Quikr Analysis.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib as mpl\n",
    "mpl.style.use('ggplot')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "car=pd.read_csv('quikr_car.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "        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>company</th>\n",
       "      <th>year</th>\n",
       "      <th>Price</th>\n",
       "      <th>kms_driven</th>\n",
       "      <th>fuel_type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Hyundai Santro Xing XO eRLX Euro III</td>\n",
       "      <td>Hyundai</td>\n",
       "      <td>2007</td>\n",
       "      <td>80,000</td>\n",
       "      <td>45,000 kms</td>\n",
       "      <td>Petrol</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Mahindra Jeep CL550 MDI</td>\n",
       "      <td>Mahindra</td>\n",
       "      <td>2006</td>\n",
       "      <td>4,25,000</td>\n",
       "      <td>40 kms</td>\n",
       "      <td>Diesel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Maruti Suzuki Alto 800 Vxi</td>\n",
       "      <td>Maruti</td>\n",
       "      <td>2018</td>\n",
       "      <td>Ask For Price</td>\n",
       "      <td>22,000 kms</td>\n",
       "      <td>Petrol</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Hyundai Grand i10 Magna 1.2 Kappa VTVT</td>\n",
       "      <td>Hyundai</td>\n",
       "      <td>2014</td>\n",
       "      <td>3,25,000</td>\n",
       "      <td>28,000 kms</td>\n",
       "      <td>Petrol</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Ford EcoSport Titanium 1.5L TDCi</td>\n",
       "      <td>Ford</td>\n",
       "      <td>2014</td>\n",
       "      <td>5,75,000</td>\n",
       "      <td>36,000 kms</td>\n",
       "      <td>Diesel</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                     name   company  year          Price  \\\n",
       "0    Hyundai Santro Xing XO eRLX Euro III   Hyundai  2007         80,000   \n",
       "1                 Mahindra Jeep CL550 MDI  Mahindra  2006       4,25,000   \n",
       "2              Maruti Suzuki Alto 800 Vxi    Maruti  2018  Ask For Price   \n",
       "3  Hyundai Grand i10 Magna 1.2 Kappa VTVT   Hyundai  2014       3,25,000   \n",
       "4        Ford EcoSport Titanium 1.5L TDCi      Ford  2014       5,75,000   \n",
       "\n",
       "   kms_driven fuel_type  \n",
       "0  45,000 kms    Petrol  \n",
       "1      40 kms    Diesel  \n",
       "2  22,000 kms    Petrol  \n",
       "3  28,000 kms    Petrol  \n",
       "4  36,000 kms    Diesel  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "car.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(892, 6)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "car.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 892 entries, 0 to 891\n",
      "Data columns (total 6 columns):\n",
      " #   Column      Non-Null Count  Dtype \n",
      "---  ------      --------------  ----- \n",
      " 0   name        892 non-null    object\n",
      " 1   company     892 non-null    object\n",
      " 2   year        892 non-null    object\n",
      " 3   Price       892 non-null    object\n",
      " 4   kms_driven  840 non-null    object\n",
      " 5   fuel_type   837 non-null    object\n",
      "dtypes: object(6)\n",
      "memory usage: 41.9+ KB\n"
     ]
    }
   ],
   "source": [
    "car.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Creating backup copy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "backup=car.copy()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Quality\n",
    "\n",
    "- names are pretty inconsistent\n",
    "- names have company names attached to it\n",
    "- some names are spam like 'Maruti Ertiga showroom condition with' and 'Well mentained Tata Sumo'\n",
    "- company: many of the names are not of any company like 'Used', 'URJENT', and so on.\n",
    "- year has many non-year values\n",
    "- year is in object. Change to integer\n",
    "- Price has Ask for Price\n",
    "- Price has commas in its prices and is in object\n",
    "- kms_driven has object values with kms at last.\n",
    "- It has nan values and two rows have 'Petrol' in them\n",
    "- fuel_type has nan values"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Cleaning Data "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### year has many non-year values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "car=car[car['year'].str.isnumeric()]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### year is in object. Change to integer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "car['year']=car['year'].astype(int)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Price has Ask for Price"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "car=car[car['Price']!='Ask For Price']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Price has commas in its prices and is in object"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "car['Price']=car['Price'].str.replace(',','').astype(int)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "####  kms_driven has object values with kms at last."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "car['kms_driven']=car['kms_driven'].str.split().str.get(0).str.replace(',','')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### It has nan values and two rows have 'Petrol' in them"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "car=car[car['kms_driven'].str.isnumeric()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "car['kms_driven']=car['kms_driven'].astype(int)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### fuel_type has nan values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "car=car[~car['fuel_type'].isna()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(816, 6)"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "car.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### name and company had spammed data...but with the previous cleaning, those rows got removed."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Company does not need any cleaning now. Changing car names. Keeping only the first three words"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "car['name']=car['name'].str.split().str.slice(start=0,stop=3).str.join(' ')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Resetting the index of the final cleaned data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "car=car.reset_index(drop=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Cleaned Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "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>company</th>\n",
       "      <th>year</th>\n",
       "      <th>Price</th>\n",
       "      <th>kms_driven</th>\n",
       "      <th>fuel_type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Hyundai Santro Xing</td>\n",
       "      <td>Hyundai</td>\n",
       "      <td>2007</td>\n",
       "      <td>80000</td>\n",
       "      <td>45000</td>\n",
       "      <td>Petrol</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Mahindra Jeep CL550</td>\n",
       "      <td>Mahindra</td>\n",
       "      <td>2006</td>\n",
       "      <td>425000</td>\n",
       "      <td>40</td>\n",
       "      <td>Diesel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Hyundai Grand i10</td>\n",
       "      <td>Hyundai</td>\n",
       "      <td>2014</td>\n",
       "      <td>325000</td>\n",
       "      <td>28000</td>\n",
       "      <td>Petrol</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Ford EcoSport Titanium</td>\n",
       "      <td>Ford</td>\n",
       "      <td>2014</td>\n",
       "      <td>575000</td>\n",
       "      <td>36000</td>\n",
       "      <td>Diesel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Ford Figo</td>\n",
       "      <td>Ford</td>\n",
       "      <td>2012</td>\n",
       "      <td>175000</td>\n",
       "      <td>41000</td>\n",
       "      <td>Diesel</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>811</th>\n",
       "      <td>Maruti Suzuki Ritz</td>\n",
       "      <td>Maruti</td>\n",
       "      <td>2011</td>\n",
       "      <td>270000</td>\n",
       "      <td>50000</td>\n",
       "      <td>Petrol</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>812</th>\n",
       "      <td>Tata Indica V2</td>\n",
       "      <td>Tata</td>\n",
       "      <td>2009</td>\n",
       "      <td>110000</td>\n",
       "      <td>30000</td>\n",
       "      <td>Diesel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>813</th>\n",
       "      <td>Toyota Corolla Altis</td>\n",
       "      <td>Toyota</td>\n",
       "      <td>2009</td>\n",
       "      <td>300000</td>\n",
       "      <td>132000</td>\n",
       "      <td>Petrol</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>814</th>\n",
       "      <td>Tata Zest XM</td>\n",
       "      <td>Tata</td>\n",
       "      <td>2018</td>\n",
       "      <td>260000</td>\n",
       "      <td>27000</td>\n",
       "      <td>Diesel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>815</th>\n",
       "      <td>Mahindra Quanto C8</td>\n",
       "      <td>Mahindra</td>\n",
       "      <td>2013</td>\n",
       "      <td>390000</td>\n",
       "      <td>40000</td>\n",
       "      <td>Diesel</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>816 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                       name   company  year   Price  kms_driven fuel_type\n",
       "0       Hyundai Santro Xing   Hyundai  2007   80000       45000    Petrol\n",
       "1       Mahindra Jeep CL550  Mahindra  2006  425000          40    Diesel\n",
       "2         Hyundai Grand i10   Hyundai  2014  325000       28000    Petrol\n",
       "3    Ford EcoSport Titanium      Ford  2014  575000       36000    Diesel\n",
       "4                 Ford Figo      Ford  2012  175000       41000    Diesel\n",
       "..                      ...       ...   ...     ...         ...       ...\n",
       "811      Maruti Suzuki Ritz    Maruti  2011  270000       50000    Petrol\n",
       "812          Tata Indica V2      Tata  2009  110000       30000    Diesel\n",
       "813    Toyota Corolla Altis    Toyota  2009  300000      132000    Petrol\n",
       "814            Tata Zest XM      Tata  2018  260000       27000    Diesel\n",
       "815      Mahindra Quanto C8  Mahindra  2013  390000       40000    Diesel\n",
       "\n",
       "[816 rows x 6 columns]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "car"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "car.to_csv('Cleaned_Car_data.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 816 entries, 0 to 815\n",
      "Data columns (total 6 columns):\n",
      " #   Column      Non-Null Count  Dtype \n",
      "---  ------      --------------  ----- \n",
      " 0   name        816 non-null    object\n",
      " 1   company     816 non-null    object\n",
      " 2   year        816 non-null    int32 \n",
      " 3   Price       816 non-null    int32 \n",
      " 4   kms_driven  816 non-null    int32 \n",
      " 5   fuel_type   816 non-null    object\n",
      "dtypes: int32(3), object(3)\n",
      "memory usage: 28.8+ KB\n"
     ]
    }
   ],
   "source": [
    "car.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "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>company</th>\n",
       "      <th>year</th>\n",
       "      <th>Price</th>\n",
       "      <th>kms_driven</th>\n",
       "      <th>fuel_type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>816</td>\n",
       "      <td>816</td>\n",
       "      <td>816.000000</td>\n",
       "      <td>8.160000e+02</td>\n",
       "      <td>816.000000</td>\n",
       "      <td>816</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>unique</th>\n",
       "      <td>254</td>\n",
       "      <td>25</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>top</th>\n",
       "      <td>Maruti Suzuki Swift</td>\n",
       "      <td>Maruti</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Petrol</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>freq</th>\n",
       "      <td>51</td>\n",
       "      <td>221</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>428</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2012.444853</td>\n",
       "      <td>4.117176e+05</td>\n",
       "      <td>46275.531863</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.002992</td>\n",
       "      <td>4.751844e+05</td>\n",
       "      <td>34297.428044</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1995.000000</td>\n",
       "      <td>3.000000e+04</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2010.000000</td>\n",
       "      <td>1.750000e+05</td>\n",
       "      <td>27000.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2013.000000</td>\n",
       "      <td>2.999990e+05</td>\n",
       "      <td>41000.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015.000000</td>\n",
       "      <td>4.912500e+05</td>\n",
       "      <td>56818.500000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019.000000</td>\n",
       "      <td>8.500003e+06</td>\n",
       "      <td>400000.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       name company         year         Price     kms_driven  \\\n",
       "count                   816     816   816.000000  8.160000e+02     816.000000   \n",
       "unique                  254      25          NaN           NaN            NaN   \n",
       "top     Maruti Suzuki Swift  Maruti          NaN           NaN            NaN   \n",
       "freq                     51     221          NaN           NaN            NaN   \n",
       "mean                    NaN     NaN  2012.444853  4.117176e+05   46275.531863   \n",
       "std                     NaN     NaN     4.002992  4.751844e+05   34297.428044   \n",
       "min                     NaN     NaN  1995.000000  3.000000e+04       0.000000   \n",
       "25%                     NaN     NaN  2010.000000  1.750000e+05   27000.000000   \n",
       "50%                     NaN     NaN  2013.000000  2.999990e+05   41000.000000   \n",
       "75%                     NaN     NaN  2015.000000  4.912500e+05   56818.500000   \n",
       "max                     NaN     NaN  2019.000000  8.500003e+06  400000.000000   \n",
       "\n",
       "       fuel_type  \n",
       "count        816  \n",
       "unique         3  \n",
       "top       Petrol  \n",
       "freq         428  \n",
       "mean         NaN  \n",
       "std          NaN  \n",
       "min          NaN  \n",
       "25%          NaN  \n",
       "50%          NaN  \n",
       "75%          NaN  \n",
       "max          NaN  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "car.describe(include='all')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "car=car[car['Price']<6000000]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Checking relationship of Company with Price"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Hyundai', 'Mahindra', 'Ford', 'Maruti', 'Skoda', 'Audi', 'Toyota',\n",
       "       'Renault', 'Honda', 'Datsun', 'Mitsubishi', 'Tata', 'Volkswagen',\n",
       "       'Chevrolet', 'Mini', 'BMW', 'Nissan', 'Hindustan', 'Fiat', 'Force',\n",
       "       'Mercedes', 'Land', 'Jaguar', 'Jeep', 'Volvo'], dtype=object)"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "car['company'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1080x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.subplots(figsize=(15,7))\n",
    "ax=sns.boxplot(x='company',y='Price',data=car)\n",
    "ax.set_xticklabels(ax.get_xticklabels(),rotation=40,ha='right')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Checking relationship of Year with Price"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1440x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.subplots(figsize=(20,10))\n",
    "ax=sns.swarmplot(x='year',y='Price',data=car)\n",
    "ax.set_xticklabels(ax.get_xticklabels(),rotation=40,ha='right')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Checking relationship of kms_driven with Price"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x1d3534604c0>"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 756x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.relplot(x='kms_driven',y='Price',data=car,height=7,aspect=1.5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Checking relationship of Fuel Type with Price"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1d353660d60>"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1008x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.subplots(figsize=(14,7))\n",
    "sns.boxplot(x='fuel_type',y='Price',data=car)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Relationship of Price with FuelType, Year and Company mixed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x1d353675f40>"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1090.12x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax=sns.relplot(x='company',y='Price',data=car,hue='fuel_type',size='year',height=7,aspect=2)\n",
    "ax.set_xticklabels(rotation=40,ha='right')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Extracting Training Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "X=car[['name','company','year','kms_driven','fuel_type']]\n",
    "y=car['Price']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "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>company</th>\n",
       "      <th>year</th>\n",
       "      <th>kms_driven</th>\n",
       "      <th>fuel_type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Hyundai Santro Xing</td>\n",
       "      <td>Hyundai</td>\n",
       "      <td>2007</td>\n",
       "      <td>45000</td>\n",
       "      <td>Petrol</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Mahindra Jeep CL550</td>\n",
       "      <td>Mahindra</td>\n",
       "      <td>2006</td>\n",
       "      <td>40</td>\n",
       "      <td>Diesel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Hyundai Grand i10</td>\n",
       "      <td>Hyundai</td>\n",
       "      <td>2014</td>\n",
       "      <td>28000</td>\n",
       "      <td>Petrol</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Ford EcoSport Titanium</td>\n",
       "      <td>Ford</td>\n",
       "      <td>2014</td>\n",
       "      <td>36000</td>\n",
       "      <td>Diesel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Ford Figo</td>\n",
       "      <td>Ford</td>\n",
       "      <td>2012</td>\n",
       "      <td>41000</td>\n",
       "      <td>Diesel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>811</th>\n",
       "      <td>Maruti Suzuki Ritz</td>\n",
       "      <td>Maruti</td>\n",
       "      <td>2011</td>\n",
       "      <td>50000</td>\n",
       "      <td>Petrol</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>812</th>\n",
       "      <td>Tata Indica V2</td>\n",
       "      <td>Tata</td>\n",
       "      <td>2009</td>\n",
       "      <td>30000</td>\n",
       "      <td>Diesel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>813</th>\n",
       "      <td>Toyota Corolla Altis</td>\n",
       "      <td>Toyota</td>\n",
       "      <td>2009</td>\n",
       "      <td>132000</td>\n",
       "      <td>Petrol</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>814</th>\n",
       "      <td>Tata Zest XM</td>\n",
       "      <td>Tata</td>\n",
       "      <td>2018</td>\n",
       "      <td>27000</td>\n",
       "      <td>Diesel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>815</th>\n",
       "      <td>Mahindra Quanto C8</td>\n",
       "      <td>Mahindra</td>\n",
       "      <td>2013</td>\n",
       "      <td>40000</td>\n",
       "      <td>Diesel</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>815 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                       name   company  year  kms_driven fuel_type\n",
       "0       Hyundai Santro Xing   Hyundai  2007       45000    Petrol\n",
       "1       Mahindra Jeep CL550  Mahindra  2006          40    Diesel\n",
       "2         Hyundai Grand i10   Hyundai  2014       28000    Petrol\n",
       "3    Ford EcoSport Titanium      Ford  2014       36000    Diesel\n",
       "4                 Ford Figo      Ford  2012       41000    Diesel\n",
       "..                      ...       ...   ...         ...       ...\n",
       "811      Maruti Suzuki Ritz    Maruti  2011       50000    Petrol\n",
       "812          Tata Indica V2      Tata  2009       30000    Diesel\n",
       "813    Toyota Corolla Altis    Toyota  2009      132000    Petrol\n",
       "814            Tata Zest XM      Tata  2018       27000    Diesel\n",
       "815      Mahindra Quanto C8  Mahindra  2013       40000    Diesel\n",
       "\n",
       "[815 rows x 5 columns]"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(815,)"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Applying Train Test Split"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "X_train,X_test,y_train,y_test=train_test_split(X,y,test_size=0.2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.linear_model import LinearRegression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.preprocessing import OneHotEncoder\n",
    "from sklearn.compose import make_column_transformer\n",
    "from sklearn.pipeline import make_pipeline\n",
    "from sklearn.metrics import r2_score"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Creating an OneHotEncoder object to contain all the possible categories"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "OneHotEncoder()"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ohe=OneHotEncoder()\n",
    "ohe.fit(X[['name','company','fuel_type']])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Creating a column transformer to transform categorical columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "column_trans=make_column_transformer((OneHotEncoder(categories=ohe.categories_),['name','company','fuel_type']),\n",
    "                                    remainder='passthrough')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Linear Regression Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [],
   "source": [
    "lr=LinearRegression()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Making a pipeline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [],
   "source": [
    "pipe=make_pipeline(column_trans,lr)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Fitting the  model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Pipeline(steps=[('columntransformer',\n",
       "                 ColumnTransformer(remainder='passthrough',\n",
       "                                   transformers=[('onehotencoder',\n",
       "                                                  OneHotEncoder(categories=[array(['Audi A3 Cabriolet', 'Audi A4 1.8', 'Audi A4 2.0', 'Audi A6 2.0',\n",
       "       'Audi A8', 'Audi Q3 2.0', 'Audi Q5 2.0', 'Audi Q7', 'BMW 3 Series',\n",
       "       'BMW 5 Series', 'BMW 7 Series', 'BMW X1', 'BMW X1 sDrive20d',\n",
       "       'BMW X1 xDrive20d', 'Chevrolet Beat', 'Chevrolet Beat...\n",
       "                                                                            array(['Audi', 'BMW', 'Chevrolet', 'Datsun', 'Fiat', 'Force', 'Ford',\n",
       "       'Hindustan', 'Honda', 'Hyundai', 'Jaguar', 'Jeep', 'Land',\n",
       "       'Mahindra', 'Maruti', 'Mercedes', 'Mini', 'Mitsubishi', 'Nissan',\n",
       "       'Renault', 'Skoda', 'Tata', 'Toyota', 'Volkswagen', 'Volvo'],\n",
       "      dtype=object),\n",
       "                                                                            array(['Diesel', 'LPG', 'Petrol'], dtype=object)]),\n",
       "                                                  ['name', 'company',\n",
       "                                                   'fuel_type'])])),\n",
       "                ('linearregression', LinearRegression())])"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pipe.fit(X_train,y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_pred=pipe.predict(X_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Checking R2 Score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.7627456237676113"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r2_score(y_test,y_pred)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Finding the model with a random state of TrainTestSplit where the model was found to give almost 0.92 as r2_score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [],
   "source": [
    "scores=[]\n",
    "for i in range(1000):\n",
    "    X_train,X_test,y_train,y_test=train_test_split(X,y,test_size=0.1,random_state=i)\n",
    "    lr=LinearRegression()\n",
    "    pipe=make_pipeline(column_trans,lr)\n",
    "    pipe.fit(X_train,y_train)\n",
    "    y_pred=pipe.predict(X_test)\n",
    "    scores.append(r2_score(y_test,y_pred))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "655"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.argmax(scores)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.920088412025344"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "scores[np.argmax(scores)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([400707.28215338])"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pipe.predict(pd.DataFrame(columns=X_test.columns,data=np.array(['Maruti Suzuki Swift','Maruti',2019,100,'Petrol']).reshape(1,5)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### The best model is found at a certain random state "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.920088412025344"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_train,X_test,y_train,y_test=train_test_split(X,y,test_size=0.1,random_state=np.argmax(scores))\n",
    "lr=LinearRegression()\n",
    "pipe=make_pipeline(column_trans,lr)\n",
    "pipe.fit(X_train,y_train)\n",
    "y_pred=pipe.predict(X_test)\n",
    "r2_score(y_test,y_pred)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pickle"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [],
   "source": [
    "pickle.dump(pipe,open('LinearRegressionModel.pkl','wb'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([416109.14071676])"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pipe.predict(pd.DataFrame(columns=['name','company','year','kms_driven','fuel_type'],data=np.array(['Maruti Suzuki Swift','Maruti',2019,100,'Petrol']).reshape(1,5)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Audi A3 Cabriolet', 'Audi A4 1.8', 'Audi A4 2.0', 'Audi A6 2.0',\n",
       "       'Audi A8', 'Audi Q3 2.0', 'Audi Q5 2.0', 'Audi Q7', 'BMW 3 Series',\n",
       "       'BMW 5 Series', 'BMW 7 Series', 'BMW X1', 'BMW X1 sDrive20d',\n",
       "       'BMW X1 xDrive20d', 'Chevrolet Beat', 'Chevrolet Beat Diesel',\n",
       "       'Chevrolet Beat LS', 'Chevrolet Beat LT', 'Chevrolet Beat PS',\n",
       "       'Chevrolet Cruze LTZ', 'Chevrolet Enjoy', 'Chevrolet Enjoy 1.4',\n",
       "       'Chevrolet Sail 1.2', 'Chevrolet Sail UVA', 'Chevrolet Spark',\n",
       "       'Chevrolet Spark 1.0', 'Chevrolet Spark LS', 'Chevrolet Spark LT',\n",
       "       'Chevrolet Tavera LS', 'Chevrolet Tavera Neo', 'Datsun GO T',\n",
       "       'Datsun Go Plus', 'Datsun Redi GO', 'Fiat Linea Emotion',\n",
       "       'Fiat Petra ELX', 'Fiat Punto Emotion', 'Force Motors Force',\n",
       "       'Force Motors One', 'Ford EcoSport', 'Ford EcoSport Ambiente',\n",
       "       'Ford EcoSport Titanium', 'Ford EcoSport Trend',\n",
       "       'Ford Endeavor 4x4', 'Ford Fiesta', 'Ford Fiesta SXi', 'Ford Figo',\n",
       "       'Ford Figo Diesel', 'Ford Figo Duratorq', 'Ford Figo Petrol',\n",
       "       'Ford Fusion 1.4', 'Ford Ikon 1.3', 'Ford Ikon 1.6',\n",
       "       'Hindustan Motors Ambassador', 'Honda Accord', 'Honda Amaze',\n",
       "       'Honda Amaze 1.2', 'Honda Amaze 1.5', 'Honda Brio', 'Honda Brio V',\n",
       "       'Honda Brio VX', 'Honda City', 'Honda City 1.5', 'Honda City SV',\n",
       "       'Honda City VX', 'Honda City ZX', 'Honda Jazz S', 'Honda Jazz VX',\n",
       "       'Honda Mobilio', 'Honda Mobilio S', 'Honda WR V', 'Hyundai Accent',\n",
       "       'Hyundai Accent Executive', 'Hyundai Accent GLE',\n",
       "       'Hyundai Accent GLX', 'Hyundai Creta', 'Hyundai Creta 1.6',\n",
       "       'Hyundai Elantra 1.8', 'Hyundai Elantra SX', 'Hyundai Elite i20',\n",
       "       'Hyundai Eon', 'Hyundai Eon D', 'Hyundai Eon Era',\n",
       "       'Hyundai Eon Magna', 'Hyundai Eon Sportz', 'Hyundai Fluidic Verna',\n",
       "       'Hyundai Getz', 'Hyundai Getz GLE', 'Hyundai Getz Prime',\n",
       "       'Hyundai Grand i10', 'Hyundai Santro', 'Hyundai Santro AE',\n",
       "       'Hyundai Santro Xing', 'Hyundai Sonata Transform', 'Hyundai Verna',\n",
       "       'Hyundai Verna 1.4', 'Hyundai Verna 1.6', 'Hyundai Verna Fluidic',\n",
       "       'Hyundai Verna Transform', 'Hyundai Verna VGT',\n",
       "       'Hyundai Xcent Base', 'Hyundai Xcent SX', 'Hyundai i10',\n",
       "       'Hyundai i10 Era', 'Hyundai i10 Magna', 'Hyundai i10 Sportz',\n",
       "       'Hyundai i20', 'Hyundai i20 Active', 'Hyundai i20 Asta',\n",
       "       'Hyundai i20 Magna', 'Hyundai i20 Select', 'Hyundai i20 Sportz',\n",
       "       'Jaguar XE XE', 'Jaguar XF 2.2', 'Jeep Wrangler Unlimited',\n",
       "       'Land Rover Freelander', 'Mahindra Bolero DI',\n",
       "       'Mahindra Bolero Power', 'Mahindra Bolero SLE',\n",
       "       'Mahindra Jeep CL550', 'Mahindra Jeep MM', 'Mahindra KUV100',\n",
       "       'Mahindra KUV100 K8', 'Mahindra Logan', 'Mahindra Logan Diesel',\n",
       "       'Mahindra Quanto C4', 'Mahindra Quanto C8', 'Mahindra Scorpio',\n",
       "       'Mahindra Scorpio 2.6', 'Mahindra Scorpio LX',\n",
       "       'Mahindra Scorpio S10', 'Mahindra Scorpio S4',\n",
       "       'Mahindra Scorpio SLE', 'Mahindra Scorpio SLX',\n",
       "       'Mahindra Scorpio VLX', 'Mahindra Scorpio Vlx',\n",
       "       'Mahindra Scorpio W', 'Mahindra TUV300 T4', 'Mahindra TUV300 T8',\n",
       "       'Mahindra Thar CRDe', 'Mahindra XUV500', 'Mahindra XUV500 W10',\n",
       "       'Mahindra XUV500 W6', 'Mahindra XUV500 W8', 'Mahindra Xylo D2',\n",
       "       'Mahindra Xylo E4', 'Mahindra Xylo E8', 'Maruti Suzuki 800',\n",
       "       'Maruti Suzuki A', 'Maruti Suzuki Alto', 'Maruti Suzuki Baleno',\n",
       "       'Maruti Suzuki Celerio', 'Maruti Suzuki Ciaz',\n",
       "       'Maruti Suzuki Dzire', 'Maruti Suzuki Eeco',\n",
       "       'Maruti Suzuki Ertiga', 'Maruti Suzuki Esteem',\n",
       "       'Maruti Suzuki Estilo', 'Maruti Suzuki Maruti',\n",
       "       'Maruti Suzuki Omni', 'Maruti Suzuki Ritz', 'Maruti Suzuki S',\n",
       "       'Maruti Suzuki SX4', 'Maruti Suzuki Stingray',\n",
       "       'Maruti Suzuki Swift', 'Maruti Suzuki Versa',\n",
       "       'Maruti Suzuki Vitara', 'Maruti Suzuki Wagon', 'Maruti Suzuki Zen',\n",
       "       'Mercedes Benz A', 'Mercedes Benz B', 'Mercedes Benz C',\n",
       "       'Mercedes Benz GLA', 'Mini Cooper S', 'Mitsubishi Lancer 1.8',\n",
       "       'Mitsubishi Pajero Sport', 'Nissan Micra XL', 'Nissan Micra XV',\n",
       "       'Nissan Sunny', 'Nissan Sunny XL', 'Nissan Terrano XL',\n",
       "       'Nissan X Trail', 'Renault Duster', 'Renault Duster 110',\n",
       "       'Renault Duster 110PS', 'Renault Duster 85', 'Renault Duster 85PS',\n",
       "       'Renault Duster RxL', 'Renault Kwid', 'Renault Kwid 1.0',\n",
       "       'Renault Kwid RXT', 'Renault Lodgy 85', 'Renault Scala RxL',\n",
       "       'Skoda Fabia', 'Skoda Fabia 1.2L', 'Skoda Fabia Classic',\n",
       "       'Skoda Laura', 'Skoda Octavia Classic', 'Skoda Rapid Elegance',\n",
       "       'Skoda Superb 1.8', 'Skoda Yeti Ambition', 'Tata Aria Pleasure',\n",
       "       'Tata Bolt XM', 'Tata Indica', 'Tata Indica V2', 'Tata Indica eV2',\n",
       "       'Tata Indigo CS', 'Tata Indigo LS', 'Tata Indigo LX',\n",
       "       'Tata Indigo Marina', 'Tata Indigo eCS', 'Tata Manza',\n",
       "       'Tata Manza Aqua', 'Tata Manza Aura', 'Tata Manza ELAN',\n",
       "       'Tata Nano', 'Tata Nano Cx', 'Tata Nano GenX', 'Tata Nano LX',\n",
       "       'Tata Nano Lx', 'Tata Sumo Gold', 'Tata Sumo Grande',\n",
       "       'Tata Sumo Victa', 'Tata Tiago Revotorq', 'Tata Tiago Revotron',\n",
       "       'Tata Tigor Revotron', 'Tata Venture EX', 'Tata Vista Quadrajet',\n",
       "       'Tata Zest Quadrajet', 'Tata Zest XE', 'Tata Zest XM',\n",
       "       'Toyota Corolla', 'Toyota Corolla Altis', 'Toyota Corolla H2',\n",
       "       'Toyota Etios', 'Toyota Etios G', 'Toyota Etios GD',\n",
       "       'Toyota Etios Liva', 'Toyota Fortuner', 'Toyota Fortuner 3.0',\n",
       "       'Toyota Innova 2.0', 'Toyota Innova 2.5', 'Toyota Qualis',\n",
       "       'Volkswagen Jetta Comfortline', 'Volkswagen Jetta Highline',\n",
       "       'Volkswagen Passat Diesel', 'Volkswagen Polo',\n",
       "       'Volkswagen Polo Comfortline', 'Volkswagen Polo Highline',\n",
       "       'Volkswagen Polo Highline1.2L', 'Volkswagen Polo Trendline',\n",
       "       'Volkswagen Vento Comfortline', 'Volkswagen Vento Highline',\n",
       "       'Volkswagen Vento Konekt', 'Volvo S80 Summum'], dtype=object)"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pipe.steps[0][1].transformers[0][1].categories[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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