{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1. Датасет: Диабет у индейцев Пима\n",
    "https://www.kaggle.com/datasets/uciml/pima-indians-diabetes-database\n",
    "##### О наборе данных: \n",
    "Этот набор данных был получен из Национального института диабета, болезней органов пищеварения и почек. Цель набора данных - диагностически предсказать, есть ли у пациента сахарный диабет, на основе определенных диагностических измерений, включенных в набор данных. На выбор этих образцов из более обширной базы данных было наложено несколько ограничений. В частности, все пациенты были женщинами в возрасте не менее 21 года, родом из племени пима.\n",
    "##### Таким образом:\n",
    "* Объект наблюдения - женщины племени пима, возрастом от 21 года.\n",
    "* Атрибуты: Pregnancies, Glucose, BloodPressure, SkinThickness, Insulin, BMI, DiabetesPedigreeFunction, Age, Outcome.\n",
    "* Проблемная область: Предсказание диабета у пациента на основе измерений."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Количество колонок: 9\n",
      "Колонки: Pregnancies, Glucose, BloodPressure, SkinThickness, Insulin, BMI, DiabetesPedigreeFunction, Age, Outcome\n",
      "\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 768 entries, 0 to 767\n",
      "Data columns (total 9 columns):\n",
      " #   Column                    Non-Null Count  Dtype  \n",
      "---  ------                    --------------  -----  \n",
      " 0   Pregnancies               768 non-null    int64  \n",
      " 1   Glucose                   768 non-null    int64  \n",
      " 2   BloodPressure             768 non-null    int64  \n",
      " 3   SkinThickness             768 non-null    int64  \n",
      " 4   Insulin                   768 non-null    int64  \n",
      " 5   BMI                       768 non-null    float64\n",
      " 6   DiabetesPedigreeFunction  768 non-null    float64\n",
      " 7   Age                       768 non-null    int64  \n",
      " 8   Outcome                   768 non-null    int64  \n",
      "dtypes: float64(2), int64(7)\n",
      "memory usage: 54.1 KB\n"
     ]
    },
    {
     "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>Pregnancies</th>\n",
       "      <th>Glucose</th>\n",
       "      <th>BloodPressure</th>\n",
       "      <th>SkinThickness</th>\n",
       "      <th>Insulin</th>\n",
       "      <th>BMI</th>\n",
       "      <th>DiabetesPedigreeFunction</th>\n",
       "      <th>Age</th>\n",
       "      <th>Outcome</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>6</td>\n",
       "      <td>148</td>\n",
       "      <td>72</td>\n",
       "      <td>35</td>\n",
       "      <td>0</td>\n",
       "      <td>33.6</td>\n",
       "      <td>0.627</td>\n",
       "      <td>50</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>85</td>\n",
       "      <td>66</td>\n",
       "      <td>29</td>\n",
       "      <td>0</td>\n",
       "      <td>26.6</td>\n",
       "      <td>0.351</td>\n",
       "      <td>31</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>8</td>\n",
       "      <td>183</td>\n",
       "      <td>64</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>23.3</td>\n",
       "      <td>0.672</td>\n",
       "      <td>32</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>89</td>\n",
       "      <td>66</td>\n",
       "      <td>23</td>\n",
       "      <td>94</td>\n",
       "      <td>28.1</td>\n",
       "      <td>0.167</td>\n",
       "      <td>21</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>137</td>\n",
       "      <td>40</td>\n",
       "      <td>35</td>\n",
       "      <td>168</td>\n",
       "      <td>43.1</td>\n",
       "      <td>2.288</td>\n",
       "      <td>33</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Pregnancies  Glucose  BloodPressure  SkinThickness  Insulin   BMI  \\\n",
       "0            6      148             72             35        0  33.6   \n",
       "1            1       85             66             29        0  26.6   \n",
       "2            8      183             64              0        0  23.3   \n",
       "3            1       89             66             23       94  28.1   \n",
       "4            0      137             40             35      168  43.1   \n",
       "\n",
       "   DiabetesPedigreeFunction  Age  Outcome  \n",
       "0                     0.627   50        1  \n",
       "1                     0.351   31        0  \n",
       "2                     0.672   32        1  \n",
       "3                     0.167   21        0  \n",
       "4                     2.288   33        1  "
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "df = pd.read_csv(\".//static//csv//diabetes.csv\", sep=\",\")\n",
    "print('Количество колонок: ' + str(df.columns.size))  \n",
    "print('Колонки: ' + ', '.join(df.columns)+'\\n')\n",
    "\n",
    "df.info()\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Получение сведений о пропущенных данных\n",
    "Типы пропущенных данных:\n",
    "\n",
    "- None - представление пустых данных в Python\n",
    "- NaN - представление пустых данных в Pandas\n",
    "- '' - пустая строка"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Pregnancies                 0\n",
      "Glucose                     0\n",
      "BloodPressure               0\n",
      "SkinThickness               0\n",
      "Insulin                     0\n",
      "BMI                         0\n",
      "DiabetesPedigreeFunction    0\n",
      "Age                         0\n",
      "Outcome                     0\n",
      "dtype: int64\n",
      "\n",
      "Pregnancies                 False\n",
      "Glucose                     False\n",
      "BloodPressure               False\n",
      "SkinThickness               False\n",
      "Insulin                     False\n",
      "BMI                         False\n",
      "DiabetesPedigreeFunction    False\n",
      "Age                         False\n",
      "Outcome                     False\n",
      "dtype: bool\n",
      "\n",
      "Pregnancies процент пустых значений: %0.00\n",
      "Glucose процент пустых значений: %0.00\n",
      "BloodPressure процент пустых значений: %0.00\n",
      "SkinThickness процент пустых значений: %0.00\n",
      "Insulin процент пустых значений: %0.00\n",
      "BMI процент пустых значений: %0.00\n",
      "DiabetesPedigreeFunction процент пустых значений: %0.00\n",
      "Age процент пустых значений: %0.00\n",
      "Outcome процент пустых значений: %0.00\n"
     ]
    }
   ],
   "source": [
    "# Количество пустых значений признаков\n",
    "print(df.isnull().sum())\n",
    "print()\n",
    "\n",
    "# Есть ли пустые значения признаков\n",
    "print(df.isnull().any())\n",
    "print()\n",
    "\n",
    "# Процент пустых значений признаков\n",
    "for i in df.columns:\n",
    "    null_rate = df[i].isnull().sum() / len(df) * 100\n",
    "    print(f\"{i} процент пустых значений: %{null_rate:.2f}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Проверим выбросы и устраним их:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Колонка Pregnancies:\n",
      "  Есть выбросы: Да\n",
      "  Количество выбросов: 4\n",
      "  Минимальное значение: 0.0\n",
      "  Максимальное значение: 13.5\n",
      "  1-й квартиль (Q1): 1.0\n",
      "  3-й квартиль (Q3): 6.0\n",
      "\n",
      "Колонка Glucose:\n",
      "  Есть выбросы: Да\n",
      "  Количество выбросов: 5\n",
      "  Минимальное значение: 37.125\n",
      "  Максимальное значение: 199.0\n",
      "  1-й квартиль (Q1): 99.0\n",
      "  3-й квартиль (Q3): 140.25\n",
      "\n",
      "Колонка BloodPressure:\n",
      "  Есть выбросы: Да\n",
      "  Количество выбросов: 45\n",
      "  Минимальное значение: 35.0\n",
      "  Максимальное значение: 107.0\n",
      "  1-й квартиль (Q1): 62.0\n",
      "  3-й квартиль (Q3): 80.0\n",
      "\n",
      "Колонка SkinThickness:\n",
      "  Есть выбросы: Да\n",
      "  Количество выбросов: 1\n",
      "  Минимальное значение: 0.0\n",
      "  Максимальное значение: 80.0\n",
      "  1-й квартиль (Q1): 0.0\n",
      "  3-й квартиль (Q3): 32.0\n",
      "\n",
      "Колонка Insulin:\n",
      "  Есть выбросы: Да\n",
      "  Количество выбросов: 34\n",
      "  Минимальное значение: 0.0\n",
      "  Максимальное значение: 318.125\n",
      "  1-й квартиль (Q1): 0.0\n",
      "  3-й квартиль (Q3): 127.25\n",
      "\n",
      "Колонка BMI:\n",
      "  Есть выбросы: Да\n",
      "  Количество выбросов: 19\n",
      "  Минимальное значение: 13.35\n",
      "  Максимальное значение: 50.550000000000004\n",
      "  1-й квартиль (Q1): 27.3\n",
      "  3-й квартиль (Q3): 36.6\n",
      "\n",
      "Колонка DiabetesPedigreeFunction:\n",
      "  Есть выбросы: Да\n",
      "  Количество выбросов: 29\n",
      "  Минимальное значение: 0.078\n",
      "  Максимальное значение: 1.2\n",
      "  1-й квартиль (Q1): 0.24375\n",
      "  3-й квартиль (Q3): 0.62625\n",
      "\n",
      "Колонка Age:\n",
      "  Есть выбросы: Да\n",
      "  Количество выбросов: 9\n",
      "  Минимальное значение: 21.0\n",
      "  Максимальное значение: 66.5\n",
      "  1-й квартиль (Q1): 24.0\n",
      "  3-й квартиль (Q3): 41.0\n",
      "\n"
     ]
    }
   ],
   "source": [
    "numeric_columns = ['Pregnancies', 'Glucose', 'BloodPressure', 'SkinThickness', 'Insulin', 'BMI', 'DiabetesPedigreeFunction', 'Age']\n",
    "for column in numeric_columns:\n",
    "    if pd.api.types.is_numeric_dtype(df[column]):  # Проверяем, является ли колонка числовой\n",
    "        q1 = df[column].quantile(0.25)  # Находим 1-й квартиль (Q1)\n",
    "        q3 = df[column].quantile(0.75)  # Находим 3-й квартиль (Q3)\n",
    "        iqr = q3 - q1  # Вычисляем межквартильный размах (IQR)\n",
    "\n",
    "        # Определяем границы для выбросов\n",
    "        lower_bound = q1 - 1.5 * iqr  # Нижняя граница\n",
    "        upper_bound = q3 + 1.5 * iqr  # Верхняя граница\n",
    "\n",
    "        # Подсчитываем количество выбросов\n",
    "        outliers = df[(df[column] < lower_bound) | (df[column] > upper_bound)]\n",
    "        outlier_count = outliers.shape[0]\n",
    "\n",
    "        # Устраняем выбросы: заменяем значения ниже нижней границы на саму нижнюю границу, а выше верхней — на верхнюю\n",
    "        df[column] = df[column].apply(lambda x: lower_bound if x < lower_bound else upper_bound if x > upper_bound else x)\n",
    "\n",
    "        print(f\"Колонка {column}:\")\n",
    "        print(f\"  Есть выбросы: {'Да' if outlier_count > 0 else 'Нет'}\")\n",
    "        print(f\"  Количество выбросов: {outlier_count}\")\n",
    "        print(f\"  Минимальное значение: {df[column].min()}\")\n",
    "        print(f\"  Максимальное значение: {df[column].max()}\")\n",
    "        print(f\"  1-й квартиль (Q1): {q1}\")\n",
    "        print(f\"  3-й квартиль (Q3): {q3}\\n\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Постараемся выявить зависимости Outcome от остальных колонок:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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TJ07U+P1XHr/Ype+rwWAAACQkJFRpdzqdrn/bjh49CiEE2rVrV+X9PnToUIMWPRLVhcGVyEOVWyNt374dQMX804EDB+K3337DCy+8gJUrV2LdunV45ZVXAKDKnq9XXnkl1q1bh3Xr1mHZsmWIiIjA9ddfX+3/iA8dOoSlS5fipZdeqnUOo6fS09Oxfv16V221efDBB/HZZ5/h0KFD+Omnn9wWhTQHiYmJbq9jZGQk7r//fmzbts3jc4SEhGDQoEH49NNPMWbMGBw7dsz1vlYaNmwYhBB4+eWX67V/b007DYhG7DzYFOe8WJcuXdChQwd8/PHHOH78eIPrqHydnn76add7dOlX5bzS6667DseOHcPixYvRtWtXfPDBB+jRowc++OAD13knTZqE33//HWlpadDpdJg2bRo6deqEX3/91Svfd0MZDAbExsa6Be3q7N27F/Hx8QgJCQFQ86cMly7m9LWa3ldP3m9JkrBmzZpq3+v333+/yWqmvy4uziLykMlkAnDhH/NNmzbh3Llz+O9//4vrrrvO1a+m//GHhYUhJSXF9fj6669HXFwclixZgqlTp7r1nTp1Krp374677rqr2nO1adMG27dvh81mqzPYCiEwZcoU3Hbbbbj22mvr/D6HDBkCnU6Hu+++G/3790ebNm2wefNmtz6tW7cGABw5cgQ33nij27EjR464jlduA3Tp7gmNERgY6PY6DhgwAPHx8UhPT/fo+7tUr1698OGHH+LMmTNu7cOHD8fgwYPxwAMPIDg4GPPmzWt07b7Upk0bOJ1OHDx4sM5pDpGRkfjqq6/Qv39/3HTTTdiyZQvi4uLqfc3K91utVru9RzUJDw/H2LFjMXbsWJSWluK6667DzJkz8dBDD7l9H0899RSeeuopHD16FN27d8frr7+OTz75pNpzXvyzeanDhw8jMjISgYGB9f7eLvX3v/8dCxcuxJYtW9w+kq+0efNmZGVluX1iEhYWhqKioip9Lx0BBaoPuS1atEBISEidf59at25d4/dfedwb2rRpAyEEkpKS0L59e6+ck6guHHElukRNc+AWLlwISZJcQa0ywF486mW1WvHee+95dJ3KIHzp9jIZGRn43//+h5dffrnGEZoRI0YgPz8f7777bpVjl47Cff7559i7d2+1uxNUR6VSYfTo0di7d2+VOW6VevXqhaioKMyfP9+t/tWrV+PQoUMYOnQogIr/0V533XVYvHhxld0TvDVaWDnKV9uequXl5cjIyKj22OrVqwFU/9Hy6NGj8fbbb2P+/Pl49tlnvVCt7wwfPhwKhQIvvPBClRHj6l77li1bYv369TCZTBg0aBDOnTtX72tGRUXh+uuvx/vvv1/lFwEAblutXXr+oKAgtG3b1vXzVF5eXmX6Rps2bRAcHFztlkyVYmNj0b17d3z44YduIXH//v1IT0/HzTffXO/vqzrPPPMM9Ho9HnnkkSrfS0FBAR599FEEBAS4Tb1o06YNiouL3UZqz5w5g2+++abK+QMDA6uEXIVCgeHDh2PlypVVtqYDLryvN998M3755Re3n/mysjIsWLAAiYmJHk0f8cTtt98OpVKJWbNmVfmZEkI06GeIqC4ccSW6xL333ouOHTvitttuQ3R0NM6ePYvVq1dj48aNeP7559GtWzcAFXc2CgsLw5gxY/D4449DkiR8/PHHNQay3Nxc1yhRfn4+3n//fahUqipzTtPT0zFo0KBaR6xGjx6Njz76CJMnT8Yvv/yCAQMGoKysDOvXr8djjz2GYcOGuZ3v4YcfrjaY1eTFF1/EM88847YQ52JqtRqvvPIKxo4di4EDB+Kee+5xbYeVmJjotp3W22+/jf79+6NHjx4YP3686+5C33//Pfbs2eNxTZVKS0tdt2gtKCjA22+/DbVa7QrL1SkvL0ffvn1x7bXX4m9/+xsSEhJQVFSEFStWYPPmzRg+fDiuvvrqap/7z3/+E0ajEc8//zwMBgOee+65etcsh7Zt2+L555/Hiy++iAEDBuD222+HVqvFjh07EBcXV+0vMm3btkV6ejquv/56pKam4ocffnB9zO2puXPnon///ujWrRsefvhhXHHFFcjNzUVGRgb+/PNP/PbbbwAqFrFdf/316NmzJ8LDw7Fz50589dVX+Oc//wkA+P3333HTTTdh5MiR6Ny5M1QqFb755hvk5ubi7rvvrrWGOXPmYMiQIUhOTsa4ceNc22EZDIYq+yQ3VLt27fDhhx9i1KhR6NatW5U7Z+Xn5+Ozzz5z25ru7rvvxrPPPovbbrsNjz/+OMrLyzFv3jy0b98eu3fvdjt/z549sX79erzxxhuIi4tDUlIS+vTpg//7v/9Deno6Bg4ciPHjx6NTp044c+YMli9fji1btiA0NBRTpkzBZ599hiFDhuDxxx9HeHg4PvzwQxw/fhxff/11jYsz66tNmzZ46aWXMHXqVGRlZWH48OEIDg7G8ePH8c0332D8+PF13vGNqN58vY0BUXM3b948cfPNN4u4uDihUqlEaGioSE1NFatWrarSd+vWreLaa68Ver1exMXFiX/9619i7dq1AoDYuHGjq9/AgQPdttYKDQ0V/fr1q3JOAEKSpCrbNFW3nVZ5ebl4/vnnRVJSklCr1SImJkbccccd4tixY0KIC1sY6fV6kZ2d7fbcS7f+qdzaqbotdmo7/sUXX4irr75aaLVaER4eLkaNGiX+/PPPKs/fv3+/uO2220RoaKjQ6XSiQ4cOYtq0adVeq67tsKp7HVevXl1t/0o2m00sXLhQDB8+XLRu3VpotVoREBAgrr76ajFnzhxhsVhcfS/eDuti//rXvwQA8e6777q9Jpduh1XdFk/VvX+VPNkOq7otoXDJ1mnVbakkRMXWaZXvUVhYmBg4cKBYt25drTVv375dBAcHi+uuu06Ul5fXqw4hhDh27JgYPXq0iImJEWq1WsTHx4u///3v4quvvnL1eemll0Tv3r1FaGio0Ov1omPHjmL27NmubZny8/PFhAkTRMeOHUVgYKAwGAyiT58+4ssvv6z2dbzU+vXrRb9+/YRerxchISHilltuEQcPHqyxf322w7rY3r17xT333CNiY2Ndfw/vuecesW/fvmr7p6eni65duwqNRiM6dOggPvnkk2rfu8OHD4vrrrtO6PV6AcCtthMnTojRo0eLFi1aCK1WK6644goxYcIEt5/jY8eOiTvuuMP1d653797iu+++c7tGTT/rNf19r6zz7Nmzbu1ff/216N+/vwgMDBSBgYGiY8eOYsKECeLIkSMev45EnpKE8NLndURERERETYhzXImIiIjILzC4EhEREZFfYHAlIiIiIr/A4EpEREREfoHBlYiIiIj8AoMrEREREfmFy/4GBE6nE6dPn0ZwcHCNdyEiIiIiIvkIIVBSUoK4uLhab5Jx2QfX06dPIyEhQe4yiIiIiKgOp06dQsuWLWs8ftkH1+DgYAAVL0R9b13YEDabDenp6Rg8eDDUanWTX4+IiIjI23ydZ4xGIxISEly5rSaXfXCtnB4QEhLis+AaEBCAkJAQBlciIiLyS3LlmbqmdXJxFhERERH5BQZXIiIiIvILDK5ERERE5BcYXImIiIjILzC4EhEREZFfYHAlIiIiIr/A4EpEREREfoHBlYiIiIj8AoMrEREREfkFBlciIiIi8gsMrkRERETkFxhciYiIiMgvMLgSERERkV9gcCUiIiIiF6dTILvQBADILjTB6RQyV3SBrMHV4XBg2rRpSEpKgl6vR5s2bfDiiy9CiAsvkBAC06dPR2xsLPR6PVJSUnD06FEZqyYiIiK6PGXmlWDepmOYuzETADB3YybmbTqGzLwSmSurIGtwfeWVVzBv3jy8++67OHToEF555RW8+uqreOedd1x9Xn31Vbz99tuYP38+tm/fjsDAQKSmpsJsNstYOREREdHlJTOvBEu2ZmH/6WIY9GoAgEGvxv7TxViyNatZhFeVnBf/+eefMWzYMAwdOhQAkJiYiM8++wy//PILgIrR1rfeegv//ve/MWzYMADARx99hOjoaKxYsQJ33323bLUTERERXS6cToG1+3NRUGZFu6ggKOAETECQToV2Og2O5pUi/UAurogMgkIhyVanrMG1b9++WLBgAX7//Xe0b98ev/32G7Zs2YI33ngDAHD8+HHk5OQgJSXF9RyDwYA+ffogIyOj2uBqsVhgsVhcj41GIwDAZrPBZrM18XcE1zV8cS0iIiIib8guNCHrrBHxIRoo4IQkHAAASTigkID4EA2O5xlxMr8E8WF6r1/f09wka3CdMmUKjEYjOnbsCKVSCYfDgdmzZ2PUqFEAgJycHABAdHS02/Oio6Ndxy6VlpaGWbNmVWlPT09HQECAl7+Dmq1bt85n1yIiIiJqrP46AAKA6UJbovnYhQc64LeMU/itCa5dXl7uUT9Zg+uXX36JTz/9FMuWLUOXLl2wZ88eTJo0CXFxcRgzZkyDzjl16lRMnjzZ9dhoNCIhIQGDBw9GSEiIt0qvkc1mw7p16zBo0CCo1eomvx4RERFRY2UXmjB3YyYMejWCdCpIwoFE8zFk6dpASEqUmu0oNtkw4Ya2TTLiWvkJeV1kDa7PPPMMpkyZ4vrIv1u3bjhx4gTS0tIwZswYxMTEAAByc3MRGxvrel5ubi66d+9e7Tm1Wi20Wm2VdrVa7dMg6evrERERETVUq0gVEluEYP/pYrTTaVA5jVVISjihQLbRim7xBrSKDG6SOa6eZiZZdxUoLy+HQuFeglKphNPpBAAkJSUhJiYGGzZscB03Go3Yvn07kpOTfVorERER0eVKoZCQ2jUa4YEVC7FKzXYAQKnZjqN5pQgP1GBwl2hZF2YBMo+43nLLLZg9ezZatWqFLl264Ndff8Ubb7yBBx98EAAgSRImTZqEl156Ce3atUNSUhKmTZuGuLg4DB8+XM7SiYiIiC4rbaOCMbZfItbuz0XWWSOgA4pNNnSLN2Bwl2i0jQqWu0R5g+s777yDadOm4bHHHkNeXh7i4uLwyCOPYPr06a4+//rXv1BWVobx48ejqKgI/fv3x5o1a6DT6WSsnIiIiOjy0zYqGFdcH4ST+SX4LeMUJtzQtsmmBzSEJC6+TdVlyGg0wmAwoLi42GeLs1atWoWbb76Zc1yJiIjIL/k6z3ia12Sd40pERERE5CkGVyIiIiLyCwyuREREROQXGFyJiIiIyC8wuBIRERGRX2BwJSIiIiK/wOBKRERERH6BwZWIiIiI/AKDKxERERH5BQZXIiIiIvILDK5ERERE5BcYXImIiIjILzC4EhEREZFfYHAlIiIiIr/A4EpEREREfoHBlYiIiIj8AoMrEREREfkFBlciIiIi8gsMrkRERETkFxhciYiIiMgvMLgSERERkV9gcCUiIiIiv8DgSkRERER+gcGViIiIiPwCgysRERER+QUGVyIiIiLyCwyuREREROQXGFyJiIiIyC8wuBIRERGRX2BwJSIiIiK/wOBKRERERH6BwZWIiIiI/AKDKxERERH5BQZXIiIiIvILDK5ERERE5BcYXImIiIjILzC4EhEREZFfYHAlIiIiIr/A4EpEREREfoHBlYiIiIj8AoMrEREREfkFWYNrYmIiJEmq8jVhwgQAgNlsxoQJExAREYGgoCCMGDECubm5cpZMRERERDKRNbju2LEDZ86ccX2tW7cOAHDnnXcCAJ588kmsXLkSy5cvx48//ojTp0/j9ttvl7NkIiIiIpKJSs6Lt2jRwu3xyy+/jDZt2mDgwIEoLi7GokWLsGzZMtx4440AgCVLlqBTp07Ytm0brr32WjlKJiIiIiKZyBpcL2a1WvHJJ59g8uTJkCQJu3btgs1mQ0pKiqtPx44d0apVK2RkZNQYXC0WCywWi+ux0WgEANhsNthstqb9Js5f5+I/iYiIiPyNr/OMp9dpNsF1xYoVKCoqwgMPPAAAyMnJgUajQWhoqFu/6Oho5OTk1HietLQ0zJo1q0p7eno6AgICvFlyrSqnPRARERH5K1/lmfLyco/6NZvgumjRIgwZMgRxcXGNOs/UqVMxefJk12Oj0YiEhAQMHjwYISEhjS2zTjabDevWrcOgQYOgVqub/HpERERE3ubrPFP5CXldmkVwPXHiBNavX4///ve/rraYmBhYrVYUFRW5jbrm5uYiJiamxnNptVpotdoq7Wq12qdB0tfXIyIiIvI2X+UZT6/RLPZxXbJkCaKiojB06FBXW8+ePaFWq7FhwwZX25EjR3Dy5EkkJyfLUSYRERERyUj2EVen04klS5ZgzJgxUKkulGMwGDBu3DhMnjwZ4eHhCAkJwcSJE5GcnMwdBYiIiIj+gmQPruvXr8fJkyfx4IMPVjn25ptvQqFQYMSIEbBYLEhNTcV7770nQ5VEREREJDfZg+vgwYMhhKj2mE6nw9y5czF37lwfV0VEREREzU2zmONKRERERFQXBlciIiIi8gsMrkRERETkFxhciYiIiMgvMLgSERERkV9gcCUiIiIiv8DgSkRERER+gcGViIiIiPwCgysRERER+QUGVyIiIiLyCwyuREREROQXGFyJiIiIyC8wuBIRERGRX2BwJSIiIiK/wOBKRERERH6BwZWIiIiI/AKDKxERERH5BQZXIiIiIvILDK5ERERE5BcYXImIiIjILzC4EhEREZFfYHAlIiIiIr/A4EpEREREfoHBlYiIiIj8AoMrEREREfkFBlciIiIicnE6BbILTQCA7EITnE4hc0UXqOQugIiIiIiah8y8Eqzdn4uss0b01wFzN2YisUUIUrtGo21UsNzlccSViIiIiCpC65KtWdh/uhgGvRoAYNCrsf90MZZszUJmXonMFTK4EhEREf3lOZ0Ca/fnoqDMinZRQQjSVXwoH6RToV1UEArKrEg/kCv7tAEGVyIiIqK/uOwiE46dLUWsQQdJktyOSZKEWIMOmXmlyC4yyVRhBQZXIiIior+4MqsdZrsDAZrqlz/pNUpY7A6UWe0+rswdgysRERHRX1ygRgWdSonyGoKpyeqAVqVEYA3B1lcYXImIiIj+4uJD9WjTIghnis0Qwn0eqxACZ4rNaBsVhPhQvUwVVmBwJSIiIvqLUygkpHaNRnigBkfzSlFqrhh5LTXbcTSvFOGBGgzuEg2FQqrjTE1cp6xXJyIiIqJmoW1UMMb2S0TXOAOKTTYAQLHJhm7xBoztl9gs9nHlDQiIiIiICEBFeL3i+iCczC/BbxmnMOGGtmgVGSz7SGsljrgSERERkYtCISE+rGIua3yYvtmEVoDBlYiIiIj8BIMrEREREfkFBlciIiIi8gsMrkRERETkFxhcvcjpFMgurLiHb3ahCU6nqOMZREREROQp2YNrdnY27rvvPkRERECv16Nbt27YuXOn67gQAtOnT0dsbCz0ej1SUlJw9OhRGSuuXmZeCeZtOoa5GzMBAHM3ZmLepmPIzCuRuTIiIiKiy4OswbWwsBD9+vWDWq3G6tWrcfDgQbz++usICwtz9Xn11Vfx9ttvY/78+di+fTsCAwORmpoKs9ksY+XuMvNKsGRrFvafLoZBrwYAGPRq7D9djCVbsxheiYiIiLxA1hsQvPLKK0hISMCSJUtcbUlJSa7/FkLgrbfewr///W8MGzYMAPDRRx8hOjoaK1aswN133+3zmi/ldAqs3Z+LgjIr2kUFQQEnYAKCdCq001XcNi39QC6uiAxqVvugEREREfkbWYPrt99+i9TUVNx555348ccfER8fj8ceewwPP/wwAOD48ePIyclBSkqK6zkGgwF9+vRBRkZGtcHVYrHAYrG4HhuNRgCAzWaDzWbz+veQXWhC1lkj4kM0UMAJSTgAAJJwQCEB8SEaHM8z4mR+iWszXyIiIqLmrDIzNUV2qu16dZE1uP7xxx+YN28eJk+ejOeeew47duzA448/Do1GgzFjxiAnJwcAEB0d7fa86Oho17FLpaWlYdasWVXa09PTERAQ4P1vAkB/HQABwHShLdF87MIDHfBbxin81iRXJyIiImoa69at88l1ysvLPeonCSFkW/qu0WjQq1cv/Pzzz662xx9/HDt27EBGRgZ+/vln9OvXD6dPn0ZsbKyrz8iRIyFJEr744osq56xuxDUhIQH5+fkICQnx+veQXWjC3I2ZMOjVCNKpIAkHEs3HkKVrAyEpUWq2o9hkw4Qb2nLElYiIiPyCzWbDunXrMGjQIKjV6ia/ntFoRGRkJIqLi2vNa7KOuMbGxqJz585ubZ06dcLXX38NAIiJiQEA5ObmugXX3NxcdO/evdpzarVaaLXaKu1qtbpJXvhWkSoktgjB/tPFaKfToHIaq5CUcEKBbKMV3eINaBUZzDmuRERE5FeaKj9Vdx1PyLqrQL9+/XDkyBG3tt9//x2tW7cGULFQKyYmBhs2bHAdNxqN2L59O5KTk31aa00UCgmpXaMRHlixEKvUbAcAlJrtOJpXivBADQZ3iWZoJSIiImokWYPrk08+iW3btuH//u//kJmZiWXLlmHBggWYMGECAECSJEyaNAkvvfQSvv32W+zbtw+jR49GXFwchg8fLmfpbtpGBWNsv0R0jTOg2FQxubjYZEO3eAPG9ktE26hgmSskIiIi8n+yThW45ppr8M0332Dq1Kl44YUXkJSUhLfeegujRo1y9fnXv/6FsrIyjB8/HkVFRejfvz/WrFkDnU4nY+VVtY0KxhXXB+Fkfgl+yziFCTe05fQAIiIiIi+SdXGWLxiNRhgMhjon+3qLzWbDqlWrcPPNN/tkTggRERGRt/k6z3ia12S/5SsRERERkScYXImIiIjILzC4EhEREZFfYHAlIiIiIr/A4EpEREREfoHBlYiIiIj8AoMrEREREfkFBlciIiIi8gsMrkRERETkFxhciYiIiMjF6RTILjQBALILTXA6m89NVlVyF0BEREREzUNmXgnW7s9F1lkj+uuAuRszkdgiBKldo9E2Klju8jjiSkREREQVoXXJ1izsP10Mg14NADDo1dh/uhhLtmYhM69E5goZXImIiIj+8pxOgbX7c1FQZkW7qCAE6So+lA/SqdAuKggFZVakH8iVfdoAgysRERHRX1x2kQnHzpYi1qCDJEluxyRJQqxBh8y8UmQXmWSqsAKDKxEREdFfXJnVDrPdgQBN9cuf9BolLHYHyqx2H1fmjsGViIiI6C8uUKOCTqVEeQ3B1GR1QKtSIrCGYOsrDK5EREREf3HxoXq0aRGEM8VmCOE+j1UIgTPFZrSNCkJ8qF6mCiswuBIRERH9xSkUElK7RiM8UIOjeaUoNVeMvJaa7TiaV4rwQA0Gd4mGQiHVcaYmrlPWqxMRERFRs9A2Khhj+yWia5wBxSYbAKDYZEO3eAPG9ktsFvu48gYEXmS3O7HrRAEAYNeJAvRKbAGVir8bEBERkX9oGxWMK64Pwsn8EvyWcQoTbmiLVpHBso+0VmJw9ZINh3KxdGsWTheW4vH2wPPf7EdcWBAe6JeImzpFy10eERERkUcUCgnxYXr8BiA+TN9sQivA4OoVGw7lIm31YZSYbYgJqrjTRJBWhd/zSpC2+jAAMLwSERERNRI/x24ku92JpVuzUGK2oVWY3u1OE63C9Cgx2/Dhz1mw250yV0pERETk3xhcG2n3qUJknStDRKAGCoX7y6lQKBARqMHx/DLsPlUoU4VERERElwcG10Y6V2aFzeGEXqOs9rheo4TN4cS5MquPKyMiIiK6vDC4NlJEoAZqpQImq6Pa4yarA2plxcgrERERETUcg2sj9UgIQ2JEIM6VWeF0us9jdTorRlqTIgPRIyFMpgqJiIiILg8Mro2kUinwQL9EBOvUOFlocrvTxMlCE0J0aozpm8j9XImIiIgaidtheUHlVleV+7gCQKnFjg7RwRjTl/u4EhEREXkDg6uX3NQpGgPbtcDOrLPIPbANs2/ryjtnEREREXkRUxURERER+QWOuHoJb/lKRERE1LQYXL2At3wlIiIianqcKtBIvOUrERERkW8wuDYSb/lKRERE5BsMro3EW74SERHR5cTpFMguNAEAsgtNcDqFzBVdwDmujXTxLV+DdVV/D+AtX4mIiMhfZOaVYO3+XGSdNaK/Dpi7MROJLUKQ2jUabaOC5S6PI66NxVu+EhER0eUgM68ES7ZmYf/pYhj0FYvNDXo19p8uxpKtWcjMK5G5QgbXRuMtX4mIiMjfOZ0Ca/fnoqDMinZRQW6LzdtFBaGgzIr0A7myTxvgVAEv4C1fiYiIyJ9lF5lw7GwpYg06SJIEXJRPJUlCrEGHzLxSZBeZkBAeIFudDK5eclOnaCS3DsfCrb8D5Zm4tXsMHu7XHgEBarlLIyIiIqpVmdUOs92BAI2+2uN6jRK5RjPKrHYfV+ZO1s+vZ86cCUmS3L46duzoOm42mzFhwgREREQgKCgII0aMQG5urowV1+zjjCwMeXcLlm45AQBYuuUEhry7BR9nZMlbGBEREVEdAjUq6FRKlNcQTE1WB7QqJQI18o55yj7xskuXLjhz5ozra8uWLa5jTz75JFauXInly5fjxx9/xOnTp3H77bfLWG31Ps7Iwpy1R5BjNEGrrtgWS6tWIsdowpy1RxheiYiIqFmLD9WjTYsgnCk2Qwj3eaxCCJwpNqNtVBDiQ6sfkfUV2acKqFQqxMTEVGkvLi7GokWLsGzZMtx4440AgCVLlqBTp07Ytm0brr32Wl+XWi2r1YEPNh+Hxe5AeIAaOpUEoGJIXVIoUFBuw6Itx3FXzwRoatjrlYiIiEhOCoWE1K7ROF1swtG8UsSHVGzjWWq2I9toRXigBoO7REOhkGStU/bgevToUcTFxUGn0yE5ORlpaWlo1aoVdu3aBZvNhpSUFFffjh07olWrVsjIyKgxuFosFlgsFtdjo9EIALDZbLDZbF6vf+3BMzCWmRCmU0KnkqBRVPyWolEIQCUhTKdEcakJaw9m429dYr1+fSIiIiJvaB2mw+g+LbHhUB5O5pcAOqDUZMGVccG4sWMUWofpmiRLAfD4vLIG1z59+mDp0qXo0KEDzpw5g1mzZmHAgAHYv38/cnJyoNFoEBoa6vac6Oho5OTk1HjOtLQ0zJo1q0p7eno6AgKaZhXczB4A4P6CP9au3O2x88SvWHXi1ya5PhEREZG3xAOI11X8d7IuGygBDu84jMNNeM3y8vK6OwGQxKUTGWRUVFSE1q1b44033oBer8fYsWPdRk8BoHfv3rjhhhvwyiuvVHuO6kZcExISkJ+fj5CQEK/XvObAGUz/Zj+0aiX0GiU0CoHH2pXjvaMBsDolmKwOWGwOvHBbV464EhERUbP2+S8n8VHGCZSUmTC1ux1pe1QIDtRjdHJr3N27VZNd12g0IjIyEsXFxbXmNdmnClwsNDQU7du3R2ZmJgYNGgSr1YqioiK3Udfc3Nxq58RW0mq10Gq1VdrVajXUau9vTZXaOR6vpR9DjtEESaEAzs9xtTolmO0ChWYHYg16pHaOh1rNOa5ERETUPH2ckYU56zJhsTsQplMBsANKFU4WmTFnXSagUOL+5MQmubanGU32XQUuVlpaimPHjiE2NhY9e/aEWq3Ghg0bXMePHDmCkydPIjk5WcYq3Wk0Sjw0IAlalRIF5TaYrA4AFdtGFJTboFMpMa5/EhdmERERUbN16WJz/fncotcoER6ghsXuwKItx2E9n3PkIuuI69NPP41bbrkFrVu3xunTpzFjxgwolUrcc889MBgMGDduHCZPnozw8HCEhIRg4sSJSE5ObjY7ClSq/O3jg83HYSwzAQAstoqR1nH9k5rstxMiIiIib0g/nIOzJWYEaFRQKBS4+NZZCoUCARoV8oxmpB/Owd+vjJetTlmD659//ol77rkH586dQ4sWLdC/f39s27YNLVq0AAC8+eabUCgUGDFiBCwWC1JTU/Hee+/JWXKN7k9OxF09E7D2YDacJ37FC7d1RWrneI60EhERUbOXU2yBQwhoVdVvd6VVSSi3CuQUW6o97iteCa4OhwP79u1D69atERYW5vHzPv/881qP63Q6zJ07F3Pnzm1siT6hUEhoEaRFLoAWQVrZ9zojIiIi8kSMQQulJMFiF9CrAYvNCeD8nwolLHYBpSQhxlB1HZEvNWiO66RJk7Bo0SIAFaF14MCB6NGjBxISErBp0yZv1uc3NhzKxdilO/D8N/sBAM9/sx9jl+7AhkPN8xa1RERERJUGd4xBi2AdSs12nDWaUWiyAgAKTVacNZpRarYjKkSHwR1rXiDvCw0Krl999RWuuuoqAMDKlStx/PhxHD58GE8++SSef/55rxboDzYcykXa6sP4Pa8EQdqKQewgrQq/55UgbfVhhlciIiJq1jQaJfq3i4RDCNgELkxxFYBNAA4h0K9tpOxTIBsUXPPz811bUq1atQp33nkn2rdvjwcffBD79u3zaoHNnd3uxNKtWSgx29AqTI8g3fngqlOhVZgeJWYbPvw5C3a7U+ZKiYiIiKpntztx8lw5AjQqaJXSxbkVWqWEAI0KpwrKZc8zDQqu0dHROHjwIBwOB9asWYNBgwYBqLjrgVL511qMtPtUIbLOlSEiUHN+Fd4FCoUCEYEaHM8vw+5ThTJVSERERFS7yjzTKlyPbvEhSIoIBAAkRQSiW3wIWoXrm0WeaVBwHTt2LEaOHImuXbtCkiSkpKQAALZv346OHTt6tcDm7lyZFTaHE3qNEkIIlJjtAIASsx1CCOg1StgcTpwrs8pcKREREVH1Ls4zCoUCalVFRFSrFFAoFM0mzzRoV4GZM2eia9euOHXqFO68807XnaqUSiWmTJni1QKbu4hADdRKBc4azSgy2SEcdqA1cPxsKSSlCqF6FdTKipFXIiIioubIX/JMg7fDuuOOO9weFxUVYcyYMY0uyN/0SAhDsE6FIzklAIBgTcUWWEqFhBKLHWUWOzrEhKBHgufbhBERERH5kr/kmQZNFXjllVfwxRdfuB6PHDkSERERaNmyJfbu3eu14vyKBCgk931bFZIESIAkiRqeRERERNSMNPM806DgOn/+fCQkJAAA1q1bh3Xr1mH16tX429/+hqefftqrBTZ3u08VosRsR1yIDnq1Ag5nxZvqcAro1UrEhehgNNlln8xMREREVBN/yTMNmiqQk5PjCq7fffcdRo4cicGDByMxMRF9+vTxaoHNXeVk5vgwPaKCNThXagZgR0SQBhFBOkChQHahSfbJzEREREQ1uTjPRAQokWu0ALAjSKtCdIgWSrW6WeSZBgXXsLAwnDp1CgkJCVizZg1eeuklAIAQAg6Hw6sFNneVk5lPF5ajoMwGCRX7m+UYLThjtCE8UA21Uin7ZGYiIiKimlTmmWO5pSg226FRVoy4FphsyCm1w6BTIVivlj3PNCi43n777bj33nvRrl07nDt3DkOGDAEA/Prrr2jbtq1XC2zueiSEQaOU8GehFQJAwPlXVCEB5XaBHKMVV0QGyj6ZmYiIiKgmPRLCYLM7UHR+W8+LCQBFZjv0GoXseaZBwfXNN99EYmIiTp06hVdffRVBQUEAgDNnzuCxxx7zaoHNndMpYDTbIQBIACrnM5+fxwwBoMRig9Mp/4RmIiIioupYrY46pwHkl9pgtTqgUjVoiZRXNCi4qtXqahdhPfnkk40uyN+kH85BmcWOII0CVoeAU1QEVKcA1EoJGqWEUrMd6Ydz8Pcr42WuloiIiKiqBT8fg62Ou7nanAILfj6GSSny3WyqwZH5448/Rv/+/REXF4cTJ04AAN566y3873//81px/iCn2AKHEAjSqRAeoEaAquKWtwEqJcID1AjSqeAQAjnFFpkrJSIiIqrenwVmAIBSAtQKCYrznyArzj9WSu795NKg4Dpv3jxMnjwZQ4YMQVFRkWtBVmhoKN566y1v1tfsxRi0UEoSik02nC21otRW8VqU2hw4W2pFsckGpSQhxqCVuVIiIiKi6rUM1wEAHKJiZLVyhqPz/GOHcO8nlwYF13feeQcLFy7E888/D6VS6Wrv1asX9u3b57Xi/MHgjjHQqpUw2Sre1MoteyVUvPkmm4BOrcTgjjFylklERERUo/F920BZRypUKSr6yalBwfX48eO4+uqrq7RrtVqUlZU1uih/Ji75k4iIiKi5U6kU0NWx6EqnUsi6MAtoYHBNSkrCnj17qrSvWbMGnTp1amxNfiX9cA4sNgcC1Bfmg1RSSECAWoLZ5kD64Rx5CiQiIiKqQ/rhHAgBaJTVH9coK6YNyJ1nGrSrwOTJkzFhwgSYzWYIIfDLL7/gs88+Q1paGj744ANv19isVS7OCgtQwwAJwukA4ECYXg1JoYSAQGG5jYuziIiIqNmqzDPhgRo4HU44HE4ADgSplTDoFFAoFc0izzQouD700EPQ6/X497//jfLyctx7772Ii4vDf/7zH9x9993errFZq1ycZbEL6NUKSOeHXRUKCZAkmG1OLs4iIiKiZu3iPKNTKV0fyauVCkhKJcz25pFnGhRcAWDUqFEYNWoUysvLUVpaiqioKG/W5TcGd4zBnODfcbrIhFKTDarzt0grLLfC7qgIr/Fhei7OIiIiomarMs9kF5ajWADqyjxjtsHmsEMhAS3DA2TPM42eYRsQEPCXDa0AoNEo0b9dJBxCwCbgtjrLJgCHEOjXNhKamiaNEBEREclMo1GiW0sD7AK49D4ETgB2AXSNN8ieZxoUXHNzc3H//fcjLi4OKpUKSqXS7euvxG534uS5cgRolNAqJbddBbRKCQEaJU4VlMNur+N2FEREREQysVod2PdnMZSSVCUcKgAoJQn7s4thtTrkKM+lQVMFHnjgAZw8eRLTpk1DbGwsJEmq+0mXqd2nCpF1rgytwgMQoFagzGwDYERSRCACdWqU25w4nl+G3acK0TspQu5yiYiIiKpIP5yDsyVmhOhV0KkUEI7zi811atcc1zyjWfZb2DcouG7ZsgWbN29G9+7dvVyO/zlXZoXN4YReo4RwOmFzVIys2hxOCCGg1yhRUGbFuTKrzJUSERERVa9yVwGtSoIk4ZLF5oBWJaHcKv8t7BsUXBMSEiAEt9gHgIhADdRKBU6cLUOhyQaVouJ1OVVkwvECM8L0aui1KkQEamSulIiIiKh6lbsKlJrtsDoElFLFQFyhyQqHUECjlJrFrgINmuP61ltvYcqUKcjKyvJyOf6nR0IYIATyy22u+/hWcgggv9wGCaKiHxEREVEzNLhjDAK1KpRanbA5hOumSgoJsDkESq1OBOlUsu8q0KAR17vuugvl5eVo06YNAgICoFar3Y4XFBR4pTh/YLc7ca78wjQA6ZI/AeBcmQ12u1P226QRERERVUehkBCiUyG/1AoBoPKDdSEqFpxLAIK16oqpAzJqUHB98803/9ILsi72xe6TsNicUCkqboV28a4CCqniy2xz4IvdJzGm7xVylkpERERUrd2nCmF1CMSEaFBQZoPzfHJ1iopdksID1bA6nLIvNm/wrgI1MZlMDa3FL2UXmuEUgF4lQYIEiIptIlQSoFIpICBgsglkF5plrpSIiIioepWLzePDAhAb4sSpc6UAHAjWKJEQEQRJqUB2oUn2xeYN+uz68ccfr7a9rKwMN998c6MK8jfxYTooJMBkEyizOWE/P+RqF0CZzQmTrWKeSHyYTt5CiYiIiGpQudj899wS7P7TCOP5/VqNVgd2/2nE7zklUCsVsi82b1Bw/f777zFjxgy3trKyMvztb3+D3W73SmH+4q4eraCQLkwRuFTllIG7erTyZVlEREREHuuREAaT1YESc/U3GCixOGCyOmRfbN6gqQLp6ekYMGAAwsLCMGnSJJSUlCA1NRUqlQqrV6/2do3NmtMpquwmcCmHqOhHRERE1ByZLfY6pwGcK7PCbLEjSCXfqGuDRlzbtGmDNWvW4MUXX8Tbb7+NwYMHQ6PRYPXq1QgMDPR2jc3agp+Poa5M6hQV/YiIiIiao9d/OFLjp8eVxPl+cmrQiCsAXHnllfjuu+8waNAg9OnTB9999x30er03a/MLfxZULLpSSqh25LWyvbIfERERUXPjaU6RO894HFyvvvrqarfA0mq1OH36NPr16+dq2717t3eq8wMtwysWXdU0XaCyvbIfERERUXPjaU6RO894HFyHDx/ehGX4r/F92+Ct9XVPAxjft40PqiEiIiKqv6du7IAlW0961E9OHgfXS3cRoApWR/Wr76rrFwB13R2JiIiIfKzyhgPe6tdUGrQ4a8eOHdi+fXuV9u3bt2Pnzp2NLsqfTP3fPq/2IyIiIvK1F1Yf9Gq/ptKg4DphwgScOnWqSnt2djYmTJjQ6KL8iad3xOKds4iIiKi58pfFWQ0KrgcPHkSPHj2qtF999dU4eFDeJO5rnt4Ri3fOIiIioubKXxZnNSi4arVa5ObmVmk/c+YMVKqG7bD18ssvQ5IkTJo0ydVmNpsxYcIEREREICgoCCNGjKj2unJKG9bNq/2IiIiIfG36kM6ouneUO+l8Pzk1KLgOHjwYU6dORXFxsautqKgIzz33HAYNGlTv8+3YsQPvv/8+rrzySrf2J598EitXrsTy5cvx448/4vTp07j99tsbUnKTCQ3WQV3Hq6hWVPQjIiIiao5CgrSICan9jlgxIRqEBGl9VFH1GhRcX3vtNZw6dQqtW7fGDTfcgBtuuAFJSUnIycnB66+/Xq9zlZaWYtSoUVi4cCHCwi7c/7a4uBiLFi3CG2+8gRtvvBE9e/bEkiVL8PPPP2Pbtm0NKbtJ5BWVweasvY/NWdGPiIiIqDkqL7ehoMxea5+CcjvKy20+qqh6DfpcPz4+Hnv37sWnn36K3377DXq9HmPHjsU999wDtbp+Wz5NmDABQ4cORUpKCl566SVX+65du2Cz2ZCSkuJq69ixI1q1aoWMjAxce+211Z7PYrHAYrG4HhuNRgCAzWaDzeb9F3vCpzuhVV7YGkKrEG5/Xtxv2fi+Xr8+ERERUWMt3Po7AAf0SkAhASqpIsfoFAIqqeL29U7hwMKtv+Ox69t7/fqeZrQG3/I1MDAQ48ePb+jTAQCff/45du/ejR07dlQ5lpOTA41Gg9DQULf26Oho5OTk1HjOtLQ0zJo1q0p7eno6AgICGlVvde5rCaBl1fYXe106DFuEVatWef36RERERI2VCODV3lXbX7g0z5RnYtWqTK9fv7y83KN+HgfXb7/9FkOGDIFarca3335ba99bb721zvOdOnUKTzzxBNatWwedznvzP6dOnYrJkye7HhuNRiQkJGDw4MEICQnx2nUq3bvgZ+w9XeJ6rFUIvNjLiWk7FbA4L0xzvjIumCOuRERE1Cy9t+l3vLfpuOtxTXnmseuTmmTEtfIT8rrU65avOTk5iIqKqvX2r5IkweHB3aR27dqFvLw8t221HA4HfvrpJ7z77rtYu3YtrFYrioqK3EZdc3NzERMTU+N5tVottNqqE4fVanW9pzF4Yu6oXuj98qYq7RanBItDcuvXFNcnIiIiaqyH+7XHmxuyqrRfmmce7te+SfKMp+f0OLg6nc5q/7uhbrrpJuzb5343qbFjx6Jjx4549tlnkZCQALVajQ0bNmDEiBEAgCNHjuDkyZNITk5u9PW9RSHVtXlE/foRERER+Zq/3MK+wXNcGys4OBhdu3Z1awsMDERERISrfdy4cZg8eTLCw8MREhKCiRMnIjk5ucaFWXKY8PmvHvf74pF+TVwNERERUf3V5xb28+67pomrqVmDg+uGDRuwYcMG5OXlVRmBXbx4caMLA4A333wTCoUCI0aMgMViQWpqKt577z2vnNtbzhRb6u5Uj35EREREvuYvt7BvUHCdNWsWXnjhBfTq1QuxsbGQvPQx+KZNm9we63Q6zJ07F3PnzvXK+ZtCrEGLkwUmj/oRERERNUfxYTrsza57gZTct7BvUHCdP38+li5divvvv9/b9fiduXdfjV5pGz3qR0RERNQcpQ3rhtX7N3jUT04NunOW1WpF377c2gkAAjxcBedpPyIiIiJfC9JrEKxR1tonWKtEkL7228I2tQYF14ceegjLli3zdi1+acHPx7zaj4iIiMjXdp8qRGigBjpV9dFQp1IgNECD3acKfVyZO4+nCly8qb/T6cSCBQuwfv16XHnllVX23nrjjTe8V2Ez92dBxSRlpQQ4RNXjle2V/YiIiIiam3NlVtgcTnSJD4G53ITjlfkGQJcWWugC9MguNOFcmVXWOj0Orr/+6r7tU/fu3QEA+/fvd2v31kItf9EyvGKScnWh9eL2yn5EREREzU1EoAZqpQIHsothtgtoz88acAA4cNYCncqKFsE6RATKO1XA4+C6cWPdC5D+isb3bYO31tc9DWB83zY+qIaIiIio/nokhKGo3AqzvfqROLNdoKjcih4JYT6uzF295rgqlUrk5eU1VS1+qT53miAiIiJqjkpNVpRYas8qJRYHSk3yThWoV3AVoobPw//C6nOnCSIiIqLmyF/yTIN2FaAL/OVOE0REREQ18Zc8U+8bEHzwwQcICgqqtc/jjz/e4IL8jb/caYKIiIioJv6SZ+odXOfPnw+lsuYNaiVJ+ksFV3+50wQRERFRTfwlz9Q7uO7cuRNRUVFNUYtfCg3WIVSvQpHJXnMfvQqhwRxxJSIiouYpNFiHALUC5TZnjX0C1ArZ80y95rj+1fZo9URpmRUl5ppDKwCUmO0olXnDXiIiIqKaFJWYaw2tAFBuc6KoRN45rtxVoJFe/+GI6yYDl8b6yscOUdGPiIiIqDm6LHcVmDFjRp0Ls/5qPL2VK2/5SkRERM3VZbmrwIwZM1z/XVRUhF9++QV5eXlwOt2HlkePHu2d6vzAxbdyvXQ8WtTQj4iIiKg5uWx3FQCAlStXYtSoUSgtLUVISIjb3FdJkv5SwfWpGztgydaTHvUjIiIiao78ZVeBBt2A4KmnnsKDDz6I0tJSFBUVobCw0PVVUFDg7RqbNaeH83497UdERERE1WtQcM3Ozsbjjz+OgIAAb9fjd15YfdCr/YiIiIh87bJcnFUpNTUVO3fu9HYtfomLs4iIiMjfXZaLsyoNHToUzzzzDA4ePIhu3bpBrVa7Hb/11lu9Upw/aBmuA4572I+IiIioGbqsF2c9/PDDAIAXXnihyjFJkuBwOBpXlR+ZPqQzvtp12qN+RERERM2RvyzOalBwvXT7q78ylcKz2Rae9iMiIiLytQCtGholYK1l7FGjrOgnJ6apRlrw8zGv9iMiIiLytfTDOVApFFDWcFyJikG49MM5viyrCo9HXN9++22MHz8eOp0Ob7/9dq19H3/88UYX5i8qF10pJbhu/XqxynYuziIiIqLmKqfYAocQaBGigc1qQ6ntQqiJ0ElQa9QoLLchp9giY5X1CK5vvvkmRo0aBZ1OhzfffLPGfpIk/aWCa+Wiq+pC68XtXJxFREREzVWMQQulJCHXaIUAoL1o6PWcWUAyW6FXKxBj0MpWI1CP4Hr8+PFq//uvbnzfNnhrfd3TAMb3beODaoiIiIjqb3DHGDzp2FPl9vWVBACbw4nBHWN8WVYVDZrjun///hqPrVixoqG1+KVSq9Wr/YiIiIh8rdRsha2Otfc2Z0U/OTX4BgTVjbp+/fXXGDVqVKOL8ifjP9nl1X5EREREvvbkV795tV9TaVBwfeihh5CSkoKcnAsry7744guMHj0aS5cu9VZtfiHH6NlvHp72IyIiIvK100WeLSL3tF9TaVBwnTVrFm6++WakpKSgoKAAy5Ytw9ixY/HRRx/hzjvv9HaNzVpMiMar/YiIiIh8LS7Us0XknvZrKg3ex/Wdd97BVVddhWuvvRYPP/wwPvvsM4wYMcKbtfmFBff19Go/IiIiIl97846rvNqvqXi8q8C3335bpe3222/H5s2bcc8990CSJFefW2+91XsVNnNRoYFe7UdERETka+EhekhAjbsKAIB0vp+cPA6uw4cPr/HY4sWLsXjxYgAV+7g6HLXcL+wy80deocf9rogKa+JqiIiIiOrvz3PGWkMrUBFq/zxnRMuIEF+UVC2Ppwo4nU6Pvv5KoRUA7pz/i1f7EREREfnavR94llM87ddU6jXHNSMjA999951b20cffYSkpCRERUVh/PjxsFjkvRWYrxktdq/2IyIiIvK1gnLPcoqn/ZpKvYLrrFmzcODAAdfjffv2Ydy4cUhJScGUKVOwcuVKpKWleb3I5ixE69lsC0/7EREREflaeIBnOcXTfk2lXsH1t99+w0033eR6/Pnnn6NPnz5YuHAhJk+ejLfffhtffvml14tszpY/2tur/YiIiIh8bdlDnuUUT/s1lXoF18LCQkRHR7se//jjjxgyZIjr8TXXXINTp055rzo/oFN59puHp/2IiIiIfC1U59n+rJ72ayr1Cq7R0dGuW71arVbs3r0b1157ret4SUkJ1Gq1dyts5u5fvMOr/YiIiIh87fUfjni1X1OpV3C9+eabMWXKFGzevBlTp05FQEAABgwY4Dq+d+9etGnTxutFNmf5ZTav9iMiIiLytT8LPLuVq6f9mkq9guuLL74IlUqFgQMHYuHChVi4cCE0mgu3Ml28eDEGDx7s8fnmzZuHK6+8EiEhIQgJCUFycjJWr17tOm42mzFhwgREREQgKCgII0aMQG5ubn1KbnKRgZ6NMHvaj4iIiMjXWoZ7NgXA035NpV7BNTIyEj/99BMKCwtRWFiI2267ze348uXLMWPGDI/P17JlS7z88svYtWsXdu7ciRtvvBHDhg1z7Vzw5JNPYuXKlVi+fDl+/PFHnD59Grfffnt9Sm5yHz94jVf7EREREfnaUzd28Gq/ptKgFUMGg6Ha9vDw8Hqd55ZbbnF7PHv2bMybNw/btm1Dy5YtsWjRIixbtgw33ngjAGDJkiXo1KkTtm3b5ja3Vk7lNs+mAHjaj4iIiMjXrB7eQMrTfk2l2Sx1dzgcWL58OcrKypCcnIxdu3bBZrMhJSXF1adjx45o1aoVMjIyagyuFovF7SYIRqMRAGCz2WBrgvA46v3t0Cov3CRNqxBuf17cb8vUFBARERE1N898/atHeeaZr3/F/Pu8/ymypxlN9uC6b98+JCcnw2w2IygoCN988w06d+6MPXv2QKPRIDQ01K1/dHQ0cnJyajxfWloaZs2aVaU9PT0dAQEB3i4fz11VffuLvZyXtDiwatUqr1+fiIiIqLFuDQdurWaL1qp55myT5Jny8nKP+skeXDt06IA9e/aguLgYX331FcaMGYMff/yxweebOnUqJk+e7HpsNBqRkJCAwYMHIyQkxBslu+mfth5FlgvD5lqFwIu9nJi2UwGLU3K1h2qVHHElIiKiZunRT3ZgS2aB63FNeaZ/2/AmGXGt/IS8LrIHV41Gg7Zt2wIAevbsiR07duA///kP7rrrLlitVhQVFbmNuubm5iImJqbG82m1Wmi12irtarW6SfaY/fSRPkh5M6NKu8UpweKQ3Pr91fa4JSIiIv8wZ8TV6PF/P1RpvzTPzBlxdZPkGU/PWa9dBXzB6XTCYrGgZ8+eUKvV2LBhg+vYkSNHcPLkSSQnJ8tYoTt/udMEERERUU1UCs8ioaf9moqsV586dSp++uknZGVlYd++fZg6dSo2bdqEUaNGwWAwYNy4cZg8eTI2btyIXbt2YezYsUhOTm42OwoAwITPf/VqPyIiIiJfe2H1Qa/2ayqyThXIy8vD6NGjcebMGRgMBlx55ZVYu3YtBg0aBAB48803oVAoMGLECFgsFqSmpuK9996Ts+QqzhRb6u5Uj35EREREvuYvd86SNbguWrSo1uM6nQ5z587F3LlzfVRR/cUatDhZYPKoHxEREVFz1DJcBxz3sJ+Mmt0cV38z9+6rvdqPiIiIyNemD+kMqY4+0vl+cmJwbaRIg2d7w3raj4iIiMjXQoK0iAnR1NonJkSDkCB5P0FmcG2kk/nFXu1HRERE5Gvl5TYUlNlr7VNQbkd5uby3sGdwbaS7F/zi1X5EREREvrbg52OwOJw1BkMFAIvdiQU/H/NlWdXWQY1QaKr9t5P69iMiIiLytcrdAqQaJrpWtsu9qwCDayOF6T3bmMHTfkRERES+VrlbgENUf7yynbsK+LnPx/f2aj8iIiIiXxvft41X+zUVBtdGcooafjVpYD8iIiIiX7M7nV7t11QYXBtp5PueLbrytB8RERGRr/nLLV8ZXBup2OzZoitP+xERERH5mr/c8pXBtZEMOs8WXXnaj4iIiMjXPF10xcVZfu7LRzxbdOVpPyIiIiJf8/RWrrzlq58L0tR+e7T69iMiIiLyNUVNG7g2sF9TYXBtpAmf/+rVfkRERES+9voPR7zar6kwuDbSmWKLV/sRERER+RoXZ/1FxBq0Xu1HRERE5GtcnPUXMffuq73aj4iIiMjXnrqxg1f7NRUG10binbOIiIjI3ykkCXUtu5LAxVl+b/wnu7zaj4iIiMjXFvx8DHUNsYnz/eTEXfEbKcdo9Wo/IiIiIl+rXHSllCpGVivHVSUAKqkitDoEF2f5vZgQz/Zn9bQfERERka9VLroSAnAKuEZfBc4/Fu795MLg2kgL7uvp1X5EREREvja+bxtolQo4ATgvOVbZplUpML5vG98XdxEG10aKCg2ETlX7RGWdSkJUaKCPKiIiIiKqn4AANaLr+HQ4OliDgAC1jyqqHoNrI5WWWWFz1D6d2eYQKC3jHFciIiJqnkrLrMguqn3+anaRWfY8w+DaSK//cAR15FY4hPy3SCMiIiKqycV55tLPkSsfN4c8w+DaSP5yizQiIiKimvhLnmFwbSR/uUUaERERUU0uzimXfpAsaugnBwbXRvKXW6QRERER1cRf8gyDayPllJZ6tR8RERGRr6mUCqjqSIVqRUU/OTG4NtId837xaj8iIiIiX/ti90nXTQZq4hQV/eTEW742UqnV4dV+RERERL6WXWiGUwABagnCKVzzWiUAeiUgKSSYbALZhVyc5deCNEqv9iMiIiLytfgwHRQSYLYJmBzut3w1OSraFVJFPzkxuDbSV//o7dV+RERERL52V49WUCqlKrd7reQEoFJKuKtHK1+WVQWDayMFaWq/PVp9+xERERHJQapjjmuVfbJkwODaSGM/3OnVfkRERES+9sXuk7A7RY3BUAHA7hRcnOXv8ko8u2evp/2IiIiIfK1ycZZeLUGSJEiiYlF55RZYQgguzrocRAV7NgXA035EREREvla5OMvqEDDZnLCdn+xqcwImmxNWBxdnXRaWjOnl1X5EREREvnZXj1bQqhWwOyv2a5XOt0uoeGx3Ajq1gouz/J1O5dlsC0/7EREREfmaSqVARMCFT4fFJX8CQHigBqq6bq/VxBhcG2nq//Z5tR8RERGRr+0+VQhIEiID1VBK7seUEhAZqAYgVfSTEYcBG8nTScpyT2YmIiIiqsm5MitsDidaRwaitdOJ4nIrgFIkhOphCNAACgWyC004VybvYnOOuDaSp5OU5Z7MTERERFSTiEAN1EoFTFYHFAoFAjQVY5sBGhUUiop2tVKBiEB5F5vLGlzT0tJwzTXXIDg4GFFRURg+fDiOHDni1sdsNmPChAmIiIhAUFAQRowYgdzcXJkqriptWDev9iMiIiLytR4JYUiMCER2kRlHckpwPL8UAHA8vxRHckqQXWRGUmQgeiSEyVqnrMH1xx9/xIQJE7Bt2zasW7cONpsNgwcPRllZmavPk08+iZUrV2L58uX48ccfcfr0adx+++0yVu0uNFgHdR2volpR0Y+IiIioOVKpFOjeKhTlVjtKrA63XQVKrA6YrHZclRAq++IsWee4rlmzxu3x0qVLERUVhV27duG6665DcXExFi1ahGXLluHGG28EACxZsgSdOnXCtm3bcO2118pRtpu8ojLXXmc1sTkr+kWFBvqmKCIiIqJ6sNud2HOyCIEaFRxOB4SzItwIAEEaJZQKBX47VQS73SlreG1Wi7OKi4sBAOHh4QCAXbt2wWazISUlxdWnY8eOaNWqFTIyMqoNrhaLBRaLxfXYaDQCAGw2G2w2m9drnvDpTmiVFzaL0CqE258X91s2vq/Xr09ERETUWLtOFOB0YSlah2kRqFXCYrEDKEb7FoHQalUosziQXVCKnVln0bN1uNev72lGazbB1el0YtKkSejXrx+6du0KAMjJyYFGo0FoaKhb3+joaOTk5FR7nrS0NMyaNatKe3p6OgICArxe930tAbSs2v5ir0uHYYuwatUqr1+fiIiIyBseb1+1bXTrYrfHuQe2YdUB71+7vLzco37NJrhOmDAB+/fvx5YtWxp1nqlTp2Ly5Mmux0ajEQkJCRg8eDBCQkIaW2YV9y74GXtPl7geaxUCL/ZyYtpOBSzOCxuhXRkXzBFXIiIiapZ2nSjA89/sh83hQFGZDRKceKGXE9N3KiCgQGigGmqlErNv69okI66Vn5DXpVkE13/+85/47rvv8NNPP6FlywvDlzExMbBarSgqKnIbdc3NzUVMTEy159JqtdBqtVXa1Wo11Gq112ufO6oXer+8qUq7xSnB4pDc+jXF9YmIiIgaq1diC0BS4FRRxb7zelVFhrEJCSY7UFJkwxWRavRKbNEkc1w9zUiyLg0TQuCf//wnvvnmG/zwww9ISkpyO96zZ0+o1Wps2LDB1XbkyBGcPHkSycnJvi63Wma73av9iIiIiHzN6RQwmu2uW7xKkvufAkCJxQ6nU1T3dJ+RNbhOmDABn3zyCZYtW4bg4GDk5OQgJycHJpMJAGAwGDBu3DhMnjwZGzduxK5duzB27FgkJyc3ix0FAODuBb94tR8RERGRr6UfzkGZxY4grQJqpYTKfOoUgFopIUirQKnZjvTD1a8x8hVZpwrMmzcPAHD99de7tS9ZsgQPPPAAAODNN9+EQqHAiBEjYLFYkJqaivfee8/Hldas0OTZSKqn/YiIiIh8LafYAocQCNGqAQ1gsdoAOKBTKqDVqAEJKCy3IafYUue5mpKswVWIuoebdTod5s6di7lz5/qgovoL06tgstV9394wfbOYTkxERERURYxBC6UkoajcBotdQHN+q89yuxNFFis0KglKSUKMoeo6Il+S9/YHl4HPx/f2aj8iIiIiXxvcMQZqhQSzXeDSYUUBwGIXUCslDO5Y/eJ4X2FwbSSnB6PG9elHRERE5GtOp4DFWfutQK0O5197cdblYOT7ni268rQfERERka99sfskbHYBpVT9caUEWO0CX+w+6dvCLsGJl41UbPZs0ZWn/YiIiIh8LbvQDKcA9GoJEgDp/IQBtQJQKSoemWwC2YVmWevkiGsjGXSeZX9P+xERERH5WnyYDorzo6omu4Dt/KwBmxMw2QWsdgGFVNFPTgyujfTlI54tuvK0HxEREZGv3dWjFbRqBeyiYu/WyhkDEioe2wWgUytwV49WcpbJ4NpYOpVnI6me9iMiIiLyNZVKgYhAjeuxuORPAAgP1DTJ7V7rg8G1kcZ+uNOr/YiIiIh8bfepQgASIgPVVRZoKSUgMlANQDrfTz4cBmykvJK6bz5Qn35EREREvnauzAqbw4nWkYFIFALF5RYApWgVpochQAshScguNOFcmbx5hiOujRQVrKm7Uz36EREREflaRKAGaqUCJqsDSqUSUSEVi7CiQnRQKpUwWR1QK92nE8iBwbWRlozp5dV+RERERL7WIyEMiRGBOFdmhfOSGxE4nU6cK7MiKTIQPRLCZKqwAoNrI8WEBUGjrL2PRlnRj4iIiKg5UqkUeKBfIoJ1apwsNKH0/P7zpWY7ThaaEKJTY0zfRNkXZ3GOayOVllnhqP0OaXA4K/oFyTy8TkRERFSTmzpFAwCWbs3C6cJSAECpxY4O0cEY0zfRdVxODK6N9PoPR+Co47a9DlHRb8Yt3XxTFBEREVED3NQpGgPbtcDOrLPIPbANs2/ril6JLWQfaa3UPKrwY38WeHbrM0/7EREREclJoZAQE6IHAMSE6KFQSHU8w3c44tpILcM9u/WZp/2IiIiI5JKZV4K1+3ORddaI/jpg7sZMJLYIQWrXaLSNCpa7PI64NtZTN3bwaj8iIiIiOWTmlWDJ1izsP10Mg14NADDo1dh/uhhLtmYhM69E5goZXBvNaLF4tR8RERGRrzmdAmv356KgzIp2UUEI0lV8KB+kU6FdVBAKyqxIP5ALp7OOhT1NjMG1ke5fvMOr/YiIiIh8LbvIhGNnSxFr0EGS3Oe0SpKEWIMOmXmlyC4yyVRhBQbXRsovs3m1HxEREZGvlVntMNsdCNCo4HQ6ceZ8QD1TZILT6YReo4TF7kCZ1S5rnVyc1UiRgWoUm+p+EyMD1T6ohoiIiKj+AjUq6FRKHM4pxu85pTBZrOh7FfDD4TzotRq0jwlCiE6DQI280ZEjro308YPXeLUfERERka/Fh+oBCGQcK8C5MivU5/dtVasUOFdmRcaxAgDifD/5MLg2UniAZ2+gp/2IiIiIfM3pFDhxrhxOIaBWSlCe37tVqZCgVkpwCoGTBeVcnOXvvth9Eso69uVVShX9iIiIiJqj3acKkVdiQVyoDkFaNeznbwtqdwgE6dSIC9Uh12jB7lOFstbJOa6NlF1ohlMAAWoJNpv7byFqAGq1BJNNILuQd84iIiKi5ulcmRU2hxNRIXooJQlmiw2ACS2CtNBp1XAIgexCE86VWWWtk8G1keLDdFBIQPn50Kq96JgNgM0moJQq+hERERE1RxGBGqiVChSVW2GxCTgcFQvPz5ZaoDQ5oFVLUCsViAjUyFonpwo00l09WsFRx3QPh6joR0RERNQc9UgIQ1SwFqeLzCi12KA6Pw9SpZRQarHhdJEZ0SFa9EgIk7VOBtdGKrV4NmTuaT8iIiIiX1MoJLSOCIBCkmBzCDjOL8JyOAVsDgGFJKFVeAAUijoW9jR1nbJe/TIw4fNfvdqPiIiIyNcq7oglIblNOCICNbDZnQAAm92JiCANktuEA5Bkv3MW57g20plii1f7EREREfla5Z2zOsYY0CkmBHnF5QBO4caOUYgyBMAJICu/TPY7Z3HEtZFiDdq6O9WjHxEREZGvVd45q9xqhyRJCNJW3PEzSKuGJEkwWR3QqpS8c5a/m3v31V7tR0RERORr8aF6tGkRhKO5pdiRVYBfsgoAAL9kFWBHVgGO5paibVQQ75zl7yINAQhQ1/4yBqgViDQE+KgiIiIiovpRKCR0jA3GGaMZf+SXoXINlkIC/sgvwxmjGR1igrk4y9+VlllhOT+BuSYWuxOlMm/YS0RERFQTp1Pg8JkSxBp0uCIiEJV3dnUK4IrIQMQadDiSU8Jbvvq713844tE+rq//cMQ3BRERERHVU3aRCcfOlqJdVBCuSQpH78RwAEDvxHBckxiOdlFByMwrlX1XAQbXRvqzwLNbuXraj4iIiMjXKncVCNCoIEkSgvUVi7CC9RWP9RolLHYHdxXwdy3DPbuVq6f9iIiIiHzt4l0FqsNdBS4TT93Ywav9iIiIiHytcleBM8VmCOE+B1IIgTPFZu4qQERERETyUygkpHaNRnigBkfzSlFqrhh5LTXbcTSvFOGBGgzuEs1dBfydp4uuuDiLiIiImrO2UcEY2y8RXeMMKDbZAADFJhu6xRswtl8i2kYFy1whb/naaFycRURERJeLtlHBuOL6IJzML8FvGacw4Ya2aBUp//6tlWQdcf3pp59wyy23IC4uDpIkYcWKFW7HhRCYPn06YmNjodfrkZKSgqNHj8pTbA24OIuIiIguJwqFhPiwirms8WH6ZhNaAZmDa1lZGa666irMnTu32uOvvvoq3n77bcyfPx/bt29HYGAgUlNTYTY3n9FLLs4iIiIi8g1ZpwoMGTIEQ4YMqfaYEAJvvfUW/v3vf2PYsGEAgI8++gjR0dFYsWIF7r77bl+WWiOFJEECUNs9CKTz/YiIiIio4ZrtHNfjx48jJycHKSkprjaDwYA+ffogIyOjxuBqsVhgsVhcj41GIwDAZrPBZrN5vc6FW3+HRnkhtmoVwu3Pi/s9dn17r1+fiIiIyNsqM1NTZKfarleXZhtcc3JyAADR0dFu7dHR0a5j1UlLS8OsWbOqtKenpyMgIMC7RQJIBPBq76rtL/ZyujeUZ2LVqkyvX5+IiIioqaxbt84n1ykvL/eoX7MNrg01depUTJ482fXYaDQiISEBgwcPRkhIiNev996m3/HepuNQAFApJGgVAtN6OPDibiUsTgl2p4ATwGPXJ3HElYiIiPyCzWbDunXrMGjQIKjV6ia/XuUn5HVptsE1JiYGAJCbm4vY2FhXe25uLrp3717j87RaLbRabZV2tVrdJC/8w/3a471NJ2FyOKFyAlBVzGW1OCWY7IBdSNCqFHi4X3ufvPFERERE3tJU+am663ii2d6AICkpCTExMdiwYYOrzWg0Yvv27UhOTpaxMncBAWrc0aslFBJgF4DdWTG31e4UsAtAIQF39GyJgACGViIiIqLGkHXEtbS0FJmZF+Z9Hj9+HHv27EF4eDhatWqFSZMm4aWXXkK7du2QlJSEadOmIS4uDsOHD5ev6GrMvq0bAOCrnX/CCQcAwAlAq1Lgjp4tXceJiIiIqOFkDa47d+7EDTfc4HpcOTd1zJgxWLp0Kf71r3+hrKwM48ePR1FREfr37481a9ZAp2t+m/nPvq0bnk/tiIVbfwfKM/HY9Ul4uF97jrQSEREReYkkhKhtC1K/ZzQaYTAYUFxc3CSLsy5mtzuxM+sscg9sQ3SXa9ErsQVUqmY7G4OIiIioWjabDatWrcLNN9/ss8VZnuS1Zrs4y99sOJSLpVuzcLqwFI+3B57/Zj/iwoLwQL9E3NQpuu4TEBEREVGtGFy9YMOhXKStPowSsw0xQRW/lQRpVfg9rwRpqw8DAMMrERERUSPxc+xGstudWLo1CyVmG1qF6RGkq/hdIEinQqswPUrMNnz4cxbsdmcdZyIiIiKi2jC4NtLuU4XIOleGiEANFAr3l1OhUCAiUIPj+WXYfapQpgqJiIiILg8Mro10rswKm8MJvUYJIQSstortsKw2B4QQ0GuUsDmcOFdmlblSIiIioro5nQLZhSYAQHahCU5n81nHzzmujRQRqIFaqUBRmRUWuxMOhwNoCfxZZIZSqYRWpYBaWTHySkRERNScZeaVYO3+XGSdNaK/Dpi7MROJLUKQ2jUabaOC5S6PI66N1SMhDFHBWpwuNqPU4oBaWXHLV7VSQqnFgdPFZkSHaNEjIUzmSomIiIhqlplXgiVbs7D/dDEM+orF5ga9GvtPF2PJ1ixk5pXIXCGDa6MpFBJaRQRAoZBgtTvcbvlqtTsqjocHQqGQZK6UiIiIqHpOp8Da/bkoKLOiXVSQ22LzdlFBKCizIv1AruzTBhhcGym7yAQJEvpeEYHIIC1s53cPsNmdiAzWou8VEa5+RERERM1RdpEJx86WItaggyS5D7ZJkoRYgw6ZeaWy5xnOcW2kMqsdZrsDHWJC0DEmBHnGMgCncGOnKESFBMIJgaz8MpRZ7XKXSkRERFStyjwToNFXe1yvUSLXaJY9z3DEtZECNSroVEqUW+1QKCTEGire8FiDHgqFBJPVAa1KiUANf0cgIiKi5uniPFOd5pJnGFwbKT5UjzYtgnCm2Awh3Od9CCFwptiMtlFBiA+t/jcYIiIiIrn5S55hcG0khUJCatdohAdqcDSvFKXmit9USs12HM0rRXigBoO7RHNxFhERETVb/pJnGFy9oG1UMMb2S0TXOAOKTTYAQLHJhm7xBoztl9gs9j0jIiIiqo0/5BlJXDoefJkxGo0wGAwoLi5GSEhIk17L6RQ4mV+C3zI24qrkG9AqMlj230yIiIiI6kOOPONpXuOIqxcpFBLiwyrmfsSH6RlaiYiIyO805zzD4EpEREREfoHBlYiIiIj8AoMrEREREfkFBlciIiIi8gsMrkRERETkFxhciYiIiMgvMLgSERERkV9gcCUiIiIiv8DgSkRERER+gcGViIiIiPwCgysRERER+QUGVyIiIiLyCwyuREREROQXGFyJiIiIyC8wuBIRERGRX2BwJSIiIiK/wOBKRERERH6BwZWIiIiI/AKDKxERERH5BQZXIiIiIvILDK5ERERE5BcYXImIiIjILzC4EhEREZFfYHAlIiIiIr/A4EpEREREfoHB1YtSpnyPrjPXAgC6zlyLlCnfy1wRERERUf08+7F7nnn24+aTZ/wiuM6dOxeJiYnQ6XTo06cPfvnlF7lLqiJxyvfIvKQt83w7ERERkT9InPI9vjjg3vbFgeaTZ5p9cP3iiy8wefJkzJgxA7t378ZVV12F1NRU5OXlyV2aS11vZnN5s4mIiIhq4g95ptkH1zfeeAMPP/wwxo4di86dO2P+/PkICAjA4sWL5S4NADyeDsBpA0RERNRceTodQO5pAypZr14Hq9WKXbt2YerUqa42hUKBlJQUZGRkVPsci8UCi8Xiemw0GgEANpsNNpvN6zWeUgpoL3qsVQi3P139ztdARERE1NysOCygVV54XFOeWXEYeKkJ8oynGalZB9f8/Hw4HA5ER0e7tUdHR+Pw4cPVPictLQ2zZs2q0p6eno6AgACv1/hq7+rbX+zlrNK2atUqr1+fiIiIqLHkzjPl5eUe9WvWwbUhpk6dismTJ7seG41GJCQkYPDgwQgJCfH69SpX3VXSKgRe7OXEtJ0KWJyS27H9M1O9fn0iIiKixpI7z1R+Ql6XZh1cIyMjoVQqkZub69aem5uLmJiYap+j1Wqh1WqrtKvVaqjVaq/XmOCQquwmAAAWpwSL48Ib3fZ8DURERETNzfCOUpXdBICqeeauLk2TZzw9Z7NenKXRaNCzZ09s2LDB1eZ0OrFhwwYkJyfLWNkF618e6tV+RERERL72yv2e5RRP+zWVZh1cAWDy5MlYuHAhPvzwQxw6dAj/+Mc/UFZWhrFjx8pdmktWHaG0ruNEREREcvOHPNPsg+tdd92F1157DdOnT0f37t2xZ88erFmzpsqCLbllvTwUbS9pa4vm8SYTEREReSLr5aG4q4t7211dmk+ekYQQou5u/stoNMJgMKC4uLhJFmddymazYdWqVbj55ps5p5WIiIj8kq/zjKd5rdmPuBIRERERAQyuREREROQnGFyJiIiIyC8wuBIRERGRX2BwJSIiIiK/wOBKRERERH6BwZWIiIiI/AKDKxERERH5BQZXIiIiIvILDK5ERERE5BcYXImIiIjILzC4EhEREZFfYHAlIiIiIr+gkruApiaEAAAYjUafXM9ms6G8vBxGoxFqtdon1yQiIiLyJl/nmcqcVpnbanLZB9eSkhIAQEJCgsyVEBEREVFtSkpKYDAYajwuibqirZ9zOp04ffo0goODIUlSk1/PaDQiISEBp06dQkhISJNfj4iIiMjbfJ1nhBAoKSlBXFwcFIqaZ7Je9iOuCoUCLVu29Pl1Q0JCGFyJiIjIr/kyz9Q20lqJi7OIiIiIyC8wuBIRERGRX2Bw9TKtVosZM2ZAq9XKXQoRERFRgzTXPHPZL84iIiIiossDR1yJiIiIyC8wuBIRERGRX2BwJSIiIiK/wOBKRERERH6BwdXL5s6di8TEROh0OvTp0we//PKL3CUREREReeSnn37CLbfcgri4OEiShBUrVshdkhsGVy/64osvMHnyZMyYMQO7d+/GVVddhdTUVOTl5cldGhEREVGdysrKcNVVV2Hu3Llyl1ItboflRX369ME111yDd999FwDgdDqRkJCAiRMnYsqUKTJXR0REROQ5SZLwzTffYPjw4XKX4sIRVy+xWq3YtWsXUlJSXG0KhQIpKSnIyMiQsTIiIiKiywODq5fk5+fD4XAgOjrarT06Oho5OTkyVUVERER0+WBwJSIiIiK/wODqJZGRkVAqlcjNzXVrz83NRUxMjExVEREREV0+GFy9RKPRoGfPntiwYYOrzel0YsOGDUhOTpaxMiIiIqLLg0ruAi4nkydPxpgxY9CrVy/07t0bb731FsrKyjB27Fi5SyMiIiKqU2lpKTIzM12Pjx8/jj179iA8PBytWrWSsbIK3A7Ly959913MmTMHOTk56N69O95++2306dNH7rKIiIiI6rRp0ybccMMNVdrHjBmDpUuX+r6gSzC4EhEREZFf4BxXIiIiIvILDK5ERERE5BcYXImIiIjILzC4EhEREZFfYHAlIiIiIr/A4EpEREREfoHBlYiIiIj8AoMrEREREfkFBlciIi9btGgRBg8eLHcZ5AVTpkzBxIkT5S6DiM5jcCWiRjt16hQefPBBxMXFQaPRoHXr1njiiSdw7ty5ep0nKysLkiRhz549TVOoD5jNZkybNg0zZsxwa1++fDk6duwInU6Hbt26YdWqVTJV6HuzZ89G3759ERAQgNDQULnLqZenn34aH374If744w+5SyEiMLgSUSP98ccf6NWrF44ePYrPPvsMmZmZmD9/PjZs2IDk5GQUFBTIXaJPffXVVwgJCUG/fv1cbT///DPuuecejBs3Dr/++iuGDx+O4cOHY//+/TJW6jtWqxV33nkn/vGPf8hdSr1FRkYiNTUV8+bNk7sUIgIAQUTUCH/7299Ey5YtRXl5uVv7mTNnREBAgHj00UddbQDEN99849bPYDCIJUuWuI5f/DVw4EBXv0WLFonOnTsLjUYjYmJixIQJE1zHTpw4IW699VYRGBgogoODxZ133ilycnJcx2fMmCGuuuoqsWjRIpGQkCACAwPFP/7xD2G328Urr7wioqOjRYsWLcRLL73kVlthYaEYN26ciIyMFMHBweKGG24Qe/bsqfX1GDp0qHj66afd2kaOHCmGDh3q1tanTx/xyCOP1Hquxqj8ni+2ceNGAUAUFha62jZv3iz69+8vdDqdaNmypZg4caIoLS0VQggxcODAKu9J5deMGTPqXdOSJUuEwWBo+DfVgOtdWvfFr4ndbhcPPvigSExMFDqdTrRv31689dZbVc7z4YcfipYtW/qsbiKqGUdciajBCgoKsHbtWjz22GPQ6/Vux2JiYjBq1Ch88cUXEEJ4dL5ffvkFALB+/XqcOXMG//3vfwEA8+bNw4QJEzB+/Hjs27cP3377Ldq2bQsAcDqdGDZsGAoKCvDjjz9i3bp1+OOPP3DXXXe5nfvYsWNYvXo11qxZg88++wyLFi3C0KFD8eeff+LHH3/EK6+8gn//+9/Yvn276zl33nkn8vLysHr1auzatQs9evTATTfdVOso8pYtW9CrVy+3toyMDKSkpLi1paamIiMjo8bzbN68GUFBQbV+ffrppx68qjU7duwY/va3v2HEiBHYu3cvvvjiC2zZsgX//Oc/AQD//e9/cebMGZw5cwbJycl46qmnXI+ffvrpRl27Lo8++mid378nQkJCXDU/9dRTbsecTidatmyJ5cuX4+DBg5g+fTqee+45fPnll279evfujT///BNZWVne+vaIqIFUchdARP7r6NGjEEKgU6dO1R7v1KkTCgsLcfbsWURFRdV5vhYtWgAAIiIiEBMT42p/6aWX8NRTT+GJJ55wtV1zzTUAgA0bNmDfvn04fvw4EhISAAAfffQRunTpgh07drj6OZ1OLF68GMHBwejcuTNuuOEGHDlyBKtWrYJCoUCHDh3wyiuvYOPGjejTpw+2bNmCX375BXl5edBqtQCA1157DStWrMBXX32F8ePHV6m/qKgIxcXFiIuLc2vPyclBdHS0W1t0dDRycnJqfC169epV51zfS89ZX2lpaRg1ahQmTZoEAGjXrh3efvttDBw4EPPmzUN4eLirr0ajQVBQkNv70pReeOGFRodji8UCjUbjqvnSsKtWqzFr1izX46SkJGRkZODLL7/EyJEjXe2V7+eJEyeQmJjYqJqIqHEYXImo0TwdUW2IvLw8nD59GjfddFO1xw8dOoSEhARXaAWAzp07IzQ0FIcOHXIF18TERAQHB7v6REdHQ6lUQqFQuLXl5eUBAH777TeUlpYiIiLC7XomkwnHjh2rthaTyQQA0Ol0DfhO3en1eteockPt27fPLaw5HA6347/99hv27t3rNnIrhIDT6cTx48dr/IXEF6Kiojz6Zac2586dQ0hISK195s6di8WLF+PkyZMwmUywWq3o3r27W5/KTxPKy8sbVQ8RNR6DKxE1WNu2bSFJEg4dOoTbbrutyvFDhw4hLCzMNZIqSVKVkGuz2Wq9xqVTEBpKrVa7PZYkqdo2p9MJACgtLUVsbCw2bdpU5Vw1rYyPiIiAJEkoLCx0a4+JiUFubq5bW25ubq2jl5s3b8aQIUNqPA4A77//PkaNGlXj8Q4dOuDbb791Pd6+fTvuu+8+1+PS0lI88sgjePzxx6s8t1WrVrVeu6k9+uij+OSTT2rtU1paWuvxP/74A0lJSTUe//zzz/H000/j9ddfR3JyMoKDgzFnzhy36SIAXFNDKn+OiUg+DK5E1GAREREYNGgQ3nvvPTz55JNuITMnJweffvopRo8eDUmSAFT8j//MmTOuPkePHnUbxdJoNADcRwaDg4ORmJiIDRs24IYbbqhSQ6dOnXDq1CmcOnXKNep68OBBFBUVoXPnzg3+3nr06IGcnByoVCqPPx7WaDTo3LkzDh486LaPa3JyMjZs2OD6SB4A1q1bh+Tk5BrP5Y2pAhqNxm3U9s8//3Q73qNHDxw8eLDRI7tNwRtTBX766adag/3WrVvRt29fPPbYY6626kbT9+/fD7VajS5dujSqHiJqPAZXImqUd999F3379kVqaipeeuklJCUl4cCBA3jmmWcQHx+P2bNnu/reeOONePfdd5GcnAyHw4Fnn33WbdQzKioKer0ea9asQcuWLaHT6WAwGDBz5kw8+uijiIqKwpAhQ1BSUoKtW7di4sSJSElJQbdu3TBq1Ci89dZbsNvteOyxxzBw4MAqi6TqIyUlBcnJyRg+fDheffVVtG/fHqdPn8b333+P2267rcZzp6amYsuWLW4h9YknnsDAgQPx+uuvY+jQofj888+xc+dOLFiwoMbre2OqQF2effZZXHvttfjnP/+Jhx56CIGBgTh48CDWrVuHd99912vXOXnyJAoKCnDy5Ek4HA5XIG/btm2Ni6waM1XAZDLhgw8+wLFjxzBkyBDXXOLS0lLY7XYUFBQgPDwc7dq1w0cffYS1a9ciKSkJH3/8MXbs2FFllHbz5s0YMGCA10b/iagRZN3TgIguC1lZWWLMmDEiOjpaqNVqkZCQICZOnCjy8/Pd+mVnZ4vBgweLwMBA0a5dO7Fq1Sq37bCEEGLhwoUiISFBKBQKt+2w5s+fLzp06CDUarWIjY0VEydOdB3zdDusi40ZM0YMGzbMrW3gwIHiiSeecD02Go1i4sSJIi4uzvV9jRo1Spw8ebLG1+LAgQNCr9eLoqIit/Yvv/xStG/fXmg0GtGlSxfx/fff13gOb/B0O6xffvlFDBo0SAQFBYnAwEBx5ZVXitmzZ1c538CBA6vdAmvGjBmidevWtdYyZsyYarfU2rhxY/2/MQ9Utw0WqtlmzWw2iwceeEAYDAYRGhoq/vGPf4gpU6ZUed06dOggPvvssyaplYjqRxKiCVdVEBH9Bd15553o0aMHpk6dKncpTW7MmDGQJAlLly6VuxSXpUuXYtOmTdXWtGfPHkyaNKnaucvVWb16NZ566ins3bsXKhU/pCSSG/dxJSLysjlz5ni8z6g/E0Jg06ZNePHFF+UuxY1er4fBYKj2mFqtdtvmqy5lZWVYsmQJQytRM8ERVyIiIiLyCxxxJSIiIiK/wOBKRERERH6BwZWIiIiI/AKDKxERERH5BQZXIiIiIvILDK5ERERE5BcYXImIiIjILzC4EhEREZFfYHAlIiIiIr/w/19ZBJ+uk2JpAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "    # Создание диаграмм зависимости\n",
    "for column in numeric_columns:\n",
    "    plt.figure(figsize=(8, 6))  # Установка размера графика\n",
    "    if pd.api.types.is_numeric_dtype(df[column]):  # Проверяем, является ли колонка числовой\n",
    "        # Проверяем, содержит ли колонка только два уникальных значения (0 и 1)\n",
    "        if df[column].nunique() == 2 and set(df[column].unique()).issubset({0, 1}):\n",
    "            # Если да, то строим столбчатую диаграмму\n",
    "            counts = df[column].value_counts()  # Считаем количество повторений каждого значения\n",
    "            counts.plot(kind='bar')  # Создаем столбчатую диаграмму\n",
    "            plt.title(f'Количество значений для {column}')\n",
    "            plt.xlabel(column)\n",
    "            plt.ylabel('Количество повторений')\n",
    "        else:\n",
    "            # Если колонка числовая, создаем диаграмму рассеяния\n",
    "            plt.scatter(df['Outcome'], df[column], alpha=0.5)  # Создаем диаграмму рассеяния\n",
    "            plt.title(f'Зависимость {column} от Outcome')\n",
    "            plt.xlabel('Outcome (0 = нет, 1 = да)')\n",
    "            plt.ylabel(column)\n",
    "            plt.xticks([0, 1])  # Установка меток по оси X\n",
    "            plt.grid()  # Добавление сетки для удобства восприятия\n",
    "    else:\n",
    "        # Если колонка не числовая, строим столбчатую диаграмму\n",
    "        counts = df[column].value_counts()  # Считаем количество повторений каждого значения\n",
    "        counts.plot(kind='bar')  # Создаем столбчатую диаграмму\n",
    "        plt.title(f'Количество значений для {column}')\n",
    "        plt.xlabel(column)\n",
    "        plt.ylabel('Количество повторений')\n",
    "\n",
    "    plt.show()  # Отображение графика"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Разобьем наш набор на выборки относительно параметра Outcome:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Функция для создания выборок\n",
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "def split_stratified_into_train_val_test(\n",
    "    df_input,\n",
    "    stratify_colname=\"y\",\n",
    "    frac_train=0.6,\n",
    "    frac_val=0.15,\n",
    "    frac_test=0.25,\n",
    "    random_state=None,\n",
    "):\n",
    "\n",
    "    if frac_train + frac_val + frac_test != 1.0:\n",
    "        raise ValueError(\n",
    "            \"fractions %f, %f, %f do not add up to 1.0\"\n",
    "            % (frac_train, frac_val, frac_test)\n",
    "        )\n",
    "\n",
    "    if stratify_colname not in df_input.columns:\n",
    "        raise ValueError(\"%s is not a column in the dataframe\" % (stratify_colname))\n",
    "\n",
    "    X = df_input  # Contains all columns.\n",
    "    y = df_input[\n",
    "        [stratify_colname]\n",
    "    ]  # Dataframe of just the column on which to stratify.\n",
    "\n",
    "    # Split original dataframe into train and temp dataframes.\n",
    "    df_train, df_temp, y_train, y_temp = train_test_split(\n",
    "        X, y, stratify=y, test_size=(1.0 - frac_train), random_state=random_state\n",
    "    )\n",
    "\n",
    "    # Split the temp dataframe into val and test dataframes.\n",
    "    relative_frac_test = frac_test / (frac_val + frac_test)\n",
    "    df_val, df_test, y_val, y_test = train_test_split(\n",
    "        df_temp,\n",
    "        y_temp,\n",
    "        stratify=y_temp,\n",
    "        test_size=relative_frac_test,\n",
    "        random_state=random_state,\n",
    "    )\n",
    "\n",
    "    assert len(df_input) == len(df_train) + len(df_val) + len(df_test)\n",
    "\n",
    "    return df_train, df_val, df_test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Outcome\n",
      "0    500\n",
      "1    268\n",
      "Name: count, dtype: int64\n",
      "\n",
      "Обучающая выборка:  (460, 9)\n",
      "Outcome\n",
      "0    299\n",
      "1    161\n",
      "Name: count, dtype: int64\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Контрольная выборка:  (154, 9)\n",
      "Outcome\n",
      "0    101\n",
      "1     53\n",
      "Name: count, dtype: int64\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Тестовая выборка:  (154, 9)\n",
      "Outcome\n",
      "0    100\n",
      "1     54\n",
      "Name: count, dtype: int64\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Вывод распределения количества наблюдений по меткам (классам)\n",
    "print(df.Outcome.value_counts())\n",
    "print()\n",
    "\n",
    "data = df.copy()\n",
    "\n",
    "df_train, df_val, df_test = split_stratified_into_train_val_test(\n",
    "   data, stratify_colname=\"Outcome\", frac_train=0.60, frac_val=0.20, frac_test=0.20\n",
    ")\n",
    "\n",
    "print(\"Обучающая выборка: \", df_train.shape)\n",
    "print(df_train.Outcome.value_counts())\n",
    "counts = df_train['Outcome'].value_counts()\n",
    "plt.figure(figsize=(2, 2))# Установка размера графика\n",
    "plt.pie(counts, labels=counts.index, autopct='%1.1f%%', startangle=90)# Построение круговой диаграммы\n",
    "plt.title('Распределение классов Outcome в обучающей выборке')# Добавление заголовка\n",
    "plt.show()# Отображение графика\n",
    "\n",
    "print(\"Контрольная выборка: \", df_val.shape)\n",
    "print(df_val.Outcome.value_counts())\n",
    "counts = df_val['Outcome'].value_counts()\n",
    "plt.figure(figsize=(2, 2))\n",
    "plt.pie(counts, labels=counts.index, autopct='%1.1f%%', startangle=90)\n",
    "plt.title('Распределение классов Outcome в контрольной выборке')\n",
    "plt.show()\n",
    "\n",
    "print(\"Тестовая выборка: \", df_test.shape)\n",
    "print(df_test.Outcome.value_counts())\n",
    "counts = df_test['Outcome'].value_counts()\n",
    "plt.figure(figsize=(2, 2))\n",
    "plt.pie(counts, labels=counts.index, autopct='%1.1f%%', startangle=90)\n",
    "plt.title('Распределение классов Outcome в тестовой выборке')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Сбалансируем распределение:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. Балансировка данных оверсемплингом. Это метод, увеличивающий число наблюдений в меньшинственном классе для достижения более равномерного распределения классов."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Обучающая выборка:  (460, 9)\n",
      "Outcome\n",
      "0    299\n",
      "1    161\n",
      "Name: count, dtype: int64\n",
      "Обучающая выборка после oversampling:  (586, 9)\n",
      "Outcome\n",
      "0    299\n",
      "1    287\n",
      "Name: count, dtype: int64\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "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>Pregnancies</th>\n",
       "      <th>Glucose</th>\n",
       "      <th>BloodPressure</th>\n",
       "      <th>SkinThickness</th>\n",
       "      <th>Insulin</th>\n",
       "      <th>BMI</th>\n",
       "      <th>DiabetesPedigreeFunction</th>\n",
       "      <th>Age</th>\n",
       "      <th>Outcome</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>4.000000</td>\n",
       "      <td>171.000000</td>\n",
       "      <td>72.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>43.600000</td>\n",
       "      <td>0.479000</td>\n",
       "      <td>26.000000</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4.000000</td>\n",
       "      <td>110.000000</td>\n",
       "      <td>76.000000</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>28.400000</td>\n",
       "      <td>0.118000</td>\n",
       "      <td>27.000000</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>106.000000</td>\n",
       "      <td>72.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>25.800000</td>\n",
       "      <td>0.207000</td>\n",
       "      <td>27.000000</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>141.000000</td>\n",
       "      <td>35.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>42.400000</td>\n",
       "      <td>0.205000</td>\n",
       "      <td>29.000000</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>66.000000</td>\n",
       "      <td>15.000000</td>\n",
       "      <td>56.000000</td>\n",
       "      <td>23.600000</td>\n",
       "      <td>0.666000</td>\n",
       "      <td>26.000000</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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>581</th>\n",
       "      <td>4.223037</td>\n",
       "      <td>113.446073</td>\n",
       "      <td>77.243141</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>30.687204</td>\n",
       "      <td>0.404846</td>\n",
       "      <td>46.797068</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>582</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>78.972919</td>\n",
       "      <td>65.566707</td>\n",
       "      <td>31.513540</td>\n",
       "      <td>79.243727</td>\n",
       "      <td>32.556671</td>\n",
       "      <td>0.711110</td>\n",
       "      <td>26.486460</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>583</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>79.630698</td>\n",
       "      <td>76.091174</td>\n",
       "      <td>31.184651</td>\n",
       "      <td>73.323715</td>\n",
       "      <td>33.609117</td>\n",
       "      <td>1.024212</td>\n",
       "      <td>26.815349</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>584</th>\n",
       "      <td>2.984921</td>\n",
       "      <td>95.708532</td>\n",
       "      <td>66.462302</td>\n",
       "      <td>28.552777</td>\n",
       "      <td>159.015079</td>\n",
       "      <td>36.005535</td>\n",
       "      <td>0.685819</td>\n",
       "      <td>27.432143</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>585</th>\n",
       "      <td>10.312967</td>\n",
       "      <td>142.374065</td>\n",
       "      <td>77.082295</td>\n",
       "      <td>41.915212</td>\n",
       "      <td>124.164589</td>\n",
       "      <td>37.666584</td>\n",
       "      <td>0.495783</td>\n",
       "      <td>40.875312</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>586 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Pregnancies     Glucose  BloodPressure  SkinThickness     Insulin  \\\n",
       "0       4.000000  171.000000      72.000000       0.000000    0.000000   \n",
       "1       4.000000  110.000000      76.000000      20.000000  100.000000   \n",
       "2       3.000000  106.000000      72.000000       0.000000    0.000000   \n",
       "3       0.000000  141.000000      35.000000       0.000000    0.000000   \n",
       "4       1.000000  100.000000      66.000000      15.000000   56.000000   \n",
       "..           ...         ...            ...            ...         ...   \n",
       "581     4.223037  113.446073      77.243141       0.000000    0.000000   \n",
       "582     3.000000   78.972919      65.566707      31.513540   79.243727   \n",
       "583     3.000000   79.630698      76.091174      31.184651   73.323715   \n",
       "584     2.984921   95.708532      66.462302      28.552777  159.015079   \n",
       "585    10.312967  142.374065      77.082295      41.915212  124.164589   \n",
       "\n",
       "           BMI  DiabetesPedigreeFunction        Age  Outcome  \n",
       "0    43.600000                  0.479000  26.000000        1  \n",
       "1    28.400000                  0.118000  27.000000        0  \n",
       "2    25.800000                  0.207000  27.000000        0  \n",
       "3    42.400000                  0.205000  29.000000        1  \n",
       "4    23.600000                  0.666000  26.000000        0  \n",
       "..         ...                       ...        ...      ...  \n",
       "581  30.687204                  0.404846  46.797068        1  \n",
       "582  32.556671                  0.711110  26.486460        1  \n",
       "583  33.609117                  1.024212  26.815349        1  \n",
       "584  36.005535                  0.685819  27.432143        1  \n",
       "585  37.666584                  0.495783  40.875312        1  \n",
       "\n",
       "[586 rows x 9 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from imblearn.over_sampling import ADASYN\n",
    "\n",
    "ada = ADASYN()\n",
    "\n",
    "print(\"Обучающая выборка: \", df_train.shape)\n",
    "print(df_train.Outcome.value_counts())\n",
    "\n",
    "X_resampled, y_resampled = ada.fit_resample(df_train, df_train[\"Outcome\"])\n",
    "df_train_adasyn = pd.DataFrame(X_resampled)\n",
    "\n",
    "print(\"Обучающая выборка после oversampling: \", df_train_adasyn.shape)\n",
    "print(df_train_adasyn.Outcome.value_counts())\n",
    "\n",
    "counts = df_train_adasyn['Outcome'].value_counts()\n",
    "plt.figure(figsize=(2, 2))\n",
    "plt.pie(counts, labels=counts.index, autopct='%1.1f%%', startangle=90)\n",
    "plt.title('Распределение классов Outcome в тренировочной выборке после ADASYN')\n",
    "plt.show()\n",
    "\n",
    "df_train_adasyn"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "2. Балансировка данных андерсемплингом. Этот метод помогает сбалансировать выборку, уменьшая количество экземпляров класса большинства, чтобы привести его в соответствие с классом меньшинства."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Обучающая выборка после undersampling:  (322, 9)\n",
      "Outcome\n",
      "0    161\n",
      "1    161\n",
      "Name: count, dtype: int64\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from imblearn.under_sampling import RandomUnderSampler\n",
    "\n",
    "rus = RandomUnderSampler()# Создание экземпляра RandomUnderSampler\n",
    "\n",
    "# Применение RandomUnderSampler\n",
    "X_resampled, y_resampled = rus.fit_resample(df_train.drop(columns=['Outcome']), df_train['Outcome'])\n",
    "\n",
    "# Создание нового DataFrame\n",
    "df_train_undersampled = pd.DataFrame(X_resampled)\n",
    "df_train_undersampled['Outcome'] = y_resampled  # Добавление целевой переменной\n",
    "\n",
    "# Вывод информации о новой выборке\n",
    "print(\"Обучающая выборка после undersampling: \", df_train_undersampled.shape)\n",
    "print(df_train_undersampled['Outcome'].value_counts())\n",
    "\n",
    "# Визуализация распределения классов\n",
    "counts = df_train_undersampled['Outcome'].value_counts()\n",
    "plt.figure(figsize=(2, 2))\n",
    "plt.pie(counts, labels=counts.index, autopct='%1.1f%%', startangle=90)\n",
    "plt.title('Распределение классов Outcome в тренировочной выборке после Undersampling')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2. Датасет: Данные по инсультам\n",
    "https://www.kaggle.com/datasets/fedesoriano/stroke-prediction-dataset\n",
    "##### О наборе данных: \n",
    "По данным Всемирной организации здравоохранения (ВОЗ), инсульт является второй по значимости причиной смертности во всем мире, на его долю приходится примерно 11% от общего числа смертей.\n",
    "Этот набор данных используется для прогнозирования вероятности инсульта у пациента на основе входных параметров, таких как пол, возраст, различные заболевания и статус курильщика. Каждая строка в данных содержит соответствующую информацию о пациенте.\n",
    "\n",
    "Атрибуты:\n",
    "1) id: уникальный идентификатор\n",
    "2) gender: \"Male\", \"Female\" или \"Other\"\n",
    "3) age: возраст пациента\n",
    "4) hypertension: 0, если у пациента нет артериальной гипертензии, 1, если у пациента есть артериальная гипертензия\n",
    "5) heart_disease: 0, если у пациента нет сердечных заболеваний, 1, если у пациента есть сердечные заболевания\n",
    "6) ever_married: \"No\" или \"Yes\"\n",
    "7) work_type: \"children\", \"Govt_jov\", \"Never_worked\", \"Private\" or \"Self-employed\"\n",
    "8) Residence_type: \"Rural\" or \"Urban\"\n",
    "9) avg_glucose_level: средний уровень глюкозы в крови\n",
    "10) bmi: индекс массы тела\n",
    "11) smoking_status: \"formerly smoked\", \"never smoked\", \"smokes\" или \"Unknown\"*\n",
    "12) stroke: 1, если у пациента был инсульт, или 0, если нет.\n",
    "##### Таким образом:\n",
    "* Объект наблюдения - Реальные пациенты.\n",
    "* Атрибуты: id, gender, age, hypertension, heart_disease, ever_married, work_type, Residence_type, avg_glucose_level, bmi, smoking_status, stroke.\n",
    "* Проблемная область: Прогнозирование вероятности инсульта у пациента."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Количество колонок: 12\n",
      "Колонки: id, gender, age, hypertension, heart_disease, ever_married, work_type, Residence_type, avg_glucose_level, bmi, smoking_status, stroke\n",
      "\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 5110 entries, 0 to 5109\n",
      "Data columns (total 12 columns):\n",
      " #   Column             Non-Null Count  Dtype  \n",
      "---  ------             --------------  -----  \n",
      " 0   id                 5110 non-null   int64  \n",
      " 1   gender             5110 non-null   object \n",
      " 2   age                5110 non-null   float64\n",
      " 3   hypertension       5110 non-null   int64  \n",
      " 4   heart_disease      5110 non-null   int64  \n",
      " 5   ever_married       5110 non-null   object \n",
      " 6   work_type          5110 non-null   object \n",
      " 7   Residence_type     5110 non-null   object \n",
      " 8   avg_glucose_level  5110 non-null   float64\n",
      " 9   bmi                4909 non-null   float64\n",
      " 10  smoking_status     5110 non-null   object \n",
      " 11  stroke             5110 non-null   int64  \n",
      "dtypes: float64(3), int64(4), object(5)\n",
      "memory usage: 479.2+ KB\n"
     ]
    },
    {
     "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>id</th>\n",
       "      <th>gender</th>\n",
       "      <th>age</th>\n",
       "      <th>hypertension</th>\n",
       "      <th>heart_disease</th>\n",
       "      <th>ever_married</th>\n",
       "      <th>work_type</th>\n",
       "      <th>Residence_type</th>\n",
       "      <th>avg_glucose_level</th>\n",
       "      <th>bmi</th>\n",
       "      <th>smoking_status</th>\n",
       "      <th>stroke</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>9046</td>\n",
       "      <td>Male</td>\n",
       "      <td>67.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Private</td>\n",
       "      <td>Urban</td>\n",
       "      <td>228.69</td>\n",
       "      <td>36.6</td>\n",
       "      <td>formerly smoked</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>51676</td>\n",
       "      <td>Female</td>\n",
       "      <td>61.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Self-employed</td>\n",
       "      <td>Rural</td>\n",
       "      <td>202.21</td>\n",
       "      <td>NaN</td>\n",
       "      <td>never smoked</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>31112</td>\n",
       "      <td>Male</td>\n",
       "      <td>80.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Private</td>\n",
       "      <td>Rural</td>\n",
       "      <td>105.92</td>\n",
       "      <td>32.5</td>\n",
       "      <td>never smoked</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>60182</td>\n",
       "      <td>Female</td>\n",
       "      <td>49.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Private</td>\n",
       "      <td>Urban</td>\n",
       "      <td>171.23</td>\n",
       "      <td>34.4</td>\n",
       "      <td>smokes</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1665</td>\n",
       "      <td>Female</td>\n",
       "      <td>79.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Self-employed</td>\n",
       "      <td>Rural</td>\n",
       "      <td>174.12</td>\n",
       "      <td>24.0</td>\n",
       "      <td>never smoked</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      id  gender   age  hypertension  heart_disease ever_married  \\\n",
       "0   9046    Male  67.0             0              1          Yes   \n",
       "1  51676  Female  61.0             0              0          Yes   \n",
       "2  31112    Male  80.0             0              1          Yes   \n",
       "3  60182  Female  49.0             0              0          Yes   \n",
       "4   1665  Female  79.0             1              0          Yes   \n",
       "\n",
       "       work_type Residence_type  avg_glucose_level   bmi   smoking_status  \\\n",
       "0        Private          Urban             228.69  36.6  formerly smoked   \n",
       "1  Self-employed          Rural             202.21   NaN     never smoked   \n",
       "2        Private          Rural             105.92  32.5     never smoked   \n",
       "3        Private          Urban             171.23  34.4           smokes   \n",
       "4  Self-employed          Rural             174.12  24.0     never smoked   \n",
       "\n",
       "   stroke  \n",
       "0       1  \n",
       "1       1  \n",
       "2       1  \n",
       "3       1  \n",
       "4       1  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "df = pd.read_csv(\".//static//csv//stroke.csv\", sep=\",\")\n",
    "print('Количество колонок: ' + str(df.columns.size))  \n",
    "print('Колонки: ' + ', '.join(df.columns)+'\\n')\n",
    "\n",
    "df.info()\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Получение сведений о пропущенных данных\n",
    "Типы пропущенных данных:\n",
    "\n",
    "- None - представление пустых данных в Python\n",
    "- NaN - представление пустых данных в Pandas\n",
    "- '' - пустая строка"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "id                     0\n",
      "gender                 0\n",
      "age                    0\n",
      "hypertension           0\n",
      "heart_disease          0\n",
      "ever_married           0\n",
      "work_type              0\n",
      "Residence_type         0\n",
      "avg_glucose_level      0\n",
      "bmi                  201\n",
      "smoking_status         0\n",
      "stroke                 0\n",
      "dtype: int64\n",
      "\n",
      "id                   False\n",
      "gender               False\n",
      "age                  False\n",
      "hypertension         False\n",
      "heart_disease        False\n",
      "ever_married         False\n",
      "work_type            False\n",
      "Residence_type       False\n",
      "avg_glucose_level    False\n",
      "bmi                   True\n",
      "smoking_status       False\n",
      "stroke               False\n",
      "dtype: bool\n",
      "\n",
      "id процент пустых значений: %0.00\n",
      "gender процент пустых значений: %0.00\n",
      "age процент пустых значений: %0.00\n",
      "hypertension процент пустых значений: %0.00\n",
      "heart_disease процент пустых значений: %0.00\n",
      "ever_married процент пустых значений: %0.00\n",
      "work_type процент пустых значений: %0.00\n",
      "Residence_type процент пустых значений: %0.00\n",
      "avg_glucose_level процент пустых значений: %0.00\n",
      "bmi процент пустых значений: %3.93\n",
      "smoking_status процент пустых значений: %0.00\n",
      "stroke процент пустых значений: %0.00\n"
     ]
    }
   ],
   "source": [
    "# Количество пустых значений признаков\n",
    "print(df.isnull().sum())\n",
    "print()\n",
    "\n",
    "# Есть ли пустые значения признаков\n",
    "print(df.isnull().any())\n",
    "print()\n",
    "\n",
    "# Процент пустых значений признаков\n",
    "for i in df.columns:\n",
    "    null_rate = df[i].isnull().sum() / len(df) * 100\n",
    "    print(f\"{i} процент пустых значений: %{null_rate:.2f}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Пропущенные данные существуют. Необходимо заполнить пропуски медианными значениями.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Заполнение пропущенных данных:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(5110, 12)\n",
      "id                   False\n",
      "gender               False\n",
      "age                  False\n",
      "hypertension         False\n",
      "heart_disease        False\n",
      "ever_married         False\n",
      "work_type            False\n",
      "Residence_type       False\n",
      "avg_glucose_level    False\n",
      "bmi                  False\n",
      "smoking_status       False\n",
      "stroke               False\n",
      "dtype: bool\n"
     ]
    },
    {
     "data": {
      "text/html": [
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>gender</th>\n",
       "      <th>age</th>\n",
       "      <th>hypertension</th>\n",
       "      <th>heart_disease</th>\n",
       "      <th>ever_married</th>\n",
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       "      <th>stroke</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>5105</th>\n",
       "      <td>18234</td>\n",
       "      <td>Female</td>\n",
       "      <td>80.0</td>\n",
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       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Private</td>\n",
       "      <td>Urban</td>\n",
       "      <td>83.75</td>\n",
       "      <td>27.7</td>\n",
       "      <td>never smoked</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5106</th>\n",
       "      <td>44873</td>\n",
       "      <td>Female</td>\n",
       "      <td>81.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Self-employed</td>\n",
       "      <td>Urban</td>\n",
       "      <td>125.20</td>\n",
       "      <td>40.0</td>\n",
       "      <td>never smoked</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5107</th>\n",
       "      <td>19723</td>\n",
       "      <td>Female</td>\n",
       "      <td>35.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Self-employed</td>\n",
       "      <td>Rural</td>\n",
       "      <td>82.99</td>\n",
       "      <td>30.6</td>\n",
       "      <td>never smoked</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5108</th>\n",
       "      <td>37544</td>\n",
       "      <td>Male</td>\n",
       "      <td>51.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Private</td>\n",
       "      <td>Rural</td>\n",
       "      <td>166.29</td>\n",
       "      <td>25.6</td>\n",
       "      <td>formerly smoked</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5109</th>\n",
       "      <td>44679</td>\n",
       "      <td>Female</td>\n",
       "      <td>44.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Govt_job</td>\n",
       "      <td>Urban</td>\n",
       "      <td>85.28</td>\n",
       "      <td>26.2</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         id  gender   age  hypertension  heart_disease ever_married  \\\n",
       "5105  18234  Female  80.0             1              0          Yes   \n",
       "5106  44873  Female  81.0             0              0          Yes   \n",
       "5107  19723  Female  35.0             0              0          Yes   \n",
       "5108  37544    Male  51.0             0              0          Yes   \n",
       "5109  44679  Female  44.0             0              0          Yes   \n",
       "\n",
       "          work_type Residence_type  avg_glucose_level   bmi   smoking_status  \\\n",
       "5105        Private          Urban              83.75  27.7     never smoked   \n",
       "5106  Self-employed          Urban             125.20  40.0     never smoked   \n",
       "5107  Self-employed          Rural              82.99  30.6     never smoked   \n",
       "5108        Private          Rural             166.29  25.6  formerly smoked   \n",
       "5109       Govt_job          Urban              85.28  26.2          Unknown   \n",
       "\n",
       "      stroke  \n",
       "5105       0  \n",
       "5106       0  \n",
       "5107       0  \n",
       "5108       0  \n",
       "5109       0  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fillna_df = df.fillna(0)\n",
    "\n",
    "print(fillna_df.shape)\n",
    "\n",
    "print(fillna_df.isnull().any())\n",
    "\n",
    "# Замена пустых данных на 0\n",
    "df[\"bmi\"] = df[\"bmi\"].fillna(0)\n",
    "\n",
    "# Вычисляем медиану для колонки \"bmi\"\n",
    "median_bmi = df[\"bmi\"].median()\n",
    "\n",
    "# Заменяем значения 0 на медиану\n",
    "df.loc[df[\"bmi\"] == 0, \"bmi\"] = median_bmi\n",
    "\n",
    "df.tail()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Удалим наблюдения с пропусками:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(5110, 12)\n",
      "id                   False\n",
      "gender               False\n",
      "age                  False\n",
      "hypertension         False\n",
      "heart_disease        False\n",
      "ever_married         False\n",
      "work_type            False\n",
      "Residence_type       False\n",
      "avg_glucose_level    False\n",
      "bmi                  False\n",
      "smoking_status       False\n",
      "stroke               False\n",
      "dtype: bool\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>gender</th>\n",
       "      <th>age</th>\n",
       "      <th>hypertension</th>\n",
       "      <th>heart_disease</th>\n",
       "      <th>ever_married</th>\n",
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       "      <th>bmi</th>\n",
       "      <th>smoking_status</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>5105</th>\n",
       "      <td>18234</td>\n",
       "      <td>Female</td>\n",
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       "      <td>Yes</td>\n",
       "      <td>Private</td>\n",
       "      <td>Urban</td>\n",
       "      <td>83.75</td>\n",
       "      <td>27.7</td>\n",
       "      <td>never smoked</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>5106</th>\n",
       "      <td>44873</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Self-employed</td>\n",
       "      <td>Urban</td>\n",
       "      <td>125.20</td>\n",
       "      <td>40.0</td>\n",
       "      <td>never smoked</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>5107</th>\n",
       "      <td>19723</td>\n",
       "      <td>Female</td>\n",
       "      <td>35.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Self-employed</td>\n",
       "      <td>Rural</td>\n",
       "      <td>82.99</td>\n",
       "      <td>30.6</td>\n",
       "      <td>never smoked</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5108</th>\n",
       "      <td>37544</td>\n",
       "      <td>Male</td>\n",
       "      <td>51.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Private</td>\n",
       "      <td>Rural</td>\n",
       "      <td>166.29</td>\n",
       "      <td>25.6</td>\n",
       "      <td>formerly smoked</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>5109</th>\n",
       "      <td>44679</td>\n",
       "      <td>Female</td>\n",
       "      <td>44.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Govt_job</td>\n",
       "      <td>Urban</td>\n",
       "      <td>85.28</td>\n",
       "      <td>26.2</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         id  gender   age  hypertension  heart_disease ever_married  \\\n",
       "5105  18234  Female  80.0             1              0          Yes   \n",
       "5106  44873  Female  81.0             0              0          Yes   \n",
       "5107  19723  Female  35.0             0              0          Yes   \n",
       "5108  37544    Male  51.0             0              0          Yes   \n",
       "5109  44679  Female  44.0             0              0          Yes   \n",
       "\n",
       "          work_type Residence_type  avg_glucose_level   bmi   smoking_status  \\\n",
       "5105        Private          Urban              83.75  27.7     never smoked   \n",
       "5106  Self-employed          Urban             125.20  40.0     never smoked   \n",
       "5107  Self-employed          Rural              82.99  30.6     never smoked   \n",
       "5108        Private          Rural             166.29  25.6  formerly smoked   \n",
       "5109       Govt_job          Urban              85.28  26.2          Unknown   \n",
       "\n",
       "      stroke  \n",
       "5105       0  \n",
       "5106       0  \n",
       "5107       0  \n",
       "5108       0  \n",
       "5109       0  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dropna_df = df.dropna()\n",
    "\n",
    "print(dropna_df.shape)\n",
    "\n",
    "print(fillna_df.isnull().any())\n",
    "df.tail()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Проверим выбросы и усредним их:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Колонка age:\n",
      "  Есть выбросы: Нет\n",
      "  Количество выбросов: 0\n",
      "  Минимальное значение: 0.08\n",
      "  Максимальное значение: 82.0\n",
      "  1-й квартиль (Q1): 25.0\n",
      "  3-й квартиль (Q3): 61.0\n",
      "\n",
      "Колонка avg_glucose_level:\n",
      "  Есть выбросы: Нет\n",
      "  Количество выбросов: 0\n",
      "  Минимальное значение: 55.12\n",
      "  Максимальное значение: 169.35750000000002\n",
      "  1-й квартиль (Q1): 77.245\n",
      "  3-й квартиль (Q3): 114.09\n",
      "\n",
      "Колонка bmi:\n",
      "  Есть выбросы: Нет\n",
      "  Количество выбросов: 0\n",
      "  Минимальное значение: 10.300000000000006\n",
      "  Максимальное значение: 46.29999999999999\n",
      "  1-й квартиль (Q1): 23.8\n",
      "  3-й квартиль (Q3): 32.8\n",
      "\n"
     ]
    }
   ],
   "source": [
    "numeric_columns = ['age', 'avg_glucose_level', 'bmi']\n",
    "for column in numeric_columns:\n",
    "    if pd.api.types.is_numeric_dtype(df[column]):  # Проверяем, является ли колонка числовой\n",
    "        q1 = df[column].quantile(0.25)  # Находим 1-й квартиль (Q1)\n",
    "        q3 = df[column].quantile(0.75)  # Находим 3-й квартиль (Q3)\n",
    "        iqr = q3 - q1  # Вычисляем межквартильный размах (IQR)\n",
    "\n",
    "        # Определяем границы для выбросов\n",
    "        lower_bound = q1 - 1.5 * iqr  # Нижняя граница\n",
    "        upper_bound = q3 + 1.5 * iqr  # Верхняя граница\n",
    "\n",
    "        # Подсчитываем количество выбросов\n",
    "        outliers = df[(df[column] < lower_bound) | (df[column] > upper_bound)]\n",
    "        outlier_count = outliers.shape[0]\n",
    "\n",
    "        print(f\"Колонка {column}:\")\n",
    "        print(f\"  Есть выбросы: {'Да' if outlier_count > 0 else 'Нет'}\")\n",
    "        print(f\"  Количество выбросов: {outlier_count}\")\n",
    "        print(f\"  Минимальное значение: {df[column].min()}\")\n",
    "        print(f\"  Максимальное значение: {df[column].max()}\")\n",
    "        print(f\"  1-й квартиль (Q1): {q1}\")\n",
    "        print(f\"  3-й квартиль (Q3): {q3}\\n\")\n",
    "\n",
    "        # Устраняем выбросы: заменяем значения ниже нижней границы на саму нижнюю границу, а выше верхней — на верхнюю\n",
    "        df[column] = df[column].apply(lambda x: lower_bound if x < lower_bound else upper_bound if x > upper_bound else x)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Постараемся выявить зависимости Stroke от остальных колонок:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Разобьем наш набор на выборки относительно параметра Stroke:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "# Список колонок для построения графиков\n",
    "columns = ['gender', 'age', 'hypertension', 'heart_disease', 'ever_married',\n",
    "           'work_type', 'Residence_type', 'avg_glucose_level', 'bmi',\n",
    "           'smoking_status']\n",
    "\n",
    "# Создание диаграмм зависимости\n",
    "for column in columns:\n",
    "    plt.figure(figsize=(8, 6))  # Установка размера графика\n",
    "    if pd.api.types.is_numeric_dtype(df[column]):  # Проверяем, является ли колонка числовой\n",
    "        # Проверяем, содержит ли колонка только два уникальных значения (0 и 1)\n",
    "        if df[column].nunique() == 2 and set(df[column].unique()).issubset({0, 1}):\n",
    "            # Если да, то строим столбчатую диаграмму\n",
    "            counts = df[column].value_counts()  # Считаем количество повторений каждого значения\n",
    "            counts.plot(kind='bar')  # Создаем столбчатую диаграмму\n",
    "            plt.title(f'Количество значений для {column}')\n",
    "            plt.xlabel(column)\n",
    "            plt.ylabel('Количество повторений')\n",
    "        else:\n",
    "            # Если колонка числовая, создаем диаграмму рассеяния\n",
    "            plt.scatter(df['stroke'], df[column], alpha=0.5)  # Создаем диаграмму рассеяния\n",
    "            plt.title(f'Зависимость {column} от stroke')\n",
    "            plt.xlabel('stroke (0 = нет, 1 = да)')\n",
    "            plt.ylabel(column)\n",
    "            plt.xticks([0, 1])  # Установка меток по оси X\n",
    "            plt.grid()  # Добавление сетки для удобства восприятия\n",
    "    else:\n",
    "        # Если колонка не числовая, строим столбчатую диаграмму\n",
    "        counts = df[column].value_counts()  # Считаем количество повторений каждого значения\n",
    "        counts.plot(kind='bar')  # Создаем столбчатую диаграмму\n",
    "        plt.title(f'Количество значений для {column}')\n",
    "        plt.xlabel(column)\n",
    "        plt.ylabel('Количество повторений')\n",
    "\n",
    "    plt.show()  # Отображение графика"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Функция для создания выборок\n",
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "def split_stratified_into_train_val_test(\n",
    "    df_input,\n",
    "    stratify_colname=\"y\",\n",
    "    frac_train=0.6,\n",
    "    frac_val=0.15,\n",
    "    frac_test=0.25,\n",
    "    random_state=None,\n",
    "):\n",
    "\n",
    "    if frac_train + frac_val + frac_test != 1.0:\n",
    "        raise ValueError(\n",
    "            \"fractions %f, %f, %f do not add up to 1.0\"\n",
    "            % (frac_train, frac_val, frac_test)\n",
    "        )\n",
    "\n",
    "    if stratify_colname not in df_input.columns:\n",
    "        raise ValueError(\"%s is not a column in the dataframe\" % (stratify_colname))\n",
    "\n",
    "    X = df_input  # Contains all columns.\n",
    "    y = df_input[\n",
    "        [stratify_colname]\n",
    "    ]  # Dataframe of just the column on which to stratify.\n",
    "\n",
    "    # Split original dataframe into train and temp dataframes.\n",
    "    df_train, df_temp, y_train, y_temp = train_test_split(\n",
    "        X, y, stratify=y, test_size=(1.0 - frac_train), random_state=random_state\n",
    "    )\n",
    "\n",
    "    # Split the temp dataframe into val and test dataframes.\n",
    "    relative_frac_test = frac_test / (frac_val + frac_test)\n",
    "    df_val, df_test, y_val, y_test = train_test_split(\n",
    "        df_temp,\n",
    "        y_temp,\n",
    "        stratify=y_temp,\n",
    "        test_size=relative_frac_test,\n",
    "        random_state=random_state,\n",
    "    )\n",
    "\n",
    "    assert len(df_input) == len(df_train) + len(df_val) + len(df_test)\n",
    "\n",
    "    return df_train, df_val, df_test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "stroke\n",
      "0    4861\n",
      "1     249\n",
      "Name: count, dtype: int64\n",
      "\n",
      "Обучающая выборка:  (3066, 12)\n",
      "stroke\n",
      "0    2917\n",
      "1     149\n",
      "Name: count, dtype: int64\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Контрольная выборка:  (1022, 12)\n",
      "stroke\n",
      "0    972\n",
      "1     50\n",
      "Name: count, dtype: int64\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Тестовая выборка:  (1022, 12)\n",
      "stroke\n",
      "0    972\n",
      "1     50\n",
      "Name: count, dtype: int64\n"
     ]
    },
    {
     "data": {
      "image/png": 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cnBykp6fj6dOn+O6776BSqTTf7dIyMzM1+8iqcHBwwIcffqh5LRAIMGPGDBQVFSEiIgJAybIKBAJMnz5da95Zs2aBMYZjx45pTe/UqRP8/f01rxs3box33nkHJ06cgFKp1Cqr3i7NzMxw5MgRre8uYwzh4eF4++23wRjT2lbUVxSX3pe8So26c9evXw9vb28IhUI4ODigWbNmWl9S9fmGDRs2ID4+XmsB1V2+QEk3cLNmzSAU1u49H5o2bar1msfjwcvLS3N+KSYmBgAwatSoCuvIycmBlZWV5nV6erpOvWXFxMSAMVZhubJdZ+rzUmUTV9k6c3JyKhygnJqaqvX65MmTsLOzqzTOsubPnw9nZ2dMmjRJ59xiTEwMHjx4UGGdZdsvT2JiIgYMGACZTIaMjIwKd1RVWR9ASVfj4sWLcfPmTa3zsqXrjYuLA5/PR4sWLSqsR30aorLxkU+ePAEANGvWTOc9Hx8fXLp0SWvas2fPtNaVk5MTwsPDK10msViMZcuWYdasWXBwcEDHjh0xcOBAfPTRR3B0dKxwvrI8PDyqFLuRkRGaNGmieV8tPj4eI0eOxHvvvYe1a9dqvRcbGwvGGObNm4d58+aV235qaqrmh3RFpk2bpvWjecyYMfj0008rX7AqiomJwe3bt1+5rcbFxcHZ2RnW1tav3eaTJ0/QtGlTnR9q6h9NZdfxq5b/yZMn6NChg047pesru70qlUrMnTsXI0aMQKtWraoV/6BBgzT/5/P5+OqrrzBkyBCdcqW3IXt7e0yYMAELFy7U+tGmxuPx4O3tXeE6Ue+Hnzx5AmdnZ60DntLlyq678var3t7eyM/PR1pamtZ3ZeDAgYiOjoa9vb3O+dW0tDRkZ2dj8+bN2Lx5s06dQNX2a2o1yl4BAQGaq3PL85///Afz5s3D2LFj8c0338Da2hp8Ph8zZszQOcLjgjqG5cuXo02bNuWWKb3Tk8vlSEpKQp8+fV5ZL4/Hw7Fjx8rduMruSJOTkwGg0h2lSqWCvb09du/eXe77ZXcYHTp0wOLFi7WmrVu3DocPHy53/gcPHmD79u3YtWtXuefHVCoV/Pz8sHLlynLnd3V1rTB2tdjYWLz11ltYtWoVPvzwQ+zYsaPcHzBVWR8XL15EaGgounXrhg0bNsDJyQkikQjbtm3TuRiICw4ODti1axeAkh9iW7duRf/+/XHp0iX4+flVON+MGTPw9ttv49ChQzhx4gTmzZuHpUuX4syZM2jbtm2V2n7d8YFOTk6aHptr165pfcfV35nPPvsM/fr1K3d+Ly+vV7bx+eefo2/fvlAqlbh37x4WLVoExhi2bdv2WrGrY+zTpw+++OKLct/39vZ+7TZelz6Wf8uWLUhISMCJEyeqPe+KFSvQunVrFBcX4+rVq1i8eDGEQqHOUXp4eDjMzc2Rn5+PgwcPYsmSJTA3Ny93Xb8J41QfPnyIY8eOISwsDLNmzdJav+pteeTIkRUeSFXnx4hebvt34MAB9OjRA1u2bNGanp2drTkxD5RcEHD58mUUFxfXysUxauojTTXGGGJjYzUrRn0hgrm5OXr37v3K+m7duoXi4uJKfzio62WMwcPDo0pf2Pv374PH45V7lFO6zoiICHTu3LlKG6etra3OMlV28c+cOXPQpk0bvP/++xW2f+vWLfTq1avGXezqHbODgwMOHz6MWbNmISQkROcHQFXWR3h4OCQSCU6cOKHV7Vt2J+Tp6QmVSoX79+9X+ENJvR3cvXu3wgTg5uYGAIiOjtbp5oqOjta8ryaRSLTWf2hoKKytrbFu3Tps2rSpwuVSxzNr1izMmjULMTExaNOmDb7//ntNUq7u+i8de5MmTTTT5XI54uPjdbYTiUSCo0ePomfPnujfvz/Onz8PX19fANDMLxKJqvSdqUiLFi008/fr1w9FRUWYO3culixZorngsKY8PT2Rl5f3yvg8PT1x4sQJZGZmvvbRqJubG27fvg2VSqV15PXw4UPN+6W9avnd3NwQHR2t005F9eXn52PhwoWYPHmyzntV4e/vr7nSODg4GImJiVi2bBnmzZuntTzdunXT7LtDQ0MRGRmJ48ePl5tEPTw8cP369QrXibu7u2ZZIiIikJubq3U0WtGylt2vA8CjR49gbGyssy85cuQIunbtiqVLl2Lq1KkYOXKkptvczs4OZmZmUCqVr7Utq+llVK5AINA5hN6/f7/OOZMhQ4YgPT0d69at06mj7PzV8csvvyA3N1fz+sCBA0hKSkJwcDCAkg3H09MTK1asQF5ens78aWlpOrELBIJyh4+UNnjwYAgEAixcuFAnfsYYMjIyNK8VCgXCw8MREBBQaVdfWFgYlEpluVcvKhSKKg1VqEhUVBQOHz6Mb7/9tsIddFhYGBITE8u9PL2goKBK50i8vb01VzOuXbsWKpVK56rFqq4PgUAAHo+ndYogISFB54fCoEGDwOfzsWjRIp3eD/Vn07dvX5iZmWHp0qU6543VZdq1awd7e3v8+OOPWl3Hx44dw4MHD7SuBi6PXC6HQqGodDhQfn6+Tvuenp4wMzPTms/ExKRan3fv3r1hZGSEH374QWt73LJlC3JycsqN3cLCAidOnIC9vT369Omj6fK2t7dH9+7dsWnTJiQlJenMV/Y7U1UFBQUAUOkwl6oKCwtDVFRUuUdk2dnZmmE6Q4YMAWMMCxcu1ClX3f1OSEgIkpOTsXfvXs00hUKBtWvXwtTUFEFBQZXOX3b5Q0JCcOXKFURFRWnKyGQybN68Ge7u7jqnJ9asWQOZTKa5Yvt1FRQUQKFQaNZVeRhjYIyV29umXoay60R9ik8sFmsSV0hICJRKpc7+f9WqVeDxeJr9tVpUVJTWucpnz57h8OHD6Nu3r04s6qv7J0+ejMDAQEyaNEmzrgUCAYYMGYLw8HDcvXtXJ/7qbst6ORIdOHAgFi1ahDFjxiAwMBB37tzB7t27tX4NAyUXAP3yyy+YOXMmrly5gq5du0ImkyEiIgKTJ0/GO++8U6P2ra2t0aVLF4wZMwYpKSlYvXo1vLy8MGHCBAAlff8///wzgoOD4evrizFjxsDFxQWJiYk4e/YszM3N8fvvv0Mmk2H9+vX44Ycf4O3tjXPnzmnaUCff27dvIyoqCp06dYKnpycWL16MOXPmICEhAYMGDYKZmRni4+Nx8OBBTJw4EZ999hkiIiIwb9483L59G7///nulyxIUFIRJkyZh6dKluHnzJvr27QuRSISYmBjs378fa9aswdChQ2u0nk6ePIk+ffpU+mvsww8/xL59+/Dxxx/j7Nmz6Ny5M5RKJR4+fIh9+/bhxIkTrzxCL83R0RHLly/H+PHjMXLkSISEhFRrfQwYMAArV65E//79MXz4cKSmpmL9+vXw8vLC7du3NeW8vLzw5Zdf4ptvvkHXrl0xePBgiMViXL16Fc7Ozli6dCnMzc2xatUqjB8/Hu3bt8fw4cNhZWWFW7duIT8/Hzt27IBIJMKyZcswZswYBAUF4YMPPtAMcXF3d9c5nyeTybS6c3fu3InCwsJKhyY8evQIvXr1QlhYGFq0aAGhUIiDBw8iJSUFw4YN05Tz9/fHxo0bsXjxYnh5ecHe3r7ci0DU7OzsMGfOHCxcuBD9+/dHaGgooqOjsWHDBrRv3x4jR44sdz5bW1ucOnUKXbp0Qe/evXHp0iW4uLhg/fr16NKlC/z8/DBhwgQ0adIEKSkpiIqKwvPnz8sdB15WVFQUhEKhpjtz7dq1aNu2rebo5HV8/vnnOHLkCAYOHIjRo0fD398fMpkMd+7cwYEDB5CQkABbW1v06NEDH374IX744QfExMSgf//+UKlUuHjxInr06IGpU6dWuc2JEydi06ZNGD16NP7++2+4u7vjwIEDiIyMxOrVq3XO971q+WfPno09e/YgODgY06dPh7W1NXbs2IH4+HiEh4frnGc8efIklixZonWtSXWcOnUKz58/13Tn7t69G6GhoTAyMtIqd+bMGa3u3NjY2AqHgYwbNw4bN27E6NGjce3aNXh4eODQoUM4ffo0vv32W02sb7/9Nnr06IEvv/wSCQkJaN26NU6ePInDhw9jxowZWkMcgZJrF/r166c1xAVAuT+G1Hg8Hn7++We0adMG8+fPx3fffQcA+Pbbb3H27Fl06NABEyZMQIsWLZCZmYnr168jIiICmZmZVV+JVb6Ol/1zqffVq1crLVdYWMhmzZrFnJycmFQqZZ07d2ZRUVFawx3U8vPz2Zdffsk8PDyYSCRijo6ObOjQoSwuLo4xVrMhLnv27GFz5sxh9vb2TCqVsgEDBrAnT57ozH/jxg02ePBgZmNjw8RiMXNzc2NhYWHs9OnTWm2/6q/05d2MlQwR6NKlCzMxMWEmJibMx8eHTZkyhUVHRzPGGJs2bRrr1q0bO378uE5MFV3Cv3nzZubv78+kUikzMzNjfn5+7IsvvmAvXrzQlKnuEBcej8f+/vtvrenlfUZyuZwtW7aM+fr6MrFYzKysrJi/vz9buHAhy8nJ0WnvVfUxxljPnj1Z48aNWW5ubrXXx5YtW1jTpk2ZWCxmPj4+bNu2bRWut61bt7K2bdtq4g4KCmKnTp3SKnPkyBEWGBjIpFIpMzc3ZwEBAWzPnj1aZfbu3aupx9ramo0YMUIzpEtt1KhRWtuFqakpe+utt9jOnTsrXUfp6elsypQpzMfHh5mYmDALCwvWoUMHtm/fPq1yycnJbMCAAczMzIwB0KzXV30v161bx3x8fJhIJGIODg7sk08+YVlZWVplSg9xUYuNjWVOTk6sefPmmiEOcXFx7KOPPmKOjo5MJBIxFxcXNnDgQHbgwIFKl7Hsd4nP57NGjRqxUaNG6azHylQ2xIWxkuEgc+bMYV5eXszIyIjZ2tqywMBAtmLFCiaXyzXlFAoFW758OfPx8WFGRkbMzs6OBQcH63wfGKt8iAtjjKWkpLAxY8YwW1tbZmRkxPz8/HSGslRn+ePi4tjQoUOZpaUlk0gkLCAggB09elSrjHpf5+TkxGQymdZ7qMYQF/WfUChkbm5ubPr06Vrbhnp9q/+kUilr0aIFW7VqlaZM2SEujJUMrxo7dqxmnbRs2ZL99NNPOnHk5uayTz/9lDk7OzORSMSaNm3Kli9frjPUCACbMmUK27Vrl+a737ZtW60hOqXjLWvhwoVMKBSy69eva6alpKSwKVOmMFdXV03u6dWrF9u8eXOl664s3v8CrBfOnTuHHj16YP/+/TU+OistISEBHh4eiI+Pr/CX8oIFC5CQkEA3BieEED3h8XiYMmVKuaf+uEaPQiOEEEJqiB7KXQlTU1OMGDGi0gtdWrVq9dpXFRJCCDFMlEQrYWtrq7lIpCKDBw+uo2gIIYS8aerVOVFCCCGkLtE5UUIIIaSGKIkSQgghNURJlBBCCKkhSqKEEEJIDVESJYQQQmqIkighhBBSQ5RECSGEkBqiJEoIIYTUECVRQuqZCxcu4O2334azszN4PF6lD2UnhLweSqKE1DMymQytW7fG+vXruQ6FkHqP7p1LSD0THByM4OBgrsMgpEGgI1FCCCGkhiiJEkIIITVESZQQQgipIUqihBBCSA1REiWEEEJqiK7OJaSeycvLQ2xsrOZ1fHw8bt68CWtrazRu3JjDyAipf3iMMcZ1EISQ2nPu3Dn06NFDZ/qoUaOwffv2ug+IkHqMkighHMopKEZabiFSc4uQ9r+/DJkcBXIlFCoVepo8QU/5OUBgBAiNSv41MgUsXQFLN8DKHTC25noxCGmwqDuXkDqgVDHEpeXh/ouXuPciB/eTXuJBUi4yZfJK52vZ5C7w4qfKKzcyA2y9AAdfwMGv5F/HloDUqhaXgBBSHkqihOjJs8x8nItOxdnoNPz1OAP5cqV+GpLnAi9ulPxp8ACnVkDTviV/Lu0APl1HSEhtoyRKSC26lpCJ43eTcTY6FXFpMg4jYUDSrZK/C8sBqTU2t9gOTy8fdG1qByMhJVRCagMlUUJeU8rLQuy/9gwH/n6OhIx8rsMpl0JojP9E5gGR12AuESK0jTNGdXJHUwczrkMjxKBREiWkhv6MTceOqAScfpAKherNvj7voWUQkFby/5eFCuz66yl2/fUUnb1s8FEnd/Ru7gABn8dtkIQYIEqihFTTpZh0rI54hGtPsrgOpcr2y9qUOz0yNgORsRlwsZRiXBcPjOzoRl29hFQDJVFCqujPuHSsPhWDKwmZXIdSLSqpLXYlOVVaJjG7AIuO3sfWyHjM7OONQW1cwKcjU0JeiZIoIa8Qk5KLrw/fQ9TjDK5DqZF4m25QZlXt6PJ5VgFm7ruFny7G44v+zdCjmb2eoyPEsFESJaQChcVKrDsTi00X4lCsfLPPeVbmiPytas/zIOklxmy7im7edvh2sB+cLaV6iIwQw0cnPwgpR2RsOoLXXMS6s7EGnUCZkSl+fuFW4/kvPEpDv1UXsOfK01qMipD6g5IoIaUUyJX44sAtjPj5MuLTuRznWTte2HWFTCF4rTpyixSY89sdfLjlMhKzC2opMkLqB0qihPxPXFoeBq2PxL5rz7kOpdYcV7WvtbouxqSj36oLOHQjsdbqJMTQURIlBMDvt14gdO0lRKfkch1KrWECMTa98KzVOvOKFJix9yYWHLmHYqWqVusmxBBREiUNWrFShfmH72LanhuQ6evethzJcOiE1CKRXure/mcCRvx8+ZU30CekvqMkShqsvCIFxm6/ih1RT7gORS/OIkCv9V+Jz8Q76y8hph4dvRNSXZRESYOUnleEYZujcDEmnetQ9ILxBNiY7KP3dp5lFmDoj1G4/Txb720R8iaiJEoanKScAoT9GIW7iS+5DkVvcu3b4XG+pE7ayikoxoifL+P6U8O5DSIhtYWSKGlQnmXm470fo/C4Hgxfqcyfoo512l5uoQIfbbmCqwZ2S0RCXhclUdJgpOcVYeSWy3ieVf/HOm5O863zNvOKFBi19Qqi4gzz9oiE1AQlUdIgyP53EdGTN/B5nzl/7ceTZQORGbG5wjLFSoZF54vg+UMuJItfovWPeTgeq9Aqs/t2MVxX5cLqOxkiftuj9Z4iJwWJmydCVaTf5c+XKzFux1Xce5Gj13YIeVNQEiX1XrFShU92X8ft52/ejr0o6RFybx6HyM690nJfnSnCpr/lWBsswf0ppvjY3wjv7s3HjaSSYTnp+SqM/70AK/pIsGzmcMjun0N+7BXN/BknN8AqaDT4YmN9Lg6AkkQ6fsc1pLws1HtbhHCNkiip9/4dfhsXHqVxHYYOlbwA6b+vgE3/aeBLTCstu/N2MeZ2ESOkqQhNrPj4pL0RQpoK8X1UyTjNx1kMFmIe3m8pwl8WfSBp3ArFGc8AALL758HjC2HcLFDvy6SWlFOI8TuuoaCejb0lpCxKoqRe+/F8HH67/mbepi7z1EZIPdtD6t7mlWWLlICkzDOXpEIeLj0t6dJtas1HfjHDlTwnnHougjzpEYzs3KEszEP2xV2w7vOxHpagcncSczBj7w0wZrg38CfkVSiJknrr7ydZWHEimuswyiW7fx7y5DhYBY2qUvl+ngKs/EuOmAwlVIzhVJwCvz0oRlJeSYKykvKwY5AUw39NR/IvM2HSsiekTfyRdWYLzN4aCEVOCl5sm44XWyZD9vCSPhdNy4l7KVgVEVNn7RFS1+h5oqReyskvxvQ9N6BQvXlHQYqXacg8/RMc3v8GPKFRleZZ01+CCb8Xwme9DDwAntZ8jGkjwtabxZoy7zYXIbLTdziQ7AAAKHx6B8VpCbDuMwkvNk+E7dufQ2BihaRfZkLi2hICE0s9LJ2u9WdjEeRtB383qzppj5C6REmU1EtfhN96Yx/bJU+OhSo/G0nb//XPRKZC0bN7yL1+FI0/OwgeX/vxZXYmfBwaZoxCBUNGPoOzGQ+zI4rQxOqfziSlqTPCU+xLqlMUI/PkRtgMnAlFVhKYSglJYz8AgMjaBUVJ0TD26qD/hQWgVDF8uvcmjv2rK0zEtMsh9Qtt0aTe2RmVgBP3UrgOo0ISt9ZwGrtOa1rGH2sgsmkE8w5DdBKo1rxCHlzMeShWMoQ/KEaY7z83mH9k1Q0snQcAyPnzV0iavAWxoxfkKXGA6p8LfJhKAajq9gksTzPzsej3+1g2tFWdtkuIvlESJfVKystCLDv+Zp4HVeOLjWFUZkgLTyQGX2KmmZ5+9HsIzGyAJv4AgMvPFUjMZWjjKEDiSxUWnC+CigFfdBZr6ggvaAsAkKc/hezhRTiN/gEAILRuBPD4yL11EgJTKxRnPIeRU1P9L2gZe689Q6/m9ujr61jnbROiL5RESb3yzdH7yCtSvLrgG07xMg3g/dNVW6goGSv6OEsFUyMeQpoKsfNdKSwlJUeeKqk1dr5wAWMMmcfXwarnePCNSu6dyxeJYRMyA5mnNoIpi2Hd52MIzWw5Wa65B++ik6cNzCT6eUQbIXWNx+j6c1JPRMamY8TPl7kOo1Z92+QOhr1Y+spy8Y0GoUdsWB1E9PrGd/HAVwNbcB0GIbWChriQekGuUGHe4btch8GZo3J/rkOosh1RCYhNzeM6DEJqBSVRUi9sjYzH47T6/WSWijCRCTa/cOM6jCorVjJ8e+wh12EQUisoiRKDl1tYjI3n4rgOgzPJ9p2RqzCsyxsiHqTgSjw9No0YPkqixOBti0xATkHxqwvWU6dUAVyHUCMrT73ZV1ETUhWURIlBkxUpsDUynuswOMP4ImxM8uI6jBr563Em7ia+eU/WIaQ6KIkSg7bnylNk5zfco9As+45IKqzarQPfRJsvPOY6BEJeCyVRYrAUShW2Xmq4R6EAcE7QkesQXssfd5Lw4g29PSMhVUFJlBisMw9T8SKn4T74mfH4+DHZh+swXotCxbCtAXfHE8NHSZQYrPDrz7kOgVN5dm/hkUzKdRiv7dcrz1BYTA/vJoaJkigxSJkyOc48TOU6DE79ZdSJ6xBqRW6RosF/lsRwURIlBunIzUQUKxv2HSt/SvflOoRac/T2C65DIKRGKIkSg3SggXflFtq0wJVsc67DqDVnHqZCVg8eHEAaHkqixOA8yZDhbuJLrsPg1A3jLlyHUKsKi1WIePDmPgOWkIpQEiUG50JMOtchcO6X7JZch1Drfr+VxHUIhFQbJVFicC7FpHEdAqeKLdxxLI2b54HqU1RcOpSqhn2emxgeSqLEoChVDH/GZXAdBqfuW3TlOgS9kMmVdBtAYnAoiRKDcut5NnILG/YFKL/mtuY6BL25mkBPdiGGhZIoMSiRDfx8qNLEAb8mO3Edht5cpsejEQNDSZQYlDsNvLsvzrobGONxHYbeXEvIBGN0XpQYDkqixKA8SsnlOgROHSxsy3UIepWVX4zH6TKuwyCkyiiJEoNRIFfiaWY+12FwhoktsP2FK9dh6F1MSh7XIRBSZZREicGISc1FQx4B8cyuGwqUAq7D0Lu4NEqixHBQEiUGIzq5YXfl/lHsz3UIdYKSKDEklESJwYhLa7jnyphQik0vmnAdRp14nkkP6SaGg5IoMRipuQ33Adyp9p2RVSzkOow68Tyr4Z73JoaHkigxGGm5RVyHwJnTaM91CHUmLa/hfs7E8FASJQYjUybnOgROML4QG154cx1GnSlWMhQplFyHQUiVUBIlBiOnoJjrEDiRYx+A54VirsOoU7IiSqLEMFASJQajod4z96KwE9ch1Dl6QDcxFJREicFoiF18KgA/pvhwHUadk8kpiRLDQEmUGAwBr/7eM7YiJ7Mb4V6uCddh1Dk6EiWGgpIoMRgCfsNLoucyrbgOgRP8BviDiRgmSqLEYIgEtLk2FCbihjEmlhg+2isRg9EQj0QbKqmo/t8jmNQPlESJwaAj0YbD2IiSKDEMtFciBsNCKuI6BFJHjI2oO5cYBkqixGA4WUi4DoHUAQGfB4mIdk3EMNCWSgyGkyUl0YbAxVIKHl2dSwwEJVFiMJwspFyHQOqAm40x1yEQUmWURInBcDSnI9GGoLE1JVFiOCiJEoPhYkVHog2Bu03Du0MTMVyURInBaO5kDjpVVv81pu5cYkAoiRKDYSEVwY26+uo9L3tTrkMgpMooiRKD0qqRJdchED2ykIrQxJa6c4nhoCRKDEqrRhZch0D0qLWrJQ1vIQaFkigxKHQkWr+1d2uYT60hhouSKDEofi4WMBLSZltfdfS04ToEQqqF9kbEoEiNBOjgYc11GEQPpCIBWlNPAzEwlESJwenRzJ7rEIgedPO2pV4GYnBoiyUGp08LB65DIHowoJUz1yEQUm2URInBcbU2hq+zOddhkFokEfHRuzn1MBDDQ0mUGKQQPyeuQyC1qEcze3qGKDFIlESJQRryViMI+TSesL4Y0Ip+FBHDREmUGCRHCwl6UfdfvWAuEaKXD53nJoaJkigxWB92dOc6BFILPujQGFIjAddhEFIjlESJwersZQMPus+qQRPyeRgd6M51GITUGCVRYrB4PB5GdGjMdRjkNQT7OcHJgp4TSwwXJVFi0N5v7wpLYxHXYZAaGt/Fg+sQCHktlESJQTOTiPBxkCfXYZAaCPCwRmtXS67DIOS1UBIlBm90oDvszcRch0GqgccD5gT7cB0GIa+NkigxeBKRANN6NeU6DFINA1s5o21jeuwZMXyUREm9MKy9KxpbG3MdBqkCsZCPf/dvxnUYhNQKus8WqRdEAj6+HNAck3b+XWdtqorykX1xF/JjoqDKz4GRfRNY9Z4IsZM3ACD9v6sgu3taax6Jx1twCFtUYZ2Fz+7i5eVwyFPioMzLhN27X8LYu5NWmZzLv+HllXAAgEWHITAPGKx5r+hFNDJPboDjRyvB47+ZYy/HdPZAIyv6wUPqB0qipN7o5+uIED9H/HEnuU7ayzi+FsVpT2A7cBYEptaQ3TuLlF+/gvP4DRCa2QIAJB7+sA2Z8c9MwsqvJGbyQojsm8C0VR+kHfyPzvvy1HjkXNoNu6FfA4whLXwRJB5vwcjOHUylRMaJ9bDpP/WNTaC2pmJM6UEXgpH6g7pzSb2yMLRlnQx5URUXIT86EpY9xkDi2hIiK2dYdhkBkZUTcm8c05TjCUUQmFr98ycxrbReqWc7WHX7EMbegeW+X5zxHCI7d0jdWkPq3gYiO3cUZzwHALy8HA6Jq6/mSPhNtOTdljCT0JAkUn9QEiX1ip2ZGPMGtNB/QyolwFTgCbQTAk8oRtHze5rXhU/v4NnaEUj8aRIyTqyHsuDlazVrZOcORVYiFC9TochJhSIzEUa2bijOSkLenQhYdv3wterXp3faOKOfryPXYRBSq6g7l9Q7Q/wb4citFzj/KE1vbfDFxhA7+yDnz18hsnGFwMQSsgcXUPTiIYRWJU8kkXq8BWPvQAgtHaDISkL2hV+Qun8+HEeuqHF3q8jWFZbdPkLK3nkAAMugURDZuiLl1y9h1X0MCuKvIyfy/wC+ENa9J0Li2rLWlvl1OFlIsCj0zYiFkNpESZTUS8uHtsKAtZeQlluktzZsBs5CxrE1SNwwCuDxYeToCZPm3VCUHAsAMGkRpClrZOcOkb0HXmwaj8KndyB1b1Pjds3ahsCsbYjmdd6d0+AZSSF28UHiTx/D6aOVUOZmIP3Id3CZtAW8V5yH1Tc+D1gZ1gYWdGcpUg9REiX1kr25BGs/aIsRP1+GUsX00obIygmOw7+FSl4IlTwfQlNrpB1eBpFl+V2WIktH8KXmUGQnAWhTKzEo83OQE/l/cBi+DEUvHkFk7QyRtQtE1i5gSgWKsxJhZOdeK23V1LSeTdHJ04bTGAjRFzonSuqtjk1s6mQ8It9IAqGpNZSFeSiIvw5p047lllO8TIeqIBcCE+taazvrzM8waz8IQnNbgCnBlMp/3lQpAZWq1tqqiQF+TpjRm26EQeovOhIl9drEbp54mJSL324k1nrdBY9LxqQKrV2gyEpC1rmtEFk3gqlfb6jkBciJ3ANj70AITK1QnJWE7HPbILRygtTjLU0dKb/OhbRpJ5j7vw0AUMkLoMhK0ryvyEmBPOUx+FJTCM21H0JeEH8DxZmJsBnwKQDAyNEbisznKIi7BkVuOsAXQGjtUuvLXVWtGlng+7DW4PF4nMVAiL5REiX13n8G++FpZj6uPcmq1XpVRfnIvrADitx0CCRmMG4WCMtuH4EnEIKplJCnxiPv7mmoCmUQmFpD6tEWll1Hap2jLM5KhrjUFbvy5Bik7JmreZ115mcAgEnLXrD9X7IESobYZEb8CLvQf4PHK+lQEprbwqr3JKQfWw2eQASbAZ+CL+LmnsKO5hL89FE7SERv5nhVQmoLjzGmnxNGhLxBXhYWY8RPl3EnMYfrUOo9EyMB9k7qhJYuFlyHQoje0TlR0iCYS0T4ZWwAmjmYcR1KvWYqFmL72ABKoKTBoCRKGgwrEyPsHB8AD1sTrkOpl0zFQuwY2x7t3WvvwilC3nSUREmDYm8mwe7xHeBmQzdAr01mYiF2jA2AvxslUNKw0DlR0iBl5BVh/C/XcONpNtehGDxzSUkCpeeDkoaIkihpsAqLlfh0700cu1s3T32pj5rYmeDnj9qhiV3lN9YnpL6iJEoaNMYYlh57iM0XHnMdisEJ8rbD2uFtYU5PZSENGCVRQgD8euUpFvx+D4XF3N7hx1BM7NYEs/v7gM+nGymQho2SKCH/E5OSi+m/3sSDpNd7XFl9ZiYW4ptBLTGoLXd3QiLkTUJJlJBSihRKfHc8Glsj40HfDG0B7tb4Pqw1XK3pymZC1CiJElKO84/S8MWBW0h5qb9HqRkKqUiAz/o1w5hAd+q+JaQMSqKEVCCvSIHVpx5h+58JUOjpcWpvum7edlj8Tks0pnG1hJSLkighr/AoJRffHL2PizHpXIdSZ1o4mWNOiA+6NrXjOhRC3miURAmponPRqVh+Ihr3XtTfC49cLKWY1dcb77Z1oUeYEVIFlEQJqaYLj9Kw6UIcImMzuA6l1jS2NsboQHeM6NgYYiE9voyQqqIkSkgN3Xmegx8vxOH43WQoDfScaaCnDcZ09kAvH3u6aIiQGqAkSshrepFdgCO3XuDQjUQ8TM7lOpxXsjQWIcTPCaMD3eFNj4Yj5LVQEiWkFkUn5+LwzUQcvvkCidkFXIejYWcmRj9fBwS3dEIHD2sIBfQAJ0JqAyVRQvQkNjUXUXEZ+OtxJv56nIEMmbzO2jYS8NGqkQXae1ijp489/BtbUXctIXpASZSQOsAYQ0xqHq7EZyI6ORfRKbmIS82rlcRqbWKERlZSeNiaoFUjS7RuZIGWLhaQiOgCIUL0jZIoIRzKK1IgIV2G1NxCvCxQILewGC8LFXhZWIzcQgV4AMRCASQivuZfYyMBnCykcLU2RiMrKUzEQq4Xg5AGi5IoIXq0fv16LF++HMnJyWjdujXWrl2LgIAArsMihNQSurqAED3Zu3cvZs6cifnz5+P69eto3bo1+vXrh9TUVK5DI4TUEjoSJURPOnTogPbt22PdunUAAJVKBVdXV0ybNg2zZ8/mODpCSG2gI1FC9EAul+Pvv/9G7969NdP4fD569+6NqKgoDiMjhNQmSqKE6EF6ejqUSiUcHBy0pjs4OCA5OZmjqAghtY2SKCGEEFJDlEQJ0QNbW1sIBAKkpKRoTU9JSYGjoyNHURFCahslUUL0wMjICP7+/jh9+rRmmkqlwunTp9GpUycOIyOE1CYapU2InsycOROjRo1Cu3btEBAQgNWrV0Mmk2HMmDFch0YIqSWURAnRk/fffx9paWn4+uuvkZycjDZt2uD48eM6FxsRQgwXjRMlhBBCaojOiRJCCCE1REmUEEIIqSFKooQQQkgNURIlhBBCaoiSKCGEEFJDlEQJIYSQGqIkSgghhNQQJVFCCCGkhiiJEkIIITVESZQQQgipIUqihBBCSA1REiWEEEJqiJIoIYQQUkOURAkhhJAa+n+UZ21TL3/Z0AAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Вывод распределения количества наблюдений по меткам (классам)\n",
    "print(df.stroke.value_counts())\n",
    "print()\n",
    "\n",
    "data = df.copy()\n",
    "\n",
    "df_train, df_val, df_test = split_stratified_into_train_val_test(\n",
    "   data, stratify_colname=\"stroke\", frac_train=0.60, frac_val=0.20, frac_test=0.20\n",
    ")\n",
    "\n",
    "print(\"Обучающая выборка: \", df_train.shape)\n",
    "print(df_train.stroke.value_counts())\n",
    "counts = df_train['stroke'].value_counts()\n",
    "plt.figure(figsize=(2, 2))# Установка размера графика\n",
    "plt.pie(counts, labels=counts.index, autopct='%1.1f%%', startangle=90)# Построение круговой диаграммы\n",
    "plt.title('Распределение классов stroke в обучающей выборке')# Добавление заголовка\n",
    "plt.show()# Отображение графика\n",
    "\n",
    "print(\"Контрольная выборка: \", df_val.shape)\n",
    "print(df_val.stroke.value_counts())\n",
    "counts = df_val['stroke'].value_counts()\n",
    "plt.figure(figsize=(2, 2))\n",
    "plt.pie(counts, labels=counts.index, autopct='%1.1f%%', startangle=90)\n",
    "plt.title('Распределение классов stroke в контрольной выборке')\n",
    "plt.show()\n",
    "\n",
    "print(\"Тестовая выборка: \", df_test.shape)\n",
    "print(df_test.stroke.value_counts())\n",
    "counts = df_test['stroke'].value_counts()\n",
    "plt.figure(figsize=(2, 2))\n",
    "plt.pie(counts, labels=counts.index, autopct='%1.1f%%', startangle=90)\n",
    "plt.title('Распределение классов stroke в тестовой выборке')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Сбалансируем распределение:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. Балансировка данных оверсемплингом. Это метод, увеличивающий число наблюдений в меньшинственном классе для достижения более равномерного распределения классов."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Обучающая выборка после oversampling:  (5811, 18)\n",
      "stroke\n",
      "0    2917\n",
      "1    2894\n",
      "Name: count, dtype: int64\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from imblearn.over_sampling import ADASYN\n",
    "from sklearn.compose import ColumnTransformer\n",
    "from sklearn.preprocessing import OneHotEncoder\n",
    "\n",
    "categorical_features = ['gender', 'ever_married', 'work_type', 'Residence_type']  # Ваши категориальные признаки\n",
    "numeric_features = ['age', 'hypertension', 'heart_disease', 'avg_glucose_level', 'bmi']  # Ваши числовые признаки\n",
    "\n",
    "# Создание пайплайна для обработки категориальных данных\n",
    "preprocessor = ColumnTransformer(\n",
    "    transformers=[\n",
    "        ('cat', OneHotEncoder(), categorical_features),  # OneHotEncoder для категориальных данных\n",
    "        ('num', 'passthrough', numeric_features)  # Оставляем числовые колонки без изменений\n",
    "    ]\n",
    ")\n",
    "\n",
    "# Создание экземпляра ADASYN\n",
    "ada = ADASYN()\n",
    "\n",
    "# Преобразование данных с помощью пайплайна\n",
    "X = preprocessor.fit_transform(df_train.drop(columns=['stroke']))\n",
    "y = df_train['stroke']\n",
    "\n",
    "# Применение ADASYN\n",
    "X_resampled, y_resampled = ada.fit_resample(X, y)\n",
    "\n",
    "# Создание нового DataFrame\n",
    "df_train_adasyn = pd.DataFrame(X_resampled)\n",
    "# Восстанавливаем названия столбцов для DataFrame\n",
    "ohe_columns = preprocessor.named_transformers_['cat'].get_feature_names_out(categorical_features)\n",
    "new_column_names = list(ohe_columns) + numeric_features\n",
    "df_train_adasyn.columns = new_column_names\n",
    "\n",
    "# Добавление целевой переменной\n",
    "df_train_adasyn['stroke'] = y_resampled\n",
    "\n",
    "# Вывод информации о новой выборке\n",
    "print(\"Обучающая выборка после oversampling: \", df_train_adasyn.shape)\n",
    "print(df_train_adasyn['stroke'].value_counts())\n",
    "\n",
    "# Визуализация\n",
    "counts = df_train_adasyn['stroke'].value_counts()\n",
    "plt.figure(figsize=(6, 6))\n",
    "plt.pie(counts, labels=counts.index, autopct='%1.1f%%', startangle=90)\n",
    "plt.title('Распределение классов Stroke в тренировочной выборке после ADASYN')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "2. Балансировка данных андерсемплингом. Этот метод помогает сбалансировать выборку, уменьшая количество экземпляров класса большинства, чтобы привести его в соответствие с классом меньшинства."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Обучающая выборка после undersampling:  (298, 12)\n",
      "stroke\n",
      "0    149\n",
      "1    149\n",
      "Name: count, dtype: int64\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from imblearn.under_sampling import RandomUnderSampler\n",
    "\n",
    "rus = RandomUnderSampler()# Создание экземпляра RandomUnderSampler\n",
    "\n",
    "# Применение RandomUnderSampler\n",
    "X_resampled, y_resampled = rus.fit_resample(df_train.drop(columns=['stroke']), df_train['stroke'])\n",
    "\n",
    "# Создание нового DataFrame\n",
    "df_train_undersampled = pd.DataFrame(X_resampled)\n",
    "df_train_undersampled['stroke'] = y_resampled  # Добавление целевой переменной\n",
    "\n",
    "# Вывод информации о новой выборке\n",
    "print(\"Обучающая выборка после undersampling: \", df_train_undersampled.shape)\n",
    "print(df_train_undersampled['stroke'].value_counts())\n",
    "\n",
    "# Визуализация распределения классов\n",
    "counts = df_train_undersampled['stroke'].value_counts()\n",
    "plt.figure(figsize=(2, 2))\n",
    "plt.pie(counts, labels=counts.index, autopct='%1.1f%%', startangle=90)\n",
    "plt.title('Распределение классов stroke в тренировочной выборке после Undersampling')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3. Датасет: Набор данных для анализа и прогнозирования сердечного приступа\n",
    "https://www.kaggle.com/datasets/kamilpytlak/personal-key-indicators-of-heart-disease\n",
    "##### О наборе данных: \n",
    "По данным CDC, болезни сердца являются основной причиной смерти представителей большинства рас в США (афроамериканцев, американских индейцев и коренных жителей Аляски, а также белых). Около половины всех американцев (47%) имеют по крайней мере 1 из 3 основных факторов риска сердечно-сосудистых заболеваний: высокое кровяное давление, высокий уровень холестерина и курение. Другие ключевые показатели включают сахарный диабет, ожирение (высокий ИМТ), недостаточную физическую активность или чрезмерное употребление алкоголя. Выявление и профилактика факторов, оказывающих наибольшее влияние на сердечно-сосудистые заболевания, очень важны в здравоохранении. В свою очередь, достижения в области вычислительной техники позволяют применять методы машинного обучения для выявления \"закономерностей\" в данных, которые позволяют предсказать состояние пациента.\n",
    "\n",
    "##### Таким образом:\n",
    "* Объект наблюдения - представители большинства рас в США\n",
    "* Атрибуты: HeartDisease, BMI, Smoking, AlcoholDrinking, Stroke, PhysicalHealth(как много дней за месяц вы чувствовали себя плохо), MentalHealth(как много дней за месяц вы чувствовали себя ментально плохо), DiffWalking, Sex, AgeCategory, Race, Diabetic, PhysicalActivity, GenHealth, SleepTime, Asthma, KidneyDisease, SkinCancer.\n",
    "* Проблемная область: прогнозирование сердечного приступа у человека."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Количество колонок: 18\n",
      "Колонки: HeartDisease, BMI, Smoking, AlcoholDrinking, Stroke, PhysicalHealth, MentalHealth, DiffWalking, Sex, AgeCategory, Race, Diabetic, PhysicalActivity, GenHealth, SleepTime, Asthma, KidneyDisease, SkinCancer\n",
      "\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 319795 entries, 0 to 319794\n",
      "Data columns (total 18 columns):\n",
      " #   Column            Non-Null Count   Dtype  \n",
      "---  ------            --------------   -----  \n",
      " 0   HeartDisease      319795 non-null  object \n",
      " 1   BMI               319795 non-null  float64\n",
      " 2   Smoking           319795 non-null  object \n",
      " 3   AlcoholDrinking   319795 non-null  object \n",
      " 4   Stroke            319795 non-null  object \n",
      " 5   PhysicalHealth    319795 non-null  float64\n",
      " 6   MentalHealth      319795 non-null  float64\n",
      " 7   DiffWalking       319795 non-null  object \n",
      " 8   Sex               319795 non-null  object \n",
      " 9   AgeCategory       319795 non-null  object \n",
      " 10  Race              319795 non-null  object \n",
      " 11  Diabetic          319795 non-null  object \n",
      " 12  PhysicalActivity  319795 non-null  object \n",
      " 13  GenHealth         319795 non-null  object \n",
      " 14  SleepTime         319795 non-null  float64\n",
      " 15  Asthma            319795 non-null  object \n",
      " 16  KidneyDisease     319795 non-null  object \n",
      " 17  SkinCancer        319795 non-null  object \n",
      "dtypes: float64(4), object(14)\n",
      "memory usage: 43.9+ MB\n"
     ]
    },
    {
     "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>HeartDisease</th>\n",
       "      <th>BMI</th>\n",
       "      <th>Smoking</th>\n",
       "      <th>AlcoholDrinking</th>\n",
       "      <th>Stroke</th>\n",
       "      <th>PhysicalHealth</th>\n",
       "      <th>MentalHealth</th>\n",
       "      <th>DiffWalking</th>\n",
       "      <th>Sex</th>\n",
       "      <th>AgeCategory</th>\n",
       "      <th>Race</th>\n",
       "      <th>Diabetic</th>\n",
       "      <th>PhysicalActivity</th>\n",
       "      <th>GenHealth</th>\n",
       "      <th>SleepTime</th>\n",
       "      <th>Asthma</th>\n",
       "      <th>KidneyDisease</th>\n",
       "      <th>SkinCancer</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>No</td>\n",
       "      <td>16.60</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>3.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>No</td>\n",
       "      <td>Female</td>\n",
       "      <td>55-59</td>\n",
       "      <td>White</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Very good</td>\n",
       "      <td>5.0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>No</td>\n",
       "      <td>20.34</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>No</td>\n",
       "      <td>Female</td>\n",
       "      <td>80 or older</td>\n",
       "      <td>White</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Very good</td>\n",
       "      <td>7.0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>No</td>\n",
       "      <td>26.58</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>20.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>No</td>\n",
       "      <td>Male</td>\n",
       "      <td>65-69</td>\n",
       "      <td>White</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Fair</td>\n",
       "      <td>8.0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>No</td>\n",
       "      <td>24.21</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>No</td>\n",
       "      <td>Female</td>\n",
       "      <td>75-79</td>\n",
       "      <td>White</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Good</td>\n",
       "      <td>6.0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>No</td>\n",
       "      <td>23.71</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>28.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Female</td>\n",
       "      <td>40-44</td>\n",
       "      <td>White</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Very good</td>\n",
       "      <td>8.0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  HeartDisease    BMI Smoking AlcoholDrinking Stroke  PhysicalHealth  \\\n",
       "0           No  16.60     Yes              No     No             3.0   \n",
       "1           No  20.34      No              No    Yes             0.0   \n",
       "2           No  26.58     Yes              No     No            20.0   \n",
       "3           No  24.21      No              No     No             0.0   \n",
       "4           No  23.71      No              No     No            28.0   \n",
       "\n",
       "   MentalHealth DiffWalking     Sex  AgeCategory   Race Diabetic  \\\n",
       "0          30.0          No  Female        55-59  White      Yes   \n",
       "1           0.0          No  Female  80 or older  White       No   \n",
       "2          30.0          No    Male        65-69  White      Yes   \n",
       "3           0.0          No  Female        75-79  White       No   \n",
       "4           0.0         Yes  Female        40-44  White       No   \n",
       "\n",
       "  PhysicalActivity  GenHealth  SleepTime Asthma KidneyDisease SkinCancer  \n",
       "0              Yes  Very good        5.0    Yes            No        Yes  \n",
       "1              Yes  Very good        7.0     No            No         No  \n",
       "2              Yes       Fair        8.0    Yes            No         No  \n",
       "3               No       Good        6.0     No            No        Yes  \n",
       "4              Yes  Very good        8.0     No            No         No  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "df = pd.read_csv(\".//static//csv//heart.csv\", sep=\",\")\n",
    "print('Количество колонок: ' + str(df.columns.size))  \n",
    "print('Колонки: ' + ', '.join(df.columns)+'\\n')\n",
    "\n",
    "df.info()\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Получение сведений о пропущенных данных\n",
    "Типы пропущенных данных:\n",
    "\n",
    "- None - представление пустых данных в Python\n",
    "- NaN - представление пустых данных в Pandas\n",
    "- '' - пустая строка"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "HeartDisease        0\n",
      "BMI                 0\n",
      "Smoking             0\n",
      "AlcoholDrinking     0\n",
      "Stroke              0\n",
      "PhysicalHealth      0\n",
      "MentalHealth        0\n",
      "DiffWalking         0\n",
      "Sex                 0\n",
      "AgeCategory         0\n",
      "Race                0\n",
      "Diabetic            0\n",
      "PhysicalActivity    0\n",
      "GenHealth           0\n",
      "SleepTime           0\n",
      "Asthma              0\n",
      "KidneyDisease       0\n",
      "SkinCancer          0\n",
      "dtype: int64\n",
      "\n",
      "HeartDisease        False\n",
      "BMI                 False\n",
      "Smoking             False\n",
      "AlcoholDrinking     False\n",
      "Stroke              False\n",
      "PhysicalHealth      False\n",
      "MentalHealth        False\n",
      "DiffWalking         False\n",
      "Sex                 False\n",
      "AgeCategory         False\n",
      "Race                False\n",
      "Diabetic            False\n",
      "PhysicalActivity    False\n",
      "GenHealth           False\n",
      "SleepTime           False\n",
      "Asthma              False\n",
      "KidneyDisease       False\n",
      "SkinCancer          False\n",
      "dtype: bool\n",
      "\n",
      "HeartDisease процент пустых значений: %0.00\n",
      "BMI процент пустых значений: %0.00\n",
      "Smoking процент пустых значений: %0.00\n",
      "AlcoholDrinking процент пустых значений: %0.00\n",
      "Stroke процент пустых значений: %0.00\n",
      "PhysicalHealth процент пустых значений: %0.00\n",
      "MentalHealth процент пустых значений: %0.00\n",
      "DiffWalking процент пустых значений: %0.00\n",
      "Sex процент пустых значений: %0.00\n",
      "AgeCategory процент пустых значений: %0.00\n",
      "Race процент пустых значений: %0.00\n",
      "Diabetic процент пустых значений: %0.00\n",
      "PhysicalActivity процент пустых значений: %0.00\n",
      "GenHealth процент пустых значений: %0.00\n",
      "SleepTime процент пустых значений: %0.00\n",
      "Asthma процент пустых значений: %0.00\n",
      "KidneyDisease процент пустых значений: %0.00\n",
      "SkinCancer процент пустых значений: %0.00\n"
     ]
    }
   ],
   "source": [
    "# Количество пустых значений признаков\n",
    "print(df.isnull().sum())\n",
    "print()\n",
    "\n",
    "# Есть ли пустые значения признаков\n",
    "print(df.isnull().any())\n",
    "print()\n",
    "\n",
    "# Процент пустых значений признаков\n",
    "for i in df.columns:\n",
    "    null_rate = df[i].isnull().sum() / len(df) * 100\n",
    "    print(f\"{i} процент пустых значений: %{null_rate:.2f}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Пропущенные данные отсутствуют.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Проверим выбросы и усредним их:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Колонка BMI:\n",
      "  Есть выбросы: Да\n",
      "  Количество выбросов: 10396\n",
      "  Минимальное значение: 12.02\n",
      "  Максимальное значение: 94.85\n",
      "  1-й квартиль (Q1): 24.03\n",
      "  3-й квартиль (Q3): 31.42\n",
      "\n",
      "Колонка PhysicalHealth:\n",
      "  Есть выбросы: Да\n",
      "  Количество выбросов: 47146\n",
      "  Минимальное значение: 0.0\n",
      "  Максимальное значение: 30.0\n",
      "  1-й квартиль (Q1): 0.0\n",
      "  3-й квартиль (Q3): 2.0\n",
      "\n",
      "Колонка MentalHealth:\n",
      "  Есть выбросы: Да\n",
      "  Количество выбросов: 51576\n",
      "  Минимальное значение: 0.0\n",
      "  Максимальное значение: 30.0\n",
      "  1-й квартиль (Q1): 0.0\n",
      "  3-й квартиль (Q3): 3.0\n",
      "\n",
      "Колонка SleepTime:\n",
      "  Есть выбросы: Да\n",
      "  Количество выбросов: 4543\n",
      "  Минимальное значение: 1.0\n",
      "  Максимальное значение: 24.0\n",
      "  1-й квартиль (Q1): 6.0\n",
      "  3-й квартиль (Q3): 8.0\n",
      "\n"
     ]
    }
   ],
   "source": [
    "numeric_columns = ['BMI', 'PhysicalHealth', 'MentalHealth', 'AgeCategory', 'SleepTime']\n",
    "for column in numeric_columns:\n",
    "    if pd.api.types.is_numeric_dtype(df[column]):  # Проверяем, является ли колонка числовой\n",
    "        q1 = df[column].quantile(0.25)  # Находим 1-й квартиль (Q1)\n",
    "        q3 = df[column].quantile(0.75)  # Находим 3-й квартиль (Q3)\n",
    "        iqr = q3 - q1  # Вычисляем межквартильный размах (IQR)\n",
    "\n",
    "        # Определяем границы для выбросов\n",
    "        lower_bound = q1 - 1.5 * iqr  # Нижняя граница\n",
    "        upper_bound = q3 + 1.5 * iqr  # Верхняя граница\n",
    "\n",
    "        # Подсчитываем количество выбросов\n",
    "        outliers = df[(df[column] < lower_bound) | (df[column] > upper_bound)]\n",
    "        outlier_count = outliers.shape[0]\n",
    "\n",
    "        print(f\"Колонка {column}:\")\n",
    "        print(f\"  Есть выбросы: {'Да' if outlier_count > 0 else 'Нет'}\")\n",
    "        print(f\"  Количество выбросов: {outlier_count}\")\n",
    "        print(f\"  Минимальное значение: {df[column].min()}\")\n",
    "        print(f\"  Максимальное значение: {df[column].max()}\")\n",
    "        print(f\"  1-й квартиль (Q1): {q1}\")\n",
    "        print(f\"  3-й квартиль (Q3): {q3}\\n\")\n",
    "\n",
    "        # Устраняем выбросы: заменяем значения ниже нижней границы на саму нижнюю границу, а выше верхней — на верхнюю\n",
    "        df[column] = df[column].apply(lambda x: lower_bound if x < lower_bound else upper_bound if x > upper_bound else x)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Постараемся выявить зависимости HeartDisease от остальных колонок:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Разобьем наш набор на выборки относительно параметра HeartDisease:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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9+uqrqlSpknr16qUff/zxjvVprl27pr/++sturu3txMTEqEiRIipcuPAta3x9fTVv3jy9+OKLqlOnjt2+O/3HgGEY+vzzz5WUlKSAgIB0+8+cOaPExERL/6F6K5n97cut5gEb/7iBNqfs27dPUvrgWahQIUvjZPZ9lClTRmXKlNGqVau0c+dOcx55dr4GkB0I0UAuuXlKQP369TVw4EDNmjVLPXv2VKNGjST9HQak/1sl4maHDx8296dJ+5Vt2tWnOxk9erRq166tLl263LJm7Nix6tevnw4dOmReOX3qqafsaipUqKDExEQFBQXd9vUqVKigNWvW6MKFC9l2Nbpu3brmSgBt27bVqVOnNHXqVL3++usqVaqUXF1ddfjw4XTHHTp0SA4ODpla+7Z+/frm+J6enurZs6deffVVu/Nco0aNdO//n/+HvnTpUrVo0UIff/yx3fa4uDi7pcWk7D3vaSpVqpSu9lZh9PLlyxo/frxeeOGFdJ+zf/rll1/0xRdfaPny5ZbXN//11191/fr1TAelAwcOZOrz3aNHDx0/flzjx4/Xp59+qmLFiqU7fxnZtGmTTp48qQkTJqR7nYsXL6pfv35avnz5LcfKzGfc19dXqampOnLkiN1rxMbGKi4u7o7n+1Zj3upznrY/q9Ju9g0ODs7yGFa4uLhoxYoVatmypdq0aaNNmzbd8bdFmZV2Hn7//Xf5+/ub28+fP5/uijhwJ8yJBvKISZMmqUyZMurXr5+5jFO9evXk6empOXPm2C199f333+vgwYPpfq28ePFilSlTJlMhIyoqSt98842mTJlyxytiZcqUUYsWLRQUFKSgoKB0v67/z3/+o6ioqAyvWMbFxZnvp1OnTjIMQ+PHj09Xl11Xiq5cuaIbN27oxo0bcnR0VOvWrfXNN9/YLfEXGxurRYsWqWnTpnJzc7M0ftpc56x8i5ujo2O697lkyZJbLleYXec9K2bMmKGkpCS9+uqrd6wdNWqUmjRpovbt21t+nSVLlsjR0TFTS8+dOHFCW7ZsSfcflBnZvXu3xo4dqylTpujJJ5/M8PxlJG0qx8svv6zOnTvbPZ577jlVqlTptr8dyMxnvF27dpKUbvWUt99+W5JuO13kVtq1a6ft27crKirK3JaUlKQPP/xQfn5+GV5Vz4xFixZp7ty5CgwMVKtWrbI0Rla4u7trzZo18vT01KOPPqqjR49my7itWrVSgQIFNHv2bLvtM2fOzJbxcX/hSjSQRxQtWlTvvfeeOnbsqGnTpmnkyJEqWLCgpk6dqj59+qh58+bq1q2bucSdn5+fuWTXzp079frrr2v16tWaM2dOpn5NnLZcVWavYt7Oyy+/rG+//VaPPfaYufRWUlKSfvvtNy1dulTHjh1TyZIl1aJFCz399NN69913deTIEbVp00apqan68ccf1aJFCw0aNMjya69bt04nT540p3MsXLhQ7du3N+dqTpw4UevWrVPTpk31wgsvqECBAvrggw+UnJys8PDw2449YcIEnTp1StWrV5ezs7N2796tefPmqWbNmnecFpCRxx57TBMmTFCfPn3UuHFj/fbbb1q4cKHdTY9WZPa8Z8XatWs1adKkTN2ct3btWm3ZssXS+ElJSZo1a5beffddPfjgg3ZrSqfNwd27d6+ioqIUGBio2bNna/LkyXJ1db3jjYuXL19W9+7d9cgjj+jFF1/MdE/Jycn66quv9Oijj94ycLdv314zZszQmTNnzBtAb5aZz3itWrXUq1cvffjhh4qLi1Pz5s21fft2zZ8/X6GhoWrRokWme04zatQoff7552rbtq2GDBmi4sWLa/78+YqOjtZXX32VqRvzli5dqiJFiujatWvmNxZu2bJFtWrVyvDG55xWsmRJ8+9uUFCQfvrpJ5UtW/ZfjVm6dGm9+OKLmjZtmtq3b682bdro119/1ffff6+SJUtm+QZn3J8I0UAe0qFDBz3xxBOaMGGC/vOf/8jf31+9e/eWq6urpkyZopEjR5pfIDB16lRzjej169fr/PnzWrhwobp3756p17LZbJlacSEzXF1dtWnTJr355ptasmSJFixYIDc3Nz344IMaP3683c2SaSH0448/1ssvvyx3d3fVq1cvU+vvZuTNN9+UJBUoUEBly5bVoEGD7K4CVqtWTT/++KNGjx6tyZMnKzU1VQ0bNtRnn3122zWi045dsWKFvvjiC12/fl1ly5bV4MGDNWrUqCx95fArr7yipKQkLVq0SIsXL1adOnW0cuVKjRo1yvJYkrXzblWZMmU0dOjQTNU+8cQTlv/8zp49q5EjR0r6e27+008/na5m2bJlcnNzU2BgoCIiItSoUSO98cYbd1xPe9iwYTp37pzWr19vKRStXLlScXFx6eay3+zxxx/XtGnT9MUXX9wyzGfmMz537lw98MADioiI0LJly+Tl5aXRo0dneS5/6dKl9fPPP2vkyJF67733dPXqVdWsWVPfffddpq9sp63N7eLiopIlS6p27dr65JNP1L1791z7hsCyZcvqhx9+ULNmzfToo49q8+bNWf4PwzRTp06Vq6urPvroI/3www8KDAzU2rVr1bRpU74tFpbYDGbbAwDusmPHjsnf31/R0dHy8/PLsGbcuHE6duyYIiIi7mpvuP/ExcWpWLFimjhxYqamMAESc6IBAMB95MqVK+m2pc1P/+fXxwO3w3QOAMBdV6RIEfXo0eO2S8XVrFnT8lehA3eyePFiRUREqF27dipSpIh++uknff7552rdurWaNGmS2+0hH2E6BwAAuG/s3r1bI0aM0J49e5SQkKDSpUurU6dOdl9sBGQGIRoAAACwiDnRAAAAgEWEaAAAAMAibiy8i1JTU3X69GkVLVqUBd0BAADyIMMwdOnSJXl7e9/2OwEI0XfR6dOn5ePjk9ttAAAA4A5OnDihcuXK3XI/IfouKlq0qKS//1Dc3NxyuRsAAAD8U0JCgnx8fMzcdiuE6LsobQqHm5sbIRoAACAPu9PUW24sBAAAACwiRAMAAAAWEaIBAAAAiwjRAAAAgEWEaAAAAMAiQjQAAABgESEaAAAAsIgQDQAAAFhEiAYAAAAsIkQDAAAAFhGiAQAAAIsI0QAAAIBFuRqiZ8+erZo1a8rNzU1ubm4KDAzU999/b+6/evWqBg4cqBIlSqhIkSLq1KmTYmNj7cY4fvy4QkJC5OrqKk9PT7388su6ceOGXc3GjRtVp04dOTs7q2LFioqIiEjXy6xZs+Tn5ycXFxc1bNhQ27dvt9ufmV4AAABwf8jVEF2uXDlNmTJFu3bt0s6dO9WyZUs98cQT2r9/vyRp2LBh+u6777RkyRJt2rRJp0+fVseOHc3jU1JSFBISomvXrunnn3/W/PnzFRERoTFjxpg10dHRCgkJUYsWLbRnzx4NHTpUzz77rNasWWPWLF68WGFhYRo7dqx2796tWrVqKTg4WGfOnDFr7tQLAAAA7iNGHlOsWDFj7ty5RlxcnFGwYEFjyZIl5r6DBw8akoyoqCjDMAxj1apVhoODgxETE2PWzJ4923BzczOSk5MNwzCMESNGGNWqVbN7jS5duhjBwcHm8wYNGhgDBw40n6ekpBje3t7G5MmTDcMwMtVLZsTHxxuSjPj4+EwfAwAAgLsns3ktz8yJTklJ0RdffKGkpCQFBgZq165dun79uoKCgsyaKlWqqHz58oqKipIkRUVFqUaNGipdurRZExwcrISEBPNqdlRUlN0YaTVpY1y7dk27du2yq3FwcFBQUJBZk5leMpKcnKyEhAS7BwAAAPK/XA/Rv/32m4oUKSJnZ2f1799fy5YtU0BAgGJiYuTk5CQPDw+7+tKlSysmJkaSFBMTYxeg0/an7btdTUJCgq5cuaJz584pJSUlw5qbx7hTLxmZPHmy3N3dzYePj0/mTgoAAADytFwP0ZUrV9aePXu0bds2DRgwQL169dKBAwdyu61sMXr0aMXHx5uPEydO5HZLAAAAyAYFcrsBJycnVaxYUZJUt25d7dixQzNmzFCXLl107do1xcXF2V0Bjo2NlZeXlyTJy8sr3SoaaStm3Fzzz1U0YmNj5ebmpkKFCsnR0VGOjo4Z1tw8xp16yYizs7OcnZ0tnA0AAADkB7keov8pNTVVycnJqlu3rgoWLKjIyEh16tRJknT48GEdP35cgYGBkqTAwEBNmjRJZ86ckaenpyRp3bp1cnNzU0BAgFmzatUqu9dYt26dOYaTk5Pq1q2ryMhIhYaGmj1ERkZq0KBBkpSpXpBz/EatzO0WcJ84NiUkt1sAAOQTuRqiR48erbZt26p8+fK6dOmSFi1apI0bN2rNmjVyd3dX3759FRYWpuLFi8vNzU2DBw9WYGCgGjVqJElq3bq1AgIC9PTTTys8PFwxMTF67bXXNHDgQPMKcP/+/TVz5kyNGDFCzzzzjNavX68vv/xSK1f+XzALCwtTr169VK9ePTVo0EDTp09XUlKS+vTpI0mZ6gUAAAD3j1wN0WfOnFHPnj31119/yd3dXTVr1tSaNWv06KOPSpLeeecdOTg4qFOnTkpOTlZwcLDef/9983hHR0etWLFCAwYMUGBgoAoXLqxevXppwoQJZo2/v79WrlypYcOGacaMGSpXrpzmzp2r4OBgs6ZLly46e/asxowZo5iYGNWuXVurV6+2u9nwTr0AAADg/mEzDMPI7SbuFwkJCXJ3d1d8fLzc3Nxyu518g+kcuFuYzgEAyGxey/XVOQAAAID8hhANAAAAWESIBgAAACwiRAMAAAAWEaIBAAAAiwjRAAAAgEWEaAAAAMAiQjQAAABgESEaAAAAsIgQDQAAAFhEiAYAAAAsIkQDAAAAFhGiAQAAAIsI0QAAAIBFhGgAAADAIkI0AAAAYBEhGgAAALCIEA0AAABYRIgGAAAALCJEAwAAABYRogEAAACLCNEAAACARYRoAAAAwCJCNAAAAGARIRoAAACwiBANAAAAWESIBgAAACwiRAMAAAAWEaIBAAAAiwjRAAAAgEWEaAAAAMAiQjQAAABgESEaAAAAsIgQDQAAAFhEiAYAAAAsIkQDAAAAFhGiAQAAAIsI0QAAAIBFhGgAAADAIkI0AAAAYBEhGgAAALCIEA0AAABYRIgGAAAALCJEAwAAABYRogEAAACLCNEAAACARYRoAAAAwCJCNAAAAGARIRoAAACwiBANAAAAWESIBgAAACwiRAMAAAAWEaIBAAAAiwjRAAAAgEWEaAAAAMAiQjQAAABgESEaAAAAsIgQDQAAAFhEiAYAAAAsIkQDAAAAFhGiAQAAAIsI0QAAAIBFhGgAAADAolwN0ZMnT1b9+vVVtGhReXp6KjQ0VIcPH7areeSRR2Sz2ewe/fv3t6s5fvy4QkJC5OrqKk9PT7388su6ceOGXc3GjRtVp04dOTs7q2LFioqIiEjXz6xZs+Tn5ycXFxc1bNhQ27dvt9t/9epVDRw4UCVKlFCRIkXUqVMnxcbGZs/JAAAAQL6RqyF606ZNGjhwoLZu3ap169bp+vXrat26tZKSkuzqnnvuOf3111/mIzw83NyXkpKikJAQXbt2TT///LPmz5+viIgIjRkzxqyJjo5WSEiIWrRooT179mjo0KF69tlntWbNGrNm8eLFCgsL09ixY7V7927VqlVLwcHBOnPmjFkzbNgwfffdd1qyZIk2bdqk06dPq2PHjjl4hgAAAJAX2QzDMHK7iTRnz56Vp6enNm3apIcffljS31eia9eurenTp2d4zPfff6/HHntMp0+fVunSpSVJc+bM0ciRI3X27Fk5OTlp5MiRWrlypfbt22ce17VrV8XFxWn16tWSpIYNG6p+/fqaOXOmJCk1NVU+Pj4aPHiwRo0apfj4eJUqVUqLFi1S586dJUmHDh1S1apVFRUVpUaNGqXrLTk5WcnJyebzhIQE+fj4KD4+Xm5ubv/+hN0n/EatzO0WcJ84NiUkt1sAAOSyhIQEubu73zGv5ak50fHx8ZKk4sWL221fuHChSpYsqerVq2v06NG6fPmyuS8qKko1atQwA7QkBQcHKyEhQfv37zdrgoKC7MYMDg5WVFSUJOnatWvatWuXXY2Dg4OCgoLMml27dun69et2NVWqVFH58uXNmn+aPHmy3N3dzYePj4/lcwIAAIC8p0BuN5AmNTVVQ4cOVZMmTVS9enVze/fu3eXr6ytvb2/t3btXI0eO1OHDh/X1119LkmJiYuwCtCTzeUxMzG1rEhISdOXKFV28eFEpKSkZ1hw6dMgcw8nJSR4eHulq0l7nn0aPHq2wsDDzedqVaAAAAORveSZEDxw4UPv27dNPP/1kt71fv37mzzVq1FCZMmXUqlUrHT16VBUqVLjbbVri7OwsZ2fn3G4DAAAA2SxPTOcYNGiQVqxYoQ0bNqhcuXK3rW3YsKEk6ffff5ckeXl5pVshI+25l5fXbWvc3NxUqFAhlSxZUo6OjhnW3DzGtWvXFBcXd8saAAAA3B9yNUQbhqFBgwZp2bJlWr9+vfz9/e94zJ49eyRJZcqUkSQFBgbqt99+s1tFY926dXJzc1NAQIBZExkZaTfOunXrFBgYKElycnJS3bp17WpSU1MVGRlp1tStW1cFCxa0qzl8+LCOHz9u1gAAAOD+kKvTOQYOHKhFixbpm2++UdGiRc25xe7u7ipUqJCOHj2qRYsWqV27dipRooT27t2rYcOG6eGHH1bNmjUlSa1bt1ZAQICefvpphYeHKyYmRq+99poGDhxoTqXo37+/Zs6cqREjRuiZZ57R+vXr9eWXX2rlyv9b9SEsLEy9evVSvXr11KBBA02fPl1JSUnq06eP2VPfvn0VFham4sWLy83NTYMHD1ZgYGCGK3MAAADg3pWrIXr27NmS/l7G7mbz5s1T79695eTkpB9++MEMtD4+PurUqZNee+01s9bR0VErVqzQgAEDFBgYqMKFC6tXr16aMGGCWePv76+VK1dq2LBhmjFjhsqVK6e5c+cqODjYrOnSpYvOnj2rMWPGKCYmRrVr19bq1avtbjZ855135ODgoE6dOik5OVnBwcF6//33c+jsAAAAIK/KU+tE3+syu+4g7LFONO4W1okGAOTLdaIBAACA/IAQDQAAAFhEiAYAAAAsIkQDAAAAFhGiAQAAAIsI0QAAAIBFhGgAAADAIkI0AAAAYBEhGgAAALCIEA0AAABYRIgGAAAALCJEAwAAABYRogEAAACLCNEAAACARYRoAAAAwCJCNAAAAGARIRoAAACwiBANAAAAWESIBgAAACwiRAMAAAAWEaIBAAAAiwjRAAAAgEWEaAAAAMAiQjQAAABgESEaAAAAsIgQDQAAAFhEiAYAAAAsIkQDAAAAFhGiAQAAAIsI0QAAAIBFhGgAAADAIkI0AAAAYBEhGgAAALCIEA0AAABYRIgGAAAALCJEAwAAABYRogEAAACLCNEAAACARYRoAAAAwCJCNAAAAGARIRoAAACwiBANAAAAWESIBgAAACwiRAMAAAAWEaIBAAAAiwpYPeDdd9+97f4hQ4ZkuRkAAAAgP8hUiD5w4IACAgIkSUOHDpWrq6s8PT1lGIZdnc1mI0QDAADgnpep6Rz9+/dX586dJUmvvvqqHBwcFBQUpK1btyo6Otp8/PHHHznaLAAAAJAXZCpEr127Vt9++63OnTunN954QwcPHtS1a9dUuXJlTZo0ScnJyTndJwAAAJBnZCpEnzp1So6OjipSpIgkqWzZsoqIiND69esVGRmpihUrasGCBTnaKAAAAJBXZGpOdM+ePTVv3jy5uLho7969/3dwgQKaPn26vvnmGw0aNEgzZszQrl27cqxZAAAAIC/IVIjesmWL+XPt2rVls9nMmwpv/nnPnj3Z3yEAAACQx1he4i46Ojon+gAAAADyDcsh2tfXNyf6AAAAAPINyyH622+/ve3+9u3bZ7kZAAAAID+wHKJDQ0Nls9kkKcMvW0lJScmezgAAAIA8KlNL3N2sR48eKlq0qN544w1duXJFqamp5oMADQAAgPuB5RD96aefKjIyUmvXrtWDDz6ohQsX5kRfAAAAQJ5lOURLUt26dbVx40bNmDFDEyZMUL169bR58+bs7g0AAADIkyyH6ISEBPPRsmVLbdmyRU888YQee+wxhYaG5kCLAAAAQN5i+cZCDw8P88bCmxmGoe+++y5bmgIAAADyMsshesOGDTnRBwAAAJBvWA7RzZs3z4k+AAAAgHzD8pzovXv33vZhxeTJk1W/fn0VLVpUnp6eCg0N1eHDh+1qrl69qoEDB6pEiRIqUqSIOnXqpNjYWLua48ePKyQkRK6urvL09NTLL7+sGzdu2NVs3LhRderUkbOzsypWrKiIiIh0/cyaNUt+fn5ycXFRw4YNtX37dsu9AAAA4N5nOUTXrl1bDz30kPm/aT+nPbdi06ZNGjhwoLZu3ap169bp+vXrat26tZKSksyaYcOG6bvvvtOSJUu0adMmnT59Wh07djT3p6SkKCQkRNeuXdPPP/+s+fPnKyIiQmPGjDFroqOjFRISohYtWmjPnj0aOnSonn32Wa1Zs8asWbx4scLCwjR27Fjt3r1btWrVUnBwsM6cOZPpXgAAAHB/sBn//NrBO/jzzz8l/X0jYfXq1bVq1Sr5+vqa+2/+2aqzZ8/K09NTmzZt0sMPP6z4+HiVKlVKixYtUufOnSVJhw4dUtWqVRUVFaVGjRrp+++/12OPPabTp0+rdOnSkqQ5c+Zo5MiROnv2rJycnDRy5EitXLlS+/btM1+ra9euiouL0+rVqyVJDRs2VP369TVz5kxJUmpqqnx8fDR48GCNGjUqU738U3JyspKTk83nCQkJ8vHxUXx8vNzc3LJ8nu43fqNW5nYLuE8cmxKS2y0AAHJZQkKC3N3d75jXLF+J9vX1la+vr/z8/GSz2VSuXDlz278J0JIUHx8vSSpevLgkadeuXbp+/bqCgoLMmipVqqh8+fKKioqSJEVFRalGjRpmgJak4OBgJSQkaP/+/WbNzWOk1aSNce3aNe3atcuuxsHBQUFBQWZNZnr5p8mTJ8vd3d18+Pj4ZO3EAAAAIE/J0pet5ITU1FQNHTpUTZo0UfXq1SVJMTExcnJykoeHh11t6dKlFRMTY9bcHKDT9qftu11NQkKCrly5onPnziklJSXDmpvHuFMv/zR69GjFx8ebjxMnTmTybAAAACAvs7w6x81sNluGa0ZnxcCBA7Vv3z799NNP2TJeXuDs7CxnZ+fcbgMAAADZzHKILlasmBmcExMT9dBDD8nB4f8uaF+4cMFyE4MGDdKKFSu0efNmlStXztzu5eWla9euKS4uzu4KcGxsrLy8vMyaf66ikbZixs01/1xFIzY2Vm5ubipUqJAcHR3l6OiYYc3NY9ypFwAAANwfLIfo6dOnZ9uLG4ahwYMHa9myZdq4caP8/f3t9tetW1cFCxZUZGSkOnXqJEk6fPiwjh8/rsDAQElSYGCgJk2apDNnzsjT01OStG7dOrm5uSkgIMCsWbVqld3Y69atM8dwcnJS3bp1FRkZaX51eWpqqiIjIzVo0KBM9wIAAID7g+UQ3atXr2x78YEDB2rRokX65ptvVLRoUXNusbu7uwoVKiR3d3f17dtXYWFhKl68uNzc3DR48GAFBgaaq2G0bt1aAQEBevrppxUeHq6YmBi99tprGjhwoDmVon///po5c6ZGjBihZ555RuvXr9eXX36plSv/b9WHsLAw9erVS/Xq1VODBg00ffp0JSUlqU+fPmZPd+oFAAAA94cszYk+evSo5s2bp6NHj2rGjBny9PTU999/r/Lly6tatWqZHmf27NmSpEceecRu+7x589S7d29J0jvvvCMHBwd16tRJycnJCg4O1vvvv2/WOjo6asWKFRowYIACAwNVuHBh9erVSxMmTDBr/P39tXLlSg0bNkwzZsxQuXLlNHfuXAUHB5s1Xbp00dmzZzVmzBjFxMSodu3aWr16td3NhnfqBQAAAPcHy+tEb9q0SW3btlWTJk20efNmHTx4UA888ICmTJminTt3aunSpTnVa76X2XUHYY91onG3sE40ACDH1okeNWqUJk6cqHXr1snJycnc3rJlS23dujVr3QIAAAD5iOUQ/dtvv6lDhw7ptnt6eurcuXPZ0hQAAACQl1kO0R4eHvrrr7/Sbf/ll19UtmzZbGkKAAAAyMssh+iuXbtq5MiRiomJkc1mU2pqqrZs2aKXXnpJPXv2zIkeAQAAgDzFcoh+8803VaVKFfn4+CgxMVEBAQF6+OGH1bhxY7322ms50SMAAACQp1he4s7JyUkfffSRXn/9de3bt8/81sJKlSrlRH8AAABAnpOldaIlqXz58vLx8ZEk82vAAQAAgPuB5ekckvTxxx+revXqcnFxkYuLi6pXr665c+dmd28AAABAnmT5SvSYMWP09ttvm195LUlRUVEaNmyYjh8/bvdNgQAAAMC9yHKInj17tj766CN169bN3Na+fXvVrFlTgwcPJkQDAADgnmd5Osf169dVr169dNvr1q2rGzduZEtTAAAAQF5mOUQ//fTTmj17drrtH374oXr06JEtTQEAAAB5WZZW5/j444+1du1aNWrUSJK0bds2HT9+XD179lRYWJhZ9/bbb2dPlwAAAEAeYjlE79u3T3Xq1JEkHT16VJJUsmRJlSxZUvv27TPrWPYOAAAA9yrLIXrDhg050QcAAACQb2Rpneg0J0+e1MmTJ7OrFwAAACBfsByiU1NTNWHCBLm7u8vX11e+vr7y8PDQG2+8odTU1JzoEQAAAMhTLE/nePXVV/Xxxx9rypQpatKkiSTpp59+0rhx43T16lVNmjQp25sEAAAA8hLLIXr+/PmaO3eu2rdvb26rWbOmypYtqxdeeIEQDQAAgHue5ekcFy5cUJUqVdJtr1Klii5cuJAtTQEAAAB5meUQXatWLc2cOTPd9pkzZ6pWrVrZ0hQAAACQl1mezhEeHq6QkBD98MMPCgwMlCRFRUXpxIkTWrVqVbY3CAAAAOQ1lq9EN2/eXP/73//UoUMHxcXFKS4uTh07dtThw4fVrFmznOgRAAAAyFMsX4k+fvy4fHx8uIEQAAAA9y3LV6L9/f119uzZnOgFAAAAyBcsh2jDMHKiDwAAACDfsDydQ/r7676vXr2a4b7y5cv/q4YAAACAvC5LIbp+/frpthmGIZvNppSUlH/dFAAAAJCXZSlEb9u2TaVKlcruXgAAAIB8wXKIttlsKl++vDw9PXOiHwAAACDP48ZCAAAAwCLLITo6OpqpHAAAALivWQ7Rvr6+Wrt2rbZu3SpJWrZsmXr27KnJkyfr+vXr2d4gAAAAkNdYDtGjRo1S27Zt1axZM7322mt69tlndeXKFb3zzjsKCwvLiR4BAACAPMXyjYWffvqpFi9eLF9fXzVu3Fhff/212rdvrw0bNuipp57Se++9lxN9AgAAAHmG5RAdGxurpk2bqkyZMnJyclK1atUkSVWrVlVsbGy2NwgAAADkNVlanaNAgb+zd4ECBeTg8PcQNpuNlTsAAABwX7B8JdowDD344IOy2WxKTEzUQw89JAcHBwI0AAAA7huWQ/S8efNyog8AAAAg37Aconv16pUTfQAAAAD5huUQLUkpKSlavny5Dh48KEmqVq2a2rdvL0dHx2xtDgAAAMiLLIfo33//Xe3atdOpU6dUuXJlSdLkyZPl4+OjlStXqkKFCtneJAAAAJCXWF6dY8iQIapQoYJOnDih3bt3a/fu3Tp+/Lj8/f01ZMiQnOgRAAAAyFMsX4netGmTtm7dquLFi5vbSpQooSlTpqhJkybZ2hwAAACQF1m+Eu3s7KxLly6l256YmCgnJ6dsaQoAAADIyyyH6Mcee0z9+vXTtm3bZBiGDMPQ1q1b1b9/f7Vv3z4negQAAADyFMsh+t1331WFChUUGBgoFxcXubi4qEmTJqpYsaJmzJiREz0CAAAAeYrlOdEeHh765ptvdOTIER06dEiSVLVqVVWsWDHbmwMAAADyoiytEy1JlSpVUqVKlbKzFwAAACBfsByiw8LCbrv/7bffznIzAAAAQH5gOURPnz5dgYGBGa7EYbPZsqUpAAAAIC/L0nSOZcuWydPTM7t7AQAAAPIFy6tzAAAAAPc7QjQAAABgUZamc6xZs0bu7u4Z7uMLVwAAAHCvy1KI7tWrV4bbbTabUlJS/lVDAAAAQF5nOUSnpqbmRB8AAABAvsGcaAAAAMAiQjQAAABgESEaAAAAsIgQDQAAAFhEiAYAAAAsylKITklJ0VdffaWJEydq4sSJWrZsWZaWttu8ebMef/xxeXt7y2azafny5Xb7e/fuLZvNZvdo06aNXc2FCxfUo0cPubm5ycPDQ3379lViYqJdzd69e9WsWTO5uLjIx8dH4eHh6XpZsmSJqlSpIhcXF9WoUUOrVq2y228YhsaMGaMyZcqoUKFCCgoK0pEjRyy/ZwAAAOR/lkP077//roCAAPXs2VNff/21vv76az311FOqVq2ajh49ammspKQk1apVS7NmzbplTZs2bfTXX3+Zj88//9xuf48ePbR//36tW7dOK1as0ObNm9WvXz9zf0JCglq3bi1fX1/t2rVLb731lsaNG6cPP/zQrPn555/VrVs39e3bV7/88otCQ0MVGhqqffv2mTXh4eF69913NWfOHG3btk2FCxdWcHCwrl69auk9AwAAIP+zGYZhWDmgXbt2MgxDCxcuVPHixSVJ58+f11NPPSUHBwetXLkya43YbFq2bJlCQ0PNbb1791ZcXFy6K9RpDh48qICAAO3YsUP16tWTJK1evVrt2rXTyZMn5e3trdmzZ+vVV19VTEyMnJycJEmjRo3S8uXLdejQIUlSly5dlJSUpBUrVphjN2rUSLVr19acOXNkGIa8vb01fPhwvfTSS5Kk+Ph4lS5dWhEREeratWum3mNCQoLc3d0VHx8vNzc3q6fovuU3KmufKcCqY1NCcrsFAEAuy2xes3wletOmTQoPDzcDtCSVKFFCU6ZM0aZNm7LW7W1s3LhRnp6eqly5sgYMGKDz58+b+6KiouTh4WEGaEkKCgqSg4ODtm3bZtY8/PDDZoCWpODgYB0+fFgXL140a4KCguxeNzg4WFFRUZKk6OhoxcTE2NW4u7urYcOGZk1GkpOTlZCQYPcAAABA/mc5RDs7O+vSpUvpticmJtoF1ezQpk0bLViwQJGRkZo6dao2bdqktm3bmvOvY2Ji5OnpaXdMgQIFVLx4ccXExJg1pUuXtqtJe36nmpv333xcRjUZmTx5stzd3c2Hj4+PpfcPAACAvMlyiH7sscfUr18/bdu2TYZhyDAMbd26Vf3791f79u2ztbmuXbuqffv2qlGjhkJDQ7VixQrt2LFDGzduzNbXySmjR49WfHy8+Thx4kRutwQAAIBsYDlEv/vuu6pQoYICAwPl4uIiFxcXNWnSRBUrVtSMGTNyokfTAw88oJIlS+r333+XJHl5eenMmTN2NTdu3NCFCxfk5eVl1sTGxtrVpD2/U83N+28+LqOajDg7O8vNzc3uAQAAgPzPcoj28PDQN998o8OHD2vp0qVaunSpDh8+rGXLlsnd3T0nejSdPHlS58+fV5kyZSRJgYGBiouL065du8ya9evXKzU1VQ0bNjRrNm/erOvXr5s169atU+XKlVWsWDGzJjIy0u611q1bp8DAQEmSv7+/vLy87GoSEhK0bds2swYAAAD3jwJZPbBSpUqqVKmSJGVpjWjp73nUaVeVpb9v4NuzZ4+KFy+u4sWLa/z48erUqZO8vLx09OhRjRgxQhUrVlRwcLAkqWrVqmrTpo2ee+45zZkzR9evX9egQYPUtWtXeXt7S5K6d++u8ePHq2/fvho5cqT27dunGTNm6J133jFf98UXX1Tz5s01bdo0hYSE6IsvvtDOnTvNZfBsNpuGDh2qiRMnqlKlSvL399frr78ub29vu9VEAAAAcH+wfCU6Ojpa3bp104ABA3Tx4kW1b99ezs7Oqly5svbu3WtprJ07d+qhhx7SQw89JEkKCwvTQw89pDFjxsjR0VF79+5V+/bt9eCDD6pv376qW7eufvzxRzk7O5tjLFy4UFWqVFGrVq3Url07NW3a1G4NaHd3d61du1bR0dGqW7euhg8frjFjxtitJd24cWMtWrRIH374oWrVqqWlS5dq+fLlql69ulkzYsQIDR48WP369VP9+vWVmJio1atXy8XFxeopBAAAQD5neZ3o1q1b68yZMypatKgSExNVunRpDR48WHPnzlV8fLzWr1+fU73me6wTnTWsE427hXWiAQCZzWuWp3Ns27ZNP/74o3x9fVW8eHHt2LFDderUUcWKFc15yAAAAMC9zPJ0jkuXLqlMmTJyd3eXq6urPDw8JP19w2FG60cDAAAA95os3Vi4evVqubu7KzU1VZGRkdq3b5/i4uKyuTUAAAAgb8pSiO7Vq5f58/PPP2/+bLPZ/n1HAAAAQB5nOUSnpqbmRB8AAABAvmF5TvSCBQuUnJycE70AAAAA+YLlEN2nTx/Fx8fnRC8AAABAvmA5RFtcVhoAAAC452TpxsIvv/zylotP9+zZ8181BAAAAOR1WQrR4eHhcnR0TLfdZrMRogEAAHDPy1KI3rlzpzw9PbO7FwAAACBfsDwnGgAAALjfWQ7Rvr6+GU7lAAAAAO4XlqdzREdH50QfAAAAQL5h+Ur0kCFD9O6776bbPnPmTA0dOjQ7egIAAADyNMsh+quvvlKTJk3SbW/cuLGWLl2aLU0BAAAAeZnlEH3+/Hm5u7un2+7m5qZz585lS1MAAABAXmY5RFesWFGrV69Ot/3777/XAw88kC1NAQAAAHmZ5RsLw8LCNGjQIJ09e1YtW7aUJEVGRmratGmaPn16dvcHAAAA5DmWQ/Qzzzyj5ORkTZo0SW+88YYkyc/PT7Nnz+bbCgEAAHBfyNI3Fg4YMEADBgzQ2bNnVahQIRUpUiS7+wIAAADyrCx9Y+GNGzf0ww8/6Ouvv5ZhGJKk06dPKzExMVubAwAAAPIiy1ei//zzT7Vp00bHjx9XcnKyHn30URUtWlRTp05VcnKy5syZkxN9AgAAAHmG5SvRL774ourVq6eLFy+qUKFC5vYOHTooMjIyW5sDAAAA8iLLV6J//PFH/fzzz3JycrLb7ufnp1OnTmVbYwAAAEBeZflKdGpqqlJSUtJtP3nypIoWLZotTQEAAAB5meUQ3bp1a7v1oG02mxITEzV27Fi1a9cuO3sDAAAA8iTL0zmmTZum4OBgBQQE6OrVq+revbuOHDmikiVL6vPPP8+JHgEAAIA8xXKILleunH799Vd98cUX2rt3rxITE9W3b1/16NHD7kZDAAAA4F6VpS9bKVCggJ566qns7gUAAADIFyyH6G+//fa2+9u3b5/lZgAAAID8wHKIDg0NtXtus9nMby202WwZrtwBAAAA3EuytMTdzQ9XV1f9/vvvt1z6DgAAALjXWA7R/2Sz2bKjDwAAACDf+Fch+tixY0pKSuJLVgAAAHBfsTwnumPHjpKkK1euaOvWrWrVqpVKlSqV7Y0BAAAAeZXlEO3u7i5J8vLy0uOPP65nnnkm25sCAAAA8jLLIXrevHk50QcAAACQb1gO0QkJCbfd7+bmluVmAAAAgPzAcoj28PDIcEUOwzBYJxoAAAD3Bcsh+oEHHtCZM2c0atQoNWnSJCd6AgAAAPI0yyH64MGDeu+99zRp0iT98ssvCg8Pl7+/f070BgAAAORJlteJLliwoMLCwnTkyBGVLVtWNWvW1PDhwxUXF5cD7QEAAAB5T5a/bKV48eKaPn26fvnlFx07dkwVK1bU9OnTs7E1AAAAIG+yPJ3joYceSndjoWEYSk5O1vDhwzV06NDs6g0AAADIkyyH6NDQ0BxoAwAAAMg/LIfosWPH5kQfAAAAQL7Bl60AAAAAFvFlKwAAAIBFlkO0JC1dulTFixfP7l4AAACAfCFLIbpJkyby9PTM7l4AAACAfCFLIfrAgQM6f/68ChcuLC8vLzk5OWV3XwAAAECelaUvW2nVqpWqVasmf39/FS5cWDVq1NA777yT3b0BAAAAeZLlK9HR0dEyDEPXr19XQkKCTp8+re3bt+v111/XjRs39PLLL+dEnwAAAECeYTlE+/r62j2vW7euHn/8cT344IOaMGECIRoAAAD3vCzNic5I165dVa1atewaDgAAAMizshyid+3apYMHD0qSAgICVKdOHdWpUyfbGgMAAADyKssh+syZM+ratas2btwoDw8PSVJcXJxatGihL774QqVKlcruHgEAAIA8xfLqHIMHD9alS5e0f/9+XbhwQRcuXNC+ffuUkJCgIUOG5ESPAAAAQJ5i+Ur06tWr9cMPP6hq1armtoCAAM2aNUutW7fO1uYAAACAvMjylejU1FQVLFgw3faCBQsqNTU1W5oCAAAA8jLLIbply5Z68cUXdfr0aXPbqVOnNGzYMLVq1SpbmwMAAADyIssheubMmUpISJCfn58qVKigChUqyN/fXwkJCXrvvfdyokcAAAAgT7Econ18fLR7926tXLlSQ4cO1dChQ7Vq1Srt3r1b5cqVszTW5s2b9fjjj8vb21s2m03Lly+3228YhsaMGaMyZcqoUKFCCgoK0pEjR+xqLly4oB49esjNzU0eHh7q27evEhMT7Wr27t2rZs2aycXFRT4+PgoPD0/Xy5IlS1SlShW5uLioRo0aWrVqleVeAAAAcH/IdIi+dOmS+bPNZtOjjz6qwYMHa/DgwQoKCpIk7dixw9KLJyUlqVatWpo1a1aG+8PDw/Xuu+9qzpw52rZtmwoXLqzg4GBdvXrVrOnRo4f279+vdevWacWKFdq8ebP69etn7k9ISFDr1q3l6+urXbt26a233tK4ceP04YcfmjU///yzunXrpr59++qXX35RaGioQkNDtW/fPku9AAAA4P5gMwzDyExhYGCg1q1bpyJFiqTbd+PGDY0bN07h4eG6du1a1hqx2bRs2TKFhoZK+vvKr7e3t4YPH66XXnpJkhQfH6/SpUsrIiJCXbt21cGDBxUQEKAdO3aoXr16kv5ePaRdu3Y6efKkvL29NXv2bL366quKiYmRk5OTJGnUqFFavny5Dh06JEnq0qWLkpKStGLFCrOfRo0aqXbt2pozZ06mesmMhIQEubu7Kz4+Xm5ublk6T/cjv1Erc7sF3CeOTQnJ7RYAALkss3nN0pXooKAgJSQk2G3ft2+f6tevr4iIiHTTMf6N6OhoxcTEmFe5Jcnd3V0NGzZUVFSUJCkqKkoeHh5mgJakoKAgOTg4aNu2bWbNww8/bAZoSQoODtbhw4d18eJFs+bm10mrSXudzPSSkeTkZCUkJNg9AAAAkP9lOkRv2LBBSUlJevTRR5WQkCDDMDR16lTVq1dPVatW1W+//aZ27dplW2MxMTGSpNKlS9ttL126tLkvJiZGnp6edvsLFCig4sWL29VkNMbNr3Grmpv336mXjEyePFnu7u7mw8fH5w7vGgAAAPlBpr9spVSpUlq/fr2CgoLUsmVLOTs768iRI/rss8/UuXPnnOwx3xo9erTCwsLM5wkJCQRpAACAe4Cl1TlKlSqlyMhI3bhxQ7t27dLmzZtzLEB7eXlJkmJjY+22x8bGmvu8vLx05swZu/03btzQhQsX7GoyGuPm17hVzc3779RLRpydneXm5mb3AAAAQP5neYm7kiVLav369QoICFD37t3NecXZzd/fX15eXoqMjDS3JSQkaNu2bQoMDJT0982OcXFx2rVrl1mzfv16paamqmHDhmbN5s2bdf36dbNm3bp1qly5sooVK2bW3Pw6aTVpr5OZXgAAAHD/yPR0jo4dO9o9d3Nz0+bNm9WgQQPVqFHD3P71119n+sUTExP1+++/m8+jo6O1Z88eFS9eXOXLl9fQoUM1ceJEVapUSf7+/nr99dfl7e1truBRtWpVtWnTRs8995zmzJmj69eva9CgQeratau8vb0lSd27d9f48ePVt29fjRw5Uvv27dOMGTP0zjvvmK/74osvqnnz5po2bZpCQkL0xRdfaOfOneYyeDab7Y69AAAA4P6R6RDt7u6e7rm/v/+/evGdO3eqRYsW5vO0+cO9evVSRESERowYoaSkJPXr109xcXFq2rSpVq9eLRcXF/OYhQsXatCgQWrVqpUcHBzUqVMnvfvuu3Z9rl27VgMHDlTdunVVsmRJjRkzxm4t6caNG2vRokV67bXX9Morr6hSpUpavny5qlevbtZkphcAAADcHzK9TjT+PdaJzhrWicbdwjrRAIBsXycaAAAAwN8I0QAAAIBFhGgAAADAIkI0AAAAYBEhGgAAALCIEA0AAABYRIgGAAAALCJEAwAAABYRogEAAACLCNEAAACARYRoAAAAwCJCNAAAAGARIRoAAACwiBANAAAAWESIBgAAACwiRAMAAAAWEaIBAAAAiwjRAAAAgEWEaAAAAMAiQjQAAABgESEaAAAAsIgQDQAAAFhEiAYAAAAsIkQDAAAAFhGiAQAAAIsI0QAAAIBFhGgAAADAIkI0AAAAYBEhGgAAALCIEA0AAABYRIgGAAAALCJEAwAAABYRogEAAACLCNEAAACARYRoAAAAwCJCNAAAAGARIRoAAACwiBANAAAAWESIBgAAACwiRAMAAAAWEaIBAAAAiwjRAAAAgEWEaAAAAMAiQjQAAABgESEaAAAAsIgQDQAAAFhEiAYAAAAsIkQDAAAAFhGiAQAAAIsI0QAAAIBFhGgAAADAIkI0AAAAYBEhGgAAALCIEA0AAABYRIgGAAAALCJEAwAAABYRogEAAACLCNEAAACARYRoAAAAwCJCNAAAAGARIRoAAACwiBANAAAAWESIBgAAACzK0yF63Lhxstlsdo8qVaqY+69evaqBAweqRIkSKlKkiDp16qTY2Fi7MY4fP66QkBC5urrK09NTL7/8sm7cuGFXs3HjRtWpU0fOzs6qWLGiIiIi0vUya9Ys+fn5ycXFRQ0bNtT27dtz5D0DAAAg78vTIVqSqlWrpr/++st8/PTTT+a+YcOG6bvvvtOSJUu0adMmnT59Wh07djT3p6SkKCQkRNeuXdPPP/+s+fPnKyIiQmPGjDFroqOjFRISohYtWmjPnj0aOnSonn32Wa1Zs8asWbx4scLCwjR27Fjt3r1btWrVUnBwsM6cOXN3TgIAAADyFJthGEZuN3Er48aN0/Lly7Vnz550++Lj41WqVCktWrRInTt3liQdOnRIVatWVVRUlBo1aqTvv/9ejz32mE6fPq3SpUtLkubMmaORI0fq7NmzcnJy0siRI7Vy5Urt27fPHLtr166Ki4vT6tWrJUkNGzZU/fr1NXPmTElSamqqfHx8NHjwYI0aNSrT7ychIUHu7u6Kj4+Xm5tbVk/Lfcdv1MrcbgH3iWNTQnK7BQBALstsXsvzV6KPHDkib29vPfDAA+rRo4eOHz8uSdq1a5euX7+uoKAgs7ZKlSoqX768oqKiJElRUVGqUaOGGaAlKTg4WAkJCdq/f79Zc/MYaTVpY1y7dk27du2yq3FwcFBQUJBZcyvJyclKSEiwewAAACD/y9MhumHDhoqIiNDq1as1e/ZsRUdHq1mzZrp06ZJiYmLk5OQkDw8Pu2NKly6tmJgYSVJMTIxdgE7bn7bvdjUJCQm6cuWKzp07p5SUlAxr0sa4lcmTJ8vd3d18+Pj4WD4HAAAAyHsK5HYDt9O2bVvz55o1a6phw4by9fXVl19+qUKFCuViZ5kzevRohYWFmc8TEhII0gAAAPeAPH0l+p88PDz04IMP6vfff5eXl5euXbumuLg4u5rY2Fh5eXlJkry8vNKt1pH2/E41bm5uKlSokEqWLClHR8cMa9LGuBVnZ2e5ubnZPQAAAJD/5asQnZiYqKNHj6pMmTKqW7euChYsqMjISHP/4cOHdfz4cQUGBkqSAgMD9dtvv9mtorFu3Tq5ubkpICDArLl5jLSatDGcnJxUt25du5rU1FRFRkaaNQAAALi/5OkQ/dJLL2nTpk06duyYfv75Z3Xo0EGOjo7q1q2b3N3d1bdvX4WFhWnDhg3atWuX+vTpo8DAQDVq1EiS1Lp1awUEBOjpp5/Wr7/+qjVr1ui1117TwIED5ezsLEnq37+//vjjD40YMUKHDh3S+++/ry+//FLDhg0z+wgLC9NHH32k+fPn6+DBgxowYICSkpLUp0+fXDkvAAAAyF15ek70yZMn1a1bN50/f16lSpVS06ZNtXXrVpUqVUqS9M4778jBwUGdOnVScnKygoOD9f7775vHOzo6asWKFRowYIACAwNVuHBh9erVSxMmTDBr/P39tXLlSg0bNkwzZsxQuXLlNHfuXAUHB5s1Xbp00dmzZzVmzBjFxMSodu3aWr16dbqbDQEAAHB/yNPrRN9rWCc6a1gnGncL60QDAO6ZdaIBAACAvIYQDQAAAFhEiAYAAAAsIkQDAAAAFhGiAQAAAIsI0QAAAIBFhGgAAADAIkI0AAAAYBEhGgAAALCIEA0AAABYRIgGAAAALCJEAwAAABYRogEAAACLCNEAAACARYRoAAAAwCJCNAAAAGARIRoAAACwiBANAAAAWESIBgAAACwiRAMAAAAWEaIBAAAAiwjRAAAAgEWEaAAAAMAiQjQAAABgESEaAAAAsIgQDQAAAFhEiAYAAAAsIkQDAAAAFhGiAQAAAIsI0QAAAIBFhGgAAADAIkI0AAAAYBEhGgAAALCIEA0AAABYVCC3GwAA4H7jN2plbreA+8SxKSG53cI9iyvRAAAAgEWEaAAAAMAiQjQAAABgESEaAAAAsIgQDQAAAFhEiAYAAAAsIkQDAAAAFhGiAQAAAIsI0QAAAIBFhGgAAADAIkI0AAAAYBEhGgAAALCIEA0AAABYRIgGAAAALCJEAwAAABYRogEAAACLCNEAAACARYRoAAAAwCJCNAAAAGARIRoAAACwiBANAAAAWESIBgAAACwiRAMAAAAWEaIBAAAAiwjRAAAAgEWEaAAAAMAiQjQAAABgESEaAAAAsIgQbdGsWbPk5+cnFxcXNWzYUNu3b8/tlgAAAHCXEaItWLx4scLCwjR27Fjt3r1btWrVUnBwsM6cOZPbrQEAAOAuIkRb8Pbbb+u5555Tnz59FBAQoDlz5sjV1VWffPJJbrcGAACAu6hAbjeQX1y7dk27du3S6NGjzW0ODg4KCgpSVFRUhsckJycrOTnZfB4fHy9JSkhIyNlm7zGpyZdzuwXcJ/i7ibuFf9dwt/DvmnVp58wwjNvWEaIz6dy5c0pJSVHp0qXttpcuXVqHDh3K8JjJkydr/Pjx6bb7+PjkSI8A/h336bndAQBkL/5dy7pLly7J3d39lvsJ0Tlo9OjRCgsLM5+npqbqwoULKlGihGw2Wy52hntdQkKCfHx8dOLECbm5ueV2OwDwr/HvGu4WwzB06dIleXt737aOEJ1JJUuWlKOjo2JjY+22x8bGysvLK8NjnJ2d5ezsbLfNw8Mjp1oE0nFzc+P/bADcU/h3DXfD7a5Ap+HGwkxycnJS3bp1FRkZaW5LTU1VZGSkAgMDc7EzAAAA3G1cibYgLCxMvXr1Ur169dSgQQNNnz5dSUlJ6tOnT263BgAAgLuIEG1Bly5ddPbsWY0ZM0YxMTGqXbu2Vq9ene5mQyC3OTs7a+zYsemmEwFAfsW/a8hrbMad1u8AAAAAYIc50QAAAIBFhGgAAADAIkI0AAAAYBEhGgAAALCIEA0AAPKcK1eu6PLly+bzP//8U9OnT9fatWtzsSvg/xCiAQBAnvPEE09owYIFkqS4uDg1bNhQ06ZN0xNPPKHZs2fncncAIRq4JxmGIVavBJCf7d69W82aNZMkLV26VKVLl9aff/6pBQsW6N13383l7gBCNHBPWbBggWrUqKFChQqpUKFCqlmzpj799NPcbgsALLt8+bKKFi0qSVq7dq06duwoBwcHNWrUSH/++WcudwcQooF7xttvv60BAwaoXbt2+vLLL/Xll1+qTZs26t+/v955553cbg8ALKlYsaKWL1+uEydOaM2aNWrdurUk6cyZM3Jzc8vl7gC+sRC4Z/j7+2v8+PHq2bOn3fb58+dr3Lhxio6OzqXOAMC6pUuXqnv37kpJSVHLli21bt06SdLkyZO1efNmff/997ncIe53hGjgHuHi4qJ9+/apYsWKdtuPHDmiGjVq6OrVq7nUGQBkTUxMjP766y/VqlVLDg5///J8+/btcnNzU5UqVXK5O9zvmM4B3CMqVqyoL7/8Mt32xYsXq1KlSrnQEQD8O15eXipatKjWrVunK1euSJLq169PgEaeUCC3GwCQPcaPH68uXbpo8+bNatKkiSRpy5YtioyMzDBcA0Bedv78ef3nP//Rhg0bZLPZdOTIET3wwAPq27evihUrpmnTpuV2i7jPcSUauEd06tRJ27ZtU4kSJbR8+XItX75cJUuW1Pbt29WhQ4fcbg8ALBk2bJgKFiyo48ePy9XV1dzepUsXrV69Ohc7A/7GnGgAAJDneHl5ac2aNapVq5aKFi2qX3/9VQ888ID++OMP1axZU4mJibndIu5zTOcA8jkHBwfZbLbb1thsNt24ceMudQQA/15SUpLdFeg0Fy5ckLOzcy50BNgjRAP53LJly265LyoqSu+++65SU1PvYkcAkHWnT5+Wt7e3mjVrpgULFuiNN96Q9PfFgNTUVIWHh6tFixa53CXAdA7gnnT48GGNGjVK3333nXr06KEJEybI19c3t9sCgDsqVqyYZs2apVq1aqlly5aqU6eO1q9fr/bt22v//v26cOGCtmzZogoVKuR2q7jPcWMhcA85ffq0nnvuOdWoUUM3btzQnj17NH/+fAI0gHxj0qRJev755zVu3DgdOHBATZs21RNPPKGkpCR17NhRv/zyCwEaeQJXooF7QHx8vN5880299957ql27tqZOnapmzZrldlsAkCXR0dHq27evDhw4oA8//FDt27fP7ZaAdAjRQD4XHh6uqVOnysvLS2+++aaeeOKJ3G4JALLFzJkzNWzYMFWtWlUFCtjfxrV79+5c6gr4GyEayOccHBxUqFAhBQUFydHR8ZZ1X3/99V3sCgD+nT///FN9+vTRvn379Pzzz6cL0WPHjs2lzoC/sToHkM/17NnzjkvcAUB+8tFHH2n48OEKCgrS/v37VapUqdxuCUiHK9EAACDPaNOmjbZv367p06erZ8+eud0OcEtciQYAAHlGSkqK9u7dq3LlyuV2K8BtcSUaAAAAsIh1ogEAAACLCNEAAACARYRoAAAAwCJCNAAAAGARIRoAAACwiBANAHnExo0bZbPZFBcXl6fGs9lsWr58ebb0JEm9e/dWaGhotvbg5+en6dOn/6u+AMAKQjQA3GVRUVFydHRUSEhIbreSJTabzXwULlxYlSpVUu/evbVr165MHT9jxgxFRERka087duxQv379snVMALgdQjQA3GUff/yxBg8erM2bN+v06dO53U6WzJs3T3/99Zf279+vWbNmKTExUQ0bNtSCBQtueUxKSopSU1Pl7u4uDw+PbO2nVKlScnV1zdYxAeB2CNEAcBclJiZq8eLFGjBggEJCQu54RXbLli165JFH5OrqqmLFiik4OFgXL16UJCUnJ2vIkCHy9PSUi4uLmjZtqh07dqQbY9euXapXr55cXV3VuHFjHT582G7/7NmzVaFCBTk5Oaly5cr69NNP7/g+PDw85OXlJT8/P7Vu3VpLly5Vjx49NGjQILO/iIgIeXh46Ntvv1VAQICcnZ11/PjxdNM5HnnkEQ0ZMkQjRoxQ8eLF5eXlpXHjxt329ceOHasyZcpo7969ktJP57DZbJo7d646dOggV1dXVapUSd9++63dGN9++60qVaokFxcXtWjRQvPnz8/W6TQA7m2EaAC4i7788ktVqVJFlStX1lNPPaVPPvlEt/ri2D179qhVq1YKCAhQVFSUfvrpJz3++ONKSUmRJI0YMUJfffWV5s+fr927d6tixYoKDg7WhQsX7MZ59dVXNW3aNO3cuVMFChTQM888Y+5btmyZXnzxRQ0fPlz79u3T888/rz59+mjDhg2W39uwYcN06dIlrVu3ztx2+fJlTZ06VXPnztX+/fvl6emZ4bHz589X4cKFtW3bNoWHh2vChAl246QxDEODBw/WggUL9OOPP6pmzZq37Gf8+PH6z3/+o71796pdu3bq0aOHeW6io6PVuXNnhYaG6tdff9Xzzz+vV1991fJ7BnAfMwAAd03jxo2N6dOnG4ZhGNevXzdKlixpbNiwwTAMw9iwYYMhybh48aJhGIbRrVs3o0mTJhmOk5iYaBQsWNBYuHChue3atWuGt7e3ER4ebjfeDz/8YNasXLnSkGRcuXLF7Oe5556zG/vJJ5802rVrZz6XZCxbtuyWz9NcuXLFkGRMnTrVMAzDmDdvniHJ2LNnj11dr169jCeeeMJ83rx5c6Np06Z2NfXr1zdGjhxp95pLliwxunfvblStWtU4efKkXb2vr6/xzjvv2NW/9tprdudLkvH9998bhmEYI0eONKpXr243xquvvmp3/gHgdrgSDQB3yeHDh7V9+3Z169ZNklSgQAF16dJFH3/8cYb1aVeiM3L06FFdv35dTZo0MbcVLFhQDRo00MGDB+1qb75aW6ZMGUnSmTNnJEkHDx60G0OSmjRpkm6MzDD+/xV1m81mbnNycrrt1eKMekzrM63HNMOGDdO2bdu0efNmlS1b1tKYhQsXlpubmznm4cOHVb9+fbv6Bg0a3HFMAEhDiAaAu+Tjjz/WjRs35O3trQIFCqhAgQKaPXu2vvrqK8XHx6erL1SoULa8bsGCBc2f0wJuampqtox9s7Tg7e/vb24rVKiQXai+lZt7lP7u8589Pvroozp16pTWrFmTqX4yMyYAZBUhGgDughs3bmjBggWaNm2a9uzZYz5+/fVXeXt76/PPP093TM2aNRUZGZnheGk3Am7ZssXcdv36de3YsUMBAQGZ7qtq1ap2Y0h/38xoZYw006dPl5ubm4KCgiwfmxnt27fXokWL9Oyzz+qLL774V2NVrlxZO3futNuW0U2ZAHArBXK7AQC4H6xYsUIXL15U37595e7ubrevU6dO+vjjj/XWW2/ZbR89erRq1KihF154Qf3795eTk5M2bNigJ598UiVLltSAAQP08ssvq3jx4ipfvrzCw8N1+fJl9e3bN9N9vfzyy/rPf/6jhx56SEFBQfruu+/09ddf64cffrjtcXFxcYqJiVFycrL+97//6YMPPtDy5cu1YMGCbF++7mYdOnTQp59+qqeffloFChRQ586dszTO888/r7ffflsjR45U3759tWfPHnOllMxcOQcAQjQA3AUff/yxgoKC0gVo6e8QHR4ebi7XlubBBx/U2rVr9corr6hBgwYqVKiQGjZsaM6pnjJlilJTU/X000/r0qVLqlevntasWaNixYpluq/Q0FDNmDFD//3vf/Xiiy/K399f8+bN0yOPPHLb4/r06SNJcnFxUdmyZdW0aVNt375dderUyfRrZ1Xnzp3N9+3g4KCOHTtaHsPf319Lly7V8OHDNWPGDAUGBurVV1/VgAED5OzsnANdA7jX2AzjFmsrAQBwH5k0aZLmzJmjEydO5HYrAPIBrkQDAO5L77//vurXr68SJUpoy5YteuuttzRo0KDcbgtAPkGIBgDcl44cOaKJEyfqwoULKl++vIYPH67Ro0fndlsA8gmmcwAAAAAWscQdAAAAYBEhGgAAALCIEA0AAABYRIgGAAAALCJEAwAAABYRogEAAACLCNEAAACARYRoAAAAwKL/B7I56KGOC6yRAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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q6JZbbvHYdfLz89W0aVNNnTrV7f6Cf8QPHDig9u3bq2HDhpo6daqioqIUGBio1NRUvfTSSy7vg5KsLFAav/zyi7KyspzmdV4qODhY69ev19q1a7Vs2TKtWLFCH374oe644w6tXLlS/v7+Hn++FotFixYt0pdffqlPP/1UaWlpGjhwoKZMmaIvv/xSISEhys/PV0REhN5//3231yws9HlLYGCgbrrpJt10002qX7++HnnkES1cuFDjxo1z2z8/P18dO3bUyJEj3e4vCJy++Dr4+/uXqt3432qbBeP/4osvqnnz5m77FrXeMlAahFegGOfOnZP0f395r1u3Tr/99ps++ugjtWvXztEvIyPD7fHXXHON012/22+/XZGRkZo9e7ZGjRrl1HfUqFFq3ry57r//frfnqlu3rrZu3arc3Nxiw61hGEpMTFTPnj1LFO46d+6soKAgPfDAA7rttttUt25dl/AaHR0t6c8PHxX8WrnA3r17Hfvr1KkjSS6rKpRHpUqVnF7Htm3b6rrrrtPKlSs9Gl7r1q2rHTt2qH379kVOcfj0009lt9u1dOlSp7tVRf3K252yTqOYO3euJBU7FcHPz0/t27dX+/btNXXqVL3wwgsaPXq01q5dqw4dOly253vLLbfolltu0fPPP6958+apX79+mj9/vh599FHVrVtXq1evVps2bUod6i9+D17qhx9+UHh4uEfuuhamYNmyY8eOFdqnbt26ys7OLvZuf2lfh/3798swDKdx+vHHHyXJ68v4FXzQMDQ0tMS/5QDKijmvwP8UNldu5syZslgsjrBWEGKNi77f48KFC3rttddKdJ2CMHzpMkRbtmzRJ598ookTJxYaIu69915lZma6XVDfuOT7RubPn6+dO3e6XbXAnQoVKujhhx/Wzp07XZY1KtC6dWtFRETojTfecKp/+fLl2rNnj7p27SrpzztG7dq106xZs1xWVbi0zrIquNNT2B2hsurdu7eOHDnidnWGc+fO6ezZs07Xvfj5ZGVlafbs2aW6XqVKlXT69OlSHbNmzRolJyerdu3a6tevX6H9fv/9d5e2grtiBePn6ed76tQplzF2d828vDwlJye7XPOPP/4o8vWoWbOmmjdvrnfeecep3+7du7Vy5Up16dKl0GNLY+3atW7fqwV/T7ibtlCgd+/e2rJli9LS0lz2FaxmUtCvNK/D0aNH9fHHHzu2bTab3n33XTVv3twjUwbKo1WrVqpbt67+85//uP1CkEuX4gPKgzuvwP/07dtXDRs2VM+ePVW9enX9+uuvWr58udauXavRo0eradOmkv78dpprrrlG/fv311NPPSWLxaK5c+cWGspOnDjhWIszMzNTb775pipUqKBu3bo59Vu5cqU6duxY5F2Lhx9+WO+++66GDx+ur776Sm3bttXZs2e1evVqPfHEE7r77rudzlewJFNJJScn69lnny10XlpAQIAmTZqkRx55RPHx8erTp49jqayYmBinpbamTZum2267TS1bttRjjz2m2rVr6+DBg1q2bJnS09NLXFOB7OxsrVixQtKfoWzatGkKCAhwBGZPeeihh7RgwQI9/vjjWrt2rdq0aaO8vDz98MMPWrBggWOt1k6dOikwMFDdu3fX4MGDlZ2drZkzZyoiIqLIu3KXatWqlVavXq2pU6cqMjJStWvXdnwYRvrzB4MffvhBf/zxh06cOKE1a9Zo1apVio6O1tKlS4v8hqQJEyZo/fr16tq1q6Kjo3Xy5Em99tpruv7663Xbbbddluf7zjvv6LXXXlPPnj1Vt25dnTlzRjNnzlRoaKgjWMbHx2vw4MFKSUlRenq6OnXqpICAAO3bt08LFy7UK6+8ol69ehX6vF588UV17txZcXFxGjRokGOprLCwMJf1kstq6NChysnJUc+ePdWwYUNduHBBmzdv1ocffqiYmBg98sgjhR777LPPaunSperWrZsGDBigVq1a6ezZs9q1a5cWLVqkgwcPKjw8vNSvQ/369TVo0CBt27ZN1atX16xZs3TixIlS/8B0Ofj5+entt99W586d1aRJEz3yyCO67rrrdOTIEa1du1ahoaH69NNPvV0mrhZeWuUA8Dmvv/660aVLFyMyMtKoUKGCUaVKFSMhIcFITU116btp0ybjlltuMYKDg43IyEjHMjqSjLVr1zr6xcfHOy3JVKVKFaNNmzYu55RkWCwW4+uvv3Zqd7fUVk5OjjF69Gijdu3aRkBAgFGjRg2jV69exoEDBwzD+L+lsoKDg40jR444HXvpkj7FLcdU2P4PP/zQaNGihWG1Wo1rr73W6Nevn/HLL7+4HL97926jZ8+eRpUqVYygoCCjQYMGxpgxY9xeq7ilsty9jsuXL3fb/2L9+/c3KlWqVOh+XbJUlmH8uSTYpEmTjCZNmhhWq9W45pprjFatWhnjx483srKyHP2WLl1qNGvWzAgKCjJiYmKMSZMmOZYzu3i5oejoaKNr165ur//DDz8Y7dq1M4KDgw1Jjteg4LUveAQGBho1atQwOnbsaLzyyitOyxYVuHT5o88//9y4++67jcjISCMwMNCIjIw0+vTp47KEkyef7zfffGP06dPHqFWrlmG1Wo2IiAijW7duxvbt213qfeutt4xWrVoZwcHBRuXKlY2mTZsaI0eONI4ePep+sC6yevVqo02bNkZwcLARGhpqdO/e3fj+++8L7V/apbKWL19uDBw40GjYsKEREhJiBAYGGvXq1TOGDh1qnDhxothznzlzxhg1apRRr149IzAw0AgPDzduvfVW4z//+Y/LclsleR0K3kNpaWlGs2bNDKvVajRs2NBYuHBhoc+hLEtlXfr/QsHfJy+++KJT+9q1aw1JLtf/9ttvjXvuuceoWrWqYbVajejoaKN3797G559/XmidQGlZDMNDv8MDAACXRUxMjGJjY/XZZ595uxTA65jzCgAAANMgvAIAAMA0CK8AAAAwDea8AgAAwDS48woAAADTILwCAADANK76LynIz8/X0aNHVbly5TJ/DSMAAAAuH8MwdObMGUVGRsrPr+h7q1d9eD169KiioqK8XQYAAACK8fPPP+v6668vss9VH14rV64s6c8XIzQ09LJfLzc3VytXrnR8zR8AAIDZXOk8Y7PZFBUV5chtRbnqw2vBVIHQ0NArFl4rVqyo0NBQwisAADAlb+WZkkzx5ANbAAAAMA3CKwAAAEyD8AoAAADTILwCAADANAivAAAAMA3CKwAAAEyD8AoAAADTILwCAADANAivAAAAMA3CKwAAAEyD8AoAAADTILwCAADANAivAAAAMI0K3i7gahKTuExWf0OTb5Zik9Jkz7Po4MSu3i4LAACgxHw9z3j1zuv69evVvXt3RUZGymKxaMmSJU77P/roI3Xq1ElVq1aVxWJRenq6V+osiZjEZaVqBwAA8DVmyDNeDa9nz57VjTfeqFdffbXQ/bfddpsmTZp0hSsrneIG1JcGHAAAwB2z5BmvThvo3LmzOnfuXOj+hx56SJJ08ODBK1RR6ZV0IGMSl/nULXcAAIACZsozV92cV7vdLrvd7ti22WySpNzcXOXm5nr8elZ/w3nbz3D682KX4/oAAADl5e08U5pzXnXhNSUlRePHj3dpX7lypSpWrOjx602+2X17cut8l7bU1FSPXx8AAKC8vJ1ncnJyStz3qguvo0aN0vDhwx3bNptNUVFR6tSpk0JDQz1+vdikNKdtq5+h5Nb5GrPdT/Z8i9O+3UkJHr8+AABAeXk7zxT8prwkrrrwarVaZbVaXdoDAgIUEBDg8evZ8yzu2/MtLvsux/UBAADKy9t5pjTn5EsKyqmkk5a9PbkZAACgMGbKM14Nr9nZ2UpPT3es35qRkaH09HQdPnxYkvT7778rPT1d33//vSRp7969Sk9P1/Hjx71VslvFDaQvDDQAAEBRzJJnvBpet2/frhYtWqhFixaSpOHDh6tFixYaO3asJGnp0qVq0aKFunb988V64IEH1KJFC73xxhteq7kwhQ2orww0AABAccyQZyyGYbiugXAVsdlsCgsLU1ZW1mX5wNalcnNzlZqaqi5dujDHFQAAmNKVzjOlyWvMeQUAAIBpEF4BAABgGoRXAAAAmAbhFQAAAKZBeAUAAIBpEF4BAABgGoRXAAAAmAbhFQAAAKZBeAUAAIBpEF4BAABgGoRXAAAAmAbhFQAAAKZBeAUAAIBpEF4BAABgGoRXAAAAmAbhFQAAAKZBeAUAAIBpEF4BAABgGoRXAAAAmAbhFQAAAKZBeAUAAIBpEF4BAABgGoRXAAAAmAbhFQAAAKZBeAUAAIBpEF4BAABgGoRXAAAAmAbhFQAAAKZBeAUAAIBpEF4BAABgGoRXAAAAmAbhFQAAAKZBeAUAAIBpEF4BAABgGoRXAAAAmAbhFQAAAKZBeAUAAIBpEF4BAABgGoRXAAAAmAbhFQAAAKZRwdsFXE1iEpfJ6m9o8s1SbFKa7HkWHZzY1dtlAQAAlJiv5xmv3nldv369unfvrsjISFksFi1ZssRpv2EYGjt2rGrWrKng4GB16NBB+/bt806xxYhJXFaqdgAAAF9jhjzj1fB69uxZ3XjjjXr11Vfd7p88ebKmTZumN954Q1u3blWlSpWUkJCg8+fPX+FKi1bcgPrSgAMAALhjljzj1fDauXNn/fvf/1bPnj1d9hmGoZdffln/+te/dPfdd6tZs2Z69913dfToUZc7tN5U0oH0lQEHAAC4lJnyjM/Oec3IyNDx48fVoUMHR1tYWJj+8pe/aMuWLXrggQfcHme322W32x3bNptNkpSbm6vc3FyP12n1N5y3/QynPy92Oa4PAABQXt7OM6U5p8+G1+PHj0uSqlev7tRevXp1xz53UlJSNH78eJf2lStXqmLFip4tUtLkm923J7fOd2lLTU31+PUBAADKy9t5Jicnp8R9fTa8ltWoUaM0fPhwx7bNZlNUVJQ6deqk0NBQj18vNinNadvqZyi5db7GbPeTPd/itG93UoLHrw8AAFBe3s4zBb8pLwmfDa81atSQJJ04cUI1a9Z0tJ84cULNmzcv9Dir1Sqr1erSHhAQoICAAI/Xac+zuG/Pt7jsuxzXBwAAKC9v55nSnNNnv6Sgdu3aqlGjhj7//HNHm81m09atWxUXF+fFypyVdN0zX1ofDQAA4GJmyjNeDa/Z2dlKT09Xenq6pD8/pJWenq7Dhw/LYrFo2LBh+ve//62lS5dq165devjhhxUZGakePXp4s2wXxQ2kLww0AABAUcySZ7waXrdv364WLVqoRYsWkqThw4erRYsWGjt2rCRp5MiRGjp0qB577DHddNNNys7O1ooVKxQUFOTNst0qbEB9ZaABAACKY4Y8YzEMw3UNhKuIzWZTWFiYsrKyLssHti6Vm5ur1NRUdenShTmuAADAlK50nilNXvPZOa8AAADApQivAAAAMA3CKwAAAEyD8AoAAADTILwCAADANAivAAAAMA3CKwAAAEyD8AoAAADTILwCAADANAivAAAAMA3CKwAAAEyD8AoAAADTILwCAADANAivAAAAMA3CKwAAAEyD8AoAAADTILwCAADANAivAAAAMA3CKwAAAEyD8AoAAADTILwCAADANAivAAAAMA3CKwAAAEyD8AoAAADTILwCAADANAivAAAAMA3CKwAAAEyD8AoAAADTILwCAADANAivAAAAMA3CKwAAAEyD8AoAAADTILwCAADANAivAAAAMA3CKwAAAEyD8AoAAADTILwCAADANAivAAAAMA3CKwAAAEyD8AoAAADTILwCAADANCp4u4CrSUziMln9DU2+WYpNSpM9z6KDE7t6uywAAIAS8/U84/N3Xs+cOaNhw4YpOjpawcHBuvXWW7Vt2zZvl+UiJnFZqdoBAAB8jRnyjM+H10cffVSrVq3S3LlztWvXLnXq1EkdOnTQkSNHvF2aQ3ED6ksDDgAA4I5Z8oxPh9dz585p8eLFmjx5stq1a6d69eopKSlJ9erV0+uvv+7t8iSVfCB9ZcABAAAuZaY849NzXv/44w/l5eUpKCjIqT04OFgbN250e4zdbpfdbnds22w2SVJubq5yc3M9XqPV33De9jOc/rzY5bg+AABAeXk7z5TmnBbDMFyr8iG33nqrAgMDNW/ePFWvXl0ffPCB+vfvr3r16mnv3r0u/ZOSkjR+/HiX9nnz5qlixYpXomQAAACUQk5Ojvr27ausrCyFhoYW2dfnw+uBAwc0cOBArV+/Xv7+/mrZsqXq16+vr7/+Wnv27HHp7+7Oa1RUlDIzM4t9McoiNinNadvqZyi5db7GbPeTPd/itG93UoLHrw8AAFBe3s4zNptN4eHhJQqvPj1tQJLq1q2rL774QmfPnpXNZlPNmjV1//33q06dOm77W61WWa1Wl/aAgAAFBAR4vD57nsV9e77FZd/luD4AAEB5eTvPlOacPv2BrYtVqlRJNWvW1KlTp5SWlqa7777b2yVJUonXPfOl9dEAAAAuZqY84/PhNS0tTStWrFBGRoZWrVqlv/71r2rYsKEeeeQRb5fmUNxA+sJAAwAAFMUsecbnw2tWVpaGDBmihg0b6uGHH9Ztt92mtLQ0n/sVfGED6isDDQAAUBwz5Bmf/8BWedlsNoWFhZVoArAn5ObmKjU1VV26dPG5gA0AAFASVzrPlCav+fydVwAAAKAA4RUAAACmQXgFAACAaRBeAQAAYBqEVwAAAJgG4RUAAACmQXgFAACAaRBeAQAAYBqEVwAAAJgG4RUAAACmQXgFAACAaRBeAQAAYBqEVwAAAJgG4RUAAACmQXgFAACAaRBeAQAAYBqEVwAAAJgG4RUAAACmQXgFAACAaRBeAQAAYBqEVwAAAJgG4RUAAACmQXgFAACAaRBeAQAAYBqEVwAAAJgG4RUAAACmQXgFAACAaRBeAQAAYBqEVwAAAJgG4RUAAACmQXgFAACAaRBeAQAAYBqEVwAAAJgG4RUAAACmQXgFAACAaRBeAQAAYBqEVwAAAJgG4RUAAACmQXgFAACAaRBeAQAAYBoVvF3A1SQmcZms/oYm3yzFJqXJnmfRwYldvV0WAABAifl6nvHpO695eXkaM2aMateureDgYNWtW1fJyckyDMPbpbmISVxWqnYAAABfY4Y849PhddKkSXr99dc1Y8YM7dmzR5MmTdLkyZM1ffp0b5fmpLgB9aUBBwAAcMcsecanw+vmzZt19913q2vXroqJiVGvXr3UqVMnffXVV94uzaGkA+krAw4AAHApM+UZn57zeuutt+qtt97Sjz/+qPr162vHjh3auHGjpk6dWugxdrtddrvdsW2z2SRJubm5ys3N9XiNVn/nKQxWP8Ppz4tdjusDAACUl7fzTGnOaTF8cQLp/+Tn5+u5557T5MmT5e/vr7y8PD3//PMaNWpUocckJSVp/PjxLu3z5s1TxYoVL2e5AAAAKIOcnBz17dtXWVlZCg0NLbKvT4fX+fPn69lnn9WLL76oJk2aKD09XcOGDdPUqVPVv39/t8e4u/MaFRWlzMzMYl+MsohNSnPatvoZSm6drzHb/WTPtzjt252U4PHrAwAAlJe384zNZlN4eHiJwqtPTxt49tlnlZiYqAceeECS1LRpUx06dEgpKSmFhler1Sqr1erSHhAQoICAAI/XaM+zuG/Pt7jsuxzXBwAAKC9v55nSnNOnP7CVk5MjPz/nEv39/ZWfn++lilyVdN0zX1ofDQAA4GJmyjM+HV67d++u559/XsuWLdPBgwf18ccfa+rUqerZs6e3S3NS3ED6wkADAAAUxSx5xqfD6/Tp09WrVy898cQTatSokUaMGKHBgwcrOTnZ26W5KGxAfWWgAQAAimOGPOPTH9jyBJvNprCwsBJNAPaE3NxcpaamqkuXLsxxBQAApnSl80xp8ppP33kFAAAALkZ4BQAAgGkQXgEAAGAahFcAAACYBuEVAAAApkF4BQAAgGkQXgEAAGAahFcAAACYBuEVAAAApkF4BQAAgGkQXgEAAGAahFcAAACYBuEVAAAAplHm8LphwwY9+OCDiouL05EjRyRJc+fO1caNGz1WHAAAAHCxMoXXxYsXKyEhQcHBwfr2229lt9slSVlZWXrhhRc8WiAAAABQoEzh9d///rfeeOMNzZw5UwEBAY72Nm3a6JtvvvFYcQAAAMDFyhRe9+7dq3bt2rm0h4WF6fTp0+WtCQAAAHCrTOG1Ro0a2r9/v0v7xo0bVadOnXIXBQAAALhTpvD6t7/9TU8//bS2bt0qi8Wio0eP6v3339eIESP097//3dM1AgAAAJKkCmU5KDExUfn5+Wrfvr1ycnLUrl07Wa1WjRgxQkOHDvV0jQAAAICkMoZXi8Wi0aNH69lnn9X+/fuVnZ2txo0bKyQkxNP1AQAAAA5lCq8FAgMD1bhxY0/VAgAAABSpTOH1/Pnzmj59utauXauTJ08qPz/faT/LZQEAAOByKFN4HTRokFauXKlevXrp5ptvlsVi8XRdAAAAgIsyhdfPPvtMqampatOmjafrAQAAAApVpqWyrrvuOlWuXNnTtQAAAABFKlN4nTJliv75z3/q0KFDnq4HAAAAKFSZpg20bt1a58+fV506dVSxYkUFBAQ47f/99989UhwAAABwsTKF1z59+ujIkSN64YUXVL16dT6wBQAAgCuiTOF18+bN2rJli2688UZP1wMAAAAUqkxzXhs2bKhz5855uhYAAACgSGUKrxMnTtQzzzyjdevW6bfffpPNZnN6AAAAAJdDmaYN3HnnnZKk9u3bO7UbhiGLxaK8vLzyVwYAAABcokzhde3atZ6uAwAAAChWmcJrfHy8p+sAAAAAilXi8Lpz507FxsbKz89PO3fuLLJvs2bNyl0YAAAAcKkSh9fmzZvr+PHjioiIUPPmzWWxWGQYhks/5rwCAADgcilxeM3IyFC1atUc/w0AAABcaSUOr9HR0fL399exY8cUHR19OWsCAAAA3CrVOq/upgkAAAAAV0qZvqQAAAAA8IZSL5X19ttvKyQkpMg+Tz31VJkLMrOYxGWy+huafLMUm5Qme55FByd29XZZAAAAJebreabU4fWNN96Qv79/ofstFotHw2tMTIwOHTrk0v7EE0/o1Vdf9dh1yismcVmh7b404AAAAIUxQ54pdXjdvn27IiIiLkctbm3bts1p6a3du3erY8eOuu+++65YDcUpbKAv3u8rAw4AAOCOWfJMqea8WiyWy1VHoapVq6YaNWo4Hp999pnq1q3rM9/yVdxAl7YfAADAlWamPFOqO6/eXm3gwoULeu+99zR8+PBCg7Tdbpfdbnds22w2SVJubq5yc3M9XpPV3/k1sfoZTn9e7HJcHwAAoLy8nWdKc06LUYpEOn78eD377LOqWLFimQorrwULFqhv3746fPiwIiMj3fZJSkrS+PHjXdrnzZvntboBAABQuJycHPXt21dZWVkKDQ0tsm+pwuvFTp06pf/+97/as2ePJKlRo0YaOHCgrr322rKcrkQSEhIUGBioTz/9tNA+7u68RkVFKTMzs9gXoyxik9Kctq1+hpJb52vMdj/Z853vDu9OSvD49QEAAMrL23nGZrMpPDy8ROG11B/YkqT169frrrvuUmhoqFq3bi1Jmj59upKTk/Xpp5+qXbt2ZTltkQ4dOqTVq1fro48+KrKf1WqV1Wp1aQ8ICFBAQIDH67LnFTJ9Id/isu9yXB8AAKC8vJ1nSnPOMn1JwZAhQ9S7d29lZGToo48+0kcffaSffvpJDzzwgIYMGVKWUxZr9uzZioiIUNeu3v+U28VK+qk7X/h0HgAAgDtmyjNlCq/79+/XM88847Teq7+/v4YPH679+/d7rLgC+fn5mj17tvr3768KFcp0s/iyKm4gfWGgAQAAimKWPFOm8NqyZUvHXNeL7dmzRzfeeGO5i7rU6tWrdfjwYQ0cONDj5/aUwgbUVwYaAACgOGbIM2X6wNaHH36okSNHaujQobrlllskSV9++aVeffVVTZw4UY0aNXL0bdasmeeqLQObzaawsLASTQD2hNzcXKWmpqpLly7McQUAAKZ0pfNMafJamX4H36dPH0nSyJEj3e6zWCwyDEMWi8Xp27EAAACA8ihTeM3IyPB0HQAAAECxyhReo6OjPV0HAAAAUKwyfWBLkubOnas2bdooMjJShw4dkiS9/PLL+uSTTzxWHAAAAHCxMoXX119/XcOHD1eXLl10+vRpx7zWKlWq6OWXX/ZkfQAAAIBDmcLr9OnTNXPmTI0ePdpprdfWrVtr165dHisOAAAAuFiZwmtGRoZatGjh0m61WnX27NlyFwUAAAC4U6bwWrt2baWnp7u0r1ixwmmNVwAAAMCTyrTawPDhwzVkyBCdP39ehmHoq6++0gcffKCUlBS9/fbbnq4RAAAAkFTG8Proo48qODhY//rXv5STk6O+ffsqMjJSr7zyih544AFP1wgAAABIKmN4laR+/fqpX79+ysnJUXZ2tiIiIjxZFwAAAOCizOu8/vHHH1q9erXmzp2r4OBgSdLRo0eVnZ3tseIAAACAi5XpzuuhQ4d055136vDhw7Lb7erYsaMqV66sSZMmyW6364033vB0nQAAAEDZ7rw+/fTTat26tU6dOuW46ypJPXv21Oeff+6x4gAAAICLlenO64YNG7R582YFBgY6tcfExOjIkSMeKQwAAAC4VJnuvObn5zu+EvZiv/zyiypXrlzuogAAAAB3yhReO3XqpJdfftmxbbFYlJ2drXHjxqlLly6eqg0AAABwUqZpA1OmTFFCQoIaN26s8+fPq2/fvtq3b5/Cw8P1wQcfeLpGAAAAQFIZw+v111+vHTt2aP78+dq5c6eys7M1aNAg9evXz+kDXAAAAIAnlflLCipUqKAHH3zQk7UAAAAARSpxeF26dGmJT3rXXXeVqRgAAACgKCUOrz169ChRP4vF4nYlAgAAAKC8Shxe8/PzL2cdAAAAQLFKtVTWli1b9Nlnnzm1vfvuu6pdu7YiIiL02GOPyW63e7RAAAAAoECpwuv48eP13XffObZ37dqlQYMGqUOHDkpMTNSnn36qlJQUjxcJAAAASKUMrzt27FD79u0d2/Pnz9df/vIXzZw5U8OHD9e0adO0YMECjxcJAAAASKUMr6dOnVL16tUd21988YU6d+7s2L7pppv0888/e646AAAA4CKlCq/Vq1dXRkaGJOnChQv65ptvdMsttzj2nzlzRgEBAZ6tEAAAAPifUoXXLl26KDExURs2bNCoUaNUsWJFtW3b1rF/586dqlu3rseLBAAAAKRSfsNWcnKy7rnnHsXHxyskJETvvPOOAgMDHftnzZqlTp06ebxIAAAAQCpleA0PD9f69euVlZWlkJAQ+fv7O+1fuHChQkJCPFogAAAAUKBU4bVAWFiY2/Zrr722XMUAAAAARSnVnFcAAADAmwivAAAAMA3CKwAAAEyD8AoAAADTILwCAADANAivAAAAMA3CKwAAAEyD8AoAAADTKNOXFMC9mMRlsvobmnyzFJuUJnueRQcndvV2WQAAACXm63nG5++8HjlyRA8++KCqVq2q4OBgNW3aVNu3b/d2WS5iEpeVqh0AAMDXmCHP+HR4PXXqlNq0aaOAgAAtX75c33//vaZMmaJrrrnG26U5KW5AfWnAAQAA3DFLnvHpaQOTJk1SVFSUZs+e7WirXbu2FytyVdKBjElc5lO33AEAAAqYKc/4dHhdunSpEhISdN999+mLL77QddddpyeeeEJ/+9vfCj3GbrfLbrc7tm02myQpNzdXubm5Hq/R6m84b/sZTn9e7HJcHwAAoLy8nWdKc06LYRiuVfmIoKAgSdLw4cN13333adu2bXr66af1xhtvqH///m6PSUpK0vjx413a582bp4oVK17WegEAAFB6OTk56tu3r7KyshQaGlpkX58Or4GBgWrdurU2b97saHvqqae0bds2bdmyxe0x7u68RkVFKTMzs9gXoyxik9Kctq1+hpJb52vMdj/Z8y1O+3YnJXj8+gAAAOXl7Txjs9kUHh5eovDq09MGatasqcaNGzu1NWrUSIsXLy70GKvVKqvV6tIeEBCggIAAj9doz7O4b8+3uOy7HNcHAAAoL2/nmdKc06dXG2jTpo327t3r1Pbjjz8qOjraSxW5KumkZW9PbgYAACiMmfKMT4fXf/zjH/ryyy/1wgsvaP/+/Zo3b57eeustDRkyxNulOSluIH1hoAEAAIpiljzj0+H1pptu0scff6wPPvhAsbGxSk5O1ssvv6x+/fp5uzQXhQ2orww0AABAccyQZ3z6A1ueYLPZFBYWVqIJwJ6Qm5ur1NRUdenShTmuAADAlK50nilNXvPpO68AAADAxQivAAAAMA3CKwAAAEyD8AoAAADTILwCAADANAivAAAAMA3CKwAAAEyD8AoAAADTILwCAADANAivAAAAMA3CKwAAAEyD8AoAAADTILwCAADANAivAAAAMA3CKwAAAEyD8AoAAADTILwCAADANAivAAAAMA3CKwAAAEyD8AoAAADTILwCAADANAivAAAAMA3CKwAAAEyD8AoAAADTILwCAADANAivAAAAMA3CKwAAAEyD8AoAAADTILwCAADANAivAAAAMA3CKwAAAEyD8AoAAADTILwCAADANAivAAAAMA3CKwAAAEyD8AoAAADTILwCAADANAivAAAAMA3CKwAAAEyD8AoAAADTILwCAADANCp4u4CrSUziMln9DU2+WYpNSpM9z6KDE7t6uywAAIAS8/U84/N3XpOSkmSxWJweDRs29HZZLmISl5WqHQAAwNeYIc/4fHiVpCZNmujYsWOOx8aNG71dkpPiBtSXBhwAAMAds+QZU4TXChUqqEaNGo5HeHi4t0tyKOlA+sqAAwAAXMpMecYUc1737dunyMhIBQUFKS4uTikpKapVq5bbvna7XXa73bFts9kkSbm5ucrNzfV4bVZ/w3nbz3D682KX4/oAAADl5e08U5pzWgzDcK3KhyxfvlzZ2dlq0KCBjh07pvHjx+vIkSPavXu3Kleu7NI/KSlJ48ePd2mfN2+eKlaseCVKBgAAQCnk5OSob9++ysrKUmhoaJF9fT68Xur06dOKjo7W1KlTNWjQIJf97u68RkVFKTMzs9gXoyxik9Kctq1+hpJb52vMdj/Z8y1O+3YnJXj8+gAAAOXl7Txjs9kUHh5eovBqimkDF6tSpYrq16+v/fv3u91vtVpltVpd2gMCAhQQEODxeux5Fvft+RaXfZfj+gAAAOXl7TxTmnOa4gNbF8vOztaBAwdUs2ZNb5ciSSVe98yX1kcDAAC4mJnyjM+H1xEjRuiLL77QwYMHtXnzZvXs2VP+/v7q06ePt0tzKG4gfWGgAQAAimKWPOPz4fWXX35Rnz591KBBA/Xu3VtVq1bVl19+qWrVqnm7NCeFDaivDDQAAEBxzJBnTPeBrdKy2WwKCwsr0QRgT8jNzVVqaqq6dOnCHFcAAGBKVzrPlCav+fydVwAAAKAA4RUAAACmQXgFAACAaRBeAQAAYBqEVwAAAJgG4RUAAACmQXgFAACAaRBeAQAAYBqEVwAAAJgG4RUAAACmQXgFAACAaRBeAQAAYBqEVwAAAJgG4RUAAACmQXgFAACAaRBeAQAAYBqEVwAAAJgG4RUAAACmQXgFAACAaRBeAQAAYBqEVwAAAJgG4RUAAACmQXgFAACAaRBeAQAAYBqEVwAAAJgG4RUAAACmQXgFAACAaRBeAQAAYBqEVwAAAJgG4RUAAACmQXgFAACAaRBeAQAAYBqEVwAAAJgG4RUAAACmQXgFAACAaRBeAQAAYBqEVwAAAJgG4RUAAACmQXgFAACAaRBeAQAAYBoVvF3A1SQmcZms/oYm3yzFJqXJnmfRwYldvV0WAABAifl6njHVndeJEyfKYrFo2LBh3i7FRUzislK1AwAA+Boz5BnThNdt27bpzTffVLNmzbxdioviBtSXBhwAAMAds+QZU4TX7Oxs9evXTzNnztQ111zj7XKclHQgfWXAAQAALmWmPGOKOa9DhgxR165d1aFDB/373/8usq/dbpfdbnds22w2SVJubq5yc3M9XpvV33De9jOc/rzY5bg+AABAeXk7z5TmnD4fXufPn69vvvlG27ZtK1H/lJQUjR8/3qV95cqVqlixoqfL0+Sb3bcnt853aUtNTfX49QEAAMrL23kmJyenxH0thmG4Rmof8fPPP6t169ZatWqVY67r7bffrubNm+vll192e4y7O69RUVHKzMxUaGiox2uMTUpz2rb6GUpuna8x2/1kz7c47dudlODx6wMAAJSXt/OMzWZTeHi4srKyis1rPn3n9euvv9bJkyfVsmVLR1teXp7Wr1+vGTNmyG63y9/f3+kYq9Uqq9Xqcq6AgAAFBAR4vEZ7nsV9e77FZd/luD4AAEB5eTvPlOacPv2Brfbt22vXrl1KT093PFq3bq1+/fopPT3dJbh6Q0nXPfOl9dEAAAAuZqY849PhtXLlyoqNjXV6VKpUSVWrVlVsbKy3y3MobiB9YaABAACKYpY849Ph1UwKG1BfGWgAAIDimCHP+PQHtjzBZrMpLCysRBOAPSE3N1epqanq0qULc1wBAIApXek8U5q8xp1XAAAAmAbhFQAAAKZBeAUAAIBpEF4BAABgGoRXAAAAmAbhFQAAAKZBeAUAAIBpEF4BAABgGoRXAAAAmAbhFQAAAKZBeAUAAIBpEF4BAABgGoRXAAAAmAbhFQAAAKZBeAUAAIBpEF4BAABgGoRXAAAAmAbhFQAAAKZBeAUAAIBpEF4BAABgGoRXAAAAmAbhFQAAAKZBeAUAAIBpEF4BAABgGoRXAAAAmAbhFQAAAKZBeAUAAIBpEF4BAABgGoRXAAAAmAbhFQAAAKZBeAUAAIBpEF4BAABgGoRXAAAAmAbhFQAAAKZBeAUAAIBpEF4BAABgGoRXAAAAmAbhFQAAAKZBeAUAAIBpEF4BAABgGoRXAAAAmEYFbxdwNYlJXCarv6HJN0uxSWmy51l0cGJXb5cFAABQYr6eZ3z+zuvrr7+uZs2aKTQ0VKGhoYqLi9Py5cu9XZaLmMRlpWoHAADwNWbIMz4fXq+//npNnDhRX3/9tbZv36477rhDd999t7777jtvl+ZQ3ID60oADAAC4Y5Y84/PhtXv37urSpYtuuOEG1a9fX88//7xCQkL05Zdfers0SSUfSF8ZcAAAgEuZKc+Yas5rXl6eFi5cqLNnzyouLs5tH7vdLrvd7ti22WySpNzcXOXm5nq8Jqu/4bztZzj9ebHLcX0AAIDy8naeKc05LYZhuFblY3bt2qW4uDidP39eISEhmjdvnrp06eK2b1JSksaPH+/SPm/ePFWsWPFylwoAAIBSysnJUd++fZWVlaXQ0NAi+5oivF64cEGHDx9WVlaWFi1apLfffltffPGFGjdu7NLX3Z3XqKgoZWZmFvtilEVsUprTttXPUHLrfI3Z7id7vsVp3+6kBI9fHwAAoLy8nWdsNpvCw8NLFF5NMW0gMDBQ9erVkyS1atVK27Zt0yuvvKI333zTpa/VapXVanVpDwgIUEBAgMdrs+dZ3LfnW1z2XY7rAwAAlJe380xpzunzH9hyJz8/3+nuqjeVdN0zX1ofDQAA4GJmyjM+H15HjRql9evX6+DBg9q1a5dGjRqldevWqV+/ft4uzaG4gfSFgQYAACiKWfKMz4fXkydP6uGHH1aDBg3Uvn17bdu2TWlpaerYsaO3S3NS2ID6ykADAAAUxwx5xhQf2CoPm82msLCwEk0A9oTc3FylpqaqS5cuzHEFAACmdKXzTGnyms/feQUAAAAKEF4BAABgGoRXAAAAmAbhFQAAAKZBeAUAAIBpEF4BAABgGoRXAAAAmAbhFQAAAKZBeAUAAIBpEF4BAABgGoRXAAAAmAbhFQAAAKZBeAUAAIBpVPB2AZebYRiSJJvNdkWul5ubq5ycHNlsNgUEBFyRawIAAHjSlc4zBTmtILcV5aoPr2fOnJEkRUVFebkSAAAAFOXMmTMKCwsrso/FKEnENbH8/HwdPXpUlStXlsViuezXs9lsioqK0s8//6zQ0NDLfj0AAABPu9J5xjAMnTlzRpGRkfLzK3pW61V/59XPz0/XX3/9Fb9uaGgo4RUAAJjalcwzxd1xLcAHtgAAAGAahFcAAACYBuHVw6xWq8aNGyer1ertUgAAAMrEl/PMVf+BLQAAAFw9uPMKAAAA0yC8AgAAwDQIrwAAADANwisAAABMg/BaBgMGDJDFYtHEiROd2pcsWXJFvsULAACgLAzDUIcOHZSQkOCy77XXXlOVKlX0yy+/eKGykiO8llFQUJAmTZqkU6dOebsUAACAErFYLJo9e7a2bt2qN99809GekZGhkSNHavr06V75ZtLSILyWUYcOHVSjRg2lpKQU2mfx4sVq0qSJrFarYmJiNGXKlCtYIQAAgKuoqCi98sorGjFihDIyMmQYhgYNGqROnTqpRYsW6ty5s0JCQlS9enU99NBDyszMdBy7aNEiNW3aVMHBwapatao6dOigs2fPXtH6Ca9l5O/vrxdeeEHTp093e3v966+/Vu/evfXAAw9o165dSkpK0pgxYzRnzpwrXywAAMBF+vfvr/bt22vgwIGaMWOGdu/erTfffFN33HGHWrRooe3bt2vFihU6ceKEevfuLUk6duyY+vTpo4EDB2rPnj1at26d7rnnHl3prwzgSwrKYMCAATp9+rSWLFmiuLg4NW7cWP/973+1ZMkS9ezZU4ZhqF+/fvr111+1cuVKx3EjR47UsmXL9N1333mxegAAAOnkyZNq0qSJfv/9dy1evFi7d+/Whg0blJaW5ujzyy+/KCoqSnv37lV2drZatWqlgwcPKjo62mt1c+e1nCZNmqR33nlHe/bscWrfs2eP2rRp49TWpk0b7du3T3l5eVeyRAAAABcREREaPHiwGjVqpB49emjHjh1au3atQkJCHI+GDRtKkg4cOKAbb7xR7du3V9OmTXXfffdp5syZXvnsD+G1nNq1a6eEhASNGjXK26UAAACUSoUKFVShQgVJUnZ2trp376709HSnx759+9SuXTv5+/tr1apVWr58uRo3bqzp06erQYMGysjIuLI1X9GrXaUmTpyo5s2bq0GDBo62Ro0aadOmTU79Nm3apPr168vf3/9KlwgAAFCkli1bavHixYqJiXEE2ktZLBa1adNGbdq00dixYxUdHa2PP/5Yw4cPv2J1cufVA5o2bap+/fpp2rRpjrZnnnlGn3/+uZKTk/Xjjz/qnXfe0YwZMzRixAgvVgoAAODekCFD9Pvvv6tPnz7atm2bDhw4oLS0ND3yyCPKy8vT1q1b9cILL2j79u06fPiwPvroI/36669q1KjRFa2T8OohEyZMUH5+vmO7ZcuWWrBggebPn6/Y2FiNHTtWEyZM0IABA7xXJAAAQCEiIyO1adMm5eXlqVOnTmratKmGDRumKlWqyM/PT6GhoVq/fr26dOmi+vXr61//+pemTJmizp07X9E6WW0AAAAApsGdVwAAAJgG4RUAAACmQXgFAACAaRBeAQAAYBqEVwAAAJgG4RUAAACmQXgFAACAaRBeAQAAYBqEVwBXhXXr1slisej06dPeLqVc/vvf/6pTp07eLgMekJiYqKFDh3q7DOCqQ3gFoAEDBqhHjx4u7VcyECYlJal58+Yu7TExMbJYLLJYLAoODlZMTIx69+6tNWvWOPW79dZbdezYMYWFhV32Wi+X8+fPa8yYMRo3bpxT+8KFC9WwYUMFBQWpadOmSk1N9VKFV97zzz+vW2+9VRUrVlSVKlW8XU6pjBgxQu+8845++uknb5cCXFUIrwC8yjAM/fHHH0X2mTBhgo4dO6a9e/fq3XffVZUqVdShQwc9//zzjj6BgYGqUaOGLBbL5S75slm0aJFCQ0PVpk0bR9vmzZvVp08fDRo0SN9++6169OihHj16aPfu3V6s9Mq5cOGC7rvvPv3973/3dimlFh4eroSEBL3++uveLgW4qhBeAZTKxo0b1bZtWwUHBysqKkpPPfWUzp4969g/d+5ctW7dWpUrV1aNGjXUt29fnTx50rG/4G7u8uXL1apVK1mtVr333nsaP368duzY4bjLOmfOHMcxBeeqVauW2rVrp7feektjxozR2LFjtXfvXqfzFtwlPnTokLp3765rrrlGlSpVUpMmTZzuWO7evVudO3dWSEiIqlevroceekiZmZmO/StWrNBtt92mKlWqqGrVqurWrZsOHDjg2H/hwgU9+eSTqlmzpoKCghQdHa2UlBTH/tOnT+vRRx9VtWrVFBoaqjvuuEM7duwo8rWdP3++unfv7tT2yiuv6M4779Szzz6rRo0aKTk5WS1bttSMGTNKMFpl4+4uuLu78EW9F26//XbHWF76SEpKKnEt48eP1z/+8Q81bdrUA8+s5ObMmeNS98WvSV5engYNGqTatWsrODhYDRo00CuvvOJynu7du2v+/PlXsHLg6kd4BVBiBw4c0J133ql7771XO3fu1IcffqiNGzfqySefdPTJzc1VcnKyduzYoSVLlujgwYMaMGCAy7kSExM1ceJE7dmzRx07dtQzzzyjJk2a6NixYzp27Jjuv//+Imt5+umnZRiGPvnkE7f7hwwZIrvdrvXr12vXrl2aNGmSQkJCJP0ZLO+44w61aNFC27dv14oVK3TixAn17t3bcfzZs2c1fPhwbd++XZ9//rn8/PzUs2dP5efnS5KmTZumpUuXasGCBdq7d6/ef/99xcTEOI6/7777dPLkSS1fvlxff/21WrZsqfbt2+v3338v9Dlt3LhRrVu3dmrbsmWLOnTo4NSWkJCgLVu2FHqeDRs2KCQkpMjH+++/X+jxJVHce+Gjjz5yjGVcXJyeeeYZx/aIESPKde3iPP7448U+/5IIDQ111PzMM8847cvPz9f111+vhQsX6vvvv9fYsWP13HPPacGCBU79br75Zv3yyy86ePCgp54e8P+9Ct4uAIBv+Oyzz1z+Uc/Ly3PaTklJUb9+/TRs2DBJ0g033KBp06YpPj5er7/+uoKCgjRw4EBH/zp16mjatGm66aablJ2d7XT+CRMmqGPHjo7tkJAQVahQQTVq1ChRvddee60iIiIKDQWHDx/Wvffe67hjV6dOHce+GTNmqEWLFnrhhRccbbNmzVJUVJR+/PFH1a9fX/fee6/T+WbNmqVq1arp+++/V2xsrA4fPqwbbrhBt912mywWi6Kjox19N27cqK+++konT56U1WqVJP3nP//RkiVLtGjRIj322GMu9Z4+fVpZWVmKjIx0aj9+/LiqV6/u1Fa9enUdP3680NemdevWSk9PL3R/wTnKo7j3wrXXXuvoGxgYqJCQkBKPbXlNmDCh3AHZbrc7pqJIcvl/IyAgQOPHj3ds165dW1u2bNGCBQucfggqGM9Dhw45/XADoOwIrwAkSX/9619d5uZt3bpVDz74oGN7x44d2rlzp9NdO8MwlJ+fr4yMDDVq1Ehff/21kpKStGPHDp06dcpxp/Lw4cNq3Lix47hL7zCWhWEYhc5xfeqpp/T3v/9dK1euVIcOHXTvvfeqWbNmjuexdu1at3fgDhw4oPr162vfvn0aO3astm7dqszMTKfnERsbqwEDBqhjx45q0KCB7rzzTnXr1s2xSsCOHTuUnZ2tqlWrOp373LlzTlMPLt0nSUFBQWV7MS4SHBysevXqlescu3btcnp9Lv1BpiTvBW+JiIhQREREuc7x22+/KTQ0tMg+r776qmbNmqXDhw/r3LlzunDhgst0i+DgYElSTk5OueoB8H8IrwAkSZUqVXIJPL/88ovTdnZ2tgYPHqynnnrK5fhatWrp7NmzSkhIUEJCgt5//31Vq1ZNhw8fVkJCgi5cuOByvfL47bff9Ouvv6p27dpu9z/66KNKSEjQsmXLtHLlSqWkpGjKlCkaOnSosrOz1b17d02aNMnluJo1a0r6c65idHS0Zs6cqcjISOXn5ys2NtbxPFq2bKmMjAwtX75cq1evVu/evdWhQwctWrRI2dnZqlmzptatW+dy/sI+MV+1alVZLBadOnXKqb1GjRo6ceKEU9uJEyeKvIu5YcMGde7cudD9kvTmm2+qX79+he5v0KCBli5d6ti+9AeZ4t4L3vT444/rvffeK7JPdnZ2kft/+umnQt9b0p/zk0eMGKEpU6YoLi5OlStX1osvvqitW7c69SuYJlKtWrUSVg+gOIRXACXWsmVLff/994Xe1du1a5d+++03TZw4UVFRUZKk7du3l+jcgYGBLnf3ivLKK6/Iz8/P7RJfBaKiovT444/r8ccf16hRozRz5kwNHTpULVu21OLFixUTE6MKFVz/Gvztt9+0d+9ezZw5U23btpX051SAS4WGhur+++/X/fffr169eunOO+/U77//rpYtW+r48eOqUKFCiX9VHBgYqMaNG+v77793Wuc1Li5On3/+uePX85K0atUqxcXFFXouT0wbCAwMdBrnS3+QKe694E2emDawfv36IsP9pk2bdOutt+qJJ55wtLm7q757924FBASoSZMm5aoHwP8hvAIosX/+85+65ZZb9OSTT+rRRx9VpUqV9P3332vVqlWaMWOGatWqpcDAQE2fPl2PP/64du/ereTk5BKdOyYmRhkZGUpPT9f111+vypUrO+aLnjlzRsePH1dubq4yMjL03nvv6e2331ZKSkqh4WnYsGHq3Lmz6tevr1OnTmnt2rWOX2UPGTJEM2fOVJ8+fTRy5Ehde+212r9/v+bPn6+3335b11xzjapWraq33npLNWvW1OHDh5WYmOh0/qlTp6pmzZpq0aKF/Pz8tHDhQtWoUcOxjFdcXJx69OihyZMnq379+jp69KiWLVumnj17FjplIiEhQRs3bnQKqk8//bTi4+M1ZcoUde3aVfPnz9f27dv11ltvFfpaemLaQHGKey94yuHDh/X777/r8OHDysvLc4TyevXqFfrBq/JMGzh37pzefvttHThwQJ07d3bMLc7OztYff/yh33//Xddee61uuOEGvfvuu0pLS1Pt2rU1d+5cbdu2zeVu7YYNGxwrMgDwEAPA//f69+9v3H333S7ta9euNSQZp06dcrR99dVXRseOHY2QkBCjUqVKRrNmzYznn3/esX/evHlGTEyMYbVajbi4OGPp0qWGJOPbb78t9JyGYRjnz5837r33XqNKlSqGJGP27NmGYRhGdHS0IcmQZAQGBhq1atUyevfubaxZs6bIWp988kmjbt26htVqNapVq2Y89NBDRmZmpqP/jz/+aPTs2dOoUqWKERwcbDRs2NAYNmyYkZ+fbxiGYaxatcpo1KiRYbVajWbNmhnr1q0zJBkff/yxYRiG8dZbbxnNmzc3KlWqZISGhhrt27c3vvnmG8f5bTabMXToUCMyMtIICAgwoqKijH79+hmHDx8udBy+++47Izg42Dh9+rRT+4IFC4z69esbgYGBRpMmTYxly5YVeg5PGDdunHHjjTc6tZXlvVAgPj7eGDdunNvrREdHF1lL//79HeN/8WPt2rWlf2IlMHv2bLfXK3jEx8cbhvHn+3XAgAFGWFiYUaVKFePvf/+7kZiY6PK6NWjQwPjggw8uS63A/68shmEYVzQtAwAKdd9996lly5YaNWqUt0u57Pr37++ypq+3zZkzR+vWrXNbU3p6uoYNG+Z2LrM7y5cv1zPPPKOdO3e6nZ4CoGxY5xUAfMiLL75Y4nVIzcwwDK1bt67E00qulODg4EK/YjggIMBpCbDinD17VrNnzya4Ah7GnVcAAACYBndeAQAAYBqEVwAAAJgG4RUAAACmQXgFAACAaRBeAQAAYBqEVwAAAJgG4RUAAACmQXgFAACAaRBeAQAAYBr/Dyoi6q2cLQdxAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "# Список колонок для построения графиков\n",
    "columns = ['BMI', 'Smoking', 'AlcoholDrinking', 'Stroke',\n",
    "           'PhysicalHealth', 'MentalHealth', 'DiffWalking', 'Sex',\n",
    "           'AgeCategory', 'Race', 'Diabetic', 'PhysicalActivity', 'GenHealth', 'SleepTime', 'Asthma', 'KidneyDisease', 'SkinCancer']\n",
    "\n",
    "# Создание диаграмм зависимости\n",
    "for column in columns:\n",
    "    plt.figure(figsize=(8, 6))  # Установка размера графика\n",
    "    if pd.api.types.is_numeric_dtype(df[column]):  # Проверяем, является ли колонка числовой\n",
    "        # Проверяем, содержит ли колонка только два уникальных значения (0 и 1)\n",
    "        if df[column].nunique() == 2 and set(df[column].unique()).issubset({0, 1}):\n",
    "            # Если да, то строим столбчатую диаграмму\n",
    "            counts = df[column].value_counts()  # Считаем количество повторений каждого значения\n",
    "            counts.plot(kind='bar')  # Создаем столбчатую диаграмму\n",
    "            plt.title(f'Количество значений для {column}')\n",
    "            plt.xlabel(column)\n",
    "            plt.ylabel('Количество повторений')\n",
    "        else:\n",
    "            # Если колонка числовая, создаем диаграмму рассеяния\n",
    "            plt.scatter(df['HeartDisease'], df[column], alpha=0.5)  # Создаем диаграмму рассеяния\n",
    "            plt.title(f'Зависимость HeartDisease от {column}')\n",
    "            plt.xlabel('HeartDisease (0 = нет, 1 = да)')\n",
    "            plt.ylabel(column)\n",
    "            plt.xticks([0, 1])  # Установка меток по оси X\n",
    "            plt.grid()  # Добавление сетки для удобства восприятия\n",
    "    else:\n",
    "        # Если колонка не числовая, строим столбчатую диаграмму\n",
    "        counts = df[column].value_counts()  # Считаем количество повторений каждого значения\n",
    "        counts.plot(kind='bar')  # Создаем столбчатую диаграмму\n",
    "        plt.title(f'Количество значений для {column}')\n",
    "        plt.xlabel(column)\n",
    "        plt.ylabel('Количество повторений')\n",
    "\n",
    "    plt.show()  # Отображение графика"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Функция для создания выборок\n",
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "def split_stratified_into_train_val_test(\n",
    "    df_input,\n",
    "    stratify_colname=\"y\",\n",
    "    frac_train=0.6,\n",
    "    frac_val=0.15,\n",
    "    frac_test=0.25,\n",
    "    random_state=None,\n",
    "):\n",
    "\n",
    "    if frac_train + frac_val + frac_test != 1.0:\n",
    "        raise ValueError(\n",
    "            \"fractions %f, %f, %f do not add up to 1.0\"\n",
    "            % (frac_train, frac_val, frac_test)\n",
    "        )\n",
    "\n",
    "    if stratify_colname not in df_input.columns:\n",
    "        raise ValueError(\"%s is not a column in the dataframe\" % (stratify_colname))\n",
    "\n",
    "    X = df_input  # Contains all columns.\n",
    "    y = df_input[\n",
    "        [stratify_colname]\n",
    "    ]  # Dataframe of just the column on which to stratify.\n",
    "\n",
    "    # Split original dataframe into train and temp dataframes.\n",
    "    df_train, df_temp, y_train, y_temp = train_test_split(\n",
    "        X, y, stratify=y, test_size=(1.0 - frac_train), random_state=random_state\n",
    "    )\n",
    "\n",
    "    # Split the temp dataframe into val and test dataframes.\n",
    "    relative_frac_test = frac_test / (frac_val + frac_test)\n",
    "    df_val, df_test, y_val, y_test = train_test_split(\n",
    "        df_temp,\n",
    "        y_temp,\n",
    "        stratify=y_temp,\n",
    "        test_size=relative_frac_test,\n",
    "        random_state=random_state,\n",
    "    )\n",
    "\n",
    "    assert len(df_input) == len(df_train) + len(df_val) + len(df_test)\n",
    "\n",
    "    return df_train, df_val, df_test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "HeartDisease\n",
      "0    53\n",
      "1    47\n",
      "Name: count, dtype: int64\n",
      "\n",
      "Обучающая выборка:  (60, 2)\n",
      "HeartDisease\n",
      "0    32\n",
      "1    28\n",
      "Name: count, dtype: int64\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Контрольная выборка:  (20, 2)\n",
      "HeartDisease\n",
      "0    11\n",
      "1     9\n",
      "Name: count, dtype: int64\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Тестовая выборка:  (20, 2)\n",
      "HeartDisease\n",
      "1    10\n",
      "0    10\n",
      "Name: count, dtype: int64\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Вывод распределения количества наблюдений по меткам (классам)\n",
    "print(df.HeartDisease.value_counts())\n",
    "print()\n",
    "\n",
    "data = df.copy()\n",
    "\n",
    "df_train, df_val, df_test = split_stratified_into_train_val_test(\n",
    "   data, stratify_colname=\"HeartDisease\", frac_train=0.60, frac_val=0.20, frac_test=0.20\n",
    ")\n",
    "\n",
    "print(\"Обучающая выборка: \", df_train.shape)\n",
    "print(df_train.HeartDisease.value_counts())\n",
    "counts = df_train['HeartDisease'].value_counts()\n",
    "plt.figure(figsize=(2, 2))# Установка размера графика\n",
    "plt.pie(counts, labels=counts.index, autopct='%1.1f%%', startangle=90)# Построение круговой диаграммы\n",
    "plt.title('Распределение классов HeartDisease в обучающей выборке')# Добавление заголовка\n",
    "plt.show()# Отображение графика\n",
    "\n",
    "print(\"Контрольная выборка: \", df_val.shape)\n",
    "print(df_val.HeartDisease.value_counts())\n",
    "counts = df_val['HeartDisease'].value_counts()\n",
    "plt.figure(figsize=(2, 2))\n",
    "plt.pie(counts, labels=counts.index, autopct='%1.1f%%', startangle=90)\n",
    "plt.title('Распределение классов HeartDisease в контрольной выборке')\n",
    "plt.show()\n",
    "\n",
    "print(\"Тестовая выборка: \", df_test.shape)\n",
    "print(df_test.HeartDisease.value_counts())\n",
    "counts = df_test['HeartDisease'].value_counts()\n",
    "plt.figure(figsize=(2, 2))\n",
    "plt.pie(counts, labels=counts.index, autopct='%1.1f%%', startangle=90)\n",
    "plt.title('Распределение классов HeartDisease в тестовой выборке')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Сбалансируем распределение:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. Балансировка данных оверсемплингом. Это метод, увеличивающий число наблюдений в меньшинственном классе для достижения более равномерного распределения классов."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "A given column is not a column of the dataframe",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "File \u001b[1;32mc:\\Users\\K\\source\\repos\\AIM-PIbd-31-Ievlewa-M-D\\aimenv\\Lib\\site-packages\\pandas\\core\\indexes\\base.py:3805\u001b[0m, in \u001b[0;36mIndex.get_loc\u001b[1;34m(self, key)\u001b[0m\n\u001b[0;32m   3804\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m-> 3805\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_engine\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_loc\u001b[49m\u001b[43m(\u001b[49m\u001b[43mcasted_key\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m   3806\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m err:\n",
      "File \u001b[1;32mindex.pyx:167\u001b[0m, in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[1;34m()\u001b[0m\n",
      "File \u001b[1;32mindex.pyx:196\u001b[0m, in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[1;34m()\u001b[0m\n",
      "File \u001b[1;32mpandas\\\\_libs\\\\hashtable_class_helper.pxi:7081\u001b[0m, in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[1;34m()\u001b[0m\n",
      "File \u001b[1;32mpandas\\\\_libs\\\\hashtable_class_helper.pxi:7089\u001b[0m, in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[1;34m()\u001b[0m\n",
      "\u001b[1;31mKeyError\u001b[0m: 'Smoking'",
      "\nThe above exception was the direct cause of the following exception:\n",
      "\u001b[1;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "File \u001b[1;32mc:\\Users\\K\\source\\repos\\AIM-PIbd-31-Ievlewa-M-D\\aimenv\\Lib\\site-packages\\sklearn\\utils\\_indexing.py:361\u001b[0m, in \u001b[0;36m_get_column_indices\u001b[1;34m(X, key)\u001b[0m\n\u001b[0;32m    360\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m col \u001b[38;5;129;01min\u001b[39;00m columns:\n\u001b[1;32m--> 361\u001b[0m     col_idx \u001b[38;5;241m=\u001b[39m \u001b[43mall_columns\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_loc\u001b[49m\u001b[43m(\u001b[49m\u001b[43mcol\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    362\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(col_idx, numbers\u001b[38;5;241m.\u001b[39mIntegral):\n",
      "File \u001b[1;32mc:\\Users\\K\\source\\repos\\AIM-PIbd-31-Ievlewa-M-D\\aimenv\\Lib\\site-packages\\pandas\\core\\indexes\\base.py:3812\u001b[0m, in \u001b[0;36mIndex.get_loc\u001b[1;34m(self, key)\u001b[0m\n\u001b[0;32m   3811\u001b[0m         \u001b[38;5;28;01mraise\u001b[39;00m InvalidIndexError(key)\n\u001b[1;32m-> 3812\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m(key) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01merr\u001b[39;00m\n\u001b[0;32m   3813\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mTypeError\u001b[39;00m:\n\u001b[0;32m   3814\u001b[0m     \u001b[38;5;66;03m# If we have a listlike key, _check_indexing_error will raise\u001b[39;00m\n\u001b[0;32m   3815\u001b[0m     \u001b[38;5;66;03m#  InvalidIndexError. Otherwise we fall through and re-raise\u001b[39;00m\n\u001b[0;32m   3816\u001b[0m     \u001b[38;5;66;03m#  the TypeError.\u001b[39;00m\n",
      "\u001b[1;31mKeyError\u001b[0m: 'Smoking'",
      "\nThe above exception was the direct cause of the following exception:\n",
      "\u001b[1;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "Cell \u001b[1;32mIn[25], line 20\u001b[0m\n\u001b[0;32m     17\u001b[0m ada \u001b[38;5;241m=\u001b[39m ADASYN()\n\u001b[0;32m     19\u001b[0m \u001b[38;5;66;03m# Преобразование данных с помощью пайплайна\u001b[39;00m\n\u001b[1;32m---> 20\u001b[0m X \u001b[38;5;241m=\u001b[39m \u001b[43mpreprocessor\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfit_transform\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdf_train\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdrop\u001b[49m\u001b[43m(\u001b[49m\u001b[43mcolumns\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mHeartDisease\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m     21\u001b[0m y \u001b[38;5;241m=\u001b[39m df_train[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mHeartDisease\u001b[39m\u001b[38;5;124m'\u001b[39m]\n\u001b[0;32m     23\u001b[0m \u001b[38;5;66;03m# Применение ADASYN\u001b[39;00m\n",
      "File \u001b[1;32mc:\\Users\\K\\source\\repos\\AIM-PIbd-31-Ievlewa-M-D\\aimenv\\Lib\\site-packages\\sklearn\\utils\\_set_output.py:316\u001b[0m, in \u001b[0;36m_wrap_method_output.<locals>.wrapped\u001b[1;34m(self, X, *args, **kwargs)\u001b[0m\n\u001b[0;32m    314\u001b[0m \u001b[38;5;129m@wraps\u001b[39m(f)\n\u001b[0;32m    315\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mwrapped\u001b[39m(\u001b[38;5;28mself\u001b[39m, X, \u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[1;32m--> 316\u001b[0m     data_to_wrap \u001b[38;5;241m=\u001b[39m \u001b[43mf\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mX\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    317\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(data_to_wrap, \u001b[38;5;28mtuple\u001b[39m):\n\u001b[0;32m    318\u001b[0m         \u001b[38;5;66;03m# only wrap the first output for cross decomposition\u001b[39;00m\n\u001b[0;32m    319\u001b[0m         return_tuple \u001b[38;5;241m=\u001b[39m (\n\u001b[0;32m    320\u001b[0m             _wrap_data_with_container(method, data_to_wrap[\u001b[38;5;241m0\u001b[39m], X, \u001b[38;5;28mself\u001b[39m),\n\u001b[0;32m    321\u001b[0m             \u001b[38;5;241m*\u001b[39mdata_to_wrap[\u001b[38;5;241m1\u001b[39m:],\n\u001b[0;32m    322\u001b[0m         )\n",
      "File \u001b[1;32mc:\\Users\\K\\source\\repos\\AIM-PIbd-31-Ievlewa-M-D\\aimenv\\Lib\\site-packages\\sklearn\\base.py:1473\u001b[0m, in \u001b[0;36m_fit_context.<locals>.decorator.<locals>.wrapper\u001b[1;34m(estimator, *args, **kwargs)\u001b[0m\n\u001b[0;32m   1466\u001b[0m     estimator\u001b[38;5;241m.\u001b[39m_validate_params()\n\u001b[0;32m   1468\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m config_context(\n\u001b[0;32m   1469\u001b[0m     skip_parameter_validation\u001b[38;5;241m=\u001b[39m(\n\u001b[0;32m   1470\u001b[0m         prefer_skip_nested_validation \u001b[38;5;129;01mor\u001b[39;00m global_skip_validation\n\u001b[0;32m   1471\u001b[0m     )\n\u001b[0;32m   1472\u001b[0m ):\n\u001b[1;32m-> 1473\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfit_method\u001b[49m\u001b[43m(\u001b[49m\u001b[43mestimator\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[1;32mc:\\Users\\K\\source\\repos\\AIM-PIbd-31-Ievlewa-M-D\\aimenv\\Lib\\site-packages\\sklearn\\compose\\_column_transformer.py:968\u001b[0m, in \u001b[0;36mColumnTransformer.fit_transform\u001b[1;34m(self, X, y, **params)\u001b[0m\n\u001b[0;32m    965\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_validate_transformers()\n\u001b[0;32m    966\u001b[0m n_samples \u001b[38;5;241m=\u001b[39m _num_samples(X)\n\u001b[1;32m--> 968\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_validate_column_callables\u001b[49m\u001b[43m(\u001b[49m\u001b[43mX\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    969\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_validate_remainder(X)\n\u001b[0;32m    971\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m _routing_enabled():\n",
      "File \u001b[1;32mc:\\Users\\K\\source\\repos\\AIM-PIbd-31-Ievlewa-M-D\\aimenv\\Lib\\site-packages\\sklearn\\compose\\_column_transformer.py:536\u001b[0m, in \u001b[0;36mColumnTransformer._validate_column_callables\u001b[1;34m(self, X)\u001b[0m\n\u001b[0;32m    534\u001b[0m         columns \u001b[38;5;241m=\u001b[39m columns(X)\n\u001b[0;32m    535\u001b[0m     all_columns\u001b[38;5;241m.\u001b[39mappend(columns)\n\u001b[1;32m--> 536\u001b[0m     transformer_to_input_indices[name] \u001b[38;5;241m=\u001b[39m \u001b[43m_get_column_indices\u001b[49m\u001b[43m(\u001b[49m\u001b[43mX\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcolumns\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    538\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_columns \u001b[38;5;241m=\u001b[39m all_columns\n\u001b[0;32m    539\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_transformer_to_input_indices \u001b[38;5;241m=\u001b[39m transformer_to_input_indices\n",
      "File \u001b[1;32mc:\\Users\\K\\source\\repos\\AIM-PIbd-31-Ievlewa-M-D\\aimenv\\Lib\\site-packages\\sklearn\\utils\\_indexing.py:369\u001b[0m, in \u001b[0;36m_get_column_indices\u001b[1;34m(X, key)\u001b[0m\n\u001b[0;32m    366\u001b[0m         column_indices\u001b[38;5;241m.\u001b[39mappend(col_idx)\n\u001b[0;32m    368\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[1;32m--> 369\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mA given column is not a column of the dataframe\u001b[39m\u001b[38;5;124m\"\u001b[39m) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01me\u001b[39;00m\n\u001b[0;32m    371\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m column_indices\n",
      "\u001b[1;31mValueError\u001b[0m: A given column is not a column of the dataframe"
     ]
    }
   ],
   "source": [
    "from imblearn.over_sampling import ADASYN\n",
    "from sklearn.compose import ColumnTransformer\n",
    "from sklearn.preprocessing import OneHotEncoder\n",
    "\n",
    "categorical_features = ['Smoking', 'AlcoholDrinking', 'Stroke', 'DiffWalking', 'Sex', 'AgeCategory', 'Race', 'Diabetic', 'PhysicalActivity', 'GenHealth', 'Asthma', 'KidneyDisease', 'SkinCancer']  # Ваши категориальные признаки\n",
    "numeric_features = ['BMI', 'PhysicalHealth', 'MentalHealth', 'SleepTime']  # Ваши числовые признаки\n",
    "\n",
    "# Создание пайплайна для обработки категориальных данных\n",
    "preprocessor = ColumnTransformer(\n",
    "    transformers=[\n",
    "        ('cat', OneHotEncoder(), categorical_features),  # OneHotEncoder для категориальных данных\n",
    "        ('num', 'passthrough', numeric_features)  # Оставляем числовые колонки без изменений\n",
    "    ]\n",
    ")\n",
    "\n",
    "# Создание экземпляра ADASYN\n",
    "ada = ADASYN()\n",
    "\n",
    "# Преобразование данных с помощью пайплайна\n",
    "X = preprocessor.fit_transform(df_train.drop(columns=['HeartDisease']))\n",
    "y = df_train['HeartDisease']\n",
    "\n",
    "# Применение ADASYN\n",
    "X_resampled, y_resampled = ada.fit_resample(X, y)\n",
    "\n",
    "# Создание нового DataFrame\n",
    "df_train_adasyn = pd.DataFrame(X_resampled)\n",
    "# Восстанавливаем названия столбцов для DataFrame\n",
    "ohe_columns = preprocessor.named_transformers_['cat'].get_feature_names_out(categorical_features)\n",
    "new_column_names = list(ohe_columns) + numeric_features\n",
    "df_train_adasyn.columns = new_column_names\n",
    "\n",
    "# Добавление целевой переменной\n",
    "df_train_adasyn['HeartDisease'] = y_resampled\n",
    "\n",
    "# Вывод информации о новой выборке\n",
    "print(\"Обучающая выборка после oversampling: \", df_train_adasyn.shape)\n",
    "print(df_train_adasyn['HeartDisease'].value_counts())\n",
    "\n",
    "# Визуализация\n",
    "counts = df_train_adasyn['HeartDisease'].value_counts()\n",
    "plt.figure(figsize=(6, 6))\n",
    "plt.pie(counts, labels=counts.index, autopct='%1.1f%%', startangle=90)\n",
    "plt.title('Распределение классов HeartDisease в тренировочной выборке после ADASYN')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "2. Балансировка данных андерсемплингом. Этот метод помогает сбалансировать выборку, уменьшая количество экземпляров класса большинства, чтобы привести его в соответствие с классом меньшинства."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Обучающая выборка после undersampling:  (32848, 18)\n",
      "HeartDisease\n",
      "No     16424\n",
      "Yes    16424\n",
      "Name: count, dtype: int64\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from imblearn.under_sampling import RandomUnderSampler\n",
    "\n",
    "rus = RandomUnderSampler()# Создание экземпляра RandomUnderSampler\n",
    "\n",
    "# Применение RandomUnderSampler\n",
    "X_resampled, y_resampled = rus.fit_resample(df_train.drop(columns=['HeartDisease']), df_train['HeartDisease'])\n",
    "\n",
    "# Создание нового DataFrame\n",
    "df_train_undersampled = pd.DataFrame(X_resampled)\n",
    "df_train_undersampled['HeartDisease'] = y_resampled  # Добавление целевой переменной\n",
    "\n",
    "# Вывод информации о новой выборке\n",
    "print(\"Обучающая выборка после undersampling: \", df_train_undersampled.shape)\n",
    "print(df_train_undersampled['HeartDisease'].value_counts())\n",
    "\n",
    "# Визуализация распределения классов\n",
    "counts = df_train_undersampled['HeartDisease'].value_counts()\n",
    "plt.figure(figsize=(2, 2))\n",
    "plt.pie(counts, labels=counts.index, autopct='%1.1f%%', startangle=90)\n",
    "plt.title('Распределение классов HeartDisease в тренировочной выборке после Undersampling')\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "aimenv",
   "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": "3.12.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}