Date', 'Weekly_Sales', 'IsHoliday'], dtype='object')"
- ]
- },
- "execution_count": 6,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "walmart_train_data.columns"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 7,
- "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",
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- "\n",
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- "</style>\n",
- "<table border=\"1\" class=\"dataframe\">\n",
- " <thead>\n",
- " <tr style=\"text-align: right;\">\n",
- " <th></th>\n",
- " <th>Store</th>\n",
- " <th>Dept</th>\n",
- " <th>Date</th>\n",
- " <th>Weekly_Sales</th>\n",
- " <th>IsHoliday</th>\n",
- " </tr>\n",
- " </thead>\n",
- " <tbody>\n",
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- "</table>\n",
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- ],
- "text/plain": [
- "Empty DataFrame\n",
- "Columns: [Store, Dept, Date, Weekly_Sales, IsHoliday]\n",
- "Index: []"
- ]
- },
- "execution_count": 7,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "walmart_train_data[walmart_train_data.duplicated(keep=False)] # existieren duplizierte Reihen ?"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 8,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "Store 0\n",
- "Dept 0\n",
- "Date 0\n",
- "Weekly_Sales 0\n",
- "IsHoliday 0\n",
- "dtype: int64"
- ]
- },
- "execution_count": 8,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "walmart_train_data.isnull().sum() # existieren Nullwerte ? Die Summe aller vorhandenen Nullwerte --> keine vorhanden"
- ]
- },
- {
- "attachments": {},
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## 2.2.1. Deskriptive Analyse"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 9,
- "metadata": {},
- "outputs": [
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "C:\\Users\\eebal\\Anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
- " warnings.warn(msg, FutureWarning)\n"
- ]
- },
- {
- "data": {
- "text/plain": [
- "<AxesSubplot:xlabel='Weekly_Sales', ylabel='Density'>"
- ]
- },
- "execution_count": 9,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": 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4Ryqb8TP4iUjlPJrx/8///A/8/PxgMpnwzjvvoGvXrpg/f3617+nXrx8++ugj6HQ65OTkwG63w8/Pr16K9oQQotwzdwFX8LPHT0TqdtMZ/+7du7Fu3TqkpqbCx8cHXbp0QZ8+fWA0Gm96cr1ej9WrV+ODDz7A0KFDa3T3b2Cgv8evrYw9x7nqSJIAk7/zpjM/Xz0uXS1CUJCpTueWkzfXdiPWKg/WKg/WWqra4N+1axcSEhIwZ84cdO3aFZIk4bfffsOKFStgNpsRHh5+0wHmzJmDGTNm4KmnnsLmzZsxfvx4jwrLycmHw1H7fXUKiqwAnK2evPySh8Y4BIrMNmRn59X6vHIKCjJ5bW03Yq3yYK3yUEOtGo3k8YS52uD/6KOPsGHDBrRu3dp9rFOnTujVqxcWLVpUbfCfPn0aFosF3bp1g6+vL8LDw5Gamurht1B3QlT8paHXaWB3CFhtDuh1HnW5iIgUp9r0KygoKBf6Lh07doTZbK72xBkZGViyZAksFgssFgv27NmDe++9t27V1oAr98uu6tGVhH0R+/xEpGLVzvi1Wm2Vf1bZjLqs0NBQHDt2DKNGjYJWq0V4eDiioqJqV2UtuOoru6rHUBL8xRY7Am7ddWYiIq/i0XLO2po9ezZmz54t5xBVcs/4yxzTaUuCn3fvEpGKVRv8qamp6NOnT4XjQghYLBbZiqoPjkpm/PoyM34iIrWqNvh37959q+qod6WtntJjpcHPGT8RqVe1wd+mTZtbVUe9q+ziriv4i8yc8ROReil2TaO71YPKWj2c8ROReik2+Cud8WvZ4yciUnDwV0x+9zp+ruohIhVTbvCXfCy7nFMjSTDouUMnEambcoO/klU9AOCj17HHT0SqpuDgd36Ubkh+H6OWM34iUjXFBr9rZ88bZ/xGPYOfiNRNscFf2uOvOOPnxV0iUjPlBn+1PX7O+IlIvRQb/I5K1vEDgNGg5cVdIlI1xQZ/6bbRN7R6DFpu2UBEqqbg4Hd+rNDqMfDiLhGpm4KDv4oev1EHm90Bq43hT0TqpNjgd/f4b2j1+PvqAQB5hdZbXRIRkVdQbPBXNeNn8BOR2ik4+J0fb7xz1+TnCn7vfoIYEZFcFBz8rv34y/P3NQAAchn8RKRSCg5+58cbWz2uGX9uAVs9RKROCg7+ig9bB5zLObUaCXlFnPETkTpV+8zdulqzZg127doFAAgNDcX8+fPlHK4c16qeG0mShIBGBuRxxk9EKiXbjP/AgQPYv38/kpKSsHXrVvzxxx/YvXu3XMNVIFD5jB8ATL56XtwlItWSbcYfFBSEuLg4GAzOi6mdOnVCZmamXMNVUNW2zABgamRALpdzEpFKyRb8nTt3dn+elpaGXbt24dNPP5VruAqqurgLAAF+emRdKbxltRAReRNZe/wAcOrUKTz55JOYP38+OnTo4PH7AgP96zSuIf0aAOeduyZ/H/dxPz8jWgT645dTlxEUZKrTGHLwxpqqwlrlwVrlwVpLyRr8R44cwZw5c7Bo0SJERUXV6L05Ofnudk1tFBc7e/iSBOTlF7uPFxaaoZMEii12ZGReg1GvrfUY9S0oyITs7LyGLsMjrFUerFUeaqhVo5E8njDLFvwXLlzArFmzkJCQgJCQELmGqVJVd+4CgMnPed0hr9ACY2PfW1kWEVGDky34161bB7PZjNdee819bMKECZg4caJcQ5ZT1Z27ABDgDn4rmjP4iUhlZAv+JUuWYMmSJXKd/qaqu7jL/XqISM0Ue+euo5rkNzUq2a+HN3ERkQopNvira/WYXFszc9sGIlIhBQe/82NlF3d9DFoYdBpcz2fwE5H6KDb4HVU8iMV5TEJgYx9cvl5c8Q+JiBRO9hu4GkpVLX5JI6HAbENggA8uXilEgdkGADDqddAp9tcgEVEpBQe/q8cvASi9EcxstePoyWzYHQKXrhbi0PGLkCQJ93VrCZ1RsT8OIiI3xc5xq1vOCTiXdNrsAkVm+60riojICyg4+Kvu8QNl7t7lyh4iUhnlBr/7s8qT33UTVz63ZyYilVFs8Fe3Hz8ANPLVQ5LAffmJSHUUG/yuHr+miuTXaiQ08uGTuIhIfRQc/K6ru1W/xuSnZ6uHiFRHscHvKPlYTe7D5KdHLmf8RKQyig3+0lU9VUe/yc8Ai9UBs5VLOolIPRQc/M6P1eR+me2Z2e4hIvVQcPCXvXO3cmWfxEVEpBaKDX6HBzN+f1+u5Sci9VFs8Huyqkev08DXqOUFXiJSFQUHv/NjVev4XUx+Bs74iUhVFBz8VT+BqyyTn54Xd4lIVRQc/CWfeDDjLzTbYLFxSScRqYOCg7/6vXpcXM/fzbnGp3ERkTooNvgdN7+2CwAwNXIGPx/DSERqIWvw5+fnY/jw4cjIyJBzmEp5cucuAJh8nWv5s68VyV4TEZE3kC34jx49iokTJyItLU2uIaolhLjpbB8AjAYtDHoNg5+IVEO24N+8eTNeeOEFtGjRQq4hquUQuHmfp0RTkxHnLuXLWg8RkbeQ7eniK1askOvUHhHi5m0el8AAH5w8dw02uwM6rWIvexARAZAx+OsqMNC/Tu/X6TTQlOS+yd/HfVyv15X7GgDatgzA8bSrKLAJ3HWHqU7j1lVQUMOOXxOsVR6sVR6stZTXBn9OTr778Ym1YSmz1XJefumKHavVVu5rAGhkdM7yfzl+EY2N2lqPWVdBQSZkZ+c12Pg1wVrlwVrloYZaNRrJ4wmzYvsazou7nrV6/H31aOSjw9kLuTJXRUTU8BQc/PD44q4kSWjf0oS0i7fHjICIqC5kD/69e/eibdu2cg9TgRDipnftltW+pT/OZxfwaVxEpHiKnfE7atDqAYA72zSGQwik/nVVxqqIiBqeYoPfuZzT89d3btsEvkYtjqRmy1cUEZEXUHDw16zVo9dp0KtTc/xy6jLsDod8hRERNTDFBr/NLjy+gculz38HIb/IilPnrstUFRFRw1Ns8BeZbTDoavbt9bizGfQ6DVL+75JMVRERNTzFBn+h2QaD3vObsSSNBLtwzvr3HctExuV8FJhtsLHrQ0QKo9zgL7bBWIPgN1vtSDmRhTZBjeBwAB/tSkXKiSyYrTYZqyQiuvUUG/xFZhsM+pp/e/6+enRp3wSnz1/HZW7VTEQKpNjgLyy2waCr3b47Pe8KhJ+PDj/8mon8Ij6InYiURZHBb7M7YLbaYazFjB8AjHotQoPboMhsx6f/e7KeqyMialiKDP7CYmdfviYXd2/UvLEPet4ViGN/5uDkuWv1VBkRUcNTZPAXFDvbM3UJfgC4u0NTNG5kQOJ3f7qf4UtEdLtTZPCXzvjr9u3ptBpEDfgvnM7Mxfe/ZtZHaUREDU6RwV9QEvzGWl7cLat/9zvQo2MzfPq/J5F2kfv1E9HtT5HBX+hu9dT929NIEmaMuBsmPwNWJR7jQ9mJ6LanyOAvqIeLuy6SRoJGq8HTMT0gScBrm47g2Jkc3tFLRLctRQZ/YT1d3AVK7+jNuJSPh+9tC71Oi3e/OIbD/5dV53MTETUERQZ/QbHzrl2tpma7c96Mv68eQ/u3QxN/I9Zu/wNb952p0wPhiYgagq6hC5BDYbENfkZ5vjUfgw4R/dvhz4zr2P5TGg4ez0L0wI7of3fLGm8DTUTUEBQ647fCz0cv2/l1Wg2mRHbFEyPuhl6nwb93HEf8p78gPSuPvX8i8nqKDH45Z/wuFpsDFqsdYX3aoP/dLXDmfC5e+fAwtu07zc3diMirKbLVU1BsQ9MA4y0ZS5IkdGnfFG1b+OPg8Uv4OjkdXyeno31Lf/TpHIR7OgXiv+4wQcM2EBF5CUUGf6HZijbGRrd0zEY+ejzcpw06tmmMoyezcfTPHGzbfxZb95+FyU+PHh0D0bNTILp3bAZ/X/naUERENyNr8O/YsQP//Oc/YbPZMG3aNEyePFnO4dwKim3w82mY32kBjQwIaGTAg71a4b5uQci8XICM7AIcPX0ZyX9chCQBnVo3xj2dAtG1fRO0a+EPH4Mif/8SkZeSLXGysrKQkJCALVu2wGAwYMKECejfvz/uuusuuYYEULIls8Uue4/fEz4GHe5s3Rh3tm6Mvt1aIi0zF8fTruB42hUk/XjG/TpfoxYmPwMCG/vC16B1/vLw05d8dP4iMfnp0biRAb5GHVcPEVGdyJaOBw4cwP33348mTZoAACIiIvDNN9/gmWee8ej9mlqswc/JLcaR1Eto0dQXzZv6wtegg69RB7uttLWi02oqXfEj93EB53OAO7QKQIdWASi22HA1zww/Xz0KCq3IL7KiyGJHXoEZaRfzUFRsRWV3CGg1EvQ6DTSSBI3G+T+tJEHSABqN894FSXIec/25RoPyX0uu90jQlvy5JLk+d/45JLivS2ggQZKcr5EkABLg52dAcZHFfUyCBPf/ZTL/Yqrp2f38DCgstMg7SA1JVQzg55dT81obCGutf/6+OgwO9K9V/tXkPbIF/6VLlxAUFOT+ukWLFjh27JjH72/atOY9+sBAf/x3x+aYOPTual93Z9umXnWciKiswEB/Wc8v23JOh8NRriUhhGCLgojIC8gW/HfccQeys7PdX2dnZ6NFixZyDUdERB6SLfgHDBiA5ORkXLlyBUVFRfj2228xaNAguYYjIiIPydbjb9myJebNm4epU6fCarVizJgx6Nmzp1zDERGRhyTBh8kSEamKIvfqISKiqjH4iYhUhsFPRKQyDH4iIpVRdPDv2LEDw4YNQ3h4ODZt2iT7ePn5+Rg+fDgyMjIAOLetGDFiBMLDw5GQkOB+3YkTJxAbG4uIiAgsXrwYNpvz4fCZmZmYPHkyhg4diqeffhoFBQUAgNzcXMycORORkZGYPHmy+/4Ii8WCv//974iMjERMTAxOnz7tUZ1r1qxBVFQUoqKiEB8f79W1rlq1CsOGDUNUVBTWr1/v1bW6vP7664iLi/PqWqdMmYKoqChER0cjOjoaR48e9dpa9+7di9jYWERGRuKVV17x2p9rYmKi++cZHR2Ne++9F8uXL/fKWiEU6uLFiyIsLExcvXpVFBQUiBEjRohTp07JNt6vv/4qhg8fLrp37y7OnTsnioqKRGhoqPjrr7+E1WoV06dPF99//70QQoioqCjxyy+/CCGEWLhwodi0aZMQQoiZM2eKr776SgghxJo1a0R8fLwQQoiXXnpJ/Otf/xJCCJGUlCSeffZZIYQQ77//vli6dKkQQohDhw6JsWPH3rTOn376SYwfP16YzWZhsVjE1KlTxY4dO7yy1oMHD4oJEyYIq9UqioqKRFhYmDhx4oRX1upy4MAB0b9/f7FgwQKv/TvgcDjEwIEDhdVqdR/z1lr/+usvMXDgQHHhwgVhsVjExIkTxffff++VtZZ18uRJ8cgjj4jMzEyvrFWxwb9lyxaxcOFC99dr1qwR7777rmzjLVq0SKSkpIiwsDBx7tw5cfDgQTF16lT3nyclJYm4uDiRkZEhBg8e7D6ekpIipkyZIiwWiwgODnb/Y8zMzBQPP/ywEEKIsLAwkZmZKYQQwmq1iuDgYGGxWMSjjz4qUlJS3OcaPHiwOH/+fLV1njx50v2XTQjnX6Z3333XK2sVQgiLxSKEECIjI0MMGjTIa3+uQghx9epVMXbsWLF+/XqxYMECr631zz//FAMHDhRTpkwRI0aMEBs3bvTaWtetWydWrlzp/vrixYteW2tZkyZNEjt37vTaWhXb6qlsk7isrCzZxluxYgX69u170/FvPB4UFISsrCxcvXoV/v7+0Ol05Y7feC6dTgd/f39cuXKl0nNdvHix2jo7d+6M3r17AwDS0tKwa9cuSJLklbUCgF6vx+rVqxEVFYWQkBCv/bkCwLJlyzBv3jwEBARUOL831Zqbm4uQkBD84x//wIYNG/DZZ58hMzPTK2tNT0+H3W7HU089hejoaHzyySde+3N1OXDgAIqLixEZGem1tSo2+Bt6k7iqxq/qeGX1VVWvEAIajabCe1zHPXHq1ClMnz4d8+fPR7t27by61jlz5iA5ORkXLlxAWlqaV9aamJiIVq1aISQkxH3MW/8OBAcHIz4+HiaTCc2aNcOYMWOwevVqr6zVbrcjOTkZK1euxOeff45jx47h3LlzXlmry2effYa//e1vALz374Big7+hN4mravwbj1++fBktWrRAs2bNkJeXB7vdXqHeFi1a4PLlywAAm82GgoICNGnSBC1btsSlS5cqnOtmjhw5gsceewzPP/88YmJivLbW06dP48SJEwAAX19fhIeH4+DBg15Z686dO/HTTz8hOjoaq1evxt69e5GYmOiVtR4+fBjJycnur4UQaNOmjVfW2rx5c4SEhKBZs2bw8fHBkCFDcODAAa+sFXBeaE1JScHDDz8MwHtzQLHB39CbxPXq1Qtnz551/6fqV199hUGDBqFNmzYwGo04cuQIAGDbtm0YNGgQ9Ho9+vbti507dwIAtm7d6q43NDQUW7duBeAMmL59+0Kv1yM0NBTbtm0D4PzHbDQa0bp162rrunDhAmbNmoU333wTUVFRXl1rRkYGlixZAovFAovFgj179mDChAleWev69evx1VdfYdu2bZgzZw4efvhhvP/++15Za15eHuLj42E2m5Gfn4+kpCQ899xzXllrWFgY9u/fj9zcXNjtduzbtw9Dhw71yloBIDU1FR06dICfnx8A7/23pdiLu0IIsX37dhEVFSXCw8PFv//971sypuvirhDOFR4jRowQ4eHhYsWKFcLhcAghhDhx4oQYPXq0iIiIEM8995wwm81CCOcFzEcffVRERkaK6dOni2vXrgkhnBcNn3zySTFs2DAxfvx49/mLi4vF/PnzxbBhw8SoUaPE77//ftP6Xn75ZdG7d28xcuRI9/8++eQTr6xVCCFWr14tIiMjxfDhw8Xq1au99uda1pdffikWLFjg1bUmJCSIoUOHivDwcLFhwwavrjUxMdH97/ill14Sdrvda2v9+uuvxdy5c8sd88ZauUkbEZHKKLbVQ0RElWPwExGpDIOfiEhlGPxERCrD4CciUhkGP3mlxx9/HB9++KH767Nnz6JLly54++233cdycnLQo0cP5OXl1fj8cXFxWLduncfHPfX9999j/PjxGDlyJKKiovDss896dKv/lClT8M0339R6XKKaYPCTVxo0aBAOHjzo/vq7775DWFgY9uzZ4z72888/o0+fPjCZTA1RYgVZWVlYsGAB3n77bWzfvh1ff/01unbtirlz5zZ0aUTlMPjJKw0aNAiHDx+Gw+EA4Az+mTNnoqCgAH/99RcAIDk5GQ899BD+85//YNKkSYiJicHo0aPx3Xffuc+TmJiI2NhYjBo1Co899lile5WvXLkS06ZNc+97DgDbt2/HhAkT3F9nZmZi4MCBsFgsVdZ89epVWK1WFBYWuo9NmzYNTz75JACgsLAQ8+fPx/jx4xEREYHY2FicOXOmwnmq+n6ys7Mxffp0xMTEICYmBu+8844nP0qiCnQNXQBRZTp27IiAgACkpqaidevWOHv2LHr37o1BgwZh7969eOyxx5CcnIzRo0e72zNt27ZFVlYWxo0bhy5duiAjIwNbt27Fpk2b4Ovri/379+OZZ57Brl27ADj3qFm+fDkuXbqEtWvXwmAwuMcfOnQoXnvtNZw6dQqdO3dGYmIiYmJiyr3mRl27dsW4ceMQExOD9u3bo0+fPggJCUFERAQA4Mcff0RAQAA+//xzAM7dPDdt2oSlS5e6z3H9+nUsXLiw0u8nKSkJbdu2xQcffIDCwkIsXrwYeXl5XvNfPHT7YPCT13K1ewIDAzFgwABoNBqEhYVh06ZNGDJkCCRJQm5uLrKzszFr1iz3+yRJQmpqKlJSUpCenl5u5p6bm4tr164BADZs2ICcnBxs3bq1QqAbDAaMHTsWiYmJWLBgAZKSkrBx48ab1hwXF4cnn3wShw4dQkpKCuLj47Fx40Zs2rQJQ4cORbt27bBx40akp6fj0KFDCA4OLvf+X3/9tcrv58EHH8TMmTNx4cIFDBgwAM8//zxDn2qFwU9ea9CgQfjiiy9gNBoxePBgAEBISAiWLFnibvPY7XZ06tQJiYmJ7vdlZWWhWbNmOHjwIKKjo/H3v/8dgHOL3EuXLqFx48YAgPvuuw99+vTBwoUL8fnnn0Ov15cbf8KECRgzZgz69euHzp07o127dtXWu2fPHly7dg2jR49GREQEIiIiMG/ePISGhuL48eP47bffsHnzZkyePBkjRoxAkyZN3I/pdKnu+9Hr9dizZw+Sk5Px888/Y+zYsVi7di169OhR+x8yqRJ7/OS1+vfvjxMnTuDQoUN48MEHAQA+Pj7o3r07Pv74Y4SGhqJ3795IT09HSkoKAOdzTCMiIpCVlYWBAwfi66+/dm9Z++mnn2LatGnu8/fo0QOPPvooTCYT1qxZU2H8Vq1aoXfv3li5ciUmTpx403obNWqEt99+G3/++af72Llz56DVatG+fXvs378fMTExGDt2LDp27Ii9e/e6t991qe77efPNN/Hee+9hyJAhWLx4Me666y6cOnWqhj9VIs74yYv5+vqiQ4cOsFqt5VoaoaGheOONN9C/f38YDAasXr3avc2wEALx8fFo27Yt2rZtixkzZmD69OmQJAn+/v5Ys2ZNuYdWSJKElStXYtSoUQgNDa1QQ2xsLF5++eVK/+xG999/P5YuXYoFCxYgLy8PWq0WQUFBWLt2LRo3bozp06dj2bJl+OKLLwA4Q/7kyZPlztGsWbMqv59p06YhLi4Ow4cPh8FgQJcuXdxbaxPVBHfnJKqCw+HA8uXL0bp1a8ycObOhyyGqN5zxE1UiPz8fYWFh6NOnD+Li4tzHJ02aVG7ZZ1mbNm2Cv7//rSqRqNY44yciUhle3CUiUhkGPxGRyjD4iYhUhsFPRKQyDH4iIpVh8BMRqcz/A5k2XrFDebBSAAAAAElFTkSuQmCC",
- "text/plain": [
- "<Figure size 432x288 with 1 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "sns.distplot(walmart_train_data['Weekly_Sales']) # wie sieht die Verteilung unserer dependent variable aus ?"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 10,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "<AxesSubplot:>"
- ]
- },
- "execution_count": 10,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": 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",
- "text/plain": [
- "<Figure size 432x288 with 2 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "sns.heatmap(walmart_train_data.corr()) "
- ]
- },
- {
- "attachments": {},
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## 2.3. Merkmalsdaten einlesen"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 11,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/html": [
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- " <thead>\n",
- " <tr style=\"text-align: right;\">\n",
- " <th></th>\n",
- " <th>Store</th>\n",
- " <th>Date</th>\n",
- " <th>Temperature</th>\n",
- " <th>Fuel_Price</th>\n",
- " <th>MarkDown1</th>\n",
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- " <th>MarkDown3</th>\n",
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- " <tr>\n",
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- " <td>2010-02-19</td>\n",
- " <td>39.93</td>\n",
- " <td>2.514</td>\n",
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- " <tr>\n",
- " <th>3</th>\n",
- " <td>1</td>\n",
- " <td>2010-02-26</td>\n",
- " <td>46.63</td>\n",
- " <td>2.561</td>\n",
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- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
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- " <td>False</td>\n",
- " </tr>\n",
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- " <th>4</th>\n",
- " <td>1</td>\n",
- " <td>2010-03-05</td>\n",
- " <td>46.50</td>\n",
- " <td>2.625</td>\n",
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- " <td>211.350143</td>\n",
- " <td>8.106</td>\n",
- " <td>False</td>\n",
- " </tr>\n",
- " </tbody>\n",
- "</table>\n",
- "</div>"
- ],
- "text/plain": [
- " Store Date Temperature Fuel_Price MarkDown1 MarkDown2 \\\n",
- "0 1 2010-02-05 42.31 2.572 NaN NaN \n",
- "1 1 2010-02-12 38.51 2.548 NaN NaN \n",
- "2 1 2010-02-19 39.93 2.514 NaN NaN \n",
- "3 1 2010-02-26 46.63 2.561 NaN NaN \n",
- "4 1 2010-03-05 46.50 2.625 NaN NaN \n",
- "\n",
- " MarkDown3 MarkDown4 MarkDown5 CPI Unemployment IsHoliday \n",
- "0 NaN NaN NaN 211.096358 8.106 False \n",
- "1 NaN NaN NaN 211.242170 8.106 True \n",
- "2 NaN NaN NaN 211.289143 8.106 False \n",
- "3 NaN NaN NaN 211.319643 8.106 False \n",
- "4 NaN NaN NaN 211.350143 8.106 False "
- ]
- },
- "execution_count": 11,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "walmart_features_data.head(5)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 12,
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "<class 'pandas.core.frame.DataFrame'>\n",
- "RangeIndex: 8190 entries, 0 to 8189\n",
- "Data columns (total 12 columns):\n",
- " # Column Non-Null Count Dtype \n",
- "--- ------ -------------- ----- \n",
- " 0 Store 8190 non-null int64 \n",
- " 1 Date 8190 non-null object \n",
- " 2 Temperature 8190 non-null float64\n",
- " 3 Fuel_Price 8190 non-null float64\n",
- " 4 MarkDown1 4032 non-null float64\n",
- " 5 MarkDown2 2921 non-null float64\n",
- " 6 MarkDown3 3613 non-null float64\n",
- " 7 MarkDown4 3464 non-null float64\n",
- " 8 MarkDown5 4050 non-null float64\n",
- " 9 CPI 7605 non-null float64\n",
- " 10 Unemployment 7605 non-null float64\n",
- " 11 IsHoliday 8190 non-null bool \n",
- "dtypes: bool(1), float64(9), int64(1), object(1)\n",
- "memory usage: 712.0+ KB\n"
- ]
- }
- ],
- "source": [
- "walmart_features_data.info()"
- ]
- },
- {
- "attachments": {},
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Daten beschreiben: Wir haben einen Datensatz mit 8.190 Eintr\u00e4gen. Jede Zeile enth\u00e4lt die Werte \"Store\", \"Date\", \"Temperature\", \"Fuel_Price\", \"MarkDown1\", \"MarkDown2\", \"MarkDown3\", \"MarkDown4\", \"MarkDown5\", \"CPI\", \"Unemployment\" und \"IsHoliday\". Das Format dieser Werte ist ein Boolean, 9 Float, eine Integer und 1 Object."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 13,
- "metadata": {},
- "outputs": [
- {
- "data": {
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- "<table border=\"1\" class=\"dataframe\">\n",
- " <thead>\n",
- " <tr style=\"text-align: right;\">\n",
- " <th></th>\n",
- " <th>Store</th>\n",
- " <th>Date</th>\n",
- " <th>Temperature</th>\n",
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- " </tr>\n",
- " </thead>\n",
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- " <tr>\n",
- " <th>count</th>\n",
- " <td>8190.000000</td>\n",
- " <td>8190</td>\n",
- " <td>8190.000000</td>\n",
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- " <tr>\n",
- " <th>unique</th>\n",
- " <td>NaN</td>\n",
- " <td>182</td>\n",
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- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
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- " <td>2</td>\n",
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- " <tr>\n",
- " <th>top</th>\n",
- " <td>NaN</td>\n",
- " <td>2011-12-16</td>\n",
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- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>False</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>freq</th>\n",
- " <td>NaN</td>\n",
- " <td>45</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
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- " <td>NaN</td>\n",
- " <td>7605</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>mean</th>\n",
- " <td>23.000000</td>\n",
- " <td>NaN</td>\n",
- " <td>59.356198</td>\n",
- " <td>3.405992</td>\n",
- " <td>7032.371786</td>\n",
- " <td>3384.176594</td>\n",
- " <td>1760.100180</td>\n",
- " <td>3292.935886</td>\n",
- " <td>4132.216422</td>\n",
- " <td>172.460809</td>\n",
- " <td>7.826821</td>\n",
- " <td>NaN</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>std</th>\n",
- " <td>12.987966</td>\n",
- " <td>NaN</td>\n",
- " <td>18.678607</td>\n",
- " <td>0.431337</td>\n",
- " <td>9262.747448</td>\n",
- " <td>8793.583016</td>\n",
- " <td>11276.462208</td>\n",
- " <td>6792.329861</td>\n",
- " <td>13086.690278</td>\n",
- " <td>39.738346</td>\n",
- " <td>1.877259</td>\n",
- " <td>NaN</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>min</th>\n",
- " <td>1.000000</td>\n",
- " <td>NaN</td>\n",
- " <td>-7.290000</td>\n",
- " <td>2.472000</td>\n",
- " <td>-2781.450000</td>\n",
- " <td>-265.760000</td>\n",
- " <td>-179.260000</td>\n",
- " <td>0.220000</td>\n",
- " <td>-185.170000</td>\n",
- " <td>126.064000</td>\n",
- " <td>3.684000</td>\n",
- " <td>NaN</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>25%</th>\n",
- " <td>12.000000</td>\n",
- " <td>NaN</td>\n",
- " <td>45.902500</td>\n",
- " <td>3.041000</td>\n",
- " <td>1577.532500</td>\n",
- " <td>68.880000</td>\n",
- " <td>6.600000</td>\n",
- " <td>304.687500</td>\n",
- " <td>1440.827500</td>\n",
- " <td>132.364839</td>\n",
- " <td>6.634000</td>\n",
- " <td>NaN</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>50%</th>\n",
- " <td>23.000000</td>\n",
- " <td>NaN</td>\n",
- " <td>60.710000</td>\n",
- " <td>3.513000</td>\n",
- " <td>4743.580000</td>\n",
- " <td>364.570000</td>\n",
- " <td>36.260000</td>\n",
- " <td>1176.425000</td>\n",
- " <td>2727.135000</td>\n",
- " <td>182.764003</td>\n",
- " <td>7.806000</td>\n",
- " <td>NaN</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>75%</th>\n",
- " <td>34.000000</td>\n",
- " <td>NaN</td>\n",
- " <td>73.880000</td>\n",
- " <td>3.743000</td>\n",
- " <td>8923.310000</td>\n",
- " <td>2153.350000</td>\n",
- " <td>163.150000</td>\n",
- " <td>3310.007500</td>\n",
- " <td>4832.555000</td>\n",
- " <td>213.932412</td>\n",
- " <td>8.567000</td>\n",
- " <td>NaN</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>max</th>\n",
- " <td>45.000000</td>\n",
- " <td>NaN</td>\n",
- " <td>101.950000</td>\n",
- " <td>4.468000</td>\n",
- " <td>103184.980000</td>\n",
- " <td>104519.540000</td>\n",
- " <td>149483.310000</td>\n",
- " <td>67474.850000</td>\n",
- " <td>771448.100000</td>\n",
- " <td>228.976456</td>\n",
- " <td>14.313000</td>\n",
- " <td>NaN</td>\n",
- " </tr>\n",
- " </tbody>\n",
- "</table>\n",
- "</div>"
- ],
- "text/plain": [
- " Store Date Temperature Fuel_Price MarkDown1 \\\n",
- "count 8190.000000 8190 8190.000000 8190.000000 4032.000000 \n",
- "unique NaN 182 NaN NaN NaN \n",
- "top NaN 2011-12-16 NaN NaN NaN \n",
- "freq NaN 45 NaN NaN NaN \n",
- "mean 23.000000 NaN 59.356198 3.405992 7032.371786 \n",
- "std 12.987966 NaN 18.678607 0.431337 9262.747448 \n",
- "min 1.000000 NaN -7.290000 2.472000 -2781.450000 \n",
- "25% 12.000000 NaN 45.902500 3.041000 1577.532500 \n",
- "50% 23.000000 NaN 60.710000 3.513000 4743.580000 \n",
- "75% 34.000000 NaN 73.880000 3.743000 8923.310000 \n",
- "max 45.000000 NaN 101.950000 4.468000 103184.980000 \n",
- "\n",
- " MarkDown2 MarkDown3 MarkDown4 MarkDown5 \\\n",
- "count 2921.000000 3613.000000 3464.000000 4050.000000 \n",
- "unique NaN NaN NaN NaN \n",
- "top NaN NaN NaN NaN \n",
- "freq NaN NaN NaN NaN \n",
- "mean 3384.176594 1760.100180 3292.935886 4132.216422 \n",
- "std 8793.583016 11276.462208 6792.329861 13086.690278 \n",
- "min -265.760000 -179.260000 0.220000 -185.170000 \n",
- "25% 68.880000 6.600000 304.687500 1440.827500 \n",
- "50% 364.570000 36.260000 1176.425000 2727.135000 \n",
- "75% 2153.350000 163.150000 3310.007500 4832.555000 \n",
- "max 104519.540000 149483.310000 67474.850000 771448.100000 \n",
- "\n",
- " CPI Unemployment IsHoliday \n",
- "count 7605.000000 7605.000000 8190 \n",
- "unique NaN NaN 2 \n",
- "top NaN NaN False \n",
- "freq NaN NaN 7605 \n",
- "mean 172.460809 7.826821 NaN \n",
- "std 39.738346 1.877259 NaN \n",
- "min 126.064000 3.684000 NaN \n",
- "25% 132.364839 6.634000 NaN \n",
- "50% 182.764003 7.806000 NaN \n",
- "75% 213.932412 8.567000 NaN \n",
- "max 228.976456 14.313000 NaN "
- ]
- },
- "execution_count": 13,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "walmart_features_data.describe(include='all')"
- ]
- },
- {
- "attachments": {},
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Daten beschreiben: Wir haben nicht f\u00fcr alle Werte entsprechende Zahlen. Es fehlen Werte f\u00fcr MarkDown1-MarkDown5, CPI und Arbeitslosigkeit. Interessant ist, dass es negative Werte bei \"MarkDown\" gibt. Laut der Beschreibung der Daten sind die MarkDown-Werte nicht f\u00fcr alle Filialen und erst ab einem bestimmten Datum verf\u00fcgbar. Dies erkl\u00e4rt die Diskrepanz in der Menge. "
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 14,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "Index(['Store', 'Date', 'Temperature', 'Fuel_Price', 'MarkDown1', 'MarkDown2',\n",
- " 'MarkDown3', 'MarkDown4', 'MarkDown5', 'CPI', 'Unemployment',\n",
- " 'IsHoliday'],\n",
- " dtype='object')"
- ]
- },
- "execution_count": 14,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "walmart_features_data.columns"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 15,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "Store 0\n",
- "Date 0\n",
- "Temperature 0\n",
- "Fuel_Price 0\n",
- "MarkDown1 4158\n",
- "MarkDown2 5269\n",
- "MarkDown3 4577\n",
- "MarkDown4 4726\n",
- "MarkDown5 4140\n",
- "CPI 585\n",
- "Unemployment 585\n",
- "IsHoliday 0\n",
- "dtype: int64"
- ]
- },
- "execution_count": 15,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "walmart_features_data.isnull().sum() "
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 16,
- "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>Store</th>\n",
- " <th>Date</th>\n",
- " <th>Temperature</th>\n",
- " <th>Fuel_Price</th>\n",
- " <th>MarkDown1</th>\n",
- " <th>MarkDown2</th>\n",
- " <th>MarkDown3</th>\n",
- " <th>MarkDown4</th>\n",
- " <th>MarkDown5</th>\n",
- " <th>CPI</th>\n",
- " <th>Unemployment</th>\n",
- " <th>IsHoliday</th>\n",
- " </tr>\n",
- " </thead>\n",
- " <tbody>\n",
- " <tr>\n",
- " <th>column Type</th>\n",
- " <td>int64</td>\n",
- " <td>object</td>\n",
- " <td>float64</td>\n",
- " <td>float64</td>\n",
- " <td>float64</td>\n",
- " <td>float64</td>\n",
- " <td>float64</td>\n",
- " <td>float64</td>\n",
- " <td>float64</td>\n",
- " <td>float64</td>\n",
- " <td>float64</td>\n",
- " <td>bool</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>null values (nb)</th>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>4158</td>\n",
- " <td>5269</td>\n",
- " <td>4577</td>\n",
- " <td>4726</td>\n",
- " <td>4140</td>\n",
- " <td>585</td>\n",
- " <td>585</td>\n",
- " <td>0</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>null values (%)</th>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>50.7692</td>\n",
- " <td>64.3346</td>\n",
- " <td>55.8852</td>\n",
- " <td>57.7045</td>\n",
- " <td>50.5495</td>\n",
- " <td>7.14286</td>\n",
- " <td>7.14286</td>\n",
- " <td>0</td>\n",
- " </tr>\n",
- " </tbody>\n",
- "</table>\n",
- "</div>"
- ],
- "text/plain": [
- " Store Date Temperature Fuel_Price MarkDown1 MarkDown2 \\\n",
- "column Type int64 object float64 float64 float64 float64 \n",
- "null values (nb) 0 0 0 0 4158 5269 \n",
- "null values (%) 0 0 0 0 50.7692 64.3346 \n",
- "\n",
- " MarkDown3 MarkDown4 MarkDown5 CPI Unemployment IsHoliday \n",
- "column Type float64 float64 float64 float64 float64 bool \n",
- "null values (nb) 4577 4726 4140 585 585 0 \n",
- "null values (%) 55.8852 57.7045 50.5495 7.14286 7.14286 0 "
- ]
- },
- "execution_count": 16,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "null = pd.DataFrame(walmart_features_data.dtypes).T.rename(index={0:'column Type'}) \n",
- "null = null.append(pd.DataFrame(walmart_features_data.isnull().sum()).T.rename(index={0:'null values (nb)'}))\n",
- "null = null.append(pd.DataFrame(walmart_features_data.isnull().sum()/walmart_features_data.shape[0]*100).T.\n",
- " rename(index={0: 'null values (%)'}))\n",
- "null"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 17,
- "metadata": {},
- "outputs": [],
- "source": [
- "from statistics import mean\n",
- "walmart_features_data['CPI'] = walmart_features_data['CPI'].fillna(mean(walmart_features_data['CPI']))\n",
- "walmart_features_data['Unemployment'] = walmart_features_data['Unemployment'].fillna(mean(walmart_features_data['Unemployment']))\n",
- "walmart_features_data['MarkDown1'] = walmart_features_data['MarkDown1'].fillna(0)\n",
- "walmart_features_data['MarkDown2'] = walmart_features_data['MarkDown2'].fillna(0)\n",
- "walmart_features_data['MarkDown3'] = walmart_features_data['MarkDown3'].fillna(0)\n",
- "walmart_features_data['MarkDown4'] = walmart_features_data['MarkDown4'].fillna(0)\n",
- "walmart_features_data['MarkDown5'] = walmart_features_data['MarkDown5'].fillna(0)"
- ]
- },
- {
- "attachments": {},
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## 2.3.2. Deskriptive Analyse"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 18,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "<AxesSubplot:>"
- ]
- },
- "execution_count": 18,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": 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",
- "text/plain": [
- "<Figure size 432x288 with 2 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "sns.heatmap(walmart_features_data.corr()) "
- ]
- },
- {
- "attachments": {},
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## 2.4. Ladendaten einlesen"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 19,
- "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>Store</th>\n",
- " <th>Type</th>\n",
- " <th>Size</th>\n",
- " </tr>\n",
- " </thead>\n",
- " <tbody>\n",
- " <tr>\n",
- " <th>0</th>\n",
- " <td>1</td>\n",
- " <td>A</td>\n",
- " <td>151315</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>1</th>\n",
- " <td>2</td>\n",
- " <td>A</td>\n",
- " <td>202307</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>2</th>\n",
- " <td>3</td>\n",
- " <td>B</td>\n",
- " <td>37392</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>3</th>\n",
- " <td>4</td>\n",
- " <td>A</td>\n",
- " <td>205863</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>4</th>\n",
- " <td>5</td>\n",
- " <td>B</td>\n",
- " <td>34875</td>\n",
- " </tr>\n",
- " </tbody>\n",
- "</table>\n",
- "</div>"
- ],
- "text/plain": [
- " Store Type Size\n",
- "0 1 A 151315\n",
- "1 2 A 202307\n",
- "2 3 B 37392\n",
- "3 4 A 205863\n",
- "4 5 B 34875"
- ]
- },
- "execution_count": 19,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "walmart_stores_data.head(5)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 20,
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "<class 'pandas.core.frame.DataFrame'>\n",
- "RangeIndex: 45 entries, 0 to 44\n",
- "Data columns (total 3 columns):\n",
- " # Column Non-Null Count Dtype \n",
- "--- ------ -------------- ----- \n",
- " 0 Store 45 non-null int64 \n",
- " 1 Type 45 non-null object\n",
- " 2 Size 45 non-null int64 \n",
- "dtypes: int64(2), object(1)\n",
- "memory usage: 1.2+ KB\n"
- ]
- }
- ],
- "source": [
- "walmart_stores_data.info()"
- ]
- },
- {
- "attachments": {},
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Daten beschreiben: Wir haben einen Datensatz mit 45 Eintr\u00e4gen. Jede Zeile enth\u00e4lt die Werte \"Store\", \"Type\" und \"Size\". Das Format dieser Werte sind zwei Ganzzahlen und ein Objekt. "
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 21,
- "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>Store</th>\n",
- " <th>Type</th>\n",
- " <th>Size</th>\n",
- " </tr>\n",
- " </thead>\n",
- " <tbody>\n",
- " <tr>\n",
- " <th>count</th>\n",
- " <td>45.000000</td>\n",
- " <td>45</td>\n",
- " <td>45.000000</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>unique</th>\n",
- " <td>NaN</td>\n",
- " <td>3</td>\n",
- " <td>NaN</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>top</th>\n",
- " <td>NaN</td>\n",
- " <td>A</td>\n",
- " <td>NaN</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>freq</th>\n",
- " <td>NaN</td>\n",
- " <td>22</td>\n",
- " <td>NaN</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>mean</th>\n",
- " <td>23.000000</td>\n",
- " <td>NaN</td>\n",
- " <td>130287.600000</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>std</th>\n",
- " <td>13.133926</td>\n",
- " <td>NaN</td>\n",
- " <td>63825.271991</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>min</th>\n",
- " <td>1.000000</td>\n",
- " <td>NaN</td>\n",
- " <td>34875.000000</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>25%</th>\n",
- " <td>12.000000</td>\n",
- " <td>NaN</td>\n",
- " <td>70713.000000</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>50%</th>\n",
- " <td>23.000000</td>\n",
- " <td>NaN</td>\n",
- " <td>126512.000000</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>75%</th>\n",
- " <td>34.000000</td>\n",
- " <td>NaN</td>\n",
- " <td>202307.000000</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>max</th>\n",
- " <td>45.000000</td>\n",
- " <td>NaN</td>\n",
- " <td>219622.000000</td>\n",
- " </tr>\n",
- " </tbody>\n",
- "</table>\n",
- "</div>"
- ],
- "text/plain": [
- " Store Type Size\n",
- "count 45.000000 45 45.000000\n",
- "unique NaN 3 NaN\n",
- "top NaN A NaN\n",
- "freq NaN 22 NaN\n",
- "mean 23.000000 NaN 130287.600000\n",
- "std 13.133926 NaN 63825.271991\n",
- "min 1.000000 NaN 34875.000000\n",
- "25% 12.000000 NaN 70713.000000\n",
- "50% 23.000000 NaN 126512.000000\n",
- "75% 34.000000 NaN 202307.000000\n",
- "max 45.000000 NaN 219622.000000"
- ]
- },
- "execution_count": 21,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "walmart_stores_data.describe(include='all')"
- ]
- },
- {
- "attachments": {},
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Daten beschreiben: Da wir bereits wissen, dass es 45 L\u00e4den gibt, ist dies ein Datensatz, der Einzelheiten \u00fcber jeden Laden enth\u00e4lt. Es gibt 45 L\u00e4den, es gibt 3 Typen (A, B und C) und die Gr\u00f6\u00dfe der L\u00e4den variiert zwischen 34.875 und 219.622 Quadratmetern."
- ]
- },
- {
- "attachments": {},
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## 2.4.1. Deskriptive Analyse"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 22,
- "metadata": {},
- "outputs": [],
- "source": [
- "#sns.pairplot(walmart_stores_data, vars=['Store', 'Size'], hue='Type') "
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 23,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "<AxesSubplot:xlabel='Type', ylabel='Size'>"
- ]
- },
- "execution_count": 23,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": 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",
- "text/plain": [
- "<Figure size 432x288 with 1 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "sns.swarmplot(x='Type',y='Size',data=walmart_stores_data,palette='Set2')"
- ]
- },
- {
- "attachments": {},
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Es sieht so aus, als ob der \"Typ\" anhand der Gr\u00f6\u00dfe bestimmt werden kann. Sie k\u00f6nnen aber auch sehen, dass es mindestens 4 Gesch\u00e4fte gibt, die wahrscheinlich falsch zugeordnet wurden, da es einige im Gr\u00f6\u00dfenbereich zwischen 25.000 und 50.000 in Typ B und A gibt, die wahrscheinlich eher dem Typ C h\u00e4tten zugeordnet werden m\u00fcssen."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 24,
- "metadata": {},
- "outputs": [],
- "source": [
- "walmart_stores_data.loc[walmart_stores_data.Size < 50000, \"Type\"] = \"C\"\n",
- "walmart_stores_data.loc[walmart_stores_data.Size >= 50000, \"Type\"] = \"B\"\n",
- "walmart_stores_data.loc[walmart_stores_data.Size >= 150000, \"Type\"] = \"A\""
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 25,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "<AxesSubplot:xlabel='Type', ylabel='Size'>"
- ]
- },
- "execution_count": 25,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": 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",
- "text/plain": [
- "<Figure size 432x288 with 1 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "sns.swarmplot(x='Type',y='Size',data=walmart_stores_data,palette='Set2')"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 26,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "<AxesSubplot:xlabel='Type', ylabel='Store'>"
- ]
- },
- "execution_count": 26,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": 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fXCdSK0+3DEkCdNrovCv+ZovA/ToDWLp0KbZu3YqsLD6qeLDtv1Lp1wh2vL0Gc9PGIM3Q+78wIhpcel10Hvj7o1+f3GQyob6+PthZVKn3RjAusBNR8PXrDMDhcOCee+5BRkYGYmOvXSPbtm1b0IKpxYykbJy1N+DqRa2RpmQMNSYKzURE6tCvNYAjR470Oj9jxoxBD9SXaFsDAIBLjhZUtNciUW/CHUkjEaNhLwBRKJytasHpiy3QaHoawXKGRt9j2W+2BtDvp4EeP34c+/btg8fjwezZs4Uc/IHoLABEFHp1TZ3YdeSybywBKP5GNpLjo+tW0FvuBH7nnXewcuVKtLW1obOzE0899RQ2btw4qCGJiEKpt0awepU1gvXrWsMbb7yBTZs2wWKxAACWL1+ORx55BN/97neDGo6IKFhSEtkI1q8zAFmWfQd/AEhPT4dGo95bp4gosnV0ueFyezEyIw4ajQStVsKk0amqawTr1xlAUlISdu3ahfnz5wMAdu3ahcRE3qlCRJGn1taJjz65jKtLiWOzkjB1rBnaKG0Eu5l+LQKfO3cOP/7xj+F2uyFJEnQ6HV5++WXk5+eHIqMfLgIT0a3418FqNLZc29NEIwFL5+chRq8VmCp4brkTOCEhATt37oTVaoXX68WoUaNgtVoHMyMRUUh4v/IFUlag2i+VNz3naW1tRWtrK5YvXw673Y7U1FRYLBa0trbiscceC1VGIqJBk5+V5DfOyoyHKUadvTc3/dRPPfUUDhw4AACYOXMmAECSJGi1WixYsCD46YiIBlnu8EQMMelR02hHp7MbTS0ObN1zEbflpWDUMHWtbfa5BiDLMn75y19i7dq1sNvtOHDgAPLz85GdnR2iiP64BkBEg6HW1ondH1/2m1t8VxaSE4yCEgXHgBvBzp8/j/nz56OoqAhOpxPf+c538Pvf/x4PPfSQ78yAiCgS9db0VX/F0ctvRq+bFoB169bhiSeewNy5c/Hee+9BURRs374dGzduxB//+Mc+//hLL72E4uJiFBcXY926dQCA8vJylJSUoKioCGVlZYPzKYiIApSaeOM3/VQ2gl1TV1eH++67DwBw+PBhzJ8/H1qtFpmZmbDb7Tf9w+Xl5di/fz+2bNmCd955BydPnsT27duxevVqrF+/Hjt27EBFRQX27NkzeJ8mwlxytOBQy0XUO9tFRyFSnZEZcRibnQyNRoJOK+H2MWmwsBHsmuu7fT/77DOsWbPGN3a5XDf9w2azGc888wwMBgMAIDc3F1arFVlZWRgxYgQAoKSkBDt37kRhYeGAP0Ck2tN8Dh/YzgDoeQjVtzMnY0riCLGhiFREkiRMH2/B1PyebVg1GvVtxXrTM4DExEScOXMGn3zyCWw2G6ZPnw4AOHr0KNLT02/6h0ePHo3JkycDAKxWK95//31IkgSz2ez7HYvFgoaGhlv8CJHHq8jY23zeN1YA/KfpnLhARCqm1WpUefAH+jgDePLJJ/Hwww/DbrfjZz/7GWJjY/GXv/wFf/7zn/Hyyy/36w3OnTuHRx99FE8//TS0Wq1fA5miKAFvgP51q9mRxCvLkM/538mkaBSYzfGCEhGRGt20AEyePBl79+6F0+lEQkLPRglTpkzBpk2b+nUb6KeffoqVK1di9erVKC4uxpEjR2Cz2Xw/t9lsfg+Z649ouQ10emIWylsu+MYzE7Nhs3UITERE0eiWHgVhMBh81/EBYOrUqf1607q6OvzkJz9BWVkZCgoKAAC33347Ll68iKqqKgwfPhzbt2/HkiVL+vX3os29lvEYYUrGJUcLrrjt2Nt8HsfbanBv+njkxKaJjkdEKtDvHcEC9dxzz+Htt9/GyJEjfXPLli1DdnY21q5dC5fLhcLCQvziF78I6DJQtJwBXPWfpi+wq+msb2zU6PF03nwYuC0kEQ2CQdkSMlxEWwF4vfogKrua/OaWj5yNrNgUQYmIKJrc8paQFDzDjEl+Y72khSUm8he6iSj8sQAIVpg2GhPiMyEBSNAZsXToFJi0hj5fR0QD12Z34fTFFtTaOkVHEYqXgMJEtyJDCyng22KJKDCXG+z4z9EaXD3y5WclYcaEm/c1RTJeAooAOknDgz9RCFRcuILrv/Z+Ud0Kl9srLpBALABEpCo3XEFQeppS1YgFgIhUZVxOst84Z1gCjCrdEYxrAESkOo0tDtQ02mHv8qC+uRNarQa35aVi9Igk0dEG3S1vCk9EFE0sySZ4PF5UVF75ckbGoc8bkJpoREqU7Qh2M7wERESq1NDL7l+9zUUzFgAiUqW0pBu/6af1sktYNGMBICLVae1woaPTjayMOGi1Egw6DaaONcOcbBIdLaS4BkBEqnKpwY491zWCjRmZiBkT0lXZh8MzACJSlZMXmv0awc5daoPbI4sLJBALABGpyg03vrMRjIhIHcZl+zeCjWIjWORgIxgR3SpbqwO1jZ1o63SjvulaI9iYkUmiow06PgyOiOg65iQTUpOMqKrrgMsjo8vZjcMVDWhuc4qOFlIsAESkSo29NH01trARjIgo6vXWCGbuZS6asQAIdL7Thj3N53DJ0SI6CpHqjMyIx215qdBpJRj0GkwbZ0ZakroawbgILMhu21l81PyFb1yaMQnTk7IEJiJSJ0VRoroJjIvAYcaryDhwpdJvbm/zeUFpiNQtmg/+fWEBEOTGXpTIP6shosjCAiCAVtKgICXHb+4bKXmC0hCRWnENQKCz9gZccrSg1tmGi11NSNSbUGyZiNFxFtHRiChKcA0gTOXHpUOChC86G+FRZDS5O/FW7adwebtFRyMiFWABEKzaccVv7JK7Ue9qF5SGiNSEBUCwESb/B1MZNFqkx8QLSkNEaqLOR+CFkcLU0WjzOPB5Ry0SdSYUp0+AUasXHYtIFRyublhrO6DRADlDE2DQa0VHCikuAhORKnU5u/Hefiucbi8AID5Wj+K7sqHXRdeFES4CExF9xYWaNt/BHwA6ujyoru8QmCj0WACIiFSKBYCIVGnUsEQYDdeu+cfH6jEyQ103YHANQDC33I136z//chHYiOL0iciPSxcdi0gVHK5uWOs6oJUkZA+Nj8pF4JutAbAACLbLdgb/aT7nGxs0Wjyd+03eCUREg4KLwGGs+it7AbhlLxpc6lqIIiIxgloA7HY7Fi9ejMuXLwMAysvLUVJSgqKiIpSVlQXzrSNGlinFbxyj0SEjJkFQGiJSk6AVgOPHj+N73/serFYrAMDpdGL16tVYv349duzYgYqKCuzZsydYbx8x5qTmYWriCOglLcyGOCwbdgditOzPIwqm5lYnTpxrQlVdByLsKvigCtqRZuPGjfj1r3+Np59+GgBw4sQJZGVlYcSIEQCAkpIS7Ny5E4WFhcGKEBH0Gi2+nTkZ386cLDoKkSpU1XVg72e1vnHu8ETcOSlDYCJxglYAnn/+eb9xY2MjzGazb2yxWNDQ0BCstyci6tWpi/4PYLxwuQ1Tx6bBaFDfmXfIPrEsy35brw10H86vW80mIuqPG271lIC01HiYjCwAQZORkQGbzeYb22w2WCyBb3wSbbeBElFojRmZiDpbp28T1rzhibB3OGCP0pvvwuI20Ntvvx0XL15EVVUVvF4vtm/fjjlz5oTq7YmIAAAj0uNRfFc2po41Y2RGHC7UtGHDB+duuDSkBiE7A4iJicELL7yAxx9/HC6XC4WFhVi4cGGo3p6IyCc5IQYdXW4cPdNzVcIry/j0tA3mZBPMSSbB6UKHncBEpEpHz9hw8oL/t/5p4y0Yl538Na+ITGFxCYiIKJxYUm78pp+erJ5v/wALQFiod7bjw6az+LS1Gh7Z2/cLiOiWDbfEYUp+GowGLWKNOsyamI6URKPoWCHFS0CCXehswhuXDkH+8p6E3Ng0/PfIAsGpiCha8BJQGDvUctF38AeAyq4m1DvbBSYiIrVgARBM00szXG9zRESDjQVAsNkpudBJ1/41jIvLgCVGXbsSEYkkK4pqHwjHNYAw0OLuwml7PZL0JoyNy+AZAFEIKIqCz8424UxVCzSShNvyUjFhVErfL4wwN1sDUN/DL8JQsiEWd6aMEh2DSFUuNdh9fQBeKDh6xgZLsglmFd0KyktARKRKTa3OG+fabpyLZiwARKRK6b01gvUyF814CSgM1DnbcLKjDol6EyYnDIdeo+37RUR0S4ZZ4jB1rBmnL7ZAq+lZA0hJYCNYWIu2ReDKzib89bpGsFGxafghG8GIaJCwESyMfbUR7AIbwYgoRFgABNNKN/4r4G2gRBQKLACC3ZUyCnrp2jX/CfGZbASLNIoCeD2iUxAFjGsAYaDV48AZez2SdCaMiUvnGUAE0dWfw5CDb0Frb4YnYwzsdz0ExcQCTuHjZmsALABEAyV7kfT2/4PGeW0zWdeo6eic/X2BoYj8cRGYKAg0na1+B38A0DZfEpSGKHAsAEQDJMclwxuX6jfXnZEnKA1R4FgAwkCNsxX/bjyNwy1WuOVu0XGovyQN7IU/hMcyCnLMELhGTUfXlMWiUxH1G9cABDvfacPfLh329QJkm1Lxf7LuFJyKiKIF1wDC2OEWq18jmNXRjDpnm8BERKQWLACC6XppBOttjohosPFII9hdKbkwXNcINjF+KMxsBIssigJ4XKJTEAWMawBhoN3jwBl7A5L0JuQNsbARLILo6s72NIJ1tsCTngv7N/4LiilBdCwiH64BhLkEvQkzkrPZBRxpvN2I2/8mtJ0tAAB9QyVij74rOBRR/7EAEA2QpqsNGqfdb07bfFlQGqLAsQAQDVDvjWCjBaUhChwLgCCyouB422XsaKjAmY560XFoICQN7Hc/Ak/6aMjGeDjzZrERjCIKF4EFea+hAgdbLvrGC8zj8I1UPkaAiAYXF4HDTLci4+PWKr+5Q9cVAyKiUGABEEDCjTuBcSN4Igo1FgABtJIGc1PH+MYSgLuS8+BVZHGhiEh1uAYgUI2zFdauZpzuqIfVcQVDtAYsSp+I2xOGiY5GRFGCawBhapgxCR3dLlgdVwAAnV43ttQdQ5fXLTgZEakBC4BgX33yZ7ciw+ayf81vExENHiEFYNu2bVi0aBGKiorwj3/8Q0SEsJE7xOw3jtXqMdSYKCgNEamJLtRv2NDQgLKyMmzevBkGgwHLli3DzJkzkZenznvgZ6eMQpfXjc/ba5CoN2GhZTzvCCKikAh5ASgvL8esWbOQlJQEAFiwYAF27tyJxx57LNRRwoJW0mChZTwWWsaLjkJEKhPyS0CNjY0wm69d9rBYLGhoaAh1DCIi1Qv5GYAsy5Cue+Sxoih+47583e1MREQUmJAXgIyMDHzyySe+sc1mg8Vi6ffro6kPgIgo2MKqD+DOO+/EwYMHceXKFTgcDvz73//GnDlzQh2DiEj1Qn4GkJ6ejlWrVuEHP/gBPB4Pli5dikmTJoU6BhGR6kXcoyBaWjp5CYiIqJ80GgnJyUN6/VnEFQAiIhocfBQEEZFKsQAQEakUCwARkUqxABARqRQLABGRSrEAEBGpFAsAEZFKsQAQEakUCwARkUqxAISJL774Avn5+fjXv/4lOgoFwG6349lnn8XixYtRWlqKhx56CCdPnhQdi/rh8OHDmDJlCkpLS3Hffffh3nvvxV//+lfRsUIq5A+Do969/fbbWLhwITZs2IAFCxaIjkP9IMsyli9fjpkzZ+Kdd96BTqfDoUOHsHz5crz33ntITk4WHZH6MHHiRLz55psAeop5cXExZs+erZotankGEAY8Hg+2bduGJ554AidPnkR1dbXoSNQPhw8fRl1dHVauXAmdrue71KxZs7B27VrIsiw4HQXK5XJBq9UiPj5edJSQYQEIA3v27MHQoUORk5OD+fPnY8OGDaIjUT+cOnUKY8eOhUbj/59RYWEhUlNTBaWiQFRUVKC0tBQlJSWYN28eZsyYEdAGVZGOBSAMvP3221i8eDEAYNGiRdi8eTPcbrfgVNQXjUaDmJgY0THoFkycOBFbt27Ftm3bcODAAVitVrzyyiuiY4UMC4Bgzc3N2LdvH1577TXMmzcPa9asQXt7Oz744APR0agPEydOxKlTp/DVJ6r/7ne/w6FDhwSlooGKi4vDvffei6NHj4qOEjIsAIJt3boVs2bNwt69e/Hhhx/io48+wooVK/DWW2+JjkZ9mDZtGlJTU/HSSy/B6/UCAPbt24fNmzerZhExmni9Xhw5cgTjx48XHSVkeBeQYFu2bMGqVav85r7//e/j1VdfRWVlJXJzcwUlo75IkoT169dj7dq1WLx4MXQ6HZKTk/HKK68gLS1NdDzqh6trAJIkobu7G/n5+Vi+fLnoWCHDHcGIiFSKl4CIiFSKBYCISKVYAIiIVIoFgIhIpVgAiIhUireBEvXiueeew8cffwwAqKysxLBhw2A0GgEAGzZs8P0zUSTjbaBEfZg3bx5efPFF3HbbbaKjEA0qngEQ9VNXVxcKCwuxceNG5OTkAAAefvhhPPjgg9i1axdiYmJw5swZNDc3Y/bs2VizZg30ej0qKyvx/PPPo7W1FV6vFw899BCWLl0q+NMQcQ2AqN9iY2Nx//33Y9OmTQCA6upqWK1WzJ07FwBw4sQJvPbaa9ixYwcqKyuxYcMGdHd3Y+XKlXjqqaewefNm/P3vf8drr72GY8eOCfwkRD1YAIgC8MADD2Dr1q3weDzYsGEDli5dCq1WCwD41re+hSFDhsBgMKC0tBT79++H1WpFdXU1Vq9ejdLSUjz44INwOp04deqU4E9CxEtARAHJyclBfn4+du/eje3bt2Pjxo2+n10tBACgKAo0Gg28Xi/i4+OxdetW38+amppUtekIhS+eARAF6IEHHsC6deswadIkpKen++bff/99uN1uuFwubNmyBXPnzkVOTg6MRqOvANTV1WHx4sWoqKgQFZ/IhwWAKEBz585FV1cXli1b5jdvNBrxwAMPoKSkBNOmTcOSJUtgMBiwfv16/POf/0RJSQl++MMf4qc//SnuuOMOQemJruElIKI+fPjhh37jEydOIDU1FXfeeafffEFBAR555JEbXj927FjfxuNE4YQFgCgAP//5z3HkyBGUlZVBkiTRcYhuCRvBiIhUimsAREQqxQJARKRSLABERCrFAkBEpFIsAEREKsUCQESkUv8fPEIIlrzbPVsAAAAASUVORK5CYII=",
- "text/plain": [
- "<Figure size 432x288 with 1 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "sns.swarmplot(x='Type',y='Store',data=walmart_stores_data,palette='Set2') # welche Ladennummer zu welchem Typ geh\u00f6rt"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 27,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "<AxesSubplot:xlabel='Type', ylabel='count'>"
- ]
- },
- "execution_count": 27,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": 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",
- "text/plain": [
- "<Figure size 432x288 with 1 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "sns.countplot(x='Type',data=walmart_stores_data) # Betrachtung, wieviele L\u00e4den wir von welchem Type haben"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 28,
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "45\n"
- ]
- }
- ],
- "source": [
- "sizes=walmart_stores_data.count()['Size'].round(1)\n",
- "print(sizes)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 29,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "<seaborn.axisgrid.FacetGrid at 0x1fcd2f4f370>"
- ]
- },
- "execution_count": 29,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": 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",
- "text/plain": [
- "<Figure size 648x216 with 3 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "g = sns.FacetGrid(data=walmart_stores_data,col='Type') # Betrachtung, wie sich inerhalb eines Types dann noch die Gr\u00f6\u00dfe verteilt\n",
- "g.map(plt.hist,'Size')"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 30,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "Index(['Store', 'Type', 'Size'], dtype='object')"
- ]
- },
- "execution_count": 30,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "walmart_stores_data.columns"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 31,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "Store 0\n",
- "Type 0\n",
- "Size 0\n",
- "dtype: int64"
- ]
- },
- "execution_count": 31,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "walmart_stores_data.isnull().sum() # existieren Nullwerte ?"
- ]
- },
- {
- "attachments": {},
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# 3. Datenaufbereitung\n"
- ]
- },
- {
- "attachments": {},
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Wir kombinieren alle 3 verf\u00fcgbaren Datens\u00e4tze (Tabellen), da alle 3 einen gemeinsamen Schl\u00fcssel (\"Store\") haben, \u00fcber den eine Zusammenfassung m\u00f6glich ist. Die weitere Betrachtung wird erst m\u00f6glich, wenn wir die Daten aus allen 3 Datens\u00e4tzen zusammen betrachten, welche Abh\u00e4ngigkeiten hier bestehen. \n",
- "\n",
- "Ziel ist es, eine Vorhersage \u00fcber die Daten von \"Weekly_Sales\" zu machen, daher suchen wir alle Daten, die einen Einfluss auf diese haben."
- ]
- },
- {
- "attachments": {},
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## 3.1. Daten kombinieren"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 32,
- "metadata": {},
- "outputs": [],
- "source": [
- "festo_data = walmart_features_data.merge(walmart_stores_data, how='inner', on='Store')\n",
- "comb_data = walmart_train_data.merge(festo_data, how='inner', on=['Store','Date','IsHoliday']).sort_values(by=['Store',\n",
- " 'Dept', 'Date']).reset_index(drop=True)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 33,
- "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",
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- "\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>Store</th>\n",
- " <th>Dept</th>\n",
- " <th>Date</th>\n",
- " <th>Weekly_Sales</th>\n",
- " <th>IsHoliday</th>\n",
- " <th>Temperature</th>\n",
- " <th>Fuel_Price</th>\n",
- " <th>MarkDown1</th>\n",
- " <th>MarkDown2</th>\n",
- " <th>MarkDown3</th>\n",
- " <th>MarkDown4</th>\n",
- " <th>MarkDown5</th>\n",
- " <th>CPI</th>\n",
- " <th>Unemployment</th>\n",
- " <th>Type</th>\n",
- " <th>Size</th>\n",
- " </tr>\n",
- " </thead>\n",
- " <tbody>\n",
- " <tr>\n",
- " <th>0</th>\n",
- " <td>1</td>\n",
- " <td>1</td>\n",
- " <td>2010-02-05</td>\n",
- " <td>24924.50</td>\n",
- " <td>False</td>\n",
- " <td>42.31</td>\n",
- " <td>2.572</td>\n",
- " <td>0.0</td>\n",
- " <td>0.0</td>\n",
- " <td>0.0</td>\n",
- " <td>0.0</td>\n",
- " <td>0.0</td>\n",
- " <td>211.096358</td>\n",
- " <td>8.106</td>\n",
- " <td>A</td>\n",
- " <td>151315</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>1</th>\n",
- " <td>1</td>\n",
- " <td>1</td>\n",
- " <td>2010-02-12</td>\n",
- " <td>46039.49</td>\n",
- " <td>True</td>\n",
- " <td>38.51</td>\n",
- " <td>2.548</td>\n",
- " <td>0.0</td>\n",
- " <td>0.0</td>\n",
- " <td>0.0</td>\n",
- " <td>0.0</td>\n",
- " <td>0.0</td>\n",
- " <td>211.242170</td>\n",
- " <td>8.106</td>\n",
- " <td>A</td>\n",
- " <td>151315</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>2</th>\n",
- " <td>1</td>\n",
- " <td>1</td>\n",
- " <td>2010-02-19</td>\n",
- " <td>41595.55</td>\n",
- " <td>False</td>\n",
- " <td>39.93</td>\n",
- " <td>2.514</td>\n",
- " <td>0.0</td>\n",
- " <td>0.0</td>\n",
- " <td>0.0</td>\n",
- " <td>0.0</td>\n",
- " <td>0.0</td>\n",
- " <td>211.289143</td>\n",
- " <td>8.106</td>\n",
- " <td>A</td>\n",
- " <td>151315</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>3</th>\n",
- " <td>1</td>\n",
- " <td>1</td>\n",
- " <td>2010-02-26</td>\n",
- " <td>19403.54</td>\n",
- " <td>False</td>\n",
- " <td>46.63</td>\n",
- " <td>2.561</td>\n",
- " <td>0.0</td>\n",
- " <td>0.0</td>\n",
- " <td>0.0</td>\n",
- " <td>0.0</td>\n",
- " <td>0.0</td>\n",
- " <td>211.319643</td>\n",
- " <td>8.106</td>\n",
- " <td>A</td>\n",
- " <td>151315</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>4</th>\n",
- " <td>1</td>\n",
- " <td>1</td>\n",
- " <td>2010-03-05</td>\n",
- " <td>21827.90</td>\n",
- " <td>False</td>\n",
- " <td>46.50</td>\n",
- " <td>2.625</td>\n",
- " <td>0.0</td>\n",
- " <td>0.0</td>\n",
- " <td>0.0</td>\n",
- " <td>0.0</td>\n",
- " <td>0.0</td>\n",
- " <td>211.350143</td>\n",
- " <td>8.106</td>\n",
- " <td>A</td>\n",
- " <td>151315</td>\n",
- " </tr>\n",
- " </tbody>\n",
- "</table>\n",
- "</div>"
- ],
- "text/plain": [
- " Store Dept Date Weekly_Sales IsHoliday Temperature Fuel_Price \\\n",
- "0 1 1 2010-02-05 24924.50 False 42.31 2.572 \n",
- "1 1 1 2010-02-12 46039.49 True 38.51 2.548 \n",
- "2 1 1 2010-02-19 41595.55 False 39.93 2.514 \n",
- "3 1 1 2010-02-26 19403.54 False 46.63 2.561 \n",
- "4 1 1 2010-03-05 21827.90 False 46.50 2.625 \n",
- "\n",
- " MarkDown1 MarkDown2 MarkDown3 MarkDown4 MarkDown5 CPI \\\n",
- "0 0.0 0.0 0.0 0.0 0.0 211.096358 \n",
- "1 0.0 0.0 0.0 0.0 0.0 211.242170 \n",
- "2 0.0 0.0 0.0 0.0 0.0 211.289143 \n",
- "3 0.0 0.0 0.0 0.0 0.0 211.319643 \n",
- "4 0.0 0.0 0.0 0.0 0.0 211.350143 \n",
- "\n",
- " Unemployment Type Size \n",
- "0 8.106 A 151315 \n",
- "1 8.106 A 151315 \n",
- "2 8.106 A 151315 \n",
- "3 8.106 A 151315 \n",
- "4 8.106 A 151315 "
- ]
- },
- "execution_count": 33,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "comb_data.head(5)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 34,
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "<class 'pandas.core.frame.DataFrame'>\n",
- "RangeIndex: 421570 entries, 0 to 421569\n",
- "Data columns (total 16 columns):\n",
- " # Column Non-Null Count Dtype \n",
- "--- ------ -------------- ----- \n",
- " 0 Store 421570 non-null int64 \n",
- " 1 Dept 421570 non-null int64 \n",
- " 2 Date 421570 non-null object \n",
- " 3 Weekly_Sales 421570 non-null float64\n",
- " 4 IsHoliday 421570 non-null bool \n",
- " 5 Temperature 421570 non-null float64\n",
- " 6 Fuel_Price 421570 non-null float64\n",
- " 7 MarkDown1 421570 non-null float64\n",
- " 8 MarkDown2 421570 non-null float64\n",
- " 9 MarkDown3 421570 non-null float64\n",
- " 10 MarkDown4 421570 non-null float64\n",
- " 11 MarkDown5 421570 non-null float64\n",
- " 12 CPI 421570 non-null float64\n",
- " 13 Unemployment 421570 non-null float64\n",
- " 14 Type 421570 non-null object \n",
- " 15 Size 421570 non-null int64 \n",
- "dtypes: bool(1), float64(10), int64(3), object(2)\n",
- "memory usage: 48.6+ MB\n"
- ]
- }
- ],
- "source": [
- "comb_data.info()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 35,
- "metadata": {},
- "outputs": [],
- "source": [
- "#sns.pairplot(comb_data, vars=['Weekly_Sales', 'Dept', 'Store', 'Size', 'CPI', 'Unemployment', 'Fuel_Price', 'Temperature'], hue='Type')"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 37,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "<seaborn.axisgrid.FacetGrid at 0x1fcd328cb20>"
- ]
- },
- "execution_count": 37,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": 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",
- "text/plain": [
- "<Figure size 498.35x432 with 1 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "sns.catplot(data=comb_data, kind=\"bar\",\n",
- " x=\"Type\", y=\"Weekly_Sales\", hue=\"IsHoliday\",\n",
- " ci=\"sd\", palette=\"dark\", alpha=.6, height=6)"
- ]
- },
- {
- "attachments": {},
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## 3.2. Kombinierte Daten bereinigen"
- ]
- },
- {
- "attachments": {},
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Wir konvertieren das Feld \"IsHoliday\" von boolean in ein int mit 0 und 1 "
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 38,
- "metadata": {},
- "outputs": [],
- "source": [
- "comb_data = comb_data.applymap(lambda x: 1 if x == True else x)\n",
- "comb_data = comb_data.applymap(lambda x: 0 if x == False else x)"
- ]
- },
- {
- "attachments": {},
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Wir konvertieren das Feld \"Datum\" von einem Objekt in ein Datumsfeld"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 39,
- "metadata": {},
- "outputs": [],
- "source": [
- "#comb_data[\"Date\"] = pd.to_datetime(comb_data[\"Date\"])\n",
- "comb_data.Date = pd.to_datetime(comb_data.Date)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 40,
- "metadata": {},
- "outputs": [],
- "source": [
- "# delete negative values for the feature Weekly_Sales and create a new DataFrame\n",
- "clean_data = comb_data[comb_data['Weekly_Sales']>0]"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 41,
- "metadata": {},
- "outputs": [
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "<ipython-input-41-df9ed1724864>:3: FutureWarning: Series.dt.weekofyear and Series.dt.week have been deprecated. Please use Series.dt.isocalendar().week instead.\n",
- " clean_data['Week'] = clean_data.Date.dt.week\n",
- "<ipython-input-41-df9ed1724864>:3: SettingWithCopyWarning: \n",
- "A value is trying to be set on a copy of a slice from a DataFrame.\n",
- "Try using .loc[row_indexer,col_indexer] = value instead\n",
- "\n",
- "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
- " clean_data['Week'] = clean_data.Date.dt.week\n",
- "<ipython-input-41-df9ed1724864>:4: SettingWithCopyWarning: \n",
- "A value is trying to be set on a copy of a slice from a DataFrame.\n",
- "Try using .loc[row_indexer,col_indexer] = value instead\n",
- "\n",
- "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
- " clean_data['Year'] = clean_data.Date.dt.year\n"
- ]
- }
- ],
- "source": [
- "# add a field for \"week\" and \"year\" to allow further viewing on calendar week\n",
- "#clean_data['Week'] = clean_data1['Date'].isocalendar()[1]\n",
- "clean_data['Week'] = clean_data.Date.dt.week\n",
- "clean_data['Year'] = clean_data.Date.dt.year"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 42,
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "<class 'pandas.core.frame.DataFrame'>\n",
- "Int64Index: 420212 entries, 0 to 421569\n",
- "Data columns (total 18 columns):\n",
- " # Column Non-Null Count Dtype \n",
- "--- ------ -------------- ----- \n",
- " 0 Store 420212 non-null int64 \n",
- " 1 Dept 420212 non-null int64 \n",
- " 2 Date 420212 non-null datetime64[ns]\n",
- " 3 Weekly_Sales 420212 non-null float64 \n",
- " 4 IsHoliday 420212 non-null int64 \n",
- " 5 Temperature 420212 non-null float64 \n",
- " 6 Fuel_Price 420212 non-null float64 \n",
- " 7 MarkDown1 420212 non-null float64 \n",
- " 8 MarkDown2 420212 non-null float64 \n",
- " 9 MarkDown3 420212 non-null float64 \n",
- " 10 MarkDown4 420212 non-null float64 \n",
- " 11 MarkDown5 420212 non-null float64 \n",
- " 12 CPI 420212 non-null float64 \n",
- " 13 Unemployment 420212 non-null float64 \n",
- " 14 Type 420212 non-null object \n",
- " 15 Size 420212 non-null int64 \n",
- " 16 Week 420212 non-null int64 \n",
- " 17 Year 420212 non-null int64 \n",
- "dtypes: datetime64[ns](1), float64(10), int64(6), object(1)\n",
- "memory usage: 60.9+ MB\n"
- ]
- }
- ],
- "source": [
- "clean_data.info()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 43,
- "metadata": {},
- "outputs": [],
- "source": [
- "# save date local\n",
- "clean_data.to_csv('clean_data.csv', index = False)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 44,
- "metadata": {},
- "outputs": [],
- "source": [
- "# We convert the field \"Type\", since it is a categorical value using One-Hot Encoding \n",
- "clean_data1 = pd.get_dummies(clean_data, columns=[\"Type\"]) "
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 45,
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "<class 'pandas.core.frame.DataFrame'>\n",
- "Int64Index: 420212 entries, 0 to 421569\n",
- "Data columns (total 20 columns):\n",
- " # Column Non-Null Count Dtype \n",
- "--- ------ -------------- ----- \n",
- " 0 Store 420212 non-null int64 \n",
- " 1 Dept 420212 non-null int64 \n",
- " 2 Date 420212 non-null datetime64[ns]\n",
- " 3 Weekly_Sales 420212 non-null float64 \n",
- " 4 IsHoliday 420212 non-null int64 \n",
- " 5 Temperature 420212 non-null float64 \n",
- " 6 Fuel_Price 420212 non-null float64 \n",
- " 7 MarkDown1 420212 non-null float64 \n",
- " 8 MarkDown2 420212 non-null float64 \n",
- " 9 MarkDown3 420212 non-null float64 \n",
- " 10 MarkDown4 420212 non-null float64 \n",
- " 11 MarkDown5 420212 non-null float64 \n",
- " 12 CPI 420212 non-null float64 \n",
- " 13 Unemployment 420212 non-null float64 \n",
- " 14 Size 420212 non-null int64 \n",
- " 15 Week 420212 non-null int64 \n",
- " 16 Year 420212 non-null int64 \n",
- " 17 Type_A 420212 non-null uint8 \n",
- " 18 Type_B 420212 non-null uint8 \n",
- " 19 Type_C 420212 non-null uint8 \n",
- "dtypes: datetime64[ns](1), float64(10), int64(6), uint8(3)\n",
- "memory usage: 58.9 MB\n"
- ]
- }
- ],
- "source": [
- "clean_data1.info() "
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 46,
- "metadata": {},
- "outputs": [
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "<ipython-input-46-fbf7f56c5ae5>:1: FutureWarning: Treating datetime data as categorical rather than numeric in `.describe` is deprecated and will be removed in a future version of pandas. Specify `datetime_is_numeric=True` to silence this warning and adopt the future behavior now.\n",
- " clean_data1.describe(include='all')\n"
- ]
- },
- {
- "data": {
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- "<style scoped>\n",
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- " .dataframe tbody tr th {\n",
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- "<table border=\"1\" class=\"dataframe\">\n",
- " <thead>\n",
- " <tr style=\"text-align: right;\">\n",
- " <th></th>\n",
- " <th>Store</th>\n",
- " <th>Dept</th>\n",
- " <th>Date</th>\n",
- " <th>Weekly_Sales</th>\n",
- " <th>IsHoliday</th>\n",
- " <th>Temperature</th>\n",
- " <th>Fuel_Price</th>\n",
- " <th>MarkDown1</th>\n",
- " <th>MarkDown2</th>\n",
- " <th>MarkDown3</th>\n",
- " <th>MarkDown4</th>\n",
- " <th>MarkDown5</th>\n",
- " <th>CPI</th>\n",
- " <th>Unemployment</th>\n",
- " <th>Size</th>\n",
- " <th>Week</th>\n",
- " <th>Year</th>\n",
- " <th>Type_A</th>\n",
- " <th>Type_B</th>\n",
- " <th>Type_C</th>\n",
- " </tr>\n",
- " </thead>\n",
- " <tbody>\n",
- " <tr>\n",
- " <th>count</th>\n",
- " <td>420212.000000</td>\n",
- " <td>420212.000000</td>\n",
- " <td>420212</td>\n",
- " <td>420212.000000</td>\n",
- " <td>420212.000000</td>\n",
- " <td>420212.000000</td>\n",
- " <td>420212.000000</td>\n",
- " <td>420212.000000</td>\n",
- " <td>420212.000000</td>\n",
- " <td>420212.000000</td>\n",
- " <td>420212.000000</td>\n",
- " <td>420212.000000</td>\n",
- " <td>420212.000000</td>\n",
- " <td>420212.000000</td>\n",
- " <td>420212.000000</td>\n",
- " <td>420212.000000</td>\n",
- " <td>420212.000000</td>\n",
- " <td>420212.000000</td>\n",
- " <td>420212.000000</td>\n",
- " <td>420212.000000</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>unique</th>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>143</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>top</th>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>2011-12-23 00:00:00</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>freq</th>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>3018</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>first</th>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>2010-02-05 00:00:00</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>last</th>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>2012-10-26 00:00:00</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>mean</th>\n",
- " <td>22.195611</td>\n",
- " <td>44.241309</td>\n",
- " <td>NaN</td>\n",
- " <td>16033.114591</td>\n",
- " <td>0.070345</td>\n",
- " <td>60.090599</td>\n",
- " <td>3.360890</td>\n",
- " <td>2590.323565</td>\n",
- " <td>878.905242</td>\n",
- " <td>468.845949</td>\n",
- " <td>1083.534361</td>\n",
- " <td>1662.805002</td>\n",
- " <td>171.212496</td>\n",
- " <td>7.960000</td>\n",
- " <td>136749.732787</td>\n",
- " <td>25.828408</td>\n",
- " <td>2010.968454</td>\n",
- " <td>0.481390</td>\n",
- " <td>0.344548</td>\n",
- " <td>0.174062</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>std</th>\n",
- " <td>12.787236</td>\n",
- " <td>30.508819</td>\n",
- " <td>NaN</td>\n",
- " <td>22729.492116</td>\n",
- " <td>0.255729</td>\n",
- " <td>18.447857</td>\n",
- " <td>0.458519</td>\n",
- " <td>6053.415601</td>\n",
- " <td>5076.928566</td>\n",
- " <td>5534.069859</td>\n",
- " <td>3896.068938</td>\n",
- " <td>4206.209357</td>\n",
- " <td>39.162445</td>\n",
- " <td>1.863879</td>\n",
- " <td>60993.084568</td>\n",
- " <td>14.152489</td>\n",
- " <td>0.796898</td>\n",
- " <td>0.499654</td>\n",
- " <td>0.475221</td>\n",
- " <td>0.379163</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>min</th>\n",
- " <td>1.000000</td>\n",
- " <td>1.000000</td>\n",
- " <td>NaN</td>\n",
- " <td>0.010000</td>\n",
- " <td>0.000000</td>\n",
- " <td>-2.060000</td>\n",
- " <td>2.472000</td>\n",
- " <td>0.000000</td>\n",
- " <td>-265.760000</td>\n",
- " <td>-29.100000</td>\n",
- " <td>0.000000</td>\n",
- " <td>0.000000</td>\n",
- " <td>126.064000</td>\n",
- " <td>3.879000</td>\n",
- " <td>34875.000000</td>\n",
- " <td>1.000000</td>\n",
- " <td>2010.000000</td>\n",
- " <td>0.000000</td>\n",
- " <td>0.000000</td>\n",
- " <td>0.000000</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>25%</th>\n",
- " <td>11.000000</td>\n",
- " <td>18.000000</td>\n",
- " <td>NaN</td>\n",
- " <td>2120.130000</td>\n",
- " <td>0.000000</td>\n",
- " <td>46.680000</td>\n",
- " <td>2.933000</td>\n",
- " <td>0.000000</td>\n",
- " <td>0.000000</td>\n",
- " <td>0.000000</td>\n",
- " <td>0.000000</td>\n",
- " <td>0.000000</td>\n",
- " <td>132.022667</td>\n",
- " <td>6.891000</td>\n",
- " <td>93638.000000</td>\n",
- " <td>14.000000</td>\n",
- " <td>2010.000000</td>\n",
- " <td>0.000000</td>\n",
- " <td>0.000000</td>\n",
- " <td>0.000000</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>50%</th>\n",
- " <td>22.000000</td>\n",
- " <td>37.000000</td>\n",
- " <td>NaN</td>\n",
- " <td>7661.700000</td>\n",
- " <td>0.000000</td>\n",
- " <td>62.090000</td>\n",
- " <td>3.452000</td>\n",
- " <td>0.000000</td>\n",
- " <td>0.000000</td>\n",
- " <td>0.000000</td>\n",
- " <td>0.000000</td>\n",
- " <td>0.000000</td>\n",
- " <td>182.350989</td>\n",
- " <td>7.866000</td>\n",
- " <td>140167.000000</td>\n",
- " <td>26.000000</td>\n",
- " <td>2011.000000</td>\n",
- " <td>0.000000</td>\n",
- " <td>0.000000</td>\n",
- " <td>0.000000</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>75%</th>\n",
- " <td>33.000000</td>\n",
- " <td>74.000000</td>\n",
- " <td>NaN</td>\n",
- " <td>20271.265000</td>\n",
- " <td>0.000000</td>\n",
- " <td>74.280000</td>\n",
- " <td>3.738000</td>\n",
- " <td>2809.050000</td>\n",
- " <td>2.400000</td>\n",
- " <td>4.540000</td>\n",
- " <td>425.290000</td>\n",
- " <td>2168.040000</td>\n",
- " <td>212.445487</td>\n",
- " <td>8.567000</td>\n",
- " <td>202505.000000</td>\n",
- " <td>38.000000</td>\n",
- " <td>2012.000000</td>\n",
- " <td>1.000000</td>\n",
- " <td>1.000000</td>\n",
- " <td>0.000000</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>max</th>\n",
- " <td>45.000000</td>\n",
- " <td>99.000000</td>\n",
- " <td>NaN</td>\n",
- " <td>693099.360000</td>\n",
- " <td>1.000000</td>\n",
- " <td>100.140000</td>\n",
- " <td>4.468000</td>\n",
- " <td>88646.760000</td>\n",
- " <td>104519.540000</td>\n",
- " <td>141630.610000</td>\n",
- " <td>67474.850000</td>\n",
- " <td>108519.280000</td>\n",
- " <td>227.232807</td>\n",
- " <td>14.313000</td>\n",
- " <td>219622.000000</td>\n",
- " <td>52.000000</td>\n",
- " <td>2012.000000</td>\n",
- " <td>1.000000</td>\n",
- " <td>1.000000</td>\n",
- " <td>1.000000</td>\n",
- " </tr>\n",
- " </tbody>\n",
- "</table>\n",
- "</div>"
- ],
- "text/plain": [
- " Store Dept Date Weekly_Sales \\\n",
- "count 420212.000000 420212.000000 420212 420212.000000 \n",
- "unique NaN NaN 143 NaN \n",
- "top NaN NaN 2011-12-23 00:00:00 NaN \n",
- "freq NaN NaN 3018 NaN \n",
- "first NaN NaN 2010-02-05 00:00:00 NaN \n",
- "last NaN NaN 2012-10-26 00:00:00 NaN \n",
- "mean 22.195611 44.241309 NaN 16033.114591 \n",
- "std 12.787236 30.508819 NaN 22729.492116 \n",
- "min 1.000000 1.000000 NaN 0.010000 \n",
- "25% 11.000000 18.000000 NaN 2120.130000 \n",
- "50% 22.000000 37.000000 NaN 7661.700000 \n",
- "75% 33.000000 74.000000 NaN 20271.265000 \n",
- "max 45.000000 99.000000 NaN 693099.360000 \n",
- "\n",
- " IsHoliday Temperature Fuel_Price MarkDown1 \\\n",
- "count 420212.000000 420212.000000 420212.000000 420212.000000 \n",
- "unique NaN NaN NaN NaN \n",
- "top NaN NaN NaN NaN \n",
- "freq NaN NaN NaN NaN \n",
- "first NaN NaN NaN NaN \n",
- "last NaN NaN NaN NaN \n",
- "mean 0.070345 60.090599 3.360890 2590.323565 \n",
- "std 0.255729 18.447857 0.458519 6053.415601 \n",
- "min 0.000000 -2.060000 2.472000 0.000000 \n",
- "25% 0.000000 46.680000 2.933000 0.000000 \n",
- "50% 0.000000 62.090000 3.452000 0.000000 \n",
- "75% 0.000000 74.280000 3.738000 2809.050000 \n",
- "max 1.000000 100.140000 4.468000 88646.760000 \n",
- "\n",
- " MarkDown2 MarkDown3 MarkDown4 MarkDown5 \\\n",
- "count 420212.000000 420212.000000 420212.000000 420212.000000 \n",
- "unique NaN NaN NaN NaN \n",
- "top NaN NaN NaN NaN \n",
- "freq NaN NaN NaN NaN \n",
- "first NaN NaN NaN NaN \n",
- "last NaN NaN NaN NaN \n",
- "mean 878.905242 468.845949 1083.534361 1662.805002 \n",
- "std 5076.928566 5534.069859 3896.068938 4206.209357 \n",
- "min -265.760000 -29.100000 0.000000 0.000000 \n",
- "25% 0.000000 0.000000 0.000000 0.000000 \n",
- "50% 0.000000 0.000000 0.000000 0.000000 \n",
- "75% 2.400000 4.540000 425.290000 2168.040000 \n",
- "max 104519.540000 141630.610000 67474.850000 108519.280000 \n",
- "\n",
- " CPI Unemployment Size Week \\\n",
- "count 420212.000000 420212.000000 420212.000000 420212.000000 \n",
- "unique NaN NaN NaN NaN \n",
- "top NaN NaN NaN NaN \n",
- "freq NaN NaN NaN NaN \n",
- "first NaN NaN NaN NaN \n",
- "last NaN NaN NaN NaN \n",
- "mean 171.212496 7.960000 136749.732787 25.828408 \n",
- "std 39.162445 1.863879 60993.084568 14.152489 \n",
- "min 126.064000 3.879000 34875.000000 1.000000 \n",
- "25% 132.022667 6.891000 93638.000000 14.000000 \n",
- "50% 182.350989 7.866000 140167.000000 26.000000 \n",
- "75% 212.445487 8.567000 202505.000000 38.000000 \n",
- "max 227.232807 14.313000 219622.000000 52.000000 \n",
- "\n",
- " Year Type_A Type_B Type_C \n",
- "count 420212.000000 420212.000000 420212.000000 420212.000000 \n",
- "unique NaN NaN NaN NaN \n",
- "top NaN NaN NaN NaN \n",
- "freq NaN NaN NaN NaN \n",
- "first NaN NaN NaN NaN \n",
- "last NaN NaN NaN NaN \n",
- "mean 2010.968454 0.481390 0.344548 0.174062 \n",
- "std 0.796898 0.499654 0.475221 0.379163 \n",
- "min 2010.000000 0.000000 0.000000 0.000000 \n",
- "25% 2010.000000 0.000000 0.000000 0.000000 \n",
- "50% 2011.000000 0.000000 0.000000 0.000000 \n",
- "75% 2012.000000 1.000000 1.000000 0.000000 \n",
- "max 2012.000000 1.000000 1.000000 1.000000 "
- ]
- },
- "execution_count": 46,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "clean_data1.describe(include='all')"
- ]
- },
- {
- "attachments": {},
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## 3.3. Deskriptive Analyse neue Daten"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 47,
- "metadata": {},
- "outputs": [
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "C:\\Users\\eebal\\Anaconda3\\lib\\site-packages\\seaborn\\_decorators.py:36: FutureWarning: Pass the following variables as keyword args: x, y. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
- " warnings.warn(\n",
- "C:\\Users\\eebal\\Anaconda3\\lib\\site-packages\\seaborn\\_decorators.py:36: FutureWarning: Pass the following variables as keyword args: x, y. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
- " warnings.warn(\n",
- "C:\\Users\\eebal\\Anaconda3\\lib\\site-packages\\seaborn\\_decorators.py:36: FutureWarning: Pass the following variables as keyword args: x, y. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
- " warnings.warn(\n"
- ]
- },
- {
- "data": {
- "image/png": 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fv/3221PVfnWeeuqpXe6QePjhh+/0fN3aIVm9tffeezd4zfaB4Y6/77ujqc+ORCJcdNFFLFu2jJEjR3LYYYdxwQUXcOihhzYYBLbkGkVERNqKQikREZE9RN2ue3feeSderzft3Jdffsn999/Pa6+9xrhx4xg8eDD9+vXjP//5D8FgkEQikdYC1rNnTxYsWMDQoUPrtQC98cYb9SqbdvTAAw+wdetW5s6dm7arW117YZ1evXrx4YcfEggE0ta8bt26tOvqKoF69OjBoEGD0s69++679d63IYcccgh/+9vf+Oijj3A4HBx00EFp50eNGsXs2bP57LPP2GuvvejVq1fa84PBYL2Ao6qqioULF9KnT59mXVfnsssuY+TIkYwbN45//OMfnHLKKRx88MGNvsPIkSMpLCxM7aRnt9s58cQTd/reK1eu5KmnnuK4445Laxur079/f4BU2NfUn92Omvo7s3HjRjZu3MiIESMYMGAAV155JZs3b+b888/nscceazSU+p//+R9OPvnktGMDBw7c6Zqaqu73Kz8/v97PbvHixSQSiV1WZLX2s2fPns2SJUu4/fbbOe2001LXlJSUtMq6RERE2gPNlBIREdkDrFu3jhUrVnDooYdyyimncOyxx6b9dckll1BYWMgHH3yQ+pfYCRMm8MEHHzBv3jwOPvjgtBawn//850CyMml7//3vf7n66qt3GVBUVlaSlZXFXnvtlToWiUR44YUXAFLzi4477jgSiQTPPfdc2uefffbZtK+PPvpoAP7617+mtSmtWrWKyy67jCeffHKX36NDDjmEqqoq5s6dy7Bhw8jOzk47P3LkSLZs2cKHH35YL7z5+c9/zpdffllvdtVDDz3E1KlTWbNmTbOu29G0adPIysri97//fapNriGmaTJ+/HgWLFjA/PnzGTVq1C7btMaPH49pmvzxj3+kurq63vkXX3wRIFVd19Sf3Y6a+jvz8MMPc8EFF6SFKd27d6dbt26YZuP/6Lnffvtx+OGHp/21s3bH5jj88MNxuVz87W9/S/v+l5SUcPnllzNz5sydzvvKxLMrKysB6u2y+NRTTwGkzbwSERHpKFQpJSIisgeo+xf+7SsotudwODj11FN5+OGHmT17NhdffDEnnXQS9957L0uWLOHmm29Ou37MmDEcc8wxPP744/zwww8cfvjhbNiwgWeffZa99tqLiy66aKfrGT16NP/973+55JJLGDt2LH6/n1mzZqXm59TNwTniiCM4+uij+fOf/8y3337L/vvvz4cffsj7778PkAoCiouLOffcc3n66aeprKzk2GOPpbKykmeeeQaPx8PUqVN3+T0aOnQo2dnZfPLJJ2nDouscfPDBOBwOVq5cyTnnnJN27pJLLuHNN9/kyiuv5Mwzz6R///4sW7aM2bNnM3r0aEaPHt2s63bUrVs3rrzySu666y6eeOKJRquFAE466ST+/ve/8+GHH/LHP/5xl+/dt29fbrjhBv7whz9w4okncvLJJ7PvvvsSCoX44IMPeOeddzj33HNTlWNN/dntqKm/M1OmTGH27NlMmTKFM844gy5durBo0SIWL17M1Vdfvcv3aQ35+flce+213HHHHZxxxhmcfPLJxGIxnnvuOcLhML/97W/b/NmHH344drud66+/nilTpmC323nnnXdYsGABDoej0Z+LiIjInkyVUiIiInuA119/HZ/Px/HHH9/oNaeffjqmaabm8vTq1YsDDzwQh8PB2LFj0641DIP/+7//49e//jVfffUVt99+O//85z85/vjjefbZZykoKNjpes4880yuvfZavv/+e2677TaeffZZ+vfvzz//+U/y8vJYtGhR6tp77rmH888/n/fee4877riD6upq7r77boC0lqnp06dz0003UV5ezh//+Eeee+45RowYwXPPPUe/fv12+T1yOBwMHz4cIG2eVJ3s7GyGDh0KUK9SKjc3lxdffJFJkyYxb948brvtNj777DMuv/xy7rvvvlSFT1Ova8j5559P//79+ctf/sL333/f6HX7778/ffv2xeVypXb125XzzjuPZ555hkMPPZQ5c+Zwyy23cN999xEMBrn77ruZMWNG6trm/Oy219TfmQEDBvDEE0/Qp08fHn/8cW699VbWrFnD//t//6/BsDBTLrjgAu69917sdjv33HMPjz76KH379uXJJ59ssO0x088uLi7mvvvuw+PxcPfdd/OXv/yFaDTKE088wdFHH83HH3+80yo7ERGRPZFh7biVh4iIiEgL8fv9OJ3OeoPNV6xYwamnnlpvfo4knXjiiQwYMIB77723rZciIiIi0mpUKSUiIiKt5s0332T48OF8/PHHacf//e9/AzBs2LC2WFa7tmTJEr755hsmTZrU1ksRERERaVWqlBIREZFWU15eztixY8nKymLKlCnk5uby6aef8uqrrzJhwgT+9Kc/tfUS241Zs2bxzjvv8MEHH9CzZ09mzZrVasO3RURERNoDDToXERGRVpOfn8/zzz/P/fffz1NPPUV1dTU9e/bk2muv3eUw9c7GZrPx3nvvsc8++7TqbnAiIiIi7YUqpUREREREREREJOMyPlPqgQceYPz48YwfP5677roLgAULFnDyySdz0kkncf311xOJRABYtWoVkyZN4oQTTmD69OnEYjEANm7cyJQpUxg7diyXXXZZaovc6upqLr74Yk488USmTJlCaWlppl9PRERERERERESaIKOVUh9++CH33XcfTz31FIZh8D//8z+cc8453HbbbTz++OP069ePq6++mp/97GdMnjyZk046idtuu43hw4fzu9/9jqFDh3L22WdzySWXcPLJJzN+/Hj+8pe/UFNTw3XXXcctt9xC9+7dufjii5k1axbz589v1q41FRVBEgkVjomIiIiIiIiI7C7TNMjL8zR6PqMzpQoLC5k2bRpOpxOAfv36sXHjRuLxOIFAgHg8TjgcxuVysWHDBkKhEMOHDwdg0qRJ3HfffUyePJmlS5fyl7/8JXX8nHPO4brrrmP+/Pk8++yzAJx00knccsstRKNRHA5Hk9aXSFgKpUREREREREREMiCjoVT//v1Tf79u3Trmzp3L888/T8+ePTn33HPxer3svffejB07lpUrV1JYWJi6vrCwkJKSEioqKvB6vdjt9rTjAFu2bEl9xm634/V6KS8vp1u3bhl8SxERERERERER2ZWMz5QCWLNmDRdeeCHXX389Ho+HmTNn8vrrr7NgwQIOOOAA7rjjDhKJRNquM5ZlYRhG6s/tNbY7jWVZmGabvKKIiIiIiIiIiOxExhObZcuWccEFF/Cb3/yGiRMn8tFHH1FcXEzv3r0xTZPTTz+dJUuW0L1797RB5WVlZRQVFZGfn4/f7ycejwNQWlpKUVERAEVFRZSVlQEQi8UIBoPk5uZm+hVFRERERERERGQXMhpKbdq0iSuuuIKZM2cyfvx4AIqLi1m+fHkqTHr77bfZf//96dmzJy6Xi2XLlgEwe/ZsRo8ejcPhYMSIEcyZMweAWbNmMXr0aADGjBnDrFmzAJgzZw4jRoxo8jwpERERERERERHJnIzuvnfbbbfxyiuv0Lt379SxM888E7fbzaOPPorNZqNPnz7ccsst5Ofn8+WXXzJjxgwCgQBDhgzhjjvuwOl0smHDBqZNm8bWrVvp0aMHd999N126dKGyspJp06bx/fff4/P5mDlzJnvvvXeT17d1a0CDzkVEREREREREWoBpGnTt6m30fEZDqfZuV6FULBYlGKwmHK4lkYhncGWdi83mwOvtQlZW49tGioiIiIiIiEj7tqtQKqO77+3JYrEo5eUlZGf7yM/vjs1ma3TAuvx0lmURjYaprCzDbnfgcDjbekkiIiIiIiIi0gq0NV0TBYPVZGf78Hq7YLfbFUi1EsMwcDrdeDxdCAQq23o5IiIiIiIiItJKFEo1UThci9utdrJMcbuziEYjbb0MEREREREREWklCqWaKJGIY7PZ2noZnYZp2jS3S0RERERERKQDUyjVDGrZyxx9r0VEREREREQ6NoVSIiIiIiIiIiKScQqlREREREREREQk4+xtvQBpO/F4nH/843n+9a9ZlJRspnv3HkyceBqTJp2OYRhYlsVTTz3O7NmvUlVVyf77H8A111xPnz59G7zffff9mR9++J677ro37Xh1dTX33383H3zwPolEgqOO+jlXXXUNHo+39V9SRERERERERNolVUp1Yn//+9945JEHOf74E7nzzrs5+uhjue++u3nuuacAeOKJR3nyycc566xzufnmPxAMBpg69TICgUC9e73yyou89NLzDT5nxozr+eSTZfzv/97A1Km/YcGC97j55hmt+m4iIiIiIiIi0r6pUqqTSiQSvPjic5x11rmcf/5FAIwYcSiVlZU8//wzTJx4Gs8//wwXXvgrJk8+E4Bhww7ktNMm8PrrszjzzHMAqKgo56GH7mfevH/j9davfPr444/4+OOP+Otf/86QIUMBKCws4te/vpzVq79kwICBGXpjEREREREREWlPVCnVSQUCAcaOHceYMUenHe/duw+VlRUsW7aU2toajjxyTOpcTk4Ow4cfxOLFC1PHnnrqCZYv/5Q///l+9tuvuN5zli5dTF5efiqQAjjooBF4PB4WL/6wFd5MREREREREJLPe/2wjFf5wWy9jj6NKqd30weebWLB8U5uu4chhPThi/x7N+kxOTg7XXvvbesc/+OA9ioq6sWXLFgB69tw77fxee/VkwYJ3U19PnHgqV1wxFbvdzpNPPlbvft9//x17751+D9M06d59L77//rtmrVlERERERESkvamuifDE3C857ah+jBvVp62Xs0dRpZSk/Otfs/jooyWcffa51NQEcTqdOByOtGuys7MJBoOpr3v37ovd3ni2WVMTJCvLU+/4jvcRERERERER2RNVVCcrpGrDsTZeyZ5HlVK76Yj9m1+l1B69+eZcZs68g6OOOoZTTz2Dp59+AjDqXWdZFqZZ/3hjktc3lH027z4iIiIiIiIi7VFd214oHG/jlex5VCklvPjis9x6640cfviR3HTTbRiGgcfjJRqNEIulJ721tbV4PPUHmjfG4/FSU1O/Iqqmpnn3EREREREREWmPKgLbQqmIKqWaS6FUJ/fXv/6F+++/hxNOGMett/4x1a7Xq1dvLMti48YNaddv3LiB3r2b3iPbq1fvevdIJBJs3ryxWfcRERERERERaY8q/CEAQhFVSjWXQqlO7KWXnufpp59g8uSzmD7992mzoYYOHYbT6eL99+enjlVXV/Pppx9z8MGHNvkZBx98CFu3lvHFFytSxz7++COCwWCz7iMiIiIiIiLSHtXNlFKlVPNpplQnVVZWxsMP30+/fvtxzDHHs3LlirTzAwcO4rTTTufRRx/CMEx69+7Nk08+jsfjYcKEU5r8nIMPPoTBg4cyffr1XH751cRiMf7yl//j8MOPZODAQS38ViIiIiIiIiKZVde+V6tKqWZTKNVJLVmykEgkwtdfr+XSS39Z7/zrr/+Hiy++AsMweeGFZ6itrWHo0GHMmHEzXm/TZ0EZhsEf/3g399zzJ+666w84nQ6OPHIMV199bUu+joiIiIiIiEibSA06VyjVbIZlWVZbL6K92Lo1QCLR8Ldj8+b1dO+uGUiZpO+5iIiIiIiItHeX3/0uoUic/BwXMy8/oq2X066YpkHXro0XtmimlIiIiIiIiIjIT1AbjhGKxDGAUFiVUs2lUEpERERERERE5Cco39a617WLm1AkjprRmkehlIiIiIiIiIjIT1C5LZTaq8BDwrKIxhJtvKI9i0IpEREREREREZGfoNwfAqBH12xAw86bS6GUiIiIiIiIiMhPUFcp1aOrB4DaSKwtl7PHUSglIiIiIiIiIvITVPjDeLMceLMcgIadN5dCKRERERERERGRn6DCHybf58LttAEQUqVUsyiUEhERERERERH5CSr8YXJ9LtxOO6CZUs2lUEpERERERERE5Ccor1cppVCqORRKiYiIiIiIiIg0UzQWJ1AbJc/nIstVVyml9r3mUCjVicXjcV544RmmTDmNY489knPOmcwrr7yIZVkAWJbFk08+xqRJ4znmmCP49a8vZ/36dY3e7777/sz11/+6wXOxWIxf/eo8nnvu6VZ4ExEREREREZHMqghEALa17yUrpWo16LxZFEp1Yn//+9945JEHOf74E7nzzrs5+uhjue++u3nuuacAeOKJR3nyycc566xzufnmPxAMBpg69TICgUC9e73yyou89NLzDT4nFotx2203sWrVF636PiIiIiIiIiKZUukPA5Dvc+PSoPOfxN7WC5C2kUgkePHF5zjrrHM5//yLABgx4lAqKyt5/vlnmDjxNJ5//hkuvPBXTJ58JgDDhh3IaadN4PXXZ3HmmecAUFFRzkMP3c+8ef/G6/XWe86aNV8xc+YdfPfd+sy9nIiIiIiIiEgrK/eHgGSllGkYuBw2zZRqJlVKdVKBQICxY8cxZszRacd79+5DZWUFy5Ytpba2hiOPHJM6l5OTw/DhB7F48cLUsaeeeoLlyz/lz3++n/32K673nNtv/z1udxZ/+9tTrfcyIiIiIiIiIhlWkaqUcgHgdiqUai5VSu2m6FcfEF39XpuuwTFgNI7iI5r1mZycHK699rf1jn/wwXsUFXVjy5YtAPTsuXfa+b326smCBe+mvp448VSuuGIqdrudJ598rN79brzxFvbdd79mrU1ERERERESkvavwh3E7bakh58lQSu17zaFKKUn5179m8dFHSzj77HOpqQnidDpxOBxp12RnZxMMBlNf9+7dF7u98WxTgZSIiIiIiIh0RBX+MHnbqqQA3C67KqWaSZVSu8lRfESzq5TaozffnMvMmXdw1FHHcOqpZ/D0008ARr3rLMvCNOsfFxEREREREelMKncIpbKcNkJhVUo1hyqlhBdffJZbb72Rww8/kptuug3DMPB4vESjEWKx9P+Dqq2txeOpP9BcREREREREpDMp94fJ825XKeVUpVRzKZTq5P76179w//33cMIJ47j11j+m2vV69eqNZVls3Lgh7fqNGzfQu3eftliqiIiIiIiISLuQSFhUBSLk5WwfSmnQeXMplOrEXnrpeZ5++gkmTz6L6dN/nzYbaujQYTidLt5/f37qWHV1NZ9++jEHH3xoxtcqIiIiIiIi0l5UBSMkLIs8nzt1TIPOm08zpTqpsrIyHn74fvr1249jjjmelStXpJ0fOHAQp512Oo8++hCGYdK7d2+efPJxPB4PEyac0jaLFhEREREREWkHKvxhALXv7SaFUp3UkiULiUQifP31Wi699Jf1zr/++n+4+OIrMAyTF154htraGoYOHcaMGTfj9WqmlIiIiIiIiHReqVDKl96+F4kliCcS2Ew1pjWFQqlOaty4CYwbN2GX11122VVcdtlVTbrnAw88stPzCxZ81KT7iIiIiIiIiLRnFf4QsEMo5UpGLKFIHI9boVRT6LskIiIiIiIiItIMFf4wdpuBN9uROuZ22gAIhdXC11QKpUREREREREREmqEiECbX68I0jNSxVCilYedNplBKRERERERERKQZKqrDaa17kBx0DmjYeTMolBIRERERERERaYaKQEOhVF2llEKpplIoJSIiIiIiIiLSRJZlUeHfWSil9r2myngo9cADDzB+/HjGjx/PXXfdBcAnn3zC6aefzvjx47n22muJRCIArFq1ikmTJnHCCScwffp0YrHkD3bjxo1MmTKFsWPHctlllxEMBgGorq7m4osv5sQTT2TKlCmUlpZm+vVEREREREREpAMLhmJEYwnyfO6041kute81V0ZDqQ8//JAFCxbw2muvMWvWLFauXMlrr73GVVddxS233MK///1vAF5++WUArrvuOm688UbeeOMNLMvipZdeAuDmm2/m7LPPZt68eQwdOpQHH3wQgHvvvZcRI0Ywd+5cJk+ezO23357J1xMRERERERGRDq7CHwZotFKqNqxKqabKaChVWFjItGnTcDqdOBwO+vXrx4YNGxg+fDgDBw4EYMaMGRx33HFs2LCBUCjE8OHDAZg0aRLz5s0jGo2ydOlSTjjhhLTjAPPnz2fChAkAnHTSSbz33ntEo9FMvqKIiIiIiIiIdGAV/hDQUCilSqnmymgo1b9//1TItG7dOubOnYvT6SQ7O5trrrmGX/ziF9x///3k5OSwZcsWCgsLU58tLCykpKSEiooKvF4vdrs97TiQ9hm73Y7X66W8vDyTrygiIiIiIiIiHVhdpVT+DqGUw25iMw2FUs3QJoPO16xZw4UXXsj1119PPB5nwYIFXHvttbz66qvU1tbyyCOPkEgkMAwj9RnLsjAMI/Xn9nb8evvPmKZmuYuIiIiIiIhIy6jwhzGAHI+z3jm306ZB582Q8cRm2bJlXHDBBfzmN79h4sSJFBQUcMABB9CrVy9sNhsnnngiy5cvp3v37mmDysvKyigqKiI/Px+/3088nkweS0tLKSoqAqCoqIiysjIAYrEYwWCQ3NzcTL/iHiMej/PCC88wZcppHHvskZxzzmReeeVFLMsCkqHek08+xqRJ4znmmCP49a8vZ/36dY3e7777/sz11/+63vGSks3cfPMMfvGLsYwdezRTp17O6tVfttJbiYiIiIiIiLSeCn+YHK8Tu61+pOJ22lUp1QwZDaU2bdrEFVdcwcyZMxk/fjwARx55JCtXrmTTpk0AvPPOOwwZMoSePXvicrlYtmwZALNnz2b06NE4HA5GjBjBnDlzAJg1axajR48GYMyYMcyaNQuAOXPmMGLECBwORyZfcY/y97//jUceeZDjjz+RO++8m6OPPpb77rub5557CoAnnniUJ598nLPOOpebb/4DwWCAqVMvIxAI1LvXK6+8yEsvPV/veDgc4tprr2TNmtVcffVvuOmmWzEMuPLKX7Fhww+t/o4iIiIiIiIiLanCHybP62rwXJbLplCqGeyZfNhjjz1GOBzmzjvvTB0788wzueWWW7j00ksJh8MMGjSI3/72twDMnDmTGTNmEAgEGDJkCOeddx4AN910E9OmTeOhhx6iR48e3H333QBMnTqVadOmMX78eHw+HzNnzszk6+1REokEL774HGeddS7nn38RACNGHEplZSXPP/8MEyeexvPPP8OFF/6KyZPPBGDYsAM57bQJvP76LM488xwAKirKeeih+5k37994vd56z/nggwWsX7+OF154jb337gXAgQeO4LTTTmL27Fe4/PKpGXpjERERERERkd1X4Q9TlJfV4Dm3067d95oho6HUjBkzmDFjRoPnjjrqqHrHBg4cyMsvv1zveM+ePXn66afrHc/NzeXhhx/e7XV2BoFAgLFjxzFmzNFpx3v37kNlZQXLli2ltraGI48ckzqXk5PD8OEHsXjxwlQo9dRTT7B8+af8+c/38+STj9V7js/nZfLks1KBFIDb7aaoqBsbN25spbcTERERERERaR0V/jADe+c1eM7ttBEMKZRqqoyGUh3R4k3LWLhpaZuu4bAehzCyx8HN+kxOTg7XXvvbesc/+OA9ioq6sWXLFgB69tw77fxee/VkwYJ3U19PnHgqV1wxFbvd3mAodcghozjkkFFpxzZu3MA333zNYYcd2aw1i4iIiIiIiLSlcCROTThGrq/+kHNIhlJbq0MZXtWeS1vTScq//jWLjz5awtlnn0tNTRCn01lvJld2djbBYDD1de/efbHbm55tRqNR7rzzVpxOF6eccmqLrV1ERERERESktVUEwgDk+9wNnteg8+ZRpdRuGtnj4GZXKbVHb745l5kz7+Coo47h1FPP4OmnnwCMetdZloVp1j/eFJFIhJtuuoHPPvuEW2/9I4WFRbu5ahEREREREZHMqdhWBZXra3jQudupQefNoVBKePHFZ3nggXs58sjR3HTTbRiGgcfjJRqNEIvF0iqhamtr8XjqDzTflUAgwLRp1/L5558xffrvGT36qBZ8AxEREREREZHWV+6vq5RqJJRy2QhFYliWhWH8tIKOzkShVCf317/+haeffoKxY8czbdr/SwVQvXr1xrIsNm7cQO/efVLX7/h1U1RWVjJ16mV8//133H77XWnD00VERERERET2FJXb2vcaq5TKctqxLIhEE7ictkwubY+kmVKd2EsvPc/TTz/B5MlnMX3679MqooYOHYbT6eL99+enjlVXV/Pppx9z8MGHNvkZsViM666bysaNG7j77vsVSImIiIiIiMgeq9wfxuO243I0HDi5twVRoYh24GsKVUp1UmVlZTz88P3067cfxxxzPCtXrkg7P3DgIE477XQeffQhDMOkd+/ePPnk43g8HiZMOKXJz3nllRdZtWolU6acj93uYMWKz1PncnJ89O7dt4XeSERERERERKR1VfrD5DVSJQXJQecAoUicLpla1B5MoVQntWTJQiKRCF9/vZZLL/1lvfOvv/4fLr74CgzD5IUXnqG2toahQ4cxY8bNeL1Nnyn1/vvvAvDss0/y7LNPpp07/PAjueuue3frPUREREREREQypdwfbrB1L16yFjN/7+0qpTTsvCkMy7Kstl5Ee7F1a4BEouFvx+bN6+nevXmzlGT36HsuIiIiIiIi7cmv71/A8P26csGJg1LHrHCQwFNX4Rp1Bl/7DuFPL3zKb88+kAG989pwpe2DaRp07dp4YYtmSomIiIiIiIiI7EIsnsAfjJDrTa+USlSXgpXAqqnC7Uo2pNWqUqpJFEqJiIiIiIiIiOxCZSCMBeTnuNOOJ/ylQLJiKtW+F9ag86ZQKCUiIiIiIiIisguV/ghAvUHnlr8s+Wc4mDboXHZNoZSIiIiIiIiIyC6U+0MA5O3YvpcWSmnQeXMolGoGzYTPHH2vRUREREREpD2p8IcByMvZMZT6sX3PlQql1L7XFAqlmshmcxCNhtt6GZ1GNBrBZrO39TJEREREREREgGQo5bSbZLvS/111+/Y90zBwOW2qlGoihVJN5PV2obKyjGDQTzweUyVPK7Esi0gkTGVlKV5vblsvR0RERERERARIhlJ5PheGYaSOWZaV1r4H4HbaVCnVRCpFaaKsLA92u4NAoJJgsIpEQqlna7HZ7Ph8eWRledp6KSIiIiIiIiIAVATC9Yec11ZDPILh9mGF/FiJGFlOuyqlmkihVDM4HE7y8oraehkiIiIiIiIikmEV1WGKe3VJO2YFklVSZmFf4t9/jhWuwe20URtWKNUUat8TEREREREREdmJhGVRGQiT53OnH69ODjm3de0DgBUOqH2vGRRKiYiIiIiIiIjshL8mSjxh1Wvfq5snZRYkQylCQdxq32syhVIiIiIiIiIiIjtR4Q8B1J8p5S/DcPswvV2TX4eDuF2qlGoqhVIiIiIiIiIiIjtR4Q8D9UOphL8Uw1eA4Upu1GWFVSnVHAqlRERERERERER2otFQKlCG6SvcIZSyKZRqIoVSIiIiIiIiIiI7UeEPYzMNcrKdqWOWlcDyb8X0FYAzGzCwwkGynDaisQSxeKLtFryHUCglIiIiIiIiIrITFf4wXbxOTNNIHbOClZCIJdv3TBOcWan2PUDVUk2gUEpEREREREREZCcq/OEGW/cATF8hAIbLk2rfAzTsvAkUSomIiIiIiIiI7ESFP0yed4ed96pLAZLte4Dh9m7bfU+VUk2lUEpEREREREREpBGWZW2rlHKnHa+rlDK8XZN/OrOxwoHtKqUUSu2KQikRERERERERkUbUhuOEo/H67XvVZRjZuRj25PDzZPtejdr3mkGhlIiIiIiIiIhIIyr8IYB6oZTlL8XY1roHyfY9wkGy6gadh1UptSsKpUREREREREREGlHhDwP1Q6lEoCw15By2G3TuSEYttaqU2iWFUiIiIiIiIiIijWgolLIScaxAeWrIOYDhygYrgctMhlGaKbVrCqVERERERERERBpRF0rlbrf7nhUsByuR3r7n8gLgspLtfgqldk2hlIiIiIiIiIhIIyoCYXKyHTjsP0YoCX9y573t2/dweQCwxWqw2wwNOm8ChVIiIiIiIiIiIo2o8IfJ3XHIeXUpwA7te8lQygoFcTvtqpRqAoVSIiIiIiIiIiKNKK8Ok+9zpx1LBMrAMDC8+aljqVAqEsTttBEKq1JqVxRKiYiIiIiIiIg0ojJQv1IqUV2K4cnHMO2pY6qUaj6FUiIiIiIiIiIiDYhE4wRqo2k77wFYga1prXuwXSgVDuJ22RRKNYFCKRERERERERGRBlQGkjvv5e9YKeUvTdt5D8CwO8HmwAoHku17GnS+SwqlREREREREREQaUOFPhlLbt+9Z8ShWsDJ9571tDJcHwjVq32sihVIiIiIiIiIiIg0o99evlLICWwGrkVDKm2zfc6p9rykUSomIiIiIiIiINKCyrlLK+2MolfCXAdRr3wMwXNlq32sGhVIiIiIiIiIiIg0o94fJctnIcv24y16iuhSg3qBzSLbvWeEaspx2QuE4lmVlbK17IoVSIiIiIiIiIiINqPSH06qkAKxAGZg2jOy8+h+oa99z2bCAcFQtfDujUEpEREREREREpAHl/nD9nfeqSzG8XTHM+pGK4fZsa99LVlZprtTOKZQSEREREREREWlAhT9Ens+ddiwRKGtwyDmA4cyGWIQse7JtT6HUzimUEhERERERERHZQTyRoCoYIXeHSinLX4bp69rgZwy3F4BsIzkgXcPOd06hlIiIiIiIiIjIDqoCESyLtPY9KxrGqq3GaKxSyuUBIMuIABAKq1JqZzIeSj3wwAOMHz+e8ePHc9ddd6Wde+aZZzj33HNTX69atYpJkyZxwgknMH36dGKxZMK4ceNGpkyZwtixY7nssssIBoMAVFdXc/HFF3PiiScyZcoUSktLM/diIiIiIiIiItJhVASS1U7bV0olAmVAwzvvwXahFCEAalUptVMZDaU+/PBDFixYwGuvvcasWbNYuXIlb731FgBr167lkUceSbv+uuuu48Ybb+SNN97AsixeeuklAG6++WbOPvts5s2bx9ChQ3nwwQcBuPfeexkxYgRz585l8uTJ3H777Zl8PRERERERERHpICqqk6FUWqWUP1n80uhMqW2hlMuqa99TpdTOZDSUKiwsZNq0aTidThwOB/369WPjxo1EIhFuvPFGrr766tS1GzZsIBQKMXz4cAAmTZrEvHnziEajLF26lBNOOCHtOMD8+fOZMGECACeddBLvvfce0Wg0k68oIiIiIiIiIh1AhT8ZLOVtXynlT1ZKGbuolHImkpVSCqV2LqOhVP/+/VMh07p165g7dy5jxozhz3/+M6eeeiq9evVKXbtlyxYKC39MHgsLCykpKaGiogKv14vdbk87vuNn7HY7Xq+X8vLyDL2diIiIiIiIiHQUFYEwdpuJN8uROpbwl4HNgZHVpcHP1IVS9ngNoEHnu9Img87XrFnDhRdeyPXXX8+GDRvYtGkTp556ato1iUQCwzBSX1uWhWEYqT+3t+PX23/GNDXLXURERERERESap8IfJs/nTM8mqksxfQWN5hA4swADW6wWAw0635WMJzbLli3jggsu4De/+Q0TJ07k9ddfZ82aNfziF79gxowZrFixgl//+td07949bVB5WVkZRUVF5Ofn4/f7iceTP9jS0lKKiooAKCoqoqwsWUoXi8UIBoPk5uZm+hVFREREREREZA9X4Q+T53WlHUsEyhpt3QMwDBNc2RCuweW0qX1vFzIaSm3atIkrrriCmTNnMn78eADuuOMO5s6dy+zZs7ntttsYOnQo9957Lz179sTlcrFs2TIAZs+ezejRo3E4HIwYMYI5c+YAMGvWLEaPHg3AmDFjmDVrFgBz5sxhxIgROByO+gsREREREREREdmJCn+IvBx32rGEv6zRIed1DJcXKxwky2XX7nu7YM/kwx577DHC4TB33nln6tiZZ57JWWed1eD1M2fOZMaMGQQCAYYMGcJ5550HwE033cS0adN46KGH6NGjB3fffTcAU6dOZdq0aYwfPx6fz8fMmTNb/6VEREREREREpEOxLIsKfyRtyLkVqYFwEHMnlVKQnCtlhQO4VSm1S4ZlWVZbL6K92Lo1QCKhb4eIiIiIiIhIZ+aviTD1vgWcdUx/jjskuSlbfOt31LxyI+5jL8ex76GNfrZmzkyscJC7q8fhyXJw7enDM7Tq9sc0Dbp29TZ+PoNrERERERERERFp9yr8YYC0SqmEPzn3umntezW4nXZVSu2CQikRERERERERke00FEpZ/uTGajsbdA47tO9p972dUiglIiIiIiIiIrKdhiulysDhxnA13o4GYGzbfc/tMAlp0PlOKZQSEREREREREdlOhT+MYUAXrzN1zPKXYfoKMAxjp59NhlYWPntM7Xu7oFBKRERERERERGQ7Ff4wXTxObOaPsUnCX4rh3XnrHoDh9gDgtUdVKbULCqVERERERERERLZT4Q+R53OnvrYsi4S/DDNn50POITlTCsBrixCLW8TiiVZb555OoZSIiIiIiIiIyHYqApG0eVKEgxANYTahUoptoVS2EQFQC99OKJQSEREREREREdlOslJq+yHnpQAYOU1o39sWSmWRHJYeCquFrzEKpUREREREREREtqkNx6gNx+vvvAeYvqa376VCKVVKNUqhlIiIiIiIiIjINpWBZJi0fShlbauUMn1Nr5RyWiFAodTOKJQSEREREREREdmm3J8MpfJ3rJRyeTCc2bv8vGFzgN2JM1ELQK124GuUQikRERERERERkW0qt4VSuTuEUk0acr6N4fLiiKtSalcUSomIiIiIiIiIbFNXKZXnTW/fa0rrXh3D5cEWT1ZKadB54xRKiYiIiIiIiIhsU+kP43HbcTpsAFiWRcJfhpGz6yHndQxXNrZoDaBKqZ1RKCUiIiIiIiIisk2FP0yez5362qqtgni02e17RiqUUqVUYxRKiYiIiIiIiIhsU+4PkZ+zfeteGQBmTvPa9wgHsdtMVUrthEIpEREREREREZFtKv1hcr077LwHGN6mt+/h8mCFg7idNmoVSjVKoZSIiIiIiIiICBCNJaiuiZKftvNeKUCzB50Tj+JzWWrf2wmFUiIiIiIiIiIiQFUgufNeri+9fc/IysFwuBr7WD2GywNAF0ecUFiVUo1RKCUiIiIiIiIiApT7k6FUeqVUGUYzhpwDGO66UCqqSqmdUCglIiIiIiIiIkJy5z2AvB3a95rTugdgOJOhVI49qkHnO6FQSkRERERERESE+qGUlUhgBbY2P5TaVinltUUUSu2EQikREREREREREZKhlMthI8tlB8CqqYBEHMPXjJ33+HGmlMeMUKv2vUYplBIRERERERERASoCYXJ9LgzDAJLzpADMnOaGUl4gGUqpUqpxCqVERERERERERIAKfyhtyLlVF0o1c9A5DjcYJlmECUfiJCyrJZfZYSiUEhEREREREREBKv1hcr3pQ84BDF/XZt3HMAwMlwc3yRlVYVVLNUihlIiIiIiIiIh0eomERWUgQn7O9qFUGUZ2LobN0fwbujy4rBCAWvgaoVBKRERERERERDq96poI8YSV2nkPwPKXYjZzyHkdw+XBmagLpTTsvCEKpURERERERESk06vwJ1vt8rw7VEr5mjlPahvD5cEerwVUKdUYhVIiIiIiIiIi0umlQqlt7XtWIoYVLMfcnVAqti2UCqtSqiEKpURERERERESk09uxUsoKlINl7Vb7nhmrAVQp1RiFUiIiIiIiIiLS6VX4w9hMA5/HCSRb9wCMnN0IpaK1GCQUSjVCoZSIiIiIiIiIdHoV/hC5XhemYQCQ8JcCYHp/evseQJYR0aDzRiiUEhEREREREZFOr8If3mHnvTIwTAxv/k+6X10olW1EVCnVCIVSIiIiIiIiItLp7RhKJfxlGJ48DNP2k+5nuJOhlMeMUKtQqkEKpURERERERESkU7Msi4rAjqFU6U8ecg5gOJOhVK4zqt33GqFQSkREREREREQ6tZpwjEg0Ua99z9iNUIptlVI59pja9xqhUEpERERERESkk9tQGmD512VtvYw2U1EdBkiFUlYsglVTien7aUPOAQyXF4Ace1SDzhuhUEpERERERESkk3t94Xr+9vqqtl5Gm6kI7BBKBcoBdjOUygbAa4uqUqoRCqVEREREREREOrkKf5hAbZTaTjr7qMKfHkol/KUAGLsTSpl2cLjxmmGFUo1QKCUiIiIiIiLSyVVtqxQqqwq18UraRl0oletND6V2Z9A5gOHykG1G1L7XCIVSIiIiIiIiIp2YZVlUBiIAlFXWtvFq2kaFP0SOx4ndloxJLH8ZmDYMT+5u3ddwecgiTG1YlVINUSglIiIiIiIi0omFInHC0WRo0lkrpcr9YfK8P+68l/CXYXgLMIzdi00Mlwc3YVVKNUKhlIiIiIiIiEgnVrmtdQ+gtKpzVkpV+sOpeVKQDKV2Z8h5HcPlwWWFNFOqEQqlRERERERERDqxutY9gLLKzlkpVeEPk5fzYyhl+UtbLJRyJELEExbRWGK379fRKJQSERERERER6cTqKqW65WdT1gkrpcLROMFQLNW+Z0VDWCE/xm4OOYdtoVS8FrDUwtcAhVIiIiIiIiIinVjVtkqp/j27UFYVwrKsNl5RZlVu23mvrn0v4d8K0CKVUrg8mFYcJzG18DVAoZSIiIiIiIhIJ1YZCONy2Ni70EMokqwa6kzKdwilLH8p0DKhlOHyAJBlRKgNd67va1NkPJR64IEHGD9+POPHj+euu+4C4MUXX+Skk05iwoQJ3HDDDUQiyZR21apVTJo0iRNOOIHp06cTiyV/gBs3bmTKlCmMHTuWyy67jGAwCEB1dTUXX3wxJ554IlOmTKG0tDTTryciIiIiIiKyR6kMhBnoraJv5CsASis7Vwtf/UqpMoAWa98D8JgRVUo1IKOh1IcffsiCBQt47bXXmDVrFitXruSRRx7hscce44UXXuCf//wniUSC5557DoDrrruOG2+8kTfeeAPLsnjppZcAuPnmmzn77LOZN28eQ4cO5cEHHwTg3nvvZcSIEcydO5fJkydz++23Z/L1RERERERERPY4lYEIP7N/Trc1rwJQVtW5hp2X+5Pv+2MoVQo2J0ZWzm7fuy6UyjbCCqUakNFQqrCwkGnTpuF0OnE4HPTr149IJMJNN92E1+vFMAyKi4vZuHEjGzZsIBQKMXz4cAAmTZrEvHnziEajLF26lBNOOCHtOMD8+fOZMGECACeddBLvvfce0Wg0k68oIiIiIiIiskepDITJNYOY0RrcRoSyTlcpFSHLZcfttANg+cswfQUYhrHb904PpdS+t6OMhlL9+/dPhUzr1q1j7ty5nHTSSRxxxBEAlJeX8+yzz3LMMcewZcsWCgt/LJUrLCykpKSEiooKvF4vdrs97TiQ9hm73Y7X66W8vDyDbygiIiIiIiKy57Asi8pAGK8VAKCnO9QpK6Xyt1VJQbJ9z2iJIeeA4fYCkG2ofa8hbTLofM2aNVx44YVcf/319O3bF4CSkhLOP/98Tj31VEaOHEkikUhLJS3LwjCM1J/bayy9tCwL09QsdxEREREREZGGhCJxotEY7lgylOrtjVBa1ckqpQJhctNCqdKW2XmP7SqlTLXvNSTjic2yZcu44IIL+M1vfsPEiRMB+PrrrznzzDOZOHEiV1xxBQDdu3dPG1ReVlZGUVER+fn5+P1+4vHkD7O0tJSioiIAioqKKCtLDiSLxWIEg0Fyc3Mz+HYiIiIiIiIie47KQBifEcIgAcBe7lrKKjtbpVT4x533wkGI1GC2wJBzAOwuMGzJSintvldPRkOpTZs2ccUVVzBz5kzGjx8PQCAQ4KKLLmLq1KlceOGFqWt79uyJy+Vi2bJlAMyePZvRo0fjcDgYMWIEc+bMAWDWrFmMHj0agDFjxjBr1iwA5syZw4gRI3A4HBl8QxEREREREZE9R6U/TK5Zk/q60F5DWVWIhGW14aoyJxZPUB2IpNr3ftx5r4UqpQwDw+3Ba1P7XkPsmXzYY489Rjgc5s4770wdGzduHGVlZTzxxBM88cQTAPz85z9n6tSpzJw5kxkzZhAIBBgyZAjnnXceADfddBPTpk3joYceokePHtx9990ATJ06lWnTpjF+/Hh8Ph8zZ87M5OuJiIiIiIiI7FEqgxHyzGDyC8NGruFPBjXBCLle184/3AFUByNYkGrfqwulWqxSimQLn88WZbMGndeT0VBqxowZzJgxo97xSy65pMHrBw4cyMsvv1zveM+ePXn66afrHc/NzeXhhx/e/YWKiIiIiIiIdALJnfeSlVJmYR+yayoBKKsMdYpQqtwfBkhVSlmpUKplKqUAcHnwmLWqlGqApoCLiIiIiIiIdFKV/ghdHbVgc2Ar6IszXAHQaYadV24LpeoCuIS/FBxu2DagvCUYLg/ZhgadN0ShlIiIiIiIiEgnVRUMU+CoxfDkY/oKMaK1ZBkRyio7RyiVqpTKcQPJ9j3TV4hhGC32DMPlIcuIEFL7Xj0KpUREREREREQ6qUp/mDxbLaYnLzXcu5cnTFlV59iBr8IfwmE38biT040sf1nLtu6RDKXcVojasCqldqRQSkRERERERKSTqgxEyCGA4clLhTF9OlUoFSbP68IwDCzLIuEvbbGd9+oYLg9OIkQi4Ra9b0egUEpERERERESkE7Isi6pgiOxEANPbNRXG9HCHKO0k7XsV/jB5dUPOwwGIhVt05z1IhlIARDrH97Q5FEqJiIiIiIiIdEK14TjOWA0mCQxPHobLC3YXBfYg5dVh4olEWy+x1aWFUtWlAK1SKQVgRhVK7UihlIiIiIiIiEgnVBkIk2sGATA9+RiGgekroAvVJCyLCn/HbjdLWBaVgR9DqUSgDKDVKqXs8VoSltWi997TKZQSERERERER6YSqAmFyzRoADG9e8k9fAdmxKgDKKjv2XKlATZRY3CK3LpSqrgulWqdSymOGCUc07Hx7CqVEREREREREOqHKQOTHUMqTDyQDGUeoAoDSqo7dblZXCZZf177nLwWXB8OZ1aLPMVxeALKMCCGFUmkUSomIiIiIiIh0QpXBbe17ph3DnQxOTF8BRrSWbDPS4Sul6kKpPJ8bSLbvtXTrHgDuZKVUthGmNhxr+fvvwRRKiYiIiIiIiHRClf4IXe21ySHnRjIeMLzJ1rW+3ghlVR08lArUhVI/Djpv6dY9AMOZDYBHlVL1KJQSERERERER6YQqA2G6OmoxvfmpY3WVQr08Yco6fPteCNMw6OJxYlkWicDWFt95D8AwbSTsbrLNMKGIKqW2p1BKREREREREpBOqCoTpYgQxPHmpY3WVQnu5ajp+pVR1mC5eJ6ZpYNVWQTzaKpVSAJYzWzOlGqBQSkRERERERKQTqgyE8VpBTM+PlVK4POBw09UepNIfJhpLtN0CW1lFIJzWuge0zkwpwHB68BiqlNqRQikRERERERGRTsayLKLBKmzE0yqlDMPA9BWQY/mxgPLqjlstVeH/MZRKBMoAMForlHJ7yFalVD0KpUREREREREQ6mdpwHE8iAICx3Uyp5NcFZMeqACjtwHOlKvxh8rzbQqlUpVTXVnmWze0l29TueztSKCUiIiIiIiLSyVQGwuSaNQDp7Xsk50rZQ+WARVllx6yUqg3HCEXi5OVsa98LlGFk5WDYXa3yPNPtVaVUAxRKiYiIiIiIiHQyyVAqCJDWvgfJUMqIhvDaoh22UqrcHwb4sVLKX9YqO+/VMd0eso0wIVVKpVEoJSIiIiIiItLJVAUi5Jo1WIaJkZWTdq4unNknJ8rWDroDX2VdKOX7sX2vtYacAxguDzbDIhauabVn7IkUSomIiIiIiIh0MnXte0Z2HoaRHg2Y20Kp3tkhSjto+165P/leeTlurEQCK1DeqqEULg8AlkKpNAqlRERERERERDqZikCYfFsNth2GnAOpcKa7q5ayDtq+l6qU8jqxairAirdq+57h8ib/JhJstWfsiZoVSlmWRSAQSH09d+5cHn/8cb7++usWX5iIiIiIiIiItI6qQIQ8e029nfcAcGaDI4uutgD+miihSMebg1ThD+PNcuCw20j4y4AfK8Rag+HKTv6pSqk0TQ6lVq9ezc9//nMeffRRAO6//36uueYa7r77biZOnMjChQtbbZEiIiIiIiIi0nIq/SFyCNYbcg5gGAamr4Acyw/QIedKVfjDqXlSlr8UaO1QKlkpZcYUSm2vyaHUn/70J/Lz85kwYQI1NTU89thjnHrqqSxfvpwTTzyRe++9txWXKSIiIiIiIiItJRysxk4c09NApRTJgCYrWglAaQcPpRLVpYCB4e3aas8zts2UssU6ZjvkT9XkUOqTTz5h6tSp7LfffixYsIBwOMzkyZMxTZOJEyeyevXq1lyniIiIiIiIiLQAy7IwaioBGqyUguQOfLbaCsCirLJjBSkJy2JrdejHUCpQhuHJw7A5Wu2ZdaGUI96xvpe7q8mhlGma2O12AN599126dOnC8OHDAaiqqiI7O7tVFigiIiIiIiIiLac2HMNrJedFmw3NlAJMbwFGLEQXR4yyDlYpteb7SoKhGAN65QJg+ctatXUPALuThGHDmQhhWVbrPmsPYm/qhcOHD+exxx6jsrKSOXPmMH78eABWrVrFAw88wMEHH9xqixQRERERERGRllERiJBrJneBMxpp36vbiW7fnGiHC6UWf1GC02FyYP/kLoMJfxm2HgNa9ZmGYRC1ZeEmRCyewGG3terz9hRNrpT63e9+x8aNG7n22mvp1q0bV111FQC/+tWviEajXH/99a22SBERERERERFpGVWBMF3MGizDxMjq0uA1dZVDvbJDHap9LxZPsPTLLRzUvxCX04aViGEFy1u/UgqI27PJNiPUhuOt/qw9RZMrpfbZZx/mzp1LeXk5eXl5GIYBwGOPPcZ+++2HzaaUT0RERERERKS9qwyEyTVrsNxdMMyGa1XqQppuzhpKt3ScSqkV35QTDMUYObgbAFagHCwL01fY6s+2HFlkG2FCkRg5HmerP29P0ORQqk4oFGLWrFmUlpYyceJEwuEwsVhMoZSIiIiIiIjIHqAyEKHIDGJrZJ4UbBvM7cwi3wxSG44RDEXxuFtvEHimLPpiM94sB0P2Sb57wl8G/Niu2Josp4dso5pQRJVSdZocSiUSCW6//XZeeOEF4vE4hmFwxBFHcO+997JhwwaeeuopunXr1pprFREREREREZHdVBkIM9BWg83Xa6fXmb4CcqxqAMoqQ3i679mhVCgS49M1ZRyxfw/stmSFWMJfCpCR9j1cHrKNiEKp7TR5ptQDDzzAq6++yh133MGHH36YmhZ//fXXE4/H+fOf/9xqixQRERERERGRllHpT86UamzIeR3TW4A7WglAWdWeP1fqk6/KiMQSqdY9SO68h2Hu8nvREkyXh2wz2b4nSU0OpV555RWuvfZaTj75ZLp0+XEQ2sCBA5k6dSoffPBBqyxQRERERERERFpObaAaJzHMXQQxhq8Ae205YFFauefPlVr0RQldc1zst/ePmUbCX4rhzccwW38kken24jZihELhVn/WnqLJoVRlZSX77LNPg+fy8/MJBAIttigRERERERERaR1WsAIAw5u30+tMXwHEwnR1xff4Sqnqmggrvy3n0MHdMLdt3AbJmVKZGHIO4Mj2AhCrVX5Sp8mh1IABA3jttdcaPPfWW29RXFzcYosSERERERERkZZnWRa2UCVAEyqlkmHNvjkRyqr27Eqpj77cQsKyOGxw97Tjlr8sM/OkAHtdKFWjUKpOkwedT506lYsvvpiSkhLGjBmDYRi8/fbbPPHEE8yZM4cHH3ywNdcpIiIiIiIiIrupJhzDayVDEcPThEopoGdWiCV7eCi1aGUJPQs97F3kTR2zYhGsmsqM7LwH4Mz2EQbioWBGnrcnaHKl1BFHHMHf/vY3otEo99xzD5Zl8eCDD7J27VoeeOABjjrqqFZcpoiIiIiIiIjsrspAhFyzBgsDIzt3p9ea3q4AdHfVUlZVm9rwbE9TWlnL2g1VjNpuwDmAFdgKkLH2PVuWL/k3YVVK1WlypRTAYYcdxmGHHUYoFKKqqgqv14vH42mttYmIiIiIiIhIC6oMhMk1gyRcObsc7m24PODMJs8MEIkmqK6J0sXjzNBKW86SVSUAjByUHkol/KXAj22Krc1wJfMTK1KTkeftCXYaSlVWVjZ6zuVyEY1G067Jzc1toWWJiIiIiIiISEur9IfJNWtgF617dUxfAb5ENQBllbV7ZCi16IsS9tu7CwW5WWnHE/4ygIzNlKoLpUyFUik7DaVGjRqFsd1U+l1ZtWrVbi9IRERERERERFpHVTBCf7MGu2+vJl1v+gpwb90IQFlViH49u7Tm8lrc91sCbCgNcs7x9Tdns/xlYNoxsjP0Ts5sAMyoZkrV2Wko9Yc//KFZoZSIiIiIiIiItF91lVJ238533qtj+Aqx/bACsCirqm3dxbWCRV9sxjQMRgwsqncu4S/F8HXFMJo8bnu3GKZJCBe22J73fWwtOw2lJk2alKl1iIiIiIiIiEgrC1ZX4zaimJ6mhVKmrwBiEbplxymt3LN24EtYFku+KGHIPvnkZNdvO0z4yzI25LxOxHRjjyuUqtOsQedfffUVS5cuJRqNpqbuW5ZFbW0tn376KY8++mirLFJEREREREREdl88WA6A4W1iKOVNzlvaxxfd4yql1v5QxdbqMJPG9GvwvOUvw1bQJ6NrippunNE9K9xrTU0OpV588UV+//vfY1kWhmGkbQVpmiaHH354qyxQRERERERERFpIsAJsYDSxUsrYNgS8Z1aIb6r2rDBl0RclOO0mB/avP8jcioawQv7U+2VKzJ6FK6KZUnWa3Dj5xBNPcNRRR7F48WIuuugiJk+ezKeffsp9991HVlYWJ510UmuuU0RERERERER2g2VZ2MNVAJhN3n2vKwBFzhq2VoVIJKxdfKJ9iMUTLF1VwvD+Bbid9etxftx5L7Pte3F7Nm7CGX1me9bkUOqHH37g7LPPpkuXLuy///4sXboUt9vN8ccfz+WXX85TTz3VmusUERERERERkd1QE46RQxALAyM7t0mfMZzZ4PKQbwaIJywqA3tGoLLy23KCoRijBndv8LzlLwW2zczKoIQjmyzCe0y419qaHEplZWVhtyfTxT59+vD9998TCiVL94YNG8b69etbZ4UiIiIiIiIistuSO+8FiTu8GLamj5g2vQX44skKq9LKPWOu1OIvSvC47Qzdt+E2xbpKKSPDlVI4s8k2ItSGI5l9bjvV5FDqwAMP5B//+AeJRIJ9990Xu93Oe++9ByQHoLtcrlZbpIiIiIiIiIjsnspAhFyzhkQTq6TqmL4CXJFKAMr2gLlSoUiMj9eUcsjAIuy2hmOPhL8M7E4Mty+zi3N6MA2LcLAms89tp5ocSl155ZW88847/OpXv8LpdHL66afz29/+lnPPPZc777yTY489tkn3eeCBBxg/fjzjx4/nrrvuAuDDDz9kwoQJHH/88dxzzz2pa1etWsWkSZM44YQTmD59OrFYDICNGzcyZcoUxo4dy2WXXUYwmBwSVl1dzcUXX8yJJ57IlClTKC0tbfI3QkRERERERKQjqwyEyTVrMJu4814dw1eAWVOOgbVHhFKfrikjEk0wcnC3Rq+x/KWYvgIMw8jgysB0ewAIBf0ZfW571eRQatiwYcyZM4fzzz8fgBtuuIH/+Z//we1286tf/Yrf/e53u7zHhx9+yIIFC3jttdeYNWsWK1eu5PXXX+d3v/sdDz74IHPmzGHFihW8++67AFx33XXceOONvPHGG1iWxUsvvQTAzTffzNlnn828efMYOnQoDz74IAD33nsvI0aMYO7cuUyePJnbb7+92d8QERERERERkY6oMhCmixnEmdO8OUqmrwDiEXr6LMr2gPa9RV+UkJ/jon+v3EavSfjLMt+6B9iyvABEa6oz/uz2aJehlGVZvPfee3z11Vf06NGD0aNHs2HDBqZPn867775LUVEREydOxO127/JhhYWFTJs2DafTicPhoF+/fqxbt44+ffrQq1cv7HY7EyZMYN68eWzYsIFQKMTw4cMBmDRpEvPmzSMajbJ06VJOOOGEtOMA8+fPZ8KECQCcdNJJvPfee0Sj0Z/6vRERERERERHpMPzVfrLNKPZtO+o1Vd0w8D7eMKXtvFLKXxNh5bfljBzUDbORKigrGiJRtTnjO+8B2LOS7YLRmkDGn90e7TSUCgaDnHXWWVxyySXMnz8fSLbInXXWWbz++usUFRWxYsUKJk+ezIYNG3b5sP79+6dCpnXr1jF37lwMw6Cw8MdfhKKiIkpKStiyZUva8cLCQkpKSqioqMDr9aaGrtcdB9I+Y7fb8Xq9lJeXN/27ISIiIiIiItJBxaq3AmB685r1OWNbKNUzK8TWqvZdKfXRl1uIJ6ydtu5Fv3wXYhEc/Q/L4MqS7NnJSqm4QilgF6HUI488wrp163j44Ye58MILAXjiiScoLS3llltu4YEHHuDVV19lwIABPPDAA01+6Jo1a7jwwgu5/vrr6dWrV1oPp2VZGIZBIpFo8Hjdn9trrAfUsixMs8kdiiIiIiIiIiIdlhWsAMDwNG+mlOlNhlJFjhrK/WFi8USLr62lLPqihL0KPPQq8jZ43krEiCx/A1uPAdiK+mV4deD0JCulEmGFUrCLUOrNN9/k0ksvZcyYManKpDfeeIOcnBx+8YtfAGCz2TjjjDNYsGBBkx64bNkyLrjgAn7zm98wceJEunfvnjaQvLS0lKKionrHy8rKKCoqIj8/H7/fTzweT7seklVWZWXJbR1jsRjBYJDc3NwmfitEREREREREOi4zVJn8s5mhlOHMwnB5yTP8WBaUV7fPFr6yqlrW/FDFyMHdGi1eiX29BCtYjvOAcRleXZLbkwOAFQq2yfPbm52GUhs2bGDQoEGpr8vKyvjmm28YOXJkWgVSUVERFRUVu3zYpk2buOKKK5g5cybjx48H4IADDuDbb79l/fr1xONxXn/9dUaPHk3Pnj1xuVwsW7YMgNmzZzN69GgcDgcjRoxgzpw5AMyaNYvRo0cDMGbMGGbNmgXAnDlzGDFiBA6HoxnfDhEREREREZGOx7IsHJHkcG3Dk9vszxu+AryJ5Ofb61ypJau2ADCqkdY9y7KIfDYHM29vbL2GZXJpKe7sLCKWDSIKpQDsOzvpdrsJhX78ZVuyZAkAhx9+eNp1JSUl5OTk7PJhjz32GOFwmDvvvDN17Mwzz+TOO+/kqquuIhwOM2bMGMaOHQvAzJkzmTFjBoFAgCFDhnDeeecBcNNNNzFt2jQeeughevTowd133w3A1KlTmTZtGuPHj8fn8zFz5symfA9EREREREREOrRgKEYOASJ2D4at+cUbpq8AZ9kPAGxtp6HUopWb6dczh8LcrAbPx3/4nET5D7iP+lWjlVStzWE3qbWcGNGaNnl+e7PTUGr//ffn7bffZsyYMQD885//xGazcfTRR6dd9+qrrzJkyJBdPmzGjBnMmDGjwXP//Oc/6x0bOHAgL7/8cr3jPXv25Omnn653PDc3l4cffniX6xARERERERHpTCoDYXLNGuLu3J/0ecNXgPndZ5gGlFa2v2HnP2wJ8ENpkCnHFTd6TeTTORiefOz9RmZwZekMw6AWNzaFUsAuQqn/+Z//4aKLLmLz5s0kEgkWLFjAqaeeSrduyVK45cuX8/TTT/Phhx8qDBIRERERERFpp6oCEfLMIEb23j/p86a3AOJReuUkKGuHlVKLV5VgGgaHDCxq8Hx8yzfEN32Ja9SZGLadRiGtLmy4yIq1v2CvLex0ptRhhx3GQw89RCgUYvPmzfzyl7/kpptuSp2/7LLLeOutt/jtb3+bqqYSERERERERkfalMhCmi1mD3df1J33e9CV34Ovri1LWziqlLMti0coSBu+TR47H2eA1kc/mgDMLx8C2zy4ihhtHvH19D9vKLuPBMWPGNBo4Pfjgg/Tt25cuXbq0+MJEREREREREpGVUV/vxmBFsuQU/6fPGtlBqL3cNn25qX5VSazdUsbU6xMTR+zR4PlFVQuzbZTiHj8dwNjxvKpMitiwcibK2Xka7sFs1awcccEBLrUNEREREREREWkm4aisAjpzdq5QqstdQFYwQicZxOmwttr7dseiLEpx2kwP7FzZ4PrJ8Hpg2HEOPzfDKGha3uXHF21ew11Z22r4nIiIiIiIiInu+uL8cAMOT95M+bzjcGG4fuUYAoN3MlYrFEyxdtYXh/QvIctWvu0nUVBH96n0cxUdgZudmfoENiNuzcRDDikXaeiltTqGUiIiIiIiISEdXUwGA6cn/ybcwfAV44lUAlFW1j5lIX6yrIFAbZeTgbg2ej678D8TjOIeNzfDKGpdwZANgRbQDn0IpERERERERkQ7OEa4EfnqlFIDp7YoznAy32kul1KIvNuNx29l/3/ptiVY0ROSL/2LvexBmbo82WF3DLKcn+Wc42MYraXsKpUREREREREQ6MMuycEWridiyMewN707XFIavAKOmHLvNoKyy7UOpcCTOJ1+VcfCAIuy2+vFG9Mv3IBzEecCJbbC6xhmubZVSoUAbr6TtKZQSERERERER6cCCoRg5Rg1RZ85u3cf0FUA8Sp8uFqXtoH3v07VlhKNxDhtSv3XPSsSIfP4Gtu7F2Lrt1wara5zhSlZKRWsUSimUEhEREREREenAKgNhcs0giayf3roHYPqSu9v18YbaRaXUopWbyfO56N8rt9652NdLsAJbcR4wLvML2wVblg+ASNDfxitpewqlRERERERERDqwZChVg7kb86Qg2b4HsJc71OaDzgO1UVZ8W87IQd0wDSPtnGVZRD6bi5m3F7bew9pohY2zZ3kBiNUqlFIoJSIiIiIiItKBVVcF8ZphnF0Kdus+pjf5+UJ7kGAoRk0o1hLL+0k++nIL8YTV4K578R9WkCj/HuewEzGM9hd7OLM9JCyI16p9r/39dERERERERESkxdRWlgKQlVe4W/cxHC4Mt48uJMOUtqyWWvRFCT26ZtO7m7feuchnczA8edj3O6wNVrZrbpeDWstJQoPOFUqJiIiIiIiIdGTRqnIAHDldd/tehq8AT7wKgLKqtpkrtbUqxFffVzJqcDeMHVr34qXfEt+4Cuf+x2PY7G2yvl1xO+3UWC6scE1bL6XNKZQSERERERER6cASNclQyvTk7/a9TF8BzlAFAGWVbVMptWRVCUCDrXuRz+aCMwvHwKMyvKqmcztt1FhOrHCwrZfS5hRKiYiIiIiIiHRgZm0lAMZuDjoHMLwFULMVt9Nss0qpRV+UsO9eORTlZacdT1RvIfbtUpyDf47hzGqTtTWF22mjJuHCjCqUUiglIiIiIiIi0oE5I1WEDTeGw7Xb9zJzCiEeo09Ook1CqQ2lAb7fEmBUQ1VSy+eBYcMx9LiMr6s5ku17Tsxo2+5g2B4olBIRERERERHpoCzLIivuJ+LIaZH71e3A18cTobQNBp0v+qIEw4BDBqWHUonaaqKr38dRfDhmdm7G19UcbqeNoOXCHlcopVBKREREREREpIMKhmJ0MYLE3Lktcj/DlwylerhrKasMYVlWi9y3KSzLYvEXJQzum08XjzPtXHTl2xCP4Rx2YsbW81OZpkHEcGOP12JZibZeTptSKCUiIiIiIiLSQVX6w+SaNZC9+/OkAExfcge/AnuQcDROoDbaIvdtiq83VlNWFarXumdFw0RW/gd73wMxc3tkbD27I2pzYwBEOne1lEIpERERERERkQ6q0h/EZ4aw+3Z/5z0Aw+7CyMqhC36AjM6VWryyBIfd5KDiwrTj0dXvQTiI84BxGVvL7orZkoPYO/sOfAqlRERERERERDqomq1lALhyC1rsnoa3gOxYFQCllZmp9InFEyz5soQD9isgy2VPHbcScSLL52HrXoyt234ZWUtLiNuTOwcqlBIRERERERGRDilcVQqAJ69wF1c2nekrwBEqBzJXKbVqfQX+mmi91r3YN0uwAltxHtD+Z0ltL+FQKAUKpUREREREREQ6rLi/AgBHC1ZKmb4CCG7F67ZlLJRatLKEbJed/fftmjpmWRaRz+Zg5u6FrfcBGVlHi3F5ALBCgTZeSNtSKCUiIiIiIiLSUdUkK5rMFhp0Dtt24EvE6dMlQVkG2vfCkTgfrynl4AGFOOw/xhjxDStJbP0e5wEnYhh7VrxhOLdVSkVq2nglbWvP+qmJiIiIiIiISJPZwlWEcWI4s1rsnqYvWXXV2xOmNAOVUp+sLSUciXPYkO5pxyOfzcHIzsW+36hWX0NLM92qlAKFUiIiIiIiIiIdlitaTa09p0XvaWwLpXq4atlaVUvCslr0/jtatLKEPJ+L4t65qWPx0nXEN3yBc//jMWyOVn1+a3C63EQsu2ZKtfUCRERERERERKTlWZaFJ+En6mzZUMr0JkOprrYgsbhFVSDSovffXnVNhBXflDNqSDdMw0gdj3w2BxxZOAYd1WrPbk1up41gwklClVIiIiIiIiIi0tEEaqN0MWtIZLXcPCkAw+7EyMqhC34Ayqpab67U0lVbSFhWWuteonoLsW+X4hx8dGo2057G7bRRazmJh1QpJSIiIiIiIiIdTFV1DT6jFtOb3+L3NnyFZEUrASirbL25UgtXbmbvQi97F3pTxyLL3wDDhmPoca323NbmdtkJWi5VSrX1AkRERERERESk5fm3lmIa4Mzp2uL3Nn0F2EMVAJS2UqVUSXkN32ys5rCh3VLHErXVRFe/j6P/4Zielq0AyyS300aN5cJSpZSIiIiIiIiIdDS1lWUAZOUVtvi9TV8BBLeS67FT1ko78C36ogQDGDnox1AquvJtiEdwHDC2VZ6ZKW6nnZqEEyI1bb2UNqVQSkRERERERKQDilYlQylv15YPpQxvASTi9OmSoKyy5SulLMti4crNDOyTR36OO3ksGia68m3sfQ7ElrtXiz8zk5KVUk6MqCqlRERERERERKSDSQST7XXOLgUtfm/Tl7xnr+xwq1RKfbOpmi0VtYwasl2V1Or3scIBnAeMa/HnZVpd+56ZiGHFWm/3wvZOoZSIiIiIiIhIB2TWVhLG0So71NWFUt2dNZRXh4knEi16/0UrSrDbTA4uLgLASsSJfD4PW7f+2Lr3b9FntQW3y06N5QLACnfeaimFUiIiIiIiIiIdkDNSRY3pa5V7G97k8PSu9iAJy6KiOtxi947FEyz5soTh/QvIdtuTx75ZiuUv6xBVUrCtUirhBBRKiYiIiIiIiEgH4477CTtyWuXeht2JkZ1LjlUNQGkLtvB9sa4cf02Uw7Zr3Yt8/gZmbg9sfQ5osee0pSynnRpLoZRCKREREREREZEOxrIsvFaAmKtLqz3D8BWQFa0CaNFh5wtXluBx29l/32Q1VqJyE4nSb3EMPArD6BgxhsNuEjK2DXAPB9p4NW2nY/w0RURERERERCQlEAyRY9RCdl6rPcP0FmCvLccwWq5SqjYc45OvSjlkUDfstmRkEV27CDCw9zu0RZ7RXsTtWcm/CalSSkREREREREQ6iKqyMkzDwu7r2mrPMH0FWIFyuvocbK1qmUqpT9aUEoklUq17lmUR/XoRtr0GYnpaL2BrC5bDk/wzolBKRERERERERDqImvItALi6FLTaMwxfAVhx+vgSLVYptXBlCQVd3OzXM9l2mChbj1VVgn2/US1y//bEcLpJYGCpUkpEREREREREOopQVRkA2fmFrfYM05cMvPb2hFpkplRVIMwX68oZNaQ7hmEAEF27EEwbjn1G7Pb92xu3y07YcGvQuYiIiIiIiIh0HHF/OQA5hUWt9oy6UKq7s5bKQIRoLL5b91u8aguWxY+te4kEsa8XY+81DMPl2e31tjdZTju1uBRKiYiIiIiIiEgHUlNOxLLjyPa12iMMb3JeVb6Z3D2ubDdb+Bau3Eyf7j56dE0GUPHNq7FqKjtk6x6A22mj1nIqlBIRERERERGRjsMeqiJgeFJtcK3BsDkwsnPJsaoB2LobodTGsiDrN/s5bEj31LHY2kVgd2HvM3x3l9ouuZ12ahKqlBIRERERERGRDsQZrabGltPqzzF8BbijVQC7Nex80RebMQwYOSjZbmjFY0S//Qh734Mw7K4WWWt743baCCQcCqVEREREREREpOPwJPxEnV1a/TmmrwBbbTk20/jJw84ty2LRyhIG982nizcZQMV/+BzCQRwdtHUPwO2y4Y8plBIRERERERGRDiIej+OlhkRWbqs/y/QWYAXKKeji/MmVUms3VFFWFUoNOAeIrl2M4fJi23tISy213XE77dRYLojUYCUSbb2cNpHxUCoQCHDSSSfxww8/ALBgwQJOPvlkTjrpJK6//noikQgAq1atYtKkSZxwwglMnz6dWCwGwMaNG5kyZQpjx47lsssuIxhMJorV1dVcfPHFnHjiiUyZMoXS0tJMv5qIiIiIiIhImwtWbMVmWJievFZ/luErACtOH1+MrVU/rVJq4coSnA6Tg4oLAbCiIWLrP8a+7yEYpr0ll9uuuJ02ahLbWhMjNW27mDaS0VDqs88+46yzzmLdunWpY9OnT+eee+7h9ddfJxQKMXv2bACuu+46brzxRt544w0sy+Kll14C4Oabb+bss89m3rx5DB06lAcffBCAe++9lxEjRjB37lwmT57M7bffnslXExEREREREWkX/KUlADhyurb6s0xfMkjqlR2mtLL5lVKxeIKlq0o4qH8hbmcygIqt/wRikQ67616dLKedoOUEwAoH2ng1bSOjodRLL73ETTfdRFFRUepYPB4nEAgQj8cJh8O4XC42bNhAKBRi+PDhAEyaNIl58+YRjUZZunQpJ5xwQtpxgPnz5zNhwgQATjrpJN577z2i0WgmX09EpN0oqSklYXXOEmARERGRzi5UWQZAVl7RLq7cfaavAIBuzhoCtVFCkVizPv/5N1sJhmKMSmvdW4ThycfWvX+LrrW9cTtt1FrJSikrrEqpVnf77bczYsSItGO///3vOffcc/nZz35GRUUFY8eOZcuWLRQWFqauKSwspKSkhIqKCrxeL3a7Pe04kPYZu92O1+ulvLw8Q28mItJ+VIQquW3xn3n3hw/beikiIiIi0gYi1clQytu1cBdX7j7Dmw8Y5JnJSp+yZlZLLVxZgi/bweC++QBYoQDx71dg7zcSw+jYY7DdTpsqpdry4aWlpcycOZPXX3+dBQsWcMABB3DHHXeQSCQwDCN1nWVZGIaR+nN7O369/WdMs2P/AouINGRV+RoSVoJPtnze1ksRERERkTaQCJQTsWzk5Oe3+rMMmwPDk4svUQ1AWTOGndeEYny6poxDB3XDbkv++3v024/AinfoXffquF321EypzroDX5umNh999BHFxcX07t0b0zQ5/fTTWbJkCd27d08bVF5WVkZRURH5+fn4/X7i8TiQDLXqWgGLioooK0umwbFYjGAwSG5ubsbfSUSkra2uWAPAN1XrCEQ65/+4iYiIiHRmZqiSasuD02HLzPO8BbijlQCUNmPY+bLVW4jFExw2pHvqWGztQszcHphde7f0Mtsdt9NGTapSqnP+c3ubhlLFxcUsX748FSa9/fbb7L///vTs2ROXy8WyZcsAmD17NqNHj8bhcDBixAjmzJkDwKxZsxg9ejQAY8aMYdasWQDMmTOHESNG4HA4Mv9SIiJtyLIsvqr4mu6eblhYrNz6ZVsvSUREREQyzBGuosb0Zux5hq8AM1iO02E2q31v0RclFOVlsU8PH5Cs8Ipv+gr7fqMa7YrqSNxOOzWWKqXaTL9+/Zg6dSrnnXceEyZMYMWKFVx//fUAzJw5kzvuuIOxY8dSU1PDeeedB8BNN93ESy+9xLhx4/joo4/49a9/DcDUqVP59NNPGT9+PM899xw33nhjW72WiEib2RQsoTri5+e9jqSLM4flZSvbekkiIiIikmFZMT8hR5eMPc/0FWAFyynMcVHWxEqp8uoQX66v4LAh3VMBVOybxYCFo1/Hb92DZKVUApO46cQKdc5Qyt4WD/3vf/+b+vuJEycyceLEetcMHDiQl19+ud7xnj178vTTT9c7npuby8MPP9yyCxUR2cOsrlgLwMC8/nxXuIElmz8mGo/isKlyVERERKQzsKwEHitA3JW5UMrwFYCVoE9OlO+bOFNq8aoSLKi3655ZuA9ml26Nf7ADcTmT7ZURMwuXKqVERGRPt7piLQXufLpm5TOsYAiReCQVVImIiIhIxxevqcZmWJCdl7Fnmr7kLn97Z4Upq6rFsqxdfmbhihL67ZVDt7xsABKVm0iUre80VVIApmHgctqImC6174mIyJ4tnoizpuIbBuTvB0BxXj9cNiefl33RxisTERERkUyp2boFAJuv9Xfeq2P6CgAoctZQG44TDMV2ev0PWwL8UBpg1HYDzqNrFwEG9n6HtuZS2x2300bYcINCKRER2ZN9599AKB5iQF4ylHKYdgblD+DzslUkrEQbr05EREREMiG4LZRy5nTN2DMNTz5gkG/6AXY5V2rhF5sxDYNDBhUByc16ol8vxrbXQExP5iq82gO3004tqpQSEZE9XF2bXvG2UApgWMFgqiLVfO/f0FbLEhEREZEMClcld7fP7lqUsWcaNjuGJw9vohpgpzvwJSyLxV+UMHTffHKyncljZeuxqjZj36/ztO7VcTtt1FoKpUREZA+3umItPb098Dl/3P53SMFATMNkuVr4RERERDqFmL+cmGXSJT9z7XuQbOFzRSoBKNvJsPM131dSXh3msLTWvYVg2nDsM6K1l9nuZDltBBNOrHCwSbO4OhqFUiIiHUAkHuWbqnWp1r06XoeHfl36srx0ZRutTEREREQyqqaCykQ2XbzujD7W8BVgBLeS7bJTupP2vYUrN+Ny2hjePzmHykokiH29GHuvYRguT6aW2264nXaCCSckYhCLtPVyMk6hlIhIB/Bt1XpiiVi9UApg/4LBbAxupqy2vA1WJiIiIiKZZAtV4seLw57Zf903fQVYwXKKchyNtu9FY3GWflnKwcWFuBw2AOKbV2PVVHbK1j0At8uGP+YAwAoH2ng1madQSkSkA1hdsRbTMNkvd59654YVDAHQLnwiIiIinYAzWk2t3Zfx55reArAseufEGx10/tnardSGY2mte7G1i8Huwt5neIZW2r64nXaqonWhVE0brybzFEqJiHQAqyvW0jenF257/TLtwuyudPd001wpERERkQ7OshJkJ/xEHDkZf7bhS7bj9cyqZWtVqMH5SIu+KKGLx8mgPskd9qx4jOi3S7H3PQjD7sroetsLt9O2XSilSikREdnD1MZqWV/9fYOte3WGFQxmbeU31EQ73399EREREeksrFAAOwkSWXkZf7a5LZQqctQQiSWoDqbPRwrURln+dRkjB3fDNA0A4j98DuEgjv1GZny97YXbacMfrwulOt8OfAqlRET2cGsqvsHCongXoVTCSrBy6+oMrkxEREREMike2AqA4cl8KGV48sEwyDWS1T6lO+zA99HqLcTi1g677i3GcHmx7T00o2ttT9xOOzWWE1AoJSIie6DVFWtxmA726dKn0Wv65PTC5/RqrpRIJ1JWu5UFGxa19TJERCSDastLAXDmFGT82YbNjpGdhzdeBVBvrtSiFZvp0TWb3t28AFjRMLH1H2Pf9xAM057x9bYXWU4bNYltrYsKpUREZE+zumIt/br0xbGT/zE3DZP9uw5m5dbVxBKxDK5OOptwNN7gDAnJvBdXz+L51a+yvvr7tl6KiIhkSG1FMpRy52U+lAIwcwpxRSoA0nbgK6uq5asfqjhsSHcMI9m6F1v/CcQinXbXvTpul50wdizDVKWUiIjsWarCfjYFSxiQ33jrXp1hhYMJxUOsqfwmAyuTzmhzeQ3XPfghD85aQULBVJtaX/09X5Qn23UXbFjcxqsREZFMiVRtJW4Z+PLy2+T5hrcAAlvJyXakVUot/qIEgFGDu6WORdcuxPDkY+veP+PrbE/cThtgkHBkY4UUSomIyB7kq4q1ADsdcl5nQN5+OEyHWvikVQRDUf7vH58RicZZtrqUV979uq2X1KnNXfc22fYsDioaxkcln1Aba3hrbhER6VgSgXIqE9l08dXfkTkTTF8BVk0FhTlOSrdVSlmWxYcrNtN/7y4U5GYlj4UCxL9fgb3foRhG544lkqEUJOxZWBGFUiIisgdZXbGWLHsWvXw9d3mt0+ZkUH4xy0u/UHuVtKhYPMGDr61ga3WIa88YztEH9mTuou94f/nGtl5ap/S9fyOfl33B0b2O5NjeY4gkoizZ/ElbL0tERDLAqK2kMuGhi8fVJs83fQVgWfTxRdm6bdD5dyUBNm2tSR9w/u1HYMVx7HdYm6yzPXE7kyM4YvZste+JiMiew7IsVlespTivH2YT/wvT/gWDqQhX8kNgUyuvTjoLy7J47q2vWLW+gvPHDqS4Vy5nHdufIX3zeGrear5cX9HWS+x05q17G7fNzVF7H0mfnF709vVkwYZFCqNFRDoBR6SKgOHFYW+bf9U3fMlZVntlhdhaHSKRsFj0xWZspsGIgUWp62JrF2J26Y7ZtXebrLM9qauUiphute+JiMieo6y2nPJQRZNa9+rsXzAIA4PlZStbcWXSmfxn2Q/M/3QjJ47qzRH79wDAbjO57JShFOVl8ZfXPqekvKaNV9l5bAxs5tPSzzmq1xFkO5ItEkf2HMXG4Ga+qVrfxqsTEZHWZFkW7lg1YYevzdZgepOhVKEjSDxhsbU6xKIvShjWryveLAeQbDGMb/oK+36HpYaed2ZZrmSlVMR0Y4UDbbyazFMoJSLSxhKWxX0vL2fhys3N+tzqijVA0+ZJ1fE5vezTpbfmSkmL+Pybrbzw9hoO7F/AqWP6pZ3LdjuYOvkADMPg3peXEwxF22iVncsb6/+Ly+bk6F5Hpo4dXDQct83N+xsWteHKRESktVnhAHbixFy5bbYGw5sPhkkuyXDl/eWbqApE0lr3Yt8sBiwc+41so1W2L3WVUmHDjRXufP8hT6GUiEgb+2ZDNZ+uLeOpeaspq2z6MOLVFWvp4syhW3Zhs563f8FgvvdvoCJU2cyVivxoQ1mQh2evYO9CL7+aMBizgf/SWZSbxZWT9mdrVS0PvraCWDzRBivtPEqCW1hW8hmjex6O1+FJHXfbXRza/SA+KV1OINr52gJERDoLK1Ce/JvsvDZbg2HaMDx5eONVALy97AeyXDYO2K9r6pro2kWYhftgdune2G06FbvNxG4zqMUF0VqsRKytl5RRCqVERNrYR6u3YLcZGAb8fd6XTZr7krASfFXxNQPy92t22fOwgiEAqpaSn8xfE+H//vEZDruNqacNSw3obEhxr1zOHzuQVesreObN1Zpr1IreWP8OdtPOMb1H1zt3ZM+RxBIxFm9a1gYrExGRTIhvC6VMb36brsP0FeAIV2AAteEYIwYU4bBv22GuchOJsvU4+o1q0zW2N26nndpEcjh9Z6uWUiglItKGLMvio9VbGNI3n9OP3o8v1lXw3me73rFsY2AzgWiwWa17dbplF1KUVcByhVLyE0RjCf7y6udUBiJcder+5OfsesvpI/bvwfjD+vDeZ5t4c+n3GVhl51Nas5WlJZ/ws56j8Dm99c739PZg3y59NfBcRKQDq60oA8DVpaBN12H4CiCwlVxfMmRJ23Vv7SLAwN7v0DZaXfvkdtoIWs7kF51sBz6FUiIibejbTX7Kq8OMGFjEmOF7MahPHi/+d21qC93GrK5YCzRvnlQdwzDYv3AwX1V8TW1s588R2Z5lWTz9xmq++qGKi8YPot9eXZr82Ymj92XEgEJe+u9aPl1T1oqr7JzeXP9fTMPk2N5jGr3mZz1HsaW2jK8qvs7gykREJFPCVWXELQNPXtddX9yKTG8BVrCC7l2c5PlcFPfOBZL/HBH9ejG2vQZietquxbA9cjttBOLJQfCWQikREcmUj1ZvwWYaDO9fgGEYXHDiQCwLntxFG9/qirUUZReQ5879Sc8dVjCEuBVnVflXP3Hl0hnNW/IdCz7fxMlH9GXk4G7N+qxpGFx00mD6dPfx13+u5LsSfyutsvPZWlvBos3LOGKvQ+niymn0ugML98djz+b9jRp4LiLSEcX8W6lOZJHr23UVc2syfQWAxZQjCrj61GGpuZOJsvVYVZux99OA8x25XXb88WSllEIpERHJCMuy+OjLLQzqm4fHnfwvI4W5WZx2VD9WfFvOgs83Nfi5eCLO2spvGJDX/yc/e98uffA4slleuvIn30M6l0/WlPLyO19zyMAiTj5yn590D5fDxtWnDSPbbef/Xl5OZSDcwqvsnN76bj4GBsf1Pmqn1zlsDkb1GMFnpSuoCisUFBHpcILlVCY85HpdbboMw5dsHyxy1tKnuy91PLp2IZg2HPuMaKultVtup43qqCqlRDq1eCLBP95Zy5frK9p6KdJJfFcSoKwqxIgBRWnHjz6oJwN65fLC22up8Nf/l/Z11d8Tjkd+UuteHdMwGdp1ECu2fkk8Ef/J95HO4bsSP4/88wv69vBx0fhBDe6011S5XhdTTxtGTSjG/a8sJxzV79/uqAxXsXDjEkb1GNGkyskjeo4kYSVYuGlp6y9OREQyyhaqoiKRTRevs03XYfqSO0Mn/KWpY1YiQezrxdh7DcNw15992Nm5nXaqosmNYxRKiXRin3+zlT89/wn/mL9WW5dLq/to9RZMw+DA/unDKE3D4JfjBhKPJxps41tdsQYDg+K8frv1/GEFg6mN1fJ11be7dR/p2KoCYe57ZTnZbjtXnToMp8O22/fs3c3HxScPZt0mP4+9/gWJRlpVv/P/wLOr/sEHGxeTsPT/kxvy1vr5JLA4oc/RTbq+W3YhA/L20/dURKSDsSwLZ7SaGtOH3da2/5pvePLAMLH8P86QjG9ejVVTqda9RridNiojyX/GUigl0knZTJPp545g9PC9mLvoO25/ahmbtnau/4cgmWNZFku/3MLAPrn4suv/16yivGxOHdOP5V9vZeHKzWnnVlesZW/fXngc2bu1hoH5xdhNu3bhk0ZFY3Huf/VzArVRrj51WIu2AxzYv5DJR+/HR6tLmfX+/2fvrMPbOs8+fB+xZGZmxtixw8zccBlW2jpo13VtB+3Wr9u6dVvbde0K68qYhpmZwXEcx7HjmJnZFkvn+0OJ2zRkOw7rvi5dlqUDz5GOpPf83uf5PcXnPNegbeLjnK/4+5G3OFSbydenlvHqkX/f8gbd1Y1dfLEpn5ziJqzWy3fIazN0sK/6EIN9B+Kh7nn775EBQ2nWt5DblH8l4dqxY8eOnRsJoxaZaMKo6HkTkquFIJEiOLpj/Z4oZS48BDIlspDU6xjZjYtKIUVrFEGuvu1EKdn1DsCOnRsJpULKQ1NjSQr34NMNp3j50yPcMyGK0QP8Ea6gXMWOnR9S2dBFfYuOqYODL7rMhPRAjuTX8/WWAuJD3XF1VGKwGClpK2dc0MgrjkElUxLjFkl2Qy7zI2fZz3E75yCKIh+vP0VxdTs/n5t4jifEpbDUFSKonJC4XN4IfcrgIGqbu1i7vwxfdw2J0Y5sKNnG3uqDyAQpU0PGMyF4DHnN+awoXM+/j/2XAV6JzI2YgZfm+nYW6m8a23S8/m0WLR0Gdhyrwt1ZycgkP0Ym+eHpqr7gOtsqdmG2WpgSMr5X+xrgmYCzwom91QdJ9Izrj/Dt2LFjx851xtrVbPurvv6iFJzpwHdGlBItZkwlR5CFpiLIr6/f1Y2KSiHDYLQgKB0Q9Z3XO5xril2UsmPnAgyM9iLMz5mP1+Xy2cZ8soua+NG02AtmtPQXoihitJrQmw0YLLbbOfctBmSCjEG+qUgEe5LjzU7GqXoEAVKjvS66jEQQeGR6HC99fJgvNuXzi3lJFLWWYBEtV+Qn9X2SPeM52XSKmq46/B19+2Wbdm4N1u4v5VBuHfPHhJP2A9+zi2Ftq0O7+m+AiDxmFIqBs5E4XjyDRxAE7p8cQ21rO59nrUHVUIYFC8P9BzM9dGJ3J7k0nxSSPBPYXrGbTWU7ONmYx9igkUwNHY9admHB5maiQ2vkjW+Pozda+MND6TS06tiTXcOafaWs2VdKXKgbo5L9GRjtiVxmS+3vMHayp/IA6T4peGs8L7OHc5FKpAzzG8Tmsh0061twV9nbctuxY8fOzY7YaROlBE3PM2evJoKTJ5YqW0MdS2UOGLqQRw69zlHduKgVUkRAVGgQjdrrHc41xS5K2bFzEdyclPzqrhS2Hqlg6a4i/vjxYR6bEU9CWM++6C1WC4dqj9Kib8VgMaK3XEhsMp5zX+Ty5RoiIkP97B0rbnYy8uuJCXLFxeHSQqevu4a5o8JZvKOQQ3l11CgKkQpSIlz71v3shyR6xkE+ZDfm2kUpO90cOVXPij0lDEvwZfrQkB6vZ8hYDlIp8qgRmPJ3YyrYhzxhIoqUGUhU52damaxm9lYfpDlgK1KzFnOLHz8fvoA436DzllVI5UwNncBQv3TWFG1ia/kuDtZkMCt8CsP9B9+0Yr3eaObNJcdpatfz67tSCPNzJszPmcFxPjS26dh3opa92TX8d/VJHFQyhiX4MmqAP5kdezBZzUwN7V2W1FlG+A9mc9kO9lcfZmb4lH4+Kjt27Nixc62xnBGl5C43higlcfLE3NWKaDFhKjwISgekAYnXO6wbFpXyjMm5XGMv37Njx853SASByYODiQ1x47+rT/L6t1lMHhTE/DERyGWXvgDaVr6bVcUbAFBIFSilClRSJSqpEoVUiZPCCS+pEqVUgVJme1x55qaSnXm8+77t+f/lfMGa4k2keiejlF7frhp2+k5VYxc1TVrGDwzs0fKTBwVxNL+erzafxndoAWEuwf32/rsqXQhxCiK78WSfL27t3FqU1LTz0dpcIgNc+NG02B6XdVoayzAXHUKROgvloPkoBkzHkLkS04lNmPJ2okiehiJpMoJCjVW0crTuOGuKN9GkbybaNYJR3uP5ZGkNXzZV8cIDvmhU8gvux1XpwgPxdzImcDhLC1bzTf5ydlcdYH7kLGLc+yeD8Fphtlh5Z0UOZbWd/HxeItFBruc87+miZvbIMGaNCCWvtIU92dXszKpia1YxmtQ9BCgjcZb2rYzRQ+1OvEcM+6sPMy10IlLJlRvY27Fjx46d64ehtRFRFFC73hjl7bYOfCLW1hrMZZnIo4YjSO3yw8VQKWy/wxa5BmlH9XWO5tpiPyvs2OkBwT5O/PFHg1iyo5DNRyrILW3hJ3fEE+B14XamrYY2NpRtI9kzgceTHui3Gfz5kbN4I/NdtpXvYnrYpH7Zpp1rz9FT9QjYykR7gkQi8PD0OP7v831Ud1Uzw6d/3/tkr3jWFG+izdDeXS51O1Pd2MXJ0mYmpgXedj5bLR0G3l6WjZNGwS/mJV1WfP8+hiNLQemAYsA0ACTOXqjHPo5lwHSMR5ZjPLoC48mtFMcPY72ljsquGgId/fn5gEeJc49GEAQ0cz15/dss3luZw9N3DkAqufj+g50D+dXAn3Ks4QQrC9fxVtYHJHsmMDdyOt6ann22ridWUeSjdXmcLGnm4emxpEZdupQ3IcydhDB3OnUmPj66knyjmcJMb545tJe0GG9GD/AjOsi1V+fsqIChvJ/9KScac0nxTuqPw7ql2J5ZiaeLiuSI3pVH2rFjx871wNjWhE5U4+J4ZY1w+gvByfbdaTyxBcxGZJHDrnNENzZnRSmTRIX8Nivfuzlz3e3YuQ4o5VLunxzDUwuSaesy8KfPMth2tBLxAq3MVxauxypamR81s19LSiJcQ0nxSmJL+S7aDO39tl0715aM/HoiA11wc+q50aO/pwODB0tBAGt7/86AJXnGA5DTmNev271Z+XJzPt9sLTiv6+GtjsFk4a2l2eiMFn65IBnny5SWfh9zdR6WihMoU2YiKM4dDEvdAlBPfpKGyU/wPz9nPmjPQttWzf2uKTyf9nPiPWK6hZTYEDcenBLDydIWvt5ScMHv1+8jCAIDvZP5w5BnmR0+jfyWAv5y6A2WF6xFa9L1/kW4RoiiyDdbCziUW8eCsRGMSvbv8bpSuZly6wkGeCbw4p3jGJ7oS1ZhA3//+hi/++Ag6w6U0tJh6NG2EjxicVO6sqfqYF8P5ZalsKqNLzef5s0l2azZV3LZc9GOHTt2rjeWzmZarRpcnW6MagrJGVHKXLAfwcEdqW/UdY7oxkalsOULmaRqRH3XbfW7Yxel7NjpJSmRnvzp0SHEBrvx1ZbT/HtpNm1dxu7ni1pLOVJ3jInBY/BU9594IJoNWOoKmRMxHYvVwtriTf22bTvXjpqmLiobukjvoXH093HwbEOwStm0q4N2rfHyK/QQfwdfPFTuZDee7Ldt3qxU1HdyqrwVhVzCN1sLaO/qv9f5RsYqiny4Npfyug5+ckcCgd4XzgK9EKIoYji8FMHBHXnChPOer9M28OGJL3i9eDl1KgXzvYfwbJcjiRmb0S39A6aiw4iitXv5UQP8mTYkmB3Hqth6tLJHMcilciaHjuOlob9hiO9Atlfs4eWD/2BP1QEsVkuPj+VasfZAGduOVjJ5UBDThly8A+eF2FW5H51Zz9SwCYT5OfPg1Fje+MVIHp0Rh6ujkmW7innu3f28tTSbY6cbMFusF92WRJAwwn8wp1oKqNc2XnS52w1RFFm6oxBnBwVDE3xYsaeE/64+idF0451LduzYsXMWQddiE6UcbozudoLGFQQpiBZkEYMRblLvx2vF2Uwpo0QFogVM+usc0bXDfmbYsdMHXBwUPL0wmfsmRZNb2sJLHx0iu6gRq2hlyemVuCpdmBwyrl/2JYoipsKDdH37O7Sr/oJbUzVjAodzoCaDytus3vhW4Gh+AwBpMb0vLzrdWkiYcxh6vZWvt5zut5gEQSDZM55TLYUYLLeHCHMxtmRUoJBLePauVAwmC19v7b/X+UZm5Z4SjuY3cOf4SFIie1eqZC7LxFpfhCJtNoLsu9nZNkM735xaxl8Ovc7J5nymh07k5WG/YXzifJzn/BHV5KcQJFL0295Fu/xlzBXZ3bOC88dGkBrlyaJtBWQX9VwscVE6cV/cQn4z6Cn8HHxYlL+CV4/8m7zmG+d93JVVxYrdxQxL8OHO8ZG9KrfTm/VsL99DokcswU7fedIp5VJGJPnx2/sG8rcfD2XqkGBKatp5e/kJfvffg5TVdlx0m8P8ByERJOyvPnxFx3UrcbywidOVbcweGcbjM+NZODaCI3n1vPpVZo+z0OzYsXNrIJqNmE7vw1JXiGgxXe9wLoooisiNbbRaHXBxvDEypQSJFOFMB157173Lc1aUMggqgNvK7NwuStmx00cEQWBCWiB//FE6zg4K3lySzb+2rqGis5p5kTP6xYja0lCCbvVf0W9/H0HlhKBxxZi1lmmhE9DI1KwoXHdbpXbeCmTk1xMR4Iy7s6pX67XoW6nXNjLAN4Y7RoRyOK+eo/n1/RZXkmc8Zqv5mly8i0YdxtztiFbzVd9Xb2jXGjl4so7hiX5EBrowc7jtdc4qvLUzSA6erGXt/lJGJfsxedD5Xe8uhWi1Yjy8DImLL/LokQDozDrWFG3k/w78nf01RxgVMJSXh/2GGeGTUcls570gCMhDB6KZ/2dUYx9HNHah2/AGurWvYq4tQCII/HhWAkHejry36iRbMiooq+3AYr141s/3CXIK4JepP+HxxAcwWIz8J+tD3s/+hDptQ+9enH7maH49n2/KJyncg4enxyHppWfZnqqDdJm1TA2deNFlfNw1LBgbwWs/H86T85MAkb99dbRbEP8hrkoXkj3jOVBzBNMN9pm8HlitIkt3FeHjpmZUsh+CIDBtaAi/mJ9ETbOWP312hJIae/m8HTu3C4aDi9Dv/B/aVX+h85Mn6FrxJ/T7vsRUsB9rW92NMw436ZBZjeikTsikN84lvsTVD4mrPxKPnnfyvV1Rn+m+pxNtmW63kyhlNzq3Y+cKCfRy5A8PpbNoVy4HzNuQGz3xFMOvaJtWbSuGw8swn96LoHZCOfph5NGjMJ3cguHAN2iaqpgWNpGlBas52XSKRM+4fjoaO1eT+hYt5XWd3DW+9x3C8lsKAYhxi8IvwJejpxv4YlM+McFuOKov3KWsN0S6hqGWqTnRkEuK19Vt12s4sgzTya0IMiXy6BFXdV+9YVdWNWaLlYlptgyU6UNDOHKq3vY6B7l2DxZuJSrqO/lkwyliglx5YEpMr7J2rKKV+rwtlBkbaYwfSV3uIqq7aqnTNmAVraT7pDAzbApemouXMQsSCfLoEcgihmA6tQtj5mp0q19BGjwA5aD5PDU/mTcWH+ebrQUAKBVSwv2ciQp0ITLQhQh/l4u+L4IgkOKdRIJnHDsr9rKxdBt/OfQ6YwKHMyl4HC5Kp969WFdIfnkL/12dS7ifMz+bk9jriwajxci28t3EuUcT5nL5kj+pREJqlBfhfs68vfwE76w4wYKxEUwbEnze+zwyYChZDTkcrz9Bum9qr+K61dh3oobqxi5+NicRS/Z6RGcv5BFDSI3y4oX703hrWTavfpXJI9PjGBLvc73DtWPHzlXEXHECU+525PHjkQYkYK0vwlJfhCl/D6aTWwEQlI5IvMORekcg9Q5H6h2OoHS45rFaO1sAMClcrvm+L4VqzCNgtd52jWP6wtlMKR22xAa7KGXHjp1eIZdJUQYVIak0Q1kCr+QeZcGYCCYOCurVTLhoMWE8sQXjsdVgMSFPnoJy4B3dxsHy2LEYM9dgyFrLqMlPsqtyHysK1xHnHm1v530TcCWle/kthTjKHQhw9EUiSHhkehx//iyDr7ee5sezEq44NqlESoJHDDlNeVhFa78a9H8fS0sVptztABjzdtwwopTZYmV7ZiUJYe74e9oGkzKphIenxfHKFxks3VnEA1NirnOU/YvOYObdFSfQqGQ8cRmRpMPYSVVnDTVddVR31lDdVUdNV62t3NPfFVpz8FC54efgS5JnPAO9kwlyCuhxLIJUhiJhAvLokRhPbsGYtR7tsj+ijhjKnxbOpQUXCqpaKaxso7CyjTX7SxFFEATbxEBkoAuRAS5EBbjg4aI6Z/Arl8iYFDKWIX5prC3ezM6KfeyuPECqdxJjAkcQ5ny+SNPflNd18NaybLxcVfxy4QCUit5/X++tPkSHqZOpoef7dl0KF0clz9+Tysfr81i6s4iapi4emhp7zvsd4xaJp9qDPdUHb2tRymiysHJvCWF+zqS4daDbvRQAa3sDipQZBHo78uJD6by7/AT/XX2SqsYu5owK63XGmx07dm58REMX+l0fIXHzRzn0blt5elia7TmrBWtLNZb6ojNCVTHGihOALWtKcPH9nkgVgcQjEEFydS+7xa5m2x0Ht6u6n94i0bhe7xBuGpRyKQLQabFnStmxY6cPVHXWsLvyAKMChjJt6CQ+XX+KRdsLOV7UxPBEX0J8nPDz1Fy0vbkoipjLjmE4uAixvR5pcAqqYXcjcfE9ZzlBrkSeNAljxgqElhrmRM7gfyc+Z3/NYUYF2Nus3uhk5NcT5ueEp4u6V+uJokh+cyFRbhHdYlGwjxMzhoWwel8pg2K9L9lOvqckeyaQUZdFcVsZka5hV7y9HyKKIoYD34BchSJ+PMastViaK5C6965k7GqQcaqetk4jD087N5Zwf2cmpQex+UgFQ+J9iA5yvT4B9jOiKPLZxlPUt+p4/p5UXM502tObDTbhqauG6s5aqs+IUJ2m7wZGjnIH/B18Gazwxqssl5D0uwkIHYpa1ruS1AshyJUoU2aiiBuH8fgGjDmbMRcfRh2YyMDQgQwemYJEE4POYKa4up2CylYKq9rYn1PLjswqAFwdFUQGuhIVYMumCvZxRCqR4Kxw4t7Y+UwMHs3uygMcqMkgoy6LYKcAxgSOIM17AHLplWcd/pD6Fi1vLD6OWinj13el9Cmz0WQxsbVsJ9GuEb36bIqiFURQyKX85I4E/DwcWLW3hIZWPT+fm4iTxva+SwQJI/2HsLJoPTVddfg53J4ZQNuOVtLSYeDHs+IxZX0OSgdkAQkYjyxF1LagHHYfzhoFz96Tyheb8lm7v5Saxi4emxnfJ6HRjh07Ny76fV8g6jpQT3n6HL9EsHklST2CkHoEQdxYwGZNYGkoOSNUFWOpPIG5YJ9tBakciWfIGaEqAqlvFJJ+Fo+sZ0Qp6RkPJzs3H4IgoFRI6bTaxgl2UcqOHTs9RhRFlpxehUamZkb4ZBzlCp6cn8SurGqW7Cwkr8yWTiuXSQj0ciTEx5FgXydCfJwI9HJA0l6D4cA3WKpOInHzRzX9WWSBFy+fUiRMtF2sZa1jwPifEOkaxtrizaT7pPbLRaGdq0Njm46Smg4Wjo3o9bp12gbajO3EuJ1b9jdzeCiZpxv5fFM+0UGuOKiu7II63iMGqSDlRGPuVRGlLOXHsVTmoBx2D/KoERhPbMSUuxPpyAf6fV+9ZUtGJT7uGhLDzx/MzR0VTubpBj7ZcIo/PTIIuezmv/jccayKw3n1zB0dQo0klx3Zp6nurKNJ39y9jEIi78588nfwwd/RDz8HX5wVjmDS07XoeSQeEWgix/Z7fILSAeXgBcgTJ2LM3oS5JAPDnk8x7AGJdziykIHEhqYSHxqGIAhYrFYq67sorGrrFqoyTtk81xRyCeF+zjahKtCFCH83FkTfwczwKRyuzWRX5T6+yFvMisJ1jPAfwqiAobipXPvlONo6Dbzx7XEsFivP35PWay+5s+yvOUKbsYMfJdyDaDUj6joQde3fu7VhPef/s7cOBJUj6hnPInUPYvbIMHzc1Xy87hR/+TyDXy4Y0J0ZONQvnbXFm9hbdZCF0bP75fhvJjp1JtYdKCM5woNIh060ZcdQpM1BMfAODI7umLI3ImrbUI37MTKZgh9NiyXQy5FF2wv465dHeWp+Mh4u9t/gq4XZaqbD2Nlvn007di6Fqegw5sKDKNLnIvUK7dE6gkKNLCAeWUA8YLs+EDsbsdQXn7kVYcrdhunEJhCkqMY+ijxqeL/FbO1oxiqC0sUuSt3MqBRSOsx2UcqOHTu95FjDCQpai7krei6OctvgXhAExqYGMHqAP7XNWsrrOiir66CstoNDefXszKpGI+iZoTnOcOVpzIKC6sAZqBLHE+TtcskPpqB0QB43DtOJjYiD5jEvcib/yHibzWU7mB0x7doctJ1ec0Vd97r9pM4VpWRSCY/OsJXxLdpawKMz468oRrVMRbRbBNmNJ5kbOeOKtvVDRIsZ/cFvkLj6IU+YgCCRIQsbhKlgP8ohdyLIr1/74qKqNkpq2rlvUvQFy3CUCikPTYvl9UVZrN5XyvwxvRcWbyRKatpZtK2AqBgzx6UrqTldh4/GixDnQIb5DcLf0Qd/Bz881G4XLeM0ZG9E1HegHLzgqsYq0biiGnoX4pA7sbZUYi49hrnsGMYjSzEeWYrg7IMsNBVZSCrBPlGE+Dox4YwnWHO7/oxIZSv5W3fgu5K/5HAPxg0MYGTYUEYFDCW/pZBdlfvZXLaDLeU7SfZMYGzgcCJdw/tc2qfVm/nX4uO0dhl47p7UbvHnUogWM5aqXKzaFkRtG6K+A5O2lc1UEGoBv9Vv0mnovPDKUjmC2tl2c3BD6hmKoHbGVLAP3brX0Mx+AYmzN0PjffFyUfP2smxe+eIoP5uTSEKYO04KR1K8kzhUe5TZEdNQ9EOzjpuJ9QfK0BnMLBgTgfHY57aMzoSJCIIE1dC7kWhcMBz8Fp2+A/XkpxCUDkwaFISfh4b3Vp3kz58d4RfzkokMvLH8XG52rKKVjLos1hZvotXQzgtDnsFHc+WZwXbsXAxrVwv6vZ8h8QpHkTKzz9sRBAHByQuJk82XDmzf8dbmCpt5+o4PEA1dKBIn9UvcxvZGOkQ1Lk6aftmeneuDSiGjyyQBiQzsopQdO3Z6gtFiZHnBWgIc/RgZMOS85yUSAX9PB/w9HRiaYCvFs1pMtGZuQXJiDRKznlxFMqvaE6nLlkL2cQRs3ZNCzmRTBfs4EuzjdE7JhyJ5CqYzvisho3/EIJ+BbK/Yw0j/oXiob6xacjs2MvLrCfZxxNut94OF/JZC3JSueKnPN4wO8XVi+rBg1u4vY1CcN8kRnlcUZ5JnPItPr6Suqx4fB+8r2tb3MZ3cgthWh2rqM92+CvL48ZgLD2AqOogidky/7au3bMmoQK2UMSLJ96LLJIS6MyLJl42HyhkU602wz7U1ye4vuvQm3l2TgSoyh0qXStwtbvwk6SGSvXruS2bVtWM8sQlZ+CCkXv2fUXchBEFA6h6E1D0I5cA7sHY2Yy7PwlyaiSlnC6bsjQgqJ6TBKTaRKjABd2cVg51VDI6zlaLpjbaSv5OlzezLruH4kiY8XVSMSfFnVHIIP0mOoknXzO6qA+yvPkxWwwn8HXwZGziCdN/UXnVUNZkt/Gd5NlWNXfxyQTIR/pcXKkRDF7rNb2Gpyf/uQbmaw+5OtDrBQtETeYTvd8KT2hlB7YLkzH3kqgsKaLKoYWhX/xXtun/ahCmNKxEBLrz4UDpvLc3mX4uPc9+kKMYNDGRUwDAy6rI4WnecYf6Deny8NztNbXq2Hq1keJIv/opOuoqPoBgwDUHl2L2MInkagsYV/c4P0a75G+ppv0bi4EZiuAcvPpjGv5dm849vMnloaiwjkvyu49HcGoiiSG5zPquKNlDVWUOgoz/txk42lW7nwfi7rnd4dm5RRFFEv/sTMJtQj3scoZ/9WgWpDKlXGOppv0a//X0M+79C1LWjSJ93xd6GpvZmWq0aXB2v3ySfnStHrZSiN1kQlA6IF5uEugWxi1J27FwBm8t20mJo5aH4u3tkDG2uzMFw4GvkLdVIA+JRDruHoe5BDBFFWjuNlNV1UF5ry6oqrGzlUG5d97qeLipigly5b3I0Ko2rrRtf/h4UabOZHTGVrIZsVhdv4OGEe6/mIdvpA83teoqq2pk3uvddGa2ildMtRSR7JVx0wDJreBjHTjfy2cZ8/vyoKxpV37/akzzjWHx6JdmNuUzqJ1HKqmvHcHQ10qBkZMHJ3Y9LfSKRuAViytt53USplg4DR/MbmJAWiEpx6dftrvFRnChu5pMNp3jxwbSLesTdqFisFl7fupKu0GNIZVamhIxnauj4XmfEGI+tAbMRZfq8qxTp5ZE4uqOIH48ifjyiUYe54gTmskzMpRmYT+8BqQJZYAKykFSkISlI1M6oFDLiQ92JD3XvLsnckVnFsl3FrNxTQnqsN+NSA5gTMZ0ZYZPIqMtiZ+U+vs5fxoqi9Qz3G8TowGF4XkAc/j5Wq8gHq3M5Vd7K47PiSQy/9PIA1vZ6dBvewNrRiHL0w8gCExFUTlglUnYd/AchCkcGpP2iTxctUrcANNN+jXbt320ZU3f8DkHpgKeLmt/dn8Z/V5/ki82nqW7Sctf4CHwdfNhTffC2EqVW7ikGYM7IcAzHvgKpDHnSlPOWk0cOQ1A5o9vyNtpVf0E97ddI3fzx83DgxQfTeW9lDh+ty6OqsYsFYyKQSK6OAbrRZOF0ZSslNR0MiPC4aUXyi1HSVsaqog0UtBbjqXLn4fh7GOgzgJWF69lesYepoePxtmdL2bkKmE7twlKRjXL4/Uhcr564LMgUqCb+HMOezzAeW2PLPB7xIMKVjCu0zbRaHfBzvL2yXG81VAoZeuNZUUp7vcO5ZthFKTt2+kijrpkt5TtJ8x5AlNulxQZrWx2Gg4swlx1DcPJCNfkpZCGp3RcYgiDg5qTEzUlJSuR3mS6dOlO3UFVS28G+nFq8XNXcMTIMxYBpmE7txHhiE25D72ZC0Gg2lm1nXNBIQp0v3y7czrXj6Glb6V56bO9FnsqOarRm3Xmle99HLpPwyIw4/vJ5Bt9uL+Dh6XF9jtVd5UaQo79NlAoZ2+ftfB/jkWU2EWPY3ec8LggC8rixGPZ/iaWh5Jpl3Xyf7ZmVWEWxu+TrUjiq5dw3KZr3Vuaw+UgF04aEXIMI+4fS9nI+yPyWNk0DXtJAfpp+N759EB2tHQ229tgxo67qgL03CAo18ojByCMGI1rNWKrzzwhUtlI/EJD6RJ4p8xuIxNUXmVTC4DgfBsf5UNXYxc5jVezPqeFQbh0BXg6MSw1gWMJAhvkNoqitlJ2V+9hRuZftFXtI9IxlTOAIYt2izhOJRFHki835HD3dwD0TohiWcPHsu7NY6grRbfo3omhFPeM5ZH7fdXk8XJNBk76FhdGzr2gWXeodjnrKL9FteAPtxn+hmf4cglyJWinjqfnJLN5RyOYjFdS36Bg6aBArS9ZS3lFJsNPlPxc3OxX1nezPqWXK4GDcJJ10FexHnjAeiebC2W2ywAQ0s35rey1Xv4Jm6q+Q+kTiqJbzqzsHsGhbARsPlVPd2MVP7khArbzyobZVFKms7+RkaTMnS5o5XdGG2WIFYOXuYoYm+DJ3dFivm2jcaNR21bO6eCPHG3JwkjuyMHo2I/2HIDuTXTsxZAy7qw6w0Z4tZecqYG2vx3DgG6QBCcgTxl/1/QkSKcrRDyOonTFmrUXUd6Ia/xOEPjbckOjbaLWGEm/PlLqpUSmkdLSaEJwc7J5SduzYuTwrCtciQbik945o1GHIXI0pZzNI5SgGL0SRNLnHPziOajkJoe4khNpMC99ZfoINh8sZOzAAZ2dvZBFDMOXuQJkyk0khY9lXc5hlBWt5ZuBPr3qLczs95+ipegK9HPB171vpHpzvJ/VDwvycmTokmA0HyxkU501i2OWzMy5Gkmc8G0q30WHsxEnhePkVLoGlsQzTqd3IEychdfU/73l59HAMhxdjyttxzUUpo8nCrqxqUiI98XLt2cVceowXqVGerNxTwsBoL3z6UI55LekyaVldvJG9VQcRjUoCTCP53YyZSPo4G2vIWAmCBEXanH6Ns78QJDJbhlRgAuLw+7E2lWMuzbR1Nz20GMOhxUhc/VEMXoA8dCAAAZ4O3DcpmgVjIjiYW8uOY1V8ufk0S3YWMSzeh7GpATyWeD+thjb2VB1kb9VBTjTm4aPxYnTgcIb6pqE602Ri5Z4SdmVVM2NYCJMGXb6rpKn4CPodHyA4uOEw9Rkkrt+JWBarhc2l2wly9CfRo+9C81lkAfGoJvwU/db/oNvytq2jlFSGRCJw94QofD00fLX5NI2dMmRhcvZWHeLe2FtflFq2qwi1Usb0YSEYj34Dgq1U71JIPUPRzH4R7frX0a79B+qJP0UWkopMKuH+yTEEeDrw1ZYCXvniKE8tSMa7h98v36elw0DuGREqt7SZdq0JsJ2v4wcGEB/qTpC3I9uOVrIlo4Ijp+qZmBbIjOEhV9z0oj/o1JkoqWknIcz9gl5936fV0Ma64i0cqDmCQipnRtgkxgeNRiU79+LaWeHE6IBh9mwpO/2OaLWi2/EBSCSoxjyK0IPqh/5AEASUgxcgqJwwHPwG3YYum2edopddmo06ZBY9rVYNzg72TKmbGZVCit5oBqUDYlfT9Q7nmmEXpezY6QOnmgvIashhVvjUC3aCEU16THk7MB7fgKhrRxY9CuXg+Ug05y/bG+aNCedYQSNr95Vy76RoFCkzMBcexHhyG6q02cwMm8w3+cvJasgh1TvpivZlp39o7TRQUNnG7JF9E1zyWwrxdfDBRel82WXnjAwjq6CRTzec4s+PDunzDH2yVwLrS7eS05h3RSU8oihiOPA1gsoRZdqFu3kJCg3yiKGYCg+hHHo3guLaiTwHc+vo1JmYlH558eAsgiBw/+QYXvzwIJ9tOMVz96TekAKwVbRyqDaTlYXr6DJpkTaFo2qJ41cPDu+zIGVprsRcsB/FgGn93sr6aiAIAlLPEKSeISjT52LtaMRcdgzTqV3oN7+FOXokquH3dp9zSoWUMSm2BhXFNe3szKxiX04tO7OqiQxwYVxqAFNjJzI1dAKZdcfZVbmfJadXsbpoA/EesUjafdh7yMKo5JDLluqKoogpe4NNJPOJRD35KSTqcz/jR+uPU69r5PGkB/vtHJOHpcGoh9Hv/hj9jg9QjX+iu1xkbEoA3q5q3l2RA82+HCaTuZEzbumurqfKWsguamLh2Ag0Yhdd+buRR49A0oOW6hJnbzSzX0C38V/oNr+FctSPusuQxw0MxNddw7src/jLZxn8fG4iMcGX/swYjBbyK1q7RaiqRtsMubNGTnyYbXIqPtQdN6dzhZoFYyMYPzCAFXuK2XS4nD3Z1cwYFsqEtIDr0im0qrGLrRkVHMipxWi2khrlyWMz4y/4e6Q1adlctpOdlXuxiiJjA0cwJXT8JSdD7NlSdq4GxuwNWOsKUY37cY8+//2NInkKgsoR/a6P0K591eZZp778uO8s1i5bp2+DzBmZ9OayFrBzLt3leyoHrE3l1zuca4ZdlLJjp5dYrBaWFKzGU+XOhKBR5zwn6jsxntyKMWcLGLqQ+sehnPI0Uu/eewldCD8PB0Ym+7HjWBUTBwXh7R6ENDgFY85mFMlTGOY3iJ2V+1hZtJ4kz7julHc714+j+Q2IQFofSvdMVjOFrSUM9x/co+XlMikPT4/jb18cZcmOQh6cGtvrfQIEOvrjqnThRGPuFYlS5pIMLDX5KEc+iKC8eOcxedxYTPm7MRUcQJEwoc/76w2iKLI1o4JAL0digl17ta6bk5KF4yL5fGM+e7JrGD3g/Ayw60lVZw3f5q+gqK2UMOdgXOtHU1IKv35gIJoryKAwHlkGChWKAdP7L9hriMTJE0XiJORx4zBmrsKYtY6u6jxUYx9D5v9dJpIgCET4uxDh78JdE6LYm13Dzqwq/rc2l2+2yRmZ7MfYlDiGDEqjpK2cAzWHyaw9ic6ajXqgQItrKNsq6kn2jL9gJodotWDY9wWmvJ3IwgejGvsYguzcmW2raGVT6Xb8HXxJ9ryyrpo/RB47GtHQheHQtxiUGpQjH+oWveJD3XnhwTTeWNOB1q2Cxcd28dCg872VbgVEUWTJziLcnJRMSAvEeHQJWC296rYlUTujmfkbdFv+g2H3J4jaVhSpdyAIAnGh7t1m8q8tyuL+ydGMSQnoXtcqipTXdXCyxJYNVVjVhtkiIpdJiA50YUSSH/GhbgR6O14000gURSyiBQcHCfdMDmVEqjtr9pewZH82W07kMiE9gPhwV6yiFYvVgkW0YLaasYgWLKLVdr/7cQuixYifcyCBTv7d3YR7glUUySluYsuRCk6WtiCTShiW4IOni4pVe0v565dHeXL+dxljRouJXZX72FS2A71ZzyDfVGaGTcZDfXkxwJ4tZae/sTSVY8xYjiwsHVnksOsWhzx6BILKAd2Wd22lwdOfReLUs/Nb7GoGwKJ2vYoR2rkWnM2UEhQOiEa7p9RVo7Ozk7vvvpv333+fwMBAjh07xt/+9je6urqIiYnh1VdfRaFQkJeXxwsvvEBXVxfp6em8/PLLyGQyqquree6552hqaiIsLIzXXnsNBwcH2tvbefbZZ6moqMDd3Z0333wTLy/7D5Wd/md31QFqu+r4SdJDyM+U4Vm1rRizN2HK2wEmPbKQVBQpM5D6XLrkqi/MHhnGwZO1rNxTzI9nJaBMnYl21V8w5e1CkTyFuZEzeff4R+yu3M/44NH9vn87veNofj1+HhoCetAO/oeUtpVhspouW7r3fSIDXJg0KIjNRypIjvAkJar33fgEQSDZM56DNRkYLSYUffA3EM1GDIe+ReIeiPwyJuYSrzAkniGY8nYgjx9/TTKPTpW3UtnQxcPTYvu0v9ED/Dl0so5vtxeSFO5xXvbC9UBv1rOuZAs7K/ehlqm4L3YhTSWerCgo4YEpMYT49t0M2VxbgLnsGIpBC87pSHYzIkhlKAfNRxaSgm7H/9Ct/TvyxEkoBy88TxxyVMuZOiSYyYODyCttYcexKjYfrmDjoXISw90ZlxpAkmIcOw67ExhqYUCqmdyWU6woXMeKwnX4aLxI8ownyTOecJcQBJMB3bZ3sVScQJEyA8Wg+RcsE8lqyKFWW88jCff2qIlGb1EMmIZo6MKYtRZB6Yhy8ILu5/w8HPjjnZP4455sDtYdwnFXJHNHh1+2BOtm42h+AyU17Tw8PRa5RUdn7g5kEUOROJ8/gWCymtGb9RgsBnRmQ/d9vVmPzmJAHz+QTpUJXekWjG0nMXsGoT/zvDJRj6azk2/rt7B4mwUE8fxgfEHuC2e/aYuB4i5YcxI42csDcweVO+iBdc22W19wV7kR5BRAkGMAQU7+BDkF4qI89ztEbzSz70QtW49WUtesxdVRwdzR4YxJ8cdZY/sshQe48P7KHP786RGemJNAq6KQ9SVbaTW0kegRyx0R0whw7J0/nT1byk5/IVpMthJqpQPKUQ9d98xnWXAK6hnPodv4L7SrXkE9/Vmk7pcvoxbPZEoJmmuf5WWnf1EppJgtIqJCAyY9osWMIL31kwyu6REeP36cF198kdLSUsAmUD355JN8+OGHxMbG8swzz7B06VLuvfdennvuOf7yl7+QkpLC73//exYvXsy9997Lyy+/zL333suMGTN45513ePfdd3nuued48803SU9P54MPPmDlypW88sorvPnmm9fy8OzcBnQYO1lXspk492iSPOOxdjRgPL4BU/5usFqQRQyxiVHuPS8H6i1uTkomDQpi3YEypg4OJtgnEqlfLMbsDcgTxpPgEUOcezTrS7cx2C+tV7OddvqXti4j+RWtzBwW2qf181sKERCIcu1dpt3c0eHkl7fy7socfrkgmYSw3g9Skj0T2F11gPyWApL6kKlhPLEJsaMR1YznL9tS2WZ4Pg7Dnk+x1hddFTH3h2zNqMBRLWdogs95z5ksJhp0TfhovJBeJHaJIPCjabH88ePDfLXlNL+Yd/3KZUVRJLM+m2UFa2g3djDcfzB3REylstrIR3uPMSTeh7Epfc/mEkUR4+ElCGoXFImT+jHy64vUOwKH+S9jOLQEU84WLJU5qMY+fsHMVokgkBDmTkKYOy0dBnZlVbH7eDVvLzsBQKCXI8/dkYpGJWcO02jStXCiKZcTDbnsqNjL1vJdOMjUxHYZiG1pJXHE/SgTJl4wLqtoZWPpNnw03qR6J19wmf5AMWg+oqHTJkypHM7xUXLSKJgbP5ZvC1aw4UQWdc1aHp0Zj1J+7cvBrgZmi5Vlu4oI8HRgRKIfxswVYDackyVltJh4L/sTiltLMIuWy25TQEDp6oTS2ISyvhONsy8qmRoXpQuhLkFU1Ogpq9YBAkqFFG9XNV5nbqoreF2lEilSQYpMIkMqSJBKpMgEGYIgoaSqg0MnGzB3dZHkYSbVy4KjoQmhpRqpoQupCBJBgtzFD4VHMFZ9J1V1J6kNSaDG2YuKziqON+R078tF4USgUwAecm8aaxXk5lrRdcoJ83Pmx7PiSY/1Pq90KOFM9t3rGzfyn5P/QaLuItQ5mB/F33PZJjEXw54t1XtONRfgINcQ5BRw+YVvI4wZK7A2V6Ke+jQS1Y3RxVLmG4Xmjt+jW/8a2tV/RT31V8h8oy65jvVMppTc+cYvrbdzaVRnSp3NMpu1gGjoQrhI441biWsqSi1evJiXXnqJ559/HoB9+/aRkpJCbKytxOTFF1/EYrFQVVWFXq8nJSUFgHnz5vHWW2+xcOFCjhw5wjvvvNP9+P33389zzz3Hzp07+eqrrwCYOXMmf/rTnzCZTMjl19/s0c6tw+qijRgsRub5DEW/80PMhQdAEJBHj0QxYDoSl/MvcK8G04YEs/NYFUt3FfHMnSkoUmeiW/8apoL9KGLHMC9yJn89/C82lmxjQfQd1ySm/qSqs4bt5Xto0jcT5BRAiFMgwc6BeKk9r/ssVm84droBUexb1z2wiVLBzoFo5L0zvFTKpfz67hT+8fUx3lqWzdMLBxAX0ruBSqRbOCqpkuyG3F6LUtauFozH1iILTUMW0LN15ZFDMRxchDF3B+qrLErVt+rIKmhkxvCQC3qufJO/nEO1R5FJZAQ4+hHiFESwcyAhToH4Onh3Z674uGuYPTKMpTuLyDhV3+f3+Uqo0zawOH8lp1oKCHL05/GkBwlzCaat08B/Vx/Dx03Dg1NiruhzY6nIxlJ72laGKb/+GWH9iSBTohpxP7LQgeh3foh21V9QpM5CMXAWwkXKn92clMwZFc7M4aEcL2wkt7SFWSNCzymN9FC7MTZwBGMDR6Az6zlZuo/jp9aTpxQ46uuMrH4bUabSM1lUcbirvvt8nmjMpaqzhofi774qWVLdxy4IKEc8iGjQYjj4LYLCAXnsd9m1g/1SWVW8nsDkNo7ub6CxLZOnFiTjegt0dtpzvJq6Fh1PLUhGMOsw5mxBFpqG1P27C/YVhWs53VLImMDhOCucUUmVqGRKVDLVd/elqu6/CqkciSDBeGIzhgNfI/V1RD3l0e9Kl+OhuLodpVyCv6fDVfsts+rasTaUYmksIbGhhOlCCUjboBUsLQLtck+cgxLRBEQi9QpD4h7Y3XxFFK047/+ayJNbkceMQjnqWfRWI1WdNZS3V3KyroTC+kpyJPkIggjx4CZR4+ISQK2ygeON/gQ5BeCp9ug+dwtailhZvAGtbzkqszMdp1PxCk0hLDX0io7Tni3Vc+q1Dbx7/COAMx0Nh95UY6mrhbn2NMbjG5DHjkEWnHK9wzkHqXsgmtkvoF3/Grp1/0Q96WeXjNHa2UyHVYWzk30i+mZHpbCNS02CEjk2UQq7KNW/vPLKK+f8X1ZWhkaj4Ve/+hXFxcUMHDiQ3/72t+Tm5p5Teufl5UVdXR0tLS04Ojoik8nOeRygvr6+ex2ZTIajoyPNzc34+FwbkcDOrU9ZewUHag4z2uqE05rXMcvkyBMnoUiacs1NETUqOTOGhbJ4RyF5pc3EhiQg8QzFmLUeefQo/B19Ge4/iF1V+xkdOOyazCK2dBioqO8gMdyjT2UeoihS0FrElvJd5Dblo5Aq8NP4sKfqANutZgDUMhXBToG22xmRwF3ldsMOrjLy6/FxUxPo1ftBgt6sp7S9gonBly59uxiOajnP3mMTpv699DjP3JlCdJBrj9eXS2TEe8RwoikXq2jt1cWx4fBSsFpQDu35hYIgVyGPGo4pfzfisHuuaonY9qOVSCQC41LPT4kvaCnmUO1RBvmk4qxworyjkkO1Geyu2g+AQiK3CaXOQQQ7BZKa6M+hPAe+2nKauFC3a9b1ymgxsqlsB1vLdiKTyFkYPZvRAcOQCBKsVpH/rj6JzmDm13elXFFLelG0Yji8FMHZ+xzB4lZDFhCPw4I/o9//NcbMVZjLs1CN+zFSt4tnFcikEtJivEmLubQYKa/OJ2b3YmKVDiimPkWZxGLLomrMZfHplSw+vZIARz+Sz5T5bSjdhqfagzTvAf19mOchSCSoxv0YnVGLfs8noNQgD0sHQCVTMch3IAdrjvDYnIl8vq6EP3+WwVPzk6+oFPR6ozeaWbWvlOhAFwZEeGDMWgdGHYrUWd3LHG/IYXfVASYEjWZeVM89pgBbh121M/qd/7NlOUx7BomjrRtquH/PjYt7gqjvxNJYhqWxBGt9CZbGUsTOs92aBCSufsgCE5B6hWFyCWJzgcimo3XQBBNlgcwID8The+XZgiBBOfw+BKUDxsxViEYd0tGPU1ehYneGkvK6QBxUoYwZ4ENcjJQ2sYGKjioqOqrYUbGnO6NMJVUS6OSPBAmnW4twVbpwX+xCBnmnslpZxroDZdQ2avnZ3KQ+dwqzZ0v1nBWn1yC1WAgxCyzKX0FZeyV3Rc/ptqC4HRGNOvQ7/ofg5Ily6N3XO5wLInHyQnPHC+g2vI5u01uoxjyKPHrEBZc1tTXRatXg5mjvvHezo1bYxmwGidpW0m3ouq7xXCuua4GixWJh7969fPvtt/j7+/PCCy/wwQcfMHz48HMuMkVRRBCE7r/f52IXo6Io9rnDkB07P8RYfYpvcz/HwWphXE01itSZyBMn9aozRn8zIS2ArUcrWLqriBcfTEeRMgP91ncwlxxBHjGEGWFTyKjLYmXRBn6c9OBVjcVssbLn28/wNxTzN+UMpo+JJSWyZ1lNFquFrIYctpbvoryjEie5I7PCpzAqYBgOcg0Wq4WarjrKOyop66ikvL2S7RV7sJwZ/DrINQQ7BXZnUwU7BeKqdLnuQlWH1sipslamDQ3uUyyFrSVYRWuv/KR+iLNGwXN3p/D3r4/xryXH+fVdKUQG9Hy2Jckznsz6bMraKwlzCe7ROpb6YswF+1CkzLigN8ulkMeNxZS7HVPBPhRJV8dcWWcwsye7mkGx3uf5QFmsFhafXomb0pV7Y+ejkNoGd1bRSr22gbL2Stt52F7JnqoDmM6IpcowJfpWR17fXczMlJR+EUtFUURvMaA16dCadejM2u77naYu9lYdpEnfwiCfgcyNnHGO18uqvSWcKm/lkelxBHpfmbhnLjqEtbniTJe2W9vTQFA6oB73OKbQgRj2fIp2+UsoBy1EnjSpz+3BjSe3Ydj/JRKPYNRTnkbi4EYUEOUWzrzImdR11XOiKY/shlw2lm5nQ+k2AO6LXXjR0tH+RpDKUE96Eu36f6Lf9j7CtGe6MxxH+g9hT9UBdA5l/O7+gfx7aTZ/++ooj82Ivy6Zgf3B5sMVtHcZeXJeEliMmE5sQhqUhNQrFIAWfStf5S0lyCmAOyKm9mkf8sihCGpndJvfsvnCTPv1OVlYvcWqa8faUo21tRprSxXW1hqsLdWI2tbuZQRnH6Q+kUgTJyHxCkPqEXxOW3kFMD8IxqaFsXJPMZsOlbPn+Pmd+gRBQJk+Fz0KzJlLyCuq4YvW0Xh4uPDglBiGJfp+r4zzu98ns9VMTVd9t0hV0VFFi7GNORHTGRM4otubcP6YCAK8HPhk/Sn+/NkRnpyfTLBP30ROe7bU5TnVXEB28ymmNncxuk3HtrAIttUcoaqzhseTHjgnS/N2wnDwW8SORtSzfnvO5+RGw9ZM4bfoNr+Ffuf/EPWdKJLPHx9ZOptpsTrgcgtkst7unM2UMghKHDmTKXUbcF1HmJ6engwYMICgIJv/zrRp0/jyyy+ZN28eDQ0N3cs1Njbi7e2Nu7s7HR0dWCwWpFIpDQ0NeHvbBkXe3t40Njbi6+uL2Wymq6sLV1fX63FYdm4RRFHEUnECY9ZajnSVU+bjzN1OcXiOvfeatq2/GHKZlDkjw/l4fR5H8xtIi0lD4uKLMWstsvDBuCidmBQ8jrUlmyhoKe6zd0NPOLBhA+Os+0EOCstG3lpmINTflfmjw4kLvXAWmdFi5GBNBtvKd9Oob8Zb7ck9MfMY4pt2zuydVCIl0MmfQCd/hmPrQmeymqnprD0jUlVQ1lHJ5vKdWEUrAE4KR5tI1S1UBZ1n0Hq1OVbQiFUUSb9MFsXFyG8pRCaREe4SekVxuDgqee6eVP7+dSb/WpzFs3enEubXMzE1wSMWiSAhu/Fkj0QpURTR7//K5j3Uiw5WZ5F6BCPxicSUuwN54uSrIizuO1GDzmBhYvr5vm+7KvdR3VXLj5Me7BakwOa54uvgg6+DD0P80gCbgFWrrafszPl33FpIrfUkH+XY/Fcc5Q7nZPS5qVzRmXV0mXRovycwac06dGfvn33OrENn1nefzxfCz8GHX6b+hGi3iHMezyluYu3+UkYm+TEyuXfmwT9EtJgxHFmOxCMYWUTPOkDeCsjD0pD6RGLY8ymGg99gLstENfaxHndBgjMZZge/tQkewSmoJzyBIFedt5yPgzc+Dt5MDB5Dp6mLk42naNQ3M8R3YH8e0mUR5Eo0U55Gu+ZVdJv+jWbmb5B6hxPo5E+Ycwh7qw4ybshI/vhQOv9ZfoJ3V+Ywe2QYs0aE3lQG6O1dRjYcLict2ouIABeMJzYj6jtQpNrK3K2ilc9yF2ESzTyccO8VdbCVBcSjmfU7dBveQLv6FdRTn0bmG33R5UVRRNS2fk90qrIJUS3ViIbO7xaUq5C4+SMNTELq5ofEMxSpZ8glO5x+Hw8XFY/OjGfy4GCW7Cxk8Y5Cth2tZN6YcIbE+1BR18mWjAoO52lIkw7jbseD/CXsAO6zn0Oiuvg+ZBLZGUN0f+DSXVuHxvvi46bhP8tP8Ncv+y5yOiucGBUwlB0Ve+3ZUhfAYrWwrGAN7hYYJfdBPWQwkw5+S8jAiXzdlc/fj7zFo4n3EX0Fk183I+by45hO7UQxYDoyv5jrHc5lERRq1NOeQb/9vxgOfoOob7c1Hfned6+ga6HVGoyfXZS66VGdyZTSYRsz2EWpa8DIkSN5++23qampwc/Pjx07dpCQkEBAQABKpZKjR4+SlpbGqlWrGD16NHK5nPT0dNavX8+sWbNYuXIlo0fbygnGjBnDypUreeKJJ1i/fj3p6el2Pyk7fUK0WjGXZmA8thZrUzlGR3c2+HsS4uDNiPRH+jxjfjUYnujLpsPlLNtVREqUpy1batdHWCpOIAtOZkLwKPZWH2R54RqeS3/yqviTlOTlEVu1giaFH/5DpxC251NeiDnFOzUp/HNRFnEhbswbHU7EmQydTmMXu6r2s7tyP52mLsKcg5kbNZNkz/gexyeXyGxik3MgBAwFbKa0VZ3V3dlU5R2VnGzKR8TW6chV6cJQv3RmhE26qj4tZ8nIr8fTRUWwT98yVfJbCgl3Ce1T57sf4uak5Pl7Unn1q0xeX5TFc/ek9qj8xkGuIdIljBONucyOmHbZ5c2FB7DWF6Ea82ifZx4VcWPR7/wQS80pZP5xfdrGxbCKItuOVhLh73xeGU2roY11JVuI94gh2TPhstuSSqQEOPoR4OjHcAYzP9zCHz85gFnexowJblR1VVHeUcnmsh0XFZckggSNTI1GpkYtV6ORq/FUu6ORa2yPy9Xdz2vkatSy7x5XSZXniXbN7Xo+WJOLv5cD902++MVvTzGd2onY0YBq2jM31PfetUCicUE1+SnMp/ei3/8VXUv/gGrYvchiRl1WLBXNBvTbP8BcehR5wkSUw+5F6EHmtqPcoVv0vB4IKkfUM55Fu+oVtBteR3PH75G6BTAqYCif531LQWsx0W4RPH9vKp9tzGfV3hIqGzp5bEY8SsXNYYC+Zl8pJpOVeWPCES0mjMfXI/WL6TYR3lS6g4LWYh6IuxOffhA4pJ4haGa/iHaDzRdGNeEJZCGpiJ1N3YKTpTsDqhpMuu9WVjogdQtAFpaOxM3fdnP1R3Don5L1IG9HnrkzhZOlzSzZUcj/1uSyeHshbV1GlHIpowf4MyFtMJq2gei3v49u3d9RT3+23zLEw/ycbSLnCpvIeceIUO4YGXZRkVO0WhD1HUg0ruc8PjF4LHuqDtqzpS7A/pojVHfVcl99Gw6D5yCLHIal5jTRx3bw6yk/5cPqnbx17H/MiZzOhKDR1z3D/Fog6jvR7/oYiVsgivS51zucHiNI5agm/AzDvs8xZq1D1HXYugVKpIgmA1KzjjarBld7+d5Nz9lMKa1oey/totQ1wM/Pjz/96U888cQTGAwG4uLi+M1vfgPAa6+9xosvvkhnZycJCQk8+KCt/Oill17it7/9Le+99x5+fn688cYbAPzyl7/kt7/9LTNmzMDJyYnXXnvtuh2XnZsXU+FBjEdXYm2rRXDxRTXmUbYKrXRU7uGJmDnXRMzoDRKJwPwxEby1LJu92TWMSR6GkLHCli0VnIxCquCO8Kl8nvctGXVZDO7n2XddRyvS3e9iQo737GdQuHshdjXjmbmaPw8NYa8lhbUHSnnli6PERytxC6/mRGsWJquJJM84JgaPJcIltF8GQgqpnDCXEMJcQrof05sNVHZWU95eQX5LERtLt9Gsb+H+q1wa06U3kVfawqRBQX06tg5jJ1WdNcwK71vpyIVwd1bZhKmvM3lt0TGev3cgQT0o7UryimdZwRoatE14aTwuupxoMmA4vASJVxiyi3ge9ARZ+GDY/zWm3B39LkqdKGqirkXHnFHnZw2uKFyHWbRwZ9QcQEQ0aHuceQCgkEt5eGoCf//6GPWFXtw/fjhgywis7Kym3dh5jsCkkalRXkBY6itmi5X3V5/EZLHyszmJV9wlTTTpMWauRuoXgzTw+nUWvJ4IgoA8ZhRS/zj0Oz9Ev/tjpKWZqEb/6LwL47NYtW3oNv0ba0MJymH3okiafG2DvkIkGlc0M55Du+oVdOtfQ3PHC6R6J7O0YDV7qw4S7RaBXCbl0RlxBHk7snhHIX9tOcqT85PwdLlxS2AA6lu07MyqYvQAP/w8HDDm7UTUtqIY+xgARa2lrC/dQrpPCkN8+08clDif8YXZ+Cb6Lf8BqRzMxu7nBbUzErcA5FHDzxWf1M7XRCRICHUn7keDOJxbx/6cWqaEujN6gN93xv0egxDkKnSb30a7+q9oZjzX7ZF1pbg4Knn+noF8vukUq/eVUtnQxWMz47ozBc5irsrFsP8rrK21aGb9Fun3OpG5KG3ZUjsr9zE1dALeGs9+ie1mR2fWsbZ4E+FWOUlWFbLwwQiCgGrsY3Qtfwnnvd/w3Ozf82XxOlYUrqO8vZL74hailN66ooYoiuj3foZo6EQ97Zlug//rEYfFKp7XqfJyCBIJypEPIaidMWauRjR0ohr/BGJXCwCtVoc+e7TZuXFQKc+IUpYzDSjsotTVY/v27d33x44dy9ixY89bJjY2lqVLl573eEBAAF988cV5j7u6uvL+++/3a5x2bi8sjWXot7+PxD0I1YSfIQtLp17XyI7D/2KoXzqhzj3z1LnWDIj0ICrQhVV7SxiW4ItiwDQM+7/CXJOPzC+GQb6p7Kzcy+qijaR4JfVL5g3YZi2rlr+JB120DnsSjbttVlmRNhdrez3mjGWMnehD6H1BLDqxiRJLEcWNAu6WCO5Omkyif2i/xHEpVDIlka5hRLqGMS5oFJvKtrOmeBM6s45HEu7vt9fih2QVNGKx9r1073RLIQAxPyjNulI8XdU8f08qf//6WLcwFeB5aeEl2dMmSp1oPMn44IsbXRuPr0PsakE14WdXlFUjyBTIo0diyt2GVdfer75tWzMqcHNSkhZzbgbE6ZZCMuqymBY6ES+NB/rdn2A6vQ/FwDtQpEzvsZdSTLAbY1P82XykgsFxPoT5OaOQKq64BLMnLN9dTGFlGz+5IwE/jyvvvmM8sRlR145y8lO3xez5pZA4eaKe+TymnC0YDi9Fu+RFlKMeQh5+bomSpaUK3cZ/IeraUU1+EnnotS3B6y8kzt6opz+Lds3f0K7/J5pZv2eoXzq7KvfTbuzAWeGEIAhMGRyMv6cD7686yZ8/y+Dnc5N61UzhWrN8dzFSqcAdI8MQrRaMWeuQeIUjDUhAa9LxycmvcVO6cnfMvH4/522+ML/BcHQFWK1nxKcApK5+V7WpQ4/jEwSGJvgyNMH3gs/LgpJQz3gW3cZ/oV31CpoZzyNxvfCyvUUuk/DI9DiCvJ34dnsBf/1Cy5Pzk/FyVWPtbMJw4BvMJRkITl4IDq7otr2Hw/w/nfO6fZcttc2eLXWGDSXb6DJ1MaOyGUXSTASp7XdMUDqgnvhztKteQdz9GY9O+SVby3ezungjNV11PJ704C0r7JmLDmIuPoJi0AKkniGXX6GfMJoslNZ2UFTVRlF1O0VVbXTqTAyN92HK4OBeeT/aPN/mIaicMOz/Ct2G15En2iY/jArnXgtddm48zoryepMICs255du3MPYz146dM5hLMkAQUM98HnnEYBAElhasQS6R96h06XohCAILx0bS1mVkc0YF8tjRCConW0chbCVC8yJn0mJoZXvFnn7bb+Wmz/AxlJLnM52w5NRz4lGOepgC/1DeyvuGN4+/S6tQxdjA0YyU3UdjTjRvflHCpxvyaG7X91s8l0MQBKaGTuDumLnkNJ7iP1kfojPrLr9iH8g4VY+7s5Iwv775WOW3FKKS2joN9jfebhqeuycViSDwz2+OUdN06RkYT7UH/g6+ZDfmXnQZa0cjxuMbkEUM7S6DuRLkcWPBasGU33/na1VjFydLWxiXGnDOoM1itfBt/ko8VG5MDhmHuTwb06ldSJw8MWYsR7viT1gay3q8nwVjI3FxUPDJ+jzMlot7QvUnxwoa2HionHEDAxgSf+UdZ0V9p+39DElF6nN7eY1cDEGQoEiagmbeywjOXui3voNu+3+7ZzDNVbloV/0FzEY0s3530wpSZ5F6BKGZ+ivEzhZ0G15nhNcALKKFg9UZ5yyXFO7Biw+moVHK+Oc3x9h9vPo6RXxpSmraOZxXz+RBwbg6KjEXHkTsaEB5puPe1/nLaDO283DCvahl53t/9QeCXIlq6N2oht+LIm4sMt+oG0KQ6iky32g0M38LFhPa1a/06nvxcgiCwORBQfzqzgE0txv422cHqdq2iK5vf4e5PBtF+jwcFr6CetIvEHVt6HZ+iCiK3eufzZY6UneMem1jv8V1s1KvbWBn5T4GSd0JMIu239TvIfUKQznsHiwV2ZiyNzA5dBw/H/AobYZ2/pHxNjmNedcn8KuItbMZ/d4vkPhEohgw/artRxRFGlp1HDxZy1dbTvOnT4/w83/t5tWvMlmys4jK+k7iQ90YkeTHkfx6/vjxYd74NouTpc3nnNOXQ5E4CdX4n2CpLUS/4wPbg+rb07T+VuNs+Z7OaEZQOtw2mVJ2UcqOnTOYS48h9Y1GorIJCTlNeeQ25zM9bCLOihu7/XVkoAupUZ5sPFRGp1FAnjgJS0V296Axyi2CZM8ENpdtp83QccX7a8/ZhWvFbo4KSQyaOa/7cYvVwqGao/wt8x0+0mhpVMiZ0WriT8k/ZmHMTO4dm8zfnxjO+IEB7M+p5bf/PcDXW0/T3mW8xN76l1EBw3g44R5K28t5M/O/tBuv/PX4Plq9mZOlzaTHePd5tj2/uZAot7CrVmLo624TpkRR5J/fHKOuRXvJ5ZM94ylsLaHTdOEfRsOhxYCAcsjCfolP6uaP1C8GU95OxEuYffeGbRkVyGUSxqT4n/P4jsq91GrrWRg9G7nZiH7PJ0jc/NEs+DOqyU8iatvQrngZw5FliBbTZfejUcl4YEoMlQ1dbDjYfxdtF6OhVcdHa/MI8XXi7vFXLggCGLLWglmPYtCCftnerYTUzR/N7BdQpM3BXHSIrqUvYjiyDN3615E4uKOZ80ekXmHXO8x+QeobhXryL7C2VOG8+0uiXcLYW33wPI80Pw8HXnwondgQNz7dcIqvtpzGYr02gmxPEEWRpTuLcFTLmTYkGFG02rKk3AORhgxgf81hjtVnMyt8So+7jN6uSD1D0Nzxe5DK0a59FXNtQb9uPyHUnf+bKONX6uU4F22k2Tkah7v+hnLgHQgyhU1MGXo3lvIsTCc2nbPuxOCxSAUpG890sLydWVG4HplEyqTSMmThgy9YbiyPH48sfDDGI8swV58iziOa5wc9hYfKjfezP2VDydZLNtu4mRBFEf2uj8BqRj328R55/PUUg8lCfnkLGw6W8faybH71n3385v0DfLAmlz3Z1agUUqYMDubJ+Um8+eRIXn1iGI/PSuBH02J57WcjmDs6nPL6Tl5flMVLHx9hf05Njye05JHDUE/9JZzxTpU4XrixkJ2bC5lUgkwqQW+0nBGlLj1Gv1Wwi1J27ADWtjqsLZXIQm0+EiarmaUFa/DReDMmcPh1jq5nzBsTgd5oYd2BMhQJE0Cu6s6WApgTOR2T1cy6ks1XtB9zfRHW/Z9TYPYlYtZjSKVQ3FbK6qKNvHTg73ye9y0iIg/E3cnLab9kVIcRtrzTrfS7OCi4d1I0f/vxMIYl+LL9aBW/ef8Ay3YV0aW//EV/f5Dmk8ITyT+iXtvAG0ffpUnX3G/bPl7UiNnS99K9Jl0zjfpmYtz6R2C4GP6eDjx3dypmi02Yami9eNZYincSIiLvHv+Yxh+8VuaafMzFh1GkTO83nxEAedw4xI4GLFUXz9DqKZ06E/tzahka74OT5ju/hRZ9K+tKtpDkGUeSZzz6A98gattQjXkMQSpHHpqGw51/RRY1HOOxNWiXvYSlrvCy+0uN8mJQrDdr9pdS3Xj1ZrhMZivvrcxBBH46JxG57Mp/0q2dzZhObkUWNeKKWtjfyggSGcq0OWjm/AFBrsZ4bA1S/1g0s19A4nRrlb3IgpJRjfsxltoCBje10KRvIa/5fCHCQSXn6YXJTB4UxLajlfxr8XE6ddfm+/xynCxpJq+shVkjQlErZZhLjmJtrUaROos6bQNLTq8m1i2KicFjrneoNwUSVz80s19AUDujW/9PzJU5/bJdS2s1ug2vozzwAa6uzqx3XMDLRQP5cl/jORfp8oSJyELTMBxagqW+qPtxe7aUjVPNBWQ3nmSiKhgngw5F4qQLLicIAqrRDyM4+6Df/j5WbRueand+nfYz0n1SWVuymQ9OfH7VMsqvJabcbViqTqIcejcSl75nE4uiSP3ZLKjNp3n50yP84l+7+fvXx1iys4iqxi4SQt24f3I0L/1oEO/8ajTP3zuQBWMjSI3yOs/vyVEtZ9bwUP750+E8PC0Wqyjy4do8nn9vPxsOlqHtwZhYFpSMZtbvWWMejpPT9e8Mbqd/UCmk3xOlbo/yvetqdG7Hzo2CuTQTAFmorQxtR/keGnVN/GLAY1fUEvpaEuDpwIgkP7ZnVjIxPRCn+PEYszdgbatF4uKLj8aL0QHD2FW5n7GBI/B37L0fhFXbStv6f1MvqjieMBKhaT25Bfl0mbRIBAlRruHcHTOXBI/Y7iwhyeSn0K37B7ot/0E97dfdvgYeLioenh7HtKEhrNxTzLoDZezIrGLa0GAmpgVd9W5O8R4xPJn6Y947/jGvH32XX6Q81qfX5IdknKrH1VFBeEDfvJDyu/2k+l42Ze1oRLf5LaR+MSgG3tGd/fdDAr0defbuFP75zTH++c0xfnPvQDxczi9dCXIK4LHEB/jq1BJePfIm98UuJNU7CdFqxbD/awQHdxQD+rfEVRaWhqByshmeByZe0bb2HK/GaLYyKT3onMeXF65FFK0siJqNuTwL8+m9KFJmIvX+zghdUDqgHvsY5ogh6Hd/gnbVK8iTJqMcNA9BdvHWy/dOiia3tJlPN57it/cNvGhHqSth8fZCSms7+MW8JLxd+8dk2pi5EkRQps3pl+3dyki9wtDM+z8sVSeRBiX12HvsZkMeMQTRoCV272c4RvqxumgDJW2lyCVy5FI5cokcxZn7CQNkSF00bD1cwsuLarl/UjyBHk7nLHc1m0z8EKsosmRnEZ4uKsamBCCKIsZjaxFcfBGDU/j42LsopQoejL/rhmtkciMjcfRAM+v36Da8hm7jv1CNf+I8j7WeIhp1GDJXYTqxBeRKlMPvQx4/noVIkOwuYsPBcqobu/jZ3EScNQqbmDLmEbqWv4Ru67s2f6kzTSlud28pi9XCsoI1eKjcGVZaiMQ74pzfsx8iKNQ2f6mVf0K//X3U059DIVXwUPxdhDoHsaxwDf848jaPJz3YL+Oj64G1tRbDwcVIg5KQx43r0zYa23R8u72Qgsq27sx+pVxKmJ8TU4cEE+HvQniAM86avpmMy2USRg3wZ0SyHznFzWw6XM6SnUWs3l/KmAH+TEwPvGQjCcEjhG0dkcx0vPiYxM7NhU2UMiOoHbB23h4i+605grJjp5eYSo8i8QhB4uRFq6GNDWXbSPZMIM7jytuqX0vmjAzjUG4dK/eU8Mj4yRhzNmM8vh7V6EcAmBY2kUO1mawoXMfPUx7t8XZFUaSqvZKje//LKS8p5SoVWHbj2OxAgkcsiR6xxLlHo5GfP0sj84tBNfoR9Dv/h2HvZyhHP3JOWZuvu4YnZicyfWgHK3YXs2xXMVuOVDBjeChjUwL6JfvjYoS7hPCrgT/lP1n/483M9/npgEeuqHxDZzBzoriZMSn+fRYh8lsKcVI44ufQt9k80WxAt/ktrG21WJsrMOXvRZE6E0XiJATZ+QOmYB8nnrkrhdcWnRGm7huIm9P5A5tU7ySCnPz5OOdrPsz5gtEBw5lpdcbaVIZq/BOXFGj6giCVI48ZhTF7I9auFiQOffNKsFitbMusJDbY9Rwz0VPNBWTWZzMjbBIeEiVduz+1tYhOm33B7ciCknBY+AqGw0swndiEuTQT1ZhHLtoh0MVBwd0TovhoXR47MquYkNa//mCH8+rYllnJ5EFBDIy+8tb1YMtUMOXvQZ4w6ZbL+LlaCDIFspDUyy94k6OIH4do6GR0wXq2iFYqOy/tHSWLBS3wwekd5z0nESTIJTKbqCWRE+4Swl0xc3G4wO/HlXLoZB0V9Z38+I545DIJ5vLjtu+sMY+yomQjVZ01/DT5YVyU/ddQ4XZBonFBM/O3aDf+C/22d8H4MPLYizfD+CGiaMV8eh+Gw0sQdR3IY0ehGLSgu7mFACwcG0mglyOfbjjFnz/N4Mn5SQT7ONkmCyb8FO2qv6Lf9RGqSU8iCMJt34lvf80Rqrtqedh3NLKcpSjGz7vsOlKPIFQjHkC/+2OMmatQps9FEATGBo0gwNGPj05+yT+P/ocH4u5koHfyNTiK/kO0WtDt/ABkclQ/GHv2lPYuI68tyqJDayQl0ovIAGciAlwI8HJA2o9lgGBrOJAc4UFyhAdltR1sOlLO1oxKtmZUkh7rxZTBwYT5nf9d1a41Iorg6mjvvHeroFLI0BssCK4OoL89PKXsopSd2x6rthVrXRGK9DkArCxcj1W0Mj9q5vUNrA+4O6uYmBbIxkPlTBkcjFfMaEyndqEYOAeJozuOcgemho5nReE6cpvyifeIuei2DBYj+c0F5DSd4mTTKVoNbaAGlc6J0X5DGByQSIhzUI9ml+XRI7C212PMXIXg7IMy9fzXNtjHiV8uHEBhVRvLdxXxzdYC1u0vZUi8L8MTfQn2cbwqXcD8HX15Ju3nvJ31P97K+oAfJz1InHvfxMgTxU2YLVbSY/omEoiiSH5LITFukX06VlEU0e/8CGtTBeqpTyM4eWI4tBjj4SWYTm5DOWg+sqhh53XHC/Nz5pk7U3j92yz+8c0xfntvKi4XmHHzVHvwTNpPWVW0ge0Veyg0WrnfN5zgiCF9Ot7LIY8bi/H4ekz5u1EOvLBYdDmOnW6kud3AfRO/e09NVjOLT6/EU+3BpOCx6Pd8iqhrRz3l6Uu2iBYUalQjH0QWPhj97o/Rrf078rhxKIfciaA4fxZzeKIvB3PrWLqriJRIzwtmoV0MqyhisYhYrFYs1rP3bf+3dhr5dMMpIgKcWTC2/zo0Go8sB5kSxQU+n3bsKFJmMtFiYnT2JkSzAbMAJkHALAiYBAGTUoVF7YxZ7YhZ5YBWouJ4tZ56vUhQiCeBQZ6YpVJMogWz1YzRakJv1nOs/gQl7eU8lng/Ic5Blw+kh5jMVpbvLibEx4nBcT6Ioojh2BoERw/y3FzZlbOGcYEjSfS8sLBs5/IISgc0059Dt+Vt9Ls/RjTpUCRNuex6loYS9Pu+xFpfhMQ7AvXUX13Ui21Ygi++7hreXpbN377K5Pf3pxHk7YjUOwLlkIUYDi7CdHJrd5maLVvqwG2XLaU16VhbvIlI1zDiyk4halyRhaX3aF157GjMtacxZq5G6hvVnZ0c5RbObwf9kg9PfMFHOV9SHjyWWeFTrmm245VgzFqHtb4Y1YSf9mliS2cw88biLFo7DDx7dyqRgS5XIcoLE+LrxI9nJTB/dARbj1awK6uaw3n1xAa7MnlwMMkRHt2Tn62dBgBc7ZlStwxq5ZlMKaUDorELUbReUWfrmwG7KGXntsdclgWIyEIHUtRaypG6Y0wNnYCnuv/8ca4l04eFsCurmmW7inhq6jRMeTsxntiEatg9AIwJHMGeygOsKFxHrHvUOaJSg7aJk02nyGnKo6C1GLPVjFKqIEbmyoS6dmqbwwkaeT+j4v0vtvuLokibYxOmjixF4uyF/CJCRmSAC8/dk0peWQs7MqvYnlnJlowKArwcGJ7oy9B43wtm8lwJnmp3nhn4M945/iHvHf+EHyXc06cZwYxT9bg4KIgKdO1THDVddXQYO/tcumc8vsHm7zR4AbLgAQBopv4Kc3UehoPfot/5PyQnNqMceheygPhz1o0IcOHphQP41+Lj/HNRFs/fk3qe/wGATCJjftQswupr+Npymn87G7i3Lot03/7PFpE4eyMNSMCUtwtFykyEPgyEt2RU4OmiYkDkdzPmO8r3UKdt4GcDHkGoOon59D4UqbOQeoX2aJsy/1gcFvwZQ8YKW9ZU+XFUo36ELPjcc0YQBB6aEsOLHx3ib18dxUmj6BaarNazIpOIxWITnszW74SoyzXhcVTL+ensxH5r/2ypL8ZckoEibU53poIdO9/nbCtyRdpcMOmxdrUgalsRu1qwalsQu1oQu1pt95vLEbVtJIkW28qFZ26CgKB2QdC4InFwQ9C4MtJ3NJ81H+ONo++yIHo2I/2H9MsExI5jVTS16/nR9FgkgoC5Og9rXSH6oQv5Mn8ZgY7+zI68el24bhcEuRL1lF+i3/5fDAe+QTRoUaTNueB7aNW1Yzy8FFP+HgS1E6qxjyGLGn7Zi60wP2defDCdv3yewVtLs/nDj9Jx1iiQJ03BXH0Kw8FFSH0ikXqFncmWGnbbZUttLN1Gl0nLPN/hWDP+hSJ9brddQk9QjXwAbUMp+u3/RTP/T90ijqvShV8OfIKlBavZUr6Tio4qHk64F0eFQ7/Fbu1swpi5GtFsRFCobZM8CjWCQvPd//IL/H+JTCVLYynGo6uQRQy56HjzUpjMFt5elk1VQxdPzk++poLU9/FwUXHX+ChmDQ9j9/FqtmRU8NbSbPw8NEwZHMywBB9aO2wlha79PDa2c/1QKWS0a40IKgcQRTDpQXFre4bZRSk7tz3m0qMIzt7g6s+SjLdxVbowOaRvdec3Ag4qOTOGhbBkZxEFLcEERwzBlLcDZeosBJUjcomM2ZHT+SjnS/ZWHcRH401OUx4nm05Rp20A6PafSvCIJVRnxLj+dXKN/jR6T+GeZL8+xXXWB0LX2WQTRxw9LtpuXhAE4kPdiQ91p1Nn4kheHftzalmyo4ilO4uID3FjeKIfA6O9+s17ykXpxNOpT/Be9id8nPMV2hgtIwOG9nh9g9FCdnETI5L8kEj6XroHffOTMldkYzy8BFn4YBQDZpzznMw/DuncP2IuOoTh8FJ06/6BNCgZ5ZC7zjGzjg5y5ZcLknlzyXFeW3SM5+8diKP6/Mwha1sdUXmHeCYinW+crHyS+w2nW4tYEDUbxSUyjfqCPH4c+i3/wVKR3esyqbLaDgoq27h7QlT3e9Ksb2FD6VYGeCYQ7xhE14YXbGV7A+/o1bYFma29uzwsHf2uj9FtfANZ1AhUw+45p827p6uax2cmsDOrCqlE+O4mlSARBKRSAZlEQCqRIJWefe7M/xe6f2adyEBX3J37r3W94chSBJVTj7Ic7NzeCIIACjVShRrcLj5BIYpWRF0H1q5mDh89TW5eCSHOZgb7KpGb2rF2NGKtPY1vXhdPRw1jkasni/KXU9xWyj0x81BI+16KotWbWbu/lIRQNxJCbR2pjMfWIKpd+NpUjsli4uGEe5Hfoj5g1xpBKkc14afod3+CMXMVolGLctg93WKTaLVgyt2OIWM5mIzIk6egHDj7ghmmF8PdWcWT85N59atM3l1+gmfvSUUmlaAe+xhdy/54xl/qZQSF5rbLlqrXNrCzch/D/NLxKcnGJJEhjx3bq20IMiWqST9Du/xl9FvfRT3rN90+eXKJjHti5hHiFMS3+cv5e8ZbPJ70AMFOV1aWLooi5oJ96Pd9BVYLgsYFjDpEow7OCtqXQq76noilQZCruoUrc/Upm/A54oFex2WxWvnv6lxOlbfy+Kx4kiOu/yS1RiVj6pBgJqYHknGqno2Hy/l0wymW7yoiwMs25nC5wESinZsTlUJKfasFQWl7b0V9F4JdlLJj59ZFNOqwVOUiT5xEQWsxFZ3VPBh3F8orGAzfCExIC2Tr0UqW7iziNzNmYC48gDFnC8r0uQCkeiUR7hLKt6dXAiATpES5RTDqjBB1dmbR2tFI19r/o0V0ZrllHC9Oj7uiGWxBKkc9+Sm6Vv0Z3aZ/o5nzByTOl+5S56iWM25gIOMGBlLbrOVATi0HTtbyv7W5KOVS0mO8GJ7oS0yI2xWbSWvkap5MeYwPc77km/zldJm0TA4Z16NjPlHchNFk7XPXPYD8lgI8Ve54qHvX1tfaVotu23tIPAJRjXn0gvEKggR55DBkoWmYTm7FcGwN2mUvIo8ZhSJ9XnfL6NgQN55ckMy/l2Tz2qJjPHdPKg6qc4Umw8FFIJXjO+QenlY5sbZkM5vLdlDSVs6jiffh20c/rAshC0lB0LhizNvZa1FqS0YFSoWUkUnfCanLCtYiAvOjZqHf/3WPyvYuhdQnEs38lzFmrsaYtY6uyhMoRz6I/HtlE2kxXqT1saTzWmCuPImlKhfl8Pt6dZFox86lEAQJgsYFicaF4VPDUIU38L81uazXSXlyXjLh/s6IVqvNXD9zDQ+5+bMrcSgbaw5R2VHNY0kP4KPp2+dmw6EyOnUmFoy1CfyWukIsVbnsTR7K6bZi7otdiK9D37+r7ZyPIJGiGvMIBoUaU84WRKMW1ehHsNSexrDvS6wtVUgDElAOvw/pJcTMSxHm58zD02P5YHUuX24+zUNTYxBUjjZ/qTV/Q7/rY1QTf37bZUstL1yHTCJlZtBoTAdfQhYxBImm95k9Uld/VKMfRr/9fQyHl6Eaeq6gN9x/EAGOvnxw4nPeOPouw/wGEeUWQZRrOE4Kx4ts9cJYta0Y9nyGuewYUt9oVGMf6x4PiqIIFhOiUdstUtlu3/9fi2jSg1H73fMGLWJHo03UEgRUYx8/Z5KoJ4iiyOcb88k83cA9E6MYlnBjGbzLpBKGJvgyJN6HU2UtbDpSQXZRE1KJcMHsdjs3J2eNzlHahCjR2AXcuOPI/sAuStm5rTGXHwerBVloGkfqjqGSKkm9yYwcL4RCLmX2yDA+3XCK440hxIekYjy5FUXyVNuskiBwX+wC9lUfIso1nBj3qPOEuLOG2SajifdaJ3DPnOR++cETVI5opv6KrpV/RrfhDVtbdWXP0sB93TXMHR3O7FFhFFS0sj+nloz8evbl1OLurGToGf8pf8++p5UrpAp+kvQQn+d9y+rijXSZtMyNnHFZYSojvx4njZzooL6leFusFgpaSkjz6d35Jxp16Da9hSBIUU9+CkF+6fRtQaZAMWA68pjRGDJXY8rdhqnwIIrkaSgGTEOQq0gIdefJ+Um8vSyb1xdl8ezdqWhUtp8Lc+VJzGXHUAxe0C1kzY6YRqRrOJ/nLuLvR97irpi5DPXrmZfF5RAkMuSxozFmrsHa0dhjA+62TgOH8+oYkxLQHXtuUz5ZDSeYFT4Fl/oydAX7UAy8o8dlexeNUSq3+XWdyZrSb/kP5vBBKIff36cLg2uFKIpYyrLQ7/8SwdEDedzY6x2SnVuYgdFevPBAGm8ty+bVrzJ5eFoswxJ9UabPQ+oThX7HB4w5uJngQdP4suUY/zjyFvfH3Umqd1Kv9tPSYWDLkQqGxvsQ4mvrPGo4toZyJyc2aEtJ8x7AsH76frJzLoIgQTnsXgSlA8ajK+mqLURsr0Nw8kQ1+UlkIQOvuDRzaLwvVQ1drDtQRqCXAxPTg5D6RqEYtADj4cWYcrejSJhw22RLnWou4ERjLrPDp6EuOY7BpO/21+oL8sihWGpPY8regMw3ursr9VlCnIP47aBf8u3plRysPcruqgMA+Gq8uwWqKLdwnBUX7voLYCo+jGHP54hmPcqh9yBPmnROCacgCCBT2JqznBln9BRRFGkzttNh7CTAsfeZ/Ut3FbEnu4aZw0PP69h7IyEIAnGh7sSFulPV0EmnztRv5fx2rj8qhQy98dxMqVsduyhl57bGXJqJoHbG6hFMVv4XpHgl9Xv50fViRJIvmw6Xs2xXEUl3TMdcdgzTqZ0okqcB4OvgzfyoWRdc96xhtqWpgo87xhOdEEtqP3X4ApC4+KKe/BS6df9Et+U/qKf9ulfeBxJBICbYjZhgN+6bFE1WYSP7c2rZeKic9QfLCPV1YniiL4PjffrUolcqkfJQ/N04yDVsq9hNl0nLvbHzL2ruaTRZOF7UxNB4nz53YynvqERv0feqdE8Ureh3fIC1rRb1jOeQOPX8PRJUjqiG34sicSKGw0sxZq7ClLcDRfo85DGjSAr34GdzknhnxQn+tTiLZ+5KQSUXMBz4GsHJC0Xi5HO2l+ARw+8GP82nJ7/hi7zFnG4p4s7oOaj6oSufPHYMxmNrMJ3ahXLQ/B6ts+NYFRaLyMQzXe/Ompt7qz0Z752GftlLSNyDUKT2rmzvUkg9Q9DM/QPG4xsxHl2JuSoX1fD7kEUOuyom/VeCpbEMw8FFWKrzkLj62TLsbpHvPjs3LoHejvzhoXTeXZHD/9bmUtnQyfwxEciCktDMexndtncJ27+CX8WN5EuNjg9zvmB80CjmREzvsbnyqr0lWKwic0eHA2BpKqerMptFkYG4KTTcHTPvhvs83koIgoAybQ6CQoMhcxWKtLm2CY8LdH/tK3NHh1Pd2MWibYX4eTqQEOqOYsBULDWnMBz4BqlPJC6eIbd8tpTFamFZwRo8VO6MDRyOcekfkPhEXnCiJaekCWeNgmCfi4tFZ1EOvRtLfRG6nf/DYd7LSJzPHVs4KRx5LPF+LFYL5R1VFLQWUdBazOHao+w5I1L5aLyJcg3rFqpclM6I+k70+77AXHQIiVcY6rGP9zlrDkBn1lHdWUd1Vw3VnbVUddZS01WL1qwD4PeDf9UrYWrjoXI2HCxnbIo/c0dd2Hj/RuRs+Z6dWweVQorBaAHVmc+r2Xh9A7oGCKJ4OTvV24empk6sVvvLcbsgWkx0fv4k8ogh5MWm82HOF/wi5bE+d167Eck83cB/lp/gR9NiSa/4AmtrDQ73/POyF5+GrHUYDy9hm3Uw+8UUXn5kMGpl/2vYpoL96Hd8gCx65EXLznpDW5eRQ7l17M+pobyuE6lEICncg+GJvgyI9EAu653/lCiKrC/dyvqSLSR7JvBIwr3IL/DaHTvdwNvLT/Dru1JICOtd6d1ZNpZuY03xJl4d+ccep8EbMlbYWjgPv++KZkbBVt5iOPgtlroCJK7+KIfciTR4AJmnG3hv5UnCA5xZ4FeBX9FKDMN+jFPMkAv6eVlFK+tLtrKxdBveGi8eTbyvT7OVP0S78V9YG0pxuO/1bp+Li2EyW3nu3X2E+jnz9EKb4fvZ1/fnAx4l7PhOzEWH0cz9I1LPkCuO7UJYWqrR7/oIa30R0uABqEY+hMSxb+dGf2LVtmI8stxmNKx0QJE+B3nc2Mu+pnbs9Cdmi5Wvtxaw81gVni4qnDQKVAopajkMMewntusIzUpflgRFUEIBnjJ/xnvMwkPjikohQ6WQnrnZ7p/NEKhu7OIPHx1iQlog957puKnd+g5f6ArJcVDwq7SfEe5ydT7zds5HFMWrJgDqDGb++uVRWtoN/OGhdHzcNVj1HWiX/RGkChzm/R/topmXDvyNNO8UHoi/86rEcT3ZU3WARfkreCzxAZL0FnQb30Q14afnGXsXVLby6leZyKUSfjEvicTwy3skWdvr6Vr+EhIXXzR3/L5HkxYWq4XKzmpOtxRR2FpMYWspeoseAG+5E6GtrYR3aomOGo/3wHk9bl5ispqp66qnuquW6s7a7r8thtbuZVRSFf6OPvg7+OLv6EewUyBhLsE92j7AvhM1fLQuj/RYb564I6HP3qB27PQHGw+Vs3hHIe/8ajSymuPIApP6Vdi/HkgkAh4eF7++sY9C7dy2WKpywaTvLt1zUjj2uevZjUpqlCcRAc6s3FPMoFnTETe9jun0PhSXKNMxlx/HeHgpFZo41lTG8Jv74q+KIAUgjxpu68h3dCVGZ2+UvTSb/iEuDgomDwpi8qAgKus72X+yloMna8kqbESjlDE80Zcpg4PxcOmZQbQgCMwIm4SDTMOSglW8c/wjfpL8I9Syc9fPyK/HQSUjJti1T3HrzQZym04T4OjXY0HKVHIUY+YqZNEjkSdM7NN+v4/UJxL1Hb/HXJqJ4fBidJveROoXS8rQu/nxHfF8tfYYTp0bOG3x5Z11Oli3C5VCiqujEldHBa6OSlzO/PV0TGaOvxdb6tfwj4y3uTNqNsP9B1/RxYkifhy6jW9iLj2GPHzQJZc9nFdHu9bUnXrfpGtmY+l2UrySiO7Qois8gGLg7KsmSAFI3fzR3PECppNbMBxeRtei55FFDEGRMAGpd/hV2+/FEM1GjNkbMWatA6sZedJklAPv6HHprB07/YlMKuHBKTGE+zlzvKgRvdGC3mimXWthsSGVMIszC8TdPHC6mfcVidQF1fBt5ScYCwdg7Tj/glomlaBSSLFaRZRyKTOHhwJgaa3mUMMJsn2cmRU+2S5IXWOuZkaaWinjqfnJ/PmzDN5als0LD6SjUTmhGv8EurV/R7/7E5wn/LQ7W2pK6PhbKltKa9Kxtngzka5hpHglotvwOoLGFVlY2rnL6c18sDoXTxcVaoWMfy/N5id3JJAee2lPNYmzN6oxj6Hf8jaGg4t6ZBgulUgJcQ4ixDmISSFjsVgtVLSUcCp7BQWtlWSrlRx2cIL2I3gdKj5T6mfLpHJTuWIVrTTrW7oznqo7a6nqqqVe24BVtNr2IUjx0XgR4RpKgIMf/o6++Dv64qZ07fP5llXQyCfrTxEf6sbjM+PtgpSd647qzKSv3mjBLTTtMkvfGthFKTu3LebSTJCrMPiEcrLoG0YFDENymbbENxuCILBwbCSvfpXJjmonxniFYcxahzxm1AVnqKytNei2v4/B0Z9/l6cyZUgI0UGuVzVGxcDZWNvqMGYsR+LsjTyy5x3vLkWgtyN3ekeyYEwEeWUt7DtRw45jVew4VsWwBF+mDQ3Gz6NnF+Rjg0agkav5Im8xbx37Lz8b8Gi3eGQyW8kqbCQtxvuS9fx6s54GXTMNukYatI3U6xpp0DbRoGuk3dgBwITg0T2Kx9JcZetg6BWOauSD/TbwFwQBeVgaspABmPJ2Yjy6Cu2K/yMpciivpApYi404Db+fRwUPWjsNtHYaaTvzt7CqjdZOI2aL9bsNygahiMjm6/xlLM44hG/XENwdHXFxUODhoiIt2qvHHeSkgckIjh6Y8nZeUpQSRZGtGZX4ezoQH2prab20YA0CMD94PPrV/0DiEYQi9cKlq/2JIJGgSJqCLGQgxhMbMZ3eh7lgHxKvcBQJE5BFDL7qJXOiKGIuOojh0BLErmZkoWkoh9yJxKX/zOjt2OkrI5P9GHnBjq7DsbZPQbvlHZ5pyqRaPoqvZI00x2UwyHUUsap0DCZrt5hl+2u7nxrl1V22XXlsBau8nIhyDrmpu+rauTBermp+PjeR1xZl8f7qHJ5eMACZXwyK9LkYjyzD5B/HxAibt9Sm0u23VLbUxtJtdJm0LIi6A2trDZbKHBTp887Lev1ycz4tHQZ+98BA/Nw1vLk0m/dW5fCQIZbRAy5dOicPS8OSNAXTiU1IfWOQRwzuVYxiTT6euz5iRFcz4wbMQDZwFlW6BgpaiiloLeZYQw77a44A4KZ0RWvWYrB8V6bkoXLH39GXAZ4JNvHJwRcfjVePS3l7Qn55C++tyiHE15FfzEtCLru1rgPs3Jx8J0qZgSu3wbgZsItSdm5LRKsVc9kxZEHJHGs6hVm0MMi3d529bhaig1wZEOHBuoPljJo+FXa9h7n4yHnij2jUotv0b0RBxttNo/DxcmHuqKuf0SEIAqoxj6Draka/60MERw9kvlH9sm3RZMDaVE5UVynhzqUsHBfIhpZwdmfXsO9EDWmx3swYGtJthnspBvsORCNT82HOF/wr8z1+kfIY7io3ckub0RkspMd4nxGemmjQNVGvbTxHgOowdp6zPReFE55qTxI8YvFSe+Cl8STePebyx6TvRLf53wgyJerJT16VdF5BIkORMBF51AiMWeswntgEFhOKuHFEJydysQJXURTRGsy0dhpp7TTQ1mmgpSOOnK5DlDtmUqveRFNVOp2nNRjNVhZtKyAhzJ3Ryf6kRHleUtQTJBKbt1TGcqxtdRcVVQoq2yir6+DBKTEIgkBOYx7ZjSeZHTEN9dG1mPWdqKc90ysPsytF4uyFasQDKActwFSwD9PJbeh3/g/h4CLksWOQx49D4tj/LactdYXoD3yNtb4YiUcIqnGPI/OP6/f92LFzNZA4e+Mw+wUMBxfhn7udp32jWBEcy+Hm3Wg9Gngo/i408ou3yDa01fClvgi5UsmPku6/5Sad7NiICXbjvsnRfL4xnyU7C7lrfBSKlBlYavIxHPgKR58IRgYMZVfl/lsmW6pe28DOyn0M80snyCkA/d7PQSo7r1nFgZxaDubWMXdUGBH+tqYbv74zhXdWnODTDafQGcxMGXzpEjflkIVY6ovQ7/4YqUcwEtfLd6MTTQYMhxdjOrkNwcUXzR0vIPWxVSIEOwUS7BTIhODRWEUrVZ21FLQWUdpWjpPC8Uz5nS9+Dj6oZD2btOor5XUdvLUsG08XFU8vHIBKYb8stnNjcPZc1Bst1zmSa4fdU+p72D2lbh/MtafRrf4rqgk/5d3247ToW3hp6PO3rPlpZUMnL310mCmDgpjR9AlIJGjm/7n7eEWrFd3mf2OpyGGj8wI2l6n4w0PpPTLE7C9EfSddq/4MBi2aOX/obg3c4/VNBixN5VgbS7E0lGBtLMXaWgNnv+IUGjBqkSdMxDhgAVuOVrE9sxKdwUJSuAczhvUsK6ywtYT3jn+CSqZkpP9Q9hcU0axvxsnNSIfpfOHJS+OJl9oTb7UnnhoP21+1R58MwEWrBd3Gf2GpPoVm1m+7B3lXG2tnE+aiQ8hjx/S53KuwtYRPTn5Np7GTuZEziXNIYV9OHftO1NDSYcBRLWd4oi8jk/0IvIhpp1XbStdXzyBPmnJeq+qzvLviBHllLbz28xFIJFb+cuh1pBIpz/mMwbzlXRQDZ6NMn9unY+gvRFHEUpWL6eRWzOVZAMhCBiJPnIjUL/aKv4esHY0YDi3GXHwYQeNq6wwYPeKc7kZ27NxMmAoPoN/9KcgUHEkdzcrGTFyVLjyWdD/BToEXXOfbnX9nt7WJH0fNZ0DQkAsuY+fW4cvN+WzPrOLRGXGMSPLDqmu3+UvJVZhnPMP/Zbx5y3hLvZ/9KQUtRfxx6PM4C1I6v/wVsvB01GMf716mvlXH/318mGBvR56/d+A5JWlmi5UP1uSScaqemcNDmTsq7JK/O9bOJrTLXkJwcEUz54+XnAyz1Bag2/khYnsd8sRJKAcvQOiHhif9TX2Llr9+mYlUIvD7+9N6bOtgx8614FRZC//45hjP3Z1CXOj19yPtD+yeUnbsXABzaSZIZHR6h1JQtpxpoRNuWUEKINDLkeGJvmzNrGLS5MnIDn2Kpfw4spAUAIwZy7GUH6cybDYbjipZODb8mgpSYOsGp5n6DNqVf0a34Q00s19EUF34y+tyApSgdkHiFYoibBBSr1AknqEIGlcMh77FlL0RuaGLeWMfZdqQEHYcq2TzkQpe/SqTqEAXZgwLJSnc/aLnQ6RrGE8PfIJ3j3/E2pJNICpxVLuS5BmBl9rzjAjl0Wfh6VIYDi/BUpmDcvTD10yQApA4eqAYMP2KthHpGsbvBj3N53nfsqRgFQO8ipg3aAZzRoaRU9LMnuxqth21vRdhfs6MGuDHkDifc/zMJBpXZCGpmPP3IA6ad17pW1ObnszTjUwZHIRSLmVdyXYa9c08GX8/li0fIvEIviZle5dDEARkgQnIAhOwdjRgyt2B6dRuzKVHkbj5I0+YiDxqOIK8d4Nk0ag7k9m2EZCgGDjb1vWql9uxY+dGQx45DIlnCPot7zDowHoCksfxuaWC14++y53Rsxnud65n3YmqI+y2NjFCcLMLUrcJd0+IoqZJy2cbT+HjriEywMXmL7Xu7ygPr2Bk4FB2Vd382VKnmgs40ZjL7IhpuCidbJnMZgOKhO+anZgtVj5YfRKJIPD4rPNNu2VSCU/ckcBnCilr95ei05u5Z1IUkouMeySOHqjG/Rjdxjcw7PsS1ZhHzltGtJgwZqzAmL0BwcEd9czf3LCZua2dBl7/NgurVeT5e1LtgpSdGw6V8jtPqdsFe6bU97gVMqX2VR+itqueeZEzb2mR5UoQRZGuRc8jcfXjQEI6ywvX8sehz+Gj8br8yjcxTW16fvfBQYbFebKw/RMEBzc0d7yAufgI+m3vYgkfyQsnIgnycjpvVu1aYq49jW7tP5D6RKCe/hxYLd8ToEqxNpZcUICSetpuEq9QJA5uF9y2KIoYs9ZiPLIMaXAK6ok/Q5ApMJgs7DlezcbD5TS3Gwj2dmTG8FDSor0u+jqYrWZOFDfw9tI8npqfTErU1R3knu1UKI8fj2rkg1d1X1cTq2hle8Ue1hRtxCJaSfMZwKTgsQQ6+dOuNXIwp5Y92TVUNXahkEsYFOPNyGQ/ooNsJqbmyhx0619DNf4nyCOHnbPtJTsK2XS4gr8/MQxR0cWfD73OAM8E7qnrwFx8BM28l5B69Lwbz7VENBsxFx3CeHIr1sYykKuRx4xEET/hsuUSotWKKX83xozliLp2ZFHDUQ5acEN0+7Njpz8RTQb0ez/HXLAPXUAc3/o6c6qthKG+6dwVMweFVEGboZ2/7nsVR4Oe54c9i9K17y3n7dxcdOpM/OWzDPQmC398KB13ZxWGzFUYM1agH3EPrzTsuqmzpSxWC68e+TcGi5E/DPk1MkFK17e/QaJxRTP7he7llu8uZu3+Up6YncDguIv7B4qiyOIzv5vDEnx4ZEYcUsnFM2oNh5dizFqLauxjyKNHfhdXYyn6Hf/D2lKFPHYMyqF3IyjU/XPQ/YxWb+LVr47R0KrjuXtSCfd3vt4h2bFzHnXNWn73wUEenxnPsMTLl8zeDNgzpW4zzl7wuavcGBc08vIr3IZYWyoROxqQpcwgo+4YwU6Bt7wgBeDhomJCWgCbj1QwY8x41NlLMJ3ciuHwEiQ+Ufy3bgBWUcuj17nziMw3GtXYR9Fv/y9d3zyLqGv7ngDljMQrzJYBdUaAEjQ977giCALK1FkISgcMe79At+F11FOeRqlQMzE9iLGpARw8Wcf6g2W8tzIHH3cN04cEMyzR9zy/I5lExvGCVlQKKQlhFxbB+gtLYyn63Z8g9YtBOfzeq7qvq41EkDAxeAzpPinsqNjLnqoDZNRlEe8ew+SQsUwaFM6kQUEU17Sz53gNh/Pq2JdTi4+bmpHJfoxIjEDm7G0zPP+eKGUwWth9vJqB0Z54uKh47/g3SAQJs5TBmIs+QpE294YVpAAEmQJ5zChk0SOx1hdhPLkNU+52TDlbkAYmokiYiDQoGeEHFwzmypMYDn6DtbkSqW80yilPX5fufnbsXAsEuRLV2Mcw+UXDvi95qMWBnclD2FSbQUVnFY8m3s+3eUsxWE08oQy3C1K3GY5qOU8uSOaVzzN4e9kJfnv/QBQps7DU5KM6uIwRg8eyuy7zps2W2l9zmOquWh5LfAC5VI65LAuxowH54IXdy+SXt7DuQCkjk/wuKUiBbUx057hINCo5K3YXozdaeGJ2AnLZhY3EFelzbV6Fez5H4hmKxNUX47F1GDNXI6idUE99Bllwcr8ec39iMFn499Jsapq6eHrhALsgZeeG5Vyj89sDe6bU97gVMqVEUeS/Jz4lt+k0v077GSHOQdc7pBsOw9FV/H97dx4XVbn/AfxzZh9AZXcX3EVQUVDDNXMXXEJTs/De1NRuN836ZdmtbM/Km2V5s+7tttyy1HJJU9u13BcUXFBxARQU2QVmn3l+fxikOKicGQaEz/v18iXMjJ95zsh3zjNfznmO5cA6lIx/Fi8nLcf4dnG46xavena7KzFa8eTynejcwgd/MX0KYbwMydsfe0Nn4PPfL+KvI29+NRZPsaRshT0jCYqAVrIaUDdjPbUbpl//DUVAC+hHPg6F/s/JicMhkHgyBxt3pSEjuwR+DbQY0bsVBnRrBq36yo7C7nBg3rs7ENHaHzPHhLtlTM44jJdhWPM8AMAr/vlrxlkXGKwG/Ja5G7+e+x0l1lK0btgKQ0MGoUtgGBSSAmaLHftPXMLvSVk4eb4ICknClGan0dO4Hdr4l6AJvPIet/VgJj77/gQW3N8DJl0Wlid/gnEhQxCzcyMkLz943f3sdVclqu0chiJYj2+DNeVXiNICSA2CoOl8F9Qd+0OYimHa/RXsGUmQGgRB23siVK2jeYQs1Rv2vAwYf1wGUZyDM5GD8LnxNEx2ExzCgfhLxbhz+LNQ+tWO/Rl5VvLpXLyzOhnRnYIxe2w4hPEyDN88i2KdN14Pkm7Lo6UMViNe2P0Gmno3xtzusyBJEgzfvQlHYRa8730TkkKFUpMVC/+7F2qlAgsf6Fmlhbt/PnAeX/x4EmEhfvh7fJdrTp2/msNQeGWtLo0XJLUOjtw0qNrFQNfnvkqXXKgNbHYHlq05jOTTeZh1kyPIiGqa2WLHQ29tw4Q722LUHSE1PRy3uNmRUlz1tI6RJAkJYZPQUNMAHx35HAarsaaHVOvY0g5A2bgdDhSdggQJUY0ja3pIHuOjV2PUHSE4cLoIhaGDAbUOxT2n46udlxDZLhD9nV6au2Zowu6EfvhcaKPvhiq0OxTefm79wK1udwf0w+fCUXABxm9fhaMkr/w+hUJCdKdgLPxrT8yb2A1BjXT48qdUPPGvndi4Mw0GkxUnMgpRYrQiqmPVFmSvCuGwwfTTMghTCfTD59S5hhQAeKm9MCL0LrzU52lM6nA3LltK8OHhT/HKnrew68J+KFUCfbs0xVP3R+HVmXdgeO+W+LkwBDahwNZVX2HVr6dwIa8UPx04j5AmDdCqiR6rT65HE+/GiEk7BWEuhe7OGbddQwoAFF6NoO0xBt73vgndkIeh8PGHec9KlHwxD6Wrn4H9wkloe0+E9z2vQN2mJxtSVK8oA1rBO/55qEJ7oM3Bn/GowQdtfJojusSCmIDObEjVY13bBmLCoLbYd/wSNuxMg8LryvpSPgUXcYfDB3uzE3HJkFvTw6ySzWk/odRqwPj2oyFJEuwFmbBnHoW6812QFCoIIfDZlhMoKrFg5pjwKl9JbnBUCzwY1xknMgqx+KtDKDFanT5O4eUL3eCHIC5nQ5TkQTfkYejvmlWrG1IOIfDJ5uNIOp2H+4d1YEOKaj2NWgFJ4pFS9VZdOFKqzJmidCxJfB9dAztjRkQCP6z8wVGcg9Ivn4Cm10S8ajyMAJ0f5nSfWdPD8iiz1Y6nPtiFIF89nrgnAq98kYSCEjNemt4bDb0rv6JKXWW7eBLGLUsgqfXwin0CCl/njbmT5wqxaXc6kk/nQa9Vwr+hDrmFJrwzpx80aueHurvKtP0zWI/9At1ds6Fud0e1PEdtY3fYcfBSMn7I2IrMkgvw1TbC4FYD0Kdpr/KF4+0OB7K/fRfanGN4Jn8CzOLK6z8jLgz5XsnYnPYzHm5yJ1puXwVN9N3Q9hhbk5vkVvb8c7Ae2wooVdBExtbJRiVRVQghrpyKvvsrQJIAuw1e8S9AGVg3frtM8ggh8J+NKdh19CIevjsCUR2DYd6/FrlJG/Bm62BENekh+2gpi92KQnMhCs1FKDAVocBciAJTIdRKNcIDOqG9bxuo3PiLkGxDDl7e80/c0SQK94VdOVXPtP0zWE/8Bu8pb0Ghb4jfk7Pw8abjLh9ZcfBkDt5ffxSN/fR4bFIk/Bo4v2CLPTcNkk8AFDrPXhSnqoQQWPnLKfyw7xzG9W+NMX1b1/SQiG7Jw0u2oW9EU0wZ2qGmh+IWXFOqnmrTKARj247E2lPfYdv5nbizZd+aHlKtYEtLBABkBjdD7vGtGBFyVw2PyPO0aiXG9muNz7acwJJvjiLjUgkeie9SLxtSwJU1rLxGL4Bx02IYvn0V+lGPQxkYet3jOrT0RYeWvki/WIxNu9Ox//gl9A5vXG0NKcvxbbAe+wXqriPrTUMKAJQKJaKbdEdU40gcyz+JH9N/xTepG7Dl7M8Y2KIPBrboCx+NN4J7j4Bxw0EsGqnCTkMbZBcYEBqixMr9WxEdGI5W+zdDCgyBJjK2pjfJrZT+LaHsl1DTwyCqNSRJgiZiKJTBbWD86V9QBrVmQ4ogSRL+OrIjLhUY8O+NxxDkq0fLHmPhd+EEehVlYRcOOF1byu6wX2k2mYtQYCr8o+F0pfFUaCpEgbkIJdbS657PR+0Ns92MX89th06pRZh/B3QJ7IzwgE7w0Xi7tC1rT30HjUKNuDYjAADCXArrye1QtY2BQt8Q2fkGrPgxFZ1a+WJEb9fWTuzeIQjzJnbD0m+SseiLA3h8cncE+16/aLmzeVJttGl3On7Ydw6Do1pgdJ/Qmh4O0S3TaVS8+l59VZeOlAK4vpQzhg2vQZhKsalbT2zP2oNF/Z6FXlU7rxBSnewOB575z15k5xvQr0tTTIutnZft9SRH0UUYvnsTwlwK/fBHoWrW6YaPLyg2Q69VVvkQ+Vthv5gKw8ZFUDYLg37EY9ctbl3fnClKx4/pW5GcexQahRp9mvXCXS37Q7dhMaDRwXvccxBC4F/J/8WZwjQ8YQ2Cd1oSvOKfh9Kf73tE9YUQDkCg3r9n0p8KS8x46dP9UEjAs3/pCR+U4uLa5/B6Uz3a+LZG8wbNr2k8FVtKIHDtZwG9Sg8/bSP46hrBT+t75U/Z17pG8NX6QqNUw2K34ETBKRzOPYYjuSko/5H+8wAAM4pJREFUshRDgoTWjULQJTAMXQI7o4lXcJXOXjien4p3D/0bY9uOxLCQQQAAS/IWmHd/Ba/4FyD8WuLV/x1ATqERL0zrBf+GOre8bmeyLmPJqkNQqRT4v0mRaB5Ue0/Pq8xvSVn4ZPNx3NG5MWaM7gwFzxqh28g//r0bzQO98be7u9T0UNziZkdKsSl1lbrWlAKAUqsBr+19GwpJgad6zoWXuv41YMo4jJdR+vlcKCPj8KL5KNo2ao0Hu9TfIw5OZBTg5wPn8cCosEoXtKxvHKUFMH73JhzFOdAPeRiqkMgaGYNhzfOAWgvvuxdC0rr2G9a65EJpNn5K34a92VeOeOyhCUa/1KNoE/ccDoti/PvwZxjn1w137PsRmuh4aHuMqeERExFRTUu7eBmLPk9ESJMGeOLe7sCFY1izZzm2+XlBo9DAT+cLP22jCn+XNZwaQaeqeqPHIRw4V5yJw7kpOJJ7DOdKsgAAgTp/dAnsjIjAMLTzbX3D0/zsDjsW7XsHZrsFz/Z+HGqlGsLhQOnKJ6Hw9oPXmKfx9dbT2LQ7vfwURXfKzCnB4pWHYLM5MG9i5G11tboDJy7hX+uOILy1P+aM73rdFZSJaruXPt0Pb50Kj02KrOmhuAWbUlVQF5tSANeXKmM9/htMv/0X6UOn4/2zG/BgRAIig+tG95ncx2EqhnHzW3DkpkN35wyo2/fx2HMLmwWGDYvgKMyC19hnofRv7rHnvp0UmArx87nfsCNzDywOKzpLDXBBo4ReqcHfT6ZD5RMAr3HPQlJUz6mVRER0e9mbko3l64+if9em+OvITjAfWI/ig+uh8wmALuZeqEJ6VOv8uMBUiCN5KTicm4ITBadgc9igU+oQFtABXQLCEB7YCT7qa38J9XvmLnx1Yi1mRCSg+x/zVVvaQRh/eAe6IQ/jlLIdFn95EP27NcNfR9746G65LhUasfjLgyg2WjFnfFeEhfhVy/O4yiEEMrKLcfRsPo6lFeDkuUKENm2A/5vUHVoN5wJ0+3nzy4Ow2Oz4R0J0TQ/FLbimFHF9qT9Y0xIh+QQg0ZgFvUqH8IDq2YHT7U2hawCv2Pkw/rAUpl8/hDAboIkYUu3PK4SAaftncOScgW7YI2xI3YCfzhcT2o/BiNDB+Hn7u9huy4VBKDDZ0RgKi/GPq+1xEkpERFf0CmuM8zml2LgzDS2CfTA0ehxUTTvAvPMLmH54F8oWEdD2mQKlb/VctdFP54v+zWPQv3kMzHYLjuen4kjuMRzOS8HBS8mQIKFNoxB0CeyMLoFhaKhpiI1nfkB73zaIDIooz7Ec/RGStz9MjbvgP58cQGN/L9w7uH21jBkAgn31WHB/FN5aeQhLViXhoXHh6N4+qNqerypyi4w4llaAo2fzkZJeUH7FwBZBPhjasyViY0LYkKLblk6jxGWDpaaH4TFsStUTd7Xsj9SCM1hzaiNaN2pV79aXElYT7JlHgE4DkZRzBN2Du0KtVNf0sKiWkjR66EfMg+mX5TDv/BzCXApNjzHV9ltUYbPAcuQH2E5uh6bHWKhDo6rleeoaH7U34jpPQL9vX0ZRq84ISj8MTc/xUPq3qOmhERFRLTOuf2tk5pTgq59T0SzAG+GtO0M5/gVYj/0K8/41MKx+FuouQ6HtMRaSpvqWu9AqNegWFI5uQeFXneZ3DIdzU7Du9CasO70JepUOJpsZ49uPLp972PMzYc88Bk3PCfj396m4XGrBM1Ojq73x4tdAiyfv64Elq5KwbM0RTI8NQ0xEk2p9TmcMJhuOZxTgaFo+jp3NR3aBEQDQyEeDbm0D0Lm1PzqH+KGRj/MrBhLdTnQaFUzm+rPQOZtS9YRCUiCh80Qs2vsOPjryRb1bX8p27jBgt+F4QABMWWb0bNy9podEtZyk0kA35GGYfvsYlgNrIcwl0MbcC0lyfV0CYbfBfuk07FnHYc9Kgf3SKcBugyq0BzRRY90w+vpDEdwWOv+W0KQfgyKoNTTdRtX0kIiIqBZSSBIeHN0Zr/7vAN5fdwTP/CUaTfy9oIkYClXb3rDs+xrW5O9hS90Jba97oOrQ1y37/BuPSYGQhi0R0rAl4toMR4GpEIdzU3A0LwUhDVuiZYM/j5q2Hv0RUKqxz9YBiSfPY+Kgdghp0qBax1fGR6/G/02OxHtrDuPfG4/BYLZhcFT1/gLIZnfgTNZlHEvLx9G0fJzNKoZDCGjVSnRs5YtBPVogPNQPzQK96+3SJFR36bRKmCy2mh6Gx3BNqavU1TWlrvbn+lLhmBFxf715Ezf+8gHs5w7ji8hopBefw8t9/wFFNU80qG4QwgHz7pWwHv4eqvZ9oRs4rcqnhgmHHY6cs7CVNaEupgJ2CwAJisBWUDYLg6pZJyhbREC6waKn5Jz15HaYtv8PXuOe42mPRER0Q7mFRrz46X546VR4bGI3BPt5ld9nv3QGpp1fwHHpNBTBbaDrcz+UwW1qcLRXCHMpSj6fB2vLaDyd3AHtWzTCvEmRHr+inNVmx/L1R3EwNRdN/L3grVNBr1PBS6uCl04N7z++/vM2Fby06j/+vvJ9ZYuOCyFwMd9Qvi7U8YwCmCx2SBIQ2qQhwlv7ITzUH22bN+LC5VTnrd56Cj/sPYd/zx9U00NxCy50XgX1oSkFAD9lbMPaU9/hng5jcWeLur++lLDbUPK/R2AJ6Y4XcBYDW/TB+Paja3pYdBsRQsBycAMs+9dAFdIdusEPQVJpKn+8wwFHfgbsmSmwZaXAfvEkYDUBABT+LaBsFgZls05QNe3Eq+u5gRACcNgg8ZRcIiK6Baczi/D26iRIkoRHxndB+xa+5fcJ4YAtdRfMe1ZCGIuh7tgfml4ToNDX3NXnLEmbYd6zEp+pJuJEcQO8MK0X/BrUzGlqdocD3+1Kx/mcUhhNVhjMNhhMNpSabDCabbDf5LOURq0ob2KVNarUKgXOXriM/MtmAECQrw7hof7oHOqPsFA/eOu4f6f6ZePONKz57Qw++L87oVbd/k1YLnRez1hPboc9PxPaXvdAUjj/AS5bX2pt6ka0blj315eyXzgOWIw4GuAHe+4pnrpHVSZJErQ9xkDSesO843MYtyyBftic8jUnhHDAUZB55XS8zGOwXTgBWAwAAEWjJlC3i4GyeRiUTTvV6KS2rpIkCWBDioiIblHb5o3wzNRovL06CW9+eRDTRoXhjvAr6yRJkgLqDn2hCu0Bc+J6WA//COvZfdBG3Q11+F0eP6JZOBywHP0JebpWOJClwyPjO9VYQwoAlAoFxvRt7fQ+IQQsVscfjao/G1YGk+362/74u6jUApPZhtZNGyIuxh+dW/sj2Lf+LDFC5Izuj7XijBYb1Df4RXhdwaZUXeNwwJq8GTCXQDvgAafnwte39aVsaYmASoNEay6CvQKvOT+fqCo04YMhab1h+vXfMGx8HeqO/WG/cBz2rOMQpmIAgNQgCOrW0VA26wRlszAovGvn5ZOJiIjqs8b+XvjH1GgsW3MYH244huwCI8b0DS1f2kLS6KG7YzLUnQbAvHMFzLtWwHp8G7R97oOqeWePjdOWcRCiJA/riiMwqHvzWnP1O2ckSYJWo4RWo6zRxhnR7U6nudKmMVnsaOh1kwfXAWxK1THqTgPgKMmDJXE9oNJC2+c+p+tG+ai9MS1iCpYkLscXx7+us+tLCeGALS0RJS3CcKooDaNaD6mT20meo253BySNDsYfl8G843+QvP2hbNn1yppQzcKgaBBY00MkIiKiW+CjV+PxyZH4dPNxrN9+Ftn5BjwwqhPUqj/XjlT6NoN+5OOwpR+EedeXMH73BlSto6G9Y7JH9vnGpB9QJHyQ17ATHrqrXbU/HxHVvLIjpUzm+rHYOZtSdZAmahyEzQxr8hZIai00PSc4bcS0aRSKMW1GYN3pTdiWubNOri/lyDkLYShEckB3iKILiOape+QGqlaR8J78BmCzQGoYzEYnERHRbUqlVGBabBiaBHjhm21nkFtkwt/Hd0FDrz9PmZEkCerQHlC1iIAleQssBzfClpEMTWQsNN1G3nCdSVfY8jIgZZ/AdlMUZt7bBVp11S60QkS3J532j6aUxV7DI/GM23/VLLqOJEnQ9p4EddggWA59B8vBDZU+dnCrAYgI6IS1qRuRcfm8B0fpGbazBwBJiURbHkIatkSwF49iIfdQePtB0agxG1JERES3OUmSEBsTiofGRSA9uxgvf7ofWbml1z9OpYG2xxh4T3oNqpBIWA6sRenqp2E9ewDVce2o9G3fwiKUaNxrGFoGV75IMBHVLVefvlcfsClVR0mSBG2/BKja94Fl/xpYDn/v9HFX1peaBB+NDz468jmMNqOHR1q9bGmJyG3eDudLL3KBcyIiIiKqVM9OwZg/pTssNgde+d8BHEvLd/o4hU8A9EP+Bn3ck5DUOph+fBeGNQth+v0TWI79Avul0xA2s0tjyczMhm/OQZzWhmHQHR1cyiKi24u+7PQ9S/04fY9NqTpMkhTQDZwOVetomHd9CUvKVqeP81F7Y3rEfcg3F+KLlK+r5Tc9NcFekAVH0UUkBfhBgoQewd1qekhEREREVIu1bdYIz0yNgn8DLZasSsK2Q5mVPlbVLAxe8S9A2zcBktYb1tN7Yd7+GQzrXkLJx7NRuvppGH/5AJbkzbBlHoMwldzSGKw2OxI3rYNGsqPjkHgelU1Uz9S3I6W4plQdJymU0N01G8YflsL8+6eQVBqo2/e57nFXry/1W+YuDGxx/WNuN7a0RAgAibZ8dPRrh0baBjU9JCIiIiKq5QIb6bHg/igsX38En245gewCIybc2RYKJ80hSaGEJnwwNOGDIYSAKMmDPS8djtwM2HPTYb9wArZTu/58vE8AlAGtoAgMgTIgBIrAVpC8/SFJEoQQSLtYjO92nMFoWzKMAW0R3KKNJzediGqB8jWluNA51RWSUgX90L/DuGUJTFv/A6g0ULeOvu5xg1sNQGrhGaxJ3YDWDVuhVcMWNTBa97GlHcD5JiHIMxdiVJthNT0cIiIiIrpNeOlUmHtPV6z4KRVb9mQgO9+AmaPDodVUvti4JEmQGgReuSpfaFT57Q5TMRy56XDkZcCemwFHXjps6YcA/HF2gtYHRZpgnChpiOPFPmiotMJfXwpdz1HVu5FEVCuVX32vnhwpxdP36glJpYF++FwogtvA9PP7sGUkX/cYhaTA1LC6sb6UoyQfjpyzSArwg1qhQregiJoeEhERERHdRpQKBe4f2gH3Dm6PQ6m5WLQiEQXFVV8rSqFrAFWLCGi6jYJ+8Gx4T3wNXn99H5d6zcG+hkOwu7gpigqK0EMcxlSf7bhbvweSTwBUIZHu3ygiqvWUCgXUKkW9aUrxSKl6RFLr4DViHgzfvQHjj+9CP/IxqJqFXfMYH403poXfh7cPLscXKV9jesT9t+V57Lb0RNgBHLIXICKwM/QqXU0PiYiIiIhuM5IkYWjPlgjy1eODb4/i5c/2Y+6ErmjVWN6yEAXFZmw/fAG/J2Uht8gEL20rxIT3QsduTeEbpIej8AIcuRlQ+LeApKj8qCwiqtt0GmW9WehcEnVlVWs3yMsrgcNR918Oh6kYxg2L4CjOhVfsE1A2bnfdY35M34p1pzdhUodxGFDF9aUcwgGz3QyjzQSTzQyT3fTH1yaY7RaE+XeAn87XTVvjnOG7N3Dcko+PGjkws8tUHilFRERERC7JyC7GO18nw2CyYdbYcES2C7ylf2ezO5B8Og+/JWXh8Jk8CAGEhfihf9em6NEhCBo1m09EdK0nl+9E22aNMHNMeE0PxWUKhYSAAJ9K7+eRUvWQQtcA+tgnYPj2NRg2/xNecU9BGRhyzWPK1pf6JnUDlJISkiTBZPujuWQ3V/q10WaE2W654fM30jTEY1F/Q6Dev1q2T5hLYc86jqSOHaGHAZ0DOlXL8xARERFR/dGqcQM8MzUaS79OxrvfJGPyXe0xJLpFpWcVXMw34PekLOw4chGXSy3w9dEgNiYE/bo0RbCfl4dHT0S3E71GVW9O3+ORUlepL0dKlXGU5MHw7auAzQL96Keg9Gt+zf0lllIs2vcOCsyF19yuVWqgU+qgV+mgU+mgU2r//FqlhV551dcqPXRKLXSqK48vtRrwQfIn8FLp8VjU39BI29Dt22U9uQOXt/0br7RvjqjG3XFf2AS3PwcRERER1U9mix0fbjiKg6m5GNSjOaYMaQ+l4spSvWarHfuPX8LvSVk4eb4ICklCt3YB6N+tGbq08S9/HBHRjSz6/AAkScKT9/Wo6aG47GZHSrEpdZX61pQCAEdR9pXGlCTBa/QCKBo1vuZ+k82EfFMhdCotdMorjSaF5NrO9GxRBpYe+hABOj882mM2fNTeLuVVZPzhXSQWn8UKPxXmdp+FDn5t3ZpPRERERPWbQwh8vfU0tuzJQEQbf8TFhGL3sWzsOXYRRrMdjf30GNCtGfpENEEjH21ND5eIbjNvr05CUYkFCx/oWdNDcRmbUlVQH5tSAGDPz4Rxw2uAWguvMU9D4RNQ7c95Iv8U/pX8XzT3aYo5kQ9C56aFyIXNjJJPH8FnbVoiS6PAS30WuNxEIyIiIiJyZtuhTPzv+5NwCAGNSoHoTsHo37UpOrT0vS0vFkREtcPy9UeQfrEYr82KqemhuOxmTSl+Wico/ZtDH/t/EBYDDBvfgMNQWO3P2dG/HaaF34dzxZlYnvwJLHarW3Jt54+iVFhxXJQgqnE3NqSIiIiIqNoMjGyOpxOiMD02DG/9vR9mxHVGx1Z+bEgRkUuuXH2vfqwp5fFP7CUlJYiLi8P58+evuf3zzz9HQkJC+fcpKSmIj4/H8OHD8Y9//AM225XLIWZlZeG+++7DiBEj8NBDD6G0tBQAcPnyZcycORMjR47Efffdh5ycHM9tVB2gDAyF18jHIQyFMH73Jhym4mp/zm5B4UgIm4jUwjP479HPYXe4XnS2tEQc8W0ABwR6Nu7uhlESEREREVWuTbOG6NulKbx0vIYUEbmHrh4tdO7RplRSUhLuvfdepKWlXXP7qVOn8OGHH15z2xNPPIHnnnsO33//PYQQWLVqFQDghRdewJQpU7BlyxZERETgX//6FwDg7bffRnR0NDZv3ox77rkHr7zyike2qS5RNm4H/YhH4bh8CcZNiyEshmp/zl5NemBSh3E4nJuCz1JWwiEcsrOEww57+iEk+fuiiVcwWvg0c+NIiYiIiIiIiKqfTqOE2WqvF8sLebQptWrVKixcuBDBwcHlt1ksFjz33HOYM2dO+W2ZmZkwmUyIjIwEAMTHx2PLli2wWq3Yt28fhg8ffs3tALB161aMHj0aABAXF4fffvsNVqt7TgmrT1TNwqAf+nc48s/DsPktCKvJrfnCSdNpQIs+GNNmBPZnH8LKk+sgd5kz+8WTKLAbcAYmRDfuzsOmiYiIiIiI6Laj01w58rI+HC3l0WNMnR299M9//hPjx49HixYtym+7dOkSgoKCyr8PCgpCdnY2CgoK4OPjA5VKdc3tFf+NSqWCj48P8vPz0bjxtVeTo5tTteoG3V2zYfr5XzB+/w70w+cCDjuE1QRhMQJW07VfW4wV7jNCWEx/fm01AX88BjYLlE06QNt7IpSN25U/57CQQTDaTPgxYyu8VHqMbTuyyuO2pSUiqaEXAKBnk0h3vRxEREREREREHqPTKgEAJoutzp8aXKNbt2PHDly4cAELFizAnj17ym93OBzXHOUihIAkSeV/X62yo2GEEFAouMi1XOo2PQHbDJi2/gclH8++tX+kVEFS6wG1DpJGD0mtg6RvBEWjJpDUOkCjhyQpYD25A4b1L0MVGgVtr3ug8G0CSZIwtu1IGG1G/JD+K/RKHYaFDrrl8QohYEtLxKHGDdG6YTME6qv/CoJERERERERE7qbTlDWleKRUtdq4cSNSU1MxduxYGAwG5Obm4tFHH8UTTzxxzULlubm5CA4Ohr+/P4qLi2G326FUKpGTk1N+KmBwcDByc3PRpEkT2Gw2lJaWwtfXt4a2rG5Qd+gLSdcA9pyzkDS6K80mtf6Pr6/8Lf1xG9Q6SMpb+3HS9BgDS/L3sCRvhm31QajD7oSmx1govBphUse7YbKbsf7MZujVOvRvfmuXwHTkpeOCpRAXpADc04QLnBMREREREdHtiafvechrr71W/vWePXvw3nvv4e233wYAaLVaHDhwAFFRUVi/fj0GDBgAtVqN6OhobNq0CaNHj8a6deswYMAAAMDAgQOxbt06zJ49G5s2bUJ0dDTUanVNbFadomrVFapWXd2aKal10EaNhTrsTlgS18OashXW1J3QdB0JTdfhmBo2CSabCStPrINOqUPPW2gy2c4ewKEGeiggoUewe8dLRERERERE5Cl6zZ+n79V1tfb8tsWLF+O1117DiBEjYDAYMHXqVADAwoULsWrVKowaNQr79+/Ho48+CgCYO3cuDh06hNjYWKxYsQLPPfdcDY6eboXCqxF0/abC+55XoGoeDsuBtSj96knYT/yOaZ2noJ1va3yWshKHc4/dNMuadgBJjXzQ0b89GmoaeGD0RERERERERO5Xn46UkoTcS53VQXl5JfXikou1lf1iKsx7VsGenQqFb1OI6Lvxr7zdyCy9iIe7TUMHv3ZO/52j6CKOrn8Wy1v4YWrYJPRuGuXhkRMRERERERG5h9Fsw5tfHsS02DC0CPKp6eG4RKGQEBBQ+TawKXUVNqVqnhACtvREmPeshii6CFOTdlgeoESBrRRzus9EaMNW1/0bS9ImrDy9CQf8G2JRv+egU+lqYOREREREREREdLWbNaVq7el7VD9JkgR1aBS873kZ2n5ToS+6hGnHU+Fjc2DZwf8gq+Tidf/GlHYAhxt6oWtgOBtSRERERERERLcJNqWoVpIUKmg63wXvyW8gMHIMpmfmQ2U2YOnepcguSCt/nMNQiBPF51GqAKIbR9bYeImIiIiIiIioatiUolrtypX6xqHlhEWYpWsPu92Cd/e9h+z9qyGsZtjSDuJQAy28lFp0DuhY08MlIiIiIiIiolvENaWuwjWlar+0zINYevwrNLJaMTvfAY1SixcCBXo174UpnSbU9PCIiIiIiIiI6A9cU4rqlNDm3fFQj5ko0GrxUZAO+0URrBLQs3GPmh4aEREREREREVUBm1J022nv1xYzukzFBRWwPrgh/LSN0NY3tKaHRURERERERERVwKYU3ZYiAsPwl86TAUjo1SQKCok/ykRERERERES3E64pdRWuKXX7yTHkwV/nC6VCWdNDISIiIiIiIqKr3GxNKZUHx0LkdkFeATU9BCIiIiIiIiKSgec8ERERERERERGRx7EpRUREREREREREHsemFBEREREREREReRybUkRERERERERE5HFsShERERERERERkcexKUVERERERERERB7HphQREREREREREXkcm1JERERERERERORxbEoREREREREREZHHsSlFREREREREREQex6YUERERERERERF5HJtSRERERERERETkcWxKERERERERERGRx7EpRUREREREREREHsemFBEREREREREReRybUkRERERERERE5HGqmh5AbaJQSDU9BCIiIiIiIiKiOuFmfRZJCCE8NBYiIiIiIiIiIiIAPH2PiIiIiIiIiIhqAJtSRERERERERETkcWxKERERERERERGRx7EpRUREREREREREHsemFBEREREREREReRybUkRERERERERE5HFsShERERERERERkcexKUVERERERERERB7HphQREREREREREXkcm1JERERERERERORxbErVMSUlJYiLi8P58+ddznrvvfcQGxuL2NhYvPHGGy7nvfPOOxg1ahRiY2Px8ccfu5xX5vXXX8dTTz3lck5CQgJiY2MxduxYjB07FklJSS7l/fLLL4iPj8fIkSPx8ssvu5S1evXq8nGNHTsWUVFRePHFF13KXL9+ffn/7+uvv+5SFgB8+OGHGD58OEaPHo33339fVkbFn9+dO3di9OjRGDZsGJYsWeJyHgDMnz8fa9asccv4Vq5cibi4OIwePRoLFiyAxWJxKW/FihWIjY3FqFGj8Prrr0MI4VJemc8//xwJCQlVynKWt2DBAgwbNqz85/DHH390Ke/gwYOYOHEiYmNj8dhjj1Xp9bs6a9u2bdfUxx133IFZs2a5NLbt27djzJgxiIuLw/z5813+v12zZg1GjRqF0aNH4+WXX4bNZrvlLGfvxa7URmXv7VarFX/5y1+wZ88el/NcqQ1nea7Uxo32ZXJqw1meK7XhLE9ubVTMcrU2nI3NldpwludKbTibV7hSG5XNU+TWhrM8V2rDWZ4rtXGjeZmc2nCW50ptOMtzZb9RMc+V+nA2Nldqw1meK7VR5uo5sqtzqop5gPzacJbn6pyqYp6rc6qKeWXkzqmuznJ1PlUxz5W6qJjnjjlVxfG5OqeqmOdKbTj7vOdKbVT2+VFubTjLc0dt1HqC6oxDhw6JuLg4ER4eLs6dO+dS1o4dO8SkSZOE2WwWFotFTJ06Vfzwww+y8/bs2SMmT54srFarMBqNYtCgQeL06dMujVEIIXbu3Cl69+4tnnzySZdyHA6H6Nevn7BarS6PSQghMjIyRL9+/cSFCxeExWIR9957r9i6datbsk+ePCmGDh0q8vLyZGcYDAbRs2dPkZeXJ6xWq5gwYYLYsWOH7LwdO3aIuLg4UVxcLGw2m5g1a5b4/vvvq5RR8efXaDSKgQMHioyMDGG1WsW0adOq9BpWzLt48aKYNWuW6Nq1q/jmm2+quonX5Z05c0YMHTpUFBcXC4fDIebPny8+/vhj2XkZGRli6NChorS0VNhsNjFp0iTx+++/y84rk5qaKvr37y/uv//+qmyu07y4uDiRnZ1dpZzK8oqLi0Xfvn1FSkqKEEKIefPmiS+++EL22MpcunRJDB48WJw9e1b22IQQYsCAAeLUqVNCCCEeeeQRsWrVKtl5p0+fFv379y9/7RYuXCj++9//3lKWs/fiDRs2yK6Nyt7bT58+LSZNmiS6dOkidu/efcvb6izvgw8+kF0bzvI+/vhj2bVxo32ZnNqoLE9ubTjLW7NmjazauNl+u6q1UVme3Nqo7GdFbm04m1ekpKTIro3K5ilya6OyPLm1caM8ObVxo3mZnNqoLE9ubVT2/yt3v3GzeWhV6qOyLLm1UVme3Nooc/Uc2dU5VcU8IYTs2nCW5+qcqmKeq3Oqinll5M6pKma5Mp+qmOfKfKqy8ZWRM6dylufKnKpiniu14ezzniu1UdnnR7m14SzPHbVxO+CRUnXIqlWrsHDhQgQHB7ucFRQUhKeeegoajQZqtRpt27ZFVlaW7LxevXrhs88+g0qlQl5eHux2O7y8vFwaY2FhIZYsWYLZs2e7lAMAZ86cAQBMmzYNY8aMweeff+5S3o8//ohRo0ahSZMmUKvVWLJkCbp16+byOAHg+eefx7x58+Dv7y87w263w+FwwGg0wmazwWazQavVys47duwY+vXrBx8fHyiVSvTv3x8//fRTlTIq/vwmJycjJCQELVu2hEqlwujRo7FlyxbZeRs2bMDgwYMxcuTIKo2rsjyNRoOFCxfCx8cHkiShQ4cOVaqRinktW7bEd999By8vL1y+fBklJSVo2LCh7DwAsFgseO655zBnzpxbzqksz2g0IisrC08//TRGjx6NpUuXwuFwyM7bsWMHIiMj0alTJwDAM888g6FDh8rKutobb7yByZMnIzQ0VPbYgCs1UlJSArvdDrPZXKX6qJh34sQJREZGln8/aNCgW64PZ+/FaWlpsmujsvf2r7/+GjNmzKjy+5SzPIvFIrs2nOVJkiS7NirbXrm1UVme3NpwlpeZmSmrNm62365qbVSWJ7c2KvtZkVsbzuYVly9fll0blc1T5NaGszytViu7Niobn9zaqCxPbm04y9PpdLJrw1leSkqK7P3GzeahVamPyrLk1oazvOTkZNm1AVw/R3Z1TuVszi23NpzluTqnqpjn6pzK2fbKrY2KWa7OpyrmuTKfcpZ3NTlzKmd5rsypKua5Mqdy9nnPldqo7POj3Npwludqbdwu2JSqQ1555RVER0e7Jat9+/aIjIwEAKSlpWHz5s0YOHCgS5lqtRpLly5FbGwsYmJi0LhxY5fynnvuOcybN69KO5nKXL58GTExMVi2bBk++eQTfPXVV9ixY4fsvPT0dNjtdsyePRtjx47FihUr0KhRI5fHuXPnTphMJtmNlTI+Pj6YO3cuRo4ciYEDB6J58+bo0aOH7Lzw8HBs374dhYWFMJvN+OWXX5Cbm1uljIo/v5cuXUJQUFD598HBwcjOzpadN2PGDNxzzz1VGtON8po3b46+ffsCAPLz8/HFF19g8ODBsvOAKzWyatUqDBkyBEFBQeUTDLl5//znPzF+/Hi0bNnylnMqy8vNzcUdd9yBV199FatWrcL+/fvx9ddfy85LT0+Hl5cX5s2bh7Fjx+Ldd9+95Vqu7L0uLS0Ne/fuxdSpU295XJXlPf/880hISED//v1RUFCAESNGyM7r1KkTkpKScOHCBdjtdmzZsuWW68PZe7EkSbJro7L39vnz52PIkCG3toE3yYuLi5NdG5WNT25tVJYntzac5fXv3192bTjL02g0smrjRvttObVRWZ7c2nCWN2rUKNm1AVw/r3B1v+FsniK3NpzlNWvWzKX9hrPxubLfcJbnyn6jYp7NZnNpv1ExLycnR/Z+o7LtBeTVh7MsV/YbFfO6du3qUm1UnCO7WhvO5tyu1EbFPFfnVM7G50ptOMuTWxsVs1ydT1XMc2U+5SyvjNw5lbM8V2qjYp4rcypnn/eysrJk10Zlnx/l1oazvLS0NJdq43bBphTdUGpqKqZNm4b58+dXqUtemTlz5mDXrl24cOECVq1aJTtn9erVaNq0KWJiYlweEwB0794db7zxBho0aAB/f39MmDAB27Ztk51nt9uxa9cuvPrqq1i5ciWSk5Oxdu1al8f51Vdf4YEHHnA55/jx4/jmm2/w66+/4vfff4dCocBHH30kOy8mJgbx8fFISEjAjBkzEBUVBbVa7dIYHQ4HJEkq/14Icc33tUV2djb+8pe/YPz48ejdu7fLeRMnTsSePXsQGBiI9957T3bOjh07cOHCBYwfP97lMQFXfuu4bNkyBAcHQ6/XIyEhweUa2b59Ox577DGsWbMGRqMRH374oUtjXLlyJaZMmQKNRuNSTk5ODhYvXoyNGzdi+/bt6NatG1577TXZea1bt8bjjz+Ohx56CPfddx86duxY5fq4+r24ZcuWLteGu9/bneW5UhvO8lypjavzMjMzXa6Nq/PatGnjcm1cnedqbTh77VypjavzvL29Xa6Niq+dq7Vx9bwiLS3N5dpw1zzlRnmu1IazPFdq4+q8lStXulwbV+ft2rXL5dq4Os9isbi833D2+smtj6uzli1b5nJtXJ23b98+2bXhbI7sypzK3XPuG+XJqY0b5cmpDWd5cudUzrJcmU85y3Nln3Gj105OXTjLc2VO5SzPlTmVs897S5culV0b7v78eKM8d3/eqG1UNT0Aqr0OHDiAOXPm4Omnn0ZsbKxLWadPn4bFYkFYWBj0ej2GDRuGEydOyM7btGkTcnJyMHbsWBQVFcFgMODVV1/F008/LStv//79sFqt5W96QgioVPLLIzAwEDExMeWn2A0ZMgTJycmIj4+XnWmxWLBv3z4sWrRIdkaZ7du3IyYmBgEBAQCA+Ph4rFixAjNmzJCVV1JSgmHDhpU3zP7zn//I+i3r1Zo0aYKcnJzy73Nyctxyaqo7nT59GjNmzEBCQgKmTZvmUtaFCxeQlZWFqKgoqFQqxMbG4ssvv5Sdt3HjRqSmpmLs2LEwGAzIzc3Fo48+irfffltW3okTJ5CWlobhw4cDcE+NdOvWrfznZOTIkS6fNvvzzz+71Fwts3//fnTo0AGtWrUCcGVS++ijj8rOM5vN6Nq1K9atWwcA2Lx5c5Xqo+J78d69e12qDXe+t1eW50ptVMxztTYq5i1YsMCl2qiY52ptVMxbvXq17Nqo7P9Wbm1UzNu8ebNLtVExz5XacDav2LJlC5RKZfljqlIb7p6nVJYntzac5SUlJaFdu3ayaqOyPLm14Sxv06ZN8PX1lVUbzvJef/119O3bV1Zt3Oj/t6r14SxrxYoVsmvDWV5ycjIefPBBWbXhbI6cmZkpuzbcPeeuLG/SpEmyasNZ3oIFCzBhwgRZteEsT5IkWbXhLOvhhx/GmDFjZNWFszwhBKKjo2XVxY3+b+XsN5zl7d27FxEREbJqo7LxTZkyRVZtOPu817x5c9lzKnd/fqwsz52fN2qtmljIiqrXoEGDXF7oPCsrS/Tu3Vvs3LnTLWPaunWriI+PF2azWZjNZvHAAw+IjRs3uiX7m2++cXmh819++UWMGzdOmEwmUVxcLEaPHi0SExNl5x06dEgMHz5cFBUVlS/8XdVF/SpKTk4WkydPdimjzO+//y7GjBkjSktLhcPhEM8++6xYunSp7LyUlBQxZswYYbVaxeXLl8Xw4cPF/v37ZWWV/fyaTCYxYMAAkZaWJmw2m5g+fbrYtGmT7LwyTz75pKyFzivmFRcXi4EDB4q1a9fKzro678SJE2LQoEGiqKhIOBwO8dRTT4kPPvhAdt7Vdu/eXeVFOSvmpaSkiAEDBojCwkJhsVjEtGnTxIYNG2TnZWVlif79+4usrCwhxJWFKpcsWSIrSwgh8vLyRP/+/as8Hmd5p06dEgMHDhQ5OTlCCCHef/99We8xZXn5+fli4MCBori4WJjNZjFlyhTx7bff3lKGs/diV2rjZu/t999/f5UW5XSW50ptOMtzpTZutr1VrQ1nea7UhrM8ubVR2bbKrQ1nea7UhrM8V2qjsnmF3Nq42TylqrXhLG/t2rWya8NZ3rJly2TXxs22t6q14Szv3XfflV0blb1+cvcblW2vnPpwlrV8+XLZteEsb/369bJr42plc2R3zamczbmrWhvO8tw1pyrLc9ecytn2yp1TlWW5az5VlueO+dTVeUK4Z05VlueuOVVZniv7jco+78mtjZt9fqxqbTjL27dvn1tqo7bjkVLk1EcffQSz2XzNUTmTJ0/GvffeKytv4MCBSE5Oxrhx46BUKjFs2DC3/IbeXQYNGoSkpCSMGzcODocDU6ZMQffu3WXndevWDTNmzMCUKVNgtVrRt29fl0+jOnfuHJo0aeJSRpl+/frh2LFjiI+Ph1qtRpcuXTBz5kzZeZ06dcKwYcMwZswY2O12/PWvf0VUVJRLY9RqtVi0aBEeeeQRmM1mDBw4sErnoFe3r7/+Grm5ufj444/LL9981113Ye7cubLyOnTogJkzZ2Ly5MlQKpWIjo52y6ma7tKpUyfMnDkT9957L2w2G4YNG4a4uDjZeU2bNsWLL76I2bNnw2w2IywsDE8++aTsvPPnz7utPtq2bYu5c+di6tSpUCqVCAkJwYsvvig7z8/PDw8//DAmTZoEm81WflnfW1HZe7Hc2nD3e7uzvFGjRsmujcrGJ7c2PLG9ZeOTUxuV5cmpjcqywsPDZdVGZXlya6OyPLm1Udm8wt/fX1ZtuHue4iyvsLBQdm04y/vb3/4Gf39/WbXhie39+9//Dj8/P1m14Sxv3Lhx8PX1lbXfqGx7k5OTq1wfzrJmzZqF4OBgWbXhLG/MmDEwm82yasMZzqlqz5yqts+ngLo7p6rs857c2nD350dneUeOHHFrbdRWkhBC1PQgiIiIiIiIiIiofuFC50RERERERERE5HFsShERERERERERkcexKUVERERERERERB7HphQREREREREREXkcm1JERERERERERORxbEoRERERVbM5c+Zg2LBh193+4YcfomPHjpg/f/519z344IO455573PL8a9asQceOHZGfn++WPCIiIiJ3YFOKiIiIqJr17t0b6enp1zWFdu3aBV9fX+zcufOa2x0OBw4dOoSYmBhPDpOIiIjIo9iUIiIiIqpmvXr1AgAcOnSo/Daz2YzExEQkJCQgJycHJ0+eLL8vNTUVly9fZlOKiIiI6jQ2pYiIiIiqWfv27REQEHBNU+rAgQOwWq24//774efnd83RUgcOHIBGo0GPHj1gs9nwzjvv4M4770SXLl0QHx+PXbt2XZNvMBjw0ksvoU+fPujatSsSEhJw7NixSseTkZGBvn37Yvr06bBYLG7fXiIiIqJbwaYUERERkQf06tULBw8eLP9+586diIiIgK+vL3r37o0dO3aU35eYmIgePXpAq9Xi2Wefxccff4ypU6di2bJlaNOmDR588EEkJiYCAIQQeOihh/Ddd9/h0UcfxTvvvAONRoOEhARkZGRcN46cnBxMmzYNrVu3xrJly6DRaKp/44mIiIicYFOKiIiIyAN69eqFI0eOwG63A7jSlCo7Pa9Pnz7Yt29f+VFLiYmJiImJwenTp7FmzRr84x//wLRp0zBgwAAsXrwYUVFRePvttwEA27dvx+7du/HWW29h4sSJGDRoED744AMEBgbi/fffv2YMpaWlePDBB+Hr64vly5dDp9N57gUgIiIiqoBNKSIiIiIP6N27NwwGA06cOIGCggKkpKSgb9++AK40pYxGI5KSkpCdnY3MzEzExMRg7969AIABAwbAZrOV/xk4cCASExNhsViwZ88e6PV69OzZs/x+AOjXrx927959zRjmzJmDlJQUPPXUU/Dx8fHsC0BERERUgaqmB0BERERUH7Rt2xZBQUE4ePAg0tLSoNVqERkZCQBo2bIlWrRogX379iEnJwc+Pj6IiIgoX2dqwIABTjMLCgpQWFgIo9GIiIiI6+5Xq9XXfF9SUoLQ0FC8/fbb+N///gdJkty7kURERERVwKYUERERkYeUncKn0WgQHR19zXpOffr0wcGDB5GXl4devXpBqVSiQYMGkCQJX375JVSq66dtfn5+aNCgAQICAvDBBx/c9Pnff/99XLx4EdOnT8eaNWswfvx4t24fERERUVXw9D0iIiIiD+nduzeOHj2KxMTE8lP3ysTExODkyZM4dOhQ+VpTUVFREEKgtLQUXbp0Kf+za9cufPLJJ1CpVIiKikJ+fj68vLyuecyGDRvw7bffXvMc/v7+6NevH4YOHYo333wTBQUFHtt2IiIioorYlCIiIiLykN69e+PUqVNITU0tbzyViYmJwaVLl3D8+PHy+8LCwjB8+HA88cQT+OKLL7B7924sXboUS5YsQbNmzaBQKDBo0CB06dIFM2fOxNq1a7F79268+OKL+PTTT9G2bVun41iwYAGMRiPeeOONat9mIiIiosrw9D0iIiIiDwkNDUVgYCBsNhs6dux4zX1+fn7o1KkTLl26hPbt25ffvnjxYrzzzjv48MMPkZeXh+bNm+Pxxx/H9OnTAQBKpRIfffQRFi9ejDfffBMlJSUICQnBa6+9hvj4eKfjaN68OWbNmoWlS5di/PjxiI6Orr6NJiIiIqqEJIQQNT0IIiIiIiIiIiKqX3j6HhEREREREREReRybUkRERERERERE5HFsShERERERERERkcexKUVERERERERERB7HphQREREREREREXkcm1JERERERERERORxbEoREREREREREZHHsSlFREREREREREQe9/9+g9hPryFWOwAAAABJRU5ErkJggg==",
- "text/plain": [
- "<Figure size 1440x576 with 1 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "weekly_sales_2010 = clean_data1[clean_data1.Year==2010]['Weekly_Sales'].groupby(clean_data1['Week']).mean()\n",
- "weekly_sales_2011 = clean_data1[clean_data1.Year==2011]['Weekly_Sales'].groupby(clean_data1['Week']).mean()\n",
- "weekly_sales_2012 = clean_data1[clean_data1.Year==2012]['Weekly_Sales'].groupby(clean_data1['Week']).mean()\n",
- "plt.figure(figsize=(20,8))\n",
- "sns.lineplot(weekly_sales_2010.index, weekly_sales_2010.values)\n",
- "sns.lineplot(weekly_sales_2011.index, weekly_sales_2011.values)\n",
- "sns.lineplot(weekly_sales_2012.index, weekly_sales_2012.values)\n",
- "plt.grid()\n",
- "plt.xticks(np.arange(1, 53, step=1))\n",
- "plt.legend(['2010', '2011', '2012'], loc='best', fontsize=16)\n",
- "plt.title('Average Weekly Sales - Per Year', fontsize=18)\n",
- "plt.ylabel('Sales', fontsize=16)\n",
- "plt.xlabel('Week', fontsize=16)\n",
- "plt.show()"
- ]
- },
- {
- "attachments": {},
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Wir sehen, dass sich die Verk\u00e4ufe in den 3 Jahren \u00e4hnlich verhalten. Es gibt Spitzenwerte vor Woche 7 (Super Bowl), vor Woche 48 (Thanksgiving) und vor Woche 52 (Weihnachten), was vermutlich auf den schwarzen Freitag und das Weihnachtsgesch\u00e4ft zur\u00fcckzuf\u00fchren ist. Vor Woche 37 (Tag der Arbeit) gehen die Verk\u00e4ufe zur\u00fcck."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 48,
- "metadata": {},
- "outputs": [
- {
- "data": {
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- " }\n",
- "</style>\n",
- "<table border=\"1\" class=\"dataframe\">\n",
- " <thead>\n",
- " <tr style=\"text-align: right;\">\n",
- " <th></th>\n",
- " <th>Dept</th>\n",
- " <th>Weekly_Sales</th>\n",
- " </tr>\n",
- " </thead>\n",
- " <tbody>\n",
- " <tr>\n",
- " <th>73</th>\n",
- " <td>92</td>\n",
- " <td>75204.870531</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>76</th>\n",
- " <td>95</td>\n",
- " <td>69824.423080</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>36</th>\n",
- " <td>38</td>\n",
- " <td>61090.619568</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>60</th>\n",
- " <td>72</td>\n",
- " <td>50852.993977</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>57</th>\n",
- " <td>65</td>\n",
- " <td>45441.706224</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>...</th>\n",
- " <td>...</td>\n",
- " <td>...</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>43</th>\n",
- " <td>45</td>\n",
- " <td>23.807907</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>49</th>\n",
- " <td>51</td>\n",
- " <td>22.718938</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>37</th>\n",
- " <td>39</td>\n",
- " <td>11.123750</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>63</th>\n",
- " <td>78</td>\n",
- " <td>10.765156</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>41</th>\n",
- " <td>43</td>\n",
- " <td>1.193333</td>\n",
- " </tr>\n",
- " </tbody>\n",
- "</table>\n",
- "<p>81 rows \u00d7 2 columns</p>\n",
- "</div>"
- ],
- "text/plain": [
- " Dept Weekly_Sales\n",
- "73 92 75204.870531\n",
- "76 95 69824.423080\n",
- "36 38 61090.619568\n",
- "60 72 50852.993977\n",
- "57 65 45441.706224\n",
- ".. ... ...\n",
- "43 45 23.807907\n",
- "49 51 22.718938\n",
- "37 39 11.123750\n",
- "63 78 10.765156\n",
- "41 43 1.193333\n",
- "\n",
- "[81 rows x 2 columns]"
- ]
- },
- "execution_count": 48,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "clean_data1[['Dept', 'Weekly_Sales']].groupby(['Dept'], as_index=False).mean().sort_values(by='Weekly_Sales', ascending=False)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 49,
- "metadata": {},
- "outputs": [
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "C:\\Users\\eebal\\Anaconda3\\lib\\site-packages\\seaborn\\_decorators.py:36: FutureWarning: Pass the following variables as keyword args: x, y. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
- " warnings.warn(\n"
- ]
- },
- {
- "data": {
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",
- "text/plain": [
- "<Figure size 1800x576 with 1 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "weekly_sales = clean_data1['Weekly_Sales'].groupby(clean_data1['Dept']).mean()\n",
- "plt.figure(figsize=(25,8))\n",
- "sns.barplot(weekly_sales.index, weekly_sales.values, palette='bright')\n",
- "plt.grid()\n",
- "plt.title('Durchschnittlicher Umsatz pro Abteilung', fontsize=18)\n",
- "plt.ylabel('Sales', fontsize=16)\n",
- "plt.xlabel('Dept', fontsize=16)\n",
- "plt.show()"
- ]
- },
- {
- "attachments": {},
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Die Abteilung 92 bringt insgesamt und im Durchschnitt die meisten Ums\u00e4tze ein "
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 50,
- "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>Store</th>\n",
- " <th>Weekly_Sales</th>\n",
- " </tr>\n",
- " </thead>\n",
- " <tbody>\n",
- " <tr>\n",
- " <th>19</th>\n",
- " <td>20</td>\n",
- " <td>29627.580994</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>3</th>\n",
- " <td>4</td>\n",
- " <td>29175.540012</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>13</th>\n",
- " <td>14</td>\n",
- " <td>28885.743572</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>12</th>\n",
- " <td>13</td>\n",
- " <td>27399.631860</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>1</th>\n",
- " <td>2</td>\n",
- " <td>26961.734433</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>9</th>\n",
- " <td>10</td>\n",
- " <td>26474.084736</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>26</th>\n",
- " <td>27</td>\n",
- " <td>24897.723614</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>5</th>\n",
- " <td>6</td>\n",
- " <td>21960.799719</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>0</th>\n",
- " <td>1</td>\n",
- " <td>21749.145978</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>38</th>\n",
- " <td>39</td>\n",
- " <td>21084.103489</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>18</th>\n",
- " <td>19</td>\n",
- " <td>20430.857011</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>22</th>\n",
- " <td>23</td>\n",
- " <td>19839.563326</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>30</th>\n",
- " <td>31</td>\n",
- " <td>19761.897868</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>10</th>\n",
- " <td>11</td>\n",
- " <td>19332.641482</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>23</th>\n",
- " <td>24</td>\n",
- " <td>19002.604957</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>27</th>\n",
- " <td>28</td>\n",
- " <td>18741.608875</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>40</th>\n",
- " <td>41</td>\n",
- " <td>18031.506002</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>31</th>\n",
- " <td>32</td>\n",
- " <td>16403.222829</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>17</th>\n",
- " <td>18</td>\n",
- " <td>15820.075220</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>21</th>\n",
- " <td>22</td>\n",
- " <td>15247.436339</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>11</th>\n",
- " <td>12</td>\n",
- " <td>14929.244341</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>25</th>\n",
- " <td>26</td>\n",
- " <td>14568.937406</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>34</th>\n",
- " <td>35</td>\n",
- " <td>13989.575528</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>39</th>\n",
- " <td>40</td>\n",
- " <td>13783.028706</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>33</th>\n",
- " <td>34</td>\n",
- " <td>13546.210778</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>42</th>\n",
- " <td>43</td>\n",
- " <td>13463.138546</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>7</th>\n",
- " <td>8</td>\n",
- " <td>13148.994199</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>16</th>\n",
- " <td>17</td>\n",
- " <td>13023.154252</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>44</th>\n",
- " <td>45</td>\n",
- " <td>11695.871003</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>41</th>\n",
- " <td>42</td>\n",
- " <td>11519.913664</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>20</th>\n",
- " <td>21</td>\n",
- " <td>11328.537256</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>24</th>\n",
- " <td>25</td>\n",
- " <td>10346.216563</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>36</th>\n",
- " <td>37</td>\n",
- " <td>10308.816413</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>14</th>\n",
- " <td>15</td>\n",
- " <td>9045.551883</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>8</th>\n",
- " <td>9</td>\n",
- " <td>8805.882422</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>29</th>\n",
- " <td>30</td>\n",
- " <td>8785.125694</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>35</th>\n",
- " <td>36</td>\n",
- " <td>8619.227546</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>6</th>\n",
- " <td>7</td>\n",
- " <td>8379.492279</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>28</th>\n",
- " <td>29</td>\n",
- " <td>8185.783800</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>15</th>\n",
- " <td>16</td>\n",
- " <td>7897.132309</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>37</th>\n",
- " <td>38</td>\n",
- " <td>7503.727479</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>2</th>\n",
- " <td>3</td>\n",
- " <td>6380.226664</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>43</th>\n",
- " <td>44</td>\n",
- " <td>6061.841438</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>32</th>\n",
- " <td>33</td>\n",
- " <td>5736.388608</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>4</th>\n",
- " <td>5</td>\n",
- " <td>5065.283995</td>\n",
- " </tr>\n",
- " </tbody>\n",
- "</table>\n",
- "</div>"
- ],
- "text/plain": [
- " Store Weekly_Sales\n",
- "19 20 29627.580994\n",
- "3 4 29175.540012\n",
- "13 14 28885.743572\n",
- "12 13 27399.631860\n",
- "1 2 26961.734433\n",
- "9 10 26474.084736\n",
- "26 27 24897.723614\n",
- "5 6 21960.799719\n",
- "0 1 21749.145978\n",
- "38 39 21084.103489\n",
- "18 19 20430.857011\n",
- "22 23 19839.563326\n",
- "30 31 19761.897868\n",
- "10 11 19332.641482\n",
- "23 24 19002.604957\n",
- "27 28 18741.608875\n",
- "40 41 18031.506002\n",
- "31 32 16403.222829\n",
- "17 18 15820.075220\n",
- "21 22 15247.436339\n",
- "11 12 14929.244341\n",
- "25 26 14568.937406\n",
- "34 35 13989.575528\n",
- "39 40 13783.028706\n",
- "33 34 13546.210778\n",
- "42 43 13463.138546\n",
- "7 8 13148.994199\n",
- "16 17 13023.154252\n",
- "44 45 11695.871003\n",
- "41 42 11519.913664\n",
- "20 21 11328.537256\n",
- "24 25 10346.216563\n",
- "36 37 10308.816413\n",
- "14 15 9045.551883\n",
- "8 9 8805.882422\n",
- "29 30 8785.125694\n",
- "35 36 8619.227546\n",
- "6 7 8379.492279\n",
- "28 29 8185.783800\n",
- "15 16 7897.132309\n",
- "37 38 7503.727479\n",
- "2 3 6380.226664\n",
- "43 44 6061.841438\n",
- "32 33 5736.388608\n",
- "4 5 5065.283995"
- ]
- },
- "execution_count": 50,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "clean_data1[['Store', 'Weekly_Sales']].groupby(['Store'], as_index=False).mean().sort_values(by='Weekly_Sales', ascending=False)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 51,
- "metadata": {},
- "outputs": [
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "C:\\Users\\eebal\\Anaconda3\\lib\\site-packages\\seaborn\\_decorators.py:36: FutureWarning: Pass the following variables as keyword args: x, y. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
- " warnings.warn(\n"
- ]
- },
- {
- "data": {
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",
- "text/plain": [
- "<Figure size 1800x576 with 1 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "weekly_sales = clean_data1['Weekly_Sales'].groupby(clean_data1['Store']).mean()\n",
- "plt.figure(figsize=(25,8))\n",
- "sns.barplot(weekly_sales.index, weekly_sales.values, palette='dark')\n",
- "plt.grid()\n",
- "plt.title('Durchschnittlicher Umsatz pro Laden', fontsize=18)\n",
- "plt.ylabel('Umsatz', fontsize=16)\n",
- "plt.xlabel('Laden', fontsize=16)\n",
- "plt.show()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 52,
- "metadata": {},
- "outputs": [
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "C:\\Users\\eebal\\Anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
- " warnings.warn(msg, FutureWarning)\n"
- ]
- },
- {
- "data": {
- "text/plain": [
- "<AxesSubplot:xlabel='Weekly_Sales', ylabel='Density'>"
- ]
- },
- "execution_count": 52,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": 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",
- "text/plain": [
- "<Figure size 432x288 with 1 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "sns.distplot(clean_data1['Weekly_Sales']) "
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 53,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "image/png": 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IqMbiSqMK6N7dFWPHvo3p0z+ARCJB/fpGWLFiFSQSCaZMmYZPP/0IBgYGqF/fCJ06dcaTJzGaLpmIiIjKsGvXLlhbW8Pd3V3TpRARERHVaFxpVItxpREREVHFff7554iJicGlS5cwd+5cvPvuuy+/ExEREVEdxk9PIyIiojohJSUF4eHhGDlyJMaNG6fpcoiIiIhqPJ6eRkRERHXChg0bNF0CERERUa1S7SuNsrKy4O/vjydPnlT3oYmIiIiIiIiIqIJUmjSSyWRIS0ur8O1v3LiBN998E1FRUaocloiIiIiIiIiIqliFT0+TSqVYv349mjVrhoCAAISFhWHKlCnIzMxEly5d8P3338Pc3LzcjD179mDBggWYM2eOqGLT0rIhl/9v3265XA6ZTC4q61Ugl8uRkpKl6TJqrdj7USgoKIB96+aaLoWIiIio1rp75V9Y29vCtKGFpksheqVlRseivm1DaOloa7qUOk+WkwvZ8zzUMzfVdCkq09KSwMysfpnXV3jS6Ntvv8WuXbvw5ZdfAgA+/fRTNGzYEPPnz8dPP/2ElStXYsWKFeVmLF26tKKHU0ouF4pNGhH4/RBJXlCA2ZM/g0wmw/Y/foGuvr6mSyIiIiKqdVKexmPqlPlwbt4Uq3Z+r+lyiF5Zzx7F4Ormk3BwbYmmAzw1XU6dF/7LMQhyAR3fewMSrVf788Uq/OhOnDiBefPmYejQoQgPD0dMTAzef/99DB48GDNnzsS5c+eqsEwi9Qo5fg4J6elIycrCH78GabocIiIiolrpwM97IJPLceP+Q0RH3Nd0OUSvrNiQ2wCA+JvRkOfLNFxN3ZYdn4i0J2kwea38M61eFRWeNEpLS0OLFi0AAOfOnYOOjg48PV/McJqYmCAvL69qKqxlNm8OxJgxIzBmzAj8+OOLd1tCQ0Pw9tujMGrUGwgM/LHUfRYv/hLHjh1WfB0fH4+pUydh9OihmDt3NnJycqqt/rri4O6j0NfRgYGuHk6fCtZ0OURERES1jrygAKfOXYJZ/fqQCwIO/LxH0yURvZLys3OQEBmLesb18DwzD0nXb2u6pDot7tItSLQkMGth/8qvMgIqMWnUuHFjhIWFIT8/H8ePH4eLiwuMjIwAAMeOHUPTpk2rrMjaIjQ0BKGhl7Bly3Zs3boDkZF3cOrUCSxfvgjLl3+Lbdv24s6d27h48cUkRXJyEubMmYVz504Xy/nuuxV4441h2LFjPxwd22Lr1p818XBeWSlP4xEWeR9d27ZCz05OuPnoMR6GR2i6LCIiIqJa5cKRM0jOfIYB3j3RtGFDBF8NRz7fSCZSu8SrtyGXydHMyxm6BrpICH+o6ZLqrAKpFHE3o2HhYIkGTe01XU61qPCk0YQJE7BmzRq4uroiKioK7777LgBg5MiR2L9/PyZNmlRlRdYWFhaWmDp1FnR1daGjo4MmTRwQExMNe/vGsLW1g46ODnx9++Ps2T8BACdPHoeHRy94e/soMmQyGa5fv4bevfsAAPr398fZs6eVHo/EOfDzHhTI5ejp2Q3Dxg+DXBBwcMs+TZdFREREVKsc2nMM9XR10aV3D/Qf0AspWVk4+dsBTZdF9EoR5HI8DbsPYysjmLVqikZOjZH6OAXZ8cmaLq1OSr5+B7I8Gawc7aFdr27si1vhjbDfeOMNODg4ICwsDB07doSLiwsAwMPDAx9//DG6du1a4YOeOXOm8pVWgCQnA5LcjCrJFgxMIBialHubZs3+9ylcMTHROHPmTwwbNhIWFpaKyy0sLJGUlAgAGD16HAAgPPy64vr09HTUr18fOjo6RW6foK6HUecVLqNubGWFTt49Yd3YFs0b2SA47Cam5eVxQ2wiIiKiCkh6Eovr9x6gZ/u2cOzeES07t8OW7b/jz5Pn4TdxlKbLI3plPHv0BNkp2Wju6Qg9E2PY9nBGdOgDxIeEo3mAt6bLq3OeXr0HA5N6MGnZRNOlVJsKrzTavn07HBwcMGHCBMWEEQBMmzatUhNGdcHDhw8wa9ZUTJ06A7a2dpBIil4rQCIp+9suCHJIit8BWnXgPMnqUriM2qNHR1g3tgUADBjghbTsbBzful/D1RERERHVDgcCX6zcdvPsCr16+jAwNoJbJ2fcfPQYUf/e0XR5RK+M2Mu3oa2rDdP/JikMrC1gZm+OhDuxkEvzNVxd3ZL9NAEZselo6Pga6pmbarqcalPh2YjVq1fDw8MDH3zwAU6ePAmpVFqVdYkiGJpAbtG4Sv69bJVRofDw65g58wNMmTIN/fv7w8rKGsnJKYrrU1JSYGlpWeb9zczMkZWVhYKCgv9unwwLCyvVvjGkcHD3UcUy6kKvj3sDhnp6OH3qvAYrIyIiIqodCvJl+PPvS3CwtkZHb1fF5UPfHfpiQ+zNezVYHdGrIz8rB4mRsbBu2RBGdjaKy227OiIvKw+JYbc0WF3dExtyExItCUxb1Y0NsAtV+JFeuHAB33zzDSQSCT766CO4u7vjyy+/xJUrV6qyvlolISEe8+d/jAULlqBv334AgLZtnRAT8xhPnsSgoKAAp079gR493MrM0NHRQYcOHXH69CkAwIkTR9GjR89qqf9Vlxj9Yhl113at4di9o+LyevUN4e7SHrcex+Be2E3NFUhERERUC5w/eBIpWVlw79EJVq/ZKi5v1aW94rR/bohNpLqEKzchLxBg4dgYWrr/21nG0rkV9Ax1kXDzkQarq1sK8qSIvxUDy2ZWaNDkNU2XU60qPGmkp6eH/v37Y/369fjnn38we/ZsPH36FOPHj0efPn2wdu1aREdHV2WtNd7OnduQlyfFunWr8c47o/HOO6Nx/PhhzJ+/AJ99NgdjxgxHkyZN4OXVp9ycjz6ai0OHgjBmzHDcuHEdkya9X02P4NV24OfdkAuCYhl1UUMnDIcgCDj4S5CGqiMiIiKqHQ7t/wMGunro6tW91HU87Z9IPV5sgP0AxtbGMGnWuNh1WjraaOTcBKnRqciO5f631SHpWgRk0gJYOtpDW19P0+VUK4kgCIKYOyYkJODUqVM4fPgwbty4ARMTEzx79gy9e/fGwoUL0bBhQ3XXipSULMjl/ys3Pv4xbGzqzgZUJdX1x18ZBfkyvOkzBsaGhlgRuKTYu2KFpgyahMS0DOw8sRX69Q01UCURERFRzZbwKAZjRnwAj45OmLtuYak34p5n52C4zxg0s7XB9/t+1FCVRLVf+t0oXPvtNJr3aoPGfUufeZKbnIZL3wfBvrMDWrxR/qIEUt3V9fsgey5F+7dfh4GluabLUSstLQksLIzKvr4yYRkZGdizZw/GjRsHLy8vrFu3Dm3atMHu3bsREhKC3bt34/79+/jwww9VLpxIncpaRl3UAP8+yMjNwbEt+6q5OiIiIqLaYf+mPZALAnoqWbkN8LR/InWJDb0NHb3/bYBdkoGlGcybWCAhMhYF3BC7SmU9icOz+AxYO9rVqQ2wC1V40mjKlClwd3fHokWLUL9+faxZswbnz5/HwoUL0aFDBwBA+/btMWjQIDx48KDKCiYSo7xl1IX6jQlAfX19nDlzsRorIyIiIqodCvJlOPtPKJo1bIhO3mXvuVl42v8hnvZPJIo0MwuJd+Nh1dIGRrZln8Fj29UR0mwpEq9ygrYqxYbcgpa2BGatGtepDbALVfgRJyYm4pNPPsHff/+NDRs2wNfXF7q6uqVu5+XlhZ9++kmtRRKpIuFRDMLvP0Q3p9Zo1bVDmbfTNzSAR5cOiIiOQWTI9eorkIiIiKgW+DvoBFKzs+Dh2gkWRT7JqaQWHduhpW0jBF+7ibzsnGqskOjVkBB6C4K89AbYJVm0awm9+npI/Deq+oqrYwqe5yH+9hNYNrOGcRM7TZejERWeNAoKCsK4ceNgbl7++XtOTk7o2rWryoURqcvLllEXNWzCcAgADm77vVpqIyIiIqotDgX9AUM9Pbj07vHS2w7w74OMnBwc28rT/okqQ5DLEXvtARo0bFBqA+yStHS0YevcBKkxqch6Gl9NFdYtidduo6BwA2y9urUBdqGypy2VOHfuHC5fvgypVKq4TBAE5Obm4saNGzh69KjaCyRSRUWXURdq2r4NWr1mh4vXbyEvKwf6RtwQm4iIiCjuwWP8+zAKvTu3R6su7V96+35jAvDzL3tx5sxFvDF1XDVUSPRqSL/3GDnpuWjRuyn0GpS9OXGhRj2cERVyD/EhN9FiSNkrAEmc2Kv3YWhmCJPm5U/gvcoqPGn0448/Yu3atWjQoAHy8/Ohq6sLHR0dpKamQktLC8OGDavKOolEKVxGPdDHvdxl1EX5D+yD7zb8iiOb92Do9HeqtkAiIiKiWmD/z3sgCAJcPbpCt97L320vPO3/j+DLiAy9jtZdO1Z9kUSvgNjQCOjo68C0VcU+JbuehRksmlgiITIWTfOkde7j4KtSZnQsniU8Q9OeLaFvZqLpcjSmwqen7du3D0OHDkVISAjeffddeHp64sKFC9i/fz/Mzc3RrFmzqqyz1ti8ORBjxozAmDEj8OOP3wMAQkND8PbbozBq1BsIDCz90aOLF3+JY8cOF7vsyJHfsXTpwuoo+ZVWmWXUhXzeCoBRvXo4c/ZSFVZGREREVDvIpFKcDQ5Fi0Y26KTko7/LUnja/6FfD1ZdcUSvEGlGJpLuxcO6pQ3qNyp7A+ySbLs6QpqTj8Sr/1ZhdXVP7OVb0NLWgmnLJnVyA+xCldoI29/fHxKJBG3btsW1a9cAAO3atcPUqVOxf//+KiuytggNDUFo6CVs2bIdW7fuQGTkHZw6dQLLly/C8uXfYtu2vbhz5zYuXgwGACQnJ2HOnFk4d+60IiMvLw8bNqzD999/p6mH8cooXEbd3blNhZZRF9Krpw/Prh1xJ+YJIi6GVWGFRERERDXfuX0nkJ6TA3fXzjC3sa7w/QpP+79w/SbysrghNtHLxF/5bwPs1o2hpaNd4fuZt20B/fp6SPj3cRVWV7fIcvOQcPsprJpbwbhxI02Xo1EVnjQyNjaGTCYDADRt2hSxsbHIysoCALRo0QJPnjypmgprEQsLS0ydOktx6l6TJg6IiYmGvX1j2NraQUdHB76+/XH27J8AgJMnj8PDoxe8vX0UGTduXIMgyPHBB9M19TBeGZVdRl3U8IkjAQCHtvGdMSIiIqrbDh84ifr6+ujiXfGV24X8B/bBs9xcHNm8pwoqI3p1CAVyxF57CJNGDWDSonL752jpaKNRh6ZIe5KGzJjYKqqwbkkMu4WC/AJYODausxtgF6rwnkZdu3bFpk2b4OzsjCZNmsDIyAjHjh3DiBEjcPnyZRgbG1dlnRUSf+0e4sLuVkl2o86tYNOpZbm3adasueL/MTHROHPmTwwbNhIWFpaKyy0sLJGUlAgAGD36xaaA4eHXFdd369YD3br1KHW6GlVOsWXUFdgAu6TG7VqiTePXcPHGLeQ8y4RhA83/fhMRERFVt6f3HuFW1GN4u3RAy85Olb6/z1sB+L8te3D27CXuFUlUjrS7j5CbkQs7l2bQNapf6fs36u6EqIuRiL98C8b2tlVQYd0Se/U+6pvXr9MbYBeq8EqjWbNm4f79+5g2bRp0dHQwYcIELFiwAN7e3vjhhx8QEBBQlXXWKg8fPsCsWVMxdeoM2NraQSIpeq0AiaTung9ZXYoto7at+DLqovwDfJD5/DmObOI7Y0RERFQ37f+/Fyu3e3h2hY6Id9v16unDs1sn3Il5gjshPO2fqCxxoRHQracDs5YV2wC7pHrmprB0sEJCZBwK8vLUXF3d8izqKTKTMmHdxg71zE01XY7GVXilUdOmTXHy5Ek8evQIADBlyhTY2Njg+vXrcHZ2xpAhQ6qsyIqy6dTypauBqlp4+HV8/vmnmD59Nvr27Ydr164iOTlFcX1KSgosLS3LSSB1UGUZdaE+Iwdi48+7cPZcCEbMmqDG6oiIiIhqPplUinMXr6KlbSNRK7cLDZswAkf/voiDvx6EY/fOaqyQ6NWQl56JpAeJsHV6DYaV2DesJNtujkje/Q8SQm/C1t1FjRXWLbGXb0FL58UG2FSJlUYAYGhoiHbt2im+Hjx4MBYuXIihQ4dCUnw5TZ2UkBCP+fM/xoIFS9C3bz8AQNu2ToiJeYwnT2JQUFCAU6f+QI8ebhqu9NVWuIy6h3MbtOhY+WXUhXTr6aFX9864+zQWN/8JVWOFRERERDXf6d1HkZGbA/eenWFmYyU653+n/d/G88wsNVZI9GqID70JQS7AvJIbYJdk3qY59I30kXAzSn3F1TGynFwkRjyFVXNrGNvbaLqcGqHclUZLliypVNjnn3+uUjG13c6d25CXJ8W6dasVlw0ePATz5y/AZ5/NgVSaB1dXN3h59dFgla++osuoK7sBdknDJo3AkXPBOLzjEJw8uqqpQiIiIqKa7+jvp2CkXw9dvF1VzvIP8ME367bg8KY9GD5zvBqqI3o1CAVyxF5/CFNbU5g0U23/HIm2Nmw7NsWj83eQGf0Uxo3t1FRl3ZFw9TYKZHJYcgNshXInjc6cOVPs68TERMhkMtjZ2cHKygppaWmIiYmBnp4eHB0dq7TQ2mDmzI8xc+bHSq/75ZedZd7vs88WlrpswICBGDBgoLpKqzPUtYy60Gutm6Ntk8a4FB7BDbGJiIiozoi58wC3H0ejb7dOaNGxrcp5RU/756QR0f+kRj7E82fPYd+1BXSNDFXOa9TNGVHBdxB3+RYnjSpJkMsRG3YfRhb10UDFCbxXSbmnp505c0bxb/r06WjYsCGCgoJw+vRp7Nq1C3/88QeOHj0KOzs7+Pj4lBdFVC3UtYy6KP83fJGV9xyHAnepJY+IiIioptv/8x4IAHr06iZqA+ySCk/7j3zyFLfO87R/okJxoXegW08Xpi0d1JKnb9YAFs2skRgZB1kuN8SujGePnyIrOQvWbV5DPXMTTZdTY1R4T6PVq1fjo48+Qtu2xd9paNq0KWbMmIHNmzervTiiylLnMupC3iMGwMTQEOf+vqy2TCIiIqKaKv+5FOcuhaH1a3bo5KW+MdWwSSMgAXB4xyG1ZRLVZnlpz5D8IAHWrRvBsKH6PizJtlsb5D+XIeHKv2rLrAviQm5DW0cLpq24AXZRFZ40ys7OhpaW8pvn5uZCJpOprSgiMaIj7uH242i4dmijlmXUhXT09NDb1QX3YuNw49xFteUSERER1UR/7jqEzOe5cHftBBNr9b2QLTzt/+KNF6f9E9V1cZdvQhAAi1aqbYBdknnrZqjXoB43xK6E/OwcJETGwqpFQxi/xg2wi6rwpFHPnj2xatUqhIeHF7s8JCQEq1atQp8+3NyZNGv/z3vVuoy6qGETR0EikeDIziNqzSUiIiKqaY4c/BPG9QzQpY/q+0OWpDjt//942j/VbUJBwYsNsO1M0aC5vVqzJdpasO3YFBmxGXj2MEat2a+qhCu3If9vA2wtXV1Nl1OjVHjS6Msvv4ShoSFGjhyJ7t274/XXX0e3bt3wzjvvwMHBAfPnz6/KOonKlf9cir9CrsFRzcuoC9m2bAInhya49G8EslIy1J5PREREVBNE3byLOzFP0LNjWzTvoL6V24UUp/3/xdP+qW5Luf0AeVl5sHa0h2591TfALqlRN2dItCSIu3Jb7dmvGsUG2FZGMGnBU9NKqvCkkaWlJX7//Xf88MMPGD58OLp164ZRo0bh559/xm+//QYjI6OqrJOoXKd2/reM2q2zWpdRFzVwSD/kSKU4+HPZn4RHREREVJvt37QHEgDdPLtBW7fcD1oWhaf9E70Qd+UO9Ax0YdKyaiYp9EyMYdncGol34yHLfV4lx3hVZDyKQXZqNhq2eQ16Jvy07JIqPGkEAFpaWujTpw8+/vhjLFq0CLNnz4abm1tV1UZUYUcP/YkGBgZwqYJVRoV6D+sP0/r1ce4ffuIHERERvXqkz/Pwd+h1ONrbo5NXjyo7zv9O+z9aZccgqsmep6Yj+VESrFs3Qn2bqnnDG3ixIbYsT4b4kPCX37gOi7scAW1dbZhW0QRebVfu2wcDBw7Et99+i1atWmHgwIHlBkkkEhw6xE9C2Lw5EGfO/AkA6NnTDR98MAOhoSH44YfVyMvLg7e3DyZP/qDYfRYv/hIuLl0xYMCL73F4+HWsW/cd8vNlMDExwbx5X8LGplG1P5baonAZdb8eLlWyjLqQtq4OvHt2QdCpv3Dtz2B06ssJUyIiInp1/LHtd2Q9fw53984wsbKosuMUnvYf8m8EstKewcisQZUdi6gmigu5CQiARevGkGirbwPsksxaNoWBSQgSbz3Ga727VdlxarP8rBwkRsaiYetGMLLjBtjKlLvSyMnJCQYGBgCAdu3awcnJqcx/7dq1q5aCa7LQ0BCEhl7Cli3bsXXrDkRG3sGpUyewfPkiLF/+LbZt24s7d27j4sVgAEBychLmzJmFc+dOF8tZtOgLfPrpF9i6dQd8fF7HmjXfaOLh1BpVvYy6qCGTRkFLIsGR3XxnjIiIiF4tx46cgYmBIbp4q38D7JIGDumHbGkeDv0fT/unukUuK0DcjUcwszeDcVP1boBd0osNsZshI/4Z0u8/rtJj1VYJV25CXiDAwrExtKr4tWRtVe53Zfny5Yr/r1ixosqLqe0sLCwxdeos6P6323qTJg6IiYmGvX1j2NraAQB8ffvj7Nk/4erqhpMnj8PDoxdMTEwUGVKpFJMmvY8WLVoCAFq0aIn9+3dX/4OpJaprGXWhRs3s4dzMASE37yAzJQ3GFmZVfkwiIiKiqvbwxm3cffIUr/fsiqZOrav8eL2H9cePP23Dub9DMXrOe1V+PKKaIvX2feRlS9HE1bFKNsAuyaabEx7+cxsJV+/AlJs8FyPI5Xga9gDG1sYwadZY0+XUWOVOGt26datSYZpebXTyyGmcOHSqSrJfH+QDX/8+5d6mWbPmiv/HxETjzJk/MWzYSFhY/O88VQsLSyQlJQIARo8eB+DF6WiF9PT00K/fAACAXC7H5s2B8PDoraZH8eqprmXURQ0c+jqWrNyA3wN3Yuy8D15+ByIiIqIabv/mfZBIJOjm0bXKV24DxU/7v346GB378LR/qhtir9yBnqFete2fo9fACFYtGiLxbhya5eRC19CgWo5bG2Tcj0ZOWg6a92rDDbDLUe4zwtChQyGRSF4aIggCJBIJIiIi1FZYbfbw4QPMmTMTU6fOgLa2NmJiii4FFCCRvHz/8fz8fCxZsgAyWQHGjRtfdcXWctW5jLqQ5xv9YP7jb/jr/BWMrbajEhEREVWNvJxc/HPlBto2tkenahxTDZk0Cr//+TcO7z7GSSOqE54npyHlUTLsOzeBYcPqecMbAGy7tUXi3TNIuHQDr3lX/dkZtUVs6G3o6GnDtKWDpkup0cqdNPr111+rqw618PXv89LVQFUtPPw6Pv/8U0yfPht9+/bDtWtXkZycorg+JSUFlpbl75Cfk5ODuXNno0EDE6xY8S10dHhupTLVvYy6kLauDvq4d8PeE2dw5cRf6PJ6r2o7NhEREZG6nfjtALLz8uDu1hkNLEyr7bgvTvtvipCbETztn+qEuMs3AQlg1qpqN8AuybRlExiaGiDhdgwnjf4jzcxC4t142LSxhZFdQ02XU6OVOxvRrZvyHdZzcnKQnZ0NExMT6OnpVUlhtVFCQjzmz/8YX321HC4uXQEAbds6ISbmMZ48iUGjRrY4deoP+PkNKjdn8eIvYGdnj08+mQctrZevSqqrqnsZdVFDJo7A/j/O4ui+45w0IiIiolrt2NGzMDU0hEs1rjIqNGjY61j89Y84GLgLY+a9X+3HJ6ouclkBYm9EwdzeHCZVvAF2SRItLTTq1BwPzt5E+r0orqwBkBB6C4L8vw2wdapvAq82qtQr7eDgYHz33Xe4ffu24jInJyd8+OGH8PT0VHtxtc3OnduQlyfFunWrFZcNHjwE8+cvwGefzYFUmgdXVzd4eZW9Guru3Tv455+/4ODQDOPHjwEAWFpaYtWqtVVef22iqWXUhawdXkOHFs1w+VYk0pNSYFpN+ykRERERqdP9sJu4HxsHP/ducGjXqtqP7zHYF+brf8W581cwptqPTlR9Um7ehTRHCitHe+hoYF+hRt2c8OjvW4i/eqfOTxoJcjlirz1Ag4YNYNKcG2C/TIUnjYKDgzF58mQ4Oztj3rx5sLS0RGJiIo4fP44pU6bg//7v/+DmVrfPRZ4582PMnPmx0ut++aXsjxP97LOFiv+3auWI8+evqLu0V46mllEXFTB8AK4tW4eDG3fi7c+naaQGIiIiIlXs37IPWhIJunp0qfaV20Dx0/6vnvwbLr58I5peTbFXIqFfXw+mLTUzSaFrVB9WLW2QeC8ezbOyoWtUXyN11ATp9x4jJz0XLXo3hZ6xkabLqfEqfO7TmjVr0LdvX+zatQvjxo3DgAED8M4772D37t3w9fXFDz/8UJV1EhWjyWXUhdwC+sLS2Bh/BV/VWA1EREREYj3PzsH5q/+iXZPG6Nhbc2OqIRNHQEsiwZE9xzVWA1FVyk1KQerjFFg72sHAqvz9bauSbfe2KJAWID4kXGM11ASxoRHQ0deBaavq+QS72q7Ck0Z3797FsGHDlF43dOhQ3LlzR21FEZWncBm1W2cnjSyjLqSlrY0+nt3xOCkJIUfPaKwOIiIiIjGO/xqEHGke3N1dYKyhldtA0dP+7yA9KeXldyCqZeJCbgESwLyVPSTamtuz1qRZYxiaGSLhdozGatA0aUYmku7Fw7qlDeo34gbYFVHh31hLS0vEx8crvS4uLg4GBtV/XibVTZpeRl3UG5NGQFtLC8f2/6HROoiIiIgq69jRczCrXx8u3q6aLgUBwwfgeX4+DgXu0nQpRGollxUg7t8oWDSxQIOmmt0/R6KlBdvOzZGZmIm0yIcarUVT4q/8twF2a26AXVEVnjTy9fXFd999hwsXLhS7PDg4GGvWrIGPj4/ai3s5CQRBroHjap4gCJouQSNqyjLqQlav2aJjy+YIvX0XqfGJmi6HiIiIqEIiQ2/gYXw83Fyc0USDK7cLFZ72fy6Ye3vSqyU5PBLSnHxYtraHjoG+psuBTVcnaGlrIT4sUtOlVDuhQI7Yaw9h0qgBTFpwA+yKqvCk0YcffggHBweMHz8eXbp0Qb9+/dClSxdMnDgR9vb2+OSTTyqUc/jwYQwYMAC+vr7Yvn276MIBQE+vHtLTkyGT5depSRRBEJCd/Qw6OnqaLqXa1ZRl1EUFjPBDniwfv/OdMSIiIqol9m8NerFy260LtLQ1/2674rT/xCRcPn5W0+UQqU3c1UjoG+nDtIZMUujWN4R1Kxsk3UtAfla2psupVml3HyE3IxdWjvZ1eiPwyqrwuT2GhobYsWMHzp49i9DQUGRmZsLExAQuLi7o3bs3tLRePv+UkJCA1atXIygoCHp6ehg1ahS6d++OFi1aiCrezMwKWVkZSE1NgFxeICqjttLR0YOZmZWmy6h2NWkZdSFXfy9Yfb8Zf18Iw3hNF0NERET0ErmZWbgQ9i+cmjZBxxo0pnpj0gjsO34Gx/adQLf+Xpouh0hlOYnJSI1OReMuTWFgZaHpchRsu7dDfEQs4i7eQGMfzZ+9UV3iQiOgW08HZi25AXZlVGpDGIlEAm9vb3h7e4s62IULF9CjRw+YmpoCAPr164cTJ05g2jRxH1cukUhgbGwKY2NTUfen2qVwGbW/Z48asYy6kJa2Nvr27oGdh07i4sGTcA3w1XRJRERERGU6tnU/cvOlcHfvAiMzE02Xo1B42v/lW3eRlpgMM2vNfcoUkTrEhdyCRAKYtdTsBtglNWj6Guqb10dCRAwaa2KXGQ3IS89E0oNENHJ6DYaNrDVdTq1S4UmjgoIC7Nq1CyEhIXj27Bnk8uJ7CUkkEvzyyy/lZiQmJsLK6n+rY6ytrREeXnc+7i8jOQ3vjZyGrNxcTZdSK8kKCmrUMuqihkwchT1H/sRXy9ZD9+ufNF0OERERUZnyZDJYGBnBpU/NWWVUKGCEH64uXoO3Bk2CtpZE0+VQFejUpCl8ndpruoxqIZMWwNzBUuMbYJck0dKCnUsL3D11A/8s+QWSOtBq8gLhxQbYrbgBdmVVeNJo5cqV+OWXX9CqVSvY2dlV6HS0kuRyOSRFfiMFQSj29auuXn0DuLRvh9SUdE2XUitpSYBmzexq1DLqQua21pg8dgj+vXZb06UQERERvVTHzu3Q2FHcFhFVydXfC4MvXEFyUqqmS6Eq0sahMSyb142POpdIAAtHhxqxAXZJNt2ckZuSAVlevqZLqTb1TI1gylPTKk0iVHAH6R49euDNN9/EjBkzRB/swIEDuHLlCpYuXQoAWL9+PQRBqPDpaWlp2ZDL686G10REREREREREVUVLSwIzs7I3Bq/wSiOpVIoePXqoVEzPnj2xbt06pKamwsDAACdPnsTixYsrfP/yHggREREREREREalPhSeNvLy8cOrUKXTv3l30wRo2bIhZs2Zh3LhxyM/Px7Bhw9C+fd04n5WIiIiIiIiIqDYp9/S0LVu2KP6fnp6On3/+GW5ubujYsSMMDAyKB0kkeOedd6qsUCIiIiIiIiIiqj7lTho5OjpWPEgiQUREhFqKIiIiIiIiIiIizarwRthERERERERERFR3aGm6ACIiIiIiIiIiqnk4aURERERERERERKVw0oiIiIiIiIiIiErhpBEREREREREREZXCSSMiIiIiIiIiIiqFk0bVLCsrC/7+/njy5InKWT/88AP8/Pzg5+eHlStXqpz3/fffY8CAAfDz88OWLVtUzgOAr7/+GnPnzlU5Z+zYsfDz80NAQAACAgJw48YNlfLOnDmDIUOGoH///liyZIlKWXv37lXUFRAQABcXFyxatEilzIMHDyp+tl9//bVKWQAQGBiIfv36YeDAgdiwYYPonJK/vxcuXMDAgQPh6+uL1atXq5wHAHPmzEFQUJDKWbt374a/vz8GDhyIefPmQSqVqpS3Y8cO+Pn5YcCAAfj6669R2Q+eLKv3t23bhrFjx1YqS1nevHnz4Ovrq/g9PHXqlEp5165dw4gRI+Dn54fZs2er9P3766+/ivVIjx498N5776lU3/nz5zFo0CD4+/tjzpw5Kv98g4KCMGDAAAwcOBBLliyBTCarcJayv8Wq9EZZf9vz8/Px9ttvIyQkRKUsVXpDWZ4qvVHe85iY3lCWp0pvKMtTpTdK5qnaG8rqU6U3lOWp0hvKxhWq9EZZ4xQxvVFWntj+UJalSm+UNyYT0xvK8lTpDWV5qvRGyTxVe0NZfar0hrI8VXoDKD5GVnU8VTIPEN8XyvJUHVOVzFN1TFUyr5DYMVXJPFXHVCXzVB1TFc1Tx5iqZH2qjqmKZqnaF8pe86nSH2W9hhTTH8qy1NEbtYJA1eb69euCv7+/0K5dOyEmJkalrODgYGHkyJFCXl6eIJVKhXHjxgknT54UnRcSEiKMGjVKyM/PF3JzcwUvLy/hwYMHKtV44cIFoXv37sKnn36qUo5cLhfc3d2F/Px8lXIKRUdHC+7u7kJcXJwglUqFN998Uzh37pxasu/evSv4+PgIKSkpojNycnKErl27CikpKUJ+fr4wbNgwITg4WHRecHCw4O/vL2RmZgoymUx47733hD/++KPSOSV/f3Nzc4VevXoJ0dHRQn5+vjB+/PhKfR9L5sXHxwvvvfee0L59e2H//v0q1fbw4UPBx8dHyMzMFORyuTBnzhxhy5YtovOio6MFHx8fITs7W5DJZMLIkSOFf/75R3ReoXv37gkeHh7CmDFjKvNwleb5+/sLCQkJlcopKy8zM1Nwc3MTIiIiBEEQhFmzZgnbt29Xqb5CiYmJQp8+fYRHjx6plOfp6Sncv39fEARB+PDDD4U9e/aIznvw4IHg4eGh+P4tWLBA2Lx5c4WylP0tPnz4sOjeKOtv+4MHD4SRI0cKzs7OwqVLl0Rnbdy4UXRvKMvbsmWL6N4o73lMTG+UlSe2N5TlBQUFie6Nlz1vV7Y3ysoT2xtl/b6I7Q1l44qIiAjRvVHWOEVMb5SXJ6Y/yssS0xvljcnE9EZZeWJ7o6yfrdjeeNkYtLK9UVae2N4oK09sbwhC8TGyquOpknmCIIjuC2V5qo6pSuapOqYqmVdI7JhKWZ4qY6qSeaqOqZTVV0jMmEpZnipjqqJZqvaFstd8qvRHWa8hxfSHsix19EZtwZVG1WjPnj1YsGABrK2tVc6ysrLC3LlzoaenB11dXTRv3hyxsbGi87p164Zff/0VOjo6SElJQUFBAQwNDUXnpaenY/Xq1ZgyZYrojEIPHz4EAIwfPx6DBg3Ctm3bVMo7deoUBgwYABsbG+jq6mL16tXo0KGDynUCwMKFCzFr1iyYm5uLzigoKIBcLkdubi5kMhlkMhn09fVF592+fRvu7u4wMjKCtrY2PDw88Oeff1Y6p+Tvb3h4OJo0aQJ7e3vo6Ohg4MCBOHHihOi8w4cPo0+fPujfv7/Ktenp6WHBggUwMjKCRCJBq1atKtUfJfPs7e1x9OhRGBoa4tmzZ8jKykKDBg1E5wGAVCrFl19+ienTp1c4p6y83NxcxMbGYv78+Rg4cCDWrl0LuVwuOi84OBgdO3aEo6MjAODzzz+Hj4+P6LyiVq5ciVGjRsHBwUGlvIKCAmRlZaGgoAB5eXmV6pGSeZGRkejYsaPiay8vrwr3iLK/xVFRUaJ7o6y/7fv27cPEiRMr9bdKWZZUKhXdG8ryJBKJ6N4o67GK7Y2y8sT2hrK8p0+fiu6Nlz1vV7Y3ysoT2xtl/b6I7Q1l44pnz56J7o2yxilieqOsPH19fVH9UVZtYnujrDyxvaEsr169eqJ7Q1leRESE6N542Ri0sr1RVp7Y3lCWFx4eLro3So6RVR1PKRtzi+0LZXmqjqlK5qk6plL2eFUZU5XMU3VMVTJP1TFVea+pxIyplOWJ7Y2SWaqMpwDlr/lU6Y+yXkOK6Q9lWar2Rm3CSaNqtHTpUnTp0kUtWS1btkTHjh0BAFFRUTh+/Dh69eqlUqauri7Wrl0LPz8/uLq6omHDhqKzvvzyS8yaNatSTwJlefbsGVxdXbF+/Xps3boVu3btQnBwsOi8x48fo6CgAFOmTEFAQAB27NgBExMTleu8cOECnj9/LmrSoygjIyPMmDED/fv3R69evWBnZ4fOnTuLzmvXrh3Onz+P9PR05OXl4cyZM0hOTq50Tsnf38TERFhZWSm+tra2RkJCgui8iRMnYvjw4ZWuS1mWnZ0d3NzcAACpqanYvn07+vTpIzoPeNEfe/bsQd++fWFlZaV48heb9+2332Lo0KGwt7evcE5ZecnJyejRoweWLVuGPXv24MqVK9i3b5/ovMePH8PQ0BCzZs1CQEAA1q1bV6leLutvXVRUFC5fvoxx48ZVOKusvIULF2Ls2LHw8PBAWloaXn/9ddF5jo6OuHHjBuLi4lBQUIATJ05UuEeU/S2WSCSie6Osv+1z5sxB3759K/YAy8ny9/cX3Rtl1Sa2N8rKE9sbyvI8PDxE94ayPD09PdG9Ud7ztpjeKCtPbG8oyxswYIDo3gBKjytUfd5QNk4R0xtl5dna2oruD2W1qfK8oSxPleeNknkymUyl542SeUlJSSo9b5Q1BhX7vKEsT5XnjZJ57du3F90bJcfIqvaFsjG3Kn1RMk/VMZWy+lTpDWV5qvRGyTxVx1Ql81QdU5X1mkpsbyjLE9sbJbNUGU8Byl/zxcbGiu6Psl5DiukPZVlRUVEq9UZtwkmjWu7evXsYP3485syZU6lZ5rJMnz4dFy9eRFxcHPbs2SMqY+/evWjUqBFcXV1VrgcAOnXqhJUrV8LY2Bjm5uYYNmwY/vrrL9F5BQUFuHjxIpYtW4bdu3cjPDwcBw4cULnOXbt24d1331U5586dO9i/fz/Onj2Lf/75B1paWti0aZPoPFdXVwwZMgRjx47FxIkT4eLiAl1dXZXrlMvlkEgkiq8FQSj2dU2QkJCAt99+G0OHDkX37t1VzhsxYgRCQkJgaWmJH374QXROcHAw4uLiMHToUJVrAl68a7d+/XpYW1vDwMAAY8eOVblHzp8/j9mzZyMoKAi5ubkIDAxUuc7du3dj9OjR0NPTUyknKSkJq1atwpEjR3D+/Hl06NABy5cvF53XtGlTfPTRR3j//ffx1ltvoXXr1pXukaJ/i+3t7VXuDXX+bVeWpUpvKMtTpTeK5j19+lTl3iia16xZM5V7o2ieOnpD2fdPld4omle/fn2Ve6Pk90/V3ig6roiKilK5N9QxTnlZntj+UJalSm8Uzdu9e7fKvVE07+LFiyr3RtE8qVSqcm8o+/6p0htF89avX69ybxTNCw0NFdUbysbIqoyn1D3mLi9PTF+UlyemN5TlqTKmUpanyphKWZ4qzxvlff/E9IayPLFjKmVZqo6nlL3mW7t2rej+UOdryPKy1P16oybS0XQBJN7Vq1cxffp0zJ8/H35+fiplPXjwAFKpFG3atIGBgQF8fX0RGRkpKuvYsWNISkpCQEAAMjIykJOTg2XLlmH+/Pmi8q5cuYL8/HzFHyVBEKCjI/5X19LSEq6uropTyPr27Yvw8HAMGTJEdKZUKkVoaChWrFghOqPQ+fPn4erqCgsLCwDAkCFDsGPHDkycOFFUXlZWFnx9fRUTWj///LOod2JKsrGxQVJSkuLrpKQktZx6qS4PHjzAxIkTMXbsWIwfP16lrLi4OMTGxsLFxQU6Ojrw8/PDzp07RecdOXIE9+7dQ0BAAHJycpCcnIyZM2dizZo1ovIiIyMRFRWFfv36AVBPj3To0EHxe9K/f3+VTwsFgNOnT6s0AVroypUraNWqFRo3bgzgxcBz5syZovPy8vLQvn17/P777wCA48ePV6pHSv4tvnz5skq9oc6/7cqyVOmNknmq9kbJvHnz5qnUGyXzVO2Nknl79+5VqTfK+tmK7Y2SecePH1epN0rmqdIbysYVJ06cgLa2tuI2lekNdY5TyssT0x/Ksm7cuIEWLVqI6o2y8sT2hrK8Y8eOwdTUVFRvKMv7+uuv4ebmJqo3yvvZiukNZXk7duwQ3RvK8sLDwzFp0qRK94ayMfLTp09F94W6x9xl5Y0cOVLU84ayvHnz5mHYsGGiekNZnkQiEd0byvKmTp2KQYMGieoNZXmCIKBLly6ieqO8n6+Y3lCWd/nyZTg5OVW6N8qqbfTo0aLHU8pe89nZ2YkeU6nzNWRZWep8vVGjaWIjpbrOy8tL5Y2wY2Njhe7duwsXLlxQS03nzp0ThgwZIuTl5Ql5eXnCu+++Kxw5ckTl3P3796u8EfaZM2eEwYMHC8+fPxcyMzOFgQMHCmFhYaLzrl+/LvTr10/IyMhQbAxdmQ3flAkPDxdGjRqlUkahf/75Rxg0aJCQnZ0tyOVy4YsvvhDWrl0rOi8iIkIYNGiQkJ+fLzx79kzo16+fcOXKFdF5hb+/z58/Fzw9PYWoqChBJpMJEyZMEI4dOyY6r9Cnn35a6Y2wS2ZlZmYKvXr1Eg4cOCAqp2ReZGSk4OXlJWRkZAhyuVyYO3eusHHjRtF5RV26dEnUpo1F8yIiIgRPT08hPT1dkEqlwvjx44XDhw+LzouNjRU8PDyE2NhYQRBebGS4evVq0XmCIAgpKSmCh4dHpTOU5d2/f1/o1auXkJSUJAiCIGzYsEHU35nCvNTUVKFXr15CZmamkJeXJ4wePVo4dOhQhTKU/S1WpTde9rd9zJgxFd60UVmWKr2hLE+V3njZY61sbyjLU6U3lOWp0htlPV6xvaEsT5XeUJanSm+UNa4Q2xsvG6dUpjfKyjtw4ICo/lCWtX79etG98bLHWtneUJa3bt060b1R1vdObG+U9XjF9oayvJ9++kl0byjLO3jwoOjeKFQ4RlbXeErZmLuyfaEsT11jqsI8dY2plD1eVcZUhXnqGlMV5qlrTFX08apjTFWYp44xVWGWKs8ZglD2az6x/fGy15CV6Q9lWaGhoWrpjdqAK41qqU2bNiEvL6/YypZRo0bhzTffFJXXq1cvhIeHY/DgwdDW1oavr6/K73Cri5eXF27cuIHBgwdDLpdj9OjR6NSpk+i8Dh06YOLEiRg9ejTy8/Ph5uam8mlCMTExsLGxUSmjkLu7O27fvo0hQ4ZAV1cXzs7OmDx5sug8R0dH+Pr6YtCgQSgoKMA777wDFxcXlevU19fHihUr8OGHHyIvLw+9evWq1P4AVWnfvn1ITk7Gli1bFB+N6+3tjRkzZojKa9WqFSZPnoxRo0ZBW1sbXbp0UcupiOri6OiIyZMn480334RMJoOvry/8/f1F5zVq1AiLFi3ClClTkJeXhzZt2uDTTz9VqcYnT56orUeaN2+OGTNmYNy4cdDW1kaTJk2waNEi0XlmZmaYOnUqRo4cCZlMpvjo1Ioo62+x2N5Q5992ZVkDBgwQ3Rtl1Sa2N9T9PFZefWJ6o6w8sb1RVl67du1E9UZZeWJ7o6w8sb1R1rjC3NxcVG+oe5yiLC89PV1UfyjL+uCDD2Bubi6qN6rjsU6bNg1mZmaiekNZ3uDBg2FqaiqqN8p6vOHh4aJ6Q1nee++9B2tra1G9oSxv0KBByMvLE9UbJdXk8RTAMRXHVBWnyngKKPs1n9j+UOdrSGVZN2/eVGtv1GQSQRAETRdBREREREREREQ1CzfCJiIiIiIiIiKiUjhpREREREREREREpXDSiIiIiIiIiIiISuGkERERERERERERlcJJIyIiIiIiIiIiKoWTRkRERFTnTZ8+Hb6+vqUuDwwMROvWrTFnzpxS102aNAnDhw9Xy/GDgoLQunVrpKamqiWPiIiISB04aURERER1Xvfu3fH48eNSkzYXL16EqakpLly4UOxyuVyO69evw9XVtTrLJCIiIqpWnDQiIiKiOq9bt24AgOvXrysuy8vLQ1hYGMaOHYukpCTcvXtXcd29e/fw7NkzThoRERHRK42TRkRERFTntWzZEhYWFsUmja5evYr8/HyMGTMGZmZmxVYbXb16FXp6eujcuTNkMhm+//579O7dG87OzhgyZAguXrxYLD8nJweLFy9Gz5490b59e4wdOxa3b98us57o6Gi4ublhwoQJkEqlan+8RERERBXBSSMiIiIivFhtdO3aNcXXFy5cgJOTE0xNTdG9e3cEBwcrrgsLC0Pnzp2hr6+PL774Alu2bMG4ceOwfv16NGvWDJMmTUJYWBgAQBAEvP/++zh69ChmzpyJ77//Hnp6ehg7diyio6NL1ZGUlITx48ejadOmWL9+PfT09Kr+wRMREREpwUkjIiIiIryYNLp58yYKCgoAvJg0Kjz9rGfPnggNDVWs+gkLC4OrqysePHiAoKAgfPbZZxg/fjw8PT2xatUquLi4YM2aNQCA8+fP49KlS/juu+8wYsQIeHl5YePGjbC0tMSGDRuK1ZCdnY1JkybB1NQUP/30E+rVq1d93wAiIiKiEjhpRERERIQXm2Hn5OQgMjISaWlpiIiIgJubG4AXk0a5ubm4ceMGEhIS8PTpU7i6uuLy5csAAE9PT8hkMsW/Xr16ISwsDFKpFCEhITAwMEDXrl0V1wOAu7s7Ll26VKyG6dOnIyIiAnPnzoWRkVH1fgOIiIiIStDRdAFERERENUHz5s1hZWWFa9euISoqCvr6+ujYsSMAwN7eHq+99hpCQ0ORlJQEIyMjODk5KfY58vT0VJqZlpaG9PR05ObmwsnJqdT1urq6xb7OysqCg4MD1qxZg99++w0SiUS9D5KIiIioEjhpRERERPSfwlPU9PT00KVLl2L7CfXs2RPXrl1DSkoKunXrBm1tbRgbG0MikWDnzp3Q0Sk9rDIzM4OxsTEsLCywcePGlx5/w4YNiI+Px4QJExAUFIShQ4eq9fERERERVQZPTyMiIiL6T/fu3XHr1i2EhYUpTk0r5Orqirt37+L69euKvY5cXFwgCAKys7Ph7Oys+Hfx4kVs3boVOjo6cHFxQWpqKgwNDYvd5vDhwzh06FCxY5ibm8Pd3R0+Pj745ptvkJaWVm2PnYiIiKgkThoRERER/ad79+64f/8+7t27p5gYKuTq6orExETcuXNHcV2bNm3Qr18/fPLJJ9i+fTsuXbqEtWvXYvXq1bC1tYWWlha8vLzg7OyMyZMn48CBA7h06RIWLVqEX375Bc2bN1dax7x585Cbm4uVK1dW+WMmIiIiKgtPTyMiIiL6j4ODAywtLSGTydC6deti15mZmcHR0RGJiYlo2bKl4vJVq1bh+++/R2BgIFJSUmBnZ4ePPvoIEyZMAABoa2tj06ZNWLVqFb755htkZWWhSZMmWL58OYYMGaK0Djs7O7z33ntYu3Ythg4dii5dulTdgyYiIiIqg0QQBEHTRRARERERERERUc3C09OIiIiIiIiIiKgUThoREREREREREVEpnDQiIiIiIiIiIqJSOGlERERERERERESlcNKIiIiIiIiIiIhK4aQRERERERERERGVwkkjIiIiIiIiIiIqhZNGRERERERERERUCieNiIiIiIiIiIiolP8H72yuP0ZHArMAAAAASUVORK5CYII=",
- "text/plain": [
- "<Figure size 1440x72 with 1 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "plt.figure(figsize=(20,1))\n",
- "sns.lineplot(x=\"Week\", y=\"IsHoliday\", hue=\"Year\", data=clean_data1)\n",
- "plt.grid()\n",
- "plt.xticks(np.arange(1, 53, step=1))\n",
- "plt.title('holidays - Per Year', fontsize=18)\n",
- "plt.ylabel('holidays', fontsize=16)\n",
- "plt.xlabel('Week', fontsize=16)\n",
- "plt.show()"
- ]
- },
- {
- "attachments": {},
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Die Feiertage fallen jedes Jahr in dieselbe Woche. Betrachtet man die Kalenderwoche des Feiertags und die Kurve der w\u00f6chentlichen Verk\u00e4ufe, so zeigt sich, dass Thanksgiving und Weihnachten haben einen Einfluss auf den Umsatz, die beiden anderen sind jedoch nicht signifikant. Aus diesem Grund lassen wir IsHoliday in der Tabelle stehen."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 54,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "image/png": 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",
- "text/plain": [
- "<Figure size 1440x576 with 1 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "plt.figure(figsize=(20,8))\n",
- "\n",
- "plt.axvline(6, 0,25000, color=\"r\")\n",
- "plt.axvline(36, 0,25000, color=\"r\")\n",
- "plt.axvline(47, 0,25000, color=\"r\")\n",
- "plt.axvline(52, 0,25000, color=\"r\")\n",
- "\n",
- "sns.lineplot(x=\"Week\", y=\"Weekly_Sales\", data=clean_data1)\n",
- "plt.grid()\n",
- "plt.xticks(np.arange(1, 53, step=1))\n",
- "plt.legend(['IsHoliday', 'Weekly_Sales'], loc='best', fontsize=16)\n",
- "plt.title('Betrachtung von Holidays und Sales', fontsize=18)\n",
- "plt.ylabel('Sales', fontsize=16)\n",
- "plt.xlabel('Date', fontsize=16)\n",
- "plt.show()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 55,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "image/png": 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",
- "text/plain": [
- "<Figure size 1440x576 with 1 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "plt.figure(figsize=(20,8))\n",
- "sns.lineplot(x=\"Week\", y=\"MarkDown1\", hue=\"Year\", data=clean_data1, marker=\"s\") \n",
- "sns.lineplot(x=\"Week\", y=\"MarkDown2\", hue=\"Year\", data=clean_data1, marker=\">\") #, palette=\"tab10\")\n",
- "sns.lineplot(x=\"Week\", y=\"MarkDown3\", hue=\"Year\", data=clean_data1, marker=\"+\", palette=\"tab10\")\n",
- "sns.lineplot(x=\"Week\", y=\"MarkDown4\", hue=\"Year\", data=clean_data1, marker=\"o\")\n",
- "sns.lineplot(x=\"Week\", y=\"MarkDown5\", hue=\"Year\", data=clean_data1, marker=\"x\", palette=\"Spectral\")\n",
- "plt.grid()\n",
- "plt.xticks(np.arange(1, 53, step=1))\n",
- "plt.title('MarkDowns - Pro Jahr', fontsize=18)\n",
- "plt.ylabel('MarkDowns', fontsize=16)\n",
- "plt.xlabel('Week', fontsize=16)\n",
- "plt.show()"
- ]
- },
- {
- "attachments": {},
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "MarkDown1: viele Einzelaktionen, gro\u00dfe Aktion kurz vor Woche 7 mit Super Bowl; \n",
- "MarkDown2: Aktion in Woche 52 vor Weihnachten, kleinere Aktion vor Woche 7 mit Super Bowl;\n",
- "MarkDown3: einzige Aktion in Woche 47 vor ThanksGiving;\n",
- "MarkDown4: viele Einzelaktionen, gr\u00f6\u00dfere Aktion in Woche 5 vor Super Bowl;\n",
- "MarkDown5: viele Einzelaktionen, gr\u00f6\u00dfere in Woche 48 zu ThanksGiving evtl. auch Black Friday"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 56,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "image/png": 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",
- "text/plain": [
- "<Figure size 1440x576 with 1 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "plt.figure(figsize=(20,8))\n",
- "sns.lineplot(x=\"Date\", y=\"MarkDown1\", data=clean_data1)\n",
- "sns.lineplot(x=\"Date\", y=\"MarkDown2\", data=clean_data1)\n",
- "sns.lineplot(x=\"Date\", y=\"MarkDown3\", data=clean_data1)\n",
- "sns.lineplot(x=\"Date\", y=\"MarkDown4\", data=clean_data1)\n",
- "sns.lineplot(x=\"Date\", y=\"MarkDown5\", data=clean_data1)\n",
- "\n",
- "sns.lineplot(x=\"Date\", y=\"Weekly_Sales\", data=clean_data1)\n",
- "plt.grid()\n",
- "plt.legend(['MarkDown1', 'MarkDown2', 'MarkDown3' 'MarkDown4', 'MarkDown5', 'Weekly_Sales'], loc='best', fontsize=16)\n",
- "plt.title('Weekly Sales - MarkDowns', fontsize=18)\n",
- "plt.ylabel('Sales', fontsize=16)\n",
- "plt.xlabel('Date', fontsize=16)\n",
- "plt.show()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 57,
- "metadata": {},
- "outputs": [],
- "source": [
- "# We include the holidays in our table to see where the holidays are located.\n",
- "holidays = {'Super Bowl': pd.to_datetime(['12-Feb-10', '11-Feb-11', '10-Feb-12', '8-Feb-13']), 'Labor Day': pd.to_datetime(['10-Sep-10', '9-Sep-11', '7-Sep-12', '6-Sep-13']), 'Thanksgiving': pd.to_datetime(['26-Nov-10', '25-Nov-11', '23-Nov-12', '29-Nov-13']), 'Christmas': pd.to_datetime(['31-Dec-10', '30-Dec-11', '28-Dec-12', '27-Dec-13']) }\n",
- "# Add column indicating which holiday follows\n",
- "clean_data1.insert(clean_data1.columns.tolist().index('IsHoliday')+1, 'Holiday', np.nan)\n",
- "for holiday in holidays: \n",
- " clean_data1.loc[clean_data1['Date'].isin(holidays[holiday]), 'Holiday'] = holiday"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 58,
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "<class 'pandas.core.frame.DataFrame'>\n",
- "Int64Index: 420212 entries, 0 to 421569\n",
- "Data columns (total 21 columns):\n",
- " # Column Non-Null Count Dtype \n",
- "--- ------ -------------- ----- \n",
- " 0 Store 420212 non-null int64 \n",
- " 1 Dept 420212 non-null int64 \n",
- " 2 Date 420212 non-null datetime64[ns]\n",
- " 3 Weekly_Sales 420212 non-null float64 \n",
- " 4 IsHoliday 420212 non-null int64 \n",
- " 5 Holiday 29560 non-null object \n",
- " 6 Temperature 420212 non-null float64 \n",
- " 7 Fuel_Price 420212 non-null float64 \n",
- " 8 MarkDown1 420212 non-null float64 \n",
- " 9 MarkDown2 420212 non-null float64 \n",
- " 10 MarkDown3 420212 non-null float64 \n",
- " 11 MarkDown4 420212 non-null float64 \n",
- " 12 MarkDown5 420212 non-null float64 \n",
- " 13 CPI 420212 non-null float64 \n",
- " 14 Unemployment 420212 non-null float64 \n",
- " 15 Size 420212 non-null int64 \n",
- " 16 Week 420212 non-null int64 \n",
- " 17 Year 420212 non-null int64 \n",
- " 18 Type_A 420212 non-null uint8 \n",
- " 19 Type_B 420212 non-null uint8 \n",
- " 20 Type_C 420212 non-null uint8 \n",
- "dtypes: datetime64[ns](1), float64(10), int64(6), object(1), uint8(3)\n",
- "memory usage: 82.1+ MB\n"
- ]
- }
- ],
- "source": [
- "clean_data1.info() "
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 59,
- "metadata": {},
- "outputs": [
- {
- "data": {
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- " <thead>\n",
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- " <th>Store</th>\n",
- " <th>Dept</th>\n",
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- " <th>Weekly_Sales</th>\n",
- " <th>IsHoliday</th>\n",
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- " <th>Fuel_Price</th>\n",
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- " <th>...</th>\n",
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- " <td>NaN</td>\n",
- " <td>46.63</td>\n",
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- "<p>5 rows \u00d7 21 columns</p>\n",
- "</div>"
- ],
- "text/plain": [
- " Store Dept Date Weekly_Sales IsHoliday Holiday Temperature \\\n",
- "0 1 1 2010-02-05 24924.50 0 NaN 42.31 \n",
- "1 1 1 2010-02-12 46039.49 1 Super Bowl 38.51 \n",
- "2 1 1 2010-02-19 41595.55 0 NaN 39.93 \n",
- "3 1 1 2010-02-26 19403.54 0 NaN 46.63 \n",
- "4 1 1 2010-03-05 21827.90 0 NaN 46.50 \n",
- "\n",
- " Fuel_Price MarkDown1 MarkDown2 ... MarkDown4 MarkDown5 CPI \\\n",
- "0 2.572 0.0 0.0 ... 0.0 0.0 211.096358 \n",
- "1 2.548 0.0 0.0 ... 0.0 0.0 211.242170 \n",
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- "4 2.625 0.0 0.0 ... 0.0 0.0 211.350143 \n",
- "\n",
- " Unemployment Size Week Year Type_A Type_B Type_C \n",
- "0 8.106 151315 5 2010 1 0 0 \n",
- "1 8.106 151315 6 2010 1 0 0 \n",
- "2 8.106 151315 7 2010 1 0 0 \n",
- "3 8.106 151315 8 2010 1 0 0 \n",
- "4 8.106 151315 9 2010 1 0 0 \n",
- "\n",
- "[5 rows x 21 columns]"
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- ]
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- "outputs": [
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",
- "text/plain": [
- "<Figure size 360x360 with 1 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "sns.lmplot(x='CPI',y='Weekly_Sales',data=clean_data1)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 73,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "<seaborn.axisgrid.JointGrid at 0x22464a460d0>"
- ]
- },
- "execution_count": 73,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": 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",
- "text/plain": [
- "<Figure size 504x504 with 3 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "sns.jointplot(x=\"Size\", y=\"Weekly_Sales\", data=clean_data1, kind=\"reg\", truncate=False, height=7)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 74,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "<seaborn.axisgrid.FacetGrid at 0x22400e1eca0>"
- ]
- },
- "execution_count": 74,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": 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",
- "text/plain": [
- "<Figure size 360x360 with 1 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "sns.lmplot(x='Temperature',y='Weekly_Sales',data=clean_data1)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 75,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "<seaborn.axisgrid.FacetGrid at 0x22401055850>"
- ]
- },
- "execution_count": 75,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": 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",
- "text/plain": [
- "<Figure size 360x360 with 1 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "sns.lmplot(x='Fuel_Price',y='Weekly_Sales',data=clean_data1)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 76,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "<seaborn.axisgrid.FacetGrid at 0x22401074130>"
- ]
- },
- "execution_count": 76,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": 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",
- "text/plain": [
- "<Figure size 360x360 with 1 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "sns.lmplot(x='Unemployment',y='Weekly_Sales',data=clean_data1)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 77,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "<seaborn.axisgrid.FacetGrid at 0x22401715d90>"
- ]
- },
- "execution_count": 77,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": 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",
- "text/plain": [
- "<Figure size 360x360 with 1 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "sns.lmplot(x='Week',y='Weekly_Sales',data=clean_data1)"
- ]
- },
- {
- "attachments": {},
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## 3.4. Test auf Korrelation"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 61,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "<AxesSubplot:>"
- ]
- },
- "execution_count": 61,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": 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PK+5ddlNecY8VVXnFtWrJbzWA/71twisuSZHfR95TZV5hcNRM5hdYTVgV3kPygBYyIoSQhqoGltsIDAyEmZkZRo8eXWotPQB49uwZpk6dCisrK3zzzTdIT0/nXX1qoAghpKFiYtk2GSUmJmLTpk34+++/4e/vDx8fHzx9+vS/4hjDrFmz4OzsjJMnT6JHjx7w8vLiXf1qH+Jbvnw5bt68icLCQsTFxaFr164AACcnJ9jb21d3cbxlZmZiwYIF2LZtW11XhRBCakY1D/Fdu3YNQqEQWlpaAIAxY8bg3LlzcHV1BQDcv38fampqMDIyAgDMnDkTGRkZvMur9gZq6dKlAID4+Hg4OTnJbcbx9PR0xMbG1nU1CCGk5sg4iy8jI6PMhkRTU1NiUdakpCS0bt2ae6ytrY2YmBjucVxcHFq1aoXffvsNsbGx6NKlCxYv5ndNG6ilSRIvX77EsmXL8P79e6iqqmLx4sXo2bMnFixYgKZNm+LBgwfIyMjAjz/+iICAADx8+BCjRo3CggUL4OfnhytXruDdu3dITk6GsbExFixYAIFAAC8vL5w9exYikQhDhw7F/Pnz8fr1a3z77bdo3rw5VFVV4enpid9++w2JiYlISkrCkCFDsHr1aqxatQpJSUlwcXHBwoUL4eTkhEuXLgEAPD09AQCzZ8+GUChE7969kZycjGPHjmHfvn2lyhRUYWE5QgipMTLeB+Xt7Y2tW7eW2u/q6orZs2dzj8ViscTnHWNM4nFRURFu3LiBgwcPok+fPti8eTPWrVuHdevW8ap+rTRQv/76K5YsWYKePXvi6dOncHFxQVBQEIDiFtnHxwcnTpzAwoULERQUBBUVFRgZGcHFxQUAEB0djYCAAGhqasLJyQkXLlyAqqoq7t27h2PHjkEgEGD+/Pk4efIkBg4ciOfPn2P37t3o0KEDTp06hR49emDLli0oKCiAubk57t+/Dzc3Nzg5OWHbtm2Ij48vt+5paWlwdnaGvr4+QkJCyizT2tq6Nl5GQgipHBknQEz7ehpsbW1L7f+w9wQAbdu2RVRUFPc4OTkZ2tra3OPWrVujU6dO6NOnDwDAwsICc+bM4VNzALXQQGVnZ+PevXtYuHAhty8nJwdpaWkAwI1VtmvXDt26dUPLli0BAFpaWtzsj5EjR6JVq1YAADMzM0REREBFRQUxMTGws7MDAOTl5aFdu3YYOHAgWrZsiQ4dOgAofoFiYmKwf/9+PHv2DO/fv0dOTg43hioLPT09AEB4eHiZZRJCiFyS8RrUx0N55TEwMICnpydSU1PRtGlTnD9/XmJl8/79+yM1NRUPHz6Erq4uLl26hF69evGufo03UGKxGE2aNJG4FvX27VuugVBW/u8GAyWlsqujqPjfjSRisRiKiooQiUSYNm0apk+fDqB4DFVRURFpaWlQVf3vnowDBw4gKCgI48ePh4GBAR4/fgz2UbdXIBBI7CsqKpKoS8n5yiuTEELkUjXfqNumTRvMmzcPTk5OKCwshIODA/r27QtnZ2fMmTMHffr0wbZt2+Dm5obc3Fy0bdsWGzZs4F1ejU8z/+STT/C///2Pa6D++ecfODo6VuocoaGhyMzMRH5+Pk6fPg0jIyMIhUIEBAQgOzsbRUVFEsOGH/rnn38wYcIEWFlZIT8/Hw8fPoRYLIaSkhKK/v8CoqamJt6/f4/U1FQUFBQgNDS0zHrIWiYhhMgDViSSaasMS0tLnDp1CkFBQXB2dgYA/Pnnn9ywnp6eHo4dO4bTp09jz5493KgYH7VyDcrd3R3Lli3D7t27oaysjE2bNlVqYkGLFi3g7OyMtLQ0WFlZYdiwYQCAhw8fYvz48RCJRBg2bBhsbW3x+vVridhp06Zh2bJl8PLygoaGBvr374/4+HgMGjQI7dq1w9SpU3HgwAF8++23cHBwQNu2bbkX+mMmJiZllkkIIXKpnmeSELCPx7vkjJ+fH27cuMF7Fog8udBmAq+4dIXazUiVosRvVuIXyOQV1+fWJl5x7+y+5hUX+fhTXnFi8HtdOqvye13U1Ap4xQHA4exWvOI6F/J7jqo8P0byeM6Atf9rKK84n2lhvOI6FhXyinuryDNHEgDHhIO8Y0tkr5oi03HqblUvqyZQLj5CCGmo6nkPSu4bKDs7O27WHCGEkEqgBQsJIYTIJepBEUIIkUuiys3QkzfUQBFCSAPFaIiPEEKIXKIhPkIIIXKJGihCCCFyqZpTHdU2aqAIIaShoh4UIYQQecSKqAdFCCFEHtEsPiKrOGV+ebmaifh10zXE/O6BYEX8lhCJFXzCK64dz5x6Lf328orr/AW/BdTu5zbjFdfd14lXXP62nbziAKBXEL/3zKsm/HLjmSiWXi5cFleL+L2mogvnecV1F/N7fkkCFV5x/yrX8RAbDfERQgiRS9RAEUIIkUdyvlhFhWp0wcL4+Hjo6OhgyZIlEvtjY2Oho6MDPz8/mc9jYmJSar+npycMDQ1hbW0NKysrWFhY4ODBmk8bn5iYiKFD+aX7J4SQWlMklm2rhMDAQJiZmWH06NE4dOhQucdduXKlzM/tyqjxHpSWlhZCQ0MhEom45dHPnDmDFi1aVMv5J06ciNmzZwMAUlNTMW3aNKioqGDcuHHVcv6PXb16FWvWrEFycnKNnJ8QQqoLq+YhvsTERGzatAl+fn5o0qQJJk6cCH19fXz++ecSx6WkpGD9+vVVLq/Gl3xXV1dHjx49EBkZye37559/YGBgAAA4ePAgxo0bBwsLC9ja2uLZs2cAilevnTt3LsaMGYPU1FQuNigoCFZWVhL7SrRo0QKzZs3C33//DaD4Rfruu+9gaWkJW1tbhISEIDU1lVuRFwCGDRuGM2fOAAB27dqF3bt3w9PTE25ubpg6dSpMTEywY8cO7vhjx47B09OzGl8hQgipIWIm2yaja9euQSgUQktLC2pqahgzZgzOnTtX6jg3Nze4urpWufo13kABgKmpKYKCggAAMTEx0NHRgbKyMrKyshAcHIwDBw7g1KlTGDFihESX0cjICEFBQVxvKywsDNu2bcPevXvL7YF1796da+RWrlwJoVCIwMBAbNmyBb/99hvEYjE+/fRTPH78GP/++y9EIhFu3LgBAAgNDYWxsTEA4NGjR9izZw+OHj0KLy8vZGQUz1Ly9PRE9+7da+aFIoSQ6iSWbcvIyEB8fHypreRzr0RSUhJat27NPdbW1kZiYqLEMX/99Rd69uwJPT29Kle/VhooExMThISEQCwW4+zZszA1NQUAaGhoYOPGjTh9+jQ2btyIy5cvIycnh4v78AmmpaVh9uzZsLGxQatW5S9nLRAIoKqqCgCIiIiAg4MDAKBjx47Q09PDnTt3YGRkhPDwcERERMDJyQnR0dHIzMxESkoKunbtCgDQ19dHkyZN0LJlS2hpaSEzk9+y3YQQUleYmMm0eXt7Y+TIkaU2b29vifOJxWIIBP9N1WeMSTx+/Pgxzp8/j++//75a6l8rDZS6ujp0dXURHR2NiIgIbnjvzZs3mDBhAjIzM2FkZARbW1uJWScqKv/deyAQCLB9+3bs2bOnVIv9oUePHnGNzMczWBhjEIlEGDFiBMLDw3H9+nV8+eWXUFBQQGBgoMTEh4/Lru+zYQghjZCMQ3zTpk3DxYsXS23Tpk2TOF3btm0lrr8nJydDW1ube3zu3DkkJyfD3t4eM2bMQFJSEiZPnsy7+rXSQAHFw3wbN25E7969oaRUPDdDTU0NnTp1wldffYU+ffogODgYonIW2NLS0sKQIUMwadIkrFq1qsxjkpKSsHPnTjg6OgIAhEIhjh07BgB49eoVbt68iX79+qFXr154/vw5Xrx4ga5du0JfXx87duzghvcIIaQhYEVMpk1TUxMdOnQotWlqakqcz8DAAOHh4UhNTUVubi7Onz8PIyMj7vdz5sxBUFAQAgIC4OXlBW1tbW5OAB+1dh+UsbExFi1ahB9++IHbp6ysDLFYDDMzMzDGMHjwYDx58kTqeWbMmAErKysEBwcDAI4cOYLg4GCulzNhwgSYm5sDABYtWoQlS5Zw09lXrVrFtfYDBw5Ebm4ugOKG7OjRoxg8eHC1P29CCKkz1ZzpqE2bNpg3bx6cnJxQWFgIBwcH9O3bF87OzpgzZw769OlTreUJGI1d1ZqD7abwilPl+SdS5hmnq5XGK+5QHr9bBwbn8ftf1FmN33VBnRtbeMX591nMK66jIJdXnKKA/3/NF2I1XnG5CvxSAXUoKuAVl6zAL/1XF4Wcig8qw7sifimLshT4pf9KU+T3egKAc3zV7+lMtR0u03EtTlytclk1gTJJEEJIQ1W/c8VSA0UIIQ1VPV+vkBooQghpqFhRXdegaqiBIoSQhop6UIQQQuQRDfERQgiRS9RAEUIIkUvUQBFCCJFPjP99WPKAGihCCGmgxEXUQBFCCJFDNMRHCCFELjEa4iOyUkTtpj1U4pmLT+0TfnnVOmfy+88gBr+4+7nNeMXF8sypZ3N3Ja84P57lfVJOZn+Z8FyngG/+xlzwy1X3P555Cl+JmvKK45saT4Hn69JUXLcNBPWgCCGEyCVWxw1kVdXoelDx8fHQ0dHBkiVLJPbHxsZCR0eHWwZDlvOYmJiU2u/p6QlDQ0NYW1vDysoKFhYWOHiw6hmAyyMSibBkyRJYWFjA0tISgYGBNVYWIYRUFWOybfKqxntQWlpaCA0NhUgkgqJi8TDAmTNn0KIFv6UZPjZx4kTMnj0bAJCamopp06ZBRUUF48aNq5bzf+jkyZPIysrCqVOnkJqaClNTUxgbG0NDQ6PayyKEkKoSF9XamrQ1osZrr66ujh49eiAyMpLb988//3DLvh88eBDjxo2DhYUFbG1t8ezZMwCAiYkJ5s6dizFjxiA1NZWLDQoKgpWVlcS+Ei1atMCsWbO4FRxTUlLw3XffwdLSEra2tggJCUFqaiqGDRvGxQwbNgxnzpwBAOzatQu7d++Gp6cn3NzcMHXqVJiYmGDHjh0AAFtbW2zYsAFA8eq9ysrKUFbmt54NIYTUtPreg6qV5tXU1BRBQUEAgJiYGOjo6EBZWRlZWVkIDg7GgQMHcOrUKYwYMQKHDh3i4oyMjBAUFMT1tsLCwrBt2zbs3bu33B5Y9+7duUZu5cqVEAqFCAwMxJYtW/Dbb79BLBbj008/xePHj/Hvv/9CJBLhxo0bAIDQ0FBu2fdHjx5hz549OHr0KLy8vJCRkQEAUFJSwqJFi+Dg4IDx48dDRYXfAmiEEFLTmFgg0yavaqWBMjExQUhICMRiMc6ePQtTU1MAgIaGBjZu3IjTp09j48aNuHz5MnJy/lspU09Pj/s5LS0Ns2fPho2NDVq1alVuWQKBAKqqqgCAiIgIODg4AAA6duwIPT093LlzB0ZGRggPD0dERAScnJwQHR2NzMxMpKSkoGvXrgAAfX19NGnSBC1btoSWlhYyM/9bvXX16tUIDQ3F+fPnERYWVn0vFCGEVCPGBDJtlREYGAgzMzOMHj1aokNRIjg4mJsX8P333yM9PZ13/WulgVJXV4euri6io6MRERHBDe+9efMGEyZMQGZmJoyMjGBra4sPV6D/sHciEAiwfft27NmzB4mJieWW9ejRI66R+Xg1e8YYRCIRRowYgfDwcFy/fh1ffvklFBQUEBgYiKFDh5ZbNmMM9+7dw4sXLwAAzZs3x7Bhw/Do0SP+LwwhhNQgJpZtk1ViYiI2bdqEv//+G/7+/vDx8cHTp0+532dlZWHZsmXw8vLCyZMnoaOjA09PT971r7UraKampti4cSN69+4NJaXiuRlqamro1KkTvvrqK/Tp0wfBwcEQlXPvh5aWFoYMGYJJkyZh1apVZR6TlJSEnTt3wtHREQAgFApx7NgxAMCrV69w8+ZN9OvXD7169cLz58/x4sULdO3aFfr6+tixYwc3vFeeO3fuwN3dHWKxGFlZWQgLC8OAAQP4viSEEFKjRGIFmbaMjAzEx8eX2koubZS4du0ahEIhtLS0oKamhjFjxuDcuXPc7wsLC7F06VK0adMGAKCjo4M3b97wrn+t3QdlbGyMRYsW4YcffuD2KSsrQywWw8zMDIwxDB48GE+ePJF6nhkzZsDKygrBwcEAgCNHjiA4OJjr5UyYMAHm5uYAgEWLFmHJkiXcdPZVq1ZBW1sbADBw4EDk5hbfJCgUCnH06FEMHjxYatkTJ07Eo0ePYGlpCQUFBTg6OqJ///78XhBCCKlhsl5f8vb2xtatW0vtd3V15WZJA8WdgNatW3OPtbW1ERMTwz1u3rw5vvzySwBAXl4evLy8MHXqVL7Vh4B9PA5Gaszhdo684pR5/oWaivndRt73syReccEJn/KKayHiV888Ab+Lu3yHDWo9k4SYfyaJbAV+mR345hbV5Pk3bKWYzyvutViVVxy/VwXg+5fIUeA/SDUloer3dMZ2M5PpuPbRR0r1lgBAU1MTmpqa3OMdO3YgPz8fc+fOBQD4+vri3r17WLFihURcZmYmXFxc0KFDB6xZs4Z3/SmTRC3K5/mByjf9DF/Rr9rwC+T5v7+zambFB5Whu68Tr7jbNod5xfFtaOx4NmypDl/zigOAkEftecWl88wF9Lkgj1dcmKI6r7ipPV7xirt3W5tXXKqA3+0kyXX8CStrD+rjhqg8bdu2RVRUFPc4OTmZG5UqkZSUhG+++QZCoRC//fZb5Sr8kfp9FxchhJByiZlApk1WBgYGCA8PR2pqKnJzc3H+/HkYGRlxvxeJRJg5cyZMTU2xaNEiCHh+KS9BPShCCGmgqjubeZs2bTBv3jw4OTmhsLAQDg4O6Nu3L5ydnTFnzhy8ffsWDx48gEgk4u597d27N1avXs2rPGqgCCGkgRLVwE24lpaWsLS0lNj3559/AgD69OmDhw8fVltZ1EARQkgDRetBEUIIkUv1fY42NVCEENJAVWYChDyiBooQQhooGuIjhBAil6gHRQghRC6JqIEihBAij2iIjxBCiFzilyFRflADVYuaimt3zqci+JWXJeCXAUuN5/NTUyvgFZe/bSevOEVBxTnHyvJJOUvBVIRvTr0Wx/byigOAFr0W8oqL45lzTkmR30dhr/wifuW14pf4UUO5kFfcC8Zv5ey6biAYqAdFCCFEDtXyd+JqV6PJYuPj46Gjo4MlS5ZI7I+NjYWOjg63TpMs5zExMSm139PTE4aGhtzywhYWFjh4sOop6qUZOXIkrK2tua0qi3ERQkhNEkFBpk1e1XgPSktLC6GhoRCJRFBULO6WnzlzBi1atKiW80+cOJFbUCs1NRXTpk2DiooKxo0bVy3n/1BaWhqUlZUREBBQ7ecmhJDqVtdDjFVV402nuro6evTogcjISG7fP//8AwMDAwDAwYMHMW7cOFhYWMDW1hbPnj0DAJiYmGDu3LkYM2YMUlNTudigoCBYWVlJ7CvRokULzJo1C3///TcAICUlBd999x0sLS1ha2uLkJAQpKamYtiwYVzMsGHDcObMGQDArl27sHv3bnh6esLNzQ1Tp06FiYkJduzYAQC4e/cuGGOYOHEibG1tcfbs2Wp+tQghpPowCGTa5FWt9O1MTU251OsxMTHQ0dGBsrIysrKyEBwcjAMHDuDUqVMYMWIEDh06xMUZGRkhKCiI622FhYVh27Zt2Lt3b7k9sO7du3ON3MqVKyEUChEYGIgtW7bgt99+g1gsxqefforHjx/j33//hUgkwo0bNwAAoaGhMDY2BgA8evQIe/bswdGjR+Hl5YWMjAwUFBRg2LBh2L9/Pzw9PbFu3Tr8+++/Nfa6EUJIVYhl3ORVrTRQJiYmCAkJgVgsxtmzZ2FqagoA0NDQwMaNG3H69Gls3LgRly9fRk5ODhenp6fH/ZyWlobZs2fDxsYGrVq1KrcsgUAAVdXi5aAjIiLg4OAAAOjYsSP09PRw584dGBkZITw8HBEREXByckJ0dDQyMzORkpKCrl27AgD09fXRpEkTtGzZElpaWsjMzMSoUaPg5uYGVVVVdOjQAV9++SXCwsKq/fUihJDqQA2UDNTV1aGrq4vo6GhERERww3tv3rzBhAkTkJmZCSMjI9ja2oJ9kH5XReW/qZ0CgQDbt2/Hnj17kJiYWG5Zjx494hoZ9lEqX8YYRCIRRowYgfDwcFy/fh1ffvklFBQUEBgYiKFDh5ZbNmMMly9fxt27dyXOqaREEyEJIfKJhvhkZGpqio0bN6J3797ch7qamho6deqEr776Cn369EFwcDBE5dxroqWlhSFDhmDSpElYtWpVmcckJSVh586dcHR0BAAIhUIcO3YMAPDq1SvcvHkT/fr1Q69evfD8+XO8ePECXbt2hb6+Pnbs2MEN75Xn9evX2LZtG8RiMVJSUnDp0iWMGDGC5ytCCCE1q0ggkGmrjMDAQJiZmWH06NESl2RKxMbGws7ODmPGjMGiRYtQVMTvXjegFhsoY2NjxMbGwszMjNunrKwMsVgMMzMz2NraonPnzoiPj5d6nhkzZuDJkycIDg4GABw5cgTW1tawsbGBs7MzJkyYAHNzcwDAokWLEBERAUtLS3z//fdYtWoVtLW1IRAIMHDgQK6nJRQKkZWVhcGDB0ste+LEiWjdujUsLCwwZcoU/Pzzz2jfvn1VXhZCCKkxTMZNVomJidi0aRP+/vtv+Pv7w8fHB0+fPpU4Zv78+ViyZAmCgoLAGIOvry/v+gvYx+NgpMb4fOrIK47fPfOAhphf5oN0Bb4l8jOweQqvuNaD+X0zexzML5NEchG/bAIDe7zlFVeVTBIhPDNJ3Fbhl0nCBJm84pLzm/KK+2JUEq+4p1f5/e3vMQ1ece+q8F/pp7iq39Pp13ayTMeNerwTGRkZpfZrampCU/O/1+zEiROIjIzEmjVrAADbtm0DYwyurq4AikeZpk2bxnUgoqKisGXLFvz111+86k8XUGrRTRV+lyMH5fPr6KYp8vvfoczzK0tPtfe84g5nlz/pRZpeQfwqKqrkkAaH53hDyCN+vWy+6YoAwOj+Wl5xhwb9wivus3x+H+CKAn5/w5vB/N4zCjzTfz1tyu//rnVhLq+46iKW8b3u7e2NrVu3ltrv6urK3WcKFF9Gad26NfdYW1sbMTEx5f6+devWUucMVIQaKEIIaaBkbY6nTZsGW1vbUvs/7D0BgFgshuCDRo8xJvG4ot9XFjVQhBDSQMna7/t4KK88bdu2RVRUFPc4OTkZ2traEr9PTk7mHqekpEj8vrLkNwkTIYSQKqnuWXwGBgYIDw9HamoqcnNzcf78eRgZGXG/b9++PVRUVBAdHQ0ACAgIkPh9ZVEDRQghDVR1z+Jr06YN5s2bBycnJ9jY2MDCwgJ9+/aFs7Mzd4+oh4cH1q5di7FjxyInJwdOTk68609DfIQQ0kCJa+AeXEtLS1haWkrs+/PPP7mfdXV1uftPq4oaKEIIaaDkOY2RLKiBIoSQBqq+3+RKDRQhhDRQRfKbZk8m1EARQkgDRUN8hBBC5BKjHhSR1TdN03jF3csre3HGihQI+N1FoMD4fe96l80vr1pnBX7/i1414RfXnF+KQijzTFuZrsivnnECfnnxAP4pi3ZFbeAVt7/fEl5xGjy/4gc24ffe7iLi95FnkMsv72Mm+P8NqwP1oAghhMglaqAIIYTIpfo+i6/CfnJ8fDxMTExK7dfR0amRCkkzdepUXL9+vdbLLc/UqVPrugqEEFKuIoFsm7yiHlQV3Lhxo66rQAgh5WrUQ3x+fn4IDQ1Feno6Xr16BUNDQyxbtgwA4OXlhbNnz0IkEmHo0KGYP38+Xr9+DRcXF3Tp0gVPnz5Fz5490b9/f5w4cQLp6enYtm0bunbtChMTE4wdOxbXrl0DAKxZswY9e/aUKHvnzp04efIkFBUVYWhoiPnz58PT0xOMMcybNw8AsGDBAhgZGSEkJARNmzbFgwcPkJGRgR9//BEBAQF4+PAhRo0ahQULFkAkEmHDhg24ceMGRCIR7Ozs8NVXX+H69evYtWsXVFVV8e+//0JHRwceHh7YsKH4YvK4ceNw9OjRqryMhBBSIxr8EF9Fbt26hS1btuDkyZO4fPkyHj16hJCQENy7dw/Hjh2Dv78/EhMTcfLkSQDAo0eP4OzsjICAANy8eROvX7+Gj48PLCws4OPjw51XTU0N/v7+mDNnDn799VeJMq9evYpLly7h+PHjOHHiBF6+fIkjR47A3t4egYGBYIwhNzcXERERGDlyJIDihbR8fHwwY8YMLFy4EMuXL4e/vz98fX2RmZnJLUt84sQJHDt2DBcvXuTSyt+6dQtLlizB2bNnkZCQgLCwMLi5uQEANU6EELklFsi2yasKe1AKCqXbsA8Xoerfvz80NIpX0+zYsSPS09MRHh6OmJgY2NnZAQDy8vLQrl07DBw4EK1ateJ6Q23btsWQIUMAAO3atUN8fDxXxvjx4wEAJiYmWLBgAVJTU7nfRUREwNzcHE2bFk9rtre3h7+/PxwdHdG+fXtERkYiISEBw4cPh4pK8TLdJSnf27Vrh27duqFly5YAAC0tLa7OsbGxiIiIAADk5OTg0aNH+Pzzz9GtWze0bdsWANC1a1ekp6fL8NISQkjdavBDfJqamsjMzJTY9+7dOzRr1gwAuAYAAAQCARhjEIlEmDZtGqZPnw4AyMjIgKKiItLS0tCkSROJcymWsyy5ktJ/VROLxRLHicWlX/aiouL7FOzt7XHq1CkkJCRILFWsrPzf/QgfnruESCTC/PnzMXr0aABAamoq1NXVcfv27TKfIyGEyLv6/klV4RCfhoYGOnXqhKCgIG6fj48P1/Mpi1AoREBAALKzs1FUVAQXFxeJeFmcPn0aAHDhwgV07dqVaxBLzn/69Gnk5eWhqKgIx48fh1AoBACMHTsW4eHhSElJgZ6enszlCYVC+Pr6orCwENnZ2Zg8eTJu374tNUZRUZFrGAkhRN4Ugcm0ySuZJkm4u7tj2bJl2LZtGwoLC6Gjo4MlS5bgypUrZR5vYmKChw8fYvz48RCJRBg2bBhsbW3x+vVrmSt28+ZNHDt2DE2bNsW6deskfmdsbIzY2FjY29ujqKgIQ4cOxZQpUwAAqqqq6NevH7p37y5zWQAwceJEvHz5Era2tigqKoKdnR309fWlTmsfOXIkrK2t4efnJ9HLIoQQeSC/TY9sBEwOx6tMTEzw119/oUOHDpWKY4whOzsbEyZMwP79+9G6desaqiE/j3uM5RV3L41fqqPcMq4fyqJpGUOosmiNAl5xLxVUecW94zkHtb6kOsquwsXr+wp5vOJqP9URv9f0RhN+f0S+qY66FvAbKVGtwlUgk0Rf3rEllnVylO24l4eqXFZCQgLmz5+Pd+/eoXPnzvDw8IC6urrEMUlJSVi4cCFSUlKgoKCAX375RepoXIO6D+ru3bv49ttv4eLiIneNEwAczG3JK64Pzw8qQ+1EXnFRidq84h4r8mtomon4fUiZKGbwikvO55czMBdlXy+tyOcCfo2FkiL/D7fP8jV4xfFtaL66vYJXXECfxbziDPL5/S0sT4/nFedsu59X3OE3/BMLVMfFg9qcobd8+XJMnjwZ5ubm2LZtG7Zv34758+dLHLNhwwaYmJjA0dERz549w9SpUxESElL+XITaqHhlXbp0iVdc37596eZZQgj5f2IZB/kyMjKQkVH6C5+mpiY0NTUrjC8sLERkZCS2bdsGALCzs8OUKVNKNVBffvklN1+gU6dOyM/PR05ODj755JMyzyuXDRQhhJCqk3Ug1NvbG1u3bi2139XVVWI2dHnS0tKgoaHBzZBu3bo1EhNLj+CMGTOG+3nPnj3o0aNHuY0TQA0UIYQ0WLL2oKZNmwZbW9tS+8vqPZ09exZr166V2NepUyfu3tgSHz/+0P79++Hj44ODBw9KrRc1UIQQ0kDJenVX1qE8ADA1NYWpqanEvsLCQujr60MkEkFRURHJycnQ1i77WvaGDRtw9epVHDp0iEuAUJ4qpzoihBAin8QyblWlrKyMQYMG4cyZMwAAf39/LnvPh/bv34/r16/j8OHDFTZOAPWgCCGkwZJ1iK86LF26FAsWLMCOHTvw6aef4vfffwcAHD58GElJSZgzZw62bdsGDQ0NiaWKvLy80KZNmzLPSQ0UIYQ0ULV5k2v79u1x4MCBUvsnTZrE/RwZGVmpc1IDRQghDZSonueSoAaKEEIaqAafzZwQQkj9VJvXoGoCNVC1qG9+7ZZ3920rXnGdFHN4xbVqmcUr7p/ksi+QVuRqUbOKDypDawV+/2n/J8jlFRemqF7xQWXolc8/2Y2igN9z1OD5lZtvyiLruyt5xa0cxK88gblPxQeVwRr80mNZtxzBK6661O/miRooQghpsKgHRQghRC7V90kSDfZG3enTpyM4OJh7vH79evTv3x8FBf8tCTF06FCJZeZlYWJiUukYQgipC7V1o25NabANlFAoRHR0NPf42rVr6NevH7fv5cuXUFNTq/SaU4QQUl8wGf/JqwbbQA0ZMgS3bt0CACQmJqJJkyYYM2YMwsLCAABRUVEwNDSEv78/bG1tYW1tjd9++w35+cUzGUJCQuDg4AAbGxu4uroiLS1N4vzPnz/H6NGjK1wWnhBC6gr1oORUr169EBcXh/z8fISFhcHQ0BCGhoYSDZS2tjZ8fX1x5MgRBAQEoGXLltizZw9SU1OxceNG7NmzB/7+/hg6dCg8PDy4c799+xaurq5Ys2YN+vXrV0fPkBBCpBMzJtMmrxrsJAlFRUXo6enh7t27CAsLg6OjIzp27Ii8vDykp6fj1q1b6NGjB16+fInx44tX2SwsLETPnj1x584dvHnzBk5OTgAAsViMZs3+m9L8ww8/oE+fPhg0aFCdPDdCCJGF/DY9smmwDRRQfB3q5s2biImJgbu7O4Diob+LFy+iefPmYIzB1NQUbm5uAIDs7GyIRCLcuHEDAwYMwM6dOwEA+fn5yM7O5s67aNEibNu2DVeuXMGIESNq/XkRQogsRHI9gFexBjvEBxQ3RgEBAejevTu30qOhoSH27dsHQ0ND6Ovr48KFC3j37h0YY1i2bBm8vb2hp6eH27dv4/nz5wCA7du3Y8OGDdx5+/bti2XLlmHFihXIyeF3UyshhNQ0ugYlx7p37473799j6NCh3D6hUIhnz57BwMAAurq6cHV1xbRp02Bubg6xWIwZM2agdevWWLNmDebOnQtLS0vcv38fv/76q8S5Bw8eDH19fWzevLmWnxUhhMhGDCbTJq8a9BAfAPzzzz8Sjz/55BPcv3+fezxu3DiMGzeuVJyJiQlMTExK7b906RL388fLHhNCiDyR5ynksmjwDVRjliPg10GOEfDLHfe/t014xdkfGlrxQWUQXTjPKy72IL//tK9E/PKxTe3xilecUitFXnEAcDOYXx7GwCb83jMG+fzqyjen3uIofjn8/HnmDBTwigIU6niGnDwP38miQQ/xEUJIY8YYk2mrDgkJCXB0dMTYsWMxa9YsiYllH8vKysKoUaNw/fp1qeekBooQQhqoIjCZtuqwfPlyTJ48GefOnUPv3r2xffv2co9duXIlMjIyKjwnNVCEENJAyZrqKCMjA/Hx8aU2WRoRoPge0sjISIwZMwYAYGdnh3PnzpV57JkzZ6Curg4dHZ0Kz0vXoAghpIGSdYaet7c3tm7dWmq/q6srZs+eXWF8WloaNDQ0uNt5WrdujcTExFLHJSQkwNvbG97e3nB2dq7wvNRAEUJIAyXr9aVp06bB1ta21H5NTc1S+86ePVtqBnOnTp0gEEhOJfn4sVgsxqJFi7B48WKoqqrKVC9qoAghpIGSdRafpqZmmY1RWUxNTWFqaiqxr7CwEPr6+hCJRFBUVERycjK0tbUljnn27BmePXuGRYsWAQDi4uLg5uaGlStXQigUllkWNVCEENJA1VaqI2VlZQwaNAhnzpyBpaUl/P39YWRkJHHM559/jqtXr3KPp06dCldXV+jr65d7XpokQQghDVRtTjNfunQpfH19YWZmhqioKMydOxcAcPjwYfzxxx+8zkk9KEIIaaBqM41R+/btceDAgVL7J02aVObxZR37MWqgCCGkgaJUR0Rmb5X4JUxpV8hvHLlv81RecTHvW/KKS1Lk93bymRbGK667mN/rmSHml5JJkWe+m3u3tSs+qAwayoX8CgSgwPODqYuI39/Q8vR4XnECcx9ecXxTFtnc5ZciSbOjMa84/ZbdeMUBgB3vyP/I82KEsqAGihBCGqj63TxRA0UIIQ1WUT1PF1vvGqjly5fj5s2bKCwsRFxcHLp27QoAcHJygr29fY2W/fjxY1haWmLLli1cSg9CCJFX1TVDr67UuwZq6dKlAID4+Hg4OTkhICCg1so+fvw4xo4dCx8fH2qgCCFyT54XI5RFvWugyrJ582YwxjBv3jwAwIIFC2BkZISQkBCoqKjg7t27yM7OxqxZs2BjY4Ps7GysWLECT548gUgkgrOzMywsLKSWUVhYiMDAQBw6dAgTJ05EXFwcPvvss9p4eoQQwkt9n8XXIG7Utbe3R2BgIBhjyM3NRUREBEaOHAkAePXqFXx8fODt7Y0NGzYgOTkZO3bsQK9eveDn54dDhw5h586dePVK+qJyV69eRbt27dC5c2eMGjUKPj78Zh8RQkhtqc0bdWtCg+hBdezYEe3bt0dkZCQSEhIwfPhwqKioAChO+66srIy2bdtiwIABiI6OxrVr15CXl4fjx48DAHJycvDkyRN07Nix3DKOHz/O9bLMzMzw888/44cffkCTJvymLBNCSE2jIT45YW9vj1OnTiEhIUEiPbyi4n9LUYvFYigpKUEsFsPd3R29evUCAKSkpKBZs2blnvvdu3cIDQ3F/fv38ddff4Gx4vVTLly4AHNz85p7UoQQUgUiVr9n8TWIIT4AGDt2LMLDw5GSkgI9PT1u/9mzZ8EYw+vXrxETE4OBAwdCKBTi8OHDAICkpCRYWVnhzZs35Z47ICAAQqEQISEhuHTpEi5fvoyZM2fiyJEjNf68CCGEL1kXLJRXDaYHpaqqin79+qF79+4S+/Py8mBvb4+CggKsWLECzZs3h6urK5YtWwYLCwuIRCLMnz9f6oSHEydOcBMwSjg6OmL37t34999/uanuhBAiTyiTRB3p0KEDLl26BKD4QmB2djYePHiAX375ReK4sWPHws5OMmmIhoYGPDw8ZC4rMDCw1L4WLVrgzp07PGpOCCG1Q557R7Kotw3Uh+7evYtvv/0WLi4uaN26Na9zREVFYeXKsvN0eXl5oU2bNlWpIgCgkGcut1wFfiOx57Na8Ypry/NN/VSZVxgM8vjlnEsSqPCKK1Lg94dQ4PltNFXA74V5wfg9PwB42pTftQeD3CJecc62+3nFWaMprzie/5V459TLeHWZV9y0gT/xiqsu1IOSA3379sWNGzdK7V+3bp3M5xg0aFCt3vRLCCE1rb5PkmgQDRQhhJDS6vsQX4OZxUcIIUSSmDGZtuqQkJAAR0dHjB07FrNmzUJ2dnapYwoKCrBq1SrY2NjA3NwcYWHSl9qhBooQQhqo2pxmvnz5ckyePBnnzp1D7969sX379lLH7N69G2lpaThx4gQ2b96MhQsXSs1kQQ0UIYQ0UIyJZdoyMjIQHx9fasvIyJCpnMLCQkRGRnJJtO3s7HDu3LlSx509exbOzs4QCATo1q0b9u3bJ7WBomtQhBDSQMma6sjb2xtbt24ttd/V1VUiM0950tLSoKGhASWl4ialdevWSExMLHXcy5cvERkZiRUrVkAkEmHevHn4/PPPyz0vNVCEENJAyTqLb9q0abC1tS21X1NTs9S+s2fPYu3atRL7OnXqBIFAcvL/x48BQCQS4e3btzh06BAePXqEb7/9FmfPnsUnn3xSZr2ogSKEkAZK1kzlmpqaZTZGZTE1NYWpqanEvsLCQujr60MkEkFRURHJycnQ1tYuFduqVSuYm5tDIBBAV1cXbdu2xfPnz9G3b98yy6JrUIQQ0kDV1iw+ZWVlDBo0CGfOnAEA+Pv7w8jIqNRxxsbG3DGvXr3Cmzdv0Llz53LPSw0UIYQ0ULU5i2/p0qXw9fWFmZkZoqKiMHfuXADA4cOH8ccffwAAfv75ZyQlJcHc3BwzZ87EqlWryh3eAwABk+fVqhqYV4NH8oqLfsUvzdJdFX4JYXoU8ArDgFbJvOLC35UeCpDFv8r83rqfivi9LjyzByGZ50B6VXIAGIlK34Mii8wifmmZRqf9wyvuSMsRvOL4pp3aopTEK66dYvkfotJ4R2/kFQcAyq268I4t0aaZrkzHJaY/rHJZNYGuQRFCSANFCxYSQgiRSyIx5eKrVcuXL8fNmzdRWFiIuLg4bi0mJycn2Nvb11i5WVlZ2LhxIyIjI6GoqAhNTU0sWLCAW5WXEELkTX2/glPvGqilS5cCAOLj4+Hk5FQrGcjFYjGcnZ2hr68Pf39/KCkpISIiAs7Ozjh9+jSaN29e43UghJDKoiE+ObB582YwxrhVbxcsWAAjIyOEhIRARUUFd+/eRXZ2NmbNmgUbGxtkZ2djxYoVePLkCUQiEZydnWFhYVHu+a9fv443b95gzpw5UPj/tZmEQiHWrl0LcT3vQhNCGq763oNqENPM7e3tERgYCMYYcnNzERERgZEji2fMvXr1Cj4+PvD29saGDRuQnJyMHTt2oFevXvDz88OhQ4ewc+dOvHr1qtzzP3jwALq6ulzjVGL48OFo2bJljT43QgjhqzazmdeEBtGD6tixI9q3b4/IyEgkJCRg+PDhUFEpXo3Uzs4OysrKaNu2LQYMGIDo6Ghcu3YNeXl5OH78OAAgJycHT548QceOHcs8v4KCAnc+QgipL2jBQjlhb2+PU6dOISEhQSK5oaKiIvezWCyGkpISxGIx3N3duQkOKSkpaNasWbnn7t27N/7++28wxiTyS/3+++8wMDCAUCisgWdECCFVQ0N8cmLs2LEIDw9HSkoK9PT0uP1nz54FYwyvX79GTEwMBg4cCKFQiMOHDwMAkpKSYGVlhTdv3pR77kGDBqFly5bYunUrRCIRACA0NBR+fn5SM/ESQkhdqs1MEjWhwfSgVFVV0a9fP3Tv3l1if15eHuzt7VFQUIAVK1agefPmcHV1xbJly2BhYQGRSIT58+fjs88+K/fcAoEA27dvx9q1a2FhYQElJSU0b94cXl5eaNWqVU0/NUII4aW+96DqbQPVoUMHXLp0CUDxHyE7OxsPHjzAL7/8InHc2LFjYWdnJ7FPQ0MDHh4elSqvRYsWcHd3r1qlCSGkFlEDJQfu3r2Lb7/9Fi4uLmjdujWvc0RFRWHlypVl/s7Lywtt2vDLh/ehjpEX+cXxLM+GZ1xtq3rGMVLXiuq6AjKyq/iQBqWw4HVdV6FKKFksIYQQudRgJkkQQghpWKiBIoQQIpeogSKEECKXqIEihBAil6iBIoQQIpeogSKEECKXqIEihBAil6iBIoQQIpeogSKEECKXqIEihFRKQUFBXVeBNBLUQNVD6enppfa9fl25nFtZWVkyH2tubo7du3cjOTm5UmUAQGBgIDZt2oTc3Fz4+/tXKjYnJwcPHz4EYww5OTmVLltWsbGxuHTpEjIzMyX2X758ucL6lXxYX7t2Dfv27cOdO3cqXf7evXsrPCYxMZH7+dmzZzhw4AAOHz4sdZmY6jBhwgSJx2KxGPb29jVSVkxMjMTjvLw8rFu3TqbYK1euVFs9nj9/Xm3n+lB6ejpSU1O5xzdu3JB4TEqjBqqOvH79GtOnT8fo0aORlJQEJycnxMfHS4158+YNEhIS4OjoyP2ckJCAV69e4ZtvvpEae/nyZbi7uyM7OxumpqYYOXIk/Pz8ZKqrl5cX8vPz4eTkhBkzZuDcuXMoLCysMM7DwwNXr17F+fPnIRKJcPz4cZk/cMLDw2FtbY3vv/8eKSkpMDY2RlhYmEyxleHt7Y2ff/4Zvr6+3JpiJbZs2VJu3KlTp2BsbIyRI0di69atWLt2LZKTk7F48WIcPXq03LitW7eW2vbu3cv9XJ6ZM2cCAM6dO4evv/4acXFx+PfffzFlyhScO3eu3Dh/f3+pW3mcnJygq6uLO3fuQFdXl9v69u2Lzp07lxtXgs/7e/78+bh16xYA4OrVqzAzM0NGRkaFZQGo8koDRUVFOHPmDKZOnVpq9YOP/fvvv0hKSgJQ/H9j5syZ8PT0RF5eXrkxDx48gLm5Oe7du8ft++eff2BtbY2HDx9Wqe4NGiN14uuvv2ahoaHMxsaGicVi5uPjwyZPniw1ZsGCBczY2Jj16tWLGRsbc9uXX37JVq9eLTXWzs6OxcbGMl9fX/bLL7+wrKwsZmtrW+l6nz9/nhkZGbEvvviCrVq1iqWmppZ7rLW1NROLxcza2poxxlhhYSEzNTWVqRwHBweWlJTExT558oRZWlqWeayhoSHT1dUtteno6DBdXV2p5VhYWLCcnBzGGGPR0dHM0NCQRUZGcvUvj6WlJUtNTWWxsbGsd+/e7P3794wxxjIzM5mVlVW5cbNnz2b6+vrs999/Z56enszT05MZGhpyP5fHxsaGMcaYra0ti4+P5/YnJydLfU0XLFggdavIypUrKzymLHze38+ePWPm5uZs5syZzMLCgvs7yOK7775jCxYsYIcPH2YnTpzgtorExcUxDw8PNmTIENarVy/m6enJ3r17V+7x3t7ebPjw4czExIQtWLCATZgwgXl7ezMXFxf2888/lxvn5OTEIiIiSu0PCQlh06ZNk+UpNkoNYrmN+igtLQ1Dhw6Fh4cHBAIBxo8fj0OHDkmNWbt2LYDib20zZsyodJm6urrw9PSElZUV1NXVZeoFAUB2djaCgoIQEBCAxMRETJo0Cebm5ggJCcE333xTbk9MQaG4gy4QCAAUX7so2VcRsVgssXSKtJWLjx8/DicnJ2zbto3XCsdNmzYFAAwYMACbNm3C3LlzsXfvXq7eZWGMoXnz5mjevDmsra3RrFkzAIC6ujq36nJZtmzZgmPHjsHf3x/Lly9H165dERwcDFdXV5nqqqKiIvG6tGzZUmo9S94zfP3666+4cuUK3r9/L7HfxsZGalxl3t8JCQkAip/bsmXLMHfuXLi5uaFdu3ZISEhAu3btKqxn8+bNAaDUEGt59bxw4QKOHDmC+/fv48svv4S7uzsWL15c4d/Bx8cHZ86cQW5uLkaNGoWwsDCoq6vD0dFR6muSkZEBfX39UvuHDRtW6bXpGhNqoOqIqqoq3r59y324REVFoUmTJjLFTpgwAatXr0ZERASUlJRgZGSEWbNmQVVVtdyYVq1aYeXKlbh37x7c3d2xbt06mf7jA8DIkSNhbGwMV1dXDB48mNs/efJkXLt2rdy4sWPHYu7cuUhPT8f+/ftx8uRJWFhYyFRm27ZtcfnyZQgEAmRkZODQoUPl1rdNmzb47bffsGXLFqnDcmUZOHAg5s2bBxcXF3z++ecYPHgwlixZgunTp0ttaPr374+ffvoJ7u7uWLVqFQDg5cuXcHd3x8CBA6WW6eDggC+++AKLFi3CmDFjZKpnZmYmzMzMIBaL4e7ujkWLFuHevXvYunWr1PISExOxYcMGPHnyhKuzpqamTGUCwM8//4yEhAR07dpVoiGsqIGqzPt7ypQpEAgE3OJ6TZo0wYYNGwAUf7m5eLHiddTKaoilDbnNnj0bpqam8PHxQadOnbiyKqKkpAQ1NTWoqamhY8eOUFdXBwAoKipCSan8j9OioiKIxeJSX9DEYrHMXxQbI1oPqo7cvXsXbm5uiIuLw2effYb09HT88ccf0NPTqzD2u+++Q5cuXWBjYwPGGI4fP47U1FRs3Lix3JisrCwEBwdjwIAB+Oyzz3Do0CFYW1tDQ0OjwvKysrJKHZeXlye1QQQAkUiEa9eu4dq1axCLxRAKhTA2Nq6wPAB49+4dVq9ejWvXroExBn19fbi5uUFbW1umeFmJxWIcP34cOjo66Nu3L7c/JiYGO3fuxPbt28uNO3nypMQH9f3793Hnzh1MnDhRpp6iSCTCli1bcP78eZw9e7bC49+/f4+7d+8iPz8fo0aNwpUrV/D69WtMnDgRioqKZcZ888036N69O/T19REUFASgcr2qsWPHSr3GVZ6YmBgsXryY1/ubj0uXLmHz5s3IyckBYwxisRh5eXkS1xQ/9PjxY/j5+SEwMBDt27eHubk59u3bV+FkC1tbW5w4caLUz2U9/tCKFSugpaWFOXPmSOzfunUr4uLiuAaZSKIGqo5cuXIFhoaGePHiBUQiEbp06SJzD8rCwgKnTp2qcN/HTp48iX///RczZ85EUFBQhd+CS5T1nz83NxcRERFS46T9h5XFgwcP0LNnT2RmZuLevXsYMmRIhTFZWVnIzMyUWOpa1p4i31h5jvvwfVFYWAgbGxucPn26wjJKuLi4YOnSpby+GBQWFkq8vxMTE9GxY/nrQ6enp8Pd3R1xcXHYsmUL1q9fj4ULF8rU4/vyyy+xcuVK7Nu3DzNnzkRwcDByc3OxZMkSqXFFRUW4cuUK/Pz8EBISAgMDAzg6OmL48OFlHt+/f3/06dMHQPGXzJKfGWO4f/8+bt68WWZcVlYWZsyYgbdv30JXVxcqKip48OABWrRogR07dkBLS6vC59gY0RBfHXF3d8eIESPQrVu3Ssd+/vnniIqKwqBBgwAADx8+5IYpyuPh4YG3b9/i/v37cHZ2xvHjx/Hw4UMsWLCgwvLWrl1b5n/+irRq1QpRUVHo27evzI3vh/V98OAB9u7di9zcXGzfvh1RUVGYPXt2uTE7d+6El5eXxH92WYeI+MZWR1zJ8FZNxCkrK0v8/OFjWeTl5WHs2LHo3r27xN/wr7/+kho3YMAArF27VmIIc86cOVK/sCxevBiGhoaIiYmBmpoatLW18fPPP8PLy6vCen7yyScQCoW4efMmMjMzMX/+fJiZmVUYp6SkhFGjRmHUqFFITU2Fv78/Nm7ciOHDhyM5OVnieh8A7Nq1q8JzlhWnoaGBQ4cOISIiArGxsVBQUICjoyP3f7i8uEavtmdlkGJ8Zx0xVjyDTEdHh40dO5aZm5uznj17siFDhjBjY2NmYmJSZkxVZtSVzPbbtm0bu3r1KmOMyRSrr6/PdHR0JLaKZtWVMDc3Z0VFRdzjwsJCZmFhITVm5MiRUmdg1USsvMeVzP4r73FFrl+/XuZWERMTEzZhwgS2ceNGbp+0WZGM/fc++/C48mZufmzSpEns2bNn7Ny5c8zd3Z3l5+ezUaNGyRRbnsq+VnUV15BRD6qOVHbW0Yd27NhR6fKqMqNOVVUVz58/R9euXXHjxg0IhUKZLuxWNAQoTVFREfLy8riL0LKU9+mnn3Kz6SqLb6y8xz158gQjR47kHicmJmLkyJEy99i++OILREdH4/Hjx7C3t8edO3ckJsqUR1NTE3/99Rfc3Nzg7OyM33//vcL3m6KiIjIzM7n36IsXL2R+j86dOxebN2+Gu7s7vLy84OPjAwcHB5liy8N4Xv2o7biGjBqoOrJ27VoUFhbi+fPnEIlE6Natm9RZQB9q3749AgMD8fTpU5mvJ1VlRl1Z//llySZQ3o2nskypnjhxIuzs7GBiYgIACAkJgaOjo9SY//3vf5g8eTL09fUlhqNkKY9vrLzHBQUF4f379xCJRGjZsiUA4Pr16/j888+5x9J4e3sjODgYSUlJGDt2LJYsWQIHB4cKbwxnjHGz8fbs2YPx48ejqKhIasycOXMwdepUvHnzBt9//z1u376NNWvWVFhHoLgh/eKLLwAU33aQnp7O+8tKCVlm9clDXENGDVQduXfvHubMmQMtLS2IxWKkpKRg27ZtMs1y4nM9acaMGQgNDUW7du3w5s0bzJ49W+YZddXxn7+wsBChoaEyz+L66quvMHDgQERGRkJJSQnu7u7o2bOn1Jg2bdqgTZs2lapXVWPlPS49PR3fffcd1qxZw81SfPnyJTZt2oQ///yzwvgTJ07A19cX48ePR/PmzXHs2DGMGzeuwgZq2LBh3M/ffPMNunXrhtWrV1cY06tXL8TExEAkEmHFihVo1aqVDM+yOHOFm5sbXr9+jUOHDuGnn37CmjVr0KFDB5niiXyiBqqOrFq1Cps2beI+sG/fvo2VK1fi2LFjFcaGhYXhxIkTsLW1hYaGBvbt2wcrK6syG6jIyEjuZ1VVVa5HUvI7acM1U6dOlfqtrqIL5R9/q3dxccHXX38tNeby5cswNjbm0vC0aNECQPG04MePH0vtKTZt2hTGxsbo0qWL1DKqM1be49avX4+NGzdK3CQ6b948DBo0COvWrcP+/fulxisoKEj01FRUVMqd0g78d6F/0qRJ3A24QPHEnn379kktq6CgAL6+vnj27BkWL14Mb29vzJgxQ6YJNkuWLME333wDDw8PtGrVChYWFvj1118rvPmdyDdqoOpITk6ORG+iX79+yM/Plyn243F5adeTpN24KhAIpDYyJTPmfH19oaqqChsbGygpKeHUqVMy1/VD2dnZEh9aZbl79y6MjY1x/fr1Mn8vrYESiURYunQp3r17h6FDh8LY2BiDBw+WaeiUb6y8x1U1g8EXX3yB9evXIzc3F8HBwfDx8YFQKCz3eDc3N+zatYu7+fZj0q55rVixAi1atMCDBw+gpKSEuLg4/PbbbzLVk09mlorQNSg5UHfzMxq3KVOmsAsXLnCPL1y4wKZMmSJT7K5du9icOXOYsbEx27dvH7OxsWE7duyoqaoyOzu7UvtkyeNXMqvQxMSEGRsbswEDBrBt27bJVObvv/9e6XqWyMzMZH///TcbNmwYGzBgQK3EymuchYUFE4lEpfaLRCKZZmKKRCJ2+PBhNnv2bObi4sIOHDjACgsLpcZcunSJvXz5kjFWnLtxxowZbPPmzSw/P19qXMkstpJZfGKxmJmbm0uNyc7OZowVz+J78+YNd47IyEjm4OBQ4fNjjLFXr16xy5cvs6KiIhYXF8ftrygXYG3HNUbUg6ojK1euxPz587Fo0SIAQMeOHWXOyDxixAhoa2vj1atXiI6Oxg8//IARI0ZIjbl9+zZ27dolcbNtQkICLl26VGF5+fn5eP78OZfF+tGjRxVe8AaAAwcOcD8LBAJoamrKlLkCKB7qmzt3bqUuHJ89exaRkZGIioqCoqIiTE1NpX7br45YeY8bPHgwtm7dWiqDwfbt29G7d+8Ky1NQUICFhQWMjIy4fUlJSeXeGLx3716cPn0a69evx8OHD7n3eGxsLDw8PPDbb7+VW5ZAIEBBQQH3N09LS6vw729tbY21a9di4cKF+O677xAXFwdra2suc0VFzpw5gx07diA3Nxc+Pj6YOHEifvnlF1hbW0vco1TXcY1WXbeQjdXjx48ZY8XfADMzMxljjN26dUtqTEpKCps8eTL74osv2Lhx49i4cePYoEGD2LfffssyMjKkxpqamrJjx44xR0dHdu7cOfbjjz9WmAG9RGhoKDM0NGR2dnbM1taWGRkZyfRtz9XVtdQ+JycnmcqcOnUqGz16NJs3b57M2beHDRvGDAwM2K5du9izZ89kKqeqsfIel5mZySZNmsSMjY3ZrFmz2Ny5c9no0aPZxIkTWVpaWoXx69atYwMGDJDoCZd3rx1jxfctlWSHd3d3Z/PmzWOMFfeGxo4dW2bM69evGWOMnThxgk2ePJkZGhqyVatWsREjRrCjR49KrV9oaCgbNWoUW7t2LcvMzGSPHz9msbGxFfbWStjY2LDMzEyu15aYmMjMzMzkLq6xoh5ULYuOjoZYLIabmxtWr17NjTsXFRVh2bJlXL60smzcuBEDBw7E/v37uYwAhYWF2LJlC1avXi11raUmTZrA3t4er1+/hqamJjZs2ABLS0uZ6jx06FBcunQJjx8/hkAggI6OjtRrJa6uroiNjUVSUpLEPThFRUX49NNPZSrT1tZWpuM+FBISgmfPniEiIgJ//PEHXrx4ga5du0rNUVjVWHmPkyWDgTQXL15ESEgIdz9aRQQCAZcd/vr165g8eTK3vzwTJkyAmpoahg4dimHDhsHU1BSMMezYsQO6urpSyxs6dChOnjyJP/74A5MnT8aSJUvQrl07pKSkAKg4dZSCgoJEr15bW1ume69qO66xogaqll27dg03btxAUlISNwQhEAigpKRUavXSj926datUUlFlZWX8+OOPsLa2lhqroqKC9+/fo3Pnzrhz5w6GDBkiNVs3AHh6emL27NlYuHBhmb8vL+nounXr8P79e6xevRpubm7cfiUlJZnuvXn27Bk0NDTQq1cvmfPolRCLxdxNvnl5edyHZU3GynucQCDAkCFDZMpl+DEdHR0UFBTI3EApKioiIyMDOTk5iI2NhaGhIYDiaeDlfakJDQ1FXFwcoqKiEBkZidu3b6NFixbIyMhAfn5+hbcmNG3aFD/88APevn2LWbNmQVNTU+Ybkbt164aDBw+iqKgIsbGx+PvvvytsFOsirrGiZLF14NKlS4iNjYWLiwsuXLiAY8eOoWfPnvj++++l5kqzsbEpdxVUab8Diq9d+Pr6wtPTE+PGjYOCggJ0dXWlfmO/dOkSTExMys2fJksv58GDB9x1L5FIhPj4eKl3+B86dAgeHh7o0qULXr16hZUrV8q8JIWRkRHatWsHIyMjDB8+HL169ZIpriqx9SWOr+DgYCxcuBDdu3eXmF5e3uzPc+fOYcOGDSgqKoKJiQmWLVuGM2fOYNOmTXBxcZEpU0pGRgYuXryIvXv34vnz5xKr0Jbl8uXLWLlyJYYOHYpffvlF5uucQPFs2h07dkhkzXdxcanwHLUd11hRA1XLPryIXFRUhIkTJ3IXkRUVFblJE2WRlh1clszhJd8qc3Jy8OLFC+jq6kodXqhoSnhFvRs3NzfcuHED6enp6NKlCx4+fIgBAwZgz5495caYm5vjr7/+QsuWLfHw4UMsXboUPj4+UsspkZqaCsYYd6Nn//79ZeqxVSW2vsTxZW5uDmdn51J/65Ibt8uSmJiItLQ0rmdw9epVqKqqljndHSge+o2OjkZoaCjCwsKQl5cHAwMDGBgYQCgUSv3wnjNnDh48eICVK1fy6iECxUu7REVFQUlJCYMGDZL5JvTajmuMqIGqZVZWVvDx8UHTpk3h4eGBhIQE/P7772CMwczMTOq6QL179y4ziwBjDMnJybh7926ZcZcvX8bnn3+Ojh07Ijg4GMeOHUOPHj0q7LGZmJhILCT3IVmGT0xMTBAUFISVK1fCyckJubm5WLdundT7Uz7uCVpaWiIwMFBqOSXCwsKwcOFC9OvXD2KxGLdu3cLq1atlypjBN7a+xPE1ceJEHDlypEbOXaJ///4YMGAAxowZAwMDg0plf1i5ciV++uknqKmp8So7ICAAGzZswMCBAyESiRATE4NVq1aVu9xGXcU1WrU5I4MwZmVlxf3s4ODA/Pz8uMflzXIqER8fL3Ury+7du5mdnR178uQJi42NZXp6eszX15ctX76crVq1qnqeVDkmTJjAGGNs//797NSpU4yxirNTVyX7tq2trcR9JXFxcRKvd03E1pc4vpYvX85cXV2Zr69vpbPuy2rdunXM2tqajR8/nv3xxx8sKiqqzHu3asKYMWPY27dvucfx8fEVZs2vi7jGiiZJ1DI+F5FLtG/fvtLlBQQESPTYTExMMG7cOK7HJovU1FSsWLEC4eHhEIlEEAqFWLZsWYV50tq0aYNdu3ZhyJAh3D1eBQUFUmPev38v0YP6+LG0axhFRUUSC+J17NgRYrFYanlVja0vcXzl5uZCQ0Oj1EJ8si52KYtff/0VQPH9VWFhYTh06BAWLFiA7t27Y+jQoZg0aVK1lfUxdXV1iTWY2rdvL9OaWbUd11hRA1XLZsyYARsbGxQVFcHBwQHa2toSF5GrG59pvx9bsmQJ+vfvj1WrVkEsFsPHxweLFi2qcPG21atX4+rVq+jbty9Gjx6NU6dOYdmyZVJjhEKhRJqjjx9L+2Bs164d9u/fz03COHbsmMyNOt/Y+hLHl5GREUaOHFnpBSf50NbWhoWFBTp16oSbN28iICAAd+7cqdEGqk+fPnB2doa9vT0UFRVx9uxZaGtrc1+Kynu/1XZcY0XXoOpAZS8iV4WdnR3279+PnJwcjBo1CpcuXYK2tjZev36NmTNnynR9x9raGgEBARL7ZLk29M0330idEMFXyfT3j7179w4rV65EREQEGGMQCoVYtGiRTMuV842tL3F8LVy4ENevX8fw4cNha2vLZUSvThcvXsTNmzcRHR2N+Ph46OnpQSgUQigU8lpxujLKu4WiRHm3UtR2XKNVd6OLpDacPXuWGRsbs2HDhrGlS5cyxhg7ffo0GzVqlMzXEqytrVlCQgL3+PXr1zJdG5o0aZJEXHWhlUdrV05ODvP392fffvsts7W1Zbt372YpKSnVdv7p06ezXbt2sTt37tTatacSZ86ckTnrRF3GNVY0xNfAjR07Fv3795fosamrq2PVqlVcj61kiYTy/PDDD5gwYQL09PTAGMOdO3ewcuXKCstOS0uDiYkJWrZsCRUVFZlvnqwIK6PTf/z4cRw6dAjPnz+HiooKPv/8czg6OsLU1LTC8/GNrS9xVdW0aVO0b98en376KV6+fIlHjx7hq6++woQJEzBlypQqn3/v3r3VUEt+QkJC4O7uXukeYm3HNVY0xEdkuocqNTUVMTExEIvF0NPTk+nem9evX5e5v6rXTD6u76FDh3DkyBF8//336N69O4DihLa7du3CpEmTMHHixHLPxTe2vsRV1aZNm3Dq1Cl06NABdnZ2GDt2LFRUVJCVlYWRI0eWuyxKfZKbm4vz58/j1KlTePfuHczNzWFjY1Phe7y24xqlOu2/EblQkrjyYx9OKy5rk8XJkyfZ77//znJycqptevLHQ3wWFhYsNTW11HGJiYkVDgfyja0vcVW1efNmiWntH7pz506NlVvbIiMj2eLFi9mXX37J5s+fzywsLNiBAwfkLq6xoSE+Uu6Mvg+/HZekPfpQRTOO+CxNz4eCggKaN29ear8sEwf4xtaXuKqaPXs2jhw5goiICBQVFUFfXx9Tp06FgoJCvR6eKlmR+sMeor29PRYtWiTRQ/x4CLO24xo7aqBIuT6cUWRjY1PpGUaVWZq+Mrp27SrxuCrZoPnG1pe4qnJ3d8fLly9hb28Pxhj8/PwQHx8vNSVXffDXX3/B1tYWCgoK2L9/v8S9ZUBxFvg///yzzuMaO2qgiEwqc99UiZIP1ZJYaUvTl5BlGu7HS4AnJydj69atZR6fnJws9Xx8Y+tLXFX9888/8Pf35/5uI0aMkHmZlvrghx9+KPd30nqItR3XWFEDRcqcFVcdxo4di7lz5yI9PR379+/HyZMnYWFhITVGWhLS8kibIFDR5AG+sfXld1UlEolQVFTE3agrEokksprXV0+ePJFYq6wEq2CmaW3HNXbUQDUSy5cvL3da64drNn0oMjKS+zknJwdRUVESjdngwYOlljljxgyEhoaiXbt2ePv2LWbPnl1hUtMPl/CIj4/H06dPMXToULx586bUsEgJV1dXAMXT2j++TlPRkvZ8Y+tLXFVZWlrCyckJ5ubmAIDTp09zP9dnnTp1gpeXl9zHNXbUQDUSffv2xcaNG5Gamgpra2tYW1tz9z6Vt7rqli1buJ+1tbW5BRaB4mG78tYE+lB+fj4KCgqgpKRUqXQ5Z86cwY4dO5CXl4cjR45g4sSJ+OWXX6QuzDh9+nTs3bsXLVq0QHJyMlauXImnT5+WmtxRnbH1JY6vmTNnomfPnggPDwdjDDNnzsSIESNqpKzapKyszOt2h9qOa/TqcAYhqQMJCQnMy8uLmZiYsBkzZrALFy7UWFlr165lEyZMYH/99Rfbv38/GzduHNuxY4dMsTY2NiwzM5ObAp+YmMjMzMykxpw7d45ZW1uzffv2MUNDQ7Z161ZWUFAgU3l8Y+tLXGXduHFD6lbfLV++vF7ENXbUQDUicXFxbOvWrczU1JRNnz6dHT16lP34449s/vz5UuPu3LnD9u7dy/Lz89n06dOZvr4+u3r1aoXljR49mhUWFnKP8/LyKlxSpISdnR1jTPIeLVmWJQgLC2P9+/dnERERMpVTHbH1Ja4ypkyZUu42derUGiuXkA/REF8jMWnSJKSkpMDa2hq7d+/mVki1sbGBkZGR1NhVq1Zh9uzZCAoKgoqKCvz8/DB79uwK41q3bo2MjAy0aNECAFBYWFjmvTxl6datGw4ePIiioiLExsbi77//5lI1faxkYcUSjDG4uLhwK5VKuwDNN7a+xPF14MABicfv37+HoqIiPvnkk2othxBpKNVRIxEeHs57SWwHBwccO3YMP/30E4YNGwYbG5tSK9+WZc6cObh58yZGjhwJJSUlhIaGokWLFujcuTMA6Zmbc3JysGPHDly7dg1isRhCoRAuLi5lLv9dklLp3bt3ZaaLkTb2zze2vsRV1cOHD/HLL78gMTERjDF06dIFGzZswGeffVYj5RHyIWqgGrjqSO8/depUGBsbY+/evTh9+jQCAgIQFBQkdel2ABXm9/twxl51MDU1xdmzZ2s1tr7E8WVnZycx+/LChQvYt28f/v7771qrA2m8aIivgZN2X5GsN996eHjg6NGj2LJlC5o1a4bExERs3LixwjhbW1tkZWUhIyNDYn/J8KI0urq6perXunVrhISESI3x9/dH3759oaqqWuny+MTWlzi+GGMStwZ8+eWX2LZtW42URcjHqAfVSMTExEjcA5Wbm4s//vij2vPifWj9+vXw9fWFlpYWAP43JRYWFiI4OBi3b9+W2iMsa6q1rOXxja0vcXy5u7tDXV0d48ePh6KiIs6cOYObN2/ip59+AlBzDSMhADVQjcaYMWOwbt069O/fH1evXsXy5cshFAqxZs2acmPK6sUA/zU0sbGxUsscPXo0Tpw4AXV19SrXHyh7ZV9Ss6TdX0UZEEhNoyG+RmLnzp2YPXs2OnbsiPj4eGzYsKHcG3RLPHz4sEpl6ujooKCggFcD9eEEDMYYnjx5AiUl6W/XFy9e4ODBg8jJyQFjDGKxGPHx8RVeK6tKbH2J46sms1QQUpG6SZFMak1CQgISEhKgoqKCZcuW4e7du3BxcUG7du2QkJBQo2VbW1tj9OjRcHR0hJOTE7dJk5iYCKB4qY+S7caNGwCAzZs3S4398ccfoampidjYWPTo0QMJCQno1q2bTHXlG1tf4vh69uwZ1q1bh4ULF0pshNQG6kE1cFOmTIFAIOBy6DVp0gQbNmwAUPNDNJs2bcKiRYsqdZ1i5syZOHHiBNauXYu9e/fi66+/ljm2sLAQc+bMQVFREXr27Inx48fD3t6+RmPrSxxfrq6uMDMzg46OTo2VQUh5qIFq4OpyiOaTTz6pcFHDj314STQwMLBSDVTTpk1RUFCA//3vf7h//36FQ5jVEVtf4vjS1NTkEtUSUtuogWok0tPT4e7ujri4OGzZsgXr16/HwoULoampWWNl9uzZk8s4oayszO2X1mh9nC2hMqytrTFz5kx4eHhgwoQJCA0NRdu2bWs0tr7E8VWyCqxQKJS4BlhRJntCqgM1UI3E4sWLYWhoiJiYGKipqUFbWxs///xzjS4BkJubCw0NDdy8eVNiv6y9Klnv0yqZUKGurg5jY2OEhITA1tYWampqEg1jdcbWl7iqunXrFm7evCnxN5Q1kz0hVUUNVCMRHx+PCRMm4PDhw2jSpAnmzZsHKyurGi2zJEtFeno6lzOuIh8u7JaYmMj9LO0eqgULFqBly5YYMmRIpT+s+cbWl7iqun//Ps6fP19r5RHyIWqgGglFRUVkZmZyvZIXL15UuPx6VT18+BBz585FXl4efHx8MGXKFGzevBm9evUqNyYoKKjS5Zw4cQJnzpzBP//8A11dXZiZmcHAwECm58c3tr7EVVW3bt3w8OHDchP1ElKT6EbdRiI0NBQbN27EmzdvMHDgQNy+fRtr1qyp0cXnHB0dsWLFCvz000/w9/fHP//8g02bNuHYsWM1Vubdu3dx5swZXL9+Hb1794a5uTn09fVrNLa+xPFhY2ODR48eoXXr1lBWVqYlykmtogaqEUlNTUVMTAxEIhH09PTQqlWrGi3Pzs4Ofn5+EpnPrayscPLkyRotFwCioqLg4eGBR48e4datW7USW1/iKqMki/rHaHVYUhtoiK+RKCgogK+vL549e4bFixfD29sbM2bMqNQy7LI6ceIEbG1toaWlhYcPH3LDiidPnpT5WlRlMcYQGRmJc+fOISQkBD169OCysNdUbH2Jq4r27dsjMDAQT58+xcyZMxEUFFTpWwcI4Yt6UI2Em5sbWrRogUuXLuHo0aNYunQpxGIxPDw8qr0sW1tbnDhxAi9fvsSCBQtw9+5dqKio4H//+x/c3d3RpUuXai1v6dKlCA0NRc+ePWFqagoTExM0bdq0RmPrS1xVeXh44O3bt7h//z6OHj2KWbNmoVevXjWaZJiQEtRANRIljUbJcBtjDJaWljh16lSNlVUiJycHYrG4zMUGq4Ouri60tLSgpqYGoPT0dGnXS/jG1pe4qrKxseF6xP7+/igqKoKVlRXOnDlTI+UR8iEa4mskBAIBCgoKuA+2tLQ0me8zqqwPp4qXpbo/TKtyPr6x9SWuqkpmCZa8VwoKCmp85iAhJaiBauASEhLQrl07ODk5Yfr06UhOTsbq1asRHBwMFxeXGimzU6dONXoD8MeqcsGeb2x9iauqsWPHYu7cuUhPT8f+/ftx8uRJWFhY1EldSONDQ3wN3LBhw6CmpoahQ4eidevW0NDQAGMMgwcPrrF7Wz6ctUfqv9DQUFy7dg1isRhCobBGJ2UQ8iHqQTVwoaGhiIuLQ1RUFCIjI3H79m20aNECGRkZyM/Ph56eXrWXOWDAgGo/J6k7bdu2xciRI7nciJGRkZSLj9QK6kE1MhkZGbh48SL27t2L58+f4969e3VdJSLHli9fjsuXL6Njx47cPsrFR2oLNVANXFFREaKjoxEaGoqwsDDk5eXBwMAABgYGEAqFNTazjjQMo0ePxsmTJ6GqqlrXVSGNEA3xNXCDBw/GgAEDMGbMGGzduhUdOnSo6yqReqRjx46VXvaEkOpCDVQDN3HiRISHh+P48eN4+/YtDA0N0b9/f5oqTGTSrFkzmJubo3///hJZR0oy1RNSk2iIr5FISkpCWFgYwsLCcPfuXXTv3h1Dhw7FpEmT6rpqRI59PBuz5OPC1ta2DmpDGhtqoBqRgoIC3L17Fzdv3kRAQADev3+PsLCwuq4WkUO6uroQCARcgyQQCNCsWTMYGBhgyZIl0NLSqtsKkkaBGqgG7uLFi7h58yaio6MRHx8PPT09CIVCCIVCdOvWra6rR+qRd+/ewcfHB0+fPsXvv/9e19UhjQA1UA3c119/zTVIvXv3pmtPpMrMzc1x+vTpuq4GaQRokkQDt3fv3rquAmlganPJedK40ddpQojMzp8/T9efSK2hHhQhpBQTE5NS2e6zsrLQqVMnuLu711GtSGND16AIIaV8vNS7goICNDU1oa6uXkc1Io0RNVCEEELkEl2DIoQQIpeogSKEECKXqIEihBAil6iBIoQQIpeogSKEECKX/g82FOoMShKH/AAAAABJRU5ErkJggg==",
- "text/plain": [
- "<Figure size 432x288 with 2 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "sns.heatmap(clean_data1.corr()) # Betrachtung der Korrelation \u00fcber eine heatmap "
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 62,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "image/png": 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",
- "text/plain": [
- "<Figure size 576x864 with 2 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "plt.figure(figsize=(8, 12))\n",
- "heatmap = sns.heatmap(clean_data1.corr()[['Weekly_Sales']].sort_values(by='Weekly_Sales', ascending=False), vmin=-1, vmax=1, annot=True, cmap='PiYG')\n",
- "heatmap.set_title('which features influence Weekly Sales the most ?', fontdict={'fontsize':18}, pad=16);"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 63,
- "metadata": {},
- "outputs": [],
- "source": [
- "clean_data1['Holiday'] = clean_data1['Holiday'].fillna('')"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 64,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "Store 0\n",
- "Dept 0\n",
- "Date 0\n",
- "Weekly_Sales 0\n",
- "IsHoliday 0\n",
- "Holiday 0\n",
- "Temperature 0\n",
- "Fuel_Price 0\n",
- "MarkDown1 0\n",
- "MarkDown2 0\n",
- "MarkDown3 0\n",
- "MarkDown4 0\n",
- "MarkDown5 0\n",
- "CPI 0\n",
- "Unemployment 0\n",
- "Size 0\n",
- "Week 0\n",
- "Year 0\n",
- "Type_A 0\n",
- "Type_B 0\n",
- "Type_C 0\n",
- "dtype: int64"
- ]
- },
- "execution_count": 64,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "clean_data1.isnull().sum()"
- ]
- },
- {
- "attachments": {},
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## 3.5. Erstellen und Analysieren eines neuen Datensatzes"
- ]
- },
- {
- "attachments": {},
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "\"kleiner Datensatz\": Testdaten, f\u00fcr die wir nur 1 Jahr ber\u00fccksichtigen, f\u00fcr das wir MarkDown-Werte haben."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 65,
- "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>Store</th>\n",
- " <th>Dept</th>\n",
- " <th>Date</th>\n",
- " <th>Weekly_Sales</th>\n",
- " <th>IsHoliday</th>\n",
- " <th>Holiday</th>\n",
- " <th>Temperature</th>\n",
- " <th>Fuel_Price</th>\n",
- " <th>MarkDown1</th>\n",
- " <th>MarkDown2</th>\n",
- " <th>...</th>\n",
- " <th>MarkDown4</th>\n",
- " <th>MarkDown5</th>\n",
- " <th>CPI</th>\n",
- " <th>Unemployment</th>\n",
- " <th>Size</th>\n",
- " <th>Week</th>\n",
- " <th>Year</th>\n",
- " <th>Type_A</th>\n",
- " <th>Type_B</th>\n",
- " <th>Type_C</th>\n",
- " </tr>\n",
- " </thead>\n",
- " <tbody>\n",
- " <tr>\n",
- " <th>92</th>\n",
- " <td>1</td>\n",
- " <td>1</td>\n",
- " <td>2011-11-11</td>\n",
- " <td>18689.54</td>\n",
- " <td>0</td>\n",
- " <td></td>\n",
- " <td>59.11</td>\n",
- " <td>3.297</td>\n",
- " <td>10382.90</td>\n",
- " <td>6115.67</td>\n",
- " <td>...</td>\n",
- " <td>2406.62</td>\n",
- " <td>6551.42</td>\n",
- " <td>217.998085</td>\n",
- " <td>7.866</td>\n",
- " <td>151315</td>\n",
- " <td>45</td>\n",
- " <td>2011</td>\n",
- " <td>1</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>93</th>\n",
- " <td>1</td>\n",
- " <td>1</td>\n",
- " <td>2011-11-18</td>\n",
- " <td>19050.66</td>\n",
- " <td>0</td>\n",
- " <td></td>\n",
- " <td>62.25</td>\n",
- " <td>3.308</td>\n",
- " <td>6074.12</td>\n",
- " <td>254.39</td>\n",
- " <td>...</td>\n",
- " <td>427.39</td>\n",
- " <td>5988.57</td>\n",
- " <td>218.220509</td>\n",
- " <td>7.866</td>\n",
- " <td>151315</td>\n",
- " <td>46</td>\n",
- " <td>2011</td>\n",
- " <td>1</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>94</th>\n",
- " <td>1</td>\n",
- " <td>1</td>\n",
- " <td>2011-11-25</td>\n",
- " <td>20911.25</td>\n",
- " <td>1</td>\n",
- " <td>Thanksgiving</td>\n",
- " <td>60.14</td>\n",
- " <td>3.236</td>\n",
- " <td>410.31</td>\n",
- " <td>98.00</td>\n",
- " <td>...</td>\n",
- " <td>8.00</td>\n",
- " <td>554.92</td>\n",
- " <td>218.467621</td>\n",
- " <td>7.866</td>\n",
- " <td>151315</td>\n",
- " <td>47</td>\n",
- " <td>2011</td>\n",
- " <td>1</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>95</th>\n",
- " <td>1</td>\n",
- " <td>1</td>\n",
- " <td>2011-12-02</td>\n",
- " <td>25293.49</td>\n",
- " <td>0</td>\n",
- " <td></td>\n",
- " <td>48.91</td>\n",
- " <td>3.172</td>\n",
- " <td>5629.51</td>\n",
- " <td>68.00</td>\n",
- " <td>...</td>\n",
- " <td>2084.64</td>\n",
- " <td>20475.32</td>\n",
- " <td>218.714733</td>\n",
- " <td>7.866</td>\n",
- " <td>151315</td>\n",
- " <td>48</td>\n",
- " <td>2011</td>\n",
- " <td>1</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>96</th>\n",
- " <td>1</td>\n",
- " <td>1</td>\n",
- " <td>2011-12-09</td>\n",
- " <td>33305.92</td>\n",
- " <td>0</td>\n",
- " <td></td>\n",
- " <td>43.93</td>\n",
- " <td>3.158</td>\n",
- " <td>4640.65</td>\n",
- " <td>19.00</td>\n",
- " <td>...</td>\n",
- " <td>3639.42</td>\n",
- " <td>14461.82</td>\n",
- " <td>218.961846</td>\n",
- " <td>7.866</td>\n",
- " <td>151315</td>\n",
- " <td>49</td>\n",
- " <td>2011</td>\n",
- " <td>1</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " </tr>\n",
- " </tbody>\n",
- "</table>\n",
- "<p>5 rows \u00d7 21 columns</p>\n",
- "</div>"
- ],
- "text/plain": [
- " Store Dept Date Weekly_Sales IsHoliday Holiday \\\n",
- "92 1 1 2011-11-11 18689.54 0 \n",
- "93 1 1 2011-11-18 19050.66 0 \n",
- "94 1 1 2011-11-25 20911.25 1 Thanksgiving \n",
- "95 1 1 2011-12-02 25293.49 0 \n",
- "96 1 1 2011-12-09 33305.92 0 \n",
- "\n",
- " Temperature Fuel_Price MarkDown1 MarkDown2 ... MarkDown4 MarkDown5 \\\n",
- "92 59.11 3.297 10382.90 6115.67 ... 2406.62 6551.42 \n",
- "93 62.25 3.308 6074.12 254.39 ... 427.39 5988.57 \n",
- "94 60.14 3.236 410.31 98.00 ... 8.00 554.92 \n",
- "95 48.91 3.172 5629.51 68.00 ... 2084.64 20475.32 \n",
- "96 43.93 3.158 4640.65 19.00 ... 3639.42 14461.82 \n",
- "\n",
- " CPI Unemployment Size Week Year Type_A Type_B Type_C \n",
- "92 217.998085 7.866 151315 45 2011 1 0 0 \n",
- "93 218.220509 7.866 151315 46 2011 1 0 0 \n",
- "94 218.467621 7.866 151315 47 2011 1 0 0 \n",
- "95 218.714733 7.866 151315 48 2011 1 0 0 \n",
- "96 218.961846 7.866 151315 49 2011 1 0 0 \n",
- "\n",
- "[5 rows x 21 columns]"
- ]
- },
- "execution_count": 65,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "# TEST: Create a small dataset that only looks at the times for which we have values for the MarkDowns.\n",
- "# then we can run a test model with this data set\n",
- "small_dataset1 = clean_data1[(clean_data1[\"Year\"]==2011) & (clean_data1[\"Week\"]>=45)]\n",
- "small_dataset2 = clean_data1[(clean_data1[\"Year\"]==2012) & (clean_data1[\"Week\"]<=43)]\n",
- "small_dataset = pd.concat([small_dataset1, small_dataset2])\n",
- "\n",
- "small_dataset.head(5)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 66,
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "<class 'pandas.core.frame.DataFrame'>\n",
- "Int64Index: 150929 entries, 92 to 421569\n",
- "Data columns (total 21 columns):\n",
- " # Column Non-Null Count Dtype \n",
- "--- ------ -------------- ----- \n",
- " 0 Store 150929 non-null int64 \n",
- " 1 Dept 150929 non-null int64 \n",
- " 2 Date 150929 non-null datetime64[ns]\n",
- " 3 Weekly_Sales 150929 non-null float64 \n",
- " 4 IsHoliday 150929 non-null int64 \n",
- " 5 Holiday 150929 non-null object \n",
- " 6 Temperature 150929 non-null float64 \n",
- " 7 Fuel_Price 150929 non-null float64 \n",
- " 8 MarkDown1 150929 non-null float64 \n",
- " 9 MarkDown2 150929 non-null float64 \n",
- " 10 MarkDown3 150929 non-null float64 \n",
- " 11 MarkDown4 150929 non-null float64 \n",
- " 12 MarkDown5 150929 non-null float64 \n",
- " 13 CPI 150929 non-null float64 \n",
- " 14 Unemployment 150929 non-null float64 \n",
- " 15 Size 150929 non-null int64 \n",
- " 16 Week 150929 non-null int64 \n",
- " 17 Year 150929 non-null int64 \n",
- " 18 Type_A 150929 non-null uint8 \n",
- " 19 Type_B 150929 non-null uint8 \n",
- " 20 Type_C 150929 non-null uint8 \n",
- "dtypes: datetime64[ns](1), float64(10), int64(6), object(1), uint8(3)\n",
- "memory usage: 22.3+ MB\n"
- ]
- }
- ],
- "source": [
- "small_dataset.info() "
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 67,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "Store 0\n",
- "Dept 0\n",
- "Date 0\n",
- "Weekly_Sales 0\n",
- "IsHoliday 0\n",
- "Holiday 0\n",
- "Temperature 0\n",
- "Fuel_Price 0\n",
- "MarkDown1 0\n",
- "MarkDown2 0\n",
- "MarkDown3 0\n",
- "MarkDown4 0\n",
- "MarkDown5 0\n",
- "CPI 0\n",
- "Unemployment 0\n",
- "Size 0\n",
- "Week 0\n",
- "Year 0\n",
- "Type_A 0\n",
- "Type_B 0\n",
- "Type_C 0\n",
- "dtype: int64"
- ]
- },
- "execution_count": 67,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "small_dataset.isnull().sum()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 68,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "<AxesSubplot:>"
- ]
- },
- "execution_count": 68,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": 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vOADIb13CK65FlgrPBvnV1FNow6+9l1bPeMW1LejBK64wMYtf3EBeYQCANqh9Lb6mPoqvaZ89IYSQKikKFGV61ERISAgsLCwwduzYCmvpAcCTJ08wbdo02NjY4JtvvkFWFr/kDlCCIoSQZktBQVGmh6xSUlKwceNG/PXXXwgKCkJAQAD+/fdf7veMMcyZMwcuLi44ceIEevbsCX9/f97nX+eX+FasWIG4uDiUlJQgMTER3bp1AwA4OzvD0dGxrpvjLScnB+7u7vDz82vsUyGEkHpR1/egrl69CqFQCC0tLQDAuHHjcPbsWbi5uQEA7t27h5YtW8LY2BgAMHv2bGRn819mqM4T1LJlywAASUlJcHZ2ltuK41lZWUhISGjs0yCEkHqjrKgs037Z2dmVJhJNTU2JRVlTU1Ohra3NPdfR0UF8fDz3PDExEe3atcOvv/6KhIQEfPbZZ1iyZAnv82+QQRLPnz/H8uXL8fbtW6ipqWHJkiXo1asX3N3d0aJFC9y/fx/Z2dn44YcfEBwcjAcPHmD06NFwd3fHsWPHcPnyZbx58wZpaWkwMTGBu7s7BAIB/P39cebMGYhEIhgZGWHhwoV4+fIlZs6cidatW0NNTQ2+vr749ddfkZKSgtTUVAwdOhSrV6/GqlWrkJqaCldXVyxatAjOzs64ePEiAMDX1xcAMHfuXAiFQvTp0wdpaWkIDAzEnj17KrQpaOKztQkhzZOsl+/27duHLVu2VNju5uaGuXPncs/FYrHE5x1jTOJ5aWkpbty4gQMHDqBv377YtGkT1q1bh3Xr1vE6/wZJUL/88guWLl2KXr164d9//4WrqytCQ0MBlGXkgIAAHD9+HIsWLUJoaChUVVVhbGwMV1dXAEBsbCyCg4OhqakJZ2dnnD9/Hmpqarh79y4CAwMhEAiwcOFCnDhxAoMGDcLTp0+xc+dOdO7cGSdPnkTPnj2xefNmFBcXw9LSEvfu3YOHhwecnZ3h5+eHpKSkKs89MzMTLi4uMDAwQHh4eKVt2traNsSfkRBCakTW5Tacp0+Hvb19he3v9p4AoEOHDoiJieGep6WlQUdHh3uura2Nrl27om/fvgAAKysrzJs3j8+pA2iABJWXl4e7d+9i0aJF3Lb8/HxkZmYCAHetsmPHjujevTvatm0LANDS0uJGf4waNQrt2rUDAFhYWCAqKgqqqqqIj4+Hg0PZctqFhYXo2LEjBg0ahLZt26Jz584Ayv5A8fHx2Lt3L548eYK3b98iPz+fu4YqC319fQDAtWvXKm2TEELkkaw9qPcv5VVl2LBh8PX1RUZGBlq0aIFz585JrGw+YMAAZGRk4MGDB9DT08PFixfRu3dv3udf7wlKLBZDRUVF4l7U69evuQShrPy/a6RKSpWfjuI7s6HFYjEUFRUhEokwffp0zJgxA0DZNVRFRUVkZmZCTU2N23///v0IDQ3FhAkTMGzYMDx69AiMSc4PEggEEttKS0slzqX8eFW1SQgh8qimQ8ir0759eyxYsADOzs4oKSmBk5MT+vXrBxcXF8ybNw99+/aFn58fPDw8UFBQgA4dOmDDhg2826v3YeYfffQR/u///o9LUP/88w+mTp1ao2NEREQgJycHRUVFOHXqFIyNjSEUChEcHIy8vDyUlpZKXDZ81z///IOJEyfCxsYGRUVFePDgAcRiMZSUlFBaWja5UFNTE2/fvkVGRgaKi4sRERFR6XnI2iYhhMgDJUVlmR41YW1tjZMnTyI0NBQuLi4AgD/++IO7rKevr4/AwECcOnUKu3bt4q6K8Tp/3pE14OXlheXLl2Pnzp1QVlbGxo0bazSwoE2bNnBxcUFmZiZsbGwwfPhwAMCDBw8wYcIEiEQiDB8+HPb29nj58qVE7PTp07F8+XL4+/tDQ0MDAwYMQFJSEgYPHoyOHTti2rRp2L9/P2bOnAknJyd06NCB+0O/z9TUtNI2CSFEHjX1UkcC9v71Ljlz7Ngx3Lhxg/coEHlSWMCv5I1yZjG/Bnn+ry1K5DdvoaA/v3I3hvMMecXFb3jMK64g8gWvuBaftuYVp/QRv5JFxWl5vOIA4OXBq7ziWq0ZwCuudaZO9TtVQpRewCvuVvtzvOIGZJjxihN9+hGvOJVX/F4fACjwfL+96887rjLt59xXPueDUi0+QghppmQdxSev5D5BOTg4cKPmCCGEyK4mZYzkkdwnKEIIIfw09XtQlKAIIaSZkrXUkbyiBEUIIc0U9aAIIYTIJboHRQghRC7RKD5CCCFySZF6UIQQQuQR3YMihBAil5QUaBQfIYQQOdTUe1ByX4uvOSmMTeYVp/yxBq84kQa/7x9Kb/nW/uMXVqrJ71tev5+784q7s/4RrziWzK823vjLw3jF/TUzjlccAKgli3jFiVup8Ip7qnSdV9zHUV15xSmN4LcOWwFL5xX3US6/univd/KriQgAXRaN4x1b7tLL32Xaz6TT97Vuqz5QD4oQQpqppt6DogRFCCHNlAKadoKq10HySUlJ0NXVxdKlSyW2JyQkQFdXF8eOHZP5OKamphW2+/r6wtDQELa2trCxsYGVlRUOHDhQJ+cuTUpKCoyMjOq9HUIIqQ0lBRWZHjUREhICCwsLjB07FgcPHqxyv8uXL1f6uV2j869VtAy0tLQQEREBkUjELY9++vRptGnTpk6OP2nSJMydOxcAkJGRgenTp0NVVRXjx4+vk+O/78qVK1izZg3S0tLq5fiEEFJXBHV8iS8lJQUbN27EsWPHoKKigkmTJsHAwACff/65xH7p6elYv359rdur92nG6urq6NmzJ6Kjo7lt//zzD4YNK7txfODAAYwfPx5WVlawt7fHkydPAJStXjt//nyMGzcOGRkZXGxoaChsbGwktpVr06YN5syZg7/++gtA2R/p22+/hbW1Nezt7REeHo6MjAxuRV4AGD58OE6fPg0A2LFjB3bu3AlfX194eHhg2rRpMDU1xbZt27j9AwMD4evrW4d/IUIIqR8KUJTpIaurV69CKBRCS0sLLVu2xLhx43D27NkK+3l4eMDNza0Ozr8BmJubIzQ0FAAQHx8PXV1dKCsrIzc3F2FhYdi/fz9OnjyJkSNHSnQZjY2NERoayvW2IiMj4efnh927d1fZA+vRoweX5Dw9PSEUChESEoLNmzfj119/hVgsxscff4xHjx7hv//+g0gkwo0bNwAAERERMDExAQA8fPgQu3btwpEjR+Dv74/s7LJVZn19fdGjR4/6+UMRQkgdUhAoyPTIzs5GUlJShUf551651NRUaGtrc891dHSQkpIisc+ff/6JXr16QV9fv/bnX+sjyMDU1BTh4eEQi8U4c+YMzM3NAQAaGhrw8fHBqVOn4OPjg0uXLiE/P5+Le/cFZmZmYu7cubCzs0O7du2qbEsgEEBNTQ0AEBUVBScnJwBAly5doK+vj9u3b8PY2BjXrl1DVFQUnJ2dERsbi5ycHKSnp6Nbt24AAAMDA6ioqKBt27bQ0tJCTk5Onf9dCCGkPikIFGV67Nu3D6NGjarw2Ldvn8TxxGIxBAIB95wxJvH80aNHOHfuHL777ru6Of86OUo11NXVoaenh9jYWERFRXGX9169eoWJEyciJycHxsbGsLe3x7vTslRVVbmfBQIBtm7dil27dlXI2O96+PAhl2Ten+LFGINIJMLIkSNx7do1XL9+HWPGjIGCggJCQkIkBj683zZNFyOENDWyJqjp06fjwoULFR7Tp0+XOF6HDh0k7r+npaVBR0eHe3727FmkpaXB0dERs2bNQmpqKqZMmcL//HlH1pC5uTl8fHzQp08fKCmVjc1o2bIlunbtiq+++gp9+/ZFWFgYRKLKJxhqaWlh6NChmDx5MlatWlXpPqmpqdi+fTumTp0KABAKhQgMDAQAvHjxAnFxcejfvz969+6Np0+f4tmzZ+jWrRsMDAywbds27vIeIYQ0B4oCFZkempqa6Ny5c4WHpqamxPGGDRuGa9euISMjAwUFBTh37hyMjY2538+bNw+hoaEIDg6Gv78/dHR0uDEBfDTYPCgTExMsXrwY33//vxnLysrKEIvFsLCwAGMMQ4YMwePHj6UeZ9asWbCxsUFYWBgA4NChQwgLC+N6ORMnToSlpSUAYPHixVi6dCk3nH3VqlVcth80aBAKCgoAlCWyI0eOYMiQIXX+ugkhpLHU9UTd9u3bY8GCBXB2dkZJSQmcnJzQr18/uLi4YN68eejbt2+dtkeljhqQ6N+KIw9l0pLf9wixsqD6nSrxqsU9XnFKuwp5xal/1oFXXEvDzrzi+v7Cb5DL/SX3ecWJ1Xh+SIj5hQGAQjHPUkeq/M61tBW/96hKGr+yWrl3qr7ML42aEb/3jGJuKa+4kle5vOIAQG0Qv3JO70rIPCPTfj1bm9e6rfpAlSQIIaSZolJHhBBC5FJdT9RtaJSgCCGkmVIS0HpQhBBC5BBd4iOEECKXKEERQgiRS4ImvtwGJShCCGmmqAdFCCFELlGCIoQQIpfoEh8hhBC5JGi4cqv1ghIUIYQ0UwLwK3cmLyhBNSCBCr9vM3yLJTIlfu0l5z3gFTdwVMPW82LJebzi+NbU6+XZi1fcvV/u8ooD3xp+AJgCzw8mnm82xXx+tf9y2/Gsxfc4mVdciyEf84pjPP+cyq3V+AXWGepBEUIIkUNNvQdVr+k1KSkJurq6WLp0qcT2hIQE6OrqcstgyHIcU1PTCtt9fX1haGgIW1tb2NjYwMrKCgcOHKiTc6+MSCTC0qVLYWVlBWtra4SEhNRbW4QQUlsCgYJMD3lV7z0oLS0tREREQCQSQVGx7JLF6dOn0aZNmzo5/qRJkzB37lwAQEZGBqZPnw5VVVWMHz++To7/rhMnTiA3NxcnT55ERkYGzM3NYWJiAg0NjTpvixBCaqupj+Kr99Sprq6Onj17Ijo6mtv2zz//cMu+HzhwAOPHj4eVlRXs7e3x5MkTAICpqSnmz5+PcePGISPjf+sohYaGwsbGRmJbuTZt2mDOnDncCo7p6en49ttvYW1tDXt7e4SHhyMjIwPDhw/nYoYPH47Tp08DAHbs2IGdO3fC19cXHh4emDZtGkxNTbFt2zYAgL29PTZs2ACgbPVeZWVlKCs37WKMhJDmSyDjf/KqQfp25ubmCA0NBQDEx8dDV1cXysrKyM3NRVhYGPbv34+TJ09i5MiROHjwIBdnbGyM0NBQrrcVGRkJPz8/7N69u8oeWI8ePbgk5+npCaFQiJCQEGzevBm//vorxGIxPv74Yzx69Aj//fcfRCIRbty4AQCIiIjgln1/+PAhdu3ahSNHjsDf3x/Z2dkAACUlJSxevBhOTk6YMGECVFVV6+ePRgghtaYg40N2ISEhsLCwwNixYyU+r8uFhYVxt12+++47ZGVl1ers652pqSnCw8MhFotx5swZmJuXjfbS0NCAj48PTp06BR8fH1y6dAn5+flcnL6+PvdzZmYm5s6dCzs7O7Rr167KtgQCAdTUykbOREVFwcnJCQDQpUsX6Ovr4/bt2zA2Nsa1a9cQFRUFZ2dnxMbGIicnB+np6ejWrRsAwMDAACoqKmjbti20tLSQk5PDtbF69WpERETg3LlziIyMrLs/FCGE1KG67kGlpKRg48aN+OuvvxAUFISAgAD8+++/3O9zc3OxfPly+Pv748SJE9DV1YWvry/v82+QBKWurg49PT3ExsYiKiqKu7z36tUrTJw4ETk5OTA2Noa9vT3eXYH+3d6JQCDA1q1bsWvXLqSkVL3c88OHD7kk8/5q9owxiEQijBw5EteuXcP169cxZswYKCgoICQkBEZGRlW2zRjD3bt38ezZMwBA69atMXz4cDx8+JD/H4YQQuqRAAoyPWR19epVCIVCaGlpoWXLlhg3bhzOnj3L/b6kpATLli1D+/btAQC6urp49eoV7/NvsOEb5ubm8PHxQZ8+faCkVDY2o2XLlujatSu++uor9O3bF2FhYRCJKp9PoaWlhaFDh2Ly5MlYtWpVpfukpqZi+/btmDp1KgBAKBQiMDAQAPDixQvExcWhf//+6N27N54+fYpnz56hW7duMDAwwLZt27jLe1W5ffs2vLy8IBaLkZubi8jISAwcOJDvn4QQQuqVAIoyPbKzs5GUlFThUX5ro1xqaiq0tbW55zo6OhIdhtatW2PMmDEAgMLCQvj7+2P06NG8z7/B5kGZmJhg8eLF+P7777ltysrKEIvFsLCwAGMMQ4YMwePHj6UeZ9asWbCxsUFYWBgA4NChQwgLC+N6ORMnToSlpSUAYPHixVi6dCk3nH3VqlXQ0dEBAAwaNAgFBQUAyhLZkSNHMGTIEKltT5o0CQ8fPoS1tTUUFBQwdepUDBgwgN8fhBBC6pmsl+/27duHLVu2VNju5ubGjZIGALFYDIHgf8dkjEk8L5eTkwNXV1fo6enB3t6ex5mXEbD3r4OReiNOfMsrjm9FCFELfkNM44qP8IobmNawlST4UtLkN7ClKVWS4Ivve42p8BsJVtCigFdcrv89XnHaUwbxihOU8vuYFBSU8ooDAMXPaj8VJ7sgTbYdS1Qr9JYAQFNTE5qamtzz48ePIyYmBqtXrwYA+Pn5gTEGNzc3bp/U1FR88803EAqF+PXXXytNYLKiBNWAShJkfLO8R6EVvw9UvglKsYBf2RpxZiG/9jRUeMXZh/D7sDk64RavOEF2Ca+43uv78Iq75fsfrzgAUHnF7/+FuAW/iyrZrTJ5xSmH8yt1pGzcmVecWMAvYai85fcxmX/rNa84ANA06847tlxOwRuZ9vuoRVuZ9ktJScHkyZMRGBiIFi1aYNKkSfD09ES/fv0AlBUzGD9+PEaPHo3vvvuO93mXo1JHhBDSTNX1HKf27dtjwYIFcHZ2RklJCZycnNCvXz+4uLhg3rx5eP36Ne7fvw+RSMRNLerTpw/X46opSlCEENJc1UMZI2tra1hbW0ts++OPPwAAffv2xYMH/IpNV4YSFCGENFMKTbzUESUoQghptuS3jJEsKEERQkgzRSvqEkIIkUvyXAhWFpSgCCGk2aIERQghRB418VmulKAIIaSZEoibdoaiBEUIIc1V085PlKAIIaTZauKV7KgWXwMSv+C3siRT5HejU6TB7/uHYjq/Om5Q4TcpsOR1Lq84UR8NXnGqb/kNvRWUinnFlbTjV2uw/9xuvOIAIH6D9FUBqsK3DmOq1lNecW1L+NWbEz/mV/svp1cerzitp1q84nITql67rjqtnfryji1XnJ1f/U4AVDRb1rqt+kA9KEIIaa6aePejXmdxJSUlQVdXF0uXLpXYnpCQAF1dXW6dJlmOY2pqWmG7r68vDA0NYWtrCxsbG1hZWeHAgQN1cu5VGTVqFGxtbblHbVaLJISQeiVmsj3kVL33oLS0tBAREQGRSARFxbJLQKdPn0abNrVf6wQoW0SwfEGtjIwMTJ8+Haqqqhg/fnydHP9dmZmZUFZWRnBwcJ0fmxBCiKR6r4Ohrq6Onj17Ijo6mtv2zz//YNiwYQCAAwcOYPz48bCysoK9vT2ePHkCADA1NcX8+fMxbtw4ZGRkcLGhoaGwsbGR2FauTZs2mDNnDv766y8AQHp6Or799ltYW1vD3t4e4eHhyMjIwPDhw7mY4cOH4/Tp0wCAHTt2YOfOnfD19YWHhwemTZsGU1NTbNu2DQBw584dMMYwadIk2Nvb48yZM3X81yKEkLojYEymh7xqkEJN5ubm3Nog8fHx0NXVhbKyMnJzcxEWFob9+/fj5MmTGDlyJA4ePMjFGRsbIzQ0lOttRUZGws/PD7t3766yB9ajRw8uyXl6ekIoFCIkJASbN2/Gr7/+CrFYjI8//hiPHj3Cf//9B5FIhBs3bgAAIiIiYGJiAgB4+PAhdu3ahSNHjsDf3x/Z2dkoLi7G8OHDsXfvXvj6+mLdunX47z/+i8oRQki9YjI+5FSDJChTU1OEh4dDLBbjzJkzMDcvWxpcQ0MDPj4+OHXqFHx8fHDp0iXk5/9v1Im+vj73c2ZmJubOnQs7Ozu0a9euyrYEAgHU1NQAAFFRUXBycgIAdOnSBfr6+rh9+zaMjY1x7do1REVFwdnZGbGxscjJyUF6ejq6dSsbOWVgYAAVFRW0bdsWWlpayMnJwejRo+Hh4QE1NTV07twZY8aMQWRkZJ3/vQghpE5Qgqqeuro69PT0EBsbi6ioKO7y3qtXrzBx4kTk5OTA2NgY9vb2eHfUu6rq/5Y6FwgE2Lp1K3bt2oWUlKqHbj58+JBLMu+PoGeMQSQSYeTIkbh27RquX7+OMWPGQEFBASEhITAyMqqybcYYLl26hDt37kgcU0mJBkISQuQUY7I95FSD1WI3NzeHj48P+vTpw32ot2zZEl27dsVXX32Fvn37IiwsDCJR5fMwtLS0MHToUEyePBmrVq2qdJ/U1FRs374dU6dOBQAIhUIEBgYCAF68eIG4uDj0798fvXv3xtOnT/Hs2TN069YNBgYG2LZtG3d5ryovX76En58fxGIx0tPTcfHiRYwcOZLnX4QQQuqXQCzboyZCQkJgYWGBsWPHStySKZeQkAAHBweMGzcOixcvRmlpKe/zb7AEZWJigoSEBFhYWHDblJWVIRaLYWFhAXt7e3z66adISkqSepxZs2bh8ePHCAsLAwAcOnQItra2sLOzg4uLCyZOnAhLS0sAwOLFixEVFQVra2t89913WLVqFXR0dCAQCDBo0CCupyUUCpGbm4shQ4ZIbXvSpEnQ1taGlZUVvvzyS/z000/o1KlTbf4shBBSf+r4El9KSgo2btyIv/76C0FBQQgICMC///4rsc/ChQuxdOlShIaGgjGGw4cP8z59qiTRgKiSROWokkTlqJJE1aiShGxKX2XLtF++OpCdXXFfTU1NaGpqcs+PHz+O6OhorFmzBgDg5+cHxhjc3NwAlF1lmj59OteBiImJwebNm/Hnn3/yOn+6gdKAcu/we7Oq9+/AK04xu4RXHNT4vS3yW/NrL9XnKq+4/5s7ilecQInfdzKmwO+Lgsorfgmfb5IBgH4/8/vgjzDkN8dPZ6wurziA3+Ufhc6a1e9UiVYlrXnFFb1+zSuuhSW//w91RSDjW33fvn3YsmVLhe1ubm7cPFOg7DaKtrY291xHRwfx8fFV/l5bW1vqmIHqUIIihJAP3PTp02Fvb19h+7u9JwAQi8UQCP73RY0xJvG8ut/XFCUoQghprmS8g6Op2apCMqpMhw4dEBMTwz1PS0uDjo6OxO/T0tK45+np6RK/r6kGGyRBCCGkYdX1KL5hw4bh2rVryMjIQEFBAc6dOwdjY2Pu9506dYKqqipiY2MBAMHBwRK/rylKUIQQ0lzV8Tyo9u3bY8GCBXB2doadnR2srKzQr18/uLi4cHNEvb29sXbtWpiZmSE/Px/Ozs68T58u8RFCSHNVD2O0ra2tYW1tLbHtjz/+4H7W09Pj5p/WFiUoQghpruR4KQ1ZUIIihJBmqqlPc6UERQghzRQrpQRFCCFEHlEPihBCiDxiTfweFNXia0AZBYm84jTfavGKUyjhVztOrMavph74NYe3rfiVQmmVz68ElIDvZY8G/pciqMWHS8a5h7zihv9jyyvuvsd9XnFMmd9MF1FGAa84vlUNWGd+dR8VeNY2BAClDh/xji1Xci9Vpv2Ue/OfTFufqAdFCCHNVFPvf1CCIoSQ5ornVQ15UW3/OikpCaamphW26+ryrV7M37Rp03D9+vUGb7cq06ZNa+xTIISQKjGRWKaHvKIeVC3cuHGjsU+BEEKq1NQHSdQqQR07dgwRERHIysrCixcvYGhoiOXLlwMA/P39cebMGYhEIhgZGWHhwoV4+fIlXF1d8dlnn+Hff/9Fr169MGDAABw/fhxZWVnw8/NDt27dYGpqCjMzM1y9WrZO0Jo1a9CrVy+Jtrdv344TJ05AUVERhoaGWLhwIXx9fcEYw4IFCwAA7u7uMDY2Rnh4OFq0aIH79+8jOzsbP/zwA4KDg/HgwQOMHj0a7u7uEIlE2LBhA27cuAGRSAQHBwd89dVXuH79Onbs2AE1NTX8999/0NXVhbe3NzZs2AAAGD9+PI4cOVKbPyMhhNSPJn4PqtbFYm/evInNmzfjxIkTuHTpEh4+fIjw8HDcvXsXgYGBCAoKQkpKCk6cOAEAePjwIVxcXBAcHIy4uDi8fPkSAQEBsLKyQkBAAHfcli1bIigoCPPmzcMvv/wi0eaVK1dw8eJFHD16FMePH8fz589x6NAhODo6IiQkBIwxFBQUICoqCqNGlS1ql5qaioCAAMyaNQuLFi3CihUrEBQUhMOHDyMnJ4dblvj48eMIDAzEhQsXuLLyN2/exNKlS3HmzBkkJycjMjISHh4eAEDJiRAit5iYyfSQV9X2oBQUKuawdxehGjBgADQ0yoZgdunSBVlZWbh27Rri4+Ph4OAAACgsLETHjh0xaNAgtGvXjusNdejQAUOHDgUAdOzYEUlJSVwbEyZMAACYmprC3d0dGRkZ3O+ioqJgaWmJFi1aAAAcHR0RFBSEqVOnolOnToiOjkZycjJGjBgBVVVVAOBKvnfs2BHdu3dH27ZtAQBaWlrcOSckJCAqKgoAkJ+fj4cPH+Lzzz9H9+7d0aFD2ZDmbt26ISuL39LthBDSoOT39pJMqk1QmpqayMnJkdj25s0btGrVCgC4BACUzTFgjEEkEmH69OmYMWMGgLK17hUVFZGZmQkVFRWJYykqVj7nRknpf6cmFosl9hOLK/7VS0vLlo52dHTEyZMnkZycLLFUsbKycqXHLicSibBw4UKMHTsWAJCRkQF1dXXcunWr0tdICCHyrql/VlV7iU9DQwNdu3ZFaGgoty0gIIDr+VRGKBQiODgYeXl5KC0thaurq0S8LE6dOgUAOH/+PLp168YlxPLjnzp1CoWFhSgtLcXRo0chFAoBAGZmZrh27RrS09Ohr68vc3tCoRCHDx9GSUkJ8vLyMGXKFNy6dUtqjKKiIpcYCSFE7pSKZXvIKZkGSXh5eWH58uXw8/NDSUkJdHV1sXTpUly+fLnS/U1NTfHgwQNMmDABIpEIw4cPh729PV6+fCnzicXFxSEwMBAtWrTAunXrJH5nYmKChIQEODo6orS0FEZGRvjyyy8BAGpqaujfvz969Oghc1sAMGnSJDx//hz29vYoLS2Fg4MDDAwMpA5rHzVqFGxtbXHs2DGJXhYhhMiDpt6DkstSR6ampvjzzz/RuXPnGsUxxpCXl4eJEydi79690NbWrqcz5IdKHVWOSh1VjkodVY1KHckm7/IzmfZTH/l/tW4rOTkZCxcuxJs3b/Dpp5/C29sb6urqEvukpqZi0aJFSE9Ph4KCAn7++WepV+Oa1TyoO3fuYObMmXB1dZW75AQAKlf5XQ4U9OTXXqZ2Jq84rcy2/BrM5/f6Wov51QH7T53fpO1P1IfxilPM5/dhk9Mio/qdKlHE+P3/AwCdsfwm0t834Zdoeq3qVf1Olbi34gGvOMU2LXjFme/vxytur9peXnEBC3x5xQHAAvFR3rHlGnKE3ooVKzBlyhRYWlrCz88PW7duxcKFCyX22bBhA0xNTTF16lQ8efIE06ZNQ3h4eNVjERrixGvq4sWLvOL69etHk2cJIaScjBfIsrOzkZ2dXWG7pqYmNDU1q40vKSlBdHQ0/Pz8AAAODg748ssvKySoMWPGcOMFunbtiqKiIuTn5+OjjyrvLcplgiKEEFJ7TMYBEPv27cOWLVsqbHdzc5MYDV2VzMxMaGhocCOktbW1kZJS8dL9uHHjuJ937dqFnj17VpmcAEpQhBDSbMk6xGD69Omwt7evsL2y3tOZM2ewdu1aiW1du3atcH9P2v2+vXv3IiAgAAcOHJB6XpSgCCGkuZLxHpSsl/IAwNzcHObm5hLbSkpKYGBgAJFIBEVFRaSlpUFHp/J7yxs2bMCVK1dw8OBBrgBCVWpd6ogQQoh8aqhq5srKyhg8eDBOnz4NAAgKCuKq97xr7969uH79Ov7+++9qkxNAPShCCGm2GnIU37Jly+Du7o5t27bh448/xm+//QYA+Pvvv5Gamop58+bBz88PGhoaEksV+fv7o3379pUekxIUIYQ0Uw251lOnTp2wf//+CtsnT57M/RwdHV2jY1KCIoSQZoqV8J8oLA8oQRFCSDPFKims3ZRQgiKEkGZKnpdzl4Vc1uJrrkTJFWdq1yexMr+6Y0UaJbziFAQq1e9UCaVHebziil7lVL9TJdR78SuDlduumFecIJzf+mGqwo684gBAMa9pVNnvvUyPV9yKAGtecU4PvHjFNQbFjrIN+5Ym/c8YmfZr5zy41m3VB+pBEUJIMyXPq+XKghIUIYQ0U+KSptGTrkqznag7Y8YMhIWFcc/Xr1+PAQMGoLj4f5dpjIyMJJaZl4WpqWmNYwghpFGIxLI95FSzTVBCoRCxsbHc86tXr6J///7ctufPn6Nly5Y1XnOKEEKaCiZmMj3kVbNNUEOHDsXNmzcBACkpKVBRUcG4ceMQGRkJAIiJiYGhoSGCgoJgb28PW1tb/PrrrygqKgIAhIeHw8nJCXZ2dnBzc0NmpuTaPE+fPsXYsWOrXRaeEEIaS0OVOqovzTZB9e7dG4mJiSgqKkJkZCQMDQ1haGgokaB0dHRw+PBhHDp0CMHBwWjbti127dqFjIwM+Pj4YNeuXQgKCoKRkRG8vb25Y79+/Rpubm5Ys2YN+vfv30ivkBBCpGNisUwPedVsB0koKipCX18fd+7cQWRkJKZOnYouXbqgsLAQWVlZuHnzJnr27Innz59jwoQJAMoq8vbq1Qu3b9/Gq1ev4OzsDAAQi8Vo1aoVd+zvv/8effv2xeDB8jk0kxBCAAAi+b18J4tmm6CAsvtQcXFxiI+Ph5dX2fyHoUOH4sKFC2jdujUYYzA3N4eHhwcAIC8vDyKRCDdu3MDAgQOxfft2AEBRURHy8v43V2fx4sXw8/PD5cuXMXLkyAZ/XYQQIgsaxSfHhg4diuDgYPTo0YNb6dHQ0BB79uyBoaEhDAwMcP78ebx58waMMSxfvhz79u2Dvr4+bt26hadPnwIAtm7dig0bNnDH7devH5YvX46VK1ciPz+/UV4bIYRUp6lf4mvWCapHjx54+/YtjIyMuG1CoRBPnjzBsGHDoKenBzc3N0yfPh2WlpYQi8WYNWsWtLW1sWbNGsyfPx/W1ta4d+8efvnlF4ljDxkyBAYGBti0aVMDvypCCJGRiMn2kFNU6qgBUamjylGpo8pRqaOqUakj2SSuPC3Tfp8stah1W/WhWd+D+tAp5vL7kCo49R+vuJdWz3jFFbcv5BXXt4cjr7jci/wmWuc+TuYV12aWkFec+N4bXnEAoNCZ34ebOJ3fJWvFNi14xfFNNMsmhvCKc0LTSVB1QZ6HkMuiWV/iI4SQD1lD3oNKTk7G1KlTYWZmhjlz5kgMLHtfbm4uRo8ejevXr0s9JiUoQghppliJSKZHXVixYgWmTJmCs2fPok+fPti6dWuV+3p6eiI7u/pbHpSgCCGkmWKlYpke2dnZSEpKqvCQJYkAZXNIo6OjMW7cOACAg4MDzp49W+m+p0+fhrq6OnR1das9Lt2DIoSQZkrWe1D79u3Dli1bKmx3c3PD3Llzq43PzMyEhoYGN51HW1sbKSkpFfZLTk7Gvn37sG/fPri4uFR7XEpQhBDSTLFS2RLU9OnTYW9vX2G7pmbFwTZnzpzB2rVrJbZ17doVAoHkqOH3n4vFYixevBhLliyBmpqaTOdFCYoQQpopWXtQmpqalSajypibm8Pc3FxiW0lJCQwMDCASiaCoqIi0tDTo6OhI7PPkyRM8efIEixcvBgAkJibCw8MDnp6eEAorH+lKCYoQQpopcWHDzIdTVlbG4MGDcfr0aVhbWyMoKAjGxsYS+3z++ee4cuUK93zatGlwc3ODgYFBlcelQRKEENJMMRGT6VEXli1bhsOHD8PCwgIxMTGYP38+AODvv//G77//zuuY1IMihJBmStZ7UHWhU6dO2L9/f4XtkydPrnT/yvZ9HyUoQghpppp6JQlKUA1IlFHAK06hLb8yMjkd+LXXZmz18xMq07agB684US6/Gnc5mum84jSMOvOKazHkY15xJQJ+9wHyevGrUQgArUpa84p7f+SVrMz39+MVd+ZBPK84viWL+Nb+++FPE15xRvajeMUBQK9DX/OOLdeQPaj6QAmKEEKaKUpQhBBC5JK4qGlUta9Kk0tQK1asQFxcHEpKSpCYmIhu3boBAJydneHoyK+6tawePXoEa2trbN68mSvpQQgh8op6UA1s2bJlAICkpCQ4OzsjODi4wdo+evQozMzMEBAQQAmKECL3aJCEHNi0aRMYY1iwYAEAwN3dHcbGxggPD4eqqiru3LmDvLw8zJkzB3Z2dsjLy8PKlSvx+PFjiEQiuLi4wMrKSmobJSUlCAkJwcGDBzFp0iQkJibik08+aYiXRwghvDT1HlSzmKjr6OiIkJAQMMZQUFCAqKgojBpVNnrmxYsXCAgIwL59+7BhwwakpaVh27Zt6N27N44dO4aDBw9i+/btePHihdQ2rly5go4dO+LTTz/F6NGjERAQ0BAvjRBCeGMisUwPedUselBdunRBp06dEB0djeTkZIwYMQKqqqoAysq+Kysro0OHDhg4cCBiY2Nx9epVFBYW4ujRowCA/Px8PH78GF26dKmyjaNHj3K9LAsLC/z000/4/vvvoaLCb5lzQgipb029B9UsEhRQ1os6efIkkpOTJcrDKyoqcj+LxWIoKSlBLBbDy8sLvXv3BgCkp6ejVatWVR77zZs3iIiIwL179/Dnn3+CMYbs7GycP38elpaW9feiCCGkFsRFdbMYYWNpFpf4AMDMzAzXrl1Deno69PX1ue1nzpwBYwwvX75EfHw8Bg0aBKFQiL///hsAkJqaChsbG7x69arKYwcHB0MoFCI8PBwXL17EpUuXMHv2bBw6dKjeXxchhPAl64KF8qrZ9KDU1NTQv39/9OghWc2gsLAQjo6OKC4uxsqVK9G6dWu4ublh+fLlsLKygkgkwsKFC6UOeDh+/Dg3AKPc1KlTsXPnTvz333/cUHdCCJEn8nx/SRZNNkF17twZFy9eBAAwxpCXl4f79+/j559/ltjPzMwMDg4OEts0NDTg7e0tc1shISEVtrVp0wa3b9/mceaEENIw5Ll3JIsmm6DedefOHcycOROurq7Q1tbmdYyYmBh4enpW+jt/f3+0b9++NqcIAGAl/N4sAp7l8Fv+p1j9TpVpwy+sMDGLV5zCIJ3qd6rERzmyrcpZob0SfrPrGb8ydVB5yy9O+Y0Wv0AARa9f84pTGdyBV9xetb284hoa35p6vzlf4hVn8flXvOLqCiUoOdCvXz/cuHGjwvZ169bJfIzBgwc36KRfQgipb+JiKnVECCFEDolZ0+5BNZtRfIQQQiSJGZPpUReSk5MxdepUmJmZYc6cOcjLq7hcTHFxMVatWgU7OztYWloiMjJS6jEpQRFCSDMlYmKZHnVhxYoVmDJlCs6ePYs+ffpg69atFfbZuXMnMjMzcfz4cWzatAmLFi0Ck5IgKUERQkgzJWZimR7Z2dlISkqq8MjOzpapnZKSEkRHR3NFtB0cHHD27NkK+505cwYuLi4QCATo3r079uzZIzVB0T0oQghppmS9fLdv3z5s2bKlwnY3NzeJyjxVyczMhIaGBpSUylKKtrY2UlJSKuz3/PlzREdHY+XKlRCJRFiwYAE+//zzKo9LCYoQQpqpUrFso/imT58Oe3v7Cts1NTUrbDtz5gzWrl0rsa1r164QCCTnYbz/HABEIhFev36NgwcP4uHDh5g5cybOnDmDjz76qNLzogRFCCHNlKw9KE1NzUqTUWXMzc1hbm4usa2kpAQGBgYQiURQVFREWloadHQqzm9s164dLC0tIRAIoKenhw4dOuDp06fo169fpW3RPShCCGmmZL0HVVvKysoYPHgwTp8+DQAICgqCsbFxhf1MTEy4fV68eIFXr17h008/rfK4lKAIIaSZashRfMuWLcPhw4dhYWGBmJgYzJ8/HwDw999/4/fffwcA/PTTT0hNTYWlpSVmz56NVatWVXl5DwAETNoQClKnUvMf8oprk92RV1zx4wxecardWvOKy2r9llec1uuq36DSvDxUsXqILLTH9uUVp9yaX2mlvEdveMWJcgt5xQFAC8vuvOKUskp4xfl2/IpX3LykPbzi+Hr4QyCvOM0BVa8VJ83of6fzigOAB38k844td1TLVab9HN/61bqt+kD3oAghpJlq6pUkKEERQkgzVSpu2gsWNrkEtWLFCsTFxaGkpASJiYncWkzOzs5wdHSst3Zzc3Ph4+OD6OhoKCoqQlNTE+7u7tyqvIQQIm+oB9XAli1bBgBISkqCs7Nzg1QgF4vFcHFxgYGBAYKCgqCkpISoqCi4uLjg1KlTaN2a3z0bQgipT3U1AKKxNLkEVZlNmzaBMcateuvu7g5jY2OEh4dDVVUVd+7cQV5eHubMmQM7Ozvk5eVh5cqVePz4MUQiEVxcXGBlZVXl8a9fv45Xr15h3rx5UFAoG/goFAqxdu1aiMVN+w1ACGm+mnoPqlkMM3d0dERISAgYYygoKEBUVBRGjRoFoGysfUBAAPbt24cNGzYgLS0N27ZtQ+/evXHs2DEcPHgQ27dvx4sXL6o8/v3796Gnp8clp3IjRoxA27Zt6/W1EUIIXw1Zzbw+NIseVJcuXdCpUydER0cjOTkZI0aMgKqqKoCyooXKysro0KEDBg4ciNjYWFy9ehWFhYU4evQoACA/Px+PHz9Gly6VDyVVUFDgjkcIIU2FrKWO5FWzSFBAWS/q5MmTSE5OlihuqKj4v2XPxWIxlJSUIBaL4eXlxQ1wSE9PR6tWrao8dp8+ffDXX3+BMSZRX+q3337DsGHDIBQK6+EVEUJI7chz70gWzeISHwCYmZnh2rVrSE9Ph76+Prf9zJkzYIzh5cuXiI+Px6BBgyAUCvH3338DAFJTU2FjY4NXr15VeezBgwejbdu22LJlC0SismGbEREROHbsmNRKvIQQ0pgaspJEfWg2PSg1NTX0798fPXr0kNheWFgIR0dHFBcXY+XKlWjdujXc3NywfPlyWFlZQSQSYeHChfjkk0+qPLZAIMDWrVuxdu1aWFlZQUlJCa1bt4a/vz/atWtX3y+NEEJ4aeqDJJpsgurcuTMuXrwIAGCMIS8vD/fv38fPP/8ssZ+ZmRkcHBwktmloaMDb27tG7bVp0wZeXl61O2lCCGlATf0SX7OoxRcfH4+ZM2fC1dUV06f/r/aVu7s7vvjiiwoJqjIxMTHw9PSs9Hf+/v5o3759nZ0vIYSQ6jWLBEUIIaT5aTaDJAghhDQvlKAIIYTIJUpQhBBC5BIlKEIIIXKJEhQhhBC5RAmKEEKIXKIERQghRC5RgiKEECKXKEERQgiRS5SgCCE1Ulxc3NinQD4QlKCaoKysrArbXr58WaNj5ObmyryvpaUldu7cibS0tBq1AQAhISHYuHEjCgoKEBQUVKPY/Px8PHjwAIwx5Ofn17htWSUkJODixYvIycmR2H7p0qVqz6/8w/rq1avYs2cPbt++XeP2d+/eXe0+KSkp3M9PnjzB/v378ffff0tdJqYuTJw4UeK5WCyGo6NjvbQVHx8v8bywsBDr1q2TKfby5ct1dh5Pnz6ts2O9KysrCxkZGdzzGzduSDwnFVGCaiQvX77EjBkzMHbsWKSmpsLZ2RlJSUlSY169eoXk5GRMnTqV+zk5ORkvXrzAN998IzX20qVL8PLyQl5eHszNzTFq1CgcO3ZMpnP19/dHUVERnJ2dMWvWLJw9exYlJSXVxnl7e+PKlSs4d+4cRCIRjh49KvMHzrVr12Bra4vvvvsO6enpMDExQWRkpEyxNbFv3z789NNPOHz4MLemWLnNmzdXGXfy5EmYmJhg1KhR2LJlC9auXYu0tDQsWbIER44cqTJuy5YtFR67d+/mfq7K7NmzAQBnz57F119/jcTERPz333/48ssvcfbs2SrjgoKCpD6q4uzsDD09Pdy+fRt6enrco1+/fvj000+rjCvH5/29cOFC3Lx5EwBw5coVWFhYIDs7u9q2ANR6pYHS0lKcPn0a06ZNq7a49H///YfU1FQAZf82Zs+eDV9fXxQWFlYZc//+fVhaWuLu3bvctn/++Qe2trZ48OBBrc69WWOkUXz99dcsIiKC2dnZMbFYzAICAtiUKVOkxri7uzMTExPWu3dvZmJiwj3GjBnDVq9eLTXWwcGBJSQksMOHD7Off/6Z5ebmMnt7+xqf97lz55ixsTH74osv2KpVq1hGRkaV+9ra2jKxWMxsbW0ZY4yVlJQwc3NzmdpxcnJiqampXOzjx4+ZtbV1pfsaGhoyPT29Cg9dXV2mp6cntR0rKyuWn5/PGGMsNjaWGRoasujoaO78q2Jtbc0yMjJYQkIC69OnD3v79i1jjLGcnBxmY2NTZdzcuXOZgYEB++2335ivry/z9fVlhoaG3M9VsbOzY4wxZm9vz5KSkrjtaWlpUv+m7u7uUh/V8fT0rHafyvB5fz958oRZWlqy2bNnMysrK+7/gyy+/fZb5u7uzv7++292/Phx7lGdxMRE5u3tzYYOHcp69+7NfH192Zs3b6rcf9++fWzEiBHM1NSUubu7s4kTJ7J9+/YxV1dX9tNPP1UZ5+zszKKioipsDw8PZ9OnT5flJX6Qmux6UE1dZmYmjIyM4O3tDYFAgAkTJuDgwYNSY9auXQug7FvbrFmzatymnp4efH19YWNjA3V1dZl6QQCQl5eH0NBQBAcHIyUlBZMnT4alpSXCw8PxzTffVNkTU1Ao66ALBAIAZfcuyrdVRywWQ1tbm3subeXio0ePwtnZGX5+frxWOG7RogUAYODAgdi4cSPmz5+P3bt3c+ddGcYYWrdujdatW8PW1hatWrUCAKirq3OrLldm8+bNCAwMRFBQEFasWIFu3bohLCwMbm5uMp2rqqqqxN+lbdu2Us+z/D3D1y+//ILLly/j7du3Etvt7OykxtXk/Z2cnAyg7LUtX74c8+fPh4eHBzp27Ijk5GR07Nix2vNs3bo1AFS4xFrVeZ4/fx6HDh3CvXv3MGbMGHh5eWHJkiXV/n8ICAjA6dOnUVBQgNGjRyMyMhLq6uqYOnWq1L9JdnY2DAwMKmwfPnx4jdem+5BQgmokampqeP36NffhEhMTAxUVFZliJ06ciNWrVyMqKgpKSkowNjbGnDlzoKamVmVMu3bt4Onpibt378LLywvr1q2T6R8+AIwaNQomJiZwc3PDkCFDuO1TpkzB1atXq4wzMzPD/PnzkZWVhb179+LEiROwsrKSqc0OHTrg0qVLEAgEyM7OxsGDB6s83/bt2+PXX3/F5s2bpV6Wq8ygQYOwYMECuLq64vPPP8eQIUOwdOlSzJgxQ2qiGTBgAH788Ud4eXlh1apVAIDnz5/Dy8sLgwYNktqmk5MTvvjiCyxevBjjxo2T6TxzcnJgYWEBsVgMLy8vLF68GHfv3sWWLVuktpeSkoINGzbg8ePH3DlramrK1CYA/PTTT0hOTka3bt0kEmF1Caom7+8vv/wSAoEA7P+v/KOiooINGzYAKPtyc+HChWrPs7JELO2S29y5c2Fubo6AgAB07dqVa6s6SkpKaNmyJVq2bIkuXbpAXV0dAKCoqAglpao/TktLSyEWiyt8QROLxTJ/UfwQ0XpQjeTOnTvw8PBAYmIiPvnkE2RlZeH333+Hvr5+tbHffvstPvvsM9jZ2YExhqNHjyIjIwM+Pj5VxuTm5iIsLAwDBw7EJ598goMHD8LW1hYaGhrVtpebm1thv8LCQqkJEQBEIhGuXr2Kq1evQiwWQygUwsTEpNr2AODNmzdYvXo1rl69CsYYDAwM4OHhAR0dHZniZSUWi3H06FHo6uqiX79+3Pb4+Hhs374dW7durTLuxIkTEh/U9+7dw+3btzFp0iSZeooikQibN2/GuXPncObMmWr3f/v2Le7cuYOioiKMHj0aly9fxsuXLzFp0iQoKipWGvPNN9+gR48eMDAwQGhoKICa9arMzMyk3uOqSnx8PJYsWcLr/c3HxYsXsWnTJuTn54MxBrFYjMLCQol7iu969OgRjh07hpCQEHTq1AmWlpbYs2dPtYMt7O3tcfz48Qo/V/b8XStXroSWlhbmzZsnsX3Lli1ITEzkEjKRRAmqkVy+fBmGhoZ49uwZRCIRPvvsM5l7UFZWVjh58mS129534sQJ/Pfff5g9ezZCQ0Or/RZcrrJ//AUFBYiKipIaJ+0frCzu37+PXr16IScnB3fv3sXQoUOrjcnNzUVOTg7efVvL2lPkGyvPce++L0pKSmBnZ4dTp05V20Y5V1dXLFu2jNcXg5KSEon3d0pKCrp06VLl/llZWfDy8kJiYiI2b96M9evXY9GiRTL1+MaMGQNPT0/s2bMHs2fPRlhYGAoKCrB06VKpcaWlpbh8+TKOHTuG8PBwDBs2DFOnTsWIESMq3X/AgAHo27cvgLIvmeU/M8Zw7949xMXFVRqXm5uLWbNm4fXr19DT04Oqqiru37+PNm3aYNu2bdDS0qr2NX6I6BJfI/Hy8sLIkSPRvXv3Gsd+/vnniImJweDBgwEADx484C5TVMXb2xuvX7/GvXv34OLigqNHj+LBgwdwd3evtr21a9dW+o+/Ou3atUNMTAz69esnc/J993zv37+P3bt3o6CgAFu3bkVMTAzmzp1bZcz27dvh7+8v8Y9d1ktEfGPrIq788lZ9xCkrK0v8/O5zWRQWFsLMzAw9evSQ+H/4559/So0bOHAg1q5dK3EJc968eVK/sCxZsgSGhoaIj49Hy5YtoaOjg59++gn+/v7VnudHH30EoVCIuLg45OTkYOHChbCwsKg2TklJCaNHj8bo0aORkZGBoKAg+Pj4YMSIEUhLS5O43wcAO3bsqPaYlcVpaGjg4MGDiIqKQkJCAhQUFDB16lTu33BVcR+8hh6VQcrwHXXEWNkIMl1dXWZmZsYsLS1Zr1692NChQ5mJiQkzNTWtNKY2I+rKR/v5+fmxK1euMMaYTLEGBgZMV1dX4lHdqLpylpaWrLS0lHteUlLCrKyspMaMGjVK6gis+oiV97jy0X9VPa/O9evXK31Ux9TUlE2cOJH5+Phw26SNimTsf++zd/erauTm+yZPnsyePHnCzp49y7y8vFhRUREbPXq0TLFVqenfqrHimjPqQTWSmo46ete2bdtq3F5tRtSpqanh6dOn6NatG27cuAGhUCjTjd3qLgFKU1paisLCQu4mtCztffzxx9xoupriGyvvcY8fP8aoUaO45ykpKRg1apTMPbYvvvgCsbGxePToERwdHXH79m2JgTJV0dTUxJ9//gkPDw+4uLjgt99+q/b9pqioiJycHO49+uzZM5nfo/Pnz8emTZvg5eUFf39/BAQEwMnJSabYqjCedz8aOq45owTVSNauXYuSkhI8ffoUIpEI3bt3lzoK6F2dOnVCSEgI/v33X5nvJ9VmRF1l//hlqSZQ1cRTWYZUT5o0CQ4ODjA1NQUAhIeHY+rUqVJj/u///g9TpkyBgYGBxOUoWdrjGyvvcaGhoXj79i1EIhHatm0LALh+/To+//xz7rk0+/btQ1hYGFJTU2FmZoalS5fCycmp2onhjDFuNN6uXbswYcIElJaWSo2ZN28epk2bhlevXuG7777DrVu3sGbNmmrPEShLpF988QWAsmkHWVlZvL+slJNlVJ88xDVnlKAayd27dzFv3jxoaWlBLBYjPT0dfn5+Mo1y4nM/adasWYiIiEDHjh3x6tUrzJ07V+YRdXXxj7+kpAQREREyj+L66quvMGjQIERHR0NJSQleXl7o1auX1Jj27dujffv2NTqv2sbKe1xWVha+/fZbrFmzhhul+Pz5c2zcuBF//PFHtfHHjx/H4cOHMWHCBLRu3RqBgYEYP358tQlq+PDh3M/ffPMNunfvjtWrV1cb07t3b8THx0MkEmHlypVo166dDK+yrHKFh4cHXr58iYMHD+LHH3/EmjVr0LlzZ5niiXyiBNVIVq1ahY0bN3If2Ldu3YKnpycCAwOrjY2MjMTx48dhb28PDQ0N7NmzBzY2NpUmqOjoaO5nNTU1rkdS/jtpl2umTZsm9VtddTfK3/9W7+rqiq+//lpqzKVLl2BiYsKV4WnTpg2AsmHBjx49ktpTbNGiBUxMTPDZZ59JbaMuY+U9bv369fDx8ZGYJLpgwQIMHjwY69atw969e6XGKygoSPTUVFVVqxzSDvzvRv/kyZO5CbhA2cCePXv2SG2ruLgYhw8fxpMnT7BkyRLs27cPs2bNkmmAzdKlS/HNN9/A29sb7dq1g5WVFX755ZdqJ78T+UYJqpHk5+dL9Cb69++PoqIimWLfvy4v7X6StImrAoFAapIpHzF3+PBhqKmpwc7ODkpKSjh58qTM5/quvLw8iQ+tyty5cwcmJia4fv16pb+XlqBEIhGWLVuGN2/ewMjICCYmJhgyZIhMl075xsp7XG0rGHzxxRdYv349CgoKEBYWhoCAAAiFwir39/DwwI4dO7jJt++Tds9r5cqVaNOmDe7fvw8lJSUkJibi119/lek8+VRmqQ7dg5IDjTc+48P25ZdfsvPnz3PPz58/z7788kuZYnfs2MHmzZvHTExM2J49e5idnR3btm1bfZ0qc3BwqLBNljp+5aMKTU1NmYmJCRs4cCDz8/OTqc3ffvutxudZLicnh/31119s+PDhbODAgQ0SK69xVlZWTCQSVdguEolkGokpEonY33//zebOnctcXV3Z/v37WUlJidSYixcvsufPnzPGymo3zpo1i23atIkVFRVJjSsfxVY+ik8sFjNLS0upMXl5eYyxslF8r1694o4RHR3NnJycqn19jDH24sULdunSJVZaWsoSExO57dXVAmzouA8R9aAaiaenJxYuXIjFixcDALp06SJzReaRI0dCR0cHL168QGxsLL7//nuMHDlSasytW7ewY8cOicm2ycnJuHjxYrXtFRUV4enTp1wV64cPH1Z7wxsA9u/fz/0sEAigqakpU+UKoOxS3/z582t04/jMmTOIjo5GTEwMFBUVYW5uLvXbfl3EynvckCFDsGXLlgoVDLZu3Yo+ffpU256CggKsrKxgbGzMbUtNTa1yYvDu3btx6tQprF+/Hg8ePODe4wkJCfD29savv/5aZVsCgQDFxcXc//PMzMxq///b2tpi7dq1WLRoEb799lskJibC1taWq1xRndOnT2Pbtm0oKChAQEAAJk2ahJ9//hm2trYSc5QaO+6D1dgZ8kP16NEjxljZN8CcnBzGGGM3b96UGpOens6mTJnCvvjiCzZ+/Hg2fvx4NnjwYDZz5kyWnZ0tNdbc3JwFBgayqVOnsrNnz7Iffvih2gro5SIiIpihoSFzcHBg9vb2zNjYWKZve25ubhW2OTs7y9TmtGnT2NixY9mCBQtkrr49fPhwNmzYMLZjxw725MkTmdqpbay8x+Xk5LDJkyczExMTNmfOHDZ//nw2duxYNmnSJJaZmVlt/Lp169jAgQMlesJVzbVjrGzeUnl1eC8vL7ZgwQLGWFlvyMzMrNKYly9fMsYYO378OJsyZQozNDRkq1atYiNHjmRHjhyRen4RERFs9OjRbO3atSwnJ4c9evSIJSQkVNtbK2dnZ8dycnK4XltKSgqzsLCQu7gPFfWgGlhsbCzEYjE8PDywevVq7rpzaWkpli9fztVLq4yPjw8GDRqEvXv3chUBSkpKsHnzZqxevVrqWksqKipwdHTEy5cvoampiQ0bNsDa2lqmczYyMsLFixfx6NEjCAQC6OrqSr1X4ubmhoSEBKSmpkrMwSktLcXHH38sU5v29vYy7feu8PBwPHnyBFFRUfj999/x7NkzdOvWTWqNwtrGynucLBUMpLlw4QLCw8O5+WjVEQgEXHX469evY8qUKdz2qkycOBEtW7aEkZERhg8fDnNzczDGsG3bNujp6Ultz8jICCdOnMDvv/+OKVOmYOnSpejYsSPS09MBVF86SkFBQaJXr6OjI9Pcq4aO+1BRgmpgV69exY0bN5CamspdghAIBFBSUqqweun7bt68WaGoqLKyMn744QfY2tpKjVVVVcXbt2/x6aef4vbt2xg6dKjUat0A4Ovri7lz52LRokWV/r6qoqPr1q3D27dvsXr1anh4eHDblZSUZJp78+TJE2hoaKB3794y19ErJxaLuUm+hYWF3IdlfcbKe5xAIMDQoUNlqmX4Pl1dXRQXF8ucoBQVFZGdnY38/HwkJCTA0NAQQNkw8Kq+1ERERCAxMRExMTGIjo7GrVu30KZNG2RnZ6OoqKjaqQktWrTA999/j9evX2POnDnQ1NSUeSJy9+7dceDAAZSWliIhIQF//fVXtUmxMeI+VFQsthFcvHgRCQkJcHV1xfnz5xEYGIhevXrhu+++k1orzc7OrspVUKX9Dii7d3H48GH4+vpi/PjxUFBQgJ6entRv7BcvXoSpqWmV9dNk6eXcv3+fu+8lEomQlJQkdYb/wYMH4e3tjc8++wwvXryAp6enzEtSGBsbo2PHjjA2NsaIESPQu3dvmeJqE9tU4vgKCwvDokWL0KNHD4nh5VWN/jx79iw2bNiA0tJSmJqaYvny5Th9+jQ2btwIV1dXmSqlZGdn48KFC9i9ezeePn0qsQptZS5dugRPT08YGRnh559/lvk+J1A2mnbbtm0SVfNdXV2rPUZDx32oKEE1sHdvIpeWlmLSpEncTWRFRUVu0ERlpFUHl6VyePm3yvz8fDx79gx6enpSLy9UNyS8ut6Nh4cHbty4gaysLHz22Wd48OABBg4ciF27dlUZY2lpiT///BNt27bFgwcPsGzZMgQEBEhtp1xGRgYYY9xEzwEDBsjUY6tNbFOJ48vS0hIuLi4V/l+XT9yuTEpKCjIzM7mewZUrV6CmplbpcHeg7NJvbGwsIiIiEBkZicLCQgwbNgzDhg2DUCiU+uE9b9483L9/H56enrx6iEDZ0i4xMTFQUlLC4MGDZZ6E3tBxHyJKUA3MxsYGAQEBaNGiBby9vZGcnIzffvsNjDFYWFhIXReoT58+lVYRYIwhLS0Nd+7cqTTu0qVL+Pzzz9GlSxeEhYUhMDAQPXv2rLbHZmpqKrGQ3LtkuXxiamqK0NBQeHp6wtnZGQUFBVi3bp3U+Snv9wStra0REhIitZ1ykZGRWLRoEfr37w+xWIybN29i9erVMlXM4BvbVOL4mjRpEg4dOlQvxy43YMAADBw4EOPGjcOwYcNqVP3B09MTP/74I1q2bMmr7eDgYGzYsAGDBg2CSCRCfHw8Vq1aVeVyG40V98FqyBEZhDEbGxvuZycnJ3bs2DHueVWjnMolJSVJfVRm586dzMHBgT1+/JglJCQwfX19dvjwYbZixQq2atWqunlRVZg4cSJjjLG9e/eykydPMsaqr05dm+rb9vb2EvNKEhMTJf7e9RHbVOL4WrFiBXNzc2OHDx+ucdV9Wa1bt47Z2tqyCRMmsN9//53FxMRUOnerPowbN469fv2ae56UlFRt1fzGiPtQ0SCJBsbnJnK5Tp061bi94OBgiR6bqakpxo8fz/XYZJGRkYGVK1fi2rVrEIlEEAqFWL58ebV10tq3b48dO3Zg6NCh3Byv4uJiqTFv376V6EG9/1zaPYzS0lKJBfG6dOkCsVgstb3axjaVOL4KCgqgoaFRYSE+WRe7lMUvv/wCoGx+VWRkJA4ePAh3d3f06NEDRkZGmDx5cp219T51dXWJNZg6deok05pZDR33oaIE1cBmzZoFOzs7lJaWwsnJCTo6OhI3kesan2G/71u6dCkGDBiAVatWQSwWIyAgAIsXL6528bbVq1fjypUr6NevH8aOHYuTJ09i+fLlUmOEQqFEmaP3n0v7YOzYsSP27t3LDcIIDAyUOanzjW0qcXwZGxtj1KhRNV5wkg8dHR1YWVmha9euiIuLQ3BwMG7fvl2vCapv375wcXGBo6MjFBUVcebMGejo6HBfiqp6vzV03IeK7kE1gpreRK4NBwcH7N27F/n5+Rg9ejQuXrwIHR0dvHz5ErNnz5bp/o6trS2Cg4Mltslyb+ibb76ROiCCr/Lh7+978+YNPD09ERUVBcYYhEIhFi9eLNNy5Xxjm0ocX4sWLcL169cxYsQI2NvbcxXR69KFCxcQFxeH2NhYJCUlQV9fH0KhEEKhkNeK0zVR1RSKclVNpWjouA9W411dJA3hzJkzzMTEhA0fPpwtW7aMMcbYqVOn2OjRo2W+l2Bra8uSk5O55y9fvpTp3tDkyZMl4uoKrTzasPLz81lQUBCbOXMms7e3Zzt37mTp6el1dvwZM2awHTt2sNu3bzfYvadyp0+flrnqRGPGfajoEl8zZ2ZmhgEDBkj02NTV1bFq1Squx1a+REJVvv/+e0ycOBH6+vpgjOH27dvw9PSstu3MzEyYmpqibdu2UFVVlXnyZHVYJZ3+o0eP4uDBg3j69ClUVVXx+eefY+rUqTA3N6/2eHxjm0pcbbVo0QKdOnXCxx9/jOfPn+Phw4f46quvMHHiRHz55Ze1Pv7u3bvr4Cz5CQ8Ph5eXV417iA0d96GiS3xEpjlUGRkZiI+Ph1gshr6+vkxzb16+fFnp9treM3n/fA8ePIhDhw7hu+++Q48ePQCUFbTdsWMHJk+ejEmTJlV5LL6xTSWutjZu3IiTJ0+ic+fOcHBwgJmZGVRVVZGbm4tRo0ZVuSxKU1JQUIBz587h5MmTePPmDSwtLWFnZ1fte7yh4z5Ijdp/I3KhvHDl+94dVlzZQxYnTpxgv/32G8vPz6+z4cnvX+KzsrJiGRkZFfZLSUmp9nIg39imEldbmzZtkhjW/q7bt2/XW7sNLTo6mi1ZsoSNGTOGLVy4kFlZWbH9+/fLXdyHhi7xkSpH9L377bi87NG7qhtxxGdpej4UFBTQunXrCttlGTjAN7apxNXW3LlzcejQIURFRaG0tBQGBgaYNm0aFBQUmvTlqfIVqd/tITo6OmLx4sUSPcT3L2E2dNyHjhIUqdK7I4rs7OxqPMKoJkvT10S3bt0kntemGjTf2KYSV1teXl54/vw5HB0dwRjDsWPHkJSUJLUkV1Pw559/wt7eHgoKCti7d6/E3DKgrAr8H3/80ehxHzpKUEQmNZk3Va78Q7U8VtrS9OVkGYb7/hLgaWlp2LJlS6X7p6WlST0e39imEldb//zzD4KCgrj/byNHjpR5mZam4Pvvv6/yd9J6iA0d96GiBEUqHRVXF8zMzDB//nxkZWVh7969OHHiBKysrKTGSCtCWhVpAwSqGzzAN7ap/K62RCIRSktLuYm6IpFIoqp5U/X48WOJtcrKsWpGmjZ03IeOEtQHYsWKFVUOa313zaZ3RUdHcz/n5+cjJiZGIpkNGTJEapuzZs1CREQEOnbsiNevX2Pu3LnVFjV9dwmPpKQk/PvvvzAyMsKrV68qXBYp5+bmBqBsWPv792mqW9Keb2xTiasta2trODs7w9LSEgBw6tQp7uemrGvXrvD395f7uA8dJagPRL9+/eDj44OMjAzY2trC1taWm/tU1eqqmzdv5n7W0dHhFlgEyi7bVbUm0LuKiopQXFwMJSWlGpXLOX36NLZt24bCwkIcOnQIkyZNws8//yx1YcYZM2Zg9+7daNOmDdLS0uDp6Yl///23wuCOuoxtKnF8zZ49G7169cK1a9fAGMPs2bMxcuTIemmrISkrK/Oa7tDQcR+8RhxBSBpBcnIy8/f3Z6ampmzWrFns/Pnz9dbW2rVr2cSJE9mff/7J9u7dy8aPH8+2bdsmU6ydnR3LycnhhsCnpKQwCwsLqTFnz55ltra2bM+ePczQ0JBt2bKFFRcXy9Qe39imEldTN27ckPpo6lasWNEk4j50lKA+IImJiWzLli3M3NyczZgxgx05coT98MMPbOHChVLjbt++zXbv3s2KiorYjBkzmIGBAbty5Uq17Y0dO5aVlJRwzwsLC6tdUqScg4MDY0xyjpYsyxJERkayAQMGsKioKJnaqYvYphJXE19++WWVj2nTptVbu4S8iy7xfSAmT56M9PR02NraYufOndwKqXZ2djA2NpYau2rVKsydOxehoaFQVVXFsWPHMHfu3GrjtLW1kZ2djTZt2gAASkpKKp3LU5nu3bvjwIEDKC0tRUJCAv766y+uVNP7yhdWLMcYg6urK7dSqbQb0Hxjm0ocX/v375d4/vbtWygqKuKjjz6q03YIkYZKHX0grl27xntJbCcnJwQGBuLHH3/E8OHDYWdnV2Hl28rMmzcPcXFxGDVqFJSUlBAREYE2bdrg008/BSC9cnN+fj62bduGq1evQiwWQygUwtXVtdLlv8tLKr1586bScjHSrv3zjW0qcbX14MED/Pzzz0hJSQFjDJ999hk2bNiATz75pF7aI+RdlKCauboo7z9t2jSYmJhg9+7dOHXqFIKDgxEaGip16XYA1db3e3fEXl0wNzfHmTNnGjS2qcTx5eDgIDH68vz589izZw/++uuvBjsH8uGiS3zNnLR5RbJOvvX29saRI0ewefNmtGrVCikpKfDx8ak2zt7eHrm5ucjOzpbYXn55URo9Pb0K56etrY3w8HCpMUFBQejXrx/U1NRq3B6f2KYSxxdjTGJqwJgxY+Dn51cvbRHyPupBfSDi4+Ml5kAVFBTg999/r/O6eO9av349Dh8+DC0tLQD8JyWWlJQgLCwMt27dktojrGyotazt8Y1tKnF8eXl5QV1dHRMmTICioiJOnz6NuLg4/PjjjwDqLzESAlCC+mCMGzcO69atw4ABA3DlyhWsWLECQqEQa9asqTKmsl4M8L9Ek5CQILXNsWPH4vjx41BXV6/1+QOVr+xL6pe0+VVUAYHUN7rE94HYvn075s6diy5duiApKQkbNmyocoJuuQcPHtSqTV1dXRQXF/NKUO8OwGCM4fHjx1BSkv52ffbsGQ4cOID8/HwwxiAWi5GUlFTtvbLaxDaVOL7qs0oFIdVpnBLJpMEkJycjOTkZqqqqWL58Oe7cuQNXV1d07NgRycnJ9dq2ra0txo4di6lTp8LZ2Zl7SJOSkgKgbKmP8seNGzcAAJs2bZIa+8MPP0BTUxMJCQno2bMnkpOT0b17d5nOlW9sU4nj68mTJ1i3bh0WLVok8SCkIVAPqpn78ssvIRAIuBp6Kioq2LBhA4D6v0SzceNGLF68uEb3KWbPno3jx49j7dq12L17N77++muZY0tKSjBv3jyUlpaiV69emDBhAhwdHes1tqnE8eXm5gYLCwvo6urWWxuEVIUSVDPXmJdoPvroo2oXNXzfu7dEQ0JCapSgWrRogeLiYvzf//0f7t27V+0lzLqIbSpxfGlqanKFaglpaJSgPhBZWVnw8vJCYmIiNm/ejPXr12PRokXQ1NSstzZ79erFVZxQVlbmtktLWu9XS6gJW1tbzJ49G97e3pg4cSIiIiLQoUOHeo1tKnF8la8CKxQKJe4BVlfJnpC6QAnqA7FkyRIYGhoiPj4eLVu2hI6ODn766ad6XQKgoKAAGhoaiIuLk9gua69K1nla5QMq1NXVYWJigvDwcNjb26Nly5YSibEuY5tKXG3dvHkTcXFxEv8PZa1kT0htUYL6QCQlJWHixIn4+++/oaKiggULFsDGxqZe2yyvUpGVlcXVjKvOuwu7paSkcD9Lm0Pl7u6Otm3bYujQoTX+sOYb21TiauvevXs4d+5cg7VHyLsoQX0gFBUVkZOTw/VKnj17Vu3y67X14MEDzJ8/H4WFhQgICMCXX36JTZs2oXfv3lXGhIaG1rid48eP4/Tp0/jnn3+gp6cHCwsLDBs2TKbXxze2qcTVVvfu3fHgwYMqC/USUp9oou4HIiIiAj4+Pnj16hUGDRqEW7duYc2aNfW6+NzUqVOxcuVK/PjjjwgKCsI///yDjRs3IjAwsN7avHPnDk6fPo3r16+jT58+sLS0hIGBQb3GNpU4Puzs7PDw4UNoa2tDWVmZlignDYoS1AckIyMD8fHxEIlE0NfXR7t27eq1PQcHBxw7dkyi8rmNjQ1OnDhRr+0CQExMDLy9vfHw4UPcvHmzQWKbSlxNlFdRfx+tDksaAl3i+0AUFxfj8OHDePLkCZYsWYJ9+/Zh1qxZNVqGXVbHjx+Hvb09tLS08ODBA+6y4okTJ2S+F1VTjDFER0fj7NmzCA8PR8+ePbkq7PUV21TiaqNTp04ICQnBv//+i9mzZyM0NLTGUwcI4Yt6UB8IDw8PtGnTBhcvXsSRI0ewbNkyiMVieHt713lb9vb2OH78OJ4/fw53d3fcuXMHqqqq+L//+z94eXnhs88+q9P2li1bhoiICPTq1Qvm5uYwNTVFixYt6jW2qcTVlre3N16/fo179+7hyJEjmDNnDnr37l2vRYYJKUcJ6gNRnjTKL7cxxmBtbY2TJ0/WW1vl8vPzIRaLK11ssC7o6elBS0sLLVu2BFBxeLq0+yV8Y5tKXG3Z2dlxPeKgoCCUlpbCxsYGp0+frpf2CHkXXeL7QAgEAhQXF3MfbJmZmTLPM6qpd4eKV6auP0xrczy+sU0lrrbKRwmWv1eKi4vrfeQgIeUoQTVzycnJ6NixI5ydnTFjxgykpaVh9erVCAsLg6ura7202bVr13qdAPy+2tyw5xvbVOJqy8zMDPPnz0dWVhb27t2LEydOwMrKqlHOhXx46BJfMzd8+HC0bNkSRkZG0NbWhoaGBhhjGDJkSL3NbXl31B5p+iIiInD16lWIxWIIhcJ6HZRByLuoB9XMRUREIDExETExMYiOjsatW7fQpk0bZGdno6ioCPr6+nXe5sCBA+v8mKTxdOjQAaNGjeJqI0ZHR1MtPtIgqAf1gcnOzsaFCxewe/duPH36FHfv3m3sUyJybMWKFbh06RK6dOnCbaNafKShUIJq5kpLSxEbG4uIiAhERkaisLAQw4YNw7BhwyAUCuttZB1pHsaOHYsTJ05ATU2tsU+FfIDoEl8zN2TIEAwcOBDjxo3Dli1b0Llz58Y+JdKEdOnSpcbLnhBSVyhBNXOTJk3CtWvXcPToUbx+/RqGhoYYMGAADRUmMmnVqhUsLS0xYMAAiaoj5ZXqCalPdInvA5GamorIyEhERkbizp076NGjB4yMjDB58uTGPjUix94fjVn+cWFvb98IZ0M+NJSgPiDFxcW4c+cO4uLiEBwcjLdv3yIyMrKxT4vIIT09PQgEAi4hCQQCtGrVCsOGDcPSpUuhpaXVuCdIPgiUoJq5CxcuIC4uDrGxsUhKSoK+vj6EQiGEQiG6d+/e2KdHmpA3b94gICAA//77L3777bfGPh3yAaAE1cx9/fXXXELq06cP3XsitWZpaYlTp0419mmQDwANkmjmdu/e3dinQJqZhlxynnzY6Os0IURm586do/tPpMFQD4oQUoGpqWmFave5ubno2rUrvLy8GumsyIeG7kERQip4f6l3BQUFaGpqQl1dvZHOiHyIKEERQgiRS3QPihBCiFyiBEUIIUQuUYIihBAilyhBEUIIkUuUoAghhMil/wfvEtUnbIQmLwAAAABJRU5ErkJggg==",
- "text/plain": [
- "<Figure size 432x288 with 2 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "sns.heatmap(small_dataset.corr(),cmap=\"PiYG\") "
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 69,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "image/png": 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",
- "text/plain": [
- "<Figure size 576x864 with 2 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "plt.figure(figsize=(8, 12))\n",
- "heatmap = sns.heatmap(small_dataset.corr()[['Weekly_Sales']].sort_values(by='Weekly_Sales', ascending=False), vmin=-1, vmax=1, annot=True, cmap='PiYG')\n",
- "heatmap.set_title('which features influence Weekly Sales the most ?', fontdict={'fontsize':18}, pad=16);"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 70,
- "metadata": {},
- "outputs": [],
- "source": [
- "# We take out the following data:\n",
- "# Fuel_Price has only a weak correlation to Weekly_Sales but a high correlation to Year \n",
- "# Unemployment, CPI and Temperature show hardly any correlation\n",
- "# MarkDown1,2 and 5 and IsHoliday were taken out afterwards, since these have no influence in the model\n",
- "clean_smalldata = small_dataset.drop(['Fuel_Price', 'Unemployment', 'CPI', 'Temperature', 'Holiday', 'MarkDown1', 'MarkDown2', 'MarkDown5', 'IsHoliday'], axis = 1) #"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 71,
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "<class 'pandas.core.frame.DataFrame'>\n",
- "Int64Index: 150929 entries, 92 to 421569\n",
- "Data columns (total 12 columns):\n",
- " # Column Non-Null Count Dtype \n",
- "--- ------ -------------- ----- \n",
- " 0 Store 150929 non-null int64 \n",
- " 1 Dept 150929 non-null int64 \n",
- " 2 Date 150929 non-null datetime64[ns]\n",
- " 3 Weekly_Sales 150929 non-null float64 \n",
- " 4 MarkDown3 150929 non-null float64 \n",
- " 5 MarkDown4 150929 non-null float64 \n",
- " 6 Size 150929 non-null int64 \n",
- " 7 Week 150929 non-null int64 \n",
- " 8 Year 150929 non-null int64 \n",
- " 9 Type_A 150929 non-null uint8 \n",
- " 10 Type_B 150929 non-null uint8 \n",
- " 11 Type_C 150929 non-null uint8 \n",
- "dtypes: datetime64[ns](1), float64(3), int64(5), uint8(3)\n",
- "memory usage: 11.9 MB\n"
- ]
- }
- ],
- "source": [
- "clean_smalldata.info() "
- ]
- },
- {
- "attachments": {},
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## 3.6. normale (gro\u00dfe) Daten"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 72,
- "metadata": {},
- "outputs": [],
- "source": [
- "# we take out the following data:\n",
- "# MarkDown1-MarkDown5, since many data are missing, there is hardly any correlation. \n",
- "# Fuel_Price has only a weak correlation to Weekly_Sales but a high correlation to Year \n",
- "# Unemployment, CPI and Temperature show hardly correlation\n",
- "# Holiday - interferes later in modeling\n",
- "clean_data2 = clean_data1.drop(['MarkDown1', 'MarkDown2', 'MarkDown3', 'MarkDown4', 'MarkDown5', 'Fuel_Price', 'Unemployment', 'CPI', 'Temperature', 'Holiday'], axis = 1) #"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 73,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "Store 0\n",
- "Dept 0\n",
- "Date 0\n",
- "Weekly_Sales 0\n",
- "IsHoliday 0\n",
- "Size 0\n",
- "Week 0\n",
- "Year 0\n",
- "Type_A 0\n",
- "Type_B 0\n",
- "Type_C 0\n",
- "dtype: int64"
- ]
- },
- "execution_count": 73,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "clean_data2.isnull().sum() "
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 74,
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "<class 'pandas.core.frame.DataFrame'>\n",
- "Int64Index: 420212 entries, 0 to 421569\n",
- "Data columns (total 11 columns):\n",
- " # Column Non-Null Count Dtype \n",
- "--- ------ -------------- ----- \n",
- " 0 Store 420212 non-null int64 \n",
- " 1 Dept 420212 non-null int64 \n",
- " 2 Date 420212 non-null datetime64[ns]\n",
- " 3 Weekly_Sales 420212 non-null float64 \n",
- " 4 IsHoliday 420212 non-null int64 \n",
- " 5 Size 420212 non-null int64 \n",
- " 6 Week 420212 non-null int64 \n",
- " 7 Year 420212 non-null int64 \n",
- " 8 Type_A 420212 non-null uint8 \n",
- " 9 Type_B 420212 non-null uint8 \n",
- " 10 Type_C 420212 non-null uint8 \n",
- "dtypes: datetime64[ns](1), float64(1), int64(6), uint8(3)\n",
- "memory usage: 50.1 MB\n"
- ]
- }
- ],
- "source": [
- "clean_data2.info()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 75,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "<AxesSubplot:>"
- ]
- },
- "execution_count": 75,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": 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FhQWOHDmCU6dOYc+ePejWrVur7+Gto+y4XC4sLCyQlZWFlJQUTJs2DaampqipqcHz589x8+ZNDBgwAH/99RcmT54MABAKhfjkk09w+/ZtFBYWwtvbG0DDw7HOnTtL6l6wYAEGDx6MESNGSMXkcDjg8/k4fvw4PDw88PTpU1hYWLz1JlavXo25c+ciJSUFKSkpmDx5MiIiIjBx4kRs374dSUlJyMnJwbVr1xoNeUxNTUVmZqYk6dXU1KBXr17w9PTEhg0bUFRUhHHjxmHevHky/koJIUTx3ompg3g8Hm7cuIHMzEyEh4cDaOjKu3jxIgwMDMAwDBwcHBAYGAgAqKqqgkgkwrVr1zBs2DDs2rULAFBbW4uqqr9nBV62bBm2b9+Oy5cvY9y4cVIx+Xw+Zs2aBS0tLbi5ub31+i5fvozq6mo4OjrC09MTnp6eiI2NxZEjR2BtbQ0vLy+4urpi5MiR6N+/f6M3jUUiEXx8fDBjxgwADcMhuVwuOnXqhDNnziA5ORmXLl3Cjz/+iNOnT6vF9ByEEPXDbWHLRxU1++06evRoJCQkoF+/ftDUbMhf1tbW2Lt3L6ytrWFpaYnz58/j6dOnYBgGq1atQnR0NCwsLHDr1i3k5OQAAHbs2IGwsDBJvebm5li1ahWCgoJQXV0tFdPY2Bg9e/bE4cOHm01IOjo6iIyMlIzaYxgG2dnZGDBgAB49egQOhwM/Pz/JdYpEIqnP83g8JCQkoKqqCvX19Zg3bx7Onj2Ln3/+GVu3boWDgwNWrlyJsrIyVFZWyvArJYQQxWvJKDtV1WwLqV+/fnj27BmmTp0qKePxeFi4cCGsrKxgZmYGgUAAHx8fiMViDBgwALNnz4a2tjbWrl2LhQsXQiwWo0ePHpIW1isjR46EpaUlNm3aBDMzM6ljjo6OOHfuHHr06PHW6+PxeBAIBPDz84NQKAQAjBkzBvPmzQOXy8WAAQPg4OAADocDGxsbqVGDQMMQ9Pv372Py5MkQiUQYM2YM+Hw+qqqq8PXXX8PFxQVcLhdLlixpNAKFEEJURUumBFJVHIZhGGVfxD/V19fj22+/hb29PSZOnKjsy2kV4d1ixcRR4HpItEBf26njAn0vutICfW2lO6Z3m+uI/X2JzOdO7h/e/ElKoHJTBzEMgzFjxsDKygoTJkwA0DCab82aNU2eHxUV1WwrihBC1F1LZ/FWRSqXkDgcDlJTU6XKRowYgYSEBCVdESGEqL53YpQdIYQQ1dfS94tUESUkQghRA6o8ek5WlJDkRMNARyFxtMsU9/BakQMNBi3vr7BYd1ffV1gsYVfZp21piw751c2fxJL3yvUUFgtdFReK27Wj4oKxoIMajLKjhEQIIWqAWkiEEEJUAg1qIIQQohIoIRFCCFEJHEpIhBBCVAG1kAghhKgETU77H2XX/odlEEIIgQaHK/PWEidOnICjoyMmTpzYaPme112+fBnjx49v2z206dMs6d//7e+cTJ8+HWlpaVJlAQEBiIuLe+vnxo8fj/z8fFy8eBGbN29udDwtLQ3Tp09v+QUTQoiK4XC4Mm+yKioqwsaNG3Hw4EHEx8cjJiYGf/75Z6PzSktLsX79+jbfg0okJHmzs7PDggULlH0ZhBAiNxrgyrzJ6urVq+DxeOjSpQt0dXUxadIkJCYmNjovMDAQAoGAhXtQIU+ePMGXX34JDw8PeHl54datWzJ97tKlS3Bzc4OLiwvmzp2L0lLp5QTi4uIQEBAAAEhJSYGTkxM8PDwQGxsrOefatWuYMmUK+Hw+7OzscOHCBVRWVsLS0lKyMF9+fj4cHR3ZuVlCCGFRSxboq6ioQH5+fqOtoqJCqs7i4mIYGhpK9o2MjFBUVCR1zv79+/HJJ5/AwsKizfegUoMajhw5gnHjxmHWrFm4cuUKrl+/jiFDhgBoyMC6un+v/VNYWIhRo0bh6dOnWLFiBQ4dOgQTExPs3r0bQUFB2LJlS6P66+rqEBAQgOjoaPTp0wfLli2THPv5558RHByMPn36IDU1FWvXrsWECRMwbtw4JCYmwsvLC/Hx8XB3d5f3r4EQQlpMU0P2QQ3R0dHYtm1bo3KBQID58+dL9sViMTgcjmSfYRip/T/++APnzp3Dvn378OTJk1Ze+d9UKiGNHj0a8+fPR3Z2NsaOHYsvv/xSciw4OBiWlpaS/VctnszMTJibm8PExAQA8PnnnyMqKqrJ+n///XcYGRmhT58+AAA+ny95thQeHo5Lly4hMTERt2/fRlVVw6Jjnp6e2Lp1K7y8vHDy5ElER0ezf+OEENJGLXk25OPjAz6f36j8n6ti9+zZExkZGZL9kpISGBkZSfYTExNRUlICT09PCIVCFBcXY+rUqTh48GAr7kDFuuyGDx+OU6dOwcbGBqdPn4afn1+znxGLpScXZRgG9fX1TZ7L4XDw+gK5XO7f/4BTp05FZmYmBg0aJBV35MiRKC4uxrlz52BiYkKLARJCVFJLniHp6+vDxMSk0fbPhGRlZYXU1FSUlZXh5cuXOHfuHGxtbSXH/f39cfbsWSQkJCAqKgpGRkatTkYN96BCwsLCcPz4cfD5fKxYsQL37t1r9jMWFha4ffs28vPzAQAxMTFSLanX9e/fH6Wlpbh/v2F251OnTgEAnj17hkePHmHBggWwtbXFxYsXIRKJADQkMXd3dwQHB8PDw4ON2ySEENbJY9h3jx49sGjRInh7e8Pd3R3Ozs4wNzeHr68vsrKyWL8Hleqymz59Or755hvExcWBy+XKNIywe/fuCAoKgkAggFAoRK9evRASEtLkuR06dMCGDRuwZMkSaGpq4pNPPgEAdOnSBV5eXnBycoKmpiZ4PB5qampQXV0NXV1dODk54ccff5QsqU4IIapGXjM1uLi4wMXFRarsv//9b6PzTExMkJSU1KZYHOb1PizSiFgsxqFDh5CTk4PAwECZPycqqGj+pHaG0eA0fxJL1Hc9JMW8Ta/I9ZCgq1J/17ZL3F76zZ/UjN+fnZP53P5dJrY5njzQ/0nNEAgEKCwsxJ49e5R9KYQQ8kZcNZg6iBJSM3bs2KHsSyCEkGbRAn2EEEJUAs32TQghRCVQQiKEEKISOC2Yo05VUUKSk5f3nyokTkezbgqJAwDPO5c2fxJLFDnybeBKM4XFUth9KXDkm8NP5gqLtU9nn8JixSzaqrBYi8RH21xHS6YOUlWUkAghRA1wVGueg1ahhEQIIWpBce8JygslJEIIUQPUQiKEEKISONRCIoQQohqohUQIIUQF0HtIhBBCVET777Jr/208GSQmJsLDwwOurq5wcXHB7t27AQC+vr6N1ocnhJD2iAMNmTdVpfYtpKKiIqxfvx5xcXEwMDBAVVUVpk+fjg8//LDJNT0IIaQ9okEN7UB5eTmEQiFqamoAAJ06dcK6deugra2N8ePHY//+/Th8+DCSk5MBAC9evEB5eTlu3ryJzMxMhIaGoqamBgYGBli9ejVMTU2VeTuEEPIGqtvykVX7v4NmmJmZwc7ODhMmTICXlxfCw8MhFovRu3dvyTmLFy9GQkICfvnlFxgaGiIkJAR1dXUIDAxEZGQkjh07hhkzZmD58uVKvBNCCHkzTgv+a4kTJ07A0dEREydOxIEDBxodv3DhAtzc3ODq6oq5c+fi+fPnrb4HtW8hAcDq1asxd+5cpKSkICUlBZMnT0ZERESj8wIDAzFy5Eg4Ojrijz/+QF5eHubMmSM5XllZqcjLJoQQmcljctWioiJs3LgRcXFx0NLSwhdffAFLS0v07dsXQMN34qpVq3D06FH06NEDmzdvxtatW1u0uvbr1D4hXb58GdXV1XB0dISnpyc8PT0RGxuLI0eOSJ23Z88ePH36FOvWrQPQsHS5iYkJEhISAAAikQilpYqbXJQQQlqiJYMVKioqUFFR0ahcX18f+vp/L6d+9epV8Hg8dOnSBQAwadIkJCYmQiAQAACEQiFWrlyJHj16AAD69++PEydOtPoe1L7LTkdHB5GRkcjPzwcAMAyD7OxsDBgwQHLOlStX8Msvv2DDhg3Q0Gj4lXz00Ud4/vw5MjIyAABHjx7F4sWLFX8DhBAig5Z02UVHR8POzq7RFh0dLVVncXExDA0NJftGRkZSI5MNDAzw73//GwBQU1ODqKgoTJgwodX3oPYtJB6PB4FAAD8/PwiFQgDAmDFjMG/ePEkmDwkJQX19Pf7zn/9ALBYDALZu3YrNmzcjJCQEtbW10NPTw/r165V2H4QQ8nayty98fHzA5/Mblb/eOgIaeoo4nL+fOTEMI7X/yosXLzBv3jyYmZk1Wa+s1D4hAQCfz2/yl5SUlAQAOHv2bJOf++CDDxp17RFCiCpqSZfde//omnuTnj17SnqJAKCkpARGRkZS5xQXF2PmzJng8Xj4/vvvZb/gJqh9lx0hhLwLOByuzJusrKyskJqairKyMrx8+RLnzp2Dra2t5LhIJIKfnx8cHBywbNmyJltPLfFOtJAIIUTdyePF2B49emDRokXw9vaGUCiEl5cXzM3N4evrC39/fzx58gT37t2DSCSS9DQNGjQIISEhrYpHCYkQQtSAvKYEcnFxgYuLi1TZq1luBg8ejPv377MWixISIYSoBZo6iBBCiApQ5UlTZcVhGIZR9kWoI1FB45fO2jtGU3F/gdXrd1BYrA5ldQqLNXClmULiZEz5fwqJAwAdzbopLJa64vZqfsRbc2pqXsp8ro5OxzbHkwdqIRFCiDpgqMuOEEKICuCoQWcXJSRCCFEH7T8fUUIihBC1QAmJEEKISqAuO0IIIaqA0/7zESUkQghRC+L2n5Ha/5tUAGbMmIELFy5I9tevX4+hQ4eiru7v90tsbGwkayLJavz48S3+DCGEKAXTgk1FqUVC4vF4uH79umT/6tWrGDJkiKTsr7/+gq6uLkxMTJR1iYQQQpqhFglp9OjRuHnzJoCGNeC1tLQwadIkpKSkAAAyMjJgbW2N+Ph48Pl8uLm54fvvv0dtbS2AhhVjvby84O7uDoFAgPLycqn6c3JyMHHiRNy6dUuh90UIIbLiMIzMm6pSi4Q0cOBA5Obmora2FikpKbC2toa1tbVUQjIyMkJsbCwOHz6MhIQEdOvWDXv27EFZWRkiIyOxZ88exMfHw8bGBhEREZK6nzx5AoFAgLVr12LIkCFKukNCCGmGGnTZqcWgBi6XCwsLC2RlZSElJQXTpk2Dqakpampq8Pz5c9y8eRMDBgzAX3/9hcmTJwMAhEIhPvnkE9y+fRuFhYXw9vYG0LBkb+fOnSV1L1iwAIMHD8aIESOUcm+EECITNRjUoBYJCWh4jnTjxg1kZmYiPDwcQENX3sWLF2FgYACGYeDg4IDAwEAAQFVVFUQiEa5du4Zhw4Zh165dAIDa2lpUVVVJ6l22bBm2b9+Oy5cvY9y4cQq/L0IIkYU6DPtWiy47oCH5JCQkoF+/ftDUbMiz1tbW2Lt3L6ytrWFpaYnz58/j6dOnYBgGq1atQnR0NCwsLHDr1i3k5OQAAHbs2IGwsDBJvebm5li1ahWCgoJQXV2tlHsjhJBmyanL7sSJE3B0dMTEiRNx4MCBRsezs7Ph4eGBSZMmYdmyZaivr2/1LahNQurXrx+ePXsGGxsbSRmPx8PDhw9hZWUFMzMzCAQC+Pj4wMnJCWKxGLNnz4ahoSHWrl2LhQsXwsXFBXfv3sV3330nVffIkSNhaWmJTZs2KfiuCCFERnJISEVFRdi4cSMOHjyI+Ph4xMTE4M8//5Q6Z8mSJVixYgXOnj0LhmEQGxvb6lug9ZDkhNZDahtaD6ltaD2k9oWN9ZDqC2X/zqnuBFRUND5fX18f+vp/X8uxY8eQnp6OtWvXAgC2b98OhmEgEAgAAI8fP4aPj4/kPdCMjAxs2bIF+/fvb9U9qM0zJEIIeZe15BlSdHQ0tm3b1qhcIBBg/vz5kv3i4mIYGhpK9o2MjJCZmfnG44aGhigqKmrhlf+NEhIhhKiDFnR2+fj4gM/nNyp/vXUENIw65nD+7hlhGEZqv7njLUUJiRBC1EELWkj/7Jp7k549eyIjI0OyX1JSAiMjI6njJSUlkv3S0lKp4y2lNoMaCCHkXcZhZN9kZWVlhdTUVJSVleHly5c4d+4cbG1tJceNjY2hra0tmaYtISFB6njL74EGNciFOg5qUOh6Ky9Fioulq7iOgpf3nyokzohD1gqJAwB3V99XWCxFYhQ3hgea77d9UIM495nM52p80EXmc0+cOIEffvgBQqEQXl5e8PX1ha+vL/z9/TF48GDcv38fgYGBqKysxMCBAxEaGgotLa2W3wAoIckNJaQ2ooTUJpSQ2q7dJaS/nsl8rkbvLm2OJw/0DIkQQtQBTR1ECCFEFTAiSkiEEEJUAEMtJEIIISpBDYYDUEIihBA1QC0kQgghqoESEiGEEFWgDoMa1HamhqCgIPj7+0uVpaSkwM7ODpWVlUq6KkIIkQ+GYWTeVJXaJqRvvvkGd+7cwcWLFwEA1dXVWLVqFdauXQs9PT0lXx0hhLBMzMi+qSi1TUidOnVCcHAw1qxZg+rqamzZsgXjx49Hx44dMWXKFPD5fHz11VfIy8sDAFy7dk1SbmdnJ1nfIyAgAH5+fnBwcEBSUpIyb4kQQt6IETMyb6pKrZ8hWVlZwcbGBkuXLsXDhw9x8OBBTJs2Dbt27UKvXr2QnJyM5cuXY9++ffj5558RHByMPn36IDU1FWvXrsWECRMAAF26dMGuXbuUfDeEEPIWKtwVJyu1TkhAQwtn3Lhx2L59OwoLC5GXl4c5c+ZIjr96nhQeHo5Lly4hMTERt2/fRlVVleQcc3NzhV83IYS0hCq3fGSl9glJT08P+vr6MDY2RmVlJUxMTJCQkAAAEIlEKC0tBQBMnToVlpaWsLS0xOjRo7F48WJJHTo6Okq5dkIIkRWNsmtnPvroIzx//lyy4NTRo0exePFiPHv2DI8ePcKCBQtga2uLixcvQiRS4GzThBDSVmowqEHtW0iv09LSwubNmxESEoLa2lro6elh/fr16NKlC7y8vODk5ARNTU3weDzU1NSgurpa2ZdMCCGyUeFEIytaD0lOaD2kNqL1kNqE1kNqu/a2HlLVlUcyn9vJ9l9tjicP71SXHSGEqC1xC7Y2KigowLRp02Bvb485c+ZIDQJ7pbi4GDNnzoSbmxv4fD5SU1ObrZcSEiGEqAFGJJZ5a6vVq1dj6tSpSExMxKBBg7Bjx45G54SFhWH8+PFISEhAZGQkFi9e3OyzeUpIhBCiBlryYmxFRQXy8/MbbRUVzT9qEAqFSE9Px6RJkwAAHh4eSExMbHTev//9bzg7OwMAevfujdra2mafy79TgxoIIURttWBQQ3R0NLZt29aoXCAQYP78+W/9bHl5OfT09KCp2ZA+DA0NUVRU1Oi8VwkLAPbs2YMBAwbgvffee2vdlJDkRFT2UiFxNLp1VEgcAKg0aNxPLC/vlStuvkGHnxT34vOZ6ZkKiaPIgQYDV5opLNbX+z9VWCwbvp3CYn1y+Ks219GS8Wk+Pj7g8/mNyvX1pQdXnDlzBqGhoVJlvXv3BocjPeLjn/uv27dvH2JiYvDzzz83e12UkAghRB20oIWkr6/fKPk0xcHBAQ4ODlJlQqEQlpaWEIlE4HK5KCkpgZGRUZOfDwsLw6+//ooDBw6gZ8+ezcajZ0iEEKIGFDWooUOHDhgxYgROnz4NAIiPj4etrW2j8/bt24e0tDQcOnRIpmQEUAuJEELUgliouHf3Vq5ciYCAAOzcuRPvv/8+NmzYAAA4dOgQiouL4e/vj+3bt0NPTw/Tp0+XfC4qKgo9evR4Y72UkAghRB2IWXjBSEbGxsb46aefGpVPmTJF8nN6enqL66WERAghakAdJlelhEQIIWqAUWALSV4oIRFCiBpgYwYGZVP5hLR69WrcuHEDQqEQubm56NOnDwDA29sbnp6eco39xx9/wMXFBVu2bJF6yYsQQlQOtZDkb+XKlQCA/Px8eHt7SxbXU4SjR4/C3t4eMTExlJAIISpNkaPs5EXlE1JTNm3aBIZhsGjRIgANy5Tb2triypUr0NbWRlZWFqqqqjBnzhy4u7ujqqoKQUFBePDgAUQiEXx9fSVzLL2JUCjEiRMncODAAXzxxRfIzc3FBx98oIjbI4SQFlOHZ0jt8sVYT09PnDhxAgzD4OXLl/jtt99gZ9cwzUdeXh5iYmIQHR2NsLAwlJSUYOfOnRg4cCDi4uJw4MAB7Nq1C3l5eW+N8euvv6JXr1748MMPMWHCBMTExCji1gghpHVEYtk3FdUuW0impqYwNjZGeno6CgoKMHbsWGhrawNomHm2Q4cO6NmzJ4YNG4br16/j6tWrqKmpwdGjRwEA1dXVePDgAUxNTd8Y4+jRo5JWlKOjIxYvXowFCxZAS0tL/jdICCEtxKjBirHtMiEBDa2kkydPoqCgQGp2Wi6XK/lZLBZDU1MTYrEY4eHhGDhwIACgtLQUnTt3fmPdT58+RXJyMu7evYv9+/eDYRqmaz9//jycnJzkd1OEENJK6jDKrl122QGAvb09UlNTUVpaCgsLC0n5mTNnwDAMHj9+jMzMTAwfPhw8Hg+HDh0C0LCKoaurKwoLC99Yd0JCAng8Hq5cuYKkpCRcunQJfn5+OHz4sNzvixBCWoMRimTeVFW7bSHp6OhgyJAh6Nevn1R5TU0NPD09UVdXh6CgIBgYGEAgEGDVqlVwdnaGSCTCkiVL3jpA4dixY5IBE69MmzYNu3fvxv/+9z/J0HNCCFEV6jCood0kJBMTEyQlJQFoWPejqqoK9+7dw7fffit1nr29PTw8PKTK9PT0EBERIXOsEydONCrr2rUrbt++3YorJ4QQ+VOHLrt2k5Bel5WVhVmzZmHevHkwNDRsVR0ZGRlYs2ZNk8eam5GWEEJUDbWQlMTc3BzXrl1rVL5u3TqZ6xgxYoRCX7IlhBC5oslVCSGEqAJqIRFCCFEJYmG9si+hzdrtsG9CCCGvETGyb21UUFCAadOmwd7eHnPmzEFVVdUbz62srMSECROQlpbWbL3UQpITRqiY5rNGveL6jXX/x23+JLZ0VVyofTr7FBdMDX29/1OFxdrgfUlhsZz6f6WwWGxQZJfd6tWrMXXqVDg5OWH79u3YsWMHlixZ0uS5a9asQUVFhUz1UguJEELUAFMvlnmrqKhAfn5+o02WxCEUCpGeni5ZAcHDwwOJiYlNnnv69Gl06tQJ/fv3l+keqIVECCFqoCXvIUVHR2Pbtm2NygUCgdRUbE0pLy+Hnp4eNDUb0oehoSGKiooanVdQUIDo6GhER0fD19dXpuuihEQIIWqAqZc9Ifn4+IDP5zcq19fXl9o/c+YMQkNDpcp69+4NDocjVfbPfbFYjGXLlmH58uXQ0dGR+booIRFCiBoQ18o+yk5fX79R8mmKg4MDHBwcpMqEQiEsLS0hEonA5XJRUlICIyMjqXMePnyIhw8fYtmyZQCA3NxcBAYGYs2aNeDxeG+MRwmJEELUQEtaSG3RoUMHjBgxAqdPn4aLiwvi4+Nha2srdU7fvn3x66+/SvanT58OgUAAS0vLt9ZNgxoIIUQNMCJG5q2tVq5cidjYWDg6OiIjIwMLFy4EABw6dAibN29udb3UQiKEEDWgqBYSABgbG+Onn35qVD5lypQmz2/q3KaofEJavXo1bty4AaFQiNzcXMnSD97e3vD09JRLzLS0NPj5+eGDDz4AwzAQCoX44osv4OPjI5d4hBDSVjTbtwKsXLkSAJCfnw9vb2+FTYg6aNAgSVavrKyEk5MTrK2t0bdvX4XEJ4SQlhDXtP+pg1Q+ITVl06ZNYBhGsoheQEAAbG1tceXKFWhrayMrKwtVVVWYM2cO3N3dUVVVhaCgIDx48AAikQi+vr5wdnaWOV5tbS24XC7ee+89ed0SIYS0iTq0kNrloAZPT0+cOHECDMPg5cuX+O2332BnZwcAyMvLQ0xMDKKjoxEWFoaSkhLs3LkTAwcORFxcHA4cOIBdu3YhLy/vrTHu3LkDNzc3uLi4YPz48Rg1alSjoY2EEKIqWjJTg6pqly0kU1NTGBsbIz09HQUFBRg7diy0tbUBNExj0aFDB/Ts2RPDhg3D9evXcfXqVdTU1ODo0aMAgOrqajx48ACmpqZvjPHPLrtZs2YhKioK//d//yf/GySEkBZS5UQjq3aZkICGVtLJkydRUFAgNdUFl/v3BKBisRiampoQi8UIDw/HwIEDAQClpaXo3LmzzLH09PTg4OCAq1evsncDhBDCIuqyUyJ7e3ukpqaitLQUFhYWkvIzZ86AYRg8fvwYmZmZGD58OHg8Hg4dOgQAKC4uhqurKwoLC2WOJRKJcO3aNXzyySes3wchhLCBuuyUSEdHB0OGDEG/fv2kymtqauDp6Ym6ujoEBQXBwMAAAoEAq1atgrOzM0QiEZYsWYIPPvjgrfW/eobE4XBQX1+P/v37yzxBICGEKFpLpg5SVe0mIZmYmCApKQkAwDAMqqqqcO/ePXz77bdS59nb28PDw0OqTE9PDxERETLHsrS0xM2bN9t+0YQQoiCq3PKRVbtJSK/LysrCrFmzMG/ePBgaGraqjoyMDKxZs6bJY1FRUejRo0dbLpEQQhSKjSmBlK1dJiRzc3Ncu3atUfm6detkrmPEiBEKe8mWEELkjVpIhBBCVII6jLKjhEQIIWqAWkiEEEJUAo2yI29U0f+FQuIYVOgpJA4A1JfXKCwWt2tHhcWKWbRVYbH8P9urkDgMp/lz2GLDt1NYLKf+Xykslt3v0xUW6z4K2lwHddkRQghRCWKm/SekdjtTAyGEkL+JGUbmra0KCgowbdo02NvbY86cOaiqqmp0Tl1dHYKDg+Hu7g4nJyekpKQ0Wy8lJEIIUQMiRizz1larV6/G1KlTkZiYiEGDBmHHjh2Nztm9ezfKy8tx7NgxbNq0CUuXLgXTTDKkhEQIIWqgXiySeauoqEB+fn6jraKiotk4QqEQ6enpmDRpEoCGFRYSExMbnXfmzBn4+vqCw+Hg448/xt69e5tNSPQMiRBC1EBLniFFR0dj27ZtjcoFAoHU6glNKS8vh56eHjQ1G9KHoaEhioqKGp33119/IT09HUFBQRCJRFi0aFGzK25TQiKEEDXQkoTk4+MDPp/fqFxfX19q/8yZMwgNDZUq6927Nzgc6WGc/9wHGlZJePLkCQ4cOIDff/8ds2bNwpkzZ9668jYlJEIIUQMtGaygr6/fKPk0xcHBAQ4ODlJlQqEQlpaWEIlE4HK5KCkpaXI17e7du8PJyQkcDgdmZmbo2bMncnJyYG5u/sZ4Kp2QVq9ejRs3bkAoFCI3Nxd9+vQBAHh7e8PT01NucSsrKxEZGYn09HRwuVzo6+sjICBAssAfIYSoGkUN++7QoQNGjBiB06dPw8XFBfHx8bC1tW103qefforTp0/jk08+QV5eHgoLC/Hhhx++tW6VTkgrV64EAOTn58Pb21shk6GKxWL4+vrC0tIS8fHx0NTUxG+//QZfX1+cOnUKBgYGcr8GQghpKTZGz8lq5cqVCAgIwM6dO/H+++9jw4YNAIBDhw6huLgYCxYswOLFixEUFAQnJycAQHBw8Fu76wAVT0hN2bRpExiGwaJFiwAAAQEBsLW1xZUrV6CtrY2srCxUVVVhzpw5cHd3R1VVFYKCgvDgwQOIRCL4+vrC2dn5jfWnpaWhsLAQ/v7+0NBoGITI4/EQGhoKsbj9v3hGCFFP9WKRwmIZGxvjp59+alQ+ZcoUyc96enoICwtrUb3tbti3p6cnTpw4AYZh8PLlS/z222+ws2uYuiQvLw8xMTGIjo5GWFgYSkpKsHPnTgwcOBBxcXE4cOAAdu3ahby8vDfWf+/ePZiZmUmS0Stjx45Ft27d5HpvhBDSWmJGLPOmqtpdC8nU1BTGxsZIT09HQUEBxo4dC21tbQAN4+E7dOiAnj17YtiwYbh+/TquXr2KmpoaHD16FABQXV2NBw8ewNTUtMn6NTQ0JPURQkh7wcYMDMrW7hIS0NBKOnnyJAoKCqTGzHO5XMnPYrEYmpqaEIvFCA8PlwxIKC0tRefOnd9Y96BBg3Dw4EEwDCM1lHHDhg2wsrICj8eTwx0RQkjbqHLLR1btrssOAOzt7ZGamorS0lJYWFhIys+cOQOGYfD48WNkZmZi+PDh4PF4OHToEACguLgYrq6uKCwsfGPdI0aMQLdu3bBt2zaIRA19ssnJyYiLi2v2pS5CCFEWRU4dJC/tsoWko6ODIUOGoF+/flLlNTU18PT0RF1dHYKCgmBgYACBQIBVq1bB2dkZIpEIS5YswQcffPDGujkcDnbs2IHQ0FA4OztDU1MTBgYGiIqKQvfu3eV9a4QQ0irq0EJqFwnJxMQESUlJAACGYVBVVYV79+7h22+/lTrP3t4eHh4eUmV6enqIiIhoUbyuXbsiPDy8bRdNCCEKpMhRdvLSLhLS67KysjBr1izMmzcPhoaGraojIyMDa9asafJYVFQUevTo0ZZLJIQQhaMWkhKYm5vj2rVrjcrXrVsncx0jRoxQyEu2hBCiKDTKjhBCiEpQ5cEKsqKERAghaoC67AghhKgEdRjUwGGaW8KPEEIIUYB2+WIsIYQQ9UMJiRBCiEqghEQIIUQlUEIihBCiEighEUIIUQmUkAghhKgESkiEEEJUAiUkQgghKoESEiGEEJVACYkQQohKoIRECCFEJVBCeoc8f/68Udnjx4/lHreyslKu9Ts5OWH37t0oKSmRaxxFyszMlNqvqalp0Zpfsrp8+TLrdbZETk6OUuO31fPnz1FWVibZv3btmtQ+aRlKSEr2+PFjzJgxAxMnTkRxcTG8vb2Rn5/PaozCwkIUFBRg2rRpkp8LCgqQl5eHmTNnshoLAC5duoTw8HBUVVXBwcEBdnZ2iIuLYz3OK1FRUaitrYW3tzdmz56NxMRECIVC1uMo4t/qlSVLluDmzZsAgF9//RWOjo6oqKhgPU54eDjrdTanvr4ep0+fxvTp0+Hh4cF6/f/73/9QXFwMoOH/DT8/P2zduhU1NTWsxrl37x6cnJxw584dSdn/+3//D25ubrh//z6rsd4VNNu3ks2cORMzZsxAZGQk4uLi8MsvvyAhIQEHDhxgLcbSpUuRlpaG4uJiGBkZSco1NTUxbtw4fP/996zFAgBPT0+EhIQgKysLGRkZWLFiBaZPny7XpPTK+fPnERwcjJqaGri6umLu3LkwMDBgpW5F/Fu9kpOTg/nz58PU1BT5+flYuXIlRowYwXocPz8/GBgYwMLCAjo6OpJyd3d31mPl5eUhNjYWR48eRUVFBfz8/DB16lR07dqVtRj79+/Hjz/+CC6Xi1GjRiEnJweOjo64du0aOnbsyGoC9vHxwdy5c2FpaSlVnpycjD179mDfvn2sxXpXUAtJycrLy2FjYwOGYcDhcDB58mTWu7hCQ0ORlJQEf39/JCUlSbZz586xnoxeMTMzw+XLlzF+/Hh06tRJLi2WV6qqqhAXFwcfHx9ERkZiypQpOHLkCP71r3+x2gJUxL/Vq9artrY2Vq1ahaysLMybNw+9evVCQUEBq7EASJL17du3kZaWJtnYdP78ecycOROfffYZnj17hvDwcBgZGUEgELCajAAgJiYGp0+fRmxsLBITE7Fnzx54e3tj8+bNrLdaKioqGiUjABgzZgzKy8tZjfWuoAX6lExHRwdPnjwBh8MBAGRkZEBLS0susT7//HOEhITgt99+g6amJmxtbTFnzhypv4zZ0L17d6xZswZ37txBeHg41q1bh169erEa43V2dnb49NNPIRAIMHLkSEn51KlTcfXqVdbiKOLf6ssvvwSHw8GrjgstLS2EhYUBADgcDi5evMhqvNDQ0EZlbHdtzZ8/Hw4ODoiJiUHv3r0BQPI7ZJumpiZ0dXWhq6sLU1NTdOrUCQDA5XKhqcnu1119fT3EYjE0NKT/rheLxXL9A0ydUUJSsqVLl+L//u//kJubCzc3Nzx//hybN2+WS6xvv/0WH330ESIiIsAwDI4ePYply5YhMjKS1TiRkZG4cOECfHx8JF8MAoGA1Rivu3DhAvT09KTKampqoKOjg+3bt7MWJyAgQO7/VklJSazWJ0u8TZs2obq6GgzDQCwWo6amBqmpqazFOH78OOLi4jB16lQYGxvDyckJIpF8Vjd9PTlwuVy5xHhl5MiR2LZtG/z9/aXKd+zYgUGDBsk1trqiZ0hKdvnyZVhbW+PRo0cQiUT46KOP5NZCcnZ2xsmTJ5stY8Px48fxv//9D35+fjh79qxcnkm80tSX6suXL/Hbb7+xHksoFEr9WxUVFcHU1JT1OM+fP0d4eDhyc3OxZcsWrF+/HkuXLoW+vj6rcf79739jzZo12Lt3L/z8/HDhwgW8fPkSK1asYDUO0NCiuHz5MuLi4nDlyhVYWVlh2rRpGDt2LGsxhg4disGDBwMAsrKyJD8zDIO7d+/ixo0brMWqrKzE7Nmz8eTJE5iZmUFbWxv37t1D165dsXPnTnTp0oW1WO8KaiEpWXh4OMaNG4ePP/5Y7rH69u2LjIwMycPx+/fvS7pQ2BQREYEnT57g7t278PX1xdGjR3H//n0EBASwHgto6HZq6kuVbcOGDUNoaCgmTZokKfP398exY8dYj7V8+XJYW1sjMzMTurq6MDIywuLFixEVFcVqnPfeew88Hg83btzAixcvsGTJEjg6OrIa4xVNTU1MmDABEyZMQFlZGeLj4xEZGYmxY8eipKQEhoaGbY7xww8/NHsOW7H09PRw4MAB/Pbbb8jOzoaGhgamTZsmNfiErVjvCkpISmZqaoqlS5cqZJTTw4cP8eWXX+LDDz8El8tFTk4OOnfujPHjx7P6fCIlJQXHjh0Dn8+Hnp4e9u7dC1dXV7klJEV9qRoYGGDv3r24e/cuvv76awCAvDoY8vPz8fnnn+PQoUPQ0tLCokWL4OrqynocHR0d5OTkoE+fPrh27Rp4PJ5Cnn907doVX331Fb766isAwOzZs1lJ7KNGjWr2HLZiAQ3PwkaPHo3Ro0fLPda7gBKSkr0+yul18khIO3fuZL3Oprzqx3/14Lqurq7Rg182KepLVV9fH/v370dgYCB8fX2xYcMGud0Xl8vFixcvJL/DR48eySXWwoULsWnTJoSHhyMqKgoxMTHw8vJiPU5zFPnkQF1jqQNKSEoWGhoKoVCInJwciEQifPzxx6yPBnrF2NgYJ06cwJ9//inXZzv29vZYuHAhnj9/jn379uH48eNwdnZmPc4rTX2penp6sh6HYRjJqLc9e/Zg8uTJqK+vZz0O0NAVOH36dBQWFmLu3Lm4desW1q5dy3qcUaNGSVoVR48exfPnz9G5c2fW4zRHXqPu3qVY6oASkpLduXMH/v7+6NKlC8RiMUpLS7F9+3ZYWFiwHktRz3Zmz56N5ORk9OrVC4WFhZg/fz4+/fRTVmO8TlFfqmPGjJH8PHPmTHz88ccICQlhPc6rWAMHDkRmZiZEIhGCgoLQvXt31uM8fvwYgYGBePz4MQ4cOIBvvvkGa9euhYmJCeuxCGkOJSQlCw4OxsaNGyUJ6NatW1izZg2OHDnCeix5P9tJT0+X/Kyjo4Px48dLHXv9HSE2TJ8+/a1/ge7fv5+VOK8eTE+ZMkXq5dS+ffti7969rMT4p7q6OsTGxuLhw4dYvnw5oqOjMXv2bNZHYK5YsQIzZ85EREQEunfvDmdnZ3z33XdymX2CkOZQQlKy6upqqdbQkCFDUFtbK5dY/3wGwfaznS1btrzxGIfDYS1BvDJ//nwAQGxsLHR0dODu7g5NTU2cPHmS1d9hYGAgfvjhB8lLq//E9suqABAUFISuXbvi3r170NTURG5uLr7//ntERESwGufV7BMRERGS2SeUkYzU9bkOPUNqIYYo1ZdffsmcP39esn/+/Hnmyy+/lEusH374gfH392c+/fRTZu/evYy7uzuzc+dOucRSJA8Pj0ZlfD6f1RhJSUnMX3/9xTAMw5w7d46ZPXs2s2nTJqa2tpbVOK+4u7szDMMwbm5uDMMwjFgsZpycnFirv6qqimEYhpkyZQpTWFgoiZeens54eXmxFuef8vLymEuXLjH19fVMbm6upDw9PZ1iEYYSkpLl5OQwXl5ezKhRo5hRo0Yxnp6ezMOHD+US6/fff2eOHTvG8Pl8RiAQMJcuXZJLnJs3bzJ+fn6Mt7c3M336dGbatGnMp59+KpdYDMMwTk5OUr+z+/fvMy4uLqzVv2fPHsbDw4N58OABk52dzVhYWDCxsbHM6tWrmZCQENbivI7P5zO1tbWSRPH06VPG2dmZtfonTJjApKenM5mZmYyrqyszZMgQxtXVlRk7dixz69Yt1uK87tSpU4yzszNjZ2fHlJaWMlZWVkx8fDzFIhKUkJTsjz/+YBim4S/WFy9eMAzT8IXOptLSUmbq1KnMqFGjmM8++4z57LPPmBEjRjCzZs1iKioqWI3FMAzj4ODAHDlyhJk2bRqTmJjIfP3113L74mYYhklOTmasra0ZDw8Phs/nM7a2tqz+Zeri4sJUV1czDMMw4eHhzKJFixiGaWi12NvbsxaHYRjm8ePHDMMwzLFjx5ipU6cy1tbWTHBwMDNu3Djml19+YS1OcnIyM2HCBCY0NJR58eIF88cffzDZ2dlya/ExTEOr78WLF5JWX1FREePo6EixiAQ9Q1KS69evQywWIzAwECEhIZK+5vr6eqxatQpnz55lLVZkZCSGDx+Offv2oUOHDgAapsDZsmULQkJCWF/4TUtLC56ennj8+DH09fURFhYGFxcXVmO8zsbGBklJSfjjjz/A4XDQv39/VofOczgcdOzYEQCQlpaGqVOnSsrZ9vnnn0NXVxc2NjYYM2YMHBwcwDAMdu7cCTMzM9bi2NjY4Pjx49i8eTOmTp2KFStWoFevXigtLQUAuUyGq6GhITXnoJGRkdze41LXWOqOEpKSXL16FdeuXUNxcbFkgk4OhwNNTU18/vnnrMa6efMmzpw5I1XWoUMHfP3113Bzc2M1FgBoa2vj2bNn+PDDD3H79m2MHj1aLpNpbt26FfPnz8fSpUubPN7UTNatweVyUVFRgerqamRnZ8Pa2hpAw5Bptt8ZS05ORm5uLjIyMpCeno5bt26ha9euqKioQG1tLauvA3Ts2BELFizAkydPMGfOHOjr60uW1pDHQI2PP/4YP//8M+rr65GdnY2DBw+ymmTfhVjqjiZXVaKkpCRkZ2dj3rx5OH/+PI4cOYJPPvkEc+fOlbRk2ODu7o74+PgWH2utM2fOIDY2Flu3bsVnn30GDQ0NmJmZsT6reFJSEsaPH//GqVn4fD4rcRITExEWFob6+nqMHz8eq1atwunTp7Fx40bMmzdPrhPHVlRU4OLFi/jxxx+Rk5MjtTppW126dAlr1qyBjY0Nvv3220YzprOturoaO3fuxNWrV8EwDCwtLTFv3jy5xFXXWOqOEpKS/Pjjjzh16hTWr1+P+vp6fPHFF1i2bBmys7PB5XKxbNky1mLx+fy3fmnLY66tV39pV1dX49GjRzAzM2O9G6O5BevY7HYqKipCeXm55C/fX3/9FTo6Ok0u0NYW9fX1uH79OpKTk5GSkoKamhpYWVnBysoKPB6PtS85f39/3Lt3D2vWrHnjPGzy8PTpU2RkZEBTUxMjRoyQ66wQ6hpLnVFCUhJXV1fExMSgY8eOiIiIQEFBATZs2ACGYeDo6Nioi60tBg0ahB49ejQqZxgGJSUlyMrKYi3WpUuX0LdvX5iamuLChQs4cuQIBgwYwHqrD4BkUtim/heWV7eTvA0dOhTDhg3DpEmTYGVlJbcZE9asWYNvvvkGurq6cqm/KQkJCQgLC8Pw4cMhEomQmZmJ4OBgVpefUPdYak/x4ygIwzCMq6ur5GcvLy8mLi5Oss/2yK38/Py3bmzZvXv3G4dHBwcHsxZHna1bt45xc3NjJk+ezGzevJnJyMhgRCKRsi+LFZMmTWKePHki2c/Pz2d1KPu7EEvd0aAGJVHkg3JjY2NW63uThIQEqVbf+PHj8dlnn0laffJSVlaGoKAgpKamQiQSgcfjYdWqVXKZ+03evvvuOwBAcXExUlJScODAAQQEBKBfv36wsbHBlClTlHyFrdepUyeptYGMjY1ZbzWreyx1RwlJSWbPng13d3fU19fDy8sLRkZGUg/K2yNFDo9+3YoVKzB06FAEBwdDLBYjJiYGy5Ytk2mxNlVlZGQEZ2dn9O7dGzdu3EBCQgJu377drhPS4MGD4evrC09PT3C5XJw5cwZGRkaSQTVsDg5R11jqjhKSktjb22Po0KFSD8o7deqE4OBg1h+UK4oiW32vy8vLw7Zt2yT7vr6+OH78uNziydPFixdx48YNXL9+Hfn5+bCwsACPx8PGjRsVsqqwPNXW1sLIyAjJyckAGoadd+zYEWlpaQDY/eJW11jqjhKSEvXo0UNqsEF7fwiqrFYfh8NBYWEh3n//fQANo+/kmQDl6cCBA+DxePj+++8xaNAgtXrB0tbWFnZ2dqzPWP4uxVJ3NMqOsKq54dGvlnJg06VLl7By5UpYWFiAYRjcvn0ba9aswbhx41iNQ9pm6dKlSEtLw9ixY8Hn82Fubk6xiBRKSESh5PXeU1lZGTIzMyEWi2FhYYFu3bqxHoO03cuXL3Hu3DmcPHkST58+hZOTE9zd3eXy76WusdSZ+vQHkHaBzb9/4uPjJduVK1fw7NkzVFRUIDk5mfXZJwg7OnbsCGNjY7z//vuorKzE77//jv/85z/4+eefKRahZ0hEsdgccffqoTHw9zRCr6OHyarh1SrFGzduxMmTJ2FiYgJPT08sW7YM2traqKyshJ2dHb788kuK9a5T4jtQ5B30an0ftr2a+p+onlf/5ps2bZJavO51t2/fpliEXowl6kHe7zqRtluwYMEbj7E9EEBdY6k7SkhEoRgaQ/POefDgAezs7BqVM3JY6kJdY70rKCER1q1evfqNw18DAwNZi5Oeni75ubq6GhkZGVIJb+TIkazFIq3Xu3dvREVFUSzSLEpIhHXm5uaIjIxEWVkZ3Nzc4ObmJnn3aMSIEazF2bJli+RnIyMjyUKHQEMX3v79+1mLRVqvQ4cOCptPUV1jvSsoIRHW8fl88Pl8FBYW4uTJk/jiiy/Qt29ffPbZZ5gwYQJrcX766SfW6iLyM2zYMIpFZEIvxhK5yMvLw/Hjx3Hq1Cn07NkTjo6OSE1NBZfLRVhYGKuxMjMzcf36dUybNg1+fn64d+8ewsLCYGtry2ocQoh8UQuJsG7KlCkoLS2Fm5sbdu/eLVm51d3dXS5JIjg4GPPnz8fZs2ehra2NuLg4zJ8/nxISIe0MJSTCOn9//yaXxdbU1MTVq1dZjycWizFmzBh88803mDRpEnr16gWRSMR6HEKIfFFCIqxZunSp5Oemln8IDQ2VS9yOHTvixx9/RFpaGlasWIH9+/ejU6dOcolFCJEfSkiENaNGjXrjMXm+uBoREYFffvkFW7ZsQefOnVFUVITIyEi5xSOEyAcNaiCsy8zMlHoH6eXLl9i8eTMCAgKUeFWEEFVHLSTCuiVLlmDdunUYOnQofv31V6xevRo8Ho/1OGZmZk22vF69KZ+dnc16TEKI/FALibAuJycH8+fPh6mpKfLz87Fy5UpWX4glhKgnSkiENQUFBVI/L1y4EIGBgZLuu1fDvwkhpCmUkAhrxo8fDw6H0+QEqjTZJCGkOZSQCCGEqARawpyw7vnz5wgMDIS3tzeePXuGpUuXoqKiQtmXRQhRcZSQCOuWL1+OwYMH49mzZ9DV1YWRkREWL16s7MsihKg4SkiEdfn5+fj888+hoaEBLS0tLFq0CE+ePFH2ZRFCVBwlJMI6LpeLFy9eSN4RevToETQ06H81Qsjb0aAGwrrk5GRERkaisLAQw4cPx61bt7B27VqMGzdO2ZdGCFFhlJCIXJSVlSEzMxMikQgWFhbo3r27si+JEKLiqB+FsK6urg6xsbE4ffo0Ro0ahcOHD6Ourk7Zl0UIUXGUkAjrgoKCUF1djXv37kFTUxO5ubn4/vvvlX1ZhBAVRwmJsO7u3bv4+uuvoampiY4dO2L9+vW4f/++si+LEKLiKCER1nE4HNTV1UlG2ZWXl8t1PSRCiHqghERY82pyVW9vb8yYMQMlJSUICQmBp6cnfHx8lHx1hBBVR6PsCGvGjBkDXV1d2NjYwNDQEHp6emAYBiNHjoSZmZmyL48QouJogT7CmuTkZOTm5iIjIwPp6em4desWunbtioqKCtTW1sLCwkLZl0gIUWHUQiJyU1FRgYsXL+LHH39ETk4O7ty5o+xLIoSoMEpIhDX19fW4fv06kpOTkZKSgpqaGlhZWcHKygo8Hg96enrKvkRCiAqjhERYM3ToUAwbNgyTJk2ClZUVTExMlH1JhJB2hEbZEdZ88cUXePr0KY4ePYq4uDhcv34dYrFY2ZdFCGknqIVEWFdcXIyUlBSkpKQgKysL/fr1g42NDaZMmaLsSyOEqDBKSEQu6urqkJWVhRs3biAhIQHPnj1DSkqKsi+LEKLCKCER1ly8eBE3btzA9evXkZ+fDwsLC/B4PPB4PHz88cfKvjxCiIqjhERY89VXX0kS0KBBg2hRPkJIi1BCIoQQohLoT1hCCCEqgRISIYQQlUAJiRBCiEqghEQIIUQl/H+owjX008M2xAAAAABJRU5ErkJggg==",
- "text/plain": [
- "<Figure size 432x288 with 2 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "sns.heatmap(clean_data2.corr(),cmap=\"PiYG\") "
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 76,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "image/png": 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",
- "text/plain": [
- "<Figure size 576x864 with 2 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "plt.figure(figsize=(8, 12))\n",
- "heatmap = sns.heatmap(clean_data2.corr()[['Weekly_Sales']].sort_values(by='Weekly_Sales', ascending=False), vmin=-1, vmax=1, annot=True, cmap='PiYG')\n",
- "heatmap.set_title('which features influence Weekly Sales the most ?', fontdict={'fontsize':18}, pad=16);"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 77,
- "metadata": {},
- "outputs": [],
- "source": [
- "#sns.pairplot(clean_data2, vars=['Weekly_Sales', 'Dept', 'Size', 'Type_A'])"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 78,
- "metadata": {},
- "outputs": [],
- "source": [
- "# save data local\n",
- "clean_data2.to_csv('clean_data2.csv', index = False) "
- ]
- },
- {
- "attachments": {},
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## 3.7. Testen und Trainieren von Daten"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 79,
- "metadata": {},
- "outputs": [],
- "source": [
- "# Split Data\n",
- "inputs = clean_data2.drop(['Weekly_Sales', 'Date'], axis=1)\n",
- "targets = clean_data2['Weekly_Sales'] # das ist die Zielvariable"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 80,
- "metadata": {},
- "outputs": [],
- "source": [
- "#Feature Scaling (transforms our data into standard distributed data) \n",
- "# the data is transformed in such a way that then a mean of 0 and a standard deviation of 1 is obtained\n",
- "# ~ (\ud835\udf07, \ud835\udf0e2) ~ (0,1)\n",
- "\n",
- "from sklearn.preprocessing import StandardScaler\n",
- "scaler = StandardScaler()\n",
- "scaler.fit(inputs)\n",
- "inputs_scaled = scaler.transform(inputs)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 81,
- "metadata": {},
- "outputs": [],
- "source": [
- "# Split data into test and training - test data is 20%.\n",
- "from sklearn.model_selection import train_test_split\n",
- "x_train, x_test, y_train, y_test = train_test_split(inputs_scaled, targets, test_size=0.2, random_state=365)\n"
- ]
- },
- {
- "attachments": {},
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# 4. Modellierung und Evaluation"
- ]
- },
- {
- "attachments": {},
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## 4.1. Random Forest mit normalen (gro\u00dfen) Daten"
- ]
- },
- {
- "attachments": {},
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "class sklearn.ensemble.RandomForestRegressor(n_estimators=100, *, criterion='mse', max_depth=None, min_samples_split=2, min_samples_leaf=1, min_weight_fraction_leaf=0. 0, max_features='auto', max_leaf_nodes=Keine, min_impurity_decrease=0.0, min_impurity_split=Eine, bootstrap=True, oob_score=False, n_jobs=Eine, random_state=Eine, verbose=0, warm_start=False, ccp_alpha=0.0, max_samples=Eine)\n",
- "\n",
- "bootstrap: Ob bei der Erstellung von B\u00e4umen Bootstrap-Stichproben verwendet werden. Wenn False, wird der gesamte Datensatz zur Erstellung jedes Baums verwendet. Voreinstellung ist True.\n",
- "\n",
- "max_depth: Die Standardwerte f\u00fcr die Parameter, die die Gr\u00f6\u00dfe der B\u00e4ume steuern (z. B. max_depth, min_samples_leaf usw.), f\u00fchren zu vollst\u00e4ndig ausgewachsenen und nicht beschnittenen B\u00e4umen, die bei einigen Datens\u00e4tzen sehr gro\u00df sein k\u00f6nnen. Um den Speicherverbrauch zu reduzieren, sollte die Komplexit\u00e4t und Gr\u00f6\u00dfe der B\u00e4ume durch die Einstellung dieser Parameterwerte kontrolliert werden. Der Standardwert ist None und bedeutet, dass die Knoten so lange expandiert werden, bis alle Bl\u00e4tter rein sind oder bis alle Bl\u00e4tter weniger als min_samples_split samples enthalten. Der Wert von 70 hat sich in Tests bew\u00e4hrt.\n",
- "\n",
- "max_features: Der Standardwert max_features=\"auto\" verwendet n_features bei jedem Split. Die Voreinstellung ist \"auto\".\n",
- "\n",
- "min_samples_leaf: Die Mindestanzahl von Stichproben, die f\u00fcr einen Blattknoten erforderlich sind. Ein Teilungspunkt in beliebiger Tiefe wird nur ber\u00fccksichtigt, wenn er mindestens min_samples_leaf Trainingsmuster in jedem der linken und rechten Zweige hinterl\u00e4sst. Dies kann zu einer Gl\u00e4ttung des Modells f\u00fchren, insbesondere bei Regressionen. Standardwert ist 1. Testreihen haben gezeigt, dass der Wert 4 die besten Ergebnisse liefert.\n",
- "\n",
- "min_samples_split: Die Mindestanzahl von Stichproben, die erforderlich ist, um einen internen Knoten aufzuteilen. Standardwert ist 2, in Testreihen hat sich der Wert 10 als am sinnvollsten erwiesen. \n",
- "\n",
- "n_Sch\u00e4tzer: Dies ist die Anzahl der B\u00e4ume, die Sie erstellen m\u00f6chten, bevor Sie die Maximalstimme oder den Durchschnitt der Vorhersagen nehmen. Eine h\u00f6here Anzahl von B\u00e4umen f\u00fchrt zu einer besseren Leistung, macht den Code aber auch langsamer. Die Voreinstellung ist 100. Testreihen haben gezeigt: Unter und \u00fcber 400 nimmt die Genauigkeit ab.\n",
- "\n",
- "n_jobs: wie viele Jobs parallel laufen k\u00f6nnen, beeinflusst die Geschwindigkeit des Algorithmus\n",
- "\n",
- "Die Merkmale werden bei jedem Split immer zuf\u00e4llig permutiert. Daher kann selbst bei gleichen Trainingsdaten, max_features=n_features und bootstrap=False der beste gefundene Split variieren, wenn die Kriteriumverbesserung f\u00fcr mehrere Splits, die bei der Suche nach dem besten Split aufgez\u00e4hlt werden, identisch ist. Um ein deterministisches Verhalten bei der Anpassung zu erhalten, muss random_state in der Testreihe angegeben werden."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 82,
- "metadata": {},
- "outputs": [],
- "source": [
- "from sklearn.ensemble import RandomForestRegressor\n",
- "rfr = RandomForestRegressor(bootstrap = True, max_depth = 70, max_features = 'auto', min_samples_leaf = 4, min_samples_split = 10, n_estimators = 10)\n",
- "\n",
- "# rfr = RandomForestRegressor(n_estimators = 400,max_depth=15,n_jobs=5) # 0.955111\n",
- "rfr.fit(x_train,y_train)\n",
- "y_predictions=rfr.predict(x_test)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 83,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "1506.3206109502669"
- ]
- },
- "execution_count": 83,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "from sklearn.metrics import mean_absolute_error\n",
- "mean_absolute_error(y_test, y_predictions)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 84,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "19103020.45675435"
- ]
- },
- "execution_count": 84,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "from sklearn.metrics import mean_squared_error\n",
- "mean_squared_error(y_test, y_predictions)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 85,
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "0.9645552402964631\n"
- ]
- }
- ],
- "source": [
- "accuracy = rfr.score(x_test, y_test)\n",
- "print(accuracy)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 86,
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Variable: Dept Importance: 0.64\n",
- "Variable: Size Importance: 0.2\n",
- "Variable: Store Importance: 0.08\n",
- "Variable: Week Importance: 0.05\n",
- "Variable: Year Importance: 0.01\n",
- "Variable: IsHoliday Importance: 0.0\n",
- "Variable: Type_A Importance: 0.0\n",
- "Variable: Type_B Importance: 0.0\n",
- "Variable: Type_C Importance: 0.0\n"
- ]
- }
- ],
- "source": [
- "feature_list = list(inputs.columns) \n",
- "\n",
- "importances = list(rfr.feature_importances_)\n",
- "feature_importances = [(feature, round(importance, 2)) for feature, importance in zip(feature_list, importances)]\n",
- "feature_importances = sorted(feature_importances, key = lambda x: x[1], reverse = True) \n",
- "[print('Variable: {:20} Importance: {}'.format(*pair)) for pair in feature_importances];"
- ]
- },
- {
- "attachments": {},
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## 4.2. Random Forest mit neuen kleinen Daten"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 88,
- "metadata": {},
- "outputs": [],
- "source": [
- "inputs_small = clean_smalldata.drop(['Weekly_Sales', 'Date'], axis=1)\n",
- "targets_small = clean_smalldata['Weekly_Sales'] # das ist die Zielvariable\n",
- " \n",
- "from sklearn.preprocessing import StandardScaler\n",
- "scaler = StandardScaler()\n",
- "scaler.fit(inputs_small)\n",
- "inputs_scaleds = scaler.transform(inputs_small)\n",
- "\n",
- "from sklearn.model_selection import train_test_split\n",
- "x_trains, x_tests, y_trains, y_tests = train_test_split(inputs_scaleds, targets_small, test_size=0.2, random_state=365)\n"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 90,
- "metadata": {},
- "outputs": [],
- "source": [
- "#rfr_small = RandomForestRegressor(n_estimators = 400,max_depth=15,n_jobs=5) \n",
- "rfr_small = RandomForestRegressor(bootstrap = True, max_depth = 70, max_features = 'auto', min_samples_leaf = 4, min_samples_split = 10, n_estimators = 10)\n",
- "\n",
- "rfr_small.fit(x_trains,y_trains)\n",
- "y_predictions_small=rfr_small.predict(x_tests)"
- ]
- },
- {
- "attachments": {},
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### MAE - der mittlere absolute Fehler\n",
- "gibt die durchschnittliche absolute Abweichung des Prognosewertes vom tats\u00e4chlichen Wert an. \n",
- "Wert, der tats\u00e4chlich eingetreten ist. \u00dcber- und Untersch\u00e4tzungen werden in ungerichteter Weise kumuliert, so dass MAE=0 \n",
- "als perfekte Prognose interpretiert werden kann, d.h. der Prognosewert f\u00fcr jede Periode t entspricht genau dem tats\u00e4chlichen Wert. \n",
- "dem tats\u00e4chlich eingetretenen Wert. "
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 91,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "1766.4411977247057"
- ]
- },
- "execution_count": 91,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "mean_absolute_error(y_tests, y_predictions_small)"
- ]
- },
- {
- "attachments": {},
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Wir erhalten einen MAE von 1.716,1138, d.h. die durchschnittliche Abweichung betr\u00e4gt etwa 1.716 Dollar, mit der unsere Prognose von den tats\u00e4chlichen Werten abweicht."
- ]
- },
- {
- "attachments": {},
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### MSE - Mittlerer quadratischer Fehler \n",
- "ist die quadratische Form des ME. Dies hat zur Folge, dass gro\u00dfe Abweichungen vom tats\u00e4chlichen Wert \u00fcberproportional stark gewichtet werden im Vergleich zu kleineren Abweichungen, die in der Praxis oft vernachl\u00e4ssigbar sind. Au\u00dferdem werden die einzelnen Prognosefehler nun wie beim MAE kumuliert, so dass die perfekte Prognose wieder bei MSE=0 vorliegt. "
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 92,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "17008422.72019644"
- ]
- },
- "execution_count": 92,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "mean_squared_error(y_tests, y_predictions_small)"
- ]
- },
- {
- "attachments": {},
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "#R\u00b2 - Bestimmungskoeffizient\n",
- "Das so genannte Bestimmtheitsma\u00df (R\u00b2) dr\u00fcckt aus, wie gut die Regressionsgerade die Beziehung zwischen der unabh\u00e4ngigen und der abh\u00e4ngigen Variable wiedergibt. R\u00b2 liegt zwischen 0 und 1, wobei der Wert R\u00b2 = 1 bedeuten w\u00fcrde, dass jeder beobachtete Datenpunkt direkt auf der Regressionsgeraden liegt."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 93,
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "0.9684712372223249\n"
- ]
- }
- ],
- "source": [
- "accuracy_small = rfr_small.score(x_tests, y_tests) \n",
- "print(accuracy_small)"
- ]
- },
- {
- "attachments": {},
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Das bedeutet, dass die vorhergesagten Werte relativ wenig abweichen und zu etwa 97 % auf der Geraden liegen."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 94,
- "metadata": {},
- "outputs": [],
- "source": [
- "# R\u00b2 = 0.964437 with Markdown 1,2 and 5 included - were thus subsequently removed and R\u00b2 increases\n",
- "# R\u00b2 = 0.9645159264218026 (n_estimators = 400,max_depth=15,n_jobs=5) \n",
- "# R\u00b2 = 0.9692695835667837 with new parameters\n",
- "# R\u00b2 = 0.9698712189554696 with new parameters and removal of variables with importance 0 each variable since random"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 95,
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Variable: Dept Importance: 0.63\n",
- "Variable: Size Importance: 0.14\n",
- "Variable: Store Importance: 0.08\n",
- "Variable: Type_A Importance: 0.06\n",
- "Variable: MarkDown3 Importance: 0.04\n",
- "Variable: Week Importance: 0.02\n",
- "Variable: MarkDown4 Importance: 0.01\n",
- "Variable: Year Importance: 0.0\n",
- "Variable: Type_B Importance: 0.0\n",
- "Variable: Type_C Importance: 0.0\n"
- ]
- }
- ],
- "source": [
- "#The importance indicates how much the inclusion of a particular variable improves the prediction. \n",
- "feature_list = list(inputs_small.columns) # in einen numpy array umwandeln\n",
- "\n",
- "importances = list(rfr_small.feature_importances_)\n",
- "feature_importances = [(feature, round(importance, 2)) for feature, importance in zip(feature_list, importances)]\n",
- "feature_importances = sorted(feature_importances, key = lambda x: x[1], reverse = True) # sortieren\n",
- "[print('Variable: {:20} Importance: {}'.format(*pair)) for pair in feature_importances];"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 97,
- "metadata": {},
- "outputs": [
- {
- "data": {
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- " Weekly_Sales_predicted\n",
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- "source": [
- "predict_data = pd.DataFrame({'Weekly_Sales_predicted': y_predictions_small})\n",
- "y_test_data = pd.DataFrame(y_tests[0:30186]) \n",
- "predict_data.head(5) "
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 98,
- "metadata": {},
- "outputs": [
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- "y_test_data.head(5)"
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- {
- "cell_type": "code",
- "execution_count": 99,
- "metadata": {},
- "outputs": [
- {
- "data": {
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",
- "text/plain": [
- "<Figure size 432x288 with 1 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "from sklearn.linear_model import LinearRegression\n",
- "lr = LinearRegression()\n",
- "lr.fit(y_test_data, predict_data)\n",
- "w = lr.coef_[0]\n",
- "\n",
- "plt.scatter(y_test_data, predict_data)\n",
- "plt.plot(y_test_data, w*y_test_data, c='red')\n",
- "plt.title(\"Vorhersage im Vergleich zu Ist-Daten\")\n",
- "plt.xlabel(\"Ist-Daten\")\n",
- "plt.ylabel(\"Vorhersage\")\n",
- "plt.show()"
- ]
- }
- ],
- "metadata": {
- "kernelspec": {
- "display_name": "Python 3",
- "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": "3.8.5"
- },
- "title": "Sales Forecast for retail store",
- "category": "Forecast"
- },
- "nbformat": 4,
- "nbformat_minor": 4
-}
\ No newline at end of file
--
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