golos project.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 660,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "%matplotlib inline\n",
    "mpl.style.use('ggplot')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Две организации занимались контроллем за выборами в Беларуси Зубр и Голос. Зубр занимался наблюдением, а также собрали фото протоколов (в Беларуси не публикуют данные по каждому участку). На платформе голоса каждый, кто проголосовал, мог обозначить за кого и на каком участке. Причем на голосе нужно было пройти верификацию, так что их данным можно доверять.\n",
    "После выборов обе инициативы выпустили совместный отчет : https://drive.google.com/file/d/1kSprtBUUtS1vb-W_jc4QJkPkoZPJBWxd/view?usp=sharing, а также оцифровали фотографии всех протоколов : https://drive.google.com/file/d/1tMYku50vb6jBawXXrj2SRRHlRi_OA_vy/view"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 235,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = pd.read_csv('/Users/a1/Desktop/pandas data/dataup.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Я же к данным по изибирательным участкам (вторая ссылка) спарсил подтвержденные, по данным Голоса, голоса за Тихановскую на этих участках - колонка golosdata. Вероятность, что все проголосовавшие за Тихоновскую также обозначили свой выбор на Голосе стримится к нулю. Поэтому все участки, где на фото протокола голосов за Тихоновскую больше, чем по данным голоса, я отнес к участкам с честным подсчетом. А участки, где в протоколе голосов за Тихоновскую, меньше чем на Голосе, отнес к участкам с нечестным подсчетом.\n",
    "По итогу получилась табличка, где все участки классифицированны по признаку golos=true/false(последняя колонка), где golos=true/false=1 - это участки с честным подсчетом, а golos=true/false=0 c фальсификациями.  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 236,
   "metadata": {},
   "outputs": [],
   "source": [
    "data.drop(('Unnamed: 0'), axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 237,
   "metadata": {},
   "outputs": [],
   "source": [
    "data['golos=true/false']=data['golos=true/false'].astype('category')\n",
    "data['region'] = data['region'].astype('category')\n",
    "data['winner'] = data['winner'].astype('object')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 468,
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>region</th>\n",
       "      <th>district</th>\n",
       "      <th>city</th>\n",
       "      <th>number</th>\n",
       "      <th>voters</th>\n",
       "      <th>voterst</th>\n",
       "      <th>voteearly</th>\n",
       "      <th>votehome</th>\n",
       "      <th>votemainday</th>\n",
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       "      <th>tornout</th>\n",
       "      <th>lukashenkoper</th>\n",
       "      <th>tichanivskayaper</th>\n",
       "      <th>kanopackayaper</th>\n",
       "      <th>cherchenper</th>\n",
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       "      <th>maindaytornout</th>\n",
       "      <th>againstallper</th>\n",
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       "      <th>golos=true/false</th>\n",
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       "      <th>0</th>\n",
       "      <td>Брестская</td>\n",
       "      <td>Брест - Московский</td>\n",
       "      <td>Брест</td>\n",
       "      <td>3</td>\n",
       "      <td>1512.0</td>\n",
       "      <td>1482</td>\n",
       "      <td>547.0</td>\n",
       "      <td>25.0</td>\n",
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       "      <td>101.0</td>\n",
       "      <td>14.0</td>\n",
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       "      <td>Брестская</td>\n",
       "      <td>Брест - Московский</td>\n",
       "      <td>Брест</td>\n",
       "      <td>8</td>\n",
       "      <td>1570.0</td>\n",
       "      <td>1486</td>\n",
       "      <td>503.0</td>\n",
       "      <td>46.0</td>\n",
       "      <td>937.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>16</td>\n",
       "      <td>1058</td>\n",
       "      <td>147</td>\n",
       "      <td>42.0</td>\n",
       "      <td>191.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>94.649680</td>\n",
       "      <td>71.197845</td>\n",
       "      <td>9.892328</td>\n",
       "      <td>1.076716</td>\n",
       "      <td>2.826379</td>\n",
       "      <td>2.153432</td>\n",
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       "      <td>59.681530</td>\n",
       "      <td>12.853297</td>\n",
       "      <td>2.929936</td>\n",
       "      <td>34</td>\n",
       "      <td>95.0</td>\n",
       "      <td>32.0</td>\n",
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       "      <td>Брестская</td>\n",
       "      <td>Брест - Московский</td>\n",
       "      <td>Брест</td>\n",
       "      <td>17</td>\n",
       "      <td>1445.0</td>\n",
       "      <td>1223</td>\n",
       "      <td>339.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>854.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>10</td>\n",
       "      <td>856</td>\n",
       "      <td>136</td>\n",
       "      <td>12.0</td>\n",
       "      <td>191.0</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>85.0</td>\n",
       "      <td>23.0</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Брестская</td>\n",
       "      <td>Брест - Московский</td>\n",
       "      <td>Брест</td>\n",
       "      <td>20</td>\n",
       "      <td>1678.0</td>\n",
       "      <td>1595</td>\n",
       "      <td>593.0</td>\n",
       "      <td>96.0</td>\n",
       "      <td>906.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>17</td>\n",
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       "      <td>198</td>\n",
       "      <td>16.0</td>\n",
       "      <td>154.0</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>37</td>\n",
       "      <td>95.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>230</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Брестская</td>\n",
       "      <td>Брест - Московский</td>\n",
       "      <td>Брест</td>\n",
       "      <td>30</td>\n",
       "      <td>2126.0</td>\n",
       "      <td>1880</td>\n",
       "      <td>662.0</td>\n",
       "      <td>67.0</td>\n",
       "      <td>1151.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>22</td>\n",
       "      <td>1412</td>\n",
       "      <td>169</td>\n",
       "      <td>29.0</td>\n",
       "      <td>211.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>318.0</td>\n",
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       "      <td>1.170213</td>\n",
       "      <td>1.542553</td>\n",
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       "      <td>54.139230</td>\n",
       "      <td>11.223404</td>\n",
       "      <td>3.151458</td>\n",
       "      <td>35</td>\n",
       "      <td>88.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>258</td>\n",
       "      <td>0</td>\n",
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      ],
      "text/plain": [
       "      region            district   city  number  voters  voterst  voteearly  \\\n",
       "0  Брестская  Брест - Московский  Брест       3  1512.0     1482      547.0   \n",
       "1  Брестская  Брест - Московский  Брест       8  1570.0     1486      503.0   \n",
       "2  Брестская  Брест - Московский  Брест      17  1445.0     1223      339.0   \n",
       "3  Брестская  Брест - Московский  Брест      20  1678.0     1595      593.0   \n",
       "4  Брестская  Брест - Московский  Брест      30  2126.0     1880      662.0   \n",
       "\n",
       "   votehome  votemainday  dmitriev  kanopackaya  lukashenko  tichanovskaya  \\\n",
       "0      25.0        910.0      22.0           47        1150            127   \n",
       "1      46.0        937.0      32.0           16        1058            147   \n",
       "2      30.0        854.0      18.0           10         856            136   \n",
       "3      96.0        906.0      14.0           17        1196            198   \n",
       "4      67.0       1151.0      29.0           22        1412            169   \n",
       "\n",
       "   cherchen  againstall  falseblanc  brokedblanks  other    tornout  \\\n",
       "0      21.0       101.0        14.0           1.0   32.0  98.015880   \n",
       "1      42.0       191.0         NaN           NaN    NaN  94.649680   \n",
       "2      12.0       191.0         NaN           NaN    NaN  84.636680   \n",
       "3      16.0       154.0         NaN           NaN    NaN  95.053635   \n",
       "4      29.0       211.0         8.0           NaN  318.0  88.428980   \n",
       "\n",
       "   lukashenkoper  tichanivskayaper  kanopackayaper  cherchenper  dmitrievper  \\\n",
       "0      77.597840          8.569501        3.171390     1.417004     1.484480   \n",
       "1      71.197845          9.892328        1.076716     2.826379     2.153432   \n",
       "2      69.991820         11.120196        0.817661     0.981194     1.471791   \n",
       "3      74.984330         12.413794        1.065831     1.003135     0.877743   \n",
       "4      75.106384          8.989362        1.170213     1.542553     1.542553   \n",
       "\n",
       "   earlytornout  maindaytornout  againstallper   homeper  early/main  \\\n",
       "0     36.177250       60.185184       6.815114  1.653439          37   \n",
       "1     32.038216       59.681530      12.853297  2.929936          34   \n",
       "2     23.460207       59.100346      15.617334  2.076125          28   \n",
       "3     35.339690       53.992847       9.655172  5.721096          37   \n",
       "4     31.138288       54.139230      11.223404  3.151458          35   \n",
       "\n",
       "   rtronout  rearlytornout  golosdata golos=true/false winner  \n",
       "0      98.0           36.0        299                0      0  \n",
       "1      95.0           32.0        237                0      0  \n",
       "2      85.0           23.0        159                0      0  \n",
       "3      95.0           35.0        230                0      0  \n",
       "4      88.0           31.0        258                0      0  "
      ]
     },
     "execution_count": 468,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.set_option('display.max_columns', 100)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "На уровне участковой избирательной комиссии есть три вида фальсификаций: вброс на досрочном голосовании, переписывание протокола и переброс голосов к другому кандидату. На участках, где посчитали честно остается только один способ: нарисовать досрочную явку. Что, собственное, и видно на графике зависимости процента Лукашенко и Тихановской от досрочной явки. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 662,
   "metadata": {},
   "outputs": [
    {
     "data": {
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     "execution_count": 662,
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\n",
      "text/plain": [
       "<Figure size 720x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax0=data[data['golos=true/false']==1].plot(kind='scatter', x='earlytornout', y='lukashenkoper' , figsize=(10, 7),  alpha=0.5,color='green')\n",
    "ax1=data[data['golos=true/false']==1].plot(kind='scatter', x='earlytornout', y='tichanivskayaper' , figsize=(10, 7), alpha=0.5, color=\"blue\", ax=ax0)\n",
    "ax0.set_ylabel('досрочная явка')\n",
    "ax0.set_xlabel('процент кандидата')\n",
    "ax0.legend(['Lukashenko', 'Tichanovskaya'], loc='upper right', fontsize='x-large')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 663,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x12641b550>"
      ]
     },
     "execution_count": 663,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax0=data[(data['golos=true/false']==1)& (data['district']!= 'Зарубежный')].pivot_table('lukashenkoper', index='rearlytornout', aggfunc='mean').plot(marker='o',linestyle='none', figsize=(10, 7), color='green', alpha=0.5)#kind='scatter', x ='rearlytornout', y='lukashenkoper')\n",
    "ax1=data[(data['golos=true/false']==1)& (data['district']!= 'Зарубежный')].pivot_table('tichanivskayaper', index='rearlytornout', aggfunc='mean' ).plot(marker='o',linestyle='none',figsize=(10, 7), ax=ax0, color='blue', alpha=0.5)\n",
    "ax0.set_xlabel('досрочная явка')\n",
    "ax0.set_ylabel('средний процент кандидата на всех участках с данной явкой')\n",
    "ax0.legend(['Lukashenko', 'Tichanovskaya'], loc='upper right', fontsize='x-large')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 592,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1226157c0>"
      ]
     },
     "execution_count": 592,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax0 = datal.plot(kind='scatter',x='rearlytornout',y='lukashenkoper',figsize=(14, 8),alpha=0.5, s=s1/90,color='green')\n",
    "\n",
    "ax1 = datat.plot(kind='scatter',x='rearlytornout', y='tichanivskayaper',alpha=0.5,color=\"blue\",s=s2/90,ax = ax0)\n",
    "ax0.set_xlabel('досрочная явка')\n",
    "ax0.set_ylabel('средний процент кандидата на всех участках с данной явкой')\n",
    "ax0.legend(['Lukashenko', 'Tichanovskaya'], loc='upper right', fontsize='x-large')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Размер точки соответствует кол-ву голосов отдданных за кандидата на участках с данной явкой"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "На графике зависимости кол-ва выигранных участков каждым кандидатом от досрочной явки видно что анамалии начинаются от 20%, немного выравнивается на 24-25%, а дальше уходят в отрыв.\n",
    "Так же досрочную явку проанализировал Сергей Шпилькин и тоже пришел к выводу реальная досрочная явка это 24% по среднему занчению или 20% по медиане.\n",
    "https://www.facebook.com/notes/778234429682058/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 670,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x127852ac0>"
      ]
     },
     "execution_count": 670,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = data[(data['winner']==0)  &  (data['golos=true/false']==1)].pivot_table('winner', index='rearlytornout', aggfunc='count' )\n",
    "x=x.rename(columns={'winner':'winner=0'})\n",
    "x = x.reset_index()\n",
    "x = x.merge(data[(data['winner']==1)  &  (data['golos=true/false']==1)].pivot_table('winner', index='rearlytornout', aggfunc='count' ).rename(columns={'winner':'winner=1'}).reset_index(), how='outer' )\n",
    "x = x.fillna(0)\n",
    "x = x.sort_values('rearlytornout')\n",
    "ax0 = x.plot(kind='bar', x='rearlytornout',y='winner=0', color='blue', alpha=0.5,figsize=(12,8))\n",
    "ax1 = x.plot(kind='bar', x='rearlytornout',y='winner=1', color='green', alpha=0.5,figsize=(12,8), ax=ax0)\n",
    "ax0.set_ylabel('кол-во выигранных кандидатом участков с данной явкой')\n",
    "ax0.set_xlabel('досрочная явка')\n",
    "ax0.legend(['Lukashenko', 'Tichanovskaya'], loc='upper right', fontsize='x-large')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Зная реальную досрочную явку нужно постараться вычленить участки без вбросов. Тут у меня первая загвоздка. Тк я пока не придумал по какому признаку вычленить участки без вбросов. Поэтому просто руками довел медиану до 20%. В этот моменте мне очень нужна помощь."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 255,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "20.0254315"
      ]
     },
     "execution_count": 255,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[(data['golos=true/false']==1) & (data['earlytornout'] < 29.4) ].earlytornout.median()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1085fc370>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data[(data['golos=true/false']==1) & (data['earlytornout'] < 29.4) ].rearlytornout.hist(bins=15)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 594,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x11fb08f70>"
      ]
     },
     "execution_count": 594,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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27SrHLC8vD8OHD8fIkSMhiiJu3ryJWbNmITo6GpGRkXjyySexadMm2Gw2AMCJEyeqjGHPnj1o3749CgsLAQCrVq1Cnz59EBkZie7du2PRokXIz8+/9z9gLVWbhBmNRkyaNAkAcPToURw9ehTHjx9HYGAgBg4ciI8//hizZ8+WJSgiIiJXMRjUEAQrBMEGpRIQBBsEwQqDQe3q0Bxcu3YNw4cPhyiK2LZtG44cOYKEhAT7BAoAWK1WrFy5EitWrMDhw4chCAKee+45lJaWz+rZbDZoNBps2LABn376KZYvX449e/Zg/fr1DvfKycnBjh07sGHDBhw4cAD5+fmYP3++/bzRaMTkyZPRo0cPfPTRR3jttdeQnp6ORYsWAQCeeOIJNGnSBH//+98drvv+++/jd7/7HQRBwKFDh5CSkoLly5fjs88+w65du9CvX78qP7vJZMIf/vAHNGnSBDt37oQgCLBYLOjYsSO2bt2KTz75BHPmzEFSUhL27NkDAOjVqxdat26NtLQ0h2vt2rULw4cPR0BAAABArVbj1Vdfxaeffork5GR8/vnn+Otf/1qbf6L7qjatf+KJJ+yvjx8/ftd51oYREZEnMpl8EB5udTgWGGiDyeTjooiq9vbbb0OhUGDbtm3w9/cHAERERDh8j81mw/Lly9GtWzeUlpZiwYIFGDZsGLKystC2bVsolUp7ogQALVu2RFZWFrZv344FCxbYj1ssFqxbtw6hoaEAgBkzZmDGjBkoLi6GWq3Gxo0bERUVheXLlwMA2rVrhxUrVuBPf/oTFi1ahBYtWmDkyJF4//33MWvWLACA2WxGRkYGtmzZAgDIzs5GWFgY+vXrh0aNGkGr1aJz5853fW6j0Yinn34av//977FixQp70tmkSRPMmDHD/n0PPfQQvv32W+zbtw9jxowBAIwfPx5btmzBnDlzoFQq8eOPP+LLL7/E0qVL7e+bM2eOw3gsXrwY06dPR3JyskOC6wyS5lYrB0dEROTJtNoyiKISgmCzHysoUECrLXNhVHc7e/Ysunfvbk/AqqJQKKDT6exfN2vWDEB5AtS2bVsAwP/7f/8Pu3btwqVLl1BUVISysjJYrY5JaNOmTe0JWMV1bDYbcnNzodVqkZmZiV69ejm8p2fPnrDZbMjMzESLFi0wevRopKSk4JtvvkHXrl2xf/9+BAcHo2/fvgCAoUOHYuvWrejRowd69+6NJ554AgMHDrTPUAFAbm4uRo4cibFjx2LJkiUO97NarXjjjTdw4MABXLlyBSUlJSgtLXV46OGPf/yjfZarf//+2LlzJ3Q6Hbp27Wr/nkOHDmHz5s3IyspCQUEBrFYrLBYLrl27Zh8/Z5Gc0hUWFiIjIwP79u1DRkaGfe2UiIjIk+j1xRBFJURRAasVEEUFRFEJvb7Y1aHdRaFQ3PO8UqmEj8+vM3gV31+RZB08eBAvvPAChg4dinfeeQeHDx/GnDlzcOfOHYfr+Pr6VnnfysladbFUHG/Xrh26dOmCvXv3AgD27t2LESNGQKUqnw8KDw9HRkYGkpKSoNFo8Nprr6F3794ONVxBQUF47LHHcPjwYYfaOABITU3Fhg0bMGXKFOzevRsfffQRxo4d6/BZgoODMWjQIOzcuRN37tzB3r17MX78ePv5r7/+GvHx8ejRowc2b96MDz/8EKtWrQKAu8bEGSQlYZmZmZg1axY+/vhjXLx4Eenp6Zg1axYyMzOdHhAREZEr6XSliI8vhCBYceWKEoJgRXx8oaxPR9ZGVFQUTp06ZS9+r41//etf6Ny5M+Lj4/HII4+gTZs2yM7OrvF12rdvjy+++MLh2BdffAGFQoH27dvbj40aNQoHDhzA+fPncfbsWYwePdrhPX5+fujXrx9efPFFHDlyBLdv38bhw4ft5xs1aoTNmzfj4YcfxqhRoxxi/eKLL9C3b1+MHTsWnTt3RuvWrfHzzz/fFevTTz+Njz/+GO+88w6Kiorw1FNP2c99+eWXCAkJwaJFi/Cb3/wGkZGRuHLlSo3HQypJy5Fvv/02pk6d6jDVePLkSWzbtg0rV66ULTgiIiJX0OlKodO594rPM888g3fffReTJ0/GggUL0LRpU1y4cAE+Pj7o37+/pGtERkZi165dOHz4MDp06ID09HQcOnSoxrFMmzYNAwcOxLJlyzBhwgRcunQJL774Iv7whz84LAeOGDECL730EubOnYuHH34YnTp1sp/btWsXrFYrunbtCkEQ8Nlnn6GwsBDt2rVzuFejRo2wadMmzJw5EyNHjsSePXvQqlUrREZG4v3338eJEyfQrFkz7N27F6dPn76rpdZjjz2GyMhIvPzyyxgxYgSCgoIcxiM3Nxe7du3C448/ji+//BLbt2+v8XhIJWkm7MqVK4iJiXE41rNnT1y9elWWoIiIiOjemjZtin379iEgIABPP/00+vXrh8TERHtLBikmTJiAkSNHYt68efj973+P06dPOzz1KJVOp8O2bdvwxRdf4Le//S1mz56NAQMGIDEx0eH7QkJCMGDAAJw/fx6jRo1yOCcIAtLS0jB69Gj06dMHb775Jl599VU8+eSTd91PpVIhJSUFjz32GEaOHImffvoJc+bMQc+ePTFlyhQMGzYMoihiypQpVcY7btw4WCwWh6VIAPbYV61ahQEDBuAf//iHbE9GAoDCJuFfa/HixRg8eLDDE5MnTpzAwYMH7Wul9el/14GdTaPRwGw2y3oPb8bxlQ/HVl4cX/k4a2yLioruWajurVQqlb0tBQErVqzAJ598giNHjtT5WiqVCvn5+dX+3N2rm4Sk5chJkyZh1apVMBgM0Gg0uH79Oq5cuYLnn3++dhETERER1bP8/Hx8//332Llzp1t0fpCUhHXo0AHr16/H119/jby8PDz66KP4zW9+4/DYKBEREZE7mzJlCk6fPo2hQ4fe9VCAK0jegyEgIAC9e/eWMxYiIiIi2VS0x3AXkpKwig64VXGH6TwiIiKihkZSElbxZILNZsPbb7+NyZMnyxoUERFRbdTkyUAiZ6ntz52kJKxyv5F3331Xcv8RIiKi+maz2e7bSZ7IWeqS+Dt3J0oiIiIX8vX1RUlJiavDIC9hs9lw+/ZtqNXqWr1f0kzYuXPn7K+tVqvD11XtcF6VDz74AEePHoVCoUDLli0xffp0WCwWJCcn4/r16wgLC8PcuXP5xCUREdVao0aNUFZWhlu3bnE2rBI/Pz8mp05WMQMWHh6O/Pz8Wl1DUhK2ceNG++uAgAD71wqFAhs2bLjv+2/cuAGDwYDk5GT4+vpi7dq1OHnyJLKzsxEVFYURI0Zg//792L9/PyZMmFCrD0JERASg1rMSnoyNhuXzv5ub14SkJCwlJaXWN6hgtVphsVjg4+MDi8WC4OBg7Nu3D8uWLQMA9OnTx77nFBEREZGnk9wnrC5CQkIwdOhQTJs2Db6+vujSpQu6dOkCURQRHBwMAAgODq71dB4RERFRQyMpCZsxY0a1a+tSliMLCwtx6tQppKSkwN/fH2vXrsWxY8ckB5meno709HQAwKpVq6DRaCS/tzZUKpXs9/BmHF/5cGzlxfGVD8dWXhxf+dRlbCUlYc899xyA8iK0NWvWICEhoUY3OXv2LJo0aYKgoCAAQI8ePZCZmQlBEJCXl4fg4GDk5eXZz/+v2NhYxMbG2r+We12ba+fy4vjKh2MrL46vfDi28uL4yud+Y1vnDbyjoqLsr318fBy+lkKj0eCHH35ASUkJfH19cfbsWURGRsLPzw8ZGRkYMWIEMjIyEB0dXaPrEhERETVU9VIT1q5dO/Ts2ROLFi2Cj48PIiIiEBsbi+LiYiQnJ+Po0aPQaDSYN29efYRDRERE5HKSkrCjR4/aX5eWljp8LbV7/h//+Ef88Y9/dDjWqFEjLFmyRNL7iYiIiDyJpCTs+PHj9tdt27Z1+JpbGBERERHVnKQkbOnSpXLHQURERORValwTZrPZHDarVCq5/SQRERFRTUlKwm7cuIEtW7bgu+++w61btxzOpaWlyRIYERERkSeTNI315ptvQqVSYcmSJVCr1UhMTET37t3xf//3f3LHR0REROSRJCVhmZmZmDZtGiIiIqBQKBAREYFp06bhgw8+kDs+IiIiIo8kKQlTKpXw8fEBADRu3Bj5+fnw8/PDjRs3ZA2OiIiIyFNJqglr27YtTp8+jcceewxdunRBcnIyfH19ERkZKXd8RA6MRhUMBjVMJh9otWXQ64uh05W6OiwiIqIakzQTNmvWLOh0OgDApEmT0LlzZ7Rs2RKzZ8+WNTiiyoxGFVJTAyCKSoSHWyGKSqSmBsBorJeNH4iIiJxK0m+vxo0b21/7+vpi5MiRsgVEVB2DQQ1BsEIQyluklP9thcGghk5X6NrgiIiIakhSEnbu3LkqjycmJqJDhw4ICgrirBjJzmTyQXi41eFYYKANJpOPiyIiIiKqPUlJ2Msvv4ywsDCHJq0AcOfOHbz44ouyBEaep6Key2z2gUYTUON6Lq22DKKotM+EAUBBgQJabZkc4RIREclKUhLm5+eHDRs23HX8mWeecXpA5Jkq6rkEwYoWLYCcnPJ6rvj4QsmJmF5fjNTUAABWBAbaUFCggCgqERdXJG/wREREMpBUmK9QKOSOgzxc5XoupbK8nksQyuu5pNLpShEfXwhBsOLKFSUEwVqjJI6IiMidSJoJKy4uxqxZs6BSqRAUFIRWrVqhV69ecsdGHsRZ9Vw6XSmL8ImIyCNISsJefPFF2Gw2WCwW3Lx5E1lZWVi9ejWKi4vljo88BOu5iIiIHElKwqKiou469tRTT2HGjBmYOXMmgoOD8fLLLzs9OPIcleu51GpAFFnPRURE3q3WXS5DQkKwa9cuZ8ZCHqyinstgUCM7G9BorIiLK2I9FxEReS22Gqd6U1HPpdGoYTazrouIiLybpKcjiYiIiMi5mIQRERERuQCTMCIiIiIXkJSEbd26FRcuXHA4duHCBbz99ttyxERERETk8SQlYSdOnEBkZKTDsTZt2uCzzz6TJSgiIiIiTyd52yKr1bHbudVqvWtDbyIiIiKSRlIS1rFjR+zevdueiFmtVrz33nvo2LGjrMEREREReSpJfcImT56MVatWIT4+HhqNBmazGcHBwVi0aJHc8RERERF5JElJWGhoKBITE/Hjjz8iNzcXoaGhaNu2LZRKPlxJREREVBuSO+YrlUq0b99ezliIiIiIvAansoiIiIhcgEkYERERkQswCSMiIiJyAUlJmNForPI4m7USERER1Y6kJCwpKQnvvvsuSktLAQC3bt1CcnIy3nvvPVmDIyIiIvJUkpKw1atX4+LFi1i8eDGOHj2KBQsWoHHjxkhMTJQ7PiIiIiKPJCkJCwkJQUJCAmw2G1JTU9G1a1c8++yzUKvVcsdHRERE5JEkJWFZWVl4/vnn0aRJEyxcuBDnzp3Da6+9hlu3bskdHxEREZFHkpSEvfTSSxgyZAgWLlyIRx99FKtXr4afnx8WLFggd3xEREREHklSx/yVK1eiadOm9q/VajWmTZuGr776SrbAiIiIiDyZpJmwyglYZd27d3dqMERERETeQtJMWFFREd577z0YjUYUFBTAZrPZz23cuFG24IiIiIg8laSZsM2bN+Pnn3/GqFGjUFhYiClTpkCj0WDw4MFyx0dERETkkSQlYWfOnMH8+fMRHR0NpVKJ6OhozJ07F8ePH5c7PiIiIiKPJCkJs9ls8Pf3B1BelH/r1i08+OCDuHr1qqzBEREREXkqSTVhrVq1gtFoRFRUFDp27IgtW7ZArVYjPDxc7viIiIiIPJKkmbD4+HiEhYUBAKZMmQJfX1/cunULM2fOlDU4IiIiIk8laSascouKoKAgPPfcc7IFREREROQNJM2Eff3113cdu3btGl5++WWnB0RERETkDSQlYW+99ZbDk5AGgwGLFy9Gt27dZAuMiIiIyJNJWo5cunQpXnnlFVy9ehXnzp0DAKxYsYKF+URERES1JGkmrFmzZnjppZfw5Zdfwmq1Yvny5UzAiIiIiOpA0kzY0aNHAQC9e/fGnj17sHHjRnTo0AEA0L9/f/miI5KJ0aiCwaCGyeQDrbYMen0xdLpSV4dFREReRFISVrkerG3btrh27RquXf63ZsoAACAASURBVLsGgEkYNTxGowqpqQEQBCvCw60QRSVSUwMQH1/IRIyIiOqN5JowIk9hMKghCFYIQvlG9OV/W2EwqKHTFbo2OCIi8hqSasJWrlwpdxxE9cZk8kFgoM3hWGCgDSaTj4siIiIibyRpJuz777+XOw6ieqPVlkEUlfaZMAAoKFBAqy2r0XVYV0ZERHUhaSbMarXi2rVryMnJuesPUUOj1xdDFJUQRQWsVkAUFRBFJfT6YsnXqKgrE0WlQ12Z0Sjp/9cQERFJmwmzWCyYNWtWlefS0tKcGhCR3HS6UsTHFzrMYsXFFdVoFot1ZUREVFeSkjC1Wo3t27fLHQtRvdHpSuuULJlMPggPtzocY10ZERHVhKTlSJvNdv9vIvIiWm0ZCgoUDsdqU1dGRETeS1IS1rdvX5nDIGpYnFFXRkRE3k1SEta/f3+YzWaHY2azGVlZWXLEROT2KurKBMGKK1eUEAQrm70SEVGNSKoJW79+PRYuXOhwrLS0FBs2bMCaNWtkCYzI3dW1royIiLybpJkws9mMpk2bOhxr1qwZrl+/LktQRERERJ5OUhIWEhKCn376yeHYTz/9hODgYFmCIiIiIvJ0kpYjBw8ejNWrV2PYsGFo2rQpcnJycPDgQTz11FNyx0dERETkkSQlYbGxsWjcuDGOHj2K3NxchIaGYuLEiejZs6fc8RERERF5JMl7rMTExCAmJkbOWIiIiIi8huQk7ObNm/jxxx9RUFDg0Ly1f//+sgRGRERE5MkkJWFffvkl1q9fj/DwcFy6dAktW7bEpUuX0LFjRyZhRERERLUgKQlLS0vD9OnTERMTg8mTJ+PVV1/FJ598gkuXLskdHxEREZFHktwn7H/rwfr06YNjx47JEhQRERGRp5OUhAUFBeHmzZsAgLCwMGRmZiInJwdWq1XW4IiIiIg8laTlyAEDBuD7779Hz549MXjwYCxfvhwKhQJDhgyRfKNbt25h06ZNuHTpEhQKBaZNm4bmzZsjOTkZ169fR1hYGObOnYuAgIBafxgiIiKihkJSEjZixAj76z59+qBTp04oLi5GixYtJN9o27Zt6Nq1K+bPn4/S0lKUlJRg3759iIqKwogRI7B//37s378fEyZMqPmnICIiImpgJC1H/i+NRlOjBKyoqAjfffed/UlKlUqFxo0b49SpU+jTpw+A8uTu1KlTtQmHiIiIqMGRNBM2bdq0as9t3Ljxvu+/du0agoKC8MYbb+DixYto06YNJk2aBFEU7ftPBgcHIz8/v8r3p6enIz09HQCwatUqaDQaKWHXmkqlkv0e3ozjKx+Orbw4vvLh2MqL4yufuoytpCRs1qxZAACbzYbExEQ8//zzNbpJWVkZfv75Z0yZMgXt2rXDtm3bsH//fsnvj42NRWxsrP1rs9lco/vXlEajkf0e3ozjKx+Orbw4vvLh2MqL4yuf+41t8+bNqz0nKQnT6XT21z4+Pg5fSxEaGorQ0FC0a9cOANCzZ0/s378fgiAgLy8PwcHByMvLQ1BQUI2uS0RERNRQ1agm7OLFi1CpJO90ZPfggw8iNDQUly9fBgCcPXsWLVq0QPfu3ZGRkQEAyMjIQHR0dI2vTURERNQQSa4Js9lsEEURo0aNqtWNpkyZgnXr1qG0tBRNmjTB9OnTYbPZkJycjKNHj0Kj0WDevHm1ujYRERFRQ6OwVd6NuxpGoxEKhQKhoaFo0qRJfcR1TxUzanLh2rm8OL6OjEYVDAY1TCYfaLVl0OuLodOV1upaHFt5cXzlw7GVF8dXPnWpCZO0HFlUVIT27du7RQJG5EmMRhVSUwMgikqEh1shikqkpgbAaKz5sj8RETUskpKwtLQ0PPvss9iyZQt++OEHuWMi8hoGgxqCYIUg2KBUAoJggyBYYTCoXR0aERHJTNL/3V69ejWysrJw/PhxJCUlwc/PD71798aTTz7J2TGiOjCZfBAe7rgHa2CgDSaTj4siIiKi+iJ5zSMiIgIRERGYMGECzp49i3feeQd79uxBx44dERsbi169ekGprFUDfiKvpdWWQRSVEIRfSzMLChTQastcGBUREdWHGmVNV69exd69e7F582ZYLBaMGTMGAwYMwIcffoi1a9fKFSORx9LriyGKSoiiAlYrIIoKiKISen2xq0MjIiKZSZoJ+/DDD3H8+HFcvXoVMTExmDlzJtq3b28/36NHD0ydOlW2IIk8lU5Xivj4QoenI+Piimr9dCRRfTLmGmHIMsBUaII2QAt9hB660Jo18ybyZpKSsG+++QZDhgxBdHR0lc1a/fz8sGDBAqcHR+QNdLpS6HSFrg6DqEaMuUaknkmF4CcgvHE4xBIRqWdSEf9IPBMxIokkJWFS9ors0qVLnYMhoobPmX3PyH0ZsgwQ/AQIfgIA2P82ZBmYhBFJxEp6InIa9j3zHqZCEwJ9Ax2OBfoGwlRoclFERA0PkzAichr2PfMe2gAtCiwFDscKLAXQBmhdFBFRw8MkjIicxmTyQWCg405o7HvmmfQReoglIsQSEVab1f5aH6F3dWhEDYakJKygoKDK41evXnVqMETUsGm1ZSgoUDgcY98zz6QL1SH+kXgIfgKu3LoCwU9gUT5RDUkq1Jg/fz6mTZuGbt262Y999NFHSEtLw5YtW2QLjogaFr2+GKmpAQCsCAy0oaCgvO9ZXFyRq0MjGehCdUy6iOpAUhI2bdo0bNq0CdHR0RgyZAi2bt2KvLw8LFmyRO74iKgBYd8zIqqOM/rKeVpvOoXNZrPd/9uAwsJCLFu2DJcuXUKvXr0wffr0KnuG1YfLly/Len2NRgOz2SzrPbwZx1c+HFt5cXzlw7GVl6vHt3JfuUDfQBRYCiCWiDVawnbGNeRwv7Ft3rx5teck1YQVFxdjx44dKCoqwuDBg3H69Gl8+umnNQ6UiIiIvE/lvnJKhdL+2pBlqNdruBtJU1kJCQlo37491qxZA39/f/Tu3Rvr16/HqVOnsHjxYrljJCIiogbMVGhCeONwh2M17SvnjGu4G0lJ2NixY/H444/bv46IiMDKlSuxa9cu2QIjIiIi13NGHZY2QAuxRLTvrADUvK+cM67hbiQtR1YkYFarFXl5eQAAX19fPPPMM/JFRkT1zmhUISkpAPPmCUhKYqd7Im9XUYcllogOe4Qac401uo4z+sp5Ym86SUnYrVu38Prrr2P8+PGYPXs2AOCrr77C7t27ZQ2OiKSpSJ7+7/98ap08ccshIvpfzqrDckZfOU/sTSfpv65vvfUWGjdujDfeeAPz5s0DALRv3x47duxAXFycrAES0b1VJE+CYEWLFkBOTnnyFB9fWKPWEJW3HALw37/LtxzS6Qplip6IquIurRicWYfljL5yzupN5y7jK2km7OzZs5g8eTKCg4Ptx4KCgiCKomyBEZE0ztqvkVsOEbkHZy0BOoMn7hHqTuMrKQnz9/e/a+sis9nskJQRkWs4K3lyty2HWJ9G3sqdWjF4Yh2WO42vpCRswIABSEpKwrlz52Cz2ZCZmYmUlBT89re/lTs+IroPZyVPen0xRFEJUVTAagVEsXzLIb2+2JnhSsL6NPJmpkITAn0DHY65qhWDJ9ZhudP4Svov2vDhw9GoUSNs2bIFZWVl2LhxI2JjYzFo0CC54yOi+6i8X6Na/WvyVNP9Gt1pyyHWp5E3c7dWDJ62R6g7ja+kJEyhUGDw4MEYPHiw3PEQUQ1VTp6yswGNxlrr5EmnK3WLJMdk8kF4uNXhGOvTSG7uUqytj9Aj9UwqADhszxPXoeYPwlV8JvMdMzSNNA1+r0VncOb41pWk5cj9+/fjxx9/dDj2448/4sCBA7IERUQ1o9OVYv78Qrz1Vhnmz6/ZU5HuyN3q08jzuVOxtrOWACt/phZBLVz6mdyJOy2xSpoJO3ToEAYOHOhwrEWLFli9ejWGDx8uS2BE5L0qL7EGBtpQUFC7JVYiqSoXawOw/23IMrjkl7MzlgCrKkCvOO7ts2HussQqKQkrLS2FSuX4rSqVChaLRZagiMi7uVN9mrsxGlUO46LXF3NcnMAT9yX0xM/kaSQlYW3atMHhw4cdasI++ugjtGnTRrbAiMi7uUt9mjup3Ji38lOjNW3MS3dzp2JtZ/HEz+RpJCVhzzzzDFasWIFjx46hadOmyMnJwc2bN/HXv/5V7viIiOi/+NSofNypWNtZKn8m9QNqe4+vhvyZPI2kJKxly5Z4/fXX8e9//xu5ubno0aMHHn30UajVNevITUREtcenRuVTUaxd+enIuA5xblE3VFuVP1N2fjY0fpoG/5k8jeTOh2q1Gr169QIA3LlzB6WlnPomIqpPWm0ZRFFpnwkD+NSoM3navoTAr59Jo9HAbDa7JAaqnqQWFUajEYsXL8Yrr7yC8+fP49lnn8XkyZNx9OhRueMjIqL/cqddDahq7tTqgtyfpJmwrVu3omfPnrBarVizZg0SEhKgUCjwxhtvoH///nLHSERE4FOjDYG7tbog9yYpCbt27RpGjRoFq9WKgwcPQqcr/0HKz8+XNTgiorrwxHYOfGrUvbEtBNWEpOVIhUIBm628BkGlUsFms8Fqtd7nXURErsNNwMkVtAFaFFgKHI6xLQRVR9J/jYqLixEX9+sjrZVfExG5I7ZzqJ47FY57Gk9sdUHykZSEbdiwQe44iIiciu0cqlZROC74CQ6F467aO8/TeGKrC5KPpCQsLCxM7jiIiJyK7RyqxsJx+bnLvoTk/iTVhBERNTRs51A1U6EJgb6BDsdYOE7kGqxQJSKPxHYOVfPU/QRZ50YNEZMwIvJY7tTOwV3aZXhi4Tjr3Kih4nIkEZHM3KldRkXhuOAn4MqtKxD8hAafrFSuc1MqlPbXhiyDq0MjuidJ/wUoKyvD4cOHYTQaUVDg2P9k+fLlsgTmChXT2eY7ZmgaaTidTURO4W7tMjytcJwNUqmhkjQTtn37dqSnp0On0+Gnn35Cjx49IIoiOnXqJHd89abyfl8tglpwvy8ichqTyQeBgTaHY2yX4TxskEoNlaQk7F//+hf+8pe/YNCgQfDx8cGgQYOQkJCA8+fPyx1fveF0NhHJRastQ0GBwuEY22U4jz5CD7FEhFgiwmqz2l/rI/SuDo3oniQlYRaLBaGhoQAAX19flJSUQKvVIisrS87Y6hUf2yYiubBdhrw8sc6NvIOkmjCtVov//Oc/aNu2Ldq0aYP33nsPDzzwAEJCQuSOr9546mPbROR6bJchP0+rcyPvICkJmzRpEpTK8kmzZ555Bps3b8bt27fx7LPPyhpcfar82Lb6AbV9OrshP7ZNRM5R0V7CbPaBRhNQq/YS7tQug4jcg8Jms9nu/23u5fLly7Jcl09H1g+NRgOz2ezqMDwSx9b5KtpLCIIVTZs+gJyc2xBFJeLjCzmT5UT82ZUXx1c+9xvb5s2bV3tO0kyY0Vj9E4I6neckKRXT2fxhJaIKldtLKJWuby9BRJ5DUhK2fv16++u8vDwEBwfbv964caPzoyIichMmkw/Cw60Ox9hegoicQVISVjnRmjx5MhMvIvIaWm0ZRFFpb7QKsL0EETkHty0iIroHtpcgIrkwCSMiuoeK9hKCYEV2NiAIVhblE5FTSFqOXLJkCRSK8m7PxcXFWLp0qf2cJ+0dSURUpaZngL4G4I4ZaKQBmuoBeM5DSa70wecXsW1vPq7nPICwprcxeVQQhsS0cnVYRPVCUhLWv39/++t+/frJFgwRkbup2FdW8BPQ4sEWyLmZg9QzqezI7gQffH4Rf0suQYDgg2bN7yAvzwd/Sy4BcJGJGHkFSUlY3759ZQ6DiMg9VbWvbMVxJmF1s21vPgIEHwQFlUGpbISgoNL/Hi/BkBgXB0dUD1gTRkR0D9xXVj5XL/siIMCxti4goBRXL/u6KCKi+iVpJoyIyFs5a1/Zih05TIUmaAO03JEDQLPmFuTnqxAU9Gu7j8JCFZo1t7gwKqL6w5kwIqJ70Efo7XvJWm1W+2t9hF7yNSrqysQSEeGNwyGWiEg9kwpjbvW7kXiDyaOCUCiqkJ/vA6vVhvx8HxSKKkweFVTjaxmNKiQlBWDePAFJSQEwGjnHQO6PSRgR0T3oQnWIfyQegp+A7PxsCH5CjYvyq6orE/wEGLIMMkbu/obEtMILc/0QFFSGq5cbISioDC/M9atxUX7F/p6iqER4uBWiqERqKhMxcn+Sf0KzsrLw3XffoaCgAJX3/B4zZowsgRERuYu67itrKjQhvHG4wzHWlZUbEtMKQ2LqtsF05f09Ae7vSQ2HpCQsPT0d27dvxyOPPIJvvvkGXbt2xZkzZ9C9e3e54yMiavCcVVdGVeP+ntRQSVqOPHDgAP7yl78gISEBvr6+SEhIwLx58+Djwx9wIqL7cUZdGVVPqy1DQYHC4Rj396SGQFISlp+fj4cffhgAoFAoYLVa0a1bN/z73/+WNTgiIk9Qua7syq0rtaoro+pxf09qqCQtR4aEhODatWto0qQJwsPD8dVXXyEwMBAqFYseiYikqKgrI+er2N/TYFDDZPKBVluGuLgi7u9Jbk9SFjV8+HCYTCY0adIEo0aNwtq1a1FaWorJkyfLHR8REdF96XSlLMKnBqfG2xZ169YN27ZtQ2lpKdRqtVxxERGRTIxGlcOskV5fzFkjIheQVBO2cuVKh69VKhUTMCKiBog9tYjch6T/1X3//fdyx0FE5HTcKuhu7KlF5D4kJWFWqxXXrl1zaNJaoWnTppJvZrVa8fzzzyMkJATPP/88CgsLkZycjOvXryMsLAxz585FQECA9OiJiKpRsVWQ4Cc4bBXk7U8lsqcWkfuQlIRZLBbMmjWrynNpaWmSb3bo0CFotVrcvn0bALB//35ERUVhxIgR2L9/P/bv348JEyZIvh4RUXUqbxUEwP63Icvg1UmYVlsGUVTaZ8IA9tQichVJSZharcb27dvrdKPc3Fx8/fXXeOqpp/DBBx8AAE6dOoVly5YBAPr06YNly5YxCSMip+BWQVXT64uRmhoAwIrAQBsKCsp7asXFFbk6NCKvI6kwv6plyJp6++23MWHCBCgUv3Y1FkURwcHBAIDg4GDk5+fX+T5ERED5VkEFlgKHY9wq6NeeWoJgxZUrSgiCFfHxhXw6ksgFatyiojb+/e9/QxAEtGnTBufPn6/x+9PT05Geng4AWLVqFTQaTZ3iuR+VSiX7PbwZx1c+HNtfjes6DslfJkOtVEPwEyCWiChWFGNa12m1HiNPGd/evcv/lGsEwPVPu3vK2Lorjq986jK2kpKwKVOm1OriFS5cuICvvvoKp0+fhsViwe3bt7Fu3ToIgoC8vDwEBwcjLy8PQUFBVb4/NjYWsbGx9q/NZnOd4rkfjUYj+z28GcdXPhzbX4X7hGNS+0kwZBnwn+v/gTZAi0ntJyHcJ7zWY8TxlQ/HVh4VPeHM5sbQaIrZE04G9/vZbd68ebXnJCVhRUVFeO+992A0GlFQUOCwPLlx48b7vn/cuHEYN24cAOD8+fM4ePAgZs+ejXfeeQcZGRkYMWIEMjIyEB0dLSUcIiJJuFUQebOKnnCCYEWLFkBOTnlPOC4/uw9JNWGbN2/Gzz//jFGjRqGwsBBTpkyBRqPB4MGD63TzESNG4MyZM5g9ezbOnDmDESNG1Ol6REREVK5yTzilsrwnnCCU94Qj9yBpJuzMmTNITk5GYGAglEoloqOjERkZicTERAwZMqRGN+zUqRM6deoEAAgMDMSSJUtqHjURERHdE3vCuT/JT0f6+/sDKG9XcevWLTz44IO4evWqrMERERFR7Wi1ZSgoUDgcY0849yIpCWvVqhWMRiMAoGPHjtiyZQs2b96M8PDw+7yTiIiIXEGvL4YoKiGKClitgCiW94TT64tdHRr9l6TlyPj4eHsx/pQpU7Bz507cunULM2fOlDU4IiKi+lLxJKHJ5AOttqzWTxI66zp1VdETzmBQIzsb0GisiIsrYlG+G1HYnNGJtZ5dvnxZ1uvzUWl5cXydr2KjavMdMzSNNLXeqJobXt8bf3bl4+qxrfwkYeWdBGr6JKGzruNsrh5fTyZ7i4qcnJwqjycmJiIkJARBQUGYPXu2lEsRkZNV3qi6xYMtkHMzp1YbVXPDa/JmlZ8kBPDfv8ufJNTpCuv9OiQvd5mtlJSE3SvBWrt2rdOCIaKaq7xRtVKhrPVG1dzwmryZs54k5BOJ7q/ybGV4uBWi6Lr+aZKSMD8/P+zYseOu488884zTAyKimnHWRtXc8Lph4JKxPLTaMoii0j6DBdTuSUJnXYfk406zlZKejqy86TYRuRdnbVTNDa/dX8WSsVgiOiwZG3ONrg6twXPWk4TOuo7RqEJSUgDmzROQlBQAo1HSnAlJYDL5IDDQsRzeVbOVkv5VS0pK8NJLL0GlUiEoKAitWrVCTEyM3LERkQT6CD1Sz6QCANQPqCGWiBBLRMR1iKv1dQJ9A1FgKajVdZyFMz5345KxfCo/SVhRJ1SbJwmdcR13Wi7zRO40WykpCXv22Wdhs9lgsVhw8+ZNnDt3Dnv27MGdO3fkjo+I7kMXqkP8I/EwZBmQnZ8NjZ8GcR3iavxLufJ1KhKf2lzHGfiQQNW4ZCwvna7UKctRdb2OOy2XeSK9vhipqQEAHJ9gjYsrqvdYJCVh/fv3v+vYL7/8gkWLFmH58uUICgrC3LlznR4cEUlTsVF1XR9Dd5cNrznjUzVtgBZiiWgfD4BLxp7I3Yr73eVJQmdx1qynM9R6kfmhhx7C+vXrYbPZ4OPjGU99VPygmc0+0GgCGvwPGlFDxRmfqrnbkjHJw52Wy5y5NOqMZM5ZCaGzZj3rSlJhfk5OTpV/ysrKEBYWhpCQELnjlF3FD5ooKtGiBew/aCyGJKp/fEigahVLxoKfgCu3rkDwE7x+idYTudN2Q5WXRpXK8qVRQShfGq2Jyr9jKydzNfkd64xruJs69wlLS0tzWjCuVNUPGtfgiVyDMz7Vc5clY5KPOy2XOWtp1Bl1bp5YKycpCfvtb3+Lb775BqNGjULv3r2hVEqaQGtQ3G0NnsibudNDAkSu4C7LZc5aGnXG71hP/D0tKQmbOnUqrl69ip07d+KDDz7A+PHj0a1bN7ljq1futAZPRJzxIXIHznqS0Bm/Yz3x97TkKa1mzZph3rx5eO6553DgwAEsX74cP/30k5yx1St3WoMnImoI2FDU81UsjQqCFVeuKCEI1loV5Tvjd6wn/p5W2Gw22/2+af369Q5d8202G86dO4ebN2+6pCbs8uXLslz316cjG0OjucWnI2VS1zYKVD2Orbw4vr+q/NRc5RmS2jYU5djKyx3G152ejnSm+41t8+bNqz0n6f+2NGvWTNKxhq5iDV6jUcNsdv1aPBGRu/LEImmSlzPq3NylVs5ZJCVho0ePljsOIiJqQDyxSJqovklKwqxWa5XHExMTUVZWhqCgoHu2sSAiIs/iiUXSRPVNUhI2duzYas95Sp8wIiKSzp323yNqqCQlYb6+vli7dq3DMZvNhgULFsgSFBERuTd3aihK1FBJSsKUSiXCwsLuOl75iUkiIvIunlYkTVTfJCVhFosFGzduhEqlQlBQECIiItC1a1e5YyMiIiLyWJKSsOHDhwMoT8ZycnLwxRdfYNOmTbBYLLIGR0REROSpJCVhcXF3b5r77bffYuXKlXjjjTcQEBCAiRMnOj04Imp4jLlGhz0f9RF6bj9ERFSFWu8x0aVLFyxbtgxWqxUqFbeqIKLyBCz1TCoEPwHhjcMhlohIPZOK+EfimYgREf2POmVPHTt2dFYcROQBDFkGCH4CBD8BAOx/G7IMTMKIiP6HpCRszJgx1Z5jnzAiqmAqNCG8cbjDsUDfQJgKTS6KiIjIfUlKwl5//XX760WLFiExMVG2gIio4dIGaCGWiPYZMAAosBRAG6B1YVRERO6pxht4K5VKj9y8m8hVPKmQXR+hR+qZVADlM2AFlgKIJSLiOtz9cA8RkbdTujoAIm9WUcgulogOhezGXKOrQ6sVXagO8Y/EQ/ATcOXWFQh+AovyiYiqIWkmrHLdl8Vicfj6XvViRHRvnljIrgvVNdjYiYjqk6QkLDc31/66V69eDl8TUe2xkJ2IyHtJSsKmT58udxxEXomF7ERE3qtGNWG3b9/GtWvXkJOTY/9DRLWnj9BDLBEhloiw2qz21/oIvatDIyIimUmaCcvOzsa6detw8eLFu86xTxh5K2c81VhRyF75OnEd4lhTRUTkBSQlYZs3b0anTp2wdOlSzJw5EykpKdi5cyfat28vd3xEbsmZ2/OwkJ2IyDtJWo68ePEixo8fj8aNG8Nms8Hf3x8TJkzgLBh5rcpPNSoVSvtrQ5bB1aEREVEDISkJa9SoEcrKygAAgYGBMJvNsNlsKCwslDU4IndlKjQh0DfQ4RifaiQiopqQtBzZsWNHfP755+jbty969uyJV155BY0aNUKnTp3kjo/ILfGpRiIiqitJSdi8efPsr8eOHYuWLVuiuLgYvXv3li0wInfG7XmIiKiuJCVhlSmVSnvyxeVI8lZ8qpGIiOpKUhK2c+dOjBs3zuHYyZMnsX37dqSmpsoSGJG741ONRERUF5IK8zMzM/Hmm2/CZrNBFEWsWbMG77//PhISEuSOj4iIiMgjSUrC/vKXv+DmzZtYsWIFEhISoNVqkZiYiLZt28odHxEREZFHkpSE+fr6YsGCBQgJCUFYWBieeuopqFQ1LicjIiIiov+SlEmtX78eCoUCVqsVv/zyC1544QVEREQAAGbOnClnfEREREQeSVIS1qxZM/vrYcOGyRYMERERkbeQlISNHj1a7jiIiIiIvIqkmjAiIiIici5W15NXMuYaHRqt6iP07PlFRET1ijNh5HWMuUaknkmFWCIivHE4xBIRqWdSYcw1ujo0IiLyIpKSsNzcXLnjIKo3hiwDBD8Bgp8ApUJpf23IMrg6NCIi8iKSkrDKG3gTNXSmQhMCGGcvJQAAGfZJREFUfQMdjgX6BsJUaHJRRERE5I0kJWE2m03uOIjqjTZAiwJLgcOxAksBtAFaF0VERETeSFJhfmlpKdLS0qo8N2bMGKcGRCQ3fYQeqWfKN54P9A1EgaUAYomIuA5xLo6MiIi8iaQkzGazsS6MPIYuVIf4R+Idno6M6xDHpyOJiKheSUrCfH19MX36dLljIao3ulAdky4iInIp1oQRERERuYCkJOzFF1+UOw4iIiIiryK5MN9orLqRpU7HJR0iIiKimpKUhK1fv97+Oi8vD8HBwfavN27c6PyoiIiIiDycpCSscqI1efJkJl5EREREdcS9I4mIiIhcgEkYERERkQtIWo5csmQJFAoFAKC4uBhLly61n1u+fLk8kRERERF5MElJWP/+/e2v+/XrJ1swRERERN5CUhLWt29fmcMgIiIi8i6S9448cuQITpw4gYKCAqxZswZGoxE3b97E448/LneMRERERB5HUmF+WloaPvnkE8TGxsJsNgMAQkNDceDAAVmDIyIiIvJUkpKwjIwMLFq0CL169bIX6Ddp0gTXrl2TNTgiIiIiTyVpOdJqtUKtVjscKy4uvutYdcxmM1JSUnDz5k0oFArExsZi0KBBKCwsRHJyMq5fv46wsDDMnTsXAQEBNf8URERERA2MpJmwbt26YceOHbhz5w6A8hqxtLQ0PProo5Ju4uPjg6effhrJycn429/+hsOHDyM7Oxv79+9HVFQU1q1bh6ioKOzfv7/2n4SIiIioAZGUhE2cOBE3btzApEmTUFRUhIkTJ+L69esYN26cpJsEBwejTZs2AIAHHngAWq0WN27cwKlTp9CnTx8AQJ8+fXDq1KlafgwiIiKihkXScqS/vz8WLlyImzdvwmw2Q6PR4MEHH6zVDa9du4aff/4Zbdu2hSiK9s3Ag4ODkZ+fX6trEhERETU0kpKwCg8++KBD8rVjxw4UFhaiZcuWGDp06H3fX1xcjKSkJEyaNAn+/v6S75ueno709HQAwKpVq6DRaGoSdo2pVCrZ7+HNOL7y4djKi+MrH46tvDi+8qnL2EpKwqrbmigzMxMvvPACGjdufN9rlJaWIikpCU8++SR69OgBABAEAXl5eQgODkZeXh6CgoKqfG9sbCxiY2PtX1e0yZCLRqOR/R7ejOMrH46tvDi+8uHYyovjK5/7jW3z5s2rPScpCXvyySfvOmaz2fDLL79Ap9Pd9/02mw2bNm2CVqvFkCFD7Me7d++OjIwMjBgxAhkZGYiOjpYSDhEREVGDV+O9Iyvbu3evpJtcuHABx44dw0MPPYSEhAQAwNixYzFixAgkJyfj6NGj0Gg0mDdvnsSwiYiIiBq2GtWE1VbHjh2xZ8+eKs8tWbKkPkIgIiIiciuSkrBz585Veby0tNSpwRARERF5C0lJ2MaNG6s87uvr69RgiIiIiLyFpCQsJSVF7jiIiIiIvIrkmrCysjJcuHABN27cQGhoKNq3bw8fHx85YyMiIiLyWJKSMJPJhMTERFgsFoSGhiI3NxeNGjXCokWL0KJFC7ljJCIiIvI4kpKwzZs3IzY2FkOHDoVCoQAA/OMf/8CWLVuwdOlSWQMkIiIi8kSSkrCsrCz89a9/tSdgADB48GDs27dPtsDI8xhzjTBkGWC+Y4amkQb6CD10ofdv9ktEROSJlFK+KSQkBEaj0eHYd999Z998m+h+jLlGpP7/9u49KMrr/uP4e3cpbGABEVAU1BS1UWKs1kvRoEYxtUmtSSzx1kSJJpIErW0tVWtHzahTGcHEVKzYiqlm6i1p6sTWplONlyip6diUKE3VRJrUGpHl4nIRXHZ/fzjuLwRInrisK8vnNeNkOc8ufPbkDPPlnLPnKcqnqr6KhIgEquqryC/Kp9he/MUvFhERCUCGZsKmT59OdnY2Q4YM8dwj6eTJk8yfP9/X+SRA7C/ZT2RIJJEhkZhNZiJDIj3tmg0TEZGOyFARNnToULKzsyksLKSiooIePXowZcqUz70ppcinXai+QLewbk3awoPDuVB9wU+JRERE/MvwERXdu3dn8uTJOBwOwsPDm+wPE/ki8bZ4quqrPDNgAI4GB/G2eD+mEhER8R9DRVhNTQ0FBQW8/fbbOJ1OgoKCSE5O5oknnsBms/k6owSAB+58gPyifACsd1ipqq+iqr6KaXdN83MyERER/zC0MX/jxo00NDSQnZ3Ntm3byM7O5tq1a2zcuNHX+SRAJEUnkTEwg8iQSP575b9EhkSSMTBD+8FERKTDMjQTdvr0aTZv3uy5V2RCQgKZmZlkZGT4NJwElqToJJKikzwf7hAREenIDBVh3bt3p7S0tMnp+GVlZdqYL7fcjbPGLlRfIN4Wr7PGRESk3TJUhA0YMIDVq1czatQozyzG0aNHGT16NAcPHvQ8b9y4cT4LKnLjrLHIkEi6hXXznDWmZU0REWmPDBVhZ8+eJS4ujrNnz3L27FkA4uLiOHPmDGfOnPE8T0WY+NKnzxoDdNaYiIi0a4aKMN0fUm4HOmtMREQCiaFPR4rcDuJt8TgaHE3adNaYiIi0V4ZmwqZOndrqtV27drVZGJHP8+mzxsKDw3E0OHTWmIiItFuGirDg4GDWrl3r6ywin+vGWWOf/nTktLumaT+YiIi0S4aKMLPZTFxcnK+ziHyhG2eNiYiItHfaEyYiIiLiB4Zmwq5du9bq3q/P2y8mIiIiIi0zVISlpKRgt9t9nUVERESkwzBUhD377LO+ziEiIiLSoWhPmIiIiIgfqAgTERER8QMVYSIiIiJ+oCJMRERExA8Mbcw/depUq9cGDBjQZmFEREREOopWi7DKykpsNhtBQUGsXLmSsLAwQkNDcbvdnueYTCY2bNhwS4KKiIiIBJJWi7Di4mKOHDnC4sWLmTFjBn/+858ZPXo0kyZNwmq13sqMIiIiIgGn1T1hycnJnDlzBoCHHnqInJwc6uvrWbhwIX/5y19wuVy3LKSIiIhIoGm1CPvnP/9JfHy85+uwsDAef/xxnnvuOc6cOcPChQv529/+dktCioiIiASaVpcjY2NjycrKAmDZsmWYTCbPNbfbTU1NDevWrWv1npIiIiIi0rpWi7CEhATP43Hjxt2SMCIiIiIdhaEjKu677z4fxxARERHpWAwVYQcPHmz1mmbJRERERL48Q0VYfn4+UVFRdOvWrdk1FWEiIiIiX56hImzBggXs3r2bmJgYpk6dSkxMjK9ziYiIiAQ0Q/eOHDlyJLm5ufTu3Ztly5bx8ssvU1tb6+tsIiIiIgHL8A28LRYL3/72t1m3bh3BwcH85Cc/Yd++fb7MJiIiIhKwDC1HPvPMM83a6urq2L59OxMnTmzzUCIiIiKBzlARNn/+fF/nEBEREelQDBVhSUlJvs4hIiIi0qEYKsJeeeWVVq+lpaW1WRgRERGRjsJQEXbx4kXP47fffpvk5GSAJveTFBERERHjvvSesJMnT2qPmIiIiIiXDB9RISIiIiJtx9BMmMvlavK12+3G7XYDYDarjhMRERH5sgwVYdOnT2/y9bRp0zyPd+3a1baJRERERDoAQ0XYhg0bfJ1DREREpEMxVITFxsa22G632ykrK8NsNtO5c+c2DSa3j2J7MftL9nOh+gLxtngeuPMBkqJ1dpyIiIg3DBVhBw8ebLG9oKCAUaNGYbPZ+P73v9+mweT2UGwvJr8on8iQSLqFdaOqvor8onwyBmaoEBMREfGCoSJs8+bN9O/fv1l7Y2MjGRkZbR5Kbh/7S/YTGRJJZEgkgOe/+0v2qwgTERHxgqEiLDg4mOXLlzdrnzVrVpsHktvLheoLdAvr1qQtPDicC9UX/JRIREQkMBg6X0In43dc8bZ4HA2OJm2OBgfxtng/JRIREQkMhmbCrl69ytSpUwkKCiIiIoJevXqRkpLiOStMAtcDdz5AflE+cH0GzNHgoKq+iml3TfuCV4qIiMjnMVSErV+/HoCGhgYqKys5f/48r776KvX19T4NJ/6XFJ1ExsCMJp+OnHbXNO0HExER8ZKhIiwuLs7zuGfPngwcOJD777+fJUuWMG/ePKKioli5cqXPQop/JUUnqegSERFpY4aKsJaEhoZ6ZshERERE5MsxVIS53W4OHDjAsWPHcDgc5OTkUFxcTGVlJSNHjvR1RhEREZGAY+jTkbt27eLNN99k/PjxlJWVARAdHc3evXt9Gk5EREQkUBkqwg4fPsyiRYu49957PcdVdOnShdLSUp+GExEREQlUhoowl8uF1Wpt0nb16tVmbSIiIiJijKEibPDgwWzbto1r164B1/eI7dq1iyFDhvg0nIiIiEigMlSEzZw5k/LyctLT06mtrWXmzJlcvnxZN+0WERERuUmGPh0ZGhrKT3/6U6qqqrh8+TIxMTF06tTJ19lEREREApbhc8JqamooKiqioqKCqKgoBg8ejM1m82U2ERERkYBlqAg7deoUOTk5dO/enZiYGOx2O1u2bGHhwoXcc889vs4oIiIiEnAMFWFbtmxh7ty5TQ5mLSwsZMuWLbzwwgs+CyciIiISqAxtzK+oqCA5OblJ2/Dhw6msrPRJKBEREZFAZ3K73e4velJBQQFxcXE8+OCDnrb9+/dz8eJFZs+e7dOAIiIiIoHI0EzY+fPn2b59O08//TQ/+9nPePrpp9m2bRslJSUsX77c8y9QLF682N8RApr613fUt76l/vUd9a1vqX99x5u+NbQnLDU1ldTU1Jv+ISIiIiLSlKEi7L777vNxDBEREZGOxbJixYoVX/SkgoICQkNDiYmJ8bT9+9//Zt++fQwaNMiX+fwmMTHR3xECmvrXd9S3vqX+9R31rW+pf33nZvvW0Mb8OXPmkJ+fT1DQ/0+cXbt2jWeeeYbf/OY3N/WDRURERDoyQxvzTSYTLperSZvL5cJA/SYiIiIiLTC0J6xfv37s3LmTxx57DLPZjMvlYs+ePfTr18/X+W65d999l61bt+JyuUhNTeXhhx/2d6SAkZmZidVqxWw2Y7FYWLNmjb8jtWsbN27k5MmTREZGkpubC0B1dTXPP/88ly9fJjY2lh/96Ee6vdhNaKlvd+/ezYEDB4iIiABg+vTpfOMb3/BnzHarrKyMvLw8KisrMZlMjB8/ngcffFDjtw201rcav95raGhg+fLlOJ1OGhsbSU5OZsqUKV6NW0PLkXa7nTVr1lBZWUlMTAxlZWVERUWxaNEioqOjvX5jtwuXy8WCBQv4+c9/TnR0NEuWLGHBggUkJCT4O1pAyMzM5Be/+IXnl4B4p7i4GKvVSl5enqdQePnll7HZbDz88MP84Q9/oLq6mscee8zPSduflvp29+7dWK1WJk2a5Od07V9FRQUVFRUkJiZSV1fH4sWLycrK4tChQxq/Xmqtb48fP67x6yW32019fT1WqxWn08myZctIT0/nxIkTNz1uDS1HRkdHk52dTVZWFpMmTSIrK4s1a9YEVAEGcO7cOeLi4ujatStBQUGMHDmSd955x9+xRFqUlJTU7K+td955hzFjxgAwZswYjd+b1FLfStuJiorybGS+4447iI+Pp7y8XOO3DbTWt+I9k8mE1WoFoLGxkcbGRkwmk1fj1tByJIDZbOZrX/val4zcvpSXlzcpLKOjozl79qwfEwWe1atXA3D//fczfvx4P6cJPFVVVURFRQHXfxlfuXLFz4kCyxtvvMGRI0dITExk5syZKtTaQGlpKefPn6dPnz4av23s0337/vvva/y2AZfLxaJFi/jkk0+YMGECffv29WrcGi7COoKWVmZNJpMfkgSmlStX0rlzZ6qqqli1ahXdu3cnKSnJ37FEDPnWt75FWloaALt27WLbtm08++yzfk7Vvl29epXc3FzS09MJDQ31d5yA8tm+1fhtG2azmbVr11JTU0NOTg4fffSRd9+vjXIFhOjoaOx2u+dru93uqW7Fe507dwYgMjKSYcOGce7cOT8nCjyRkZFUVFQA1/eGaP9d2+nUqRNmsxmz2UxqaioffPCBvyO1a06nk9zcXEaNGsU3v/lNQOO3rbTUtxq/bSssLIykpCTeffddr8atirBP6d27NxcvXqS0tBSn08nx48cZOnSov2MFhKtXr1JXV+d5XFRURM+ePf2cKvAMHTqUw4cPA3D48GGGDRvm50SB48YvWYATJ07Qo0cPP6Zp39xuN5s2bSI+Pp6JEyd62jV+vdda32r8eu/KlSvU1NQA1z8p+d577xEfH+/VuDX06ciO5OTJk/z2t7/F5XIxduxYJk+e7O9IAeHSpUvk5OQA1zc0pqSkqG+99MILL1BcXIzD4SAyMpIpU6YwbNgwnn/+ecrKyoiJieHHP/6x9n3chJb69vTp05SUlGAymYiNjWXu3LmaKb9J77//PsuWLaNnz56eLR/Tp0+nb9++Gr9eaq1vjx07pvHrpf/85z/k5eV5zkkdMWIEaWlpOByOmx63KsJERERE/EDLkSIiIiJ+oCJMRERExA9UhImIiIj4gYowERERET9QESYiIiLiByrCRERERPxARZiIiIiIH6gIExEREfED3cBbRNrEiy++SGFhIUFBQbhcLsLDw9m0aRMAtbW1FBQU8I9//IOQkBBSU1N55JFHMJuv/x3417/+lT/+8Y/Y7Xaio6OZP38+iYmJZGZmMn78eI4cOUJlZSXDhg3jySefJDg42PO6vXv3Ul1dTb9+/Xjqqafo3Lkzp0+f5pe//KXn53/268zMTDIyMhg4cCAABw4c4OjRo6xYsQKArVu3cuLECWpra4mLiyM9PZ3+/fsDUF9fT15eHu+99x5OpxOn00lKSgqZmZnN+sTlclFQUEBhYSENDQ24XC769u3LihUrKC0tZd68eYSEhADQpUsXZs+ezd133w3AlClTePHFF4mLi+Pvf/87W7ZsYcWKFXTt2pWTJ0+yc+dOLl26RGhoKGPHjmXKlCm++N8qIj6kIkxE2szkyZN59NFHPUXPDQUFBdTW1rJhwwYcDgerV68mKiqKcePGUVhYyJ49e8jKyqJ3795cunQJi8Xiee1bb73F0qVLsVqtZGdn8/vf/55p06Zx6tQpduzYwdKlS+nRowfbt29n/fr1PPfcc5hMJry5GUjv3r1JS0sjNDSUP/3pT6xbt468vDyCg4M5fPgwFy9eJC8vj9DQUHbu3Indbm/x+xQVFXHixAlycnKIioryFHuf9tJLL2E2m3n11VfZvn07a9asaXK9uLiYX//61yxdupSuXbsCEBISwrx580hISODjjz9m1apV3HnnnQwfPvym37OI3HpajhSRNtHQ0EBQUPO/61wuF8ePH2fGjBnccccddOnShYkTJ3LkyBEADh48yEMPPUSfPn0wmUzExcURGxvref2ECROIiYnBZrPxyCOPcOzYMQCOHj3K2LFjSUxM5Ctf+QozZszgzJkzlJaWEhMTQ1VVFSUlJTf1XkaPHk14eDgWi4Xvfve7OJ1O/ve//3muu91uXC7XF34ft9tt6Lk3nhMeHt6k/fz582RnZzN//vwmN7y/++676dmzJ2azmV69enHvvfdSXFz8Jd+liPibZsJEpE1UVlYSERHRrP3KlSs4nU5iYmI8bbGxsZSXlwNQVlbmmeFpSWuvq6io4Ktf/arnmtVqxWazUV5eTr9+/UhLS2PVqlU4nU4aGxsJCwtr8n3Xrl3rmXFzOp306dPHc+3111/n4MGDlJeXYzKZqKurw+FwADBmzBg++OAD5syZg9Vqxel0MnLkyBazf/3rX2f06NH84Ac/ICgoiMbGxiY/B2DOnDk4nU4sFgtZWVlNrm3atIlu3bpRVFTEgAEDPO1nz57ld7/7HR999JFnSTQ5ObnVPhSR25OKMBHxmtPp5OOPP6ZXr17NrkVERGCxWCgrKyMhIQG4Xnh17twZuF5kXbp0qdXvXVZW1uTxjddFRUU1uXb16lWqq6s919PS0khLSwNotjwKkJWV1WxPGMC//vUv9u7dy7Jly0hISMBsNvPEE094ljdDQkIYMmQIH374IWvWrGHPnj2tLkeazWZGjhzJ8ePHyc3NpbCwsNly5JYtW7BYLJw+fZqcnBzy8/M9e97S09MZPHgwWVlZJCcnk5iYCFzffzdhwgSWLFlCcHAwL730EleuXGm1D0Xk9qTlSBHx2qFDh+jUqRO9e/duds1sNjNixAh27NhBXV0dly9fZt++fYwaNQqAcePG8frrr/Phhx/idrv55JNPuHz5suf1b7zxBna7nerqal577TVGjBgBQEpKCm+++SYlJSVcu3aNHTt20KdPH7p06eLVe6mrq8NisRAREYHL5eKVV16htrbWc722tpatW7eSkZHRZO9aSxobG9m0aROzZs0iNDT0c59rNpupra3F6XR62vr370+nTp14/PHH+dWvfuW5VldXh81mIzg4mHPnzvHWW2958Y5FxF80EyYiXjl69CibN2/GYrEwc+ZM4Po+MKfTyebNm5k7dy6zZ8+moKCAefPmERwcTGpqKmPHjgVgxIgROBwO1q9fT3l5OV26dGHevHmefWEpKSmsWrWKiooKhg4dyve+9z0A7rnnHqZOnUpubi7V1dXcdddd/PCHP/T6/QwaNIhBgwaxYMECQkJC+M53vtNkSXT79u0MHz682bJiS/bu3UtsbOznLhWmp6cD12cMn3rqqRaLtdGjR3P8+HFee+01Hn30UZ588km2bdtGQUEBSUlJjBgxgpqami//ZkXEr0xubz5CJCId3qFDhygtLW12RILdbmfnzp0tHt1g1GePkhARCSRajhQRr4SEhLQ4e2OxWLDZbH5IJCLSPmg5UkS8cmOP1md16tSJWbNm3eI0IiLth5YjRURERPxAy5EiIiIifqAiTERERMQPVISJiIiI+IGKMBERERE/UBEmIiIi4gcqwkRERET84P8AJd5+uXuKc1QAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 720x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax0=data[(data['golos=true/false']==1)& (data['rearlytornout'] <29.4)].pivot_table('lukashenkoper', index='rearlytornout', aggfunc='mean').plot(marker='o',linestyle='none', figsize=(10, 7), color='green', alpha=0.5)#kind='scatter', x ='rearlytornout', y='lukashenkoper')\n",
    "ax1=data[(data['golos=true/false']==1)& (data['rearlytornout'] <29.4)].pivot_table('tichanivskayaper', index='rearlytornout', aggfunc='mean' ).plot(marker='o',linestyle='none',figsize=(10, 7), ax=ax0, color='blue', alpha=0.5)\n",
    "ax0.set_xlabel('досрочная явка')\n",
    "ax0.set_ylabel('средний процент кандидата на всех участках с данной явкой')\n",
    "ax0.legend(['Lukashenko', 'Tichanovskaya'], loc='upper right', fontsize='x-large')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 595,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x121fac160>"
      ]
     },
     "execution_count": 595,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "datal = pd.pivot_table(data[(data['golos=true/false']==1)& (data['rearlytornout'] <29.4)],values =['lukashenkoper', 'lukashenko'], index='rearlytornout', aggfunc={'lukashenkoper':'mean','lukashenko':'sum'})\n",
    "datal = datal.reset_index()\n",
    "s1=datal.lukashenko\n",
    "datat = pd.pivot_table(data[(data['golos=true/false']==1)& (data['rearlytornout'] <29.4)],values =['tichanivskayaper', 'tichanovskaya'], index='rearlytornout', aggfunc={'tichanivskayaper':'mean','tichanovskaya':'sum'})\n",
    "datat = datat.reset_index()\n",
    "s2 = datat.tichanovskaya\n",
    "ax0 = datal.plot(kind='scatter',x='rearlytornout',y='lukashenkoper',figsize=(14, 8),alpha=0.5, s=s1/90,color='green')\n",
    "ax1 = datat.plot(kind='scatter', x='rearlytornout',y='tichanivskayaper',alpha=0.5,color=\"blue\",s=s2/90,ax = ax0 )\n",
    "ax0.set_xlabel('досрочная явка')\n",
    "ax0.set_ylabel('средний процент кандидата на всех участках с данной явкой')\n",
    "ax0.legend(['Lukashenko', 'Tichanovskaya'], loc='upper right', fontsize='x-large')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 436,
   "metadata": {},
   "outputs": [],
   "source": [
    "re = 29.4 # фильтр для досрочной явки"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Дальше я посчитал процент избирателей, который приходится на каждую область по данным ЦИК (rdict).\n",
    "http://www.rec.gov.by/files/2020/gol_itog.pdf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 437,
   "metadata": {},
   "outputs": [],
   "source": [
    "rdict = {'Брестская': 0.145, 'Витебская': 0.123, 'Гомельская': 0.155, 'Гродненская':0.111, 'Минская' : 0.167, 'Могилевская': 0.116, 'Минск': 0.183}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 438,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "region\n",
       "Брестская       75905\n",
       "Витебская       37234\n",
       "Гомельская      33155\n",
       "Гродненская     77296\n",
       "Минск           77362\n",
       "Минская        179356\n",
       "Могилевская     25396\n",
       "Name: voterst, dtype: int64"
      ]
     },
     "execution_count": 438,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[(data['golos=true/false']==1) & (data['earlytornout'] < re)].groupby('region').voterst.sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Данные собирались волонтерами, поэтому количество протоклов распределилось неравновмерно. Меньше всего данных о Могилевской области, поэтому на ее базе считаю 100% голосов для модели."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 439,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "128782"
      ]
     },
     "execution_count": 439,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x = int(data[(data['golos=true/false']==1) & (data['earlytornout'] < re) & (data['region']=='Могилевская')].voterst.sum()/0.116/1.7)\n",
    "x"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Беру половину, чтобы была ротация для каждой симуляции. Число можно поменять, здесь тоже не помешало бы придумать какой-то метод."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 440,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'Брестская': 18673,\n",
       " 'Витебская': 15840,\n",
       " 'Гомельская': 19961,\n",
       " 'Гродненская': 14294,\n",
       " 'Минская': 21506,\n",
       " 'Могилевская': 14938,\n",
       " 'Минск': 23567}"
      ]
     },
     "execution_count": 440,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vdict = {}\n",
    "for k,v in rdict.items():\n",
    "    vdict[k]=int(v*x)\n",
    "vdict"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Посчитал кол-во голосов для каждой области пропорционально кол-ву избирателей."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 441,
   "metadata": {},
   "outputs": [],
   "source": [
    "sd  = 500 # максимальное отклонение от количества-голосов"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Я хочу написать функцию, которая будет рандомно выбирать протоколы для каждой области, но чтобы общее кол-во избирателей оставалось в пределе +-500 от значений в vdict. Сначала написал функцию, которая определяет оптимальное значение сэмплов для функции pd.sample()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 445,
   "metadata": {},
   "outputs": [],
   "source": [
    "def samples (k, v):\n",
    "    slist = []\n",
    "    for i in range(8, 20):\n",
    "        sm = 0\n",
    "        for z in range (1,10):\n",
    "            if  data[(data['golos=true/false']==1) & (data['earlytornout'] < re)& (data['region']==k)].sample(i).voterst.sum() > v-sd and data[(data['golos=true/false']==1) & (data['earlytornout'] < re) & (data['region']==k)].sample(i).voterst.sum() < v+sd :\n",
    "                sm +=1\n",
    "        slist.append(sm)\n",
    "    return slist.index(max(slist))+8\n",
    "            "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Теперь пишу саму функцию"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 443,
   "metadata": {},
   "outputs": [],
   "source": [
    "def regres (k,v, s):   \n",
    "        datax = data[(data['golos=true/false']==1) & (data['earlytornout'] < re) & (data['region']==k)].sample(s)\n",
    "        if v-sd < datax.voterst.sum() < v+sd :\n",
    "            return [datax.voterst.sum(), datax.lukashenko.sum(),datax.tichanovskaya.sum()]\n",
    "        else:\n",
    "            return regres (k,v, s)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Считаю сэмплы для каждой области. А потом сто раз выбираю рандомно протоколы в каждой области и считаю результат. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 446,
   "metadata": {},
   "outputs": [],
   "source": [
    "sdict = {}\n",
    "for k, v in vdict.items():\n",
    "    sdict[k] = samples(k,v)\n",
    "result = pd.DataFrame()\n",
    "for i in range(0,100):\n",
    "    luk = 0\n",
    "    tich = 0\n",
    "    tot = 0\n",
    "    for k, v in vdict.items():\n",
    "        x = regres(k,v, sdict[k])\n",
    "        tich += x[2]\n",
    "        luk += x[1]\n",
    "        tot += x[0]\n",
    "    dataapp = pd.Series({'Lukashenko':luk/tot,'Tichanovskaya':tich/tot})\n",
    "    dataapp = dataapp.to_frame().T\n",
    "    result = result.append(dataapp)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Вот и результат"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 447,
   "metadata": {},
   "outputs": [
    {
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       "      <td>0.452860</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.466411</td>\n",
       "      <td>0.421763</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.454686</td>\n",
       "      <td>0.436379</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.475207</td>\n",
       "      <td>0.415406</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.452838</td>\n",
       "      <td>0.440689</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.465525</td>\n",
       "      <td>0.428994</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.468218</td>\n",
       "      <td>0.425253</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.461589</td>\n",
       "      <td>0.425462</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.468876</td>\n",
       "      <td>0.424375</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.471094</td>\n",
       "      <td>0.408654</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.441374</td>\n",
       "      <td>0.453094</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.475748</td>\n",
       "      <td>0.418518</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.475657</td>\n",
       "      <td>0.413851</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.489525</td>\n",
       "      <td>0.406188</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.484019</td>\n",
       "      <td>0.404786</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.471776</td>\n",
       "      <td>0.419523</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.488679</td>\n",
       "      <td>0.405378</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.468334</td>\n",
       "      <td>0.424017</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.475388</td>\n",
       "      <td>0.419310</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.450545</td>\n",
       "      <td>0.435195</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.482571</td>\n",
       "      <td>0.409734</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Lukashenko  Tichanovskaya\n",
       "0    0.493403       0.394477\n",
       "0    0.457008       0.435460\n",
       "0    0.478878       0.413213\n",
       "0    0.467550       0.427909\n",
       "0    0.491331       0.399074\n",
       "0    0.470292       0.419576\n",
       "0    0.471564       0.416357\n",
       "0    0.440631       0.449629\n",
       "0    0.456537       0.425998\n",
       "0    0.462797       0.424622\n",
       "0    0.474685       0.415021\n",
       "0    0.464919       0.425881\n",
       "0    0.464941       0.428817\n",
       "0    0.466977       0.430601\n",
       "0    0.473355       0.414815\n",
       "0    0.441642       0.441720\n",
       "0    0.484208       0.406876\n",
       "0    0.468182       0.426286\n",
       "0    0.449984       0.444988\n",
       "0    0.473969       0.421361\n",
       "0    0.472445       0.419802\n",
       "0    0.486759       0.405685\n",
       "0    0.451039       0.441699\n",
       "0    0.457430       0.428168\n",
       "0    0.469331       0.417601\n",
       "0    0.469194       0.425492\n",
       "0    0.473033       0.419462\n",
       "0    0.461892       0.430330\n",
       "0    0.479122       0.412408\n",
       "0    0.481931       0.416865\n",
       "0    0.440029       0.450886\n",
       "0    0.472265       0.424021\n",
       "0    0.472413       0.415121\n",
       "0    0.458136       0.430181\n",
       "0    0.459057       0.428802\n",
       "0    0.457539       0.431504\n",
       "0    0.478249       0.417373\n",
       "0    0.456595       0.433290\n",
       "0    0.467783       0.418516\n",
       "0    0.470403       0.425514\n",
       "0    0.452290       0.432556\n",
       "0    0.461503       0.432703\n",
       "0    0.470308       0.418818\n",
       "0    0.476000       0.419630\n",
       "0    0.476058       0.417038\n",
       "0    0.449360       0.443502\n",
       "0    0.483660       0.412075\n",
       "0    0.465860       0.426268\n",
       "0    0.466499       0.429076\n",
       "0    0.454600       0.437124\n",
       "0    0.465909       0.428977\n",
       "0    0.472103       0.419955\n",
       "0    0.450353       0.441802\n",
       "0    0.442307       0.441182\n",
       "0    0.472174       0.422334\n",
       "0    0.469126       0.422091\n",
       "0    0.460635       0.430794\n",
       "0    0.461336       0.427148\n",
       "0    0.484115       0.404678\n",
       "0    0.446980       0.442660\n",
       "0    0.471372       0.420867\n",
       "0    0.456019       0.432151\n",
       "0    0.441869       0.446786\n",
       "0    0.490669       0.403762\n",
       "0    0.472167       0.424772\n",
       "0    0.477815       0.408585\n",
       "0    0.481810       0.412148\n",
       "0    0.506563       0.386164\n",
       "0    0.459155       0.429034\n",
       "0    0.454970       0.432289\n",
       "0    0.485905       0.408808\n",
       "0    0.454683       0.437383\n",
       "0    0.466426       0.422708\n",
       "0    0.480214       0.409448\n",
       "0    0.492079       0.397392\n",
       "0    0.461660       0.430929\n",
       "0    0.447837       0.445464\n",
       "0    0.461455       0.426368\n",
       "0    0.467006       0.423244\n",
       "0    0.431794       0.452860\n",
       "0    0.466411       0.421763\n",
       "0    0.454686       0.436379\n",
       "0    0.475207       0.415406\n",
       "0    0.452838       0.440689\n",
       "0    0.465525       0.428994\n",
       "0    0.468218       0.425253\n",
       "0    0.461589       0.425462\n",
       "0    0.468876       0.424375\n",
       "0    0.471094       0.408654\n",
       "0    0.441374       0.453094\n",
       "0    0.475748       0.418518\n",
       "0    0.475657       0.413851\n",
       "0    0.489525       0.406188\n",
       "0    0.484019       0.404786\n",
       "0    0.471776       0.419523\n",
       "0    0.488679       0.405378\n",
       "0    0.468334       0.424017\n",
       "0    0.475388       0.419310\n",
       "0    0.450545       0.435195\n",
       "0    0.482571       0.409734"
      ]
     },
     "execution_count": 447,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 448,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Lukashenko       100\n",
       "Tichanovskaya    100\n",
       "dtype: int64"
      ]
     },
     "execution_count": 448,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result.nunique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 449,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Lukashenko       0.467182\n",
       "Tichanovskaya    0.423935\n",
       "dtype: float64"
      ]
     },
     "execution_count": 449,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result.mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 450,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Lukashenko       0.468200\n",
       "Tichanovskaya    0.424498\n",
       "dtype: float64"
      ]
     },
     "execution_count": 450,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result.median()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Мой метод отличается от электоральной статистики тем, что на основе данных Голоса я классифицировал протоколы на участки с честным и не честным подсчетом. Среди протоколов с честным подсчетом постарался отобрать участки без вбросов на досрочном голосовании (хотя методология нуждается в доработке). И посчитал результаты выборов на основе протоколов с честных участков, с сохранением пропорции между всеми 7 областями."
   ]
  }
 ],
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