car.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Introduction to Python\n",
    "\n",
    "Kofi Anane Poku\n",
    "\n",
    "Linkedin Profile : linkedin.com/in/kofi-poku-anane"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Table of Contents\n",
    "\n",
    "Github can't accept files that are more than 45MB , so i uploaded it to two storage cloud.\n",
    "You can download it and try your hands on it\n",
    "\n",
    "Download Dataset from \n",
    "1. https://files.fm/u/gra75ytpum\n",
    "2. https://www.mediafire.com/file/gjq6uyymuv0h2z1/car.csv/file\n",
    "3. https://drive.google.com/file/d/1CYA4znPjo8ifsG52pnCeiGE0CEZV60fD/view?usp=drive_link"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import plotly.express as px\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import csv\n",
    "import codecs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "with codecs.open ('./car.csv', 'r', encoding= 'ISO-8859-1') as f:\n",
    "    car_analysis = pd.read_csv(f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>dateCrawled</th>\n",
       "      <th>name</th>\n",
       "      <th>seller</th>\n",
       "      <th>offerType</th>\n",
       "      <th>price</th>\n",
       "      <th>abtest</th>\n",
       "      <th>vehicleType</th>\n",
       "      <th>yearOfRegistration</th>\n",
       "      <th>gearbox</th>\n",
       "      <th>powerPS</th>\n",
       "      <th>model</th>\n",
       "      <th>kilometer</th>\n",
       "      <th>monthOfRegistration</th>\n",
       "      <th>fuelType</th>\n",
       "      <th>brand</th>\n",
       "      <th>notRepairedDamage</th>\n",
       "      <th>dateCreated</th>\n",
       "      <th>postalCode</th>\n",
       "      <th>lastSeen</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>17/03/2016 16:54</td>\n",
       "      <td>GOLF_4_1_4__3TÜRER</td>\n",
       "      <td>private</td>\n",
       "      <td>offer</td>\n",
       "      <td>1500</td>\n",
       "      <td>test</td>\n",
       "      <td>small car</td>\n",
       "      <td>2001</td>\n",
       "      <td>manual</td>\n",
       "      <td>75</td>\n",
       "      <td>golf</td>\n",
       "      <td>150000</td>\n",
       "      <td>6</td>\n",
       "      <td>petrol</td>\n",
       "      <td>volkswagen</td>\n",
       "      <td>no</td>\n",
       "      <td>17/03/2016 0:00</td>\n",
       "      <td>91074</td>\n",
       "      <td>17/03/2016 17:40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>31/03/2016 17:25</td>\n",
       "      <td>Skoda_Fabia_1.4_TDI_PD_Classic</td>\n",
       "      <td>private</td>\n",
       "      <td>offer</td>\n",
       "      <td>3600</td>\n",
       "      <td>test</td>\n",
       "      <td>small car</td>\n",
       "      <td>2008</td>\n",
       "      <td>manual</td>\n",
       "      <td>69</td>\n",
       "      <td>fabia</td>\n",
       "      <td>90000</td>\n",
       "      <td>7</td>\n",
       "      <td>diesel</td>\n",
       "      <td>skoda</td>\n",
       "      <td>no</td>\n",
       "      <td>31/03/2016 0:00</td>\n",
       "      <td>60437</td>\n",
       "      <td>06/04/2016 10:17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>04/04/2016 17:36</td>\n",
       "      <td>BMW_316i___e36_Limousine___Bastlerfahrzeug__Ex...</td>\n",
       "      <td>private</td>\n",
       "      <td>offer</td>\n",
       "      <td>650</td>\n",
       "      <td>test</td>\n",
       "      <td>limousine</td>\n",
       "      <td>1995</td>\n",
       "      <td>manual</td>\n",
       "      <td>102</td>\n",
       "      <td>3er</td>\n",
       "      <td>150000</td>\n",
       "      <td>10</td>\n",
       "      <td>petrol</td>\n",
       "      <td>bmw</td>\n",
       "      <td>yes</td>\n",
       "      <td>04/04/2016 0:00</td>\n",
       "      <td>33775</td>\n",
       "      <td>06/04/2016 19:17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>01/04/2016 20:48</td>\n",
       "      <td>Peugeot_206_CC_110_Platinum</td>\n",
       "      <td>private</td>\n",
       "      <td>offer</td>\n",
       "      <td>2200</td>\n",
       "      <td>test</td>\n",
       "      <td>cabrio</td>\n",
       "      <td>2004</td>\n",
       "      <td>manual</td>\n",
       "      <td>109</td>\n",
       "      <td>2_reihe</td>\n",
       "      <td>150000</td>\n",
       "      <td>8</td>\n",
       "      <td>petrol</td>\n",
       "      <td>peugeot</td>\n",
       "      <td>no</td>\n",
       "      <td>01/04/2016 0:00</td>\n",
       "      <td>67112</td>\n",
       "      <td>05/04/2016 18:18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>21/03/2016 18:54</td>\n",
       "      <td>VW_Derby_Bj_80__Scheunenfund</td>\n",
       "      <td>private</td>\n",
       "      <td>offer</td>\n",
       "      <td>0</td>\n",
       "      <td>test</td>\n",
       "      <td>limousine</td>\n",
       "      <td>1980</td>\n",
       "      <td>manual</td>\n",
       "      <td>50</td>\n",
       "      <td>others</td>\n",
       "      <td>40000</td>\n",
       "      <td>7</td>\n",
       "      <td>petrol</td>\n",
       "      <td>volkswagen</td>\n",
       "      <td>no</td>\n",
       "      <td>21/03/2016 0:00</td>\n",
       "      <td>19348</td>\n",
       "      <td>25/03/2016 16:47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>260960</th>\n",
       "      <td>19/03/2016 19:53</td>\n",
       "      <td>turbo_defekt</td>\n",
       "      <td>private</td>\n",
       "      <td>offer</td>\n",
       "      <td>3200</td>\n",
       "      <td>control</td>\n",
       "      <td>limousine</td>\n",
       "      <td>2004</td>\n",
       "      <td>manual</td>\n",
       "      <td>225</td>\n",
       "      <td>leon</td>\n",
       "      <td>150000</td>\n",
       "      <td>5</td>\n",
       "      <td>petrol</td>\n",
       "      <td>seat</td>\n",
       "      <td>yes</td>\n",
       "      <td>19/03/2016 0:00</td>\n",
       "      <td>96465</td>\n",
       "      <td>19/03/2016 20:44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>260961</th>\n",
       "      <td>27/03/2016 20:36</td>\n",
       "      <td>Opel_Zafira_1.6_Elegance_TÜV_12/16</td>\n",
       "      <td>private</td>\n",
       "      <td>offer</td>\n",
       "      <td>1150</td>\n",
       "      <td>control</td>\n",
       "      <td>bus</td>\n",
       "      <td>2000</td>\n",
       "      <td>manual</td>\n",
       "      <td>0</td>\n",
       "      <td>zafira</td>\n",
       "      <td>150000</td>\n",
       "      <td>3</td>\n",
       "      <td>petrol</td>\n",
       "      <td>opel</td>\n",
       "      <td>no</td>\n",
       "      <td>27/03/2016 0:00</td>\n",
       "      <td>26624</td>\n",
       "      <td>29/03/2016 10:17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>260962</th>\n",
       "      <td>05/03/2016 19:56</td>\n",
       "      <td>Smart_smart_leistungssteigerung_100ps</td>\n",
       "      <td>private</td>\n",
       "      <td>offer</td>\n",
       "      <td>1199</td>\n",
       "      <td>test</td>\n",
       "      <td>cabrio</td>\n",
       "      <td>2000</td>\n",
       "      <td>automatic</td>\n",
       "      <td>101</td>\n",
       "      <td>fortwo</td>\n",
       "      <td>125000</td>\n",
       "      <td>3</td>\n",
       "      <td>petrol</td>\n",
       "      <td>smart</td>\n",
       "      <td>no</td>\n",
       "      <td>05/03/2016 0:00</td>\n",
       "      <td>26135</td>\n",
       "      <td>11/03/2016 18:17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>260963</th>\n",
       "      <td>19/03/2016 18:57</td>\n",
       "      <td>Volkswagen_Multivan_T4_TDI_7DC_UY2</td>\n",
       "      <td>private</td>\n",
       "      <td>offer</td>\n",
       "      <td>9200</td>\n",
       "      <td>test</td>\n",
       "      <td>bus</td>\n",
       "      <td>1996</td>\n",
       "      <td>manual</td>\n",
       "      <td>102</td>\n",
       "      <td>transporter</td>\n",
       "      <td>150000</td>\n",
       "      <td>3</td>\n",
       "      <td>diesel</td>\n",
       "      <td>volkswagen</td>\n",
       "      <td>no</td>\n",
       "      <td>19/03/2016 0:00</td>\n",
       "      <td>87439</td>\n",
       "      <td>07/04/2016 7:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>260964</th>\n",
       "      <td>07/03/2016 19:39</td>\n",
       "      <td>BMW_M135i_vollausgestattet_NP_52.720____Euro</td>\n",
       "      <td>private</td>\n",
       "      <td>offer</td>\n",
       "      <td>28990</td>\n",
       "      <td>control</td>\n",
       "      <td>limousine</td>\n",
       "      <td>2013</td>\n",
       "      <td>manual</td>\n",
       "      <td>320</td>\n",
       "      <td>m_reihe</td>\n",
       "      <td>50000</td>\n",
       "      <td>8</td>\n",
       "      <td>petrol</td>\n",
       "      <td>bmw</td>\n",
       "      <td>no</td>\n",
       "      <td>07/03/2016 0:00</td>\n",
       "      <td>73326</td>\n",
       "      <td>22/03/2016 3:17</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>260965 rows × 19 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             dateCrawled                                               name  \\\n",
       "0       17/03/2016 16:54                                 GOLF_4_1_4__3TÜRER   \n",
       "1       31/03/2016 17:25                     Skoda_Fabia_1.4_TDI_PD_Classic   \n",
       "2       04/04/2016 17:36  BMW_316i___e36_Limousine___Bastlerfahrzeug__Ex...   \n",
       "3       01/04/2016 20:48                        Peugeot_206_CC_110_Platinum   \n",
       "4       21/03/2016 18:54                       VW_Derby_Bj_80__Scheunenfund   \n",
       "...                  ...                                                ...   \n",
       "260960  19/03/2016 19:53                                       turbo_defekt   \n",
       "260961  27/03/2016 20:36                 Opel_Zafira_1.6_Elegance_TÜV_12/16   \n",
       "260962  05/03/2016 19:56              Smart_smart_leistungssteigerung_100ps   \n",
       "260963  19/03/2016 18:57                 Volkswagen_Multivan_T4_TDI_7DC_UY2   \n",
       "260964  07/03/2016 19:39       BMW_M135i_vollausgestattet_NP_52.720____Euro   \n",
       "\n",
       "         seller offerType  price   abtest vehicleType  yearOfRegistration  \\\n",
       "0       private     offer   1500     test   small car                2001   \n",
       "1       private     offer   3600     test   small car                2008   \n",
       "2       private     offer    650     test   limousine                1995   \n",
       "3       private     offer   2200     test      cabrio                2004   \n",
       "4       private     offer      0     test   limousine                1980   \n",
       "...         ...       ...    ...      ...         ...                 ...   \n",
       "260960  private     offer   3200  control   limousine                2004   \n",
       "260961  private     offer   1150  control         bus                2000   \n",
       "260962  private     offer   1199     test      cabrio                2000   \n",
       "260963  private     offer   9200     test         bus                1996   \n",
       "260964  private     offer  28990  control   limousine                2013   \n",
       "\n",
       "          gearbox  powerPS        model  kilometer  monthOfRegistration  \\\n",
       "0          manual       75         golf     150000                    6   \n",
       "1          manual       69        fabia      90000                    7   \n",
       "2          manual      102          3er     150000                   10   \n",
       "3          manual      109      2_reihe     150000                    8   \n",
       "4          manual       50       others      40000                    7   \n",
       "...           ...      ...          ...        ...                  ...   \n",
       "260960     manual      225         leon     150000                    5   \n",
       "260961     manual        0       zafira     150000                    3   \n",
       "260962  automatic      101       fortwo     125000                    3   \n",
       "260963     manual      102  transporter     150000                    3   \n",
       "260964     manual      320      m_reihe      50000                    8   \n",
       "\n",
       "       fuelType       brand notRepairedDamage      dateCreated  postalCode  \\\n",
       "0        petrol  volkswagen                no  17/03/2016 0:00       91074   \n",
       "1        diesel       skoda                no  31/03/2016 0:00       60437   \n",
       "2        petrol         bmw               yes  04/04/2016 0:00       33775   \n",
       "3        petrol     peugeot                no  01/04/2016 0:00       67112   \n",
       "4        petrol  volkswagen                no  21/03/2016 0:00       19348   \n",
       "...         ...         ...               ...              ...         ...   \n",
       "260960   petrol        seat               yes  19/03/2016 0:00       96465   \n",
       "260961   petrol        opel                no  27/03/2016 0:00       26624   \n",
       "260962   petrol       smart                no  05/03/2016 0:00       26135   \n",
       "260963   diesel  volkswagen                no  19/03/2016 0:00       87439   \n",
       "260964   petrol         bmw                no  07/03/2016 0:00       73326   \n",
       "\n",
       "                lastSeen  \n",
       "0       17/03/2016 17:40  \n",
       "1       06/04/2016 10:17  \n",
       "2       06/04/2016 19:17  \n",
       "3       05/04/2016 18:18  \n",
       "4       25/03/2016 16:47  \n",
       "...                  ...  \n",
       "260960  19/03/2016 20:44  \n",
       "260961  29/03/2016 10:17  \n",
       "260962  11/03/2016 18:17  \n",
       "260963   07/04/2016 7:15  \n",
       "260964   22/03/2016 3:17  \n",
       "\n",
       "[260965 rows x 19 columns]"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "car_analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 260965 entries, 0 to 260964\n",
      "Data columns (total 19 columns):\n",
      " #   Column               Non-Null Count   Dtype \n",
      "---  ------               --------------   ----- \n",
      " 0   dateCrawled          260965 non-null  object\n",
      " 1   name                 260965 non-null  object\n",
      " 2   seller               260965 non-null  object\n",
      " 3   offerType            260965 non-null  object\n",
      " 4   price                260965 non-null  int64 \n",
      " 5   abtest               260965 non-null  object\n",
      " 6   vehicleType          260965 non-null  object\n",
      " 7   yearOfRegistration   260965 non-null  int64 \n",
      " 8   gearbox              260965 non-null  object\n",
      " 9   powerPS              260965 non-null  int64 \n",
      " 10  model                260965 non-null  object\n",
      " 11  kilometer            260965 non-null  int64 \n",
      " 12  monthOfRegistration  260965 non-null  int64 \n",
      " 13  fuelType             260965 non-null  object\n",
      " 14  brand                260965 non-null  object\n",
      " 15  notRepairedDamage    260965 non-null  object\n",
      " 16  dateCreated          260965 non-null  object\n",
      " 17  postalCode           260965 non-null  int64 \n",
      " 18  lastSeen             260965 non-null  object\n",
      "dtypes: int64(6), object(13)\n",
      "memory usage: 37.8+ MB\n"
     ]
    }
   ],
   "source": [
    "car_analysis.info()\n",
    "car_analysis.dropna(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dateCrawled            0\n",
       "name                   0\n",
       "seller                 0\n",
       "offerType              0\n",
       "price                  0\n",
       "abtest                 0\n",
       "vehicleType            0\n",
       "yearOfRegistration     0\n",
       "gearbox                0\n",
       "powerPS                0\n",
       "model                  0\n",
       "kilometer              0\n",
       "monthOfRegistration    0\n",
       "fuelType               0\n",
       "brand                  0\n",
       "notRepairedDamage      0\n",
       "dateCreated            0\n",
       "postalCode             0\n",
       "lastSeen               0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "car_analysis.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Checking whether there's duplicates present in csv file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "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>dateCrawled</th>\n",
       "      <th>name</th>\n",
       "      <th>seller</th>\n",
       "      <th>offerType</th>\n",
       "      <th>price</th>\n",
       "      <th>abtest</th>\n",
       "      <th>vehicleType</th>\n",
       "      <th>yearOfRegistration</th>\n",
       "      <th>gearbox</th>\n",
       "      <th>powerPS</th>\n",
       "      <th>model</th>\n",
       "      <th>kilometer</th>\n",
       "      <th>monthOfRegistration</th>\n",
       "      <th>fuelType</th>\n",
       "      <th>brand</th>\n",
       "      <th>notRepairedDamage</th>\n",
       "      <th>dateCreated</th>\n",
       "      <th>postalCode</th>\n",
       "      <th>lastSeen</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>17/03/2016 16:54</td>\n",
       "      <td>GOLF_4_1_4__3TÜRER</td>\n",
       "      <td>private</td>\n",
       "      <td>offer</td>\n",
       "      <td>1500</td>\n",
       "      <td>test</td>\n",
       "      <td>small car</td>\n",
       "      <td>2001</td>\n",
       "      <td>manual</td>\n",
       "      <td>75</td>\n",
       "      <td>golf</td>\n",
       "      <td>150000</td>\n",
       "      <td>6</td>\n",
       "      <td>petrol</td>\n",
       "      <td>volkswagen</td>\n",
       "      <td>no</td>\n",
       "      <td>17/03/2016 0:00</td>\n",
       "      <td>91074</td>\n",
       "      <td>17/03/2016 17:40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>31/03/2016 17:25</td>\n",
       "      <td>Skoda_Fabia_1.4_TDI_PD_Classic</td>\n",
       "      <td>private</td>\n",
       "      <td>offer</td>\n",
       "      <td>3600</td>\n",
       "      <td>test</td>\n",
       "      <td>small car</td>\n",
       "      <td>2008</td>\n",
       "      <td>manual</td>\n",
       "      <td>69</td>\n",
       "      <td>fabia</td>\n",
       "      <td>90000</td>\n",
       "      <td>7</td>\n",
       "      <td>diesel</td>\n",
       "      <td>skoda</td>\n",
       "      <td>no</td>\n",
       "      <td>31/03/2016 0:00</td>\n",
       "      <td>60437</td>\n",
       "      <td>06/04/2016 10:17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>04/04/2016 17:36</td>\n",
       "      <td>BMW_316i___e36_Limousine___Bastlerfahrzeug__Ex...</td>\n",
       "      <td>private</td>\n",
       "      <td>offer</td>\n",
       "      <td>650</td>\n",
       "      <td>test</td>\n",
       "      <td>limousine</td>\n",
       "      <td>1995</td>\n",
       "      <td>manual</td>\n",
       "      <td>102</td>\n",
       "      <td>3er</td>\n",
       "      <td>150000</td>\n",
       "      <td>10</td>\n",
       "      <td>petrol</td>\n",
       "      <td>bmw</td>\n",
       "      <td>yes</td>\n",
       "      <td>04/04/2016 0:00</td>\n",
       "      <td>33775</td>\n",
       "      <td>06/04/2016 19:17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>01/04/2016 20:48</td>\n",
       "      <td>Peugeot_206_CC_110_Platinum</td>\n",
       "      <td>private</td>\n",
       "      <td>offer</td>\n",
       "      <td>2200</td>\n",
       "      <td>test</td>\n",
       "      <td>cabrio</td>\n",
       "      <td>2004</td>\n",
       "      <td>manual</td>\n",
       "      <td>109</td>\n",
       "      <td>2_reihe</td>\n",
       "      <td>150000</td>\n",
       "      <td>8</td>\n",
       "      <td>petrol</td>\n",
       "      <td>peugeot</td>\n",
       "      <td>no</td>\n",
       "      <td>01/04/2016 0:00</td>\n",
       "      <td>67112</td>\n",
       "      <td>05/04/2016 18:18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>21/03/2016 18:54</td>\n",
       "      <td>VW_Derby_Bj_80__Scheunenfund</td>\n",
       "      <td>private</td>\n",
       "      <td>offer</td>\n",
       "      <td>0</td>\n",
       "      <td>test</td>\n",
       "      <td>limousine</td>\n",
       "      <td>1980</td>\n",
       "      <td>manual</td>\n",
       "      <td>50</td>\n",
       "      <td>others</td>\n",
       "      <td>40000</td>\n",
       "      <td>7</td>\n",
       "      <td>petrol</td>\n",
       "      <td>volkswagen</td>\n",
       "      <td>no</td>\n",
       "      <td>21/03/2016 0:00</td>\n",
       "      <td>19348</td>\n",
       "      <td>25/03/2016 16:47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>260960</th>\n",
       "      <td>19/03/2016 19:53</td>\n",
       "      <td>turbo_defekt</td>\n",
       "      <td>private</td>\n",
       "      <td>offer</td>\n",
       "      <td>3200</td>\n",
       "      <td>control</td>\n",
       "      <td>limousine</td>\n",
       "      <td>2004</td>\n",
       "      <td>manual</td>\n",
       "      <td>225</td>\n",
       "      <td>leon</td>\n",
       "      <td>150000</td>\n",
       "      <td>5</td>\n",
       "      <td>petrol</td>\n",
       "      <td>seat</td>\n",
       "      <td>yes</td>\n",
       "      <td>19/03/2016 0:00</td>\n",
       "      <td>96465</td>\n",
       "      <td>19/03/2016 20:44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>260961</th>\n",
       "      <td>27/03/2016 20:36</td>\n",
       "      <td>Opel_Zafira_1.6_Elegance_TÜV_12/16</td>\n",
       "      <td>private</td>\n",
       "      <td>offer</td>\n",
       "      <td>1150</td>\n",
       "      <td>control</td>\n",
       "      <td>bus</td>\n",
       "      <td>2000</td>\n",
       "      <td>manual</td>\n",
       "      <td>0</td>\n",
       "      <td>zafira</td>\n",
       "      <td>150000</td>\n",
       "      <td>3</td>\n",
       "      <td>petrol</td>\n",
       "      <td>opel</td>\n",
       "      <td>no</td>\n",
       "      <td>27/03/2016 0:00</td>\n",
       "      <td>26624</td>\n",
       "      <td>29/03/2016 10:17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>260962</th>\n",
       "      <td>05/03/2016 19:56</td>\n",
       "      <td>Smart_smart_leistungssteigerung_100ps</td>\n",
       "      <td>private</td>\n",
       "      <td>offer</td>\n",
       "      <td>1199</td>\n",
       "      <td>test</td>\n",
       "      <td>cabrio</td>\n",
       "      <td>2000</td>\n",
       "      <td>automatic</td>\n",
       "      <td>101</td>\n",
       "      <td>fortwo</td>\n",
       "      <td>125000</td>\n",
       "      <td>3</td>\n",
       "      <td>petrol</td>\n",
       "      <td>smart</td>\n",
       "      <td>no</td>\n",
       "      <td>05/03/2016 0:00</td>\n",
       "      <td>26135</td>\n",
       "      <td>11/03/2016 18:17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>260963</th>\n",
       "      <td>19/03/2016 18:57</td>\n",
       "      <td>Volkswagen_Multivan_T4_TDI_7DC_UY2</td>\n",
       "      <td>private</td>\n",
       "      <td>offer</td>\n",
       "      <td>9200</td>\n",
       "      <td>test</td>\n",
       "      <td>bus</td>\n",
       "      <td>1996</td>\n",
       "      <td>manual</td>\n",
       "      <td>102</td>\n",
       "      <td>transporter</td>\n",
       "      <td>150000</td>\n",
       "      <td>3</td>\n",
       "      <td>diesel</td>\n",
       "      <td>volkswagen</td>\n",
       "      <td>no</td>\n",
       "      <td>19/03/2016 0:00</td>\n",
       "      <td>87439</td>\n",
       "      <td>07/04/2016 7:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>260964</th>\n",
       "      <td>07/03/2016 19:39</td>\n",
       "      <td>BMW_M135i_vollausgestattet_NP_52.720____Euro</td>\n",
       "      <td>private</td>\n",
       "      <td>offer</td>\n",
       "      <td>28990</td>\n",
       "      <td>control</td>\n",
       "      <td>limousine</td>\n",
       "      <td>2013</td>\n",
       "      <td>manual</td>\n",
       "      <td>320</td>\n",
       "      <td>m_reihe</td>\n",
       "      <td>50000</td>\n",
       "      <td>8</td>\n",
       "      <td>petrol</td>\n",
       "      <td>bmw</td>\n",
       "      <td>no</td>\n",
       "      <td>07/03/2016 0:00</td>\n",
       "      <td>73326</td>\n",
       "      <td>22/03/2016 3:17</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>260965 rows × 19 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             dateCrawled                                               name  \\\n",
       "0       17/03/2016 16:54                                 GOLF_4_1_4__3TÜRER   \n",
       "1       31/03/2016 17:25                     Skoda_Fabia_1.4_TDI_PD_Classic   \n",
       "2       04/04/2016 17:36  BMW_316i___e36_Limousine___Bastlerfahrzeug__Ex...   \n",
       "3       01/04/2016 20:48                        Peugeot_206_CC_110_Platinum   \n",
       "4       21/03/2016 18:54                       VW_Derby_Bj_80__Scheunenfund   \n",
       "...                  ...                                                ...   \n",
       "260960  19/03/2016 19:53                                       turbo_defekt   \n",
       "260961  27/03/2016 20:36                 Opel_Zafira_1.6_Elegance_TÜV_12/16   \n",
       "260962  05/03/2016 19:56              Smart_smart_leistungssteigerung_100ps   \n",
       "260963  19/03/2016 18:57                 Volkswagen_Multivan_T4_TDI_7DC_UY2   \n",
       "260964  07/03/2016 19:39       BMW_M135i_vollausgestattet_NP_52.720____Euro   \n",
       "\n",
       "         seller offerType  price   abtest vehicleType  yearOfRegistration  \\\n",
       "0       private     offer   1500     test   small car                2001   \n",
       "1       private     offer   3600     test   small car                2008   \n",
       "2       private     offer    650     test   limousine                1995   \n",
       "3       private     offer   2200     test      cabrio                2004   \n",
       "4       private     offer      0     test   limousine                1980   \n",
       "...         ...       ...    ...      ...         ...                 ...   \n",
       "260960  private     offer   3200  control   limousine                2004   \n",
       "260961  private     offer   1150  control         bus                2000   \n",
       "260962  private     offer   1199     test      cabrio                2000   \n",
       "260963  private     offer   9200     test         bus                1996   \n",
       "260964  private     offer  28990  control   limousine                2013   \n",
       "\n",
       "          gearbox  powerPS        model  kilometer  monthOfRegistration  \\\n",
       "0          manual       75         golf     150000                    6   \n",
       "1          manual       69        fabia      90000                    7   \n",
       "2          manual      102          3er     150000                   10   \n",
       "3          manual      109      2_reihe     150000                    8   \n",
       "4          manual       50       others      40000                    7   \n",
       "...           ...      ...          ...        ...                  ...   \n",
       "260960     manual      225         leon     150000                    5   \n",
       "260961     manual        0       zafira     150000                    3   \n",
       "260962  automatic      101       fortwo     125000                    3   \n",
       "260963     manual      102  transporter     150000                    3   \n",
       "260964     manual      320      m_reihe      50000                    8   \n",
       "\n",
       "       fuelType       brand notRepairedDamage      dateCreated  postalCode  \\\n",
       "0        petrol  volkswagen                no  17/03/2016 0:00       91074   \n",
       "1        diesel       skoda                no  31/03/2016 0:00       60437   \n",
       "2        petrol         bmw               yes  04/04/2016 0:00       33775   \n",
       "3        petrol     peugeot                no  01/04/2016 0:00       67112   \n",
       "4        petrol  volkswagen                no  21/03/2016 0:00       19348   \n",
       "...         ...         ...               ...              ...         ...   \n",
       "260960   petrol        seat               yes  19/03/2016 0:00       96465   \n",
       "260961   petrol        opel                no  27/03/2016 0:00       26624   \n",
       "260962   petrol       smart                no  05/03/2016 0:00       26135   \n",
       "260963   diesel  volkswagen                no  19/03/2016 0:00       87439   \n",
       "260964   petrol         bmw                no  07/03/2016 0:00       73326   \n",
       "\n",
       "                lastSeen  \n",
       "0       17/03/2016 17:40  \n",
       "1       06/04/2016 10:17  \n",
       "2       06/04/2016 19:17  \n",
       "3       05/04/2016 18:18  \n",
       "4       25/03/2016 16:47  \n",
       "...                  ...  \n",
       "260960  19/03/2016 20:44  \n",
       "260961  29/03/2016 10:17  \n",
       "260962  11/03/2016 18:17  \n",
       "260963   07/04/2016 7:15  \n",
       "260964   22/03/2016 3:17  \n",
       "\n",
       "[260965 rows x 19 columns]"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "car_analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>dateCrawled</th>\n",
       "      <th>name</th>\n",
       "      <th>seller</th>\n",
       "      <th>offerType</th>\n",
       "      <th>price</th>\n",
       "      <th>abtest</th>\n",
       "      <th>vehicleType</th>\n",
       "      <th>yearOfRegistration</th>\n",
       "      <th>gearbox</th>\n",
       "      <th>powerPS</th>\n",
       "      <th>model</th>\n",
       "      <th>kilometer</th>\n",
       "      <th>monthOfRegistration</th>\n",
       "      <th>fuelType</th>\n",
       "      <th>brand</th>\n",
       "      <th>notRepairedDamage</th>\n",
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       "      <th>postalCode</th>\n",
       "      <th>lastSeen</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>17/03/2016 16:54</td>\n",
       "      <td>GOLF_4_1_4__3TÜRER</td>\n",
       "      <td>private</td>\n",
       "      <td>offer</td>\n",
       "      <td>1500</td>\n",
       "      <td>test</td>\n",
       "      <td>small car</td>\n",
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       "      <td>manual</td>\n",
       "      <td>75</td>\n",
       "      <td>golf</td>\n",
       "      <td>150000</td>\n",
       "      <td>6</td>\n",
       "      <td>petrol</td>\n",
       "      <td>volkswagen</td>\n",
       "      <td>no</td>\n",
       "      <td>17/03/2016 0:00</td>\n",
       "      <td>91074</td>\n",
       "      <td>17/03/2016 17:40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>31/03/2016 17:25</td>\n",
       "      <td>Skoda_Fabia_1.4_TDI_PD_Classic</td>\n",
       "      <td>private</td>\n",
       "      <td>offer</td>\n",
       "      <td>3600</td>\n",
       "      <td>test</td>\n",
       "      <td>small car</td>\n",
       "      <td>2008</td>\n",
       "      <td>manual</td>\n",
       "      <td>69</td>\n",
       "      <td>fabia</td>\n",
       "      <td>90000</td>\n",
       "      <td>7</td>\n",
       "      <td>diesel</td>\n",
       "      <td>skoda</td>\n",
       "      <td>no</td>\n",
       "      <td>31/03/2016 0:00</td>\n",
       "      <td>60437</td>\n",
       "      <td>06/04/2016 10:17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>04/04/2016 17:36</td>\n",
       "      <td>BMW_316i___e36_Limousine___Bastlerfahrzeug__Ex...</td>\n",
       "      <td>private</td>\n",
       "      <td>offer</td>\n",
       "      <td>650</td>\n",
       "      <td>test</td>\n",
       "      <td>limousine</td>\n",
       "      <td>1995</td>\n",
       "      <td>manual</td>\n",
       "      <td>102</td>\n",
       "      <td>3er</td>\n",
       "      <td>150000</td>\n",
       "      <td>10</td>\n",
       "      <td>petrol</td>\n",
       "      <td>bmw</td>\n",
       "      <td>yes</td>\n",
       "      <td>04/04/2016 0:00</td>\n",
       "      <td>33775</td>\n",
       "      <td>06/04/2016 19:17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>01/04/2016 20:48</td>\n",
       "      <td>Peugeot_206_CC_110_Platinum</td>\n",
       "      <td>private</td>\n",
       "      <td>offer</td>\n",
       "      <td>2200</td>\n",
       "      <td>test</td>\n",
       "      <td>cabrio</td>\n",
       "      <td>2004</td>\n",
       "      <td>manual</td>\n",
       "      <td>109</td>\n",
       "      <td>2_reihe</td>\n",
       "      <td>150000</td>\n",
       "      <td>8</td>\n",
       "      <td>petrol</td>\n",
       "      <td>peugeot</td>\n",
       "      <td>no</td>\n",
       "      <td>01/04/2016 0:00</td>\n",
       "      <td>67112</td>\n",
       "      <td>05/04/2016 18:18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>21/03/2016 18:54</td>\n",
       "      <td>VW_Derby_Bj_80__Scheunenfund</td>\n",
       "      <td>private</td>\n",
       "      <td>offer</td>\n",
       "      <td>0</td>\n",
       "      <td>test</td>\n",
       "      <td>limousine</td>\n",
       "      <td>1980</td>\n",
       "      <td>manual</td>\n",
       "      <td>50</td>\n",
       "      <td>others</td>\n",
       "      <td>40000</td>\n",
       "      <td>7</td>\n",
       "      <td>petrol</td>\n",
       "      <td>volkswagen</td>\n",
       "      <td>no</td>\n",
       "      <td>21/03/2016 0:00</td>\n",
       "      <td>19348</td>\n",
       "      <td>25/03/2016 16:47</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        dateCrawled                                               name  \\\n",
       "0  17/03/2016 16:54                                 GOLF_4_1_4__3TÜRER   \n",
       "1  31/03/2016 17:25                     Skoda_Fabia_1.4_TDI_PD_Classic   \n",
       "2  04/04/2016 17:36  BMW_316i___e36_Limousine___Bastlerfahrzeug__Ex...   \n",
       "3  01/04/2016 20:48                        Peugeot_206_CC_110_Platinum   \n",
       "4  21/03/2016 18:54                       VW_Derby_Bj_80__Scheunenfund   \n",
       "\n",
       "    seller offerType  price abtest vehicleType  yearOfRegistration gearbox  \\\n",
       "0  private     offer   1500   test   small car                2001  manual   \n",
       "1  private     offer   3600   test   small car                2008  manual   \n",
       "2  private     offer    650   test   limousine                1995  manual   \n",
       "3  private     offer   2200   test      cabrio                2004  manual   \n",
       "4  private     offer      0   test   limousine                1980  manual   \n",
       "\n",
       "   powerPS    model  kilometer  monthOfRegistration fuelType       brand  \\\n",
       "0       75     golf     150000                    6   petrol  volkswagen   \n",
       "1       69    fabia      90000                    7   diesel       skoda   \n",
       "2      102      3er     150000                   10   petrol         bmw   \n",
       "3      109  2_reihe     150000                    8   petrol     peugeot   \n",
       "4       50   others      40000                    7   petrol  volkswagen   \n",
       "\n",
       "  notRepairedDamage      dateCreated  postalCode          lastSeen  \n",
       "0                no  17/03/2016 0:00       91074  17/03/2016 17:40  \n",
       "1                no  31/03/2016 0:00       60437  06/04/2016 10:17  \n",
       "2               yes  04/04/2016 0:00       33775  06/04/2016 19:17  \n",
       "3                no  01/04/2016 0:00       67112  05/04/2016 18:18  \n",
       "4                no  21/03/2016 0:00       19348  25/03/2016 16:47  "
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "car_analysis.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['dateCrawled', 'name', 'seller', 'offerType', 'price', 'abtest',\n",
       "       'vehicleType', 'yearOfRegistration', 'gearbox', 'powerPS', 'model',\n",
       "       'kilometer', 'monthOfRegistration', 'fuelType', 'brand',\n",
       "       'notRepairedDamage', 'dateCreated', 'postalCode', 'lastSeen'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "car_analysis.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finding Duplicated Columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Duplicate Rows except first occurence based on all columns are:\n",
      "             dateCrawled                                               name  \\\n",
      "20284   23/03/2016 10:38  Opel_Zafira_1.7_CDTI_ecoFLEX_Edition_111_Jahre...   \n",
      "36259   13/03/2016 11:38  Volkswagen_Passat_Variant_1.6_TDI_BlueMotion_A...   \n",
      "44519   09/03/2016 22:47  Opel_Movano_EZ_2003_Diesel_Motor_2_8_Karosseri...   \n",
      "62595   03/04/2016 20:06  Fiat_500_1.3_Multijet__Lounge__Pano__Sonderedi...   \n",
      "70177   05/03/2016 14:16                               Suzuki_Swift_1.0_GLX   \n",
      "...                  ...                                                ...   \n",
      "240933   03/04/2016 9:56             A4_2.7tdi_Sportpaket_plus_::V8_Klang::   \n",
      "241009  03/04/2016 22:56                                        Mazda_323_F   \n",
      "247912  21/03/2016 16:42  Mercedes_Benz_E_200_T_CDI_Navi_AHK_Garantie__A...   \n",
      "254097  22/03/2016 18:47  BMW_320i_Touring_Automatik__110_kW_TÜV_bis_12....   \n",
      "255564  26/03/2016 15:51                            Ford_Focus_Turnier_Ghia   \n",
      "\n",
      "         seller offerType  price   abtest    vehicleType  yearOfRegistration  \\\n",
      "20284   private     offer  12200  control            bus                2011   \n",
      "36259   private     offer  11499  control  station wagon                2011   \n",
      "44519   private     offer   1200     test            bus                2003   \n",
      "62595   private     offer   6990  control      small car                2008   \n",
      "70177   private     offer    850     test      small car                2002   \n",
      "...         ...       ...    ...      ...            ...                 ...   \n",
      "240933  private     offer  13000  control  station wagon                2008   \n",
      "241009  private     offer    500  control      limousine                1997   \n",
      "247912  private     offer  20200  control  station wagon                2011   \n",
      "254097  private     offer    800  control  station wagon                1995   \n",
      "255564  private     offer    700     test  station wagon                1999   \n",
      "\n",
      "          gearbox  powerPS     model  kilometer  monthOfRegistration fuelType  \\\n",
      "20284      manual      125    zafira      40000                   10   diesel   \n",
      "36259      manual      105    passat     125000                    3   diesel   \n",
      "44519      manual      114    others     150000                    7   diesel   \n",
      "62595      manual       75       500      80000                    1   diesel   \n",
      "70177      manual       53     swift     150000                    1   petrol   \n",
      "...           ...      ...       ...        ...                  ...      ...   \n",
      "240933     manual      190        a4     150000                   12   diesel   \n",
      "241009     manual       88   3_reihe     100000                   11   petrol   \n",
      "247912  automatic      136  e_klasse     125000                    7   diesel   \n",
      "254097  automatic      150       3er     150000                   12   petrol   \n",
      "255564     manual      116     focus     150000                    6   petrol   \n",
      "\n",
      "                brand notRepairedDamage      dateCreated  postalCode  \\\n",
      "20284            opel                no  23/03/2016 0:00       26629   \n",
      "36259      volkswagen                no  13/03/2016 0:00       50354   \n",
      "44519            opel               yes  09/03/2016 0:00       25358   \n",
      "62595            fiat                no  03/04/2016 0:00       65428   \n",
      "70177          suzuki                no  04/03/2016 0:00       35794   \n",
      "...               ...               ...              ...         ...   \n",
      "240933           audi                no  03/04/2016 0:00       40589   \n",
      "241009          mazda                no  03/04/2016 0:00       87700   \n",
      "247912  mercedes_benz                no  21/03/2016 0:00       44139   \n",
      "254097            bmw                no  22/03/2016 0:00       79331   \n",
      "255564           ford                no  26/03/2016 0:00       59581   \n",
      "\n",
      "                lastSeen  \n",
      "20284    05/04/2016 7:44  \n",
      "36259   13/03/2016 11:38  \n",
      "44519    11/03/2016 8:17  \n",
      "62595   07/04/2016 13:16  \n",
      "70177    15/03/2016 1:17  \n",
      "...                  ...  \n",
      "240933  07/04/2016 10:45  \n",
      "241009   06/04/2016 0:16  \n",
      "247912  02/04/2016 16:45  \n",
      "254097  06/04/2016 11:16  \n",
      "255564  26/03/2016 15:51  \n",
      "\n",
      "[64 rows x 19 columns]\n"
     ]
    }
   ],
   "source": [
    "duplicatedcolumns = car_analysis[car_analysis.duplicated()]\n",
    "print('Duplicate Rows except first occurence based on all columns are:')\n",
    "print(duplicatedcolumns)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finding duplicated rows based on selected columns\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Duplicated rows based on columns\n",
      " 0         False\n",
      "1         False\n",
      "2         False\n",
      "3         False\n",
      "4         False\n",
      "          ...  \n",
      "260960     True\n",
      "260961     True\n",
      "260962     True\n",
      "260963     True\n",
      "260964     True\n",
      "Length: 260965, dtype: bool\n"
     ]
    }
   ],
   "source": [
    "duplicatedrows = car_analysis.duplicated(['dateCrawled'])\n",
    "print('Duplicated rows based on columns\\n', duplicatedrows)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "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>dateCrawled</th>\n",
       "      <th>name</th>\n",
       "      <th>seller</th>\n",
       "      <th>offerType</th>\n",
       "      <th>price</th>\n",
       "      <th>abtest</th>\n",
       "      <th>vehicleType</th>\n",
       "      <th>yearOfRegistration</th>\n",
       "      <th>gearbox</th>\n",
       "      <th>powerPS</th>\n",
       "      <th>model</th>\n",
       "      <th>kilometer</th>\n",
       "      <th>monthOfRegistration</th>\n",
       "      <th>fuelType</th>\n",
       "      <th>brand</th>\n",
       "      <th>notRepairedDamage</th>\n",
       "      <th>dateCreated</th>\n",
       "      <th>postalCode</th>\n",
       "      <th>lastSeen</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>17/03/2016 16:54</td>\n",
       "      <td>GOLF_4_1_4__3TÜRER</td>\n",
       "      <td>private</td>\n",
       "      <td>offer</td>\n",
       "      <td>1500</td>\n",
       "      <td>test</td>\n",
       "      <td>small car</td>\n",
       "      <td>2001</td>\n",
       "      <td>manual</td>\n",
       "      <td>75</td>\n",
       "      <td>golf</td>\n",
       "      <td>150000</td>\n",
       "      <td>6</td>\n",
       "      <td>petrol</td>\n",
       "      <td>volkswagen</td>\n",
       "      <td>no</td>\n",
       "      <td>17/03/2016 0:00</td>\n",
       "      <td>91074</td>\n",
       "      <td>17/03/2016 17:40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>31/03/2016 17:25</td>\n",
       "      <td>Skoda_Fabia_1.4_TDI_PD_Classic</td>\n",
       "      <td>private</td>\n",
       "      <td>offer</td>\n",
       "      <td>3600</td>\n",
       "      <td>test</td>\n",
       "      <td>small car</td>\n",
       "      <td>2008</td>\n",
       "      <td>manual</td>\n",
       "      <td>69</td>\n",
       "      <td>fabia</td>\n",
       "      <td>90000</td>\n",
       "      <td>7</td>\n",
       "      <td>diesel</td>\n",
       "      <td>skoda</td>\n",
       "      <td>no</td>\n",
       "      <td>31/03/2016 0:00</td>\n",
       "      <td>60437</td>\n",
       "      <td>06/04/2016 10:17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>04/04/2016 17:36</td>\n",
       "      <td>BMW_316i___e36_Limousine___Bastlerfahrzeug__Ex...</td>\n",
       "      <td>private</td>\n",
       "      <td>offer</td>\n",
       "      <td>650</td>\n",
       "      <td>test</td>\n",
       "      <td>limousine</td>\n",
       "      <td>1995</td>\n",
       "      <td>manual</td>\n",
       "      <td>102</td>\n",
       "      <td>3er</td>\n",
       "      <td>150000</td>\n",
       "      <td>10</td>\n",
       "      <td>petrol</td>\n",
       "      <td>bmw</td>\n",
       "      <td>yes</td>\n",
       "      <td>04/04/2016 0:00</td>\n",
       "      <td>33775</td>\n",
       "      <td>06/04/2016 19:17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>01/04/2016 20:48</td>\n",
       "      <td>Peugeot_206_CC_110_Platinum</td>\n",
       "      <td>private</td>\n",
       "      <td>offer</td>\n",
       "      <td>2200</td>\n",
       "      <td>test</td>\n",
       "      <td>cabrio</td>\n",
       "      <td>2004</td>\n",
       "      <td>manual</td>\n",
       "      <td>109</td>\n",
       "      <td>2_reihe</td>\n",
       "      <td>150000</td>\n",
       "      <td>8</td>\n",
       "      <td>petrol</td>\n",
       "      <td>peugeot</td>\n",
       "      <td>no</td>\n",
       "      <td>01/04/2016 0:00</td>\n",
       "      <td>67112</td>\n",
       "      <td>05/04/2016 18:18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>21/03/2016 18:54</td>\n",
       "      <td>VW_Derby_Bj_80__Scheunenfund</td>\n",
       "      <td>private</td>\n",
       "      <td>offer</td>\n",
       "      <td>0</td>\n",
       "      <td>test</td>\n",
       "      <td>limousine</td>\n",
       "      <td>1980</td>\n",
       "      <td>manual</td>\n",
       "      <td>50</td>\n",
       "      <td>others</td>\n",
       "      <td>40000</td>\n",
       "      <td>7</td>\n",
       "      <td>petrol</td>\n",
       "      <td>volkswagen</td>\n",
       "      <td>no</td>\n",
       "      <td>21/03/2016 0:00</td>\n",
       "      <td>19348</td>\n",
       "      <td>25/03/2016 16:47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>260960</th>\n",
       "      <td>19/03/2016 19:53</td>\n",
       "      <td>turbo_defekt</td>\n",
       "      <td>private</td>\n",
       "      <td>offer</td>\n",
       "      <td>3200</td>\n",
       "      <td>control</td>\n",
       "      <td>limousine</td>\n",
       "      <td>2004</td>\n",
       "      <td>manual</td>\n",
       "      <td>225</td>\n",
       "      <td>leon</td>\n",
       "      <td>150000</td>\n",
       "      <td>5</td>\n",
       "      <td>petrol</td>\n",
       "      <td>seat</td>\n",
       "      <td>yes</td>\n",
       "      <td>19/03/2016 0:00</td>\n",
       "      <td>96465</td>\n",
       "      <td>19/03/2016 20:44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>260961</th>\n",
       "      <td>27/03/2016 20:36</td>\n",
       "      <td>Opel_Zafira_1.6_Elegance_TÜV_12/16</td>\n",
       "      <td>private</td>\n",
       "      <td>offer</td>\n",
       "      <td>1150</td>\n",
       "      <td>control</td>\n",
       "      <td>bus</td>\n",
       "      <td>2000</td>\n",
       "      <td>manual</td>\n",
       "      <td>0</td>\n",
       "      <td>zafira</td>\n",
       "      <td>150000</td>\n",
       "      <td>3</td>\n",
       "      <td>petrol</td>\n",
       "      <td>opel</td>\n",
       "      <td>no</td>\n",
       "      <td>27/03/2016 0:00</td>\n",
       "      <td>26624</td>\n",
       "      <td>29/03/2016 10:17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>260962</th>\n",
       "      <td>05/03/2016 19:56</td>\n",
       "      <td>Smart_smart_leistungssteigerung_100ps</td>\n",
       "      <td>private</td>\n",
       "      <td>offer</td>\n",
       "      <td>1199</td>\n",
       "      <td>test</td>\n",
       "      <td>cabrio</td>\n",
       "      <td>2000</td>\n",
       "      <td>automatic</td>\n",
       "      <td>101</td>\n",
       "      <td>fortwo</td>\n",
       "      <td>125000</td>\n",
       "      <td>3</td>\n",
       "      <td>petrol</td>\n",
       "      <td>smart</td>\n",
       "      <td>no</td>\n",
       "      <td>05/03/2016 0:00</td>\n",
       "      <td>26135</td>\n",
       "      <td>11/03/2016 18:17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>260963</th>\n",
       "      <td>19/03/2016 18:57</td>\n",
       "      <td>Volkswagen_Multivan_T4_TDI_7DC_UY2</td>\n",
       "      <td>private</td>\n",
       "      <td>offer</td>\n",
       "      <td>9200</td>\n",
       "      <td>test</td>\n",
       "      <td>bus</td>\n",
       "      <td>1996</td>\n",
       "      <td>manual</td>\n",
       "      <td>102</td>\n",
       "      <td>transporter</td>\n",
       "      <td>150000</td>\n",
       "      <td>3</td>\n",
       "      <td>diesel</td>\n",
       "      <td>volkswagen</td>\n",
       "      <td>no</td>\n",
       "      <td>19/03/2016 0:00</td>\n",
       "      <td>87439</td>\n",
       "      <td>07/04/2016 7:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>260964</th>\n",
       "      <td>07/03/2016 19:39</td>\n",
       "      <td>BMW_M135i_vollausgestattet_NP_52.720____Euro</td>\n",
       "      <td>private</td>\n",
       "      <td>offer</td>\n",
       "      <td>28990</td>\n",
       "      <td>control</td>\n",
       "      <td>limousine</td>\n",
       "      <td>2013</td>\n",
       "      <td>manual</td>\n",
       "      <td>320</td>\n",
       "      <td>m_reihe</td>\n",
       "      <td>50000</td>\n",
       "      <td>8</td>\n",
       "      <td>petrol</td>\n",
       "      <td>bmw</td>\n",
       "      <td>no</td>\n",
       "      <td>07/03/2016 0:00</td>\n",
       "      <td>73326</td>\n",
       "      <td>22/03/2016 3:17</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>260837 rows × 19 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             dateCrawled                                               name  \\\n",
       "0       17/03/2016 16:54                                 GOLF_4_1_4__3TÜRER   \n",
       "1       31/03/2016 17:25                     Skoda_Fabia_1.4_TDI_PD_Classic   \n",
       "2       04/04/2016 17:36  BMW_316i___e36_Limousine___Bastlerfahrzeug__Ex...   \n",
       "3       01/04/2016 20:48                        Peugeot_206_CC_110_Platinum   \n",
       "4       21/03/2016 18:54                       VW_Derby_Bj_80__Scheunenfund   \n",
       "...                  ...                                                ...   \n",
       "260960  19/03/2016 19:53                                       turbo_defekt   \n",
       "260961  27/03/2016 20:36                 Opel_Zafira_1.6_Elegance_TÜV_12/16   \n",
       "260962  05/03/2016 19:56              Smart_smart_leistungssteigerung_100ps   \n",
       "260963  19/03/2016 18:57                 Volkswagen_Multivan_T4_TDI_7DC_UY2   \n",
       "260964  07/03/2016 19:39       BMW_M135i_vollausgestattet_NP_52.720____Euro   \n",
       "\n",
       "         seller offerType  price   abtest vehicleType  yearOfRegistration  \\\n",
       "0       private     offer   1500     test   small car                2001   \n",
       "1       private     offer   3600     test   small car                2008   \n",
       "2       private     offer    650     test   limousine                1995   \n",
       "3       private     offer   2200     test      cabrio                2004   \n",
       "4       private     offer      0     test   limousine                1980   \n",
       "...         ...       ...    ...      ...         ...                 ...   \n",
       "260960  private     offer   3200  control   limousine                2004   \n",
       "260961  private     offer   1150  control         bus                2000   \n",
       "260962  private     offer   1199     test      cabrio                2000   \n",
       "260963  private     offer   9200     test         bus                1996   \n",
       "260964  private     offer  28990  control   limousine                2013   \n",
       "\n",
       "          gearbox  powerPS        model  kilometer  monthOfRegistration  \\\n",
       "0          manual       75         golf     150000                    6   \n",
       "1          manual       69        fabia      90000                    7   \n",
       "2          manual      102          3er     150000                   10   \n",
       "3          manual      109      2_reihe     150000                    8   \n",
       "4          manual       50       others      40000                    7   \n",
       "...           ...      ...          ...        ...                  ...   \n",
       "260960     manual      225         leon     150000                    5   \n",
       "260961     manual        0       zafira     150000                    3   \n",
       "260962  automatic      101       fortwo     125000                    3   \n",
       "260963     manual      102  transporter     150000                    3   \n",
       "260964     manual      320      m_reihe      50000                    8   \n",
       "\n",
       "       fuelType       brand notRepairedDamage      dateCreated  postalCode  \\\n",
       "0        petrol  volkswagen                no  17/03/2016 0:00       91074   \n",
       "1        diesel       skoda                no  31/03/2016 0:00       60437   \n",
       "2        petrol         bmw               yes  04/04/2016 0:00       33775   \n",
       "3        petrol     peugeot                no  01/04/2016 0:00       67112   \n",
       "4        petrol  volkswagen                no  21/03/2016 0:00       19348   \n",
       "...         ...         ...               ...              ...         ...   \n",
       "260960   petrol        seat               yes  19/03/2016 0:00       96465   \n",
       "260961   petrol        opel                no  27/03/2016 0:00       26624   \n",
       "260962   petrol       smart                no  05/03/2016 0:00       26135   \n",
       "260963   diesel  volkswagen                no  19/03/2016 0:00       87439   \n",
       "260964   petrol         bmw                no  07/03/2016 0:00       73326   \n",
       "\n",
       "                lastSeen  \n",
       "0       17/03/2016 17:40  \n",
       "1       06/04/2016 10:17  \n",
       "2       06/04/2016 19:17  \n",
       "3       05/04/2016 18:18  \n",
       "4       25/03/2016 16:47  \n",
       "...                  ...  \n",
       "260960  19/03/2016 20:44  \n",
       "260961  29/03/2016 10:17  \n",
       "260962  11/03/2016 18:17  \n",
       "260963   07/04/2016 7:15  \n",
       "260964   22/03/2016 3:17  \n",
       "\n",
       "[260837 rows x 19 columns]"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "car_analysis = car_analysis.drop_duplicates(keep=False)\n",
    "car_analysis\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There is no duplicate elements in csv file\n"
     ]
    }
   ],
   "source": [
    "car_analysis_dupliactedRows=car_analysis[car_analysis.duplicated( keep=False)].shape[0]\n",
    "if(car_analysis_dupliactedRows==0):\n",
    "  print(\"There is no duplicate elements in csv file\")\n",
    "else:\n",
    "  print(\"There is  duplicate elements in csv file\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Index: 260837 entries, 0 to 260964\n",
      "Data columns (total 19 columns):\n",
      " #   Column               Non-Null Count   Dtype \n",
      "---  ------               --------------   ----- \n",
      " 0   dateCrawled          260837 non-null  object\n",
      " 1   name                 260837 non-null  object\n",
      " 2   seller               260837 non-null  object\n",
      " 3   offerType            260837 non-null  object\n",
      " 4   price                260837 non-null  int64 \n",
      " 5   abtest               260837 non-null  object\n",
      " 6   vehicleType          260837 non-null  object\n",
      " 7   yearOfRegistration   260837 non-null  int64 \n",
      " 8   gearbox              260837 non-null  object\n",
      " 9   powerPS              260837 non-null  int64 \n",
      " 10  model                260837 non-null  object\n",
      " 11  kilometer            260837 non-null  int64 \n",
      " 12  monthOfRegistration  260837 non-null  int64 \n",
      " 13  fuelType             260837 non-null  object\n",
      " 14  brand                260837 non-null  object\n",
      " 15  notRepairedDamage    260837 non-null  object\n",
      " 16  dateCreated          260837 non-null  object\n",
      " 17  postalCode           260837 non-null  int64 \n",
      " 18  lastSeen             260837 non-null  object\n",
      "dtypes: int64(6), object(13)\n",
      "memory usage: 39.8+ MB\n"
     ]
    }
   ],
   "source": [
    "car_analysis.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [],
   "source": [
    "car_analysis.to_csv('C:/Users/toy/Desktop/project/carAnalysis/clean_cardata.csv', index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Analysing the Car Data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "Most expensive automobile"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
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       "      <th>name</th>\n",
       "      <th>seller</th>\n",
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       "      <th>abtest</th>\n",
       "      <th>vehicleType</th>\n",
       "      <th>yearOfRegistration</th>\n",
       "      <th>gearbox</th>\n",
       "      <th>powerPS</th>\n",
       "      <th>model</th>\n",
       "      <th>kilometer</th>\n",
       "      <th>monthOfRegistration</th>\n",
       "      <th>fuelType</th>\n",
       "      <th>brand</th>\n",
       "      <th>notRepairedDamage</th>\n",
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       "      <th>postalCode</th>\n",
       "      <th>lastSeen</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>97812</th>\n",
       "      <td>14/03/2016 12:49</td>\n",
       "      <td>Mercedes_Benz_CLS_350_CDI_7G_TRONIC</td>\n",
       "      <td>private</td>\n",
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       "      <td>automatic</td>\n",
       "      <td>224</td>\n",
       "      <td>others</td>\n",
       "      <td>150000</td>\n",
       "      <td>11</td>\n",
       "      <td>diesel</td>\n",
       "      <td>mercedes_benz</td>\n",
       "      <td>yes</td>\n",
       "      <td>14/03/2016 0:00</td>\n",
       "      <td>56112</td>\n",
       "      <td>14/03/2016 22:40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89891</th>\n",
       "      <td>14/03/2016 17:49</td>\n",
       "      <td>audi_a6_c5_avant</td>\n",
       "      <td>private</td>\n",
       "      <td>offer</td>\n",
       "      <td>99999999</td>\n",
       "      <td>test</td>\n",
       "      <td>station wagon</td>\n",
       "      <td>1999</td>\n",
       "      <td>manual</td>\n",
       "      <td>165</td>\n",
       "      <td>a6</td>\n",
       "      <td>5000</td>\n",
       "      <td>12</td>\n",
       "      <td>petrol</td>\n",
       "      <td>audi</td>\n",
       "      <td>no</td>\n",
       "      <td>14/03/2016 0:00</td>\n",
       "      <td>28325</td>\n",
       "      <td>14/03/2016 17:49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>176989</th>\n",
       "      <td>21/03/2016 22:25</td>\n",
       "      <td>Audi_A6_2.7_TDI_quattro_S_Line_Luftfederung_Bose</td>\n",
       "      <td>private</td>\n",
       "      <td>offer</td>\n",
       "      <td>99000000</td>\n",
       "      <td>test</td>\n",
       "      <td>limousine</td>\n",
       "      <td>2009</td>\n",
       "      <td>automatic</td>\n",
       "      <td>190</td>\n",
       "      <td>a6</td>\n",
       "      <td>150000</td>\n",
       "      <td>11</td>\n",
       "      <td>diesel</td>\n",
       "      <td>audi</td>\n",
       "      <td>no</td>\n",
       "      <td>21/03/2016 0:00</td>\n",
       "      <td>60433</td>\n",
       "      <td>25/03/2016 4:45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196677</th>\n",
       "      <td>03/04/2016 11:56</td>\n",
       "      <td>Mercedes_Benz_CLK_Coupe_280_7G_TRONIC_Sport_Av...</td>\n",
       "      <td>private</td>\n",
       "      <td>offer</td>\n",
       "      <td>14000500</td>\n",
       "      <td>control</td>\n",
       "      <td>coupe</td>\n",
       "      <td>2008</td>\n",
       "      <td>automatic</td>\n",
       "      <td>231</td>\n",
       "      <td>clk</td>\n",
       "      <td>125000</td>\n",
       "      <td>5</td>\n",
       "      <td>petrol</td>\n",
       "      <td>mercedes_benz</td>\n",
       "      <td>no</td>\n",
       "      <td>03/04/2016 0:00</td>\n",
       "      <td>40476</td>\n",
       "      <td>03/04/2016 11:56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>169853</th>\n",
       "      <td>31/03/2016 18:56</td>\n",
       "      <td>Opel_Vectra_B_1_6i_16V_Facelift_Tuning_Showcar...</td>\n",
       "      <td>private</td>\n",
       "      <td>offer</td>\n",
       "      <td>12345678</td>\n",
       "      <td>control</td>\n",
       "      <td>limousine</td>\n",
       "      <td>2001</td>\n",
       "      <td>manual</td>\n",
       "      <td>101</td>\n",
       "      <td>vectra</td>\n",
       "      <td>150000</td>\n",
       "      <td>3</td>\n",
       "      <td>petrol</td>\n",
       "      <td>opel</td>\n",
       "      <td>no</td>\n",
       "      <td>31/03/2016 0:00</td>\n",
       "      <td>4356</td>\n",
       "      <td>31/03/2016 18:56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202254</th>\n",
       "      <td>26/03/2016 0:56</td>\n",
       "      <td>tausche_o_verkaufe</td>\n",
       "      <td>private</td>\n",
       "      <td>offer</td>\n",
       "      <td>12345678</td>\n",
       "      <td>test</td>\n",
       "      <td>station wagon</td>\n",
       "      <td>2001</td>\n",
       "      <td>manual</td>\n",
       "      <td>101</td>\n",
       "      <td>focus</td>\n",
       "      <td>150000</td>\n",
       "      <td>0</td>\n",
       "      <td>petrol</td>\n",
       "      <td>ford</td>\n",
       "      <td>no</td>\n",
       "      <td>26/03/2016 0:00</td>\n",
       "      <td>17291</td>\n",
       "      <td>01/04/2016 21:18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>148006</th>\n",
       "      <td>12/03/2016 21:50</td>\n",
       "      <td>Escort_MK_1_Hundeknochen_zum_umbauen_auf_RS_2000</td>\n",
       "      <td>private</td>\n",
       "      <td>offer</td>\n",
       "      <td>11111111</td>\n",
       "      <td>test</td>\n",
       "      <td>limousine</td>\n",
       "      <td>1973</td>\n",
       "      <td>manual</td>\n",
       "      <td>48</td>\n",
       "      <td>escort</td>\n",
       "      <td>50000</td>\n",
       "      <td>3</td>\n",
       "      <td>petrol</td>\n",
       "      <td>ford</td>\n",
       "      <td>no</td>\n",
       "      <td>12/03/2016 0:00</td>\n",
       "      <td>94469</td>\n",
       "      <td>12/03/2016 22:45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38164</th>\n",
       "      <td>08/03/2016 11:51</td>\n",
       "      <td>Mazda_5_2.0_CD_DPF_Exclusive</td>\n",
       "      <td>private</td>\n",
       "      <td>offer</td>\n",
       "      <td>10000000</td>\n",
       "      <td>control</td>\n",
       "      <td>bus</td>\n",
       "      <td>2007</td>\n",
       "      <td>manual</td>\n",
       "      <td>143</td>\n",
       "      <td>5_reihe</td>\n",
       "      <td>150000</td>\n",
       "      <td>2</td>\n",
       "      <td>diesel</td>\n",
       "      <td>mazda</td>\n",
       "      <td>no</td>\n",
       "      <td>08/03/2016 0:00</td>\n",
       "      <td>83301</td>\n",
       "      <td>10/03/2016 14:17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15102</th>\n",
       "      <td>19/03/2016 19:45</td>\n",
       "      <td>Porsche_911_911R_1_of_20_ORIGINAL_R_nur_798KG!...</td>\n",
       "      <td>private</td>\n",
       "      <td>offer</td>\n",
       "      <td>9999999</td>\n",
       "      <td>control</td>\n",
       "      <td>coupe</td>\n",
       "      <td>1967</td>\n",
       "      <td>manual</td>\n",
       "      <td>215</td>\n",
       "      <td>911</td>\n",
       "      <td>50000</td>\n",
       "      <td>10</td>\n",
       "      <td>petrol</td>\n",
       "      <td>porsche</td>\n",
       "      <td>no</td>\n",
       "      <td>19/03/2016 0:00</td>\n",
       "      <td>70435</td>\n",
       "      <td>01/04/2016 10:45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64084</th>\n",
       "      <td>30/03/2016 19:46</td>\n",
       "      <td>Verkaufe_oder_tausche_wenn_nur_gegen_Kombi_s4_...</td>\n",
       "      <td>private</td>\n",
       "      <td>offer</td>\n",
       "      <td>9999999</td>\n",
       "      <td>test</td>\n",
       "      <td>limousine</td>\n",
       "      <td>1996</td>\n",
       "      <td>manual</td>\n",
       "      <td>380</td>\n",
       "      <td>a4</td>\n",
       "      <td>60000</td>\n",
       "      <td>5</td>\n",
       "      <td>petrol</td>\n",
       "      <td>audi</td>\n",
       "      <td>no</td>\n",
       "      <td>30/03/2016 0:00</td>\n",
       "      <td>47800</td>\n",
       "      <td>30/03/2016 19:46</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             dateCrawled                                               name  \\\n",
       "97812   14/03/2016 12:49                Mercedes_Benz_CLS_350_CDI_7G_TRONIC   \n",
       "89891   14/03/2016 17:49                                   audi_a6_c5_avant   \n",
       "176989  21/03/2016 22:25   Audi_A6_2.7_TDI_quattro_S_Line_Luftfederung_Bose   \n",
       "196677  03/04/2016 11:56  Mercedes_Benz_CLK_Coupe_280_7G_TRONIC_Sport_Av...   \n",
       "169853  31/03/2016 18:56  Opel_Vectra_B_1_6i_16V_Facelift_Tuning_Showcar...   \n",
       "202254   26/03/2016 0:56                                 tausche_o_verkaufe   \n",
       "148006  12/03/2016 21:50   Escort_MK_1_Hundeknochen_zum_umbauen_auf_RS_2000   \n",
       "38164   08/03/2016 11:51                       Mazda_5_2.0_CD_DPF_Exclusive   \n",
       "15102   19/03/2016 19:45  Porsche_911_911R_1_of_20_ORIGINAL_R_nur_798KG!...   \n",
       "64084   30/03/2016 19:46  Verkaufe_oder_tausche_wenn_nur_gegen_Kombi_s4_...   \n",
       "\n",
       "         seller offerType     price   abtest    vehicleType  \\\n",
       "97812   private     offer  99999999  control          coupe   \n",
       "89891   private     offer  99999999     test  station wagon   \n",
       "176989  private     offer  99000000     test      limousine   \n",
       "196677  private     offer  14000500  control          coupe   \n",
       "169853  private     offer  12345678  control      limousine   \n",
       "202254  private     offer  12345678     test  station wagon   \n",
       "148006  private     offer  11111111     test      limousine   \n",
       "38164   private     offer  10000000  control            bus   \n",
       "15102   private     offer   9999999  control          coupe   \n",
       "64084   private     offer   9999999     test      limousine   \n",
       "\n",
       "        yearOfRegistration    gearbox  powerPS    model  kilometer  \\\n",
       "97812                 2009  automatic      224   others     150000   \n",
       "89891                 1999     manual      165       a6       5000   \n",
       "176989                2009  automatic      190       a6     150000   \n",
       "196677                2008  automatic      231      clk     125000   \n",
       "169853                2001     manual      101   vectra     150000   \n",
       "202254                2001     manual      101    focus     150000   \n",
       "148006                1973     manual       48   escort      50000   \n",
       "38164                 2007     manual      143  5_reihe     150000   \n",
       "15102                 1967     manual      215      911      50000   \n",
       "64084                 1996     manual      380       a4      60000   \n",
       "\n",
       "        monthOfRegistration fuelType          brand notRepairedDamage  \\\n",
       "97812                    11   diesel  mercedes_benz               yes   \n",
       "89891                    12   petrol           audi                no   \n",
       "176989                   11   diesel           audi                no   \n",
       "196677                    5   petrol  mercedes_benz                no   \n",
       "169853                    3   petrol           opel                no   \n",
       "202254                    0   petrol           ford                no   \n",
       "148006                    3   petrol           ford                no   \n",
       "38164                     2   diesel          mazda                no   \n",
       "15102                    10   petrol        porsche                no   \n",
       "64084                     5   petrol           audi                no   \n",
       "\n",
       "            dateCreated  postalCode          lastSeen  \n",
       "97812   14/03/2016 0:00       56112  14/03/2016 22:40  \n",
       "89891   14/03/2016 0:00       28325  14/03/2016 17:49  \n",
       "176989  21/03/2016 0:00       60433   25/03/2016 4:45  \n",
       "196677  03/04/2016 0:00       40476  03/04/2016 11:56  \n",
       "169853  31/03/2016 0:00        4356  31/03/2016 18:56  \n",
       "202254  26/03/2016 0:00       17291  01/04/2016 21:18  \n",
       "148006  12/03/2016 0:00       94469  12/03/2016 22:45  \n",
       "38164   08/03/2016 0:00       83301  10/03/2016 14:17  \n",
       "15102   19/03/2016 0:00       70435  01/04/2016 10:45  \n",
       "64084   30/03/2016 0:00       47800  30/03/2016 19:46  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "most_expensive_car = car_analysis.sort_values(ascending=False, by='price')\n",
    "most_expensive_car.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
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   "source": [
    "expensive_cars = car_analysis.sort_values('price',ascending = False).head(2)\n",
    "fig = px.bar(expensive_cars, x='brand', y='price', color='price')\n",
    "fig.show()"
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      "C:\\Users\\toy\\AppData\\Local\\Temp\\ipykernel_4604\\3108857260.py:2: UserWarning:\n",
      "\n",
      "Parsing dates in %d/%m/%Y %H:%M format when dayfirst=False (the default) was specified. Pass `dayfirst=True` or specify a format to silence this warning.\n",
      "\n",
      "C:\\Users\\toy\\AppData\\Local\\Temp\\ipykernel_4604\\3108857260.py:2: SettingWithCopyWarning:\n",
      "\n",
      "\n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "\n",
      "C:\\Users\\toy\\AppData\\Local\\Temp\\ipykernel_4604\\3108857260.py:3: UserWarning:\n",
      "\n",
      "Parsing dates in %d/%m/%Y %H:%M format when dayfirst=False (the default) was specified. Pass `dayfirst=True` or specify a format to silence this warning.\n",
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      "C:\\Users\\toy\\AppData\\Local\\Temp\\ipykernel_4604\\3108857260.py:3: SettingWithCopyWarning:\n",
      "\n",
      "\n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
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      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
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       "      <td>manual</td>\n",
       "      <td>69</td>\n",
       "      <td>fabia</td>\n",
       "      <td>90000</td>\n",
       "      <td>7</td>\n",
       "      <td>diesel</td>\n",
       "      <td>skoda</td>\n",
       "      <td>no</td>\n",
       "      <td>2016-03-31</td>\n",
       "      <td>60437</td>\n",
       "      <td>2016-04-06 10:17:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2016-04-04 17:36:00</td>\n",
       "      <td>BMW_316i___e36_Limousine___Bastlerfahrzeug__Ex...</td>\n",
       "      <td>private</td>\n",
       "      <td>offer</td>\n",
       "      <td>650</td>\n",
       "      <td>test</td>\n",
       "      <td>limousine</td>\n",
       "      <td>1995</td>\n",
       "      <td>manual</td>\n",
       "      <td>102</td>\n",
       "      <td>3er</td>\n",
       "      <td>150000</td>\n",
       "      <td>10</td>\n",
       "      <td>petrol</td>\n",
       "      <td>bmw</td>\n",
       "      <td>yes</td>\n",
       "      <td>2016-04-04</td>\n",
       "      <td>33775</td>\n",
       "      <td>2016-04-06 19:17:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2016-04-01 20:48:00</td>\n",
       "      <td>Peugeot_206_CC_110_Platinum</td>\n",
       "      <td>private</td>\n",
       "      <td>offer</td>\n",
       "      <td>2200</td>\n",
       "      <td>test</td>\n",
       "      <td>cabrio</td>\n",
       "      <td>2004</td>\n",
       "      <td>manual</td>\n",
       "      <td>109</td>\n",
       "      <td>2_reihe</td>\n",
       "      <td>150000</td>\n",
       "      <td>8</td>\n",
       "      <td>petrol</td>\n",
       "      <td>peugeot</td>\n",
       "      <td>no</td>\n",
       "      <td>2016-04-01</td>\n",
       "      <td>67112</td>\n",
       "      <td>2016-04-05 18:18:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2016-03-21 18:54:00</td>\n",
       "      <td>VW_Derby_Bj_80__Scheunenfund</td>\n",
       "      <td>private</td>\n",
       "      <td>offer</td>\n",
       "      <td>0</td>\n",
       "      <td>test</td>\n",
       "      <td>limousine</td>\n",
       "      <td>1980</td>\n",
       "      <td>manual</td>\n",
       "      <td>50</td>\n",
       "      <td>others</td>\n",
       "      <td>40000</td>\n",
       "      <td>7</td>\n",
       "      <td>petrol</td>\n",
       "      <td>volkswagen</td>\n",
       "      <td>no</td>\n",
       "      <td>2016-03-21</td>\n",
       "      <td>19348</td>\n",
       "      <td>2016-03-25 16:47:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>260960</th>\n",
       "      <td>2016-03-19 19:53:00</td>\n",
       "      <td>turbo_defekt</td>\n",
       "      <td>private</td>\n",
       "      <td>offer</td>\n",
       "      <td>3200</td>\n",
       "      <td>control</td>\n",
       "      <td>limousine</td>\n",
       "      <td>2004</td>\n",
       "      <td>manual</td>\n",
       "      <td>225</td>\n",
       "      <td>leon</td>\n",
       "      <td>150000</td>\n",
       "      <td>5</td>\n",
       "      <td>petrol</td>\n",
       "      <td>seat</td>\n",
       "      <td>yes</td>\n",
       "      <td>2016-03-19</td>\n",
       "      <td>96465</td>\n",
       "      <td>2016-03-19 20:44:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>260961</th>\n",
       "      <td>2016-03-27 20:36:00</td>\n",
       "      <td>Opel_Zafira_1.6_Elegance_TÜV_12/16</td>\n",
       "      <td>private</td>\n",
       "      <td>offer</td>\n",
       "      <td>1150</td>\n",
       "      <td>control</td>\n",
       "      <td>bus</td>\n",
       "      <td>2000</td>\n",
       "      <td>manual</td>\n",
       "      <td>0</td>\n",
       "      <td>zafira</td>\n",
       "      <td>150000</td>\n",
       "      <td>3</td>\n",
       "      <td>petrol</td>\n",
       "      <td>opel</td>\n",
       "      <td>no</td>\n",
       "      <td>2016-03-27</td>\n",
       "      <td>26624</td>\n",
       "      <td>2016-03-29 10:17:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>260962</th>\n",
       "      <td>2016-03-05 19:56:00</td>\n",
       "      <td>Smart_smart_leistungssteigerung_100ps</td>\n",
       "      <td>private</td>\n",
       "      <td>offer</td>\n",
       "      <td>1199</td>\n",
       "      <td>test</td>\n",
       "      <td>cabrio</td>\n",
       "      <td>2000</td>\n",
       "      <td>automatic</td>\n",
       "      <td>101</td>\n",
       "      <td>fortwo</td>\n",
       "      <td>125000</td>\n",
       "      <td>3</td>\n",
       "      <td>petrol</td>\n",
       "      <td>smart</td>\n",
       "      <td>no</td>\n",
       "      <td>2016-03-05</td>\n",
       "      <td>26135</td>\n",
       "      <td>2016-03-11 18:17:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>260963</th>\n",
       "      <td>2016-03-19 18:57:00</td>\n",
       "      <td>Volkswagen_Multivan_T4_TDI_7DC_UY2</td>\n",
       "      <td>private</td>\n",
       "      <td>offer</td>\n",
       "      <td>9200</td>\n",
       "      <td>test</td>\n",
       "      <td>bus</td>\n",
       "      <td>1996</td>\n",
       "      <td>manual</td>\n",
       "      <td>102</td>\n",
       "      <td>transporter</td>\n",
       "      <td>150000</td>\n",
       "      <td>3</td>\n",
       "      <td>diesel</td>\n",
       "      <td>volkswagen</td>\n",
       "      <td>no</td>\n",
       "      <td>2016-03-19</td>\n",
       "      <td>87439</td>\n",
       "      <td>2016-04-07 07:15:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>260964</th>\n",
       "      <td>2016-03-07 19:39:00</td>\n",
       "      <td>BMW_M135i_vollausgestattet_NP_52.720____Euro</td>\n",
       "      <td>private</td>\n",
       "      <td>offer</td>\n",
       "      <td>28990</td>\n",
       "      <td>control</td>\n",
       "      <td>limousine</td>\n",
       "      <td>2013</td>\n",
       "      <td>manual</td>\n",
       "      <td>320</td>\n",
       "      <td>m_reihe</td>\n",
       "      <td>50000</td>\n",
       "      <td>8</td>\n",
       "      <td>petrol</td>\n",
       "      <td>bmw</td>\n",
       "      <td>no</td>\n",
       "      <td>2016-03-07</td>\n",
       "      <td>73326</td>\n",
       "      <td>2016-03-22 03:17:00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>260837 rows × 19 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               dateCrawled                                               name  \\\n",
       "0      2016-03-17 16:54:00                                 GOLF_4_1_4__3TÜRER   \n",
       "1      2016-03-31 17:25:00                     Skoda_Fabia_1.4_TDI_PD_Classic   \n",
       "2      2016-04-04 17:36:00  BMW_316i___e36_Limousine___Bastlerfahrzeug__Ex...   \n",
       "3      2016-04-01 20:48:00                        Peugeot_206_CC_110_Platinum   \n",
       "4      2016-03-21 18:54:00                       VW_Derby_Bj_80__Scheunenfund   \n",
       "...                    ...                                                ...   \n",
       "260960 2016-03-19 19:53:00                                       turbo_defekt   \n",
       "260961 2016-03-27 20:36:00                 Opel_Zafira_1.6_Elegance_TÜV_12/16   \n",
       "260962 2016-03-05 19:56:00              Smart_smart_leistungssteigerung_100ps   \n",
       "260963 2016-03-19 18:57:00                 Volkswagen_Multivan_T4_TDI_7DC_UY2   \n",
       "260964 2016-03-07 19:39:00       BMW_M135i_vollausgestattet_NP_52.720____Euro   \n",
       "\n",
       "         seller offerType  price   abtest vehicleType  yearOfRegistration  \\\n",
       "0       private     offer   1500     test   small car                2001   \n",
       "1       private     offer   3600     test   small car                2008   \n",
       "2       private     offer    650     test   limousine                1995   \n",
       "3       private     offer   2200     test      cabrio                2004   \n",
       "4       private     offer      0     test   limousine                1980   \n",
       "...         ...       ...    ...      ...         ...                 ...   \n",
       "260960  private     offer   3200  control   limousine                2004   \n",
       "260961  private     offer   1150  control         bus                2000   \n",
       "260962  private     offer   1199     test      cabrio                2000   \n",
       "260963  private     offer   9200     test         bus                1996   \n",
       "260964  private     offer  28990  control   limousine                2013   \n",
       "\n",
       "          gearbox  powerPS        model  kilometer  monthOfRegistration  \\\n",
       "0          manual       75         golf     150000                    6   \n",
       "1          manual       69        fabia      90000                    7   \n",
       "2          manual      102          3er     150000                   10   \n",
       "3          manual      109      2_reihe     150000                    8   \n",
       "4          manual       50       others      40000                    7   \n",
       "...           ...      ...          ...        ...                  ...   \n",
       "260960     manual      225         leon     150000                    5   \n",
       "260961     manual        0       zafira     150000                    3   \n",
       "260962  automatic      101       fortwo     125000                    3   \n",
       "260963     manual      102  transporter     150000                    3   \n",
       "260964     manual      320      m_reihe      50000                    8   \n",
       "\n",
       "       fuelType       brand notRepairedDamage dateCreated  postalCode  \\\n",
       "0        petrol  volkswagen                no  2016-03-17       91074   \n",
       "1        diesel       skoda                no  2016-03-31       60437   \n",
       "2        petrol         bmw               yes  2016-04-04       33775   \n",
       "3        petrol     peugeot                no  2016-04-01       67112   \n",
       "4        petrol  volkswagen                no  2016-03-21       19348   \n",
       "...         ...         ...               ...         ...         ...   \n",
       "260960   petrol        seat               yes  2016-03-19       96465   \n",
       "260961   petrol        opel                no  2016-03-27       26624   \n",
       "260962   petrol       smart                no  2016-03-05       26135   \n",
       "260963   diesel  volkswagen                no  2016-03-19       87439   \n",
       "260964   petrol         bmw                no  2016-03-07       73326   \n",
       "\n",
       "                  lastSeen  \n",
       "0      2016-03-17 17:40:00  \n",
       "1      2016-04-06 10:17:00  \n",
       "2      2016-04-06 19:17:00  \n",
       "3      2016-04-05 18:18:00  \n",
       "4      2016-03-25 16:47:00  \n",
       "...                    ...  \n",
       "260960 2016-03-19 20:44:00  \n",
       "260961 2016-03-29 10:17:00  \n",
       "260962 2016-03-11 18:17:00  \n",
       "260963 2016-04-07 07:15:00  \n",
       "260964 2016-03-22 03:17:00  \n",
       "\n",
       "[260837 rows x 19 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "car_analysis['dateCrawled'] = pd.to_datetime(car_analysis['dateCrawled'])\n",
    "car_analysis['lastSeen'] = pd.to_datetime(car_analysis['lastSeen'])\n",
    "car_analysis['dateCreated'] = pd.to_datetime(car_analysis['dateCreated'])\n",
    "car_analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Index: 260837 entries, 0 to 260964\n",
      "Data columns (total 19 columns):\n",
      " #   Column               Non-Null Count   Dtype         \n",
      "---  ------               --------------   -----         \n",
      " 0   dateCrawled          260837 non-null  datetime64[ns]\n",
      " 1   name                 260837 non-null  object        \n",
      " 2   seller               260837 non-null  object        \n",
      " 3   offerType            260837 non-null  object        \n",
      " 4   price                260837 non-null  int64         \n",
      " 5   abtest               260837 non-null  object        \n",
      " 6   vehicleType          260837 non-null  object        \n",
      " 7   yearOfRegistration   260837 non-null  int64         \n",
      " 8   gearbox              260837 non-null  object        \n",
      " 9   powerPS              260837 non-null  int64         \n",
      " 10  model                260837 non-null  object        \n",
      " 11  kilometer            260837 non-null  int64         \n",
      " 12  monthOfRegistration  260837 non-null  int64         \n",
      " 13  fuelType             260837 non-null  object        \n",
      " 14  brand                260837 non-null  object        \n",
      " 15  notRepairedDamage    260837 non-null  object        \n",
      " 16  dateCreated          260837 non-null  datetime64[ns]\n",
      " 17  postalCode           260837 non-null  int64         \n",
      " 18  lastSeen             260837 non-null  datetime64[ns]\n",
      "dtypes: datetime64[ns](3), int64(6), object(10)\n",
      "memory usage: 39.8+ MB\n"
     ]
    }
   ],
   "source": [
    "car_analysis.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "What is the average price of cars per analysis. Average price sets as benchmark for pricing strategies to prove accurate pricing "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Ghc 8210.055272066464\n"
     ]
    }
   ],
   "source": [
    "average_price_of_cars = car_analysis['price'].mean()\n",
    "print('Ghc',average_price_of_cars)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['dateCrawled', 'name', 'seller', 'offerType', 'price', 'abtest',\n",
       "       'vehicleType', 'yearOfRegistration', 'gearbox', 'powerPS', 'model',\n",
       "       'kilometer', 'monthOfRegistration', 'fuelType', 'brand',\n",
       "       'notRepairedDamage', 'dateCreated', 'postalCode', 'lastSeen'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "car_analysis.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Car Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "model\n",
       "golf               20958\n",
       "others             20288\n",
       "3er                15637\n",
       "polo                8824\n",
       "corsa               8259\n",
       "                   ...  \n",
       "i3                     5\n",
       "rangerover             4\n",
       "samara                 3\n",
       "serie_3                3\n",
       "discovery_sport        1\n",
       "Name: count, Length: 250, dtype: int64"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "car_analysis['model'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "model\n",
       "golf               20958\n",
       "others             20288\n",
       "3er                15637\n",
       "polo                8824\n",
       "corsa               8259\n",
       "                   ...  \n",
       "i3                     5\n",
       "rangerover             4\n",
       "samara                 3\n",
       "serie_3                3\n",
       "discovery_sport        1\n",
       "Name: count, Length: 250, dtype: int64"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "car_analysis['model'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "labels = car_analysis[\"model\"][:40].value_counts().index\n",
    "sizes = car_analysis[\"model\"][:40].value_counts()\n",
    "#colors = ['#ff9999','#66b3ff','#99ff99','#ffcc99',\"pink\",\"yellow\"]\n",
    "plt.figure(figsize = (8,8))\n",
    "plt.pie(sizes, labels=labels, rotatelabels=False, autopct='%1.1f%%',shadow=True, startangle=45)\n",
    "plt.title('MODEL',color = 'red',fontsize = 15)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Car Model\n",
    "Observation of the graph shows others as most appearannce among the car models"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Manual and Automatic"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "gearbox\n",
       "manual       199964\n",
       "automatic     60873\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "car_analysis['gearbox'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "gearbox    name                                              \n",
       "automatic  Volkswagen_Golf_2.0_GTI_DSG                           136\n",
       "           Audi_A6_Avant_3.0_TDI_DPF_quattro_tiptronic           127\n",
       "           BMW_525d_Touring_Aut.                                 124\n",
       "           BMW_525d_Aut.                                         111\n",
       "           Audi_A6_Avant_2.5_TDI                                 109\n",
       "                                                                ... \n",
       "manual     »Sommerauto«_Opel_Astra_F_Cabrio_\"Bertone_Edition\"      1\n",
       "           »TWINGO_1.2«                                            1\n",
       "           »_TWINGO_«                                              1\n",
       "           »_gepflegter_VW_Passat_3c_TDI_abzugeben__!              1\n",
       "           Über_ein_Jahr_fahrspass_mit_faltdach                    1\n",
       "Name: count, Length: 153042, dtype: int64"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "car_analysis.groupby('gearbox')['name'].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Percentage of manual and automatic cars"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "gearbox\n",
       "automatic     60873\n",
       "manual       199964\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "car_analysis['gearbox'].value_counts().sort_values()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1400x700 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(14, 7))\n",
    "labels=['Automatic', 'Manuel']\n",
    "plt.pie(car_analysis['gearbox'].value_counts().sort_values(),labels=labels,explode=[0.1,0.1],\n",
    "        autopct='%1.2f%%',colors=['lightgray','cyan'], startangle=90)\n",
    "plt.title('GEARBOX')\n",
    "#plt.axis('equal')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Year Of Registration and Year Counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "yearOfRegistration  name                                                             \n",
       "1910                Charleston_Pick_Up_Ente_2CV                                          1\n",
       "                    Mercedes_Diesel_W_201                                                1\n",
       "                    SUCHE_MERCEDES_BENZ_GL_LPG                                           1\n",
       "1919                Ford_Model_T_1919                                                    1\n",
       "1923                Citroën_C3                                                           1\n",
       "                                                                                        ..\n",
       "2017                bmw_523i_tip_tronik_multifunktions_lenkrad_ahk_abnehmbar             1\n",
       "                    bmw_523i_tip_tronik_multifunktions_lenkrad_ahk_abnehmbar_tempomat    1\n",
       "2018                Bmw_e36_318ti_Compact_TÜV_NEU                                        1\n",
       "                    VW_Polo_1_4_9N_silbermet._TDI                                        1\n",
       "                    VW_Polo_9N_1.2_Klima_Sitzheizung_TÜV_NEU_2.Hand                      1\n",
       "Name: count, Length: 177907, dtype: int64"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "car_analysis.groupby('yearOfRegistration')['name'].value_counts()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Car counts based on models per year"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "72444     1910\n",
       "101440    1910\n",
       "199636    1910\n",
       "145718    1919\n",
       "238752    1923\n",
       "          ... \n",
       "39998     2017\n",
       "72157     2017\n",
       "174723    2018\n",
       "60899     2018\n",
       "117509    2018\n",
       "Name: yearOfRegistration, Length: 260837, dtype: int64"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "car_analysis['yearOfRegistration'].sort_values()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "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>yearOfRegistration</th>\n",
       "      <th>model</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>2006</td>\n",
       "      <td>16797</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>1999</td>\n",
       "      <td>16086</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>2005</td>\n",
       "      <td>15951</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>2004</td>\n",
       "      <td>15703</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>2003</td>\n",
       "      <td>15555</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1933</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>1947</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1929</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>1948</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1919</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>89 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    yearOfRegistration  model\n",
       "76                2006  16797\n",
       "69                1999  16086\n",
       "75                2005  15951\n",
       "74                2004  15703\n",
       "73                2003  15555\n",
       "..                 ...    ...\n",
       "7                 1933      1\n",
       "17                1947      1\n",
       "3                 1929      1\n",
       "18                1948      1\n",
       "1                 1919      1\n",
       "\n",
       "[89 rows x 2 columns]"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
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   "source": [
    "cars_by_model_year = car_analysis.groupby('yearOfRegistration')['model'].count().reset_index().sort_values('model',ascending = False)\n",
    "cars_by_model_year = cars_by_model_year[cars_by_model_year['yearOfRegistration'] >= 2001]\n",
    "fig = px.bar(cars_by_model_year, x='yearOfRegistration', y='model')\n",
    "fig.show()"
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  {
   "cell_type": "code",
   "execution_count": null,
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",
      "text/plain": [
       "<Figure size 800x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "labels = car_analysis[\"yearOfRegistration\"][:40].value_counts().index\n",
    "sizes = car_analysis[\"yearOfRegistration\"][:40].value_counts()\n",
    "colors = ['#ff9999','#66b3ff','#99ff99','#ffcc99',\"pink\",\"yellow\"]\n",
    "plt.figure(figsize = (8,8))\n",
    "plt.pie(sizes, labels=labels, rotatelabels=False, autopct='%1.1f%%',colors=colors,shadow=True, startangle=45)\n",
    "plt.title('Percentage of  Car Year Registration ',color = 'red',fontsize = 15)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.histplot(data=car_analysis, x=\"yearOfRegistration\", hue='gearbox')\n",
    "plt.xticks(rotation=45)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Most Common Serviced Car"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "vehicleType\n",
       "limousine        76376\n",
       "small car        59072\n",
       "station wagon    53406\n",
       "bus              24954\n",
       "cabrio           18544\n",
       "coupe            14632\n",
       "suv              12081\n",
       "others            1772\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "car_analysis['vehicleType'].value_counts()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\toy\\AppData\\Local\\Temp\\ipykernel_4604\\718345013.py:1: FutureWarning:\n",
      "\n",
      "\n",
      "\n",
      "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `x` variable to `hue` and set `legend=False` for the same effect.\n",
      "\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot( data=car_analysis, x='vehicleType' ,palette='CMRmap')\n",
    "plt.xticks(rotation=90)\n",
    "plt.xlabel('Vehicle Type', fontsize=10,color='black')\n",
    "plt.ylabel('Counts', fontsize=10, color='black')\n",
    "plt.title('VEHICLE TYPE', color=\"black\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "labels = car_analysis[\"vehicleType\"][:30].value_counts().index\n",
    "sizes = car_analysis[\"vehicleType\"][:30].value_counts()\n",
    "colors = ['#ff2499','#66b3ff','#99ff99','#ffcc99',\"green\",\"yellow\"]\n",
    "plt.figure(figsize = (8,8))\n",
    "plt.pie(sizes, labels=labels, rotatelabels=False, autopct='%1.1f%%',colors=colors,shadow=True, startangle=45)\n",
    "plt.title('PERCENTAGE OF MOST SERVICED CARS',color = 'red',fontsize = 15)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "AB TESTING"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "abtest\n",
       "test       135472\n",
       "control    125365\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#car_analysis['abtest'].isin(['test'])\n",
    "\n",
    "car_analysis.abtest.value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Fuel Type"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "fuelType\n",
       "petrol     169160\n",
       "diesel      86938\n",
       "lpg          3935\n",
       "cng           460\n",
       "hybrid        214\n",
       "other          73\n",
       "electro        57\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "car_analysis['fuelType'].value_counts()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Th Relation between gearbox and kind of fuel it accept and shows the distribution of manual and automatic cars by years."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.violinplot(data=car_analysis, x=\"yearOfRegistration\", y=\"fuelType\",hue=\"gearbox\")\n",
    "plt.legend(loc='lower left')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "name                                                                fuelType\n",
       "!!!!!!!!!!!!!!!!!!!!!!!!__GOLF_3_CABRIO___!!!!!!!!!!!!!!!!!!!!!!!   petrol      1\n",
       "!!!!!!!!!!!!!!Renault_Clio_5_Tuerig_Servolenkung_!!!!!!!!!!!!!!!!!  petrol      1\n",
       "!!!!!!!!!!!!_Seat_Toledo_1M_!!!!!!!!!!!                             petrol      1\n",
       "!!!!!!!!BMW_530D_Touring_Vollausstattung!!!!!!                      diesel      1\n",
       "!!!!!!!!_SCHROTT!!!!!!!!                                            petrol      1\n",
       "                                                                               ..\n",
       "»_gepflegter_VW_Passat_3c_TDI_abzugeben__!                          diesel      1\n",
       "Äusserst_gut_geplegtes_CLK_Cabrio                                   petrol      1\n",
       "Ökologisch___Elektrisch___Bezahlbar.__Fiat_New_500E                 electro     1\n",
       "Über_ein_Jahr_fahrspass_mit_faltdach                                petrol      1\n",
       "Übernahme_Leasingvertrag                                            petrol      1\n",
       "Name: count, Length: 151914, dtype: int64"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "car_analysis.groupby('name')['fuelType'].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The observation shows that many of the cars used petrol and are manuel based on the voilent graph declaring the results"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The table below shows most common type of fuel is petrol, followed by diesel.\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "fuelType\n",
       "petrol    169160\n",
       "diesel     86938\n",
       "lpg         3935\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "top3 = car_analysis['fuelType'].value_counts().head(3)\n",
    "top3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "labels = top3.index\n",
    "sizes = top3\n",
    "colors = ['#ff9999','#66b3ff','#99ff99','#ffcc99',\"pink\",\"yellow\"]\n",
    "plt.figure(figsize = (8,8))\n",
    "plt.pie(sizes, labels=labels, rotatelabels=False, autopct='%1.f%%',colors=colors,shadow=True, startangle=9)\n",
    "plt.title('TOP 3 FUEL TYPE PERCENTAGE USED',color = 'green',fontsize = 15)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Brand"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "brand\n",
       "volkswagen       54180\n",
       "bmw              30317\n",
       "mercedes_benz    26896\n",
       "opel             26372\n",
       "audi             24756\n",
       "ford             17434\n",
       "renault          11668\n",
       "peugeot           7845\n",
       "fiat              6361\n",
       "seat              5017\n",
       "skoda             4534\n",
       "mazda             4035\n",
       "toyota            3704\n",
       "citroen           3688\n",
       "nissan            3592\n",
       "smart             3350\n",
       "mini              2877\n",
       "hyundai           2785\n",
       "volvo             2588\n",
       "mitsubishi        2075\n",
       "kia               1966\n",
       "honda             1946\n",
       "porsche           1866\n",
       "alfa_romeo        1704\n",
       "suzuki            1679\n",
       "chevrolet         1348\n",
       "chrysler          1025\n",
       "dacia              723\n",
       "land_rover         636\n",
       "jeep               616\n",
       "subaru             550\n",
       "daihatsu           520\n",
       "jaguar             487\n",
       "saab               421\n",
       "daewoo             337\n",
       "lancia             320\n",
       "rover              262\n",
       "trabant            211\n",
       "lada               146\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "car_analysis['brand'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    volkswagen\n",
       "1         skoda\n",
       "2           bmw\n",
       "3       peugeot\n",
       "4    volkswagen\n",
       "5         mazda\n",
       "6    volkswagen\n",
       "7        nissan\n",
       "8       renault\n",
       "9          ford\n",
       "Name: brand, dtype: object"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "top10 =  car_analysis.brand.head(10)\n",
    "top10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 800x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "labels = top10.value_counts().index\n",
    "sizes = top10.value_counts()\n",
    "colors = ['#ff9999','#66b3ff','#99ff99','#ffcc99',\"pink\",\"yellow\"]\n",
    "plt.figure(figsize = (8,8))\n",
    "plt.pie(sizes, labels=labels, rotatelabels=False, autopct='%1.f%%',colors=colors,shadow=True, startangle=9)\n",
    "plt.title('TOP 10 BRAND',color = 'black',fontsize = 15)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Numbers of cars per brand ,first 10 cars"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "plotlyServerURL": "https://plot.ly"
       },
       "data": [
        {
         "alignmentgroup": "True",
         "hovertemplate": "brand=%{x}<br>model=%{y}<extra></extra>",
         "legendgroup": "",
         "marker": {
          "color": "#636efa",
          "pattern": {
           "shape": ""
          }
         },
         "name": "",
         "offsetgroup": "",
         "orientation": "v",
         "showlegend": false,
         "textposition": "auto",
         "type": "bar",
         "x": [
          "volkswagen",
          "bmw",
          "mercedes_benz",
          "opel",
          "audi",
          "ford",
          "renault",
          "peugeot",
          "fiat",
          "seat"
         ],
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         ],
         "yaxis": "y"
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        "margin": {
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            },
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          "heatmapgl": [
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            "type": "mesh3d"
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          "scatter": [
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   "source": [
    "cars_per_brand = car_analysis.groupby('brand')['model'].count().reset_index().sort_values('model',ascending = False).head(10)\n",
    "fig = px.bar(cars_per_brand, x='brand', y='model')\n",
    "fig.show()"
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  },
  {
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    "Result And Observation \n",
    "Most Serviced Car was limousine, then small car ,bus and station wagon \n",
    "Most of the cars serviced are mostly manual than automatic each time a car is serviced based on the years and overall as well \n",
    "Mercedes Bens and Audi are the most expensive cars with almost similar prices Volkswagen brand was most serviced car over other brands"
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