{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Practical-13\n",
    "## Name: Sahal Pathan\n",
    "## Enrollment: 190110107057\n",
    "## Title: Car Price Prediction\n",
    "## Aim: To Predict price of Car using machine learning\n",
    "## Tools: Jupyter notebook-python"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 🚙 , 🚗 , 🏎️ ? 💵\n",
    "### The price of a car depends on a lot of factors like the goodwill of the brand of the car, features of the car, horsepower and the mileage it gives and many more.\n",
    "### Some of the factors that contribute a lot to the price of a car are:\n",
    "- Brand\n",
    "- Model\n",
    "- Mileage\n",
    "- BHP\n",
    "- Safety Features\n",
    "- year of manufacturing\n",
    "- kms driven\n",
    "- many more. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Importing libraries"
   ]
  },
  {
   "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"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "car=pd.read_csv('car.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "        vertical-align: middle;\n",
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       "\n",
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       "        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>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": 3,
     "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": 4,
   "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": [
    "#### Backup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "backup=car.copy()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Cleaning Data "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### year has many non-year values and its type to int"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "car=car[car['year'].str.isnumeric()]\n",
    "car['year']=car['year'].astype(int)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Price has Ask for Price -remove"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "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, to int"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "car['Price']=car['Price'].str.replace(',','').astype(int)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "####  kms_driven has object values with kms"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "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": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "car=car[car['kms_driven'].str.isnumeric()]\n",
    "car['kms_driven']=car['kms_driven'].astype(int)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### fuel_type has nan values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(816, 6)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "car=car[~car['fuel_type'].isna()]\n",
    "car.shape"
   ]
  },
  {
   "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": 13,
   "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": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "car=car.reset_index(drop=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Cleaned Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</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</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": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "car"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "car.to_csv('newCar.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "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    int64 \n",
      " 3   Price       816 non-null    int64 \n",
      " 4   kms_driven  816 non-null    int64 \n",
      " 5   fuel_type   816 non-null    object\n",
      "dtypes: int64(3), object(3)\n",
      "memory usage: 38.4+ KB\n"
     ]
    }
   ],
   "source": [
    "car.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
       "    .dataframe thead th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>year</th>\n",
       "      <th>Price</th>\n",
       "      <th>kms_driven</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>816.000000</td>\n",
       "      <td>8.160000e+02</td>\n",
       "      <td>816.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>2012.444853</td>\n",
       "      <td>4.117176e+05</td>\n",
       "      <td>46275.531863</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>4.002992</td>\n",
       "      <td>4.751844e+05</td>\n",
       "      <td>34297.428044</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1995.000000</td>\n",
       "      <td>3.000000e+04</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>2010.000000</td>\n",
       "      <td>1.750000e+05</td>\n",
       "      <td>27000.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>2013.000000</td>\n",
       "      <td>2.999990e+05</td>\n",
       "      <td>41000.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>2015.000000</td>\n",
       "      <td>4.912500e+05</td>\n",
       "      <td>56818.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>2019.000000</td>\n",
       "      <td>8.500003e+06</td>\n",
       "      <td>400000.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              year         Price     kms_driven\n",
       "count   816.000000  8.160000e+02     816.000000\n",
       "mean   2012.444853  4.117176e+05   46275.531863\n",
       "std       4.002992  4.751844e+05   34297.428044\n",
       "min    1995.000000  3.000000e+04       0.000000\n",
       "25%    2010.000000  1.750000e+05   27000.000000\n",
       "50%    2013.000000  2.999990e+05   41000.000000\n",
       "75%    2015.000000  4.912500e+05   56818.500000\n",
       "max    2019.000000  8.500003e+06  400000.000000"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "car.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "car=car[car['Price']<6000000]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Checking relationship of Company with Price"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "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": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "car['company'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "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": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/sahal/opt/anaconda3/lib/python3.8/site-packages/seaborn/categorical.py:1296: UserWarning: 9.3% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/Users/sahal/opt/anaconda3/lib/python3.8/site-packages/seaborn/categorical.py:1296: UserWarning: 6.8% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/Users/sahal/opt/anaconda3/lib/python3.8/site-packages/seaborn/categorical.py:1296: UserWarning: 10.6% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/Users/sahal/opt/anaconda3/lib/python3.8/site-packages/seaborn/categorical.py:1296: UserWarning: 5.5% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.\n",
      "  warnings.warn(msg, UserWarning)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "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": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x7fa6988c9490>"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 756x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "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": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='fuel_type', ylabel='Price'>"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "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": 26,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x7fa6a8225640>"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1075x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "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": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "X=car[['name','company','year','kms_driven','fuel_type']]\n",
    "y=car['Price']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "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": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(815,)"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Applying Train Test Split"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "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=0.3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.tree import DecisionTreeRegressor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "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": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "OneHotEncoder()"
      ]
     },
     "execution_count": 33,
     "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": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "column_trans=make_column_transformer((OneHotEncoder(categories=ohe.categories_),['name','company','fuel_type']),\n",
    "                                    remainder='passthrough')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### DecisioncTree Regressor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "model = DecisionTreeRegressor()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Making a pipeline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "pipe=make_pipeline(column_trans,model)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Fitting the  model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "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",
       "                ('decisiontreeregressor', DecisionTreeRegressor())])"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pipe.fit(X_train,y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_pred=pipe.predict(X_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Checking R2 Score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.6698704636398934"
      ]
     },
     "execution_count": 39,
     "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": 40,
   "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",
    "    model=DecisionTreeRegressor()\n",
    "    pipe=make_pipeline(column_trans,model)\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": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "507"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.argmax(scores)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9313276052910379"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "scores[np.argmax(scores)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([610000.])"
      ]
     },
     "execution_count": 43,
     "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": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9269826706815704"
      ]
     },
     "execution_count": 44,
     "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",
    "model=DecisionTreeRegressor()\n",
    "pipe=make_pipeline(column_trans,model)\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": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "predictionsx = pipe.predict(X_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Lets check score/efficiency model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.0"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.metrics import mean_absolute_error,accuracy_score\n",
    "pipe.score(X_test, predictionsx)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "import joblib\n",
    "with open('CarPricePredictor','wb') as f:\n",
    "    joblib.dump(pipe,f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([610000.])"
      ]
     },
     "execution_count": 48,
     "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": 49,
   "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": 49,
     "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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