linear regression on car details.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "5766ced5",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "6c2f0a7a",
   "metadata": {},
   "outputs": [],
   "source": [
    "cardekho=pd.read_csv('CAR DETAILS FROM CAR DEKHO.csv')"
   ]
  },
  {
   "cell_type": "raw",
   "id": "acb2e78a",
   "metadata": {},
   "source": [
    "cardekho.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "2d69c8d9",
   "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>name</th>\n",
       "      <th>year</th>\n",
       "      <th>selling_price</th>\n",
       "      <th>km_driven</th>\n",
       "      <th>fuel</th>\n",
       "      <th>seller_type</th>\n",
       "      <th>transmission</th>\n",
       "      <th>owner</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Maruti 800 AC</td>\n",
       "      <td>2007</td>\n",
       "      <td>60000</td>\n",
       "      <td>70000</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>Individual</td>\n",
       "      <td>Manual</td>\n",
       "      <td>First Owner</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Maruti Wagon R LXI Minor</td>\n",
       "      <td>2007</td>\n",
       "      <td>135000</td>\n",
       "      <td>50000</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>Individual</td>\n",
       "      <td>Manual</td>\n",
       "      <td>First Owner</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Hyundai Verna 1.6 SX</td>\n",
       "      <td>2012</td>\n",
       "      <td>600000</td>\n",
       "      <td>100000</td>\n",
       "      <td>Diesel</td>\n",
       "      <td>Individual</td>\n",
       "      <td>Manual</td>\n",
       "      <td>First Owner</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Datsun RediGO T Option</td>\n",
       "      <td>2017</td>\n",
       "      <td>250000</td>\n",
       "      <td>46000</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>Individual</td>\n",
       "      <td>Manual</td>\n",
       "      <td>First Owner</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Honda Amaze VX i-DTEC</td>\n",
       "      <td>2014</td>\n",
       "      <td>450000</td>\n",
       "      <td>141000</td>\n",
       "      <td>Diesel</td>\n",
       "      <td>Individual</td>\n",
       "      <td>Manual</td>\n",
       "      <td>Second Owner</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       name  year  selling_price  km_driven    fuel  \\\n",
       "0             Maruti 800 AC  2007          60000      70000  Petrol   \n",
       "1  Maruti Wagon R LXI Minor  2007         135000      50000  Petrol   \n",
       "2      Hyundai Verna 1.6 SX  2012         600000     100000  Diesel   \n",
       "3    Datsun RediGO T Option  2017         250000      46000  Petrol   \n",
       "4     Honda Amaze VX i-DTEC  2014         450000     141000  Diesel   \n",
       "\n",
       "  seller_type transmission         owner  \n",
       "0  Individual       Manual   First Owner  \n",
       "1  Individual       Manual   First Owner  \n",
       "2  Individual       Manual   First Owner  \n",
       "3  Individual       Manual   First Owner  \n",
       "4  Individual       Manual  Second Owner  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cardekho.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "7f7b195e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       False\n",
       "1       False\n",
       "2        True\n",
       "3       False\n",
       "4       False\n",
       "        ...  \n",
       "4335    False\n",
       "4336    False\n",
       "4337    False\n",
       "4338     True\n",
       "4339    False\n",
       "Name: selling_price, Length: 4340, dtype: bool"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "d399f715",
   "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>name</th>\n",
       "      <th>year</th>\n",
       "      <th>selling_price</th>\n",
       "      <th>km_driven</th>\n",
       "      <th>fuel</th>\n",
       "      <th>seller_type</th>\n",
       "      <th>transmission</th>\n",
       "      <th>owner</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Hyundai Verna 1.6 SX</td>\n",
       "      <td>2012</td>\n",
       "      <td>600000</td>\n",
       "      <td>100000</td>\n",
       "      <td>Diesel</td>\n",
       "      <td>Individual</td>\n",
       "      <td>Manual</td>\n",
       "      <td>First Owner</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Hyundai Xcent 1.2 Kappa S</td>\n",
       "      <td>2016</td>\n",
       "      <td>550000</td>\n",
       "      <td>25000</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>Individual</td>\n",
       "      <td>Manual</td>\n",
       "      <td>First Owner</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Hyundai Creta 1.6 VTVT S</td>\n",
       "      <td>2015</td>\n",
       "      <td>850000</td>\n",
       "      <td>25000</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>Individual</td>\n",
       "      <td>Manual</td>\n",
       "      <td>First Owner</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Toyota Corolla Altis 1.8 VL CVT</td>\n",
       "      <td>2018</td>\n",
       "      <td>1650000</td>\n",
       "      <td>25000</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>Dealer</td>\n",
       "      <td>Automatic</td>\n",
       "      <td>First Owner</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Hyundai Verna 1.6 SX</td>\n",
       "      <td>2012</td>\n",
       "      <td>600000</td>\n",
       "      <td>100000</td>\n",
       "      <td>Diesel</td>\n",
       "      <td>Individual</td>\n",
       "      <td>Manual</td>\n",
       "      <td>First Owner</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4313</th>\n",
       "      <td>Ford Endeavour 2.2 Titanium AT 4X2</td>\n",
       "      <td>2019</td>\n",
       "      <td>2800000</td>\n",
       "      <td>10000</td>\n",
       "      <td>Diesel</td>\n",
       "      <td>Individual</td>\n",
       "      <td>Automatic</td>\n",
       "      <td>First Owner</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4331</th>\n",
       "      <td>Ford EcoSport 1.5 TDCi Titanium BSIV</td>\n",
       "      <td>2015</td>\n",
       "      <td>530000</td>\n",
       "      <td>175000</td>\n",
       "      <td>Diesel</td>\n",
       "      <td>Individual</td>\n",
       "      <td>Manual</td>\n",
       "      <td>Third Owner</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4332</th>\n",
       "      <td>Mahindra Scorpio S2 7 Seater</td>\n",
       "      <td>2015</td>\n",
       "      <td>750000</td>\n",
       "      <td>120000</td>\n",
       "      <td>Diesel</td>\n",
       "      <td>Individual</td>\n",
       "      <td>Manual</td>\n",
       "      <td>First Owner</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4334</th>\n",
       "      <td>Toyota Innova 2.5 VX (Diesel) 8 Seater BS IV</td>\n",
       "      <td>2012</td>\n",
       "      <td>600000</td>\n",
       "      <td>170000</td>\n",
       "      <td>Diesel</td>\n",
       "      <td>Individual</td>\n",
       "      <td>Manual</td>\n",
       "      <td>First Owner</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4338</th>\n",
       "      <td>Hyundai Creta 1.6 CRDi SX Option</td>\n",
       "      <td>2016</td>\n",
       "      <td>865000</td>\n",
       "      <td>90000</td>\n",
       "      <td>Diesel</td>\n",
       "      <td>Individual</td>\n",
       "      <td>Manual</td>\n",
       "      <td>First Owner</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1461 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                              name  year  selling_price  \\\n",
       "2                             Hyundai Verna 1.6 SX  2012         600000   \n",
       "6                        Hyundai Xcent 1.2 Kappa S  2016         550000   \n",
       "8                         Hyundai Creta 1.6 VTVT S  2015         850000   \n",
       "12                 Toyota Corolla Altis 1.8 VL CVT  2018        1650000   \n",
       "15                            Hyundai Verna 1.6 SX  2012         600000   \n",
       "...                                            ...   ...            ...   \n",
       "4313            Ford Endeavour 2.2 Titanium AT 4X2  2019        2800000   \n",
       "4331          Ford EcoSport 1.5 TDCi Titanium BSIV  2015         530000   \n",
       "4332                  Mahindra Scorpio S2 7 Seater  2015         750000   \n",
       "4334  Toyota Innova 2.5 VX (Diesel) 8 Seater BS IV  2012         600000   \n",
       "4338              Hyundai Creta 1.6 CRDi SX Option  2016         865000   \n",
       "\n",
       "      km_driven    fuel seller_type transmission        owner  \n",
       "2        100000  Diesel  Individual       Manual  First Owner  \n",
       "6         25000  Petrol  Individual       Manual  First Owner  \n",
       "8         25000  Petrol  Individual       Manual  First Owner  \n",
       "12        25000  Petrol      Dealer    Automatic  First Owner  \n",
       "15       100000  Diesel  Individual       Manual  First Owner  \n",
       "...         ...     ...         ...          ...          ...  \n",
       "4313      10000  Diesel  Individual    Automatic  First Owner  \n",
       "4331     175000  Diesel  Individual       Manual  Third Owner  \n",
       "4332     120000  Diesel  Individual       Manual  First Owner  \n",
       "4334     170000  Diesel  Individual       Manual  First Owner  \n",
       "4338      90000  Diesel  Individual       Manual  First Owner  \n",
       "\n",
       "[1461 rows x 8 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cardekho[cardekho['selling_price']>500000]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "6a76e35f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0        True\n",
       "1        True\n",
       "2        True\n",
       "3       False\n",
       "4        True\n",
       "        ...  \n",
       "4335     True\n",
       "4336     True\n",
       "4337     True\n",
       "4338    False\n",
       "4339    False\n",
       "Name: year, Length: 4340, dtype: bool"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cardekho['year']<2015"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "ae7927e4",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>year</th>\n",
       "      <th>selling_price</th>\n",
       "      <th>km_driven</th>\n",
       "      <th>fuel</th>\n",
       "      <th>seller_type</th>\n",
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       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Maruti 800 AC</td>\n",
       "      <td>2007</td>\n",
       "      <td>60000</td>\n",
       "      <td>70000</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>Individual</td>\n",
       "      <td>Manual</td>\n",
       "      <td>First Owner</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Maruti Wagon R LXI Minor</td>\n",
       "      <td>2007</td>\n",
       "      <td>135000</td>\n",
       "      <td>50000</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>Individual</td>\n",
       "      <td>Manual</td>\n",
       "      <td>First Owner</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Hyundai Verna 1.6 SX</td>\n",
       "      <td>2012</td>\n",
       "      <td>600000</td>\n",
       "      <td>100000</td>\n",
       "      <td>Diesel</td>\n",
       "      <td>Individual</td>\n",
       "      <td>Manual</td>\n",
       "      <td>First Owner</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Datsun RediGO T Option</td>\n",
       "      <td>2017</td>\n",
       "      <td>250000</td>\n",
       "      <td>46000</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>Individual</td>\n",
       "      <td>Manual</td>\n",
       "      <td>First Owner</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Honda Amaze VX i-DTEC</td>\n",
       "      <td>2014</td>\n",
       "      <td>450000</td>\n",
       "      <td>141000</td>\n",
       "      <td>Diesel</td>\n",
       "      <td>Individual</td>\n",
       "      <td>Manual</td>\n",
       "      <td>Second Owner</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
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       "    <tr>\n",
       "      <th>4335</th>\n",
       "      <td>Hyundai i20 Magna 1.4 CRDi (Diesel)</td>\n",
       "      <td>2014</td>\n",
       "      <td>409999</td>\n",
       "      <td>80000</td>\n",
       "      <td>Diesel</td>\n",
       "      <td>Individual</td>\n",
       "      <td>Manual</td>\n",
       "      <td>Second Owner</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4336</th>\n",
       "      <td>Hyundai i20 Magna 1.4 CRDi</td>\n",
       "      <td>2014</td>\n",
       "      <td>409999</td>\n",
       "      <td>80000</td>\n",
       "      <td>Diesel</td>\n",
       "      <td>Individual</td>\n",
       "      <td>Manual</td>\n",
       "      <td>Second Owner</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4337</th>\n",
       "      <td>Maruti 800 AC BSIII</td>\n",
       "      <td>2009</td>\n",
       "      <td>110000</td>\n",
       "      <td>83000</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>Individual</td>\n",
       "      <td>Manual</td>\n",
       "      <td>Second Owner</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4338</th>\n",
       "      <td>Hyundai Creta 1.6 CRDi SX Option</td>\n",
       "      <td>2016</td>\n",
       "      <td>865000</td>\n",
       "      <td>90000</td>\n",
       "      <td>Diesel</td>\n",
       "      <td>Individual</td>\n",
       "      <td>Manual</td>\n",
       "      <td>First Owner</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4339</th>\n",
       "      <td>Renault KWID RXT</td>\n",
       "      <td>2016</td>\n",
       "      <td>225000</td>\n",
       "      <td>40000</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>Individual</td>\n",
       "      <td>Manual</td>\n",
       "      <td>First Owner</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4340 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                     name  year  selling_price  km_driven  \\\n",
       "0                           Maruti 800 AC  2007          60000      70000   \n",
       "1                Maruti Wagon R LXI Minor  2007         135000      50000   \n",
       "2                    Hyundai Verna 1.6 SX  2012         600000     100000   \n",
       "3                  Datsun RediGO T Option  2017         250000      46000   \n",
       "4                   Honda Amaze VX i-DTEC  2014         450000     141000   \n",
       "...                                   ...   ...            ...        ...   \n",
       "4335  Hyundai i20 Magna 1.4 CRDi (Diesel)  2014         409999      80000   \n",
       "4336           Hyundai i20 Magna 1.4 CRDi  2014         409999      80000   \n",
       "4337                  Maruti 800 AC BSIII  2009         110000      83000   \n",
       "4338     Hyundai Creta 1.6 CRDi SX Option  2016         865000      90000   \n",
       "4339                     Renault KWID RXT  2016         225000      40000   \n",
       "\n",
       "        fuel seller_type transmission         owner  \n",
       "0     Petrol  Individual       Manual   First Owner  \n",
       "1     Petrol  Individual       Manual   First Owner  \n",
       "2     Diesel  Individual       Manual   First Owner  \n",
       "3     Petrol  Individual       Manual   First Owner  \n",
       "4     Diesel  Individual       Manual  Second Owner  \n",
       "...      ...         ...          ...           ...  \n",
       "4335  Diesel  Individual       Manual  Second Owner  \n",
       "4336  Diesel  Individual       Manual  Second Owner  \n",
       "4337  Petrol  Individual       Manual  Second Owner  \n",
       "4338  Diesel  Individual       Manual   First Owner  \n",
       "4339  Petrol  Individual       Manual   First Owner  \n",
       "\n",
       "[4340 rows x 8 columns]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cardekho[cardekho['year']>1500]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "3dbf7dc1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       False\n",
       "1       False\n",
       "2       False\n",
       "3       False\n",
       "4       False\n",
       "        ...  \n",
       "4335    False\n",
       "4336    False\n",
       "4337    False\n",
       "4338    False\n",
       "4339    False\n",
       "Name: km_driven, Length: 4340, dtype: bool"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cardekho['km_driven']<100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "21d6d83f",
   "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>name</th>\n",
       "      <th>year</th>\n",
       "      <th>selling_price</th>\n",
       "      <th>km_driven</th>\n",
       "      <th>fuel</th>\n",
       "      <th>seller_type</th>\n",
       "      <th>transmission</th>\n",
       "      <th>owner</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1312</th>\n",
       "      <td>Mahindra Quanto C6</td>\n",
       "      <td>2014</td>\n",
       "      <td>250000</td>\n",
       "      <td>1</td>\n",
       "      <td>Diesel</td>\n",
       "      <td>Individual</td>\n",
       "      <td>Manual</td>\n",
       "      <td>Second Owner</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    name  year  selling_price  km_driven    fuel seller_type  \\\n",
       "1312  Mahindra Quanto C6  2014         250000          1  Diesel  Individual   \n",
       "\n",
       "     transmission         owner  \n",
       "1312       Manual  Second Owner  "
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cardekho[cardekho['km_driven']<100]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "c3010bcd",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Matplotlib is building the font cache; this may take a moment.\n"
     ]
    }
   ],
   "source": [
    "from matplotlib import pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "871326b8",
   "metadata": {},
   "outputs": [],
   "source": [
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a72f1068",
   "metadata": {},
   "outputs": [],
   "source": [
    "sns.scatterplot(x='selling_price',y='km_driven',data=cardekho)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "4d7ead33",
   "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>name</th>\n",
       "      <th>year</th>\n",
       "      <th>selling_price</th>\n",
       "      <th>km_driven</th>\n",
       "      <th>fuel</th>\n",
       "      <th>seller_type</th>\n",
       "      <th>transmission</th>\n",
       "      <th>owner</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Maruti 800 AC</td>\n",
       "      <td>2007</td>\n",
       "      <td>60000</td>\n",
       "      <td>70000</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>Individual</td>\n",
       "      <td>Manual</td>\n",
       "      <td>First Owner</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Maruti Wagon R LXI Minor</td>\n",
       "      <td>2007</td>\n",
       "      <td>135000</td>\n",
       "      <td>50000</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>Individual</td>\n",
       "      <td>Manual</td>\n",
       "      <td>First Owner</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Hyundai Verna 1.6 SX</td>\n",
       "      <td>2012</td>\n",
       "      <td>600000</td>\n",
       "      <td>100000</td>\n",
       "      <td>Diesel</td>\n",
       "      <td>Individual</td>\n",
       "      <td>Manual</td>\n",
       "      <td>First Owner</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Datsun RediGO T Option</td>\n",
       "      <td>2017</td>\n",
       "      <td>250000</td>\n",
       "      <td>46000</td>\n",
       "      <td>Petrol</td>\n",
       "      <td>Individual</td>\n",
       "      <td>Manual</td>\n",
       "      <td>First Owner</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Honda Amaze VX i-DTEC</td>\n",
       "      <td>2014</td>\n",
       "      <td>450000</td>\n",
       "      <td>141000</td>\n",
       "      <td>Diesel</td>\n",
       "      <td>Individual</td>\n",
       "      <td>Manual</td>\n",
       "      <td>Second Owner</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       name  year  selling_price  km_driven    fuel  \\\n",
       "0             Maruti 800 AC  2007          60000      70000  Petrol   \n",
       "1  Maruti Wagon R LXI Minor  2007         135000      50000  Petrol   \n",
       "2      Hyundai Verna 1.6 SX  2012         600000     100000  Diesel   \n",
       "3    Datsun RediGO T Option  2017         250000      46000  Petrol   \n",
       "4     Honda Amaze VX i-DTEC  2014         450000     141000  Diesel   \n",
       "\n",
       "  seller_type transmission         owner  \n",
       "0  Individual       Manual   First Owner  \n",
       "1  Individual       Manual   First Owner  \n",
       "2  Individual       Manual   First Owner  \n",
       "3  Individual       Manual   First Owner  \n",
       "4  Individual       Manual  Second Owner  "
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cardekho.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "69e4df7d",
   "metadata": {},
   "outputs": [],
   "source": [
    "y=cardekho[['selling_price']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "677396f5",
   "metadata": {},
   "outputs": [],
   "source": [
    "x=cardekho[['km_driven']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "12720c2a",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "18754151",
   "metadata": {},
   "outputs": [],
   "source": [
    "x_train,x_test,y_train,y_test=train_test_split(x,y,test_size=0.3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "c4fde9b2",
   "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>km_driven</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>194</th>\n",
       "      <td>90000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3209</th>\n",
       "      <td>40000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3018</th>\n",
       "      <td>157000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2643</th>\n",
       "      <td>90000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1283</th>\n",
       "      <td>64700</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      km_driven\n",
       "194       90000\n",
       "3209      40000\n",
       "3018     157000\n",
       "2643      90000\n",
       "1283      64700"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x_train.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "66d869cc",
   "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>km_driven</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3009</th>\n",
       "      <td>100000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2026</th>\n",
       "      <td>38000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3213</th>\n",
       "      <td>104000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3836</th>\n",
       "      <td>40000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2217</th>\n",
       "      <td>10500</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      km_driven\n",
       "3009     100000\n",
       "2026      38000\n",
       "3213     104000\n",
       "3836      40000\n",
       "2217      10500"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x_test.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "94c3ca45",
   "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>selling_price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>194</th>\n",
       "      <td>170000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3209</th>\n",
       "      <td>425000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3018</th>\n",
       "      <td>509999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2643</th>\n",
       "      <td>240000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1283</th>\n",
       "      <td>78000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      selling_price\n",
       "194          170000\n",
       "3209         425000\n",
       "3018         509999\n",
       "2643         240000\n",
       "1283          78000"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_train.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "3502cc7d",
   "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>selling_price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3009</th>\n",
       "      <td>400000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2026</th>\n",
       "      <td>381000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3213</th>\n",
       "      <td>420000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3836</th>\n",
       "      <td>600000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2217</th>\n",
       "      <td>300000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      selling_price\n",
       "3009         400000\n",
       "2026         381000\n",
       "3213         420000\n",
       "3836         600000\n",
       "2217         300000"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_test.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "56aff55b",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.linear_model import LinearRegression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "74f98acf",
   "metadata": {},
   "outputs": [],
   "source": [
    "lr=LinearRegression()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "c2efaf03",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LinearRegression()"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    " lr.fit(x_train,y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "8aa7fcf0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LinearRegression()"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lr.fit(x_train,y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "44b5cd7f",
   "metadata": {},
   "outputs": [],
   "source": [
    "y_pred=lr.predict(x_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "5b3830bb",
   "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>selling_price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3009</th>\n",
       "      <td>400000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2026</th>\n",
       "      <td>381000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3213</th>\n",
       "      <td>420000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3836</th>\n",
       "      <td>600000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2217</th>\n",
       "      <td>300000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      selling_price\n",
       "3009         400000\n",
       "2026         381000\n",
       "3213         420000\n",
       "3836         600000\n",
       "2217         300000"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_test.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "958dc9aa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[416720.47672019],\n",
       "       [572496.42578321],\n",
       "       [406670.41549032],\n",
       "       [567471.39516827]])"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_pred[0:4]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "19d7ee13",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.metrics import mean_squared_error"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "27d7ca88",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "322375396937.83307"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mean_squared_error(y_test,y_pred)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "2282f8f9",
   "metadata": {},
   "outputs": [],
   "source": [
    "# model-2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "c9f8248d",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.preprocessing import LabelEncoder"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "0eb3aa80",
   "metadata": {},
   "outputs": [],
   "source": [
    "le=LabelEncoder()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "eeceb3a1",
   "metadata": {},
   "outputs": [],
   "source": [
    "cardekho.year=le.fit_transform(cardekho.year)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "43343333",
   "metadata": {},
   "outputs": [],
   "source": [
    "cardekho.fuel=le.fit_transform(cardekho.fuel)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "93159f20",
   "metadata": {},
   "outputs": [],
   "source": [
    "cardekho.seller_type=le.fit_transform(cardekho.seller_type)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "ab84262c",
   "metadata": {},
   "outputs": [],
   "source": [
    "cardekho.transmission=le.fit_transform(cardekho.transmission)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "89ed071c",
   "metadata": {},
   "outputs": [],
   "source": [
    "cardekho.owner=le.fit_transform(cardekho.owner) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "f7987158",
   "metadata": {},
   "outputs": [],
   "source": [
    "cardekho.name=le.fit_transform(cardekho.name)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "e7eb1754",
   "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>name</th>\n",
       "      <th>year</th>\n",
       "      <th>selling_price</th>\n",
       "      <th>km_driven</th>\n",
       "      <th>fuel</th>\n",
       "      <th>seller_type</th>\n",
       "      <th>transmission</th>\n",
       "      <th>owner</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>775</td>\n",
       "      <td>13</td>\n",
       "      <td>60000</td>\n",
       "      <td>70000</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1041</td>\n",
       "      <td>13</td>\n",
       "      <td>135000</td>\n",
       "      <td>50000</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>505</td>\n",
       "      <td>18</td>\n",
       "      <td>600000</td>\n",
       "      <td>100000</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>118</td>\n",
       "      <td>23</td>\n",
       "      <td>250000</td>\n",
       "      <td>46000</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>279</td>\n",
       "      <td>20</td>\n",
       "      <td>450000</td>\n",
       "      <td>141000</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   name  year  selling_price  km_driven  fuel  seller_type  transmission  \\\n",
       "0   775    13          60000      70000     4            1             1   \n",
       "1  1041    13         135000      50000     4            1             1   \n",
       "2   505    18         600000     100000     1            1             1   \n",
       "3   118    23         250000      46000     4            1             1   \n",
       "4   279    20         450000     141000     1            1             1   \n",
       "\n",
       "   owner  \n",
       "0      0  \n",
       "1      0  \n",
       "2      0  \n",
       "3      0  \n",
       "4      2  "
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cardekho.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "26fdd6cf",
   "metadata": {},
   "outputs": [],
   "source": [
    "y=cardekho[['selling_price']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "186f83ad",
   "metadata": {},
   "outputs": [],
   "source": [
    "x=cardekho[['km_driven','year','fuel','seller_type','transmission','owner',]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "eebf1dfc",
   "metadata": {},
   "outputs": [],
   "source": [
    "x_train,x_test,y_train,y_test=train_test_split(x,y,test_size=0.3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "35aea13a",
   "metadata": {},
   "outputs": [],
   "source": [
    "lr2=LinearRegression()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "id": "b648ca37",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LinearRegression()"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lr2.fit(x_train,y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "id": "ff6bf32c",
   "metadata": {},
   "outputs": [],
   "source": [
    "y_pred=lr2.predict(x_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "id": "91120179",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "214971806273.4772"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mean_squared_error(y_test,y_pred)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "44723972",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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