ArtificialInlect_Kseniy/Lab1.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Использованный датасет - Заработная плата рабочих мест в области Data Science - https://www.kaggle.com/datasets/henryshan/2023-data-scientists-salary?resource=download\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-01-19T15:08:35.210532Z",
     "start_time": "2025-01-19T15:08:34.884707Z"
    }
   },
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Загрузка данных\n",
    "file_path = 'data/Diamonds Prices2022.csv'\n",
    "data = pd.read_csv(file_path)\n",
    "\n",
    "# 1.1 Загрузка и сохранение данных\n",
    "print(\"Загруженные данные:\")\n",
    "print(data.head())\n",
    "\n",
    "# Сохранение данных в новый файл\n",
    "output_file = 'data/Diamonds_Prices2022_processed.csv'\n",
    "data.to_csv(output_file, index=False)\n",
    "print(f\"Данные сохранены в {output_file}\")\n",
    "\n",
    "# 1.2 Получение сведений о датафрейме\n",
    "print(\"\\nИнформация о датафрейме:\")\n",
    "data.info()\n",
    "\n",
    "# 1.3 Получение сведений о колонках\n",
    "print(\"\\nНазвания колонок:\", data.columns.tolist())\n",
    "\n",
    "# 1.4 Вывод отдельных строк и столбцов\n",
    "print(\"\\nВывод первых 5 строк столбца 'cut':\")\n",
    "print(data['cut'].head())\n",
    "\n",
    "print(\"\\nВывод строк с 10 по 15:\")\n",
    "print(data.iloc[10:15])\n",
    "\n",
    "# 1.5 Группировка и агрегация данных\n",
    "print(\"\\nСредняя цена по качеству огранки (cut):\")\n",
    "print(data.groupby(\"cut\")[\"price\"].mean())\n",
    "\n",
    "# 1.6 Сортировка данных\n",
    "print(\"\\nСортировка данных по цене:\")\n",
    "sorted_data = data.sort_values(by='price', ascending=False)\n",
    "print(sorted_data.head())\n",
    "\n",
    "# 1.7 Удаление строк/столбцов\n",
    "print(\"\\nУдаление столбца 'x' (если он не нужен):\")\n",
    "# Убедитесь, что столбец 'x' существует в данных\n",
    "if 'x' in data.columns:\n",
    "    data_without_x = data.drop(columns=['x'], errors='ignore')\n",
    "    print(data_without_x.head())\n",
    "else:\n",
    "    print(\"Столбец 'x' не найден в данных.\")\n",
    "\n",
    "# 1.8 Создание новых столбцов\n",
    "print(\"\\nДобавление нового столбца 'volume' (объем):\")\n",
    "# Убедитесь, что столбцы 'x', 'y' и 'z' существуют\n",
    "if {'x', 'y', 'z'}.issubset(data.columns):\n",
    "    data['volume'] = data['x'] * data['y'] * data['z']\n",
    "    print(data.head())\n",
    "else:\n",
    "    print(\"Не все столбцы для вычисления объема ('x', 'y', 'z') присутствуют в данных.\")\n",
    "\n",
    "# 1.9 Удаление строк с пустыми значениями\n",
    "print(\"\\nУдаление строк с пустыми значениями:\")\n",
    "cleaned_data = data.dropna()\n",
    "print(cleaned_data.head())\n",
    "\n",
    "# 1.10 Заполнение пустых значений медианой\n",
    "print(\"\\nЗаполнение пустых значений медианой:\")\n",
    "data_filled = data.fillna(data.median(numeric_only=True))\n",
    "print(data_filled.head())\n"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Загруженные данные:\n",
      "   Unnamed: 0  carat      cut color clarity  depth  table  price     x     y  \\\n",
      "0           1   0.23    Ideal     E     SI2   61.5   55.0    326  3.95  3.98   \n",
      "1           2   0.21  Premium     E     SI1   59.8   61.0    326  3.89  3.84   \n",
      "2           3   0.23     Good     E     VS1   56.9   65.0    327  4.05  4.07   \n",
      "3           4   0.29  Premium     I     VS2   62.4   58.0    334  4.20  4.23   \n",
      "4           5   0.31     Good     J     SI2   63.3   58.0    335  4.34  4.35   \n",
      "\n",
      "      z  \n",
      "0  2.43  \n",
      "1  2.31  \n",
      "2  2.31  \n",
      "3  2.63  \n",
      "4  2.75  \n",
      "Данные сохранены в data/Diamonds_Prices2022_processed.csv\n",
      "\n",
      "Информация о датафрейме:\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 53943 entries, 0 to 53942\n",
      "Data columns (total 11 columns):\n",
      " #   Column      Non-Null Count  Dtype  \n",
      "---  ------      --------------  -----  \n",
      " 0   Unnamed: 0  53943 non-null  int64  \n",
      " 1   carat       53943 non-null  float64\n",
      " 2   cut         53943 non-null  object \n",
      " 3   color       53943 non-null  object \n",
      " 4   clarity     53943 non-null  object \n",
      " 5   depth       53943 non-null  float64\n",
      " 6   table       53943 non-null  float64\n",
      " 7   price       53943 non-null  int64  \n",
      " 8   x           53943 non-null  float64\n",
      " 9   y           53943 non-null  float64\n",
      " 10  z           53943 non-null  float64\n",
      "dtypes: float64(6), int64(2), object(3)\n",
      "memory usage: 4.5+ MB\n",
      "\n",
      "Названия колонок: ['Unnamed: 0', 'carat', 'cut', 'color', 'clarity', 'depth', 'table', 'price', 'x', 'y', 'z']\n",
      "\n",
      "Вывод первых 5 строк столбца 'cut':\n",
      "0      Ideal\n",
      "1    Premium\n",
      "2       Good\n",
      "3    Premium\n",
      "4       Good\n",
      "Name: cut, dtype: object\n",
      "\n",
      "Вывод строк с 10 по 15:\n",
      "    Unnamed: 0  carat      cut color clarity  depth  table  price     x     y  \\\n",
      "10          11   0.30     Good     J     SI1   64.0   55.0    339  4.25  4.28   \n",
      "11          12   0.23    Ideal     J     VS1   62.8   56.0    340  3.93  3.90   \n",
      "12          13   0.22  Premium     F     SI1   60.4   61.0    342  3.88  3.84   \n",
      "13          14   0.31    Ideal     J     SI2   62.2   54.0    344  4.35  4.37   \n",
      "14          15   0.20  Premium     E     SI2   60.2   62.0    345  3.79  3.75   \n",
      "\n",
      "       z  \n",
      "10  2.73  \n",
      "11  2.46  \n",
      "12  2.33  \n",
      "13  2.71  \n",
      "14  2.27  \n",
      "\n",
      "Средняя цена по качеству огранки (cut):\n",
      "cut\n",
      "Fair         4358.757764\n",
      "Good         3928.864452\n",
      "Ideal        3457.541970\n",
      "Premium      4583.992605\n",
      "Very Good    3981.658529\n",
      "Name: price, dtype: float64\n",
      "\n",
      "Сортировка данных по цене:\n",
      "       Unnamed: 0  carat        cut color clarity  depth  table  price     x  \\\n",
      "27749       27750   2.29    Premium     I     VS2   60.8   60.0  18823  8.50   \n",
      "27748       27749   2.00  Very Good     G     SI1   63.5   56.0  18818  7.90   \n",
      "27747       27748   1.51      Ideal     G      IF   61.7   55.0  18806  7.37   \n",
      "27746       27747   2.07      Ideal     G     SI2   62.5   55.0  18804  8.20   \n",
      "27745       27746   2.00  Very Good     H     SI1   62.8   57.0  18803  7.95   \n",
      "\n",
      "          y     z  \n",
      "27749  8.47  5.16  \n",
      "27748  7.97  5.04  \n",
      "27747  7.41  4.56  \n",
      "27746  8.13  5.11  \n",
      "27745  8.00  5.01  \n",
      "\n",
      "Удаление столбца 'x' (если он не нужен):\n",
      "   Unnamed: 0  carat      cut color clarity  depth  table  price     y     z\n",
      "0           1   0.23    Ideal     E     SI2   61.5   55.0    326  3.98  2.43\n",
      "1           2   0.21  Premium     E     SI1   59.8   61.0    326  3.84  2.31\n",
      "2           3   0.23     Good     E     VS1   56.9   65.0    327  4.07  2.31\n",
      "3           4   0.29  Premium     I     VS2   62.4   58.0    334  4.23  2.63\n",
      "4           5   0.31     Good     J     SI2   63.3   58.0    335  4.35  2.75\n",
      "\n",
      "Добавление нового столбца 'volume' (объем):\n",
      "   Unnamed: 0  carat      cut color clarity  depth  table  price     x     y  \\\n",
      "0           1   0.23    Ideal     E     SI2   61.5   55.0    326  3.95  3.98   \n",
      "1           2   0.21  Premium     E     SI1   59.8   61.0    326  3.89  3.84   \n",
      "2           3   0.23     Good     E     VS1   56.9   65.0    327  4.05  4.07   \n",
      "3           4   0.29  Premium     I     VS2   62.4   58.0    334  4.20  4.23   \n",
      "4           5   0.31     Good     J     SI2   63.3   58.0    335  4.34  4.35   \n",
      "\n",
      "      z     volume  \n",
      "0  2.43  38.202030  \n",
      "1  2.31  34.505856  \n",
      "2  2.31  38.076885  \n",
      "3  2.63  46.724580  \n",
      "4  2.75  51.917250  \n",
      "\n",
      "Удаление строк с пустыми значениями:\n",
      "   Unnamed: 0  carat      cut color clarity  depth  table  price     x     y  \\\n",
      "0           1   0.23    Ideal     E     SI2   61.5   55.0    326  3.95  3.98   \n",
      "1           2   0.21  Premium     E     SI1   59.8   61.0    326  3.89  3.84   \n",
      "2           3   0.23     Good     E     VS1   56.9   65.0    327  4.05  4.07   \n",
      "3           4   0.29  Premium     I     VS2   62.4   58.0    334  4.20  4.23   \n",
      "4           5   0.31     Good     J     SI2   63.3   58.0    335  4.34  4.35   \n",
      "\n",
      "      z     volume  \n",
      "0  2.43  38.202030  \n",
      "1  2.31  34.505856  \n",
      "2  2.31  38.076885  \n",
      "3  2.63  46.724580  \n",
      "4  2.75  51.917250  \n",
      "\n",
      "Заполнение пустых значений медианой:\n",
      "   Unnamed: 0  carat      cut color clarity  depth  table  price     x     y  \\\n",
      "0           1   0.23    Ideal     E     SI2   61.5   55.0    326  3.95  3.98   \n",
      "1           2   0.21  Premium     E     SI1   59.8   61.0    326  3.89  3.84   \n",
      "2           3   0.23     Good     E     VS1   56.9   65.0    327  4.05  4.07   \n",
      "3           4   0.29  Premium     I     VS2   62.4   58.0    334  4.20  4.23   \n",
      "4           5   0.31     Good     J     SI2   63.3   58.0    335  4.34  4.35   \n",
      "\n",
      "      z     volume  \n",
      "0  2.43  38.202030  \n",
      "1  2.31  34.505856  \n",
      "2  2.31  38.076885  \n",
      "3  2.63  46.724580  \n",
      "4  2.75  51.917250  \n"
     ]
    }
   ],
   "execution_count": 2
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-01-19T15:10:00.237216Z",
     "start_time": "2025-01-19T15:09:59.598088Z"
    }
   },
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Загрузка данных\n",
    "file_path = 'data/Diamonds Prices2022.csv'\n",
    "data = pd.read_csv(file_path)\n",
    "\n",
    "# 2.1 Линейная диаграмма (Средняя цена по качеству огранки)\n",
    "plt.figure(figsize=(10, 5))\n",
    "data.groupby(\"cut\")[\"price\"].mean().plot(\n",
    "    kind=\"line\", title=\"Средняя цена по качеству огранки\"\n",
    ")\n",
    "plt.ylabel(\"Средняя цена\")\n",
    "plt.show()\n",
    "\n",
    "# 2.2 Столбчатая диаграмма (Количество бриллиантов по качеству огранки)\n",
    "plt.figure(figsize=(10, 5))\n",
    "data[\"cut\"].value_counts().plot(\n",
    "    kind=\"bar\", title=\"Количество бриллиантов по качеству огранки\"\n",
    ")\n",
    "plt.ylabel(\"Количество бриллиантов\")\n",
    "plt.show()\n",
    "\n",
    "# 2.3 Гистограмма (Распределение цен)\n",
    "plt.figure(figsize=(10, 5))\n",
    "data[\"price\"].plot(kind=\"hist\", bins=20, title=\"Распределение цен на бриллианты\")\n",
    "plt.xlabel(\"Цена\")\n",
    "plt.show()\n",
    "\n",
    "# 2.4 Ящик с усами (Распределение цен по качеству огранки)\n",
    "plt.figure(figsize=(10, 5))\n",
    "data.boxplot(column=\"price\", by=\"cut\", grid=False, rot=90)\n",
    "plt.title(\"Распределение цен по качеству огранки\")\n",
    "plt.suptitle(\"\")\n",
    "plt.ylabel(\"Цена\")\n",
    "plt.show()\n",
    "\n",
    "# 2.5 Диаграмма с областями (Средняя цена по качеству огранки)\n",
    "plt.figure(figsize=(10, 5))\n",
    "data.groupby(\"cut\")[\"price\"].mean().plot(\n",
    "    kind=\"area\", title=\"Средняя цена по качеству огранки\"\n",
    ")\n",
    "plt.ylabel(\"Средняя цена\")\n",
    "plt.show()\n",
    "\n",
    "# 2.6 Диаграмма рассеяния (Цена vs. Объем)\n",
    "plt.figure(figsize=(10, 5))\n",
    "plt.scatter(data['price'], data['volume'], alpha=0.5)\n",
    "plt.title('Диаграмма рассеяния: Цена vs Объем')\n",
    "plt.xlabel('Цена')\n",
    "plt.ylabel('Объем (x * y * z)')\n",
    "plt.show()\n",
    "\n",
    "# 2.7 Круговая диаграмма (Распределение огранок)\n",
    "plt.figure(figsize=(10, 5))\n",
    "data[\"cut\"].value_counts().plot(\n",
    "    kind=\"pie\", title=\"Распределение огранок\", autopct=\"%1.1f%%\"\n",
    ")\n",
    "plt.ylabel(\"\")\n",
    "plt.show()\n"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ],
      "image/png": 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oYsGCBTAxMdEWxBX5WSv+XNSoUQPfffcd1q5di7179z513IYNGxAdHf3UrJpEZHjY4SIig1GvXj2sX78e77zzDho3boyhQ4fCw8MD+fn5OHnyJDZv3vzUGjceHh7o1q1biWnhAeDLL7/UHvPtt9/i0KFD8PX1xejRo+Hu7o6UlBScOXMG+/fvR0pKCgBg48aN+O9//wuVSoWcnBysXbtWe460tDSo1Wrs2LEDffr0KfO1rVixAtu3b8ehQ4dgY2Pzysc9j1qtxu7du0tsK+64hYeHw9nZGW5ubhgyZAg2bdqEcePG4dChQ/D394darcbly5exadMm7NmzBz4+PmV67cDAQPz000/o3r07Bg4ciOTkZCxcuBBubm6Ijo4u87U8T/Xq1TF9+nR8+eWX6N69O3r16oXY2FgsWrQILVu2LPNtcIIgYPny5WjWrBm++OILfP/99wCKOkG//vorbGxs4O7ujtDQUOzfvx92dnYvlbu0n8OhQ4fil19+wbRp0xAeHo62bdsiKysL+/fvx3vvvfdSvwzYsWMHqlWrpr2l8NixY89cDmHo0KH473//CwClfh+//vpr7Nu3DwEBAXjvvfegUCiwdOlS5OXlad/LsjA1NcXu3bsxbNgw+Pr64q+//kJISAg+/vhjbde6sj5rY8aMwfr16zFu3DicP3++xLjOvXv3YvTo0c8cv0ZEBkai2RGJiCrMlStXxNGjR4t16tQRlUqlaGVlJfr7+4vz588Xc3Nztcfh8XTPa9euFevXry+qVCqxefPmJaY/L5aUlCQGBweLLi4uoomJiejo6Ch27txZXLZsmfaY2rVra6eaf97jyWmkSzuN+dWrV0ULCwtx+vTpJY775zTZpT3ueYqn1P63x5PTlOfn54vfffed2KRJE1GlUolVq1YVW7RoIX755ZdiWlraU+/zPz1rWvgVK1Zo/y4aNWokrlq16l+nLX9SWabZF8WiaeAbNWokmpiYiA4ODuL48ePFR48evfB1npfnyy+/FBUKhXjmzBlRFEXx0aNH4ogRI8Rq1aqJlpaWYrdu3cTLly+LtWvXLtXU3/98v0WxdJ9DUSya8vyTTz4RXV1dtce99dZbJaZef9H1iOLfn53ih1KpFN3c3MTPP/+8xPdSsXv37olyuVxs0KDBC6/vSWfOnBG7desmWlpaiubm5mLHjh3FkydPPjPLi6aFt7CwEK9fvy527dpVNDc3Fx0cHMQvvviixJT1olj6z1ppP7/Pmu5dFEUxNjZWNDU1FadOnVriODMzM/Hu3bslji3tZ4OI9IsgiuV0fwERkZ4RBAHBwcHPvPXqZdSpUwczZsx4qotW7PDhwxg+fHiJW6f0SYcOHdChQwfMmDFD6iikox48eAAnJyd8/vnn+Oyzzyr99YcPH44tW7ZUyMycREQvi2O4iIiIqFysXr0aarUaQ4YMkToKEZHO4BguIqJy0rdvX9SrV++5+x0cHNC3b99KTFS+WrVqBTc3N6ljkA46ePAgLl68iG+++QZ9+vTRzgZIREQAbykkIqNV3rcUEhmrDh064OTJk/D398fatWtRs2ZNSXLwlkIi0kUsuIiIiIiIiCoIx3ARERERERFVEBZcREREREREFYSTZpSCRqNBQkICrKysIAiC1HGIiIiIiEgioigiIyMDNWrUgEz24v4VC65SSEhIgIuLi9QxiIiIiIhIR8THx8PZ2fmFx7HgKgUrKysARW+qtbW1xGmIiIiIiEgq6enpcHFx0dYIL8KCqxSKbyO0trZmwUVERERERKUeasRJM4iIiIiIiCoICy4iIiIiIqIKwoKLiIiIiIiogrDgIiIiIiIiqiAsuIiIiIiIiCqIzhRc3377LQRBwJQpU0psDw0NRadOnWBhYQFra2u0a9cOOTk52v0pKSkYNGgQrK2tUaVKFQQFBSEzM7PEOaKjo9G2bVuYmprCxcUF33//fWVcEhERERERGTmdKLgiIiKwdOlSeHl5ldgeGhqK7t27o2vXrggPD0dERAQmTJhQYkXnQYMG4cKFC9i3bx927dqFo0ePYsyYMdr96enp6Nq1K2rXro3IyEj88MMPmDFjBpYtW1Zp10dERERERMZJEEVRlDJAZmYmvL29sWjRInz99ddo1qwZ5syZAwBo3bo1XnvtNXz11VfPfO6lS5fg7u6OiIgI+Pj4AAB2796NHj164M6dO6hRowYWL16MTz75BImJiVAqlQCAjz76CDt27MDly5dLlTE9PR02NjZIS0vjOlxEREREREasrLWB5B2u4OBgBAYGokuXLiW2JycnIywsDPb29mjTpg0cHBzQvn17HD9+XHtMaGgoqlSpoi22AKBLly6QyWQICwvTHtOuXTttsQUA3bp1Q2xsLB49evTMTHl5eUhPTy/xICIiIiIiKitJC64NGzbgzJkzmDVr1lP7bty4AQCYMWMGRo8ejd27d8Pb2xudO3fG1atXAQCJiYmwt7cv8TyFQgFbW1skJiZqj3FwcChxTPHXxcf806xZs2BjY6N9uLi4vNqFEhERERGRUZKs4IqPj8fkyZOxbt06mJqaPrVfo9EAAMaOHYsRI0agefPmmD17Nho2bIiVK1dWaLbp06cjLS1N+4iPj6/Q1yMiIiIiIsOkkOqFIyMjkZycDG9vb+02tVqNo0ePYsGCBYiNjQUAuLu7l3he48aNcfv2bQCAo6MjkpOTS+wvLCxESkoKHB0dtcckJSWVOKb46+Jj/kmlUkGlUr3C1REREREREUnY4ercuTNiYmIQFRWlffj4+GDQoEGIiopC3bp1UaNGDW3hVezKlSuoXbs2AMDPzw+pqamIjIzU7j948CA0Gg18fX21xxw9ehQFBQXaY/bt24eGDRuiatWqlXClRERERERkrCTrcFlZWcHDw6PENgsLC9jZ2Wm3v//++/jiiy/QtGlTNGvWDGvWrMHly5exZcsWAEXdru7du2P06NFYsmQJCgoKMGHCBAwYMAA1atQAAAwcOBBffvklgoKC8OGHH+L8+fOYO3cuZs+eXbkXTERERCQRURTxdcglPMrOxzd9PGGmlEsdichoSFZwlcaUKVOQm5uLqVOnIiUlBU2bNsW+fftQr1497THr1q3DhAkT0LlzZ8hkMvTr1w/z5s3T7rexscHevXsRHByMFi1aoFq1avj8889LrNVFREREZMiOX3uAFcfjAAApWflYNsQHSoXkk1UTGQXJ1+HSB1yHi4iIiPSVKIrot/gkztxO1W4L9HTCvHebQy4TpAtGpKf0bh0uIiIiIqo4R68+wJnbqVApZPi/t5vCRC4gJOYePt4WA/7enajiseAiIiIiMlCiKGL2visAgMGta+OtFs6YN6A5ZAKw8XQ8vg65xKKLqIKx4CIiIiIyUEeu3EdUfCpMTWQY274uAOB1Tyd8/1ZTAMCK43GYe+CqlBGJDB4LLiIiIiIDJIoiZu8vKqYG+9aGvZWpdt9bLZwx442itU7n7L+qnVCDiMofCy4iIiIiA3Q49j7Oabtb9Z7aP9zfFf95rQEA4KtdF7EpIr6yIxIZBRZcRERERAamqLtVNHZrqF8dVLdSPfO4CZ3cMLqtKwDgo23RCIm+V2kZiYwFCy4iIiIiA3PwcjKi76TBzESOMe3qPvc4QRDwcY/GeLeVCzQiMGXjWRyKTa7EpESGjwUXERERkQERRRFzHo/dGtqmNqpZPru7VUwQBHzdxxM9vZxQoBYxfm0kwuNSKiMqkVFgwUVERERkQA5cSkbM3TSYK+UY0/b53a0nyWUCZr/TDJ0a2SO3QIORqyMQcyetgpMSGQcWXEREREQGQhRFzDnw99gtuxd0t55kIpdh0SBvtK5ri8y8QgxdGYarSRkVFZXIaLDgIiIiIjIQ+y4m4fzddFgo/33s1vOYmsixfFhLNHW2waPsAgxeEYb4lOwKSEpkPFhwERERERmAJ8duDWtTB7YWypc6j6VKgdUjWqGhgxWS0vMwaHkYktJzyzMqkVFhwUVERERkAPZcSMLFe+mwVCkwupRjt56nqoUSvwa1Qm07c9xOycbg5WFIycovp6RExoUFFxEREZGe02hEzHm87tbwNnVQ9SW7W0+ytzbF2iBfOFqb4mpyJoatDEdGbsErn5fI2LDgIiIiItJzey8m4nJiBixVCox6vJBxeXCxNcfaUb6wtVAi5m4agtacRk6+utzOT2QMWHARERER6bGi7lbR2K0R/nVQxfzVu1tPcrO3xC8jW8FKpUB4XArGr4tEfqGmXF+DyJCx4CIiIiLSY7svFHW3rFQKjAp4tbFbz+NR0wYrR7SEqYkMh2PvY+rGKKg1YoW8FpGhYcFFREREpKc0GhFzi7tbAa6wMTepsNdqWccWS4f4wEQuICTmHj7eFgNRZNFF9CIsuIiIiIj01J/n7yE2KQNWpgoEBZTf2K3nad+gOuYNaA6ZAGw8HY+vQy6x6CJ6ARZcRERERHroye5WUIArbMwqrrv1pNc9nfBdPy8AwIrjcZh74GqlvC6RvmLBRURERKSHQmLu4WpyJqxNFRjhX/HdrSe97eOCL95wBwDM2X8VK47HVerrE+kTFlxEREREekatEbWdpaCAupXW3XrSCH9XTHutAQDgq10XsSkivtIzEOkDFlxEREREemZXdAKuFXe3AupIlmNiJzeMfrzu10fbohESfU+yLES6igUXERERkR5Ra0TMe9zdGt22LqxNK7+7VUwQBHzcozHebeUCjQhM2XgWh2OTJctDpItYcBERERHpkT/OJeD6/SxUMTfBcP86UseBIAj4uo8neno5oUAtYtzaSITHpUgdi0hnsOAiIiIi0hP/7G5ZSdjdepJcJmD2O83QqZE9cgs0GLk6AjF30qSORaQTWHARERER6Ymd5+7ixoOi7tawNnWkjlOCiVyGRYO80bquLTLzCjF0ZRiuJmVIHYtIciy4iIiIiPRAoVqDeQeuASjqblmqFBInepqpiRzLh7VEU2cbPMouwOAVYYhPyZY6FpGkWHARERER6YHfoxIQ9yALVXWwu/UkS5UCq0e0QkMHKySl52HQ8jAkpedKHYtIMiy4iIiIiHRcoVqD+QeLxm6NaVdPJ7tbT6pqocSvQa1Q284ct1OyMXh5GFKy8qWORSQJFlxEREREOm772bu4+TAbthZKDPWrLXWcUrG3NsXaIF84WpvianImhq0MR0ZugdSxiCodCy4iIiIiHVao1mDBoaKxW2Pb1YWFjne3nuRia461o1rB1kKJmLtpCFpzGjn5aqljEVUqFlxEREREOmzb2bu49TAbdhZKDNGT7taT3Oyt8MvIVrBSKRAel4Lx6yKRX6iROhZRpWHBRURERKSjCp4YuzW2fV2YK/Wnu/Ukj5o2WDmiJUxNZDgcex9TN0ZBrRGljkVUKVhwEREREemobWfuID4lB9UslRjcWv+6W09qWccWS4f4wEQuICTmHj7eFgNRZNFFho8FFxEREZEOyi/UYP7BorFb49rX09vu1pPaN6iOeQOaQyYAG0/H4+uQSyy6yOCx4CIiIiLSQVvP3MGdRzmoZqnCIF/97m496XVPJ3zXzwsAsOJ4HOYeuCpxIqKKxYKLiIiISMfkF2qw4HF3a3yHejBTyiVOVL7e9nHBF2+4AwDm7L+KFcfjJE5EVHFYcBERERHpmC2Rd3A3NQfVrVQY5FtL6jgVYoS/K6a91gAA8NWui9gUES9xIqKKwYKLiIiISIfkF2qw8PG6W+Pb14OpiWF1t540sZMbRrd1BQB8tC0aIdH3JE5EVP5YcBERERHpkE2n43E3NQf2VioMNNDuVjFBEPBxj8Z4t5ULNCIwZeNZHI5NljoWUbliwUVERESkI/IK1dru1nsdDLu7VUwQBHzdxxM9vZxQoBYxbm0kwuNSpI5FVG5YcBERERHpiE0R8biXlgtHa1MMaGXY3a0nyWUCZr/TDJ0a2SO3QIORqyMQcydN6lhE5YIFFxEREZEOKOpuXQcAvNfROLpbTzKRy7BokDda17VFZl4hhq4Mw9WkDKljEb0yFlxEREREOmBjRDwS04u6W++0dJE6jiRMTeRYPqwlmjrb4FF2AQavCEN8SrbUsYheCQsuIiIiIonlFvw9diu4Yz2oFMbV3XqSpUqB1SNaoYGDJZLS8zBoeRiS0nOljkX00lhwEREREUlsQ/htJKXnoYaNKfobaXfrSVUtlFgb5Itatua4nZKNwcvDkJKVL3UsopfCgouIiIhIQrkFaiw6XDx2y82ou1tPsrc2xbpRvnC0NsXV5EwMWxmOjNwCqWMRlRkLLiIiIiIJrQ+7jeSMPNSsYob+PuxuPcnF1hxrR7WCrYUSMXfTELTmNHLy1VLHIioTFlxEREREEsktUGPxkaLuVnBHNygV/NHsn9zsrfDLyFawUikQHpeC8esikV+okToWUanxu5qIiIhIIuvCbuP+4+7WWy2cpY6jszxq2mDliJYwNZHhcOx9TN0YBbVGlDoWUamw4CIiIiKSQE6+Gosfj92a0IndrRdpWccWS4f4wEQuICTmHj7eFgNRZNFFuk9nvrO//fZbCIKAKVOmPLVPFEW8/vrrEAQBO3bsKLHv9u3bCAwMhLm5Oezt7fH++++jsLCwxDGHDx+Gt7c3VCoV3NzcsHr16oq7ECIiIqJSWBd2Cw8y8+Bcld2t0mrfoDrmDWgOmQBsPB2Pr0MuseginacTBVdERASWLl0KLy+vZ+6fM2cOBEF4artarUZgYCDy8/Nx8uRJrFmzBqtXr8bnn3+uPSYuLg6BgYHo2LEjoqKiMGXKFIwaNQp79uypsOshIiIi+jfZ+YVY8njs1sRObjCR68SPZHrhdU8nfNev6GfGFcfjMO/ANYkTEf07yb+7MzMzMWjQIPz888+oWrXqU/ujoqLw448/YuXKlU/t27t3Ly5evIi1a9eiWbNmeP311/HVV19h4cKFyM8vWqthyZIlcHV1xY8//ojGjRtjwoQJeOuttzB79uznZsrLy0N6enqJBxEREVF5WXvqFh5k5qOWrTne9GZ3q6ze9nHBF2+4AwBm77+ClcfjJE5E9HySF1zBwcEIDAxEly5dntqXnZ2NgQMHYuHChXB0dHxqf2hoKDw9PeHg4KDd1q1bN6Snp+PChQvaY/557m7duiE0NPS5mWbNmgUbGxvtw8WFU7QSERFR+cjOL8TSIzcAFI3dYnfr5Yzwd8W01xoAAGbuuohNEfESJyJ6Nkm/wzds2IAzZ85g1qxZz9w/depUtGnTBr17937m/sTExBLFFgDt14mJif96THp6OnJycp553unTpyMtLU37iI/nNzARERGVj19Db+FhVj5q25njzeY1pY6j1yZ2csPotq4AgI+2RSMk+p7EiYieppDqhePj4zF58mTs27cPpqamT+3fuXMnDh48iLNnz1Z6NpVKBZVKVemvS0RERIYtK68QS48+7m51dIOC3a1XIggCPu7RGJl5hfgtPB5TNp6FhUqODg3tpY5GpCXZd3lkZCSSk5Ph7e0NhUIBhUKBI0eOYN68eVAoFNi3bx+uX7+OKlWqaPcDQL9+/dChQwcAgKOjI5KSkkqct/jr4lsQn3eMtbU1zMzMKvgqiYiIiP72S+gtpGTlo46dOfqyu1UuBEHA13080dPLCQVqEePWRiI8LkXqWERaknW4OnfujJiYmBLbRowYgUaNGuHDDz9EtWrVMHbs2BL7PT09MXv2bLzxxhsAAD8/P3zzzTdITk6GvX3RbzL27dsHa2truLu7a4/5888/S5xn37598PPzq6hLIyIiInpKZl4hlh0tnpmwPrtb5UguEzD7nWbIzlfj4OVkjFwdgd9Gt4ans43U0YikK7isrKzg4eFRYpuFhQXs7Oy02581UUatWrXg6lp0r27Xrl3h7u6OIUOG4Pvvv0diYiI+/fRTBAcHa28JHDduHBYsWIAPPvgAI0eOxMGDB7Fp0yaEhIRU8BUSERER/W3NyZt4lF0A12oW6N2shtRxDI6JXIZFg7wxbGU4wuJSMHRlGDaN9UN9Byupo5GR0+tfrcjlcuzatQtyuRx+fn4YPHgwhg4dipkzZ2qPcXV1RUhICPbt24emTZvixx9/xPLly9GtWzcJkxMREZExycwrxM/HisZuTerMsVsVxdREjuXDfNDU2QaPsgsweEUY4lOypY5FRk4QuTz3C6Wnp8PGxgZpaWmwtraWOg4RERHpmYWHruGHPbGoW80C+6a1h1wmSB3JoD3Kysc7y0JxJSkTtWzNsXmcHxysn56kjehllLU24K9XiIiIiCpQRm4Blh0t7m7VZ7FVCapaKLE2yBe1bM1xOyUbg5eHISUrX+pYZKRYcBERERFVoNUnbiItpwD1qlvgjaYcu1VZ7K1NsW6ULxytTXE1ORPDVoYjI7dA6lhkhFhwEREREVWQ9NyCJ8ZusbtV2VxszbF2VCvYWigRczcNQWtOIydfLXUsMjIsuPRQajZb4kRERPpg1fGbSM8thJu9JXp6sbslBTd7K/wyshWsVAqEx6Vg/LpI5BdqpI5FRoQFl565mJCOgO8OYfmxG+B8J0RERLorLacAK44Xdbcms7slKY+aNlg5oiVMTWQ4HHsfUzdFQa3hz1FUOVhw6Znfz91FZl4hvg65hLG/RiIth/ciExER6aJVJ+KQnluI+vaWCPR0kjqO0WtZxxZLh/jARC4gJPoePtkew19eU6VgwaVnPureCF/1bgKlXIa9F5PQc/4xxNxJkzoWERERPaGouxUHAJjcpT5k7G7phPYNqmPegOaQCcCGiHh8E3KJRRdVOBZcekYQBAzxq4Mt4/3gXNUM8Sk56Lf4JH49dYv/YBAREemIFcfjkJFbiIYOVujhwe6WLnnd0wnf9fMCACw/Hod5B65JnIgMHQsuPeXlXAUhE9viNXcH5Ks1+GzHeUzaEIXMvEKpoxERERm1tOwCrGJ3S6e97eOCL95wBwDM3n8FKx//fRFVBBZceszG3ATLhrTAp4GNoZAJ+ONcAnrNP47LielSRyMiIjJay4/fQEZeIRo5WqF7E0ep49BzjPB3xbTXGgAAZu66iE0R8RInIkPFgkvPCYKAUW3rYuPY1nCyMcWNB1nos/AENp/mPxpERESVLTU7H6tO3AQATGF3S+dN7OSGUQGuAICPtkUjJPqexInIELHgMhAtatsiZFJbtGtQHbkFGry/JRrvbz7Hxf2IiIgq0fJjccjMK0RjJ2t0dWd3S9cJgoBPAhtjQEsXaERgysazOBybLHUsMjAsuAyIrYUSq4e3xH+7NoBMADZH3kGfhSdw/X6m1NGIiIgM3qOsfKw68XjsVmd2t/SFIAj4pq8neno5oUAtYtzaSITHpUgdiwwICy4DI5MJmNCpPtaO8kU1SxVikzLQa/5x7DyXIHU0IiIig/bzsRvIylfD3cka3Zo4SB2HykAuE/BT/2bo2LDoTqGRqyO47A6VGxZcBqpNvWr4c3IAWte1RVa+GpN+O4tPd8Qgt4C3GBIREZW3lKx8rDl5E0DR2C1BYHdL3ygVMiwe3AK+rrbIzCvE0JVhuJqUIXUsMgAsuAyYvZUp1gb5YmInNwDA2lO38daSk7j9MFviZERERIZl2dGi7pZHTWu85s7ulr4yNZFj+TAfNHW2waPsAgxeEYb4FP7cRK+GBZeBU8hl+E/Xhlg9oiWqmpvg/N10BM4/hj0XEqWORkREZBAeZubhl9CbAIApnRuwu6XnrExNsHpEKzRwsERSeh4GLQ9DUnqu1LFIj7HgMhIdGtojZFJbeNeqgozcQoz9NRJf77qIArVG6mhERER6bdmxG8jOV8Ozpg06N7aXOg6Vg6oWSqwN8kUtW3PcTsnG4OVhSMnKlzoW6SkWXEakRhUzbBzrh9Fti9abWH48Du8sDUVCao7EyYiIiPTTg8w8/HLyFgCO3TI09tamWDfKF47WprianIlhK8ORkVsgdSzSQyy4jIyJXIZPAt2xdEgLWJkqcOZ2KgLnHcMhrjlBRERUZsuO3kBOgRpNnW3QqRG7W4bGxdYca0e1gq2FEjF30xC05jQnIKMyY8FlpLo1cUTIxLbwrFk0KHTEqgj8355YFPIWQyIiolK5n/HE2K0uHLtlqNzsrfDLyFawUikQHpeC8WsjkV/In5eo9FhwGbFadubYMt4PQ1rXBgAsOHQNg1eEIZkDQ4mIiF5o6ZHryC3QoJlLFXRoWF3qOFSBPGraYOWIljA1keFQ7H1M3RQFtUaUOhbpCRZcRk6lkOOrPh6Y925zWCjlOHUjBT3mHcfJ6w+kjkZERKSzkjNysTaMY7eMScs6tlg6xAcmcgEh0ffwyfYYiCKLLnoxFlwEAOjVtAZ2TgxAI0crPMjMw+DlYZh/4Co0/O0NERHRU5YeuYHcAg2a16qC9g3Y3TIW7RtUx9wBzSETgA0R8fgm5BKLLnohFlykVa+6Jba/54/+Ps7QiMCP+65g+OoIPMzMkzoaERGRzkhOz8XaU8XdLY7dMjY9PJ3wbT8vAEUzPs87cE3iRKTrWHBRCWZKOb5/qyl+eMsLpiYyHL1yH4HzjuP0zRSpoxEREemExUeuI69QA+9aVdCufjWp45AE+vu44POe7gCA2fuvYOXxOIkTkS5jwUXP9LaPC3YE+6NudQskpufinWWnsOzodbbNiYjIqCWl52Jd2G0AwNTX2N0yZiMDXDG1SwMAwMxdF7EpIl7iRKSrWHDRczVytMbOCQHo1bQG1BoR//vzMkb/Eom0bC76R0RExmnx4evIL9TAp3ZVBLixu2XsJnV2w6gAVwDAR9uiERJ9T+JEpItYcNG/slQpMHdAM3zdxwNKuQz7LyUhcP4xRN9JlToaERFRpUpMy8X6cHa36G+CIOCTwMYY0NIFGhGYsvEsDscmSx2LdAwLLnohQRAwuHVtbHuvDWrZmuPOoxy8tTgUv4Te5C2GRERkNBYfvob8Qg1a1bFFm3p2UschHSEIAr7p64meXk4oUIsYtzYS4XEc+05/Y8FFpeZR0wZ/TAxAtyYOyFdr8PnvFzDht7PIyOUthkREZNjupeXgt/CiMTpcd4v+SS4T8FP/ZujYsDpyCzQYuToCMXfSpI5FOoIFF5WJjZkJlgxugc96ukMhK1r4r9eCE7h0L13qaERERBVm0aHryFdr0MrVFn7sbtEzKBUyLB7cAr6utsjMK8TQlWG4mpQhdSzSASy4qMwEQUBQgCs2jvWDk40p4h5koc/CE9gUEc9bDImIyOAkpOZg4+MZ6KZy3S36F6Ymciwf5oOmzjZ4lF2AwSvCEJ+SLXUskhgLLnppLWpXRciktujQsDryCjX4YGs0/rs5Gtn5hVJHIyIiKjcLD11DvlqD1nXZ3aIXszI1weoRrdDAwRJJ6XkYtDwMSem5UsciCbHgoldia6HEymEt8X63hpAJwNYzd9Bn4QlcS2YLnYiI9N/d1BxsOl08dquBxGlIX1S1UGJtkC9q2Zrjdko2Bi8PQ0pWvtSxSCIsuOiVyWQCgju6Yf3o1qhupcKVpEz0WnACv0fdlToaERHRK1l46BoK1CL86tqhdV12t6j07K1NsW6ULxytTXE1ORPDV4VzojEjxYKLyk3runb4c1JbtKlnh+x8NSZviMLH22OQW6CWOhoREVGZ3XmUjc2Pu1tTX2N3i8rOxdYca0e1gq2FEtF30hC05jR/LjJCLLioXFW3UuHXIF9M6uQGQQDWh91Gv8UncethltTRiIiIyqS4u+XvZodWrrZSxyE95WZvhV9GtoKVSoHwuBSMXxuJ/EKN1LGoErHgonInlwmY1rUhVo8o+o3OhYR09Jx3HLvP35M6GhERUanEp2Rj8+k7AIpmJiR6FR41bbBieEuYmshwKPY+pm6KglrDmZ2NBQsuqjDtG1RHyKQA+NSuioy8QoxbewYz/7jI3+oQEZHOW3joGgo1ItrWrwafOuxu0atr5WqLJYNbwERetI7pJ9tjuJyOkWDBRRXKycYMv41pjbHt6gIAVp6IQ/+lobibmiNxMiIiomeLT8nGlsii7taULvUlTkOGpENDe8wd0BwyAdgQEY9vQi6x6DICLLiowpnIZZjeozF+HuoDa1MFouJTETjvGA5eTpI6GhER0VPmH7yq7W61qM3uFpWvHp5O+LafFwBg+fE4zDtwTeJEVNFYcFGlec3dASGT2sLL2Qap2QUYufo0vtt9GYVq3mJIRES64dbDLGw9U7SsCWcmpIrS38cFn/d0BwDM3n8FK4/HSZyIKhILLqpULrbm2DzOD8Pb1AEALD58HQO5AjsREemI+QevQa0R0b5BdXjXqip1HDJgIwNctROyzNx1EZsi4iVORBWFBRdVOpVCjhm9mmDBwOawfDxFauC8Yzhx7YHU0YiIyIjdfJCF7WfZ3aLKM6mzG0YFuAIAPtoWjZBozuhsiFhwkWR6etXAzgn+aORohQeZ+Ri8Igxz91/lNKlERCSJ4u5Wx4bV0cylitRxyAgIgoBPAhtjQEsXaERgysazOBybLHUsKmcsuEhSdatbYkewPwa0dIEoFt3HPHxVOB5k5kkdjYiIjEjcgyxsP1s8MyG7W1R5BEHAN3090dPLCQVqEePWRiI8LkXqWFSOWHCR5ExN5Pi2nxd+fLspzEzkOHb1AQLnHeM/NkREVGnmH7gKjQh0amSPpuxuUSWTywT81L8ZOjasjtwCDUaujkDMnTSpY1E5YcFFOqNfC2f8PsEfbvaWSErPw7s/n8KSI9eh4S2GRERUga7fz8SOqKKxW1x3i6SiVMiweHAL+LraIjOvEENXhuFqUobUsagcsOAindLAwQq/B/ujT7MaUGtEfPvXZYz59TRSs/OljkZERAaquLvVpbE9vJyrSB2HjJipiRzLh/mgqbMNHmUXYPCKMMSnZEsdi14RCy7SORYqBWa/0wz/6+sJpUKG/ZeSETjvOKLiU6WORkREBuZaciZ2nksAwLFbpBusTE2wekQrNHAouuNnEJfP0Xs6U3B9++23EAQBU6ZMAQCkpKRg4sSJaNiwIczMzFCrVi1MmjQJaWkl72e9ffs2AgMDYW5uDnt7e7z//vsoLCwscczhw4fh7e0NlUoFNzc3rF69upKuil6WIAgY6FsL28a3QW07c9xNzcHbS05i9Yk4iCJvMSQiovIx/2BRd+s1dwd41LSROg4RAKCqhRK/Bvmilq05bqdkY8iKMDzK4t0++konCq6IiAgsXboUXl5e2m0JCQlISEjA//3f/+H8+fNYvXo1du/ejaCgIO0xarUagYGByM/Px8mTJ7FmzRqsXr0an3/+ufaYuLg4BAYGomPHjoiKisKUKVMwatQo7Nmzp1KvkV6OR00b/DExAK97OKJALWLGHxcRvP4M0nMLpI5GRER67lpyhra7Nbkzx26RbnGwNsW6Ub5wsFbhSlImhq0KRwZ//tFLgihxuyAzMxPe3t5YtGgRvv76azRr1gxz5sx55rGbN2/G4MGDkZWVBYVCgb/++gs9e/ZEQkICHBwcAABLlizBhx9+iPv370OpVOLDDz9ESEgIzp8/rz3PgAEDkJqait27d5cqY3p6OmxsbJCWlgZra+tXvmYqO1EUserETfzvz0so1IioY2eOhYO80aQGfxtJREQvZ+JvZ/HHuQR0dXfAsqE+UscheqarSRnovzQUj7IL0MrVFr+MbAVTE7nUsYxaWWsDyTtcwcHBCAwMRJcuXV54bPFFKRQKAEBoaCg8PT21xRYAdOvWDenp6bhw4YL2mH+eu1u3bggNDX3u6+Tl5SE9Pb3Eg6QlCAJGBrhi0zg/1KxihpsPs9F30Un8Fn6btxgSEVGZXUnKwK5ojt0i3VffwQq/jPSFlUqB8LgUjF8bifxCjdSxqAwkLbg2bNiAM2fOYNasWS889sGDB/jqq68wZswY7bbExMQSxRYA7deJiYn/ekx6ejpycnKe+VqzZs2CjY2N9uHi4lKm66KK412rKnZNDECnRvbIL9Rg+rYY/GfTOWTnF774yURERI/NPXAVogh0b+II9xq8e4V0m6ezDVYMbwlTExkOxd7H1E1RUHPZHL0hWcEVHx+PyZMnY926dTA1Nf3XY9PT0xEYGAh3d3fMmDGjwrNNnz4daWlp2kd8fHyFvyaVXlULJZYP9cGH3RtBLhOw7exd9F5wgmtVEBFRqcQmZuDPmHsAgMlcd4v0RCtXWywZ3AImcgEh0ffwyfYY3uWjJyQruCIjI5GcnAxvb28oFAooFAocOXIE8+bNg0KhgFqtBgBkZGSge/fusLKywvbt22FiYqI9h6OjI5KSkkqct/hrR0fHfz3G2toaZmZmz8ymUqlgbW1d4kG6RSYTML5DPawf5Qt7KxWuJmei14IT2H72jtTRiIhIx8173N3q4emIxk78P570R4eG9pg7oDlkArAhIh7fhFxi0aUHJCu4OnfujJiYGERFRWkfPj4+GDRoEKKioiCXy5Geno6uXbtCqVRi586dT3XC/Pz8EBMTg+TkZO22ffv2wdraGu7u7tpjDhw4UOJ5+/btg5+fX8VfJFU437p2+HNyW/i72SGnQI2pG89h+rZo5BaopY5GREQ66HJiOkKKu1udOXaL9E8PTyd8269oZu/lx+Mw78A1iRPRi0hWcFlZWcHDw6PEw8LCAnZ2dvDw8NAWW1lZWVixYgXS09ORmJiIxMREbfera9eucHd3x5AhQ3Du3Dns2bMHn376KYKDg6FSqQAA48aNw40bN/DBBx/g8uXLWLRoETZt2oSpU6dKdelUzqpZqvDLSF9M7lwfggD8Fh6PvotOIu5BltTRiIhIx8zdfxUAEOjphIaOVhKnIXo5/X1c8HnPoubC7P1XsPJ4nMSJ6N9IPkvh85w5cwZhYWGIiYmBm5sbnJyctI/iMVVyuRy7du2CXC6Hn58fBg8ejKFDh2LmzJna87i6uiIkJAT79u1D06ZN8eOPP2L58uXo1q2bVJdGFUAuEzD1tQb4ZWQr2FkoceleOt6Yf1x7jz4REdHFhHT8dT4RgsCxW6T/Rga4YurjGTZn7rqITRGcc0BXvfQ6XBcvXsTt27eRn19y1etevXqVSzBdwnW49EtiWi4m/nYGETcfAQCGt6mDj3s0hlKhs79fICKiSjD219PYcyEJPb2csGCgt9RxiF6ZKIr4JuQSlh+Pg0wA5r/rjUAvJ6ljGbyy1gaKsr7AjRs30LdvX8TExEAQBO1APUEQAEB7ux+RVBxtTPHb6Nb4v71XsOTIdaw+eRNn41OxcGBzOFc1lzoeERFJ4EJCGvZcSCrqbnVmd4sMgyAI+CSwMTLzCrEhIh5TNp6FhUqODg3tpY5GTyjzr/wnT54MV1dXJCcnw9zcHBcuXMDRo0fh4+ODw4cPV0BEorJTyGX46PVGWDHMBzZmJjgXn4rAecdx4FLSi59MREQGp3js1hteNVDfgWO3yHAIgoBv+nqip5cTCtQixq2NRHhcitSx6AllLrhCQ0Mxc+ZMVKtWDTKZDDKZDAEBAZg1axYmTZpUERmJXlrnxg4ImRSApi5VkJZTgKA1pzHrr0soVHOFdiIiY3H+bhr2Xizqbk1id4sMkFwm4Kf+zdCxYXXkFmgwcnUEYu6kSR2LHitzwaVWq2FlVfSboWrVqiEhIQEAULt2bcTGxpZvOqJy4FzVHJvH+mF4mzoAgKVHbmDgz2FITMuVNhgREVWKOY+7W72a1oCbvaXEaYgqhlIhw6JBLdDK1RaZeYUYujIMV5MypI5FeImCy8PDA+fOnQMA+Pr64vvvv8eJEycwc+ZM1K1bt9wDEpUHpUKGGb2aYNEgb1iqFAi/mYLAecdw7Op9qaMREVEFirmThv2XkiBjd4uMgJlSjhXDfODlbINH2QUYvCIM8SnZUscyemUuuD799FNoNEW3Y82cORNxcXFo27Yt/vzzT8ybN6/cAxKVpx6eTtg1MQCNnazxMCsfQ1eGY/a+K1BruEo7EZEhmrP/CgCgd7OaqFed3S0yfFamJlgzohXq21siKT0Pg5aHISmdd/VI6aWnhX9SSkoKqlatqp2p0NBwWnjDk1ugxpd/XMRv4bcBAP5udpjzTnNUt1JJnIyIiMrLufhU9F54AjIB2D+tPeqy4CIjkpSei7eXhOJ2SjYaOFhi4xg/VLVQSh3LIJS1NiiXhYlsbW0Nttgiw2RqIsesNz0x+52mMDOR48S1hwicdwxhNx5KHY2IiMrJ3ANFY7f6NK/JYouMjoO1KdaN8oWDtQpXkjIxbFU4MnILpI5llMrc4XrzzTf/df+2bdteKZAuYofLsF1NysB7687ganIm5DIB/+3aEGPb1YVMxl8iEBHpq6j4VPRZeAJymYAD09qjTjULqSMRSeJqUgb6Lw3Fo+wCtHK1xS8jW8HURC51LL1W4R0uGxsb7SMkJAQymazENiJ9U9/BCr9P8MebzWtCrRHx3e7LCFoTgUdZ+VJHIyKil1Q8dqtPs5ostsio1Xewwi8jfWGlUiA8LgXj10Yiv5DL41SmVxrDZWVlhXPnzhn87ITscBkHURSxMSIen++8gPxCDWpWMcOCgc3RvFZVqaMREVEZnLn9CG8uOgm5TMDB/7RHbTsWXEThcSkYujIMuQUaBHo5Yd6A5pDzbp6XIskYLiJDIAgCBrSqhe3vtUEdO3PcTc1B/6WhWHk8DuUwtwwREVWS4nW33mxek8UW0WOtXG2xZHALmMgFhETfwyfbY/jzTSVhwUX0D01q2OCPiQHo4emIArWImbsuYvzaM0jnQFMiIp0XeesRjl65D4VMwMROXHeL6EkdGtpj7oDmkAnAhoh4fBNyiUVXJVCU9QlPrrVVWFiI1atXo1q1atptkyZNKp9kRBKyMjXBwoHeWHPyJr758xJ2X0jEpcR0LBzoDY+aHKtIRKSrisdu9fN2Ri07c4nTEOmeHp5O+LafFz7YEo3lx+NgZWqCyV34y4mKVOYxXK6urs8/mSDgxo0brxxK13AMl3GLik9F8LozuJuaA6VChi/ecMfAVrW4FAIRkY6JvJWCfotDoZAJOPTfDnCxZcFF9Dwrj8dh5q6LAIDPe7pjZMDzf8ankspaG5S5wxUXF/dSwYj0VTOXKgiZFID/bDqHA5eT8cn284iIS8E3fT1hoSrztxAREVWQ2fuKxm691cKZxRbRC4wMcEVGbiFm77+CmbsuwlKlQP+WLlLHMkgvPYYrPz8fsbGxKCwsLM88RDqpirkSPw/1wfTXG0EuE7AjKgG9FhzHlaQMqaMRERGAiJspOH7tARQyAcEd3aSOQ6QXJnV2w6jHna2PtkUjJPqexIkMU5kLruzsbAQFBcHc3BxNmjTB7du3AQATJ07Et99+W+4BiXSFTCZgbPt62DCmNRysVbh+Pwu9FhzH1sg7UkcjIjJ6s/cVjd1628eF3S2iUhIEAZ8ENsY7Pi7QiMCUjWdxODZZ6lgGp8wF1/Tp03Hu3DkcPnwYpqam2u1dunTBxo0byzUckS5qWccWIZPaom39asgt0OA/m8/hwy3RyC1QSx2NiMgohd14iJPXH8JELmBCJ3a3iMpCEAT8701PBHo5oUAtYtzaSITHpUgdy6CUueDasWMHFixYgICAgBKTBjRp0gTXr18v13BEuqqapQqrR7TC1C4NIAjAxtPx6LPwBG7cz5Q6GhGR0Sled6u/jwtqVjGTOA2R/pHLBMzu3wwdGlZHboEGQasjcP5umtSxDEaZC6779+/D3t7+qe1ZWVmctY2MilwmYHKX+lgb5ItqlkpcTsxArwUnsCs6QepoRERG49SNhwi9UdTd4tgtopenVMiweFALtHK1RUZeIYauDMe1ZI5VLw9lLrh8fHwQEhKi/bq4yFq+fDn8/PzKLxmRnvB3q4aQSW3RytUWmXmFmLD+LL74/TzyCnmLIRFRRSseu/VOSxfUYHeL6JWYKeVYMcwHXs42SMnKx6DlYYhPyZY6lt4rc8H1v//9Dx9//DHGjx+PwsJCzJ07F127dsWqVavwzTffVERGIp3nYG2K9aN88V6HegCANaG38PaSUP4jRURUgU5ef4CwuBQo5TJ2t4jKiZWpCdaMaIX69pZISs/DoOVhSErPlTqWXitzwRUQEICoqCgUFhbC09MTe/fuhb29PUJDQ9GiRYuKyEikFxRyGT7o3girhrdEFXMTRN9JQ+C8Y9h3MUnqaEREBkcURcx5vO7WgFYucLJhd4uovFS1UGLtKF/UsjXH7ZRsDFkRhkdZ+VLH0luCKIqi1CF0XVlXkya6m5qD4HVnEBWfCgAY064u3u/WECbyl176joiInnDi2gMMWh4GpUKGo+93hKON6YufRERlEp+SjbeWnERSeh68nG2wbpQvrExNpI4lubLWBuX2019hYSE6deqETp06oXv37uV1WiK9VLOKGTaN9cNI/6LFBJcdvYEBy07hXlqOxMmIiPSfKIqYs79o7NbAVrVYbBFVEBdbc6wN8kXVx3fuBK05zWVwXkKZO1zNmzd/5myEoigiOjoaZ86cgUwmg6enZ7mFlBo7XPQqdp+/h/c3RyMjrxC2FkrMeacZ2jWoLnUsIiK9dfzqAwxeUdTdOvZBRzhYs+Aiqkgxd9Iw8OdTyMgrRMeG1bF0iA+UCuO9a6estYGirC/Qp0+fZ24vKChAdHQ0mjZtWtZTEhm07h5OaOxkjffWncGFhHQMWxWOiR3dMLlLA8hlXEqBiKgsRFHE7Ce6Wyy2iCqep7MNVgxviaErw3Ao9j6mborCvAHN+XNMKZXbGK7c3FxYWFhArTa8NiM7XFQecgvU+GrXRawLuw0A8Ktrh7nvNoO9FX9YICIqraNX7mPoynCoHne37FlwEVWaw7HJGP3LaRSoRQxo6YJZb3oa5Tq8ko3hMsY3m6gsTE3k+KavJ+YOaAZzpRyhNx4icN5xhF5/KHU0IiK98GR3a5BvbRZbRJWsQ0N7zB3QHDIB2BARj29CLoHz772Y8d58SSSR3s1qYueEADRwsMT9jDwMWn4KCw9dg0bDf7CIiP7NkSv3cfZ2KkxNZBjXoa7UcYiMUg9PJ3z7phcAYPnxOMw7cE3iRLqvzGO4pk2b9szthngrIVFFcbO3xI5gf3y64zy2nbmLH/bEIuJmCmb3b4aqFkqp4xER6ZyimQmL1t0a7Fubt2MTSah/Sxdk5BXiq10XMXv/FViZKjAywFXqWDqrzAXX2bNnn7uvXbt2rxSGyJiYKxX48e2maO1qh89+P4/DsfcROO8Y5g/0RovaVaWOR0SkUw5fuY+o+KLu1tj29aSOQ2T0ggJckZFbgDn7r2LmrouwVCnQv6WL1LF0UpkLrkOHDlVEDiKjJAgC+rd0gaezDd5bdwZxD7LwztJQfPR6IwQFuHJsJBERHne39hWN3RrSujaqW6kkTkREADC5c31k5BZixfE4fLQtGhYqBQK9nKSOpXM4hotIBzR2ssbOCf4I9HJCoUbE1yGXMG5tJNJyCqSORkQkuUOxyTh3Jw1mJnJ2t4h0iCAI+DSwMd7xcYFGBKZsPIvDsclSx9I5LLiIdISVqQkWvNscX/VuAqVchj0XktBz/jHE3EmTOhoRkWSeHLs11K82qlmyu0WkSwRBwP/e9ESglxMK1CLGrY1EeFyK1LF0CgsuIh0iCAKG+NXBlvF+cK5qhviUHPRbfBK/nrrFaVeJyCgduJSM6DtpMFfKMaYdZyYk0kVymYDZ/ZuhQ8PqyC3QIGh1BM7f5S+Mi7HgItJBXs5VEDKxLbo0dkC+WoPPdpzH5A1RyMwrlDoaEVGlEUURcw4Ujd0a6lcHduxuEekspUKGxYNaoJWrLTLyCjF0ZTiuJWdIHUsnsOAi0lE25ib4eWgLfNKjMeQyATvPJaDXguO4nJgudTQiokqx/1Iyzt9NZ3eLSE+YKeVYMcwHXs42SMnKx6DlYYhPyZY6luQEsYz3Kc2bN+9f90+aNOmVAumi9PR02NjYIC0tDdbW1lLHISN0+mYKJqw/i8T0XJiayPBVbw+87cOpV4nIcImiiJ7zj+NCQjrGd6iHD7s3kjoSEZXSo6x89F8aiqvJmahla47N4/zgYG04a+eVtTYoc8Elk8ng7OwMuVwOAIiPj4eTkxMUCgUEQcCNGzdeLrkOY8FFuuBhZh6mbjqHo1fuAwDebuGMmb09YKaUS5yMiKj87bmQiLG/RsJCKcfxDztxUXgiPZOUnou3l4Tidko2GjhYYuMYP4P5Pi5rbfBStxSePn0acXFxiIuLg5mZGY4cOYK4uDiDLLaIdIWdpQqrh7fEf15rAJkAbI68g76LTuD6/UypoxERlSuN5u+ZCYf71zGYH9KIjImDtSnWjfKFg7UKV5IyMWxVODJyjXO5mzIXXHK5HGq1Wvu1Wq1GaGhouYYiomeTyQRM7Fwfa4N8Uc1ShcuJGeg1/zh2nkuQOhoRUbnZezERl+6lw1KlwOi2HLtFpK9cbM2xNsgXVc1NEH0nDUFrTiO3QP3iJxqYMhdczs7OOHDgAADg5MmT0Gg0mDZtGj7++GNOW01USdq4VcOfkwLg62qLrHw1Jv12Fp/uiEFeofH9I0ZEhuXJ7tYI/zqoYs7uFpE+q+9ghV9G+sJKpUB4XArGr41EfqFG6liVqswF19ixYzF8+HA0atQInTp1wujRo3H69Gns378fr732WkVkJKJnsH/cqp/Q0Q0AsPbUbby1OBS3H3I2ICLSX3suJOJyYgasVAoEBbhKHYeIyoGnsw1WDG8JlUKGQ7H3MXVTFNQa42nUlLng+uijj/Dnn38iKCgIa9euxbx58+Di4oJjx47Bzc2tIjIS0XMo5DL8t1tDrBrRElXNTRBzNw2B849hz4VEqaMREZUZu1tEhquVqy2WDGkBE7mAkOh7+GR7jNHcHVfmWQqNEWcpJH2QkJqDCevP4MztVADAqABXfPh6I5jIudweEemHkOh7CF5/BlamChz/oBNszE2kjkRE5Swk+h4m/nYGGrHoZ5VPAhtDEASpY5VJhc9SmJ6e/q8PIpJGjSpm2DjWD6Me34Kz/Hgc3lkaioTUHImTERG9mEYjYu6BKwCAkf6uLLaIDFSglxO+fdMLQNHPKvMOXJM4UcUrc8FVpUoVVK1a9alH8XYiko6JXIZPe7pjyeAWsDJV4MztVATOO4bDsclSRyMi+lchMfdwJSkTVqYKjOTYLSKD1r+lCz7r6Q4AmL3/ClYej5M4UcVSvMyTtmzZAltbW4iiiB49emD58uWoWbNmeWcjopfU3cMR7k7WeG99JM7fTcfwVRGY0NENU7rUh4K3GBKRjlFrRMw7UDR2a1RAXdiYsbtFZOiCAlyRkVuAOfuvYuaui7A0VaC/j4vUsSrESxVc/v7+sLe3B1C0Lpe3tzcaNWpUrsGI6NXUsjPHlnFt8E3IJfx66hYWHLqG07dSMG9Ac9hbm0odj4hIKyTmHq4mZ8LaVIERAXWkjkNElWRy5/rIyC3EiuNx+GhrNCxVCvTwdJI6Vrkr86+6bW1tcefOHQDAo0ePkJ2djZ49e+LcuXOvFOTbb7+FIAiYMmWKdltubi6Cg4NhZ2cHS0tL9OvXD0lJSSWed/v2bQQGBsLc3Bz29vZ4//33UVhYWOKYw4cPw9vbGyqVCm5ubli9evUrZSXSF6YmcnzVxwPz3m0OC6Ucp26koMe84zh5/YHU0YiIABR1t+buLxq7NaptXVibsrtFZCwEQcCngY3xjo8LNCIwecNZgxwGUeaCq127dhg+fDi+/fZb9O7dGy1atMC0adPQvn37ly5kIiIisHTpUnh5eZXYPnXqVPzxxx/YvHkzjhw5goSEBLz55pva/Wq1GoGBgcjPz8fJkyexZs0arF69Gp9//rn2mLi4OAQGBqJjx46IiorClClTMGrUKOzZs+elshLpo15Na2DnxAA0dLDCg8w8DF4ehvkHrkJjRGtgEJFu2hWdgOv3s2BjZoIR/nWkjkNElUwQBPzvTU8EejmhQC1i3NpIhMelSB2rXJV5WvjExERMmzYN586dg6urK2bPno369evj1KlT6N+/P27fvl2mAJmZmfD29saiRYvw9ddfo1mzZpgzZw7S0tJQvXp1rF+/Hm+99RYA4PLly2jcuDFCQ0PRunVr/PXXX+jZsycSEhLg4OAAAFiyZAk+/PBD3L9/H0qlEh9++CFCQkJw/vx57WsOGDAAqamp2L17d6kyclp4MhQ5+Wp8/vt5bI4s6lK3a1Adc95pBlsLrnVDRJVPrRHx2uwjuHE/C//t2gATOtWXOhIRSSS/UIMxv57G4dj7sFIp8NuY1vCoaSN1rGeq8GnhHR0dsX79ely4cAG7du1C/fpF/zi2bt0aZ86cKXPg4OBgBAYGokuXLiW2R0ZGoqCgoMT2Ro0aoVatWggNDQUAhIaGwtPTU1tsAUC3bt2Qnp6OCxcuaI/557m7deumPcez5OXlcbp7MkhmSjl+eLspvn/LC6YmMhy9ch895h7D6ZuG9ZskItIPO8/dxY37WahiboJhbepIHYeIJKRUyLB4UAu0crVFRl4hhq4Mx7XkDKljlYtyna6sWrVqZTp+w4YNOHPmDGbNmvXUvsTERCiVSlSpUqXEdgcHByQmJmqPebLYKt5fvO/fjklPT0dOzrPXJ5o1axZsbGy0DxcXw5wxhYxXfx8X7Aj2R93qFkhMz8U7y07h56M3jGbFdyKSXqFag/mP198Z3bYurDh2i8jomSnlWDHMB17ONkjJyseg5WGIT8mWOtYrK/MshdOmTfvX/T/99FOpzhMfH4/Jkydj3759MDXVrRnTpk+fXuI609PTWXSRwWnkaI2dEwIwfVsM/jiXgG/+vITwmyn4v7eacsFRIqpwO88l4MaDLFRld4uInmBlaoI1I1qh/9JQXE3OxKDlYdg8zg8OejzDcpk7XGfPntU+5s+fj5MnT2q/joqKKvV5IiMjkZycDG9vbygUCigUChw5cgTz5s2DQqGAg4MD8vPzkZqaWuJ5SUlJcHR0BFB0e+M/Zy0s/vpFx1hbW8PMzOyZ2VQqFaytrUs8iAyRpUqBeQOa4as+HlDKZdh3MQmB848h+k6q1NGIyIAVqjXadbdGt6sLS9VLrVJDRAaqqoUSa0f5wsXWDLdTsjFkRRgeZeVLHeullbngOnTokPZhamqK9evXa78+ePBgqc/TuXNnxMTEICoqSvvw8fHBoEGDtH82MTHBgQMHtM+JjY3F7du34efnBwDw8/NDTEwMkpP/nj5y3759sLa2hru7u/aYJ89RfEzxOYiMnSAIGNK6NraObwMXWzPceZSDtxaH4pfQm7zFkIgqxI6oBNx8mA1bCyWG+dWROg4R6SAHa1OsC2oNB2sVriRlYtiqcGTkFkgd66WU6xiusrCysoKHh0eJh4WFBezs7ODh4QEbGxsEBQVh2rRpOHToECIjIzFixAj4+fmhdevWAICuXbvC3d0dQ4YMwblz57Bnzx58+umnCA4OhkqlAgCMGzcON27cwAcffIDLly9j0aJF2LRpE6ZOnSrVpRPpJE9nG+ya2BZd3R2Qr9bg898vYOJvZ5GZV/jiJxMRlVKhWoP5B4u6W2Pa1YUFu1tE9By17MyxNsgXVc1NEH0nDUFrTiO3QC11rDKTrOAqjdmzZ6Nnz57o168f2rVrB0dHR2zbtk27Xy6XY9euXZDL5fDz88PgwYMxdOhQzJw5U3uMq6srQkJCsG/fPjRt2hQ//vgjli9fjm7duklxSUQ6zcbMBEuHtMCngY2hkAnYFX0PveYfx6V7nKmTiMrH9rN3cethNuwslBjqV1vqOESk4+o7WOGXkb6wVCkQHpeC36PuSh2pzMq8DtfOnTu1f3733XcxZ86cErMA9urVq/zS6Qiuw0XGKPLWI0xYfwb30nKhUsjwVW8PvO3jDEEQpI5GRHqqQK1B5x+P4HZKNj7u0Qhj2tWTOhIR6YmwGw8RcTMFwR3dJP9ZpKy1QZkLLpns+U0xQRCgVutfm+9FWHCRsUrJysfUjVE4cuU+AKCftzO+6tME5kreAkREZbcpIh4fbI1GNUsljn7Qkf+WEJFeqvCFjzUazXMfhlhsERkzWwslVg1vife7NYRMALaeuYM+C08YzEKERFR5CtQazD9UNHZrbLt6LLaIyGjo9BguIpKeTCYguKMb1o1qjepWRTMF9VpwQi/voSYi6WyNvIP4lBxUs1RhcGuO3SIi41Hmgis9Pf2Zj2vXrkEul8PW1haNGzeuiKxEJCG/enYImRQAv7p2yM5XY/KGKHyyPUYvZwsiosqVX6jB/IPXAADj2teFmVIucSIiospT5n5+lSpVnjlQTRRFCIKAlJSUcglGRLrH3soUa0f5Yu7+K5h/6BrWhd1GVHwqFg3yRm07C6njEZGO2nrmDu6m5qC6FbtbRGR8XuoG6i1btsDW1rbEtocPH+Ltt98ul1BEpLvkMgHTujZEizq2mLoxChcS0tFz3nH88LYXuns4SR2PiHRMfqEGCx53t8a3rwdTE3a3iMi4vFTB5e/vD3t7+xLbkpKSyiUQEemH9g2qI2RSACasP4vIW48wbu0ZjPR3xUevN4JSweGhRFRkc2Q87qbmwN5KhYG+taSOQ0RU6V7qp6KLFy/i0qVLuHv3Lso4qzwRGRAnGzNsGNMaY9rVBQCsPBGH/ktDcTc1R+JkRKQL8grVWFjc3erA7hYRGaeXKrg6d+4MDw8P1KpVC+bm5ujcuTO2bNlS3tmISA+YyGX4uEdjLBvSAtamCkTFpyJw3jEcupwsdTQiktim03eQkJYLB2sV3m3F7hYRGacy31IYFxcHAMjLy8PDhw9x48YNHDlyBB9++GG5hyMi/dG1iSNCnKwRvP4Mou+kYcTqCLzXoR6mvdYACjlvMSQyNnmFaiw6VNTdeq+DG7tbRGS0BLGc7gk8evQoOnTogDp16qB69eoICwsrj9PqhLKuJk1kzPIK1fhfyCWsCb0FAGjlaov57zaHg7WpxMmIqDL9GnoTn/1+AY7Wpjj8fgcWXERkMMpaG5TbMu8BAQHa7pdczn9UiYyVSiHHl7094FPHFh9tjUZ4XAoC5x3D3AHN4e9WTep4RFQJcgvUWHjoOgAguCPHbhGRcXup+3wKCwuxf/9+LF26FBkZGQCAxMRE2NnZoXbt2nB2di7XkESkf95oWgN/TAxAI0crPMjMx+AVYZi7/yrUGk60Q2ToNkbEIzE9F042pujf0kXqOEREkipzwXXr1i14enqid+/eCA4Oxv379wEA3333Hf773/+We0Ai0l91q1tiR7A/3vFxgSgCs/dfwfBV4XiQmSd1NCKqILkFaiw6/HjsVkc3qBTsbhGRcStzwTV58mT4+Pjg0aNHMDMz027v27cvDhw4UK7hiEj/mZrI8d1bXvi/t5vC1ESGY1cfoNf847iYkC51NCKqAL+F30ZSeh5q2Jiivw/veCEiKnPBdezYMXz66adQKpUlttepUwd3794tt2BEZFjeauGM34MD4FrNAglpuXhryUnsuZAodSwiKkdF3a3HY7c6sbtFRAS8RMGl0WigVquf2n7nzh1YWVmVSygiMkwNHa2w4z1/BLhVQ3a+GmN/jcTCQ9e4gDqRgVgfdhv3M/JQs4oZ3m7BsVtERMBLFFxdu3bFnDlztF8LgoDMzEx88cUX6NGjR3lmIyIDZGNuglUjWmKoX20AwA97YjF1YxRyC57+RQ4R6Y/cAjUWHynqbk3o5AalguvvEREBL1Fw/fjjjzhx4gTc3d2Rm5uLgQMHam8n/O677yoiIxEZGBO5DDN7e+CrPh6QywTsiErAgGWnkJyRK3U0InpJa0/d0na3+nlz7BYRUbGXWvi4sLAQGzZsQHR0NDIzM+Ht7Y1BgwaVmETDkHDhY6KKc/LaA4xfdwZpOQVwsjHFz0N94FHTRupYRFQGOflqtP3+EB5k5uHbNz0xoFUtqSMREVWYstYGL1VwGRsWXEQVK+5BFoLWRODG/SyYmcjxU/+meN3TSepYRFRKPx+9gW/+vAQXWzMc/E8HmMh5OyERGa6y1gYv9S9ibGwsJkyYgM6dO6Nz586YMGECLl++/DKnIiKCazULbH/PH23rV0NOgRrj153BvANXOZkGkR7Izi/EksdjtyZ2rM9ii4joH8r8r+LWrVvh4eGByMhING3aFE2bNsWZM2fg6emJrVu3VkRGIjICNmYmWDW8JYa3qQMA+GnfFUzawMk0iHTd2lO38DArH7VszdHXu6bUcYiIdE6ZbymsV68eBg0ahJkzZ5bY/sUXX2Dt2rW4fv16uQbUBbylkKhyrQ+7jc9/P49CjYimzjZYNtQHDtamUscion/Izi9E2+8O4WFWPn54ywtv+3AqeCIyfBV+S+G9e/cwdOjQp7YPHjwY9+7dK+vpiIieMtC3Fn4N8kUVcxOcu5OGXguOI/pOqtSxiOgffgkt6m7VtjNH3+bsbhERPUuZC64OHTrg2LFjT20/fvw42rZtWy6hiIj86tnh92B/uNlbIik9D/2XhmJXdILUsYjosay8Qiw7egMAMLFTfSg4douI6JkUZX1Cr1698OGHHyIyMhKtW7cGAJw6dQqbN2/Gl19+iZ07d5Y4lojoZdW2s8C299pg0m9ncTj2PiasP4tryZmY3Lk+BEGQOh6RUVsTehMpWflwrWaBPs1qSB2HiEhnlXkMl0xWut9gCYIAtdowBrtzDBeRtNQaEf/78xJWHI8DAAR6OeH/3moKM6Vc4mRExikzrxAB3x1EanYBfurfFG9yoWMiMiIVPoZLo9GU6mEoxRYRSU8uE/BZT3d8188TJnIBIdH30H9pKBLTcqWORmSU1py8idTsAtStZoFeTdndIiL6N7zhmoj0xjsta2FtkC+qmpsg5m7RZBrn4lOljkVkVDJyC/DzsaKxW5M6c+wWEdGLlPpfyYMHD8Ld3R3p6elP7UtLS0OTJk1w9OjRcg1HRPRPvnXtsHNCABo4WCI5o2gyjZ3nOJkGUWXRdreqW+ANdreIiF6o1AXXnDlzMHr06Gfep2hjY4OxY8di9uzZ5RqOiOhZXGzNsXV8G3RqZI+8Qg0m/XYWP+6NhUZTpiGpRFRG6bkF+PlY0VjKyZ3rQy7j5DVERC9S6oLr3Llz6N69+3P3d+3aFZGRkeUSiojoRaxMTfDzUB+MaVcXADD/4DUErz+D7PxCiZMRGa7VJ24iLacAbvaW6OnF7hYRUWmUuuBKSkqCiYnJc/crFArcv3+/XEIREZWGXCbg4x6N8cNbXjCRC/jrfCLeXhKKhNQcqaMRGZy0nAIsf2LsFrtbRESlU+qCq2bNmjh//vxz90dHR8PJyalcQhERlcXbPi74bXRr2FkocSEhHb0WnMDZ24+kjkVkUFafuIn03ELUt7dEoCf/vyciKq1SF1w9evTAZ599htzcp6dhzsnJwRdffIGePXuWazgiotLyqWOLHcH+aORohQeZeXhn2SnsOHtX6lhEBiEtpwDLjxd1tyZ3YXeLiKgsSr3wcVJSEry9vSGXyzFhwgQ0bNgQAHD58mUsXLgQarUaZ86cgYODQ4UGlgIXPibSH5l5hZiyIQr7LyUBAII71sN/XmsIGX9AJHpps/ddwdwDV9HAwRK7J7fj9xMRGbWy1galLrgA4NatWxg/fjz27NmD4qcJgoBu3bph4cKFcHV1ffnkOowFF5F+0WhE/LA3FosPXwcAdGvigJ/6N4OFSiFxMiL9k5ZdgIDvDiIjrxALB3oj0Iu3ExKRcavQgqvYo0ePcO3aNYiiiPr166Nq1aovFVZfsOAi0k/bztzBR1tjkK/WoLGTNZYP80HNKmZSxyLSKz/tjcW8g9fQyNEKf05qy+4WERm9stYGL7U8fNWqVdGyZUu0atXK4IstItJfb3o747cxvqhmqcSle+noveA4Im9xMg2i0krNzsfKEzcBFK27xWKLiKjsXqrgIiLSFy1qF02m0djJGg8y8/HuslPYduaO1LGI9MKK43HIzCtEI0crdGviKHUcIiK9xIKLiAyec1VzbBnnh67uDshXazBt0zl8+9dlqDVlvqOayGikZudj1ePu1pQuDdjdIiJ6SSy4iMgoWKgUWDK4BYI71gMALDlyHWN/PY3MvEKJkxHppp+P3UBmXiEaO1mjq7vhzUBMRFRZWHARkdGQyQS8360R5rzTDEqFDPsvJeOtxScRn5ItdTQinZKSlY/V2u4Wx24REb0KFlxEZHT6NK+JjWNao7qVCpcTM9Bn4QlE3EyROhaRzvj52A1k5avRpAa7W0REr4oFFxEZpea1quL3YH80qWGNh1n5GPjzKWw+HS91LCLJPczMw5qTNwEUjd0SBHa3iIheBQsuIjJaNaqYYfM4P7zu4YgCtYj3t0Tjm5CLnEyDjNrPx+KQna+GZ00bdGlsL3UcIiK9x4KLiIyauVKBhQO9MamTG4CiHzZH/3IaGbkFEicjqnwPM/PwS+hNAEVjt9jdIiJ6dSy4iMjoyWQCpnVtiPnvNodKIcPBy8not/gkbj/kZBpkXJYdvYHsfDW8nG3QqRG7W0RE5YEFFxHRY280rYFNY/1gb6XClaRM9F54HGE3Hkodi6hSPMjMwy+htwCwu0VEVJ5YcBERPaGpSxXsnBAAz5o2eJRdgMErwrAx4rbUsYgq3NIj15FToEZTlyro2JDdLSKi8iJpwbV48WJ4eXnB2toa1tbW8PPzw19//aXdn5iYiCFDhsDR0REWFhbw9vbG1q1bS5wjJSUFgwYNgrW1NapUqYKgoCBkZmaWOCY6Ohpt27aFqakpXFxc8P3331fK9RGRfnK0McWmsX4I9HRCgVrEh1tj8NUuTqZBhis5Ixe/nmJ3i4ioIkhacDk7O+Pbb79FZGQkTp8+jU6dOqF37964cOECAGDo0KGIjY3Fzp07ERMTgzfffBP9+/fH2bNntecYNGgQLly4gH379mHXrl04evQoxowZo92fnp6Orl27onbt2oiMjMQPP/yAGTNmYNmyZZV+vUSkP8yUciwY2BxTutQHAKw4HoeRqyOQzsk0yAAtO3IDuQUaNHOpgg4Nqksdh4jIoAiiKOrUr2xtbW3xww8/ICgoCJaWlli8eDGGDBmi3W9nZ4fvvvsOo0aNwqVLl+Du7o6IiAj4+PgAAHbv3o0ePXrgzp07qFGjBhYvXoxPPvkEiYmJUCqVAICPPvoIO3bswOXLl0uVKT09HTY2NkhLS4O1tXX5XzQR6bSQ6Hv4z+Yo5BZo4GZviRXDfFDbzkLqWETlIjkjF+2+P4TcAg3WjGyF9iy4iIj+VVlrA50Zw6VWq7FhwwZkZWXBz88PANCmTRts3LgRKSkp0Gg02LBhA3Jzc9GhQwcAQGhoKKpUqaIttgCgS5cukMlkCAsL0x7Trl07bbEFAN26dUNsbCwePXr0zCx5eXlIT08v8SAi4xXo5YTNY9vAwVqFa8mZ6L3wBEKvczINMgxLDhd1t5rXqoJ29atJHYeIyOBIXnDFxMTA0tISKpUK48aNw/bt2+Hu7g4A2LRpEwoKCmBnZweVSoWxY8di+/btcHMrWi8nMTER9vYlB/YqFArY2toiMTFRe4yDg0OJY4q/Lj7mn2bNmgUbGxvtw8XFpVyvmYj0j6ezDXZOCEBTZxukZhdgyIowrA/jZBqk35LTc7EurGjs1tQuDTh2i4ioAkhecDVs2BBRUVEICwvD+PHjMWzYMFy8eBEA8NlnnyE1NRX79+/H6dOnMW3aNPTv3x8xMTEVmmn69OlIS0vTPuLj4yv09YhIPzhYm2LjWD+80bQGCjUiPt4egxk7L6BQrZE6GtFLWXT4OvIKNWhRuyrasrtFRFQhFFIHUCqV2o5VixYtEBERgblz5+KDDz7AggULcP78eTRp0gQA0LRpUxw7dgwLFy7EkiVL4OjoiOTk5BLnKywsREpKChwdHQEAjo6OSEpKKnFM8dfFx/yTSqWCSqUq1+skIsNgaiLHvAHN0MDeEj/uu4LVJ2/i+v1MLBjoDRszE6njEZVaYlou1ocXdWnZ3SIiqjiSd7j+SaPRIC8vD9nZ2QAAmaxkRLlcDo2m6LfJfn5+SE1NRWRkpHb/wYMHodFo4Ovrqz3m6NGjKCj4e2axffv2oWHDhqhatWpFXw4RGSBBEDCxc30sHuQNMxM5jl19gL6LTiDuQZbU0YhKbcmR68gv1KBlnarwd7OTOg4RkcGStOCaPn06jh49ips3byImJgbTp0/H4cOHMWjQIDRq1Ahubm4YO3YswsPDcf36dfz444/Yt28f+vTpAwBo3LgxunfvjtGjRyM8PBwnTpzAhAkTMGDAANSoUQMAMHDgQCiVSgQFBeHChQvYuHEj5s6di2nTpkl45URkCF73dMLmcX5wsjHFjftZ6LPwBE5eeyB1LKIXYneLiKjySFpwJScnY+jQoWjYsCE6d+6MiIgI7NmzB6+99hpMTEzw559/onr16njjjTfg5eWFX375BWvWrEGPHj2051i3bh0aNWqEzp07o0ePHggICCixxpaNjQ327t2LuLg4tGjRAv/5z3/w+eefl1iri4joZXnUtMHvE/zRzKUK0nIKMGRluHYBWSJdtejwNeQXatCqji386rG7RURUkXRuHS5dxHW4iOhFcgvU+GhrNHZEJQAAhvrVxuc93aGQ69yd22TkElJz0OGHw8hXa7B+tC/a1ONkGUREZaG363AREekzUxM5Zr/TDO93awgA+CX0FoavikBadsELnklUuRYdvoZ8tQa+rrYstoiIKgELLiKiciIIAoI7umHpkBYwV8px/NoD9Fl0AtfvZ0odjQgAcDc1BxsjipY6mfpaA4nTEBEZBxZcRETlrFsTR2wZ1wY1bEwR9yALfReewLGr96WORYRFh66hQC3Cr64dWtfl2C0iosrAgouIqAK417DG7xMC4F2rCtJzCzF8VQTWnLwJDpslqdx5lI1Np4u6W1O61Jc4DRGR8WDBRURUQapbqfDbmNZ407sm1BoRX+y8gE93nEeBWiN1NDJCCw9dR4FaRJt6dvBld4uIqNKw4CIiqkAqhRw/vt0UH73eCIIArAu7jaErwvEoK1/qaGRE4lOysfk0x24REUmBBRcRUQUTBAHj2tfDsiE+sFDKEXrjIfosOoFryRlSRyMjsfDQNRRqRAS4VUPLOrZSxyEiMiosuIiIKslr7g7Y+l4bOFc1w62H2ei78CSOXOFkGlSx4lOysSXyDgBg6mscu0VEVNlYcBERVaJGjtb4PdgfLetURUZeIUasCsfK43GcTIMqzIKDRd2ttvWroUVtdreIiCobCy4iokpmZ6nC2lG+eLuFMzQiMHPXRXy8PQb5hZxMg8rX7YfZ2HKmqLs1pQvHbhERSYEFFxGRBFQKOb5/ywuf9GgMQQB+C4/HkBVhnEyDytX8g1eh1oho16A6WtSuKnUcIiKjxIKLiEgigiBgdLu6WDHMB5YqBcLiUtB74QlcTeJkGvTqbj7IwrazdwEAU7nuFhGRZFhwERFJrFMjB2x7rw1cbM1wOyUbfRedxKHLyVLHIj03/+A1qDUiOjSsjua12N0iIpIKCy4iIh3QwMEKvwcHoJWrLTLzChG0JgLLj93gZBr0UuIeZGH7WY7dIiLSBSy4iIh0hK2FEmuDfPGOjws0IvB1yCV8uDWak2lQmc0/eBUaEejUyB7NXKpIHYeIyKix4CIi0iFKhQzf9vPEZz3dIROATafvYPDyMDzMzJM6GumJG/czsePx2K0pHLtFRCQ5FlxERDpGEAQEBbhixfCWsFIpEH6zaDKN2EROpkEvNv/gNWhEoHMje3g5V5E6DhGR0WPBRUSkozo2tMf24DaobWeOO49y8OaiEzhwKUnqWKTDrt/PxO9Rxd0tjt0iItIFLLiIiHSYm70Vdrznj9Z1bZGVr8aoX05j6ZHrnEyDnmnegaKxW10aO8DT2UbqOEREBBZcREQ6r6qFEr8G+WKgby2IIjDrr8t4f0s08grVUkcjHXItOQM7zyUA4NgtIiJdwoKLiEgPmMhl+KaPB2a8UTSZxpbIOxj0cxgecDINemzegWsQRaCruwM8arK7RUSkK1hwERHpCUEQMNzfFatHtIKVqQKnbz1C7wUncOleutTRSGJXkzLwR3RRd2syu1tERDqFBRcRkZ5p16A6tr/njzp25ribmoN+i09i74VEqWORhOYeuApRBLo1cUCTGuxuERHpEhZcRER6yM3eEjuC/dGmnh2y89UYuzYSiw5f42QaRuhKUgZCYu4B4MyERES6iAUXEZGeqmKuxJqRrTC4ddFkGt/vjsV/Np1DbgEn0zAmc/cXdbde93BEYydrqeMQEdE/sOAiItJjJnIZvu7jia96N4FcJmDb2bt49+dTSM7IlToaVYLYxL+7Wxy7RUSkm1hwEREZgCF+dbBmRCtYmypw9nYq+iw4gQsJaVLHogo298AVAECgpxMaObK7RUSki1hwEREZiID61bAj2B91q1kgIS0Xby0Oxe7z96SORRXk0r10/BmTCEEAJnVmd4uISFex4CIiMiB1q1ti+3v+aFu/GnIK1Bi39gwWHLzKyTQM0Nz9VwEAPTyd0NDRSuI0RET0PCy4iIgMjI25CVYNb4nhbeoAAP5v7xVM2RjFyTQMyIWENOy+UNTdmsLuFhGRTmPBRURkgBRyGWb0aoJv+npAIRPwe1QC3ll2CsnpnEzDEBR3t3p61UB9B3a3iIh0GQsuIiIDNsi3Nn4JagUbMxOci09F74UncP4uJ9PQZ+fvpmHvxSQIAjC5s5vUcYiI6AVYcBERGbg29arh92B/1KtugXtpuXhryUn8FcPJNPTV3ANF3a1eTWvAzZ7dLSIiXceCi4jICNSpZoFt7/mjXYPqyC3QYPy6M48XzOVkGvrk/N007LuYBJkATOzEsVtERPqABRcRkZGwMTPBymE+GOFfBwAwe/8VTPztLCfT0CNz9hetu1XU3bKUOA0REZUGCy4iIiOikMvwxRtNMOtNTyhkAnZF30P/paFI4mQaOi/6Tir2X0qGjOtuERHpFRZcRERG6N1WtbB2lC+qmpsg+k4aei04jug7qVLHon8x5/HMhH2a1UTd6uxuERHpCxZcRERGqnVdO/weHID69pZISs/D20tC8ce5BKlj0TOci0/FwcvJkMsETGR3i4hIr7DgIiIyYrXszLHtvTbo2LA68go1mPjbWfy07wo0Gk6moUuKx271aVYTrtUsJE5DRERlwYKLiMjIWZmaYPmwlhjd1hUAMO/AVUz47Qxy8jmZhi44e/sRDsXeL+pudeK6W0RE+oYFFxERQS4T8EmgO77v5wUTuYA/YxLx9tKTuJeWI3U0o1c8dqtv85qow+4WEZHeYcFFRERa/Vu6YN2o1rC1UOL83XT0XnACUfGpUscyWpG3HuHIFXa3iIj0GQsuIiIqoZWrLX4P9kdDByskZ+ThnaWh+D3qrtSxjFLx2K1+3jVR247dLSIifcSCi4iInuJia44t4/3QuZE98go1mLwhCj/ujeVkGpUo8lYKjl19AIVMwMROnJmQiEhfseAiIqJnsjI1wbKhPhjbri4AYP7Ba3hv3Rlk5xdKnMw4FI/dequFM1xszSVOQ0REL4sFFxERPZdcJmB6j8b44S0vKOUy7L6QiLcWhyIhlZNpVKTTN//ubgV35NgtIiJ9xoKLiIhe6G0fF6wf7Qs7CyUu3ktHrwUncOb2I6ljGazZj8duve3D7hYRkb5jwUVERKXiU8cWv0/wRyNHKzzIzMOAZaew/ewdqWMZnPC4FJy49hAmcna3iIgMAQsuIiIqNeeq5tg6vg1ec3dAfqEGUzeew3e7L3MyjXI0e19xd8sFzlXZ3SIi0ncsuIiIqEwsVAosHdwC4zvUAwAsPnwdY9dGIiuPk2m8qlM3HiL0BrtbRESGhAUXERGVmUwm4MPujTD7naZQKmTYdzEJ/RafxJ1H2VJH02vF626909IFNauYSZyGiIjKg6QF1+LFi+Hl5QVra2tYW1vDz88Pf/31V4ljQkND0alTJ1hYWMDa2hrt2rVDTs7fs2OlpKRg0KBBsLa2RpUqVRAUFITMzMwS54iOjkbbtm1hamoKFxcXfP/995VyfUREhq5vc2dsGNMa1SxVuJyYgT4LTyDyVorUsfRS6PWHOHUjBUq5DO91YHeLiMhQSFpwOTs749tvv0VkZCROnz6NTp06oXfv3rhw4QKAomKre/fu6Nq1K8LDwxEREYEJEyZAJvs79qBBg3DhwgXs27cPu3btwtGjRzFmzBjt/vT0dHTt2hW1a9dGZGQkfvjhB8yYMQPLli2r9OslIjJE3rWq4vcJ/nB3ssaDzHy8uywMWyM5mUZZiKKonZnwnZYuqMHuFhGRwRBEUdSpkc62trb44YcfEBQUhNatW+O1117DV1999cxjL126BHd3d0RERMDHxwcAsHv3bvTo0QN37txBjRo1sHjxYnzyySdITEyEUqkEAHz00UfYsWMHLl++XKpM6enpsLGxQVpaGqytrcvnQomIDEx2fiGmbozCngtJAICx7evig26NIJcJEifTfSevPcDA5WFQymU48kEHONmw4CIi0lVlrQ10ZgyXWq3Ghg0bkJWVBT8/PyQnJyMsLAz29vZo06YNHBwc0L59exw/flz7nNDQUFSpUkVbbAFAly5dIJPJEBYWpj2mXbt22mILALp164bY2Fg8evTsNWTy8vKQnp5e4kFERP/OXKnA4kEtMOHxZA9Lj9zA2F9PI5OTafyrJ7tb77ZyYbFFRGRgJC+4YmJiYGlpCZVKhXHjxmH79u1wd3fHjRs3AAAzZszA6NGjsXv3bnh7e6Nz5864evUqACAxMRH29vYlzqdQKGBra4vExETtMQ4ODiWOKf66+Jh/mjVrFmxsbLQPFxeXcr1mIiJDJZMJ+G+3hpg7oBmUChn2X0pGv0UnEZ/CyTSe5+T1h4i4+QhKhQzvcWZCIiKDI3nB1bBhQ0RFRSEsLAzjx4/HsGHDcPHiRWg0GgDA2LFjMWLECDRv3hyzZ89Gw4YNsXLlygrNNH36dKSlpWkf8fHxFfp6RESGpnezmtg4pjWqW6kQm5SB3gtPIOImJ9P4J1EUtetuDWxVCw7WphInIiKi8iZ5waVUKuHm5oYWLVpg1qxZaNq0KebOnQsnJycAgLu7e4njGzdujNu3bwMAHB0dkZycXGJ/YWEhUlJS4OjoqD0mKSmpxDHFXxcf808qlUo7c2Lxg4iIyqZ5rarYOcEfHjWtkZKVj4E/n8Km0/wF1pOOX3uA07ceQaWQadc1IyIiwyJ5wfVPGo0GeXl5qFOnDmrUqIHY2NgS+69cuYLatWsDAPz8/JCamorIyEjt/oMHD0Kj0cDX11d7zNGjR1FQUKA9Zt++fWjYsCGqVq1aCVdERGS8nGzMsGmsH3p4OqJALeKDLdH4etdFqDU6NV+TJEp0t3zZ3SIiMlSSFlzTp0/H0aNHcfPmTcTExGD69Ok4fPgwBg0aBEEQ8P7772PevHnYsmULrl27hs8++wyXL19GUFAQgKJuV/fu3TF69GiEh4fjxIkTmDBhAgYMGIAaNWoAAAYOHAilUomgoCBcuHABGzduxNy5czFt2jQpL52IyGiYKxVY8K43JnWuDwBYfjwOo9ZEICO34AXPNGxHrz7AmdupRd2t9uxuEREZKoWUL56cnIyhQ4fi3r17sLGxgZeXF/bs2YPXXnsNADBlyhTk5uZi6tSpSElJQdOmTbFv3z7Uq/f3f0zr1q3DhAkT0LlzZ8hkMvTr1w/z5s3T7rexscHevXsRHByMFi1aoFq1avj8889LrNVFREQVSyYTMO21Bqhvb4n/bj6HQ7H38eaik1gxrCVq2ZlLHa/SPdndGty6NuzZ3SIiMlg6tw6XLuI6XERE5Sf6TipG/3IaSel5qGpugsWDW6B1XTupY1Wqw7HJGL4qAqYmMhz7oBOqW6mkjkRERKWkt+twERGRcfByroLfgwPg5WyDR9kFGLw8DBvCb0sdq9IUrbtVtLzJkNa1WWwRERk4FlxERFTpHG1MsXGMH3p6OaFQI+KjbTGY+cdFFKo1UkercIdj7+NcfCpMTWQY045jt4iIDB0LLiIikoSZUo757zbH1C4NAAArT8QhaM1ppBvwZBpF3a2isVtD/eqwu0VEZARYcBERkWQEQcDkLvWxcKA3TE1kOHLlPvouPIGbD7KkjlYhDl5ORvSdNJiZyDGmXV2p4xARUSVgwUVERJIL9HLC5rFt4Ghtiuv3s9Bn0QmcvP5A6ljlShRFzHk8dmtom9qoZsnuFhGRMWDBRUREOsHT2QY7J/ijqbMNUrMLMHRFONaF3ZI6Vrk5cCkZMXfTYK6UYyzHbhERGQ0WXEREpDPsrU2xcawfejWtgUKNiE+2n8eMnRf0fjINURQx50DR2K1hberA1kIpcSIiIqosLLiIiEinmJrIMXdAM/y3a9FkGqtP3sSI1RFIy9bfyTT2XUzC+bvpsFDKMbotx24RERkTFlxERKRzBEHAhE71sWSwN8xM5Dh29QH6LjqBG/czpY5WZk+O3WJ3i4jI+LDgIiIindXdwwlbxvuhho0pbjzIQp+FJ3D8qn5NprHnQhIu3kuHpUrB7hYRkRFiwUVERDqtSQ0b7Jjgj+a1qiA9txDDVoXj19CbUscqFY1GxJzH624Nb1MHVdndIiIyOiy4iIhI59lbmeK30a3Rt3lNqDUiPvv9Aj7bcR4FOj6Zxt6LibicmAErlQKj2rpKHYeIiCTAgouIiPSCqYkcP/Vvig+6N4QgAL+euoXhq8J1djKNou5W0ditEf51UMWc3S0iImPEgouIiPSGIAh4r4Mblg5uAXOlHCeuPUSfRSdwXQcn09h94e/uVlAAx24RERkrFlxERKR3ujZxxJZxbVCzihniHk+mcfTKfaljaWk0IuYWd7cCXGFjbiJxIiIikgoLLiIi0kvuNayxI9gfLWpXRUZuIUasjsDqE3EQRVHqaPjz/D3EJmXAylSBoACO3SIiMmYsuIiISG9Vt1Jh/WhfvOldNJnGjD8u4hOJJ9NQP9HdCgpwhY0Zu1tERMaMBRcREek1lUKOH99uiumvN4IgAOvDbmPIijA8ysqXJM+fMfdwNTkT1qYKjGR3i4jI6LHgIiIivScIAsa2r4efh/jAQinHqRsp6LPoBK4lZ1RqDrVGxNwDRd2tUW3rwtqU3S0iImPHgouIiAxGF3cHbH2vDZyrmuHWw2z0XXgSh2OTK+31d0Un4Nrj7tZw/zqV9rpERKS7WHAREZFBaeRojd+D/dGqji0y8goxcnUEVhyv+Mk01BoR8x53t0azu0VERI+x4CIiIoNjZ6nC2lG+6O/jDI0IfLXrIqZvi0F+YcVNpvHHuQRcv5+FKuYm7G4REZEWCy4iIjJISoUM3/XzwqeBjSETgA0R8RiyIgwpFTCZRqFaU6K7ZcXuFhERPcaCi4iIDJYgCBjVti5WDGsJS5UCYXEp6LPwBK4kle9kGn9EJ+DGgyxUNTfBsDZ1yvXcRESk31hwERGRwevYyB7b3msDF1sz3E7JxpuLTuLg5aRyOXdRd+saAGB0u7qwVCnK5bxERGQYWHAREZFRaOBghd+DA9DK1RaZeYUIWnMaPx+98cqTafwelYC4x92toX51yicsEREZDBZcRERkNGwtlFgb5IsBLV0gisA3f17CB1uikVeofqnzFao1mH+waOzWmHb12N0iIqKnsOAiIiKjolTIMOtNT3ze0x0yAdgceQeDl4fhYWZemc+1/exd3HyYDVsLJYb61a6AtEREpO9YcBERkdERBAEjA1yxcnhLWKkUiLj5CL0WnMDlxPRSn6NArcH8g0Vjt8a2qwsLdreIiOgZWHAREZHR6tDQHtuD26C2nTnupuag36KT2H+xdJNpbD97F7dTslHNUokh7G4REdFzsOAiIiKj5mZvhR3v+cOvrh2y8tUY/etpLDly/V8n0yh4YuzW2Hb1YK5kd4uIiJ6NBRcRERm9qhZK/BLUCoN8a0EUgW//uoz/bD733Mk0tp25g/iUHFSzVGJQ61qVnJaIiPQJCy4iIiIAJnIZvu7jgS97NYFcJmDbmbsY+HMYHvxjMo38wr/Hbo1rz+4WERH9OxZcREREjwmCgGFt6mD1iJawMlUg8tYj9F5wApfu/T2ZxtYzd3DnUQ6qWaowyJdjt4iI6N+x4CIiIvqHtvWrY0ewP1yrWRRNprH4JPZeSER+oQYLHne3xneoBzOlXOKkRESk61hwERERPUO96pbY8Z4//N3skJ2vxti1kQhaE4G7qTmwt1JhkC/HbhER0Yux4CIiInoOG3MTrB7RCkNa14YoAseuPgBQ1N0yNWF3i4iIXowFFxER0b8wkcvwVR8PfNW7aDKN2nbmeLcVu1tERFQ6nFqJiIioFIb41UF3Dyco5TJ2t4iIqNRYcBEREZVSdSuV1BGIiEjP8JZCIiIiIiKiCsKCi4iIiIiIqIKw4CIiIiIiIqogLLiIiIiIiIgqCAsuIiIiIiKiCsKCi4iIiIiIqIKw4CIiIiIiIqogLLiIiIiIiIgqCAsuIiIiIiKiCsKCi4iIiIiIqIKw4CIiIiIiIqogLLiIiIiIiIgqCAsuIiIiIiKiCsKCi4iIiIiIqIIopA6gD0RRBACkp6dLnISIiIiIiKRUXBMU1wgvwoKrFDIyMgAALi4uEichIiIiIiJdkJGRARsbmxceJ4ilLc2MmEajQUJCAqysrCAIgtRxkJ6eDhcXF8THx8Pa2lrqOAaH72/F4vtbsfj+Viy+vxWL72/F4vtbsfj+Vixden9FUURGRgZq1KgBmezFI7TY4SoFmUwGZ2dnqWM8xdraWvIPnCHj+1ux+P5WLL6/FYvvb8Xi+1ux+P5WLL6/FUtX3t/SdLaKcdIMIiIiIiKiCsKCi4iIiIiIqIKw4NJDKpUKX3zxBVQqldRRDBLf34rF97di8f2tWHx/Kxbf34rF97di8f2tWPr8/nLSDCIiIiIiogrCDhcREREREVEFYcFFRERERERUQVhwERERERERVRAWXAZg9erVqFKlitQxiCqFIAjYsWOH1DHIgHXo0AFTpkzR+XMSlZebN29CEARERUVJHYVI573Mv+csuHTI8OHDIQjCU49r16796/PeeecdXLlypZJSEgGJiYmYPHky3NzcYGpqCgcHB/j7+2Px4sXIzs6WOh7Rvxo+fDj69OkjdQyiEv/vK5VKuLm5YebMmSgsLKzUHC4uLrh37x48PDwq9XVJ973xxhvo3r37M/cdO3YMgiAgOjq6UjPl5+fjhx9+gLe3NywsLGBjY4OmTZvi008/RUJCQqVmKS2F1AGopO7du2PVqlUltlWvXv1fn2NmZgYzM7Pn7s/Pz4dSqSyXfEQ3btyAv78/qlSpgv/973/w9PSESqVCTEwMli1bhpo1a6JXr15SxyQi0gv/3969R9WU9nEA/55Opctxq4lEZRRNTKLCUMmQyXJZGUZWE4XjGmKmYjIuzZD7LfdZhhiXBkthuaWJklxqhCaKSo0y1mSFIZdTznneP7z260yY5uUofD9rtZb93PazW1vP/u397Gc/HfdVKhUOHjyI8ePHw8DAABEREVrldDmWy+VyWFpa6qRtersplUoMHDgQJSUlaNasmVZeTEwM3Nzc0LZt23/d7v97PqtUKnz22WfIysrCd999B3d3d1hYWKCwsBCxsbFYuXIl5s2b96/b1TU+4apl6tSpA0tLS62f6OhoODk5wdTUFNbW1ggODkZ5eblU5+9TCiMjI9GuXTv8+OOP+PDDD2FkZFQDR0LvquDgYOjr6+PXX3+Fn58fHB0d0aJFC/j6+uLAgQPo168fAODatWvw9fWFQqFAvXr14Ofnhz///FOrrbVr18LOzg6GhoZwcHDAli1btPLz8vLQtWtXGBkZoXXr1khMTHxjx0nvh/v37yMwMBAKhQJNmjTBkiVLqpRRqVQICwtD06ZNYWpqik6dOiE5OVnKLysrg7+/P5o2bQoTExM4OTkhNjb2DR4Fvc2ejvu2trYYN24cvL29sW/fPulJbFRUFKysrODg4AAAKC4uhp+fHxo0aAAzMzP4+vqiqKhIau9pvblz56Jx48Zo0KCB9NQsPDwcZmZmaNasmdbN3b9PKXzeqwp79uyBTCaTtp9ea2zcuBE2NjZQKBQIDg6GWq3GwoULYWlpiUaNGiEqKkpnvzvSvb59+8LCwgKbNm3SSi8vL8euXbugVCoBACdOnICnpyeMjY1hbW2NkJAQ3L9/XyrfvHlzzJ49G4GBgahXrx5Gjx6N7t27Y8KECVrt3rx5E4aGhkhKSnpuf5YtW4YTJ07g6NGjCAkJgaurK2xsbODl5YV169Zh7ty5UlmVSoWQkBA0atQIRkZG8PDwQEZGhlZ7KSkp6NixI+rUqYMmTZrgm2++0XrCXJ0xojoYcL0F9PT0sGLFCly8eBGbN2/G0aNHMWXKlJfWyc/Px+7duxEXF8c52fTalJWV4ciRIxg/fjxMTU2fW0Ymk0Gj0cDX1xe3bt1CSkoKEhMTcfXqVQwePFgqFx8fj0mTJiE0NBTZ2dkYM2YMhg8fjmPHjgEANBoNBgwYAENDQ5w5cwbr1q3D1KlT38hx0vsjPDwcKSkp2Lt3L44cOYLk5GRkZmZqlZkwYQJOnTqFn3/+GVlZWRg0aBB69eqFvLw8AMCjR4/g6uqKAwcOIDs7G6NHj8bQoUORnp5eE4dEbzljY2NUVFQAAJKSknD58mUkJiZi//79qKyshI+PD+rWrYvU1FSkpaVBoVCgV69eUh0AOHr0KP744w8cP34cS5cuxaxZs9C3b180bNgQZ86cwdixYzFmzBiUlJS8Ul8LCgpw6NAhHD58GLGxsdiwYQP69OmDkpISpKSkYMGCBZg+fTrOnDnzSvuhmqOvr4/AwEBs2rQJz366d9euXVCr1fD390dBQQF69eqFgQMHIisrCzt27MCJEyeqBFOLFy+Gs7Mzzp07hxkzZmDkyJHYvn07VCqVVGbr1q1o2rQpunfv/tz+xMbGomfPnmjfvv1z85+9KTBlyhTs3r0bmzdvRmZmJuzt7eHj44Nbt24BAK5fv47evXujQ4cOuHDhAtauXYsNGzZgzpw5UhvVGSOqRVCtERQUJORyuTA1NZV+vvjiiyrldu3aJczNzaXtmJgYUb9+fWl71qxZwsDAQJSWlr6JbtN75PTp0wKAiIuL00o3NzeXztkpU6aII0eOCLlcLq5duyaVuXjxogAg0tPThRBCdOnSRYwaNUqrnUGDBonevXsLIYRISEgQ+vr64vr161L+oUOHBAARHx+voyOk90FQUJDw9fUV9+7dE4aGhmLnzp1SXllZmTA2NhaTJk0SQgjx+++/C7lcrnUeCiFEjx49RERExAv30adPHxEaGipte3l5SW0SPfX0XBRCCI1GIxITE0WdOnVEWFiYCAoKEo0bNxYqlUoqv2XLFuHg4CA0Go2UplKphLGxsUhISJDatLW1FWq1Wirj4OAgPD09pe3Hjx8LU1NTERsbK4QQorCwUAAQ586dE0JUva4QQoj4+Hjx7GXjrFmzhImJibh7966U5uPjI5o3b15l3/Pmzfs/f0NUG+Tk5AgA4tixY1Kap6enGDJkiBBCCKVSKUaPHq1VJzU1Vejp6YmHDx8KIYSwtbUV/fv31yrz8OFD0bBhQ7Fjxw4prW3btiIyMvKFfTEyMhIhISFaaf3795euQTp37iyEEKK8vFwYGBiIbdu2SeUqKiqElZWVWLhwoRBCiGnTplX5/7R69WqhUCiEWq2u1hhRXXyHq5b59NNPsXbtWmnb1NQUv/zyC+bNm4fc3FzcvXsXjx8/xqNHj/DgwQOYmJg8tx1bW9t/fPeL6HVJT0+HRqNBQEAAVCoVcnJyYG1tDWtra6lM69at0aBBA+Tk5KBDhw7IycnB6NGjtdpxd3dHdHQ0AEhtWFlZSfmdO3d+MwdE74WCggJUVFSgU6dOUpqZmZk0dQsAfvvtN6jVarRq1Uqrrkqlgrm5OQBArVZj7ty52LlzJ65fv46KigqoVKoX/n0metb+/fuhUChQWVkJjUaDL7/8EpGRkRg/fjycnJy03nO5cOEC8vPzUbduXa02Hj16hIKCAmm7TZs20NP73ySmxo0bay2IIZfLYW5ujtLS0lfqe/PmzbX60rhxY8jl8ir7ftX9UM366KOP0KVLF2zcuBHdunVDfn4+UlNT8f333wN4cl5mZWVh27ZtUh0hBDQaDQoLC+Ho6AgAcHNz02rXyMgIQ4cOxcaNG+Hn54fMzExkZ2dj3759/6p/a9aswf3797FixQocP34cwJO/75WVlXB3d5fKGRgYoGPHjsjJyQHw5Dqjc+fOWk/F3N3dUV5ejpKSEty+ffsfx4jqYsBVy5iamsLe3l7aLioqQt++fTFu3DhERUXBzMwMJ06cgFKpREVFxQsH9BdN9yJ6Ffb29pDJZLh8+bJWeosWLQDgpYu3EL2NysvLIZfLcfbsWcjlcq08hUIBAFi0aBGio6OxfPly6X3byZMna03xInqRpzdaDQ0NYWVlBX39/12a/X0sLy8vh6urq9aF7VPP3mQ1MDDQypPJZM9N02g0z+2Tnp6e1vQxAKisrKxS7lX3Q28PpVKJiRMnYvXq1YiJiYGdnR28vLwAPDkvx4wZg5CQkCr1bGxspH8/79p05MiRaNeuHUpKShATE4Pu3bvD1tb2hf1o2bJllWuQJk2aAHgSDNVWfIerljt79iw0Gg2WLFmCTz75BK1ataq1S17Su8/c3Bw9e/bEqlWrtF6G/TtHR0cUFxejuLhYSrt06RLu3LmD1q1bS2XS0tK06qWlpWnlFxcX48aNG1L+6dOnX+fh0HvOzs4OBgYGWu+X3L59W+szG+3bt4darUZpaSns7e21fp6u6paWlgZfX18MGTIEzs7OaNGiBT/VQdX29EarjY2NVrD1PC4uLsjLy0OjRo2qnI/169d/bX2ysLDAvXv3tP7O833w95ufnx/09PSwfft2/PTTTxgxYoT0ZMjFxQWXLl2qck7a29v/40qETk5OcHNzw/r167F9+3aMGDHipeX9/f2RmJiIc+fOvbTc0wW5nr3OqKysREZGhtZ1xqlTp7RuLqSlpaFu3bpo1qxZtcaI6mLAVcvZ29ujsrISK1euxNWrV7FlyxasW7euprtF77E1a9bg8ePHcHNzw44dO5CTk4PLly9j69atyM3NhVwuh7e3N5ycnBAQEIDMzEykp6cjMDAQXl5e0pSC8PBwbNq0CWvXrkVeXh6WLl2KuLg4hIWFAQC8vb3RqlUrBAUF4cKFC0hNTcW3335bk4dO7xiFQgGlUonw8HAcPXoU2dnZGDZsmNZ0qFatWiEgIACBgYGIi4tDYWEh0tPTMW/ePBw4cADAkzuuiYmJOHnyJHJycjBmzJgqK3ISvQ4BAQH44IMP4Ovri9TUVBQWFiI5ORkhISGvvADGszp16gQTExNMmzYNBQUF2L59e5VV6uj9olAoMHjwYERERODGjRsYNmyYlDd16lScPHkSEyZMwPnz55GXl4e9e/dWWTTjRUaOHIn58+dDCIHPP//8pWW/+uordO7cGT169EB0dDQyMzNRWFiIhIQEHDp0SJqJYGpqinHjxiE8PByHDx/GpUuXMGrUKDx48EBaWTE4OBjFxcWYOHEicnNzsXfvXsyaNQtff/019PT0qjVGVBcDrlrO2dkZS5cuxYIFC/Dxxx9j27ZttfL7AvT+sLOzw7lz5+Dt7Y2IiAg4OzvDzc0NK1euRFhYGGbPng2ZTIa9e/eiYcOG6Nq1K7y9vdGiRQvs2LFDaqd///6Ijo7G4sWL0aZNG/zwww+IiYlBt27dADyZ0hIfH4+HDx+iY8eOGDlyJJcXptdu0aJF8PT0RL9+/eDt7Q0PDw+4urpqlYmJiUFgYCBCQ0Ph4OCA/v37IyMjQ5oqM336dLi4uMDHxwfdunWDpaUlP6xMOmFiYoLjx4/DxsYGAwYMgKOjI5RKJR49eoR69eq9tv2YmZlh69atOHjwoPSZg8jIyNfWPr2dlEolbt++DR8fH633q9u2bYuUlBRcuXIFnp6eaN++PWbOnKlV5mX8/f2hr68Pf3//f/yUkZGREZKSkjB16lTExMTAw8MDjo6OmDx5Mtzd3bFnzx6p7Pz58zFw4EAMHToULi4uyM/PR0JCAho2bAgAaNq0KQ4ePIj09HQ4Oztj7NixUCqVmD59utRGdcaI6pCJv0/SJSIiIiIiegOKiopgZ2eHjIwMuLi41HR3dIIBFxERERERvVGVlZUoKytDWFgYCgsLq7zX/S7hlEIiIiIiInqj0tLS0KRJE2RkZLzz6xPwCRcREREREZGO8AkXERERERGRjjDgIiIiIiIi0hEGXERERERERDrCgIuIiIiIiEhHGHARERERERHpCAMuIiIiIiIiHWHARURE9Bps2rQJDRo0qOluEBFRLcOAi4iIiIiISEcYcBEREf2XRqPBwoULYW9vjzp16sDGxgZRUVFITk6GTCbDnTt3pLLnz5+HTCZDUVERkpOTMXz4cPz111+QyWSQyWSIjIysseMgIqLaQ7+mO0BERFRbREREYP369Vi2bBk8PDxw48YN5Obm/mO9Ll26YPny5Zg5cyYuX74MAFAoFLruLhERvQUYcBEREQG4d+8eoqOjsWrVKgQFBQEA7Ozs4OHhgeTk5JfWNTQ0RP369SGTyWBpafkGektERG8LTikkIiICkJOTA5VKhR49etR0V4iI6B3CgIuIiAiAsbHxC/P09J4Ml0IIKa2yslLnfSIiorcfAy4iIiIALVu2hLGxMZKSkqrkWVhYAABu3LghpZ0/f16rjKGhIdRqtU77SEREbx++w0VERATAyMgIU6dOxZQpU2BoaAh3d3fcvHkTFy9eRGBgIKytrREZGYmoqChcuXIFS5Ys0arfvHlzlJeXIykpCc7OzjAxMYGJiUkNHQ0REdUWfMJFRET0XzNmzEBoaChmzpwJR0dHDB48GKWlpTAwMEBsbCxyc3PRtm1bLFiwAHPmzNGq26VLF4wdOxaDBw+GhYUFFi5cWENHQUREtYlMPDshnYiIiIiIiF4bPuEiIiIiIiLSEQZcREREREREOsKAi4iIiIiISEcYcBEREREREekIAy4iIiIiIiIdYcBFRERERESkIwy4iIiIiIiIdIQBFxERERERkY4w4CIiIiIiItIRBlxEREREREQ6woCLiIiIiIhIR/4D7zHO+yAHqA0AAAAASUVORK5CYII="
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 1000x500 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "ename": "KeyError",
     "evalue": "'volume'",
     "output_type": "error",
     "traceback": [
      "\u001B[1;31m---------------------------------------------------------------------------\u001B[0m",
      "\u001B[1;31mKeyError\u001B[0m                                  Traceback (most recent call last)",
      "File \u001B[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.12_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python312\\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: 'volume'",
      "\nThe above exception was the direct cause of the following exception:\n",
      "\u001B[1;31mKeyError\u001B[0m                                  Traceback (most recent call last)",
      "Cell \u001B[1;32mIn[4], line 48\u001B[0m\n\u001B[0;32m     46\u001B[0m \u001B[38;5;66;03m# 2.6 Диаграмма рассеяния (Цена vs. Объем)\u001B[39;00m\n\u001B[0;32m     47\u001B[0m plt\u001B[38;5;241m.\u001B[39mfigure(figsize\u001B[38;5;241m=\u001B[39m(\u001B[38;5;241m10\u001B[39m, \u001B[38;5;241m5\u001B[39m))\n\u001B[1;32m---> 48\u001B[0m plt\u001B[38;5;241m.\u001B[39mscatter(data[\u001B[38;5;124m'\u001B[39m\u001B[38;5;124mprice\u001B[39m\u001B[38;5;124m'\u001B[39m], \u001B[43mdata\u001B[49m\u001B[43m[\u001B[49m\u001B[38;5;124;43m'\u001B[39;49m\u001B[38;5;124;43mvolume\u001B[39;49m\u001B[38;5;124;43m'\u001B[39;49m\u001B[43m]\u001B[49m, alpha\u001B[38;5;241m=\u001B[39m\u001B[38;5;241m0.5\u001B[39m)\n\u001B[0;32m     49\u001B[0m plt\u001B[38;5;241m.\u001B[39mtitle(\u001B[38;5;124m'\u001B[39m\u001B[38;5;124mДиаграмма рассеяния: Цена vs Объем\u001B[39m\u001B[38;5;124m'\u001B[39m)\n\u001B[0;32m     50\u001B[0m plt\u001B[38;5;241m.\u001B[39mxlabel(\u001B[38;5;124m'\u001B[39m\u001B[38;5;124mЦена\u001B[39m\u001B[38;5;124m'\u001B[39m)\n",
      "File \u001B[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.12_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python312\\site-packages\\pandas\\core\\frame.py:4090\u001B[0m, in \u001B[0;36mDataFrame.__getitem__\u001B[1;34m(self, key)\u001B[0m\n\u001B[0;32m   4088\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39mcolumns\u001B[38;5;241m.\u001B[39mnlevels \u001B[38;5;241m>\u001B[39m \u001B[38;5;241m1\u001B[39m:\n\u001B[0;32m   4089\u001B[0m     \u001B[38;5;28;01mreturn\u001B[39;00m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_getitem_multilevel(key)\n\u001B[1;32m-> 4090\u001B[0m indexer \u001B[38;5;241m=\u001B[39m \u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mcolumns\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mget_loc\u001B[49m\u001B[43m(\u001B[49m\u001B[43mkey\u001B[49m\u001B[43m)\u001B[49m\n\u001B[0;32m   4091\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m is_integer(indexer):\n\u001B[0;32m   4092\u001B[0m     indexer \u001B[38;5;241m=\u001B[39m [indexer]\n",
      "File \u001B[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.12_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python312\\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   3807\u001B[0m     \u001B[38;5;28;01mif\u001B[39;00m \u001B[38;5;28misinstance\u001B[39m(casted_key, \u001B[38;5;28mslice\u001B[39m) \u001B[38;5;129;01mor\u001B[39;00m (\n\u001B[0;32m   3808\u001B[0m         \u001B[38;5;28misinstance\u001B[39m(casted_key, abc\u001B[38;5;241m.\u001B[39mIterable)\n\u001B[0;32m   3809\u001B[0m         \u001B[38;5;129;01mand\u001B[39;00m \u001B[38;5;28many\u001B[39m(\u001B[38;5;28misinstance\u001B[39m(x, \u001B[38;5;28mslice\u001B[39m) \u001B[38;5;28;01mfor\u001B[39;00m x \u001B[38;5;129;01min\u001B[39;00m casted_key)\n\u001B[0;32m   3810\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;250m \u001B[39m\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[0;32m   3817\u001B[0m     \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_check_indexing_error(key)\n",
      "\u001B[1;31mKeyError\u001B[0m: 'volume'"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 1000x500 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "execution_count": 4
  },
  {
   "metadata": {},
   "cell_type": "code",
   "outputs": [],
   "execution_count": null,
   "source": ""
  }
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