assignment_2.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\tomge\\AppData\\Local\\Temp\\ipykernel_9864\\377724952.py:2: DeprecationWarning: \n",
      "Pyarrow will become a required dependency of pandas in the next major release of pandas (pandas 3.0),\n",
      "(to allow more performant data types, such as the Arrow string type, and better interoperability with other libraries)\n",
      "but was not found to be installed on your system.\n",
      "If this would cause problems for you,\n",
      "please provide us feedback at https://github.com/pandas-dev/pandas/issues/54466\n",
      "        \n",
      "  import pandas as pd\n"
     ]
    }
   ],
   "source": [
    "# loading necessary libraries\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "from sklearn.linear_model import LinearRegression as lm\n",
    "from sklearn.tree import DecisionTreeClassifier as treem\n",
    "from sklearn.tree import plot_tree as treeplt\n",
    "from sklearn.model_selection import train_test_split as tts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# loading datasets\n",
    "sberbankTrain = pd.read_csv('sberbank-russian-housing-market/train.csv')\n",
    "sberbankTest = pd.read_csv('sberbank-russian-housing-market/test.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>full_sq</th>\n",
       "      <th>life_sq</th>\n",
       "      <th>floor</th>\n",
       "      <th>max_floor</th>\n",
       "      <th>material</th>\n",
       "      <th>build_year</th>\n",
       "      <th>num_room</th>\n",
       "      <th>kitch_sq</th>\n",
       "      <th>state</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>30471.000000</td>\n",
       "      <td>24088.000000</td>\n",
       "      <td>30304.000000</td>\n",
       "      <td>20899.000000</td>\n",
       "      <td>20899.000000</td>\n",
       "      <td>1.686600e+04</td>\n",
       "      <td>20899.000000</td>\n",
       "      <td>20899.000000</td>\n",
       "      <td>16912.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>54.214269</td>\n",
       "      <td>34.403271</td>\n",
       "      <td>7.670803</td>\n",
       "      <td>12.558974</td>\n",
       "      <td>1.827121</td>\n",
       "      <td>3.068057e+03</td>\n",
       "      <td>1.909804</td>\n",
       "      <td>6.399301</td>\n",
       "      <td>2.107025</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>38.031487</td>\n",
       "      <td>52.285733</td>\n",
       "      <td>5.319989</td>\n",
       "      <td>6.756550</td>\n",
       "      <td>1.481154</td>\n",
       "      <td>1.543878e+05</td>\n",
       "      <td>0.851805</td>\n",
       "      <td>28.265979</td>\n",
       "      <td>0.880148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>38.000000</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.967000e+03</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>49.000000</td>\n",
       "      <td>30.000000</td>\n",
       "      <td>6.500000</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.979000e+03</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>2.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>63.000000</td>\n",
       "      <td>43.000000</td>\n",
       "      <td>11.000000</td>\n",
       "      <td>17.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.005000e+03</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>3.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>5326.000000</td>\n",
       "      <td>7478.000000</td>\n",
       "      <td>77.000000</td>\n",
       "      <td>117.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>2.005201e+07</td>\n",
       "      <td>19.000000</td>\n",
       "      <td>2014.000000</td>\n",
       "      <td>33.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            full_sq       life_sq         floor     max_floor      material  \\\n",
       "count  30471.000000  24088.000000  30304.000000  20899.000000  20899.000000   \n",
       "mean      54.214269     34.403271      7.670803     12.558974      1.827121   \n",
       "std       38.031487     52.285733      5.319989      6.756550      1.481154   \n",
       "min        0.000000      0.000000      0.000000      0.000000      1.000000   \n",
       "25%       38.000000     20.000000      3.000000      9.000000      1.000000   \n",
       "50%       49.000000     30.000000      6.500000     12.000000      1.000000   \n",
       "75%       63.000000     43.000000     11.000000     17.000000      2.000000   \n",
       "max     5326.000000   7478.000000     77.000000    117.000000      6.000000   \n",
       "\n",
       "         build_year      num_room      kitch_sq         state  \n",
       "count  1.686600e+04  20899.000000  20899.000000  16912.000000  \n",
       "mean   3.068057e+03      1.909804      6.399301      2.107025  \n",
       "std    1.543878e+05      0.851805     28.265979      0.880148  \n",
       "min    0.000000e+00      0.000000      0.000000      1.000000  \n",
       "25%    1.967000e+03      1.000000      1.000000      1.000000  \n",
       "50%    1.979000e+03      2.000000      6.000000      2.000000  \n",
       "75%    2.005000e+03      2.000000      9.000000      3.000000  \n",
       "max    2.005201e+07     19.000000   2014.000000     33.000000  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# descriptive statistics for numerical variables\n",
    "sberbankTrain.loc[:, sberbankTrain.columns.isin(['full_sq','life_sq','floor','max_floor','material','build_year','num_room','kitch_sq','state'])].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>product_type</th>\n",
       "      <th>sub_area</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>30471</td>\n",
       "      <td>30471</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>unique</th>\n",
       "      <td>2</td>\n",
       "      <td>146</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>top</th>\n",
       "      <td>Investment</td>\n",
       "      <td>Poselenie Sosenskoe</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>freq</th>\n",
       "      <td>19448</td>\n",
       "      <td>1776</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       product_type             sub_area\n",
       "count         30471                30471\n",
       "unique            2                  146\n",
       "top      Investment  Poselenie Sosenskoe\n",
       "freq          19448                 1776"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# descriptive statistics for categorical variables\n",
    "sberbankTrain.loc[:, sberbankTrain.columns.isin(['product_type','sub_area'])].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "product_type\n",
       "Investment       19448\n",
       "OwnerOccupier    11023\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sberTrainAggProdT = sberbankTrain['product_type'].value_counts()\n",
    "sberTrainAggProdT"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "sub_area\n",
       "Poselenie Sosenskoe               1776\n",
       "Nekrasovka                        1611\n",
       "Poselenie Vnukovskoe              1372\n",
       "Poselenie Moskovskij               925\n",
       "Poselenie Voskresenskoe            713\n",
       "                                  ... \n",
       "Molzhaninovskoe                      3\n",
       "Poselenie Shhapovskoe                2\n",
       "Poselenie Kievskij                   2\n",
       "Poselenie Klenovskoe                 1\n",
       "Poselenie Mihajlovo-Jarcevskoe       1\n",
       "Name: count, Length: 146, dtype: int64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sberTrainAggSubArea = sberbankTrain['sub_area'].value_counts()\n",
    "sberTrainAggSubArea"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "material\n",
       "1.0    14197\n",
       "2.0     2993\n",
       "5.0     1561\n",
       "4.0     1344\n",
       "6.0      803\n",
       "3.0        1\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sberTrainAggMaterial = sberbankTrain['material'].value_counts()\n",
    "sberTrainAggMaterial"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "build_year\n",
       "2014.0    919\n",
       "2015.0    824\n",
       "0.0       530\n",
       "2013.0    464\n",
       "1970.0    418\n",
       "         ... \n",
       "1948.0      1\n",
       "1895.0      1\n",
       "1925.0      1\n",
       "4965.0      1\n",
       "71.0        1\n",
       "Name: count, Length: 119, dtype: int64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sberTrainAggBldYr = sberbankTrain['build_year'].value_counts()\n",
    "sberTrainAggBldYr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "state\n",
       "2.0     5844\n",
       "3.0     5790\n",
       "1.0     4855\n",
       "4.0      422\n",
       "33.0       1\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sberTrainAggState = sberbankTrain['state'].value_counts()\n",
    "sberTrainAggState"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,6))\n",
    "sns.barplot(x = sberTrainAggProdT.index, y = sberTrainAggProdT.values)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,6))\n",
    "sns.barplot(x = sberTrainAggSubArea.index, y = sberTrainAggSubArea.values)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,6))\n",
    "sns.barplot(x = sberTrainAggMaterial.index, y = sberTrainAggMaterial.values)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,6))\n",
    "sns.barplot(x = sberTrainAggBldYr.index, y = sberTrainAggBldYr.values)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,6))\n",
    "sns.barplot(x = sberTrainAggState.index, y = sberTrainAggState.values)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,6))\n",
    "sns.histplot(sberbankTrain['full_sq'], kde = True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,6))\n",
    "sns.histplot(sberbankTrain['life_sq'], kde = True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,6))\n",
    "sns.histplot(sberbankTrain['floor'], kde = True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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NGCJXUJikYw0j9Px3b0WDXG7zVJYHAACALoSwBXRAndPz395HCVuhdslmSE63qbJq9toCAADoqQhbQDs5XW41uw1JrTc09rIZUq9wuySpmKGEAAAAPRZhC2inmkZPt1aI3VB06NGnPSa2rP++mxUJAQAAeizCFtBO3rCVEG6XYRhHbZMU4enZYpEMAACAnouwBbTToWHrWJJaerbYawsAAKDnImwB7eQLW2HHDlveYYT0bAEAAPRchC2gnWobXJKkhPBjb1PnG0ZIzxYAAECP5dewtXLlSv3whz9UamqqDMPQO++80+q8aZqaPXu2evfurbCwME2YMEFbt25t1aa8vFxTp05VdHS0YmNjNX36dNXU1LRq8/XXX+s73/mOQkND1bdvXz366KNWfzR0Y20ZRugNYmXVjaekJgAAAHQ9fg1btbW1OvPMMzV37tyjnn/00Uf11FNPad68eVq9erUiIiI0adIkNTR8u3fR1KlTtXHjRi1evFgLFy7UypUrdeONN/rOV1VVaeLEierfv7/WrVunP//5z3rwwQf1/PPPW/750D21ZRhhTIjnV6uyvlnNLvcpqQsAAABdy7HHQZ0Cl1xyiS655JKjnjNNU0888YTuv/9+XXrppZKkV155RcnJyXrnnXd01VVXKT8/Xx988IHWrl2r0aNHS5L++te/6vvf/77+8pe/KDU1Va+++qqampr04osvKjg4WMOGDVNubq4ee+yxVqEMaKu29GxFBttkGJJpSgfrmpQUdeR+XAAAAOjeuuycrR07dqikpEQTJkzwHYuJidGYMWOUk5MjScrJyVFsbKwvaEnShAkTZLPZtHr1al+b888/X8HBwb42kyZNUkFBgQ4ePHjU925sbFRVVVWrByB5wlNdkyds9TpO2LLbDMWHe/7OHahpOiW1AQAAoGvpsmGrpKREkpScnNzqeHJysu9cSUmJkpKSWp13OByKj49v1eZo1zj0PQ73yCOPKCYmxvfo27fvyX8gdAsNLsltSpKp2NBjhy1Jio/whK3yWsIWAABAT9Rlw5Y/3XfffaqsrPQ9ioqK/F0Suoh6z0KECrV7eq+Oxxu2DhC2AAAAeiS/ztk6npSUFElSaWmpevfu7TteWlqqESNG+NqUlZW1ep3T6VR5ebnv9SkpKSotLW3Vxvvc2+ZwISEhCgkJ6ZTPYTWn06n8/PxWxzIzM+VwdNlbG9DqPSMIFdaGH29CZEvPVg0rEgIAAPREXbZnKyMjQykpKVqyZInvWFVVlVavXq3s7GxJUnZ2tioqKrRu3Tpfm6VLl8rtdmvMmDG+NitXrlRzc7OvzeLFizVkyBDFxcWdok9jnfz8fM1ZsFyv5OzUKzk7NWfB8iPCFzqPL2wdfwShJCkhwhPY6dkCAADomfwatmpqapSbm6vc3FxJnkUxcnNzVVhYKMMwNGvWLP2///f/9J///Ed5eXm69tprlZqaqssuu0ySpwfn4osv1i9+8QutWbNGn332mWbOnKmrrrpKqampkqSf//znCg4O1vTp07Vx40a98cYbevLJJ3XnnXf66VN3vsS0dKVmDFFqxhAlpqX7u5xurd7lGTrYlp4thhECAAD0bH4da/bFF1/oggsu8D33BqBp06Zp/vz5uueee1RbW6sbb7xRFRUVOu+88/TBBx8oNPTbZbRfffVVzZw5UxdddJFsNpsuv/xyPfXUU77zMTEx+uijjzRjxgyNGjVKvXr10uzZs1n2HR3i7dkKd5gnbPvtMELCFgAAQE/k17A1fvx4meaxv7QahqGHHnpIDz300DHbxMfH67XXXjvu+wwfPlyffPJJh+sEvLwLZLRvGCFztgAAAHqiLjtnC+iK2rNABsMIAQAAejbCFtBGpmmqzjeM8MTtfcMICVsAAAA9EmELaKOqRrdcZtsXyEho6dmqqGuW0+W2sjQAAAB0QYQtoI321XombEUE22U//n7GkqTY8GAZLe3K6+jdAgAA6GkIW0AbldV6xhBGhQa1qb3dZigunKGEAAAAPRVhC2ijfXXesNX2RTy9i2Sw/DsAAEDPQ9gC2qisZRhhe8KWd97Wfnq2AAAAehzCFtBG+1qGEUa3cRihdOjGxuy1BQAA0NMQtuB3NY1urdxr6OvdFf4u5bj2daBnyzeMkJ4tAACAHoewBb/L2V2n0npDywr2aW+dv6s5tvYukCFJCREhktjYGAAAoCcibMHvtpd/G0RWlxkqq3H6sZqjq29yqarRs1dWu+ZstQwjPMACGQAAAD0OYQt+901L2AqyG2p2G3rkk/1qdLr8XFVreyrqJUkOw1SIo+2/NgwjBAAA6LkIW/Arl9vUjopmSdL3s3or2GZqW3mTHl64yc+VtVbcErbCHZJhtGFH4xbfDiNkgQwAAICehrAFv9p5oFYNTlN2w1S/+HCdk2TKkPTPzwu1ble5v8vz2XNI2GoP32qE9GwBAAD0OIQt+NXG4ipJUkywZDMM9Q6XxqSFSZLW7Troz9Ja8fZsRbR9bQxJ3w4jPFjXLKfL3dllAQAAoAsjbMGvNhZXSpJig789NiDO82RLaY0/SjqqPQe9PVtmu14XFx4s76jDg3XNnV0WAAAAurB2DooCOtemlp6tuJBvQ0y/WE/30ZbSar/UdDQdHUZotxmKCw9WeW2TymublBgV0in1OJ1O5efn+55nZmbK4eDXGQAAoCvh2xn8xjRNbdjT0rN1SAbp3xK2tpbWyO02ZbO1fUEKq3Q0bEmeoYTltU06UNMoKapT6snPz9ecBcuVmJaufbt36q4rpaysrJO6JgEOAACgc/FNCn6zt7JBB+uaZTOkmEPmQvWOdCjYblN9s0u7D9arX0K4/4qUZ8XEksoGSR0PW1Lnb2ycmJau1IwhnXY9KwIcAABAT8acLfiNd3GMfjFBsh/yN9FuMzQwKVKSVNAFhhKWVTfI6TZlN6Qwe/tf3yuAViT0BrjEtHR/lwIAABDwCFvwG+/iGN4FMQ41JNkTtrrCvC3vSoQJ4Xa1Y4stH6t6tgAAANC1EbbgN96erQHxR66nPjjZM7epK4St3S0rESZGdGzUbbx3Y+MaNjYGAADoSQhb8BvvSoRH79nyhK2CEv+HLe/iGEkRHRhDqMAaRggAAIDOQ9iCXxysbfKFmKOFrdNawtb2fbV+3wzYO4wwsSOrY4hhhAAAAD0VYQt+4R1C2D8hXBHBR/41TIsLU1iQXU0ut3YeqDvV5bXi3dA4KfIkwxbDCAEAAHoUwhb8wrs4xrDU6KOet9kMndaySMZWP8/bKq7wLPue2MFhhAktc7YYRggAANCzELbgF96erWGpMcds410kw5/Lv5um6Rvu2NFhhAktc7Yq6pvlcpudVhsAAAC6NsIW/CJ/rydsDT1Gz5b07SIZ/lyRsKrBqZpGp6SO92zFhQfLMCTTlA7W0bsFAADQUxC2cFymaepfX1fqy/2G9lV3zpwjl9vUrpZ5WIMSI4/Z7rQUb9iq6ZT37QjvfK34iGCFOjr262K3GYoN8yxvf6CGsAUAANBTELZwXAWl1Xotr1LfVBl6bU2hlhUb+nRXndwnMRxub2W9mlxuBdttSo0NO2Y775ytHftr1eh0tfn6pmmqrF76y2f79acPNss0O16rdwhhn+PU2RYJkS17bdWySAYAAEBP0bFJKOgxPv/mgCQp2Gaq2TS0v8HQnz7dr6CYHbrhOwM6dE1vr1bf+DDZbcYx26VEhyoq1KHqBqd27K/V6SnHHnIoeYbpbSiu1FdFFdpfY5NUpxU7v9F3BvXS2EG9OlTrul0HJUmDko7dA9cW3hUJWSQDAACg56BnC8f1+fZySdJpMaauH5uhfpGeXqJPt+3v8DV37K+VJKUnRBy3nWEYvv222rK58aaDhpbkl2l/TZPshqn0WM/QvaeWbu1wrcsLyiRJ44ckdvga0rcbG+/vpKGYAAAA6PoIWzgmt9vU6h2enq2kMCky1KHB0Z6wlVtU0eHhebsOeMJW/xOELenbzY1PtEiGaZra2TK1a1T/OP2gn6nZ4xMVZDf0+fZyrd1Z3u4691TUa3NJtWyG9N3TTi5spUR7hiEWVzac1HUAAAAQOAhbOKYtZdU6WNesELuhOM+UI8WGSEE2qaKuucObDXtfl94r/IRth7TM2zrRIhk7DjarzmnIYTM0JiNewXYpMcKhK0alSZKeWtL+3q1lmz29Wmf1i1NseHC7X3+oPnGesOVdcAMAAADdH2ELx+SdrzU0KUTeqVU2QxoU7wke6wsPdui6O9s4jFD6dkXCjXsqj9uTtnq3J8T0iw9XkP3bv9a3fHeQ7DZDn2zdr9yiinbV6Q1bF5ye1K7XHY13gY3dFYQtAACAnoKwFYCcTqfy8vKUl5enLVu2yLRoo1zvfK2spJBWx0/r5Xm+vrCi3dd0u03tKm/p2WpD2DozLVYOm6HiygYVlh+7J+3z3Z5zAxJbX7NfQrguG9FHkvR0O+ZuNTS79Nk3nnlpF3ZC2EqjZwsAAKDHIWwFoPz8fM1ZsFyv5OzUKx99oYMV7Z+PdCKHztfKSg5tdW5IL0/PVnt7iiSppKpBTU63HDZDqbGhJ2wfEeLQyH6xkqTPth04apvdB+u0/WCzJFMZvY4McLdeMFCGIX2cX6aNxZVtqvPz7QfU0OxW75hQnd7Su3YyvD1b+2sa1dDc9mXsAQAAELgIWwEqMS1dqRlDFJeSasn1vfO1woLsGpTQer7SkJaerfy9Vapval9w8A4h7BcfLoe9bX/9xg70LNvu7Wk63MebSiVJvUKl8OAjdzMYmBipHwz3/Jzuf2eDnC73Cd/TO4Rw/JAkGcaxl6dvq9jwIIUH2yVJxQwlBAAA6BEIWzgq73yt0elxchy2F1ZiuF2JUSFyuk1taGNPkZd3cYz+CSdeHMNrXMseWTnfHDjqZsqL8z1hKzX82MMp7714iKJCHVpfWHHCxTJM09TSliXfO2MIoeRZxt7bu7WHsAUAANAjELZwVN75WucOSDjinGEYGtk3VpKU2855W+1Z9t1rRN9YhQXZVV7bpM2H7bdVWdes1S219jnOJdPiwvX7H2dJkp5etk1rdhx76OXuKqeKyusV7LBp3KAjP39HsSIhAABAz0LYwhEOna91tLAlSSP7xUmS1he1b0XCnS1h62hzq44l2GHTORnxkqRVhw0lXFZQJqfbVN+YIEUGHf86PzozVVeMSpPblGa9vl6Vdc1Hbbd2jycMnTsg4ajDEjuKni0AAICehbCFIxw6X2t4WsxR24zoYM/Wzv3tH0YoSee1DCX8bFvrsLW4Zb7WuWlhbbrOgz8apvSEcBVXNuiXr6/Xlv2N8q4o73Kb2lMrfbTNs6fXBUNObiPjw9GzBQAA0LN03v9tj27j0PlaQcdYxGJ4WoxshlRc2aCSygalxJx4ZUHPsu9t32PrUGNbhvOt2VGuZpdbQXab6ptcWt4yt2pMWphWb6044XUiQxx68qqRuvzZVVqxZZ9WbJFC7YbSavdqz8F61TfbJDkVFeLQpGEp7arxROjZAgAA6Fno2cIR1u70DA081hBCybMk+5CUaElSbhuHEpZVN6qh2S27zfD18rRVZkq04iOCVdvk0lctS84/vGiTaptc6hMbpsGHrZh4PGf2jdUr08/R5KzeCnMYanAZ2lZWo/pml0Ltpn6cGaV3Z45Tamz7ajwR315bhC0AAIAegZ4tHMG7f5Z3f6tjGdE3Vvl7q7S+qEIXn9H7hNfd0bLse9+4sGP2mB2LzWYoe0CCFuXt1WfbDmh/TaNeW10ow5D+dPlw2Rr2tut6Ywf20tiBvfRl7td6YvkuNYX1UlJ0qIKqdut/zorTgMTIdl2vLfrEeoZOllQ2yOU2Zbed/JLyAAAA6Lro2UIrZdUN2lNRL8OQhqfFHretN4ytb+O8rY6sRHgo71DC/+bt1b3/zpMk3XT+QJ03uFeHridJQXZDyeHSmAEJyugVISvzT1JUiILshpxuU6VVDda9EQAAALoEwhZa8S54MTgpUpEhx+/4PKslbOXtrmzTRsHePbbS27k4hte4ls2NC0qrVVnfrDP7xuquiad16Fr+YLMZvrltDCUEAADo/ghbaOWr3RWSvl1t8HgG9IpUVKhD9c0uFZRWn7D9zpZhhOntWPb9UP0Twn2LTESGOPTUVSPaPRzR33yLZLAiIQAAQLcXWN9UYTnvfK0RfeNO2NZmM3yhrC1DCb17bLV3JUIvwzB06YhUOWyGHpmS1eHhiP7knbdFzxYAAED3xwIZ8HG7TX1dVClJOrPv0ffXOtzIvrH6ZOt+rS+s0NXn9j9mO9M0tetAx/bYOtTdk4bolvEDFRV6gh2MuyjvKoy7/dSz5XQ6lZ+f73uemZkph4N/BgAAAKzAtyz4bN9fo+pGp8KC7BqSHNWm14xombd1ouXf91U3qr7ZJZshpcV1PGwZhhGwQUuS0vy811Z+fr7mLFiuxLR07du9U3ddKWVlZfmlFgAAgO6OsAUf71DArD4xcrRxLpR3uOE3+2pVWdesmPCjByHvsu9pceEKdvTc0avenq09B+v8VkNiWrpSM4b47f0BAAB6ip77rRdH8M3XOsH+WoeKjwj2DQvMbVlc42i2ltVIOrkhhN1Bn0N6tkzT9HM1AAAAsBJhCz7elQjPPMH+Wocb2bJIRu5xFslYvaNcknRWvxMvvNGd9Y71LP3e0OxWeW2Tn6sBAACAlQhbAW6vK0oba6O0Y3+t3CfRU9LQ7NLmvZ7l29vTsyVJI1sC1PpjzNsyTVM53xyQJGUPTOhwjd1BiMOupKgQSaxICAAA0N0xZyuAldc2qcDZS5Kh/3xVrKhQh/qFSbVNJ95g+HAb9lTK6TaVGBWi1JaNd9vKu/x7blGFTNOUYRitzm8rq9H+mkaFOGwa2c4g1x31iQtTWXWj9hys1/B29iICAAAgcNCzFcA+3bZfkqFwm1MhDpuqG5zaeNCmP6zc1+75QN/urxV7RFg6kcze0Qp22FRR16ydB45c+GFVS6/W2enxCnHY23Xt7qiPn1ckBAAAwKlB2ApQpXWeFf4MmTozoko3nJehiUOTZTNMfV3a6As4bXVo2GqvYIdNWX08+3KtLzxyKOGqb/ZLYgihl7/32gIAAMCpQdgKQC63qa/KPb1PqfYqhdtdcthtyuwdrQEt22M98fGWdvVunUzYOvR13ut4ud2mPt/uWRwjSRXKy8tTXl6enE5nh96nO/D3XlsAAAA4NQhbAWjpjlpVNhkKcdiUbm/dk3R6rKkgm7R250F9tq1tvVtl1Q3afbBehiFlpcV0qCbvXKz1h61IuGlvlSrrmxXmMPTe0hy9krNTcxYsV35+fofepzv4dq8twhYAAEB3xgIZAaa20al/5FZIks7JiJe9cFur82EO6eLBkXqvoEZPfLxF4wYlHHUOltPp9AWe/2yukiQNiA3Srq2bJUmZmZlyONr+18O7ImH+3io1NLsUGuSZm+VdhXBYUoiSQ9u/me6hdXakrq6oT6xnr7Gig3VHXVAEAAAA3QM9WwHmuRXf6GCDWxEOU8OP0Qt1xbAYhThs+mLXwZZFNI6Un5+vOQuW6+VVO/Vmnqd3rLH0mw73PKXGhCoxKkROt6kNeyp9x73ztYantG+Fw8Pr7E49Yum9whUWZPcsaFJc5e9yAAAAYBHCVoC5+IzeOjMlRMMTTDlsR7998WF2/XxMP0nSEx9vPebcrcS0dNl79VdlkyFDbg3oFa7UjCFKTEtvd12GYfg2N16z0zNHq9nl1pqWzYyHJ3csbHnr7GhdXVGIw65xg3pJkpYXlPm1lmaXqf9bt1sPL9ykygaXX2sBAADobghbAWZoarQevjBJfcKP3+6W7w5UiMOmdbsOakn+sb/Qb2rpWUm01SrI1vFNkSVpzADPaoNPLN6qd3P3KG9PpWqbXIoJC1JGXNBJXbu7ueD0REnSsoJ9fnn/JqdbWyqlG/9TrP9d8JX+/ukOzV5apibyFgAAQKcJ7MkvPZRhGDrRNJ+k6FD9z7h0Pbdiux5auEnnDe7lm0fl5XRLBSXVkqTe9mpJJxeIpo7ppzU7DujDjaW6/fVcDe0dLUk6d0C8bAEyL8ntcmnLli2+51bNERs/JEmSZ6n8g7VNiosI7vT3OJZ99dLCVTtV32yT5FJiVIhcblPbDzapos5Qanr7N8UGAADAkejZ6sZuu3CwUqJDVVhep+dWbD/i/J5aqcnlVnSoQ7FGw0m/X2iQXc9OHaUbzx8gybMSoSSNHdjrpK99qhwoKdI/V26yfI5Yn9gwDUmOktuUVm49+d6tuma3Vm3br1Xb9svtPnYP5ae76rSyxFB9s0sRDlMzzonXJ/dcoFdvGKPIYJvKGw2993WxXOQtAACAk0bY6sYiQxz6zeRMSdIzy7epqLyu1fkd1Z7epmGpMSfsKWsrm83Qr7+fqT/8OEt2m+ei5w0OnLAlSfG9+1o2R8zpdPr2GjsjwfPzWZpf2qFrNbqkpZvL9EGRoave3K2fv7BaP39htS558hP9N2/vEaHrhU+269FP98ttGhqYGKGJaaYuHhyp0CC7MntH63cXJsphmNp9sF5r9gVGTyQAAEBXxjDCbu4Hw3vrX2sKteqbA/rde5v0wrTRkqTi6mbtazBkSMrsHaXtezr3fX8+pp+Gp8XoQG2TBiZGKq+kc68fqLyrKyampetAvSTZtGxzqVxuU6bbdURP2rGGMTa5TH1aYqi8sVKSJxj1iQ1TVX2zCkqrdeurX2pIcpQGJkXoYG2z9tc0amtZjSRpYLSp72f1VsnO6lbXPC0hROelmFpRYmh3raFtB5qUZcUPAQAAoIcgbHVzhmHooUuH6eInPtHH+aV68D8bVd/kUs5Wz5Ls/RLCFRVqzeIVZ/Tp2AbJ3c2he4Vt2bJFvVL7KzVjiJLdpj4r3aqqRre+3l0hR+VuXxCTpH27d+quK6WsrNaRxzRNPb36gMobPRtbj0pw6pbz+uo7Z49QZV2zXvxsh178dIcKSqtVUNo6UF03MlbVFeXHnEOXGCYNSY7S5pJqvZVfpR+P7+yfBgAAQM9B2OoBBiVFafp5GXpu5XbNX7Wz1bkz02L9UlNPcmhv1pZ1X6hXxhD1kWS3GUoOk3bXSss2l+l7vb9d5v545q3YrmU76mTI00PlqCxSbKhn8ZOY8CDd8b3TdP24jJa5V6Ziw4MUFx6sjF4RqtjzjV7JKT/u9c/qF6fNJdX6rLBOhQfq1C/hBEtfAgAA4KgIWz3ELy8arIq6ZjU6XUrvFSF7XbnyCvcpo1eEv0vrEbwhat+ena2O9w43tbvW0LKCffpe7xP3BC7eVKpHP9wsSRqRYKpffLiKK49sFxMepKvP7X/E8Yo2DBdNjApRcpip0npDL3y6XQ9desaJXwQAAIAjELZ6iIgQh/50xXDf87y8PBWW+GePJ3wrJczz37w9lTpYH3nctrlFFfrlv9bLNKVLBkcq0lVlWV2nx3rC1ptfFOn2iwYrITLEsvcCAADorliNEPCjUIc0KN6zx9bS7bXHbLd9X42un79W9c0ufWdwL904Os7SuhJDPXU1NLv1Ss4uS98LAACguyJs4aQcupR5Xl6enE6nv0sKON9N98yJmp9boW1HGRJYVt2ga19co/LaJmX1idGzV4+Sw2bt0uyGIU0ZGiVJeiVnp+qbXJa+HwAAQHdE2MJJ8S7+YPUmwN3Zj06P0nXj0iVJ6w/YtGZHuUzTlMuUNu9r1P+8uFa7D9arf0K4XvyfsxUZcmpG/47tG65+8eE6WNesf60pPCXvCQAA0J0QtnDSvIs/WLEJcE9gMwzN/sFQ/TzLs0BGzvYDenVNod7Zaejuj0q1aW+VekUG65Xrz1Fi1KmbO2W3GbrpuwMkSc8s/4beLQAAgHYibMEShw8v3LJli0y36e+yuizDMPSz4TE6M8EtSTpQ0yS3aSg6xKZJw5L16g3nqn/CqV858spRfZUWF6b9NY36x+c7T/n7AwAABDJWI+zGDt1M1yszM1MOh/W3/dC9pSS12l8Kx3ZajDSgXx/VNDplr9qrW8/vq+HDh5/4hRYJdtj0y4sG657/+1rzVmzXz8f0P2XDGAEAAAId35q6scMDz77dO3XXlVJWVtYpef9DN+g9fH8pHFu/eM+CGcUNe2UY7V8I4/CQfbIBe8rIPnp2+Tfasb9WL6/aqRkXDOrwtQAAAHoShhF2c97Aw5yqnqOzFy1x2G26/aLBkqTnV25XVUNzZ5QJAADQ7RG2gG6osxct+eGZqRqcFKnK+mb9/ZMdnXJNAACA7o5hhAgYbpdLW7ZsaXWsLUPk/Dl3rbMc/hk8C44EnbL3t9sMzZpwmma89qWeW/mNxg5M0JgBCafs/QEAAAJR4HzbRI93oKRI/9xcoUEHgiW1fQ6av+eudYausODIJWek6MLTk7R0c5mun79W/7hhjM7qF3cKKwAAAAgshC0ElPjefX2LbrTHoYt1BCp/Lzhisxl6ZupZmv7yWn227YCmvbhGr91wrrLSYjp0vc5eyAMAAKCr6VFztubOnav09HSFhoZqzJgxWrNmjb9LAgJKaJBdf7t2tM5Jj1d1g1PXvLhar68pVGVd+xfN6OyFPALF4XvQ5eXlyel0+rssAABggR7zfyO/8cYbuvPOOzVv3jyNGTNGTzzxhCZNmqSCggIlJSX5uzwgYATbpLvOCdfsmhoV7G/Sr97K0wPvbtAFQ5L0ndMS1SsiWLHhwYoJC5LbNNXkcqvJ6VZ9s0u1jU7VNjpV3eDU9qJKFYdlaH9DjGqCM/T8F+XqX1ygiBCHIkMdigyxKyLYocgQh8KC7QoLtivIkHbv2q5Qh6EQuyG7zQiYHjGny60Gp1tffrVBz7y3SsmpfeWwSQf2BN6wVgAA0DZd/xtKJ3nsscf0i1/8Qtddd50kad68eVq0aJFefPFF/epXv/JzdUDXcrzFSPLz8/XsOyuVmZquYLe0/aBTta5gfbSpVB9tKm3nOxlSZZUkQzsLaqSCbe18talQ+y6FBTsU4jAUGxHmC2YhDpvqa2vksBmyG1Kv+DgFOWxy2Gyy2zz7l7lNU27TlMstmd4/u9wqr6iQaUout+eYW4bcLc/DIyLlNj3hqbqm1vMaU3KbUlBwiOec2626+kY1ukw1Ot1qdJlyug+tvL+0y/MnmzK05o1dinxnj8IcNsVFhyssyKHQIJtCHDY11lUr2G5TiN1Q7+RestuOHJDgdrt14MCBVscSEhJks9nkdru1f/8BmZIkU25Tio9PkAxDpun5GXh/Ft7npiSXy62DBw/KlDzH3W7PNVpeFx0TI7vNJpthyG7zLKJitxmyG4ZsLf+12zx/dtiMlnaeh2FIhtq/h5xV3G6Xysr2tTqWlJQom83up4rQlZktv02BxAy8ki3jcrm1b1+Z73liYpLs9s4Z6GUG4A+6q5fsdru1b9+3/z4nJibqJ+f0U++YMD9W1T49Imw1NTVp3bp1uu+++3zHbDabJkyYoJycnCPaNzY2qrGx0fe8srJSklRVVWV9sW1QU1OjPd/kq7G+TmWFO2QLCVNEmOcv3f7iXcoNq1BNTY22bdumPd/sVWN93QnPHXqdQ9tJatW2reesuH5nfdZT+XOw6jNYXee23NVaXXlQfdI9GxhX7CvR1RPP0aBBg7Rt2zY1NdbL3VinjBApyr1LIwemqki9tLm4Qrv2V8sMCpNLdpkul6LCgxQWHCTT2ayKyiqFBDvkkEv1leUKD49QQmIv1VdXKj0xSmFRMSo9UKVte8tlCwmXSzY1OV2KiAiX23CovsmlJrekQ76o10qq9fxYtGf/8X5H9x/nXHuUn/QVDJkyWz6DW1JNo1RT6zm3o6zyOK9sT5gt6aTrHEtn/Ty7qmJ/FwDglNjr7wLQLns1MjVUEYZ/F+jyZoK2BGzDDMQY3k7FxcXq06ePVq1apezsbN/xe+65RytWrNDq1atbtX/wwQf1u9/97lSXCQAAACBAFBUVKS0t7bhtekTPVnvdd999uvPOO33P3W63ysvLlZCQIMPw/9CXqqoq9e3bV0VFRYqOjvZ3Oehk3N/uj3vcvXF/uzfub/fHPe7eOuP+mqap6upqpaamnrBtjwhbvXr1kt1uV2lp66EzpaWlSklJOaJ9SEiIQkJCWh2LjY21ssQOiY6O5h+Bboz72/1xj7s37m/3xv3t/rjH3dvJ3t+YmLZtfdMjln4PDg7WqFGjtGTJEt8xt9utJUuWtBpWCAAAAACdpUf0bEnSnXfeqWnTpmn06NE655xz9MQTT6i2tta3OiEAAAAAdKYeE7Z++tOfat++fZo9e7ZKSko0YsQIffDBB0pOTvZ3ae0WEhKi3/72t0cMdUT3wP3t/rjH3Rv3t3vj/nZ/3OPu7VTf3x6xGiEAAAAAnGo9Ys4WAAAAAJxqhC0AAAAAsABhCwAAAAAsQNgCAAAAAAsQtgLM3LlzlZ6ertDQUI0ZM0Zr1qzxd0nogEceeURnn322oqKilJSUpMsuu0wFBQWt2jQ0NGjGjBlKSEhQZGSkLr/88iM25kZg+OMf/yjDMDRr1izfMe5v4NuzZ4+uvvpqJSQkKCwsTFlZWfriiy98503T1OzZs9W7d2+FhYVpwoQJ2rp1qx8rRnu4XC498MADysjIUFhYmAYOHKiHH35Yh64rxj0OHCtXrtQPf/hDpaamyjAMvfPOO63Ot+VelpeXa+rUqYqOjlZsbKymT5+umpqaU/gpcDzHu8fNzc269957lZWVpYiICKWmpuraa69VcXFxq2tYcY8JWwHkjTfe0J133qnf/va3+vLLL3XmmWdq0qRJKisr83dpaKcVK1ZoxowZ+vzzz7V48WI1Nzdr4sSJqq2t9bW544479N5772nBggVasWKFiouLNWXKFD9WjY5Yu3atnnvuOQ0fPrzVce5vYDt48KDGjRunoKAgvf/++9q0aZPmzJmjuLg4X5tHH31UTz31lObNm6fVq1crIiJCkyZNUkNDgx8rR1v96U9/0rPPPqunn35a+fn5+tOf/qRHH31Uf/3rX31tuMeBo7a2Vmeeeabmzp171PNtuZdTp07Vxo0btXjxYi1cuFArV67UjTfeeKo+Ak7gePe4rq5OX375pR544AF9+eWXeuutt1RQUKAf/ehHrdpZco9NBIxzzjnHnDFjhu+5y+UyU1NTzUceecSPVaEzlJWVmZLMFStWmKZpmhUVFWZQUJC5YMECX5v8/HxTkpmTk+OvMtFO1dXV5uDBg83Fixeb3/3ud83bb7/dNE3ub3dw7733muedd94xz7vdbjMlJcX885//7DtWUVFhhoSEmP/6179ORYk4SZMnTzavv/76VsemTJliTp061TRN7nEgk2S+/fbbvudtuZebNm0yJZlr1671tXn//fdNwzDMPXv2nLLa0TaH3+OjWbNmjSnJ3LVrl2ma1t1jerYCRFNTk9atW6cJEyb4jtlsNk2YMEE5OTl+rAydobKyUpIUHx8vSVq3bp2am5tb3e/TTz9d/fr1434HkBkzZmjy5Mmt7qPE/e0O/vOf/2j06NG68sorlZSUpJEjR+pvf/ub7/yOHTtUUlLS6h7HxMRozJgx3OMAMXbsWC1ZskRbtmyRJH311Vf69NNPdckll0jiHncnbbmXOTk5io2N1ejRo31tJkyYIJvNptWrV5/ymnHyKisrZRiGYmNjJVl3jx0nWyhOjf3798vlcik5ObnV8eTkZG3evNlPVaEzuN1uzZo1S+PGjdMZZ5whSSopKVFwcLDvHwCv5ORklZSU+KFKtNfrr7+uL7/8UmvXrj3iHPc38G3fvl3PPvus7rzzTv3617/W2rVr9ctf/lLBwcGaNm2a7z4e7d9s7nFg+NWvfqWqqiqdfvrpstvtcrlc+v3vf6+pU6dKEve4G2nLvSwpKVFSUlKr8w6HQ/Hx8dzvANTQ0KB7771XP/vZzxQdHS3JuntM2AL8bMaMGdqwYYM+/fRTf5eCTlJUVKTbb79dixcvVmhoqL/LgQXcbrdGjx6tP/zhD5KkkSNHasOGDZo3b56mTZvm5+rQGd588029+uqreu211zRs2DDl5uZq1qxZSk1N5R4DAay5uVk/+clPZJqmnn32Wcvfj2GEAaJXr16y2+1HrFZWWlqqlJQUP1WFkzVz5kwtXLhQy5YtU1pamu94SkqKmpqaVFFR0ao99zswrFu3TmVlZTrrrLPkcDjkcDi0YsUKPfXUU3I4HEpOTub+BrjevXtr6NChrY5lZmaqsLBQknz3kX+zA9fdd9+tX/3qV7rqqquUlZWla665RnfccYceeeQRSdzj7qQt9zIlJeWIBcmcTqfKy8u53wHEG7R27dqlxYsX+3q1JOvuMWErQAQHB2vUqFFasmSJ75jb7daSJUuUnZ3tx8rQEaZpaubMmXr77be1dOlSZWRktDo/atQoBQUFtbrfBQUFKiws5H4HgIsuukh5eXnKzc31PUaPHq2pU6f6/sz9DWzjxo07YruGLVu2qH///pKkjIwMpaSktLrHVVVVWr16Nfc4QNTV1clma/01yW63y+12S+IedydtuZfZ2dmqqKjQunXrfG2WLl0qt9utMWPGnPKa0X7eoLV161Z9/PHHSkhIaHXesnvc4aU1cMq9/vrrZkhIiDl//nxz06ZN5o033mjGxsaaJSUl/i4N7XTLLbeYMTEx5vLly829e/f6HnV1db42N998s9mvXz9z6dKl5hdffGFmZ2eb2dnZfqwaJ+PQ1QhNk/sb6NasWWM6HA7z97//vbl161bz1VdfNcPDw81//vOfvjZ//OMfzdjYWPPdd981v/76a/PSSy81MzIyzPr6ej9WjraaNm2a2adPH3PhwoXmjh07zLfeesvs1auXec899/jacI8DR3V1tbl+/Xpz/fr1piTzscceM9evX+9bia4t9/Liiy82R44caa5evdr89NNPzcGDB5s/+9nP/PWRcJjj3eOmpibzRz/6kZmWlmbm5ua2+u7V2Njou4YV95iwFWD++te/mv369TODg4PNc845x/z888/9XRI6QNJRHy+99JKvTX19vXnrrbeacXFxZnh4uPnjH//Y3Lt3r/+Kxkk5PGxxfwPfe++9Z55xxhlmSEiIefrpp5vPP/98q/Nut9t84IEHzOTkZDMkJMS86KKLzIKCAj9Vi/aqqqoyb7/9drNfv35maGioOWDAAPM3v/lNqy9m3OPAsWzZsqP+7+60adNM02zbvTxw4ID5s5/9zIyMjDSjo6PN6667zqyurvbDp8HRHO8e79ix45jfvZYtW+a7hhX32DDNQ7ZCBwAAAAB0CuZsAQAAAIAFCFsAAAAAYAHCFgAAAABYgLAFAAAAABYgbAEAAACABQhbAAAAAGABwhYAAAAAWICwBQDASXjnnXc0aNAg2e12zZo1S/Pnz1dsbKy/ywIAdAGELQAATsJNN92kK664QkVFRXr44Yf9XQ4AoAtx+LsAAAACVU1NjcrKyjRp0iSlpqaesvdtampScHDwKXs/AEDH0LMFAAgY48eP12233aZZs2YpLi5OycnJ+tvf/qba2lpdd911ioqK0qBBg/T+++9Lklwul6ZPn66MjAyFhYVpyJAhevLJJ33Xa2ho0LBhw3TjjTf6jn3zzTeKiorSiy++eNxali9frqioKEnShRdeKMMwtHz58qO2ffbZZzVw4EAFBwdryJAh+sc//tHqfGFhoS699FJFRkYqOjpaP/nJT1RaWuo7/+CDD2rEiBF64YUXlJGRodDQ0Hb93AAA/kHYAgAElJdfflm9evXSmjVrdNttt+mWW27RlVdeqbFjx+rLL7/UxIkTdc0116iurk5ut1tpaWlasGCBNm3apNmzZ+vXv/613nzzTUlSaGioXn31Vb388st699135XK5dPXVV+t73/uerr/++uPWMXbsWBUUFEiS/v3vf2vv3r0aO3bsEe3efvtt3X777brrrru0YcMG3XTTTbruuuu0bNkySZLb7dall16q8vJyrVixQosXL9b27dv105/+tNV1tm3bpn//+9966623lJub2wk/SQCA1QzTNE1/FwEAQFuMHz9eLpdLn3zyiSRPz1VMTIymTJmiV155RZJUUlKi3r17KycnR+eee+4R15g5c6ZKSkr0f//3f75jf/7zn/Xoo4/qqquu0r///W/l5eUpISHhhPVUVFQoLi5Oy5Yt0/jx4yVJ8+fP16xZs1RRUSFJGjdunIYNG6bnn3/e97qf/OQnqq2t1aJFi7R48WJdcskl2rFjh/r27StJ2rRpk4YNG6Y1a9bo7LPP1oMPPqg//OEP2rNnjxITEzv0swMAnHr0bAEAAsrw4cN9f7bb7UpISFBWVpbvWHJysiSprKxMkjR37lyNGjVKiYmJioyM1PPPP6/CwsJW17zrrrt02mmn6emnn9aLL77YpqDVVvn5+Ro3blyrY+PGjVN+fr7vfN++fX1BS5KGDh2q2NhYXxtJ6t+/P0ELAAIMYQsAEFCCgoJaPTcMo9UxwzAkeYbnvf766/rf//1fTZ8+XR999JFyc3N13XXXqampqdU1ysrKtGXLFtntdm3dutX6D9EBERER/i4BANBOhC0AQLf12WefaezYsbr11ls1cuRIDRo0SN98880R7a6//nplZWXp5Zdf1r333tuqR+lkZWZm6rPPPjuirqFDh/rOFxUVqaioyHd+06ZNqqio8LUBAAQmln4HAHRbgwcP1iuvvKIPP/xQGRkZ+sc//qG1a9cqIyPD12bu3LnKycnR119/rb59+2rRokWaOnWqPv/8805ZXv3uu+/WT37yE40cOVITJkzQe++9p7feeksff/yxJGnChAnKysrS1KlT9cQTT8jpdOrWW2/Vd7/7XY0ePfqk3x8A4D/0bAEAuq2bbrpJU6ZM0U9/+lONGTNGBw4c0K233uo7v3nzZt1999165plnfHOmnnnmGe3fv18PPPBAp9Rw2WWX6cknn9Rf/vIXDRs2TM8995xeeukl34IahmHo3XffVVxcnM4//3xNmDBBAwYM0BtvvNEp7w8A8B9WIwQAAAAAC9CzBQAAAAAWIGwBAHAMl1xyiSIjI4/6+MMf/uDv8gAAXRzDCAEAOIY9e/aovr7+qOfi4+MVHx9/iisCAAQSwhYAAAAAWIBhhAAAAABgAcIWAAAAAFiAsAUAAAAAFiBsAQAAAIAFCFsAAAAAYAHCFgAAAABYgLAFAAAAABYgbAEAAACABf4/z7qoya3ie4sAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,6))\n",
    "sns.histplot(sberbankTrain['max_floor'], kde = True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,6))\n",
    "sns.histplot(sberbankTrain['num_room'], kde = True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,6))\n",
    "sns.histplot(sberbankTrain['kitch_sq'], kde = True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "full_sq             0\n",
       "life_sq          6383\n",
       "floor             167\n",
       "max_floor        9572\n",
       "material         9572\n",
       "build_year      13605\n",
       "num_room         9572\n",
       "kitch_sq         9572\n",
       "state           13559\n",
       "product_type        0\n",
       "sub_area            0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sberbankTrain.loc[:, sberbankTrain.columns.isin(['full_sq','life_sq','floor','max_floor','material','build_year','num_room','kitch_sq','state','product_type','sub_area'])].isna().sum()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}