House-price prediction with Linear Regression.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "6d6c7f0e",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.linear_model import LinearRegression\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "6a882724",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\n",
       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ADDRESS</th>\n",
       "      <th>SUBURB</th>\n",
       "      <th>PRICE</th>\n",
       "      <th>BEDROOMS</th>\n",
       "      <th>BATHROOMS</th>\n",
       "      <th>GARAGE</th>\n",
       "      <th>LAND_AREA</th>\n",
       "      <th>FLOOR_AREA</th>\n",
       "      <th>BUILD_YEAR</th>\n",
       "      <th>CBD_DIST</th>\n",
       "      <th>NEAREST_STN</th>\n",
       "      <th>NEAREST_STN_DIST</th>\n",
       "      <th>DATE_SOLD</th>\n",
       "      <th>POSTCODE</th>\n",
       "      <th>LATITUDE</th>\n",
       "      <th>LONGITUDE</th>\n",
       "      <th>NEAREST_SCH</th>\n",
       "      <th>NEAREST_SCH_DIST</th>\n",
       "      <th>NEAREST_SCH_RANK</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1 Acorn Place</td>\n",
       "      <td>South Lake</td>\n",
       "      <td>565000</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>2.0</td>\n",
       "      <td>600</td>\n",
       "      <td>160</td>\n",
       "      <td>2003.0</td>\n",
       "      <td>18300</td>\n",
       "      <td>Cockburn Central Station</td>\n",
       "      <td>1800</td>\n",
       "      <td>09-2018\\r</td>\n",
       "      <td>6164</td>\n",
       "      <td>-32.115900</td>\n",
       "      <td>115.842450</td>\n",
       "      <td>LAKELAND SENIOR HIGH SCHOOL</td>\n",
       "      <td>0.828339</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1 Addis Way</td>\n",
       "      <td>Wandi</td>\n",
       "      <td>365000</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>2.0</td>\n",
       "      <td>351</td>\n",
       "      <td>139</td>\n",
       "      <td>2013.0</td>\n",
       "      <td>26900</td>\n",
       "      <td>Kwinana Station</td>\n",
       "      <td>4900</td>\n",
       "      <td>02-2019\\r</td>\n",
       "      <td>6167</td>\n",
       "      <td>-32.193470</td>\n",
       "      <td>115.859554</td>\n",
       "      <td>ATWELL COLLEGE</td>\n",
       "      <td>5.524324</td>\n",
       "      <td>129.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1 Ainsley Court</td>\n",
       "      <td>Camillo</td>\n",
       "      <td>287000</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>719</td>\n",
       "      <td>86</td>\n",
       "      <td>1979.0</td>\n",
       "      <td>22600</td>\n",
       "      <td>Challis Station</td>\n",
       "      <td>1900</td>\n",
       "      <td>06-2015\\r</td>\n",
       "      <td>6111</td>\n",
       "      <td>-32.120578</td>\n",
       "      <td>115.993579</td>\n",
       "      <td>KELMSCOTT SENIOR HIGH SCHOOL</td>\n",
       "      <td>1.649178</td>\n",
       "      <td>113.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1 Albert Street</td>\n",
       "      <td>Bellevue</td>\n",
       "      <td>255000</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2.0</td>\n",
       "      <td>651</td>\n",
       "      <td>59</td>\n",
       "      <td>1953.0</td>\n",
       "      <td>17900</td>\n",
       "      <td>Midland Station</td>\n",
       "      <td>3600</td>\n",
       "      <td>07-2018\\r</td>\n",
       "      <td>6056</td>\n",
       "      <td>-31.900547</td>\n",
       "      <td>116.038009</td>\n",
       "      <td>SWAN VIEW SENIOR HIGH SCHOOL</td>\n",
       "      <td>1.571401</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1 Aman Place</td>\n",
       "      <td>Lockridge</td>\n",
       "      <td>325000</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>2.0</td>\n",
       "      <td>466</td>\n",
       "      <td>131</td>\n",
       "      <td>1998.0</td>\n",
       "      <td>11200</td>\n",
       "      <td>Bassendean Station</td>\n",
       "      <td>2000</td>\n",
       "      <td>11-2016\\r</td>\n",
       "      <td>6054</td>\n",
       "      <td>-31.885790</td>\n",
       "      <td>115.947780</td>\n",
       "      <td>KIARA COLLEGE</td>\n",
       "      <td>1.514922</td>\n",
       "      <td>NaN</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33651</th>\n",
       "      <td>9C Gold Street</td>\n",
       "      <td>South Fremantle</td>\n",
       "      <td>1040000</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>2.0</td>\n",
       "      <td>292</td>\n",
       "      <td>245</td>\n",
       "      <td>2013.0</td>\n",
       "      <td>16100</td>\n",
       "      <td>Fremantle Station</td>\n",
       "      <td>1500</td>\n",
       "      <td>03-2016\\r</td>\n",
       "      <td>6162</td>\n",
       "      <td>-32.064580</td>\n",
       "      <td>115.751820</td>\n",
       "      <td>CHRISTIAN BROTHERS' COLLEGE</td>\n",
       "      <td>1.430350</td>\n",
       "      <td>49.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33652</th>\n",
       "      <td>9C Pycombe Way</td>\n",
       "      <td>Westminster</td>\n",
       "      <td>410000</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>2.0</td>\n",
       "      <td>228</td>\n",
       "      <td>114</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9600</td>\n",
       "      <td>Stirling Station</td>\n",
       "      <td>4600</td>\n",
       "      <td>02-2017\\r</td>\n",
       "      <td>6061</td>\n",
       "      <td>-31.867055</td>\n",
       "      <td>115.841403</td>\n",
       "      <td>JOHN SEPTIMUS ROE ANGLICAN COMMUNITY SCHOOL</td>\n",
       "      <td>1.679644</td>\n",
       "      <td>35.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33653</th>\n",
       "      <td>9D Pycombe Way</td>\n",
       "      <td>Westminster</td>\n",
       "      <td>427000</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>2.0</td>\n",
       "      <td>261</td>\n",
       "      <td>112</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9600</td>\n",
       "      <td>Stirling Station</td>\n",
       "      <td>4600</td>\n",
       "      <td>02-2017\\r</td>\n",
       "      <td>6061</td>\n",
       "      <td>-31.866890</td>\n",
       "      <td>115.841418</td>\n",
       "      <td>JOHN SEPTIMUS ROE ANGLICAN COMMUNITY SCHOOL</td>\n",
       "      <td>1.669159</td>\n",
       "      <td>35.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33654</th>\n",
       "      <td>9D Shalford Way</td>\n",
       "      <td>Girrawheen</td>\n",
       "      <td>295000</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>2.0</td>\n",
       "      <td>457</td>\n",
       "      <td>85</td>\n",
       "      <td>1974.0</td>\n",
       "      <td>12600</td>\n",
       "      <td>Warwick Station</td>\n",
       "      <td>4400</td>\n",
       "      <td>10-2016\\r</td>\n",
       "      <td>6064</td>\n",
       "      <td>-31.839680</td>\n",
       "      <td>115.842410</td>\n",
       "      <td>GIRRAWHEEN SENIOR HIGH SCHOOL</td>\n",
       "      <td>0.358494</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33655</th>\n",
       "      <td>9E Margaret Street</td>\n",
       "      <td>Midland</td>\n",
       "      <td>295000</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>2.0</td>\n",
       "      <td>296</td>\n",
       "      <td>95</td>\n",
       "      <td>NaN</td>\n",
       "      <td>16700</td>\n",
       "      <td>Midland Station</td>\n",
       "      <td>1700</td>\n",
       "      <td>05-2016\\r</td>\n",
       "      <td>6056</td>\n",
       "      <td>-31.882163</td>\n",
       "      <td>116.014755</td>\n",
       "      <td>LA SALLE COLLEGE</td>\n",
       "      <td>1.055564</td>\n",
       "      <td>53.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>33656 rows × 19 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                  ADDRESS           SUBURB    PRICE  BEDROOMS  BATHROOMS  \\\n",
       "0           1 Acorn Place       South Lake   565000         4          2   \n",
       "1             1 Addis Way            Wandi   365000         3          2   \n",
       "2         1 Ainsley Court          Camillo   287000         3          1   \n",
       "3         1 Albert Street         Bellevue   255000         2          1   \n",
       "4            1 Aman Place        Lockridge   325000         4          1   \n",
       "...                   ...              ...      ...       ...        ...   \n",
       "33651      9C Gold Street  South Fremantle  1040000         4          3   \n",
       "33652      9C Pycombe Way      Westminster   410000         3          2   \n",
       "33653      9D Pycombe Way      Westminster   427000         3          2   \n",
       "33654     9D Shalford Way       Girrawheen   295000         3          1   \n",
       "33655  9E Margaret Street          Midland   295000         3          1   \n",
       "\n",
       "       GARAGE  LAND_AREA  FLOOR_AREA  BUILD_YEAR  CBD_DIST  \\\n",
       "0         2.0        600         160      2003.0     18300   \n",
       "1         2.0        351         139      2013.0     26900   \n",
       "2         1.0        719          86      1979.0     22600   \n",
       "3         2.0        651          59      1953.0     17900   \n",
       "4         2.0        466         131      1998.0     11200   \n",
       "...       ...        ...         ...         ...       ...   \n",
       "33651     2.0        292         245      2013.0     16100   \n",
       "33652     2.0        228         114         NaN      9600   \n",
       "33653     2.0        261         112         NaN      9600   \n",
       "33654     2.0        457          85      1974.0     12600   \n",
       "33655     2.0        296          95         NaN     16700   \n",
       "\n",
       "                    NEAREST_STN  NEAREST_STN_DIST  DATE_SOLD  POSTCODE  \\\n",
       "0      Cockburn Central Station              1800  09-2018\\r      6164   \n",
       "1               Kwinana Station              4900  02-2019\\r      6167   \n",
       "2               Challis Station              1900  06-2015\\r      6111   \n",
       "3               Midland Station              3600  07-2018\\r      6056   \n",
       "4            Bassendean Station              2000  11-2016\\r      6054   \n",
       "...                         ...               ...        ...       ...   \n",
       "33651         Fremantle Station              1500  03-2016\\r      6162   \n",
       "33652          Stirling Station              4600  02-2017\\r      6061   \n",
       "33653          Stirling Station              4600  02-2017\\r      6061   \n",
       "33654           Warwick Station              4400  10-2016\\r      6064   \n",
       "33655           Midland Station              1700  05-2016\\r      6056   \n",
       "\n",
       "        LATITUDE   LONGITUDE                                  NEAREST_SCH  \\\n",
       "0     -32.115900  115.842450                  LAKELAND SENIOR HIGH SCHOOL   \n",
       "1     -32.193470  115.859554                               ATWELL COLLEGE   \n",
       "2     -32.120578  115.993579                 KELMSCOTT SENIOR HIGH SCHOOL   \n",
       "3     -31.900547  116.038009                 SWAN VIEW SENIOR HIGH SCHOOL   \n",
       "4     -31.885790  115.947780                                KIARA COLLEGE   \n",
       "...          ...         ...                                          ...   \n",
       "33651 -32.064580  115.751820                  CHRISTIAN BROTHERS' COLLEGE   \n",
       "33652 -31.867055  115.841403  JOHN SEPTIMUS ROE ANGLICAN COMMUNITY SCHOOL   \n",
       "33653 -31.866890  115.841418  JOHN SEPTIMUS ROE ANGLICAN COMMUNITY SCHOOL   \n",
       "33654 -31.839680  115.842410                GIRRAWHEEN SENIOR HIGH SCHOOL   \n",
       "33655 -31.882163  116.014755                             LA SALLE COLLEGE   \n",
       "\n",
       "       NEAREST_SCH_DIST  NEAREST_SCH_RANK  \n",
       "0              0.828339               NaN  \n",
       "1              5.524324             129.0  \n",
       "2              1.649178             113.0  \n",
       "3              1.571401               NaN  \n",
       "4              1.514922               NaN  \n",
       "...                 ...               ...  \n",
       "33651          1.430350              49.0  \n",
       "33652          1.679644              35.0  \n",
       "33653          1.669159              35.0  \n",
       "33654          0.358494               NaN  \n",
       "33655          1.055564              53.0  \n",
       "\n",
       "[33656 rows x 19 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "house_data = pd.read_csv(\"housing.csv\")\n",
    "house_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "b90da047",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "PRICE               1.000000\n",
       "BEDROOMS            0.252637\n",
       "BATHROOMS           0.377133\n",
       "GARAGE              0.134343\n",
       "LAND_AREA           0.056855\n",
       "FLOOR_AREA          0.548497\n",
       "BUILD_YEAR         -0.157218\n",
       "CBD_DIST           -0.354327\n",
       "NEAREST_STN_DIST   -0.095089\n",
       "POSTCODE           -0.171553\n",
       "LATITUDE            0.053041\n",
       "LONGITUDE          -0.183734\n",
       "NEAREST_SCH_DIST   -0.021941\n",
       "NEAREST_SCH_RANK   -0.461991\n",
       "Name: PRICE, dtype: float64"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# To see how the data correlates with price\n",
    "\n",
    "house_data.corr()['PRICE']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "56276456",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x7fa80ac1b430>"
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     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
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\n",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Scattering the plot with Seaborn\n",
    "\n",
    "sns.lmplot(x = 'FLOOR_AREA', y = 'PRICE', data = house_data, fit_reg = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "2fe2959e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index(['ADDRESS', 'SUBURB', 'PRICE', 'BEDROOMS', 'BATHROOMS', 'GARAGE',\n",
      "       'LAND_AREA', 'FLOOR_AREA', 'BUILD_YEAR', 'CBD_DIST', 'NEAREST_STN',\n",
      "       'NEAREST_STN_DIST', 'DATE_SOLD', 'POSTCODE', 'LATITUDE', 'LONGITUDE',\n",
      "       'NEAREST_SCH', 'NEAREST_SCH_DIST', 'NEAREST_SCH_RANK'],\n",
      "      dtype='object')\n"
     ]
    }
   ],
   "source": [
    "# Getting all the columns in the CSV file\n",
    "\n",
    "print(house_data.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "c711b1af",
   "metadata": {},
   "outputs": [],
   "source": [
    "x = house_data[['BEDROOMS','BATHROOMS', 'GARAGE', 'FLOOR_AREA', 'BUILD_YEAR']]\n",
    "y = house_data[['PRICE']]/1000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "02ffc311",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "       BEDROOMS  BATHROOMS  GARAGE  FLOOR_AREA  BUILD_YEAR\n",
      "0             4          2     2.0         160      2003.0\n",
      "1             3          2     2.0         139      2013.0\n",
      "2             3          1     1.0          86      1979.0\n",
      "3             2          1     2.0          59      1953.0\n",
      "4             4          1     2.0         131      1998.0\n",
      "...         ...        ...     ...         ...         ...\n",
      "33648         3          2     2.0         108      2011.0\n",
      "33649         4          2     2.0         132      2014.0\n",
      "33650         3          2     1.0         127      1997.0\n",
      "33651         4          3     2.0         245      2013.0\n",
      "33654         3          1     2.0          85      1974.0\n",
      "\n",
      "[28256 rows x 5 columns]\n"
     ]
    }
   ],
   "source": [
    "# Dropping missing values\n",
    "\n",
    "x = x.dropna()\n",
    "print(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "7ece9218",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "       PRICE\n",
      "0      565.0\n",
      "1      365.0\n",
      "2      287.0\n",
      "3      255.0\n",
      "4      325.0\n",
      "...      ...\n",
      "28251  631.0\n",
      "28252  340.0\n",
      "28253  585.0\n",
      "28254  188.0\n",
      "28255  695.0\n",
      "\n",
      "[28256 rows x 1 columns]\n"
     ]
    }
   ],
   "source": [
    "# Dropping the missing values in x makes the training data unequal\n",
    "# Both the rows of x and y must be same\n",
    "# First calculate the rows of dataframe x\n",
    "\n",
    "x_rows = x.shape[0]\n",
    "# print(x_rows)\n",
    "\n",
    "# Selecting the data from dataframe y, number of rows equal to that of x\n",
    "\n",
    "y = y.iloc[0:x_rows]\n",
    "print(y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "1a28442f",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Splitting the training and testing data\n",
    "\n",
    "x_train, x_test, y_train, y_test = train_test_split(x, y, train_size = 0.7)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "8051abfb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LinearRegression()"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Training the model\n",
    "\n",
    "reg = LinearRegression()\n",
    "reg.fit(x_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9d943bf3",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cb9740cc",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "812319a9",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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