Project2_Haoyue.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Data loading and Cleaning\n",
    "airing = pd.read_csv('/Users/zhanghaoyue/Downloads/airing.csv')\n",
    "ads = pd.read_csv('/Users/zhanghaoyue/Downloads/ads.csv')\n",
    "airing['message'] = airing['message'].replace('mix', 'mixed')\n",
    "ads = ads[ads['air_count'] != 0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>wp_identifier</th>\n",
       "      <th>cycle</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>375350.000000</td>\n",
       "      <td>375350.000000</td>\n",
       "      <td>346249.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>243678.989394</td>\n",
       "      <td>3997.479342</td>\n",
       "      <td>2016.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>142753.578957</td>\n",
       "      <td>2715.888143</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>232.000000</td>\n",
       "      <td>2016.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>117888.250000</td>\n",
       "      <td>1184.000000</td>\n",
       "      <td>2016.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>228181.500000</td>\n",
       "      <td>4641.000000</td>\n",
       "      <td>2016.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>380614.750000</td>\n",
       "      <td>6603.000000</td>\n",
       "      <td>2016.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>475694.000000</td>\n",
       "      <td>8404.000000</td>\n",
       "      <td>2016.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  id  wp_identifier     cycle\n",
       "count  375350.000000  375350.000000  346249.0\n",
       "mean   243678.989394    3997.479342    2016.0\n",
       "std    142753.578957    2715.888143       0.0\n",
       "min         1.000000     232.000000    2016.0\n",
       "25%    117888.250000    1184.000000    2016.0\n",
       "50%    228181.500000    4641.000000    2016.0\n",
       "75%    380614.750000    6603.000000    2016.0\n",
       "max    475694.000000    8404.000000    2016.0"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "airing.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>wp_identifier</th>\n",
       "      <th>cycle</th>\n",
       "      <th>air_count</th>\n",
       "      <th>reference_count</th>\n",
       "      <th>market_count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1400.000000</td>\n",
       "      <td>1321.0</td>\n",
       "      <td>1400.000000</td>\n",
       "      <td>1400.00000</td>\n",
       "      <td>1400.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>4055.952857</td>\n",
       "      <td>2016.0</td>\n",
       "      <td>268.107143</td>\n",
       "      <td>0.07500</td>\n",
       "      <td>2.902857</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>2539.242220</td>\n",
       "      <td>0.0</td>\n",
       "      <td>451.743189</td>\n",
       "      <td>0.30615</td>\n",
       "      <td>3.657103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>232.000000</td>\n",
       "      <td>2016.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1691.250000</td>\n",
       "      <td>2016.0</td>\n",
       "      <td>13.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>3999.000000</td>\n",
       "      <td>2016.0</td>\n",
       "      <td>135.500000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>6320.250000</td>\n",
       "      <td>2016.0</td>\n",
       "      <td>332.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>3.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>8404.000000</td>\n",
       "      <td>2016.0</td>\n",
       "      <td>5084.000000</td>\n",
       "      <td>4.00000</td>\n",
       "      <td>23.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       wp_identifier   cycle    air_count  reference_count  market_count\n",
       "count    1400.000000  1321.0  1400.000000       1400.00000   1400.000000\n",
       "mean     4055.952857  2016.0   268.107143          0.07500      2.902857\n",
       "std      2539.242220     0.0   451.743189          0.30615      3.657103\n",
       "min       232.000000  2016.0     1.000000          0.00000      1.000000\n",
       "25%      1691.250000  2016.0    13.000000          0.00000      1.000000\n",
       "50%      3999.000000  2016.0   135.500000          0.00000      1.000000\n",
       "75%      6320.250000  2016.0   332.000000          0.00000      3.000000\n",
       "max      8404.000000  2016.0  5084.000000          4.00000     23.000000"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ads.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>wp_identifier</th>\n",
       "      <th>airtime_mean</th>\n",
       "      <th>airtime_sum</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>442</th>\n",
       "      <td>2257</td>\n",
       "      <td>300.000000</td>\n",
       "      <td>900.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>334</th>\n",
       "      <td>1665</td>\n",
       "      <td>236.000000</td>\n",
       "      <td>5428.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>687</th>\n",
       "      <td>3896</td>\n",
       "      <td>235.000000</td>\n",
       "      <td>1410.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>207</th>\n",
       "      <td>987</td>\n",
       "      <td>216.000000</td>\n",
       "      <td>4536.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>676</th>\n",
       "      <td>3758</td>\n",
       "      <td>195.000000</td>\n",
       "      <td>22425.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>378</th>\n",
       "      <td>1829</td>\n",
       "      <td>14.813725</td>\n",
       "      <td>1511.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>394</th>\n",
       "      <td>1951</td>\n",
       "      <td>14.724138</td>\n",
       "      <td>427.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>379</th>\n",
       "      <td>1830</td>\n",
       "      <td>14.500000</td>\n",
       "      <td>1566.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>365</th>\n",
       "      <td>1769</td>\n",
       "      <td>14.400000</td>\n",
       "      <td>216.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>366</th>\n",
       "      <td>1770</td>\n",
       "      <td>14.062500</td>\n",
       "      <td>450.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1400 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     wp_identifier  airtime_mean  airtime_sum\n",
       "442           2257    300.000000        900.0\n",
       "334           1665    236.000000       5428.0\n",
       "687           3896    235.000000       1410.0\n",
       "207            987    216.000000       4536.0\n",
       "676           3758    195.000000      22425.0\n",
       "..             ...           ...          ...\n",
       "378           1829     14.813725       1511.0\n",
       "394           1951     14.724138        427.0\n",
       "379           1830     14.500000       1566.0\n",
       "365           1769     14.400000        216.0\n",
       "366           1770     14.062500        450.0\n",
       "\n",
       "[1400 rows x 3 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Calculating Airtime\n",
    "airing['start_time'] = pd.to_datetime(airing['start_time'])\n",
    "airing['end_time'] = pd.to_datetime(airing['end_time'])\n",
    "airing['airtime'] = (airing['end_time'] - airing['start_time']).dt.total_seconds()\n",
    "airtime_avg = airing.groupby('wp_identifier')[['airtime']].agg(['mean', 'sum']).reset_index()\n",
    "airtime_avg.columns = ['_'.join(col).strip('_') for col in airtime_avg.columns.to_flat_index()]\n",
    "airtime_avg.sort_values(by='airtime_mean', ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>wp_identifier</th>\n",
       "      <th>airtime_mean</th>\n",
       "      <th>airtime_sum</th>\n",
       "      <th>reference_count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>232</td>\n",
       "      <td>29.706814</td>\n",
       "      <td>61909.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>238</td>\n",
       "      <td>29.905089</td>\n",
       "      <td>21741.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>240</td>\n",
       "      <td>29.578338</td>\n",
       "      <td>43421.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>243</td>\n",
       "      <td>29.000000</td>\n",
       "      <td>29.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>244</td>\n",
       "      <td>15.000000</td>\n",
       "      <td>1305.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1395</th>\n",
       "      <td>8360</td>\n",
       "      <td>31.434783</td>\n",
       "      <td>2169.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1396</th>\n",
       "      <td>8361</td>\n",
       "      <td>60.425926</td>\n",
       "      <td>3263.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1397</th>\n",
       "      <td>8364</td>\n",
       "      <td>30.000000</td>\n",
       "      <td>8280.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1398</th>\n",
       "      <td>8403</td>\n",
       "      <td>30.183784</td>\n",
       "      <td>5584.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1399</th>\n",
       "      <td>8404</td>\n",
       "      <td>29.748201</td>\n",
       "      <td>4135.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1400 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      wp_identifier  airtime_mean  airtime_sum  reference_count\n",
       "0               232     29.706814      61909.0                0\n",
       "1               238     29.905089      21741.0                0\n",
       "2               240     29.578338      43421.0                1\n",
       "3               243     29.000000         29.0                0\n",
       "4               244     15.000000       1305.0                0\n",
       "...             ...           ...          ...              ...\n",
       "1395           8360     31.434783       2169.0                0\n",
       "1396           8361     60.425926       3263.0                0\n",
       "1397           8364     30.000000       8280.0                0\n",
       "1398           8403     30.183784       5584.0                0\n",
       "1399           8404     29.748201       4135.0                0\n",
       "\n",
       "[1400 rows x 4 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Combining Airtime and Reference Count\n",
    "airtime_ref = pd.merge(airtime_avg, ads, how='left', on='wp_identifier')\n",
    "airtime_ref[['wp_identifier', 'airtime_mean','airtime_sum', 'reference_count']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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hISEVlpWVlcl/4C5YsEBlWU0Tns6dO6sko0I82h+VR+LOnDmjsoyDluvZO++8gz/++APBwcGwsLCAEAIJCQlYt24dxo4di9atW+s0Mdi4ceNgY2NToVx5jl05fggA4uPjkZycDBsbGzz77LMV1vHx8UHfvn2r9frKQYuvvPKK2uWdOnWCt7c3rl27htu3b2vd7pEjR5CUlIRGjRph9OjRcnnbtm3RpUsXlJSUYMuWLdWKVWnChAk6rQc8GhfTtGnTCuXq+vv+/fs4fvw4gEfnkh/n4OCgsm21Rbl/3L9/X6/tVtWP6enpWL58OV544QX84x//QJ8+fdCnTx95np1z587pLZYDBw4AgDxm6XGvv/66Sr3HVedzpI2ysjLs2rUL06dPx/Dhw9G3b1/06dMHgwcPhiRJSExMREFBgdp11X2WnJ2d5XEn5WM5cOAAhBDo168f2rdvr7YtCwuLasVeXlRUlDz+wcLCAm3atMGaNWvQrl077N27V75kXamq74Nhw4bBwsICR48e1Tjm7XH79u1DYWEhhg4dqvazZ2JiIo8ziYqKqrBcoVAgJCSkQnlRURH27dsHU1NTjWPCRo0apbFdoHrv1b59+1BcXIxevXpp9T1748YNnDlzBq6urnIc1Y3vccrvAHX7ujaUn5+ZM2dWWCZJEmbNmqVST18mT54MExPVdMPc3BydO3cGUP3Pp644D081DBw4EAMHDsSDBw9w6tQpHD9+HPv27UNkZCRu3ryJ4OBgnDlzBm3atNG6zVatWqktd3V1BfBobhalxMREAECbNm00fgl26tSpWonX+fPnATwaAPfxxx+rraOcWyg5OVntF5Y6ysHKo0aNqvDhHD9+POLi4rBx40a1H7yqtG3bttrrKFWnv69cuQIhBJycnODp6al2vU6dOukci7aUMT1+JUZNODs7w9nZWePyAwcO4LnnnkNOTo7GOllZWXqL56+//gLwaJClOspk4O7du8jNza3QF9V5X6uSnZ2N4OBgxMbGVlrv3r17ai9iqCyWhIQElViU261pn7a1tUWTJk2QlJSkbfgqys/Dc//+ffz11194+PAhmjRpgm7duqnUzcvLkwelvvrqq5W2+/DhQ2RmZsLNza3KGJTfMceOHUOfPn3U1rl79y6AR98xj/P19VU7D5VyWywsLBAcHKy2XSGExnaB6r1XygG9vXr1UrvO45Tb/fDhQ43brbx4Q1N8j7O1tQUAjQPnK5OdnS1PZlrV50y5X+qLPj+fNcGERwfW1tbo27cv+vbtizfffBNHjhzBsGHDkJ+fj88//xzff/+91m1pytSV2bDyAwv8bydX7vTqVLZMHeUP2unTp6usq7z0tCqFhYXy6Hvl5a/ljRs3DvPmzcPJkyeRkJAAPz+/akSs+183la1bV/2ti1u3bgH435eDPlTWh9nZ2Rg7dixycnIwYcIETJs2DX5+frCzs4OJiQl+//13DB48WK9XECm/8DRtY/kf1vv371dIeKrzvlZlzpw5iI2NhZ+fHz7++GP06tULzs7O8h8ZTZs2RXJyssbtr04syu12cXHRGI+bm5vOCU/Xrl1V/gDKyMjASy+9hF9++QXPPvssDhw4IF9NVT65jYmJqbJtbb8PlO3eunVL3per06am/lS2W1RUVGW8mq4Krc57lZubC+DRNCTaUMaXm5tbZXza9qVyQlZd9ofySUVVnzN9H03W5+ezJnhKSw/69OmDadOmAXh0+WFtUe40lWXD1d1RGzduDODR0SPxaEyXxoemS6Aft2fPHmRnZwN4dITn8UuUmzZtKl/qbshz8tRGf1dXfHy8fCSlR48ecrnyR0rTF4UufwEq7d+/H/fu3UNgYCDWrVuHnj17wt7eXv5yqupHSxfK/TAtLU3tcuURAKB2k8ySkhI5Wd+1axeefvppeHp6yslOSUmJ2kuodaXc7spuI6KpT3Th7OyMzZs3o0mTJvj999/x448/VogFeJREVPV9oO397pTtvvvuu1W2WZ174CnbbdKkSZXt6uMHVbnfKb/btI0vKCioytg0Xe79uN69ewMALly4UO0jrOXf36o+Z49/xmrz+6YuMeHRk5YtWwJ49EVRW1q3bg3g0ZwTmv66VB5G1Zby0OaFCxdqFlw5yiTG1tYWbm5uah+Ojo4AHt1qoq6y++ry8fGBiYkJMjIykJKSorZOdfu7ur799lsAj055KOe5Af6XjGn6obxy5YrOr6n88g0MDFR7CxBNY3c03S5EG8p9Oz4+Xu3yixcvAnj0F6g+T+09Lj09Hfn5+XB0dFR75PHChQsoLS3V2+uV/0yrk5eXV62xc9po3LgxFixYAODR/FTK7VEoFPKpW2V/60NtfMcAj051mZubIyUlRa+nVzVRnu7RNCfU45TbfenSJb3dt6xnz57w9vZGSUkJvvvuu2qta29vLx9JrOpzptwvlar6vrl69Wq1YqlKTb5LKsOERwsZGRlV/igfPXoUwKMPYW1p27YtmjRpgry8vAoTgAGPBn4dPny4Wm0+/fTTAIAVK1boJfHIzMzE/v37AQC7d+9Gamqq2kdSUhKsrKxw48aNasdcV2xtbdGzZ08AUPuXZ05ODnbu3Flrr//rr79i1apVAB4Nmi9PmWBfu3ZN7Q0CV69erfPrKmfLLX9URSkzMxNr1qypdD1tD8+XN3ToUADAypUr1S5fsWKFSr3aotyG3NxctduxdOlSvb7ekCFDAADR0dFqf4RWr15dK39ETZo0Ce7u7rh69arKxQPK7wN93gB2xIgRsLCwwL59++RxiPrQqFEjDB06FGVlZfL+UZuCg4Nhbm6OY8eOaXXKz9fXFx06dEBWVhY2bNiglxhMTU0xf/58AMCHH36IM2fOVFr/0qVL+OWXX+Tnys/PV199VaGuEEIuf/xzpvy+OXnyZIX1wsPDce/evWpsRdVq8l1SGSY8Wti0aRO6dOmC77//vsKPS3Z2Nt577z1s2rQJgPqrefTFxMREvinjrFmzVP7SuH37Np577rlqZ8avvfYaWrZsiYiICIwfP77CkYy8vDz89NNPmDNnjlbtbdmyBcXFxWjWrBn69++vsZ6dnR1GjhwJwLBPaym3+8MPP8SePXvk8nv37mHs2LG1MtjuypUrmDt3Lp588kmUlpbin//8p3xbDiVHR0f06NEDhYWFmDNnjnzEr7S0FEuWLMFvv/2m8+srr0D56aef8Pvvv8vlKSkpGDNmjMarc1xcXGBra4u0tDSNM7ZqMnXqVNjZ2SEuLg5vvPGG/CNfVlaGpUuXYu/evTA3N8fcuXN13Crt2Nvbo3379igpKVGJo7S0FJ988gm2bt1ao6umHufj44OQkBAIITBx4kSVozmRkZFYtGgRzM3N9fZ6SpaWlvKVb2FhYfIfO/PmzYOjoyPWr1+POXPmVDh9k5WVhR9++AGLFy/W+rU8PT0xe/ZsFBcXY+jQoRUuqhBC4MSJE5g6dWq1r9b58MMPYWlpicWLF2PJkiUVfiBTUlKwfPly+UhpTXh4eMhXET799NMVrmS6c+cOPvjgA5WyTz75BJIkYfr06Vi9enWFz861a9fw0UcfVesWH6+++irGjBmDgoICDBw4EF999VWFU+u3bt3Cv//9bwQEBKgc7Z07dy7MzMywa9cufP755/KRp6KiIrz++uu4cOECFAoFpk6dqtLe8OHDATxK+MsnrSdPnsSsWbP0vo8qE6zo6Gj9ngHQy8XtRu7LL79UmYOnRYsWokePHsLX11ee4ROAePPNNyusW9U8PJrmGVDOo/H4fDrFxcViyJAh8mu2adNGdO3atcJMy4/P61DZPBmXLl2S58wxMTERbdu2FT179hStW7eW5/VRNwmXOj179hQAxPz586usu2vXLnmiK+WEVNrMw1OZqubhebw/lSrrn/IzLbds2VIEBAQIa2tr4eDgIM8f8/g8H5UpPxdOQECAPItoly5d5BlGgUcTLC5atKjCpFxKERER8iRiypmJnZychJmZmTz/SGUzLVdGOcEeAOHj4yPP5m1rayt/HtTNAaTsKysrKxEQECD69++vUq+qmZaVnycHBwfRvXt3uT9MTEzEf/7znwrr6Po5qszu3btVZsYNCAiQbx68YMECjXOS6DpXSXJysjzjt7m5uejatato3bq1AB7drLg2ZloWQojs7Gxha2srAIgdO3bI5UeOHJG319zcXHTs2FH07NlTtGzZUu6X559/XqWtqiYeLC4uFv/85z/lfcrd3V306NFDdO7cWY4BUJ34s6q5ppS2b98uz9hsZWUlunTpInr06KEyO/S8efNU1tH1vXr48KEICQmR2/X09BTdu3cXTZs21TjT8sqVK+XvUeVMwwEBAcLNzU1u55tvvql0Gx9XXFwspk2bJr+mubm5aNu2rejRo4fK7PGOjo7i0KFDKuuWn2lZOVu9cj4xS0tLtTMtP3jwQJ6jx8zMTHTo0EHeR8eOHVvlPDya9l1Nn98rV67I3wXNmzcXffv2Ff3796/xvDw8wqOFadOm4Y8//sBbb72F3r17o7S0FHFxcUhOTkbz5s0xYcIEHD58GJ9++mmtx2JmZoY9e/Zg8eLF8PX1xbVr15CamoqJEyfi+PHjsLS0BFC9gZ1t2rTBuXPnsGTJEnTv3h3JycmIi4tDUVER+vfvj88++0yrOXMSExPleWsePyKhzvDhw+Hk5IScnByVoyeG5vvvv8eqVavQsWNHJCcn48aNGxg5ciROnDgBDw8PALoPpD116hRiYmIQGxuL69evw9bWFk899RSWLVuG27dvY+HChWovyQUe3afmt99+Q58+fVBUVIS//voL3bp1Q2RkpNr751THjz/+iAULFsDb2xs3btxAamoqnnnmGZw8eVKeO0Od5cuX4/XXX4e7uzvOnTuHqKgorecYGTVqFE6fPo3x48fDysoKcXFxEELgqaeewpEjR6q8VFpfRo4cif3796N379548OABEhIS4OPjg02bNlX4C14fPD09ceLECYSGhsLZ2Rnx8fEQQuCDDz7Ajh07am08g0KhwGuvvQYAKlNSBAUFIT4+Hu+++y7atWuHpKQk/PnnnzAxMcGwYcOwatUqLF++vFqvZWZmho0bN2Lv3r3y3FVnz55FSkoKWrdujRkzZiAyMrLC2BFtPPXUU4iPj8frr78Ob29vJCQkID4+Ho0aNcJTTz2F9evX4+233652u+pYWlpix44d+PHHHzFo0CA8fPgQ586dg4mJCYKDg9Weupo+fTri4uLwyiuvwMXFBRcvXkRiYiKcnZ0xbtw4/Pzzz9WeW8zMzAxff/014uLiMGPGDLRu3Rp37tzB2bNnUVBQgEGDBmH58uW4evUqnnjiCZV1p06disOHD2P06NEoKytDXFwcGjVqhH/+8584c+YMRowYUeH1rKys8Mcff+Dll1+Go6MjEhMTYWJigs8++0xl4Lu+tGrVCnv27EH//v1x7949HDlyBFFRUVoP7tZEEsJAR4ySTkaOHIlffvkFO3bsqJNJ8f7uZs6ciZUrV+KLL76QTzcSEZHhYcJjRG7fvg0fHx+UlJTg9u3bcHd3r++QjFpeXh58fX2RmpqKEydOyLP6EhGR4eEprQZo8eLFFa52SEhIQEhICAoLCxESEsJkR4++/PJLxMXFqZQlJydjzJgxSE1NRbdu3ZjsEBEZOB7haYCU4yqU93zJycmRE6CWLVsiOjpanpGTam7AgAGIioqCQqFAy5YtUVhYiMuXL6OsrAzOzs6IiIhAhw4d6jtMIiKqBBOeBmjNmjX4+eefceHCBWRmZsLExAQtWrTA6NGjMXfuXDg4ONR3iEZlx44d2LBhA86cOYP09HQIIeDl5YXhw4fjX//6F5NLIqIGgAkPERERGT2O4SEiIiKjx7ul49Fsrnfu3IGtrW2tzXlBRERE+iWEwP379+Hp6Snf4FgTJjx4NCW4l5dXfYdBREREOrh16xaaNm1aaR0mPPjfLLm3bt2q1TsxExERkf7k5ubCy8tLq9numfDgf7eit7OzY8JDRETUwGgzHIWDlomIiMjoMeEhIiIio8eEh4iIiIweEx4iIiIyekx4iIiIyOgx4SEiIiKjx4SHiIiIjB4THiIiIjJ6THiIiIjI6DHhISIiIqNn0AlPWFgYJEnC7NmzK60XFRUFf39/WFlZoWXLlvj222/rJkADcS09DxEJaUjKyK/vUIiIiAySwd5L6+TJk/juu+/QqVOnSuslJSUhODgYU6ZMwaZNmxATE4Np06bBxcUFY8aMqaNo60d2QRFmbY5DdGK6XNbP1wVfjesKRSPzeoyMiIjIsBjkEZ68vDyMHz8e33//PRwcHCqt++2336JZs2b48ssv0bZtW7zyyiuYPHkyPvvsszqKtv7M2hyHmCsZKmUxVzIwc/PZeoqIiIjIMBlkwjN9+nSMGDEC//jHP6qsGxsbiyFDhqiUDR06FKdOnUJxcbHadQoLC5Gbm6vyaGiupechOjEdpUKolJcKgejEdJ7eIiIiKsfgEp4tW7bgzJkzCAsL06p+amoq3NzcVMrc3NxQUlKCjIwMteuEhYVBoVDIDy8vrxrHXdduZBVUuvx6JhMeIiIiJYNKeG7duoXXX38dmzZtgpWVldbrSZKk8lz896jH4+VK8+fPR05Ojvy4deuW7kHXk+aOjSpd7u1kU0eREBERGT6DGrR8+vRppKWlwd/fXy4rLS1FdHQ0Vq5cicLCQpiamqqs4+7ujtTUVJWytLQ0mJmZwcnJSe3rWFpawtLSUv8bUIdaujRGP18XxFzJUDmtZSpJCPJxRgtnJjxERERKBnWEZ9CgQTh//jzi4uLkR0BAAMaPH4+4uLgKyQ4ABAYG4uDBgyplBw4cQEBAAMzNjftKpa/GdUWQj7NKWZCPM74a17WeIiIiIjJMBnWEx9bWFh06dFAps7GxgZOTk1w+f/58JCcnY8OGDQCA0NBQrFy5EnPmzMGUKVMQGxuLNWvWYPPmzXUef11TNDLHhpd7ICkjH9cz8+HtZMMjO0RERGoYVMKjjZSUFNy8eVN+3qJFC+zbtw9vvPEGvv76a3h6emLFihVGPwdPeS2cmegQERFVRhLiseua/4Zyc3OhUCiQk5MDOzu7+g6HiIiItFCd32+DGsNDREREVBuY8BAREZHRY8JDRERERo8JDxERERk9JjxERERk9JjwEBERkdFjwkNERERGjwkPERERGT0mPERERGT0mPAQERGR0WPCQ0REREaPCQ8REREZPSY8REREZPSY8BAREZHRY8JDRERERo8JDxERERk9JjxERERk9JjwEBERkdFjwkNERERGjwkPERERGT0mPERERGT0mPAQERGR0WPCQ0REREaPCQ8REREZPSY8REREZPSY8BAREZHRY8JDRERERo8JDxERERk9JjxERERk9JjwEBERkdFjwkNERERGz+ASnm+++QadOnWCnZ0d7OzsEBgYiP3792usHxkZCUmSKjwuX75ch1ETERGRITOr7wAe17RpUyxZsgQ+Pj4AgPXr1yMkJARnz55F+/btNa6XkJAAOzs7+bmLi0utx0pEREQNg8ElPCNHjlR5/tFHH+Gbb77BsWPHKk14XF1dYW9vX8vRERERUUNkcKe0yistLcWWLVuQn5+PwMDASut27doVHh4eGDRoECIiIiqtW1hYiNzcXJUHERERGS+DTHjOnz+Pxo0bw9LSEqGhodixYwfatWuntq6Hhwe+++47hIeHY/v27fDz88OgQYMQHR2tsf2wsDAoFAr54eXlVVubQkRERAZAEkKI+g7icUVFRbh58yays7MRHh6O1atXIyoqSmPS87iRI0dCkiTs3r1b7fLCwkIUFhbKz3Nzc+Hl5YWcnByVcUBERERkuHJzc6FQKLT6/Ta4MTwAYGFhIQ9aDggIwMmTJ7F8+XL85z//0Wr9Xr16YdOmTRqXW1pawtLSUi+xEhERkeEzyFNajxNCqByRqcrZs2fh4eFRixERERFRQ2JwR3jeeecdDB8+HF5eXrh//z62bNmCyMhI/PrrrwCA+fPnIzk5GRs2bAAAfPnll/D29kb79u1RVFSETZs2ITw8HOHh4fW5GURERGRADC7huXv3Ll588UWkpKRAoVCgU6dO+PXXXzF48GAAQEpKCm7evCnXLyoqwptvvonk5GRYW1ujffv22Lt3L4KDg+trE4iIiMjAGOSg5bpWnUFPREREZBiq8/vdIMbwEBEREdUEEx4iIiIyekx4iIiIyOgx4SEiIiKjx4SHiIiIjB4THiIiIjJ6THiIiIjI6DHhISIiIqPHhIeIiIiMHhMeIiIiMnpMeIiIiMjoMeEhIiIio8eEh4iIiIweEx4iIiIyekx4iIiIyOgx4SEiIiKjx4SHiIiIjB4THiIiIjJ6THiIiIjI6DHhISIiIqPHhIeIiIiMHhMeIiIiMnpMeIiIiMjoMeEhIiIio8eEh4iIiIweEx4iIiIyekx4iIiIyOgx4SEiIiKjx4SHiIiIjB4THiIiIjJ6THiIiIjI6BlcwvPNN9+gU6dOsLOzg52dHQIDA7F///5K14mKioK/vz+srKzQsmVLfPvtt3UUrWG4lp6HiIQ0JGXk13coREREBsmsvgN4XNOmTbFkyRL4+PgAANavX4+QkBCcPXsW7du3r1A/KSkJwcHBmDJlCjZt2oSYmBhMmzYNLi4uGDNmTF2HX6eyC4owa3McohPT5bJ+vi74alxXKBqZ12NkREREhkUSQoj6DqIqjo6O+PTTT/Hyyy9XWDZv3jzs3r0bly5dkstCQ0Nx7tw5xMbGatV+bm4uFAoFcnJyYGdnp7e4a9uENScQcyUDpeXeQlNJQpCPMza83KMeIyMiIqp91fn9NrhTWuWVlpZiy5YtyM/PR2BgoNo6sbGxGDJkiErZ0KFDcerUKRQXF6tdp7CwELm5uSqPhuZaeh6iE9NVkh0AKBUC0YnpPL1FRERUjkEmPOfPn0fjxo1haWmJ0NBQ7NixA+3atVNbNzU1FW5ubiplbm5uKCkpQUZGhtp1wsLCoFAo5IeXl5fet6G23cgqqHT59UwmPEREREoGmfD4+fkhLi4Ox44dw9SpUzFx4kTEx8drrC9Jkspz5Vm6x8uV5s+fj5ycHPlx69Yt/QVfR5o7Nqp0ubeTTR1FQkREZPgMbtAyAFhYWMiDlgMCAnDy5EksX74c//nPfyrUdXd3R2pqqkpZWloazMzM4OTkpLZ9S0tLWFpa6j/wOtTSpTH6+bpoHMPTwpkJDxERkZJBHuF5nBAChYWFapcFBgbi4MGDKmUHDhxAQEAAzM2N+0qlr8Z1RZCPs0pZkI8zvhrXtZ4iIiIiMkw6HeGZPHkyRo8ejVGjRmmss2/fPmzbtg0//PBDtdp+5513MHz4cHh5eeH+/fvYsmULIiMj8euvvwJ4dDoqOTkZGzZsAPDoiqyVK1dizpw5mDJlCmJjY7FmzRps3rxZl01rUBSNzLHh5R5IysjH9cx8eDvZ8MgOERGRGjod4Vm3bh3i4uIqrXP+/HmsX7++2m3fvXsXL774Ivz8/DBo0CAcP34cv/76KwYPHgwASElJwc2bN+X6LVq0wL59+xAZGYkuXbrgww8/xIoVK4x+Dp7yWjjbYKCfK5MdIiIiDWptDM/Dhw9hZlb95tesWVPp8nXr1lUo69+/P86cOVPt1yIiIqK/B50THk1XQAkhcPv2bezbtw+enp46B0ZERESkL1qf0jIxMYGpqSlMTU0BAIsWLZKfl3+YmZnB29sbJ0+exNixY2stcCIiIiJtaX2Ep1+/fvJRnejoaDRr1gze3t4V6pmamsLR0RFPPPEEpkyZordAiYiIiHSldcITGRkp/9/ExAQvvfQS3nvvvdqIiYiIiEivdBrDU1ZWpu84iIiIiGpNg5h4kIiIiKgmdL5KKz4+HitXrsTJkyeRnZ2N0tLSCnUkScLVq1drFCARERFRTemU8ERFRWHYsGEoLCyEmZkZ3Nzc1M65I8rd44mIiIiovuiU8Lz99tsoKSnB6tWrMXHiRPlSdSIiIiJDpFPCc+7cOYwdOxaTJ0/WdzxEREREeqfToGVbW1u4urrqOxYiIiKiWqFTwjNixAgcPnxY37EQERER1QqdEp6lS5ciJycHs2bNQkFBgb5jIiIiItIrSehwKdUTTzyB7OxsnDt3DjY2NvD19YVCoajYuCTh0KFDegm0NuXm5kKhUCAnJwd2dnb1HQ4RERFpoTq/3zolPCYm2h0YkiRJ7fw8hoYJDxERUcNTnd9v3lqCiIiIjB5vLUFERERGjwkPERERGT2dTml98MEHWtWTJAkLFizQ5SWIiIiI9KZWBi1LkgQhBActExERUa2p9UHLERERastzcnJw5swZrFixAv/4xz8wffp0XZonIiIi0iudEp7+/ftrXDZq1CiMHz8e3bp1w5gxY3QOjIiIiEhfamXQsq+vL5566iksWbKkNponIiIiqpZau0rL1dUVCQkJtdU8ERERkdZqJeEpLCzEr7/+Cnt7+9ponoiIiKhadBrDs2HDBrXlJSUlSE5OxpYtW3D58mXMnDmzRsERERER6YNOCc+kSZMgSVKFcuUV7pIk4fnnn+cYHiIiIjIIOiU8a9euVVtuYmICBwcHdOvWDZ6enjUKjIiIiEhfdEp4Jk6cqO84iIiIiGoN76VFRERERk+nIzxKR48exbp16xAXFydP69y1a1dMmDABffr00VeMRERERDWi8xGeN998E3379sXq1atx6tQpXL16FadPn8bq1avRv39/zJkzR6d2w8LC0L17d9ja2sLV1RWjR4+ucj6fyMhISJJU4XH58mWdYiAiIiLjolPCs2HDBixbtgx+fn7YvHkzUlJSUFJSgtTUVGzZsgVt2rTB8uXLNV6+XpmoqChMnz4dx44dw8GDB1FSUoIhQ4YgPz+/ynUTEhKQkpIiP3x9fXXZPCIiIjIyOt0tPTAwEHfu3MGFCxdga2tbYXlubi46duwIDw8PHDt2rEYBpqenw9XVFVFRUejXr5/aOpGRkRg4cCDu3bun02SHvFs6ERFRw1Od32+djvBcuHABY8aMUZvsAICdnR2efvppXLx4UZfmVeTk5AAAHB0dq6zbtWtXeHh4YNCgQRrv6A48mgk6NzdX5UFERETGS+cxPFUdGFI3MaEurzFnzhz06dMHHTp00FjPw8MD3333HcLDw7F9+3b4+flh0KBBiI6OVls/LCwMCoVCfnh5edU4ViIiIjJcOp/SSk5ORnx8PBo3blxh+f3799GhQ4can9KaPn069u7diyNHjqBp06bVWnfkyJGQJAm7d++usKywsBCFhYXy89zcXHh5efGUFhERUQNS66e0QkNDcfv2bQQGBiI8PBwZGRkAgIyMDGzbtg29e/fG7du3MXXqVF2aBwDMnDkTu3fvRkRERLWTHQDo1asXEhMT1S6ztLSEnZ2dyoOIiIiMl84zLcfFxWH58uV47rnnADy6rURZWRmAR6eiZs6cqdOMzMp1d+zYgcjISLRo0UKXEHH27Fl4eHjotC4REREZF50nHvziiy8wZswYrF27FnFxccjNzZUnHpw4cSL69u2rU7vTp0/H//3f/2HXrl2wtbVFamoqAEChUMDa2hoAMH/+fCQnJ8uXvX/55Zfw9vZG+/btUVRUhE2bNiE8PBzh4eG6bh4REREZkRrNtNynTx+9z6j8zTffAAAGDBigUr527VpMmjQJAJCSkoKbN2/Ky4qKivDmm28iOTkZ1tbWaN++Pfbu3Yvg4GC9xkZEREQNk06Dlo0N5+EhIiJqeGpl0HJ+fj58fX0RFBSE4uJijfWKiorQp08ftGnTBg8ePNA+aiIiIqJaonXCs3btWly7dg1hYWEwNzfXWM/CwgJhYWH466+/8MMPP+glSCIiIqKa0Drh2bVrF9q2bavx9g7l9e3bFx07dsT27dtrFBwRERGRPmid8Jw7d06rZEcpKCgI58+f1ykoIiIiIn3SOuHJzs6Gk5OT1g07OjrK98EiIiIiqk9aJzx2dnbIzMzUuuGsrCyNNxclIiIiqktaJzytW7fWeDNOdaKjo+Hn56dTUERERET6pHXCExwcjEuXLmHLli1V1v3pp58QHx+PESNG1Cg4IiIiIn3QOuGZMWMG7O3t8corr2DdunUa661fvx4vv/wynJycMG3aNH3ESERERFQj1Zpp+dChQxg1ahQePnyIpk2bYsCAAfKdzJOTkxEZGYlbt27BysoKv/zyCwYOHFhrgesTZ1omIiJqeKrz+13tW0ucO3cOs2bNwuHDh9Uu79evH1asWIFOnTpVp9l6xYSHiIio4anO73e1bx7auXNnREVF4erVq4iJiZHvZu7u7o6goCC0atVKt6iJiIiIaonOd0tv1aoVkxsiIiJqELQetExERETUUDHhISIiIqPHhIeIiIiMHhMeIiIiMnpMeIiIiMjoMeEhIiIio6fzZelKeXl5+Ouvv5Cfn4++ffvqIyYiIiIivdL5CM/169cREhICBwcHdO/eXeU2EjExMWjXrh0iIyP1ESMRERFRjeiU8Ny8eRO9evXCvn37EBISgsDAQJS/Q0XPnj2RkZGBzZs36y1QIiIiIl3plPAsXLgQ9+7dQ1RUFLZt24bBgwerLDczM0Pfvn0RExOjlyCJiIiIakKnhOe3337DU089hd69e2us06xZMyQnJ+scGBEREZG+6JTwZGVlwdvbu8p6hYWFujRPREREpFc6JTxubm64cuVKpXUuXLiAZs2a6RQUERERkT7plPAMHjwYe/bswYULF9QuP3z4MA4dOoTg4OAaBUdERESkDzolPP/+979hbW2NPn364OOPP5aP9uzfvx8LFizAsGHD4OzsjLfeekuvwRIRERHpQhLlryevhuPHj2Ps2LG4ceMGJEmCEEL+t1mzZti2bRsCAgL0HW+tyM3NhUKhQE5ODuzs7Oo7HCIiItJCdX6/dZ5puWfPnkhMTMSePXtw/PhxZGVlwc7ODj179kRISAgsLCx0bZqIiIhIr3Q+wmNMeISHiIio4anO77dOY3hKS0uRm5uLsrKySpeXlpZWu+2wsDB0794dtra2cHV1xejRo5GQkFDlelFRUfD394eVlRVatmyJb7/9ttqv3VB9sPsinvgsAuO/P4bNJ24iKSO/vkPS2bX0PEQkpDXobSAiIsOjU8Lz/vvvw9XVFZmZmWqXZ2Vlwc3NDR999FG1246KisL06dNx7NgxHDx4ECUlJRgyZAjy8zX/ACYlJSE4OBh9+/bF2bNn8c4772DWrFkIDw+v9us3JAcupMD77b344eh1XMsoQMzVTMzffh4DP4vEuO+OIaeguL5D1Fp2QREmrDmBJz6PwktrT2LgZ5GYsOZEg9oGIiIyXDqd0urWrRs8PDywd+9ejXVGjhyJO3fu4PTp0zUKMD09Ha6uroiKikK/fv3U1pk3bx52796NS5cuyWWhoaE4d+4cYmNjq3yNhnpKy/ttzf0PAP18XbDh5R51FE3NTFhzAjFXMlBabnc0lSQE+Tg3mG0gIqK6VeuntK5du4Y2bdpUWsfPzw9JSUm6NK8iJycHAODo6KixTmxsLIYMGaJSNnToUJw6dQrFxRWPEBQWFiI3N1fl0dB8sPtilXWiE9MbxKmha+l5iE5MV0l2AKBUiAazDUREZNh0SnhKSkpgYlL5qpIk4eHDhzoFpSSEwJw5c9CnTx906NBBY73U1FS4ubmplLm5uaGkpAQZGRkV6oeFhUGhUMgPLy+vGsVZH45eq7hd6lzPNPxk4UZWQaXLG8I2EBGRYdMp4WnVqhX++OOPSuv88ccfaNGihU5BKc2YMQN//vknNm/eXGVdSZJUnivP1D1eDgDz589HTk6O/Lh161aN4qwPvVs6a1XP28mmliOpueaOjSpd3hC2gYiIDJtOCc+YMWMQFxeH9957r8KVWKWlpViwYAHi4uLw7LPP6hzYzJkzsXv3bkRERKBp06aV1nV3d0dqaqpKWVpaGszMzODk5FShvqWlJezs7FQeDc17o9pXWaefrwtaOBt+stDSpTH6+brA9LHk1FSSGsw2EBGRYdNp0HJeXh569uyJy5cvo1WrVhg4cCCaNGmC5ORkRERE4OrVq2jbti2OHTuGxo0bV6ttIQRmzpyJHTt2IDIyEr6+vlWuM2/ePOzZswfx8fFy2dSpUxEXF2fUg5YPxd/FyxtOqV0W2NIJ3/7TH4pG5nUclW5yCooxc/NZRCemy2X9fF3w1biuDWYbiIioblXn91vniQczMzMxdepUhIeHo3wTJiYmGDNmDFatWqX26EpVpk2bhv/7v//Drl274OfnJ5crFApYW1sDeHRKKjk5GRs2bADw6LL0Dh064LXXXsOUKVMQGxuL0NBQbN68GWPGjKnyNRtqwqO0+Jd4/HH5LjwV1hjR2RO9Wjo12KMiSRn5uJ6ZD28nmwa7DUREVDfqJOFRSktLw6lTp5CdnQ17e3sEBATA1dVV5/bUjbkBgLVr12LSpEkAgEmTJuH69euIjIyUl0dFReGNN97AxYsX4enpiXnz5iE0NFSr12zoCQ8REdHfUZ0mPMaACQ8REVHDU+vz8BARERE1JDrfLT0+Ph4rV67EyZMnkZ2drfa+WZIk4erVqzUKkIiIiKimdEp4oqKiMGzYMBQWFsLMzAxubm4wM6vYFM+WERERkSHQKeF5++23UVJSgtWrV2PixIkwNTXVd1xEREREeqNTwnPu3DmMHTsWkydP1nc8RERERHqn06BlW1vbGl16TkRERFSXdEp4RowYgcOHD+s7FiIiIqJaoVPCs3TpUuTk5GDWrFkoKKj8TtdERERE9U2niQefeOIJZGdn49y5c7CxsYGvry8UCkXFxiUJhw4d0kugtYkTDxIRETU8tT7TsomJdgeGJElSOz+PoWHCQ0RE1PBU5/dbp6u0ysrKdAqMiIiIqD7w1hJERERk9HS+tYRSXl4e/vrrL+Tn56Nv3776iImIiIhIr3Q+wnP9+nWEhITAwcEB3bt3x8CBA+VlMTExaNeuHSIjI/URIxEREVGN6JTw3Lx5E7169cK+ffsQEhKCwMBAlftm9ezZExkZGdi8ebPeAiUiIiLSlU4Jz8KFC3Hv3j1ERUVh27ZtGDx4sMpyMzMz9O3bFzExMXoJkoiIiKgmdEp4fvvtNzz11FPo3bu3xjrNmjVDcnKyzoERERER6YtOCU9WVha8vb2rrFdYWKhL80RERER6pVPC4+bmhitXrlRa58KFC2jWrJlOQRERERHpk04Jz+DBg7Fnzx5cuHBB7fLDhw/j0KFDCA4OrlFwRERERPqgU8Lz73//G9bW1ujTpw8+/vhj+WjP/v37sWDBAgwbNgzOzs5466239BosERERkS50upcWABw/fhxjx47FjRs3IEkShBDyv82aNcO2bdsQEBCg73hrBe+lRURE1PDU+r20gEdz7SQmJmLPnj04fvw4srKyYGdnh549eyIkJAQWFha6Nk1ERESkVzod4fnggw/QsmVL/POf/6yNmOocj/AQERE1PNX5/dZpDM/ixYtx/vx5nYIjIiIiqms6JTzNmzdHVlaWvmMhIiIiqhU6JTzjxo3Db7/9hpycHH3HQ0RERKR3Ol+W3qlTJzzxxBPYu3cv0tLS9B0XERERkd7odJWWtbU1AEAIgVGjRmmsJ0kSSkpKdIuMiIiISE90Snj69u0LSZL0HQsRERFRrdAp4YmMjNRzGERERES1R6cxPLUpOjoaI0eOhKenJyRJws6dOyutHxkZCUmSKjwuX75cNwETERGRwdN5pmUAKCoqwu+//47Lly8jPz8fCxYsAAA8fPgQubm5cHZ2holJ9XKq/Px8dO7cGS+99BLGjBmj9XoJCQkqkw65uLhU63WJiIjIeOmc8OzevRuvvvoq0tPT5ftoKROeP//8E4GBgdi4cSNeeOGFarU7fPhwDB8+vNrxuLq6wt7evtrrERERkfHT6ZRWTEwMnnnmGVhaWmL58uUVkpoePXrAx8cH4eHheglSG127doWHhwcGDRqEiIiISusWFhYiNzdX5UFERETGS6cjPIsXL4a9vT1OnToFFxcXZGZmVqjj7++PEydO1DjAqnh4eOC7776Dv78/CgsLsXHjRgwaNAiRkZHo16+f2nXCwsLw/vvv13psREREZBh0SniOHTuGZ555ptJxMl5eXti9e7fOgWnLz88Pfn5+8vPAwEDcunULn332mcaEZ/78+ZgzZ478PDc3F15eXrUeKxEREdUPnU5pFRYWQqFQVFonJyen2gOW9aVXr15ITEzUuNzS0hJ2dnYqDyIiIjJeOmUkLVu2xKlTpyqtExsbizZt2ugUVE2dPXsWHh4e9fLaREREZHh0SnjGjBmDw4cPY8OGDWqXf/bZZ7hw4QKef/75aredl5eHuLg4xMXFAQCSkpIQFxeHmzdvAnh0OmrChAly/S+//BI7d+5EYmIiLl68iPnz5yM8PBwzZsyo/oYRERGRUdJpDM9bb72F8PBwvPTSS9i0aRMePnwIAPjXv/6F2NhYHD16FF26dNEp6Th16hQGDhwoP1eOtZk4cSLWrVuHlJQUOfkBHs0F9OabbyI5ORnW1tZo37499u7di+DgYF02jYiIiIyQJIQQuqx47949zJgxAz/99BNKS0v/16Ak4bnnnsOqVavg4OCgt0BrU25uLhQKBXJycjieh4iIqIGozu+3zgmPUmZmJk6ePImsrCzY2dmhe/fucHNzq0mTdY4JDxERUcNTnd9vrU5ptWzZErNnz8asWbMAABs2bECXLl3QqVMnODk5YdiwYTWPmoiIiKiWaDVo+fr168jOzpafT5o0qcqbehIREREZCq0SHldXVyQnJ9d2LERERES1QqtTWj179sTGjRthZmYmj8+JjIyscr3yNxQlIiIiqi9aDVr+66+/MHr0aFy+fPnRSpIEbcY6S5KkcgWXoeKgZSIiooZH74OWW7dujQsXLiApKQnJyckYMGAAJk2ahIkTJ+olYCIiIqLapPXEgyYmJmjVqhVatWqF5s2bo0uXLujfv39txkZERESkFzrNtJyUlKTvOIiIiIhqjU4Jj1Jqaiq2b9+Oy5cvo6CgAKtXrwYApKenIykpCR07doS1tbVeAiUiIiLSlc4Jz6pVqzB37lwUFhYCeDRAWZnwpKWlITAwEN9++y2mTJmin0iJiIiIdKTT3dL37NmDGTNmoGPHjti9ezemTp2qsrx9+/bo1KkTJyckIiIig6DTEZ5PP/0UzZo1Q0REBGxsbHD69OkKdTp27IjDhw/XOEAiIiKimtLpCE9cXBxGjBgBGxsbjXWaNGmCu3fv6hwYERERkb7olPCUlZXB3Ny80jrp6emwtLTUKSgiIiIifdIp4fHz88ORI0c0Li8pKUFUVBQ6duyoc2BERERE+qJTwjN+/HicOXMGixcvrrCstLQUb775Jq5du4YJEybUOEAiIiKimtLqXlqPKy4uxpAhQxAdHQ0fHx9YWlri4sWLGDNmDE6dOoXr169jyJAh2L9/PyRJqo249Yr30iIiImp4qvP7rdMRHnNzc/z22294++23kZGRgQsXLkAIgW3btiErKwvz5s3D7t27G0SyQ0RERMZPpyM85QkhkJCQgKysLNjZ2aFt27YwNTXVV3x1gkd4iIiIGp5aP8JTniRJaNOmDXr37o0OHTrIyU5SUhImTZpU0+aJiIiIaqzGCc/jbt68iSlTpqBNmzbYuHGjvpsnIiIiqrZqJTxHjhzBwIEDYWdnB0dHR4SEhCAhIQEAUFBQgDlz5qB169ZYs2YNXFxcsGLFiloJmoiIiKg6tL61xOnTp/GPf/wDRUVFctmePXtw8uRJREdHY/To0YiPj4enpyfmzZuHV199lRMPEhERkUHQ+gjP0qVLUVRUhLCwMKSlpSEtLQ0ffPABUlNT0bdvX1y+fBn//ve/ceXKFcycOZPJDhERERkMra/Satq0Kdq0aYPff/9dpXzgwIGIjo7Gp59+ijlz5tRKkLWNV2kRERE1PLVylVZaWhr8/f0rlHfv3h0AMHHixGqGSURERFQ3tE54SkpK1N4dXVnm5OSkv6iIiIiI9Ejvl6UTERERGRqtr9ICgE2bNuHYsWMqZVeuXAEABAcHV6gvSRL27t1bg/CIiIiIak7rQcsmJtU/GCRJEkpLS6u9Xl3joGUiIqKGpzq/31of4UlKSqpxYNpQXvF1+vRppKSkYMeOHRg9enSl60RFRWHOnDm4ePEiPD098a9//QuhoaF1Em9du5aehxtZBfB2skELZxusPJSIzw7+JS/3sreChZkJxvh7YdpAn3qMVDsf7L6Io9cy0MfHBf9+sl2F7auOmqxLRETGTeuEp3nz5rUZhyw/Px+dO3fGSy+9hDFjxlRZPykpCcHBwZgyZQo2bdqEmJgYTJs2DS4uLlqt31BkFxRh1uY4RCemV1rvVvZDAMDS3xKw9LcEbJ3SCz1bGd6A8gMXUvDqpjPy88upeVh9RDWp7ufrgq/GdYWikXmlbanrG23XJSKiv4ca3y29NkmSVOURnnnz5mH37t24dOmSXBYaGopz584hNjZWq9dpCKe0Jqw5gZgrGSjV4e26vmRELURUM95vVz22y1SSEOTjjA0v96i0nrq+0XZdIiJquOr0bun1LTY2FkOGDFEpGzp0KE6dOoXi4mK16xQWFiI3N1flYciupechOjFdp2QHAFZFXNFzRDXzwe6LWtUrFQLRielIysjXWEdT32izLhER/X00+IQnNTUVbm5uKmVubm4oKSlBRkaG2nXCwsKgUCjkh5eXV12EqrMbWQU1Wv9wFafB6trRa+rfF02uZ2pOWqrqm8rWJSKiv48Gn/AAj059lac8S/d4udL8+fORk5MjP27dulXrMdZEc8dGNVq/r6+LniLRj94tnatV39tJ8wDkqvqmsnWJiOjvo8EnPO7u7khNTVUpS0tLg5mZmcbZny0tLWFnZ6fyMGQtXRqjn68LTDUkcFUxtKu13hvVXqt6ppKEfr4ulV5xpalvtFmXiIj+Php8whMYGIiDBw+qlB04cAABAQEwNzeeK3S+GtcVQT7VOzICAFun9KqFaGpuzYSAKusE+Tjjq3Fdq6ynrm+0XZeIiP4eDO4qrby8PHn25q5du2LZsmUYOHAgHB0d0axZM8yfPx/JycnYsGEDgEeXpXfo0AGvvfYapkyZgtjYWISGhmLz5s1aX5beEK7SUkrKyMf1zHx5rplVEVew9LcEebmXgzUsTKUGMw/P4l/iceRKujwPz+PbVx01WZeIiBqe6vx+G1zCExkZiYEDB1YonzhxItatW4dJkybh+vXriIyMlJdFRUXhjTfekCcenDdvXrUmHmxICQ8RERE90qATnvrAhIeIiKjh+VvNw0NERERUFSY8REREZPSY8BAREZHRY8JDRERERo8JDxERERk9JjxERERk9JjwEBERkdFjwkNERERGjwkPERERGT0mPERERGT0mPAQERGR0WPCQ0REREaPCQ8REREZPSY8REREZPSY8BAREZHRY8JDRERERo8JDxERERk9JjxERERk9JjwEBERkdFjwkNERERGjwkPERERGT0mPERERGT0mPAQERGR0WPCQ0REREaPCQ8REREZPSY8REREZPSY8BAREZHRY8JDRERERo8JDxERERk9JjxERERk9JjwEBERkdEzyIRn1apVaNGiBaysrODv74/Dhw9rrBsZGQlJkio8Ll++XIcRExERkSEzuIRn69atmD17Nt59912cPXsWffv2xfDhw3Hz5s1K10tISEBKSor88PX1raOIiYiIyNAZXMKzbNkyvPzyy3jllVfQtm1bfPnll/Dy8sI333xT6Xqurq5wd3eXH6ampnUUMRERERk6g0p4ioqKcPr0aQwZMkSlfMiQITh69Gil63bt2hUeHh4YNGgQIiIiKq1bWFiI3NxclQcREREZL4NKeDIyMlBaWgo3NzeVcjc3N6Smpqpdx8PDA9999x3Cw8Oxfft2+Pn5YdCgQYiOjtb4OmFhYVAoFPLDy8tLr9tBREREhsWsvgNQR5IkledCiAplSn5+fvDz85OfBwYG4tatW/jss8/Qr18/tevMnz8fc+bMkZ/n5uYy6SEiIjJiBnWEx9nZGaamphWO5qSlpVU46lOZXr16ITExUeNyS0tL2NnZqTyIiIjIeBlUwmNhYQF/f38cPHhQpfzgwYPo3bu31u2cPXsWHh4e+g6PiIiIGiiDO6U1Z84cvPjiiwgICEBgYCC+++473Lx5E6GhoQAenY5KTk7Ghg0bAABffvklvL290b59exQVFWHTpk0IDw9HeHh4fW4GERERGRCDS3ief/55ZGZm4oMPPkBKSgo6dOiAffv2oXnz5gCAlJQUlTl5ioqK8OabbyI5ORnW1tZo37499u7di+Dg4PraBCIiIjIwkhBC1HcQ9S03NxcKhQI5OTkcz0NERNRAVOf326DG8BARERHVBiY8REREZPSY8BAREZHRY8JDRERERo8JDxERERk9JjxERERk9JjwEBERkdFjwkNERERGjwkPERERGT0mPERERGT0mPAQERGR0WPCQ0REREaPCQ8REREZPSY8REREZPSY8BAREZHRY8JDRERERo8JDxERERk9JjxERERk9JjwEBERkdFjwkNERERGjwkPERERGT0mPERERGT0mPAQERGR0WPCQ0REREaPCQ8REREZPSY8REREZPSY8BAREZHRY8JDRERERo8JDxERERk9JjxERERk9JjwEBERkdEzq+8A1Fm1ahU+/fRTpKSkoH379vjyyy/Rt29fjfWjoqIwZ84cXLx4EZ6envjXv/6F0NDQOoxYs6iENExce1J+PndIa2TlFSHnQTFautjgXl4RYq5lwMnGEqEDWqGvr0ul7V1Lz8ONrAKYShLibt3DsoOJGuuaASgDoLA2g42VGVo42SA5+wEy8grRuak9gjt5AJCQmVeImCuZsLU0g521GZKzH6CpgzVKygQkAGn3H+JCci5srcwwtJ07SgTg3NgCLo0tkXr/IeKTc5CYlgcfV1vMD26LE9cyEZuUifTcQmTmF8IUwJ2chwAAT3trPCguha+rLW5l5iP+bp4cr6WZhNJSgRLx6HmAlz06eilw694DNHdqhEt3cnGvoAjNnWxgZWGKxJRc3Lz3AK62Vni6WxNcSc+DBAl3cx/iRlY+Als6I6C5A2KTMuHr2hgZ9wtx694D2FubIzn7ARpbmWFwOze42FohPjkHZ29lo5ljIwzwc0XcrXtIysiHiSThanoeCovL0N7TDl5OjXArswDHkjIhQUJzx0a4k/MAVmameKlPC/g3d5Dfn1IhYCoBydkPAEgwkYBLKblwamyJJzt5ooWzTYX39pc/7yArvxiD2rrizr0HiE3KRFArZzwb4KX9Tqdhn/F2soEQAseTsiAByMgrxJX0PPi62MKxsQUkAD1bOuFmZj7ibmcjt6AYN7IK0MyxEV4M9FYbr7Ldx5dVFoOybnXWry3X0vPk/vC0t0KpgN7iqWz7ohLSEHc7G92aOah85vXRJ4bSr/URw/++H6HX95JqzhD2S0kIIerllTXYunUrXnzxRaxatQpBQUH4z3/+g9WrVyM+Ph7NmjWrUD8pKQkdOnTAlClT8NprryEmJgbTpk3D5s2bMWbMGK1eMzc3FwqFAjk5ObCzs9PLdtzIzEf/TyOrvV5jS1Psn9UPXk6NVMqzC4owa3McohPT9RIf1b/uzR2wemJ3CAhM2XAKJ6/f01jXzETC7ulBaNdEoXX7+t5nujZVYN3knhAQFdrt5+uCr8Z1haKReZUxBLZ0giQBR69mVrl+bckuKMLUTWcQey1T7fKaxKNum5XtZT8owuivY3CvoFhe5tDIHJte7olPfk3Qqk91ed267Nf6iKGyfb2u+4BU1fY+UZ3fb4NLeHr27Ilu3brhm2++kcvatm2L0aNHIywsrEL9efPmYffu3bh06ZJcFhoainPnziE2Nlar16yNhKfrBwdUvtSqw6GROc6+N0SlbMKaE4i5koFSw3q7qIb6/feve22SEjMTCVc+Dta67drYZ5TxPt6uqSQhyMcZG17uoVMMmtavLRPWnKi0z2sSj7ptVrZ3Pjlb7feCmYkEIaBVn+ryunXZr/URQ2X7WV33Aamq7X2iOr/fBjWGp6ioCKdPn8aQIao/9kOGDMHRo0fVrhMbG1uh/tChQ3Hq1CkUF6tPOAoLC5Gbm6vy0KeohDSdkx0AuFdQjMPlvoyvpechOjGdyY4Rik5M1/oITEmZwM+nbmlVt7b2GWW8j7dbKgSiE9ORlJGvUwzq1q8tyrhqIx5N26xsT9P3QkmZ0KpPdX3duuzXuo6hqv2sLvuAVBnCflmeQSU8GRkZKC0thZubm0q5m5sbUlNT1a6Tmpqqtn5JSQkyMjLUrhMWFgaFQiE/vLx0Hx+hTtzt7Bq3cebm/05v3MgqqHF7ZBxirqrfpx9XX/vM9cz/fYHpEkP59WtLdeKqbjy10e/axFDV6xpCv9ZWDNr2eV30AakyhP2yPINKeJQkSVJ5LoSoUFZVfXXlSvPnz0dOTo78uHVLu7+atdWlqX2N2+jWzEH+f3PHRpXUpL+ToFbOWtWrr33G2+l/gxF1iaH8+rWlOnFVN57a6HdtYqjqdQ2hX2srBm37vC76gFQZwn5ZnkElPM7OzjA1Na1wNCctLa3CURwld3d3tfXNzMzg5OSkdh1LS0vY2dmpPPSpv58rHGowGMuhkbnKlRstXRqjn68LTCtJ+qhh6ufrIo+LqYqZiaT11Vq1tc8o4328XVNJQj9fF5WrL6oTg7r1a4syrtqIR9M2K9vT9L1gZiJp1ae6vm5d9mtdx1DVflaXfUCqDGG/LM+gEh4LCwv4+/vj4MGDKuUHDx5E79691a4TGBhYof6BAwcQEBAAc/P6G5W/e3ofndZrbGmqdt2vxnVFkI92f91Tw9C9uQO+GtcVX43rih7eDpXWVV6lVR363me6NlXI8T7ebpCPM74a11WrGAJbOqF3K9U/RjStX1u+GtcVgS3V/0FU03gq65/d0/tUSHocGplj9/QgrftUl9etK/UVQ2X7el33AakyhP1SyeCu0lJelv7tt98iMDAQ3333Hb7//ntcvHgRzZs3x/z585GcnIwNGzYA+N9l6a+99hqmTJmC2NhYhIaG1vtl6UqHE9Px4poT8vO5Q1ojO78I9woezcOTXVCMmCvpcNRyHp6kjHxcz8yHmYmEc7ey8dmBvzTWVc7DY29thkb/nYfnTvZDpOc9ROem9hjRyRMCwL38IhxJzEBjSzMoGpnj9r0CNHVohNIyAUAg/X4hLiTnoLGVGYa290BJmYBzYwu42VnhTs4DXLqTi7/u3pfn4Tl1PQsxVzOQeb8Q6XmFMJOk/85FAzSxt0bBf+fhSb5XgAsp9+V4Lc0klJUKFCvn4Wlmj85e9vLcDZdScpCV/795eK6k3sfNewVwaWyFMf5NcSXtPgAJ6fcfIinz0Tw8PVo4IuZqBlq72iIzrxA3sgrg0MgCydkFsLE0w5B27nC2tcSlO7k4e/MevBwbYWAbV5y7lY1r6XkwkSRcS8/Dg+IydGiiQFNHa9zOeoBj/72c2dupEe5kP4Dlf+fhCfB2lN+fkjIBMxMJyfceQOBR0hJ/JxeOjS3UzsOTlJGPvX/eQUZeEQa1dUVqzkPEXM2o8Tw8yn1Gefj42LVMSACy8ovwV9p9tHa1hYPN/+bhuX2vAGdu3sP9ByW4kZkPLw3z8JRvt6q/1NTVrc76tSUpI1/ujyb/nXtKX/FUtn2HE9Nx5ua9CvPw6KNPDKVf6yOG8t+P+nwvqeZqa59o0JelA48mHly6dClSUlLQoUMHfPHFF+jXrx8AYNKkSbh+/ToiIyPl+lFRUXjjjTfkiQfnzZtXrYkHazPhISIiotrR4BOeusaEh4iIqOFpsPPwEBEREdUGJjxERERk9JjwEBERkdFjwkNERERGjwkPERERGT0mPERERGT0mPAQERGR0WPCQ0REREaPCQ8REREZPbP6DsAQKCebzs3NredIiIiISFvK321tbhrBhAfA/fuPbmDp5aX7DRqJiIiofty/fx8KhaLSOryXFoCysjIkJCSgXbt2uHXrFu+nVU25ubnw8vJi31UT+0137Dvdse90x77TXW31nRAC9+/fh6enJ0xMKh+lwyM8AExMTNCkSRMAgJ2dHXdkHbHvdMN+0x37TnfsO92x73RXG31X1ZEdJQ5aJiIiIqPHhIeIiIiMHhOe/7K0tMTChQthaWlZ36E0OOw73bDfdMe+0x37TnfsO90ZQt9x0DIREREZPR7hISIiIqPHhIeIiIiMHhMeIiIiMnpMeIiIiMjoMeEBsGrVKrRo0QJWVlbw9/fH4cOH6zskg7No0SJIkqTycHd3l5cLIbBo0SJ4enrC2toaAwYMwMWLF+sx4voTHR2NkSNHwtPTE5IkYefOnSrLtemrwsJCzJw5E87OzrCxscGoUaNw+/btOtyK+lFV302aNKnCftirVy+VOn/HvgsLC0P37t1ha2sLV1dXjB49GgkJCSp1uN+pp03fcb9T75tvvkGnTp3kyQQDAwOxf/9+ebmh7XN/+4Rn69atmD17Nt59912cPXsWffv2xfDhw3Hz5s36Ds3gtG/fHikpKfLj/Pnz8rKlS5di2bJlWLlyJU6ePAl3d3cMHjxYvk/Z30l+fj46d+6MlStXql2uTV/Nnj0bO3bswJYtW3DkyBHk5eXhySefRGlpaV1tRr2oqu8AYNiwYSr74b59+1SW/x37LioqCtOnT8exY8dw8OBBlJSUYMiQIcjPz5frcL9TT5u+A7jfqdO0aVMsWbIEp06dwqlTp/DEE08gJCRETmoMbp8Tf3M9evQQoaGhKmVt2rQRb7/9dj1FZJgWLlwoOnfurHZZWVmZcHd3F0uWLJHLHj58KBQKhfj222/rKELDBEDs2LFDfq5NX2VnZwtzc3OxZcsWuU5ycrIwMTERv/76a53FXt8e7zshhJg4caIICQnRuA777pG0tDQBQERFRQkhuN9Vx+N9JwT3u+pwcHAQq1evNsh97m99hKeoqAinT5/GkCFDVMqHDBmCo0eP1lNUhisxMRGenp5o0aIFxo4di2vXrgEAkpKSkJqaqtKPlpaW6N+/P/vxMdr01enTp1FcXKxSx9PTEx06dGB/AoiMjISrqytat26NKVOmIC0tTV7GvnskJycHAODo6AiA+111PN53StzvKldaWootW7YgPz8fgYGBBrnP/a0TnoyMDJSWlsLNzU2l3M3NDampqfUUlWHq2bMnNmzYgN9++w3ff/89UlNT0bt3b2RmZsp9xX6smjZ9lZqaCgsLCzg4OGis83c1fPhw/Pjjj/jjjz/w+eef4+TJk3jiiSdQWFgIgH0HPBo3MWfOHPTp0wcdOnQAwP1OW+r6DuB+V5nz58+jcePGsLS0RGhoKHbs2IF27doZ5D7Hu6UDkCRJ5bkQokLZ393w4cPl/3fs2BGBgYFo1aoV1q9fLw/eYz9qT5e+Yn8Czz//vPz/Dh06ICAgAM2bN8fevXvx9NNPa1zv79R3M2bMwJ9//okjR45UWMb9rnKa+o77nWZ+fn6Ii4tDdnY2wsPDMXHiRERFRcnLDWmf+1sf4XF2doapqWmFTDItLa1CVkqqbGxs0LFjRyQmJspXa7Efq6ZNX7m7u6OoqAj37t3TWIce8fDwQPPmzZGYmAiAfTdz5kzs3r0bERERaNq0qVzO/a5qmvpOHe53/2NhYQEfHx8EBAQgLCwMnTt3xvLlyw1yn/tbJzwWFhbw9/fHwYMHVcoPHjyI3r1711NUDUNhYSEuXboEDw8PtGjRAu7u7ir9WFRUhKioKPbjY7TpK39/f5ibm6vUSUlJwYULF9ifj8nMzMStW7fg4eEB4O/bd0IIzJgxA9u3b8cff/yBFi1aqCznfqdZVX2nDvc7zYQQKCwsNMx9Tu/DoBuYLVu2CHNzc7FmzRoRHx8vZs+eLWxsbMT169frOzSDMnfuXBEZGSmuXbsmjh07Jp588klha2sr99OSJUuEQqEQ27dvF+fPnxfjxo0THh4eIjc3t54jr3v3798XZ8+eFWfPnhUAxLJly8TZs2fFjRs3hBDa9VVoaKho2rSp+P3338WZM2fEE088ITp37ixKSkrqa7PqRGV9d//+fTF37lxx9OhRkZSUJCIiIkRgYKBo0qTJ377vpk6dKhQKhYiMjBQpKSnyo6CgQK7D/U69qvqO+51m8+fPF9HR0SIpKUn8+eef4p133hEmJibiwIEDQgjD2+f+9gmPEEJ8/fXXonnz5sLCwkJ069ZN5XJEeuT5558XHh4ewtzcXHh6eoqnn35aXLx4UV5eVlYmFi5cKNzd3YWlpaXo16+fOH/+fD1GXH8iIiIEgAqPiRMnCiG066sHDx6IGTNmCEdHR2FtbS2efPJJcfPmzXrYmrpVWd8VFBSIIUOGCBcXF2Fubi6aNWsmJk6cWKFf/o59p67PAIi1a9fKdbjfqVdV33G/02zy5Mnyb6eLi4sYNGiQnOwIYXj7nCSEEPo/bkRERERkOP7WY3iIiIjo74EJDxERERk9JjxERERk9JjwEBERkdFjwkNERERGjwkPERERGT0mPERERGT0mPAQERGR0WPCQ/Q34e3tDW9vb722OWnSJEiShOvXr+u13ZrKy8uDh4cHpk2bVt+hGBR171dERAQkScK+ffvqLzCiOsCEh8gITJgwAZIkwd3dHSUlJXprd926dZAkCevWrdNbm3Vh6dKlyMrKwvz58+s7FIM3cOBA9O/fH2+99RZKS0vrOxyiWsOEh6iBy83NRXh4OCRJwt27d7F371619Q4dOoRDhw7p9bXDwsJw6dIlNGnSRK/t1kR2djaWLVuGcePGwcvLq77DaRDefPNNxMfHY/PmzfUdClGtYcJD1MBt3rwZBQUFmDt3LiRJwpo1a9TWa9WqFVq1aqXX1/bw8ECbNm1gbm6u13ZrYuPGjcjPz8eLL75Y36E0GMOGDYOLiwu+/fbb+g6FqNYw4SFq4NasWQMLCwvMnz8fQUFB2LdvH1JSUirUUzeGZ9GiRZAkCZGRkVi/fj38/f3RqFEjDBgwAJMmTcJLL70EAHjppZcgSZL8UFI3JiQyMhKSJGHRokU4evQoBg4cCFtbW7i4uGDatGl48OABAODXX39FUFAQbGxs4Obmhnnz5mk8pbJr1y4MGjQIDg4OsLKyQocOHfDZZ5+prb9u3To4OTlh4MCBFZYlJibipZdeQosWLWBlZQVnZ2d069YNc+fOrVD3/v37WLhwIdq3bw9ra2vY29tj2LBhOHLkiNoY79+/jw8++ACdOnWCjY0NFAoFunbtigULFqC4uFil7tGjRzFixAg4OjrCysoKbdq0waJFi1BQUFChXUmSMGDAAKSnp2Py5MlwdXWFtbU1evXqhcjISLWxXLx4EU8++SRsbW2hUCgQHByMCxcuqK0LAGZmZhg9ejRiYmKQmJiosR5RQ2ZW3wEQke7Onz+PkydP4qmnnoKjoyMmTJiAI0eOYP369Xj77be1bufTTz9FREQERo0ahcGDB8PMzAwBAQHIzs7Grl27EBISgi5dulQrtuPHj+OTTz7B0KFD8dprryEiIgLffPMNcnNzERISgokTJ2LUqFHo2bMn9u7di6VLl8LOzg7vvvuuSjvvvPMOwsLC0LRpU4wZMwZ2dnaIjo7GW2+9hePHj+Pnn3+W6967dw9nz57FsGHDYGKi+vfcnTt30KNHD+Tn52PEiBF4/vnnkZeXh8TERHz11Vf4/PPP5bpZWVno168fLl68iL59+2Lo0KHIycnBrl27MHDgQPz8888YPXq0XD8jIwP9+/dHfHw8unTpgtDQUJSVleHy5cv45JNPMHfuXNjb2wMAwsPDMXbsWFhYWOD555+Hq6srfv/9d7z//vs4cOAAIiIiYGlpqRJ7dnY2goKCYGdnh/HjxyMtLQ1bt27F0KFDcfr0aXTo0EGue+HCBQQFBSEvLw9PP/00fH19ceLECQQFBaFz584a36/AwEB8//33+OOPP+Dr66v1+0zUYAgiarBef/11AUBs375dCCFEdna2sLKyEr6+vhXqNm/eXDRv3lylbOHChQKAsLGxEX/++WeFddauXSsAiLVr16p9/YkTJwoAIikpSS6LiIgQAAQAsXPnTrm8qKhIdOrUSUiSJJydncWJEyfkZbm5ucLV1VU4OTmJ4uJiufzAgQMCgBg+fLjIz8+Xy8vKykRoaKgAILZt2yaX7927VwAQ7777boVYV6xYIQCI5cuXV1iWnp6u8vyFF14QAMQPP/ygUp6amiq8vLyEi4uLePDggVz+7LPPCgDinXfeqdB2amqqvE25ubnC3t5eWFpainPnzqlsj/I1P/zwQ5X1lX05bdo0UVpaKpevXr1aABCvvfaaSv3+/fsLAGLTpk0q5fPnz5fbKv9+KZ07d04AEBMmTKiwjMgY8JQWUQNVVFSETZs2wcHBASNGjAAAKBQKhISEIDExEdHR0Vq39eqrr6Jjx456jW/AgAEICQmRn5ubm+OZZ56BEAIjR45E9+7d5WW2trZ48sknkZmZidu3b8vlK1euBAD85z//QaNGjeRySZKwZMkSSJKkMtBWua6bm5vGuKytrSuUOTs7y//PyMjA1q1bMWjQIPmUnpKbmxveeustpKen4/fffwcA3L17F9u2bUOrVq2waNGiCm27ubnBzOzRwfSdO3ciOzsbkydPRqdOnSpsj5mZmdor4mxsbPDJJ5+oHLWaOHEizMzMcPLkSbns5s2biIqKQqdOnTB+/HiVNt555x35KJM6yj4r3/9ExoSntIgaqJ07dyIzMxOhoaGwsLCQyydMmICtW7fihx9+QL9+/bRqq0ePHnqPr2vXrhXKPDw8AEDt6THlsuTkZHms0bFjx2BjY6NxILa1tTUuX74sP8/MzAQAODg4VKj75JNP4u2338b06dNx8OBBDBs2DH369EHr1q1V6p08eRKlpaV4+PCh2gRGOcbl8uXLePLJJ3Hq1CkIITBw4MAqB2+fPXsWwKNk8HFeXl5o1aoVEhIScP/+fdja2srLfH190bhxY5X6ZmZmcHNzQ3Z2tlx27tw5AECfPn0qtN+4cWN06dJF47gfR0dHAI8SPiJjxISHqIH64YcfAKDC1UhDhw6Fu7s7fv75Z6xYsQJ2dnZVtlXZERFdqXtd5ZGOypaVH+CblZWFkpISvP/++xpfJz8/X/6/8uiNcmB0eS1atEBsbCzef/997N+/Xx774+fnhw8//BDPPvus/JoAEBMTg5iYmCpfV5lwaHNpfm5uLgDN/e3u7o6EhATk5uaqJDwKhUJtfTMzM5WB2zk5OQAAV1dXtfUre5+VfVb+SBqRMeEpLaIG6NatWzh48CAAICgoSOUKKjMzM6SmpqKgoABbtmzRqr3yV14ZEjs7Ozg5OUEIofGRlJQk13dxcQHwv6TlcZ06dUJ4eDiysrIQGxuL9957D3fv3sXzzz8vJzfKZGzu3LmVvu7ChQsBQD5NlJycrNX2AI9Og6mjLNcmSVVHmRilpaVV2r46yj5T9iGRseERHqIGaO3atSgrK0OfPn3g5+dXYXlRURE2btyINWvW4NVXX9X5dUxNTQGg3mbg7dmzJ/bv34/ExEStrhxSjkOq6tJqc3Nz9OrVC7169YKPjw8mTJiAX375BUFBQejevTskSUJsbKxWMQYEBMDExAQREREoLi6u9LSW8jRfZGQknnvuOZVlycnJuHr1Klq2bKlydKc6lFdhqbt0Pi8vD3FxcRrXTUhIAAC9j+UiMhQ8wkPUwAghsHbtWkiShA0bNmD16tUVHhs2bEDXrl1x4sSJSudfqYpyXEd9DWSdNWsWAGDy5Mny+JzyUlNTcenSJfl5x44d4ejoiBMnTlSoe/LkSbVHPpRHPZSnw9zd3fHcc8/h6NGj+PTTTyGEqLDO8ePH5Tlz3NzcMGbMGFy9elXtqbe0tDT5dh8hISFQKBRYu3YtLl68KNcRQmD+/PkoLi7GpEmTNPZHVZo1a4Z+/frhzz//xI8//qiy7OOPP1YZ76NumwCgf//+Or8+kSHjER6iBubQoUO4fv06Bg4ciBYtWmis99JLL+Hs2bNYs2YNvvjiC51eKzAwENbW1vjyyy+Rm5srn+6ozhw/NTFs2DAsWLAAH374IXx8fDBs2DA0b94cmZmZuHLlCg4fPozFixejbdu2AB6dmhs1ahQ2bNiAlJQUeSA0APz4449YtWoVBgwYAB8fH9jZ2SE+Ph779u2Ds7MzJk+eLNddtWoVEhIS8K9//QsbN25EYGAgFAoFbt26hdOnTyMxMREpKSnyeJdVq1bhwoUL+Oijj7Bv3z488cQTEELgr7/+woEDB3D37l3Y29vDzs4O33//PcaNG4eePXvi+eefh4uLCw4dOoRTp06hR48eeOutt2rUZ19//TWCgoIwYcIE7Ny5E76+vjh58iROnDiBvn374vDhw2rXO3jwIBwcHLQe6E7U4NTtVfBEVFNjx44VAMTGjRsrrZeRkSEsLCyEs7OzKCwsrHQenoiICI3t7N27V3Tv3l1YW1vL87goVTYPz8KFCyu0Vdm8PpXFcvDgQTFy5Ejh4uIizM3Nhbu7uwgMDBQffvihuHnzpkrd2NhYAUB8/vnnKuXHjh0Tr732mujQoYOwt7cX1tbWwtfXV8yaNatCG0IIUVBQIJYuXSr8/f2FjY2NsLa2Fi1atBCjR48WGzZsUJkvSAghcnJyxIIFC0SbNm2EpaWlUCgUokuXLuK9994TRUVFKnWjo6PF8OHDhb29vbCwsBCtW7cWCxYsEHl5eRXiACD69+9foVwI9XMrCSHE+fPnRXBwsGjcuLGwtbUVw4cPF+fPn1f7fgkhxPXr14UkSWL27NlqX4fIGEhCqDleS0TUgPXu3Rs5OTm4cOGCwQ7INiTvvfcelixZgkuXLun9fmtEhoJjeIjI6Hz22WeIj49Xue0EqZednY0VK1Zg6tSpTHbIqHEMDxEZnd69e+Pbb7+tcNNOquj69euYPXs2Zs6cWd+hENUqntIiIiIio8dTWkRERGT0mPAQERGR0WPCQ0REREaPCQ8REREZPSY8REREZPSY8BAREZHRY8JDRERERo8JDxERERk9JjxERERk9P4fuX17UVl/vLQAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot reference count & single ad duration\n",
    "airtime_ref.plot(kind='scatter', x = 'airtime_mean', y = 'reference_count')\n",
    "plt.xlabel('Airtime(second)' , fontsize = 14)\n",
    "plt.ylabel('Reference Count', fontsize = 14)\n",
    "plt.title('Single Airing Duration and Reference Count', fontsize=16)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot reference count & total airtime \n",
    "airtime_ref['airtime_sum'] = airtime_ref['airtime_sum'] / 60\n",
    "airtime_ref.plot(kind='scatter', x = 'airtime_sum', y = 'reference_count')\n",
    "plt.xlabel('Airtime(total minutes)', fontsize = 14)\n",
    "plt.ylabel('Reference Count', fontsize =14)\n",
    "plt.title('Total Airing Time and Reference Count', fontsize=16)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>location</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cand_list</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Hillary Clinton</th>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Donald Trump</th>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Marco Rubio</th>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ted Cruz</th>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bernie Sanders</th>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Andy Biggs</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kumar Barve</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Loretta Sanchez</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Maggie Hassan</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kelli Ward</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>88 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                 location\n",
       "cand_list                \n",
       "Hillary Clinton        25\n",
       "Donald Trump           25\n",
       "Marco Rubio            24\n",
       "Ted Cruz               23\n",
       "Bernie Sanders         23\n",
       "...                   ...\n",
       "Andy Biggs              1\n",
       "Kumar Barve             1\n",
       "Loretta Sanchez         1\n",
       "Maggie Hassan           1\n",
       "Kelli Ward              1\n",
       "\n",
       "[88 rows x 1 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Unpivot candidate column and compute coving locations for candidate\n",
    "airing['cand_list'] = airing['candidates'].str.split(', ')\n",
    "candidate_explode = airing.explode('cand_list', ignore_index=True)\n",
    "candidate_loc = candidate_explode.groupby('cand_list')[['location']].nunique()\n",
    "candidate_loc.sort_values(by='location', ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>message</th>\n",
       "      <th>con</th>\n",
       "      <th>mixed</th>\n",
       "      <th>pro</th>\n",
       "      <th>unknown</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cand_list</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Alan Grayson</th>\n",
       "      <td>NaN</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Andy Biggs</th>\n",
       "      <td>100.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ann Kirkpatrick</th>\n",
       "      <td>9.683739</td>\n",
       "      <td>65.547159</td>\n",
       "      <td>24.769102</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Anthony Brown</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ben Carson</th>\n",
       "      <td>0.051046</td>\n",
       "      <td>NaN</td>\n",
       "      <td>48.034712</td>\n",
       "      <td>51.914242</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Tim Kaine</th>\n",
       "      <td>100.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Todd Young</th>\n",
       "      <td>100.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Warren Davidson</th>\n",
       "      <td>NaN</td>\n",
       "      <td>24.216867</td>\n",
       "      <td>75.783133</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Willie Wilson</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>none</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>100.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>88 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "message                 con       mixed         pro     unknown\n",
       "cand_list                                                      \n",
       "Alan Grayson            NaN  100.000000         NaN         NaN\n",
       "Andy Biggs       100.000000         NaN         NaN         NaN\n",
       "Ann Kirkpatrick    9.683739   65.547159   24.769102         NaN\n",
       "Anthony Brown           NaN         NaN  100.000000         NaN\n",
       "Ben Carson         0.051046         NaN   48.034712   51.914242\n",
       "...                     ...         ...         ...         ...\n",
       "Tim Kaine        100.000000         NaN         NaN         NaN\n",
       "Todd Young       100.000000         NaN         NaN         NaN\n",
       "Warren Davidson         NaN   24.216867   75.783133         NaN\n",
       "Willie Wilson           NaN         NaN  100.000000         NaN\n",
       "none                    NaN         NaN         NaN  100.000000\n",
       "\n",
       "[88 rows x 4 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Unpivot Candidate tone and compute % of tone\n",
    "candidate_tone = candidate_explode.groupby(['cand_list', 'message'])[['wp_identifier']].count().reset_index()\n",
    "candidate_tone_pivot = candidate_tone.pivot(index='cand_list', columns='message', values='wp_identifier')\n",
    "candidate_tone_pivot_perc = candidate_tone_pivot.div(candidate_tone_pivot.sum(axis=1), axis=0) * 100\n",
    "candidate_tone_pivot_perc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot relationship between negative tone and covering locations\n",
    "loc_tone = pd.merge(candidate_tone_pivot_perc, candidate_loc, on='cand_list', how='left')\n",
    "loc_tone.plot(x='location', y='con', kind='scatter')\n",
    "plt.xlabel('Count of Cities', fontsize = 14)\n",
    "plt.ylabel('Negative Messsge %', fontsize =14)\n",
    "plt.title('Total Airing Time and Reference Count', fontsize=16)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot relationship between positive tone and covering locations\n",
    "loc_tone.plot(x='location', y='pro', kind='scatter')\n",
    "plt.xlabel('Count of Cities', fontsize = 14)\n",
    "plt.ylabel('Positive Messsge %', fontsize =14)\n",
    "plt.title('Total Airing Time and Reference Count', fontsize=16)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>cand_list</th>\n",
       "      <th>subjects</th>\n",
       "      <th>wp_identifier</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>263</th>\n",
       "      <td>Donald Trump</td>\n",
       "      <td>Candidate Biography</td>\n",
       "      <td>46633</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>396</th>\n",
       "      <td>Hillary Clinton</td>\n",
       "      <td>Candidate Biography</td>\n",
       "      <td>29889</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>325</th>\n",
       "      <td>Donald Trump</td>\n",
       "      <td>Terrorism</td>\n",
       "      <td>21600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>424</th>\n",
       "      <td>Hillary Clinton</td>\n",
       "      <td>Health Care</td>\n",
       "      <td>20584</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>308</th>\n",
       "      <td>Donald Trump</td>\n",
       "      <td>Military</td>\n",
       "      <td>19721</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>589</th>\n",
       "      <td>John Kasich</td>\n",
       "      <td>Immigration</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>Carson</td>\n",
       "      <td>Negative Campaigning</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>349</th>\n",
       "      <td>Evan Bayh</td>\n",
       "      <td>Jobs</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>863</th>\n",
       "      <td>Martin O'Malley</td>\n",
       "      <td>Immigration</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>585</th>\n",
       "      <td>John Kasich</td>\n",
       "      <td>Government regulation</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1311 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           cand_list               subjects  wp_identifier\n",
       "263     Donald Trump    Candidate Biography          46633\n",
       "396  Hillary Clinton    Candidate Biography          29889\n",
       "325     Donald Trump              Terrorism          21600\n",
       "424  Hillary Clinton            Health Care          20584\n",
       "308     Donald Trump               Military          19721\n",
       "..               ...                    ...            ...\n",
       "589      John Kasich            Immigration              1\n",
       "102           Carson   Negative Campaigning              1\n",
       "349        Evan Bayh                   Jobs              1\n",
       "863  Martin O'Malley            Immigration              1\n",
       "585      John Kasich  Government regulation              1\n",
       "\n",
       "[1311 rows x 3 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# unpivot subjects of Candidates and count subject frequency\n",
    "candidate_explode['subjects'] = candidate_explode['subjects'].str.split(', ')\n",
    "candidate_explode_contnet = candidate_explode.explode('subjects', ignore_index=True)\n",
    "candidate_contnet = candidate_explode_contnet.groupby(['cand_list', 'subjects'])[['wp_identifier']].count().reset_index()\n",
    "candidate_contnet.sort_values(by='wp_identifier', ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Analysis between gepgraphic reach and subjects\n",
    "loc_content = pd.merge(candidate_loc, candidate_contnet, on='cand_list', how='left')\n",
    "loc_content_count = loc_content.groupby('cand_list').agg({\n",
    "    'location': 'mean',       # Apply mean to 'location'\n",
    "    'subjects': 'nunique'     # Apply unique count to 'subjects'\n",
    "})\n",
    "loc_content_count.plot(x='location', y='subjects', kind='scatter')\n",
    "plt.xlabel('Count of Cities', fontsize = 14)\n",
    "plt.ylabel('Count of Subjects', fontsize =14)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Generating examples from two extreme\n",
    "hillary_data = loc_content[loc_content['cand_list'] == 'Hillary Clinton'].nlargest(10, 'wp_identifier')\n",
    "joy_data = loc_content[loc_content['cand_list'] == 'Roy Cooper'].nlargest(10, 'wp_identifier')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot top 10 subjects for Hillary Clinton\n",
    "plt.barh(hillary_data['subjects'], hillary_data['wp_identifier'], color='skyblue')\n",
    "plt.xlabel('Airing Count',fontsize = 14)\n",
    "plt.ylabel('Subjects',fontsize = 14)\n",
    "plt.title('Hillary Clinton',fontsize = 14)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot top 10 subjects for Roy Cooper\n",
    "plt.barh(joy_data['subjects'], hillary_data['wp_identifier'], color='skyblue')\n",
    "plt.xlabel('Airing Count',fontsize = 14)\n",
    "plt.ylabel('Subjects',fontsize = 14)\n",
    "plt.title('Roy Cooper',fontsize = 14)\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "base",
   "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": "3.12.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}