null_values.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "99af977c",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "65b775cf",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv(r\"E:\\machine learning excercise\\pista\\جلسه 20\\Ames_outliers_removed.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "91ab7dd3",
   "metadata": {},
   "outputs": [
    {
     "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>PID</th>\n",
       "      <th>MS SubClass</th>\n",
       "      <th>MS Zoning</th>\n",
       "      <th>Lot Frontage</th>\n",
       "      <th>Lot Area</th>\n",
       "      <th>Street</th>\n",
       "      <th>Alley</th>\n",
       "      <th>Lot Shape</th>\n",
       "      <th>Land Contour</th>\n",
       "      <th>Utilities</th>\n",
       "      <th>...</th>\n",
       "      <th>Pool Area</th>\n",
       "      <th>Pool QC</th>\n",
       "      <th>Fence</th>\n",
       "      <th>Misc Feature</th>\n",
       "      <th>Misc Val</th>\n",
       "      <th>Mo Sold</th>\n",
       "      <th>Yr Sold</th>\n",
       "      <th>Sale Type</th>\n",
       "      <th>Sale Condition</th>\n",
       "      <th>SalePrice</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>526301100</td>\n",
       "      <td>20</td>\n",
       "      <td>RL</td>\n",
       "      <td>141.0</td>\n",
       "      <td>31770</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>IR1</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>215000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>526350040</td>\n",
       "      <td>20</td>\n",
       "      <td>RH</td>\n",
       "      <td>80.0</td>\n",
       "      <td>11622</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MnPrv</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>2010</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>105000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>526351010</td>\n",
       "      <td>20</td>\n",
       "      <td>RL</td>\n",
       "      <td>81.0</td>\n",
       "      <td>14267</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>IR1</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Gar2</td>\n",
       "      <td>12500</td>\n",
       "      <td>6</td>\n",
       "      <td>2010</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>172000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>526353030</td>\n",
       "      <td>20</td>\n",
       "      <td>RL</td>\n",
       "      <td>93.0</td>\n",
       "      <td>11160</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>2010</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>244000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>527105010</td>\n",
       "      <td>60</td>\n",
       "      <td>RL</td>\n",
       "      <td>74.0</td>\n",
       "      <td>13830</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>IR1</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MnPrv</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>2010</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>189900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2922</th>\n",
       "      <td>923275080</td>\n",
       "      <td>80</td>\n",
       "      <td>RL</td>\n",
       "      <td>37.0</td>\n",
       "      <td>7937</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>IR1</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>GdPrv</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>2006</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>142500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2923</th>\n",
       "      <td>923276100</td>\n",
       "      <td>20</td>\n",
       "      <td>RL</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8885</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>IR1</td>\n",
       "      <td>Low</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MnPrv</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>2006</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>131000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2924</th>\n",
       "      <td>923400125</td>\n",
       "      <td>85</td>\n",
       "      <td>RL</td>\n",
       "      <td>62.0</td>\n",
       "      <td>10441</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MnPrv</td>\n",
       "      <td>Shed</td>\n",
       "      <td>700</td>\n",
       "      <td>7</td>\n",
       "      <td>2006</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>132000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2925</th>\n",
       "      <td>924100070</td>\n",
       "      <td>20</td>\n",
       "      <td>RL</td>\n",
       "      <td>77.0</td>\n",
       "      <td>10010</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>2006</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>170000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2926</th>\n",
       "      <td>924151050</td>\n",
       "      <td>60</td>\n",
       "      <td>RL</td>\n",
       "      <td>74.0</td>\n",
       "      <td>9627</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>11</td>\n",
       "      <td>2006</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>188000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2927 rows × 81 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            PID  MS SubClass MS Zoning  Lot Frontage  Lot Area Street Alley  \\\n",
       "0     526301100           20        RL         141.0     31770   Pave   NaN   \n",
       "1     526350040           20        RH          80.0     11622   Pave   NaN   \n",
       "2     526351010           20        RL          81.0     14267   Pave   NaN   \n",
       "3     526353030           20        RL          93.0     11160   Pave   NaN   \n",
       "4     527105010           60        RL          74.0     13830   Pave   NaN   \n",
       "...         ...          ...       ...           ...       ...    ...   ...   \n",
       "2922  923275080           80        RL          37.0      7937   Pave   NaN   \n",
       "2923  923276100           20        RL           NaN      8885   Pave   NaN   \n",
       "2924  923400125           85        RL          62.0     10441   Pave   NaN   \n",
       "2925  924100070           20        RL          77.0     10010   Pave   NaN   \n",
       "2926  924151050           60        RL          74.0      9627   Pave   NaN   \n",
       "\n",
       "     Lot Shape Land Contour Utilities  ... Pool Area Pool QC  Fence  \\\n",
       "0          IR1          Lvl    AllPub  ...         0     NaN    NaN   \n",
       "1          Reg          Lvl    AllPub  ...         0     NaN  MnPrv   \n",
       "2          IR1          Lvl    AllPub  ...         0     NaN    NaN   \n",
       "3          Reg          Lvl    AllPub  ...         0     NaN    NaN   \n",
       "4          IR1          Lvl    AllPub  ...         0     NaN  MnPrv   \n",
       "...        ...          ...       ...  ...       ...     ...    ...   \n",
       "2922       IR1          Lvl    AllPub  ...         0     NaN  GdPrv   \n",
       "2923       IR1          Low    AllPub  ...         0     NaN  MnPrv   \n",
       "2924       Reg          Lvl    AllPub  ...         0     NaN  MnPrv   \n",
       "2925       Reg          Lvl    AllPub  ...         0     NaN    NaN   \n",
       "2926       Reg          Lvl    AllPub  ...         0     NaN    NaN   \n",
       "\n",
       "     Misc Feature Misc Val Mo Sold Yr Sold  Sale Type  Sale Condition  \\\n",
       "0             NaN        0       5    2010        WD           Normal   \n",
       "1             NaN        0       6    2010        WD           Normal   \n",
       "2            Gar2    12500       6    2010        WD           Normal   \n",
       "3             NaN        0       4    2010        WD           Normal   \n",
       "4             NaN        0       3    2010        WD           Normal   \n",
       "...           ...      ...     ...     ...        ...             ...   \n",
       "2922          NaN        0       3    2006        WD           Normal   \n",
       "2923          NaN        0       6    2006        WD           Normal   \n",
       "2924         Shed      700       7    2006        WD           Normal   \n",
       "2925          NaN        0       4    2006        WD           Normal   \n",
       "2926          NaN        0      11    2006        WD           Normal   \n",
       "\n",
       "      SalePrice  \n",
       "0        215000  \n",
       "1        105000  \n",
       "2        172000  \n",
       "3        244000  \n",
       "4        189900  \n",
       "...         ...  \n",
       "2922     142500  \n",
       "2923     131000  \n",
       "2924     132000  \n",
       "2925     170000  \n",
       "2926     188000  \n",
       "\n",
       "[2927 rows x 81 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "a1f99629",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 2927 entries, 0 to 2926\n",
      "Data columns (total 81 columns):\n",
      " #   Column           Non-Null Count  Dtype  \n",
      "---  ------           --------------  -----  \n",
      " 0   PID              2927 non-null   int64  \n",
      " 1   MS SubClass      2927 non-null   int64  \n",
      " 2   MS Zoning        2927 non-null   object \n",
      " 3   Lot Frontage     2437 non-null   float64\n",
      " 4   Lot Area         2927 non-null   int64  \n",
      " 5   Street           2927 non-null   object \n",
      " 6   Alley            198 non-null    object \n",
      " 7   Lot Shape        2927 non-null   object \n",
      " 8   Land Contour     2927 non-null   object \n",
      " 9   Utilities        2927 non-null   object \n",
      " 10  Lot Config       2927 non-null   object \n",
      " 11  Land Slope       2927 non-null   object \n",
      " 12  Neighborhood     2927 non-null   object \n",
      " 13  Condition 1      2927 non-null   object \n",
      " 14  Condition 2      2927 non-null   object \n",
      " 15  Bldg Type        2927 non-null   object \n",
      " 16  House Style      2927 non-null   object \n",
      " 17  Overall Qual     2927 non-null   int64  \n",
      " 18  Overall Cond     2927 non-null   int64  \n",
      " 19  Year Built       2927 non-null   int64  \n",
      " 20  Year Remod/Add   2927 non-null   int64  \n",
      " 21  Roof Style       2927 non-null   object \n",
      " 22  Roof Matl        2927 non-null   object \n",
      " 23  Exterior 1st     2927 non-null   object \n",
      " 24  Exterior 2nd     2927 non-null   object \n",
      " 25  Mas Vnr Type     1152 non-null   object \n",
      " 26  Mas Vnr Area     2904 non-null   float64\n",
      " 27  Exter Qual       2927 non-null   object \n",
      " 28  Exter Cond       2927 non-null   object \n",
      " 29  Foundation       2927 non-null   object \n",
      " 30  Bsmt Qual        2847 non-null   object \n",
      " 31  Bsmt Cond        2847 non-null   object \n",
      " 32  Bsmt Exposure    2844 non-null   object \n",
      " 33  BsmtFin Type 1   2847 non-null   object \n",
      " 34  BsmtFin SF 1     2926 non-null   float64\n",
      " 35  BsmtFin Type 2   2846 non-null   object \n",
      " 36  BsmtFin SF 2     2926 non-null   float64\n",
      " 37  Bsmt Unf SF      2926 non-null   float64\n",
      " 38  Total Bsmt SF    2926 non-null   float64\n",
      " 39  Heating          2927 non-null   object \n",
      " 40  Heating QC       2927 non-null   object \n",
      " 41  Central Air      2927 non-null   object \n",
      " 42  Electrical       2926 non-null   object \n",
      " 43  1st Flr SF       2927 non-null   int64  \n",
      " 44  2nd Flr SF       2927 non-null   int64  \n",
      " 45  Low Qual Fin SF  2927 non-null   int64  \n",
      " 46  Gr Liv Area      2927 non-null   int64  \n",
      " 47  Bsmt Full Bath   2925 non-null   float64\n",
      " 48  Bsmt Half Bath   2925 non-null   float64\n",
      " 49  Full Bath        2927 non-null   int64  \n",
      " 50  Half Bath        2927 non-null   int64  \n",
      " 51  Bedroom AbvGr    2927 non-null   int64  \n",
      " 52  Kitchen AbvGr    2927 non-null   int64  \n",
      " 53  Kitchen Qual     2927 non-null   object \n",
      " 54  TotRms AbvGrd    2927 non-null   int64  \n",
      " 55  Functional       2927 non-null   object \n",
      " 56  Fireplaces       2927 non-null   int64  \n",
      " 57  Fireplace Qu     1505 non-null   object \n",
      " 58  Garage Type      2770 non-null   object \n",
      " 59  Garage Yr Blt    2768 non-null   float64\n",
      " 60  Garage Finish    2768 non-null   object \n",
      " 61  Garage Cars      2926 non-null   float64\n",
      " 62  Garage Area      2926 non-null   float64\n",
      " 63  Garage Qual      2768 non-null   object \n",
      " 64  Garage Cond      2768 non-null   object \n",
      " 65  Paved Drive      2927 non-null   object \n",
      " 66  Wood Deck SF     2927 non-null   int64  \n",
      " 67  Open Porch SF    2927 non-null   int64  \n",
      " 68  Enclosed Porch   2927 non-null   int64  \n",
      " 69  3Ssn Porch       2927 non-null   int64  \n",
      " 70  Screen Porch     2927 non-null   int64  \n",
      " 71  Pool Area        2927 non-null   int64  \n",
      " 72  Pool QC          12 non-null     object \n",
      " 73  Fence            572 non-null    object \n",
      " 74  Misc Feature     105 non-null    object \n",
      " 75  Misc Val         2927 non-null   int64  \n",
      " 76  Mo Sold          2927 non-null   int64  \n",
      " 77  Yr Sold          2927 non-null   int64  \n",
      " 78  Sale Type        2927 non-null   object \n",
      " 79  Sale Condition   2927 non-null   object \n",
      " 80  SalePrice        2927 non-null   int64  \n",
      "dtypes: float64(11), int64(27), object(43)\n",
      "memory usage: 1.8+ MB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "8feded52",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df.drop(\"PID\",axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "3cfae6f4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "MS SubClass         0\n",
       "MS Zoning           0\n",
       "Lot Frontage      490\n",
       "Lot Area            0\n",
       "Street              0\n",
       "                 ... \n",
       "Mo Sold             0\n",
       "Yr Sold             0\n",
       "Sale Type           0\n",
       "Sale Condition      0\n",
       "SalePrice           0\n",
       "Length: 80, dtype: int64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "a3e74ad2",
   "metadata": {},
   "outputs": [],
   "source": [
    "def percent_missing(df):\n",
    "    percent_nan = 100*df.isnull().sum() /len(df)\n",
    "    percent_nan = percent_nan[percent_nan >0].sort_values()\n",
    "    \n",
    "    return percent_nan"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "22c6385d",
   "metadata": {},
   "outputs": [],
   "source": [
    "percent_nan = percent_missing(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "0f68b00c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Total Bsmt SF      0.034165\n",
       "Bsmt Unf SF        0.034165\n",
       "BsmtFin SF 2       0.034165\n",
       "Electrical         0.034165\n",
       "BsmtFin SF 1       0.034165\n",
       "Garage Area        0.034165\n",
       "Garage Cars        0.034165\n",
       "Bsmt Full Bath     0.068329\n",
       "Bsmt Half Bath     0.068329\n",
       "Mas Vnr Area       0.785787\n",
       "Bsmt Qual          2.733174\n",
       "Bsmt Cond          2.733174\n",
       "BsmtFin Type 1     2.733174\n",
       "BsmtFin Type 2     2.767339\n",
       "Bsmt Exposure      2.835668\n",
       "Garage Type        5.363854\n",
       "Garage Qual        5.432183\n",
       "Garage Finish      5.432183\n",
       "Garage Cond        5.432183\n",
       "Garage Yr Blt      5.432183\n",
       "Lot Frontage      16.740690\n",
       "Fireplace Qu      48.582166\n",
       "Mas Vnr Type      60.642296\n",
       "Fence             80.457807\n",
       "Alley             93.235395\n",
       "Misc Feature      96.412709\n",
       "Pool QC           99.590024\n",
       "dtype: float64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "percent_nan"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "3936f4a0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "([0,\n",
       "  1,\n",
       "  2,\n",
       "  3,\n",
       "  4,\n",
       "  5,\n",
       "  6,\n",
       "  7,\n",
       "  8,\n",
       "  9,\n",
       "  10,\n",
       "  11,\n",
       "  12,\n",
       "  13,\n",
       "  14,\n",
       "  15,\n",
       "  16,\n",
       "  17,\n",
       "  18,\n",
       "  19,\n",
       "  20,\n",
       "  21,\n",
       "  22,\n",
       "  23,\n",
       "  24,\n",
       "  25,\n",
       "  26],\n",
       " [Text(0, 0, 'Total Bsmt SF'),\n",
       "  Text(1, 0, 'Bsmt Unf SF'),\n",
       "  Text(2, 0, 'BsmtFin SF 2'),\n",
       "  Text(3, 0, 'Electrical'),\n",
       "  Text(4, 0, 'BsmtFin SF 1'),\n",
       "  Text(5, 0, 'Garage Area'),\n",
       "  Text(6, 0, 'Garage Cars'),\n",
       "  Text(7, 0, 'Bsmt Full Bath'),\n",
       "  Text(8, 0, 'Bsmt Half Bath'),\n",
       "  Text(9, 0, 'Mas Vnr Area'),\n",
       "  Text(10, 0, 'Bsmt Qual'),\n",
       "  Text(11, 0, 'Bsmt Cond'),\n",
       "  Text(12, 0, 'BsmtFin Type 1'),\n",
       "  Text(13, 0, 'BsmtFin Type 2'),\n",
       "  Text(14, 0, 'Bsmt Exposure'),\n",
       "  Text(15, 0, 'Garage Type'),\n",
       "  Text(16, 0, 'Garage Qual'),\n",
       "  Text(17, 0, 'Garage Finish'),\n",
       "  Text(18, 0, 'Garage Cond'),\n",
       "  Text(19, 0, 'Garage Yr Blt'),\n",
       "  Text(20, 0, 'Lot Frontage'),\n",
       "  Text(21, 0, 'Fireplace Qu'),\n",
       "  Text(22, 0, 'Mas Vnr Type'),\n",
       "  Text(23, 0, 'Fence'),\n",
       "  Text(24, 0, 'Alley'),\n",
       "  Text(25, 0, 'Misc Feature'),\n",
       "  Text(26, 0, 'Pool QC')])"
      ]
     },
     "execution_count": 10,
     "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": [
    "sns.barplot(x=percent_nan.index,y=percent_nan)\n",
    "plt.xticks(rotation=90)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "17ad92f7",
   "metadata": {},
   "source": [
    "#ستون هایی که تعداد missing value کمتری دارند"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "5d0fb84e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.0, 1.0)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1600x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8,4),dpi=200)\n",
    "sns.barplot(x=percent_nan.index,y=percent_nan)\n",
    "plt.xticks(rotation=90)\n",
    "plt.ylim(0,1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "092d599b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Total Bsmt SF     0.034165\n",
       "Bsmt Unf SF       0.034165\n",
       "BsmtFin SF 2      0.034165\n",
       "Electrical        0.034165\n",
       "BsmtFin SF 1      0.034165\n",
       "Garage Area       0.034165\n",
       "Garage Cars       0.034165\n",
       "Bsmt Full Bath    0.068329\n",
       "Bsmt Half Bath    0.068329\n",
       "Mas Vnr Area      0.785787\n",
       "dtype: float64"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "percent_nan[percent_nan<1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "662779e2",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>MS SubClass</th>\n",
       "      <th>MS Zoning</th>\n",
       "      <th>Lot Frontage</th>\n",
       "      <th>Lot Area</th>\n",
       "      <th>Street</th>\n",
       "      <th>Alley</th>\n",
       "      <th>Lot Shape</th>\n",
       "      <th>Land Contour</th>\n",
       "      <th>Utilities</th>\n",
       "      <th>Lot Config</th>\n",
       "      <th>...</th>\n",
       "      <th>Pool Area</th>\n",
       "      <th>Pool QC</th>\n",
       "      <th>Fence</th>\n",
       "      <th>Misc Feature</th>\n",
       "      <th>Misc Val</th>\n",
       "      <th>Mo Sold</th>\n",
       "      <th>Yr Sold</th>\n",
       "      <th>Sale Type</th>\n",
       "      <th>Sale Condition</th>\n",
       "      <th>SalePrice</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1576</th>\n",
       "      <td>80</td>\n",
       "      <td>RL</td>\n",
       "      <td>73.0</td>\n",
       "      <td>9735</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Inside</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>2008</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>167500</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1 rows × 80 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      MS SubClass MS Zoning  Lot Frontage  Lot Area Street Alley Lot Shape  \\\n",
       "1576           80        RL          73.0      9735   Pave   NaN       Reg   \n",
       "\n",
       "     Land Contour Utilities Lot Config  ... Pool Area Pool QC Fence  \\\n",
       "1576          Lvl    AllPub     Inside  ...         0     NaN   NaN   \n",
       "\n",
       "     Misc Feature Misc Val Mo Sold  Yr Sold  Sale Type  Sale Condition  \\\n",
       "1576          NaN        0       5     2008        WD           Normal   \n",
       "\n",
       "      SalePrice  \n",
       "1576     167500  \n",
       "\n",
       "[1 rows x 80 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['Electrical'].isnull()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "538e49a2",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>MS SubClass</th>\n",
       "      <th>MS Zoning</th>\n",
       "      <th>Lot Frontage</th>\n",
       "      <th>Lot Area</th>\n",
       "      <th>Street</th>\n",
       "      <th>Alley</th>\n",
       "      <th>Lot Shape</th>\n",
       "      <th>Land Contour</th>\n",
       "      <th>Utilities</th>\n",
       "      <th>Lot Config</th>\n",
       "      <th>...</th>\n",
       "      <th>Pool Area</th>\n",
       "      <th>Pool QC</th>\n",
       "      <th>Fence</th>\n",
       "      <th>Misc Feature</th>\n",
       "      <th>Misc Val</th>\n",
       "      <th>Mo Sold</th>\n",
       "      <th>Yr Sold</th>\n",
       "      <th>Sale Type</th>\n",
       "      <th>Sale Condition</th>\n",
       "      <th>SalePrice</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1341</th>\n",
       "      <td>20</td>\n",
       "      <td>RM</td>\n",
       "      <td>99.0</td>\n",
       "      <td>5940</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>IR1</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>FR3</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>MnPrv</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>2008</td>\n",
       "      <td>ConLD</td>\n",
       "      <td>Abnorml</td>\n",
       "      <td>79000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1497</th>\n",
       "      <td>20</td>\n",
       "      <td>RL</td>\n",
       "      <td>123.0</td>\n",
       "      <td>47007</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>IR1</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Inside</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>2008</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>284700</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2 rows × 80 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      MS SubClass MS Zoning  Lot Frontage  Lot Area Street Alley Lot Shape  \\\n",
       "1341           20        RM          99.0      5940   Pave   NaN       IR1   \n",
       "1497           20        RL         123.0     47007   Pave   NaN       IR1   \n",
       "\n",
       "     Land Contour Utilities Lot Config  ... Pool Area Pool QC  Fence  \\\n",
       "1341          Lvl    AllPub        FR3  ...         0     NaN  MnPrv   \n",
       "1497          Lvl    AllPub     Inside  ...         0     NaN    NaN   \n",
       "\n",
       "     Misc Feature Misc Val Mo Sold  Yr Sold  Sale Type  Sale Condition  \\\n",
       "1341          NaN        0       4     2008      ConLD         Abnorml   \n",
       "1497          NaN        0       7     2008        WD           Normal   \n",
       "\n",
       "      SalePrice  \n",
       "1341      79000  \n",
       "1497     284700  \n",
       "\n",
       "[2 rows x 80 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['Bsmt Full Bath'].isnull()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "059e0116",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df.dropna(axis=0, subset=['Electrical','Garage Area'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "6497f195",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>MS SubClass</th>\n",
       "      <th>MS Zoning</th>\n",
       "      <th>Lot Frontage</th>\n",
       "      <th>Lot Area</th>\n",
       "      <th>Street</th>\n",
       "      <th>Alley</th>\n",
       "      <th>Lot Shape</th>\n",
       "      <th>Land Contour</th>\n",
       "      <th>Utilities</th>\n",
       "      <th>Lot Config</th>\n",
       "      <th>...</th>\n",
       "      <th>Pool Area</th>\n",
       "      <th>Pool QC</th>\n",
       "      <th>Fence</th>\n",
       "      <th>Misc Feature</th>\n",
       "      <th>Misc Val</th>\n",
       "      <th>Mo Sold</th>\n",
       "      <th>Yr Sold</th>\n",
       "      <th>Sale Type</th>\n",
       "      <th>Sale Condition</th>\n",
       "      <th>SalePrice</th>\n",
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      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [MS SubClass, MS Zoning, Lot Frontage, Lot Area, Street, Alley, Lot Shape, Land Contour, Utilities, Lot Config, Land Slope, Neighborhood, Condition 1, Condition 2, Bldg Type, House Style, Overall Qual, Overall Cond, Year Built, Year Remod/Add, Roof Style, Roof Matl, Exterior 1st, Exterior 2nd, Mas Vnr Type, Mas Vnr Area, Exter Qual, Exter Cond, Foundation, Bsmt Qual, Bsmt Cond, Bsmt Exposure, BsmtFin Type 1, BsmtFin SF 1, BsmtFin Type 2, BsmtFin SF 2, Bsmt Unf SF, Total Bsmt SF, Heating, Heating QC, Central Air, Electrical, 1st Flr SF, 2nd Flr SF, Low Qual Fin SF, Gr Liv Area, Bsmt Full Bath, Bsmt Half Bath, Full Bath, Half Bath, Bedroom AbvGr, Kitchen AbvGr, Kitchen Qual, TotRms AbvGrd, Functional, Fireplaces, Fireplace Qu, Garage Type, Garage Yr Blt, Garage Finish, Garage Cars, Garage Area, Garage Qual, Garage Cond, Paved Drive, Wood Deck SF, Open Porch SF, Enclosed Porch, 3Ssn Porch, Screen Porch, Pool Area, Pool QC, Fence, Misc Feature, Misc Val, Mo Sold, Yr Sold, Sale Type, Sale Condition, SalePrice]\n",
       "Index: []\n",
       "\n",
       "[0 rows x 80 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['Electrical'].isnull()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "2afb2936",
   "metadata": {},
   "outputs": [],
   "source": [
    "percent_nan = percent_missing(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "8ca34815",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Total Bsmt SF      0.034188\n",
       "Bsmt Unf SF        0.034188\n",
       "BsmtFin SF 2       0.034188\n",
       "BsmtFin SF 1       0.034188\n",
       "Bsmt Full Bath     0.068376\n",
       "Bsmt Half Bath     0.068376\n",
       "Mas Vnr Area       0.786325\n",
       "BsmtFin Type 1     2.735043\n",
       "Bsmt Qual          2.735043\n",
       "Bsmt Cond          2.735043\n",
       "BsmtFin Type 2     2.769231\n",
       "Bsmt Exposure      2.837607\n",
       "Garage Type        5.367521\n",
       "Garage Qual        5.401709\n",
       "Garage Yr Blt      5.401709\n",
       "Garage Finish      5.401709\n",
       "Garage Cond        5.401709\n",
       "Lot Frontage      16.752137\n",
       "Fireplace Qu      48.547009\n",
       "Mas Vnr Type      60.615385\n",
       "Fence             80.478632\n",
       "Alley             93.230769\n",
       "Misc Feature      96.410256\n",
       "Pool QC           99.589744\n",
       "dtype: float64"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "percent_nan"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "faa9260d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Total Bsmt SF     0.034188\n",
       "Bsmt Unf SF       0.034188\n",
       "BsmtFin SF 2      0.034188\n",
       "BsmtFin SF 1      0.034188\n",
       "Bsmt Full Bath    0.068376\n",
       "Bsmt Half Bath    0.068376\n",
       "Mas Vnr Area      0.786325\n",
       "dtype: float64"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "percent_nan[percent_nan<1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "bc3b3d2c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['MS SubClass', 'MS Zoning', 'Lot Frontage', 'Lot Area', 'Street',\n",
       "       'Alley', 'Lot Shape', 'Land Contour', 'Utilities', 'Lot Config',\n",
       "       'Land Slope', 'Neighborhood', 'Condition 1', 'Condition 2', 'Bldg Type',\n",
       "       'House Style', 'Overall Qual', 'Overall Cond', 'Year Built',\n",
       "       'Year Remod/Add', 'Roof Style', 'Roof Matl', 'Exterior 1st',\n",
       "       'Exterior 2nd', 'Mas Vnr Type', 'Mas Vnr Area', 'Exter Qual',\n",
       "       'Exter Cond', 'Foundation', 'Bsmt Qual', 'Bsmt Cond', 'Bsmt Exposure',\n",
       "       'BsmtFin Type 1', 'BsmtFin SF 1', 'BsmtFin Type 2', 'BsmtFin SF 2',\n",
       "       'Bsmt Unf SF', 'Total Bsmt SF', 'Heating', 'Heating QC', 'Central Air',\n",
       "       'Electrical', '1st Flr SF', '2nd Flr SF', 'Low Qual Fin SF',\n",
       "       'Gr Liv Area', 'Bsmt Full Bath', 'Bsmt Half Bath', 'Full Bath',\n",
       "       'Half Bath', 'Bedroom AbvGr', 'Kitchen AbvGr', 'Kitchen Qual',\n",
       "       'TotRms AbvGrd', 'Functional', 'Fireplaces', 'Fireplace Qu',\n",
       "       'Garage Type', 'Garage Yr Blt', 'Garage Finish', 'Garage Cars',\n",
       "       'Garage Area', 'Garage Qual', 'Garage Cond', 'Paved Drive',\n",
       "       'Wood Deck SF', 'Open Porch SF', 'Enclosed Porch', '3Ssn Porch',\n",
       "       'Screen Porch', 'Pool Area', 'Pool QC', 'Fence', 'Misc Feature',\n",
       "       'Misc Val', 'Mo Sold', 'Yr Sold', 'Sale Type', 'Sale Condition',\n",
       "       'SalePrice'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "50c5a606",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MSSubClass: Identifies the type of dwelling involved in the sale.\t\n",
      "\n",
      "        20\t1-STORY 1946 & NEWER ALL STYLES\n",
      "        30\t1-STORY 1945 & OLDER\n",
      "        40\t1-STORY W/FINISHED ATTIC ALL AGES\n",
      "        45\t1-1/2 STORY - UNFINISHED ALL AGES\n",
      "        50\t1-1/2 STORY FINISHED ALL AGES\n",
      "        60\t2-STORY 1946 & NEWER\n",
      "        70\t2-STORY 1945 & OLDER\n",
      "        75\t2-1/2 STORY ALL AGES\n",
      "        80\tSPLIT OR MULTI-LEVEL\n",
      "        85\tSPLIT FOYER\n",
      "        90\tDUPLEX - ALL STYLES AND AGES\n",
      "       120\t1-STORY PUD (Planned Unit Development) - 1946 & NEWER\n",
      "       150\t1-1/2 STORY PUD - ALL AGES\n",
      "       160\t2-STORY PUD - 1946 & NEWER\n",
      "       180\tPUD - MULTILEVEL - INCL SPLIT LEV/FOYER\n",
      "       190\t2 FAMILY CONVERSION - ALL STYLES AND AGES\n",
      "\n",
      "MSZoning: Identifies the general zoning classification of the sale.\n",
      "\t\t\n",
      "       A\tAgriculture\n",
      "       C\tCommercial\n",
      "       FV\tFloating Village Residential\n",
      "       I\tIndustrial\n",
      "       RH\tResidential High Density\n",
      "       RL\tResidential Low Density\n",
      "       RP\tResidential Low Density Park \n",
      "       RM\tResidential Medium Density\n",
      "\t\n",
      "LotFrontage: Linear feet of street connected to property\n",
      "\n",
      "LotArea: Lot size in square feet\n",
      "\n",
      "Street: Type of road access to property\n",
      "\n",
      "       Grvl\tGravel\t\n",
      "       Pave\tPaved\n",
      "       \t\n",
      "Alley: Type of alley access to property\n",
      "\n",
      "       Grvl\tGravel\n",
      "       Pave\tPaved\n",
      "       NA \tNo alley access\n",
      "\t\t\n",
      "LotShape: General shape of property\n",
      "\n",
      "       Reg\tRegular\t\n",
      "       IR1\tSlightly irregular\n",
      "       IR2\tModerately Irregular\n",
      "       IR3\tIrregular\n",
      "       \n",
      "LandContour: Flatness of the property\n",
      "\n",
      "       Lvl\tNear Flat/Level\t\n",
      "       Bnk\tBanked - Quick and significant rise from street grade to building\n",
      "       HLS\tHillside - Significant slope from side to side\n",
      "       Low\tDepression\n",
      "\t\t\n",
      "Utilities: Type of utilities available\n",
      "\t\t\n",
      "       AllPub\tAll public Utilities (E,G,W,& S)\t\n",
      "       NoSewr\tElectricity, Gas, and Water (Septic Tank)\n",
      "       NoSeWa\tElectricity and Gas Only\n",
      "       ELO\tElectricity only\t\n",
      "\t\n",
      "LotConfig: Lot configuration\n",
      "\n",
      "       Inside\tInside lot\n",
      "       Corner\tCorner lot\n",
      "       CulDSac\tCul-de-sac\n",
      "       FR2\tFrontage on 2 sides of property\n",
      "       FR3\tFrontage on 3 sides of property\n",
      "\t\n",
      "LandSlope: Slope of property\n",
      "\t\t\n",
      "       Gtl\tGentle slope\n",
      "       Mod\tModerate Slope\t\n",
      "       Sev\tSevere Slope\n",
      "\t\n",
      "Neighborhood: Physical locations within Ames city limits\n",
      "\n",
      "       Blmngtn\tBloomington Heights\n",
      "       Blueste\tBluestem\n",
      "       BrDale\tBriardale\n",
      "       BrkSide\tBrookside\n",
      "       ClearCr\tClear Creek\n",
      "       CollgCr\tCollege Creek\n",
      "       Crawfor\tCrawford\n",
      "       Edwards\tEdwards\n",
      "       Gilbert\tGilbert\n",
      "       IDOTRR\tIowa DOT and Rail Road\n",
      "       MeadowV\tMeadow Village\n",
      "       Mitchel\tMitchell\n",
      "       Names\tNorth Ames\n",
      "       NoRidge\tNorthridge\n",
      "       NPkVill\tNorthpark Villa\n",
      "       NridgHt\tNorthridge Heights\n",
      "       NWAmes\tNorthwest Ames\n",
      "       OldTown\tOld Town\n",
      "       SWISU\tSouth & West of Iowa State University\n",
      "       Sawyer\tSawyer\n",
      "       SawyerW\tSawyer West\n",
      "       Somerst\tSomerset\n",
      "       StoneBr\tStone Brook\n",
      "       Timber\tTimberland\n",
      "       Veenker\tVeenker\n",
      "\t\t\t\n",
      "Condition1: Proximity to various conditions\n",
      "\t\n",
      "       Artery\tAdjacent to arterial street\n",
      "       Feedr\tAdjacent to feeder street\t\n",
      "       Norm\tNormal\t\n",
      "       RRNn\tWithin 200' of North-South Railroad\n",
      "       RRAn\tAdjacent to North-South Railroad\n",
      "       PosN\tNear positive off-site feature--park, greenbelt, etc.\n",
      "       PosA\tAdjacent to postive off-site feature\n",
      "       RRNe\tWithin 200' of East-West Railroad\n",
      "       RRAe\tAdjacent to East-West Railroad\n",
      "\t\n",
      "Condition2: Proximity to various conditions (if more than one is present)\n",
      "\t\t\n",
      "       Artery\tAdjacent to arterial street\n",
      "       Feedr\tAdjacent to feeder street\t\n",
      "       Norm\tNormal\t\n",
      "       RRNn\tWithin 200' of North-South Railroad\n",
      "       RRAn\tAdjacent to North-South Railroad\n",
      "       PosN\tNear positive off-site feature--park, greenbelt, etc.\n",
      "       PosA\tAdjacent to postive off-site feature\n",
      "       RRNe\tWithin 200' of East-West Railroad\n",
      "       RRAe\tAdjacent to East-West Railroad\n",
      "\t\n",
      "BldgType: Type of dwelling\n",
      "\t\t\n",
      "       1Fam\tSingle-family Detached\t\n",
      "       2FmCon\tTwo-family Conversion; originally built as one-family dwelling\n",
      "       Duplx\tDuplex\n",
      "       TwnhsE\tTownhouse End Unit\n",
      "       TwnhsI\tTownhouse Inside Unit\n",
      "\t\n",
      "HouseStyle: Style of dwelling\n",
      "\t\n",
      "       1Story\tOne story\n",
      "       1.5Fin\tOne and one-half story: 2nd level finished\n",
      "       1.5Unf\tOne and one-half story: 2nd level unfinished\n",
      "       2Story\tTwo story\n",
      "       2.5Fin\tTwo and one-half story: 2nd level finished\n",
      "       2.5Unf\tTwo and one-half story: 2nd level unfinished\n",
      "       SFoyer\tSplit Foyer\n",
      "       SLvl\tSplit Level\n",
      "\t\n",
      "OverallQual: Rates the overall material and finish of the house\n",
      "\n",
      "       10\tVery Excellent\n",
      "       9\tExcellent\n",
      "       8\tVery Good\n",
      "       7\tGood\n",
      "       6\tAbove Average\n",
      "       5\tAverage\n",
      "       4\tBelow Average\n",
      "       3\tFair\n",
      "       2\tPoor\n",
      "       1\tVery Poor\n",
      "\t\n",
      "OverallCond: Rates the overall condition of the house\n",
      "\n",
      "       10\tVery Excellent\n",
      "       9\tExcellent\n",
      "       8\tVery Good\n",
      "       7\tGood\n",
      "       6\tAbove Average\t\n",
      "       5\tAverage\n",
      "       4\tBelow Average\t\n",
      "       3\tFair\n",
      "       2\tPoor\n",
      "       1\tVery Poor\n",
      "\t\t\n",
      "YearBuilt: Original construction date\n",
      "\n",
      "YearRemodAdd: Remodel date (same as construction date if no remodeling or additions)\n",
      "\n",
      "RoofStyle: Type of roof\n",
      "\n",
      "       Flat\tFlat\n",
      "       Gable\tGable\n",
      "       Gambrel\tGabrel (Barn)\n",
      "       Hip\tHip\n",
      "       Mansard\tMansard\n",
      "       Shed\tShed\n",
      "\t\t\n",
      "RoofMatl: Roof material\n",
      "\n",
      "       ClyTile\tClay or Tile\n",
      "       CompShg\tStandard (Composite) Shingle\n",
      "       Membran\tMembrane\n",
      "       Metal\tMetal\n",
      "       Roll\tRoll\n",
      "       Tar&Grv\tGravel & Tar\n",
      "       WdShake\tWood Shakes\n",
      "       WdShngl\tWood Shingles\n",
      "\t\t\n",
      "Exterior1st: Exterior covering on house\n",
      "\n",
      "       AsbShng\tAsbestos Shingles\n",
      "       AsphShn\tAsphalt Shingles\n",
      "       BrkComm\tBrick Common\n",
      "       BrkFace\tBrick Face\n",
      "       CBlock\tCinder Block\n",
      "       CemntBd\tCement Board\n",
      "       HdBoard\tHard Board\n",
      "       ImStucc\tImitation Stucco\n",
      "       MetalSd\tMetal Siding\n",
      "       Other\tOther\n",
      "       Plywood\tPlywood\n",
      "       PreCast\tPreCast\t\n",
      "       Stone\tStone\n",
      "       Stucco\tStucco\n",
      "       VinylSd\tVinyl Siding\n",
      "       Wd Sdng\tWood Siding\n",
      "       WdShing\tWood Shingles\n",
      "\t\n",
      "Exterior2nd: Exterior covering on house (if more than one material)\n",
      "\n",
      "       AsbShng\tAsbestos Shingles\n",
      "       AsphShn\tAsphalt Shingles\n",
      "       BrkComm\tBrick Common\n",
      "       BrkFace\tBrick Face\n",
      "       CBlock\tCinder Block\n",
      "       CemntBd\tCement Board\n",
      "       HdBoard\tHard Board\n",
      "       ImStucc\tImitation Stucco\n",
      "       MetalSd\tMetal Siding\n",
      "       Other\tOther\n",
      "       Plywood\tPlywood\n",
      "       PreCast\tPreCast\n",
      "       Stone\tStone\n",
      "       Stucco\tStucco\n",
      "       VinylSd\tVinyl Siding\n",
      "       Wd Sdng\tWood Siding\n",
      "       WdShing\tWood Shingles\n",
      "\t\n",
      "MasVnrType: Masonry veneer type\n",
      "\n",
      "       BrkCmn\tBrick Common\n",
      "       BrkFace\tBrick Face\n",
      "       CBlock\tCinder Block\n",
      "       None\tNone\n",
      "       Stone\tStone\n",
      "\t\n",
      "MasVnrArea: Masonry veneer area in square feet\n",
      "\n",
      "ExterQual: Evaluates the quality of the material on the exterior \n",
      "\t\t\n",
      "       Ex\tExcellent\n",
      "       Gd\tGood\n",
      "       TA\tAverage/Typical\n",
      "       Fa\tFair\n",
      "       Po\tPoor\n",
      "\t\t\n",
      "ExterCond: Evaluates the present condition of the material on the exterior\n",
      "\t\t\n",
      "       Ex\tExcellent\n",
      "       Gd\tGood\n",
      "       TA\tAverage/Typical\n",
      "       Fa\tFair\n",
      "       Po\tPoor\n",
      "\t\t\n",
      "Foundation: Type of foundation\n",
      "\t\t\n",
      "       BrkTil\tBrick & Tile\n",
      "       CBlock\tCinder Block\n",
      "       PConc\tPoured Contrete\t\n",
      "       Slab\tSlab\n",
      "       Stone\tStone\n",
      "       Wood\tWood\n",
      "\t\t\n",
      "BsmtQual: Evaluates the height of the basement\n",
      "\n",
      "       Ex\tExcellent (100+ inches)\t\n",
      "       Gd\tGood (90-99 inches)\n",
      "       TA\tTypical (80-89 inches)\n",
      "       Fa\tFair (70-79 inches)\n",
      "       Po\tPoor (<70 inches\n",
      "       NA\tNo Basement\n",
      "\t\t\n",
      "BsmtCond: Evaluates the general condition of the basement\n",
      "\n",
      "       Ex\tExcellent\n",
      "       Gd\tGood\n",
      "       TA\tTypical - slight dampness allowed\n",
      "       Fa\tFair - dampness or some cracking or settling\n",
      "       Po\tPoor - Severe cracking, settling, or wetness\n",
      "       NA\tNo Basement\n",
      "\t\n",
      "BsmtExposure: Refers to walkout or garden level walls\n",
      "\n",
      "       Gd\tGood Exposure\n",
      "       Av\tAverage Exposure (split levels or foyers typically score average or above)\t\n",
      "       Mn\tMimimum Exposure\n",
      "       No\tNo Exposure\n",
      "       NA\tNo Basement\n",
      "\t\n",
      "BsmtFinType1: Rating of basement finished area\n",
      "\n",
      "       GLQ\tGood Living Quarters\n",
      "       ALQ\tAverage Living Quarters\n",
      "       BLQ\tBelow Average Living Quarters\t\n",
      "       Rec\tAverage Rec Room\n",
      "       LwQ\tLow Quality\n",
      "       Unf\tUnfinshed\n",
      "       NA\tNo Basement\n",
      "\t\t\n",
      "BsmtFinSF1: Type 1 finished square feet\n",
      "\n",
      "BsmtFinType2: Rating of basement finished area (if multiple types)\n",
      "\n",
      "       GLQ\tGood Living Quarters\n",
      "       ALQ\tAverage Living Quarters\n",
      "       BLQ\tBelow Average Living Quarters\t\n",
      "       Rec\tAverage Rec Room\n",
      "       LwQ\tLow Quality\n",
      "       Unf\tUnfinshed\n",
      "       NA\tNo Basement\n",
      "\n",
      "BsmtFinSF2: Type 2 finished square feet\n",
      "\n",
      "BsmtUnfSF: Unfinished square feet of basement area\n",
      "\n",
      "TotalBsmtSF: Total square feet of basement area\n",
      "\n",
      "Heating: Type of heating\n",
      "\t\t\n",
      "       Floor\tFloor Furnace\n",
      "       GasA\tGas forced warm air furnace\n",
      "       GasW\tGas hot water or steam heat\n",
      "       Grav\tGravity furnace\t\n",
      "       OthW\tHot water or steam heat other than gas\n",
      "       Wall\tWall furnace\n",
      "\t\t\n",
      "HeatingQC: Heating quality and condition\n",
      "\n",
      "       Ex\tExcellent\n",
      "       Gd\tGood\n",
      "       TA\tAverage/Typical\n",
      "       Fa\tFair\n",
      "       Po\tPoor\n",
      "\t\t\n",
      "CentralAir: Central air conditioning\n",
      "\n",
      "       N\tNo\n",
      "       Y\tYes\n",
      "\t\t\n",
      "Electrical: Electrical system\n",
      "\n",
      "       SBrkr\tStandard Circuit Breakers & Romex\n",
      "       FuseA\tFuse Box over 60 AMP and all Romex wiring (Average)\t\n",
      "       FuseF\t60 AMP Fuse Box and mostly Romex wiring (Fair)\n",
      "       FuseP\t60 AMP Fuse Box and mostly knob & tube wiring (poor)\n",
      "       Mix\tMixed\n",
      "\t\t\n",
      "1stFlrSF: First Floor square feet\n",
      " \n",
      "2ndFlrSF: Second floor square feet\n",
      "\n",
      "LowQualFinSF: Low quality finished square feet (all floors)\n",
      "\n",
      "GrLivArea: Above grade (ground) living area square feet\n",
      "\n",
      "BsmtFullBath: Basement full bathrooms\n",
      "\n",
      "BsmtHalfBath: Basement half bathrooms\n",
      "\n",
      "FullBath: Full bathrooms above grade\n",
      "\n",
      "HalfBath: Half baths above grade\n",
      "\n",
      "Bedroom: Bedrooms above grade (does NOT include basement bedrooms)\n",
      "\n",
      "Kitchen: Kitchens above grade\n",
      "\n",
      "KitchenQual: Kitchen quality\n",
      "\n",
      "       Ex\tExcellent\n",
      "       Gd\tGood\n",
      "       TA\tTypical/Average\n",
      "       Fa\tFair\n",
      "       Po\tPoor\n",
      "       \t\n",
      "TotRmsAbvGrd: Total rooms above grade (does not include bathrooms)\n",
      "\n",
      "Functional: Home functionality (Assume typical unless deductions are warranted)\n",
      "\n",
      "       Typ\tTypical Functionality\n",
      "       Min1\tMinor Deductions 1\n",
      "       Min2\tMinor Deductions 2\n",
      "       Mod\tModerate Deductions\n",
      "       Maj1\tMajor Deductions 1\n",
      "       Maj2\tMajor Deductions 2\n",
      "       Sev\tSeverely Damaged\n",
      "       Sal\tSalvage only\n",
      "\t\t\n",
      "Fireplaces: Number of fireplaces\n",
      "\n",
      "FireplaceQu: Fireplace quality\n",
      "\n",
      "       Ex\tExcellent - Exceptional Masonry Fireplace\n",
      "       Gd\tGood - Masonry Fireplace in main level\n",
      "       TA\tAverage - Prefabricated Fireplace in main living area or Masonry Fireplace in basement\n",
      "       Fa\tFair - Prefabricated Fireplace in basement\n",
      "       Po\tPoor - Ben Franklin Stove\n",
      "       NA\tNo Fireplace\n",
      "\t\t\n",
      "GarageType: Garage location\n",
      "\t\t\n",
      "       2Types\tMore than one type of garage\n",
      "       Attchd\tAttached to home\n",
      "       Basment\tBasement Garage\n",
      "       BuiltIn\tBuilt-In (Garage part of house - typically has room above garage)\n",
      "       CarPort\tCar Port\n",
      "       Detchd\tDetached from home\n",
      "       NA\tNo Garage\n",
      "\t\t\n",
      "GarageYrBlt: Year garage was built\n",
      "\t\t\n",
      "GarageFinish: Interior finish of the garage\n",
      "\n",
      "       Fin\tFinished\n",
      "       RFn\tRough Finished\t\n",
      "       Unf\tUnfinished\n",
      "       NA\tNo Garage\n",
      "\t\t\n",
      "GarageCars: Size of garage in car capacity\n",
      "\n",
      "GarageArea: Size of garage in square feet\n",
      "\n",
      "GarageQual: Garage quality\n",
      "\n",
      "       Ex\tExcellent\n",
      "       Gd\tGood\n",
      "       TA\tTypical/Average\n",
      "       Fa\tFair\n",
      "       Po\tPoor\n",
      "       NA\tNo Garage\n",
      "\t\t\n",
      "GarageCond: Garage condition\n",
      "\n",
      "       Ex\tExcellent\n",
      "       Gd\tGood\n",
      "       TA\tTypical/Average\n",
      "       Fa\tFair\n",
      "       Po\tPoor\n",
      "       NA\tNo Garage\n",
      "\t\t\n",
      "PavedDrive: Paved driveway\n",
      "\n",
      "       Y\tPaved \n",
      "       P\tPartial Pavement\n",
      "       N\tDirt/Gravel\n",
      "\t\t\n",
      "WoodDeckSF: Wood deck area in square feet\n",
      "\n",
      "OpenPorchSF: Open porch area in square feet\n",
      "\n",
      "EnclosedPorch: Enclosed porch area in square feet\n",
      "\n",
      "3SsnPorch: Three season porch area in square feet\n",
      "\n",
      "ScreenPorch: Screen porch area in square feet\n",
      "\n",
      "PoolArea: Pool area in square feet\n",
      "\n",
      "PoolQC: Pool quality\n",
      "\t\t\n",
      "       Ex\tExcellent\n",
      "       Gd\tGood\n",
      "       TA\tAverage/Typical\n",
      "       Fa\tFair\n",
      "       NA\tNo Pool\n",
      "\t\t\n",
      "Fence: Fence quality\n",
      "\t\t\n",
      "       GdPrv\tGood Privacy\n",
      "       MnPrv\tMinimum Privacy\n",
      "       GdWo\tGood Wood\n",
      "       MnWw\tMinimum Wood/Wire\n",
      "       NA\tNo Fence\n",
      "\t\n",
      "MiscFeature: Miscellaneous feature not covered in other categories\n",
      "\t\t\n",
      "       Elev\tElevator\n",
      "       Gar2\t2nd Garage (if not described in garage section)\n",
      "       Othr\tOther\n",
      "       Shed\tShed (over 100 SF)\n",
      "       TenC\tTennis Court\n",
      "       NA\tNone\n",
      "\t\t\n",
      "MiscVal: $Value of miscellaneous feature\n",
      "\n",
      "MoSold: Month Sold (MM)\n",
      "\n",
      "YrSold: Year Sold (YYYY)\n",
      "\n",
      "SaleType: Type of sale\n",
      "\t\t\n",
      "       WD \tWarranty Deed - Conventional\n",
      "       CWD\tWarranty Deed - Cash\n",
      "       VWD\tWarranty Deed - VA Loan\n",
      "       New\tHome just constructed and sold\n",
      "       COD\tCourt Officer Deed/Estate\n",
      "       Con\tContract 15% Down payment regular terms\n",
      "       ConLw\tContract Low Down payment and low interest\n",
      "       ConLI\tContract Low Interest\n",
      "       ConLD\tContract Low Down\n",
      "       Oth\tOther\n",
      "\t\t\n",
      "SaleCondition: Condition of sale\n",
      "\n",
      "       Normal\tNormal Sale\n",
      "       Abnorml\tAbnormal Sale -  trade, foreclosure, short sale\n",
      "       AdjLand\tAdjoining Land Purchase\n",
      "       Alloca\tAllocation - two linked properties with separate deeds, typically condo with a garage unit\t\n",
      "       Family\tSale between family members\n",
      "       Partial\tHome was not completed when last assessed (associated with New Homes)\n",
      "\n"
     ]
    }
   ],
   "source": [
    "with open (r\"E:\\machine learning excercise\\pista\\جلسه 20\\Ames_Housing_Feature_Description.txt\",'r') as f:\n",
    "    print(f.read())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "b5b27a1d",
   "metadata": {},
   "outputs": [],
   "source": [
    "#BSMT Numeric columns >> fillna 0\n",
    "\n",
    "df = df.copy()\n",
    "bmst_num_col = ['BsmtFin SF 1','BsmtFin SF 2','Bsmt Unf SF','Total Bsmt SF','Bsmt Full Bath','Bsmt Half Bath']\n",
    "\n",
    "df[bmst_num_col] = df[bmst_num_col].fillna(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "33bdf07f",
   "metadata": {},
   "outputs": [],
   "source": [
    "#BSMT string columns\n",
    "\n",
    "bmst_str_col = ['Bsmt Qual','Bsmt Cond','Bsmt Exposure','BsmtFin Type 1','BsmtFin Type 2']\n",
    "\n",
    "df[bmst_str_col] = df[bmst_str_col].fillna('None')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "86018fa0",
   "metadata": {},
   "outputs": [],
   "source": [
    "percent_nan = percent_missing(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "af011393",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.0, 1.0)"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1600x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8,4),dpi=200)\n",
    "sns.barplot(x=percent_nan.index,y=percent_nan)\n",
    "plt.xticks(rotation=90)\n",
    "plt.ylim(0,1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "1a8d428d",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['Mas Vnr Type'] = df['Mas Vnr Type'].fillna('None')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "cb8a6d80",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['Mas Vnr Area'] = df['Mas Vnr Area'].fillna(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "fc23655c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.0, 1.0)"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1600x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "percent_nan = percent_missing(df)\n",
    "plt.figure(figsize=(8,4),dpi=200)\n",
    "sns.barplot(x=percent_nan.index,y=percent_nan)\n",
    "plt.xticks(rotation=90)\n",
    "plt.ylim(0,1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "e945b28a",
   "metadata": {},
   "outputs": [],
   "source": [
    "gar_str_cols = ['Garage Type','Garage Finish','Garage Qual','Garage Cond']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "80c2e805",
   "metadata": {},
   "outputs": [],
   "source": [
    "df[gar_str_cols] = df[gar_str_cols].fillna('None')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "e7298969",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.0, 1.0)"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1600x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "percent_nan = percent_missing(df)\n",
    "plt.figure(figsize=(8,4),dpi=200)\n",
    "sns.barplot(x=percent_nan.index,y=percent_nan)\n",
    "plt.xticks(rotation=90)\n",
    "plt.ylim(0,1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "45581a6e",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['Garage Yr Blt'] = df['Garage Yr Blt'].fillna(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "8276d3b2",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df.drop(['Fence','Alley','Misc Feature','Pool QC'],axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "79e8642a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.0, 1.0)"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1600x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "percent_nan = percent_missing(df)\n",
    "plt.figure(figsize=(8,4),dpi=200)\n",
    "sns.barplot(x=percent_nan.index,y=percent_nan)\n",
    "plt.xticks(rotation=90)\n",
    "plt.ylim(0,1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "65d22892",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['Fireplace Qu'] = df['Fireplace Qu'].fillna('None')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "cb203495",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       141.0\n",
       "1        80.0\n",
       "2        81.0\n",
       "3        93.0\n",
       "4        74.0\n",
       "        ...  \n",
       "2922     37.0\n",
       "2923      NaN\n",
       "2924     62.0\n",
       "2925     77.0\n",
       "2926     74.0\n",
       "Name: Lot Frontage, Length: 2925, dtype: float64"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#lotfrontage: linear feet of street connected to property\n",
    "\n",
    "df['Lot Frontage']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "b1722fe7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Neighborhood\n",
       "Blmngtn    46.900000\n",
       "Blueste    27.300000\n",
       "BrDale     21.500000\n",
       "BrkSide    55.789474\n",
       "ClearCr    88.150000\n",
       "CollgCr    71.336364\n",
       "Crawfor    69.951807\n",
       "Edwards    64.794286\n",
       "Gilbert    74.207207\n",
       "Greens     41.000000\n",
       "GrnHill          NaN\n",
       "IDOTRR     62.383721\n",
       "Landmrk          NaN\n",
       "MeadowV    25.606061\n",
       "Mitchel    75.144444\n",
       "NAmes      75.210667\n",
       "NPkVill    28.142857\n",
       "NWAmes     81.517647\n",
       "NoRidge    91.629630\n",
       "NridgHt    84.184049\n",
       "OldTown    61.777293\n",
       "SWISU      59.068182\n",
       "Sawyer     74.551020\n",
       "SawyerW    70.669811\n",
       "Somerst    64.549383\n",
       "StoneBr    62.173913\n",
       "Timber     81.303571\n",
       "Veenker    72.000000\n",
       "Name: Lot Frontage, dtype: float64"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby('Neighborhood')['Lot Frontage'].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "a365bf8c",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['Lot Frontage'] = df.groupby('Neighborhood')['Lot Frontage'].transform(lambda value: value.fillna(value.mean()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "f61674af",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "MS SubClass       0\n",
       "MS Zoning         0\n",
       "Lot Frontage      3\n",
       "Lot Area          0\n",
       "Street            0\n",
       "                 ..\n",
       "Mo Sold           0\n",
       "Yr Sold           0\n",
       "Sale Type         0\n",
       "Sale Condition    0\n",
       "SalePrice         0\n",
       "Length: 76, dtype: int64"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "c4c237b7",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['Lot Frontage'] = df['Lot Frontage'].fillna(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "440daa16",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "MS SubClass       0\n",
       "MS Zoning         0\n",
       "Lot Frontage      0\n",
       "Lot Area          0\n",
       "Street            0\n",
       "                 ..\n",
       "Mo Sold           0\n",
       "Yr Sold           0\n",
       "Sale Type         0\n",
       "Sale Condition    0\n",
       "SalePrice         0\n",
       "Length: 76, dtype: int64"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "b944f995",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.to_csv('Ames_without_null.csv', index=False)"
   ]
  }
 ],
 "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": "3.13.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}