04-EDA-Correlation-Analysis.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Perform Exploratory Data Analysis - Correlation\n",
    "- Examine the level of correlation between each feature\n",
    "- Examine their level of correlation to the outcome (response feature)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import os\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Read the cleaned source file into a DataFrame.\n",
    "data_dir = os.path.join(os.getcwd(), 'Data')\n",
    "source_file = os.path.join(data_dir, 'WA-Telco-Customer-Churn-ML.xlsx')\n",
    "df = pd.read_excel(source_file, header=0)\n",
    "\n",
    "# Drop the Unique Identifier\n",
    "df = df.drop(labels=['customerID'], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "gender                 int8\n",
       "SeniorCitizen          int8\n",
       "Partner                int8\n",
       "Dependents             int8\n",
       "tenure                 int8\n",
       "PhoneService           int8\n",
       "MultipleLines          int8\n",
       "InternetService        int8\n",
       "OnlineSecurity         int8\n",
       "OnlineBackup           int8\n",
       "DeviceProtection       int8\n",
       "TechSupport            int8\n",
       "StreamingTV            int8\n",
       "StreamingMovies        int8\n",
       "Contract               int8\n",
       "PaperlessBilling       int8\n",
       "PaymentMethod          int8\n",
       "MonthlyCharges      float32\n",
       "TotalCharges        float32\n",
       "Churn                  int8\n",
       "dtype: object"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Make appropriate data type assignments.\n",
    "df.gender = pd.to_numeric(df.gender, downcast='integer', errors='coerce')\n",
    "df.SeniorCitizen = pd.to_numeric(df.SeniorCitizen, downcast='integer', errors='coerce')\n",
    "df.Partner = pd.to_numeric(df.Partner, downcast='integer', errors='coerce')\n",
    "df.Dependents = pd.to_numeric(df.Dependents, downcast='integer', errors='coerce')\n",
    "df.tenure = pd.to_numeric(df.tenure, downcast='integer', errors='coerce')\n",
    "df.PhoneService = pd.to_numeric(df.PhoneService, downcast='integer', errors='coerce')\n",
    "df.MultipleLines = pd.to_numeric(df.MultipleLines, downcast='integer', errors='coerce')\n",
    "df.InternetService = pd.to_numeric(df.InternetService, downcast='integer', errors='coerce')\n",
    "df.OnlineSecurity = pd.to_numeric(df.OnlineSecurity, downcast='integer', errors='coerce')\n",
    "df.OnlineBackup = pd.to_numeric(df.OnlineBackup, downcast='integer', errors='coerce')\n",
    "df.DeviceProtection = pd.to_numeric(df.DeviceProtection, downcast='integer', errors='coerce')\n",
    "df.TechSupport = pd.to_numeric(df.TechSupport, downcast='integer', errors='coerce')\n",
    "df.StreamingTV = pd.to_numeric(df.StreamingTV, downcast='integer', errors='coerce')\n",
    "df.StreamingMovies = pd.to_numeric(df.StreamingMovies, downcast='integer', errors='coerce')\n",
    "df.Contract = pd.to_numeric(df.Contract, downcast='integer', errors='coerce')\n",
    "df.PaperlessBilling = pd.to_numeric(df.PaperlessBilling, downcast='integer', errors='coerce')\n",
    "df.PaymentMethod = pd.to_numeric(df.PaymentMethod, downcast='integer', errors='coerce')\n",
    "df.MonthlyCharges = pd.to_numeric(df.MonthlyCharges, downcast='float', errors='coerce')\n",
    "df.TotalCharges = pd.to_numeric(df.TotalCharges, downcast='float', errors='coerce')\n",
    "df.Churn = pd.to_numeric(df.Churn, downcast='integer', errors='coerce')\n",
    "\n",
    "# Validate new data type assignments.\n",
    "df.dtypes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Examine Correlations Among the Entire Feature-Set"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></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>OnlineBackup</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>gender</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.001874</td>\n",
       "      <td>-0.001808</td>\n",
       "      <td>0.010517</td>\n",
       "      <td>0.005106</td>\n",
       "      <td>-0.006488</td>\n",
       "      <td>-0.006739</td>\n",
       "      <td>-0.000863</td>\n",
       "      <td>-0.015017</td>\n",
       "      <td>-0.012057</td>\n",
       "      <td>0.000549</td>\n",
       "      <td>-0.006825</td>\n",
       "      <td>-0.006421</td>\n",
       "      <td>-0.008743</td>\n",
       "      <td>0.000126</td>\n",
       "      <td>-0.011754</td>\n",
       "      <td>0.017352</td>\n",
       "      <td>-0.014569</td>\n",
       "      <td>-0.000080</td>\n",
       "      <td>-0.008612</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SeniorCitizen</th>\n",
       "      <td>-0.001874</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.016479</td>\n",
       "      <td>-0.211185</td>\n",
       "      <td>0.016567</td>\n",
       "      <td>0.008576</td>\n",
       "      <td>0.146185</td>\n",
       "      <td>-0.032310</td>\n",
       "      <td>-0.128221</td>\n",
       "      <td>-0.013632</td>\n",
       "      <td>-0.021398</td>\n",
       "      <td>-0.151268</td>\n",
       "      <td>0.030776</td>\n",
       "      <td>0.047266</td>\n",
       "      <td>-0.142554</td>\n",
       "      <td>0.156530</td>\n",
       "      <td>-0.038551</td>\n",
       "      <td>0.220173</td>\n",
       "      <td>0.103006</td>\n",
       "      <td>0.150889</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Partner</th>\n",
       "      <td>-0.001808</td>\n",
       "      <td>0.016479</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.452676</td>\n",
       "      <td>0.379697</td>\n",
       "      <td>0.017706</td>\n",
       "      <td>0.142410</td>\n",
       "      <td>0.000891</td>\n",
       "      <td>0.150828</td>\n",
       "      <td>0.153130</td>\n",
       "      <td>0.166330</td>\n",
       "      <td>0.126733</td>\n",
       "      <td>0.137341</td>\n",
       "      <td>0.129574</td>\n",
       "      <td>0.294806</td>\n",
       "      <td>-0.014877</td>\n",
       "      <td>-0.154798</td>\n",
       "      <td>0.096848</td>\n",
       "      <td>0.317504</td>\n",
       "      <td>-0.150448</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dependents</th>\n",
       "      <td>0.010517</td>\n",
       "      <td>-0.211185</td>\n",
       "      <td>0.452676</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.159712</td>\n",
       "      <td>-0.001762</td>\n",
       "      <td>-0.024991</td>\n",
       "      <td>0.044590</td>\n",
       "      <td>0.152166</td>\n",
       "      <td>0.091015</td>\n",
       "      <td>0.080537</td>\n",
       "      <td>0.133524</td>\n",
       "      <td>0.046885</td>\n",
       "      <td>0.021321</td>\n",
       "      <td>0.243187</td>\n",
       "      <td>-0.111377</td>\n",
       "      <td>-0.040292</td>\n",
       "      <td>-0.113890</td>\n",
       "      <td>0.062078</td>\n",
       "      <td>-0.164221</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>tenure</th>\n",
       "      <td>0.005106</td>\n",
       "      <td>0.016567</td>\n",
       "      <td>0.379697</td>\n",
       "      <td>0.159712</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.008448</td>\n",
       "      <td>0.343032</td>\n",
       "      <td>-0.030359</td>\n",
       "      <td>0.325468</td>\n",
       "      <td>0.370876</td>\n",
       "      <td>0.371105</td>\n",
       "      <td>0.322942</td>\n",
       "      <td>0.289373</td>\n",
       "      <td>0.296866</td>\n",
       "      <td>0.671607</td>\n",
       "      <td>0.006152</td>\n",
       "      <td>-0.370436</td>\n",
       "      <td>0.247900</td>\n",
       "      <td>0.826178</td>\n",
       "      <td>-0.352229</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PhoneService</th>\n",
       "      <td>-0.006488</td>\n",
       "      <td>0.008576</td>\n",
       "      <td>0.017706</td>\n",
       "      <td>-0.001762</td>\n",
       "      <td>0.008448</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.020538</td>\n",
       "      <td>0.387436</td>\n",
       "      <td>-0.015198</td>\n",
       "      <td>0.024105</td>\n",
       "      <td>0.003727</td>\n",
       "      <td>-0.019158</td>\n",
       "      <td>0.055353</td>\n",
       "      <td>0.043870</td>\n",
       "      <td>0.002247</td>\n",
       "      <td>0.016505</td>\n",
       "      <td>-0.004184</td>\n",
       "      <td>0.247398</td>\n",
       "      <td>0.113214</td>\n",
       "      <td>0.011942</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MultipleLines</th>\n",
       "      <td>-0.006739</td>\n",
       "      <td>0.146185</td>\n",
       "      <td>0.142410</td>\n",
       "      <td>-0.024991</td>\n",
       "      <td>0.343032</td>\n",
       "      <td>-0.020538</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.109216</td>\n",
       "      <td>0.007141</td>\n",
       "      <td>0.117327</td>\n",
       "      <td>0.122318</td>\n",
       "      <td>0.011466</td>\n",
       "      <td>0.175059</td>\n",
       "      <td>0.180957</td>\n",
       "      <td>0.110842</td>\n",
       "      <td>0.165146</td>\n",
       "      <td>-0.176793</td>\n",
       "      <td>0.433576</td>\n",
       "      <td>0.452577</td>\n",
       "      <td>0.038037</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>InternetService</th>\n",
       "      <td>-0.000863</td>\n",
       "      <td>-0.032310</td>\n",
       "      <td>0.000891</td>\n",
       "      <td>0.044590</td>\n",
       "      <td>-0.030359</td>\n",
       "      <td>0.387436</td>\n",
       "      <td>-0.109216</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.028416</td>\n",
       "      <td>0.036138</td>\n",
       "      <td>0.044944</td>\n",
       "      <td>-0.026047</td>\n",
       "      <td>0.107417</td>\n",
       "      <td>0.098350</td>\n",
       "      <td>0.099721</td>\n",
       "      <td>-0.138625</td>\n",
       "      <td>0.086140</td>\n",
       "      <td>-0.323260</td>\n",
       "      <td>-0.175755</td>\n",
       "      <td>-0.047291</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OnlineSecurity</th>\n",
       "      <td>-0.015017</td>\n",
       "      <td>-0.128221</td>\n",
       "      <td>0.150828</td>\n",
       "      <td>0.152166</td>\n",
       "      <td>0.325468</td>\n",
       "      <td>-0.015198</td>\n",
       "      <td>0.007141</td>\n",
       "      <td>-0.028416</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.185126</td>\n",
       "      <td>0.175985</td>\n",
       "      <td>0.285028</td>\n",
       "      <td>0.044669</td>\n",
       "      <td>0.055954</td>\n",
       "      <td>0.374416</td>\n",
       "      <td>-0.157641</td>\n",
       "      <td>-0.096726</td>\n",
       "      <td>-0.053878</td>\n",
       "      <td>0.253224</td>\n",
       "      <td>-0.289309</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OnlineBackup</th>\n",
       "      <td>-0.012057</td>\n",
       "      <td>-0.013632</td>\n",
       "      <td>0.153130</td>\n",
       "      <td>0.091015</td>\n",
       "      <td>0.370876</td>\n",
       "      <td>0.024105</td>\n",
       "      <td>0.117327</td>\n",
       "      <td>0.036138</td>\n",
       "      <td>0.185126</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.187757</td>\n",
       "      <td>0.195748</td>\n",
       "      <td>0.147186</td>\n",
       "      <td>0.136722</td>\n",
       "      <td>0.280980</td>\n",
       "      <td>-0.013370</td>\n",
       "      <td>-0.124847</td>\n",
       "      <td>0.119777</td>\n",
       "      <td>0.374410</td>\n",
       "      <td>-0.195525</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DeviceProtection</th>\n",
       "      <td>0.000549</td>\n",
       "      <td>-0.021398</td>\n",
       "      <td>0.166330</td>\n",
       "      <td>0.080537</td>\n",
       "      <td>0.371105</td>\n",
       "      <td>0.003727</td>\n",
       "      <td>0.122318</td>\n",
       "      <td>0.044944</td>\n",
       "      <td>0.175985</td>\n",
       "      <td>0.187757</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.240593</td>\n",
       "      <td>0.276652</td>\n",
       "      <td>0.288799</td>\n",
       "      <td>0.350277</td>\n",
       "      <td>-0.038234</td>\n",
       "      <td>-0.135750</td>\n",
       "      <td>0.163652</td>\n",
       "      <td>0.387897</td>\n",
       "      <td>-0.178134</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TechSupport</th>\n",
       "      <td>-0.006825</td>\n",
       "      <td>-0.151268</td>\n",
       "      <td>0.126733</td>\n",
       "      <td>0.133524</td>\n",
       "      <td>0.322942</td>\n",
       "      <td>-0.019158</td>\n",
       "      <td>0.011466</td>\n",
       "      <td>-0.026047</td>\n",
       "      <td>0.285028</td>\n",
       "      <td>0.195748</td>\n",
       "      <td>0.240593</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.161305</td>\n",
       "      <td>0.161316</td>\n",
       "      <td>0.425367</td>\n",
       "      <td>-0.113600</td>\n",
       "      <td>-0.104670</td>\n",
       "      <td>-0.008682</td>\n",
       "      <td>0.275625</td>\n",
       "      <td>-0.282492</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>StreamingTV</th>\n",
       "      <td>-0.006421</td>\n",
       "      <td>0.030776</td>\n",
       "      <td>0.137341</td>\n",
       "      <td>0.046885</td>\n",
       "      <td>0.289373</td>\n",
       "      <td>0.055353</td>\n",
       "      <td>0.175059</td>\n",
       "      <td>0.107417</td>\n",
       "      <td>0.044669</td>\n",
       "      <td>0.147186</td>\n",
       "      <td>0.276652</td>\n",
       "      <td>0.161305</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.434772</td>\n",
       "      <td>0.227116</td>\n",
       "      <td>0.096642</td>\n",
       "      <td>-0.104234</td>\n",
       "      <td>0.336706</td>\n",
       "      <td>0.391470</td>\n",
       "      <td>-0.036581</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>StreamingMovies</th>\n",
       "      <td>-0.008743</td>\n",
       "      <td>0.047266</td>\n",
       "      <td>0.129574</td>\n",
       "      <td>0.021321</td>\n",
       "      <td>0.296866</td>\n",
       "      <td>0.043870</td>\n",
       "      <td>0.180957</td>\n",
       "      <td>0.098350</td>\n",
       "      <td>0.055954</td>\n",
       "      <td>0.136722</td>\n",
       "      <td>0.288799</td>\n",
       "      <td>0.161316</td>\n",
       "      <td>0.434772</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.231226</td>\n",
       "      <td>0.083700</td>\n",
       "      <td>-0.111241</td>\n",
       "      <td>0.335459</td>\n",
       "      <td>0.398066</td>\n",
       "      <td>-0.038492</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Contract</th>\n",
       "      <td>0.000126</td>\n",
       "      <td>-0.142554</td>\n",
       "      <td>0.294806</td>\n",
       "      <td>0.243187</td>\n",
       "      <td>0.671607</td>\n",
       "      <td>0.002247</td>\n",
       "      <td>0.110842</td>\n",
       "      <td>0.099721</td>\n",
       "      <td>0.374416</td>\n",
       "      <td>0.280980</td>\n",
       "      <td>0.350277</td>\n",
       "      <td>0.425367</td>\n",
       "      <td>0.227116</td>\n",
       "      <td>0.231226</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.176733</td>\n",
       "      <td>-0.227543</td>\n",
       "      <td>-0.074195</td>\n",
       "      <td>0.446855</td>\n",
       "      <td>-0.396713</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PaperlessBilling</th>\n",
       "      <td>-0.011754</td>\n",
       "      <td>0.156530</td>\n",
       "      <td>-0.014877</td>\n",
       "      <td>-0.111377</td>\n",
       "      <td>0.006152</td>\n",
       "      <td>0.016505</td>\n",
       "      <td>0.165146</td>\n",
       "      <td>-0.138625</td>\n",
       "      <td>-0.157641</td>\n",
       "      <td>-0.013370</td>\n",
       "      <td>-0.038234</td>\n",
       "      <td>-0.113600</td>\n",
       "      <td>0.096642</td>\n",
       "      <td>0.083700</td>\n",
       "      <td>-0.176733</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.062904</td>\n",
       "      <td>0.352150</td>\n",
       "      <td>0.158574</td>\n",
       "      <td>0.191825</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PaymentMethod</th>\n",
       "      <td>0.017352</td>\n",
       "      <td>-0.038551</td>\n",
       "      <td>-0.154798</td>\n",
       "      <td>-0.040292</td>\n",
       "      <td>-0.370436</td>\n",
       "      <td>-0.004184</td>\n",
       "      <td>-0.176793</td>\n",
       "      <td>0.086140</td>\n",
       "      <td>-0.096726</td>\n",
       "      <td>-0.124847</td>\n",
       "      <td>-0.135750</td>\n",
       "      <td>-0.104670</td>\n",
       "      <td>-0.104234</td>\n",
       "      <td>-0.111241</td>\n",
       "      <td>-0.227543</td>\n",
       "      <td>-0.062904</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.193407</td>\n",
       "      <td>-0.330918</td>\n",
       "      <td>0.107062</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MonthlyCharges</th>\n",
       "      <td>-0.014569</td>\n",
       "      <td>0.220173</td>\n",
       "      <td>0.096848</td>\n",
       "      <td>-0.113890</td>\n",
       "      <td>0.247900</td>\n",
       "      <td>0.247398</td>\n",
       "      <td>0.433576</td>\n",
       "      <td>-0.323260</td>\n",
       "      <td>-0.053878</td>\n",
       "      <td>0.119777</td>\n",
       "      <td>0.163652</td>\n",
       "      <td>-0.008682</td>\n",
       "      <td>0.336706</td>\n",
       "      <td>0.335459</td>\n",
       "      <td>-0.074195</td>\n",
       "      <td>0.352150</td>\n",
       "      <td>-0.193407</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.651174</td>\n",
       "      <td>0.193356</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TotalCharges</th>\n",
       "      <td>-0.000080</td>\n",
       "      <td>0.103006</td>\n",
       "      <td>0.317504</td>\n",
       "      <td>0.062078</td>\n",
       "      <td>0.826178</td>\n",
       "      <td>0.113214</td>\n",
       "      <td>0.452577</td>\n",
       "      <td>-0.175755</td>\n",
       "      <td>0.253224</td>\n",
       "      <td>0.374410</td>\n",
       "      <td>0.387897</td>\n",
       "      <td>0.275625</td>\n",
       "      <td>0.391470</td>\n",
       "      <td>0.398066</td>\n",
       "      <td>0.446855</td>\n",
       "      <td>0.158574</td>\n",
       "      <td>-0.330918</td>\n",
       "      <td>0.651174</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.198324</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Churn</th>\n",
       "      <td>-0.008612</td>\n",
       "      <td>0.150889</td>\n",
       "      <td>-0.150448</td>\n",
       "      <td>-0.164221</td>\n",
       "      <td>-0.352229</td>\n",
       "      <td>0.011942</td>\n",
       "      <td>0.038037</td>\n",
       "      <td>-0.047291</td>\n",
       "      <td>-0.289309</td>\n",
       "      <td>-0.195525</td>\n",
       "      <td>-0.178134</td>\n",
       "      <td>-0.282492</td>\n",
       "      <td>-0.036581</td>\n",
       "      <td>-0.038492</td>\n",
       "      <td>-0.396713</td>\n",
       "      <td>0.191825</td>\n",
       "      <td>0.107062</td>\n",
       "      <td>0.193356</td>\n",
       "      <td>-0.198324</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    gender  SeniorCitizen   Partner  Dependents    tenure  \\\n",
       "gender            1.000000      -0.001874 -0.001808    0.010517  0.005106   \n",
       "SeniorCitizen    -0.001874       1.000000  0.016479   -0.211185  0.016567   \n",
       "Partner          -0.001808       0.016479  1.000000    0.452676  0.379697   \n",
       "Dependents        0.010517      -0.211185  0.452676    1.000000  0.159712   \n",
       "tenure            0.005106       0.016567  0.379697    0.159712  1.000000   \n",
       "PhoneService     -0.006488       0.008576  0.017706   -0.001762  0.008448   \n",
       "MultipleLines    -0.006739       0.146185  0.142410   -0.024991  0.343032   \n",
       "InternetService  -0.000863      -0.032310  0.000891    0.044590 -0.030359   \n",
       "OnlineSecurity   -0.015017      -0.128221  0.150828    0.152166  0.325468   \n",
       "OnlineBackup     -0.012057      -0.013632  0.153130    0.091015  0.370876   \n",
       "DeviceProtection  0.000549      -0.021398  0.166330    0.080537  0.371105   \n",
       "TechSupport      -0.006825      -0.151268  0.126733    0.133524  0.322942   \n",
       "StreamingTV      -0.006421       0.030776  0.137341    0.046885  0.289373   \n",
       "StreamingMovies  -0.008743       0.047266  0.129574    0.021321  0.296866   \n",
       "Contract          0.000126      -0.142554  0.294806    0.243187  0.671607   \n",
       "PaperlessBilling -0.011754       0.156530 -0.014877   -0.111377  0.006152   \n",
       "PaymentMethod     0.017352      -0.038551 -0.154798   -0.040292 -0.370436   \n",
       "MonthlyCharges   -0.014569       0.220173  0.096848   -0.113890  0.247900   \n",
       "TotalCharges     -0.000080       0.103006  0.317504    0.062078  0.826178   \n",
       "Churn            -0.008612       0.150889 -0.150448   -0.164221 -0.352229   \n",
       "\n",
       "                  PhoneService  MultipleLines  InternetService  \\\n",
       "gender               -0.006488      -0.006739        -0.000863   \n",
       "SeniorCitizen         0.008576       0.146185        -0.032310   \n",
       "Partner               0.017706       0.142410         0.000891   \n",
       "Dependents           -0.001762      -0.024991         0.044590   \n",
       "tenure                0.008448       0.343032        -0.030359   \n",
       "PhoneService          1.000000      -0.020538         0.387436   \n",
       "MultipleLines        -0.020538       1.000000        -0.109216   \n",
       "InternetService       0.387436      -0.109216         1.000000   \n",
       "OnlineSecurity       -0.015198       0.007141        -0.028416   \n",
       "OnlineBackup          0.024105       0.117327         0.036138   \n",
       "DeviceProtection      0.003727       0.122318         0.044944   \n",
       "TechSupport          -0.019158       0.011466        -0.026047   \n",
       "StreamingTV           0.055353       0.175059         0.107417   \n",
       "StreamingMovies       0.043870       0.180957         0.098350   \n",
       "Contract              0.002247       0.110842         0.099721   \n",
       "PaperlessBilling      0.016505       0.165146        -0.138625   \n",
       "PaymentMethod        -0.004184      -0.176793         0.086140   \n",
       "MonthlyCharges        0.247398       0.433576        -0.323260   \n",
       "TotalCharges          0.113214       0.452577        -0.175755   \n",
       "Churn                 0.011942       0.038037        -0.047291   \n",
       "\n",
       "                  OnlineSecurity  OnlineBackup  DeviceProtection  TechSupport  \\\n",
       "gender                 -0.015017     -0.012057          0.000549    -0.006825   \n",
       "SeniorCitizen          -0.128221     -0.013632         -0.021398    -0.151268   \n",
       "Partner                 0.150828      0.153130          0.166330     0.126733   \n",
       "Dependents              0.152166      0.091015          0.080537     0.133524   \n",
       "tenure                  0.325468      0.370876          0.371105     0.322942   \n",
       "PhoneService           -0.015198      0.024105          0.003727    -0.019158   \n",
       "MultipleLines           0.007141      0.117327          0.122318     0.011466   \n",
       "InternetService        -0.028416      0.036138          0.044944    -0.026047   \n",
       "OnlineSecurity          1.000000      0.185126          0.175985     0.285028   \n",
       "OnlineBackup            0.185126      1.000000          0.187757     0.195748   \n",
       "DeviceProtection        0.175985      0.187757          1.000000     0.240593   \n",
       "TechSupport             0.285028      0.195748          0.240593     1.000000   \n",
       "StreamingTV             0.044669      0.147186          0.276652     0.161305   \n",
       "StreamingMovies         0.055954      0.136722          0.288799     0.161316   \n",
       "Contract                0.374416      0.280980          0.350277     0.425367   \n",
       "PaperlessBilling       -0.157641     -0.013370         -0.038234    -0.113600   \n",
       "PaymentMethod          -0.096726     -0.124847         -0.135750    -0.104670   \n",
       "MonthlyCharges         -0.053878      0.119777          0.163652    -0.008682   \n",
       "TotalCharges            0.253224      0.374410          0.387897     0.275625   \n",
       "Churn                  -0.289309     -0.195525         -0.178134    -0.282492   \n",
       "\n",
       "                  StreamingTV  StreamingMovies  Contract  PaperlessBilling  \\\n",
       "gender              -0.006421        -0.008743  0.000126         -0.011754   \n",
       "SeniorCitizen        0.030776         0.047266 -0.142554          0.156530   \n",
       "Partner              0.137341         0.129574  0.294806         -0.014877   \n",
       "Dependents           0.046885         0.021321  0.243187         -0.111377   \n",
       "tenure               0.289373         0.296866  0.671607          0.006152   \n",
       "PhoneService         0.055353         0.043870  0.002247          0.016505   \n",
       "MultipleLines        0.175059         0.180957  0.110842          0.165146   \n",
       "InternetService      0.107417         0.098350  0.099721         -0.138625   \n",
       "OnlineSecurity       0.044669         0.055954  0.374416         -0.157641   \n",
       "OnlineBackup         0.147186         0.136722  0.280980         -0.013370   \n",
       "DeviceProtection     0.276652         0.288799  0.350277         -0.038234   \n",
       "TechSupport          0.161305         0.161316  0.425367         -0.113600   \n",
       "StreamingTV          1.000000         0.434772  0.227116          0.096642   \n",
       "StreamingMovies      0.434772         1.000000  0.231226          0.083700   \n",
       "Contract             0.227116         0.231226  1.000000         -0.176733   \n",
       "PaperlessBilling     0.096642         0.083700 -0.176733          1.000000   \n",
       "PaymentMethod       -0.104234        -0.111241 -0.227543         -0.062904   \n",
       "MonthlyCharges       0.336706         0.335459 -0.074195          0.352150   \n",
       "TotalCharges         0.391470         0.398066  0.446855          0.158574   \n",
       "Churn               -0.036581        -0.038492 -0.396713          0.191825   \n",
       "\n",
       "                  PaymentMethod  MonthlyCharges  TotalCharges     Churn  \n",
       "gender                 0.017352       -0.014569     -0.000080 -0.008612  \n",
       "SeniorCitizen         -0.038551        0.220173      0.103006  0.150889  \n",
       "Partner               -0.154798        0.096848      0.317504 -0.150448  \n",
       "Dependents            -0.040292       -0.113890      0.062078 -0.164221  \n",
       "tenure                -0.370436        0.247900      0.826178 -0.352229  \n",
       "PhoneService          -0.004184        0.247398      0.113214  0.011942  \n",
       "MultipleLines         -0.176793        0.433576      0.452577  0.038037  \n",
       "InternetService        0.086140       -0.323260     -0.175755 -0.047291  \n",
       "OnlineSecurity        -0.096726       -0.053878      0.253224 -0.289309  \n",
       "OnlineBackup          -0.124847        0.119777      0.374410 -0.195525  \n",
       "DeviceProtection      -0.135750        0.163652      0.387897 -0.178134  \n",
       "TechSupport           -0.104670       -0.008682      0.275625 -0.282492  \n",
       "StreamingTV           -0.104234        0.336706      0.391470 -0.036581  \n",
       "StreamingMovies       -0.111241        0.335459      0.398066 -0.038492  \n",
       "Contract              -0.227543       -0.074195      0.446855 -0.396713  \n",
       "PaperlessBilling      -0.062904        0.352150      0.158574  0.191825  \n",
       "PaymentMethod          1.000000       -0.193407     -0.330918  0.107062  \n",
       "MonthlyCharges        -0.193407        1.000000      0.651174  0.193356  \n",
       "TotalCharges          -0.330918        0.651174      1.000000 -0.198324  \n",
       "Churn                  0.107062        0.193356     -0.198324  1.000000  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create a Pearson Correlation Matrix of the Entire Feature-Set\n",
    "df.corr('pearson')  # default | kendall | spearman rank"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.colorbar.Colorbar at 0x2ac37e43b00>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAhwAAAH7CAYAAACHV0bbAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzs3Xm8VXW9//HXmwMCigOidp0STbCU9Ag4D2Ga18qulpRT\nqdWVLIdr3rp5y5IG77WfejPni17CzClnMxNNRc0R0AOI5pCikqaAgqIMcvj8/ljfrcvtPhN7Hfbm\n7PfTx36ctb/ruz7ru/Y5cr7nOyoiMDMzM+tOvWpdADMzM+v5XOEwMzOzbucKh5mZmXU7VzjMzMys\n27nCYWZmZt3OFQ4zMzPrdq5wmJmZNRBJ4yW9JunxNs5L0jmSnpU0XdLwIu7rCoeZmVljmQDs1875\nzwJD0msMcGERN3WFw8zMrIFExL3A6+1kOQD4bWQeAtaRtGG19+1dbQAzMzPruqa1NotYtqjwuLFo\nzkxgcS5pXESM60KIjYGXcu9np7RXqimXKxxmZmY1EMsW0XerrxQed3HL+YsjYmThgavkCoeZmVlN\nCFSXIxv+Dmyae79JSqtKXT6pmZmZ1czNwBFptsrOwIKIqKo7BdzCYWZmVhsCpJV/W+lKYBSwnqTZ\nwKlAH4CIuAi4Ffgc8CzwDvD1Iu7rCoeZmVkDiYhDOzgfwLFF39cVDjMzs1qpzzEc3aJxntTMzMxq\nxi0cZmZmtVKDMRy14gqHmZlZTdTttNhu0ThPamZmZjXjFg4zM7NaaaAuFbdwmJmZWbdzC4eZmVkt\niIYaw+EKh5mZWU3IXSpmZmZmRXILh5mZWa00UJdK4zypmZmZ1YxbOMzMzGqlgcZwuMJhZmZWE15p\n1MzMzKxQbuEwMzOrBdFQXSpu4TAzM7Nu5xYOMzOzWvEYDjMzM7PiuIXDzMysJhprloorHGZmZrXS\ny4NGzczMzArjFg4zM7NaaLDt6RvnSc3MzKxm3MJhZmZWKw208JcrHGZmZjXRWLNUGudJzczMrGbc\nwmFmZlYrDdSl4hYOMzMz63Zu4TAzM6uVBhrD4QqHmZlZLUjuUjEzMzMrkls4zMzMasVdKlZL6t0/\ntNqaVcfZcouNCihNz1RvjZhRUBw/16qliM+nqM8mCvpmFdVDUE8/O//4+0sseGNeT/0xXGlc4ahD\nWm1N+m71larjXHDF2OoLU6DlBf2LVsQ/aL3qrN+0qH/sexe082RR5Wmto+95PSri42kq6MNZ0rq8\nkDh9m4r5i72efna+M3qf6oO0paf+cFfQOG05ZmZmVjNu4TAzM6uJxlra3BUOMzOzWnGXipmZmVlx\nXOEogKQJkkbXuhxmZrYKEVmXStGvOlW/JevBJLkry8zMGkrD/eKT9GPgq8Ac4CVgKnADcD6wPvAO\ncHRE/FXSBOBNYCTwT8B/RMS1kgScC3wmxViaiz8C+B9gADAXOCoiXpE0CWgBdgeuBM7q9oc1M7M6\n5kGjPZakHYCDgO2APsCjZBWOccAxEfGMpJ2AC4BPp8s2JKskfBy4GbgW+CKwFbA18BHgCWC8pD5k\nFZEDImKOpIOB04BvpFirRcTINso2BhgDQJ8BBT61mZnVrQYaNNpQFQ5gN+CmiFgMLJb0B6AfsCtw\njd7/xvfNXXNjRCwHnpD0kZS2J3BlRLQCL0u6K6VvBQwD7kixmoBXcrGubqtgETGOrOJDr9U3KGqR\nPTMzs7rQaBWOSnoB8yOiuY3zS3LHHVVFBcyMiF3aOP92VwtnZmY9WAN1qTTOk2buB74gqZ+kAcD+\nZGM2npf0ZQBltusgzr3AwZKaJG0I7JXSnwLWl7RLitVH0jbd8iRmZmarkIZq4YiIyZJuBqYDrwIz\ngAXA4cCFkk4hG9txFTCtnVA3kI3xeAJ4EXgwxV+apseeI2ltss/3bGBm9zyRmZmt0jyGo0c7MyLG\nSlqdrKViakQ8D+xXnjEijip7PyB9DeC4SsEjooVsjEd5+qiqS25mZj2HPEulpxsnaWuywaKXRsSj\ntS6QmZlZT9dwFY6IOKzWZTAzMwPcpWK1teUWG3HBFWOrjvOFw6qPAXDD704tJM6Q9YtZX+SZOQur\njhEqZubx828WM/Fom3XXLiTOWv2L+V963ttLO87UCX16FdNcvN6A1QqJM+uNYr5fy5YX8/PzsXWr\n/3/i3hfnFlAS2G79Yn4G75o1r5A4m6/br5A4C5cuqzrG4tblBZTEXOEwMzOrETVQC0fjjFYxMzOz\nmnGFw8zMrAZE1sJR9KtT95b2k/SUpGclnVzh/NqS/iBpmqSZkr5e7fO6wmFmZlYL6qZXR7eVmsg2\nLP0s2Z5gh6bZm3nHAk9ExHbAKOAsSVUNpnKFw8zMrLHsCDwbEc9FxFKyxS4PKMsTwJppd/QBwOtA\nVSNwPWjUzMysJjrfBVKwjYGXcu9nAzuV5TmPbIf0l4E1gYPTRqYrrCYtHJJ+lPqEpktqSVvCdzXG\nSEnnrMB1O0q6N/VdPSbpEkmrS/qXUj+WpAPzzUuSfiZpn67ey8zMrAbWkzQl9xqzAjH+GWgBNgKa\ngfMkrVVNoVZ6C0fa2Gx/YHhELJG0HtDlfqGImAJM6cJ9ewODgGuAQyLiwZQ+GlgzIm4mq80BHAjc\nQrZXChHxk66Wz8zMrCPd1MIxNyJGtnP+78CmufebpLS8rwOnp608npX0PPBx4JEVLVQtWjg2JPsw\nlgBExNyIeFnSCEn3SJoqaWLahRVJkyT9UtIjkp6WtEdKHyXplnS8rqQbU4vJQ5K2TeljJV0m6X7g\nMrJBMJeWKhvp/tdGxKuSjpJ0nqRdgX8BzkitLx+TNEHS6NSq0pJeM6Rs9aiU57ZU9vskfTylT5B0\njqQHJD2XKjdmZmZAzWapTAaGSNo8DQQ9hPf/4C55Edg7lfEjwFbAc9U8ay0qHLcDm6bKwwWSPiWp\nD3AuMDoiRgDjgdNy1/SOiB2BE4FKy17+FHgsIrYFfgj8Nndua2CfiDgUGAZMba9wEfEA2Qf//Yho\njoi/5c5NSWnNwG3AmenUOOD4VPbvARfkQm4I7E7WqnN6W/eVNKbU/LXg9WJW6jMzMysXEcvINiCd\nCDwJ/D4iZko6RtIxKdvPgV0lzQDuBH4QEVUta7vSu1QiYqGkEcAewF7A1cAvyCoDd6TaWRPwSu6y\n69PXqcDgCmF3Bw5K8e+SNCjX13RzRCwq8hkkHQwMB/aVNADYFbgmV7Psm8t+Yxpo80SqJVYUEePI\nKi4MHdZczLrJZmZW12o0aJSIuBW4tSztotzxy8C+Rd6zJrNUIqIVmARMSrWnY4GZEbFLG5csSV9b\n6XqZ85snzARGADd1McZ7JA0DxgJ7RkSrpF7A/NTqUcmS3HHjrGFrZmaWs9K7VCRtJWlILqmZrEln\n/TSgFEl9JG3ThbD3AYena0eRjRF5s0K+84Aj87NiJH2pQsvDW2TTgMrLvg5wJXBERMwBSPd5XtKX\nUx5J2q4LZTczs0ZUo4W/aqUWLRwDgHPTL+9lwLPAGLLuhHMkrZ3KdTZZi0RnjAXGS5oOvAMcWSlT\nGhx6CHCmpA2A5cC9ZOMx8q4CLpZ0ApAf6HkAsFk6V4rZTFbZuVDSKUCfdP20TpbdzMwakGq3DkdN\n1GIMx1SyMQ/l5gJ7Vsg/Knc8lzSGIyImkXXLEBGvk01lLb92bIW0B8nGj5SbkF5ExP1kg01Ljsod\nX1oh5vPAfhXSjyp7X8z+7GZmZqsYrzRqZmZWI43UwuG9VMzMzKzbuYWjB7vhd5WWLOm6L371p4XE\n+dTRXyskzsABVW1YCMCRIzYpoCTQq6ARWotbWwuJ8/jsBYXEKcq7rcXM8B7wZlMhcVqXF1OeXgX9\nUXrnlDeqjvGlT2xQQElgndX7FBLnY4P6FRLn3ueK+Vk+fpfNqo5x7mrd96vSLRxmZmZmBXILh5mZ\nWY00UguHKxxmZma1UOfrZhTNXSpmZmbW7dzCYWZmViON1KXiFg4zMzPrdg1T4ZDUKqlF0uOSrpG0\nehevP7Gr15iZmbWltLR50a961TAVDmBRRDRHxDBgKXBMZy+U1AScCBRS4ZDkriwzM3OFowHcB2wJ\nIOlGSVMlzZQ0ppRB0kJJZ0maBvwI2Ai4W9LdufOnSZom6aHSjrOS1pd0naTJ6bVbSh8r6TJJ9wOX\nreTnNTMzq6mGq3Ck1oXPAjNS0jciYgQwEjhB0qCUvgbwcERsFxE/A14G9oqIvXLnH4qI7ch2nD06\npf8a+FVE7AAcBFySu/3WwD4RcWiFco2RNEXSlAWvzyvsec3MrI55e/oeqb+klnR8H/B/6fgESV9M\nx5sCQ4B5QCtwXTvxlgK3pOOpwGfS8T7A1rlmrbUklXaJvTkiFlUKFhHjgHEAQ4c1F7P+spmZWZ1o\npArHoohozidIGkVWQdglIt6RNAkobQSwOCLa2+Di3YgoVQxaef+z7AXsHBGLy+4F8HZVT2BmZj2H\nPC22kawNvJEqGx8Hdm4n71vAmp2IeTtwfOmNpOZ28pqZWQPzoNHGcRvQW9KTwOnAQ+3kHQfcVho0\n2o4TgJGSpkt6gi7MhjEzM+upGqZLJSIGVEhbQjaAtMP8EXEucG6l8xFxLXBtOp4LHFwh3tgVLLqZ\nmfVQ9dwiUbRGb+EwMzOzlaBhWjjMzMzqSWml0UbhCkedWh7Vz4wdsv6HepFWyKeO/lohce65uJj1\nzs46/3tVx+jdq5j/yYcO7Mw44o4tWLq0kDhFWbtvMf809CroH9O3li4rJM76/fsWEme1pmIah5/r\nt6TqGGv361NASWD+O+8WEmfr9dYuJE7fpqZC4hTxM9g4VYLu5QqHmZlZrTRQbcYVDjMzs1rwOhxm\nZmZmxXILh5mZWY24hcPMzMysQG7hMDMzqxG3cNSApFZJLZJmSpom6d8l1ax8kmZJWm8Frz1Q0tZF\nl8nMzHqYBtqevm4qHKTdXCNiG7Kt3j8LnFrjMq2oAwFXOMzMzJJ6qnC8JyJeA8YAxynTJOkMSZPT\npmjfgmx7eUn3SvqjpKckXVRqFZG0r6QHJT0q6RpJA1L6LEk/Tekz0i6xSBok6fbUwnIJuXqipK9K\neiS1wPyvpKaUvlDSaalF5iFJH5G0K/AvwBkp/8cknSDpiVT2q1bqh2lmZnXLu8XWgYh4DmgCNgC+\nCSyIiB2AHYCjJW2esu5Ith381sDHgC+lrpBTgH0iYjgwBTgpF35uSr8QKC1beSrwl9TCcgPwUQBJ\nnyDbjG23iGgGWoHD0zVrAA9FxHbAvcDREfEAcDPw/dRi8zfgZGD7iNiWNnaPlTRG0hRJUxa8Pm8F\nPzUzM7P6tKoMGt0X2FbS6PR+bWAIsBR4JFVOkHQlsDuwmKwCcn+q7a0GPJiLd336OhX4Ujres3Qc\nEX+U9EZK3xsYAUxOsfoDr6VzS4FbcrE+00b5pwOXS7oRuLFShogYB4wDGDqsufp1zc3MrK7Ve4tE\n0eq2wiFpC7LWhNfIujeOj4iJZXlGAeW/nCPlvyMiDm0jfGkDg1Y6/gwEXBoR/1nh3LsR72160l6s\nz5NVaL4A/EjSJyOimM0hzMxsldVIFY667FKRtD5wEXBe+oU+Efi2pD7p/FBJa6TsO0raPI3dOBj4\nC/AQsJukLVP+NSQN7eC29wKHpfyfBQam9DuB0ZI2SOfWlbRZB7HeAtZM+XsBm0bE3cAPyFpnitlV\nzczMbBVRTy0c/SW1AH2AZcBlwP+kc5cAg4FHlVUH55DNBAGYDJwHbAncDdwQEcslHQVcKam0PeQp\nwNPt3P+nKf9M4AHgRYCIeELSKcDtqfLwLnAs8EI7sa4CLpZ0AnAI8H+S1iZrLTknIuZ34vMwM7Me\nrpFaOOqmwhERbe5FHBHLgR+m13vSN+rNiNi/wjV3kQ0wLU8fnDueAoxKx/PIxopUuv/VwNUV0gfk\njq8Frk3H9/PBabG7t/FoZmZmDaFuKhxmZmYNp3EaOFbtCkdETAIm1bgYZmZm1oFVusLRkxXRrffM\nnIXVBwEGDlitkDhnnf+9jjN1wr8fe2bVMW66vJhFbC997O+FxDlq+MaFxLnlr3MLifP2kvqaRDWg\nb59C4vRf7Z1C4ixbXkgY/nD3s1XH+NRmAzvO1Am7bDGokDj/fVf1zwTwP+PuKSTOP674RtUx+jR1\n3/wKj+EwMzOz7qXGqnDU5bRYMzMz61ncwmFmZlYDopju81WFWzjMzMys27mFw8zMrCYaay+Vhmzh\nkLSOpO/UuhxmZtbYpOJf9aohKxzAOkC3VjgkufXIzMwsadQKx+nAxyS1SDpD0vclTZY0XdJPASQN\nlvSkpIslzZR0u6T+6dwkSSPT8XqSZqXjoyTdLOkusk3fqBTbzMwM3t+ivshXvWrUCsfJwN8iohm4\nAxgC7Ag0AyMk7ZnyDQHOj4htgPnAQZ2IPRwYHRGfkrRvO7HNzMwahpv9sw3b9gUeS+8HkFUSXgSe\nj4iWlD6VbMfajtwREa93EPve8oskjQHGAGyw4SZdfggzM1vF1PmYi6K5wpFNhf7viPjfDyRKg4El\nuaRWoH86Xsb7rUP9yuK93VHsSiJiHDAOYOiw5uhk2c3MbBUloFevxqlxNGqXylvAmul4IvANSQMA\nJG0saYMOrp8FjEjHo9vJtyKxzczMupWk/SQ9JelZSSe3kWdUGus4U1LVm9s0ZAtHRMyTdL+kx4E/\nAVcAD6bBNguBr5K1aLTlTOD3qRvkj+3c53ZJn6gQ+7VCHsTMzFZptehSkdQEnA98BpgNTJZ0c0Q8\nkcuzDnABsF9EvFjEH8sNWeEAiIjDypJ+XSHbsFz+M3PHfwW2zeU7JaVPACaU3efXbcQ2MzOrhR2B\nZyPiOQBJVwEHAE/k8hwGXB8RLwJERNV/KDdql4qZmVnNddO02PUkTcm9xpTddmPgpdz72Sktbygw\nMC0DMVXSEdU+a8O2cJiZmfVQcyNiZJUxepONVdybbMLEg5IeioinqwlodUZArwI69kLFTHY5ckQx\n03R7FzQa+6bLT606xgGHF7MG221X/ayQOBc8+EIhcY7Z+aOFxHnn3faGMHVen6Zivud9ehXTGDt/\nydJC4hTx/yfAAR/fueoYrcsLKAjw8POvd5xpJfrfH+1XSJwinuvtpcsKKEkFtZsW+3dg09z7TVJa\n3mxgXkS8Dbwt6V5gO2CFKxzuUjEzM6uBbHv6mqw0OhkYImlzSasBhwA3l+W5CdhdUm9JqwM7AU9W\n87xu4TAzM2sgEbFM0nFkSzc0AeMjYqakY9L5iyLiSUm3AdOB5cAlEfF4Nfd1hcPMzKwmarf3SUTc\nCtxalnZR2fszgDOKuqe7VMzMzKzbuYXDzMysRryXipmZmXW7et5OvmgrtUtFUmtal/1xSddIWl3S\n4LTEeHfet5ekc9J9Z0iaLGnzgmJfImnrImKZmZn1VCu7hWNRRDQDSLocOAa4fiXc92BgI2DbiFgu\naRM+uKtruyQ1RUTFhQki4l8LKqOZmTWSBtuevpaDRu8DtkzHTZIuTjvS3S6pP4CkZkkPSZou6QZJ\nA1P6JEm/lPSIpKcl7ZHSmySdkVowpkv6Voq/IfBKRCwHiIjZEfFGumZfSQ9KejS1upR2dp2V7vEo\n8H1Jj5QKnlplZuTKMjId75fiTJN0Z0pbQ9L4VNbHJB3QrZ+qmZlZHapJhUNSb+CzwIyUNAQ4PyK2\nAeYDB6X03wI/iIhtU978EpO9I2JH4MRc+jeBBRGxA7ADcHTqOvk98IXUnXOWpO1TOdYj23htn4gY\nDkwBTsrdY15EDI+I04HVct0wBwNXlz3T+sDFwEERsR3w5XTqR8Bdqax7AWdIWqPCZzKmtO79/Dfm\ndfwhmpnZKq2GC3/VxMqucPSX1EL2i/1F4P9S+vMR0ZKOpwKDJa0NrBMR96T0S4E9c7Guz+dPx/sC\nR6R7PAwMAoZExGxgK+A/yRYwuVPS3sDOwNbA/emaI4HNcvfIVyp+T1bRgAoVjhTr3oh4HiAiSuvp\n7gucnOJPAvoBH1p/OiLGRcTIiBi5zsBB5afNzKwHkop/1auajeEoSbWxJbmkVrKNYjpSuqaV959D\nwPERMbE8c0QsAf4E/EnSq8CBwO3AHRFxaBv3yI/zuBq4RtL1Wbh4phNlLJXpoIh4qpP5zczMepy6\nXfgrIhYAb5TGZwBfA+5p5xLIlmn9tqQ+AJKGpjEUwyVtlNJ6AdsCLwAPAbtJ2jKdW0PS0DbK8zey\nys2P+XDrBinWnqVuF0nr5sp0vFLNqtSdY2Zm1khdKvW+DseRwEXKNo55Dvh6B/kvIeteeTT9gp9D\n1pKxAXCxpL4p3yPAeRGxWNJRwJW5c6fQ9m54V5Mt8/qhKbURMUfSGOD6VKl5DfgM8HPgbGB6Sn8e\n2L+jBzczM+tJVmqFIyIGVEibBQzLvT8zd9xCNjai/JpRueO5pDEcaRbKD9Mr77b0qlSmu8gGmJan\nD66QdiZwZllavix/Iuu2yZ9fBHwLMzOzMnXcIFG4em/hMDMz65nklUbNzMzMCuUWjh7s+Tc7vZhq\nu3pRTA186MA1C4lz6WN/rzrGbVf9rICSwH6H/KSQOA/c+F+FxJnz9pKOM3UmzqLFhcRZXkgU2HiN\nzkxc69gLC4p5rogoJM66q/epOsabS5YVUBLYZ4sNCokz7cX5hcSZ+vwbhcQ5do/BVcco6vtdLluH\no1tC1yW3cJiZmVm3cwuHmZlZTdT3NNaiuYXDzMzMup1bOMzMzGqkgRo4XOEwMzOrFXepmJmZmRWo\nVtvTh6Tf5d73ljRH0i2duHZh+jpY0mG59JGSzung2sGSHl+RPJJ+JmmfjspnZmbWKd2wU2w9N5jU\nqkvlbWCYpP5p6e/PAF1dXGEwcBhwBUBETCHb9r5bREQxCy6YmZk1oFp2qdwKfD4dHwpcWTohaayk\n7+XePy5pcNn1pwN7SGqR9F1Jo0otJOn6yyQ9KOkZSUeX31xSk6QzJE2WNF1Su/udSJogaXQ6niXp\np5IelTRD0sdT+hqSxkt6RNJjkg5I6duktJZ0ryFd/KzMzKyHyRb+apzdYmtZ4bgKOERSP7Lt4h/u\n4vUnA/dFRHNE/KrC+W2BTwO7AD8pbU+f801gQUTsQLZ529GlreU7aW5EDAcuBEqVox8Bd0XEjsBe\nwBmS1gCOAX4dEc3ASGB2eTBJYyRNkTRl/hvzulAMMzNbVbnCsRJExHSybpFDyVo7inZTRCxKu8ne\nDexYdn5f4AhJLWSVnUFAV1oerk9fp5J2q00xT04xJwH9gI8CDwI/lPQDYLPUjfQBETEuIkZGxMh1\nBg7qQjHMzMzqX62nxd5Mtt37KLJf+CXL+GBlqN8KxC5f/L78vYDjI2LiBxI/3HXTltKmFa28/zkK\nOCginirL+6Skh8m6kG6V9K2IuKuT9zEzsx6qjhskClfrabHjgZ9GxIyy9FnAcABJw4FKXR1vAe3t\nBnaApH6SBpFVaCaXnZ8IfFtSn3Sfoan7oxoTgeOV2rQkbZ++bgE8FxHnADeRdfeYmZk1jJq2cETE\nbKDSVNbryLo7ZpJ1dzxdIc90oFXSNGAC8FiF83cD6wE/j4iXy1ovLiHrCnk0VRDmAAemc1tJyo+z\n+G4nH+nnwNnAdEm9gOeB/YGvAF+T9C7wD6CYrUHNzGyVVs9jLopWkwpHRAyokDaJbNwDaYzDvu1d\nGxHvkg0KzZuUO54eEUeUXTsLGJaOlwM/TK+8BUClPaOvycUZnDueQtaCUir3h2a7RMTpZLNqzMzM\nMnW+bkbRat2lYmZmZg2g1oNGu0VEjK11GczMzNqjBtuevkdWOFZ1AUT5nJoVsM26a1cfBFjc2lpI\nnAVLlxYS56jhG1cd44IHXyigJPDAjcUMx9n1wPKevRUz8eqfFRJn3X59C4kTH5octmL69W4qJM66\n/Yv5J6+pV/38kvjUZusXEqflH/MLiXPpV4cXEmfOm0s6ztQJry+s/t+dpl7uDCiCKxxmZmY10kAN\nHB7DYWZmZt3PLRxmZmY10quBmjhc4TAzM6uRBqpvuEvFzMzMup9bOMzMzGpAaqyVRgtr4ZC0sBN5\nTpS0elH3bOc+gyUdlnu/uqTLJc2Q9Likv0j60GqnK3ivWyWtU0QsMzOznmpld6mcCHSpwiFpRSbg\nDwYOy73/N+DViPhkRAwDvgm8W0QZIuJzEVHMBHYzM2sovVT8q14VXuGQNErSJEnXSvpralmQpBOA\njYC7Jd2d8u4r6UFJj0q6ptTqIGmWpF9KehT4cor3S0mPSHpa0h4pX5OkMyRNljRdUmkfk9OBPSS1\nSPousCHw91IZI+KpiFiSYnw1xW2R9L+lyoWkhZLOSpvD/aek9/ZSSc94S66s66XjI1I5pkm6LKWt\nL+m6VMbJknYr+jM3M7NVk6TCX/Wqu1o4tidrzdga2ALYLW3N/jKwV0TslX5JnwLsExHDgSnASbkY\n8yJieERcld73jogdU9xTU9o3gQURsQOwA3C0pM2Bk4H7IqI5In4FjAd+kCo3v5A0BEDSJ4CDU/ma\ngVbg8BR7DeDhiNiOrAKzU277+oOBUrlIsbZJz/PpdM2/pVO/Bn6VyngQ2S61HyJpjKQpkqYseH1e\nhx+wmZnZqqS7Bo0+kraeR1ILWRfHX8ry7ExWIbk/1chWAx7Mnb+6LP/16evUFA+yHWW3lTQ6vV8b\nGAJ8YC3biGiRtEXKvw8wWdIuwN7AiPQeoD/wWrqsFbguXb9M0m3AFyRdC3we+I+y8n0auCYi5qZr\nXk/p+wBb52qda0kaEBEfGPMSEeOAcQBDhzUXsx60mZnVtTpukChcd1U48ovgt7ZxHwF3RMShbcR4\nu42Y+XgCjo+IiR8ILI0qD5Z+wV8PXC9pOfA5sorJpRHxnxXuvzgi8puIXAUcB7wOTImIt9ood7le\nwM4RsbiT+c3MzHqclT1o9C1gzXT8ELCbpC0BJK0haWgX400Evi2pT4oxNHV75O+DpN0kDUzHq5G1\nrLwA3AmMlrRBOreupM3auNc9wHDgaMq6U5K7yMabDCrFSum3A8fnytLcxWc0M7MeSKQdYwv+r16t\n7HU4xgG3SXo5jeM4CrhSUmlrylOAp7sQ7xKy7pVHlfVZzAEOBKYDrWnA5wRgHnBhytML+CNwXUSE\npFOA2yVQWQuoAAAgAElEQVT1Ipu5cixZZeQDIqI1DRQ9CjiywvmZkk4D7pHUCjyW8p4AnC9pOtnn\nfS9wTBee0czMeqh6nlVStMIqHBExIH2dBEzKpR+XOz4XODf3/i6ywZ7lsQaXvR+VO55LGsMREcuB\nH6ZXuU+Xvf9tG+W+mg+PF3nvecrSjiPrVqlY1oi4FLi07PxcskGmZmZmDcsrjZqZmdVCnU9jLZr3\nUjEzM7Nu5xaOOiSgdwEde2v1L+bb+/jsBYXEKcotf51bdYxjdv5oASWBOW8v6ThTJ0y8+meFxPnn\ng39SSJzTzj6p40yd0FRQB/WsN4pZzHevzYvZhWB5FDNz/ffTXq06RvM/DSygJDB04JodZ+qEZ17p\ncJeLTrnp6eo/G4ATd9+i6hh9e3ff3+YN1MDhFg4zMzPrfm7hMDMzqwEBvRqoicMtHGZmZjWSbVFf\n7Ktz99V+kp6S9Kykk9vJt4OkZbkVvVeYKxxmZmYNJG1Sej7wWbKFMA+VtHUb+X5JtoBl1VzhMDMz\nq5Ea7Ra7I/BsRDwXEUvJVs8+oEK+48n2FHutwrkuc4XDzMysZ1mvtPt4eo0pO78x8FLu/eyU9h5J\nGwNfBC4sqlDdVuGQtImkmyQ9I+lvkn6d9jFp75pZadt6JD1Qxb13lvSwpBZJT0oau6KxOnm/kZLO\nScejJO3anfczM7NVX3eM30gNHHMjYmTuNW4Finc28IO0onchumWWStqz5Hrgwog4IPUDjQNOA77f\nmRgRUc0v7UuBr0TEtHTvraqI1S5JvSNiCjAlJY0CFgIrXGEyM7PGUKNZKn8HNs293ySl5Y0Erkpd\nNOsBn5O0LCJuXNGbdlcLx6fJtnf/DWQbnwHfBb4h6TuSrpd0W2r9+H+VAkhamL6OkjRJ0rWS/irp\n8lShQdIISfdImippoqQN0+UbAK+U7h0RT6T8a0gaL+kRSY9JOiClN0k6U9LjkqZLOj6l51tcRkqa\nlI7HSrpM0v3AZamMt0gaTLYx23dT68oekp7X+7vZrpV/b2ZmVgOTgSGSNk89D4cAN+czRMTmETE4\n7Rd2LfCdaiob0H3rcGwDTM0nRMSbkl5M92wGtgeWAE9JOjciXvpwmPdsn2K+DNxPtq39w2QbwR0Q\nEXMkHUzWgvIN4Fcp7iTgNuDSiFgM/Ai4KyK+IWkd4BFJfwaOINsQrjkilun9reXbszWwe0QskjQq\nPeMsSRcBCyPiTIBUhs8DN5J9U6+PiHfLg6U+tjEAH9lok07c3szMVnW1aN9Iv+eOAyYCTcD4tOP5\nMen8Rd1x31ot/HVnRCwAkPQEsBkfHMBS7pGImJ3yt5BVDuYDw4A7UoNHE++3avxM0uXAvsBhwKFk\nXR37Av8i6Xspbj/go8A+wEURsSxd/3onnuHmiFjUiXyXAP9BVuH4OnB0pUypj20cwFbDmotZN9nM\nzKyCiLgVuLUsrWJFIyKOKuKe3VXheAL4wCIhktYi++W+jKxlo6S1E+WolF/AzIjYpdIFEfE34EJJ\nFwNzJA1K1xwUEU+Vla2t+y7j/W6nfmXn3u6gzKVy3C9pcGoFaYqIxztznZmZ9XydnMbaI3TXGI47\ngdUlHQHvLR5yFjABeKegezwFrC9pl3SPPpK2Scef1/vfxSFklZT5ZM1Hx+fGgGyf8twBfEtS75Re\n6lKZBYxIxwd1slxvAeW7IP0WuAL4TaefzszMerRsafPiX/WqWyocERFk83e/LOkZ4GlgMfDDAu+x\nlKwV5ZeSpgEtQGlmy9fIxnC0AJcBh6eBqz8H+gDTJc1M7yHr9ngxpU8j64YB+Cnwa0lTyCotnfEH\n4IulQaMp7XJgIHDlij2tmZnZqq3bxnCkQaBfqHBqQnqV8u2fOx6cOx6Qvk4CJuXSj8sdtwB7Vrj3\nIW2UaRHwrQrpy4CT0iuffh8wtEL+sWXv3ytjRDwNbFt2ye7AtRFRzB7bZma26uv8yqA9gneL7WaS\nziVbr/5ztS6LmZlZrbjC0c0i4vhal8HMzOpTAzVwuMJRr6KAibHz3l5afZACrd23mB+3t5csqzrG\nO+92dkhO++YsWlxInHX79S0kzmlnn9Rxpk740Yn/U0icnxdUno3WKmatvFfeLub71VTQb4mPrF0+\n+a3rXn2zmGcatEa7O0902ow5bxYS54V5nVl1oGNvLvrQskddtny5VyoogiscZmZmNeIxHGZmZtat\nStNiG4W3pzczM7Nu5xYOMzOzGmmkLhW3cJiZmVm3cwuHmZlZjTRO+8ZKbOGQtImkmyQ9I+lvkn4t\nqd15WJJmSVovHT9Qxb0nSHo+LTf+V0mnrmCcUZJuWdFymJmZlUjQSyr8Va9WSoUjbZZ2PXBjRAwh\nWy58AHBaZ2NExK4d52rX9yOiGWgGjpS0eZXxzMzMrJNWVgvHp4HFEfEbgLSR2neBb0j6jqTrJd2W\nWj/+X6UAkhamr6MkTZJ0bWqtuDy3++sISfdImippoqQNK4QqrbTzdrrmJ5ImS3pc0rhcrC0l/VnS\nNEmPSvpYWXl2kPSYpI9JGivpe7lzj6ct6QfnyvhkKvPqVX2SZmbWY0jFv+rVyqpwbANMzSdExJtk\nO7T2Jmt1OBj4JHCwpE07iLc9cCKwNbAFsJukPsC5wOiIGAGM54MtKGek3WNnA1dFxGsp/byI2CEi\nhgH9gdJmcpcD50fEdmS70L5SCiRpV+Ai4ICI+FsHZd0KuCAiPgG8CXynUiZJYyRNkTRlwRvzOghp\nZma2aqmXWSp3RsSCiFgMPAFs1kH+RyJidkQsJ9uWfjDZL/ZhwB2pYnEKsEnumlKXyj8Be6dKA8Be\nkh6WNIOsJWYbSWsCG0fEDQARsTgi3kn5PwGMA74QES924tleioj70/HvyHaO/ZCIGBcRIyNi5NoD\nB3UirJmZreqUdowt8lWvVtYslSeA0fkESWsBHwWWAUtyp1o7Ua5K+QXMjIhd2rswIhZKmgTsLulR\n4AJgZES8JGks73e5tOWVlGd74OWUtowPVt7yMcoX4fei/GZmBtR3F0jRVlYLx53A6pKOAJDUBJwF\nTADeaee6rngKWF/SLukefSRtU55JUm9gJ+BvvF8xmCtpAKlSFBFvAbMlHZiu6ZsbezEf+Dzw35JG\npbRZwPCUdziQH5D60VKZgMOAv1T/qGZmZquWlVLhiIgAvgh8WdIzwNPAYuCHBd5jKVmF4ZeSppF1\nteRntpTGcEwHZgDXR8R84GLgcWAiMDmX/2vACZKmAw+QdcWU7vUq2ViP8yXtBFwHrCtpJnBcer6S\np4BjJT0JDAQuLOqZzcxs1SWKnxJbz9NiV9rCXxHxEvCFCqcmpFcp3/6548G54wHp6yRgUi79uNxx\nC7BnhXsf1U65TiEb71Ge/gzZmI6850r3TuM38i0o+5bHkDQYWBYRX23r/mZmZo3AK42amZnVQp1P\nYy2aKxzdKCJmkc2cMTMza2iucNShAFqj+sksfXoVM0Tn3dZiJtbUU99in6ZiyrK8kCgQBU1eaupV\nzHP9/OyTConz4xP/p5A43z/9hELi/OPNdwuJU8T/nwAL3qm+PKs1FfP/eVHTKd9a2lpInOXLi/mM\nWwuI051TC+t5GmvRXOEwMzOrkXpZDGtlaKRnNTMzsxpxC4eZmVkNiMbqUnELh5mZmXU7t3CYmZnV\nSEHjvFcJrnCYmZnVSCNVODrdpSKpVVKLpJmSpkn6d0kr1CUjaaSkc1bw2kmSnkpluF/SVl28/ihJ\nG63gvQdLOiz3foWfw8zMrJF0pYVjUdreHUkbAFcAawGndvWmETEFmNLV63IOj4gpksYAZwD/kj8p\nqSki2poMfhTZ3ikvt3G+PYPJNmC7Agp5DjMza1CSB412KCJeA8YAxynTJOkMSZMlTZf0LQBJV0n6\nfOk6SRMkjZY0StItKW2ApN9ImpGuPSil7yvpQUmPSrom7eZa7l5gy5R/lqRfpi3nvyypWdJDKeYN\nkgZKGg2MBC5PrTX9JY2QdI+kqZImStowxdtS0p9TS8qjkj4GnA7ska79btlzrCvpxnS/hyRtm9LH\nShqfWmaek1TMCkZmZmarkBWepRIRzwFNwAbAN4EFEbEDsANwtKTNgauBrwBIWg3YG/hjWagfp2s/\nGRHbAndJWo9sQ7V9ImI4WStCpaUPv0C282vJvIgYHhFXAb8FfpBizgBOjYhrU6zDU2vNMuBcYHRE\njADGA6elWJcD50fEdmS7zr4CnAzcFxHNEfGrsrL8FHgs3e+H6f4lHwf+GdgROFVSn/IHkTRG0hRJ\nUxa8Pq/Co5qZWU/TS8W/6lVRg0b3BbZNLQgAawNDgD8Bv5bUF9gPuDciFpU1Ie0DHFJ6ExFvSNof\n2Bq4P+VdDXgwd83lkhYBs4Djc+lXA0haG1gnIu5J6ZcC11Qo91Zke53cke7TBLwiaU1g44i4IZVp\ncYrb3mewO3BQyn+XpEGS1krn/hgRS4Alkl4DPgLMzl8cEeOAcQBDhzV350q6ZmZWJxqoR2XFKxyS\ntgBagdfI1i85PiImVsg3ieyv+4OBqzobHrgjIg5t4/zhafxEubc7GT9/n5kRscsHErMKR5GW5I5b\n8ewgMzNrMCs6y2R94CLgvIgIYCLw7VJXgaShktZI2a8Gvg7sAdxWIdwdwLG52AOBh4DdJJXGZ6wh\naWhnyxcRC4A3JO2Rkr4GlFo73gJKFYqngPUl7ZLu00fSNhHxFjBb0oEpva+k1cuuLXcfcHjKPwqY\nGxFvdrbMZmbWWES2qWXRr3rVlQpH/9K0WODPwO1k4xYALgGeAB6V9Djwv7z/V/ztwKeAP0fE0gpx\nfwEMlPS4pGnAXhExh2w2yZWSppN1p3y8a4/GkcAZ6fpm4GcpfQJwkaQWsi6U0cAv071byMZrQFZJ\nOSFd/wDwT8B0oDUNJP1u2f3GAiNS/tPT/c3MzIwuNO1HRFM755aTDZT8YYVz7wLrlqVNAial44VU\n+OUcEXeRDUAtTx/VRhkGl71vAXaukO864LpcUguwZ4V8zwCfrnCr8rRJKf/rwIEV4owtez+sQkwz\nM2tAjbS/SCM9q5mZmdWIBy+amZnVSB0PuSicKxx1KNuyuPo46w1YrfogwIA32+xN65K3li4rJM6A\nvh9axqTL+vQqpnFv4zX6FxKnX+9iPuNZb8wvJM5Ga1X/GQN8//Ri1rk74+RidhA447x/LyROUe54\nYmHVMdboW8w/48talxcS5xODipnk9/y8JR1n6oR1Vq/+Z7mpmxa3UJ0P8iyau1TMzMys27mFw8zM\nrEYaqIHDLRxmZmbW/dzCYWZmViP1vPdJ0VzhMDMzq4HSSqONomZdKmlzs5b0+oekv+fed3p6haRf\nSDqxjXM/kTQzbRn/mKQPLSS2skg6SVK/Wt3fzMyslmrWwhER88iWHEfSWGBhRJxZVPy0j8q+wPYR\nsTTt/1KT55XUBJwEjAcW16IMZmZWfxqogaM+B41KOlLSI6m14wJJvVL65yU9mvYyuT13yScl3SPp\nOUmljeA2BOaU9m+JiDkR8UqKM1vSOul4Z0l/Tse/kHSppIckPSPpGyl9H0l3S/qTpKckna+0V72k\nr0qakfaC+a+U1lvSfElnp71V/gPYALivdC8zM7NGUndjOCQNA74I7BoRyySNAw6RdBdwIbBHRLwg\nKb8/y1Bgb2Ad4ElJF5HtTHuKpKfINpu7KiLu60QRPkm2gdtaZJvR/TGl7wRsDbxEtsPtAZKmkG0+\nNxJYAPxZ0v7p3msD90bEiem5jk1lL2ZlJjMzW7XJg0ZrbR+yTdumpEaE/mS/5BcBd0fEC/DeZmkl\nt6SWjNckvQ6sHxH/kDQc2APYC7hW0vci4rIO7n9jRCwGFku6N5VlMfBQRMwCkHQVsDvZbrN3RcTc\nlH4F2UZwtwFLgRs6+9CSxgBjADbYaJPOXmZmZqsw0Tg1jnrsUhEwPiKa02uriPh5B9fk18BtJVWk\nImJZRNwdET8B/g34UsqzjPefvXwgZ7Txvq30tiyKiI7yvB8sYlxEjIyIkesMHNTZy8zMzLpM0n5p\niMCzkk6ucP7wNOFihqQHJG1X7T3rscLxZ+ArktaD92azfBR4ANhL0mYpfd12YiDpE5K2zCU1Ay+k\n41nAiHR8UNmlB0rqmwaZ7gFMSek7S/poGgD6FeAvwMOpTIMk9QYOAe5po0hvAcVsMmBmZqu8bFps\n8a8O75v9Hjsf+CzZUIFDJW1dlu154FMR8Ung58C4ap+37rpUImKGpJ+SjYfoBbwLHBMRkyV9G7gp\nDdh8mezDassA4BxJawHLgadIXRbAWOBiSfOBe8uue5ys0jAIODUiXpX0SeAR4CLgY2SVopsjIiT9\nGJhE9rPzh4j4Y6p8lBuXnumliNinK5+JmZlZgXYEno2I5+C9YQIHAE+UMkTEA7n8DwFV9/XXRYUj\nIsaWvb8CuKJCvj8CfyxLO6Xs/cfT4WxglzbuNwkY0kZxHouIIyukL4iIAyvE+h3wu7K0ZWQDWPNp\nvwJ+1cY9zcysAXXToNH10qSGknERkW+h2JhsbGTJbLKJEW35JvCnagtVFxUOMzMzK8zciBhZRCBJ\ne5FVOHavNpYrHDnlrSW59D+TdaOYmZkVRrVZ+evvwKa595uktA+QtC1wCfDZtFhnVVzhMDMzq4HS\noNEamAwMkbQ5WUXjEOCwfIY0WeN64GsR8XQRN3WFoweb9cbbhcRpXd7p2b3tWr9/30Li9F/tnapj\nzF+ytICSwAsLilmpft3+xfyvuNfm63ScqRNeebuY5/rHm+8WEueM8/69kDjfP+6sQuLsfcwRhcTZ\nYfOBVcd4Yu6CAkoCnxi0ViFxrpj2SiFx3lpUzM/Os69W/+/gkneXF1CS+pEW1TwOmEi2ntT4iJgp\n6Zh0/iLgJ2STJy5IrTDLqu2mcYXDzMysFlS7vVQi4lbg1rK0i3LH/wr8a5H3rMd1OMzMzKyHcQuH\nmZlZjfRqoO1iXeEwMzOrgRoOGq0Jd6mYmZlZt6tphUPSjyTNTBvEtEjaSdKJklavQVluldTlIf6S\n/jmVvUXSwrQZTouk30ual5ZWz+e/UdLBxZXczMxWVVLxr3pVswqHpF2A/YHhEbEt2bb0LwEnAhUr\nHGnDmW4REZ+LiPkrcN3E0s62ZBu9HZ7ef4VsytEXS3klrU22Wtsfiiq3mZnZqqCWLRwbki2/ugQg\nIuYCo4GNgLsl3Q2QWg3OkjQN2EXSCEn3SJoqaaKkDVO+oyVNljRN0nWlVhJJEyRdKOkhSc9JGiVp\nvKQnJU0oFUbSLEnrSRqczl2cWl9ul9Q/5dkh1xpzhqTHO3jGK8kWVCn5IjAxIqpfSMLMzFZxolc3\nvOpVLSsctwObSnpa0gWSPhUR55DtArtXROyV8q0BPBwR25FtB38uMDoiRgDjgdNSvusjYoeU70my\ntd9LBpJt5PZd4GayTdS2AT4pqblC2YYA50fENsB83t/C/jfAt1JrRmsnnnEiMFzSoPT+ELJKyIdI\nGiNpiqQp89+oegVZMzOrc8JdKitFRCwERpBtGT8HuFrSURWytgLXpeOtgGHAHZJagFN4f8vcYZLu\nkzQDOJysQlHyh4gIYAbwakTMiIjlwExgcIV7Ph8RLel4KjA4je9YMyIeTOkf2s22wjMuJavgjJa0\nHrA9WSWkUt5xETEyIkauM3BQpSxmZmarrJpOi42IVmASMClVFCptC7845YOsQjgzIiptOz8BODAi\npqWKy6jcuSXp6/Lccel9pc8gn6cV6N/ug7TvSuDHZGW/KSKKWa/XzMxWbfK02JVC0laShuSSmoEX\ngLeANdu47Clg/TTgFEl9JJVaMtYEXpHUh6yFo1BpQOlbknZKSYe0lz9nElkXzbG00Z1iZmbW09Wy\nhWMAcG7qqlgGPEvWvXIocJukl3PjOICsi0LSaOCcNOOjN3A2WdfIj8nGeMxJX9uqtFTjm8DFkpYD\n9wAd7poUEcslXQt8JV1jZmYGeKXRlSIipgK7Vjh1bnqV8g0ou64F2LNCvAuBCyukH5U7nkU2BqTS\nucHpcG5ZnjNz4WamKbxIOplsGmz+XqMqPA8RcSLZdF8zM7OG5KXNu+bzkv6T7HN7ATiqtsUxM7NV\nVWmWSqNwhaMLIuJq4Opal8PMzHqGRupS8V4qZmZm1u3cwtGDLVsehcQpatrWak3F1G+XLa8+RlF/\nVWTLu1SvqaAPeXlR5Sno82ktqDxF2fuYIwqJc+dFvy0kzsjT/63qGD31L+SifnQK+Xi68SPuod++\nitzCYWZmZt3OLRxmZmY1IBrrr35XOMzMzGpBoAbqU2mkypWZmZnViFs4zMzMaqRx2jc62cIh6UeS\nZkqaLqlF0k6STpS0encXsEJZbk3Loa/ItaMkhaR/zaU1p7TvrWDMSyRtvSLXmpmZNYoOWzjSRmn7\nA8MjYknaZn01sgWwfge8U+GaptwOr4WKiM9VGeJxsn1NLknvDwWmVVGef+04l5mZ2QeJnjutuZLO\ntHBsCMyNiCUAETEXGA1sBNwt6W4ASQslnSVpGrCLpBGS7pE0VdJESRumfEdLmixpmqTrSq0kkiZI\nulDSQ5KeS60R4yU9KWlCqTCSZklaT9LgdO7i1Ppyu6T+Kc8OudaYMyQ9nnueF4B+kj6ibLTOfsCf\ncvGbUxmmS7pB0kBJH5f0SC7PYEkz0vEkSSPT8b6SHpT0qKRrJA1I6adLeiLFzO/NYmZmDUzd8KpX\nnalw3A5sKulpSRdI+lREnAO8DOyV29F1DeDhiNiObLfWc4HRETECGA+clvJdHxE7pHxPku3AWjIQ\n2AX4LnAz8CtgG+CTkporlG0IcH5EbAPMBw5K6b8BvhURzUCllpZrgS+TbR73KLAkd+63wA/SJm0z\ngFMj4q/AapI2T3kOpmyJ89TycwqwT0QMJ9vY7SRJg4AvAtukmL+oUB4kjZE0RdKU+W/Mq5TFzMxs\nldVhhSMiFgIjyLaOnwNcLemoCllbgevS8VZkO67eIamF7BfxJuncMEn3pRaCw8kqFCV/iGzpxhnA\nqxExIyKWk20/P7jCPZ9Pu8cCTAUGp/Eda0bEgyn9igrX/Z6swnEocGUpMW15v05ElLaRv5T3d6b9\nPVlFAypUOICdga2B+9MzHwlsRraF/WLg/yR9iQpdUAARMS4iRkbEyHUGDqqUxczMehip+Fe96tQs\nlTQeYxIwKVUUjqyQbXFu3IbItnLfpUK+CcCBETEtVVxG5c6VWhqW88FWh+VtlDWfpxXo3+6DJBHx\nD0nvAp8B/o2spaMjVwPXSLo+CxHPlJ0XcEdEHFp+oaQdgb3JuqKOAz7dmXKamZn1FB22cEjaStKQ\nXFIz2TiIt4A127jsKWD9NOAUSX0klVoy1gRekdSHrIWjUBExH3hL0k4p6ZA2sv6ErOvkvS6XiFgA\nvCFpj5T0NeCedO5vZJWaH1N5x9iHgN0kbQkgaQ1JQ9M4jrUj4layrqLtqnpAMzPrIYRU/KtedaaF\nYwBwbuqqWAY8S9a9cihwm6SXc+M4AIiIpZJGA+ekborewNlkXSM/JhvjMSd9bavSUo1vAhdLWk5W\nYVhQniEiHmjj2iOBi9Jg1ueAr+fOXQ2cAWxeflFEzEktNldK6puSTyGrmN0kqR9ZK8hJK/REZmbW\no3hp8zIRMZXKXQ7nplcp34Cy61p4f/xDPv1C4MIK6f+fvfOOs6uq+vfzBUINvUsRDF1KgNCDgoLY\nEFCUYkNeRV6V8vKiovATsLyCoiggYKQpgnQUEQIYCCVIC4SEIEhVAQGD9Jry/f2x92VObu7M3HPu\nmcxMZj353E/u2ffsddYtc846a6+yX+H546QYkFavrZGfTmvap5j9MTUHaCLpCFIAJ7bHk5aGmo99\nTJPeWzfvUzjGCU1jOxSeXw9s0WLqlq3kBUEQBMFQYV6tNPoRSd8ivb+/A/v1rzpBEARBMCcDeQmk\nbuZJg8P2hbSOswiCIAiCoB+YJw2OIAiCIBgMDB3/RhgcAxIDdudyRiwzvPed2mDcXc/XIufRhd/s\nfac2+OMND3csY7f1WobplGaZRYfVIqcuLrr3mVrkrLjkwrXIefG16bXIue7+V2qRs8WaS9ciZ9Rx\nh9Qi5/gjft6xjHuuOr4GTWChYfPXIufLW6xei5yjr3mgFjmb1/CdL7ZgPZ/NUCcMjiAIgiDoDxQx\nHEEQBEEQ9DFDLS12KL3XIAiCIAj6ifBwBEEQBEE/MZSWVMLDEQRBEARBnzPPGRySVpJ0gaRHJE2U\ndJWkdSrIOTSXN69DpzUk7VuHrCAIgmDeQX3wGKjMUwaHkm/qcmC87RG2Nwe+BaxYQdyhQEuDQ1LZ\nHKk1gDA4giAIgtkYSu3p5ymDA9gRmG779MaA7XuBWyT9WNJ9kqZI2gtA0g6Sxku6RNIDks5T4mDg\nHcANkm7I+74i6SeS7gW2kfQdSXdmmWOysYOktST9WdK9ku6WNAI4Dthe0iRJ/zOXP5MgCIIg6Hfm\ntaDRDYGJLcY/DowktYZfDrhT0k35tU2BdwNPAROA7WyfJOkwYEfb0/J+iwG32/5fAEn32/5ufn4u\n8FHgj8B5wHG2L88dYucDjgAOt/3R7hSXdACpCy8rrLxq1fcfBEEQDBJSWuwAdknUzLzm4eiO0cDv\nbM+0/QypZX2jq+sdtp+wPQuYRFr+aMVM4NLC9o6Sbpc0BXgf8G5JiwOr2L4cwPYbtl9rR0HbY2yP\nsj1qyWWWLf0GgyAIgmAgM695OKYCe5acU6y3PZPuP5M3bM8EyJ6LU4FRtv8p6RignlrQQRAEwZBh\nIMdc1M285uG4HlgoL08AIGlj4AVgL0nzS1oeeA9wRy+yXgYW7+a1hnExTdJwspFj+2XgCUm752Mv\nlDNdepIVBEEQDEnUJ/8GKvOUwWHbwB7ATjktdirwQ+B8YDJwL8ko+Ybtp3sRNwYY2wgabTrOC8Cv\ngPuAa4A7Cy9/FjhY0mTgVmClfOyZOZA0gkaDIAiCIce8tqSC7aeAT7V46ev5Udx3PDC+sP21wvOT\ngcHYgKQAACAASURBVJML28Ob5h4FHNXi+A+RYjqaaTUWBEEQDGFiSSUIgiAIgqBG5jkPRxAEQRAM\nBoZaWmwYHAMQAfPX4Ge76R/Tet+pDT6+/gq1yFly4WG1yHnvO5fuWMbMWTUoArz05oxa5Lz3ncvX\nImfkSp1/NgDPvPRGLXIWnL8eJ+piC9Vzqrp/2ou1yJmvJj/4PVcd37GMTT/8zRo0gfGXfL8WOafe\n/o9a5Oy6SZUC0XNyyoRHO5bx7Ctv9r5T0CthcARBEARBfzDAS5HXTRgcQRAEQdBPDCWDI4JGgyAI\ngmCIIemDkh6U9LCkI1q8Lkkn5dcnS9qs02OGhyMIgiAI+on+KNSVO57/AtgZeILUX+wK2/cXdvsQ\nsHZ+bAWclv+vTHg4giAIgmBosSXwsO1Hbb8FXADs1rTPbsBvnLgNWErSyp0cNDwcQRAEQdAPCJiv\nbxwcy0m6q7A9xvaYwvYqwD8L208wp/ei1T6rAP+qqlRHHg5JMyVNknSfpItz35A+Q9J+kk6pUd7j\nkqbk9zBF0m6F127N/68h6b78fAdJV+bnH2u17hUEQRAE7dJHvVSmNbqP58eY3vSYG3S6pPK67ZG2\nNwTeAg6sQaeWSOorb8yOtkeSGrCd1Bi0vW1Pk2xfYfu4PtIpCIIgCPqKJ4HVCtur5rGy+5SizhiO\nm4G1ACT9XtJESVObOre+IunEPD4ud25F0ghJY/OcmyWtl8fPkXS6pNuBHxUPJml5SZdKujM/tsvj\n780ei0mS7pG0uKSVJd1U8MZs30L/JYDni7r29GaL3pas50mSbpX0qKQ98/h8kk6V9ICk6yRd1Xgt\nCIIgCKT6H21wJ7C2pDUlLQjsDVzRtM8VwOdytsrWwIu2Ky+nQE0xHNn78CFgbB7a3/Z/JC1Cin69\n1PZzwGLAXbb/R9J3gKOBr5E6sx5o+yFJWwGn0tXsbFVgW9szJe1XOOzPgRNt3yJpdVLX1vWBw4Gv\n2p6QW8e/ARwAXGP7Bzk6t7j0c4MkAe+iddO3dlkZGA2sR/qiLgE+DqwBbACsAPwVOKvV5GyYHQCw\n4jtW7UCNIAiCIOge2zMkfY103ZwfOMv2VEkH5tdPB64CPgw8DLwGfKHT43ZqcCwiaVJ+fjNwZn5+\nsKQ98vPVSGk1zwGzgAvz+G+By7JRsC1wsbpMs4UKx7jY9swWx94J2KAwZ4ksawLwU0nnAZfZfkLS\nncBZkoYBv7c9qSBnR9vTJI0Axkkab7tH70Y3/N72LOB+SY2avKOz/rOAp1u1um+Q19jGAKy74UhX\nOH4QBEEwyOiPtFgA21eRjIri2OmF5wa+WucxOzU4Xs/xD28jaQeSMbCN7dckjQcW7ma+Scs6LzTL\nKfBqN+PzAVvbbm76cJykP5EsswmSdrF9k6T3AB8BzpH0U9u/mU0R+xFJz5C8EXd0c8yeKBbbH0K1\n44IgCIIq9GGWyoCkL+pwLAk8n42N9YCtm47XiGHYF7jF9kvAY5I+CW9XN9ukjeNcCxzU2JA0Mv8/\nwvYU28eT1qnWk/RO4BnbvwLOAOaomCZpBWBN4O/l3m6PTAA+kWM5VgR2qFF2EARBEAwa+iLzYyxw\noKS/Ag8CtxVeexXYUtJRwLPAXnn808BpeXwYqQjJvb0c52DgF5Imk97HTaQsmUMl7UhavpkKXE0K\niPm6pOnAK8DnCnJukDQzH/cI289Ue9stuRR4P3A/KZ/5bqCedpVBEATBIEf9tqTSH3RkcNge3mLs\nTVIAaXdzDmsx9hjwwRbj+zVtnwOck59Po8tgKe5zUPMY8Ov8aN53jR70HJ7/fxzYMD8fD4xvoUuz\nno25syQdbvsVScuSlmqmdHfMIAiCIJhXiUqjfc+VkpYCFgS+Z/vp/lYoCIIgGABEe/q+o5VHZF7H\n9g79rUMQBEEQ9Dfh4RiA2PDmzFkdy9lk+SVr0AaWWnRYLXJeeG16LXK2edeyHcu4/bH/1KAJ7PSu\nFWqRM+npF2qRs87Si9ciZ9nFFqxFjmq6fZtRw98DwPrLLlGLnLpYaNj8HcsYf8n3a9AEdtjzqFrk\nTB77o953aoNlh9fzG/zTXzuqVQXAAvP3nRtiCDk4wuAIgiAIgv4gpcUOHZMj2tMHQRAEQdDnhIcj\nCIIgCPqJoePfCA9HEARBEARzgfBwBEEQBEF/MYRcHGFwBEEQBEE/MZQqjVZaUpE0U9IkSfdJuljS\nor3PmntI+nbTtiX9trC9gKR/S7qyFzkjJX24sH2MpMM70Kuj+UEQBEEwWKkaw/G67ZG2NwTeIvUw\nGUh8u2n7VWBDSYvk7Z2BJ9uQM5LUdTYIgiAIakeq/zFQqSNo9GZgLQBJv5c0UdJUSQfksf0l/ayx\ns6QvSTpR0hqSHpB0jqS/STpP0k6SJkh6SNKWef/FJJ0l6Q5J90jaLY/vJ+kySWPz/j/K48cBi2QP\nzHkFPa8itacH2Af4XUGnOY4haUHgu8BeWVajb8sGksZLelTSwQUZh2WPz32SDi2MH5nf3y3AujV8\n3kEQBEEw6OjI4JC0AKlRW6Mh2f62NwdGAQfnhmUXAbtKapSr/AJwVn6+FvATYL382BcYDRxOl5fi\nSOB621sCOwI/lrRYfm0kqYHbRiTDYDXbR9Dlgfl0Qd0LgL0lLQxsDNxeeG2OY5C6x34HuDDLujDv\nux6wC7AlcLSkYZI2z+9rK2Br4EuSNs3je9PlKdmih8/yAEl3Sbrrxeef6263IAiCYB5CffAYqFQN\nGl1E0qT8/GbgzPz8YEl75OerAWvbvk3S9cBHc8v6YbanSFoDeMz2FABJU4Fxti1pCrBGlvMB4GOF\n2IeFgdXz83G2X8zz7wfeSWoDPwe2J+dj7kPydhTp6RjN/Cl3xH1T0rPAiiQj6XLbr2ZdLgO2Jxl0\nl9t+LY9f0Y1MbI8BxgCs8+6R7m6/IAiCYB5iIFsINVPV4Hjd9sjigKQdgJ2AbWy/Jmk86cINcAbJ\nY/EAcHZh2puF57MK27MKugn4hO0Hm463VdP8mW28nyuAE4AdgGJDjp6O0UzZYwZBEATBkKfOwl9L\nAs9nY2M90tICALZvJ3k89qUQO9Em1wAHKXeBkrRpG3OmF5ZwipwFHNvwqrRxjJeBdrph3QzsLmnR\nvNyzRx67KY8vImlxYNc2ZAVBEARDgLQEUv+/gUqdBsdYYIG8bHIccFvT6xcBE2w/X1Lu90jxFJPz\nssv32pgzJu9fDBrF9hO2TypxjBtIQaLFoNE5sH03cA5wByk25Azb9+TxC4F7gauBO9vQPQiCIAjm\nOSotB9ge3mLsTVIAaXeMBk4s7P84sGFhe79Wr9l+Hfhyi+OdQ7rIN7Y/Wnj+TeCbveg7HhjfyzH+\nQw+BnjktuPH8p8BPW+zzA+AH3ckIgiAIhigDPI21bvq8l4qkpST9jRT3Ma6vjxcEQRAEwcCjzwMe\nbb8ArNPXxwmCIAiCwcYQcnBEhsVARIKF5u/c+XT94/XU8xix7MK979QGGyy3ZC1yfnj9w7XIqYN7\n//FCLXJ+/ZnNapHz0L9eqUXOlH+/VIucl9+aWYuc9ZdtJ3a7d86/91+1yKmLL2/RXfZ9+5x6+z9q\n0AQmj/1RLXI2/uA3apGz0g49rdC3z1d2W69jGdNn9mGlgiFkcUR7+iAIgiAI+pzwcARBEARBvzCw\n01jrJjwcQRAEQRD0OeHhCIIgCIJ+YiilxYbBEQRBEAT9wEBvtlY3saQSBEEQBEGfU8ngkGRJvy1s\nLyDp35KurChvKUlfKWzv0J0sSeMljepF3kqSLpD0iKSJkq6StE5PcoMgCIJgrjOE+tNX9XC8Cmwo\naZG8vTPwZAd6LAV8pde92iA3YLscGG97hO3NgW+R2sh3KjuWoIIgCIKgAp0sqVwFfCQ/34dCF1hJ\ny0j6vaTJkm6TtHEeP0bSWdlL8aikg/OU44ARuUnaj/PYcEmXSHpA0nmNTq6FY+wv6WeF7S9JOhHY\nEZhu+/TGa7bvtX1zT3IlfUfSnZLukzSmMD5e0s8k3QUcImlEfk9TJH1f0isFHb6eZUyWdGweW0zS\nnyTdm2V32wQuCIIgGFpEt9j2uADYW9LCwMakLqkNjgXusb0x8G3gN4XX1gN2AbYEjs5t5I8AHrE9\n0vbX836bAocCGwDvArZrOv5FwK6FNvRfILWf3xCY2IPe3ck9xfYWuSHbIsBHC3MWtD3K9k+AnwM/\nt70R8ERjB0kfANbO72sksLmk9wAfBJ6yvUmWPbaVUpIOkHSXpLtefL6eCqFBEATBwEaq/zFQqWxw\n2J4MrEHyblzV9PJo4Ny83/XAspKWyK/9yfabtqcBz9L9UscduZ38LGBSPlbx+K8A1wMflbQeMMz2\nlDZU707ujpJulzQFeB/w7sKcCwvPtwEuzs/PL4x/ID/uAe4mGVZrA1OAnSUdL2l72y+2Usr2mGzU\njFpy6WXbeBtBEARBMHjoNCbhCuAEYAeg3avkm4XnM3vQoZ39ziB5UB4Azs5jU4E9yxw/e2lOBUbZ\n/qekY4BiA5FXe5DXQMAPbf9yjhekzYAPA9+XNM72d9uQFwRBEMzjDGCHRO10mhZ7FnBsC8/CzcCn\nIWWcANNs99QN6mWgdHcm27cDqwH70hVDcj2wkKQDGvtJ2ljS9j2IahgX0yQNp2eD5TbgE/n53oXx\na4D983wkrSJpBUnvAF6z/Vvgx0A9XbqCIAiCYBDRkYfD9hPASS1eOgY4S9Jk4DXg873IeU7SBEn3\nAVcDfyqhxkXASNvPZ1mWtAfwM0nfBN4AHifFbazSzfFfkPQr4D7gaeDOHo53KPBbSUeS4jFezDKu\nlbQ+8Jccb/oK8BlgLeDHkmYB04H/LvHegiAIgnmVAZ7GWjeVDA7bw1uMjQfG5+f/AXZvsc8xTdsb\nFp7v27T7+MJrXys836Fpv9HAiU1ynwI+1UL1h3qQexRwVAudm4/3JLB1Nmz2BtYt7PtzUlBpkUdI\n3o8gCIIgGLIM2roSkpYC7gDutT1uLh56c+CUnDb7ArD/XDx2EARBMA8xkNNY62bQGhy2XwDW6Yfj\n3gxsMrePGwRBEMxbiIGdxlo3g9bgmJcxMNPuWM6ayyzc+05tcNOjLTN5S7PQ/PPXIuenY27sWMYv\nj/xgDZrAxMeer0XOv196s/ed2uAPf3umFjl/f+71WuTMmtX57xjgsefq+Xxefn16LXJq+PME4Ohr\nHuhYxq6bdFxEGYBlhy9Yi5yVdvhQLXKeHn91LXJ2P2LHjmX8ZuFhve8U9EoYHEEQBEHQTwwhB0d0\niw2CIAiCoO8JD0cQBEEQ9BdDyMURBkcQBEEQ9BNDKUslllSCIAiCIOhz5qrBIWnZ3IJ+kqSnJT1Z\n2J4jRDq3uT+wDbkLSHqhsL2epKslPSTpbkkX5DLjXyy2tA+CIAiC/mQodYudq0sqtp8jtW4nN0h7\nxfYJPUxZBjgQOL3dY0halFQa/SDbV+Wx99N+c7meZC9ge0ancoIgCIJgqDFgllQkfUPSfflxUB4+\nDlg3e0COk7SEpOuz12KypI+2EPUZ4MaGsQFge5ztv+bNVSVdk70fPywcf4ykuyRNlfSdwvgT+dj3\nAHtI2jofe5KkEyRNyvstIOmnku7Ir38xj68i6Za8/32Stq33kwuCIAgGK+qDx0BlQASNStqK1F12\nC5JOd0gaDxwBrGW74RUZBuxu+yVJKwATgCubxG0ITOzhcJuQypNPB/4m6eTce+UI2/+RtABwg6RL\nbN+f5zxre9Osw1+Bz9u+Q1LRO3NA3m9LSQsBt0m6FtgH+KPt4yXNDyxS5TMKgiAI5kEGsoVQMwPF\nwzEauNT267ZfBn4PtGonL+C43IX2WmA1ScuVPNafbb9k+3XgAWD1PL6PpLuBu4H1gQ0Kcy4EyMda\n0PYdefz8wj4fAL6QPR63A0sBa5M6z35R0tHAhrZfaaWUpAOyh+WuF//zXMm3FARBEAQDm4FicLTL\n54Algc2y12Ma0Fy/eyrJg9EdxRrJM4EFJK0NHAK8z/bGpLbzRbmvtqGbgK/YHpkfa+alnOuBHYB/\nAb+R9OlWk22PsT3K9qgll+k43CQIgiAY4KQlkPr/daRTSta4LocdXCdp6Rb7rCbpBkn35zCEQ9qR\nPVAMjptJ8RGLSBoO7JbHXgYWL+y3JGnZYoaknYFVWsg6F9hB0tvNMiTtKGn9Ho6/RD7WS5JWBnZp\ntZPtacB0SaPy0N6Fl68BvpKXZJC0bn4/7wSetj0GOBvYtAc9giAIgqA/OQIYZ3ttYFzebmYG8L+2\nNwC2Br4qaYMW+83GgIjhyPEQvyMtPwCcZnsKgKSJkqaQMk9+Cvwxb98BPNRC1ms5mPRESSeTYjUm\nkTwY3XE3cD9pieXvpNiQ7tgfOFvSDJJR1Ohs9kvS8syk1LmeZ0mG0/uBwyRNJxk1n+3pswiCIAiG\nCAMzjXU3klce4NfAeOCbxR1s/4vktcf2yzm2cRXSdbRb+s3gsH1M0/aPgB+12O9TTUNbdSNyqcKc\n+2ntpTijSXaxZWhLQ8D2qk1Dk21vBCDpSOCuvN9MkiXYbA2elR9BEARBMDdYTtJdhe0x2cveDitm\ngwLgaaDHdsSS1iB57m/vTfCA8HAMMj4m6Rukz+5xYL9+1SYIgiAYtPSRg2Oa7VHdvSjpz8BKLV46\nsrhh25Lcg5zhwKXAobZf6k2pMDhKYvt8Zs9OCYIgCIJq9MOSiu2duntN0jOSVrb9rxzT+Gw3+w0j\nGRvn2b6sneMOlKDRIAiCIAj6nyuAz+fnnwf+0LyDUqDimcBfbf+0XcGyu/WWBP3EuhuO9KmX/Llj\nOQ8937LkR2m2X71sqZPWzFdTdNQ7lm7OhC7P7Y/9pwZN4M2Zs2qRs+zCc7QSqsSIFYfXIuel16fX\nImfmrHrOL0stOqwWOQ8/006Ge+/UFei3+ZpzZByW5pQJj9agCay4WD2f8dOvvFWLnN3XX7kWORt/\n8Bsdy3jzwYuY9dqztfsiNhq5uf9wXU85CtUYscIiE3taUukJScsCF5GSIP4OfCoXxXwHcIbtD0sa\nTUqamAI0ToLfLlb4bkUsqQRBEARBALzd8+z9LcafAj6cn99ChcWgMDiCIAiCoJ8YgGmxfUYYHEEQ\nBEHQDwz0Zmt1E0GjQRAEQRD0OeHhCIIgCIL+Ygi5OMLgACStBPwM2AJ4AXiG1LH2Y7Y/2p+6BUEQ\nBMG8wJA3OHI+8eXAr23vncc2AT7WodwFbM+oQcUgCIJgHqXT7q6DiYjhgB2B6bZPbwzYvpeUYzxc\n0iWSHpB0XjZOkPS4pOXy81GSxufnx0g6V9IE4FxJ+0m6TNLY3Op3jl4xQRAEwdBFqv8xUAmDAzYE\nJnbz2qbAocAGwLuA7dqQtwGwk+198vZIYC9gI2AvSau1miTpAEl3SbrrheefK6N/EARBEAx4wuDo\nmTtsP2F7FqnF/RptzLnC9uuF7XG2X7T9Bql17ztbTbI9xvYo26OWWnrZjhUPgiAIBj7qg8dAJQwO\nmAps3s1rbxaez6Qr5mUGXZ9dc53t5trJ3ckIgiAIgiFDGBxwPbCQpAMaA5I2BrbvYc7jdBkpn+g7\n1YIgCIJ5lj6I34gYjgGMU/e6PYCdJD0iaSrwQ+DpHqYdC/xc0l0kr0UQBEEQBD0Q7n3ebkrzqRYv\n/aqwz9cKz28G1mkh55im7XOAcwrbUdMjCIIgKDCAXRI1EwZHEARBEPQDYmAvgdTNkF9SCYIgCIKg\n7wkPRxAEQRD0E0PIwREGx0Dkb1PvnbbT+sv/vZfdlgOmdXioOmSEnMElZyDpEnLmjpyBpEvbcr5R\nk5w2aEdOy/pJQTnC4BiA2F6+t30k3WV7VCfHqUNGyBlccgaSLiFn7sgZSLrMy3KqH7+/jjz3CYMj\nCIIgCPqJaN4WBEEQBEFQI+HhGLyMGSAyQs7gkjOQdAk5c0fOQNJlXpZTjaHj4ECp0GYQBEEQBHOT\nTTbd3NfceFvtcldecsGJ/RmX0h3h4QiCIAiCfmIIOTjC4AiCIAiC/mCgN1urmwgaDYIgCIKgzwmD\nIwiCQYeka9sZC+YdJG0tadH8fB9JP5K0Wn/r1Snqg38DlTA4BgGS5pf0P/2tR4Osz3l9IHc+SUtU\nnDta0hfy8+UlrdmBHotIWrfq/CxjhKSF8vMdJB0saakO5C3awdz5q85tkrOwpMMkXSbpUkn/I2nh\nqjpJeoek1RuPNuctmH8jK0paXNIS+bEq0JaMgqxPVtW/r5B0SDtjbcj5eIvH+yWtUI+mpfX5pKTF\n8/Oj8m9os5JixgCvS9oY+CbwJHBuRX1WkbStpPc0HlXkBOUIg2MQYHsmsE8dsvKJ5yFJL0p6SdLL\nkl6qoM87JS1Ygz7n5wvGYsB9wP2Svl5SxtGkE9C38tAw4LcV9dkVmASMzdsjJV1RQdSlwExJa5FO\nlKsB51fQZ1tJ9wMP5O1NJJ1aUsxDkn4saYOyx2/iN8C7gZOBU4ANqHDCl3QQ8AxwHfCn/Liyzelf\nBaYC6+X/G49rgNNLqrIv8A9J50r6cCeGWb7bXkLSMEnjJP1b0mcqiPp8i7H9Ksj5L+AM4NP58SvS\n38gESZ/tbXI2LLt9VNDn/9l+WdJoYCfgTOC0kjJmOKVV7gacYvvnQOkbFEnHAxOAo4Cv58fhZeXU\nhvrgMUCJoNHBwwRJpwAXAq82Bm3fXVLOj4Bdbf+1Q30ezTpd0aTPT0vK2cD2S5I+DVwNHAFMBH5c\nQsYewKbA3VmHpxp3UxU4BtgSGJ9lTaroLZlle4akPYCTbZ8s6Z4Kck4EdgGuyPrcW+FubBNgb+AM\nSfMBZwEX2C5laAIb2i4aLTdkY6gshwDr2n6u7ETbJ0o6Cfi67eMqHLsoa4/sLdkDOAg4U9IfgN/Z\nvrGkuA/Y/kb+vh8HPg7cRJuGr6R9SAbQmk0G7uLAf0rqAuncvr7tZ7L8FUkG41ZZr94Mxcbfz7rA\nFuTfH7ArcEcFfWbm/z8CjLH9J0nfLynj1Xwz8lngvfm3PKyCLruTfn9vVphbOwPYPqidMDgGDyPz\n/98tjBl4X0k5z9RgbAA8kh/z0XVyqsIwScNIJ4FTbE9X+bDtt2xbkgGyt6Qq022/2KRDlWI10/NF\n5POkkzRUOzli+59N+szsbt9u5r9MusP9laT3kjwtJ0q6BPie7YfbFHW3pK1t3wYgaSvgrjK6ZP4J\nvFhhHpA8bJL2BjoyOLKsl4BfA7+WtCywJ3CSpGVsl4kPaJxLPwJc3OI31Bu3Av8iNRL7SWH8ZWBy\nGUGZ1RrGRubZPPYfSdN7m2z7WABJNwGb5d8Qko4heaTK8qSkXwI7A8crLTeW9bDvBXwG+LLtf+Vl\nuLI3OJBuloYBA8LgGEqEwTFIsL1jTaLuknQh8HsKf3C2LyupT+OEtKjt1zrQ55ekO8J7gZskvZPy\nF6OL8slsKUlfAvYnXWCrMFXSvsD8ktYGDiZdDMryBeBA4Ae2H8tekirrzf+UtC3gbJgdApQyGPNS\nwUeyTmuQLmjnAdsDVwHrtClqc+BWSf/I26sDD0qaAtj2xm3KeRQYL+lPzP4bLHPxuEHSbrb/UGJO\nt0hamuSV2AtYBrikpIgrJT0AvA78t6TlgTfanWz778Dfs6fvKdtvZL0WAVYl/Y2UYbykK4GL8/Yn\n8thiwAsl5KwIvFXYfiuPleVTwAeBE2y/IGll0lJG22TP5fnA2nnoWeCiCrq8BkySNI7Zf38HV5DV\nMUMpLTYqjQ4Sskv0/4B32P5QXo/fxvaZJeWc3WLYtvcvKWcb0jrscNurS9qEdOfxlZJy1rT9WGFb\nwFq2HyopZ2fgAyQP5TW2ryszvyBnUeDILAtSbMD3GxeAkrIWAVa3/WAVXbKM5YCfk9a9BVwLHFJm\nOULSo8ANwJm2b2167aR2T7TZGOyWfNFsR87R3cw/tp35WcbzwJKkC8brpM/GtpcpIWM4aTllH9KS\n3BXABcB4VzgxSloGeDF7YBYDFrf9dEkZdwHb2n4rby8ITLC9RUk5IhkZ2+WhCcClZd+XpCNJxsLl\npM94N+BC2z8sIyfLGg2sbfvsbJANL/7ttzF/f+BrwJK2R0haBzjV9k4l9WgVJ4PtX5eRUwcjN9vc\n426+vXa5yw0fNiArjYbBMUiQdDVwNnCk7U0kLQDcY3ujftLndpL7+Qrbm+ax+2xvWFLO3bY3axqb\naHvzNufPD/y5Rg9QLSgFn54ALGh7TUkjge/a/lg/6DLa9i1NY9vZnlBSTsssENv/aDXehrzhef4r\nFea2DPDMAc3typhGCg6+gGSk9rrU0IOsRYHDSAbmAdk7tq7tdoNhG3Im2R7ZNHav7U2q6tYpStkk\n25OWFm+2XToWKRuZo0ifyTqS3kFaetqul6lFGZNI8VW3F845U8qcA/Pv5je2P13uHfQNIzcb5ev7\nwOBYdvgCA9LgiCyVwcNyti8CZgHYnkHJtXwASesoRdHfl7c3lnRUFYVs/7NpqMzJfj1JnwCW1Oyp\ne/sBbacq5gvMLElLtjunF72uUyF9VdLSkq6pIOoY0snxhaznJOBdFfT5dQt9ziop5qQWYyeX1YWu\nbJI/AeNISyNXlxUiaUOlANqppCWsiZLeXUZG/t53AX6QHzuXMTYy42x/xvaVnRgbmbNJyw3b5u0n\ngbJBkQD/lvS2USppN2BaWSGqIRutwEzSeafxqMIewMfIAea2n6J87NcbDc8PVEv3do0ZdkF5IoZj\n8PBqDmprBEZuTbXAu1+R1k5/CWB7cl4XLXty7DS2YF3go8BSdAVVQgqS+1JJXV4Bpki6jtkzZqqs\nyS5n++01btvPq1rtglbBp1VO1hu30GfTdibmZa9tgeU1eyrjEkCVk/Vsd5L5zrfUElpmDHCY7Ruy\nnB1Iv8tte5rUdOwfkJYLGqnG38ienDLG89q979I2I2zvpRQojO3XpEqr8wcC5yllpIkUYPu5CnJq\nyUZTqgHyJVKat4DfShpju6zBWkdg9wRJ3wAWlrQjKUW6lAcpU1eGXceIoRXDEQbH4OEw0hrzsQFq\negAAIABJREFUCEkTgOVJSxplWdT2HU3nwhkV5BxIii1YhXQ3dy3pBNAWOdjvD5K2sf2XCscvcll+\n1MEsSas3lgly3EKVdce6gk/nk7S07eezPsvQ/t/tgsDwvH/xbvIlqv12ZsP23UqZKmVZrGFsZDnj\nK1yAdgU2bXg1stfnblJthXZZNBtvLU/5Lpdy/laO2WlcUEdQIQvC9iPA1p0sN2Xqykb7L2Ar26/C\n2zUs/kJ5D1kdgd3fAA4g1aQ5hBRf9cuSMqC+DLugJGFwDBLyyf29JM+AgAcruoGn5ZNh48S4Jykd\nr6w+00gFhTrlYUnfJmVPvP17LBPEWnOw15HALZJuJH3O25NOcmU5KMt6E/gd6eT4vQpyfgL8RdLF\nWZ89SUsIveJUS+JGSee0G9DZE01ekvmAzYCnKoh6VNL/oytr5zOku86yLAE8n59XuXCsQvp8Wxkc\nZVPOjybFg6ymVIV3O6oV7ELSR0gF1hZu3BjY/m6Pk+aklmw00mdTXKqaSYXSEbZPUArsfol0DvtO\n2cDubFyeRvmCYc1y2g5ODuolDI4BjqSPd/PSOpKqnEC+SnJpryfpSeAx0gm/rF7Lk1yta1DRUMj8\nAbgZ+DMVYlKyLo/Rwgthu3TMhO2xealg6zx0aDauysp5jWRwHFl2bpOc3yhlLjQufh+33VaxLUk/\ns30ocErDld0ku2wAa/GiPoMUy3FpSRmQ7m6PpcsrdXMeK8OPSHVBxpEugDsA/6+kjIdtl61j0xLb\n10m6m/S7ESmTqErsxenAosCOpEqhe1Kt0NYSpPTPDxTGTHlP4NnA7ZIuz9u7k7LTSpMNjErZYwA5\n7qf5d/wiqRbMD223VSBN0g0t5FDXb6EsQ2lJJbJUBjjqSmNdgbTGfX3e3hG41fZHK8pdDJjPuaBP\nhfm3ki4UEykYCrZLXYBaReVX0GXZwubCwCeBZWx/p4SM9Ww/oG76O5R0r6OUsnc4cxpkbZ3UJC3h\nVIG1ZZpnOydXSZvbnpg9Y61klKqmqaYU5jy2he07y8ipC0mrkCpnGrjD9pMl59/TyHboQIe6fzeT\nbW9c+H84cLXt7TvRsxMkbU5Xem3VLJWX6d5Y+F/bvXq4JDWqDzfidvYGFiLV49i6XQM6v58GC5PS\nh2fY/kY78+tk081G+YYJ9WepLL3owMxSCQ/HAMd2oyHZtaQy4P/K2ysD55SVJ2kmqWz4t5ytTbVI\nTW2DRW1/s+zxW3ClpA/bvqqqAM9Zk+JnkiYCbRscpBiZA5i9yuPbh6B8RdeLSb09zqCa5+Z8UlDt\nRGY/UStv9+q9ycbG/MABNaUBXiLpY40LezZkTgHaSktseFwk/ZHWd5hlPS6bkzwKJnlcShkcpN4i\nnVL376ZR7+U1pdTR54CV250s6Ru2fyTpZFp/xlUCqSeRll0XyMd4O8apBD8DniD9rkUyFkaQ4m7O\nInmoeuP9Teepe5RT6JWKz7WF7YlNQxMkVfEi1cJA7u5aN2FwDB5WaxgbmWco2R0zM5W0/n6tpL3y\nnXKVX3zHhkLmEODbkt4ipRU2Cji13ZSp6e5yPlK+f6nftu0D8v911fOYYbvyWnPDc2W7ctfbPH+m\npHdKWrCYUliRA4HfK9UY2Qz4IfDhEvMbMRsndKgH+YK6AamGBsDBknYuc0G1fW2WNYXu776/38Kg\nLcqo+3fzR6U06B+TLsamXHBlI1C0Ssn5OVBqtHc06XzTiN8w0G5V2QYf8+y1RMZk7+Y3cwxXO8zf\n8Npl3Tajq11A24HvTV7D+UiGay1p9aXR0FpSCYNj8DBOqR7E7/L2XqS4h7LMcGoytRdws6TPUS0L\no2EovAlMp4KhQJpQR5R48e5yBqkM9KeqCJI0mfQZX5QzBqryR0lfIVVoLAbtlWrElVP3fgf8wdVL\nyNeSBmj7TkkHkzKS3gB2sv3vEvMbd5YjnTp9vk1OvyyzxLMTyePX8NKdReo2XIWrSRfToqt+UeBp\nkhdx19bTuqjjd6PUjGycUxr0pUqlyRe23Xb6u+0/5v/rCqSu3GividckfYqukvF70uXNaff8cwBw\nrlIavkg3KPvn5eEfldCl4TUU6XzxGCkbJ+hjIoZjEJEDSBtruTfZvryn/buR8fa6taQNSSfZ1W0v\n1fPMvkEpDP/TwJq2vydpNWBl2/3i4sxpsHvlxyxSd96LyrqQcyBrMy4byJqXLfYi9UK5k3RHf6VL\nlFpXh6XEWyyBbEBysT+f5ZRaCmm1hFc2nkLSVaRS+v/M26sCp1eJaepGn7ttb6Y2K1nW+LvpKK6k\nu+WqBhW+qxtIRdWqpM4X5byLlEa/TdbvNuB/SMtgm7upEm6L+fMDu9u+tBGzVYMR1O9stvko3zih\n/lPdEovMPyBjOMLgGGIUXZJ5e0lgN9u/KSlnnO339zbWhpzTSCfo99leX6mJ1rUu0TtCqfPkJ5gz\nQLNsKmGz3LVJmQ+ftl26UFad5BPu+0iZQR8s60nq8Ngtg04btBt8qq4W7KNJAccNFgdmlfntSLqe\nVMn1tjy0FSmb48WsU3fZXa1k3Qt8qWHkStoCOMOphUBpA6CT342kE0h1Li5zhZNzjd9VIwX63aQ0\n1sqN9vJv92DbJ7Y7pxs5bbc8aEPWtsx5vih1DqyDoWZwxJLKICF7N44nZauIkksYkt5n+3pSWd/m\nJlxtFxeStDDJ3bxcNg4aK5BLkOoalGWrfCd5D7xdSbNs2eE/kC40E6mh5XTT3epMUsGhdue+z/b1\n6iad2eXTmFEqKLVr1mczUjv1MvM7SgNsXKSUOt7+y7N3Mi3TObTOFuxt1SJpky8CZ+WMEJFqRXwx\nu+rbblLWye+mwJdJgagzJL1Byb/zdg2KNmgsdf4jPxbMDyi5BJvjiPYBOjI4SHFnh5K8R8WlwVIl\n2yWdSwpYnURXQLeBuW5wJIX65aj9Qhgcg4dOSxW/l5RS22o9ukx+/peBQ4F3kC7wjT+Xl0gZC2WZ\nnu+AGmvxy1O+BPiqtj9Y4dhzoNSUbhip7fUn3Ua6XhN1fc4NfS4i3cmPJX2+N9ou+/kcXnj+dhpg\nSRmQMm+K5cdn5rG2vFGusQW77XH5t7IF6XO9q0w8SZOsO4GNsrePppiJttqfF343F1Ptd9PQpaOY\npm4CYIvy2wr2bCy3Sfqk7YuLr0n6ZAXVJiiVa282FsqkDTfqBf1vUVXKB8+PohD/099ElkowEOmo\nVLHtxjr+dz1nLYW2MyFs/zyfOL5tu0rlzGZOIgVWrqDUH2NPypWnBrhV0ka2206Na0UO2rvM9vFV\nZTQ+Z+d05ib5n6igzyRgH5dvTFbUqa40wAWKmS6236rgjYJ0Ea9suABI+gLwXVKgqYDTJX2nSrBk\n85KcqlX3/JztB8seu4UunS5VVqrL0wPfIn03vY31RqPWTvEzLZU2bHu1ksfsjvuAlahQYTnojDA4\nBg91lSq+lOSWL3IJKTWsLbKL9ONUK9XdLOs8pZoZ7yddOHavYFiNBvbLgZpv0uWGLpW6Z3tWvnur\nbHD0womUqMzZ0Mf2/3Vy0BrTAP+tVIfjiiy3UidT6jFcjgA2a3g1srfjFkouN2XqWJJ7WtJPgffk\n7RtJxn1bGSZ1LVW6hhL2WZ8PkVKeV5FU7Da8BBW8Y64pbVjSeqSg5bc7Sts+v/sZs81tBNQuDtyf\nje7iubRsHZhaiLTYYCDSUani/If6bnI7+Ca5bbeDLzAu37FXDW4rXgSfpSvdF0nLuFz66IfKHr8H\n/izpcOZ0/ZZKZ+2GKqeWjj7nTF1pgHV1Mq3DcPkP8EJh+4U8VoU6luQaabmNdOzPksqCtxu8WstS\npaRbbI/WnJU9y6atP0Wq5fGxrE+Dl0nZJaVRoUdMY6yMF0nSUaTz33qk3kS7kIzMtgwOUvPLFZk9\nYBlS5l94O+YCkaUyRMgn9d1JJ5ArCi+9DFxgu1Qn03xCW4x0ASsd3Kau/icircE+n58vBfzDJQte\nSRoNrG377Hy3O7x56aiEXs3YFfqytJD9D9ul1psLn/NM4HUq1jupE3XYyVSpeeB5pDt3kypQfs72\nwyVknANsSPL4mfTbvg9oBB+f1O3kOWWNAU7uZElOLUr0txprQ85BLt/6vc9QqnmxACl1vvKSkbrp\nEWO7bcM3x6eMBO7OGUQrA+fY3qXN+VeSKixPaRrfCPg/273WW6mbzTYf5Vv+Un9ngMUWmi+yVILq\nKPXmOA1Y0faGkjYmVe/7fjvzXW87+I6D2xoGhaRfAZc7VyzNrtzdy8hSqjMxipS+dzYpeO+3dPV/\nKK1XVXoI2hPlMjoa+nRcGE3SV4HznApKkV32+9g+tYKsjjuZup4W7P/Mj4Xy9tj8//IVZNWxJPe6\npNHO9SQkbUcyEEth++Q6UzYlLUpagnjcFZrJAR8kVYZdEFhT0kjSUlHZ5Ydt3dUj5lhJPyEVXCvD\n63k5d4akxUmF2Zoz7npixVZGpe0pktYoqUtQgTA4Bg+/Ar4O/BLA9mRJ5wNtGRzKPRaAfXOK2my4\nQo+FfOFam9ldpDeVFLO17S8V5l8tqUzVQIA9gE1JpaCx/VQ+IZUmn6API93RHaBUU2Fd21e2KaLW\noD2plsJoX7L9i8aGU+rxl4BSBkd3d6llZGQ5KwL/B7zD9ockbQBsY7vtLqS2y3aG7Yk6luT+G/h1\nznQRaXlnv7JCOk3ZlPQxUiD2f0jB178glSVfQ9I3KwTVHkPKkhoPYHtSmSDzAg3jq1KPmMw9SmXf\nzyIt97xEud9fT8UNFympS31EDEcwAFnU9h2aPcKoTPBW3T0Wvkgqe7wq6eS4NalgUdlmVU/ltdnf\n5u1Pk9aPy/CWbSu3YFeqn1CVs0lr1o0siidJEfltGRzFoD2lugxr2/6zUupnlb+3U8mF0UhBuq+Q\nLiJtZ3SQelCoEQOilIZcJbukjrtUSOXCzwaOzNt/I8XMtG1wSLqO1rVFPtBi9+5kLOFUw6FSx+Sm\n404CNpG0RN4uVRuiQKcpm98jxTksCdwAbGz7UUkrAOMoH1Q73faLTeedKrpdqTl7xJxRRoDtL+en\nv1Bq87CEy6XV3iXpS7Zn602Tz2XNmVxzjUiLDQYi0/Lad+OisSflAp2uk7R88x1OjneocsI9hHTR\nu832jjkotUo2xT6k5lCNMu035bEyXCTpl8BS+c59f8o1vCoywvZeDS+Q7dek8nHkWY8DgGVId6yr\nkrrHlqrESj2F0cYCF+bPCFKA4tge9u+OOu5SAZazfZGkbwHYnqHUxbgMxdTpRm2RshkmzR15i99z\nWx151VWRs3k8CSnZr4bOUzZn2f5b1uEx53ogtp+VVKX2ylRJ+5KM1rWBg0kF3ErhrhT6Sj1iGkha\niRTz1ehcu22J+LNDgcuV6sA0DIxRJON7j7K6BOUJg2Pw8FVgDLCepCdJmQZlWo6fRLrINGe1jCbd\nEf13SX3esP2GJCQtZPsBSeuWlNHI/jik7Lwmliel9r5EiuP4Dqm5VxXeyt6IhmE3gmqpkl8luaJv\nB7D9UL7LLEsdhdG+STIyGt/xdZS8u8y0ukutYti9qtQPo/GetiaXJG8X27c3Dd2oVHyrjIw6OvKe\nQPLwXU1X/EcnLEdnKZvz5aXO+YBZmj3Fdr4K+hxE8kS9Scoku4aK6fDNsSmSSsWmSPo/UvGvB5h9\nuamtjsW2nwG2lbQjKeAY4E9OFZj7BTG00mIjS2WQULiTWoR04niVXDsgu3N7m99tHwJJU22/u6Q+\nlwNfIN01vI+UZTLMdpl25Y1g2MOZM0iu7aUZtW6+Nblk0F9j3s6ku+cNSF1RtwP2sz2+pJzbbW+l\n3ItD0gKk6PpSOuW7sWJJ8z2Bo9xU/bENOYvQYaZBk7yFqH6XuhlwMumkfx/JYPyk7XtLyChm6TRq\ni5xme52y+mR5GzPnb7DXlHNJm5A8ch8k3TX/jtTxtdKJVd30QnH7PVAeJxmkrS5jdg3ZVlXoLjal\nTOyYpAeBTVyiceFAR9JYkpFZN9NcU/XlOgmDY5CQA0RHkVJaRXIFTyadJC/OAaE9zf+r7fXLvtam\nbu8lrRmPdaGgU5tz7yUtNUyk60TUqjpmq7n/DXyF5PoutgRfHJhg+zMtJ/Yud1lSTIpIS0alo/tz\n4OsLpDoVB2U977d9ZI8TW8taj66lmOtdsjBaDiT8MbCg7TVVIdMgx6O8anta9kiMBh62/fsyumRZ\nC5G+63VJn/GDwHy22/YkSfonc9YWObbdC3OTrLOAjYGpdHmPbHv/knK2JRkfOwHfdK4zUkGfFemK\n0bnD9rNV5HSCpB51L5ulIumvdFhOPF+cP2H71V53DgYksaQyeFiVVFnxFXg7FfRPpMqGE0m9Vnri\nWUlbNmc3KHXGbLsHhVJFxAOBtYApwJlVTvIFZtg+reLc80mu7B+SKk82eNklC3XlC+oLtl+0/Zyk\n10jpuetIOqWsIZX1+S/SZ/Rl4CpKLGMoZctMtz09L1c1XMfr0xUA3C5H00GmgaT/R8q4sKQLSBfU\n8cBHJO1g+9CS+vwle6SmFo5xN3NWwO0W11fmGlKm1AadCMhLXZsCG5HqilQyEiR9imQcjicZUydL\n+rrtS0rK2Q6YZPtVSZ8hfbY/d/uVSLchpR3/jrQs2Knjv3JsiqQTScbly8Ddkv7M7MtNLeNogoFH\nGByDhxWYPZZgOimv/HVJ7dwZfp0UXHkOswdMfQ7Yu4Qev87HvpmUTrgBncVg/FHSV0hBo8WTSK8G\nQ3bnv0j5INNWXEQKHHsxewAuJhkym5AyRb5YRphTg7VfUT14dSzJYHlI0lqkDKDzgI9K2sL2t0rI\n6jTTYB+SobMoqXPoSjmYdgGSi7wtcsDfKsAikjal6yK2RJbdjozNgSfyenxjyenjwN9JXpsXeprf\nDX+RtIHt+8tOlLQ/qbrowqQ4ok916JE4EtiiISMbMn/OsstwGilrZhNSs7MzSKm1PbavL7ASsDPp\nu9+XdHPzO9tTe5zVhOopJ35f/n8q1YKdgwFCGByDh/OA2yX9IW/vCpyvlALa64nSKaV2S1Iw4355\neCopC6LMCXID2xsBSDqTCnUYmvh8/v/rRXVpI0OgZhax3UjH/Qxwlu2fqKuBWluopm6dwNK2H8rP\nP0862R+UM1QmkhpotUunmQZvZA/PW5Iesf0avJ1dUsbzswvpt7cqUMzeeBn4dpsyxpDL+ytVlz2B\nFEc0Mr/2qe6ndstvSEbH05Qv/HUG6YL4d9L7+0DRsCu79EBaWir+PT5HtWDPGbatVGH4FNtnSmq7\nqqdTs8CxwNi8BLYPMF7SsbbLdIU+oZzaLfkDsGxz/FFeaqzUITjoH8LgGCQ4FX26mq7qmQfabtTU\naDdb5TlgLdulupY2Mb2g0wx1GGLdYYZAnRTfyPvIF3SnBmpl5NRV+KtotLyP5GZvNDorm6XSaabB\nUkr9dwQsoa5ePKJEEzinlOxfS/qE7bab2DWxgO3n8vO9gTG2LySl/bYddNrEmaTeJ1MonwFUS1Oy\nAmOVakw0egvtRVqOK8vLSmnHnwHekw3nYWUEZEPjIyRjYw26OjuX4UmSJ3ZCk+zRtL+8chLJU9gc\n8LwSKcC7UqxWMPeJoNEhhqRbgPdViElozJ9JV1MzkbJmXqPrrrBUjw91XtmzFiT9nFRT4l+kfjPr\n2J6u1K/hj67QlyAvIWxJMh7utP10ibm/JZVufoqU1rpmXsZYCrjR9iZl9clylybFqrT9hy/p7J5e\nt/2FkjosRUpdLt1ZVdJ9pEyFmTkQ8cBGDJGkKQ3vW0l9/mJ7m7Lz6iQvm61oe0I26Ebnl14glaV/\npPvZLeWtRFoKudP2zZJWB3Zwm2mokn5DyiK6itRr6b5epnQnp+P+JZLu6u7vT9J9tjds9Vow8AiD\nY4iRTyTrk7Jdit1QyxYoqkufC0lLBJ9z6hGzKHCrSza9qkEPke4mVwYusv1kHt8UWMH2NSXlfZF0\nUb2eZIy9l3RRPavN+YuQYmNWAs52ThnNmRAjbJ/bhozv5PfyQL5bvZoUkzIT2Nf2n8u8p7qQdClp\nGaJRhO6zJCOi186q+T3tRHKlrwVsmr1QI4BzbW/bo4DWMk8llb3+I7PHF7TViTnLaLWU9iKpsu/3\nC16Z7ubX2lgsL7W+kQ2zdUgdVq+2Pb2XqY35s+g6P1TuOivpTtstq+K2ayBKetB2yxo/Pb0WDDxi\nSWXo8Uh+zEcK5Opvaqns2Sn5jv8CSBkrknbKF+QHgba7mBb4Ouli+FyWuSwpbqItg8P268Bxkg5x\noT6F7VtzZlE77EXX0snnSd/5CsA6pIt9KYNDNfRAyYxoWtY7VlJbcTK2vyvpepJhODYH50JaLijd\nDyizCMnQKJZFN3MWyeuJq0mGXKNV+t6kQNinSaXcezMY6m4sdhOwffZoXQvcSfo9tLX8artK3Egr\n6uhf8oikXZqNfkkfIKVDB4OEMDiGGLaPBVCHLcZrpK7KnrWgOUuSr0K1kuTPMXvJ+JfzWFk+D/y8\naWy/FmOteKuwdLILKfB0JvDXnGFSlnPosAdKpqPOqoV5UqreugCpymyl/iVll4S6YSfPXnxuinJB\nOqW01N6ou7GYsvH+X8Cptn9UJcZF0rm2P9vbWA/U0b/kMFKV2/HMnmH3Xmpulhj0LWFwDDEkbQic\nS7qgImkaaTmjVLpbjRxNioZfTdJ55Mqe/aQL1FeS/GG6sooM7AZMVq4Y29sSVvb47AusqdmLMC1O\n6gTaDm/m7/sZUnDj4YXX2kpDbaKOHiiQ6rj8RqmzKqQqtZ/vYf85UCr69j2SEfd2sS5SmnYplGrL\n/BfwbmbvfFym8Nf8KtS5yV6o+fNr7fQwqbuxmCRtQ/JoNLJTqngtZqtAnA3VlhWLu6Hj/iV5SXAj\nUnBoI17jduBr2RMYDBLC4Bh6jAEOs30DgKQdSBHgpde+68D2dUpFnxqVPQ9xhcqeNfJmzgQB3j7B\nVgl0aixdNWikM7e7jHUrKYB1OeAnhfGXSRVm2+EQUv2G5YETbT8GIOnDwD1tyijScQ+UnC2xru1O\nO6v+L7C+7TrSIs8l9efYBfgu6SJdtrjaF4GzsudQJG/LF3MsxQ/bmF93Y7FDSZlWl9ueKuldpO6x\nbZGNym+TaqY0vh8Bb5HOIW3hmvqXZMOiak2bYIAQQaNDDEn3Nmc4tBqbyzo1ovIN3GK7bOpdnbrU\nVpK8Rp3maHNvu+OW6hX0aNUDZU/b7RpADTndZh2UkDEeeH9eIuoIdfW7mWx7Y0nDgJttb11B1pLw\ndlG6KroUL8xTy16YW8hb1LluSsX5P3S5InPdyfkJqbZNaU+qpOdpbfQ3AliX6VS/YO4QBscQQ6np\n2t2kuzpIbsrNbfdLe+acIbAWs9cdeMT2V/tJn/lILugPkE5o1wBntJtGKulntg9VV4XF2XD5HhRv\nx5TYHqGUNny67bZjSmoM9mx4fN7ugdJu1kOTjOOAaaT4j2KmVK9LRZIagaEbA2sDVzJ7ZslJFfS5\nw/aWkm4iGZhPk3qYtF18LmcBfYI5G8B9t6w+dZCXU84EhtteXani6Jdtf6WCrFWAdzL7+7qppIwv\nkpo9LkCKA/pdu0aZUrfkbqnD6AzmDmFwDDFy1PqxdOX53wwcY/v5ftLnAZJrvOGmn490Z1e5mVx/\nImlz2xPVYdfPgrxJ5JgS25vmsVL1JpQKxp0NHJmXMhYA7ikjoyBrthbjQKkW41lGq8wCt3OBl9Rj\nwTLb/6+MLlnmF4FLSUbM2cBw4Du2Ty8hYyy5ezOzNyH8SbeT+hBJt5M6C19R+N2UrlmRjcO9SdWM\ni11ey1ZQbchbl2R47ANMAH7VWN4tIWMZZo+1eaqH3YMBRMRwDDGyYVE1fbAveBhYnVQaGmA1qqWh\n1kLOmDiGrju6htu2rbtdd3W5HWl7tkwSSYeQilyVoY6YklqCPdVNi3FSafC2cQfVZasYFG3IbDTV\nu5HqJfVX9QBrB277n5o9w7yKJ2APUsxNx5lj2VOxXn5MA+4FDpP0Zdu99nOS9BHgRFJp/OdIGWR/\ny/KCQUAYHEOEul39NbI4KU3zDpJeW5Ii9q/oJ73OBP6HpjvVCnSSzlrkRkmN4L2dSS7/P5aU0XGw\nZ2YUHbQYz8tBJ5CMlinA4c4F1irIGgvs7dysLXvufmv7IxVk1bHkdKukjdyilkY/8c/sjXKOSTmE\n8oGwAI+Sapx0ZHAodXzdFRhHKmTW6MF0vKTmkuXd8QNSFtu1OeZmZ6r1zgn6iTA4hg6NmI06minV\nyXf6W4EmXrR9ddXJNaWzFumozX3mMFJl2RGSJpCDPSvoUrnFeOYskjfkJlL5+JNJnV6rsJILnWFt\nPy/pHRVlnUPn9UVGA/vl5aKyDeD6ggNJxu0qpH4m15JSvsvyGjBJ0jhmj5Up6yWdDBxl+9UWr23Z\npowZtv8taT5JyhluA+18FvRAxHAE/c5AycLIuhxHqp9wGbOfYO9uc/47gTVJqZBHFF56GZhsu52a\nDLVTU7DnDaSurFVajCNpkgsl65ULY5XVI8+dCOxm+4m8vTrwh0a8QklZd9reopGt0krXNmS8s9W4\n7b+3Gh8sSGpZH8WpEV8783v8ftv9u8qyxpHq2RwPLAE8C2xXJZso6B/CwzHE6DRGoQ/0aa7suSrV\nKnvWxVb5/2LapkkdW3slX2D+DtTSDKzG72tLuoI9N5NUOtgz69EJCyv1pmkEFixS3C5z8SF5xiYo\nlTkXsAPw3xX1qrzkJGkJpzoi/WIgNyPpZHqI8SnrmbD963wTsLqb2sO3SU9Bs23/XWV2J1WkPZSU\ntr4kUWl0UBEejiFGzgqZI0bBvTSX6kN9Os7CGEhIepmeawaU7abb8ffVXbBnBbd4R2QPSXfYdpmL\nTyP2omHY3Wr72Yp6Va4vIulK2x/NSymmy5iCfjDku/NINGjXM1GQtytpGXZB22tKGklqQjjXY74k\n/Z/tb/c2FgxcwuAYYki63fZWve85d2joo67iSwsAd/fX2rdS4aajqdA6vY/06fj7UmrgBgU7AAAO\nl0lEQVTj3kmw5y22R7cwpioZUXUhaW9SI7gfSFqN1NW3VBnwnIa9NWmZqKMlp4FCzgY53vbhve7c\nu6yJJC/E+E7Sa/O8jlKqWy3BqZ+LFgbliCWVoccNkn5MxRiFPqCOLIw6OYt0l9uIfv8sKaCwVHBj\njimYA9v/KKlPHd9XR8Getkfn/2vpLixpUVIg6+q2D8jZK+vavrKEjFNI2RPvIWUvvEpaimu3ky4A\nTq3tf5Evph31E5K0MXNeUMt0nK0Fp5b029UkbrrtF5vSa2d1t3N3dJJSLenLpCDYdZTaIDRYnGp9\nZoJ+IjwcQ4xu3Nql3dl1oQ4re/aBPnMEC5YNIMxziumRC5MCSR+0/e5upnQnp+Pvq4Zgzx5LR7uN\nCqFN8i4kXSg+Z3vDbIDcWjJIs9GJtRjoWeluN2c6/AW4rAMv0FmkwmFTKTSTc7kGcLUh6TRShsrF\nzF7NtZQBJOlMUirrEaRKqgcDw2wfWFJOZS9bTnlelhaB2FWX0YL+ITwcQwzbO/a3DkXyHebvgd+7\nnkZcndJR6/QGzTEoOU6gVFnpbIydZvuissdv4pgO509kzviEBqZ8sawRtvfKKcQ4tVFvJbsnpufP\npxHouSwV7rwzXyZ5XGZIeoNqS0Vb2y7dqbYPWZhUHKtomJrkKSvDQaR04TdJ7QeuIXXpLUtlL5tT\nscLngU9KejewfX7pZlKmSjBICA/HEEM19tXoUA+RYiW+Rlfb7JnAye6n/hNZr01Ibt4lSRee/wD7\n2b63Btmlg2FVQ6OzgYakW0lZSBOyl2IEqbdGr/UYJC3gVCn1c6QqmKNIy2CfAo61fUFf6t6DXmcC\nP7F9f38cf6CirkKDi9OBly3L+iqplsjv89BuwC9sn1qbwkGfEgbHEEM19tXoUI/DgA8BB7irbfq7\ngNOAsbZPnJv6tNCvk9bpjffXYD5gM2BZ27uUlNNJo7Pagz1VTyOvnYGjgA1IBam2Ixl149uY+3bg\nYL7b3Yn0fv5s+74yehRkjnNTM7xWY73IeC+puNrTDIDCX5LWIf0trZiXrTYGPmb7+yXljCK1qV+D\n2b/ztt6XuukpVJDTdql/SZOBbW2/kreHk5bi+qu4WlCSMDiGGKqhyFFNetwD7Gx7WtP48uTSxXNT\nn8Lxa+n6KenowuYM4HHgUttvlJRTudFZ3Ug6ntTNt+NGXnkJZGvShfm25t9BD/Puqeu3Ien/t3eu\nMXaVVRh+3g5YpFW5qogochVooBKKiIgKVEX+iGCwgaDcUpFL4QfxB+FSfpgIRIyVqAWpXISGpKAk\nReR+UbRFgQByEQMiECU0SCDlUtIsf6zvdM6cOZ053977nL1nznqSSXP26V79ZuZ077W/tdb7bgZs\nDtyD63i0yjofxJPenj06JP0TL8s8Tltpx2oS/pJ0H3AO8Msy0yVy2fFzKPl9SfqRmf1gsmOTxHgc\nd7Zel17PBP466IeloDjRwzF8VOWrUZZNu91kzKWLN61hPS1+x6jrZ2H/CDNbXMVirITRWdXNnrjw\nUmkjL0lHAneb2cr0egtJ3zCz305yKsC2HbtHYzCzH2csZSEuIvUxxk47vAn8LCMOwKtmdsvkf21g\nbG5mqztaY4qo3Fb1fc0HOpOLw7scG0erjIbbM6yStCK9dSSQpSsS1EskHMNHVb4aZVlX8L1+U8r1\nU2P9U8aRuxtQcoS06mbPSoy8gAvM7OYNCzF7Pe0I9ZJwjOD28blNpt14ELgRF/laIhfNOgrfjbo+\nM9Yjkq7HR7rbexQGPhabWJN6Y1oPFkdTbCz6AklX4pMq2d+XpFPxZumdUkmkxQfwn38vrAb2NbOL\nJd2L+9YAfM/MHuoxRtAAoqQyJEiaB7xoZv9NfRsL8Yvrk8D5BZ52y65nPW09Ce1vAZuZWS27HJKW\n4o2rhVw/Jb0KvIh39K+i48aYU7NO8UqPkFZFerLch/E3nyzFUkmPddbde22oVQn/lW6xgMPM7DVJ\nBwPL8amMucAeZtZzIi5pWZfDdY7F7gQsBQ7EJzyeB44tUAq5Drd/LzTuKxfS25LuI609XXOqLKMF\n9RIJx5BQ5cV1OpLqw4bv+u2KP81nN//JVR7nAwtwXYaV+ARGIVGp1pRKWb2Jipo9T03nG749/3aK\nkyuXfRXwOnB5OnQasJWZfbeHc6vs4djwc5R0OV4+uDC9HnhfUz+QNAuYYQXNECU9Y2a7V7SWEeAj\njP0MTiqEJ+klYKOlsswyWlAjUVIZHkbaniiOAZaa2QpghdzPZNipxATKzNYDtwG3paa2BcC9khab\nWW5fAMA6uXlWa2t8ZzJLGhtr9sRt4ns5fxN8lPpE3JhOwCfwaaciPhZnAOfhkzcAd9C7dXqVpn4j\nbf0Bh+Imgi2yro2pAfUkYC9cAwOAGnc4tsbHzg8CTNIfcYn+XM+kByXtWXbcV9LpuB7MK7TtlOBJ\n+WRUWUYLaiQSjuGhsovrNOUVXD55F7wj/1dW0Eo+JRpH4MnGjsBPgZsnOmcCLsQTmB0k/QYfIT0h\nM0bZZs9L8Jr7p1pPymls+NL03lk5wcxsLWO313POrbL0dwMurb8G3615AEDSLuQ3Ul8LPA18FbgI\nOBZ4qrqlZrMcTyiPSq+PxRO8wzLjHAA8mqalyoz7noV/BouYRP4nd0osaCZRUhkSJJ0LfB3XdPgE\n3oRl6eJ6tZlV5b0wJUm9Eu/hN53DgRfMbFGBONfgrqO3AsuLakN0xCw0Qtp2/u+Bb7X0Cwr8+88C\nu1nHxSJtkT9tZrv2GOcnZnaWRsWgxlBkvLYsaUprO3wUe206thsw2zL8ajRqPviYme2dJq0eMLMD\n+rPySdczbgS21z6ZjnM+2e14gV6Qe/Ax+OwkPno4pg/xZDskmDtq3sXoxbV1wZ+Bb3EPO3u2LsZy\n1cjVBeMchzfDLgLObBtLLGpP3xKgWtnlWK+8hT+lFm32tM5kIx1cLynnieXa9OelGef0FTP7S5dj\n/ygQquUu+7qkObgA2IfLrK0kt8vddFuy+EfjsuS5nInv9pVVUH0OLy2uZOxnsJf+iyrLaEGNRMIx\nRFR4cZ2ObLAjN5fOLhTEzGZM/rcmp02Uahu5eVW7KNX2meHuBO6lo9kzgyclHW8dVuKSjsPLCD1h\no9bxWwMry+p5NIyl6fd0Hj52Phs4v8b1nIKXMa5Lr2fgGjwLyUt8nwKuSH08y/AG6CK6Pf9OX+9L\nXz0z6Am6oH9ESSUIGDemK+D9+M5AYRnwkutZxKgo1cuMJhxvAFf00oA6WbOnmb03wentcbbHTb/e\nZlQgaz/8Z3Skmb3c47fVircMNxW7H+8ruK1ov0wwGCTtjvcOLQD+hH8GuzkZTxZnNkDR8l4wtYmE\nIwgajKQzzGxJwXMvw5s9z+7S7PmWmWU1e0o6BJ/CAHjSzO4qsq4Ua1O8V+YYfJLiDjM7uWi8ulFD\nTBE71rQlPuLdPjWTNQqd4ozgU1wnADvgZZqDgLVm9u0eY8zBS2ot9ds1uLZMoXHxYGoSCUcQNBxJ\nBzLe2+WajZ4wel4lzZ79IiUdX8NvZAeb2TZ1rqcMaogpYtt6Tsb7iD4OPIo3Hf/ZzA6Z8MTxcS7D\nk4278V6O1W3v9azRIXcIPre1KyLpS8APzezAnPUEU5tK6s1BEPQHSdfiOxIHAfPSV6929Rtt9qTL\nlMigkHS4pF8Dz+Jjm1cCH61rPRWxjZndSNKYSCWi9ROf0lcW4Z+VF8zsy8BncLG1XB4D5prZwvZk\nI7F/RpxZ7SUYc2fgWQXWE0xhomk0CJrNfvgETZEEoZJmzz5wPN67sXAaNY42xRSxxTtm9o4kJM00\ns6dTH0YWZrZM0paSOgXN7s9sHn1O0nmMTiodh0+uBENEJBxB0GyewJ/+ixhvnQbcJOlEujR7VrO8\nfMxsQdJ3+AJwZ1JS3aSo/HZDaIopYouXJG2BG+LdIel/eONwFhsrzeBNvzmcCCzGm4/B9W5qUWEN\n6iN6OIKgwSTBpLm4Lki7fkHPIllVNntWgaRTcKXbrcxsZ7kD7i8ytUUag6QZ+I14NbA7Pg30TK9T\nQP1G0heBD+HTQFlOzHKPoXm44NxcSZ/Gey++2YelBtOcSDiCoMGkm8U4LNN1tkkk7579gVU2akiX\nrYLZJJqihpn0WyqR6E/xHjKzeel39lkze1fS381sr0lP9vNvmej9OtRlg/qIkkoQNJipnFhMwLtm\ntq4lrpYmOqb6k89dko4CbirYb1MVVzNWon9PvCRSlLKlmc8BL+K+NasIA7ahJnY4gqCBSHqT7jfh\nWoTIqkTSxfjExPG4rP738VLPubUurATp9zULV3J9h/oE4zbsFKVEbrWZ7VtR7OzSTBrBno8Lhu2N\nS/TfEPobw0kkHEEQDJTU83AS8BX8xvwH4MqadwamBZIebk8wOl9nxKm0NJNizsQTj0uAxb2o5QbT\ni0g4giAYOJK2BTCzV+teSxV0M9QrYLJXxToqkeivyj05xZoJHIEnGzvi0zxX5UriB1Of6OEIgmAg\nyJs2LgBOJ4kOphvkEjO7qM61FaVik73SmNlIRaEqcU+WdA0wB7gV39V4oqL1BVOQSDiCIBgUZwOf\nB+aZ2fMAknYCfi7pbDO7rNbVFWMhoyZ7f2s7/iYwlUsGlbgn4wJfa/HG1TPb4kz5XqQgnyipBEEw\nECQ9Asw3szUdx7cFbm/CWGkukuYBLwFHm9kSSd/B5dr/BVw4Va3Vm+aeHEwPIuEIgmAgSHrCzObk\nvtdkJD0MHGZmr0k6GFiOT97MBfYwszrVRoOgUURJJQiCQTHRKGWWAmaDGGnbxTgGWGpmK4AVSSwr\nCIJEJBxBEAyKfSS90eW4aDMGm2KMSNokjYweiku2t4jraxC0Ef8hgiAYCBVOUDSJG4D7JK0B3sbH\nSJG0C/W6xQZB44gejiAIghIkK/rt8MbXtenYbsBsM3u41sUFQYOIhCMIgiAIgr4zo+4FBEEQBEEw\n/YmEIwiCIAiCvhMJRxAEQRAEfScSjiAIgiAI+s7/AX4bO/h1kIpvAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x2ac3769ea58>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot a Colorbar of the Entire Feature-Set\n",
    "plt.figure(figsize=(8,8))\n",
    "plt.imshow(df.corr('pearson'), cmap=plt.cm.Blues, interpolation='nearest')\n",
    "tick_marks = [i for i in range(len(df.columns))]\n",
    "plt.xticks(tick_marks, df.columns, rotation='vertical')\n",
    "plt.yticks(tick_marks, df.columns)\n",
    "plt.colorbar()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Examine Correlations Among Only the Continuous Numerical Features and Churn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>tenure</th>\n",
       "      <th>MonthlyCharges</th>\n",
       "      <th>TotalCharges</th>\n",
       "      <th>Churn</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>tenure</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.247900</td>\n",
       "      <td>0.826178</td>\n",
       "      <td>-0.352229</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MonthlyCharges</th>\n",
       "      <td>0.247900</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.651174</td>\n",
       "      <td>0.193356</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TotalCharges</th>\n",
       "      <td>0.826178</td>\n",
       "      <td>0.651174</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.198324</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Churn</th>\n",
       "      <td>-0.352229</td>\n",
       "      <td>0.193356</td>\n",
       "      <td>-0.198324</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  tenure  MonthlyCharges  TotalCharges     Churn\n",
       "tenure          1.000000        0.247900      0.826178 -0.352229\n",
       "MonthlyCharges  0.247900        1.000000      0.651174  0.193356\n",
       "TotalCharges    0.826178        0.651174      1.000000 -0.198324\n",
       "Churn          -0.352229        0.193356     -0.198324  1.000000"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create a Pearson Correlation Matrix of the Continuous Numerical Features and the Response (Churn)\n",
    "num_df = df[['tenure','MonthlyCharges','TotalCharges', 'Churn']]\n",
    "num_df.corr('pearson')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.colorbar.Colorbar at 0x2ac37eb79b0>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXsAAAFECAYAAADGEp5zAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x2ac376838d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot a Colorbar of the Continuous Numerical Features and the Response (Churn)\n",
    "plt.imshow(num_df.corr('pearson'), cmap=plt.cm.Blues, interpolation='nearest')\n",
    "tick_marks = [i for i in range(len(num_df.columns))]\n",
    "plt.xticks(tick_marks, num_df.columns, rotation='vertical')\n",
    "plt.yticks(tick_marks, num_df.columns)\n",
    "plt.colorbar()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Examine Correlations Among Only PhoneService, MultipleLines and Churn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Create a Spearman Correlation Matrix of Only PhoneService, MultipleLines and Churn.\n",
    "phoneline_df = df[['PhoneService','MultipleLines','Churn']]\n",
    "phoneline_df.rank()\n",
    "phoneline_df.corr('spearman')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Plot a Colorbar of Only PhoneService, MultipleLines and Churn. \n",
    "plt.imshow(phoneline_df.corr('spearman'), cmap=plt.cm.Blues, interpolation='nearest')\n",
    "tick_marks = [i for i in range(len(phoneline_df.columns))]\n",
    "plt.xticks(tick_marks, phoneline_df.columns, rotation='vertical')\n",
    "plt.yticks(tick_marks, phoneline_df.columns)\n",
    "plt.colorbar()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Examine Correlations Between the Internet-Related Services and Churn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Plot a Spearman Correlation Matrix of Only the Internet-Related Services and Churn.\n",
    "intsvcs_df = df[['InternetService','OnlineSecurity','OnlineBackup','DeviceProtection',\n",
    "                 'TechSupport','StreamingTV','StreamingMovies', 'Churn']]\n",
    "intsvcs_df.rank()\n",
    "intsvcs_df.corr('spearman') # spearman rank"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Plot a Colorbar of Only the Internet-Related Services and Churn.\n",
    "plt.figure(figsize=(6,6))\n",
    "plt.imshow(intsvcs_df.corr('spearman'), cmap=plt.cm.Blues, interpolation='nearest')\n",
    "tick_marks = [i for i in range(len(intsvcs_df.columns))]\n",
    "plt.xticks(tick_marks, intsvcs_df.columns, rotation='vertical')\n",
    "plt.yticks(tick_marks, intsvcs_df.columns)\n",
    "plt.colorbar()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Examine Correlation Between the Remaining Independent Categorical Features and Churn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Plot a Spearman Correlation Matrix of Only the Remaining Independent Categorical Features and Churn.\n",
    "ind_df = df[['gender','SeniorCitizen','Partner','Dependents','Contract','PaperlessBilling','PaymentMethod', 'Churn']]\n",
    "ind_df.rank()\n",
    "ind_df.corr('spearman') # spearman rank"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Plot a Colorbar of Only the Remaining Independent Categorical Features and Churn.\n",
    "plt.figure(figsize=(6,6))\n",
    "plt.imshow(ind_df.corr('spearman'), cmap=plt.cm.Blues, interpolation='nearest')\n",
    "tick_marks = [i for i in range(len(ind_df.columns))]\n",
    "plt.xticks(tick_marks, ind_df.columns, rotation='vertical')\n",
    "plt.yticks(tick_marks, ind_df.columns)\n",
    "plt.colorbar()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}