{
 "cells": [
  {
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   },
   "source": [
    "# Churn Prediction for Customers in the Telecom Industry "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b18794f0",
   "metadata": {
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   },
   "source": [
    "![Picture](https://capgemini-engineering.com/as-content/uploads/sites/8/2017/05/2-8_telecom-media_v2_1600.jpg)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e464582c",
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   "source": [
    "## About the Dataset\n",
    "\n",
    "Each row represents a customer, each column contains customer’s attributes described on the column Metadata.\n",
    "\n",
    "**The data set includes information about:**\n",
    "\n",
    "**Customers who left within the last month** – the column is called Churn\n",
    "\n",
    "**Services that each customer has signed up for** – phone, multiple lines, internet, online security, online backup, device protection, tech support, and streaming TV and movies\n",
    "\n",
    "**Customer account information** – how long they’ve been a customer, contract, payment method, paperless billing, monthly charges, and total charges\n",
    "\n",
    "**Demographic info about customers** – gender, age range, and if they have partners and dependents"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ed0c4a3f",
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    "tags": []
   },
   "source": [
    "## The Mission\n",
    "\n",
    "Explore the Dataset and create a model to predict if a customer is going to churn or not\n",
    "\n",
    "\n",
    "### Let's get started"
   ]
  },
  {
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   "id": "1658e554",
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   "source": [
    "#importing Libraries\n",
    "\n",
    "import pandas as pd \n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "ca209eca",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-11T16:31:44.510089Z",
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   "outputs": [],
   "source": [
    "#reading the data \n",
    "\n",
    "cust = pd.read_csv('../input/telco-customer-churn/WA_Fn-UseC_-Telco-Customer-Churn.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "afd11373",
   "metadata": {
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   "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>customerID</th>\n",
       "      <th>gender</th>\n",
       "      <th>SeniorCitizen</th>\n",
       "      <th>Partner</th>\n",
       "      <th>Dependents</th>\n",
       "      <th>tenure</th>\n",
       "      <th>PhoneService</th>\n",
       "      <th>MultipleLines</th>\n",
       "      <th>InternetService</th>\n",
       "      <th>OnlineSecurity</th>\n",
       "      <th>...</th>\n",
       "      <th>DeviceProtection</th>\n",
       "      <th>TechSupport</th>\n",
       "      <th>StreamingTV</th>\n",
       "      <th>StreamingMovies</th>\n",
       "      <th>Contract</th>\n",
       "      <th>PaperlessBilling</th>\n",
       "      <th>PaymentMethod</th>\n",
       "      <th>MonthlyCharges</th>\n",
       "      <th>TotalCharges</th>\n",
       "      <th>Churn</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>7590-VHVEG</td>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>1</td>\n",
       "      <td>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>29.85</td>\n",
       "      <td>29.85</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5575-GNVDE</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>34</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>One year</td>\n",
       "      <td>No</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>56.95</td>\n",
       "      <td>1889.5</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3668-QPYBK</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>2</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>53.85</td>\n",
       "      <td>108.15</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>7795-CFOCW</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>45</td>\n",
       "      <td>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>One year</td>\n",
       "      <td>No</td>\n",
       "      <td>Bank transfer (automatic)</td>\n",
       "      <td>42.30</td>\n",
       "      <td>1840.75</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>9237-HQITU</td>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>2</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>70.70</td>\n",
       "      <td>151.65</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   customerID  gender  SeniorCitizen Partner Dependents  tenure PhoneService  \\\n",
       "0  7590-VHVEG  Female              0     Yes         No       1           No   \n",
       "1  5575-GNVDE    Male              0      No         No      34          Yes   \n",
       "2  3668-QPYBK    Male              0      No         No       2          Yes   \n",
       "3  7795-CFOCW    Male              0      No         No      45           No   \n",
       "4  9237-HQITU  Female              0      No         No       2          Yes   \n",
       "\n",
       "      MultipleLines InternetService OnlineSecurity  ... DeviceProtection  \\\n",
       "0  No phone service             DSL             No  ...               No   \n",
       "1                No             DSL            Yes  ...              Yes   \n",
       "2                No             DSL            Yes  ...               No   \n",
       "3  No phone service             DSL            Yes  ...              Yes   \n",
       "4                No     Fiber optic             No  ...               No   \n",
       "\n",
       "  TechSupport StreamingTV StreamingMovies        Contract PaperlessBilling  \\\n",
       "0          No          No              No  Month-to-month              Yes   \n",
       "1          No          No              No        One year               No   \n",
       "2          No          No              No  Month-to-month              Yes   \n",
       "3         Yes          No              No        One year               No   \n",
       "4          No          No              No  Month-to-month              Yes   \n",
       "\n",
       "               PaymentMethod MonthlyCharges  TotalCharges Churn  \n",
       "0           Electronic check          29.85         29.85    No  \n",
       "1               Mailed check          56.95        1889.5    No  \n",
       "2               Mailed check          53.85        108.15   Yes  \n",
       "3  Bank transfer (automatic)          42.30       1840.75    No  \n",
       "4           Electronic check          70.70        151.65   Yes  \n",
       "\n",
       "[5 rows x 21 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cust.head()"
   ]
  },
  {
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['customerID', 'gender', 'SeniorCitizen', 'Partner', 'Dependents',\n",
       "       'tenure', 'PhoneService', 'MultipleLines', 'InternetService',\n",
       "       'OnlineSecurity', 'OnlineBackup', 'DeviceProtection', 'TechSupport',\n",
       "       'StreamingTV', 'StreamingMovies', 'Contract', 'PaperlessBilling',\n",
       "       'PaymentMethod', 'MonthlyCharges', 'TotalCharges', 'Churn'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cust.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "3c336e08",
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     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 7043 entries, 0 to 7042\n",
      "Data columns (total 21 columns):\n",
      " #   Column            Non-Null Count  Dtype  \n",
      "---  ------            --------------  -----  \n",
      " 0   customerID        7043 non-null   object \n",
      " 1   gender            7043 non-null   object \n",
      " 2   SeniorCitizen     7043 non-null   int64  \n",
      " 3   Partner           7043 non-null   object \n",
      " 4   Dependents        7043 non-null   object \n",
      " 5   tenure            7043 non-null   int64  \n",
      " 6   PhoneService      7043 non-null   object \n",
      " 7   MultipleLines     7043 non-null   object \n",
      " 8   InternetService   7043 non-null   object \n",
      " 9   OnlineSecurity    7043 non-null   object \n",
      " 10  OnlineBackup      7043 non-null   object \n",
      " 11  DeviceProtection  7043 non-null   object \n",
      " 12  TechSupport       7043 non-null   object \n",
      " 13  StreamingTV       7043 non-null   object \n",
      " 14  StreamingMovies   7043 non-null   object \n",
      " 15  Contract          7043 non-null   object \n",
      " 16  PaperlessBilling  7043 non-null   object \n",
      " 17  PaymentMethod     7043 non-null   object \n",
      " 18  MonthlyCharges    7043 non-null   float64\n",
      " 19  TotalCharges      7043 non-null   object \n",
      " 20  Churn             7043 non-null   object \n",
      "dtypes: float64(1), int64(2), object(18)\n",
      "memory usage: 1.1+ MB\n"
     ]
    }
   ],
   "source": [
    "cust.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "7c101a0d",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-11T16:31:44.788917Z",
     "iopub.status.busy": "2022-07-11T16:31:44.788472Z",
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     "shell.execute_reply": "2022-07-11T16:31:44.811976Z"
    },
    "papermill": {
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   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "customerID          0\n",
       "gender              0\n",
       "SeniorCitizen       0\n",
       "Partner             0\n",
       "Dependents          0\n",
       "tenure              0\n",
       "PhoneService        0\n",
       "MultipleLines       0\n",
       "InternetService     0\n",
       "OnlineSecurity      0\n",
       "OnlineBackup        0\n",
       "DeviceProtection    0\n",
       "TechSupport         0\n",
       "StreamingTV         0\n",
       "StreamingMovies     0\n",
       "Contract            0\n",
       "PaperlessBilling    0\n",
       "PaymentMethod       0\n",
       "MonthlyCharges      0\n",
       "TotalCharges        0\n",
       "Churn               0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Checking for Null values\n",
    "\n",
    "cust.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d9aaf677",
   "metadata": {
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   },
   "source": [
    "### Null values\n",
    "Since those are only 11 values we can delete them without fearing that our results get falsified\n",
    "\n",
    "We also drop the customer ID since we don't need it"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "0758dde5",
   "metadata": {
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   "outputs": [],
   "source": [
    "cust.TotalCharges = pd.to_numeric(cust.TotalCharges, errors='coerce')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "3079e4e0",
   "metadata": {
    "execution": {
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   "outputs": [],
   "source": [
    "cust = cust.drop('customerID', axis = 1)\n",
    "cust.dropna(inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "272e25b5",
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     "duration": 0.040154,
     "end_time": "2022-07-11T16:31:45.000234",
     "exception": false,
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     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "gender              0\n",
       "SeniorCitizen       0\n",
       "Partner             0\n",
       "Dependents          0\n",
       "tenure              0\n",
       "PhoneService        0\n",
       "MultipleLines       0\n",
       "InternetService     0\n",
       "OnlineSecurity      0\n",
       "OnlineBackup        0\n",
       "DeviceProtection    0\n",
       "TechSupport         0\n",
       "StreamingTV         0\n",
       "StreamingMovies     0\n",
       "Contract            0\n",
       "PaperlessBilling    0\n",
       "PaymentMethod       0\n",
       "MonthlyCharges      0\n",
       "TotalCharges        0\n",
       "Churn               0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#checking again\n",
    "cust.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2cbffa80",
   "metadata": {
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     "start_time": "2022-07-11T16:31:45.015339",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### Transforming values\n",
    "As we can see, there are a lot of object values in the dataset. In the next steps we will convert them to numeric values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "8886c552",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-11T16:31:45.061200Z",
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   "outputs": [],
   "source": [
    "#now we convert our goal variable 'Churn' into numeric values\n",
    "\n",
    "df = cust.copy()\n",
    "\n",
    "df['Churn'].replace(to_replace='Yes', value=1, inplace=True)\n",
    "df['Churn'].replace(to_replace='No',  value=0, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "be31e20d",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-11T16:31:45.107244Z",
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     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "#Converting the rest of the object variables to dummies\n",
    "\n",
    "cust_final = pd.get_dummies(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "c2564a68",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-11T16:31:45.173303Z",
     "iopub.status.busy": "2022-07-11T16:31:45.172919Z",
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     "status": "completed"
    },
    "tags": []
   },
   "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",
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       "    }\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>SeniorCitizen</th>\n",
       "      <th>tenure</th>\n",
       "      <th>MonthlyCharges</th>\n",
       "      <th>TotalCharges</th>\n",
       "      <th>Churn</th>\n",
       "      <th>gender_Female</th>\n",
       "      <th>gender_Male</th>\n",
       "      <th>Partner_No</th>\n",
       "      <th>Partner_Yes</th>\n",
       "      <th>Dependents_No</th>\n",
       "      <th>...</th>\n",
       "      <th>StreamingMovies_Yes</th>\n",
       "      <th>Contract_Month-to-month</th>\n",
       "      <th>Contract_One year</th>\n",
       "      <th>Contract_Two year</th>\n",
       "      <th>PaperlessBilling_No</th>\n",
       "      <th>PaperlessBilling_Yes</th>\n",
       "      <th>PaymentMethod_Bank transfer (automatic)</th>\n",
       "      <th>PaymentMethod_Credit card (automatic)</th>\n",
       "      <th>PaymentMethod_Electronic check</th>\n",
       "      <th>PaymentMethod_Mailed check</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>29.85</td>\n",
       "      <td>29.85</td>\n",
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       "      <td>0</td>\n",
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       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>34</td>\n",
       "      <td>56.95</td>\n",
       "      <td>1889.50</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>53.85</td>\n",
       "      <td>108.15</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>45</td>\n",
       "      <td>42.30</td>\n",
       "      <td>1840.75</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "      <td>1</td>\n",
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       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>70.70</td>\n",
       "      <td>151.65</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
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       "      <td>1</td>\n",
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       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 46 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   SeniorCitizen  tenure  MonthlyCharges  TotalCharges  Churn  gender_Female  \\\n",
       "0              0       1           29.85         29.85      0              1   \n",
       "1              0      34           56.95       1889.50      0              0   \n",
       "2              0       2           53.85        108.15      1              0   \n",
       "3              0      45           42.30       1840.75      0              0   \n",
       "4              0       2           70.70        151.65      1              1   \n",
       "\n",
       "   gender_Male  Partner_No  Partner_Yes  Dependents_No  ...  \\\n",
       "0            0           0            1              1  ...   \n",
       "1            1           1            0              1  ...   \n",
       "2            1           1            0              1  ...   \n",
       "3            1           1            0              1  ...   \n",
       "4            0           1            0              1  ...   \n",
       "\n",
       "   StreamingMovies_Yes  Contract_Month-to-month  Contract_One year  \\\n",
       "0                    0                        1                  0   \n",
       "1                    0                        0                  1   \n",
       "2                    0                        1                  0   \n",
       "3                    0                        0                  1   \n",
       "4                    0                        1                  0   \n",
       "\n",
       "   Contract_Two year  PaperlessBilling_No  PaperlessBilling_Yes  \\\n",
       "0                  0                    0                     1   \n",
       "1                  0                    1                     0   \n",
       "2                  0                    0                     1   \n",
       "3                  0                    1                     0   \n",
       "4                  0                    0                     1   \n",
       "\n",
       "   PaymentMethod_Bank transfer (automatic)  \\\n",
       "0                                        0   \n",
       "1                                        0   \n",
       "2                                        0   \n",
       "3                                        1   \n",
       "4                                        0   \n",
       "\n",
       "   PaymentMethod_Credit card (automatic)  PaymentMethod_Electronic check  \\\n",
       "0                                      0                               1   \n",
       "1                                      0                               0   \n",
       "2                                      0                               0   \n",
       "3                                      0                               0   \n",
       "4                                      0                               1   \n",
       "\n",
       "   PaymentMethod_Mailed check  \n",
       "0                           0  \n",
       "1                           1  \n",
       "2                           1  \n",
       "3                           0  \n",
       "4                           0  \n",
       "\n",
       "[5 rows x 46 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cust_final.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a3f06a71",
   "metadata": {
    "papermill": {
     "duration": 0.014723,
     "end_time": "2022-07-11T16:31:45.227872",
     "exception": false,
     "start_time": "2022-07-11T16:31:45.213149",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "#### We will use this Dataframe later for building the predicition models. But for the EDA we will use the original Dataframe."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8b5ed2de",
   "metadata": {
    "papermill": {
     "duration": 0.014991,
     "end_time": "2022-07-11T16:31:45.257819",
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     "start_time": "2022-07-11T16:31:45.242828",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### Exploring the Data - EDA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "5cfca77a",
   "metadata": {
    "execution": {
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     "start_time": "2022-07-11T16:31:45.272833",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Checking correlations of the features with Churn\n",
    "\n",
    "plt.figure(figsize=(15,8))\n",
    "colors = ['#264653']\n",
    "\n",
    "cust_final.corr()['Churn'].sort_values(ascending = False).plot(kind = 'bar', color = colors)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ff8f98fc",
   "metadata": {
    "papermill": {
     "duration": 0.015941,
     "end_time": "2022-07-11T16:31:46.061306",
     "exception": false,
     "start_time": "2022-07-11T16:31:46.045365",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "#### Demographics of the dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "6cc13e40",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-11T16:31:46.096975Z",
     "iopub.status.busy": "2022-07-11T16:31:46.096523Z",
     "iopub.status.idle": "2022-07-11T16:31:46.272335Z",
     "shell.execute_reply": "2022-07-11T16:31:46.271377Z"
    },
    "papermill": {
     "duration": 0.196496,
     "end_time": "2022-07-11T16:31:46.274730",
     "exception": false,
     "start_time": "2022-07-11T16:31:46.078234",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Gender Distribution')"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#distribution of gender \n",
    "\n",
    "colors = ['#264653', '#2a9d8f']\n",
    "\n",
    "ax = ((cust['gender'].value_counts()/len(cust['gender']))*100).plot(kind = 'bar', color = colors)\n",
    "\n",
    "ax.set_ylabel('Customers in %')\n",
    "ax.set_xlabel('Gender')\n",
    "ax.set_title('Gender Distribution')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "2c5ded8c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-11T16:31:46.311299Z",
     "iopub.status.busy": "2022-07-11T16:31:46.310579Z",
     "iopub.status.idle": "2022-07-11T16:31:46.461634Z",
     "shell.execute_reply": "2022-07-11T16:31:46.460052Z"
    },
    "papermill": {
     "duration": 0.17331,
     "end_time": "2022-07-11T16:31:46.465489",
     "exception": false,
     "start_time": "2022-07-11T16:31:46.292179",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(-1.1059512938819451,\n",
       " 1.1065875007007335,\n",
       " -1.1055497655464688,\n",
       " 1.1002643080914476)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Distribution of Senior Citizens in the Datset\n",
    "\n",
    "colors = ['#264653', '#2a9d8f']\n",
    "mpl.rcParams.update({'text.color' : \"black\"})\n",
    "labels = 'No', 'Yes'\n",
    "plt.figure(figsize = (12,5))\n",
    "ax = ((cust['SeniorCitizen'].value_counts()/len(cust['SeniorCitizen']))*100).plot.pie(labels=labels, autopct='%1.1f%%', shadow=False, startangle=90, colors = colors)\n",
    "ax.set_ylabel('Senior Citizens',fontsize = 12)\n",
    "ax.set_title('% of Senior Citizens', fontsize = 12)\n",
    "ax.axis('equal') "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "9af34e60",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-11T16:31:46.528303Z",
     "iopub.status.busy": "2022-07-11T16:31:46.527276Z",
     "iopub.status.idle": "2022-07-11T16:31:46.704412Z",
     "shell.execute_reply": "2022-07-11T16:31:46.703180Z"
    },
    "papermill": {
     "duration": 0.209711,
     "end_time": "2022-07-11T16:31:46.707152",
     "exception": false,
     "start_time": "2022-07-11T16:31:46.497441",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Customers with Partner')"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#how many of the customers have a partner and how many dependents? \n",
    "\n",
    "colors = ['#264653', '#2a9d8f']\n",
    "plt.figure(figsize = (10,5))\n",
    "\n",
    "ax = ((cust['Partner'].value_counts()/len(cust['Partner']))*100).plot(kind = 'bar', color = colors)\n",
    "\n",
    "ax.set_ylabel('Customers in %')\n",
    "ax.set_xlabel('Partner')\n",
    "ax.set_title('Customers with Partner')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "e7b2599c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-11T16:31:46.745918Z",
     "iopub.status.busy": "2022-07-11T16:31:46.745116Z",
     "iopub.status.idle": "2022-07-11T16:31:46.937488Z",
     "shell.execute_reply": "2022-07-11T16:31:46.936339Z"
    },
    "papermill": {
     "duration": 0.214505,
     "end_time": "2022-07-11T16:31:46.939947",
     "exception": false,
     "start_time": "2022-07-11T16:31:46.725442",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Customers with Dependents')"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "colors = ['#264653', '#2a9d8f']\n",
    "plt.figure(figsize = (10,5))\n",
    "\n",
    "ax = ((cust['Dependents'].value_counts()/len(cust['Dependents']))*100).plot(kind = 'bar', color = colors)\n",
    "\n",
    "ax.set_ylabel('Customers in %')\n",
    "ax.set_xlabel('Dependents')\n",
    "ax.set_title('Customers with Dependents')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "16595816",
   "metadata": {
    "papermill": {
     "duration": 0.01757,
     "end_time": "2022-07-11T16:31:46.975880",
     "exception": false,
     "start_time": "2022-07-11T16:31:46.958310",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "#### Exploring the Contract Types"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "71437f59",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-11T16:31:47.014948Z",
     "iopub.status.busy": "2022-07-11T16:31:47.014521Z",
     "iopub.status.idle": "2022-07-11T16:31:47.367882Z",
     "shell.execute_reply": "2022-07-11T16:31:47.366938Z"
    },
    "papermill": {
     "duration": 0.375691,
     "end_time": "2022-07-11T16:31:47.370257",
     "exception": false,
     "start_time": "2022-07-11T16:31:46.994566",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, '# of Customers by their tenure')"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 720x360 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Distribution of tenure\n",
    "\n",
    "colors = ['#264653', '#2a9d8f']\n",
    "sns.set_palette(sns.color_palette(colors))\n",
    "plt.figure(figsize = (10,5))\n",
    "\n",
    "ax = sns.displot(cust[\"tenure\"], kde = False, bins = 30)\n",
    "plt.title('# of Customers by their tenure')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "db324b98",
   "metadata": {
    "papermill": {
     "duration": 0.018549,
     "end_time": "2022-07-11T16:31:47.407408",
     "exception": false,
     "start_time": "2022-07-11T16:31:47.388859",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "We can see that the highest number of customers have a short term tenure. Also a high number of customers has a long term tenure. \n",
    "\n",
    "This also complies with the distribution of the contract types. Most of the customers have a month-to-month contract or a two-year contract:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "06aab817",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-11T16:31:47.446584Z",
     "iopub.status.busy": "2022-07-11T16:31:47.445514Z",
     "iopub.status.idle": "2022-07-11T16:31:47.632508Z",
     "shell.execute_reply": "2022-07-11T16:31:47.631043Z"
    },
    "papermill": {
     "duration": 0.209331,
     "end_time": "2022-07-11T16:31:47.635211",
     "exception": false,
     "start_time": "2022-07-11T16:31:47.425880",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Contract', ylabel='count'>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#number of customers by contract type \n",
    "colors = ['#264653', '#2a9d8f', '#e9c46a', '#f4a261', '#e76f51']\n",
    "plt.figure(figsize = (10,5))\n",
    "sns.set_palette(sns.color_palette(colors))\n",
    "\n",
    "sns.countplot(data = cust, x = 'Contract')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "cc7cee48",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-11T16:31:47.675449Z",
     "iopub.status.busy": "2022-07-11T16:31:47.675012Z",
     "iopub.status.idle": "2022-07-11T16:31:48.284083Z",
     "shell.execute_reply": "2022-07-11T16:31:48.282661Z"
    },
    "papermill": {
     "duration": 0.632803,
     "end_time": "2022-07-11T16:31:48.286905",
     "exception": false,
     "start_time": "2022-07-11T16:31:47.654102",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x504 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Tenure by Contract Type\n",
    "\n",
    "fig, axs = plt.subplots(nrows = 1, ncols = 3, sharey = True, figsize=(20,7))\n",
    "\n",
    "cols = ['Month-to-month', 'One year', 'Two year']\n",
    "\n",
    "for i, col in enumerate(cols):\n",
    "    ax = sns.histplot(cust[cust['Contract'] == col]['tenure'], kde = False, bins = 30, ax = axs[i], color = colors[i])\n",
    "    ax.set_title('Contract: ' + col)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e53497eb",
   "metadata": {
    "papermill": {
     "duration": 0.019097,
     "end_time": "2022-07-11T16:31:48.325390",
     "exception": false,
     "start_time": "2022-07-11T16:31:48.306293",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "#### Which services are used by the most customers?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "482a880b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-11T16:31:48.366366Z",
     "iopub.status.busy": "2022-07-11T16:31:48.365762Z",
     "iopub.status.idle": "2022-07-11T16:31:49.900274Z",
     "shell.execute_reply": "2022-07-11T16:31:49.899116Z"
    },
    "papermill": {
     "duration": 1.557723,
     "end_time": "2022-07-11T16:31:49.902591",
     "exception": false,
     "start_time": "2022-07-11T16:31:48.344868",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x864 with 9 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# looking at the services used by the customers\n",
    "services = ['PhoneService','MultipleLines','InternetService','OnlineSecurity',\n",
    "           'OnlineBackup','DeviceProtection','TechSupport','StreamingTV','StreamingMovies']\n",
    "\n",
    "fig, axs = plt.subplots(nrows = 3,ncols = 3,figsize = (20,12))\n",
    "fig.tight_layout()\n",
    "\n",
    "left  = 0.125  # the left side of the subplots of the figure\n",
    "right = 0.9    # the right side of the subplots of the figure\n",
    "bottom = 0.1   # the bottom of the subplots of the figure\n",
    "top = 1        # the top of the subplots of the figure\n",
    "wspace = 0.3   # the amount of width reserved for blank space between subplots\n",
    "hspace = 0.4   # the amount of height reserved for white space between subplots\n",
    "\n",
    "plt.subplots_adjust(left, bottom, right, top, wspace, hspace)\n",
    "\n",
    "\n",
    "for i, service in enumerate(services):\n",
    "    if(i < 3):\n",
    "        ax = sns.countplot(data = cust, x = service, hue = 'SeniorCitizen', ax = axs[i,0])\n",
    "        ax.set_title(service)\n",
    "    elif(i >= 3 and i < 6):\n",
    "        ax = sns.countplot(data = cust, x = service, hue = 'SeniorCitizen', ax = axs[i-3,1])\n",
    "        ax.set_title(service)\n",
    "    elif(i < 9):\n",
    "        ax = sns.countplot(data = cust, x = service, hue = 'SeniorCitizen', ax = axs[i-6, 2])\n",
    "        ax.set_title(service)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "08064312",
   "metadata": {
    "papermill": {
     "duration": 0.020145,
     "end_time": "2022-07-11T16:31:49.944014",
     "exception": false,
     "start_time": "2022-07-11T16:31:49.923869",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "#### Inspecting the Churn Variable\n",
    "\n",
    "About 25% of the customers did churn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "d89948bb",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-11T16:31:49.986644Z",
     "iopub.status.busy": "2022-07-11T16:31:49.985928Z",
     "iopub.status.idle": "2022-07-11T16:31:50.167441Z",
     "shell.execute_reply": "2022-07-11T16:31:50.166307Z"
    },
    "papermill": {
     "duration": 0.206167,
     "end_time": "2022-07-11T16:31:50.170542",
     "exception": false,
     "start_time": "2022-07-11T16:31:49.964375",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Churn Rate')"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 720x360 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = ((cust['Churn'].value_counts()/len(cust['Churn']))*100).plot(kind = 'bar', color = colors)\n",
    "plt.figure(figsize = (10,5))\n",
    "\n",
    "ax.set_ylabel('Customers in %')\n",
    "ax.set_xlabel('Churn')\n",
    "ax.set_title('Churn Rate')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "30a7e0fa",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-11T16:31:50.213339Z",
     "iopub.status.busy": "2022-07-11T16:31:50.212953Z",
     "iopub.status.idle": "2022-07-11T16:31:50.427324Z",
     "shell.execute_reply": "2022-07-11T16:31:50.426134Z"
    },
    "papermill": {
     "duration": 0.238654,
     "end_time": "2022-07-11T16:31:50.429698",
     "exception": false,
     "start_time": "2022-07-11T16:31:50.191044",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Churn by Contract Type')"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Churn Rate by contract type\n",
    "\n",
    "ax = sns.countplot(data = cust, x = 'Contract', hue = 'Churn')\n",
    "\n",
    "ax.set_ylabel('Customers')\n",
    "ax.set_xlabel('Contract Type')\n",
    "ax.set_title('Churn by Contract Type')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f40772f7",
   "metadata": {
    "papermill": {
     "duration": 0.020955,
     "end_time": "2022-07-11T16:31:50.471767",
     "exception": false,
     "start_time": "2022-07-11T16:31:50.450812",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "As we saw at the beginning of the EDA, the contract Type is higly correlated with the probability of churn. Most churn customers purchased a short term month-to-month contract "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "7f0144a2",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-11T16:31:50.517269Z",
     "iopub.status.busy": "2022-07-11T16:31:50.516876Z",
     "iopub.status.idle": "2022-07-11T16:31:50.719164Z",
     "shell.execute_reply": "2022-07-11T16:31:50.718312Z"
    },
    "papermill": {
     "duration": 0.227849,
     "end_time": "2022-07-11T16:31:50.721425",
     "exception": false,
     "start_time": "2022-07-11T16:31:50.493576",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Churn by Seniority')"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Churn Rate by seniority\n",
    "\n",
    "ax = sns.countplot(data = cust, x = 'SeniorCitizen', hue = 'Churn')\n",
    "\n",
    "ax.set_ylabel('Customers')\n",
    "ax.set_xlabel('Seniority')\n",
    "ax.set_title('Churn by Seniority')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8b90e124",
   "metadata": {
    "papermill": {
     "duration": 0.021317,
     "end_time": "2022-07-11T16:31:50.764551",
     "exception": false,
     "start_time": "2022-07-11T16:31:50.743234",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "#### Looking at the Churn rate by charges\n",
    "\n",
    "Looks like the monthly charges are also an important factor for churn."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "501accc8",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-11T16:31:50.810033Z",
     "iopub.status.busy": "2022-07-11T16:31:50.809300Z",
     "iopub.status.idle": "2022-07-11T16:31:51.282225Z",
     "shell.execute_reply": "2022-07-11T16:31:51.281070Z"
    },
    "papermill": {
     "duration": 0.498694,
     "end_time": "2022-07-11T16:31:51.284768",
     "exception": false,
     "start_time": "2022-07-11T16:31:50.786074",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Churn by Total Charges')"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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1rW+ddfyFF17gT//0TwF4//vfz7PPPjvje73zne8EYOPGjRw/fnzS8y0WC+9617vOfG2z2bjhhhum1IZSSs11Os6fTYNzpVTB++QnP8ntt99OJBKZUTtr165lx44d4z5vt9uB5GA8MDAAJD9yHRoaOnPOyPJYDofjrPxDq9V6ZpX+yDaUUkpNTMf512hwPkt09fr58D99ka/edieRvr58d0epjKqsrOSP//iPuf32288cu/zyy7nrrrsA+PnPf85VV10FgNfrJRQKjdnOZz/7Wf7+7/+etrY2ABKJBLfddtuE925qauKVV15haGiIU6dOsXXr1ky8JKXS8sCR/dzy4C/53ssv5rsrSmWVjvOv0eB8lvjlw48R6Yvx7I6d3P/4M/nujlIZ93d/93d0db1WReDb3/42P/7xjzn//PO58847+eY3vwnAzTffzFe/+lUuuOACjhw5clYb119/PbfeeitvfOMbWbt2LRdeeCHBYHDC+15xxRUsXryYNWvW8IlPfIILL7ww8y9OqTEYY/j+K1tZWVHNT/e8TEt44v+rShU7HeeTxBiT1w7k06ZNm0wx1LuczNDQENd84K/4i5vfQW8wxLPbX+F///uL+e6WKnL79u1j9erVZ77OR4mt2Wj09xVARHYYYzblqUuzXrGO9Xu7Orj10c18+XVv5n/37mR1VS1/ecEl+e6WmkV0nM+emYz1WkpxFnjupV24HHaWLKynf2CAH927mbbObubXVOW7a2oWmasDrFL5ct+hPVxWt5ASES6vb+RHr+7gYxsu1h0dVdboOF8YNK1lFnhm28tcuG4VANbSUjatW81DTz+f516p6UoMDvDw0YP8zytbuWf/Lrr7ovnuklIqD544eYSLFjQAsLisgiFj2N/TmedeKaWyTYPzWeDVQ0dYXF935utVS5rYvntfHnukpmt/dydvvfcn/Hj3Do76u/nD8cNcf+9P+NaO50kMauUPpeaKYDxGIB5jvtsLJLc4X1ZRxZ6ujjz3TCmVbZrWUuSGhoY4eOwEH3r3H5051lg3n/uf0EWhxWZ/dycfevhXvHf1ei5OzZYB9Mb6+Omel9nW1sx333gjPrsjj71USuXCod5uFnrLKRmRwrLQW8arnW28e+W6PPZMKZVtOnNe5JrbOnA67Hjd7jPHFtRU0dXrJxzVkorFItrfz6eeeID3rDzvrMAcoMLh5K8vvIwqh4sPPnQv4UQ8T71USuXK/p5O6r2+s441lVWwu6s9Tz1SSuWKBudFbu+RYyyqX3DWsZKSEhYumMfBYyfy1Cs1Vd97+UXqPT4ur28c8/kSEd67+nzqPWV8/A+bSQwO5riHSqlc2t/dSb3n7OC80VfG8UCv/vwrNctpcF7k9hw6wsL58845vnD+PPYdPZ77Dqkp6+qLcO/BV3nXirUTnicivG/NegyGL7/4ZG46l2dtbW3cfPPNLF26lI0bN3L99dfzgx/84MzWyUrNVvt7OlnoLTvrmN1SSq3bw+He7jz1Sqns0LH+bJpzXuR2HzzKxeevOed4w/xa9hw6moceqan64c5tXLqgkUqna9JzS0T40Hmb+PKLT3Lfwd28c0Xuck+vvfs22iLhjLU33+3hsT/58LjPG2N4xzvewS233HJmh7idO3eyefPmGd13YGCA0lId+lThGhwa4migh4ZRwTnAIl85u7vaWVNdm4eeqdku1+M86Fg/luLstTrj+OkW3v7G159zfFHdfH71yBN56JGaimh/P785tJd/u+LatK9xWq18bMMlfHXr05xfs4BlFbmpZ98WCfPjt74rY+39n4d+NeHzTzzxBFarlY997GNnjq1fv57e3l4ee+wx3v3ud7N79242btzIz372M0SEpqYmtm/fTnV1Ndu3b+fTn/40Tz75JJ///Oc5cuQIR48epbGxkZUrV3Ly5EmOHj3KyZMn+eQnP8knPvGJjL02pWaiORzEa7XjslrPea7O49WZc5U1uR7nQcf6sWhaSxEbGByks8dPVcW5syt1tTWcaGllLu8AWwz+cPwQyyuq0po1H6ne6+NdK9bxt48/QHxgdpZYHB6Mx/Lyyy/zjW98g71793L06FGee+65Sdvbu3cvjz76KL/4xS8A2L9/P4888ghbt27l3/7t3+jv789o/5WartOhAPPcnjGfm+fycDzYk+MeKZU9OtafS4PzItbW2U25z4N1jI9t3C4nIoI/lLmPp1Tm3XtgN5fXL5rWtVc2LKLG5eJr2+Ze2cyLL76YhoYGSkpK2LBhA8ePH5/0mhtvvBGn03nm67e97W3Y7Xaqq6upra2lvV2rYKjC0BIOUelwjvncfLeH4wF/bjukVJ7M1bFeg/MidqqtndrKynGfn1ddxanWwv9POFe1hIMc9nezoXbB5CePQUR4/9oL+P3xQzx3evZV5lm7di07duwY8zm73X7mscViYSD16UFpaSlDQ0MAxGKxs65xjyg3OlEbSuVbSzhIxTjBeY3LQ0c0Qv+QVmxRs4OO9efS4LyINbd1UF1RPu7z1RXlNLfpbnKF6omTR1lfu4DSkun/GLqtNv7Puo3809O/xx+bXXXtr7nmGuLxOD/4wQ/OHNu1axfPPDP+JwVNTU1nBvlf/WryXEelClFzKEDVOKlupSUlVDqctISCOe6VUtmhY/25NDgvYs2t7VSW+8Z9vrqijOY2nTkvVI+dOMz5NfNn3M6a6lo2zq/nn5/9w6xaYyAi/PrXv+bRRx9l6dKlrF27ls9+9rPMnz/+9+xf//Vf+Zu/+Rs2bdqExWLJYW+VypzT4eC4wTkkU1tOBP2565BSWaRj/bkkm2/mInId8E3AAtxmjPmPUc/bgZ8CG4Fu4E+MMcdFpAq4F7gI+Ikx5tbU+V5g5K9SDcDPjDGfFJEPAl8FTqee+44x5raJ+rdp0yazffv2Gb7K/PnbL/83C+fP44qN68d8/vEXthGK9vHlT/1VjnumJhNOxHnDXbfxX2+4HkcGSj31Dw7y5Ref5IPrNvKeVedloIewb98+Vq9efebrfJTYmo1Gf18BRGSHMWZTnro06xXbWH/NXbfxqU1XUDvOotCf732FTfMbeP/aC3LcMzXb6DifPTMZ67NWSlFELMB3gTcBzcA2EdlsjNk74rQPAb3GmGUicjPwFeBPgBjwL8C61B8AjDEhYMOIe+wA7hvR3t3DgfxccKq1gwvWrBz3+erKCvYeOZbDHql0PXf6JMsrqjISmANYLRY+sv4i/nPL01wwry4r5RXn6gCrVC4NDA3RHYuOm3MOUONycyygFVtU5uk4XxiymdZyMXDYGHPUGJMA7gJuGnXOTcAdqcf3AteKiBhjIsaYZ0kG6WMSkRVALWfPpM8pp9s7qKmsGPf52soKzTkvUC+0nGB1VWY3Eanz+Hj3yvP45OO/I9KfyGjbSqnc6IiG8dnsWCf4qH6+26sVW5SaxbIZnNcDp0Z83Zw6NuY5xpgBIACkO+V3M8mZ8pF5Oe8SkV0icq+ILJxet4tDXyxOONpHuXfsjz0hmXPe2eOnvwhWJs81W1ubWVlZnfF2r6hvpNFbzj8+/cisyj9Xaq5oDYeodronPKfW5aY5FMhRj5RSuVbMC0JvBn4x4uv7gSZjzPnAH3htRv4sIvJREdkuIts7Oztz0M3saO3sorqijJIJKn2UlpZS7vPS2tGVw56pyXT1Rejui9LoK8942yLC+9as53jAz3dffnHG7WmAn1n6/VSTaY2EJlwMClDpcNERjTCk/59UBui4lHkz/Z5mMzg/DYycvW7gtcWa55wjIqVAGcmFoRMSkfVAqTHmTGFMY0y3MSae+vI2kotMz2GM+YExZpMxZlNNTU26r6XgdPb0UuEbv1LLsOqKclo7NTgvJNtbT7OispoSkay0b7VYuPXCS/nVwd3cd3D3tNtxOBx0d3frwJ0hxhi6u7txOBz57ooqYMka5xP/H7FZLLitVrr7ojnqlZqtdJzPvEyM9VlbEApsA5aLyGKSQfjNwJ+OOmczcAvwAvBu4HGT3v+Q93L2rDkissAY05r68kZg3wz6XvA6unsp942f0jKswuelvVsXDhWSLW2nWFae+QWbI5XZHXxy4xV8bdsz2Cyl3LB01ZTbaGhooLm5mWL+hKnQOBwOGhoa8t0NVcDaI2HK7JO/qVc5XbSGg9S4Jk6BUWoiOs5nx0zH+qwF58aYARG5FXiEZCnFHxlj9ojIF4DtxpjNwO3AnSJyGOghGcADICLHAR9gE5G3A28eUenlj4HrR93yEyJyIzCQauuD2XpthaCjuwefZ/JBuczrob1Lg/NC8nJ7C3+yMjPlDieywOPlbzddwVe2PEUgFuN9azdM6Xqr1crixYuz0zml1Ji6+iJp/fJe5XTRGglxPtPbYVgp0HG+UGVz5hxjzIPAg6OOfW7E4xjwnnGubZqg3SVjHPss8Nnp9rXYtHf3UDbBYtBh5T4PbZ2TZgqpHOkb6Odk0J+VfPOxNHjL+Owlr+cbO55nX08H/3zZNRkr36iUyryuaJSN80bXTjhXhd1JSziUgx4ppXKtmBeEzmntXT2Ue72Tnlfh82nOeQHZ391Jg7dswjJpmVbtcvNPl11NeyTMTff9lBdOn8zZvZVSU9Mdi+Kz2yc9r9Lp5HQ4mIMeKaVyTYPzItXR00u5L43gvExzzgvJ7q52FvnGr02fLc5SKx9ZfxHvXLGWf3rm93zk4fvY2dE6+YVKqZzqiUXTyzl3uDit5RSVmpX08+0i1dmT3oLQyjIfHd29OeiRSscrHa00lZXn7f4XzKvjvJr5PHPqOJ98/Hcs9JbzsQ0Xc1ldI5Kl6jFKqfTEBgZIDA7iKrVOeu5wzrlSavbR4LxIdfX6qUhj5rzc56XHH2BoaGjCmugqN3Z3tXNFfWNe+1BaUsIbFi3hqoVNbG09xeefe4wal5t/vuwNGd+1VCmVvu6+CGV2R1q/KFc5XbRFwjnolVIq1zRaK0LhaB9myOBIIy/RWlqK2+mgJ6C5ifkWSsTpikao80xenz4XSktKuLx+EV+48o1cUFvHhx++j+++/KJubKJUnnT1RSm3O9M612O1kRgcJNKfyHKvlFK5psF5Eero7qGy3Jd2GkJleZmWUywAh3q7Wegty9rmQ9NVIsLrFjbxr5dfw+MnjvCpxx9gYGgo391Sas7p7ksv3xySuwFXO120asUWpWYdDc6LUGeai0GHVZT5dFFoATjY00m9tzBmzcdS7nDyqU1X0BmN8JmnHtYd45TKsa6+CF6bLe3zKxxOOqKa2qLUbKPBeRHq6O5Nq4zisHKvh/YurXWeb/t7OqkvkJSW8VgtFv7ygks42NvFHXteynd3lJpTuvqieG2TpysOK7c7aNfgXKlZR4PzItTV609rd9BhuktoYRiucV7obBYLH1t/MT/cuY193R357o5Sc0ZHNJJWjfNhZXYHHZFIFnuklMoHDc6LUFevH6/blfb55V4PHZrWkldDxnDE31MUwTkkNy56+/I1/H/PP67pLUrlSFdfhDJbejnnAOUOh5ZTVGoW0uC8CE01OPd5PXT2+rPXITWplnAQl9WKZwr5pPl2VUMToUScB48eyHdXlJoTuqKRtBeEAlTYnbRrOUWlZh0NzotQtz+AdyppLR433b26k1w+HeztYmGRzJoPKxHhXSvW8R0tr6hUTvTE+qaUc64LQpWanTQ4L0I9geCUc867/Rqc59OR3h7mu9NfxFsoVlfVUColPHHySL67otSsF0zEplytpTOqOedKzTYanBeh3kAQ31TSWjxuegJBzR3OoyP+bua7PfnuxpSJCNctXs5tu7bnuyuqgInIdSJyQEQOi8hnxnjeLiJ3p57fIiJNI577bOr4ARF5yxTa/JaIzJpp44GhISL9/bis6QfnPpudQDym+xIoNctocF6EeoMhvO70Z87tNhsWSwnhaDSLvVITOeLvYYGn+GbOAS6cV0dzKMDhXi3Hqc4lIhbgu8BbgTXAe0VkzajTPgT0GmOWAV8HvpK6dg1wM7AWuA74nohYJmtTRDYBFVl9YTkWjMfwWG1T2qTMUlKCz26nq09nz5WaTTQ4LzLxRIKBgUGcjvTzEgHKvV66NO88L4wxnAj2sqAI01ogGQBcXreI+w7uyXdXVGG6GDhsjDlqjEkAdwE3jTrnJuCO1ON7gWslucXxTcBdxpi4MeYYcDjV3rhtpgL3rwL/kOXXlVO98diU8s2HVTicdOiiUKVmFQ3Oi0yPP4jP60amuAV8uc9Dt1ZsyYuuviilJRY803jjLRRXNDSy+cg++ocG890VVXjqgVMjvm5OHRvzHGPMABAAqia4dqI2bwU2G2NaM9T/guCf4mLQYRUOJ+2ad67UrKLBeZHpDgSmtBh0mM/jpksXhebF0UAPdUWa0jJsvttLtdPFlpZTk5+sVJaISB3wHuDbaZz7URHZLiLbOzs7s9+5GfLH+6ZVarXM7tCKLUrNMhqcF5kefxDfFPLNh3ndbp05z5Oj/h7mu4o7OAe4oLaOR08cznc3VOE5DSwc8XVD6tiY54hIKVAGdE9w7XjHLwCWAYdF5DjgEpEx/1MaY35gjNlkjNlUU1MzvVeWQ72xGO4pLAYdVmZzaK1zpWYZDc6LTE8gOKXFoMO8bhedPf7Md0hN6oi/h3lFWKlltAvmLeDxE0e15rkabRuwXEQWi4iN5ALPzaPO2Qzcknr8buBxkywftRm4OVXNZTGwHNg6XpvGmAeMMfONMU3GmCYgmlpkWvT88T7cVuuUr9OZc6VmHw3Oi0xvIIjH5ZzydWUeNx09vVnokZrMsVkSnM93e3FZrezqnFWpvmqGUjnktwKPAPuAe4wxe0TkCyJyY+q024Gq1Cz3p4DPpK7dA9wD7AUeBj5ujBkcr81cvq5c6+nrm9bMebnDQYfmnCs1q5TmuwNqarp6/XjcUw/OfV4Px05rUJUPp0IBbnStznc3MmJD7QKeOHmUDbV1+e6KKiDGmAeBB0cd+9yIxzGSueJjXfsl4EvptDnGOcX/W29Kb6yPKufUx/Zyu0NLKSo1y+jMeZHp9gemlXNe5vXQpTnnOdc/NEhHNEyNa+r/ZoVobXUtzzafyHc3lJp1euN906rolAzOdQ8LpWYTDc6LTLc/gHea1Vp6/MEs9EhNpCUcotLhorRkdvyoLS2v4mTQjz/Wl++uKDWrJEspTj2txWOzE0kkSAxqmVOlZovZETHMIclqLa4pX+dzu+gNhrLQIzWRk0H/rMg3H1ZaUsLKyhq2tDbnuytKzSr+1A6hU1UiQplDU1uUmk00OC8ygVAYj2vqwbnDbmdwcJBYPJ6FXqnxnAz6qXHOjpSWYasqq3nu9PF8d0OpWSUQj017o7IKu4MuXRSq1KyhwXmRCYTD01oQKiL4vG56AprakksnAn5qpvHLVCFbXVXLi7oZkVIZMzg0RLg/Ma1qLQBldiedOnOu1KyhwXkRGRwcJBztwz2NFf0AZR6PBuc5djzYS61r9qS1ANR7ffjjffoxulIZEkzEcVttlIhM63qf3U6nzpwrNWtocF5EgpEoLoedkmkuLvS6XbooNMdOBf2zLjgvEWF5RTWvtGtpTqUywR/vwzvNWXMAn02Dc6VmEw3Oi0ggFJ7W7qDDvG6Xzpzn0ODQEK2R2VNGcaQlZZXsaB+9Q7tSajoC8RjuaVRqGVZmd9Cmu4QqNWtocF5E/MHQtPLNh3lcLno1OM+ZjmgEr82GzWLJd1cybnlFFTvaNDhXKhOC8fi0880huSC0U4NzpWYNDc6LiD8YmlallmEel5NufyCDPVITOR0OzMpZc4DF5RUc9vfQN9Cf764oVfSCiTiuUuu0ry9zOOmM6kZESs0WWQ3OReQ6ETkgIodF5DNjPG8XkbtTz28RkabU8SoReUJEwiLynVHXPJlq85XUn9qJ2ppNksH59GfOvW4X3b0anOdKcyhI9SwrozjMbiml3uPjQE9nvruiVNELxGM4rTMIzm12unWXUKVmjawF5yJiAb4LvBVYA7xXRNaMOu1DQK8xZhnwdeArqeMx4F+AT4/T/PuMMRtSfzomaWvW8IdCuJyOaV/v9bjpDmhwnivNoQCVjun/MlXoFpWVs6erY/ITlVITCsRjM5o599kd+ON9DA4NZbBXSql8yebM+cXAYWPMUWNMArgLuGnUOTcBd6Qe3wtcKyJijIkYY54lGaSna8y2pt/9wuMPhnE7ZhCca7WWnGoOBah2zq4a5yMt8pWzq0Mrtig1U4F4DPcMZs5LS0pwW230xvsy2CulVL5kMzivB0buVNKcOjbmOcaYASAAVKXR9o9TKS3/MiIAn25bRaMnEMTjnn6w53O76Q1qcJ4rp0IBqmdpzjlAk6+CV7va890NpYpeIB7DNYMFoQDlDiddmneu1KxQjAtC32eMOQ+4KvXn/VO5WEQ+KiLbRWR7Z2dx5cv2BoIzyzn3uPAHQxnskZpISzhIzSzNOYfkZkRtkRCR/kS+u6JUUZvpzDlAud2hu4QqNUtkMzg/DSwc8XVD6tiY54hIKVAGdE/UqDHmdOrvEPC/JNNn0m7LGPMDY8wmY8ymmpqaKb6k/PKHZlatxeVw0BePk+jXChvZlhgcpDfWN6tzzktLSmj0lbOvW/POlZqJZM75zGbOfTa77tqr1CyRzeB8G7BcRBaLiA24Gdg86pzNwC2px+8GHjfGmPEaFJFSEalOPbYCNwC7p9NWMfIHw7hnMHNeUlKSSm3R2fNsa42EqHC4sExzN9di0ejTRaFKzVQwMbM65wA+u13TWpSaJUqz1bAxZkBEbgUeASzAj4wxe0TkC8B2Y8xm4HbgThE5DPSQDOABEJHjgA+wicjbgTcDJ4BHUoG5BXgU+GHqknHbmi0C4fCM0loAfB4Pvf4g86oqM9QrNZaWUJDaWZxvPqzB42O/zpwrNSOhRHzGaS0+m4MO3YhIqVkha8E5gDHmQeDBUcc+N+JxDHjPONc2jdPsxnHOH7et2SIQisworQXA63bqotAcaIkEZ3VKy7CF3jJeaDk1+YlKqXGFMjBzXmZ3cNTfk6EeKaXyaXZ/5j6LJBL9DAwM4LDPbAD3uN30BnV2JdtawkEq5kBw3uAt40SwlwGtr6zUtMQHBhgcMtgslhm1owtClZo9NDgvEr2hEF63i5mWbnc7HTpzngOnQ0EqHbO3xvkwe2kpVQ4XxwO9+e6KUkUpmIjjsdlmPLaX2e106S6hSs0KGpwXiWAoMqMa58PcLie9AV0Qmm0t4SBVztk/cw7Q4CvjQE9xlSVVqlAkyyjO7BNRSKa19GhwrtSsoMF5kQiEw7gzEOx5XE56AoEM9EhNpC0SpmoW7w46Ur3Hx34NzpWalmAijicDwbmz1MrA0BBRLZWrVNHT4LxIBEIzK6M4zOt20RvQtJZsGjKGjmhkTqS1QHJR6P5uDc6Vmo5M7A4KICKUO5yad67ULKDBeZEIhiO4HI4Zt+N1u+jR4DyruvuiuK3WGS/wKhb1Hh9HtEqEUtMSjMdwzbCM4rAKu4NuTW1RquhpcF4kAqEwLqd9xu14XC7NOc+y1nBwzqS0AFS73PjjfUT6E/nuilJFJ5iI4yzNTHDuszvojOrMuVLFToPzIhEIh3HaZx6ce90uAiEtpZhNLeHQnArOS0So8/g4phVblJqyYDyGK1PBuc1Ol6a1KFX0NDgvEv5AaMa7g0Jy5tyvwXlWtUZCVNjnRqWWYXVuL4d7u/PdDaWKTjARx2XNzH6APrudLp05V6roaXBeJPyhzFRrcdhtDA4OEovHM9ArNZbT4bmxO+hI8zQ4V2paAvEYztKZLwiFZDnF9qhOvihV7DQ4LxKBcBiXc+YLQkUEr9uFX3cJzZqWcJDKOZTWAlDn8XKotyvf3VCq6CRnzjOT1lJmd2hai1KzgAbnRSKYoVKKAD6PG39QF4VmS1skNOdmzus8Po4GtGKLUlMVynBw3hnVai1KFTsNzotEIBzJSFoLgMftojeo5RSzpSMSnnPBea3LTVc0SmxgIN9dUaqohBLxjC0ILbPZtZSiUrOABudFIhSO4HbNPK0FwKvlFLMmMThAuD+Bz56Zf6tiYSkpodbt4URQK7YoNRWZnDn32R34430MDg1lpD2lVH5ocF4EjDGEItGMzZy7XU56QxqcZ0N7JEKFw0mJSL67knML3B6OB/z57oZSRSXSn8CVoQWhpSUluK02euN9GWlPKZUfGpwXgb54HIulBGtpZsptuZ0OenWX0KxI5pvPrcWgw2pdHo5rrXOl0jZkDJFEP84Mje0AFQ4nXZp3rlRR0+C8CASCYTzuzAV8bpeTHg3Os2IuLgYdVuvycNSv5RSVSle0P4G91IKlJHNvxWV2B51asUWpoqbBeREIhMN4Mliaz+t26cx5lrRFwpQ75la++bAFHg9HdeZcqbQFE3Hc1syktAzTXUKVKn4anBeBYAYXg0Jyl1BdEJodLZHgnNsddNg8l5eTQT/GmHx3RamiEMpGcK67hCpV9DQ4LwLBcCQjGxAN87ic+HVBaFa0hkNUZmjhbrHx2pJBRm9MF6MplY5MllEcVmZz0K7BuVJFTYPzIuAPhTJWqQWSdc4DId0hNBvaI2Eq5uiCUBGhzuPjmKa2KJWWUCKBM0NlFIeVORx0RHR8V6qYaXBeBELhKE67PWPteVxO/EEdvLOhIzr3NiAaaZ7bw4mgP9/dUKooZGPmvFwXhCpV9DQ4LwKBUBiXI3PBucvhIN6fINHfn7E2FcQHBoj0J/DaMvdvVWyqnS5OanCuVFpCiTjOTKe12B26IFSpIqfBeREIhMK4XJmbjRURvG63prZkWEd07m5ANExrnSuVvmAijiODNc4Byu1OuvuiujBbqSKmwXkR8IfCuDNcns/rdmlqS4Z1RMNUzOGUFoBal1tnzpVKUzAey/jMuaO0lBIRwv2JjLarlModDc6LQKartQB4XS6t2JJhbZHQnA/O57k9NIcDOmunVBoC8RiuDC8IBaiwO+nUii1KFS0NzotAMBzOeHDudjnxBzU4z6SOaIQy29zcgGiY22pDEC2nqFQaQolExheEApQ7nLooVKkipsF5EQhForizEJzrLqGZ1RoOUTFHdwcdab7by8mQP9/dUKrgBRPZmTkvszt05lypIqbBeRFIprVkNl3C43Ti1wWhGdUWCVE+x9NaYDjvPJDvbihV8LJRrQXAZ9NdQpUqZhqcF4FwNBsz5w56dOY8o9qiYSrsGpxXO92cCGrFFqUmE04ksjRzbqc9qpMvShUrDc4LXCLRz+DgELYMD+Ael0vTWjKsc45vQDSs1u3mmF+Dc6UmE+7PTs55md1Jh86cK1W0NDgvcMFIBLfLiWS4drbH5aRXF4RmzODQED2xPk1rAWqcbprD+oufUhMxxhDpT2QlraXc7qBTZ86VKloanBe4YDiCO8P55gAet86cZ1JPrA+P1UZpif5I1bjctIQ051ypicQHBxEEq8WS8bbLHQ46+6IZb1cplRtZjSRE5DoROSAih0XkM2M8bxeRu1PPbxGRptTxKhF5QkTCIvKdEee7ROQBEdkvIntE5D9GPPdBEekUkVdSfz6czdeWK8FwBLcr8xVAPC5dEJpJbZGQprSklNkdRPr7iegmKEqNK5SI485CvjkkdwnVBaFKFa+sBeciYgG+C7wVWAO8V0TWjDrtQ0CvMWYZ8HXgK6njMeBfgE+P0fTXjDGrgAuAK0TkrSOeu9sYsyH157YMvpy8CYYjuLMQ9HndLgIanGdMZzSiKS0pJSLUuj2cDuknM0qNJ9wfz0q+OYCztJTBVNqMUqr4ZHPm/GLgsDHmqDEmAdwF3DTqnJuAO1KP7wWuFRExxkSMMc+SDNLPMMZEjTFPpB4ngJeAhiy+hrzLxu6gAG6nk3A0ytDQUMbbnovao2HK7VrjfFity01zWFNblBpPKEuVWgBEhEqH7hKqVLHKZnBeD5wa8XVz6tiY5xhjBoAAUJVO4yJSDvwR8NiIw+8SkV0icq+ILBznuo+KyHYR2d7Z2ZnWC8mnYDiC02HPeLsWiwWHzU4oonmJmdAeCeOb47uDjlTlcNGseedKjSuciOOy2rLWfoXDqeUUlSpSRbl6TURKgV8A3zLGHE0dvh9oMsacD/yB12bkz2KM+YExZpMxZlNNTU1uOjwDwXA4K8E5gNfj0ootGdIW0d1BR6p2unQjIqUmEErEcZSWZq193SVUqeKVzeD8NDBy9rohdWzMc1IBdxnQnUbbPwAOGWO+MXzAGNNtjImnvrwN2Di9bheWQDiCK0tBn9ftwq/BeUa0R8NUaM75GdUuNyeD/nx3Q6mCFUpkp4zisHK7gw6dOVeqKGUzON8GLBeRxSJiA24GNo86ZzNwS+rxu4HHjTFmokZF5Iskg/hPjjq+YMSXNwL7pt/1whEIhrKScw7JjYg0OM+MjoguCB2pxuXWtJY5ZLqVuVLPfTZ1/ICIvGWyNkXkdhHZOSKF0ZP1F5gF4UQchyWbM+d22iManCtVjLIWnKdyyG8FHiEZKN9jjNkjIl8QkRtTp90OVInIYeBTwMgB+Djw38AHRaRZRNaISAPwTySrv7w0qmTiJ1LlFXcCnwA+mK3XlkuBcAR31oJzpwbnGdLZF6HCrsH5sBqnm9ZIiEl+11azwEwqc6XOuxlYC1wHfE9ELJO0+bfGmPWpFMaTJN9nik6201rK7U7aIjq+K1WMsjcyAMaYB4EHRx373IjHMeA941zbNE6zY26VaYz5LPDZaXW0gAXD4azNnLudTvwhHbxnKtrfT//gYNZqFhcjR2kpDkspXX1RalzufHdHZdeZylwAIjJcmWvviHNuAj6fenwv8B1Jbnt8E3BXKiXxWGqi5uLUeWO2aYwJpo4J4ASK8jfAYCJ7pRQhuRFRh+acK1WUinJB6FwSDEezlnPucjro0V1CZ6wzGqbS6SQZK6hhtS4PLWH9/zUHzKQy13jXTtimiPwYaANWAd8eq1OFXpkrlIjjzOIv9OV2LaWoVLHS4LzAhSIR3M7spEt43S56/Bo8zZQuBh1bldPFaQ3OVRYYY/4PUEcyZfJPxjmnoCtzBRPx7C4IdTjo6otqaplSRUiD8wIXjkSzuCDUqaUUM6AjGqFc883PUeV06i6hc8NMKnONd+2kbRpjBklubveuGb+CPEjWOc9ecG63lGK3WAjEY5OfrJQqKBqcFzBjDKFoH64s1TnXai2Z0aG7g46pyuHilFZsmQtmUplrM3BzqprLYmA5sHW8NiVpGZzJOb8R2J/l15cV4UQiqznnAJW6EZFSRSmrC0LVzERjMWylpZRmaUW/x60z55nQFg5TZs/OL1DFrMrp4lDLqclPVEXNGDMgIsOVuSzAj4YrcwHbjTGbSVbmujO14LOHZLBN6rx7SC4eHQA+npoRZ5w2S4A7RMRHsjjATuAvc/l6MyXUn920FkjuEtoRCbOysvDSepRS49PgvICFwlHcruylS3hdLgIhnVWZqfZoiGUVVfnuRsGpdro153yOmGFlri8BX0qzzSHgigx0Oe/CWd6ECKDc4aRNZ86VKjqa1lLAgpHs1TgH8LhdBMJhXTA0Q+2RsNY4H0O1y0V7NMyQ/v9S6izGGCL9iazmnENyl1Ctda5U8dHgvIAFwxFcWarUAmCzWikRoS8ez9o95oLOvgjlWSp3WczsllJcpVa6+6L57opSBSU2OIBFSigtye5bcIXDSWtYg3Olio2mtRSwUBZ3Bx3mdbvxB0NZq6U+2xlj6O7r02ot46hxuWkOBXQjIqVGCCdmNmt+4NhJHnr6eSwlJdz8tjdTU1k+5nnldgf7uguvxrtSamI6c17AgpEoziwHzT6Pm96AzqxMV2+sD0dpKTaLJd9dKUiVDpduRKTUKKFEHJfVNq1rDx4/yTd+8gtqK8txOux8/ts/4MTp1jHPrXS46NCcc6WKjgbnBSwYDuPMUhnFYR6XU8spzkBHNKIbEE2g0uGkRT9WV+os4UR8WmUUB4eG+P4v7uO6qy7lgjUrueLC87n64o189+f3MtA/eM75FQ4nHbpLqFJFR4PzAhYMR3IQnLu0nOIMdER1MehEKp1OToe11rlSI4X6p1epZevOPbicDlYsbjxzbO3yJZT7vPz60SfPOd9ttTIwNEikPzGT7iqlckyD8wIWCIWztgHRMLfOnM9IRzRCeZb/jYpZtcOlu4QqNUo4EcdpndqSL2Pgt48/zaXr1511XASuvWwTj72wjVAkOuo5ocrhoj2iqS1KFRMNzgtYMBzJ+kJNt9NBT0CDp+lqj4Tw2XQx7XiqnG5Na1FqlNA0apyfam2jry/GkoX15zzn87hZtWQRDz39/DnPVTidGpwrVWQ0OC9ggXAEV5artXjcLnoCmnYwXe3RMOX27AfnxkAo0kdrZzdtXT1Eon0UQ/nwKqeLtmhIa+krNUI4EcdhmdrM+Y49+1nWtBCRsZ+/ZP06Hn9hO32xs1NYKuxO2nVRqFJFRUspFrBkKcXs5jN7XE6ON4+90l9Nri0SZuO8uqy0HU/0s3XXHra+upfDx08xMDh45v9DJNpHqaWExY31XLh6JRevX4vPU3jlCl1WKxYRAvEY5bpwVikgWa3FUTq1t9/tu/dz1cb14z5f7vPQWDef51/eybWXXXTmeJndQatuRKRUUdHgvIAFczBz7nW7NK1lBjqi4YwHnfFEPw89/TyPPPMidfNqWLW4kSsvXI/P4zrrvFA4SnN7By/tO8g9Dz/KeSuWceO1r2NR3fyM9memalKpLRqcK5UUnGK1lh5/kK7eXhbOr53wvA2rl/Po81u55tKLzsywVzqctOi6D6WKigbnBSwUiWY/ONdqLTPSFY1QkcG0lj2HjvKDe37D/Ooq3nfjW6gqLxv3XK/HxWpPE6uXNhFPXMQr+w7xnz/8KWuXLeG9f/QWKnzejPVrJqpdblrCQdZUTxxYKDVXhBLxKW3M9eqhwyxpqKfEMnEm6qK6Bfw+vpXDJ06xvGkhkEwtO9R7akb9VUrlluacF7BwNJr1BaEet4tASPMRpyMxOEgokcCXgeB8aGiIXz70GP/vf3/Fmy6/mLe/8XUTBuaj2W02Llm/lo/+8duxWEr4x//6Hk++uKMg8tIr7E5aIjpzp9SwYCI+pQWhB4+epH5ezaTnlZQI561YytPbXz5zrNLp0rQWpYqMBucFyhhDONqX9VKKXreLQEgH7uno6otQ7nBQMt4KrTQl+vv55h13s+vAIT74zrextPHcagzpstmsvO6iC3jvDW/mgaef41t33kVfLD6j/s1UpdOp5RSVGmGqmxAdPHGShklSWoatXbaYbbv20t8/AECVw0VHNKKLspUqIhqcF6hIXwy71Yoly9vC26xWjCHvAVwxao+EZ7w7aCye4D9/eCeJ/n7+5Po34nZlJi+7prKc9990PWbI8Llv/Q/tXT0ZaXc6qhwuToc1OFdqWDiRwGlNLzgPR/rwB8LUVJSndX6Z18O86kpe3ncQSC7KFpKz9Uqp4pBWcC4i94nI20REg/kcCYbDGQvUJiIieD0u3YhoGjqiEcpnsDtoPNHPV2//GU6ngxvecGXGfxGzllp4y1WXsmHVCr7w3ds5evJ0RttPV5XTRavWOi8KOtbnRrg/gTPNai1HTjZTP79m0nzzkdYsW8wzI1Jbql1u/RlUqoik+9P+PeBPgUMi8h8isjKLfVIkK7V4chCcA/jcbnqDOrM5VR0zqHE+ODTEd352D3ableuuvJSSkpmlxkzkwrUrecuVl/DV23/G/iPHs3af8VQ5XbRpzmux0LE+B5LBeXoz5wdPnGRBTfWU2l/R1MiBoyeI9sWA5KdXmneuVPFIKzg3xjxqjHkfcCFwHHhURJ4Xkf8jIlPb5kylJReVWoZ5XC78QV0UOlXtkTBl0wzO7/zNg4QjUa5/3eVZDcyHLW9ayI3XXMU3f3o3+4+eyPr9RvLa7ET6+4kNDOT0vmrqdKzPPmMMkf5E2jnnR040s6Cmakr3cNhtLKpfwPbd+wCocDh15lypIpL252QiUgV8EPgw8DLwTZID+B+y0rM5LhiOZL1SyzCP26kz59PQGglRMY1/o8de2MauA4e58drXYZnCR9Uz1dSwgD+65kq+ecddHD2VuxSXEhGdPS8iOtZnV3xwEAGsaaaxNbd1MK+6csr3Wb1kEc+9tAuACoeDFl33oVTRSDfn/NfAM4AL+CNjzI3GmLuNMX8NeLLZwbkqFI7gzFVw7nLRG9DAaaqSaS1TSz06fKKZex9+nHe9+Q047LYs9Wx8ixvquO6qS/mvH/0vrZ3dObtvteadFwUd67MvlIjjsqb3sx8KR0gM9ON1T33332WLFnL01GlC4QhVDpcG50oVkXSn7X5ojFljjPl3Y0wrgIjYAYwxm7LWuzksEI7gzHIZxWFup0N3CZ2GjmhkSjPn4Ugf377zbq676lIqy31Z7NnEVixu5KqN6/nqbT8lFI7k5J6VDq11XiR0rM+ycH/6ZRRPtnUwr6qS6VRrtVpLWdpYz/bd+6lyanCuVDFJNzj/4hjHXshkR9TZQpFI1mucD/O4XfQEAjm512xhjKErGkl7S3pj4LZf/oZlTQtZsbgxy72b3PrVy1m5eBH//eP/ZaB/MOv3K7c7NTgoDjrWZ1kokcCVZhnFUy1tVFdWTPteKxcv4oVXXk1WTNK0MqWKxoTBuYjMF5GNgFNELhCRC1N/rib5safKEn8onLOcc6/LRXevBudTEUrEEZG0Ky48tWUHLR1dXH3xhVnuWfqu3LgBm83K7b/anPWdRKucTlp0I6KCpWN97oSnsDvoiZY2airS3yl4tKWNDRxvbsEyMEQgHiMxqIuylSoGkxVafQvJhUENwH+POB4C/jFLfVJAMBSmZgYzJlPh9bjo1TrnU9IRjVCV5qx5R08vdz/0KO+94c2UZnlTqakoKRHe9voruHPzQ/zhuS28+cpLsnavKqeLV7vas9a+mjEd63MklEi/jOLJ1nbeMINf6K2lFpY2NrBj974z+w0sKsvN+4pSavomDM6NMXcAd4jIu4wxv8pRnxQQCIVZVL8gJ/fyul2acz5F7dH0dgc1Q4Yf3v0bLl6/lprK8ux3bIqs1lLe8caruXPzQzTWzWfVkkVZuU+lQxeEFjId63Mn3B9PawOioaEh2jo7qZ7huLFicSNbdu6heuMymsNBDc6VKgKTpbX8Wephk4h8avSfHPRvzgpGorlLa3G7dYfQKWqPpBecP75lB+FolIvPW5ODXk1PRZmXt73+Cr7zs19mrd59pdNJRzTCULbzZ9S06FifO+FEAkcaM+dd/gBOhxO7bWbl5YdTW3ylVk5raplSRWGyBaHD9Zs8gHeMPxMSketE5ICIHBaRz4zxvF1E7k49v0VEmlLHq0TkCREJi8h3Rl2zUUReTV3zLZHkOnYRqRSRP4jIodTfRT09EApHcrYJkdftIhAKYzRwSlt7NIxvkg2IevxB7n34sZxtNDQTSxvr2bBqGd+6824Gh4Yy3r7dUoqztJSeWDTjbauMmNFYr9IXSqQ3c97W2U31DPLNh1lLLSxprCfqD3M6rGuLlCoGk6W1/E/q73+basMiYgG+C7wJaAa2ichmY8zeEad9COg1xiwTkZuBrwB/AsSAfwHWpf6M9P+AjwBbgAeB64CHgM8Ajxlj/iP1i8BngP871X4XilAkijtHwbm1tBSb1UooEsXnmXo93bmoNRykYpLg/Ce//h0Xrl0544+lc+WyC87n3kce554Hk/nxmTZc67zaqf/HCs1Mxno1NcF4usF5F+W+zPxetHLxIrY0N3Nqfk1G2lNKZVe6mxD9p4j4RMQqIo+JSOeIj0HHczFw2Bhz1BiTAO4Cbhp1zk3AHanH9wLXiogYYyLGmGdJBukj+7EA8BljXjTJad6fAm8fo607RhwvSqFI7mbOAXxeN72ad562tknSWrbv3kdzWweXbhj9u2XhKikRbrj6Cp5/eRcv7TmQ8fYrnS7aItlJm1GZMc2xXk1BMBFLa0FoS0cXlWWZCc6XNjbQ1dLJCX9PRtpTSmVXunXO32yMCQI3AMeBZcDfT3JNPXBqxNfNqWNjnmOMGQACQNUkbTaP0+a84U0zgDZg3lgNiMhHRWS7iGzv7Oyc5CXkx+DgIH2xOE57buqcA/jcbl0UOgUT5Zz3xRL89DcP8OYrLimo6izpcDkd3HjN6/jhL39DR09vRtsutztp1Y2ICt10xno1BelWa2nt7KaybOZpLZBMbVlUXcXJoD8j7Smlsivd4Hz4M7i3Ab80xhR04lpqVn3MBGpjzA+MMZuMMZtqagrzI75wtA+nw0FJSbr/PDPndWs5xano7IuMG5zf9/vHWTh/Povq5+e4V5nRML+Gyzas49s/vTujGxRVOhxasaXwFdVYX4zC/fG0NiFq6+ymsixzOwmvXbiQvoEBYgNa61ypQpdu9Pc7EdkPbAQeE5EaRqWcjOE0sHDE1w2pY2OeIyKlQBnQPUmbDeO02Z5KexlOf+mYpH8FKxiJ4HalV0M7U3SX0PTFBwaI9ifw2s79ZONUazvP7tjJGy4tnM2GpmPTujU47HZ+/ruHM9ZmpdOl1SIK33TGejUFoTQ2IUr09xOKRCjzejJ232WLFmJiCfa0jH4bVkoVmrSCc2PMZ4DLgU3GmH4gwrn546NtA5aLyGIRsQE3A5tHnbMZuCX1+N3A42aCkiGptJWgiFyaqtLyAeC3Y7R1y4jjRScUjuRsMegwt9NJj18Dp3QM1zgvkbMrsJghw49+dT9XbVqP25nbX64yTQSuf/3lvLTnAFt27slIm1UO3UK80E1zrFdTEE4kJp05b+/qoaLMl9EqT9ZSCx6x8Lut2zLWplIqOyZfMv6aVSRr4I685qfjnWyMGRCRW4FHAAvwI2PMHhH5ArDdGLMZuB24U0QOAz0kA3gAROQ44ANsIvJ2krmQe4G/An4COElWaXkodcl/APeIyIeAE8AfT+G1FZRAOJLz4M7rdmrOeZo6omEqHefuaP7sjp30xeOsX7UiD73KPIfdxtvf+Dp+ct/vaKybz4KaiZaDTK7S4aRdF4QWgymN9Wpqwv2T55xnOqVlWK3bw7MHMr/YWymVWWkF5yJyJ7AUeAUYTkIdrpYyLmPMgyTLHY489rkRj2PAe8a5tmmc49s5t7wixphu4NqJ+lMskjXOc7cYFJIbEXV0Z3YB4GzVFglTPmqDqHCkj7se/D3vess1BV/TfCrm11Rx1ab1fPOOu/i3T3x0RhuilDucBOIxEoMD2CxTmRdQuTLdsV6lxxhDpD+Ba5LgvKOnN6MpLcMWllfyzJGTdHT3UltV1FuBKDWrpfsOuQlYM1HKicqcYCSCM0e7gw7zul3sP3oip/csVu2RMOX2sz/ZuPvBP7Bi8aIZzy4Xog2rV9Lc3smP77ufv/iTdyLT/N2jRIRKp5P2SISFvsxUoVAZp2N9FsUHBxHAOkkVp47uHsq8md8PoNLhwFtbySPPvsD7b7o+4+0rpTIj3QWhu4HiLD1RhIKhCE5HrmfOXVrnPE0tozYgOnT8JC/t3c/rNm3IX6eySASuu/JSDh0/xVNbdsyorUqHS8spFjYd67MolIjjttomPa+9q4cKb+Y3Zq2w2sHj4P7Hn8l420qpzEl35rwa2CsiW4H48EFjzI1Z6dUcFwxHcOWwxjmA16N1ztPVFgmxtjpZRn9gcJDb772fN1yyCYd98jfdYmW1lvL2a1/P//7uERY31rOobnrxW5XDqRsRFTYd67Mo3B+fNKUFoLPXT1kWgvMyq50Igxw5dZrWji4W1FZn/B5KqZlLNzj/fDY7oc7mD4VyujsoJDch0jrn6WmNhLiyoQmAB554FqfDzppli/PbqRyorizj2ssu4pt33MUX//ZjuKaRelXucNKmFVsK2efz3YHZLBSfvMb50NAQPYEgZb7M55xbS0pwWaysXL+GB556jg+/RwvxKFWI0i2l+BTJ3eKsqcfbgJey2K85LRAK57xai8NuY2hoiGhMSxpPpiMSptLhpKW9i4eefoE3X3HJtPOwi83a5YtZVL+AH9z9G6aTlVzpcNKstc4Llo712RVKo1JLbyCEy2HHWpqd3YUrbHYWrWzid088m5X2lVIzl1ZwLiIfAe4F/id1qB74TZb6NOcFwpGcz5yLCGVej9Y6n0RicIBQIoHXauN/7v41V25cT3kWZrgK2TWXbqS1o4s/PLdlytdWOpy0ac55wdKxPrvCaWxA1NnrpyILZRSHlVvtOKvKaOvs4vjp1qzdRyk1fekuCP04cAUQBDDGHAJqs9WpuS4Yyv0OoUAqONddQifSFglT6XTy0FPPY4aGuGDNynx3KedKLRZuuvZ1/Pr3T3K8eWpv7pVOF61hTWspYDrWZ1EokcBpnTibtLO7lzJP9n7hL7Pa6Ij3cdF5a3jgSZ09V6oQpRucx40xieEvUptTaKmtLAmGI9PK550pn8dNtwbnE2qLhHCJhQefep7rr758VtU0n4qKMi9vvOIivv2ze4jFE5NfkFLpcNEejWSxZ2qGdKzPonAijsMyWY3zHnyezJdRHFZptdMai3Dx+rXc//gzaNVMpQpPusH5UyLyj4BTRN4E/BK4P3vdmttC0QjuHKe1QLKcYndAg/OJHOvuouVUK2+64uKsbBJSTNYsW8yCmip+tvmhyU9OcVutDAwNEUrEJz9Z5YOO9VkUSsRxlE48c97e1ZvVVLkKm4O2eJRljQ2Eo30cPH4ya/dSSk1PusH5Z4BO4FXgL0ju+vnP2erUXBeKRPOS1uJ1uTTnfAKDg4P85KHfU+F0snppU767UxDeePlFvHrgMC/vTW9LcBGhxunSii2FS8f6LAokJi+l2NWb3bSWCqudnkQMI3DJ+Wu15rlSBSjdai1DJBcF/ZUx5t3GmB/qDnLZEYvHwYBtknJb2eB1u+jq8ef8vsXAGMOXvv9jAkMDrF24MN/dKRh2m43rX3c5t997P+FIX1rXVDpdtGneeUHSsT67QvEYzknG9m5/MKtpLaUlJXhKbXTFY1yyYS0PPPmsprYoVWAmDM4l6fMi0gUcAA6ISKeIfC433Zt7AuEInjzMmkMy57yz15+Xexe67/zslzyz7WXqmuops+V2g6hC11g/n5WLG/nZ5gfTOr/S4aRVZ84Lio71uRFMTFxKcXBoiGA4jM/jymo/qmx22uNRGhfMp6SkhJ37D2X1fkqpqZls5vxvSa7cv8gYU2mMqQQuAa4Qkb/Neu/moFA4P5VaILlLaLffn5d7F6qhoSG+etud/Paxp/j0h/+MwGA/3tLZuxPodL1u0wb2HD7GnsPHJj233O6kRWfOC42O9Tkw2Q6h/kAIt9OJxZKdGufDyqwO2mJRRERTW5QqQJMF5+8H3muMOfOOa4w5CvwZ8IFsdmyuCoQjOd+AaJjP49ac8xG6ev38xef+nede2sn//cgHKPd66UnEKLNqcD6azWblTZdfzI/vvZ+BgcEJz610OmkJ6/+zAqNjfQ6EE4kJ01q6A4GcLDSvsNpojSWrJl28fi0PPf08g4MT/9wqpXJnsuDcaozpGn3QGNMJ5D4peg4IhsI534BomM/jpicwu4KmoaEh2ru6OXKymeOnWwlFJi/jF4pEuO2e3/C2j/4tZR43f/+hP8PncRMdHGAIg6Mku7NaxWp500J8XjePPPvihOdVOVya1lJ4dKzPgVAijnuCmfOunkBW882HVdocZ4LzBTXVlHs9bH11b9bvq5RKz8Q1nWCiAsbpFzdWaQtGonkpowjgc7vwh0IMDQ1RUpJuIZ/CY4zh+Zd28fP7H+aFl1/FbrPidjkZGBwkEAxjsVhYuKCWRXULqJ9XQ7nPC0BPIMjew8fYdeAQF6xeyd9/6M9YuGDemXa7432UWe2IzM3a5um45tKN/Oy3D3PlxvXjzgBWOp1araXw6FifA+H+BK4JZs57AgG87uzmmwNU2ZJpLcMuOn8t9z/2NJdtOC/r91ZKTW6y4Hy9iIw1lSpAfiLIWS4YDuPMwwZEAKWlpTjtdoLhyJmAtdi0dXbzD1/9NqfbO3jLlZfyjjddfdZMlDGGcDRKe1cP7d099PiDtHV1IwhOp53LNqzjz991w5j/Bt2JGGWabz6hqvIy1i5fwm8efYpb3vG2Mc+pdLjojEYZMoYS/UWnUOhYn2XGGCL9Ey8I7ezpxZvlxaAA3lIrsaEBogP9uEqtXHz+Gv7t2z/k85/4aF4qhSmlzjZhcG6M0c/vcywQiuBy5K8aSJnXQ7c/UJTB+a4Dh/mLf/ky11y2ib987zvHnP0XEbxuN163m2WLplYSsTsR08WgabjsgvO47Z7f8tbXXU5tVcU5z9ssFpylpXT3RalxZf8jfDU5HeuzLzrQj91iwTLBp5KdvX5WLV6U9b6ICDU2Jy2xCMs85VRXlLOgtpoXXn6V1198Ydbvr5SaWPHmLsxSgVAYV55mziEZnHcVYTnFXQcO85F/+hIfePv13HjN67KSltMV78Ors0qTcjsdbFy3ivv+8MS451Q73ZraouaUYDyOa5LF5N29uck5h2RqS0vstTU4m85bo1VblCoQGpwXmEAohMulwflUtHV281ef/wq3vON6Lly7Kmv36Uz04dOZ87RsWreaV/YepKOnd8znq5xa61zNLZMtBgXoDQSzujvoSBU2O6f7XgvOLz5/DU9s2UE8oUsMlMo3Dc4LTCAUzlspRUhtRFREu4QODg7yiS9+jTdcspGN61Zn9V7dWkYxbQ67jQvWrOD+x8aeiSu3O2nVWudqDgklJp45j8ZiDBmD3Z6bMabK5uB0X/jM1+VeL03183lm+ys5ub9SanwanBeYYCSa17QWn9tN5ziznYXotl/+loHBQa5//eVZv1dPIqYz51Owad1qtuzaTSAUPue5CoeTVq11ruaQYCI+caUWfwifx02u1khX2ZxnyikO27RuNfc/oaktSuWbBucFJhAK48nTDqGQTGvp6C6O4PxkSxu3/fK3/Pm7/ijrpR/7hwaJDg7gmeRjafUal9PBmqWLeez5rec8V+V0cVpnzmcNEblORA6IyGER+cwYz9tF5O7U81tEpGnEc59NHT8gIm+ZrE0R+Xnq+G4R+ZGIFMUPZSgRn7BSS08gQFmO8s0Byqw2wgP9xAYHzhzbdN5qntn+Cn2xeM76oZQ6lwbnBSYUjuDOc3BeLDPnX/7+j7nuqsuoqTy3IkimdSViWuN8GjauW81jL26nv3/grOOVDietEZ05nw1ExAJ8F3grsAZ4r4isGXXah4BeY8wy4OvAV1LXrgFuBtYC1wHfExHLJG3+HFgFnAc4gQ9n8eVlzKTBuT+AJwc1zoeViFBtP3tRqM/jYenCep7a9lLO+qGUOpcG5wUmGI7kbRMiKJ4FoS++spt9R47z5isvycn9OuN9VGi++ZRVV5RRW1nJll17zjpe5XTRHjk33UUVpYuBw8aYo8aYBHAXcNOoc24C7kg9vhe4VpK/6d4E3GWMiRtjjgGHU+2N26Yx5kGTAmwFGrL8+jIiGZyPX724xx/E48pdcA5QbXPS3Hf2z+HGtat46KnnctoPpdTZNDgvIIlEPwODg9ht+QsCy1N1zguZMYb//vH/8vY3vj5nG2Z0xvvwleav/nwx27B6OY+OSm0pszsIJeIkBgfGuUoVkXrg1Iivm1PHxjzHGDMABICqCa6dtM1UOsv7gYdn/ApyIBCPTThz3uX352QDopGqbA5ORc9OL9u4bjXP7NhJLK6pLUrliwbnBSQQDuNxu/KaOuF1uwiEwwwODuatD5N57qWddPv9XLphXc7u2RHvw6c1zqdlWWMDXT1+Tra0nTlWIkKFw0Wbzp6r6fse8LQxZswVjCLyURHZLiLbOzs7c9y1c022ILTbH8Tnzu2mXDV2JydHzZz7PG6WNNTx9LaXc9oXpdRrNDgvIPleDApgsVjwut30BAo3H/i7P/slN1x9ZdYXgY7UEY9SbtWZ8+kosZRw/qplPLl1x1nHq50urXU+O5wGRm6325A6NuY5IlIKlAHdE1w7YZsi8q9ADfCp8TpljPmBMWaTMWZTTU3NFF9S5gXjcVyTLAj15XjmvMbu5HRfmGSG0Gs2rl3FA5raolTeaHBeQALhSF5rnA8r9xVO3vmQMTxy7BC3PrqZTz/xILc9/wwnW9u5eP3anPajM95HmQbn07Zu+VJeeHk3AwOvfSJT6dBa57PENmC5iCwWERvJBZ6bR52zGbgl9fjdwOOpnPHNwM2pai6LgeUk88jHbVNEPgy8BXivMWYoy68tY4KJ2IQz5/5AGG+OZ87dlmQOfGDg7I2HNq5LVm3RDYmUyg8NzgtIIcycA5R7vAWxEVH/0CCfffoRvrXjORaXVTDf7eX7u7fjvmY9lOQu9ccYQ3ciRrkuCJ22ijIv1RVl7Nx/6LVjWut8VkjlkN8KPALsA+4xxuwRkS+IyI2p024HqkTkMMnZ7s+krt0D3APsJZk7/nFjzOB4baba+j4wD3hBRF4Rkc/l5IXO0ETVWqKxGEMM5Xy9kYhQa3fSHD07taXM62FR3Xyee2lXTvujlEoaf+m4yrlAKIyrAGbOfd7C2IjoSy88yamgn89c+nrsllJ6gyHu3HYI+zUb+fHxvXy4aW1O8vNDA/2UiOCw6I/LTKxdvoQnt73ExnWrgGRwflqD81nBGPMg8OCoY58b8TgGvGeca78EfCmdNlPHi/IHMZxIjDtz3uMPUebx5GwDopGq7U5O9YVYV1Z11vEL16zkoaee55pLN+W+U0rNcTpzXkCSwXn+UycKYZfQp08d46lTR/no+ouxp4LiJ7fsYO2SJm6sX8KxSJBnu1ty0peuRB8VmtIyY6uWLGL/keNEon1Aspxii6a1qDki3J/ANc4Owz3+AL4cbkA0Uq3NyfHoub8kb1q3mie37qB/QCsqKZVrWQ3OM71rnIisTH2MOfwnKCKfTD33eRE5PeK567P52rIhEArhcuSvxvmwMp+H9u6evN0/MTjA5597jA+uu/DMTNPg0BBPbtnB+lUrsJVYuG5+I/c0H8bfn/1yXx3xPso0pWXG7DYbixvq2LFnPwBVDl0QquYGYwzhCaq19ASDeHO4AdFItQ4nJ6Ln/hxWlpcxr7qSrTv3jHGVUiqbshacZ2PXOGPMAWPMBmPMBmAjEAV+PaK9rw8/n/pItKj4g+G8bkA0rMLnpa2zO2/3/+X+3dR5fKyuqj1zbNf+Q7icDubXVAJQa3exzlfJvc2Hs96f9lhEF4NmyKrFjTz/cjKPtdLhpCNybqUIpWabvoEBSksslI5TYarHH8zbztBVNie9iTixMfYcuHDNSh559sU89EqpuS2bM+fZ2DVupGuBI8aYE1l7BTnmD4XyNkCPVOHz5m3mPD4wwA92beXGZavOOv7Utpc4b8XSs45dUjmPnYFOWkdsP50NrbGoprVkyLJFCzl68jShcASn1UppSQn+eCzf3VIqq0KJOO4JKrX0BAJ4c7w76DCLCDX2c3cKBbhw7SoefX4rQ0NFUxRHqVkhm8F5NnaNG+lm4Bejjt0qIrtE5EciUjFWpwptY4qRkjPnBRCcl/no7M5PzvnDxw5S7/HRVPbaP18o0sfew8dYvXTxWec6LKVsLK/lNy1Hs9qntliUSpsG55lgtZayeGE9L+07AKRqnWveuZrlgokY7glS43oC+UtrAai1j53asqCmGrfLySv7DuahV0rNXUW5IDRV9/ZG4JcjDv8/YCmwAWgF/musawttY4qRAuFwQcycl3s99ASCedkl9Od7X+HqhWcH4VteeZVljQ047Oe+uV1QXsPuYDdd8b6s9McYQ0c8SqUt/+lGs8WyRQ1s3bkXgCqnmxat2KJmuWA8XtDBeY3dyfHI2D+HF6xZyR+e25LjHik1t2UzOM/GrnHD3gq8ZIxpHz5gjGlP1ccdAn7IuWkwBS8YjhREznlpaSlul5Nuf26Dpj1d7XREI5xfu+Cs48/seIU1y5aMeY3dYuE8XxWPdpzMSp9CA/2ICE4to5gxyxobOHjsJH2xBBUOBy3jBAVKzRaBSTYgCgRCeHO8O+hI8+yuMSu2QDLv/PfPbdG1IUrlUDaD82zsGjfsvYxKaRGRkRHdO4DdGXslORIskE2IACrLfXT05Dbv/L6De7iyYRElI4r9dnT30tHdS1P9gnGvu6C8mme7W8dc0DRTbfEoVTprnlEOu42GBbXsOnCISoeTlpAG52p2C8bjuMbZgKi/f4BYoh+nPX/jTK3dSUe8j/jQuZ+WNtUvIJ5IcORkcx56ptTclLXgPBu7xgGIiBt4E3DfqFv+p4i8KiK7gDcAf5ut15YNQ0NDhKJ9BbEJEUClz0d7V+6C84GhIR45dohLFiw86/gLL+9i1dImLJbx/6uWWe00OD1s7W0f95zpao9FdDFoFixrbGDH7v1UOd00a1qLmuWCE8yc9waTs+YlOdz1eLTSkhJq7E5OjZF3LiJcsGaVprYolUNZzTk3xjxojFlhjFma2gUOY8znjDGbU49jxpj3GGOWGWMuNsYcHXHtl1LXrTTGPDTieMQYU2WMCYy61/uNMecZY843xtxojGnN5mvLtEhfH3ablVKLJd9dAZLbN+cyOH+h5STVLhfz3J6zjj/30i5WL1k06fXn+ap4oiPzMzutsSjlWuM845YtauDVA4eotDs051zNeoF4DOc4M+c9gWDeNiAaaZ7dxbHx8s5Xr+D3GpwrlTNFuSB0NvKHwnjyVEprLMngPHe1zn93ZB8Xz28461hzWyfRvhj182rHueo1i90+/ANxToyTNzldrX0RKjStJeN8Hjdej5tgt5/2yLkl3JSaTQLx8Tcg6g0ECyKdcb7DxeFIYMznVi5ZxMnW9py+Jyg1l2lwXiD8wVBeV+uPVuHz0pajgbh/aJCnTh1n4/yzq2Vu3bWblUsWpfVxb4kI67xVPNPVktG+nY6FqdHgPCuWNtZz4OBRIv399A3057s7SmVNID5+KcVkcJ7/sX++wzVuxZZSi4UNq5bz2Avbc9wrpeYmDc4LhD9YWDPnuQzOd7SdZr7LQ4Xj7NmjLTv3sDKNlJZha32VbOlpYyBDG2bEBwfx9yco1+A8K5YsbGDnvkNa61zNeoF4DPc4aS1dgUBBzJxX2RwEBxKEx/lFecPqFfz+Od0tVKlc0OC8QPiDoYIYoIdVlOVuQejvjx9m/ajyiS3tnUSifdTXpl+Lvtxmp9ruZFewKyP9aolFqLI5sEj+FmrNZnW11fQGg5RZbbRGNDhXs1cwHsM1zsx5jz+/Nc6HlYhQ53BzdJzUlvNWLGPnvkOEItndkVkppcF5wfCHQgWxAdGwqvIy2rq6s17b1hjD4yePcMG8s4Pzba/uZcXixilXMFjtrchYasvpPk1pyaaSEqGpvo6hvoQuClWzWjAx/iZEvYHCSWmc73BxOOwf8zmnw87KJYt4ZtsrOe2TUnORBucFojcQKogNiIa5nA4EIRjO7izJ/p5OLFLCArf3rONbX93L8qbGKbe30lPB/lDvuB/NTkVzX5jKPNYengsWNywg1OPXWudqVgslxl8Q6g8G8brzX60FoM7h5uA4wTnA+lXLtWqLUjmgwXmB6A0EC2rmXESoriyntSMzKSLjeab5OOuq5yEjUke6egN09wZonD95lZbR7BYLS9w+tmeg5vmpvhDVtsL5N5mNFjfU0dnSycmgP99dUSprQonEmDPnZsgQDEfxuAtjnKlzujkRDTFoxl63c8HqFTy74xX6BzK/4ZtS6jUanBeI3mBhlNMaqbqinJbO7AbnT506xnk18846tmP3PpY3LaRkgo2HJrLKW8Fz3TMvc3+6L0KNzpxnlc/jxlVi4XBXZ767olRWxFKBrG2MPSyCkQgOm61g9rdwWkrxldpo7hu7vGlFmY/5NVVs27U3xz1Tam7R4LxA9AZDBVWtBZIDcUt79oKmYDzGgZ5OVlWevehz26t7WdbYMM5Vk1vi9tEai9AV75t+3/oTJIYG8ZXqBkTZtrCiUnPO1awVTMTw2MYeR/yp3UELSZ3TzaFJUlv+8LymtiiVTRqcF4hAKFxwM+eVZV5Od2QvOH+h5RQrK2vOmlEKRfo40dLG4oX1E1w5MYuUsNJTwYs9bdNu41g0yAKH+6x0G5Udy+bNo29okMTgYL67olTGBePjLwbtCQTxFsDuoCPVO9zsD/WO+/yFa1by2PPbsl4sQKm5TIPzAhEIhfEUyIr9YVXlZTS3zjx3ezzPNh8/Z9Z85/6DNNUvwFo6s495V/sqeKGnddpvIMfCAeY5CuvfY7Zqqp+Pifdzold3H1SzT3IDonF2Bw2G8DgLa1JmocvDwbB/3LGzfl4tIsK+I8dy3DOl5g4NzgtEIc6cV5WX0ZKlBaHGGJ5vOcna6rMXfW7fvZdli6af0jKs3uGmb3CAU+PkTk7mcCTAfLsG57lgt9mwDxme3qN5rGr2mbiMYhC3q7DWtZRZ7VhEaItHx3xeRLhgzQoefX5rjnum1NyhwXkB6B8YoC+ewGm357srZ6muKM/aLqEnQwESgwPUe3xnjvX3D7D38DGWziDffJiIsNpbOa2FocYYTkSDLNCZ85wps9rZcvhwvruhVMYF4zFc4+wO2u0PFNwnpgALnV4OTJDacsGalfzhOQ3OlcoWDc4LQCAUxutyUlJSWP8c5V4PgVCYRP/Ma4aP9sLpE6ytrj0rp3vfkePUVlVmrN77Gl8lL/a0jlsWbDzdiRglInjHme1SmVfj9rC/feYVdpQqNMFEHOc4wXmPP4ivwAoBADQ4J847X75oIe1d3TS3deSwV0rNHYUVDc5R/mCoYDahGMlisVBR5qOtM/Oz58+ePnFOvvmOPftY2jj9haCjVdkc+Ept7A32TOm6w5EAdY7C+/eYzerLK+jpjxOOTr/CjlKFyB/vG3cDot5gqCBnzhudXvaFesbNO7dYLGxYs5LHX9yW454pNTdocF4A/AU6QAPUVlVwKsOLQgeHhtjedprVVa/lmxsDL+09wLLGhRm91xpfJU93tUzpmr3Bbhqcnoz2Q02s0u7AXuFjx559+e6KUhnVG+vDM86ncP5QCG8Bjv3lNjulUsLp2Pg7RF+wegUPP/NiDnul1NyhwXkB8BfgYtBhNRXlnGydfknCsezv6aTM7qDC8dprPnG6FYvFQlV5WUbvtdpbwZ5gN6GBRFrnG2PYE+xhkcub0X6oiZVZbRiXjRdffjXfXVEqo/yx2JgLQhP9/SQSAzgdhbUgdNgil5e9wfE/NV23Yin7jhyjNxjKYa+Umhs0OC8AvcEQ7gINzqsryznRktng/MWWk+ektLy0dz/LGhvIdFlxh6WUZZ5ynutKL5+5M9HHgBmiylaYb5izlbfURn8JPL9rd767olRG+eNjb0LUGwjh87gzPuZlSqPLy6sTBOc2q5Xzli/liRe357BXSs0NGpwXgN5AEHeB1bodNq+qkuPNU0sLmcxzp0+yuqr6rGM7du+f0a6gEznPV8WTXc1p1TzfG+xhkcunmw/lWIkIZVY7x7q7Ne9czSr+eN+YM+c9gQC+AtsddKRFLi+HwwEGhsZfUL9hzQoeevr5HPZKqblBg/MC0BMI4nUXZnBeW1XJyQzmnCcGB3m1s42VI2bOewNBOv1+GubXTnDl9DU43QjC7glmgYa97O9kkUvzzfOh3Gpn/qI6Xtl3IN9dUSpjAvHYmDnnvYHCzDcf5rSUUm1zcDDsH/ecDatWsP3VfUT69BdqpTJJg/MC0N0bKMhqLQDzqio43d6Zsa2aX+1sY4HHe9ZM0sv7DrKssQGLJTv/HUWEjRU1PNR2YsLzQgMJDob9LHOXZ6UfamJlVhsVdTVs3bkn311RKmNCifiYaS09gWDBpjMOa3L72BkYfyM6t8vJ8qaFPLX15Rz2SqnZT4PzAtAdCBTsDIrT4cBus9LZ489Ie2Plm2/fvZ+lCzNXQnEsq70VnI6FORENjnvO9t4OlrrLsFssWe2LGpu31IajwsuWXRqcq9mhf2iQvoEBHGPUOe8JBPE4C3PcH7bE7WNnoHPCcy5cs5KHNbVFqYzS4LwA9PqDBRucA8yvrspYxZbnT59kZeVr+ebxRIJDx06yJMvBuUVKuLRyPvc0Hxr3nGe7WljlrchqP9T4yqw2BpxW9h89QSwez3d3lJqx4ZSWkjHWsHT7AwWbzjhsvt1FdHCAjnh03HM2rlvFsy/t1J9ZpTJIg/MC0BsM4vVkJq1lwAzRHovSnYhlpD3IXK3zaH8/+3s6WVHxWnD+6sEj1M2vwWHP/m6c55dV0xHvY3fg3NzzfcEe/P1xFrt9We+HGlu51U5Pf4KFC2rZdeBwvruj1IwF4nG8NvuYz/UGMjfuZ4uIsMTl4xX/+LPnPo+HxQ11PLtjZw57ptTspsF5AfCHwvgyMHPe0hfhc3te5D8P7uBf977Ibcd2Ex8anHG71RXlHDt1esbtvNzRQlNZBfbS0jPHduzen9FdQSdiEeENNfX86MRegv2v1T0fMoZfNB/kquo6LFqlJW/KrDa6En0sa1zIjt26GZEqfv6JNiAKFvaC0GHLPGVs7+2Y8JwL16zkgSefzVGPlJr9NDjPs3giwcDAIA772LMr6epNxPnKwe1sKK/hI4vX8pGmtfj7E3z3yE4GzPilsNJRP6+GQydOzagNgBdGpbQMDQ3xyv6DLM/wrqATWeIuY5Wngu8c2UmgP86QMfzs5H4EWOkpz1k/1LlcllL6h4ZoWlSveedqVgjEY7jHWAw6NDREKBIt2M3nRmpy+WjuCxPoHz9t5aLz1vD0tlc0tUWpDNHgPM96/MHURhTTn7E1xnD78T2cX1bN+WVVANgtFt46fxF9g4Pcd/rIjPpYV1vD4ZPNM2oD4PmWk6yuem0x6KHjp/C6XJT7clu68MrqBdTanfzTnhf41K5nOBYN8s66pVrbPM9EhAqbnfK6GnbtP8Tg4Mw/9VEqn8YroxgIR3A47FiKYPF5aUkJS9xlvOIfv2pLmdfD4oYFPL1Nq7YolQkanOdZTyAZnM/Ey4FOuhMxLq2cf9ZxiwjXzWvk2a6WCauUTGZ+dSVtnd0kEv3TbsMfj3Ey6GdpedWZY9t372PZouxsPDSREhGurK7jlsZVvHfhct5Tv0wrtBSIcqudSImhsryMA8cmLn2pVKHzx2M4x6jU0hsI4ivQ8rljWeYpY0vvxEUBNq5bze+e0NQWpTJBg/M86w3OrFKLMYbftR7j0sp5Y+ZLu0utXFVdxx0n9k27VnlpaSm1VRUcOz39nUK3tzazoqKK0pKSVL9hx579rGhqnHabM+W12iiz2sespKDyo8xqozPex4pFC9mueeeqyPXGxt4dtNA3IBptqbuM45HgJKktq3n2pZ26IZFSGaDBeZ71BIJ4ZjBIHwz7CQ30s3yCfOl1vkqigwMTbiYxmfp5NRw5Mf3UludaTpy1K+jp9g4GBgeoraqcdptq9imz2mmLRVm6qIFtr+7Nd3eUmpHeWN+4GxDNZNzPNWtJCcs95WzpGX/23Ot2s3LxIh59flsOe6bU7KTBeZ71+IN4XNMfpB/rOMUF5TUTzv6KCFdULeBXpw9Pe/Z8fnUVh05Of1Ho86dPsra69szXW3ftZXlTIzpprUYqt9roiEdZ3tTIS3sOZGxnWqXywR+PjTlz3u0PFMVi0JFWeyt4vnvi1JaLz1/Dbx59MjcdUmoW0+A8z3oC0x+k+wYH2B3sZnUaG+csc5cxYAy7g+fW+E5HXW0NB4+dnNa1LeEgoUScBm/ZmWNbX93DyjymtKjCVG610xnvo7aygsGhIU63T7w7oVKFzB8fu5Rit99PWYHXOB+t0eWltz9Gc1943HM2rl3Fzn2H6Or1565jSs1CWQ3OReQ6ETkgIodF5DNjPG8XkbtTz28RkaYRz302dfyAiLxlxPHjIvKqiLwiIttHHK8UkT+IyKHU30Wx1WNXb2DauYcv+TtodHlxWkonPVdE2FRRw4Ntx6d1r/r5NRw8Pr3g/PnTJ1lbVXtmdr+9q4dgKEz9vNpJrlRzTZnVRmAgwaAxrGhqZMee/fnuklLT5o/Fxkxr6fYH8RTRglBILqQ/z1fNU53jpzfabTY2rl2lC0OVmqGsBeciYgG+C7wVWAO8V0TWjDrtQ0CvMWYZ8HXgK6lr1wA3A2uB64Dvpdob9gZjzAZjzKYRxz4DPGaMWQ48lvq64PUGpr8g9Lnu1iltN7/KW0FrLMrJaGjK96qrraGjq4dwdOqLfZ5tPs6qESUUt726lxWLF1FSojkt6mwWKcFbaqM7EWPpwnq279a8c1W8euN9Y+4QmqzWUjw558POK6vkhZ42EhNsbnf5hefzy4cf05Q0pWYgmzPnFwOHjTFHjTEJ4C7gplHn3ATckXp8L3CtJItN3wTcZYyJG2OOAYdT7U1kZFt3AG+f+UvIvm5/YFoltaKDAxyLBFnqLpv85BSLlLChrJpHO6Y+A15qsbCofgH7jhyb0nWDQ0NsaT3F2qrXZslfeOVVTWlR46qw2umIR1mxuJHtr2rFFlWchowhOEadc2OSu0IXU7WWYWVWO3UON1t62sc9Z9WSRQTD4Sm/VyilXpPN4LweGLmCsDl1bMxzjDEDQAComuRaA/xeRHaIyEdHnDPPGNOaetwGzMvEi8i2bn8An3fqwfmeYDcLnR6sJVP7JzyvrIodvR1EBqZes7yxbj67D05tQ6PdXe2UO5xUOpNvRO1dPfQGgjTWzZ/kSjVXlVvtdMT7aKybT0tHJ8FwJN9dUmrKgok4dksp1lF7KIQjEWzWUqzWydMRC9GF5TU83H583JnxkpISrrhwPfc89FiOe6bU7FGMC0KvNMZcSDJd5uMi8rrRJ5jkqDHmyCEiHxWR7SKyvbMz/4vNevxByjxT3yHzZX8ni92+KV/nLrWyxF3GM11Tr1neVD+fXQcOTemap5uPsa76td+TXnzlVVYuadKUFjWuMquNtliEUouFpY0NvLLvYL67pNSU9cai+OyOc473BKY35heKRS4vQwZenaC4wFWbNvDAk8/SFxu/LrpSanzZDM5PAwtHfN2QOjbmOSJSCpQB3RNda4wZ/rsD+DWvpbu0i8iCVFsLgI6xOmWM+YExZpMxZlNNTc1Yp+RMLB6nf2AAl/PcAXwiQ8bwaqCLJdMIzgHWl1fzZFfzlHMCFzfUTXnm/KlTx1iXKqFoDLzw8qusXrJoSm2ouaXCZqctHgVgaWMDL+miUFWEevr68I2Rb56JXaHzabi4wP2tx8Z9D6muKGdZYwMPPvVcjnun1OyQzeB8G7BcRBaLiI3kAs/No87ZDNySevxu4PHUrPdm4OZUNZfFwHJgq4i4RcQLICJu4M3A7jHaugX4bZZeV8Z09QYo93mQKRb7PhEN4i61UmY9d+BPR70j+cawP9w7pesW1FTT0dNLKJJemkFPX5STQT/LK6oBONnaRjQe0yotakKVVjsdseTC4+WNDbpTqCpKvbGxF4Mm97Yorhrno632VhLoj7Mn2DPuOa+/+EJ+fv/DOeyVUrNH1oLzVA75rcAjwD7gHmPMHhH5gojcmDrtdqBKRA4DnyJVYcUYswe4B9gLPAx83BgzSDKP/FkR2QlsBR4wxgz/9P8H8CYROQS8MfV1Qevq9VPmnfrHm3uDPSx0eqd9XxHhfF81j3dMbcdPSyrN4OW96aUZPN18nLVV8yhN5cU/ve1l1i5bqiktakJlVju9/TEGzRDLFi1kz6GjDAyOXx1CqULUM87uoN0BPx53cQfnJSJcXrWAX54+xNA4s+frVy2nq9fPzv2alqbUVGU159wY86AxZoUxZqkx5kupY58zxmxOPY4ZY95jjFlmjLnYGHN0xLVfSl230hjzUOrYUWPM+tSftcNtpp7rNsZca4xZbox5ozFm/F/pC0RXr39auYd7Qz00umaWs7jGV8GeYDeB/qnlBK5cvIgXXt6V1rmPnjjM+bXJhZ8Dg4O88PIu1i1fMuW+qrmltKQET6mNrngMt8tJdWU5B46eyHe3lJqS3tjYGxB19QbxFlmN87Gs9JQzZAzPdbeO+XxJSQnXXnoRP/7V73LcM6WKXzEuCJ01uv0BvFPMPRwYGuJoJMhC58yCc4ellBWecp6d4sLQ1UubeP7lVyc9LzYwwJbWU5xfkwzOd+0/TIXPR2X59PLk1dxSabPTnso7X9bYwEt7Ne9cFZfuvijeMTcgChR1zvkwEeHa2oXce/oQ4XGqf1110Qae3fEK7V3T25laqblKg/M86ur1T3kjiqORAFU2B440dgWdzPqyap7sOj3ux5JjWbqwnhMtrQRC42/hDPBiy0mafBVnci7/8PwWzl+1bEb9VXNHudVOe2x4UWi91jtXRac7Fh0n5zxA2SwIzgHmO1ys8FRw58n9Yy4OdTudXLFxPbffO3q5mVJqIhqc51FnT++UZ1D2h3ppmOGs+bD5DhdWKWHvBIt6RistLWVFUyPbXp1458bfHz90Zta8o7uXY6daWL108Yz6q+aOcqudtnhy4fHyRY28tPdAnnuk1NT0jBGcmyGDPxjGMwvSWoa9rrqOY5EAz/eMnd5y3ZWXct/vn6A3OPWdqZWaqzQ4z6POHj++KeacHwj3Uu/MzMAuIqwvq+YPU9wxdM2yxTz2wrZxn08MDvL4yaNsmp/cN+qxF7aybsVSrKWWca9RaqQKq53W1Mz5vOpK4okErR1dee6VUukbq1pLIBzB4bDNqrHQWlLCDQuauOvUQY5Fguc8X1lexqZ1q/mxzp4rlTYNzvMoWa0l/UB70AxxLBKkPkMz5wCrfRUciQToivelfc1F563h0ee3kugfO8/w+dMnqPf4qHK6iPbFeGrry2xcuypTXVZzQKXNcSatRURY0dTIyzp7ropIbyx2TnDe7Z9eha5CV2t38eZ5jXzryCtnfm5HuuENV/KLB35Ptz+Qh94pVXw0OM+jbn9gSgN1c18Yb6kNVwbyzYfZSiys9VXxWMeptK+priinrraG518au2rLg0cPsHFeHQCPPr+VpY0NlPtm3xuSyp4yq43QQD/xoWQJxSUL69i+R/POVXEwxhCInztz3u0Pzpp889GWe8q5tGI+Xzm4g7bY2Xth1FRWcOn6dfy/X/wqT71TqrhocJ5HyYVB6Qeth8L+jKW0jHRBWTXPdLcQGxxI+5qLzlvN5sefPud4pD/BU6eOcdGCBqKxGI88+yKXrF+bye6qOaBEJFmxJTULt7ypkR27tWKLKg6R/gQWKcFmOTt9pdsfwOOaWhGAYrK+vJrLKufz7we2sz909lqmP7rmKn776FMcPz12brpS6jUanOdJPJEg0T+Ay+lI+5oDIT91WQjOy212Gl3eKZVVvGT9Op7e9jJtnWeXyHr42EFWVdZQZnfwm0efYmljAzWV5RnusZoLKm0OWlMzcE31Czje3EKkL/30K5U7InKdiBwQkcMi8pkxnreLyN2p57eISNOI5z6bOn5ARN4yWZsicmvqmBGR6qy/uGnoifXhs587tnf29uKdYoWuYnNeWRVvnbeI7x19lc0tR89UAyvzerj+9Vfwxe/dnuceKlX4NDjPk46eXsp9HkTS3y3zSCRAnSM7H4luLK/hkY6TDJqhtM73edy8btMFfP+usz+m/OWB3Vxe38jp9k6e3voyV23akIXeqrkguSg0GZzbrFYW1S9g14HDee6VGk1ELMB3gbcCa4D3isiaUad9COg1xiwDvg58JXXtGuBmYC1wHfA9EbFM0uZzJHeBLtidqbr6olSMEZx398yOGueTaXL7eP/ClbwS6OSL+7dyui9ZevfNV1zMkZOn+cNzW/LcQ6UKmwbnedLR3UtlWVna5/cmYiSGBqmwnls3NxPqnR48Fisv9rSlfc1bX38Zv3viWY6cbAbgUG8Xp0MBVvgq+eYdd3H1JRficRX3NtUqfyptdlr6XstdXdbYwMt7dFFoAboYOJzawTkB3AXcNOqcm4A7Uo/vBa6V5MzETcBdxpi4MeYYcDjV3rhtGmNeNsYcz/aLmomuvsiYM+fdgdlT43wyXquN99QvY6Wngv84sJ17mg8xKML/edcN/Ou3foBfSysqNS4NzvOkvauHcp837fOPRALUO9xTmmmfqkur5nF/67G0NyXyeTzc/LY385F//hJdvX5+tGsHl89fyLfuuIt51ZWsX7U8a31Vs9/ItBaAZYsaJq2vr/KiHhi5orw5dWzMc4wxA0AAqJrg2nTanJCIfFREtovI9s7OzqlcOmNd0Si+cTYgmmr53GImIqwvr+aWRas5FQ3xj3ueJ1rh5KLz1vDP3/j+mBsXKaU0OM+bju6eKVVqORIOMD9LKS3DGp1e7CUWnutOf8HOVZs2cNkF5/GWv/oUDxzcyx9+9TBlXg/XXXlpFnuq5oJKq4OOeN+ZXxaXNy1k14FDDA4O5rlnqhgYY35gjNlkjNlUU1OT03t39UXOCc4T/f30xRJTWmc0W3hKrbxtQRNvntfI/546SOeqWg62tvDzzQ/nu2tKFSQNzvOkvbuH8ikE54cjfhY4sruQSER4fXU997UcJj6FAOjGa17Hpne/icZSJx+4/i284dKNlFj0v5aaGbvFgtNSSnciBiQ/qSnzejh0Iv2ynyonTgMLR3zdkDo25jkiUgqUAd0TXJtOmwWrIxrGZz87OO/qCVDu81BSkr1PPwvdIpeXWxpX4Sq14r9kKV///cO88PLYJXmVmss0gsqTts4uKtJMaxkwQ5zqC7MgyzPnAHVON/UOD/e3Hkv7ms54Hy+Fu3nr4uVUlKWfqqPUZKrtjjOLyQCWL1rIS5p3Xmi2ActFZLGI2Egu8By9HeRm4JbU43cDj5tkTsNm4OZUNZfFwHJga5ptFqzOaISyUTnnnb29lHt1fCwtKeGq6jreXr+E0k3L+Niv72anLvRW6iwanOdJe1dP2oHs6b4wZVY7dktutny+uqaep7qaORE9dyvmsdzTfIgLymvwlFqz3DM111RZHbSMyDtfuqiBba/uyWOP1GipHPJbgUeAfcA9xpg9IvIFEbkxddrtQJWIHAY+BXwmde0e4B5gL/Aw8HFjzOB4bQKIyCdEpJnkbPouEbktV681XZ195wbnXT3+ObMYNB31Tg9/vmQt1Yvr+bP77+JZ/blW6ozMbTWppiRZSjG94PxoJMgCe+5q43pKrVxdU8//HN3Nv6y+GOcEO5Ju6WnjRDTI+xtX5ax/au6osjtojr5W1WHFokYeeOK5PPZIjcUY8yDw4KhjnxvxOAa8Z5xrvwR8KZ02U8e/BXxrhl3Oqu6+vnNnznt68WpwfhaHpZT3L1vLb+UAH3vqd/zfjnbef+01+e6WUnmnM+d5YIyhs8efdlrLkXCAeVnONx9tjbeSBQ433z/6KgPj1D5v7gvzs5MHuH5+E9YS/a+kMq/a5qR5xMz5/Joq+mKxcza/UqpQDBmDP953zoLQjp7eKRUBmCtEhLcvW8XF1Qv4ysGXuPUb3yEUiUx+oVKzmEZUeRCJ9iECTkd6q/aPZnHzofGICNfUNhAbGuTrh14mMtB/1vPHIgG+dvAl3lBTz/wc/+Kg5o4qm4P2WPRMxRYRYcWSRWzfvS/PPVNqbIF4DIelFOuoNMSuHr8G5xN4fUMT1zUs5ll3P9f+zT9w528fJBaP57tbSuWFprXkQXt3D5VlvrTO7RscoKc/RrU995v5WES4acFinupq4TO7n+PyqgVU250cCQfYG+rh2poGVnorct4vNXfYLRZcpaV0JfqoTaV2LWtsYOuuPdzwhivz3DulztXVF6HCce543eX3T6lC11x0XkUN9tJSfl9ayq+3bOU7P/slN7zhSt561WVsWLOS0hytu1Iq3zQ4z4OO7h4q0gzOj0eDzLO7sGRx86GJlIjwhpp61pdVcSDkZ3+wl2q7gw8uWo1rglx0pTKl2ubkdF/kTHC+cvEifvqbc1KRlSoIXdHoOfnm8UQ/sfjcrHE+VSu8FQwaw9MWCx97/RUcePUA//yN79Pe1cPa5UtYvbSJpoY6FtRUU11ehs/rwe104LDbsFmtWEtLKdE0S1XkNLrKg/aunrRLah3NQ775WCptDi6rmp/vbqg5qNrm4FQ0xAXlyY1kGuvm09rZhT8YmtIuu0rlQldfhLJR+ebdvf45X+N8Klb7KkkMDfHjziP889WX8Y43XU0oEuXoqdM0t7Xz7PZX8IfCBMMRItE++uJxEol++gcG6B8YQEQotViwWCxYSy3YrFacDjtup5Myr5vKsjJqqyqoq61h4YJ5LKpbwKL6+disWnFMFQYNzvOgtbM77TKKRyNB6p26wl/NXTV2Jyf7XqvYUmqxJOud7z3ANZduymPPlDpXZ18E7zmVWvyUefQXyalYX15NeKCfrx96hc+u3ITX7WL9quWsX7V80muHhoYYHBpiYGCQgcFB+gcGiCcS9MXiRPtiBCMRAsEwL+87wB+e30JbZzedPX7q59WwemkT561YxroVS1m7fAluZ+5TSpXS4DwPmts70s45PxYNsqmiNss9Uqpw1dqdbOlpP+vYskUL2bZrjwbnquC0hkOUjwrO23t6KPNpvvlUXV41n0faT/L9Y6/y10vXU5JmemdJSQklJSVYS9MPcfoHBmjp6ORkSxsv7z3Abx59ihOnW6mbV8P6VcvZsHoF61ctZ3lTo+a+q6zT4DwPTrd1cPkF5016nr8/TnxokHKrLQe9UqowVdocyZ+FwcEzG3GtXNzI5seeyXPPlDpXSzjEmqqas461dXbrYtBpEBHeNG8h954+wj3NB7l54cqs3ctaWppMb6lbwFWp3/kHBgY41dbBkZPNPPbCNm775W/p7PGzvGnhmVn881cuZ1HdfCRP68LU7KTBeR60dHRRVVE26XnHIkHqHG79oVdzWokI1XYHzX1hlnqSPzdLGxs4crKZSF+ffuysCkp7NMSV9Y1nHWvr6mFl08I89ai4WaSEGxcs5ucnD1Dv9HBVdX3O7l1aWsrihjoWN9SdOdYXi3GsuZVjzae59+HH+c8f/pRYPMF5K5axcd0qNq5bzYZVK3A67BO0rNTENDjPMWMM7V3dVJWXT3ru0UiA2jyUUFSq0NTYnJzqC50Jzm1WK4sX1vPy3gNcuXFDfjun1AgdkXNLKXZ093Dp+rV56lHxc1pKeUf9Uu46dZAFDjfLPOX564vDwZpli1mzbPGZY/5giCMnmzl8opnfP7uFE6dbWbG4kcsuOJ/LLjiPC1avwGHXYF2lT4PzHOsNhii1lqb1W/WRSIA1WkdcKartTk5EQ2cdW9G0kK279mpwrgpGYnCQQDxG+YjgfGhoiG5/QCsLzVCVzcF18xbx3SO7+JfVF1NpK5yylOU+LxvXrWbjutUAxBMJDp9oZt/R4/z793/CydY21ixbzOUXnM9F563h/JXLdWZdTUiD8xxr7eiipqJ80vOGjOFEJMi1NQ3Z75RSBW6e3ckLPW1nHVu5eBGPPPtinnqk1Lm6+iKUOxxnLVzsCYRwOx1YS3UR4Uwt9ZTRlYjx7SM7+ceVm7CWFOb31G6zsXb5EtYuXwIkU2EOHjvJ/mMneOSZFznZ0kZj3XzWrVjKqiVNLFlYT+OCeSyoqcZm03KOSoPznGvp6Ewr37w9HsVuKcVdqj+oStU6XJzuizBghiiV5AYjy5sW8q077yEai+FyFM4smpq72iJhKkftS9He3UOlL73qXGpyF1fU0hGP8pMT+/hw09qiWJPldDhYv3oF61evACDR38+p1naOn25l66493P/4M3T29NLV68ftclJVXkZ1RRlV5WXUVlayoLaautoaFtXPZ0lDvQbwc4AG5zl2ur0zrYH6WCTIggLYfEipQmAvsVBmtdHSF6HRlUwPsNtsLG5YwEt79mtqiyoIbZHQufnmXT2UpbmvhZqciPCWeY384tQh/tBxkjfPW5TvLk2ZzWplaWMDSxvP/mR8aGiIUCRKILXBUiAUxh9K1mN/7IVttHZ20dnTy6K6BWw6bzVXXLieyy44TxfFz0IanOdYS3snleWTB+dHIn7m2TU4V2rYfLuLE9HgmeAcYMXiRbz4ym4NzlVBaI+Ez61x3tVNmUc3ksskW4mFt9ct5uenDtLg9LLGV5nvLmVESUkJZV4PZROU3Uz093OypY2Dx0/yP3fdx99/5VtcumEd73zzG7j6ko1Tqu2uCldJvjsw15xq76CqfPK0liPhIHW6M6hSZ9Q4nByNBM86tnrJIl54eVeeeqTU2VrD586ct3Z2p73pnEpfmdXO2+Y38f1jr9IRj+a7Ozljs1pZtmgh17/+Cj79oT/jvz7zNyxeWMf3fn4vr3/fX/DNO+6iq9ef726qGcpqcC4i14nIARE5LCKfGeN5u4jcnXp+i4g0jXjus6njB0TkLaljC0XkCRHZKyJ7RORvRpz/eRE5LSKvpP5cn83XNl3Nbe3UVE5cgaV/aJDWWERnzpUaYb7dzfHo2cH5skULOXyymXBk7rw5q8LVEglSOSo4b+nsTGtCRk3dIpeXyyrn841Dr9A3OJDv7uSF2+Xk9RddyGf+4hb+7s/fx4FjJ3jLn/81n/vm/9Dc1pHv7qlpylpwLiIW4LvAW4E1wHtFZM2o0z4E9BpjlgFfB76SunYNcDOwFrgO+F6qvQHg74wxa4BLgY+PavPrxpgNqT8PZuu1TZcxhubWDuZVTfwR3IloiGq7A2uJfrCh1LB5DictfRH6h4bOHLNZrSxf1Mi2V/fmsWdKJbVFQmcF5wODg3T1BqjQmfOs2VBWzQKHm+8d2cWgGZr8glmsYX4tt7zjbfzHpz9ONBbj7X/1af7pv79HS0dnvrumpiib0d/FwGFjzFFjTAK4C7hp1Dk3AXekHt8LXCvJpdc3AXcZY+LGmGPAYeBiY0yrMeYlAGNMCNgH5G67sBnq9gcoLbXgdk28eONwJMACh6a0KDWSrcRClc3Byb6z652vWrqIZ3fszFOvlHrN6VCQGtdrY3dnjx+fx61lFLNIRLimtoG+oQF+dvIAxph8dynvfB4P77nuWv7j07cS7+/nxo99mv/ve7fT7Q/ku2sqTdkMzuuBUyO+bubcQPrMOcaYASAAVKVzbSoF5gJgy4jDt4rILhH5kYgU3O49J1ramF9dNel5h8N+rdSi1BgWONwcCZ/9BrN22RKee0mDc5VfoUScxOAgXttrm8u0dnRRnca+FmpmLCL80fzF7Av18EDb8Xx3p2B43S7ec921fPlTf0lHVw/XfegTfPvOe4j09eW7a2oSRZk3ISIe4FfAJ40xw0mo/w9YCmwAWoH/Gufaj4rIdhHZ3tmZ2496Tra0UTtJSgskdwatc4y/WlupuWqBw8WhsP+sY031C+jq9dPe3ZOfTikFNIcC1Lo9Z9XdbunopEJ3Bs0Ju8XCu+qW8njnKZ7uPJ3v7hSUMq+HP7vprXzu4x/ipb37edMHb+UXv/s9A4OD+e6aGkc2g/PTwMIRXzekjo15joiUAmVA90TXioiVZGD+c2PMfcMnGGPajTGDxpgh4Ick02rOYYz5gTFmkzFmU01NzQxe3tSdON1KTWX5hOf0JGIMDA1RbrXlplNKFZE6p5sjkbNnzktKSlizbAkvvKRVW1T+NIeC1LrOTkc8nWbpXJUZXquNd9cv41cth9kyakdhBbVVlXzs5nfyiQ/8Cfc+/Chv+8gnefzF7ZoKVICyGZxvA5aLyGIRsZFc4Ll51DmbgVtSj98NPG6S/0s2AzenqrksBpYDW1P56LcD+4wx/z2yIRFZMOLLdwC7M/6KZuhYcwu1VRNn2xwOB6hzeopi1zOlcq3CaicxNEhvInbW8TXLFvPk1pfy1CulkjPnVaPSEVs6uqjWSi05VWlz8O76Zfz81AFe6G7Nd3cK0uKGOv7+w+/nnW9+A1/+/o/5s7//HHsOHc13t9QIWQvOUznktwKPkFy4eY8xZo+IfEFEbkyddjtQJSKHgU8Bn0lduwe4B9gLPAx83BgzCFwBvB+4ZoySif8pIq+KyC7gDcDfZuu1TdeJltZJK7UcDPdSr4tBlRqTiFDvcJ+T2nL+ymU8/9JOBvVjWpUnJ4J+qp2vBefGQFtXl86c50GN3cl76pdxV/NBHus4me/uFCQRYcPqFXzhEx/lvOVL+dA/fZFP/8c3aevsznfXFFneITRVzvDBUcc+N+JxDHjPONd+CfjSqGPP8v+3d99xcpXlAsd/z2yZ2d5rtmXTewipEJBOkCBSpAapooKIgCgIKPFyuXpRUbAgFyNeQDoXIx1CjEAKpO6mZzdlszXba7a/9485SWaTrWFn5uzm+X4+88mcMuc8583M+757zlug21vKxpjrvmy83mSMYX9JGUl9dAjd2VDDV+JTfRSVUkPPiJBwttVXMzs2+fC6uOgooiIj2LJrN1PHj/FjdOpEtb+uhrmpR1pj1tTV4XA4dGp1P0lwhnB1+lheL8qnrOUgV6aNIUCGZDc7rwoICODMuTOZO30y76xYycJv3821F53PrVddot9dP9Jvqo9U17r7rYb3MoziwY52DrQ06eRDSvUiPTScHfXVx6yfPCabFV9s8ENESkFhQ9dhFAtKyvp8Uqq8KzrIyTXpY9ndWMtjO9cf0xxOHRHicnHZ+Wex+PvfYvOufM678Q5ee3+ZPo30E62c+8iufftJT0nqtS15vjW+eaBOPqRUj5KcodS0tVDX1tpl/ZSxo1m+eq2folInso7OTsoa64kPOVI5319SpsMo2kBIQCCXpo4iyRnKT7eu4d/lRXRqB8gexcdEc+uVl3D7tZfz3JvvcvFt97JqY66/wzrhaC3QR/L27Sc1Ib7XfXbWV5Oq7c2V6pVDhPSQcHY2dL17Pm5kBnuLSiivOvauulLeVNpYT0Swk+CAI5MN7Svue3Qu5RsOEebFJXP5iFF8eKCAxdvWkFNboaOU9GJURhr3f/t6zp8/hx8/9iS3PvQo+QU6RKWvaOXcR7bv2UdKUu9DN26vr2ZEiFbOlerLiJBwttZ1Hdc8MDCQKeNG6agtyud211QxIrxrx8+C4jISY7VZi50kuUK5Jn0sJ0Un8OL+nTywZRXvle6lokUn5emOiDB76iQevfs2UhPjufquB/jZE0/rTKM+oJVzH9m1p4C0XirnrZ0dFBysJy1EJx9Sqi9ZYRFsrjt2VIFp48fw0crP/RCROpHl11SRHHZksqH29g7Kq6qJi9FhFO1GRBgfEcM3M8ZxRsIIdjTU8PC2Ndy/eSV/3beVFeVF5DfU0tje5u9QbSMoMJALTj+FR++5jeq6Ohbc/H3+8MKrNDVrG35v8epoLcrNGENeQSE3Jyf2uE9eQy2JzlCCHQE97qOUcksIDqG5s4MDLU0kenSgnjpuDM+9+S7NLS24nM5ejqDU4NlVU0lK+JHKefGBcmKjIgkK1PzcrkSEjNAIMkIjODcxnQMtByk62MD6mgN8eKCAytZmAkSIC3YRHxxCojOEBGcIia5Qkp2hxAa7cJxg85FEhIVy7UULOOeU2bzxwXL+/s/3+d6ib3D5grMJCtTq5GDS1PSB8qoaHCJEhvd8V3xbfRXpetdcqX4REUaGRrK5tpKzEo9UziPCQsnOGMGn6zZxzindThKs1KDLq67kwuxxh5f3FpWQGK9NWoYKhwjJrlCSXZ7j1BuaOtqpbWultr2F2rZWNtdVUlNZTGVrM62dnSS7QskIiWBkWCTZYVGMCAk7IYZrTIqL5btXX8bu/UW8/v5y/vLaUu6+4RoWnD4Phw5oMSi0cu4DedZILb3ZVlfFzJie76wrpbrKDI0gp7aSsxLTu6yfMXEc765YqZVz5RPGGPbWVpPq0eY8v6CQZK2cD2kiQlhgEGGBQaRybF+w5o52KlqbKWtuYkNNOe+W7qOuvZXM0AjGhkczLiKGUWFRuAKGbzUrO30E996yiM278vnDC6/yp5de54c3LeL0WSfpLOdf0vD91tjI9t17SU3queJ9sKOdwuYGLg7J9mFUSg1tWWGRfHRgP62dHV2ag508aTwPPP4Ura1tBAcH+TFCdSKoONjkfjLq0Ywqr6CIM2af5MeolLe5AgJJCwnv0k+suaOdooONFDU3klOYR2lLI8nOMMZFxDA2PJox4dFEBgX7MWrvmDxmFJNGZ7Nuy3Z+/odniI+J5t5brmPm5An+Dm3I0sq5D2zcvpOsEck9bt9WX0WaK5wgfRykVL+FBgSS5Apla10V06OPdLaOiYokPSWRlRtyOGPOyX6MUJ0I8muqSIs40vGzra2d0vKKPmeDVsOPKyCQUeFRjAp3fx/aOzspaW6k8GAj75Xt4y97txAeGMTosGhGW/uNCAkncBg0hRERZk6ewIyJ4/hsfQ53PfobxmZlcu8tixifneXv8IYcrZz7QO7OfM6Y3XMlIae2gszQyB63K6W6NyosinXVB7pUzgFmTp7A0o//rZVz5XX5NZUkhx25e1pQUkp8TLR2BlUEOhykh0aQHuruLGyMoaK1maKDjeTWVfLBgQJq2lpIc4WTHR5FdlgU2WGRJASHDNlmIQ6Hg9NmTmfu9MksX7OO63+8mK/MnsE9N12rM+YOgFbOvay6rp6a2npSErq/i2KMYXNtJV9P1SYtSg3UmPAoni/YQYfp7NIRa860Sfz4V3+gqbmZUJfLjxGq4S63vJSMyOjDy/n7i0jRu+aqGyJCgjXqyyEtHR2UtjRR2tzEivJCXtzfiAFGhUYxNsLdFCYrLHLI3V0PCgzkvFPnMH/GNN5e8RkLv3UXN1y2kFu+cTHO4OHXtGewaeXcyzbvzGdkemqPPZhLW5poN4a4YK1AKDVQUUFOIgKD2Vlfw4TII3dlIsPDGZuVwbKVX3DRWaf5MUI13G2uKOP6STMOL+/aW0ByolbOVf84AwLIDI0g0+Puen17G8XNjexurOOTymKqW1sYGRbJpIhYJkbGkRkaMWSGcQwNcfGNBWdzxuwZvPTOh7zx/nIW33kr80+e7u/QbE0r516WuyOPrNSUHrdvrClnVFjUkH2EpZS/TYiIZWVlSZfKObjvnr/x4XKtnCuvaWxrpbihnhER7maJxsD23fu4+sLz/ByZGqpEhMigYCKDghkfEQO4O5ruP9jA3qZ6/l1RTGNHGxMiYpkaFc+UqDiig+w/p0NCbAx3LLqCTdt28pNf/5HZUyfx4G03ER0Z0feHT0BD6znJELRh2w6y0nqunK+rPsDocJ1FTqnjNT4ymvW15bR2dnRZf/Kk8eTuyKPkQIWfIlPD3fbKcjIiogi0noyWVVZhDFrhUIPKFRDImPBozk5M48asCVyfMZ4Ep4tVVSU8sGUVP926mjeK8shrqKHTGH+H26tpE8byHz/4Ni2trSz89t18snajv0OyJa2ce1FHRwcbtu5g3MjMbrfXtrVQ3NxIRqhOPqTU8YoIDCbZGcrGmq6VcGdwMHOnT+G19z/2U2RquNtSWUZGVPTh5e15e8hMTUYfhCpviggKZmpUPF9LGcnt2VM4LS6FipaDPLN3C3duWsFTu3NZXVVKQ3ubv0PtlsvpZNHFF3DTZRdx369+z6NP/ZXWNnvG6i9aOfei7bv3ERUR3uNdlA1Wk5YTYUYxpbxpYmQsKyoKj1l/+qzpvPreR3R0dHTzKaW+nJwDpWR5dAbdkr+b9GSdTE75jkOE9NAITk8YwQ2ZE7guYzxRQcEsLy/k3txPeWTb5ywt3s2exlrb3VWfNCabxd+/lc278rnm7of0KacHrRV60eqNuUwYNbLn7VWl2qRFqUEwLjyagqZ6ypqbuqzPTE0hKjyc5WvW+SkyNVwZY9hwoJjs6FhrGbbl7SUjtffZoJXypsigYE6KTuCS1Gxuz57CyTGJFDY38NTuzdy5aQV/ys/hk4piKlub/R0qABFhodyx6AomjM7isjt+zNrcrf4OyRa0Q6gXrdyQw/QJY7vdVtXazP6DDSxMzvJtUEoNQ4EOB5Mj4/hXeSFXpnf9zZ1zyiyWvP5Pzjlltp+iU8PR/vpaWjs6SAlzPxndV1RCUFAg0ZE6Z4Wyh0CHg5FhkYwMi4QEqGtrZU9THWuqSnm5cCdhAUFMiIxhYkQs4yJiiPJTx1KHw8HCM+aTkZLM7T9/jHtvXsTlC872Syx2oXfOvaStvZ0NW3cwYVRWt9vXVJUyLjz6cEcipdSXMy0qnk8riznY0d5l/cwpE9lbWMzWvN1+ikwNR6uL9zMxLvHwSFvrt2xjTGa6tjdXthUZFMy0qHgWpmRxe/YULkzJJECEj8sLuX/zSu7b/BnP7tvK6qpSatpafB7f1HGjuf/W6/n986/y2DPP0dnZ6fMY7EJrhl7y+aYtpCYlEBEWdsw2YwyfVpYcHiZJKfXlRQc7yQyN5F/lXdueBwYEcO6ps3nqxTf8FJkajlYVFzA2Nv7w8rot2xmdmebHiJTqPxEh0RnKrJgkvp6azfdGTWVBkruy/q/yQh7Ysor7Nn/G3/ZtY211mc86l6YkxvPgbTfy6bqN3PXo47S2npgdRbVy7iXvfrKKGRPHd7ttV0MNrZ0dpIfoKC1KDaZZMYl8UFZA21HDKp41dyZrcraQt2+/nyJTw0mnMXxesp8JcQkAVFbXUllTx4jEBD9HptTxcYiQ7DpSWb89ewoXJGXiEPigrIB7cz/l59vW8GZxPvua6jBe7FwaERbGD29eRFVtHTfcv5i6hkavncuutHLuBR0dHSxb+Tkzp0zodvtHB/YzPSpBJx5SapAluUJJcoWy7EDXSrjL6eS8+XN48rmX/RSZGk42V5QRGhREfIj7yeiqjbmMHZmBI0CLVDU8OERIsirrl44Yxe3ZU5gTm0RJcyNP5udwT+6n/H3/DvIaarxSUQ8OCuK2ay4jLjqaq+9+gLKKykE/h51pTuIF67fuICoinKS42GO2Vbe2sLmuksmRx25TSn15p8Wn8k7pvmMew557ymy+yN3Gpu07/RSZGi7e3b2DmckjAPcoLSu+WM/ksaP8HJVS3hPocJAZGsmZCWncnDmBS1OzOdjRztN7NvOjzZ/xf0X5lLccHNRzOhwOrr3ofGZMHM8VP/gJ+QVFg3p8O9PKuRe8+t4yZk+d1O22d0r3MDkqDmdAgI+jUurEEBfsYkx4NG8U5XVZ7wwO5tLzzuCRPy7x6iNZNbwZY3hvz05mJbvbl+cXFNLR0UFako5vrk4MIkK8M4RT41K4MXMCFyZnUdzcyOJta3hs5zo21BwYtDHVRYSFZ87nojNPY9EPH2L9lu2Dcly708r5IKuuq2fZys85fdb0Y7bVtLWwsqqU2TE6Dq5S3nRafArrag6Q11DTZf2pM6bR1NzCK+9+5J/A1JC3qbwEZ0AgaRHuOSqWrfqCSWNG6Sgt6oQkVlv1sxPT+M7IyWSHRfJGUT4/yv2U90v3HTN61vE6beZ0brzsIr7zs1/wwaerB+WYdqaV80H2xgfLOWniuG5HaVlavJtJkbGEBwb5ITKlThyugEDOSkjjmb1buhQODoeDGy9dyK+XvEBp+YnVhlENjpe35TInJR1wdwRdv3UHJ/Uwn4VSJ5JAh4NJkXFcmzGOryZnkVNXwb25n/JaYR51ba1f+vjTxo/hnhuv4eEn/4dnXnlzWD8B1cr5IDrY3MKzr/+Ts+fNOmbbvqY61tYcYF5ssh8iU+rEMy4ihhRXGP+7b1uXTDw9JYlzT53N3b94nPaOjl6OoFRX5U2NfFyQz1fSswB4e8VnTBs3mhCXfyZvUcquUkPCuChlJIvSx1HS0sj9W1byQsF2qr7kzKRZaak8eNtNvPreMu771e+H7VCLWjkfRP/75tuMTE8lO31El/XtppNn921jflwqIQE6KatSvnJWQhp7m+p5u3Rvl/ULz5hPW1s7v1nygn8CU0PS81s3MDc1g/BgJwcqqli5PodZUyb6OyylbCs62Mm5iencmDmB+vY2Htq6mmf3baXiS3QejYuO4iffuYGS8kquuvsBisrKBzFie9DK+SApq6zimVf/waXnnXnMtv8ryidQHEzREVqU8qkgh4NLU7NZVr6/y+REDoeDb191Ce/+eyUvvvW+HyNUQ0VJQz2vbM/lvKzRGANLXv8nc6ZPJjwsxN+hKWV74YFBnJEwgpszJ9DW2cnD29bwP3s2U3zw+MYwdzmd3HbNZUwdN5rLvvcjPvxszSBH7F9aOR8EnZ2d3PvLJzjnlNmkJMR32fZ5VSmfVZawIClDxzVXyg8igoK5YsRolpbs5p3SvYebuESEhXH3jdfw5HOv8NLbH/g5SmV3j65ezlmZo0gIDWP5mrVU1tQya3L3c1kopboXGhjEafGp3JI1kUBx8F871vK7vI3sqK8ecBtyEeGC00/hjuuu4JE/LuHe/36Cmrp6L0XuW1o5HwSPP/siNXX1XHTm/C7rN9aU83zBDi4dkU2YdgJVym9igl1clTaWTyuKeXrPZpqsTqKJcbHcd+s3+ePfX+NXf3le26Crbr20bRM7qyr46six7NhTwKvvLuPic04nQCcdUuq4uAICmReXzK0jJ5HkDOWZvVv42dY1rCgvGvAIL6Mz0/n5nbfS3NLKBbfcySvvfETHEM/LvZqziMgCEdkhInkicl83250i8rK1fY2IZHlsu99av0NEzu/rmCIy0jpGnnXMYG9eG7jvmP/uby/xzorPuOO6Kwiwxi7vNIYPyvaxZN9WLknNJtEZ6u1QlFJ9iAwK5ur0sbR0dvDgllV8UV2GMYak+Dgeuu0mVm/M5dp7HiK/oLDvg6kuhnNe/3FBPk+uX8X3Zsxj554Cfvvsiyw881TioqO8eVqlTghBDgfTo+O5KXMC8+KSWV1Vwg9zPuHPu3PZWFNOW2dnv47jcjpZ9LUF3Hn9Vfz9rfe48Na7ePtfnw7ZGy7iraFoRCQA2AmcCxQCXwBXG2O2euxzGzDVGPMdEbkKuMQYc6WITAReBGYDqcBHwKGxqro9poi8ArxhjHlJRJ4CNhlj/tRbjDNnzjRr1649rusrKivn4SefprS8ku8t+gbRkRGAe1SWF/fvpLG9jQuTs4gO1l78StlNQVM9KyqKCMDB+ckZzIxOIkiEj1ev5c2PVnD+/LnccsXXyRqR4pN4RGSdMWamT042yIZrXt/e2cmzuev425b1fHvKLHLW5bJs5Rd8/ezTyRiho24p5S2N7W1sr69mV0MtB1qaGBcRw+TIOMZFxJDqCsPRRxNhYww5O/J4Z8VKqmpr+caCc/jaWaeR6aP8vDf9zeu9WTmfBzxsjDnfWr4fwBjzXx77vG/ts0pEAoFSIAG4z3PfQ/tZHzvmmMAvgHIg2RjTfvS5e3I8Gfbu/UU888qbfPDZ55x7yiwWnjmfBtNBbm0lKyuLKW5uZE5MMtOj4/v8Aiml/McYw+7GOjbVVlB4sIHxEbFMjYojxeEkZ20On3y+gay0VM49dQ5zp09m3MhMggK9M9rSEK+cD7u8vq2zgyv+8SJ0dpLVJKxctZak+FjOPWUOkeH6JFQpX2lqb2NPUx37mxoobG6kqb2NtJBw0kPDSXWFk+QMJc7pIjbI1e3M63uLSvhk7Ua+yNlCbHQUp82czqwpE5k0JpuUhHif9wXsb17vzXH9RgD7PZYLgTk97WNltLVAnLV+9VGfPTQ+YXfHjANqjDHt3ew/qB575jnKKqs4+9JzWdZWzdJN/wIg3BFIRlAop4TEEtDcxtbSEm+cXik1yMY6QsgIdVLUfJCl9fnUdLZBPPDV6ezshB0l2/n1zvXQ2gZtHYQGBRPhchHmdBISHIwzOIjgwEAiA4KY4Ixk2rjRzDtpqr8vy5eGXV6fX1TMjvIyOjfsoSI2mkknTSQuOoqC+hqorxns0yml+pBGEGnOaFqCO6nqaGVvbQ05VeXUd7bTaro2fXEALgnA6XDgkgCCR0aRnH0qrQdbeKeujJc/zKf1n63Q2QmdhrAQF+EuF6EulztPD3Ln6UEBAQQEBBDgcBDgcOBwCCKCIES4XNxz/gIiXd4ZremEG3RbRG4FbrUWG0RkRz8/Gg9UBDpDUhxBQTHyUnCAhLuCMUBnpwHI8UK8/dHe0Ehg+LEzktqBnWMDe8dn59jA3vENSmwBjgHfUjG1TZj29ubWhrotfewaD1R4LGcO9Fyqd18ir0ccAU5nSuIkRNgHHF/jx4Gz82+qP4Zy/Bq7fwxq7CJYtWef+M+K6n0djY3QNS/vS7/yem9WzouAdI/lNGtdd/sUWo86o4DKPj7b3fpKIFpEAq07Kt2dCwBjzNPA0wO9GBFZa9fHziKytq26RmM7DnaOz86xgb3js3NsYO/85DgMq7zen+z+ve3LUI5fY/ePoRw7eC8v9+ZoLV8AY6ye9cHAVcDSo/ZZClxvvb8c+Ni4G8EvBa6yeviPBMYAn/d0TOszy61jYB3zH168NqWUUm6a1yul1CDy2p1zq13h94D3gQBgiTFmi4j8HFhrjFkK/AV4TkTygCrcGTDWfq8AW4F24HZjTAdAd8e0Tvlj4CUReQTYYB1bKaWUF2ler5RSg8tro7UMNyJyq/WY1HY0tuNn5/jsHBvYOz47xwb2j0/5x1D/Xgzl+DV2/xjKsYP34tfKuVJKKaWUUjahcw8rpZRSSillE1o570Nf01L7OJZ0EVkuIltFZIuI3GmtjxWRD0Vkl/VvjJ/jDBCRDSLylrXs0+m2e4krWkReE5HtIrJNRObZKe1E5C7r/3WziLwoIi5/pZ2ILBGRAyKy2WNdt2klbk9YMeaIyAw/xfeY9X+bIyL/JyLRHtu6nSLeV7F5bLtHRIyIxFvLPk87ZU92KmsOGWiZ09v3WUSut/bfJSLX93ROL1xDv8ojcXdKftlav0ZEsjyO4bP8w+Oc/S6vbJru/S7P/J32PZQng5bWInKyiORan3lCpB8zHxlj9NXDC3dHpHwgGwgGNgET/RhPCjDDeh+Be3rricB/A/dZ6+8DfunndLsb+DvwlrX8CnCV9f4p4Lt+iutvwC3W+2Ag2i5ph3silT1AiEea3eCvtANOB2YAmz3WdZtWwFeBdwEB5gJr/BTfeUCg9f6XHvFNtH67TmCk9ZsO8GVs1vp03B0c9wHx/ko7fdnvZbeyxiOuAZU5PX2fgVhgt/VvjPU+xkfX0K/yCLgNeMp6fxXwsvXep/mHR9z9Lq/slu4MsDzzd9p3l2cPZlrjHoFqrvWZd4EL+ozJFz+OofoC5gHveyzfD9zv77g84vkHcC6wA0ix1qUAO/wYUxqwDDgLeMv6MlZwpNLUJU19GFeUlVnIUettkXYcmUExFvcoSm8B5/sz7YCsozKrbtMK+DNwdXf7+TK+o7ZdArxgve/yu8VdQZ7n69iA14BpwF6OVM79knb6stfL7mWNR1y9ljk9fZ+Bq4E/e6zvsp8X4+13eeSZL1h5cIW1vz/yjwGVVzZM9wGVZ3ZI+6Pz7MFKa2vbdo/1Xfbr6aXNWnrX3bTUgz5V9PGwHvucBKwBkowxJdamUiDJX3EBvwV+BByaT9cn0233w0igHPir9YjzGREJwyZpZ4wpAn4FFAAlQC2wDnuk3SE9pZUdfyc34b5DATaIT0QuBoqMMZuO2uT32JQt2P570M8yp6fr8Nf1/Zb+l0eHY7S211r7+yP2gZZXtkr34yjP7JT2hwxWWo+w3h+9vldaOR+CRCQceB34gTGmznObcf9p5pcheERkIXDAGLPOH+fvQyDux1Z/MsacBDTiflR1mJ/TLga4GHemnAqEAQv8EUt/+DOt+iIiD+AeM/sFf8cCICKhwE+An/o7FqWOh13LnN7YvDzqi63Lq74MtfKsL/5Ia62c964/01L7lIgE4c4kXzDGvGGtLhORFGt7CnDAT+GdCnxNRPYCL+F+lPg7rOm2rX38lYaFQKExZo21/BruzM8uaXcOsMcYU26MaQPewJ2edki7Q3pKK9v8TkTkBmAhcK2VoYL/4xuFu5DaZP020oD1IpJsg9iUPdj2ezDAMqen6/DH9Q20PDoco7U9Cqj0U+wDLa/slO4w8PLMTml/yGCldZH1/uj1vdLKee/6My21z1g9fP8CbDPG/MZjk+fU2Nfjp+msjTH3G2PSjDFZuNPqY2PMtdhgum1jTCmwX0TGWavOxj0roS3SDvfjv7kiEmr9Px+Kz+9p56GntFoKfNPqxT4XqPV4HOgzIrIA9yPsrxljmjw29TRFvE8YY3KNMYnGmCzrt1GIu5NdKTZJO+V3tiprDjmOMqen7/P7wHkiEmPdVT3PWuc1x1EeeV7T5db+Bj/kH8dRXtkm3S0DLc9sk/YeBiWtrW11IjLXSotv0p9y3BsN64fTC3fP3J24ewk/4OdY5uN+tJIDbLReX8XdNmsZsAv4CIi1QbqdwZHe8dm4f1B5wKuA008xTQfWWun3Ju4e1bZJO2AxsB3YDDyHu4e6X9IOeBF3W8E23JXJm3tKK9wdd/5g/UZygZl+ii8Pd5u/Q7+Npzz2f8CKbwf96Ck/2LEdtX0vRzqE+jzt9GXPl53KGo+YBlTm9PZ9xt0PJM963ejj6+izPAJc1nKetT3b4/M+yz88ztnv8sqO6c4AyjN/p313efZgpjUw00qHfOD3HNXRt7uXzhCqlFJKKaWUTWizFqWUUkoppWxCK+dKKaWUUkrZhFbOlVJKKaWUsgmtnCullFJKKWUTWjlXSimllFLKJrRyrmxNRIyIPO+xHCgi5SLy1nEeL1pEbvNYPqOnY4nIv0Rk5gCOHS4ifxaRfBFZZ31+johkicjm44lXKaVOZCISJyIbrVepiBR5LAcfte8PrBl5+zpmt3m7iASJyC9EZJeIrBeRVSJygbWtYfCuSqneaeVc2V0jMFlEQqzlc/lyM4RFA7f1tdNxegaoAsYYY04GbgTiv+xBPWZUU0qpE4oxptIYM90YMx14Cnj80LIxpvWo3X8A9Fk578V/ACnAZGPMDODrQMSXOB6gebgaOK2cq6HgHeBC6/3VuCcMAEBEYkXkTRHJEZHVIjLVWv+wiCyx7pDsFpHvWx/5BTDKuuvymLUuXEReE5HtIvKCNYsXHue4SUR+67H8LRF5/Kh9RgFzgAeNMZ0Axpg9xpi3rV0CROR/RGSLiHxw6I8N61hfiMgmEXn90F0fEXlWRJ4SkTXAf4vIKOv6ckXkEc+7OCJyr3WMHBFZbK0LE5G3reNuFpErjzPtlVLKVkTkbBHZYOWHS6wZJL8PpALLRWS5td+fRGStle8u7uOYocC3gDuMMS0AxpgyY8wrHvv8p5WnrhaRJGvdRSKyxornI4/1D4vIcyLyGfCciCSIyIdWLM+IyD4Ribf2XSQin1vl0p9FJMB6PWvl37kicpcXklLZlFbO1VDwEu4pfF3AVGCNx7bFwAZjzFTgJ8D/emwbD5wPzAZ+JiJBwH1AvnXX5V5rv5Nw33GZiHsGs1OPOv8rwEXW58F9R3zJUftMAjYaYzp6uIYxwB+MMZOAGuAya/0bxphZxphpwDbcM5MdkgacYoy5G/gd8DtjzBTcM5gBICLnWceejXtGuZNF5HRgAVBsjJlmjJkMvNdDXEopNZS4gGeBK638MBD4rjHmCaAYONMYc6a17wPGmJm4y42vHLp504PRQIExpq6H7WHAaiuv/jfuijzAp8BcY8xJuMuqH3l8ZiJwjjHmauBnuKelnwS8BmQAiMgE4ErgVOvpQAdwLe78fIQxZrJ1nX/tM2XUsKGVc2V7xpgcIAv3XfN3jto8H/fUwBhjPgbiRCTS2va2MabFGFMBHACSejjF58aYQuuO90brXJ7nbwA+BhaKyHggyBiTO8DL2GOM2Wi9X+dxjski8omI5OLOkCd5fOZVj8r+PNzTGwP83WOf86zXBmA97j9IxuCeVvhcEfmliJxmjKkdYLxKKWVHAbjz053W8t+A03vY9woRWY87f5yEu7J8vFqBQ/2TPPPwNOB9Kw+/l655+FJjzEHr/XzclXeMMe8B1db6s4GTgS9EZKO1nA3sBrJF5EkRWQD09EeDGoa0HZQaKpYCvwLOAOL6+ZkWj/cd9Px9789+z+C+M7+d7u9gbAGmiUhAD3fPjz7HoTb0zwJfN8ZsEpEbcF/fIY09xOtJgP8yxvz5mA0iM4CvAo+IyDJjzM/7cTyllBryRGQk8ENgljGmWkSexX3XvSd5QIaIRPZw97zNGGOs957lxJPAb4wxS0XkDOBhj8/0Nw//mzHm/m6uYRrup7/fAa4AburH8dQwoHfO1VCxBFjczR3rT3DfccbKGCt6eSwJUM9xdPAxxqwB0oFr8Gjz7rE9H1gLLD7UZl3co7RcePS+R4kASqwmM9f2st9qjjSFucpj/fvATSISbp1zhIgkikgq0GSMeR54DJjR1zUqpdQQ0AFkichoa/k6YIX13jN/j8RdOa612oFf0NtBjTFNwF+A34k1CozVTvwbfcQTxZFBCq7vZb/PcFewDzVHjLHWLwMuF5FEa1usiGRa7dEdxpjXgQfRPPyEonfO1ZBgjCkEnuhm08PAEhHJAZroPXPEGFMpIp+Je2jDd4G3e9v/KK8A040x1T1svwX4NZAnIgeBCtyPOXvzEO429OXWvz394fAD4HkReQB3+/FaAGPMB1abxVXW3wQNwCLc7ScfE5FOoA34bn8uUCmlbK4Zd7+fV8U9CsoXuEdxAXgaeE9Eio0xZ4rIBtxPO/fjrhz35UHgEWCriDTjrtz/tI/PPGzFUo27+ePIHvZbDLwoItcBq4BSoN4YUyEiDwIfiIgDd359O3AQ+Ku1DuCYO+tq+JIjT2mUUr0R93jojxtjlvnh3KHAQWOMEZGrgKuNMRf7Og6llFIDJyJOoMMY0y4i84A/WR1AlTqG3jlXqg8iEg18DmzyR8XccjLwe6vJTA3a9lAppYaSDOAV6054K0dGe1HqGHrnXCmllFJKKZvQDqFKKaWUUkrZhFbOlVJKKaWUsgmtnCullFJKKWUTWjlXSimllFLKJrRyrpRSSimllE1o5VwppZRSSimb+H+VK69eUclUcQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 864x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axs = plt.subplots(nrows = 1, ncols = 2, figsize=(12,5))\n",
    "wspace = 0.3  # the left side of the subplots of the figur\n",
    "plt.subplots_adjust(left, bottom, right, top, wspace, hspace)\n",
    "\n",
    "\n",
    "\n",
    "ax = sns.kdeplot(cust.MonthlyCharges[(cust[\"Churn\"] == 'No') ],\n",
    "                ax = axs[0],shade = True)\n",
    "ax = sns.kdeplot(cust.MonthlyCharges[(cust[\"Churn\"] == 'Yes') ],\n",
    "                ax = axs[0], shade= True)\n",
    "\n",
    "ax.legend([\"Not Churn\",\"Churn\"],loc='upper right')\n",
    "ax.set_ylabel('Density')\n",
    "ax.set_xlabel('Monthly Charges')\n",
    "ax.set_title('Churn by Monthly Charges')\n",
    "\n",
    "\n",
    "\n",
    "ax = sns.kdeplot(cust.TotalCharges[(cust[\"Churn\"] == 'No') ],\n",
    "                ax = axs[1],shade = True)\n",
    "ax = sns.kdeplot(cust.TotalCharges[(cust[\"Churn\"] == 'Yes') ],\n",
    "                ax = axs[1], shade= True)\n",
    "\n",
    "ax.legend([\"Not Churn\",\"Churn\"],loc='upper right')\n",
    "ax.set_ylabel('Density')\n",
    "ax.set_xlabel('Total Charges')\n",
    "ax.set_title('Churn by Total Charges')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c7dbc2f5",
   "metadata": {
    "papermill": {
     "duration": 0.022199,
     "end_time": "2022-07-11T16:31:51.330153",
     "exception": false,
     "start_time": "2022-07-11T16:31:51.307954",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### Building models and Prediction\n",
    "\n",
    "#### 1. Logistic Regression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "604a0b15",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-11T16:31:51.377181Z",
     "iopub.status.busy": "2022-07-11T16:31:51.376762Z",
     "iopub.status.idle": "2022-07-11T16:31:51.385983Z",
     "shell.execute_reply": "2022-07-11T16:31:51.384920Z"
    },
    "papermill": {
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     "end_time": "2022-07-11T16:31:51.388572",
     "exception": false,
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     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "#starting with prediction\n",
    "#logisitic regression\n",
    "\n",
    "X = cust_final.drop('Churn', axis = 1)\n",
    "y = cust_final['Churn']  \n",
    "features = X.columns.values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "b8dd3f14",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-11T16:31:51.436641Z",
     "iopub.status.busy": "2022-07-11T16:31:51.435841Z",
     "iopub.status.idle": "2022-07-11T16:31:51.600437Z",
     "shell.execute_reply": "2022-07-11T16:31:51.599277Z"
    },
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     "start_time": "2022-07-11T16:31:51.411716",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "#scaling the features\n",
    "from sklearn.preprocessing import MinMaxScaler\n",
    "scaler = MinMaxScaler(feature_range = (0,1))\n",
    "scaler.fit(X)\n",
    "X = pd.DataFrame(scaler.transform(X))\n",
    "X.columns = features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "56143014",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-11T16:31:51.650796Z",
     "iopub.status.busy": "2022-07-11T16:31:51.649934Z",
     "iopub.status.idle": "2022-07-11T16:31:51.682213Z",
     "shell.execute_reply": "2022-07-11T16:31:51.681011Z"
    },
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     "duration": 0.058713,
     "end_time": "2022-07-11T16:31:51.684600",
     "exception": false,
     "start_time": "2022-07-11T16:31:51.625887",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>SeniorCitizen</th>\n",
       "      <th>tenure</th>\n",
       "      <th>MonthlyCharges</th>\n",
       "      <th>TotalCharges</th>\n",
       "      <th>gender_Female</th>\n",
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       "      <th>Dependents_No</th>\n",
       "      <th>Dependents_Yes</th>\n",
       "      <th>...</th>\n",
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       "      <th>Contract_Month-to-month</th>\n",
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       "      <th>PaperlessBilling_No</th>\n",
       "      <th>PaperlessBilling_Yes</th>\n",
       "      <th>PaymentMethod_Bank transfer (automatic)</th>\n",
       "      <th>PaymentMethod_Credit card (automatic)</th>\n",
       "      <th>PaymentMethod_Electronic check</th>\n",
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      "text/plain": [
       "   SeniorCitizen    tenure  MonthlyCharges  TotalCharges  gender_Female  \\\n",
       "0            0.0  0.000000        0.115423      0.001275            1.0   \n",
       "1            0.0  0.464789        0.385075      0.215867            0.0   \n",
       "2            0.0  0.014085        0.354229      0.010310            0.0   \n",
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       "4            0.0  0.014085        0.521891      0.015330            1.0   \n",
       "\n",
       "   gender_Male  Partner_No  Partner_Yes  Dependents_No  Dependents_Yes  ...  \\\n",
       "0          0.0         0.0          1.0            1.0             0.0  ...   \n",
       "1          1.0         1.0          0.0            1.0             0.0  ...   \n",
       "2          1.0         1.0          0.0            1.0             0.0  ...   \n",
       "3          1.0         1.0          0.0            1.0             0.0  ...   \n",
       "4          0.0         1.0          0.0            1.0             0.0  ...   \n",
       "\n",
       "   StreamingMovies_Yes  Contract_Month-to-month  Contract_One year  \\\n",
       "0                  0.0                      1.0                0.0   \n",
       "1                  0.0                      0.0                1.0   \n",
       "2                  0.0                      1.0                0.0   \n",
       "3                  0.0                      0.0                1.0   \n",
       "4                  0.0                      1.0                0.0   \n",
       "\n",
       "   Contract_Two year  PaperlessBilling_No  PaperlessBilling_Yes  \\\n",
       "0                0.0                  0.0                   1.0   \n",
       "1                0.0                  1.0                   0.0   \n",
       "2                0.0                  0.0                   1.0   \n",
       "3                0.0                  1.0                   0.0   \n",
       "4                0.0                  0.0                   1.0   \n",
       "\n",
       "   PaymentMethod_Bank transfer (automatic)  \\\n",
       "0                                      0.0   \n",
       "1                                      0.0   \n",
       "2                                      0.0   \n",
       "3                                      1.0   \n",
       "4                                      0.0   \n",
       "\n",
       "   PaymentMethod_Credit card (automatic)  PaymentMethod_Electronic check  \\\n",
       "0                                    0.0                             1.0   \n",
       "1                                    0.0                             0.0   \n",
       "2                                    0.0                             0.0   \n",
       "3                                    0.0                             0.0   \n",
       "4                                    0.0                             1.0   \n",
       "\n",
       "   PaymentMethod_Mailed check  \n",
       "0                         0.0  \n",
       "1                         1.0  \n",
       "2                         1.0  \n",
       "3                         0.0  \n",
       "4                         0.0  \n",
       "\n",
       "[5 rows x 45 columns]"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "508fcf39",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-11T16:31:51.732825Z",
     "iopub.status.busy": "2022-07-11T16:31:51.732023Z",
     "iopub.status.idle": "2022-07-11T16:31:51.803992Z",
     "shell.execute_reply": "2022-07-11T16:31:51.802711Z"
    },
    "papermill": {
     "duration": 0.100246,
     "end_time": "2022-07-11T16:31:51.807630",
     "exception": false,
     "start_time": "2022-07-11T16:31:51.707384",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3, random_state=101)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "23774b2b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-11T16:31:51.855517Z",
     "iopub.status.busy": "2022-07-11T16:31:51.855116Z",
     "iopub.status.idle": "2022-07-11T16:31:52.068329Z",
     "shell.execute_reply": "2022-07-11T16:31:52.066910Z"
    },
    "papermill": {
     "duration": 0.241526,
     "end_time": "2022-07-11T16:31:52.072164",
     "exception": false,
     "start_time": "2022-07-11T16:31:51.830638",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn import metrics\n",
    "log_reg = LogisticRegression()\n",
    "log_reg.fit(X_train, y_train)\n",
    "pred = log_reg.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "e19b43d7",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-11T16:31:52.162098Z",
     "iopub.status.busy": "2022-07-11T16:31:52.161478Z",
     "iopub.status.idle": "2022-07-11T16:31:52.568610Z",
     "shell.execute_reply": "2022-07-11T16:31:52.567108Z"
    },
    "papermill": {
     "duration": 0.455363,
     "end_time": "2022-07-11T16:31:52.570946",
     "exception": false,
     "start_time": "2022-07-11T16:31:52.115583",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Features with negative influence on churn')"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Values with positive influence on churn\n",
    "coef = pd.Series(log_reg.coef_[0], index = features)\n",
    "\n",
    "fig, axs = plt.subplots(nrows = 1, ncols = 2, figsize=(12,5))\n",
    "\n",
    "ax = coef.sort_values(ascending = False)[:10].plot(kind = 'bar', ax = axs[0])\n",
    "ax.set_title('Features with positive influence on churn')\n",
    "\n",
    "ax = coef.sort_values(ascending = False)[-10:].plot(kind = 'bar', ax = axs[1])\n",
    "ax.set_title('Features with negative influence on churn')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "26201fd4",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-11T16:31:52.621896Z",
     "iopub.status.busy": "2022-07-11T16:31:52.621462Z",
     "iopub.status.idle": "2022-07-11T16:31:52.630117Z",
     "shell.execute_reply": "2022-07-11T16:31:52.628913Z"
    },
    "papermill": {
     "duration": 0.037817,
     "end_time": "2022-07-11T16:31:52.633083",
     "exception": false,
     "start_time": "2022-07-11T16:31:52.595266",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The Model has an accuarcy of 80.7583 %\n"
     ]
    }
   ],
   "source": [
    "print('The Model has an accuarcy of', round(metrics.accuracy_score(y_test, pred)*100, 4), '%')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "17b2c1b3",
   "metadata": {
    "papermill": {
     "duration": 0.0237,
     "end_time": "2022-07-11T16:31:52.681936",
     "exception": false,
     "start_time": "2022-07-11T16:31:52.658236",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "#### Findings\n",
    "\n",
    "* As we already thought during the EDA, the charges and the contract type have a high influence on churn\n",
    "* Especially the tenure has a negative impact on churn"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e58a3b5f",
   "metadata": {
    "papermill": {
     "duration": 0.024514,
     "end_time": "2022-07-11T16:31:52.731097",
     "exception": false,
     "start_time": "2022-07-11T16:31:52.706583",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### Random Forest Classifier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "d0f4433f",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-11T16:31:52.782426Z",
     "iopub.status.busy": "2022-07-11T16:31:52.781600Z",
     "iopub.status.idle": "2022-07-11T16:31:56.398154Z",
     "shell.execute_reply": "2022-07-11T16:31:56.397235Z"
    },
    "papermill": {
     "duration": 3.645574,
     "end_time": "2022-07-11T16:31:56.401039",
     "exception": false,
     "start_time": "2022-07-11T16:31:52.755465",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "RandomForestClassifier(max_leaf_nodes=30, n_estimators=1000, n_jobs=-1)"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Building the model\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "\n",
    "rf_model = RandomForestClassifier(n_estimators = 1000, max_features = \"auto\", max_leaf_nodes = 30, n_jobs = -1)\n",
    "\n",
    "rf_model.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "be783d74",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-11T16:31:56.452515Z",
     "iopub.status.busy": "2022-07-11T16:31:56.452111Z",
     "iopub.status.idle": "2022-07-11T16:31:56.968114Z",
     "shell.execute_reply": "2022-07-11T16:31:56.966829Z"
    },
    "papermill": {
     "duration": 0.544845,
     "end_time": "2022-07-11T16:31:56.971297",
     "exception": false,
     "start_time": "2022-07-11T16:31:56.426452",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy of the Model is:  80.9479 %\n"
     ]
    }
   ],
   "source": [
    "#Making the Predictions\n",
    "pred = rf_model.predict(X_test)\n",
    "\n",
    "print('Accuracy of the Model is: ', round(metrics.accuracy_score(y_test, pred)*100, 4), '%')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "69594d02",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-11T16:31:57.022413Z",
     "iopub.status.busy": "2022-07-11T16:31:57.022029Z",
     "iopub.status.idle": "2022-07-11T16:31:57.492941Z",
     "shell.execute_reply": "2022-07-11T16:31:57.491814Z"
    },
    "papermill": {
     "duration": 0.499658,
     "end_time": "2022-07-11T16:31:57.495712",
     "exception": false,
     "start_time": "2022-07-11T16:31:56.996054",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                                  Weight\n",
      "Contract_Month-to-month         0.154473\n",
      "tenure                          0.138017\n",
      "TotalCharges                    0.098277\n",
      "TechSupport_No                  0.075323\n",
      "InternetService_Fiber optic     0.071358\n",
      "OnlineSecurity_No               0.069088\n",
      "MonthlyCharges                  0.052552\n",
      "PaymentMethod_Electronic check  0.048368\n",
      "Contract_Two year               0.047595\n",
      "InternetService_DSL             0.024471\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Weight of features on churn probability')"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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i0UcfZYUVVsA2H/rQh9hoo404/PDDF/v12r03kq63Pa3d/nFGH0IIPXbqqaey1VZbsemmm/Lwww9z0EEHFT1+dMaGEEKPHX744Ut0Br+k4ow+hBBqLhJ9CKFv9VsfYj9YnPckEn0IoS9NmDCBBx54IJJ9k0Y9+gkTJizS86KNPoTQl9Zee23mzp27yLXX666xwtSiiEQfQuhLSy+99CKtohSGFk03IYRQcx0lekm7Srpd0hxJR7Z5/BWSbpC0QNJCs5kkrShprqSvdyPoEEIInRsx0UsaB3wD2A2YCkyXNLVlt7uBA4AfDPEynwZ+t/hhhhBCWFydnNFvC8yxfaftp4BzgD2ad7D9N9s3Ac+2PlnS1sDqwKVdiDeEEMIi6iTRrwXc03R/bt42IklLAV8CPrrooYUQQuiGXnfGfhC42Pbc4XaSdKCkWZJmxVCqEELork6GV84D1mm6v3be1omXAS+X9EFgBWAZSY/aHtSha/sU4BRI1Ss7fO0QQggd6CTRzwQ2kjSFlOD3Bvbp5MVt79u4LekAYFprkh+tolRyCGG0GLHpxvYC4GDgEuBW4DzbsyUdJ2l3AEnbSJoL7AV8W9LsoV8xhBBCSR3NjLV9MXBxy7ajm27PJDXpDPca3wW+u8gRhhBCWCIxMzaEEGouEn0IIdRcJPoQQqi5SPQhhFBzkehDCKHmItGHEELNRaIPIYSai0QfQgg1F4k+hBBqLhJ9CCHUXCT6EEKouUj0IYRQc5HoQwih5iLRhxBCzUWiDyGEmotEH0IINReJPoQQai4SfQgh1FxHiV7SrpJulzRH0kKLe0t6haQbJC2QtGfT9q0kXSNptqSbJL2jm8GHEEIY2YiJXtI44BvAbsBUYLqkqS273Q0cAPygZfvjwH62NwV2BU6StNISxhxCCGERdLI4+LbAHNt3Akg6B9gDuKWxg+2/5ceebX6i7f/XdPteSf8CJgMPLWngIYQQOtNJ081awD1N9+fmbYtE0rbAMsAdbR47UNIsSbPuu+++RX3pEEIIwyjSGStpDeAs4N22n2193PYptqfZnjZ58uQSIYUQwpjRSaKfB6zTdH/tvK0jklYEfgEcZfsPixZeCCGEJdVJop8JbCRpiqRlgL2BCzt58bz/T4Dv2b5g8cMMIYSwuEZM9LYXAAcDlwC3AufZni3pOEm7A0jaRtJcYC/g25Jm56e/HXgFcICkG/O/rXrxg4QQQmivk1E32L4YuLhl29FNt2eSmnRan/d94PtLGGMIIYQlEDNjQwih5iLRhxBCzUWiDyGEmotEH0IINReJPoQQai4SfQgh1Fwk+hBCqLlI9CGEUHOR6EMIoeYi0YcQQs1Fog8hhJqLRB9CCDUXiT6EEGouEn0IIdRcJPoQQqi5SPQhhFBzkehDCKHmItGHEELNdZToJe0q6XZJcyQd2ebxV0i6QdICSXu2PLa/pL/kf/t3K/AQQgidGTHRSxoHfAPYDZgKTJc0tWW3u4EDgB+0PHdl4BjgpcC2wDGSnr/kYYcQQuhUJ2f02wJzbN9p+yngHGCP5h1s/832TcCzLc/dBbjM9r9tPwhcBuzahbhDCCF0qJNEvxZwT9P9uXlbJzp6rqQDJc2SNOu+++7r8KVDCCF0oi86Y22fYnua7WmTJ0+uOpwQQqiVThL9PGCdpvtr522dWJLnhhBC6ILxHewzE9hI0hRSkt4b2KfD178E+GxTB+zrgE8ucpRhSJvssufIO43g9ksu6EIkIYR+NeIZve0FwMGkpH0rcJ7t2ZKOk7Q7gKRtJM0F9gK+LWl2fu6/gU+TvixmAsflbSGEEArp5Iwe2xcDF7dsO7rp9kxSs0y7554OnL4EMYYQQlgCfdEZG0IIoXci0YcQQs1Fog8hhJqLRB9CCDUXiT6EEGouEn0IIdRcJPoQQqi5SPQhhFBzkehDCKHmItGHEELNRaIPIYSai0QfQgg1F4k+hBBqLhJ9CCHUXCT6EEKouUj0IYRQc5HoQwih5jpK9JJ2lXS7pDmSjmzz+LKSzs2PXytpvbx9aUlnSrpZ0q2SYr3YEEIobMREL2kc8A1gN2AqMF3S1Jbd3gs8aHtD4ETg83n7XsCytjcHtgYOanwJhBBCKKOTM/ptgTm277T9FHAOsEfLPnsAZ+bbFwCvkSTAwPKSxgPLAU8Bj3Ql8hBCCB3pJNGvBdzTdH9u3tZ2H9sLgIeBVUhJ/zHg78DdwAm2/72EMYcQQlgEve6M3RZ4BlgTmAJ8RNL6rTtJOlDSLEmz7rvvvh6HFEIIY0sniX4esE7T/bXztrb75GaaScADwD7Ar2w/bftfwNXAtNYD2D7F9jTb0yZPnrzoP0UIIYQhdZLoZwIbSZoiaRlgb+DCln0uBPbPt/cEfm3bpOaaVwNIWh7YDritG4GHEELozIiJPre5HwxcAtwKnGd7tqTjJO2edzsNWEXSHOAIoDEE8xvACpJmk74wzrB9U7d/iBBCCEMb38lOti8GLm7ZdnTT7SdIQylbn/dou+0hhBDKiZmxIYRQcx2d0YcwnE122XOJX+P2Sy7oQiQhhHbijD6EEGouEn0IIdRcJPoQQqi5SPQhhFBzkehDCKHmYtRNqI0lHf0TI39CXcUZfQgh1Fwk+hBCqLlougmhi2LyWOhHcUYfQgg1F4k+hBBqLhJ9CCHUXCT6EEKouUj0IYRQc5HoQwih5iLRhxBCzXWU6CXtKul2SXMkHdnm8WUlnZsfv1bSek2PbSHpGkmzJd0saUIX4w8hhDCCERO9pHGkRb53A6YC0yVNbdntvcCDtjcETgQ+n587Hvg+8J+2NwV2Ap7uWvQhhBBG1MkZ/bbAHNt32n4KOAfYo2WfPYAz8+0LgNdIEvA64CbbfwKw/YDtZ7oTegghhE50kujXAu5puj83b2u7j+0FwMPAKsDGgCVdIukGSR9f8pBDCCEsil7XuhkP7AhsAzwOXCHpettXNO8k6UDgQIB11123xyGFEMLY0skZ/Txgnab7a+dtbffJ7fKTgAdIZ/+/s32/7ceBi4GXtB7A9im2p9meNnny5EX/KUIIIQypk0Q/E9hI0hRJywB7Axe27HMhsH++vSfwa9sGLgE2l/S8/AXwSuCW7oQeQgihEyM23dheIOlgUtIeB5xue7ak44BZti8ETgPOkjQH+DfpywDbD0r6MunLwsDFtn/Ro58lhBBCGx210du+mNTs0rzt6KbbTwB7DfHc75OGWIYQQqhAzIwNIYSai0QfQgg1F4k+hBBqLhJ9CCHUXCT6EEKouV7PjA0hVGCTXfZcoufffskFXYok9IM4ow8hhJqLRB9CCDUXiT6EEGouEn0IIdRcdMaGEHpiSTuEITqFuyUSfQih1mIEUjTdhBBC7UWiDyGEmotEH0IINReJPoQQai4SfQgh1Fwk+hBCqLmOEr2kXSXdLmmOpCPbPL6spHPz49dKWq/l8XUlPSrpo12KO4QQQodGTPSSxgHfAHYDpgLTJU1t2e29wIO2NwROBD7f8viXgV8uebghhBAWVSdn9NsCc2zfafsp4Bxgj5Z99gDOzLcvAF4jSQCS3gz8FZjdlYhDCCEskk4S/VrAPU335+ZtbfexvQB4GFhF0grAJ4BPLXmoIYQQFkevO2OPBU60/ehwO0k6UNIsSbPuu+++HocUQghjSye1buYB6zTdXztva7fPXEnjgUnAA8BLgT0lfQFYCXhW0hO2v978ZNunAKcATJs2zYvxc4QQQhhCJ4l+JrCRpCmkhL43sE/LPhcC+wPXAHsCv7Zt4OWNHSQdCzzamuRDCCH01oiJ3vYCSQcDlwDjgNNtz5Z0HDDL9oXAacBZkuYA/yZ9GYQQQugDHZUptn0xcHHLtqObbj8B7DXCaxy7GPGFEEJYQjEzNoQQai4SfQgh1Fwk+hBCqLlI9CGEUHOR6EMIoeYi0YcQQs1Fog8hhJqLRB9CCDUXiT6EEGouEn0IIdRcJPoQQqi5SPQhhFBzkehDCKHmItGHEELNRaIPIYSa66gefQghhMW3yS57LvFr3H7JBYv93DijDyGEmotEH0IINddRope0q6TbJc2RdGSbx5eVdG5+/FpJ6+XtO0u6XtLN+f9Xdzn+EEIIIxgx0UsaB3wD2A2YCkyXNLVlt/cCD9reEDgR+Hzefj/wJtubA/sDZ3Ur8BBCCJ3p5Ix+W2CO7TttPwWcA+zRss8ewJn59gXAayTJ9h9t35u3zwaWk7RsNwIPIYTQmU4S/VrAPU335+ZtbfexvQB4GFilZZ+3ATfYfrL1AJIOlDRL0qz77ruv09hDCCF0oEhnrKRNSc05B7V73PYptqfZnjZ58uQSIYUQwpjRSaKfB6zTdH/tvK3tPpLGA5OAB/L9tYGfAPvZvmNJAw4hhLBoOkn0M4GNJE2RtAywN3Bhyz4XkjpbAfYEfm3bklYCfgEcafvqLsUcQghhEYyY6HOb+8HAJcCtwHm2Z0s6TtLuebfTgFUkzQGOABpDMA8GNgSOlnRj/rda13+KEEIIQ+qoBILti4GLW7Yd3XT7CWCvNs87Hjh+CWMMIYSwBGJmbAgh1Fwk+hBCqLlI9CGEUHOR6EMIoeYi0YcQQs1Fog8hhJqLRB9CCDUXiT6EEGouEn0IIdRcJPoQQqi5SPQhhFBzkehDCKHmItGHEELNRaIPIYSai0QfQgg1F4k+hBBqLhJ9CCHUXCT6EEKouY4SvaRdJd0uaY6kI9s8vqykc/Pj10par+mxT+btt0vapYuxhxBC6MCIiV7SOOAbwG7AVGC6pKktu70XeND2hsCJwOfzc6cCewObArsCJ+fXCyGEUEgnZ/TbAnNs32n7KeAcYI+WffYAzsy3LwBeI0l5+zm2n7T9V2BOfr0QQgiFjO9gn7WAe5ruzwVeOtQ+thdIehhYJW//Q8tz12o9gKQDgQPz3Ucl3d5R9ENbFbh/uB3S91DPDRtHP8TQL3GMoRj6JY5+iKFf4uiHGLoRxwuHeqCTRN9ztk8BTunW60maZXtat15vNMfRDzH0Sxz9EEO/xNEPMfRLHP0QQ6/j6KTpZh6wTtP9tfO2tvtIGg9MAh7o8LkhhBB6qJNEPxPYSNIUScuQOlcvbNnnQmD/fHtP4Ne2nbfvnUflTAE2Aq7rTughhBA6MWLTTW5zPxi4BBgHnG57tqTjgFm2LwROA86SNAf4N+nLgLzfecAtwALgQ7af6dHP0qxrzUBLqB/i6IcYoD/i6IcYoD/i6IcYoD/i6IcYoIdxKJ14hxBCqKuYGRtCCDUXiT6EEGouEn0IoRhJK7fZNqXg8cdJOqHU8fpFJPouk7ScpE0qPP5ekibm2/8t6ceSXlJRLKtLemP+t1pFMZwpaaWm+8+XdHoVsQQAfi5pxcadXCbl56UOngeD7FjqeP2iNole0mRJ/yXpFEmnN/4VjuFNwI3Ar/L9rSS1DkXttf+xPV/SjsBrSSOivlk4BiS9nTSUdi/g7cC1kvYsHQewhe2HGndsPwj8RwVxVP7FJ2kHScvn2++U9GVJQ86m7JHPkpL9CpK2Bs4H3lk4hj9KulDSuyS9tfGvcAxDknR3t1+zL2bGdsnPgKuAy4ESQzjbOZZUy+c3ALZvLHlZmjV+9jcAp9j+haTjC8cAcBSwje1/QfoiJv1uLigcx1KSnp8TfKPpoPjnPn/xfZH02RDwNUkfs13y/fgmsKWkLYGPAN8Bvge8slQA+fO4NHApMBF4i+3/V+r42QTShM5XN4cG/LhwHEPpes2FOiX659n+RMUxPG374ZaaFKXHr86T9G1gZ+Dzkpalmiu3pRpJPnugoji+BFwj6XzSH9CewGcqiKMfvvgW2LakPYCv2z5N0ntLHFjS1xj8tzAJuAM4WBK2DykRB4Dtd5c61mLqes6oU6K/SNLrbV9cYQyzJe0DjJO0EXAIMKNwDG8nlYQ+wfZDktYAPlY4BoBfSboE+GG+/w6g+O/G9vckzWLg7O2ttm8pHQf98cU3X9IngXcBL5e0FLB0oWPParl/faHjLkTSBFJp9U1JZ/cA2H5PwRiOGOohYIWuH2+0T5iSNJ/0DShgeeBJ4Ol837ZXHObp3Y7leaQzt9flTZcAx9t+olQMOY4dgY1sn5HPHFfIZaKLkvQ2YId89yrbPyl47BVtP9JulAeA7X+XiiXH80VgCwZ/8d1U8ipU0guAfYCZtq+StC6wk+3vFYxheeCJxgz5vD7FsrYfLxjD+cBtpPfiOGBf4FbbhxaM4ZjhHrf9qa4eb7Qn+n6RP7CX235VxXEcA0wDNrG9saQ1gfNt7zDCU2tF0kW23yjprwy+FG6cAKxfQUyVffE1xfBC0knA5fnEZJzt+QWP/wfgtbYfzfdXAC61vX3BGP5o+z8k3WR7i9xncJXt7UrFUFptmm4kXWH7NSNt6xXbz0h6VtIk2w+XOOYQ3kIaVXJDjuvexnDLEtok1ma2vUGJOGy/Mf9fujN8SLZ/BPyoquNLej9p3YeVgQ1Ia0N8CyjyN5JNaCR5ANuP5i+ckp7O/z8kaTPgH0DRUVD5d/Eb239R6tQ7DXgbcBewv+0/dvN4oz7R5/a25YFVJT2fgR7rFWmzyEmPPQrcLOky4LHGxpIdTcBTucPN8Nylckmt9bSXIvUbfBTo6oe3E1WfAPTLF1/2IdKosGvzwf9SwTDPxyS9xPYNAHmI5f8VjuGUnCv+h1RhdwXg6MIxHAp8N9+eDmwJrE86Sfsq8PJuHmzUJ3rgIOAwYE1SB08j0T8CfL1wLD+m+iFa5+VRNyvls4b3AKeWOrjtBwByR9+7SB3BNwJvKNkJmk8Ankf1JwD99MX3pO2nGqPClNaOKN12exhwvqR7Sb+TF5D6K4qx/Z1887ek5FqFBbYbVxZvBL6X/3Yul/SFbh+sNm30kj5s+2tVx9EPJO1M6hAWcIntywoee2nSl8vhwO+Bz9meU+r4TXEcysAJwL1NDz0CnGq76ElAmy++z5Ye/ZMTyEPAfsCHgQ8Ct9g+qnAcSwON2eO3NyW8UsdfnTRxa03bu+XZuS+zfVrBGG4gzXV5kNRc82rbs/Njt9p+cVePV5dEDyBpe2A9mq5UCo8oaHuZXkXHX1UkzSWtPXASsNAMP9tFr3iqPgHoly++HMtSpGGFz50EAN9xwSSQ2+OPAF5o+/15GPImti8qGMMvgTOAo2xvma9s/mh784IxvBH4NmmNj5/bfn/e/krg47bf0NXj1SXRSzqL1MF0IwOzQ12yfVzSKk13J5Cm/69su1j7X9Nw02YPk8Yxf8T2nT0+/nfbHL/BJccqQ6o9BHyAVN/EpNnT3yo15LXfvviqJulcUhPrfrY3y4l/hu2tCsYw0/Y2jdE3eduNJWPIxxwPTGzM2s7blifl5UeHfuaiq0MbfcM0YGrJs5NWjfbpJidJup6yHT0nAXOBH5DO2vYmfQHeAJwO7NTLg9s+oJP9JO1v+8xexpKdCcwHGmf1+wBnkb6ES7ic9AWzZf7XrOi0e0k3M/RJwPFtPr+9sIHtd0iaDmD7cbVMJS/gsXxS1hiwsB3pfShtErCPpBfl+7cCP+zF76FOif7PpI6dv1cVgAZXiVyK9OVT+j3e3XZzQjkln618QtJ/FY5lOIeSknCvbWZ7atP9KyUVaxvvsy++X5Kudn+Q7+9N6rD+B2kEyJt6fHyAp/JVViPJbkCa5FjSR0ijbTaQdDUwmVQaoxhJLwZ+TWo++yPppGwb4L8kvdr2bd08Xp0S/arALZKuo+mDY3v3gjF8qen2AuBvpBEWJT2uVECrUUNlT6DRTNFP7XSlzuJukLSd7T8ASHopC0/H7wclvvhea7v5ZORmSTfYfomkUhUkjyFVd11H0tmkCWQHFDo2ALavz23hm5A+h8U7hIFPA4faPq95Y55U9xnSmPquqVOiP7bqAKqeFZvtC3wFOJmU2P8AvDOfRR1cZWAtSn3pbA3M0EDp13WB2xvNGLa3KBTHSEp88Y2TtK3t6wAkbUPqDIR0YtJzti/LI062I/3Mh9q+v8SxG3Jz6mmkZpIHR9q/Rza3vdBVhO0fSfpstw9Wm0Rv+7d52NQ2edN1HlxEqueUKkW+jYVH/hxX6PjjgA/aHuoS/Pcl4uhQqTP6XQsdZ0mV+OJ7L3BGLjsAqe/ivbkD8H8LHL9hAmlY4XhgqlL1yt8VPP47gHcDM5UK3p1BKsNQ8or3scV8bLHUJtGrP+p9/4zUqXM95dsdG2UY+mL1HElT3FJIrWXb1SXisH2XUv31xkzDq2z/qcSxF1FPv/jyScDLbW8uaRJAS6mO89o/s+txfJ6UaGcDz+bNBool+jy89ShJ/0OarHQ68IykM4CvuEzBu9XUvoKlSH0GXVWn4ZV/AnZ2S73vlo7JXsfwZ9ublTreEDF8kzTz83wGl2EoPX79hpb2YCRdb3vrwnEcCryfgdEtbyEtyFJ0bL2kcc4VG4d4/Ou2e9q0Juk629v28hgdxHA7adWv4idCLXFsQTqrfz2pQ/Rs0hDcd5UYZqnC1Strc0ZPf9T7niFpc9s3Fz5us0pXz8lDxTYFJmnw8mwr0lT7u6D3Ai+1/ViO7/PANQwMtyzlL5J+BJzRbkZsr5N8drWkrwPnMvgk4IYCx264k1QDv7JEn9voHyK10x/Z9KVzraQiVV47TeSSPml7iZvV6nRG367e9822P14whluADYG/kj7IjZK4/dLh13NKqxe9GdidNIStYT5wju2iC7HkTtdtGhOkcg2cmSVnQebjTiQNZ3w36QTkdNL78UjBGK5ss9m2X91me7eP3Vhhai3SfIIrGDw6ruTExvV7PXGwW9pdGS/W69Ql0UP19b41xELLtu8qGEM/rJ4zDviE7a6PHliMWI4A9gcan4U3A9+1fVKFMb2SNJZ9JdIw2E9XVRahFEn7D/d4oclzo07z7N0lep06JXoASSsyeMRL6ZWEKl3dSX2wek6Oo/L24IY8ka3RSX2Vu1zru8MYxpGKWL2bNCrrLFK78MtJBc42LhTHG1j4JKDIqLB8/MpXmBpN4oy+haSDgE+RJgc9C+VXElIfrO6kPlk9R9KJpLbYKtuD+4akO4ErgdNam68kfbVE04Wkb5Fmwr4K+A5pMt11tossEJ5jqHyFqdGkW2f0deqM/ShpunvRyRctKl3dKat89Zxsq/x/89miGdxJPJbsZ3vQPAZJO9i+umD79Pb5y/8m25+S9CVSWYSSKl9hKp/8fAB4Rd70W1Khu9KzYztxfjdepE6J/g6g6su/qld3gv5YPadfZgn3k68CrZfgX2uzrZcaKzk9nq82HwDWKHh86I8Vpr5Juto8Od9/V972vsJxIGnjfOzVnap5bkGqV3U8QLf6ueqU6D9JGt54LRX15lPx6k7QN6vnkCflHMPgs6bjXHA9XfXBgu2SXgZsD0xumSCzIgPlB0q5SNJKpImFN5CusL4z7DO67zAqXmGKNAqreX7Nr/M8nCqcSlqM5tsAtm+S9APg+G4epE6J/tukanA3MzDjrrTJpFEUj5AKJh0NvLZkAFWXYWhyOqmiaKOo27tIU83fOuQzusz9sWD7MqSrqvFAczPeIxSumGj70/nmjyRdRGpGKfq+2J6Z51pUtsIUaRbsBrbvgDTckoE1LEp7nu3rNLhSc9frDtWpM7YrnRZLGEO72aA3lRxHL+lXDJRheO7Da/tLQz6pN3EstJBDu20F4vgZqd+kygXbkfTCksNsh4mj0lXY+oGk15BOOu4kXVW8EHi37XbzDHodyy9JxQbPd6oiuifwXtu7dfM4dTqj/6WkA4GfM7jppufDKyV9gLT+5vqSbmp6aCKFaro0Wdt2PxTy+j9JOzY6IPOMw9JtsVDxgu2STrJ9GPD1Rt9NMxcso60hVmEDxlSit32F8hKGedPtFZZk+BBwCvAiSfNIky27XjK6Tmf07caqFxlemdujn0+qAHhk00PzKxjHfwrwtYrLMCBpK1J99Umks6Z/A/vbvmm45/UoluWAdW3fXsGxt/ZA/fOF2P5twVhupeJV2PqBpN+T+oyuAq62Pb/ikBoDN5bqVSy1SfRjnQaWiRsPbES6LK28DEOewEbJqf4tx38TcAKwjO0p+QvouMJn0uOA79net9Qxh4jjfOAQ21WuwvYW4NeNvoHcObyT7Z8WjGEKaaLay0l18Z8kzTU5vFQMTbF8FviC7Yfy/eeT1nb+764ep46JXtIptg+sOo6Shiq/0FC6fVhpTc5jGFiU+/ekBFtiXdLmOK4njd3/jQcWgi5eZTSfRb7a9lMlj5uP/XPS72AiaX5DZauwDdF3U7x/TdIawCtJyf5VwN1VNHm2+9m7NRu2WZ3a6JtNqzqACqwGrGp70AQYSbsB/wJKdwSeQ6ox3lgSbV/SLNmio5CAp20/3DKqoYpRWXeSqkdeyOBO4S8XOPYJBY7RqXYVZYvmIUl3APeT6g2dBnzYdlUj9cZJWrbRR5CbGZft9kHqmuiLrizVJz5PqqPS6hbSCIPSM1LXaBrOB3C8pNLjpQFmS9qH9Ae1EXAIULSCZnZH/rcUg4dZljCPNCFn0MCAXJepdDPOLElfBr6R73+INEKspK+SrjSnk0Zk/VbS7xrDLQs7G7hCadETSH/DXS/wVsumm7FI0kzb2wzxWNEhnvmYXyY1ETRWLtoT2Nb2RwvH8TzgKOB1pP6KS0jVIp8Y9ok1ksfMf7K1g17S5qSCakMtPdmLWJYnzdpuXNldBhzvvF5ASbnOzrtJ5VPWtl16Alsjjt2A1+S7l9m+pOvHqEuil7Q2aUp5o034KtLCw3MrDawQSXNsb7ioj/UwnvnA8gw0kyzFQJOFba9YOJ4V83ErGWGhVAu+3fDKErXghzsJuNmFa/NXRdJ3bR+Qa/zsSJrINoPUf3SVR0mN+sVRp6abM0htbnvl++/M23auLKKyLpf0GeC/G8PnlBqmP0WaMVyU7dLNE21J2oY0S3divv8w8B7bpZsLmq9kJpD6Lro+A3IIKw3z2HIlAmjMJ2jqGB6kUIdw46r2GtJIl38WOGZbkn5ve8d8QtT8fjRGyXX1RKhOZ/R9MROzKvmS+DvAtqQJMZBW8pkFvM9NFQMLxvRWmq6wSg6ha4rhJuBDtq/K93cETq5quGkzFarZL+mHpCGNp7Zsfx9pneWe9530w3wCSbeR2uXbLsTuGpfQrlOiv4J0Bt9YSnA6aVrza4Z+Vv3kuh2b5ruzq7oclXQyaVnF5qUd77D9ocJxFBm+1kEcKzfdXQrYGviq7U2GeEo3j706aYWtpxjo+JxGqsPzFtv/6HUM/SCfPc+kfaJ3iWa0VpK+CvzQ9jU9PU6NEv0LSW30LyOdQc4gDZu6p9LAClFaRWlIpc9W8tnTi5uakZYiffG8uNDxG+/HfqTmiR+SPhfvIK1wdMRQz+1RPH/NxxepyeavpHkFvx/2id2N4VVAY/7AbNvFm/RyKYxjSfVlxkO5BYL6oR5WK6UlFt9BKsfwE9I6wrO6fZw6tdGv3drOlz9UYyLRA8MVLatiwY85wLoMjN9fJ28rpfX9OKbpdvGzG9tTSh+zjTcCp9ueXWEMpwGH01J0b6xyWiv3zHzF9zbg85LWtb1RN49Tp0TfbhGH0gs7VMb9t9DHROBWSdeREuu2pDHUF0LvO9/67f2Q9CHg7Jap7tNtnzzsE7vrVtLCNOPJzZwuX7754dZJfQV9opOdJP3I9ttG3rOrNgReRLrSubXbLz7qm240sLDDYcCJTQ+tSGp/3LLd8+pMaQnBqQxeALpohcKhOt0aet35Jumdtr+vwYt9NB+/xIzU5nj6Yup/Pu4mpPHj00nVVU91oRK9kj5HWnDlxwwuw9A3HaElfy+SvkBagvQO0mzynzZOBrqpDmf0fbOwQz9QWqB8J1KivxjYjTROuGiiLzGKYgSNdUj7YpgnaWaumvosxpE+u0Xl474o/7sf+BNwhKSDbO9dIISX5v+by5T021rCRc5+8/Dn+cDL3OO1rkf9GX2DmhZ2kPSCsTKSoJVSFcstgT/a3jKPuPi+7aLzCVrGBy9DWqPzsVITpSR91vZ/5ds7276sxHGHieeLpMvyb+dNBwH32P5IwRhOBN4EXAGcZvu6psduLzECaDQoOSqr1IS1dgWGRiUPrs54cWWBVO//coGmBXk26L9IHaFF2Z5oe8Wc2JcjdTSVbI9urkT4+YLHHcongCuBD+R/VwAfLxzDTcCWtg9qTvJZz8fzA0iaJOnLkmblf19SWs+hn7QdZ98jN+RJfT1Vh6abdkr+ovrNLKUa36eSRjY8SpoJWJncXPHT3Kx05Ej715HtZyV9lzRxqegCKE1DTf8EbNJSyRPbNxTslK18LWFJh9r+yjDbOuq07ZKXAvtKuotUIqQn60fUpummmaQPFh7N0JckrQes6GpWdWr+w12K1Cb7StsvK3T8ucCXSX84h+fbz6mgM3Z34ItUsABKrrMzlKIThfphBnu7ppkKO8bbriPhLq8fUasz+tzRtDpwkaR1AWzfXW1UZUm6ojEb2PbfWrcV1FwRcQHwN2CPgsc/lYGO2ObbVTmG1DzyGwDbNyqtdNRzfTbUtLK1hCVNB/YBpjSG+WYTSUtdFmf7rlyWYyPbZ0iaTBpc0lW1SfSSPkz6Y/onaSKGSJ2Bldc0KUHSBNJIk1XzGO3G9fmKwFql47HdrjZ+yeN/qpP9JH3S9v/2Oh7aL4BS/HJa0vbAejT97RceevufwPea2uUfBPYvdOwZpPr7qzJ4Qt18Uv9Fcbk5cxppZuwZpEEL3wd26OZxapPogUOBTVx4qbo+chBpLsGaQPOY5EeAr5cKQtL7Scv2/SUPHzuN1BF7F3BAP42XzvYiLerea5UvgCLpLGADUtG7xqxUU2jobb7iflceDVZ8LeHcHHKXpH2Be53XJFBa1Wlt0lVnaW8hLX5yQ47xXkldv/qsU6K/Byg9y69v5I6kr0j6sO2vVRjKocB38+3ppKGe65M+zF8hrdHZT0p13H+YtADKk6S6O5cAnx72Gd03DZjaGMtfmu1ncjNFZYvFZ+eRJlk2PAOcD/R89EsbT9m2pMb8iuV7cZBRn+ibZj7eCfxG0i8YPOOuaKdbH/i2pEOAV+T7vwG+bfvpQsdf0HSsNwLfy1dZl+dZgP2mSNKz/Tgp0R+Vm9YeqiDh/hl4AeWXD2z2x9w+fj6D1879ccEYxrtpkXbbT0kqPnktO0/St4GV8tXwe0h9Sl016hM9A51sd+d/yzAw47B+Q4pGdjKpna8x6uhdwDeB9xU6/rOS1iC1vb4G+EzTY0UWuVhEPT2jl3Q0cJ7t2yQtC/ySdJXzjKR9bF/ey+PnGBqLfUwEbsn1h5pPhkos+tEwAXiAwTNhTSqJUMp9kna3fSGApD1Is4SLs32CpJ1JTawbA0f3YnLfqE/0jU43SXvZPr/5MUl7tX9W/Ugab3sBsE1LfZ9fS/pTwVCOJi12Mg640LlSYq59049LtZ0/8i5L5B0MNNHsTxpquhrpj/pMoOeJHjihwDE69R0vvEh5VzseO/CfwNmSvk76or+HVM66ErYvk3QD6Sq8N6N/bNfiH3BDJ9vq+q/xs5I6dTZo2r5+6feBdALx/JZtywMrVPC+bEyahfrnfH8L0nKLpY7/x6bbPwIOav2dFYzl851s63EMffN3ShrGWPwzmY99EbBZvr0GqTnt58AtwGHdPt6oP6NXWkH99cBaSqu1NKxIuTU5+0GjCeKjwJWSGmfP65EqFRbjdGXxYLuhfBQurkZq7/wYucaM7Zsk/QA4vtDxn1SqJvpP4FUMXjv2ee2f0jM7s/Csz93abOs6DVSZndxSUXRF0tVfUZLeQFqJbUJjyKvt4wqGMMX2n/PtdwOX2d4vj7i5Gjipmwcb9YkeuJfUVLA7A8ukQRobe3glEVWj+Q/o2wz88TxDGvFSpAxtQ9VD+Zo8z/Z1LePXS54AHApcAEwGTrT9VwBJrwf+WCIASR8APgisr7SGbsNEyg3x7Jsqs5K+RfqSfRVpneU9gdbaP73WPDjiNeQOWNvzJT3b7YPVpgSCpKVdbmRJ35H0d1Kn61ALH3c0gaiL8dxKhUP5muL4JXAwcL7tl0jaE3iv7d2qjKukPDnp+aT5As21hubbLjojVE1VZqsi6SbbWzT9vwLwS9vFhv7mDvJLgXmkuSZTbD+Ux/TPsr3psC+wiOpwRt+wraRjqWAtyj7x98KXniPph6F8AB8CTgFeJGkeaa3Wd5YOQqlc9GeBNW3vJmkqqQ75ab0+tlPBsoeB6U1lQsYDK0hawWXLhHwnD5x4CJ5baesc27sUjOGJ/P/jktYkjQJao+DxAd4LHEc6m3+HBxYb2Y40Q7ar6pTox/palH1RsbPPhvJh+07gtXkiylK255c8fpPvkv6Aj8r3/x9wLulzW4Skg0kLc/8TaDQPlC4TsmpTUsP2g5JWK3h8gJ8rVXj9ImnwgunB2PXh2P4X8J/5S+/Spu1XSlq128erU9PNtbZfOvKe9SRp5dKX4UPEUekSgq0kfRb4QssZ5Eds/3fhOGba3qa5SmIFVRvnAC91hWVCJF1PWuLz7nz/hcBPXG6hj6WA7WzPyPeXBSa4/Nq5jXjaVdLs+sIndTqjv1JpFZ++XYuyl/ohycNAIs+VGf/uwfVEVq8gpN2cV5rK8T2YO0KLJnrgMUmrkCfxSdqO8iU7+qFMyFHA7yX9lnQV+nLgwFIHd1oX4BukAQrYfpKmfFFK6dGCdUr0o2EtyrHkfPqjnsg4ScvmP+jGF86yhWMAOAK4ENhA0tWkUTil1zSuvEyI7V8pLYSyXd50mHu8XmobV0h6G/DjCgcLFB0tWJumm9Bf2jVLSPqTB8/aLRHHJ0i18RsdXO8mzdgtXndH0nhSOVoBt5ceJZZL4i6k5IisXNF0X2B928cprRvxAi+8tGEvY5hPmsC3gNQx2xi4UWQ945ZYliadcK/rHq48VptEn4eQHcNAMa/fklbwqfpSdUySdBnwNQ+uJ3KIyy+A0rhMbhz3MtuXlI4hx1F1LfhGHCvkYz9awbG/SeoIfrXtF+c+k0ttV1E5snKS3kQqUdHTlcfqlOh/RBrSd2be9C7SQsjF1qIMAyRtAJxNWvTEwFxgP9tzKg2sIkNNILN9SMEYNgPOAlbOm+4n/U5mF4zhhjyfoblTuuiVntqsuNZuW6FYric1L/+m6f242fbm3TxOndroN7D9tqb7n5J0Y1XBjHW27wC2q+rsUdLvbe+YL9Obz2aqukyvtBZ8dgpwhO0rASTtRBpWuP0wz+m2p/NY/kan9GQGhnr2lPpsFbasyMpjdUr0la1FGRZW5QQhANuNBS6qXiu2oR8mkC3fSPIAtn+jHi10MYyvAj8BVpP0GVKHdKkRUM2rsF3PQKIvugpbiyIrj9Wp6WYrUrPNJNIv8N+kpetKlugNWS49cAZwlNPSceNJlRy7eknaQRxfBX5o+5qSx20Tx5XAVqSaKpVMIJP0E9IEobPypncCW9t+S6kYchwvIvWZCLjC9q2Fj1/1KmzPkfQ80pDT15Hej0uATzeGJXftOHVJ9A2qYC3KMEC5Ln4/TBDKx9yfVBN+E9KZ5Dm2Z5WMIcfRdiJZyQlkubniU8COedNVwLG2Hyxw7JWHe7z0PJB+6RgvZdQneg0uebqQkmOEw6DOtt+QFgW/LN/fjlT7fNiZsz2Ma+Ucz96koWwbVRHHWCXpr6S250ZzSSPxFK9J1Q8d402xbEwqXb0eg790ujr/pw5t9CeQfmG/JF0S90XNlzGs8f73wwShZhsCLyIVvSvWVNAPncJKa7QOqUTzke0pvT7GIuiHjvGG84Fvkcol96xGVx3O6LcEpgO7kjpYfkhq9xvdP9goJWku0LiKWoo0C1WkL+FnSl9hKS1I/hbgDuAc4KduKqo1Fki6j1T+4IfAtbScDJVoPpL0Ttvfz7d3cNNygpIOtl2sM1TS+aQ5HVVXVkXS9ba37vlx6pQPc7vbdOC1wCcak3VCOeqjuvh5FuZ/A9+sYJp9I4bK26bzcMadSX8bWwC/IHVQFx8/33q73f0CsVTeMd4Uy7HAv0j9R82xdPVzUYemG+C58bj/AWxOmpzzr2ojGrP6pi6+bUt6u+1Pj7x3z1zP4LbpZiat6dtTtp8BfgX8KldrnE6qefOpgmfSGuJ2u/u9dmzh4w1n//z/x5q2df1zMeoTvaT3AG8HJpCWbHu7U63nUI1+6yO5QdI2tmdWcfB+aZvOCf4NpCS/HgPj2UvxELfb3e9tIPZv8zyPRtmF66rIGUolk4+0fW7PjzXam26U1lf8M9BYnmzQD1TF5dhYpj6pi98g6TZSR+xdwGMMdIKWXGyjEctaDKyABimQ3xU47veAzYCLScNL/zzCU3oRw+PAHNL7v0G+Tb6/vu1iE7ckvZ206MhvGCiV/DHbF5SKoSmWWbanjbznEh6nBom+rxa6CP1FaWGLhbjwuqWSPk8az38Lg4f09fxEJJ8MPdY4ZvNDlBv50/b30FDy9yHpT8DOjbP43Ox7ecl6O02xfI5Uc+hcBn5HXW+jH/WJvlOSftRSCyeMEZJ2BDayfUb+o17B9l8Lx3A7sIVzXfzQnqRrbL+sx8cYVDQsN6H8qfSs7Xzsdp/Drs8rGPVt9ItgrCwSHpoo1WCfRpoZewawNPB9YIfCodyZjx2JfngTChzjV5IuIQ03hXSl9csCx11IqT6csZTox8alS2j1FtJorBsAbN8rqYpCZ48DN0q6gsHD6IrPxuxzPf87tf0xSW9loBTEKbZLdkw/J9e6OYI0W/vAXNhsE9sXdfM4YynRh7HpqTzMslEWt3S1xobLSZ1/Jq1sFJVVC5O0IbC67att/5i0vjSSdpS0gVNp7dLOIA3BbZSKnkeaLdvVRL9UN1+sz/XbsL9QxnmSvg2sJOn9pIR7aqmDSxqfZ+d+GjgAeA9wPGkUzA9KxTGK9PLv9CRSSeJWD+fHqrCB07KWTwPYfpwevAe1SfSSDh1h2ycKhhP6hO0TSPMrfgRsDBxduETtF0krOk2xvXWeAbo+qZz2FwvGMVq8q4evvbrtm1s35m3r9fC4w3lKacH6xhXnBvSgH6c2o27aTaNuLpEbxjZJq5DWE77b9vUFj/sXYOPW2ku5LMFtY6WKZpuiboMUGuL5l6Heb0lzbG/Y6xjaHPd1pHr0U4FLSYME3u2mBWK6YdS30UuaDuwDTGmp0jeRtPhIGIMkXUSadfhnSWuQOmNnkappnmL7pEKhuF2BPdvPNPoNxgLnlb4kfZq0ytZZpCaKfYE1CoUxS9L7bQ9qupP0PlI7eXG2L1VaN3Y70vtxaC/qMo36M/o8EWMK8L/AkU0PzQdusr2gksBCpSTNtr1pvv1fwIts75dH3FxdamaspJ8CP3bLohaS3kkq1zGmZm6rzULg7bb16Nirk8o+PMVAYp8GLAO8xfY/eh1Dm5iKLFQ+6s/o84y6uyTtC9zrvARXbvdaG/hbheGF6jzddPs15A5Y2/PzTNFSPgT8ONdkak4uy5GGfo41j+W/1XNITTnTaZoR2ku2/wlsL+lVpM5wgF/Y/nWJ4zdT4YXKR/0ZfYOkWcD2tp/K95chnbltM/wzQx1J+jmpzXMecBqpM/ShfAIwq3G2XzCeVwONY95i+4qSx+8XktYDvsLAhLXfA4fZ/ltVMVUhDxQ5jLRQ+TwYtFD5qd2uKlqnRL/QeqSlLglD/5G0GnAc8ALgZNuX5u2vIi2IfUKV8YUAFFuofNQ33TS5T9LujcVGJO1BKhYUxqBcsOo/Je3VSPJ5+5WSVq0wtDFN0trA1xg4o7+K1AE5t7qoqmP7ayqwUHmdzug3AM4mXQqJtHTafrbnDPvEUGtDDLstuqJRGCDpMtJEsbPypncC+9reubqoqqNCC5XXJtE3SFoBwPajVccSqiNpN+D1pEVpmhd2WJG0MPS2lQQ2xg3RxLrQtrFC0q0UWKi8Tk03SHoDqcNrgpT6Ntwny9qF4u4ljZvfncFjpOcDh1cSUQB4IA8tbVSOnA48UGE8VfszqR+ppwuV1+aMXtK3SMOVXgV8B9iTtETYeysNLFRK0tKkE5p1bd9edTxjXZ738jXgZaThlTOAQ2zfXWlgFVGhhcrrlOhvsr1F0/8rAL+0/fKqYwvVkfQm4ARgGdtTJG0FHDfWJiqF/jTUCnndXhmvTk03T+T/H5e0JulysNTU6tC/jgW2JZUIxvaNkvpiwe6xKK/w9X4WHmXynqpiqlK3E/pQ6pTofy5pJVJFwBtIl4XFytGGvvW07YcbfTZZPS5jR6efkYZUXs7AKJMxZ5gibz1Zx7cWiT6v+XiF7YeAH+WCVhNsP1xtZKEPzJa0DzAur95zCKldOFTjebbHfMnwRpG3UmpRj972s8A3mu4/GUk+ZB8mjcR6kjTS4xHS1PNQjYskvb7qIMaaOnXGngBcQ6oUWI8fKoSaaGqqELA86Yv3aXrUVBEGq1Oin0/6AC0gdczGByggaWPgoyzc+ffqqmIKobTaJPoQ2pH0J+BbpElTz3X+lVxlKgwoVX89DFaLzliID1AY0gLb36w6iLEu119fnkL118Ngoz7Rly7gH0adn0v6IGlloeaZh7HMZFkHMVB//Yam7Y8AXa29HhY26ptuShfwD6OLpL+22Wzb6xcPJhSrvx4GG/WJviE+QKFVnl+xl+1zR9w5FCFpeVJRuXVtH5jnNmxi+6KKQ6u12iR6gBIF/MPoImmW7WlVxxESSeeSOsb3s72ZpOcBM8ZqmeJSRn0bfcNQBfyBSPRj2+WSPkqqSf/cItTRRl+ZDWy/Q9J0ANuPq6U+Rei+2iR6YBoFCviHUecd+f8PNW0zEG301XgqL9BueG5luCeHf0pYUnVK9EUK+IfRxXZUquwvxwC/AtaRdDZp7dgDKo1oDKhNG32pAv5hdMltwEcQnX99Q9IqwHakEXJ/sH1/xSHVXp0SfZEC/mF0ic6//iBp2MXYbd8w3ONhydQm0QNIWh3YJt+9zva/qownVK8x6kbSH23/R972J9tbVh3bWCLpWVLzauPsvbkD1lF7qLdqUaYYQNLbSc02ewFvB66VtGe1UYU+EJ1//eEI0iTG/wPOAN5k+1X5XyT5HqvNGX0uXrVz4yw+L1l2eZy5jW2SXgccBUwFLiV1/r3b9pWVBjZGSVof2BvYA7gL+KztGysNagyo06ibpVqaah6gRlcsYfHYvlTS9Qx0/h0anX/VsX2npJ8BywHvAjYmzX0JPVSnM/ovAluQVhGCNH76pli2bGyLqqb9oeVM/h7gHOAXtv+v0sDGiFGf6CVtCKxu+2pJbwV2zA89BJxt+47KgguVaapqeiWwE4Ormv7K9osqCm1Myp2xN5EWB3+EloWxbX+5irjGijo03ZwEfBLA9o+BHwNI2jw/9qaqAguVai6Lez2Dq5pGRdPyjmMgua/Q8tjoPtscBepwRj/T9jZDPHaz7c1LxxT6R1Q17S+SdrB99UjbQnfVIdH/xfZGQzw2x/aGpWMK/SWqmvYPSTfYfslI20J31aHpZpak99s+tXmjpPeRLtnDGBZVTfuDpJcB2wOTJR3R9NCKwLhqoho76pDoDwN+ImlfBhL7NGAZ4C1VBRX6RlQ17Q/LkNrmxwMTm7Y/AsTExh4b9U03DZJeBWyW7862/esq4wn9QdL5wCG2o6ppH5D0Qtt3VR3HWFObRB9CO1HVtL9I2hj4KAv3mUQZhB6KRB9qLaqa9pdcquRbpGbWRp8JtqM/rYci0YcQipF0ve2tq45jrIlEH2pJ0nzaT8QRqSzuioVDCoCkY4F/AT9hcFNarOHbQ5HoQwjFSPprm822HWv49lAk+hBCqLko4xtCKEbS8yT9t6RT8v2NJL2x6rjqLhJ9CKGkM4CnSLNkAeYBx1cXztgQiT6EUNIGtr8APA1g+3EGrx8beiASfQihpFjDtwJ1qHUTQhg9jgF+Bawj6WzSGr4HVBrRGBCjbkIIRUlahYE1fP8Qa/j2XiT6EEJRkrZg4Vo3P64soDEgmm5CCMVIOh3YApgNPJs3m7wEaOiNOKMPIRQj6RbbU6uOY6yJUTchhJKukRSJvrA4ow8hFJPLRl8I/IM0rLJRZG6LSgOruUj0IYRiJM0BjgBuZqCNnlh1qreiMzaEUNJ9ti+sOoixJs7oQwjFSDoZWAn4OYPr0ceomx6KM/oQQknLkRL865q2xfDKHosz+hBCMZJWsf1A1XGMNTG8MoRQ0h8knS/p9ZKiamUhkehDCCVtDJwCvAv4i6TPStq44phqL5puQgiVkPQq4PvA8sCfgCNtX1NtVPUUiT6EUEyuXPlO0hn9P4HTSBOotgLOtz2luujqK0bdhBBKugY4C3iz7blN22dJ+lZFMdVenNGHEIqRJEfSKS7O6EMIJa0q6ePApsCExkbbr64upPqLUTchhJLOBm4DpgCfAv4GzKwyoLEgmm5CCMVIut721pJualSslDTT9jZVx1Zn0XQTQijp6fz/3yW9AbgXWLnCeMaESPQhhJKOlzQJ+AjwNWBF4PBqQ6q/aLoJIfScpAnAfwIbkmrRn2Z7QbVRjR2R6EMIPSfpXFKzzVXAbsBdtg+tNqqxIxJ9CKHnJN1se/N8ezxwne2XVBzWmBHDK0MIJTQ6YYkmm/LijD6E0HOSngEea9wlLUDyOAOLg69YVWxjQST6EEKouWi6CSGEmotEH0IINReJPoQQai4SfQgh1Fwk+hBCqLlI9CGEUHP/Hyr1smtCJtP2AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "imp = rf_model.feature_importances_\n",
    "\n",
    "weights = pd.DataFrame(imp, index=X.columns.values, columns = ['Weight'])\n",
    "\n",
    "print(weights.sort_values(by =\"Weight\", ascending = False).head(10))\n",
    "\n",
    "\n",
    "ax = weights.sort_values(by =\"Weight\", ascending = False)[:10].plot(kind = 'bar')\n",
    "\n",
    "ax.set_title('Weight of features on churn probability')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1dda3438",
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    },
    "tags": []
   },
   "source": [
    "#### Findings\n",
    "\n",
    "* We get a similiar but slightly more accurate result from the Randomforest Classifier\n",
    "* The importance of contract type and tenure for churn probability gets even more emphasized"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e8c45c5a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-04T17:13:17.115946Z",
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     "iopub.status.idle": "2022-07-04T17:13:17.391481Z",
     "shell.execute_reply": "2022-07-04T17:13:17.390290Z",
     "shell.execute_reply.started": "2022-07-04T17:13:17.115905Z"
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     "start_time": "2022-07-11T16:31:57.571721",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### XGBoost\n",
    "\n",
    "Using XGBoost get a additional reference"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "db71d801",
   "metadata": {
    "execution": {
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     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "XGBClassifier(base_score=0.5, booster='gbtree', callbacks=None,\n",
       "              colsample_bylevel=1, colsample_bynode=1, colsample_bytree=1,\n",
       "              early_stopping_rounds=None, enable_categorical=False,\n",
       "              eval_metric=None, gamma=0, gpu_id=-1, grow_policy='depthwise',\n",
       "              importance_type=None, interaction_constraints='',\n",
       "              learning_rate=0.300000012, max_bin=256, max_cat_to_onehot=4,\n",
       "              max_delta_step=0, max_depth=6, max_leaves=0, min_child_weight=1,\n",
       "              missing=nan, monotone_constraints='()', n_estimators=100,\n",
       "              n_jobs=0, num_parallel_tree=1, predictor='auto', random_state=0,\n",
       "              reg_alpha=0, reg_lambda=1, ...)"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Building the model\n",
    "\n",
    "from xgboost import XGBClassifier\n",
    "\n",
    "xgb_model = XGBClassifier()\n",
    "\n",
    "xgb_model.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "1ede7221",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-11T16:31:58.670489Z",
     "iopub.status.busy": "2022-07-11T16:31:58.669127Z",
     "iopub.status.idle": "2022-07-11T16:31:58.690069Z",
     "shell.execute_reply": "2022-07-11T16:31:58.689097Z"
    },
    "papermill": {
     "duration": 0.050786,
     "end_time": "2022-07-11T16:31:58.692994",
     "exception": false,
     "start_time": "2022-07-11T16:31:58.642208",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy of the Model is:  79.7156 %\n"
     ]
    }
   ],
   "source": [
    "#Making predictions\n",
    "\n",
    "pred = xgb_model.predict(X_test)\n",
    "\n",
    "print('Accuracy of the Model is: ', round(metrics.accuracy_score(y_test, pred)*100, 4), '%')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7bff1397",
   "metadata": {
    "papermill": {
     "duration": 0.026351,
     "end_time": "2022-07-11T16:31:58.745849",
     "exception": false,
     "start_time": "2022-07-11T16:31:58.719498",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "* With the XGB Model we recieved the worst predicitions so far\n",
    "\n",
    "* The best model seems to be the Random Forest Classifier\n",
    "\n",
    "#### Thanks for having a look at my notebook!"
   ]
  }
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