{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 105,
   "id": "e312113e",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "import pandas as pd\n",
    "import matplotlib as plt\n",
    "import seaborn as sns\n",
    "import numpy as np\n",
    "import pickle"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "de2c028d",
   "metadata": {},
   "source": [
    "# Загрузка и знакомство с данными"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "id": "5cd00195",
   "metadata": {},
   "outputs": [],
   "source": [
    "# dataset https://www.kaggle.com/datasets/mrdaniilak/russia-real-estate-20182021/data \n",
    "\n",
    "df = pd.read_csv('data/all_v2.csv')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "id": "05b57100",
   "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>price</th>\n",
       "      <th>date</th>\n",
       "      <th>time</th>\n",
       "      <th>geo_lat</th>\n",
       "      <th>geo_lon</th>\n",
       "      <th>region</th>\n",
       "      <th>building_type</th>\n",
       "      <th>level</th>\n",
       "      <th>levels</th>\n",
       "      <th>rooms</th>\n",
       "      <th>area</th>\n",
       "      <th>kitchen_area</th>\n",
       "      <th>object_type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>6050000</td>\n",
       "      <td>2018-02-19</td>\n",
       "      <td>20:00:21</td>\n",
       "      <td>59.805808</td>\n",
       "      <td>30.376141</td>\n",
       "      <td>2661</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "      <td>10</td>\n",
       "      <td>3</td>\n",
       "      <td>82.6</td>\n",
       "      <td>10.8</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>8650000</td>\n",
       "      <td>2018-02-27</td>\n",
       "      <td>12:04:54</td>\n",
       "      <td>55.683807</td>\n",
       "      <td>37.297405</td>\n",
       "      <td>81</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>24</td>\n",
       "      <td>2</td>\n",
       "      <td>69.1</td>\n",
       "      <td>12.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4000000</td>\n",
       "      <td>2018-02-28</td>\n",
       "      <td>15:44:00</td>\n",
       "      <td>56.295250</td>\n",
       "      <td>44.061637</td>\n",
       "      <td>2871</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>9</td>\n",
       "      <td>3</td>\n",
       "      <td>66.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1850000</td>\n",
       "      <td>2018-03-01</td>\n",
       "      <td>11:24:52</td>\n",
       "      <td>44.996132</td>\n",
       "      <td>39.074783</td>\n",
       "      <td>2843</td>\n",
       "      <td>4</td>\n",
       "      <td>12</td>\n",
       "      <td>16</td>\n",
       "      <td>2</td>\n",
       "      <td>38.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5450000</td>\n",
       "      <td>2018-03-01</td>\n",
       "      <td>17:42:43</td>\n",
       "      <td>55.918767</td>\n",
       "      <td>37.984642</td>\n",
       "      <td>81</td>\n",
       "      <td>3</td>\n",
       "      <td>13</td>\n",
       "      <td>14</td>\n",
       "      <td>2</td>\n",
       "      <td>60.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>3300000</td>\n",
       "      <td>2018-03-02</td>\n",
       "      <td>21:18:42</td>\n",
       "      <td>55.908253</td>\n",
       "      <td>37.726448</td>\n",
       "      <td>81</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>32.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>4704280</td>\n",
       "      <td>2018-03-04</td>\n",
       "      <td>12:35:25</td>\n",
       "      <td>55.621097</td>\n",
       "      <td>37.431002</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>25</td>\n",
       "      <td>1</td>\n",
       "      <td>31.7</td>\n",
       "      <td>6.0</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>3600000</td>\n",
       "      <td>2018-03-04</td>\n",
       "      <td>20:52:38</td>\n",
       "      <td>59.875526</td>\n",
       "      <td>30.395457</td>\n",
       "      <td>2661</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>31.1</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>3390000</td>\n",
       "      <td>2018-03-05</td>\n",
       "      <td>07:07:05</td>\n",
       "      <td>53.195031</td>\n",
       "      <td>50.106952</td>\n",
       "      <td>3106</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>24</td>\n",
       "      <td>2</td>\n",
       "      <td>64.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2800000</td>\n",
       "      <td>2018-03-06</td>\n",
       "      <td>09:57:10</td>\n",
       "      <td>55.736972</td>\n",
       "      <td>38.846457</td>\n",
       "      <td>81</td>\n",
       "      <td>1</td>\n",
       "      <td>9</td>\n",
       "      <td>10</td>\n",
       "      <td>2</td>\n",
       "      <td>55.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     price        date      time    geo_lat    geo_lon  region  building_type  \\\n",
       "0  6050000  2018-02-19  20:00:21  59.805808  30.376141    2661              1   \n",
       "1  8650000  2018-02-27  12:04:54  55.683807  37.297405      81              3   \n",
       "2  4000000  2018-02-28  15:44:00  56.295250  44.061637    2871              1   \n",
       "3  1850000  2018-03-01  11:24:52  44.996132  39.074783    2843              4   \n",
       "4  5450000  2018-03-01  17:42:43  55.918767  37.984642      81              3   \n",
       "5  3300000  2018-03-02  21:18:42  55.908253  37.726448      81              1   \n",
       "6  4704280  2018-03-04  12:35:25  55.621097  37.431002       3              2   \n",
       "7  3600000  2018-03-04  20:52:38  59.875526  30.395457    2661              1   \n",
       "8  3390000  2018-03-05  07:07:05  53.195031  50.106952    3106              2   \n",
       "9  2800000  2018-03-06  09:57:10  55.736972  38.846457      81              1   \n",
       "\n",
       "   level  levels  rooms  area  kitchen_area  object_type  \n",
       "0      8      10      3  82.6          10.8            1  \n",
       "1      5      24      2  69.1          12.0            1  \n",
       "2      5       9      3  66.0          10.0            1  \n",
       "3     12      16      2  38.0           5.0           11  \n",
       "4     13      14      2  60.0          10.0            1  \n",
       "5      4       5      1  32.0           6.0            1  \n",
       "6      1      25      1  31.7           6.0           11  \n",
       "7      2       5      1  31.1           6.0            1  \n",
       "8      4      24      2  64.0          13.0           11  \n",
       "9      9      10      2  55.0           8.0            1  "
      ]
     },
     "execution_count": 107,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "id": "701c5e26",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 5477006 entries, 0 to 5477005\n",
      "Data columns (total 13 columns):\n",
      " #   Column         Non-Null Count    Dtype  \n",
      "---  ------         --------------    -----  \n",
      " 0   price          5477006 non-null  int64  \n",
      " 1   date           5477006 non-null  object \n",
      " 2   time           5477006 non-null  object \n",
      " 3   geo_lat        5477006 non-null  float64\n",
      " 4   geo_lon        5477006 non-null  float64\n",
      " 5   region         5477006 non-null  int64  \n",
      " 6   building_type  5477006 non-null  int64  \n",
      " 7   level          5477006 non-null  int64  \n",
      " 8   levels         5477006 non-null  int64  \n",
      " 9   rooms          5477006 non-null  int64  \n",
      " 10  area           5477006 non-null  float64\n",
      " 11  kitchen_area   5477006 non-null  float64\n",
      " 12  object_type    5477006 non-null  int64  \n",
      "dtypes: float64(4), int64(7), object(2)\n",
      "memory usage: 543.2+ MB\n"
     ]
    }
   ],
   "source": [
    "df.info(show_counts=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "id": "c085b0c6",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['region'] = df['region'].astype('category')\n",
    "df['building_type'] = df['building_type'].astype('category')\n",
    "df['object_type'] = df['object_type'].astype('category')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "id": "73fc1a17",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['level'] = df['level'].astype('int8')\n",
    "df['levels'] = df['levels'].astype('int8')\n",
    "df['rooms'] = df['rooms'].astype('int8')\n",
    "df['rooms'] = df['rooms'].astype('int8')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "id": "870155e0",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "df['area'] = df['area'].astype('float16')\n",
    "df['kitchen_area'] = df['kitchen_area'].astype('float16')\n",
    "df['kitchen_area'] = df['kitchen_area'].astype('float16')\n",
    "df['geo_lat'] = df['geo_lat'].astype('float32')\n",
    "df['geo_lon'] = df['geo_lon'].astype('float32')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "id": "8e7a34e7",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/andrey/work/institute/MLE/assets/eda/.venv_eda/lib/python3.10/site-packages/pandas/core/nanops.py:1487: RuntimeWarning: overflow encountered in cast\n",
      "  return dtype.type(n)\n",
      "/home/andrey/work/institute/MLE/assets/eda/.venv_eda/lib/python3.10/site-packages/numpy/_core/_methods.py:53: RuntimeWarning: overflow encountered in reduce\n",
      "  return umr_sum(a, axis, dtype, out, keepdims, initial, where)\n",
      "/home/andrey/work/institute/MLE/assets/eda/.venv_eda/lib/python3.10/site-packages/pandas/core/nanops.py:731: RuntimeWarning: invalid value encountered in scalar divide\n",
      "  the_mean = the_sum / count if count > 0 else np.nan\n",
      "/home/andrey/work/institute/MLE/assets/eda/.venv_eda/lib/python3.10/site-packages/pandas/core/nanops.py:1487: RuntimeWarning: overflow encountered in cast\n",
      "  return dtype.type(n)\n",
      "/home/andrey/work/institute/MLE/assets/eda/.venv_eda/lib/python3.10/site-packages/numpy/_core/_methods.py:53: RuntimeWarning: overflow encountered in reduce\n",
      "  return umr_sum(a, axis, dtype, out, keepdims, initial, where)\n",
      "/home/andrey/work/institute/MLE/assets/eda/.venv_eda/lib/python3.10/site-packages/pandas/core/nanops.py:731: RuntimeWarning: invalid value encountered in scalar divide\n",
      "  the_mean = the_sum / count if count > 0 else np.nan\n"
     ]
    },
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>price</th>\n",
       "      <th>geo_lat</th>\n",
       "      <th>geo_lon</th>\n",
       "      <th>level</th>\n",
       "      <th>levels</th>\n",
       "      <th>rooms</th>\n",
       "      <th>area</th>\n",
       "      <th>kitchen_area</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>5.477006e+06</td>\n",
       "      <td>5.477006e+06</td>\n",
       "      <td>5.477006e+06</td>\n",
       "      <td>5.477006e+06</td>\n",
       "      <td>5.477006e+06</td>\n",
       "      <td>5.477006e+06</td>\n",
       "      <td>5.477006e+06</td>\n",
       "      <td>5.477006e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>4.422029e+06</td>\n",
       "      <td>5.403825e+01</td>\n",
       "      <td>5.324431e+01</td>\n",
       "      <td>6.214530e+00</td>\n",
       "      <td>1.139892e+01</td>\n",
       "      <td>1.726173e+00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>2.150752e+07</td>\n",
       "      <td>4.622758e+00</td>\n",
       "      <td>2.074763e+01</td>\n",
       "      <td>4.957419e+00</td>\n",
       "      <td>6.535734e+00</td>\n",
       "      <td>1.082133e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>-2.144967e+09</td>\n",
       "      <td>4.145906e+01</td>\n",
       "      <td>1.989020e+01</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>-2.000000e+00</td>\n",
       "      <td>7.000732e-02</td>\n",
       "      <td>1.000214e-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1.950000e+06</td>\n",
       "      <td>5.337767e+01</td>\n",
       "      <td>3.777790e+01</td>\n",
       "      <td>2.000000e+00</td>\n",
       "      <td>5.000000e+00</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>3.800000e+01</td>\n",
       "      <td>7.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>2.990000e+06</td>\n",
       "      <td>5.517139e+01</td>\n",
       "      <td>4.306774e+01</td>\n",
       "      <td>5.000000e+00</td>\n",
       "      <td>1.000000e+01</td>\n",
       "      <td>2.000000e+00</td>\n",
       "      <td>4.803125e+01</td>\n",
       "      <td>9.703125e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>4.802000e+06</td>\n",
       "      <td>5.622613e+01</td>\n",
       "      <td>6.564895e+01</td>\n",
       "      <td>9.000000e+00</td>\n",
       "      <td>1.600000e+01</td>\n",
       "      <td>2.000000e+00</td>\n",
       "      <td>6.312500e+01</td>\n",
       "      <td>1.270312e+01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>2.147484e+09</td>\n",
       "      <td>7.198040e+01</td>\n",
       "      <td>1.625361e+02</td>\n",
       "      <td>3.900000e+01</td>\n",
       "      <td>3.900000e+01</td>\n",
       "      <td>1.000000e+01</td>\n",
       "      <td>7.856000e+03</td>\n",
       "      <td>1.000000e+04</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              price       geo_lat       geo_lon         level        levels  \\\n",
       "count  5.477006e+06  5.477006e+06  5.477006e+06  5.477006e+06  5.477006e+06   \n",
       "mean   4.422029e+06  5.403825e+01  5.324431e+01  6.214530e+00  1.139892e+01   \n",
       "std    2.150752e+07  4.622758e+00  2.074763e+01  4.957419e+00  6.535734e+00   \n",
       "min   -2.144967e+09  4.145906e+01  1.989020e+01  1.000000e+00  1.000000e+00   \n",
       "25%    1.950000e+06  5.337767e+01  3.777790e+01  2.000000e+00  5.000000e+00   \n",
       "50%    2.990000e+06  5.517139e+01  4.306774e+01  5.000000e+00  1.000000e+01   \n",
       "75%    4.802000e+06  5.622613e+01  6.564895e+01  9.000000e+00  1.600000e+01   \n",
       "max    2.147484e+09  7.198040e+01  1.625361e+02  3.900000e+01  3.900000e+01   \n",
       "\n",
       "              rooms          area  kitchen_area  \n",
       "count  5.477006e+06  5.477006e+06  5.477006e+06  \n",
       "mean   1.726173e+00           NaN           NaN  \n",
       "std    1.082133e+00  0.000000e+00  0.000000e+00  \n",
       "min   -2.000000e+00  7.000732e-02  1.000214e-02  \n",
       "25%    1.000000e+00  3.800000e+01  7.000000e+00  \n",
       "50%    2.000000e+00  4.803125e+01  9.703125e+00  \n",
       "75%    2.000000e+00  6.312500e+01  1.270312e+01  \n",
       "max    1.000000e+01  7.856000e+03  1.000000e+04  "
      ]
     },
     "execution_count": 112,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "id": "10867be6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['region', 'building_type', 'object_type']"
      ]
     },
     "execution_count": 113,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cat_features = df.select_dtypes(include=['category']).columns.to_list()\n",
    "cat_features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "id": "88249b5c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['price',\n",
       " 'geo_lat',\n",
       " 'geo_lon',\n",
       " 'level',\n",
       " 'levels',\n",
       " 'rooms',\n",
       " 'area',\n",
       " 'kitchen_area']"
      ]
     },
     "execution_count": 114,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "num_features = df.select_dtypes(include=['number']).columns.to_list()\n",
    "num_features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "id": "637c7446",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df.drop(columns=['date', 'time'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "id": "1ab16b00",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 5477006 entries, 0 to 5477005\n",
      "Data columns (total 11 columns):\n",
      " #   Column         Non-Null Count    Dtype   \n",
      "---  ------         --------------    -----   \n",
      " 0   price          5477006 non-null  int64   \n",
      " 1   geo_lat        5477006 non-null  float32 \n",
      " 2   geo_lon        5477006 non-null  float32 \n",
      " 3   region         5477006 non-null  category\n",
      " 4   building_type  5477006 non-null  category\n",
      " 5   level          5477006 non-null  int8    \n",
      " 6   levels         5477006 non-null  int8    \n",
      " 7   rooms          5477006 non-null  int8    \n",
      " 8   area           5477006 non-null  float16 \n",
      " 9   kitchen_area   5477006 non-null  float16 \n",
      " 10  object_type    5477006 non-null  category\n",
      "dtypes: category(3), float16(2), float32(2), int64(1), int8(3)\n",
      "memory usage: 135.8 MB\n"
     ]
    }
   ],
   "source": [
    "df.info(show_counts=True) # уменьшили размер в 3 раза (135 Мб против 543)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "id": "76a6c9a9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "region - numer of unique = 84\n",
      "building_type - numer of unique = 6\n",
      "object_type - numer of unique = 2\n"
     ]
    }
   ],
   "source": [
    "for cat in cat_features:\n",
    "    print(f'{cat} - numer of unique = {df[cat].nunique()}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "id": "b76cc3d5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Unique categories in region: region\n",
      "9654     1049435\n",
      "2843      637224\n",
      "81        500368\n",
      "2661      461820\n",
      "3         439511\n",
      "          ...   \n",
      "16705        139\n",
      "69            77\n",
      "4963          65\n",
      "1901          12\n",
      "61888          5\n",
      "Name: count, Length: 84, dtype: int64\n",
      "Unique categories in building_type: building_type\n",
      "1    1955661\n",
      "3    1892756\n",
      "2    1130731\n",
      "0     307165\n",
      "4     174356\n",
      "5      16337\n",
      "Name: count, dtype: int64\n",
      "Unique categories in object_type: object_type\n",
      "1     3863809\n",
      "11    1613197\n",
      "Name: count, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "for col in cat_features:\n",
    "    print(f'Unique categories in {col}: {df[col].value_counts()}')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6c892b3e",
   "metadata": {},
   "source": [
    "# Очистка данных"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "id": "e9d29872",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df.loc[df['price'] > 50000]\n",
    "df = df.query('area >= 8')\n",
    "df = df.query('kitchen_area >= 3')\n",
    "df = df.query('kitchen_area < area')\n",
    "df = df.query('rooms != -2')\n",
    "df = df.query('level <= levels')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "id": "67dd3a9c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# меняем признак \"студии\" -1 на 0\n",
    "df.loc[df['rooms'] == -1, 'rooms'] = 0 "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a3d3ad69",
   "metadata": {},
   "source": [
    "# Анализ признаков для модели\n",
    "\n",
    "https://seaborn.pydata.org/examples/index.html - галерея примеров"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "78845b8b",
   "metadata": {},
   "source": [
    "## displot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "8f5ee97a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x7df3e5371c00>"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 604.986x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.displot(df, x='price', bins=100, hue='building_type', kde=True, log_scale=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "a872743b",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Создаем новый признак - уровень высоты этажа в здании\n",
    "df['floor_level'] = df.apply(lambda x: 'low' if x['level']/x['levels'] <= 0.3 \\\n",
    "                             else 'hi' if x['level']/x['levels'] > 0.7 \\\n",
    "                             else 'mid', axis = 1) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "fa63fc34",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['floor_level'] = df.apply(lambda x: 'first' if x['level'] == 1 \\\n",
    "                            else 'last' if x['level'] == x['levels'] \\\n",
    "                            else x['floor_level'], axis = 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "374d184b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "floor_level\n",
       "mid      2092890\n",
       "hi       1208629\n",
       "low       740915\n",
       "last      697099\n",
       "first     654013\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['floor_level'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "c03175ff",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x7df3e55f4be0>"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 582.736x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.displot(df, x='price', bins=100, hue='floor_level', kde=True, log_scale=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9318a819",
   "metadata": {},
   "source": [
    "## heatmap"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "7ae43e0e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "feature_correlation = df[num_features].corr()\n",
    "sns.heatmap(feature_correlation, annot=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f4ab2ef2",
   "metadata": {},
   "source": [
    "# Групповые операции"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "11e4da4e",
   "metadata": {},
   "outputs": [],
   "source": [
    "def flat_index(df_stats): \n",
    "    df_stats.columns = df_stats.columns.get_level_values(0) + '_' +  df_stats.columns.get_level_values(1) \n",
    "    df_stats.columns = df_stats.columns.to_flat_index() \n",
    "    df_stats.reset_index(inplace=True) \n",
    "    return df_stats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "8fdbd526",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_1524625/3084051676.py:1: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  aggregated_df = df[num_features+['building_type']].groupby(by='building_type').agg(['mean', 'std'])\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>building_type</th>\n",
       "      <th>price_mean</th>\n",
       "      <th>price_std</th>\n",
       "      <th>geo_lat_mean</th>\n",
       "      <th>geo_lat_std</th>\n",
       "      <th>geo_lon_mean</th>\n",
       "      <th>geo_lon_std</th>\n",
       "      <th>level_mean</th>\n",
       "      <th>level_std</th>\n",
       "      <th>levels_mean</th>\n",
       "      <th>levels_std</th>\n",
       "      <th>rooms_mean</th>\n",
       "      <th>rooms_std</th>\n",
       "      <th>area_mean</th>\n",
       "      <th>area_std</th>\n",
       "      <th>kitchen_area_mean</th>\n",
       "      <th>kitchen_area_std</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>5.284833e+06</td>\n",
       "      <td>1.279574e+07</td>\n",
       "      <td>53.747444</td>\n",
       "      <td>5.098192</td>\n",
       "      <td>55.518322</td>\n",
       "      <td>22.517204</td>\n",
       "      <td>8.851292</td>\n",
       "      <td>5.923950</td>\n",
       "      <td>16.738440</td>\n",
       "      <td>6.499030</td>\n",
       "      <td>1.686900</td>\n",
       "      <td>0.934588</td>\n",
       "      <td>58.559349</td>\n",
       "      <td>37.077482</td>\n",
       "      <td>12.792236</td>\n",
       "      <td>6.599672</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>3.512978e+06</td>\n",
       "      <td>1.952254e+07</td>\n",
       "      <td>54.790298</td>\n",
       "      <td>3.357936</td>\n",
       "      <td>61.443077</td>\n",
       "      <td>21.923780</td>\n",
       "      <td>5.571202</td>\n",
       "      <td>4.060143</td>\n",
       "      <td>10.213742</td>\n",
       "      <td>4.642660</td>\n",
       "      <td>1.794023</td>\n",
       "      <td>0.966615</td>\n",
       "      <td>51.407722</td>\n",
       "      <td>25.746609</td>\n",
       "      <td>9.298869</td>\n",
       "      <td>4.062081</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>7.126816e+06</td>\n",
       "      <td>1.267507e+07</td>\n",
       "      <td>53.999779</td>\n",
       "      <td>5.346035</td>\n",
       "      <td>42.106968</td>\n",
       "      <td>13.565219</td>\n",
       "      <td>9.031732</td>\n",
       "      <td>6.130808</td>\n",
       "      <td>16.850670</td>\n",
       "      <td>6.862993</td>\n",
       "      <td>1.697287</td>\n",
       "      <td>0.928301</td>\n",
       "      <td>57.157982</td>\n",
       "      <td>32.994183</td>\n",
       "      <td>13.154365</td>\n",
       "      <td>6.146328</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>4.068649e+06</td>\n",
       "      <td>8.331654e+06</td>\n",
       "      <td>53.556213</td>\n",
       "      <td>4.910420</td>\n",
       "      <td>51.249592</td>\n",
       "      <td>19.097178</td>\n",
       "      <td>4.929223</td>\n",
       "      <td>3.997643</td>\n",
       "      <td>8.741839</td>\n",
       "      <td>5.626125</td>\n",
       "      <td>1.878324</td>\n",
       "      <td>0.944347</td>\n",
       "      <td>55.062199</td>\n",
       "      <td>36.979730</td>\n",
       "      <td>10.442657</td>\n",
       "      <td>6.912905</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>4.004994e+06</td>\n",
       "      <td>3.367351e+07</td>\n",
       "      <td>51.181896</td>\n",
       "      <td>5.909806</td>\n",
       "      <td>47.777088</td>\n",
       "      <td>17.570242</td>\n",
       "      <td>5.430987</td>\n",
       "      <td>4.308443</td>\n",
       "      <td>9.746289</td>\n",
       "      <td>5.743188</td>\n",
       "      <td>1.811687</td>\n",
       "      <td>0.892482</td>\n",
       "      <td>52.034588</td>\n",
       "      <td>42.411056</td>\n",
       "      <td>10.051356</td>\n",
       "      <td>4.793207</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>5</td>\n",
       "      <td>2.618608e+06</td>\n",
       "      <td>1.543122e+07</td>\n",
       "      <td>56.440563</td>\n",
       "      <td>3.981515</td>\n",
       "      <td>63.951946</td>\n",
       "      <td>28.464556</td>\n",
       "      <td>2.472882</td>\n",
       "      <td>3.850120</td>\n",
       "      <td>3.766808</td>\n",
       "      <td>5.931042</td>\n",
       "      <td>2.031180</td>\n",
       "      <td>0.907434</td>\n",
       "      <td>50.446354</td>\n",
       "      <td>52.361071</td>\n",
       "      <td>9.285330</td>\n",
       "      <td>4.603177</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  building_type    price_mean     price_std  geo_lat_mean  geo_lat_std  \\\n",
       "0             0  5.284833e+06  1.279574e+07     53.747444     5.098192   \n",
       "1             1  3.512978e+06  1.952254e+07     54.790298     3.357936   \n",
       "2             2  7.126816e+06  1.267507e+07     53.999779     5.346035   \n",
       "3             3  4.068649e+06  8.331654e+06     53.556213     4.910420   \n",
       "4             4  4.004994e+06  3.367351e+07     51.181896     5.909806   \n",
       "5             5  2.618608e+06  1.543122e+07     56.440563     3.981515   \n",
       "\n",
       "   geo_lon_mean  geo_lon_std  level_mean  level_std  levels_mean  levels_std  \\\n",
       "0     55.518322    22.517204    8.851292   5.923950    16.738440    6.499030   \n",
       "1     61.443077    21.923780    5.571202   4.060143    10.213742    4.642660   \n",
       "2     42.106968    13.565219    9.031732   6.130808    16.850670    6.862993   \n",
       "3     51.249592    19.097178    4.929223   3.997643     8.741839    5.626125   \n",
       "4     47.777088    17.570242    5.430987   4.308443     9.746289    5.743188   \n",
       "5     63.951946    28.464556    2.472882   3.850120     3.766808    5.931042   \n",
       "\n",
       "   rooms_mean  rooms_std  area_mean   area_std  kitchen_area_mean  \\\n",
       "0    1.686900   0.934588  58.559349  37.077482          12.792236   \n",
       "1    1.794023   0.966615  51.407722  25.746609           9.298869   \n",
       "2    1.697287   0.928301  57.157982  32.994183          13.154365   \n",
       "3    1.878324   0.944347  55.062199  36.979730          10.442657   \n",
       "4    1.811687   0.892482  52.034588  42.411056          10.051356   \n",
       "5    2.031180   0.907434  50.446354  52.361071           9.285330   \n",
       "\n",
       "   kitchen_area_std  \n",
       "0          6.599672  \n",
       "1          4.062081  \n",
       "2          6.146328  \n",
       "3          6.912905  \n",
       "4          4.793207  \n",
       "5          4.603177  "
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "aggregated_df = df[num_features+['building_type']].groupby(by='building_type').agg(['mean', 'std'])\n",
    "aggregated_df = flat_index(aggregated_df)\n",
    "aggregated_df "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "77fe1bda",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "0fbb62de",
   "metadata": {},
   "source": [
    "## lineplot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "acb4cdee",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='building_type', ylabel='price_mean'>"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "sns.lineplot(aggregated_df,x='building_type',y='price_mean', label='mean')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b8bc652d",
   "metadata": {},
   "source": [
    "## subplots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "20ca7cc9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='building_type', ylabel='area'>"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1650x1400 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axs = plt.pyplot.subplots(2,2)\n",
    "fig.tight_layout(pad=1)\n",
    "fig.set_size_inches(16.5, 14, forward=True)\n",
    "\n",
    "sns.lineplot(aggregated_df,x='building_type',y='price_mean', label='mean', ax=axs[0,0])\n",
    "\n",
    "sns.lineplot(aggregated_df,x='building_type',y='area_mean', label='area',ax=axs[0,1])\n",
    "sns.lineplot(aggregated_df,x='building_type',y='kitchen_area_mean', label='kitchen_area_mean',ax=axs[0,1])\n",
    "\n",
    "sns.lineplot(aggregated_df,x='building_type',y='level_mean', label='level_mean',ax=axs[1,0])\n",
    "\n",
    "# Группировка непосредственно в seaborn\n",
    "sns.lineplot(df, x='building_type', y='area', label='area', ax=axs[1,1])\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5d64d58a",
   "metadata": {},
   "source": [
    "# Bokeh\n",
    "https://bokeh.org/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "fddb38a2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "    <style>\n",
       "        .bk-notebook-logo {\n",
       "            display: block;\n",
       "            width: 20px;\n",
       "            height: 20px;\n",
       "            background-image: url(data:image/png;base64,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);\n",
       "        }\n",
       "    </style>\n",
       "    <div>\n",
       "        <a href=\"https://bokeh.org\" target=\"_blank\" class=\"bk-notebook-logo\"></a>\n",
       "        <span id=\"dec2ab1e-cda5-49ce-8f7d-85a26b4e3d5b\">Loading BokehJS ...</span>\n",
       "    </div>\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": "'use strict';\n(function(root) {\n  function now() {\n    return new Date();\n  }\n\n  const force = true;\n\n  if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n    root._bokeh_onload_callbacks = [];\n    root._bokeh_is_loading = undefined;\n  }\n\nconst JS_MIME_TYPE = 'application/javascript';\n  const HTML_MIME_TYPE = 'text/html';\n  const EXEC_MIME_TYPE = 'application/vnd.bokehjs_exec.v0+json';\n  const CLASS_NAME = 'output_bokeh rendered_html';\n\n  /**\n   * Render data to the DOM node\n   */\n  function render(props, node) {\n    const script = document.createElement(\"script\");\n    node.appendChild(script);\n  }\n\n  /**\n   * Handle when an output is cleared or removed\n   */\n  function handleClearOutput(event, handle) {\n    function drop(id) {\n      const view = Bokeh.index.get_by_id(id)\n      if (view != null) {\n        view.model.document.clear()\n        Bokeh.index.delete(view)\n      }\n    }\n\n    const cell = handle.cell;\n\n    const id = cell.output_area._bokeh_element_id;\n    const server_id = cell.output_area._bokeh_server_id;\n\n    // Clean up Bokeh references\n    if (id != null) {\n      drop(id)\n    }\n\n    if (server_id !== undefined) {\n      // Clean up Bokeh references\n      const cmd_clean = \"from bokeh.io.state import curstate; print(curstate().uuid_to_server['\" + server_id + \"'].get_sessions()[0].document.roots[0]._id)\";\n      cell.notebook.kernel.execute(cmd_clean, {\n        iopub: {\n          output: function(msg) {\n            const id = msg.content.text.trim()\n            drop(id)\n          }\n        }\n      });\n      // Destroy server and session\n      const cmd_destroy = \"import bokeh.io.notebook as ion; ion.destroy_server('\" + server_id + \"')\";\n      cell.notebook.kernel.execute(cmd_destroy);\n    }\n  }\n\n  /**\n   * Handle when a new output is added\n   */\n  function handleAddOutput(event, handle) {\n    const output_area = handle.output_area;\n    const output = handle.output;\n\n    // limit handleAddOutput to display_data with EXEC_MIME_TYPE content only\n    if ((output.output_type != \"display_data\") || (!Object.prototype.hasOwnProperty.call(output.data, EXEC_MIME_TYPE))) {\n      return\n    }\n\n    const toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n\n    if (output.metadata[EXEC_MIME_TYPE][\"id\"] !== undefined) {\n      toinsert[toinsert.length - 1].firstChild.textContent = output.data[JS_MIME_TYPE];\n      // store reference to embed id on output_area\n      output_area._bokeh_element_id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n    }\n    if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n      const bk_div = document.createElement(\"div\");\n      bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n      const script_attrs = bk_div.children[0].attributes;\n      for (let i = 0; i < script_attrs.length; i++) {\n        toinsert[toinsert.length - 1].firstChild.setAttribute(script_attrs[i].name, script_attrs[i].value);\n        toinsert[toinsert.length - 1].firstChild.textContent = bk_div.children[0].textContent\n      }\n      // store reference to server id on output_area\n      output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n    }\n  }\n\n  function register_renderer(events, OutputArea) {\n\n    function append_mime(data, metadata, element) {\n      // create a DOM node to render to\n      const toinsert = this.create_output_subarea(\n        metadata,\n        CLASS_NAME,\n        EXEC_MIME_TYPE\n      );\n      this.keyboard_manager.register_events(toinsert);\n      // Render to node\n      const props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n      render(props, toinsert[toinsert.length - 1]);\n      element.append(toinsert);\n      return toinsert\n    }\n\n    /* Handle when an output is cleared or removed */\n    events.on('clear_output.CodeCell', handleClearOutput);\n    events.on('delete.Cell', handleClearOutput);\n\n    /* Handle when a new output is added */\n    events.on('output_added.OutputArea', handleAddOutput);\n\n    /**\n     * Register the mime type and append_mime function with output_area\n     */\n    OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n      /* Is output safe? */\n      safe: true,\n      /* Index of renderer in `output_area.display_order` */\n      index: 0\n    });\n  }\n\n  // register the mime type if in Jupyter Notebook environment and previously unregistered\n  if (root.Jupyter !== undefined) {\n    const events = require('base/js/events');\n    const OutputArea = require('notebook/js/outputarea').OutputArea;\n\n    if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n      register_renderer(events, OutputArea);\n    }\n  }\n  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n    root._bokeh_timeout = Date.now() + 5000;\n    root._bokeh_failed_load = false;\n  }\n\n  const NB_LOAD_WARNING = {'data': {'text/html':\n     \"<div style='background-color: #fdd'>\\n\"+\n     \"<p>\\n\"+\n     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n     \"</p>\\n\"+\n     \"<ul>\\n\"+\n     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n     \"</ul>\\n\"+\n     \"<code>\\n\"+\n     \"from bokeh.resources import INLINE\\n\"+\n     \"output_notebook(resources=INLINE)\\n\"+\n     \"</code>\\n\"+\n     \"</div>\"}};\n\n  function display_loaded(error = null) {\n    const el = document.getElementById(\"dec2ab1e-cda5-49ce-8f7d-85a26b4e3d5b\");\n    if (el != null) {\n      const html = (() => {\n        if (typeof root.Bokeh === \"undefined\") {\n          if (error == null) {\n            return \"BokehJS is loading ...\";\n          } else {\n            return \"BokehJS failed to load.\";\n          }\n        } else {\n          const prefix = `BokehJS ${root.Bokeh.version}`;\n          if (error == null) {\n            return `${prefix} successfully loaded.`;\n          } else {\n            return `${prefix} <b>encountered errors</b> while loading and may not function as expected.`;\n          }\n        }\n      })();\n      el.innerHTML = html;\n\n      if (error != null) {\n        const wrapper = document.createElement(\"div\");\n        wrapper.style.overflow = \"auto\";\n        wrapper.style.height = \"5em\";\n        wrapper.style.resize = \"vertical\";\n        const content = document.createElement(\"div\");\n        content.style.fontFamily = \"monospace\";\n        content.style.whiteSpace = \"pre-wrap\";\n        content.style.backgroundColor = \"rgb(255, 221, 221)\";\n        content.textContent = error.stack ?? error.toString();\n        wrapper.append(content);\n        el.append(wrapper);\n      }\n    } else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(() => display_loaded(error), 100);\n    }\n  }\n\n  function run_callbacks() {\n    try {\n      root._bokeh_onload_callbacks.forEach(function(callback) {\n        if (callback != null)\n          callback();\n      });\n    } finally {\n      delete root._bokeh_onload_callbacks\n    }\n    console.debug(\"Bokeh: all callbacks have finished\");\n  }\n\n  function load_libs(css_urls, js_urls, callback) {\n    if (css_urls == null) css_urls = [];\n    if (js_urls == null) js_urls = [];\n\n    root._bokeh_onload_callbacks.push(callback);\n    if (root._bokeh_is_loading > 0) {\n      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n      return null;\n    }\n    if (js_urls == null || js_urls.length === 0) {\n      run_callbacks();\n      return null;\n    }\n    console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n    root._bokeh_is_loading = css_urls.length + js_urls.length;\n\n    function on_load() {\n      root._bokeh_is_loading--;\n      if (root._bokeh_is_loading === 0) {\n        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n        run_callbacks()\n      }\n    }\n\n    function on_error(url) {\n      console.error(\"failed to load \" + url);\n    }\n\n    for (let i = 0; i < css_urls.length; i++) {\n      const url = css_urls[i];\n      const element = document.createElement(\"link\");\n      element.onload = on_load;\n      element.onerror = on_error.bind(null, url);\n      element.rel = \"stylesheet\";\n      element.type = \"text/css\";\n      element.href = url;\n      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n      document.body.appendChild(element);\n    }\n\n    for (let i = 0; i < js_urls.length; i++) {\n      const url = js_urls[i];\n      const element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error.bind(null, url);\n      element.async = false;\n      element.src = url;\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n  };\n\n  function inject_raw_css(css) {\n    const element = document.createElement(\"style\");\n    element.appendChild(document.createTextNode(css));\n    document.body.appendChild(element);\n  }\n\n  const js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-3.5.2.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-3.5.2.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-3.5.2.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-3.5.2.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-mathjax-3.5.2.min.js\"];\n  const css_urls = [];\n\n  const inline_js = [    function(Bokeh) {\n      Bokeh.set_log_level(\"info\");\n    },\nfunction(Bokeh) {\n    }\n  ];\n\n  function run_inline_js() {\n    if (root.Bokeh !== undefined || force === true) {\n      try {\n            for (let i = 0; i < inline_js.length; i++) {\n      inline_js[i].call(root, root.Bokeh);\n    }\n\n      } catch (error) {display_loaded(error);throw error;\n      }if (force === true) {\n        display_loaded();\n      }} else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(run_inline_js, 100);\n    } else if (!root._bokeh_failed_load) {\n      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n      root._bokeh_failed_load = true;\n    } else if (force !== true) {\n      const cell = $(document.getElementById(\"dec2ab1e-cda5-49ce-8f7d-85a26b4e3d5b\")).parents('.cell').data().cell;\n      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n    }\n  }\n\n  if (root._bokeh_is_loading === 0) {\n    console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n    run_inline_js();\n  } else {\n    load_libs(css_urls, js_urls, function() {\n      console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n      run_inline_js();\n    });\n  }\n}(window));",
      "application/vnd.bokehjs_load.v0+json": ""
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from bokeh.plotting import figure, show\n",
    "from bokeh.models import ColumnDataSource,  HoverTool, Legend\n",
    "from bokeh.io import output_notebook \n",
    "output_notebook()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "75e6c73b",
   "metadata": {},
   "outputs": [],
   "source": [
    "source = ColumnDataSource(data=df.sample(frac=0.1))\n",
    "p = figure(width=1000)\n",
    "p.scatter(source=source, x='area', y='price' )\n",
    "hover = HoverTool(tooltips=[('flat area ', '@area'),\n",
    "                              ('price', '@price'),\n",
    "                              ('level', '@level')])\n",
    "\n",
    "p.add_tools(hover)\n",
    "show(p)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "15c89262",
   "metadata": {},
   "outputs": [],
   "source": [
    "from bokeh.transform import factor_cmap\n",
    "\n",
    "types = df['floor_level'].unique().tolist()\n",
    "source = ColumnDataSource(data=df.sample(frac=0.1))\n",
    "p = figure(width=1000)\n",
    "p.scatter(source=source, x='area', y='level', color=factor_cmap('floor_level', 'Category10_5', types) )\n",
    "hover = HoverTool(tooltips=[('area', '@area'),\n",
    "                              ('price', '@price'),\n",
    "                              ('level', '@level')])\n",
    "\n",
    "p.add_tools(hover)\n",
    "\n",
    "show(p)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "082960cc",
   "metadata": {},
   "source": [
    "# Save clean dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "id": "ec654599",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Сохраняем обработанный датафрейм, чтобы на следующих этапах не проводить повторно ту же обработку.\n",
    "# Лучше сохранить в pickle формате, чтобы сохранились все типы данных, в т.ч. category\n",
    "df.to_pickle('./data/clean_data.pkl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "id": "d410d06a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Index: 5393546 entries, 0 to 5477005\n",
      "Data columns (total 11 columns):\n",
      " #   Column         Dtype   \n",
      "---  ------         -----   \n",
      " 0   price          int64   \n",
      " 1   geo_lat        float32 \n",
      " 2   geo_lon        float32 \n",
      " 3   region         category\n",
      " 4   building_type  category\n",
      " 5   level          int8    \n",
      " 6   levels         int8    \n",
      " 7   rooms          int8    \n",
      " 8   area           float16 \n",
      " 9   kitchen_area   float16 \n",
      " 10  object_type    category\n",
      "dtypes: category(3), float16(2), float32(2), int64(1), int8(3)\n",
      "memory usage: 174.9 MB\n"
     ]
    }
   ],
   "source": [
    "# Считать можно так:\n",
    "df = pd.read_pickle('./data/clean_data.pkl')\n",
    "df.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3a7cbaaa",
   "metadata": {},
   "source": [
    "# Выводы после EDA"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "695334e5",
   "metadata": {},
   "source": [
    "Выводы, полученные в ходе анализа:\n",
    "* перечислить все действия, проведенные на этапе очистки данных\n",
    "* Создавались ли новые признаки? \n",
    "* Какие закономерности выявлены по графикам, которые могут быть полезны в дальнейшем для решния задачи?"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": ".venv_sprint02",
   "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": "3.10.12"
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 "nbformat": 4,
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