Data_cleaning_R8106_Seher.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "323e2584-4db9-470a-9f3f-017d7d91ff6a",
   "metadata": {},
   "source": [
    "\n",
    "\n",
    "AUTOSCOUT Project\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 142,
   "id": "2a4aaa62-7940-4035-9806-626d2f383252",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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      "               make_model         short_description               make  \\\n",
      "0     Mercedes-Benz A 160                       CDi  \\nMercedes-Benz\\n   \n",
      "1   Mercedes-Benz EQE 350                      350+  \\nMercedes-Benz\\n   \n",
      "2  Mercedes-Benz A 45 AMG          S 4Matic+ 8G-DCT  \\nMercedes-Benz\\n   \n",
      "3  Mercedes-Benz A 35 AMG            4Matic+ 7G-DCT  \\nMercedes-Benz\\n   \n",
      "4  Mercedes-Benz A 45 AMG  200CDI BE Line 4M 7G-DCT  \\nMercedes-Benz\\n   \n",
      "\n",
      "                model                                           location  \\\n",
      "0     [\\n, A 160 ,\\n]  P.I. EL PALMAR C/FORJA 6,  11500 PUERTO DE SAN...   \n",
      "1   [\\n, EQE 350 ,\\n]       APARTADO DE CORREOS 1032,  26140 LOGROÑO, ES   \n",
      "2  [\\n, A 45 AMG ,\\n]  PORT. TARRACO, MOLL DE LLEVANT, Nº 5, LOC. 6-8...   \n",
      "3  [\\n, A 35 AMG ,\\n]  Carrer de Provença, 31 Local,  8029 BARCELONA, ES   \n",
      "4  [\\n, A 45 AMG ,\\n]             CARRIL ARAGONES 4,  30007 CASILLAS, ES   \n",
      "\n",
      "        price          Body type                      Type        Doors  \\\n",
      "0  € 16,950.-  [\\n, Compact, \\n]            [\\n, Used, \\n]  [\\n, 5, \\n]   \n",
      "1  € 80,900.-  [\\n, Compact, \\n]  [\\n, Pre-registered, \\n]  [\\n, 4, \\n]   \n",
      "2  € 69,900.-  [\\n, Compact, \\n]            [\\n, Used, \\n]  [\\n, 5, \\n]   \n",
      "3  € 46,990.-  [\\n, Compact, \\n]            [\\n, Used, \\n]  [\\n, 5, \\n]   \n",
      "4  € 16,800.-  [\\n, Compact, \\n]            [\\n, Used, \\n]  [\\n, 5, \\n]   \n",
      "\n",
      "   Country version       Offer number             Warranty     Mileage  \\\n",
      "0  [\\n, Spain, \\n]  [\\n, 7468157, \\n]  [\\n, 24 months, \\n]  120,200 km   \n",
      "1  [\\n, Spain, \\n]  [\\n, 7054863, \\n]  [\\n, 24 months, \\n]    5,000 km   \n",
      "2  [\\n, Spain, \\n]  [\\n, 7410454, \\n]  [\\n, 12 months, \\n]   18,900 km   \n",
      "3  [\\n, Spain, \\n]  [\\n, 7464503, \\n]  [\\n, 12 months, \\n]   18,995 km   \n",
      "4  [\\n, Spain, \\n]  [\\n, 7127931, \\n]  [\\n, 12 months, \\n]  197,000 km   \n",
      "\n",
      "  First registration          Gearbox Fuel type  Colour     Paint  \\\n",
      "0            06/2016     [\\nManual\\n]    Diesel   Black  Metallic   \n",
      "1            06/2022  [\\nAutomatic\\n]  Electric     NaN       NaN   \n",
      "2            07/2020  [\\nAutomatic\\n]  Gasoline    Grey       NaN   \n",
      "3            01/2020  [\\nAutomatic\\n]  Gasoline  Yellow       NaN   \n",
      "4            09/2015  [\\nAutomatic\\n]    Diesel   White  Metallic   \n",
      "\n",
      "                                                desc  seller        Seats  \\\n",
      "0  [ , Precio al contado: 16950 euros,  ,  , Vehí...  Dealer          NaN   \n",
      "1  [ , Precio al contado: 88900 euros,  , AUTO OJ...  Dealer  [\\n, 5, \\n]   \n",
      "2  [Gris MANUFAKTUR mountaingrau magno,  , Linea/...  Dealer  [\\n, 5, \\n]   \n",
      "3  [ , Precio al contado: 48990 euros,  ,  , BONI...  Dealer  [\\n, 5, \\n]   \n",
      "4  [ , Precio al contado: 17400 euros,  , Vehícul...  Dealer  [\\n, 5, \\n]   \n",
      "\n",
      "                   Power     Engine size    Gears   CO₂-emissions  \\\n",
      "0                    NaN             NaN      NaN             NaN   \n",
      "1  [\\n215 kW (292 hp)\\n]      [\\n1 cc\\n]  [\\n9\\n]  0 g/km (comb.)   \n",
      "2  [\\n310 kW (421 hp)\\n]  [\\n1,991 cc\\n]  [\\n8\\n]             NaN   \n",
      "3  [\\n225 kW (306 hp)\\n]  [\\n1,991 cc\\n]  [\\n7\\n]             NaN   \n",
      "4  [\\n100 kW (136 hp)\\n]  [\\n2,143 cc\\n]  [\\n7\\n]             NaN   \n",
      "\n",
      "  Manufacturer colour     Drivetrain Cylinders  \\\n",
      "0                 NaN            NaN       NaN   \n",
      "1     Negro Obsidiana            NaN       NaN   \n",
      "2  Mountaingrau magno  [\\n, 4WD, \\n]   [\\n4\\n]   \n",
      "3        Amarillo Sol  [\\n, 4WD, \\n]   [\\n4\\n]   \n",
      "4                 NaN  [\\n, 4WD, \\n]   [\\n4\\n]   \n",
      "\n",
      "                                    Fuel consumption  \\\n",
      "0                                                NaN   \n",
      "1                                                NaN   \n",
      "2  [[8.4 l/100 km (comb.)], [10.9 l/100 km (city)...   \n",
      "3  [[7.3 l/100 km (comb.)], [9.3 l/100 km (city)]...   \n",
      "4  [[4.9 l/100 km (comb.)], [5.7 l/100 km (city)]...   \n",
      "\n",
      "                           \\nComfort & Convenience\\n  \\\n",
      "0                                                NaN   \n",
      "1                                                NaN   \n",
      "2                                                NaN   \n",
      "3  [Air conditioning, Automatic climate control, ...   \n",
      "4  [Air conditioning, Electrical side mirrors, Mu...   \n",
      "\n",
      "          \\nEntertainment & Media\\n  \\\n",
      "0                               NaN   \n",
      "1                               NaN   \n",
      "2                               NaN   \n",
      "3                             [USB]   \n",
      "4  [Bluetooth, CD player, MP3, USB]   \n",
      "\n",
      "                               \\nSafety & Security\\n     \\nExtras\\n  \\\n",
      "0                                                NaN            NaN   \n",
      "1                                                NaN            NaN   \n",
      "2                                                NaN            NaN   \n",
      "3  [ABS, Central door lock, Driver-side airbag, E...  [Sport seats]   \n",
      "4  [ABS, Central door lock, Driver-side airbag, E...            NaN   \n",
      "\n",
      "     Empty weight Model code General inspection Last service  \\\n",
      "0             NaN        NaN                NaN          NaN   \n",
      "1             NaN        NaN                NaN          NaN   \n",
      "2             NaN        NaN                NaN          NaN   \n",
      "3             NaN        NaN                NaN          NaN   \n",
      "4  [\\n1,545 kg\\n]        NaN                NaN          NaN   \n",
      "\n",
      "  Full service history Non-smoker vehicle Emission class Emissions sticker  \\\n",
      "0                  NaN                NaN            NaN               NaN   \n",
      "1                  NaN                NaN            NaN               NaN   \n",
      "2                  NaN                NaN            NaN               NaN   \n",
      "3                  NaN                NaN            NaN               NaN   \n",
      "4                  NaN                NaN            NaN               NaN   \n",
      "\n",
      "  Upholstery colour Upholstery  Production date Previous owner  \\\n",
      "0               NaN        NaN              NaN            NaN   \n",
      "1               NaN        NaN              NaN            NaN   \n",
      "2               NaN        NaN              NaN            NaN   \n",
      "3               NaN        NaN              NaN            NaN   \n",
      "4               NaN        NaN              NaN            NaN   \n",
      "\n",
      "  Other fuel types Power consumption Energy efficiency class CO₂-efficiency  \\\n",
      "0              NaN               NaN                     NaN            NaN   \n",
      "1              NaN               NaN                     NaN            NaN   \n",
      "2              NaN               NaN                     NaN            NaN   \n",
      "3              NaN               NaN                     NaN            NaN   \n",
      "4              NaN               NaN                     NaN            NaN   \n",
      "\n",
      "  Fuel consumption (WLTP) CO₂-emissions (WLTP) Available from  \\\n",
      "0                     NaN                  NaN            NaN   \n",
      "1                     NaN                  NaN            NaN   \n",
      "2                     NaN                  NaN            NaN   \n",
      "3                     NaN                  NaN            NaN   \n",
      "4                     NaN                  NaN            NaN   \n",
      "\n",
      "  Taxi or rental car Availability Last timing belt change  \\\n",
      "0                NaN          NaN                     NaN   \n",
      "1                NaN          NaN                     NaN   \n",
      "2                NaN          NaN                     NaN   \n",
      "3                NaN          NaN                     NaN   \n",
      "4                NaN          NaN                     NaN   \n",
      "\n",
      "  Electric Range (WLTP) Power consumption (WLTP) Battery Ownership  \n",
      "0                   NaN                      NaN               NaN  \n",
      "1                   NaN                      NaN               NaN  \n",
      "2                   NaN                      NaN               NaN  \n",
      "3                   NaN                      NaN               NaN  \n",
      "4                   NaN                      NaN               NaN  \n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 29480 entries, 0 to 29479\n",
      "Data columns (total 58 columns):\n",
      " #   Column                    Non-Null Count  Dtype  \n",
      "---  ------                    --------------  -----  \n",
      " 0   make_model                28630 non-null  object \n",
      " 1   short_description         28630 non-null  object \n",
      " 2   make                      28630 non-null  object \n",
      " 3   model                     28630 non-null  object \n",
      " 4   location                  28630 non-null  object \n",
      " 5   price                     28630 non-null  object \n",
      " 6   Body type                 28630 non-null  object \n",
      " 7   Type                      28630 non-null  object \n",
      " 8   Doors                     28271 non-null  object \n",
      " 9   Country version           16889 non-null  object \n",
      " 10  Offer number              23100 non-null  object \n",
      " 11  Warranty                  15784 non-null  object \n",
      " 12  Mileage                   28629 non-null  object \n",
      " 13  First registration        28628 non-null  object \n",
      " 14  Gearbox                   28382 non-null  object \n",
      " 15  Fuel type                 26843 non-null  object \n",
      " 16  Colour                    26906 non-null  object \n",
      " 17  Paint                     14495 non-null  object \n",
      " 18  desc                      28047 non-null  object \n",
      " 19  seller                    28630 non-null  object \n",
      " 20  Seats                     25505 non-null  object \n",
      " 21  Power                     28058 non-null  object \n",
      " 22  Engine size               27227 non-null  object \n",
      " 23  Gears                     18954 non-null  object \n",
      " 24  CO₂-emissions             18594 non-null  object \n",
      " 25  Manufacturer colour       21787 non-null  object \n",
      " 26  Drivetrain                16893 non-null  object \n",
      " 27  Cylinders                 18852 non-null  object \n",
      " 28  Fuel consumption          23385 non-null  object \n",
      " 29  \n",
      "Comfort & Convenience\n",
      "   25433 non-null  object \n",
      " 30  \n",
      "Entertainment & Media\n",
      "   23644 non-null  object \n",
      " 31  \n",
      "Safety & Security\n",
      "       25415 non-null  object \n",
      " 32  \n",
      "Extras\n",
      "                  23480 non-null  object \n",
      " 33  Empty weight              17758 non-null  object \n",
      " 34  Model code                8367 non-null   object \n",
      " 35  General inspection        12254 non-null  object \n",
      " 36  Last service              2003 non-null   object \n",
      " 37  Full service history      12565 non-null  object \n",
      " 38  Non-smoker vehicle        11594 non-null  object \n",
      " 39  Emission class            17859 non-null  object \n",
      " 40  Emissions sticker         9414 non-null   object \n",
      " 41  Upholstery colour         14569 non-null  object \n",
      " 42  Upholstery                18610 non-null  object \n",
      " 43  Production date           5908 non-null   float64\n",
      " 44  Previous owner            14015 non-null  object \n",
      " 45  Other fuel types          2313 non-null   object \n",
      " 46  Power consumption         515 non-null    object \n",
      " 47  Energy efficiency class   7804 non-null   object \n",
      " 48  CO₂-efficiency            7804 non-null   object \n",
      " 49  Fuel consumption (WLTP)   100 non-null    object \n",
      " 50  CO₂-emissions (WLTP)      116 non-null    object \n",
      " 51  Available from            393 non-null    object \n",
      " 52  Taxi or rental car        422 non-null    object \n",
      " 53  Availability              301 non-null    object \n",
      " 54  Last timing belt change   572 non-null    object \n",
      " 55  Electric Range (WLTP)     16 non-null     object \n",
      " 56  Power consumption (WLTP)  16 non-null     object \n",
      " 57  Battery Ownership         7 non-null      object \n",
      "dtypes: float64(1), object(57)\n",
      "memory usage: 13.0+ MB\n",
      "None\n",
      "       Production date\n",
      "count          5908.00\n",
      "mean           2018.00\n",
      "std               6.49\n",
      "min            1954.00\n",
      "25%            2018.00\n",
      "50%            2019.00\n",
      "75%            2021.00\n",
      "max            2022.00\n"
     ]
    }
   ],
   "source": [
    " # Importing the libraries\n",
    "\n",
    "!pip install skimpy\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns \n",
    "import matplotlib.pyplot as plt\n",
    "from ipywidgets import interact, Dropdown, IntSlider, Output, widgets\n",
    "# from IPython.core.display import display\n",
    "from IPython.display import display\n",
    "import re\n",
    "\n",
    "from skimpy import clean_columns, skim\n",
    "# import requests\n",
    "# import geopy\n",
    "# from geopy.geocoders import Nominatim\n",
    "\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "warnings.warn(\"this will not show\")\n",
    "\n",
    "%matplotlib inline\n",
    "# %matplotlib notebook\n",
    "\n",
    "plt.rcParams[\"figure.figsize\"] = (10, 6)\n",
    "# plt.rcParams['figure.dpi'] = 100\n",
    "\n",
    "sns.set_style(\"whitegrid\")\n",
    "pd.set_option('display.float_format', lambda x: '%.2f' % x)\n",
    "\n",
    "pd.options.display.max_rows = 300\n",
    "pd.options.display.max_columns = 100\n",
    "\n",
    "# Upload the data\n",
    "df0 = pd.read_json(r\"C:\\Users\\omerk\\Desktop\\AUTOSCOUT PROJECT\\as24_cars.json\")\n",
    "df = df0.copy()\n",
    "print(df.head())\n",
    "\n",
    "# Information about data\n",
    "print(df.info())\n",
    "print(df.describe())\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 146,
   "id": "e3c2cad9-63fe-471d-96a4-538358c573e7",
   "metadata": {},
   "outputs": [
    {
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       "    .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>make_model</th>\n",
       "      <th>short_description</th>\n",
       "      <th>make</th>\n",
       "      <th>model</th>\n",
       "      <th>location</th>\n",
       "      <th>price</th>\n",
       "      <th>Body type</th>\n",
       "      <th>Type</th>\n",
       "      <th>Doors</th>\n",
       "      <th>Country version</th>\n",
       "      <th>Offer number</th>\n",
       "      <th>Warranty</th>\n",
       "      <th>Mileage</th>\n",
       "      <th>First registration</th>\n",
       "      <th>Gearbox</th>\n",
       "      <th>Fuel type</th>\n",
       "      <th>Colour</th>\n",
       "      <th>Paint</th>\n",
       "      <th>desc</th>\n",
       "      <th>seller</th>\n",
       "      <th>Seats</th>\n",
       "      <th>Power</th>\n",
       "      <th>Engine size</th>\n",
       "      <th>Gears</th>\n",
       "      <th>CO₂-emissions</th>\n",
       "      <th>Manufacturer colour</th>\n",
       "      <th>Drivetrain</th>\n",
       "      <th>Cylinders</th>\n",
       "      <th>Fuel consumption</th>\n",
       "      <th>\\nComfort &amp; Convenience\\n</th>\n",
       "      <th>\\nEntertainment &amp; Media\\n</th>\n",
       "      <th>\\nSafety &amp; Security\\n</th>\n",
       "      <th>\\nExtras\\n</th>\n",
       "      <th>Empty weight</th>\n",
       "      <th>Model code</th>\n",
       "      <th>General inspection</th>\n",
       "      <th>Last service</th>\n",
       "      <th>Full service history</th>\n",
       "      <th>Non-smoker vehicle</th>\n",
       "      <th>Emission class</th>\n",
       "      <th>Emissions sticker</th>\n",
       "      <th>Upholstery colour</th>\n",
       "      <th>Upholstery</th>\n",
       "      <th>Production date</th>\n",
       "      <th>Previous owner</th>\n",
       "      <th>Other fuel types</th>\n",
       "      <th>Power consumption</th>\n",
       "      <th>Energy efficiency class</th>\n",
       "      <th>CO₂-efficiency</th>\n",
       "      <th>Fuel consumption (WLTP)</th>\n",
       "      <th>CO₂-emissions (WLTP)</th>\n",
       "      <th>Available from</th>\n",
       "      <th>Taxi or rental car</th>\n",
       "      <th>Availability</th>\n",
       "      <th>Last timing belt change</th>\n",
       "      <th>Electric Range (WLTP)</th>\n",
       "      <th>Power consumption (WLTP)</th>\n",
       "      <th>Battery Ownership</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Mercedes-Benz A 160</td>\n",
       "      <td>CDi</td>\n",
       "      <td>\\nMercedes-Benz\\n</td>\n",
       "      <td>[\\n, A 160 ,\\n]</td>\n",
       "      <td>P.I. EL PALMAR C/FORJA 6,  11500 PUERTO DE SAN...</td>\n",
       "      <td>€ 16,950.-</td>\n",
       "      <td>[\\n, Compact, \\n]</td>\n",
       "      <td>[\\n, Used, \\n]</td>\n",
       "      <td>[\\n, 5, \\n]</td>\n",
       "      <td>[\\n, Spain, \\n]</td>\n",
       "      <td>[\\n, 7468157, \\n]</td>\n",
       "      <td>[\\n, 24 months, \\n]</td>\n",
       "      <td>120,200 km</td>\n",
       "      <td>06/2016</td>\n",
       "      <td>[\\nManual\\n]</td>\n",
       "      <td>Diesel</td>\n",
       "      <td>Black</td>\n",
       "      <td>Metallic</td>\n",
       "      <td>[ , Precio al contado: 16950 euros,  ,  , Vehí...</td>\n",
       "      <td>Dealer</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Mercedes-Benz EQE 350</td>\n",
       "      <td>350+</td>\n",
       "      <td>\\nMercedes-Benz\\n</td>\n",
       "      <td>[\\n, EQE 350 ,\\n]</td>\n",
       "      <td>APARTADO DE CORREOS 1032,  26140 LOGROÑO, ES</td>\n",
       "      <td>€ 80,900.-</td>\n",
       "      <td>[\\n, Compact, \\n]</td>\n",
       "      <td>[\\n, Pre-registered, \\n]</td>\n",
       "      <td>[\\n, 4, \\n]</td>\n",
       "      <td>[\\n, Spain, \\n]</td>\n",
       "      <td>[\\n, 7054863, \\n]</td>\n",
       "      <td>[\\n, 24 months, \\n]</td>\n",
       "      <td>5,000 km</td>\n",
       "      <td>06/2022</td>\n",
       "      <td>[\\nAutomatic\\n]</td>\n",
       "      <td>Electric</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[ , Precio al contado: 88900 euros,  , AUTO OJ...</td>\n",
       "      <td>Dealer</td>\n",
       "      <td>[\\n, 5, \\n]</td>\n",
       "      <td>[\\n215 kW (292 hp)\\n]</td>\n",
       "      <td>[\\n1 cc\\n]</td>\n",
       "      <td>[\\n9\\n]</td>\n",
       "      <td>0 g/km (comb.)</td>\n",
       "      <td>Negro Obsidiana</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Mercedes-Benz A 45 AMG</td>\n",
       "      <td>S 4Matic+ 8G-DCT</td>\n",
       "      <td>\\nMercedes-Benz\\n</td>\n",
       "      <td>[\\n, A 45 AMG ,\\n]</td>\n",
       "      <td>PORT. TARRACO, MOLL DE LLEVANT, Nº 5, LOC. 6-8...</td>\n",
       "      <td>€ 69,900.-</td>\n",
       "      <td>[\\n, Compact, \\n]</td>\n",
       "      <td>[\\n, Used, \\n]</td>\n",
       "      <td>[\\n, 5, \\n]</td>\n",
       "      <td>[\\n, Spain, \\n]</td>\n",
       "      <td>[\\n, 7410454, \\n]</td>\n",
       "      <td>[\\n, 12 months, \\n]</td>\n",
       "      <td>18,900 km</td>\n",
       "      <td>07/2020</td>\n",
       "      <td>[\\nAutomatic\\n]</td>\n",
       "      <td>Gasoline</td>\n",
       "      <td>Grey</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[Gris MANUFAKTUR mountaingrau magno,  , Linea/...</td>\n",
       "      <td>Dealer</td>\n",
       "      <td>[\\n, 5, \\n]</td>\n",
       "      <td>[\\n310 kW (421 hp)\\n]</td>\n",
       "      <td>[\\n1,991 cc\\n]</td>\n",
       "      <td>[\\n8\\n]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Mountaingrau magno</td>\n",
       "      <td>[\\n, 4WD, \\n]</td>\n",
       "      <td>[\\n4\\n]</td>\n",
       "      <td>[[8.4 l/100 km (comb.)], [10.9 l/100 km (city)...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Mercedes-Benz A 35 AMG</td>\n",
       "      <td>4Matic+ 7G-DCT</td>\n",
       "      <td>\\nMercedes-Benz\\n</td>\n",
       "      <td>[\\n, A 35 AMG ,\\n]</td>\n",
       "      <td>Carrer de Provença, 31 Local,  8029 BARCELONA, ES</td>\n",
       "      <td>€ 46,990.-</td>\n",
       "      <td>[\\n, Compact, \\n]</td>\n",
       "      <td>[\\n, Used, \\n]</td>\n",
       "      <td>[\\n, 5, \\n]</td>\n",
       "      <td>[\\n, Spain, \\n]</td>\n",
       "      <td>[\\n, 7464503, \\n]</td>\n",
       "      <td>[\\n, 12 months, \\n]</td>\n",
       "      <td>18,995 km</td>\n",
       "      <td>01/2020</td>\n",
       "      <td>[\\nAutomatic\\n]</td>\n",
       "      <td>Gasoline</td>\n",
       "      <td>Yellow</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[ , Precio al contado: 48990 euros,  ,  , BONI...</td>\n",
       "      <td>Dealer</td>\n",
       "      <td>[\\n, 5, \\n]</td>\n",
       "      <td>[\\n225 kW (306 hp)\\n]</td>\n",
       "      <td>[\\n1,991 cc\\n]</td>\n",
       "      <td>[\\n7\\n]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Amarillo Sol</td>\n",
       "      <td>[\\n, 4WD, \\n]</td>\n",
       "      <td>[\\n4\\n]</td>\n",
       "      <td>[[7.3 l/100 km (comb.)], [9.3 l/100 km (city)]...</td>\n",
       "      <td>[Air conditioning, Automatic climate control, ...</td>\n",
       "      <td>[USB]</td>\n",
       "      <td>[ABS, Central door lock, Driver-side airbag, E...</td>\n",
       "      <td>[Sport seats]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Mercedes-Benz A 45 AMG</td>\n",
       "      <td>200CDI BE Line 4M 7G-DCT</td>\n",
       "      <td>\\nMercedes-Benz\\n</td>\n",
       "      <td>[\\n, A 45 AMG ,\\n]</td>\n",
       "      <td>CARRIL ARAGONES 4,  30007 CASILLAS, ES</td>\n",
       "      <td>€ 16,800.-</td>\n",
       "      <td>[\\n, Compact, \\n]</td>\n",
       "      <td>[\\n, Used, \\n]</td>\n",
       "      <td>[\\n, 5, \\n]</td>\n",
       "      <td>[\\n, Spain, \\n]</td>\n",
       "      <td>[\\n, 7127931, \\n]</td>\n",
       "      <td>[\\n, 12 months, \\n]</td>\n",
       "      <td>197,000 km</td>\n",
       "      <td>09/2015</td>\n",
       "      <td>[\\nAutomatic\\n]</td>\n",
       "      <td>Diesel</td>\n",
       "      <td>White</td>\n",
       "      <td>Metallic</td>\n",
       "      <td>[ , Precio al contado: 17400 euros,  , Vehícul...</td>\n",
       "      <td>Dealer</td>\n",
       "      <td>[\\n, 5, \\n]</td>\n",
       "      <td>[\\n100 kW (136 hp)\\n]</td>\n",
       "      <td>[\\n2,143 cc\\n]</td>\n",
       "      <td>[\\n7\\n]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[\\n, 4WD, \\n]</td>\n",
       "      <td>[\\n4\\n]</td>\n",
       "      <td>[[4.9 l/100 km (comb.)], [5.7 l/100 km (city)]...</td>\n",
       "      <td>[Air conditioning, Electrical side mirrors, Mu...</td>\n",
       "      <td>[Bluetooth, CD player, MP3, USB]</td>\n",
       "      <td>[ABS, Central door lock, Driver-side airbag, E...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[\\n1,545 kg\\n]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <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",
       "      <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",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29475</th>\n",
       "      <td>Volvo S40</td>\n",
       "      <td>2.4i Momentum/ Airco/ NAP/ APK/ Elek. Ramen</td>\n",
       "      <td>\\nVolvo\\n</td>\n",
       "      <td>[\\n, S40 ,\\n]</td>\n",
       "      <td>Stobbeweg 6,  2461 EX TER AAR, NL</td>\n",
       "      <td>€ 5,499.-</td>\n",
       "      <td>[\\n, Sedan, \\n]</td>\n",
       "      <td>[\\n, Used, \\n]</td>\n",
       "      <td>[\\n, 4, \\n]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[\\n, 09-PF-XS, \\n]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>145,000 km</td>\n",
       "      <td>06/2004</td>\n",
       "      <td>[\\nAutomatic\\n]</td>\n",
       "      <td>Gasoline</td>\n",
       "      <td>Grey</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[Een goed rijdende auto met APK + NAP + Elektr...</td>\n",
       "      <td>Dealer</td>\n",
       "      <td>[\\n, 5, \\n]</td>\n",
       "      <td>[\\n125 kW (170 hp)\\n]</td>\n",
       "      <td>[\\n2,435 cc\\n]</td>\n",
       "      <td>[\\n5\\n]</td>\n",
       "      <td>217 g/km (comb.)</td>\n",
       "      <td>Grijs</td>\n",
       "      <td>[\\n, Front, \\n]</td>\n",
       "      <td>[\\n5\\n]</td>\n",
       "      <td>[[9.1 l/100 km (comb.)], [13.2 l/100 km (city)...</td>\n",
       "      <td>[Air conditioning, Armrest, Automatic climate ...</td>\n",
       "      <td>[On-board computer, Radio]</td>\n",
       "      <td>[ABS, Central door lock, Central door lock wit...</td>\n",
       "      <td>[Alloy wheels (16\"), Trailer hitch]</td>\n",
       "      <td>[\\n1,357 kg\\n]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>08/2023</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Yes</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Euro 4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29476</th>\n",
       "      <td>Volvo C30</td>\n",
       "      <td>1.6 D DRIVe Start/Stop R-design</td>\n",
       "      <td>\\nVolvo\\n</td>\n",
       "      <td>[\\n, C30 ,\\n]</td>\n",
       "      <td>Sur rendez-vous,  5060 Sambreville, BE</td>\n",
       "      <td>€ 7,300.-</td>\n",
       "      <td>[\\n, Sedan, \\n]</td>\n",
       "      <td>[\\n, Used, \\n]</td>\n",
       "      <td>[\\n, 3, \\n]</td>\n",
       "      <td>[\\n, Belgium, \\n]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[\\n, 13 months, \\n]</td>\n",
       "      <td>96,000 km</td>\n",
       "      <td>04/2011</td>\n",
       "      <td>[\\nManual\\n]</td>\n",
       "      <td>Diesel (Particle filter)</td>\n",
       "      <td>Grey</td>\n",
       "      <td>Metallic</td>\n",
       "      <td>[*** VOLVO C30 2011 TRES PROPRE EN PARFAIT ETA...</td>\n",
       "      <td>Dealer</td>\n",
       "      <td>[\\n, 4, \\n]</td>\n",
       "      <td>[\\n84 kW (114 hp)\\n]</td>\n",
       "      <td>[\\n1,560 cc\\n]</td>\n",
       "      <td>[\\n6\\n]</td>\n",
       "      <td>99 g/km (comb.)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[\\n, Front, \\n]</td>\n",
       "      <td>[\\n4\\n]</td>\n",
       "      <td>[[3.8 l/100 km (comb.)], [4.3 l/100 km (city)]...</td>\n",
       "      <td>[Air conditioning, Armrest, Automatic climate ...</td>\n",
       "      <td>[Bluetooth, CD player, Hands-free equipment, M...</td>\n",
       "      <td>[ABS, Alarm system, Central door lock with rem...</td>\n",
       "      <td>[Alloy wheels, Automatically dimming interior ...</td>\n",
       "      <td>[\\n1,356 kg\\n]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Yes</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Euro 5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Black</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[[96,000 km, 04/2011], 1]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29477</th>\n",
       "      <td>Volvo S90</td>\n",
       "      <td>T5 AUT(8) MOMENTUM BUSINESS SCHUIFDAK 360GR CA...</td>\n",
       "      <td>\\nVolvo\\n</td>\n",
       "      <td>[\\n, S90 ,\\n]</td>\n",
       "      <td>Bergambachterstraat 5,  2871 JB SCHOONHOVEN, NL</td>\n",
       "      <td>€ 29,900.-</td>\n",
       "      <td>[\\n, Sedan, \\n]</td>\n",
       "      <td>[\\n, Used, \\n]</td>\n",
       "      <td>[\\n, 4, \\n]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[\\n, 2791, \\n]</td>\n",
       "      <td>[\\n, 12 months, \\n]</td>\n",
       "      <td>94,343 km</td>\n",
       "      <td>11/2017</td>\n",
       "      <td>[\\nAutomatic\\n]</td>\n",
       "      <td>Gasoline</td>\n",
       "      <td>Blue</td>\n",
       "      <td>Metallic</td>\n",
       "      <td>[Bekijk deze auto in unieke 360 graden present...</td>\n",
       "      <td>Dealer</td>\n",
       "      <td>[\\n, 5, \\n]</td>\n",
       "      <td>[\\n187 kW (254 hp)\\n]</td>\n",
       "      <td>[\\n1,969 cc\\n]</td>\n",
       "      <td>[\\n8\\n]</td>\n",
       "      <td>149 g/km (comb.)</td>\n",
       "      <td>Denim Blue metallic (blauw met</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[\\n4\\n]</td>\n",
       "      <td>[[6.5 l/100 km (comb.)], [8.6 l/100 km (city)]...</td>\n",
       "      <td>[Air conditioning, Armrest, Automatic climate ...</td>\n",
       "      <td>[Android Auto, Apple CarPlay, Bluetooth, Hands...</td>\n",
       "      <td>[Adaptive Cruise Control, Adaptive headlights,...</td>\n",
       "      <td>[Alloy wheels (18\"), Automatically dimming int...</td>\n",
       "      <td>[\\n1,617 kg\\n]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>New</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Yes</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Euro 6</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Other</td>\n",
       "      <td>Full leather</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29478</th>\n",
       "      <td>Volvo S80</td>\n",
       "      <td>2.9 Executive G. NETTE AUTO! LEER! NAVI! CRUIS...</td>\n",
       "      <td>\\nVolvo\\n</td>\n",
       "      <td>[\\n, S80 ,\\n]</td>\n",
       "      <td>Lage Ham 106,  5102 AE DONGEN, NL</td>\n",
       "      <td>€ 4,440.-</td>\n",
       "      <td>[\\n, Sedan, \\n]</td>\n",
       "      <td>[\\n, Used, \\n]</td>\n",
       "      <td>[\\n, 4, \\n]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[\\n, 43-JR-LR, \\n]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>230,047 km</td>\n",
       "      <td>07/2002</td>\n",
       "      <td>[\\nAutomatic\\n]</td>\n",
       "      <td>Super 95</td>\n",
       "      <td>Grey</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[YOUNGTIMER !, Bedrijfsinformatie, NEEM VOOR U...</td>\n",
       "      <td>Dealer</td>\n",
       "      <td>[\\n, 5, \\n]</td>\n",
       "      <td>[\\n147 kW (200 hp)\\n]</td>\n",
       "      <td>[\\n2,922 cc\\n]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>251 g/km (comb.)</td>\n",
       "      <td>Grijs</td>\n",
       "      <td>[\\n, Front, \\n]</td>\n",
       "      <td>[\\n6\\n]</td>\n",
       "      <td>[[10.4 l/100 km (comb.)], [15.3 l/100 km (city...</td>\n",
       "      <td>[Air conditioning, Armrest, Cruise control, El...</td>\n",
       "      <td>[On-board computer]</td>\n",
       "      <td>[ABS, Alarm system, Central door lock, Central...</td>\n",
       "      <td>[Alloy wheels, Automatically dimming interior ...</td>\n",
       "      <td>[\\n1,573 kg\\n]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>05/2023</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Euro 3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Beige</td>\n",
       "      <td>Full leather</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[[230,047 km, 07/2002], 5]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29479</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>29480 rows × 58 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                   make_model  \\\n",
       "0         Mercedes-Benz A 160   \n",
       "1       Mercedes-Benz EQE 350   \n",
       "2      Mercedes-Benz A 45 AMG   \n",
       "3      Mercedes-Benz A 35 AMG   \n",
       "4      Mercedes-Benz A 45 AMG   \n",
       "...                       ...   \n",
       "29475               Volvo S40   \n",
       "29476               Volvo C30   \n",
       "29477               Volvo S90   \n",
       "29478               Volvo S80   \n",
       "29479                     NaN   \n",
       "\n",
       "                                       short_description               make  \\\n",
       "0                                                    CDi  \\nMercedes-Benz\\n   \n",
       "1                                                   350+  \\nMercedes-Benz\\n   \n",
       "2                                       S 4Matic+ 8G-DCT  \\nMercedes-Benz\\n   \n",
       "3                                         4Matic+ 7G-DCT  \\nMercedes-Benz\\n   \n",
       "4                               200CDI BE Line 4M 7G-DCT  \\nMercedes-Benz\\n   \n",
       "...                                                  ...                ...   \n",
       "29475        2.4i Momentum/ Airco/ NAP/ APK/ Elek. Ramen          \\nVolvo\\n   \n",
       "29476                    1.6 D DRIVe Start/Stop R-design          \\nVolvo\\n   \n",
       "29477  T5 AUT(8) MOMENTUM BUSINESS SCHUIFDAK 360GR CA...          \\nVolvo\\n   \n",
       "29478  2.9 Executive G. NETTE AUTO! LEER! NAVI! CRUIS...          \\nVolvo\\n   \n",
       "29479                                                NaN                NaN   \n",
       "\n",
       "                    model                                           location  \\\n",
       "0         [\\n, A 160 ,\\n]  P.I. EL PALMAR C/FORJA 6,  11500 PUERTO DE SAN...   \n",
       "1       [\\n, EQE 350 ,\\n]       APARTADO DE CORREOS 1032,  26140 LOGROÑO, ES   \n",
       "2      [\\n, A 45 AMG ,\\n]  PORT. TARRACO, MOLL DE LLEVANT, Nº 5, LOC. 6-8...   \n",
       "3      [\\n, A 35 AMG ,\\n]  Carrer de Provença, 31 Local,  8029 BARCELONA, ES   \n",
       "4      [\\n, A 45 AMG ,\\n]             CARRIL ARAGONES 4,  30007 CASILLAS, ES   \n",
       "...                   ...                                                ...   \n",
       "29475       [\\n, S40 ,\\n]                  Stobbeweg 6,  2461 EX TER AAR, NL   \n",
       "29476       [\\n, C30 ,\\n]             Sur rendez-vous,  5060 Sambreville, BE   \n",
       "29477       [\\n, S90 ,\\n]    Bergambachterstraat 5,  2871 JB SCHOONHOVEN, NL   \n",
       "29478       [\\n, S80 ,\\n]                  Lage Ham 106,  5102 AE DONGEN, NL   \n",
       "29479                 NaN                                                NaN   \n",
       "\n",
       "            price          Body type                      Type        Doors  \\\n",
       "0      € 16,950.-  [\\n, Compact, \\n]            [\\n, Used, \\n]  [\\n, 5, \\n]   \n",
       "1      € 80,900.-  [\\n, Compact, \\n]  [\\n, Pre-registered, \\n]  [\\n, 4, \\n]   \n",
       "2      € 69,900.-  [\\n, Compact, \\n]            [\\n, Used, \\n]  [\\n, 5, \\n]   \n",
       "3      € 46,990.-  [\\n, Compact, \\n]            [\\n, Used, \\n]  [\\n, 5, \\n]   \n",
       "4      € 16,800.-  [\\n, Compact, \\n]            [\\n, Used, \\n]  [\\n, 5, \\n]   \n",
       "...           ...                ...                       ...          ...   \n",
       "29475   € 5,499.-    [\\n, Sedan, \\n]            [\\n, Used, \\n]  [\\n, 4, \\n]   \n",
       "29476   € 7,300.-    [\\n, Sedan, \\n]            [\\n, Used, \\n]  [\\n, 3, \\n]   \n",
       "29477  € 29,900.-    [\\n, Sedan, \\n]            [\\n, Used, \\n]  [\\n, 4, \\n]   \n",
       "29478   € 4,440.-    [\\n, Sedan, \\n]            [\\n, Used, \\n]  [\\n, 4, \\n]   \n",
       "29479         NaN                NaN                       NaN          NaN   \n",
       "\n",
       "         Country version        Offer number             Warranty     Mileage  \\\n",
       "0        [\\n, Spain, \\n]   [\\n, 7468157, \\n]  [\\n, 24 months, \\n]  120,200 km   \n",
       "1        [\\n, Spain, \\n]   [\\n, 7054863, \\n]  [\\n, 24 months, \\n]    5,000 km   \n",
       "2        [\\n, Spain, \\n]   [\\n, 7410454, \\n]  [\\n, 12 months, \\n]   18,900 km   \n",
       "3        [\\n, Spain, \\n]   [\\n, 7464503, \\n]  [\\n, 12 months, \\n]   18,995 km   \n",
       "4        [\\n, Spain, \\n]   [\\n, 7127931, \\n]  [\\n, 12 months, \\n]  197,000 km   \n",
       "...                  ...                 ...                  ...         ...   \n",
       "29475                NaN  [\\n, 09-PF-XS, \\n]                  NaN  145,000 km   \n",
       "29476  [\\n, Belgium, \\n]                 NaN  [\\n, 13 months, \\n]   96,000 km   \n",
       "29477                NaN      [\\n, 2791, \\n]  [\\n, 12 months, \\n]   94,343 km   \n",
       "29478                NaN  [\\n, 43-JR-LR, \\n]                  NaN  230,047 km   \n",
       "29479                NaN                 NaN                  NaN         NaN   \n",
       "\n",
       "      First registration          Gearbox                 Fuel type  Colour  \\\n",
       "0                06/2016     [\\nManual\\n]                    Diesel   Black   \n",
       "1                06/2022  [\\nAutomatic\\n]                  Electric     NaN   \n",
       "2                07/2020  [\\nAutomatic\\n]                  Gasoline    Grey   \n",
       "3                01/2020  [\\nAutomatic\\n]                  Gasoline  Yellow   \n",
       "4                09/2015  [\\nAutomatic\\n]                    Diesel   White   \n",
       "...                  ...              ...                       ...     ...   \n",
       "29475            06/2004  [\\nAutomatic\\n]                  Gasoline    Grey   \n",
       "29476            04/2011     [\\nManual\\n]  Diesel (Particle filter)    Grey   \n",
       "29477            11/2017  [\\nAutomatic\\n]                  Gasoline    Blue   \n",
       "29478            07/2002  [\\nAutomatic\\n]                  Super 95    Grey   \n",
       "29479                NaN              NaN                       NaN     NaN   \n",
       "\n",
       "          Paint                                               desc  seller  \\\n",
       "0      Metallic  [ , Precio al contado: 16950 euros,  ,  , Vehí...  Dealer   \n",
       "1           NaN  [ , Precio al contado: 88900 euros,  , AUTO OJ...  Dealer   \n",
       "2           NaN  [Gris MANUFAKTUR mountaingrau magno,  , Linea/...  Dealer   \n",
       "3           NaN  [ , Precio al contado: 48990 euros,  ,  , BONI...  Dealer   \n",
       "4      Metallic  [ , Precio al contado: 17400 euros,  , Vehícul...  Dealer   \n",
       "...         ...                                                ...     ...   \n",
       "29475       NaN  [Een goed rijdende auto met APK + NAP + Elektr...  Dealer   \n",
       "29476  Metallic  [*** VOLVO C30 2011 TRES PROPRE EN PARFAIT ETA...  Dealer   \n",
       "29477  Metallic  [Bekijk deze auto in unieke 360 graden present...  Dealer   \n",
       "29478       NaN  [YOUNGTIMER !, Bedrijfsinformatie, NEEM VOOR U...  Dealer   \n",
       "29479       NaN                                                NaN     NaN   \n",
       "\n",
       "             Seats                  Power     Engine size    Gears  \\\n",
       "0              NaN                    NaN             NaN      NaN   \n",
       "1      [\\n, 5, \\n]  [\\n215 kW (292 hp)\\n]      [\\n1 cc\\n]  [\\n9\\n]   \n",
       "2      [\\n, 5, \\n]  [\\n310 kW (421 hp)\\n]  [\\n1,991 cc\\n]  [\\n8\\n]   \n",
       "3      [\\n, 5, \\n]  [\\n225 kW (306 hp)\\n]  [\\n1,991 cc\\n]  [\\n7\\n]   \n",
       "4      [\\n, 5, \\n]  [\\n100 kW (136 hp)\\n]  [\\n2,143 cc\\n]  [\\n7\\n]   \n",
       "...            ...                    ...             ...      ...   \n",
       "29475  [\\n, 5, \\n]  [\\n125 kW (170 hp)\\n]  [\\n2,435 cc\\n]  [\\n5\\n]   \n",
       "29476  [\\n, 4, \\n]   [\\n84 kW (114 hp)\\n]  [\\n1,560 cc\\n]  [\\n6\\n]   \n",
       "29477  [\\n, 5, \\n]  [\\n187 kW (254 hp)\\n]  [\\n1,969 cc\\n]  [\\n8\\n]   \n",
       "29478  [\\n, 5, \\n]  [\\n147 kW (200 hp)\\n]  [\\n2,922 cc\\n]      NaN   \n",
       "29479          NaN                    NaN             NaN      NaN   \n",
       "\n",
       "          CO₂-emissions             Manufacturer colour       Drivetrain  \\\n",
       "0                   NaN                             NaN              NaN   \n",
       "1        0 g/km (comb.)                 Negro Obsidiana              NaN   \n",
       "2                   NaN              Mountaingrau magno    [\\n, 4WD, \\n]   \n",
       "3                   NaN                    Amarillo Sol    [\\n, 4WD, \\n]   \n",
       "4                   NaN                             NaN    [\\n, 4WD, \\n]   \n",
       "...                 ...                             ...              ...   \n",
       "29475  217 g/km (comb.)                           Grijs  [\\n, Front, \\n]   \n",
       "29476   99 g/km (comb.)                             NaN  [\\n, Front, \\n]   \n",
       "29477  149 g/km (comb.)  Denim Blue metallic (blauw met              NaN   \n",
       "29478  251 g/km (comb.)                           Grijs  [\\n, Front, \\n]   \n",
       "29479               NaN                             NaN              NaN   \n",
       "\n",
       "      Cylinders                                   Fuel consumption  \\\n",
       "0           NaN                                                NaN   \n",
       "1           NaN                                                NaN   \n",
       "2       [\\n4\\n]  [[8.4 l/100 km (comb.)], [10.9 l/100 km (city)...   \n",
       "3       [\\n4\\n]  [[7.3 l/100 km (comb.)], [9.3 l/100 km (city)]...   \n",
       "4       [\\n4\\n]  [[4.9 l/100 km (comb.)], [5.7 l/100 km (city)]...   \n",
       "...         ...                                                ...   \n",
       "29475   [\\n5\\n]  [[9.1 l/100 km (comb.)], [13.2 l/100 km (city)...   \n",
       "29476   [\\n4\\n]  [[3.8 l/100 km (comb.)], [4.3 l/100 km (city)]...   \n",
       "29477   [\\n4\\n]  [[6.5 l/100 km (comb.)], [8.6 l/100 km (city)]...   \n",
       "29478   [\\n6\\n]  [[10.4 l/100 km (comb.)], [15.3 l/100 km (city...   \n",
       "29479       NaN                                                NaN   \n",
       "\n",
       "                               \\nComfort & Convenience\\n  \\\n",
       "0                                                    NaN   \n",
       "1                                                    NaN   \n",
       "2                                                    NaN   \n",
       "3      [Air conditioning, Automatic climate control, ...   \n",
       "4      [Air conditioning, Electrical side mirrors, Mu...   \n",
       "...                                                  ...   \n",
       "29475  [Air conditioning, Armrest, Automatic climate ...   \n",
       "29476  [Air conditioning, Armrest, Automatic climate ...   \n",
       "29477  [Air conditioning, Armrest, Automatic climate ...   \n",
       "29478  [Air conditioning, Armrest, Cruise control, El...   \n",
       "29479                                                NaN   \n",
       "\n",
       "                               \\nEntertainment & Media\\n  \\\n",
       "0                                                    NaN   \n",
       "1                                                    NaN   \n",
       "2                                                    NaN   \n",
       "3                                                  [USB]   \n",
       "4                       [Bluetooth, CD player, MP3, USB]   \n",
       "...                                                  ...   \n",
       "29475                         [On-board computer, Radio]   \n",
       "29476  [Bluetooth, CD player, Hands-free equipment, M...   \n",
       "29477  [Android Auto, Apple CarPlay, Bluetooth, Hands...   \n",
       "29478                                [On-board computer]   \n",
       "29479                                                NaN   \n",
       "\n",
       "                                   \\nSafety & Security\\n  \\\n",
       "0                                                    NaN   \n",
       "1                                                    NaN   \n",
       "2                                                    NaN   \n",
       "3      [ABS, Central door lock, Driver-side airbag, E...   \n",
       "4      [ABS, Central door lock, Driver-side airbag, E...   \n",
       "...                                                  ...   \n",
       "29475  [ABS, Central door lock, Central door lock wit...   \n",
       "29476  [ABS, Alarm system, Central door lock with rem...   \n",
       "29477  [Adaptive Cruise Control, Adaptive headlights,...   \n",
       "29478  [ABS, Alarm system, Central door lock, Central...   \n",
       "29479                                                NaN   \n",
       "\n",
       "                                              \\nExtras\\n    Empty weight  \\\n",
       "0                                                    NaN             NaN   \n",
       "1                                                    NaN             NaN   \n",
       "2                                                    NaN             NaN   \n",
       "3                                          [Sport seats]             NaN   \n",
       "4                                                    NaN  [\\n1,545 kg\\n]   \n",
       "...                                                  ...             ...   \n",
       "29475                [Alloy wheels (16\"), Trailer hitch]  [\\n1,357 kg\\n]   \n",
       "29476  [Alloy wheels, Automatically dimming interior ...  [\\n1,356 kg\\n]   \n",
       "29477  [Alloy wheels (18\"), Automatically dimming int...  [\\n1,617 kg\\n]   \n",
       "29478  [Alloy wheels, Automatically dimming interior ...  [\\n1,573 kg\\n]   \n",
       "29479                                                NaN             NaN   \n",
       "\n",
       "      Model code General inspection Last service Full service history  \\\n",
       "0            NaN                NaN          NaN                  NaN   \n",
       "1            NaN                NaN          NaN                  NaN   \n",
       "2            NaN                NaN          NaN                  NaN   \n",
       "3            NaN                NaN          NaN                  NaN   \n",
       "4            NaN                NaN          NaN                  NaN   \n",
       "...          ...                ...          ...                  ...   \n",
       "29475        NaN            08/2023          NaN                  Yes   \n",
       "29476        NaN                NaN          NaN                  Yes   \n",
       "29477        NaN                New          NaN                  Yes   \n",
       "29478        NaN            05/2023          NaN                  NaN   \n",
       "29479        NaN                NaN          NaN                  NaN   \n",
       "\n",
       "      Non-smoker vehicle Emission class Emissions sticker Upholstery colour  \\\n",
       "0                    NaN            NaN               NaN               NaN   \n",
       "1                    NaN            NaN               NaN               NaN   \n",
       "2                    NaN            NaN               NaN               NaN   \n",
       "3                    NaN            NaN               NaN               NaN   \n",
       "4                    NaN            NaN               NaN               NaN   \n",
       "...                  ...            ...               ...               ...   \n",
       "29475                NaN         Euro 4               NaN               NaN   \n",
       "29476                NaN         Euro 5               NaN             Black   \n",
       "29477                NaN         Euro 6               NaN             Other   \n",
       "29478                NaN         Euro 3               NaN             Beige   \n",
       "29479                NaN            NaN               NaN               NaN   \n",
       "\n",
       "         Upholstery  Production date              Previous owner  \\\n",
       "0               NaN              NaN                         NaN   \n",
       "1               NaN              NaN                         NaN   \n",
       "2               NaN              NaN                         NaN   \n",
       "3               NaN              NaN                         NaN   \n",
       "4               NaN              NaN                         NaN   \n",
       "...             ...              ...                         ...   \n",
       "29475           NaN              NaN                         NaN   \n",
       "29476           NaN              NaN   [[96,000 km, 04/2011], 1]   \n",
       "29477  Full leather              NaN                         NaN   \n",
       "29478  Full leather              NaN  [[230,047 km, 07/2002], 5]   \n",
       "29479           NaN              NaN                         NaN   \n",
       "\n",
       "      Other fuel types Power consumption Energy efficiency class  \\\n",
       "0                  NaN               NaN                     NaN   \n",
       "1                  NaN               NaN                     NaN   \n",
       "2                  NaN               NaN                     NaN   \n",
       "3                  NaN               NaN                     NaN   \n",
       "4                  NaN               NaN                     NaN   \n",
       "...                ...               ...                     ...   \n",
       "29475              NaN               NaN                     NaN   \n",
       "29476              NaN               NaN                     NaN   \n",
       "29477              NaN               NaN                     NaN   \n",
       "29478              NaN               NaN                     NaN   \n",
       "29479              NaN               NaN                     NaN   \n",
       "\n",
       "      CO₂-efficiency Fuel consumption (WLTP) CO₂-emissions (WLTP)  \\\n",
       "0                NaN                     NaN                  NaN   \n",
       "1                NaN                     NaN                  NaN   \n",
       "2                NaN                     NaN                  NaN   \n",
       "3                NaN                     NaN                  NaN   \n",
       "4                NaN                     NaN                  NaN   \n",
       "...              ...                     ...                  ...   \n",
       "29475            NaN                     NaN                  NaN   \n",
       "29476            NaN                     NaN                  NaN   \n",
       "29477            NaN                     NaN                  NaN   \n",
       "29478            NaN                     NaN                  NaN   \n",
       "29479            NaN                     NaN                  NaN   \n",
       "\n",
       "      Available from Taxi or rental car Availability Last timing belt change  \\\n",
       "0                NaN                NaN          NaN                     NaN   \n",
       "1                NaN                NaN          NaN                     NaN   \n",
       "2                NaN                NaN          NaN                     NaN   \n",
       "3                NaN                NaN          NaN                     NaN   \n",
       "4                NaN                NaN          NaN                     NaN   \n",
       "...              ...                ...          ...                     ...   \n",
       "29475            NaN                NaN          NaN                     NaN   \n",
       "29476            NaN                NaN          NaN                     NaN   \n",
       "29477            NaN                NaN          NaN                     NaN   \n",
       "29478            NaN                NaN          NaN                     NaN   \n",
       "29479            NaN                NaN          NaN                     NaN   \n",
       "\n",
       "      Electric Range (WLTP) Power consumption (WLTP) Battery Ownership  \n",
       "0                       NaN                      NaN               NaN  \n",
       "1                       NaN                      NaN               NaN  \n",
       "2                       NaN                      NaN               NaN  \n",
       "3                       NaN                      NaN               NaN  \n",
       "4                       NaN                      NaN               NaN  \n",
       "...                     ...                      ...               ...  \n",
       "29475                   NaN                      NaN               NaN  \n",
       "29476                   NaN                      NaN               NaN  \n",
       "29477                   NaN                      NaN               NaN  \n",
       "29478                   NaN                      NaN               NaN  \n",
       "29479                   NaN                      NaN               NaN  \n",
       "\n",
       "[29480 rows x 58 columns]"
      ]
     },
     "execution_count": 146,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 148,
   "id": "ccbcfe2a-bfb6-44b8-8cbc-6ff859bad148",
   "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>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>make_model</th>\n",
       "      <td>Mercedes-Benz A 160</td>\n",
       "      <td>Mercedes-Benz EQE 350</td>\n",
       "      <td>Mercedes-Benz A 45 AMG</td>\n",
       "      <td>Mercedes-Benz A 35 AMG</td>\n",
       "      <td>Mercedes-Benz A 45 AMG</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>short_description</th>\n",
       "      <td>CDi</td>\n",
       "      <td>350+</td>\n",
       "      <td>S 4Matic+ 8G-DCT</td>\n",
       "      <td>4Matic+ 7G-DCT</td>\n",
       "      <td>200CDI BE Line 4M 7G-DCT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>make</th>\n",
       "      <td>\\nMercedes-Benz\\n</td>\n",
       "      <td>\\nMercedes-Benz\\n</td>\n",
       "      <td>\\nMercedes-Benz\\n</td>\n",
       "      <td>\\nMercedes-Benz\\n</td>\n",
       "      <td>\\nMercedes-Benz\\n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>model</th>\n",
       "      <td>[\\n, A 160 ,\\n]</td>\n",
       "      <td>[\\n, EQE 350 ,\\n]</td>\n",
       "      <td>[\\n, A 45 AMG ,\\n]</td>\n",
       "      <td>[\\n, A 35 AMG ,\\n]</td>\n",
       "      <td>[\\n, A 45 AMG ,\\n]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>location</th>\n",
       "      <td>P.I. EL PALMAR C/FORJA 6,  11500 PUERTO DE SAN...</td>\n",
       "      <td>APARTADO DE CORREOS 1032,  26140 LOGROÑO, ES</td>\n",
       "      <td>PORT. TARRACO, MOLL DE LLEVANT, Nº 5, LOC. 6-8...</td>\n",
       "      <td>Carrer de Provença, 31 Local,  8029 BARCELONA, ES</td>\n",
       "      <td>CARRIL ARAGONES 4,  30007 CASILLAS, ES</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>price</th>\n",
       "      <td>€ 16,950.-</td>\n",
       "      <td>€ 80,900.-</td>\n",
       "      <td>€ 69,900.-</td>\n",
       "      <td>€ 46,990.-</td>\n",
       "      <td>€ 16,800.-</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Body type</th>\n",
       "      <td>[\\n, Compact, \\n]</td>\n",
       "      <td>[\\n, Compact, \\n]</td>\n",
       "      <td>[\\n, Compact, \\n]</td>\n",
       "      <td>[\\n, Compact, \\n]</td>\n",
       "      <td>[\\n, Compact, \\n]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Type</th>\n",
       "      <td>[\\n, Used, \\n]</td>\n",
       "      <td>[\\n, Pre-registered, \\n]</td>\n",
       "      <td>[\\n, Used, \\n]</td>\n",
       "      <td>[\\n, Used, \\n]</td>\n",
       "      <td>[\\n, Used, \\n]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Doors</th>\n",
       "      <td>[\\n, 5, \\n]</td>\n",
       "      <td>[\\n, 4, \\n]</td>\n",
       "      <td>[\\n, 5, \\n]</td>\n",
       "      <td>[\\n, 5, \\n]</td>\n",
       "      <td>[\\n, 5, \\n]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Country version</th>\n",
       "      <td>[\\n, Spain, \\n]</td>\n",
       "      <td>[\\n, Spain, \\n]</td>\n",
       "      <td>[\\n, Spain, \\n]</td>\n",
       "      <td>[\\n, Spain, \\n]</td>\n",
       "      <td>[\\n, Spain, \\n]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Offer number</th>\n",
       "      <td>[\\n, 7468157, \\n]</td>\n",
       "      <td>[\\n, 7054863, \\n]</td>\n",
       "      <td>[\\n, 7410454, \\n]</td>\n",
       "      <td>[\\n, 7464503, \\n]</td>\n",
       "      <td>[\\n, 7127931, \\n]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Warranty</th>\n",
       "      <td>[\\n, 24 months, \\n]</td>\n",
       "      <td>[\\n, 24 months, \\n]</td>\n",
       "      <td>[\\n, 12 months, \\n]</td>\n",
       "      <td>[\\n, 12 months, \\n]</td>\n",
       "      <td>[\\n, 12 months, \\n]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mileage</th>\n",
       "      <td>120,200 km</td>\n",
       "      <td>5,000 km</td>\n",
       "      <td>18,900 km</td>\n",
       "      <td>18,995 km</td>\n",
       "      <td>197,000 km</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>First registration</th>\n",
       "      <td>06/2016</td>\n",
       "      <td>06/2022</td>\n",
       "      <td>07/2020</td>\n",
       "      <td>01/2020</td>\n",
       "      <td>09/2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gearbox</th>\n",
       "      <td>[\\nManual\\n]</td>\n",
       "      <td>[\\nAutomatic\\n]</td>\n",
       "      <td>[\\nAutomatic\\n]</td>\n",
       "      <td>[\\nAutomatic\\n]</td>\n",
       "      <td>[\\nAutomatic\\n]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Fuel type</th>\n",
       "      <td>Diesel</td>\n",
       "      <td>Electric</td>\n",
       "      <td>Gasoline</td>\n",
       "      <td>Gasoline</td>\n",
       "      <td>Diesel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Colour</th>\n",
       "      <td>Black</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Grey</td>\n",
       "      <td>Yellow</td>\n",
       "      <td>White</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Paint</th>\n",
       "      <td>Metallic</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Metallic</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>desc</th>\n",
       "      <td>[ , Precio al contado: 16950 euros,  ,  , Vehí...</td>\n",
       "      <td>[ , Precio al contado: 88900 euros,  , AUTO OJ...</td>\n",
       "      <td>[Gris MANUFAKTUR mountaingrau magno,  , Linea/...</td>\n",
       "      <td>[ , Precio al contado: 48990 euros,  ,  , BONI...</td>\n",
       "      <td>[ , Precio al contado: 17400 euros,  , Vehícul...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>seller</th>\n",
       "      <td>Dealer</td>\n",
       "      <td>Dealer</td>\n",
       "      <td>Dealer</td>\n",
       "      <td>Dealer</td>\n",
       "      <td>Dealer</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Seats</th>\n",
       "      <td>NaN</td>\n",
       "      <td>[\\n, 5, \\n]</td>\n",
       "      <td>[\\n, 5, \\n]</td>\n",
       "      <td>[\\n, 5, \\n]</td>\n",
       "      <td>[\\n, 5, \\n]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Power</th>\n",
       "      <td>NaN</td>\n",
       "      <td>[\\n215 kW (292 hp)\\n]</td>\n",
       "      <td>[\\n310 kW (421 hp)\\n]</td>\n",
       "      <td>[\\n225 kW (306 hp)\\n]</td>\n",
       "      <td>[\\n100 kW (136 hp)\\n]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Engine size</th>\n",
       "      <td>NaN</td>\n",
       "      <td>[\\n1 cc\\n]</td>\n",
       "      <td>[\\n1,991 cc\\n]</td>\n",
       "      <td>[\\n1,991 cc\\n]</td>\n",
       "      <td>[\\n2,143 cc\\n]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gears</th>\n",
       "      <td>NaN</td>\n",
       "      <td>[\\n9\\n]</td>\n",
       "      <td>[\\n8\\n]</td>\n",
       "      <td>[\\n7\\n]</td>\n",
       "      <td>[\\n7\\n]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CO₂-emissions</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0 g/km (comb.)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Manufacturer colour</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Negro Obsidiana</td>\n",
       "      <td>Mountaingrau magno</td>\n",
       "      <td>Amarillo Sol</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Drivetrain</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[\\n, 4WD, \\n]</td>\n",
       "      <td>[\\n, 4WD, \\n]</td>\n",
       "      <td>[\\n, 4WD, \\n]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cylinders</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[\\n4\\n]</td>\n",
       "      <td>[\\n4\\n]</td>\n",
       "      <td>[\\n4\\n]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Fuel consumption</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[[8.4 l/100 km (comb.)], [10.9 l/100 km (city)...</td>\n",
       "      <td>[[7.3 l/100 km (comb.)], [9.3 l/100 km (city)]...</td>\n",
       "      <td>[[4.9 l/100 km (comb.)], [5.7 l/100 km (city)]...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>\\nComfort &amp; Convenience\\n</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[Air conditioning, Automatic climate control, ...</td>\n",
       "      <td>[Air conditioning, Electrical side mirrors, Mu...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>\\nEntertainment &amp; Media\\n</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[USB]</td>\n",
       "      <td>[Bluetooth, CD player, MP3, USB]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>\\nSafety &amp; Security\\n</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[ABS, Central door lock, Driver-side airbag, E...</td>\n",
       "      <td>[ABS, Central door lock, Driver-side airbag, E...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>\\nExtras\\n</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[Sport seats]</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Empty weight</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[\\n1,545 kg\\n]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Model code</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>General inspection</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Last service</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Full service history</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Non-smoker vehicle</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Emission class</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Emissions sticker</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Upholstery colour</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Upholstery</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Production date</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Previous owner</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Other fuel types</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Power consumption</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Energy efficiency class</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CO₂-efficiency</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Fuel consumption (WLTP)</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CO₂-emissions (WLTP)</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Available from</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Taxi or rental car</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Availability</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Last timing belt change</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Electric Range (WLTP)</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Power consumption (WLTP)</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Battery Ownership</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                                           0  \\\n",
       "make_model                                               Mercedes-Benz A 160   \n",
       "short_description                                                        CDi   \n",
       "make                                                       \\nMercedes-Benz\\n   \n",
       "model                                                        [\\n, A 160 ,\\n]   \n",
       "location                   P.I. EL PALMAR C/FORJA 6,  11500 PUERTO DE SAN...   \n",
       "price                                                             € 16,950.-   \n",
       "Body type                                                  [\\n, Compact, \\n]   \n",
       "Type                                                          [\\n, Used, \\n]   \n",
       "Doors                                                            [\\n, 5, \\n]   \n",
       "Country version                                              [\\n, Spain, \\n]   \n",
       "Offer number                                               [\\n, 7468157, \\n]   \n",
       "Warranty                                                 [\\n, 24 months, \\n]   \n",
       "Mileage                                                           120,200 km   \n",
       "First registration                                                   06/2016   \n",
       "Gearbox                                                         [\\nManual\\n]   \n",
       "Fuel type                                                             Diesel   \n",
       "Colour                                                                 Black   \n",
       "Paint                                                               Metallic   \n",
       "desc                       [ , Precio al contado: 16950 euros,  ,  , Vehí...   \n",
       "seller                                                                Dealer   \n",
       "Seats                                                                    NaN   \n",
       "Power                                                                    NaN   \n",
       "Engine size                                                              NaN   \n",
       "Gears                                                                    NaN   \n",
       "CO₂-emissions                                                            NaN   \n",
       "Manufacturer colour                                                      NaN   \n",
       "Drivetrain                                                               NaN   \n",
       "Cylinders                                                                NaN   \n",
       "Fuel consumption                                                         NaN   \n",
       "\\nComfort & Convenience\\n                                                NaN   \n",
       "\\nEntertainment & Media\\n                                                NaN   \n",
       "\\nSafety & Security\\n                                                    NaN   \n",
       "\\nExtras\\n                                                               NaN   \n",
       "Empty weight                                                             NaN   \n",
       "Model code                                                               NaN   \n",
       "General inspection                                                       NaN   \n",
       "Last service                                                             NaN   \n",
       "Full service history                                                     NaN   \n",
       "Non-smoker vehicle                                                       NaN   \n",
       "Emission class                                                           NaN   \n",
       "Emissions sticker                                                        NaN   \n",
       "Upholstery colour                                                        NaN   \n",
       "Upholstery                                                               NaN   \n",
       "Production date                                                          NaN   \n",
       "Previous owner                                                           NaN   \n",
       "Other fuel types                                                         NaN   \n",
       "Power consumption                                                        NaN   \n",
       "Energy efficiency class                                                  NaN   \n",
       "CO₂-efficiency                                                           NaN   \n",
       "Fuel consumption (WLTP)                                                  NaN   \n",
       "CO₂-emissions (WLTP)                                                     NaN   \n",
       "Available from                                                           NaN   \n",
       "Taxi or rental car                                                       NaN   \n",
       "Availability                                                             NaN   \n",
       "Last timing belt change                                                  NaN   \n",
       "Electric Range (WLTP)                                                    NaN   \n",
       "Power consumption (WLTP)                                                 NaN   \n",
       "Battery Ownership                                                        NaN   \n",
       "\n",
       "                                                                           1  \\\n",
       "make_model                                             Mercedes-Benz EQE 350   \n",
       "short_description                                                       350+   \n",
       "make                                                       \\nMercedes-Benz\\n   \n",
       "model                                                      [\\n, EQE 350 ,\\n]   \n",
       "location                        APARTADO DE CORREOS 1032,  26140 LOGROÑO, ES   \n",
       "price                                                             € 80,900.-   \n",
       "Body type                                                  [\\n, Compact, \\n]   \n",
       "Type                                                [\\n, Pre-registered, \\n]   \n",
       "Doors                                                            [\\n, 4, \\n]   \n",
       "Country version                                              [\\n, Spain, \\n]   \n",
       "Offer number                                               [\\n, 7054863, \\n]   \n",
       "Warranty                                                 [\\n, 24 months, \\n]   \n",
       "Mileage                                                             5,000 km   \n",
       "First registration                                                   06/2022   \n",
       "Gearbox                                                      [\\nAutomatic\\n]   \n",
       "Fuel type                                                           Electric   \n",
       "Colour                                                                   NaN   \n",
       "Paint                                                                    NaN   \n",
       "desc                       [ , Precio al contado: 88900 euros,  , AUTO OJ...   \n",
       "seller                                                                Dealer   \n",
       "Seats                                                            [\\n, 5, \\n]   \n",
       "Power                                                  [\\n215 kW (292 hp)\\n]   \n",
       "Engine size                                                       [\\n1 cc\\n]   \n",
       "Gears                                                                [\\n9\\n]   \n",
       "CO₂-emissions                                                 0 g/km (comb.)   \n",
       "Manufacturer colour                                          Negro Obsidiana   \n",
       "Drivetrain                                                               NaN   \n",
       "Cylinders                                                                NaN   \n",
       "Fuel consumption                                                         NaN   \n",
       "\\nComfort & Convenience\\n                                                NaN   \n",
       "\\nEntertainment & Media\\n                                                NaN   \n",
       "\\nSafety & Security\\n                                                    NaN   \n",
       "\\nExtras\\n                                                               NaN   \n",
       "Empty weight                                                             NaN   \n",
       "Model code                                                               NaN   \n",
       "General inspection                                                       NaN   \n",
       "Last service                                                             NaN   \n",
       "Full service history                                                     NaN   \n",
       "Non-smoker vehicle                                                       NaN   \n",
       "Emission class                                                           NaN   \n",
       "Emissions sticker                                                        NaN   \n",
       "Upholstery colour                                                        NaN   \n",
       "Upholstery                                                               NaN   \n",
       "Production date                                                          NaN   \n",
       "Previous owner                                                           NaN   \n",
       "Other fuel types                                                         NaN   \n",
       "Power consumption                                                        NaN   \n",
       "Energy efficiency class                                                  NaN   \n",
       "CO₂-efficiency                                                           NaN   \n",
       "Fuel consumption (WLTP)                                                  NaN   \n",
       "CO₂-emissions (WLTP)                                                     NaN   \n",
       "Available from                                                           NaN   \n",
       "Taxi or rental car                                                       NaN   \n",
       "Availability                                                             NaN   \n",
       "Last timing belt change                                                  NaN   \n",
       "Electric Range (WLTP)                                                    NaN   \n",
       "Power consumption (WLTP)                                                 NaN   \n",
       "Battery Ownership                                                        NaN   \n",
       "\n",
       "                                                                           2  \\\n",
       "make_model                                            Mercedes-Benz A 45 AMG   \n",
       "short_description                                           S 4Matic+ 8G-DCT   \n",
       "make                                                       \\nMercedes-Benz\\n   \n",
       "model                                                     [\\n, A 45 AMG ,\\n]   \n",
       "location                   PORT. TARRACO, MOLL DE LLEVANT, Nº 5, LOC. 6-8...   \n",
       "price                                                             € 69,900.-   \n",
       "Body type                                                  [\\n, Compact, \\n]   \n",
       "Type                                                          [\\n, Used, \\n]   \n",
       "Doors                                                            [\\n, 5, \\n]   \n",
       "Country version                                              [\\n, Spain, \\n]   \n",
       "Offer number                                               [\\n, 7410454, \\n]   \n",
       "Warranty                                                 [\\n, 12 months, \\n]   \n",
       "Mileage                                                            18,900 km   \n",
       "First registration                                                   07/2020   \n",
       "Gearbox                                                      [\\nAutomatic\\n]   \n",
       "Fuel type                                                           Gasoline   \n",
       "Colour                                                                  Grey   \n",
       "Paint                                                                    NaN   \n",
       "desc                       [Gris MANUFAKTUR mountaingrau magno,  , Linea/...   \n",
       "seller                                                                Dealer   \n",
       "Seats                                                            [\\n, 5, \\n]   \n",
       "Power                                                  [\\n310 kW (421 hp)\\n]   \n",
       "Engine size                                                   [\\n1,991 cc\\n]   \n",
       "Gears                                                                [\\n8\\n]   \n",
       "CO₂-emissions                                                            NaN   \n",
       "Manufacturer colour                                       Mountaingrau magno   \n",
       "Drivetrain                                                     [\\n, 4WD, \\n]   \n",
       "Cylinders                                                            [\\n4\\n]   \n",
       "Fuel consumption           [[8.4 l/100 km (comb.)], [10.9 l/100 km (city)...   \n",
       "\\nComfort & Convenience\\n                                                NaN   \n",
       "\\nEntertainment & Media\\n                                                NaN   \n",
       "\\nSafety & Security\\n                                                    NaN   \n",
       "\\nExtras\\n                                                               NaN   \n",
       "Empty weight                                                             NaN   \n",
       "Model code                                                               NaN   \n",
       "General inspection                                                       NaN   \n",
       "Last service                                                             NaN   \n",
       "Full service history                                                     NaN   \n",
       "Non-smoker vehicle                                                       NaN   \n",
       "Emission class                                                           NaN   \n",
       "Emissions sticker                                                        NaN   \n",
       "Upholstery colour                                                        NaN   \n",
       "Upholstery                                                               NaN   \n",
       "Production date                                                          NaN   \n",
       "Previous owner                                                           NaN   \n",
       "Other fuel types                                                         NaN   \n",
       "Power consumption                                                        NaN   \n",
       "Energy efficiency class                                                  NaN   \n",
       "CO₂-efficiency                                                           NaN   \n",
       "Fuel consumption (WLTP)                                                  NaN   \n",
       "CO₂-emissions (WLTP)                                                     NaN   \n",
       "Available from                                                           NaN   \n",
       "Taxi or rental car                                                       NaN   \n",
       "Availability                                                             NaN   \n",
       "Last timing belt change                                                  NaN   \n",
       "Electric Range (WLTP)                                                    NaN   \n",
       "Power consumption (WLTP)                                                 NaN   \n",
       "Battery Ownership                                                        NaN   \n",
       "\n",
       "                                                                           3  \\\n",
       "make_model                                            Mercedes-Benz A 35 AMG   \n",
       "short_description                                             4Matic+ 7G-DCT   \n",
       "make                                                       \\nMercedes-Benz\\n   \n",
       "model                                                     [\\n, A 35 AMG ,\\n]   \n",
       "location                   Carrer de Provença, 31 Local,  8029 BARCELONA, ES   \n",
       "price                                                             € 46,990.-   \n",
       "Body type                                                  [\\n, Compact, \\n]   \n",
       "Type                                                          [\\n, Used, \\n]   \n",
       "Doors                                                            [\\n, 5, \\n]   \n",
       "Country version                                              [\\n, Spain, \\n]   \n",
       "Offer number                                               [\\n, 7464503, \\n]   \n",
       "Warranty                                                 [\\n, 12 months, \\n]   \n",
       "Mileage                                                            18,995 km   \n",
       "First registration                                                   01/2020   \n",
       "Gearbox                                                      [\\nAutomatic\\n]   \n",
       "Fuel type                                                           Gasoline   \n",
       "Colour                                                                Yellow   \n",
       "Paint                                                                    NaN   \n",
       "desc                       [ , Precio al contado: 48990 euros,  ,  , BONI...   \n",
       "seller                                                                Dealer   \n",
       "Seats                                                            [\\n, 5, \\n]   \n",
       "Power                                                  [\\n225 kW (306 hp)\\n]   \n",
       "Engine size                                                   [\\n1,991 cc\\n]   \n",
       "Gears                                                                [\\n7\\n]   \n",
       "CO₂-emissions                                                            NaN   \n",
       "Manufacturer colour                                             Amarillo Sol   \n",
       "Drivetrain                                                     [\\n, 4WD, \\n]   \n",
       "Cylinders                                                            [\\n4\\n]   \n",
       "Fuel consumption           [[7.3 l/100 km (comb.)], [9.3 l/100 km (city)]...   \n",
       "\\nComfort & Convenience\\n  [Air conditioning, Automatic climate control, ...   \n",
       "\\nEntertainment & Media\\n                                              [USB]   \n",
       "\\nSafety & Security\\n      [ABS, Central door lock, Driver-side airbag, E...   \n",
       "\\nExtras\\n                                                     [Sport seats]   \n",
       "Empty weight                                                             NaN   \n",
       "Model code                                                               NaN   \n",
       "General inspection                                                       NaN   \n",
       "Last service                                                             NaN   \n",
       "Full service history                                                     NaN   \n",
       "Non-smoker vehicle                                                       NaN   \n",
       "Emission class                                                           NaN   \n",
       "Emissions sticker                                                        NaN   \n",
       "Upholstery colour                                                        NaN   \n",
       "Upholstery                                                               NaN   \n",
       "Production date                                                          NaN   \n",
       "Previous owner                                                           NaN   \n",
       "Other fuel types                                                         NaN   \n",
       "Power consumption                                                        NaN   \n",
       "Energy efficiency class                                                  NaN   \n",
       "CO₂-efficiency                                                           NaN   \n",
       "Fuel consumption (WLTP)                                                  NaN   \n",
       "CO₂-emissions (WLTP)                                                     NaN   \n",
       "Available from                                                           NaN   \n",
       "Taxi or rental car                                                       NaN   \n",
       "Availability                                                             NaN   \n",
       "Last timing belt change                                                  NaN   \n",
       "Electric Range (WLTP)                                                    NaN   \n",
       "Power consumption (WLTP)                                                 NaN   \n",
       "Battery Ownership                                                        NaN   \n",
       "\n",
       "                                                                           4  \n",
       "make_model                                            Mercedes-Benz A 45 AMG  \n",
       "short_description                                   200CDI BE Line 4M 7G-DCT  \n",
       "make                                                       \\nMercedes-Benz\\n  \n",
       "model                                                     [\\n, A 45 AMG ,\\n]  \n",
       "location                              CARRIL ARAGONES 4,  30007 CASILLAS, ES  \n",
       "price                                                             € 16,800.-  \n",
       "Body type                                                  [\\n, Compact, \\n]  \n",
       "Type                                                          [\\n, Used, \\n]  \n",
       "Doors                                                            [\\n, 5, \\n]  \n",
       "Country version                                              [\\n, Spain, \\n]  \n",
       "Offer number                                               [\\n, 7127931, \\n]  \n",
       "Warranty                                                 [\\n, 12 months, \\n]  \n",
       "Mileage                                                           197,000 km  \n",
       "First registration                                                   09/2015  \n",
       "Gearbox                                                      [\\nAutomatic\\n]  \n",
       "Fuel type                                                             Diesel  \n",
       "Colour                                                                 White  \n",
       "Paint                                                               Metallic  \n",
       "desc                       [ , Precio al contado: 17400 euros,  , Vehícul...  \n",
       "seller                                                                Dealer  \n",
       "Seats                                                            [\\n, 5, \\n]  \n",
       "Power                                                  [\\n100 kW (136 hp)\\n]  \n",
       "Engine size                                                   [\\n2,143 cc\\n]  \n",
       "Gears                                                                [\\n7\\n]  \n",
       "CO₂-emissions                                                            NaN  \n",
       "Manufacturer colour                                                      NaN  \n",
       "Drivetrain                                                     [\\n, 4WD, \\n]  \n",
       "Cylinders                                                            [\\n4\\n]  \n",
       "Fuel consumption           [[4.9 l/100 km (comb.)], [5.7 l/100 km (city)]...  \n",
       "\\nComfort & Convenience\\n  [Air conditioning, Electrical side mirrors, Mu...  \n",
       "\\nEntertainment & Media\\n                   [Bluetooth, CD player, MP3, USB]  \n",
       "\\nSafety & Security\\n      [ABS, Central door lock, Driver-side airbag, E...  \n",
       "\\nExtras\\n                                                               NaN  \n",
       "Empty weight                                                  [\\n1,545 kg\\n]  \n",
       "Model code                                                               NaN  \n",
       "General inspection                                                       NaN  \n",
       "Last service                                                             NaN  \n",
       "Full service history                                                     NaN  \n",
       "Non-smoker vehicle                                                       NaN  \n",
       "Emission class                                                           NaN  \n",
       "Emissions sticker                                                        NaN  \n",
       "Upholstery colour                                                        NaN  \n",
       "Upholstery                                                               NaN  \n",
       "Production date                                                          NaN  \n",
       "Previous owner                                                           NaN  \n",
       "Other fuel types                                                         NaN  \n",
       "Power consumption                                                        NaN  \n",
       "Energy efficiency class                                                  NaN  \n",
       "CO₂-efficiency                                                           NaN  \n",
       "Fuel consumption (WLTP)                                                  NaN  \n",
       "CO₂-emissions (WLTP)                                                     NaN  \n",
       "Available from                                                           NaN  \n",
       "Taxi or rental car                                                       NaN  \n",
       "Availability                                                             NaN  \n",
       "Last timing belt change                                                  NaN  \n",
       "Electric Range (WLTP)                                                    NaN  \n",
       "Power consumption (WLTP)                                                 NaN  \n",
       "Battery Ownership                                                        NaN  "
      ]
     },
     "execution_count": 148,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head().T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 150,
   "id": "af45edc0-26a3-4387-bfcf-1e885915a3e1",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<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",
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       "        text-align: right;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>make_model</th>\n",
       "      <th>short_description</th>\n",
       "      <th>make</th>\n",
       "      <th>model</th>\n",
       "      <th>location</th>\n",
       "      <th>price</th>\n",
       "      <th>Body type</th>\n",
       "      <th>Type</th>\n",
       "      <th>Doors</th>\n",
       "      <th>Country version</th>\n",
       "      <th>Offer number</th>\n",
       "      <th>Warranty</th>\n",
       "      <th>Mileage</th>\n",
       "      <th>First registration</th>\n",
       "      <th>Gearbox</th>\n",
       "      <th>Fuel type</th>\n",
       "      <th>Colour</th>\n",
       "      <th>Paint</th>\n",
       "      <th>desc</th>\n",
       "      <th>seller</th>\n",
       "      <th>Seats</th>\n",
       "      <th>Power</th>\n",
       "      <th>Engine size</th>\n",
       "      <th>Gears</th>\n",
       "      <th>CO₂-emissions</th>\n",
       "      <th>Manufacturer colour</th>\n",
       "      <th>Drivetrain</th>\n",
       "      <th>Cylinders</th>\n",
       "      <th>Fuel consumption</th>\n",
       "      <th>\\nComfort &amp; Convenience\\n</th>\n",
       "      <th>\\nEntertainment &amp; Media\\n</th>\n",
       "      <th>\\nSafety &amp; Security\\n</th>\n",
       "      <th>\\nExtras\\n</th>\n",
       "      <th>Empty weight</th>\n",
       "      <th>Model code</th>\n",
       "      <th>General inspection</th>\n",
       "      <th>Last service</th>\n",
       "      <th>Full service history</th>\n",
       "      <th>Non-smoker vehicle</th>\n",
       "      <th>Emission class</th>\n",
       "      <th>Emissions sticker</th>\n",
       "      <th>Upholstery colour</th>\n",
       "      <th>Upholstery</th>\n",
       "      <th>Production date</th>\n",
       "      <th>Previous owner</th>\n",
       "      <th>Other fuel types</th>\n",
       "      <th>Power consumption</th>\n",
       "      <th>Energy efficiency class</th>\n",
       "      <th>CO₂-efficiency</th>\n",
       "      <th>Fuel consumption (WLTP)</th>\n",
       "      <th>CO₂-emissions (WLTP)</th>\n",
       "      <th>Available from</th>\n",
       "      <th>Taxi or rental car</th>\n",
       "      <th>Availability</th>\n",
       "      <th>Last timing belt change</th>\n",
       "      <th>Electric Range (WLTP)</th>\n",
       "      <th>Power consumption (WLTP)</th>\n",
       "      <th>Battery Ownership</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Mercedes-Benz A 160</td>\n",
       "      <td>CDi</td>\n",
       "      <td>\\nMercedes-Benz\\n</td>\n",
       "      <td>[\\n, A 160 ,\\n]</td>\n",
       "      <td>P.I. EL PALMAR C/FORJA 6,  11500 PUERTO DE SAN...</td>\n",
       "      <td>€ 16,950.-</td>\n",
       "      <td>[\\n, Compact, \\n]</td>\n",
       "      <td>[\\n, Used, \\n]</td>\n",
       "      <td>[\\n, 5, \\n]</td>\n",
       "      <td>[\\n, Spain, \\n]</td>\n",
       "      <td>[\\n, 7468157, \\n]</td>\n",
       "      <td>[\\n, 24 months, \\n]</td>\n",
       "      <td>120,200 km</td>\n",
       "      <td>06/2016</td>\n",
       "      <td>[\\nManual\\n]</td>\n",
       "      <td>Diesel</td>\n",
       "      <td>Black</td>\n",
       "      <td>Metallic</td>\n",
       "      <td>[ , Precio al contado: 16950 euros,  ,  , Vehí...</td>\n",
       "      <td>Dealer</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Mercedes-Benz EQE 350</td>\n",
       "      <td>350+</td>\n",
       "      <td>\\nMercedes-Benz\\n</td>\n",
       "      <td>[\\n, EQE 350 ,\\n]</td>\n",
       "      <td>APARTADO DE CORREOS 1032,  26140 LOGROÑO, ES</td>\n",
       "      <td>€ 80,900.-</td>\n",
       "      <td>[\\n, Compact, \\n]</td>\n",
       "      <td>[\\n, Pre-registered, \\n]</td>\n",
       "      <td>[\\n, 4, \\n]</td>\n",
       "      <td>[\\n, Spain, \\n]</td>\n",
       "      <td>[\\n, 7054863, \\n]</td>\n",
       "      <td>[\\n, 24 months, \\n]</td>\n",
       "      <td>5,000 km</td>\n",
       "      <td>06/2022</td>\n",
       "      <td>[\\nAutomatic\\n]</td>\n",
       "      <td>Electric</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[ , Precio al contado: 88900 euros,  , AUTO OJ...</td>\n",
       "      <td>Dealer</td>\n",
       "      <td>[\\n, 5, \\n]</td>\n",
       "      <td>[\\n215 kW (292 hp)\\n]</td>\n",
       "      <td>[\\n1 cc\\n]</td>\n",
       "      <td>[\\n9\\n]</td>\n",
       "      <td>0 g/km (comb.)</td>\n",
       "      <td>Negro Obsidiana</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Mercedes-Benz A 45 AMG</td>\n",
       "      <td>S 4Matic+ 8G-DCT</td>\n",
       "      <td>\\nMercedes-Benz\\n</td>\n",
       "      <td>[\\n, A 45 AMG ,\\n]</td>\n",
       "      <td>PORT. TARRACO, MOLL DE LLEVANT, Nº 5, LOC. 6-8...</td>\n",
       "      <td>€ 69,900.-</td>\n",
       "      <td>[\\n, Compact, \\n]</td>\n",
       "      <td>[\\n, Used, \\n]</td>\n",
       "      <td>[\\n, 5, \\n]</td>\n",
       "      <td>[\\n, Spain, \\n]</td>\n",
       "      <td>[\\n, 7410454, \\n]</td>\n",
       "      <td>[\\n, 12 months, \\n]</td>\n",
       "      <td>18,900 km</td>\n",
       "      <td>07/2020</td>\n",
       "      <td>[\\nAutomatic\\n]</td>\n",
       "      <td>Gasoline</td>\n",
       "      <td>Grey</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[Gris MANUFAKTUR mountaingrau magno,  , Linea/...</td>\n",
       "      <td>Dealer</td>\n",
       "      <td>[\\n, 5, \\n]</td>\n",
       "      <td>[\\n310 kW (421 hp)\\n]</td>\n",
       "      <td>[\\n1,991 cc\\n]</td>\n",
       "      <td>[\\n8\\n]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Mountaingrau magno</td>\n",
       "      <td>[\\n, 4WD, \\n]</td>\n",
       "      <td>[\\n4\\n]</td>\n",
       "      <td>[[8.4 l/100 km (comb.)], [10.9 l/100 km (city)...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Mercedes-Benz A 35 AMG</td>\n",
       "      <td>4Matic+ 7G-DCT</td>\n",
       "      <td>\\nMercedes-Benz\\n</td>\n",
       "      <td>[\\n, A 35 AMG ,\\n]</td>\n",
       "      <td>Carrer de Provença, 31 Local,  8029 BARCELONA, ES</td>\n",
       "      <td>€ 46,990.-</td>\n",
       "      <td>[\\n, Compact, \\n]</td>\n",
       "      <td>[\\n, Used, \\n]</td>\n",
       "      <td>[\\n, 5, \\n]</td>\n",
       "      <td>[\\n, Spain, \\n]</td>\n",
       "      <td>[\\n, 7464503, \\n]</td>\n",
       "      <td>[\\n, 12 months, \\n]</td>\n",
       "      <td>18,995 km</td>\n",
       "      <td>01/2020</td>\n",
       "      <td>[\\nAutomatic\\n]</td>\n",
       "      <td>Gasoline</td>\n",
       "      <td>Yellow</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[ , Precio al contado: 48990 euros,  ,  , BONI...</td>\n",
       "      <td>Dealer</td>\n",
       "      <td>[\\n, 5, \\n]</td>\n",
       "      <td>[\\n225 kW (306 hp)\\n]</td>\n",
       "      <td>[\\n1,991 cc\\n]</td>\n",
       "      <td>[\\n7\\n]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Amarillo Sol</td>\n",
       "      <td>[\\n, 4WD, \\n]</td>\n",
       "      <td>[\\n4\\n]</td>\n",
       "      <td>[[7.3 l/100 km (comb.)], [9.3 l/100 km (city)]...</td>\n",
       "      <td>[Air conditioning, Automatic climate control, ...</td>\n",
       "      <td>[USB]</td>\n",
       "      <td>[ABS, Central door lock, Driver-side airbag, E...</td>\n",
       "      <td>[Sport seats]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Mercedes-Benz A 45 AMG</td>\n",
       "      <td>200CDI BE Line 4M 7G-DCT</td>\n",
       "      <td>\\nMercedes-Benz\\n</td>\n",
       "      <td>[\\n, A 45 AMG ,\\n]</td>\n",
       "      <td>CARRIL ARAGONES 4,  30007 CASILLAS, ES</td>\n",
       "      <td>€ 16,800.-</td>\n",
       "      <td>[\\n, Compact, \\n]</td>\n",
       "      <td>[\\n, Used, \\n]</td>\n",
       "      <td>[\\n, 5, \\n]</td>\n",
       "      <td>[\\n, Spain, \\n]</td>\n",
       "      <td>[\\n, 7127931, \\n]</td>\n",
       "      <td>[\\n, 12 months, \\n]</td>\n",
       "      <td>197,000 km</td>\n",
       "      <td>09/2015</td>\n",
       "      <td>[\\nAutomatic\\n]</td>\n",
       "      <td>Diesel</td>\n",
       "      <td>White</td>\n",
       "      <td>Metallic</td>\n",
       "      <td>[ , Precio al contado: 17400 euros,  , Vehícul...</td>\n",
       "      <td>Dealer</td>\n",
       "      <td>[\\n, 5, \\n]</td>\n",
       "      <td>[\\n100 kW (136 hp)\\n]</td>\n",
       "      <td>[\\n2,143 cc\\n]</td>\n",
       "      <td>[\\n7\\n]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[\\n, 4WD, \\n]</td>\n",
       "      <td>[\\n4\\n]</td>\n",
       "      <td>[[4.9 l/100 km (comb.)], [5.7 l/100 km (city)]...</td>\n",
       "      <td>[Air conditioning, Electrical side mirrors, Mu...</td>\n",
       "      <td>[Bluetooth, CD player, MP3, USB]</td>\n",
       "      <td>[ABS, Central door lock, Driver-side airbag, E...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[\\n1,545 kg\\n]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               make_model         short_description               make  \\\n",
       "0     Mercedes-Benz A 160                       CDi  \\nMercedes-Benz\\n   \n",
       "1   Mercedes-Benz EQE 350                      350+  \\nMercedes-Benz\\n   \n",
       "2  Mercedes-Benz A 45 AMG          S 4Matic+ 8G-DCT  \\nMercedes-Benz\\n   \n",
       "3  Mercedes-Benz A 35 AMG            4Matic+ 7G-DCT  \\nMercedes-Benz\\n   \n",
       "4  Mercedes-Benz A 45 AMG  200CDI BE Line 4M 7G-DCT  \\nMercedes-Benz\\n   \n",
       "\n",
       "                model                                           location  \\\n",
       "0     [\\n, A 160 ,\\n]  P.I. EL PALMAR C/FORJA 6,  11500 PUERTO DE SAN...   \n",
       "1   [\\n, EQE 350 ,\\n]       APARTADO DE CORREOS 1032,  26140 LOGROÑO, ES   \n",
       "2  [\\n, A 45 AMG ,\\n]  PORT. TARRACO, MOLL DE LLEVANT, Nº 5, LOC. 6-8...   \n",
       "3  [\\n, A 35 AMG ,\\n]  Carrer de Provença, 31 Local,  8029 BARCELONA, ES   \n",
       "4  [\\n, A 45 AMG ,\\n]             CARRIL ARAGONES 4,  30007 CASILLAS, ES   \n",
       "\n",
       "        price          Body type                      Type        Doors  \\\n",
       "0  € 16,950.-  [\\n, Compact, \\n]            [\\n, Used, \\n]  [\\n, 5, \\n]   \n",
       "1  € 80,900.-  [\\n, Compact, \\n]  [\\n, Pre-registered, \\n]  [\\n, 4, \\n]   \n",
       "2  € 69,900.-  [\\n, Compact, \\n]            [\\n, Used, \\n]  [\\n, 5, \\n]   \n",
       "3  € 46,990.-  [\\n, Compact, \\n]            [\\n, Used, \\n]  [\\n, 5, \\n]   \n",
       "4  € 16,800.-  [\\n, Compact, \\n]            [\\n, Used, \\n]  [\\n, 5, \\n]   \n",
       "\n",
       "   Country version       Offer number             Warranty     Mileage  \\\n",
       "0  [\\n, Spain, \\n]  [\\n, 7468157, \\n]  [\\n, 24 months, \\n]  120,200 km   \n",
       "1  [\\n, Spain, \\n]  [\\n, 7054863, \\n]  [\\n, 24 months, \\n]    5,000 km   \n",
       "2  [\\n, Spain, \\n]  [\\n, 7410454, \\n]  [\\n, 12 months, \\n]   18,900 km   \n",
       "3  [\\n, Spain, \\n]  [\\n, 7464503, \\n]  [\\n, 12 months, \\n]   18,995 km   \n",
       "4  [\\n, Spain, \\n]  [\\n, 7127931, \\n]  [\\n, 12 months, \\n]  197,000 km   \n",
       "\n",
       "  First registration          Gearbox Fuel type  Colour     Paint  \\\n",
       "0            06/2016     [\\nManual\\n]    Diesel   Black  Metallic   \n",
       "1            06/2022  [\\nAutomatic\\n]  Electric     NaN       NaN   \n",
       "2            07/2020  [\\nAutomatic\\n]  Gasoline    Grey       NaN   \n",
       "3            01/2020  [\\nAutomatic\\n]  Gasoline  Yellow       NaN   \n",
       "4            09/2015  [\\nAutomatic\\n]    Diesel   White  Metallic   \n",
       "\n",
       "                                                desc  seller        Seats  \\\n",
       "0  [ , Precio al contado: 16950 euros,  ,  , Vehí...  Dealer          NaN   \n",
       "1  [ , Precio al contado: 88900 euros,  , AUTO OJ...  Dealer  [\\n, 5, \\n]   \n",
       "2  [Gris MANUFAKTUR mountaingrau magno,  , Linea/...  Dealer  [\\n, 5, \\n]   \n",
       "3  [ , Precio al contado: 48990 euros,  ,  , BONI...  Dealer  [\\n, 5, \\n]   \n",
       "4  [ , Precio al contado: 17400 euros,  , Vehícul...  Dealer  [\\n, 5, \\n]   \n",
       "\n",
       "                   Power     Engine size    Gears   CO₂-emissions  \\\n",
       "0                    NaN             NaN      NaN             NaN   \n",
       "1  [\\n215 kW (292 hp)\\n]      [\\n1 cc\\n]  [\\n9\\n]  0 g/km (comb.)   \n",
       "2  [\\n310 kW (421 hp)\\n]  [\\n1,991 cc\\n]  [\\n8\\n]             NaN   \n",
       "3  [\\n225 kW (306 hp)\\n]  [\\n1,991 cc\\n]  [\\n7\\n]             NaN   \n",
       "4  [\\n100 kW (136 hp)\\n]  [\\n2,143 cc\\n]  [\\n7\\n]             NaN   \n",
       "\n",
       "  Manufacturer colour     Drivetrain Cylinders  \\\n",
       "0                 NaN            NaN       NaN   \n",
       "1     Negro Obsidiana            NaN       NaN   \n",
       "2  Mountaingrau magno  [\\n, 4WD, \\n]   [\\n4\\n]   \n",
       "3        Amarillo Sol  [\\n, 4WD, \\n]   [\\n4\\n]   \n",
       "4                 NaN  [\\n, 4WD, \\n]   [\\n4\\n]   \n",
       "\n",
       "                                    Fuel consumption  \\\n",
       "0                                                NaN   \n",
       "1                                                NaN   \n",
       "2  [[8.4 l/100 km (comb.)], [10.9 l/100 km (city)...   \n",
       "3  [[7.3 l/100 km (comb.)], [9.3 l/100 km (city)]...   \n",
       "4  [[4.9 l/100 km (comb.)], [5.7 l/100 km (city)]...   \n",
       "\n",
       "                           \\nComfort & Convenience\\n  \\\n",
       "0                                                NaN   \n",
       "1                                                NaN   \n",
       "2                                                NaN   \n",
       "3  [Air conditioning, Automatic climate control, ...   \n",
       "4  [Air conditioning, Electrical side mirrors, Mu...   \n",
       "\n",
       "          \\nEntertainment & Media\\n  \\\n",
       "0                               NaN   \n",
       "1                               NaN   \n",
       "2                               NaN   \n",
       "3                             [USB]   \n",
       "4  [Bluetooth, CD player, MP3, USB]   \n",
       "\n",
       "                               \\nSafety & Security\\n     \\nExtras\\n  \\\n",
       "0                                                NaN            NaN   \n",
       "1                                                NaN            NaN   \n",
       "2                                                NaN            NaN   \n",
       "3  [ABS, Central door lock, Driver-side airbag, E...  [Sport seats]   \n",
       "4  [ABS, Central door lock, Driver-side airbag, E...            NaN   \n",
       "\n",
       "     Empty weight Model code General inspection Last service  \\\n",
       "0             NaN        NaN                NaN          NaN   \n",
       "1             NaN        NaN                NaN          NaN   \n",
       "2             NaN        NaN                NaN          NaN   \n",
       "3             NaN        NaN                NaN          NaN   \n",
       "4  [\\n1,545 kg\\n]        NaN                NaN          NaN   \n",
       "\n",
       "  Full service history Non-smoker vehicle Emission class Emissions sticker  \\\n",
       "0                  NaN                NaN            NaN               NaN   \n",
       "1                  NaN                NaN            NaN               NaN   \n",
       "2                  NaN                NaN            NaN               NaN   \n",
       "3                  NaN                NaN            NaN               NaN   \n",
       "4                  NaN                NaN            NaN               NaN   \n",
       "\n",
       "  Upholstery colour Upholstery  Production date Previous owner  \\\n",
       "0               NaN        NaN              NaN            NaN   \n",
       "1               NaN        NaN              NaN            NaN   \n",
       "2               NaN        NaN              NaN            NaN   \n",
       "3               NaN        NaN              NaN            NaN   \n",
       "4               NaN        NaN              NaN            NaN   \n",
       "\n",
       "  Other fuel types Power consumption Energy efficiency class CO₂-efficiency  \\\n",
       "0              NaN               NaN                     NaN            NaN   \n",
       "1              NaN               NaN                     NaN            NaN   \n",
       "2              NaN               NaN                     NaN            NaN   \n",
       "3              NaN               NaN                     NaN            NaN   \n",
       "4              NaN               NaN                     NaN            NaN   \n",
       "\n",
       "  Fuel consumption (WLTP) CO₂-emissions (WLTP) Available from  \\\n",
       "0                     NaN                  NaN            NaN   \n",
       "1                     NaN                  NaN            NaN   \n",
       "2                     NaN                  NaN            NaN   \n",
       "3                     NaN                  NaN            NaN   \n",
       "4                     NaN                  NaN            NaN   \n",
       "\n",
       "  Taxi or rental car Availability Last timing belt change  \\\n",
       "0                NaN          NaN                     NaN   \n",
       "1                NaN          NaN                     NaN   \n",
       "2                NaN          NaN                     NaN   \n",
       "3                NaN          NaN                     NaN   \n",
       "4                NaN          NaN                     NaN   \n",
       "\n",
       "  Electric Range (WLTP) Power consumption (WLTP) Battery Ownership  \n",
       "0                   NaN                      NaN               NaN  \n",
       "1                   NaN                      NaN               NaN  \n",
       "2                   NaN                      NaN               NaN  \n",
       "3                   NaN                      NaN               NaN  \n",
       "4                   NaN                      NaN               NaN  "
      ]
     },
     "execution_count": 150,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df0.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 152,
   "id": "f31beaa0-7b73-4794-ae42-2ca3fcb82bad",
   "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>make_model</th>\n",
       "      <th>short_description</th>\n",
       "      <th>make</th>\n",
       "      <th>model</th>\n",
       "      <th>location</th>\n",
       "      <th>price</th>\n",
       "      <th>Body type</th>\n",
       "      <th>Type</th>\n",
       "      <th>Doors</th>\n",
       "      <th>Country version</th>\n",
       "      <th>Offer number</th>\n",
       "      <th>Warranty</th>\n",
       "      <th>Mileage</th>\n",
       "      <th>First registration</th>\n",
       "      <th>Gearbox</th>\n",
       "      <th>Fuel type</th>\n",
       "      <th>Colour</th>\n",
       "      <th>Paint</th>\n",
       "      <th>desc</th>\n",
       "      <th>seller</th>\n",
       "      <th>Seats</th>\n",
       "      <th>Power</th>\n",
       "      <th>Engine size</th>\n",
       "      <th>Gears</th>\n",
       "      <th>CO₂-emissions</th>\n",
       "      <th>Manufacturer colour</th>\n",
       "      <th>Drivetrain</th>\n",
       "      <th>Cylinders</th>\n",
       "      <th>Fuel consumption</th>\n",
       "      <th>\\nComfort &amp; Convenience\\n</th>\n",
       "      <th>\\nEntertainment &amp; Media\\n</th>\n",
       "      <th>\\nSafety &amp; Security\\n</th>\n",
       "      <th>\\nExtras\\n</th>\n",
       "      <th>Empty weight</th>\n",
       "      <th>Model code</th>\n",
       "      <th>General inspection</th>\n",
       "      <th>Last service</th>\n",
       "      <th>Full service history</th>\n",
       "      <th>Non-smoker vehicle</th>\n",
       "      <th>Emission class</th>\n",
       "      <th>Emissions sticker</th>\n",
       "      <th>Upholstery colour</th>\n",
       "      <th>Upholstery</th>\n",
       "      <th>Production date</th>\n",
       "      <th>Previous owner</th>\n",
       "      <th>Other fuel types</th>\n",
       "      <th>Power consumption</th>\n",
       "      <th>Energy efficiency class</th>\n",
       "      <th>CO₂-efficiency</th>\n",
       "      <th>Fuel consumption (WLTP)</th>\n",
       "      <th>CO₂-emissions (WLTP)</th>\n",
       "      <th>Available from</th>\n",
       "      <th>Taxi or rental car</th>\n",
       "      <th>Availability</th>\n",
       "      <th>Last timing belt change</th>\n",
       "      <th>Electric Range (WLTP)</th>\n",
       "      <th>Power consumption (WLTP)</th>\n",
       "      <th>Battery Ownership</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>12345</th>\n",
       "      <td>SEAT Leon</td>\n",
       "      <td>2.0TDI CR S&amp;S FR DSG7 150</td>\n",
       "      <td>\\nSEAT\\n</td>\n",
       "      <td>[\\n, Leon ,\\n]</td>\n",
       "      <td>ROTONDA DE PITAGORAS, 1, NAVE 602,  28806 ALCA...</td>\n",
       "      <td>€ 17,000.-</td>\n",
       "      <td>[\\n, Compact, \\n]</td>\n",
       "      <td>[\\n, Used, \\n]</td>\n",
       "      <td>[\\n, 5, \\n]</td>\n",
       "      <td>[\\n, Spain, \\n]</td>\n",
       "      <td>[\\n, 7468152, \\n]</td>\n",
       "      <td>[\\n, 12 months, \\n]</td>\n",
       "      <td>155,000 km</td>\n",
       "      <td>06/2019</td>\n",
       "      <td>[\\nAutomatic\\n]</td>\n",
       "      <td>Diesel</td>\n",
       "      <td>Grey</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[ , Precio al contado: 17800 euros,  , Buen es...</td>\n",
       "      <td>Dealer</td>\n",
       "      <td>[\\n, 5, \\n]</td>\n",
       "      <td>[\\n110 kW (150 hp)\\n]</td>\n",
       "      <td>[\\n1,968 cc\\n]</td>\n",
       "      <td>[\\n7\\n]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[\\n, Front, \\n]</td>\n",
       "      <td>[\\n4\\n]</td>\n",
       "      <td>[[4.3 l/100 km (comb.)], [5 l/100 km (city)], ...</td>\n",
       "      <td>[Cruise control, Electrical side mirrors, Mult...</td>\n",
       "      <td>[Bluetooth, On-board computer]</td>\n",
       "      <td>[ABS, Central door lock, Fog lights, Isofix, P...</td>\n",
       "      <td>[Alloy wheels]</td>\n",
       "      <td>[\\n1,372 kg\\n]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5343</th>\n",
       "      <td>Renault Wind</td>\n",
       "      <td>1.6-16V Exception 133PK Cabriolet</td>\n",
       "      <td>\\nRenault\\n</td>\n",
       "      <td>[\\n, Wind ,\\n]</td>\n",
       "      <td>5431KR Cuijk, NL</td>\n",
       "      <td>€ 7,500.-</td>\n",
       "      <td>[\\n, Convertible, \\n]</td>\n",
       "      <td>[\\n, Used, \\n]</td>\n",
       "      <td>[\\n, 2, \\n]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>133,000 km</td>\n",
       "      <td>05/2011</td>\n",
       "      <td>[\\nManual\\n]</td>\n",
       "      <td>Gasoline</td>\n",
       "      <td>Black</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[• 1.6/ 133PK: Van deze versie zijn er maar en...</td>\n",
       "      <td>Private seller</td>\n",
       "      <td>[\\n, 2, \\n]</td>\n",
       "      <td>[\\n98 kW (133 hp)\\n]</td>\n",
       "      <td>[\\n1,598 cc\\n]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>160 g/km (comb.)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[\\n4\\n]</td>\n",
       "      <td>[[6.9 l/100 km (comb.)], [9.1 l/100 km (city)]...</td>\n",
       "      <td>[Air conditioning, Automatic climate control, ...</td>\n",
       "      <td>[Bluetooth, CD player, Hands-free equipment, O...</td>\n",
       "      <td>[ABS, Adaptive Cruise Control, Central door lo...</td>\n",
       "      <td>[Alloy wheels, Spare tyre, Spoiler, Sport seats]</td>\n",
       "      <td>[\\n1,148 kg\\n]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>06/2023</td>\n",
       "      <td>06/2022</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Euro 5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Black</td>\n",
       "      <td>Full leather</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>06/2021</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20337</th>\n",
       "      <td>Nissan Qashqai</td>\n",
       "      <td>Visia 1.3 DIG-T EU6d-T LED-Tagfahrlicht Multif...</td>\n",
       "      <td>\\nNissan\\n</td>\n",
       "      <td>[\\n, Qashqai ,\\n]</td>\n",
       "      <td>Rudolf-Diesel-Str. 9,  52351 Düren, DE</td>\n",
       "      <td>€ 19,480.-</td>\n",
       "      <td>[\\n, Off-Road/Pick-up, \\n]</td>\n",
       "      <td>[\\n, Used, \\n]</td>\n",
       "      <td>[\\n, 5, \\n]</td>\n",
       "      <td>[\\n, Germany, \\n]</td>\n",
       "      <td>[\\n, dn1877-21, \\n]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14,337 km</td>\n",
       "      <td>12/2018</td>\n",
       "      <td>[\\nManual\\n]</td>\n",
       "      <td>Gasoline</td>\n",
       "      <td>Silver</td>\n",
       "      <td>Metallic</td>\n",
       "      <td>[Getriebe:,  Schaltgetriebe, Technik:,  Bordco...</td>\n",
       "      <td>Dealer</td>\n",
       "      <td>[\\n, 5, \\n]</td>\n",
       "      <td>[\\n103 kW (140 hp)\\n]</td>\n",
       "      <td>[\\n1,332 cc\\n]</td>\n",
       "      <td>[\\n6\\n]</td>\n",
       "      <td>121 g/km (comb.)</td>\n",
       "      <td>Silver (m)</td>\n",
       "      <td>[\\n, Front, \\n]</td>\n",
       "      <td>[\\n4\\n]</td>\n",
       "      <td>[[5.3 l/100 km (comb.)], [6.6 l/100 km (city)]...</td>\n",
       "      <td>[Air conditioning, Armrest, Cruise control, El...</td>\n",
       "      <td>[Bluetooth, CD player, Digital radio, Hands-fr...</td>\n",
       "      <td>[ABS, Central door lock, Daytime running light...</td>\n",
       "      <td>[Catalytic Converter]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[\\n, 1329/ALO, \\n]</td>\n",
       "      <td>12/2021</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Euro 6d-TEMP</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Cloth</td>\n",
       "      <td>2018.00</td>\n",
       "      <td>[[14,337 km, 12/2018], 1]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>A</td>\n",
       "      <td>Calculated on basis of measured CO₂-emissions ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13024</th>\n",
       "      <td>SEAT Leon</td>\n",
       "      <td>ST 2.0 TSI S&amp;S Cupra DSG 300</td>\n",
       "      <td>\\nSEAT\\n</td>\n",
       "      <td>[\\n, Leon ,\\n]</td>\n",
       "      <td>CARRETERA FUENCARRAL A HORTALEZA 89 D,  28050 ...</td>\n",
       "      <td>€ 24,117.-</td>\n",
       "      <td>[\\n, Station wagon, \\n]</td>\n",
       "      <td>[\\n, Used, \\n]</td>\n",
       "      <td>[\\n, 5, \\n]</td>\n",
       "      <td>[\\n, Spain, \\n]</td>\n",
       "      <td>[\\n, 7422507, \\n]</td>\n",
       "      <td>[\\n, 12 months, \\n]</td>\n",
       "      <td>53,936 km</td>\n",
       "      <td>05/2017</td>\n",
       "      <td>[\\nAutomatic\\n]</td>\n",
       "      <td>Gasoline</td>\n",
       "      <td>Black</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[ , Precio al contado: 26499 euros,  , AUTOHER...</td>\n",
       "      <td>Dealer</td>\n",
       "      <td>[\\n, 5, \\n]</td>\n",
       "      <td>[\\n221 kW (300 hp)\\n]</td>\n",
       "      <td>[\\n1,984 cc\\n]</td>\n",
       "      <td>[\\n6\\n]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Negro</td>\n",
       "      <td>[\\n, Front, \\n]</td>\n",
       "      <td>[\\n4\\n]</td>\n",
       "      <td>[[6.8 l/100 km (comb.)], [8.5 l/100 km (city)]...</td>\n",
       "      <td>[Air conditioning, Automatic climate control, ...</td>\n",
       "      <td>[Bluetooth, On-board computer]</td>\n",
       "      <td>[ABS, Central door lock, Fog lights, Isofix, P...</td>\n",
       "      <td>[Alloy wheels, Sport suspension]</td>\n",
       "      <td>[\\n1,466 kg\\n]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23242</th>\n",
       "      <td>Ford Focus</td>\n",
       "      <td>Turnier Cool &amp; Connect 1.0 Sitzheizung - Navi ...</td>\n",
       "      <td>\\nFord\\n</td>\n",
       "      <td>[\\n, Focus ,\\n]</td>\n",
       "      <td>Hellweg 282,  45721 Haltern am See, DE</td>\n",
       "      <td>€ 20,990.-</td>\n",
       "      <td>[\\n, Station wagon, \\n]</td>\n",
       "      <td>[\\n, Used, \\n]</td>\n",
       "      <td>[\\n, 5, \\n]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[\\n, 202485, \\n]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>26,600 km</td>\n",
       "      <td>04/2020</td>\n",
       "      <td>[\\nManual\\n]</td>\n",
       "      <td>Super 95</td>\n",
       "      <td>Grey</td>\n",
       "      <td>Metallic</td>\n",
       "      <td>[Getriebe:,  Schaltgetriebe, Technik:,  Bordco...</td>\n",
       "      <td>Dealer</td>\n",
       "      <td>[\\n, 5, \\n]</td>\n",
       "      <td>[\\n92 kW (125 hp)\\n]</td>\n",
       "      <td>[\\n998 cc\\n]</td>\n",
       "      <td>[\\n6\\n]</td>\n",
       "      <td>108 g/km (comb.)</td>\n",
       "      <td>Magnetic-grau (metallic)</td>\n",
       "      <td>[\\n, Front, \\n]</td>\n",
       "      <td>[\\n3\\n]</td>\n",
       "      <td>[[4.8 l/100 km (comb.)], [5.9 l/100 km (city)]...</td>\n",
       "      <td>[Electrical side mirrors, Electrically heated ...</td>\n",
       "      <td>[Android Auto, Apple CarPlay, Bluetooth, Digit...</td>\n",
       "      <td>[ABS, Central door lock, Daytime running light...</td>\n",
       "      <td>[Alloy wheels, Catalytic Converter, Roof rack,...</td>\n",
       "      <td>[\\n1,383 kg\\n]</td>\n",
       "      <td>[\\n, 8566/BPP, \\n]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Yes</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Euro 6</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Cloth</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[[26,600 km, 04/2020], 1]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>A</td>\n",
       "      <td>Calculated on basis of measured CO₂-emissions ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21613</th>\n",
       "      <td>Ford Fiesta</td>\n",
       "      <td>1.0 EcoBoost S/S ST Line 140</td>\n",
       "      <td>\\nFord\\n</td>\n",
       "      <td>[\\n, Fiesta ,\\n]</td>\n",
       "      <td>AVDA SANT JAUME, S/N,  43870 AMPOSTA, ES</td>\n",
       "      <td>€ 17,500.-</td>\n",
       "      <td>[\\n, Compact, \\n]</td>\n",
       "      <td>[\\n, Used, \\n]</td>\n",
       "      <td>[\\n, 5, \\n]</td>\n",
       "      <td>[\\n, Spain, \\n]</td>\n",
       "      <td>[\\n, 7352882, \\n]</td>\n",
       "      <td>[\\n, 60 months, \\n]</td>\n",
       "      <td>11,000 km</td>\n",
       "      <td>07/2020</td>\n",
       "      <td>[\\nManual\\n]</td>\n",
       "      <td>Gasoline</td>\n",
       "      <td>Blue</td>\n",
       "      <td>Metallic</td>\n",
       "      <td>[ , Precio al contado: 19500 euros,  , VEHICUL...</td>\n",
       "      <td>Dealer</td>\n",
       "      <td>[\\n, 5, \\n]</td>\n",
       "      <td>[\\n103 kW (140 hp)\\n]</td>\n",
       "      <td>[\\n998 cc\\n]</td>\n",
       "      <td>[\\n6\\n]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>AZUL CHROME</td>\n",
       "      <td>[\\n, Front, \\n]</td>\n",
       "      <td>[\\n3\\n]</td>\n",
       "      <td>[[4.5 l/100 km (comb.)], [5.8 l/100 km (city)]...</td>\n",
       "      <td>[Air conditioning, Automatic climate control, ...</td>\n",
       "      <td>[USB]</td>\n",
       "      <td>[ABS, Central door lock, Driver-side airbag, E...</td>\n",
       "      <td>[Alloy wheels, Sport suspension]</td>\n",
       "      <td>[\\n1,101 kg\\n]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26740</th>\n",
       "      <td>Volvo C70</td>\n",
       "      <td>D3 DPF Summum Xenon Sitzhzg. Navi Memory</td>\n",
       "      <td>\\nVolvo\\n</td>\n",
       "      <td>[\\n, C70 ,\\n]</td>\n",
       "      <td>Biedenkamp  25-27,  21509 Glinde, DE</td>\n",
       "      <td>€ 19,950.-</td>\n",
       "      <td>[\\n, Convertible, \\n]</td>\n",
       "      <td>[\\n, Used, \\n]</td>\n",
       "      <td>[\\n, 2, \\n]</td>\n",
       "      <td>[\\n, Germany, \\n]</td>\n",
       "      <td>[\\n, DJ141908, \\n]</td>\n",
       "      <td>[\\n, 12 months, \\n]</td>\n",
       "      <td>97,865 km</td>\n",
       "      <td>06/2013</td>\n",
       "      <td>[\\nAutomatic\\n]</td>\n",
       "      <td>Diesel (Particle filter)</td>\n",
       "      <td>Blue</td>\n",
       "      <td>Metallic</td>\n",
       "      <td>[Fahrzeug-Nummer: DJ141908,  , C02-Effizienzkl...</td>\n",
       "      <td>Dealer</td>\n",
       "      <td>[\\n, 4, \\n]</td>\n",
       "      <td>[\\n110 kW (150 hp)\\n]</td>\n",
       "      <td>[\\n1,984 cc\\n]</td>\n",
       "      <td>[\\n6\\n]</td>\n",
       "      <td>169 g/km (comb.)</td>\n",
       "      <td>Caspian blue /</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[\\n5\\n]</td>\n",
       "      <td>[[6.4 l/100 km (comb.)], [8.7 l/100 km (city)]...</td>\n",
       "      <td>[Air conditioning, Armrest, Automatic climate ...</td>\n",
       "      <td>[Bluetooth, CD player, Hands-free equipment, M...</td>\n",
       "      <td>[ABS, Adaptive headlights, Central door lock w...</td>\n",
       "      <td>[Alloy wheels]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[\\n, 9101/ATK, \\n]</td>\n",
       "      <td>New</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Euro 5</td>\n",
       "      <td>4 (Green)</td>\n",
       "      <td>Black</td>\n",
       "      <td>Full leather</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[[97,865 km, 06/2013], 1]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>B</td>\n",
       "      <td>Calculated on basis of measured CO₂-emissions ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10426</th>\n",
       "      <td>Fiat 500</td>\n",
       "      <td>SPORT CAR PLAY NAVI BLUETOOTH CERCHIO 16</td>\n",
       "      <td>\\nFiat\\n</td>\n",
       "      <td>[\\n, 500 ,\\n]</td>\n",
       "      <td>Via Raoul Chiodelli, 46/52,  00132 Roma - Rm, IT</td>\n",
       "      <td>€ 9,900.-</td>\n",
       "      <td>[\\n, Coupe, \\n]</td>\n",
       "      <td>[\\n, Used, \\n]</td>\n",
       "      <td>[\\n, 3, \\n]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[\\n, 12 months, \\n]</td>\n",
       "      <td>24,000 km</td>\n",
       "      <td>12/2018</td>\n",
       "      <td>[\\nManual\\n]</td>\n",
       "      <td>Gasoline</td>\n",
       "      <td>Grey</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[AUTO PRONTA CONSEGNA VISIBILE IN SALONE FIAT ...</td>\n",
       "      <td>Dealer</td>\n",
       "      <td>[\\n, 5, \\n]</td>\n",
       "      <td>[\\n51 kW (69 hp)\\n]</td>\n",
       "      <td>[\\n1,242 cc\\n]</td>\n",
       "      <td>[\\n5\\n]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[Air conditioning, Air suspension, Automatic c...</td>\n",
       "      <td>[Android Auto, Apple CarPlay, Bluetooth, CD pl...</td>\n",
       "      <td>[ABS, Alarm system, Central door lock, Central...</td>\n",
       "      <td>[Alloy wheels (16\"), Ambient lighting, Emergen...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Black</td>\n",
       "      <td>Part leather</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3800</th>\n",
       "      <td>Opel Mokka</td>\n",
       "      <td>X EXCELLENCE</td>\n",
       "      <td>\\nOpel\\n</td>\n",
       "      <td>[\\n, Mokka ,\\n]</td>\n",
       "      <td>RUA REAL 60,  36860 PONTEAEREAS, ES</td>\n",
       "      <td>€ 15,990.-</td>\n",
       "      <td>[\\n, Off-Road/Pick-up, \\n]</td>\n",
       "      <td>[\\n, Used, \\n]</td>\n",
       "      <td>[\\n, 5, \\n]</td>\n",
       "      <td>[\\n, Spain, \\n]</td>\n",
       "      <td>[\\n, 7413377, \\n]</td>\n",
       "      <td>[\\n, 12 months, \\n]</td>\n",
       "      <td>69,513 km</td>\n",
       "      <td>04/2019</td>\n",
       "      <td>[\\nManual\\n]</td>\n",
       "      <td>Gasoline</td>\n",
       "      <td>Grey</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[ , Precio al contado: 17990 euros,  , GRUPO H...</td>\n",
       "      <td>Dealer</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[\\n103 kW (140 hp)\\n]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Gris</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28360</th>\n",
       "      <td>Volvo V90 Cross Country</td>\n",
       "      <td>V90 CC D5 AWD*Standhz*Luft*Head-up*PANO*B&amp;W</td>\n",
       "      <td>\\nVolvo\\n</td>\n",
       "      <td>[\\n, V90 Cross Country ,\\n]</td>\n",
       "      <td>Luckenwalder Berg 5,  14913 Jüterbog, DE</td>\n",
       "      <td>€ 40,500.-</td>\n",
       "      <td>[\\n, Station wagon, \\n]</td>\n",
       "      <td>[\\n, Used, \\n]</td>\n",
       "      <td>[\\n, 4, \\n]</td>\n",
       "      <td>[\\n, Germany, \\n]</td>\n",
       "      <td>[\\n, 290TW, \\n]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>76,500 km</td>\n",
       "      <td>06/2017</td>\n",
       "      <td>[\\nAutomatic\\n]</td>\n",
       "      <td>Diesel</td>\n",
       "      <td>Black</td>\n",
       "      <td>Metallic</td>\n",
       "      <td>[Ansprechpartner ist Herr Torsten Wiesenack un...</td>\n",
       "      <td>Dealer</td>\n",
       "      <td>[\\n, 5, \\n]</td>\n",
       "      <td>[\\n173 kW (235 hp)\\n]</td>\n",
       "      <td>[\\n1,969 cc\\n]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>139 g/km (comb.)</td>\n",
       "      <td>ONYX BLACK / Metallic</td>\n",
       "      <td>[\\n, 4WD, \\n]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[[5.3 l/100 km (comb.)], [6.1 l/100 km (city)]...</td>\n",
       "      <td>[Air conditioning, Air suspension, Armrest, Au...</td>\n",
       "      <td>[Android Auto, Apple CarPlay, Bluetooth, CD pl...</td>\n",
       "      <td>[ABS, Adaptive Cruise Control, Adaptive headli...</td>\n",
       "      <td>[Alloy wheels, Ambient lighting, Automatically...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>New</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Euro 6</td>\n",
       "      <td>4 (Green)</td>\n",
       "      <td>Black</td>\n",
       "      <td>Full leather</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[[76,500 km, 06/2017], 1]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    make_model  \\\n",
       "12345                SEAT Leon   \n",
       "5343              Renault Wind   \n",
       "20337           Nissan Qashqai   \n",
       "13024                SEAT Leon   \n",
       "23242               Ford Focus   \n",
       "21613              Ford Fiesta   \n",
       "26740                Volvo C70   \n",
       "10426                 Fiat 500   \n",
       "3800                Opel Mokka   \n",
       "28360  Volvo V90 Cross Country   \n",
       "\n",
       "                                       short_description         make  \\\n",
       "12345                          2.0TDI CR S&S FR DSG7 150     \\nSEAT\\n   \n",
       "5343                   1.6-16V Exception 133PK Cabriolet  \\nRenault\\n   \n",
       "20337  Visia 1.3 DIG-T EU6d-T LED-Tagfahrlicht Multif...   \\nNissan\\n   \n",
       "13024                       ST 2.0 TSI S&S Cupra DSG 300     \\nSEAT\\n   \n",
       "23242  Turnier Cool & Connect 1.0 Sitzheizung - Navi ...     \\nFord\\n   \n",
       "21613                       1.0 EcoBoost S/S ST Line 140     \\nFord\\n   \n",
       "26740           D3 DPF Summum Xenon Sitzhzg. Navi Memory    \\nVolvo\\n   \n",
       "10426           SPORT CAR PLAY NAVI BLUETOOTH CERCHIO 16     \\nFiat\\n   \n",
       "3800                                        X EXCELLENCE     \\nOpel\\n   \n",
       "28360        V90 CC D5 AWD*Standhz*Luft*Head-up*PANO*B&W    \\nVolvo\\n   \n",
       "\n",
       "                             model  \\\n",
       "12345               [\\n, Leon ,\\n]   \n",
       "5343                [\\n, Wind ,\\n]   \n",
       "20337            [\\n, Qashqai ,\\n]   \n",
       "13024               [\\n, Leon ,\\n]   \n",
       "23242              [\\n, Focus ,\\n]   \n",
       "21613             [\\n, Fiesta ,\\n]   \n",
       "26740                [\\n, C70 ,\\n]   \n",
       "10426                [\\n, 500 ,\\n]   \n",
       "3800               [\\n, Mokka ,\\n]   \n",
       "28360  [\\n, V90 Cross Country ,\\n]   \n",
       "\n",
       "                                                location       price  \\\n",
       "12345  ROTONDA DE PITAGORAS, 1, NAVE 602,  28806 ALCA...  € 17,000.-   \n",
       "5343                                    5431KR Cuijk, NL   € 7,500.-   \n",
       "20337             Rudolf-Diesel-Str. 9,  52351 Düren, DE  € 19,480.-   \n",
       "13024  CARRETERA FUENCARRAL A HORTALEZA 89 D,  28050 ...  € 24,117.-   \n",
       "23242             Hellweg 282,  45721 Haltern am See, DE  € 20,990.-   \n",
       "21613           AVDA SANT JAUME, S/N,  43870 AMPOSTA, ES  € 17,500.-   \n",
       "26740               Biedenkamp  25-27,  21509 Glinde, DE  € 19,950.-   \n",
       "10426   Via Raoul Chiodelli, 46/52,  00132 Roma - Rm, IT   € 9,900.-   \n",
       "3800                 RUA REAL 60,  36860 PONTEAEREAS, ES  € 15,990.-   \n",
       "28360           Luckenwalder Berg 5,  14913 Jüterbog, DE  € 40,500.-   \n",
       "\n",
       "                        Body type            Type        Doors  \\\n",
       "12345           [\\n, Compact, \\n]  [\\n, Used, \\n]  [\\n, 5, \\n]   \n",
       "5343        [\\n, Convertible, \\n]  [\\n, Used, \\n]  [\\n, 2, \\n]   \n",
       "20337  [\\n, Off-Road/Pick-up, \\n]  [\\n, Used, \\n]  [\\n, 5, \\n]   \n",
       "13024     [\\n, Station wagon, \\n]  [\\n, Used, \\n]  [\\n, 5, \\n]   \n",
       "23242     [\\n, Station wagon, \\n]  [\\n, Used, \\n]  [\\n, 5, \\n]   \n",
       "21613           [\\n, Compact, \\n]  [\\n, Used, \\n]  [\\n, 5, \\n]   \n",
       "26740       [\\n, Convertible, \\n]  [\\n, Used, \\n]  [\\n, 2, \\n]   \n",
       "10426             [\\n, Coupe, \\n]  [\\n, Used, \\n]  [\\n, 3, \\n]   \n",
       "3800   [\\n, Off-Road/Pick-up, \\n]  [\\n, Used, \\n]  [\\n, 5, \\n]   \n",
       "28360     [\\n, Station wagon, \\n]  [\\n, Used, \\n]  [\\n, 4, \\n]   \n",
       "\n",
       "         Country version         Offer number             Warranty  \\\n",
       "12345    [\\n, Spain, \\n]    [\\n, 7468152, \\n]  [\\n, 12 months, \\n]   \n",
       "5343                 NaN                  NaN                  NaN   \n",
       "20337  [\\n, Germany, \\n]  [\\n, dn1877-21, \\n]                  NaN   \n",
       "13024    [\\n, Spain, \\n]    [\\n, 7422507, \\n]  [\\n, 12 months, \\n]   \n",
       "23242                NaN     [\\n, 202485, \\n]                  NaN   \n",
       "21613    [\\n, Spain, \\n]    [\\n, 7352882, \\n]  [\\n, 60 months, \\n]   \n",
       "26740  [\\n, Germany, \\n]   [\\n, DJ141908, \\n]  [\\n, 12 months, \\n]   \n",
       "10426                NaN                  NaN  [\\n, 12 months, \\n]   \n",
       "3800     [\\n, Spain, \\n]    [\\n, 7413377, \\n]  [\\n, 12 months, \\n]   \n",
       "28360  [\\n, Germany, \\n]      [\\n, 290TW, \\n]                  NaN   \n",
       "\n",
       "          Mileage First registration          Gearbox  \\\n",
       "12345  155,000 km            06/2019  [\\nAutomatic\\n]   \n",
       "5343   133,000 km            05/2011     [\\nManual\\n]   \n",
       "20337   14,337 km            12/2018     [\\nManual\\n]   \n",
       "13024   53,936 km            05/2017  [\\nAutomatic\\n]   \n",
       "23242   26,600 km            04/2020     [\\nManual\\n]   \n",
       "21613   11,000 km            07/2020     [\\nManual\\n]   \n",
       "26740   97,865 km            06/2013  [\\nAutomatic\\n]   \n",
       "10426   24,000 km            12/2018     [\\nManual\\n]   \n",
       "3800    69,513 km            04/2019     [\\nManual\\n]   \n",
       "28360   76,500 km            06/2017  [\\nAutomatic\\n]   \n",
       "\n",
       "                      Fuel type  Colour     Paint  \\\n",
       "12345                    Diesel    Grey       NaN   \n",
       "5343                   Gasoline   Black       NaN   \n",
       "20337                  Gasoline  Silver  Metallic   \n",
       "13024                  Gasoline   Black       NaN   \n",
       "23242                  Super 95    Grey  Metallic   \n",
       "21613                  Gasoline    Blue  Metallic   \n",
       "26740  Diesel (Particle filter)    Blue  Metallic   \n",
       "10426                  Gasoline    Grey       NaN   \n",
       "3800                   Gasoline    Grey       NaN   \n",
       "28360                    Diesel   Black  Metallic   \n",
       "\n",
       "                                                    desc          seller  \\\n",
       "12345  [ , Precio al contado: 17800 euros,  , Buen es...          Dealer   \n",
       "5343   [• 1.6/ 133PK: Van deze versie zijn er maar en...  Private seller   \n",
       "20337  [Getriebe:,  Schaltgetriebe, Technik:,  Bordco...          Dealer   \n",
       "13024  [ , Precio al contado: 26499 euros,  , AUTOHER...          Dealer   \n",
       "23242  [Getriebe:,  Schaltgetriebe, Technik:,  Bordco...          Dealer   \n",
       "21613  [ , Precio al contado: 19500 euros,  , VEHICUL...          Dealer   \n",
       "26740  [Fahrzeug-Nummer: DJ141908,  , C02-Effizienzkl...          Dealer   \n",
       "10426  [AUTO PRONTA CONSEGNA VISIBILE IN SALONE FIAT ...          Dealer   \n",
       "3800   [ , Precio al contado: 17990 euros,  , GRUPO H...          Dealer   \n",
       "28360  [Ansprechpartner ist Herr Torsten Wiesenack un...          Dealer   \n",
       "\n",
       "             Seats                  Power     Engine size    Gears  \\\n",
       "12345  [\\n, 5, \\n]  [\\n110 kW (150 hp)\\n]  [\\n1,968 cc\\n]  [\\n7\\n]   \n",
       "5343   [\\n, 2, \\n]   [\\n98 kW (133 hp)\\n]  [\\n1,598 cc\\n]      NaN   \n",
       "20337  [\\n, 5, \\n]  [\\n103 kW (140 hp)\\n]  [\\n1,332 cc\\n]  [\\n6\\n]   \n",
       "13024  [\\n, 5, \\n]  [\\n221 kW (300 hp)\\n]  [\\n1,984 cc\\n]  [\\n6\\n]   \n",
       "23242  [\\n, 5, \\n]   [\\n92 kW (125 hp)\\n]    [\\n998 cc\\n]  [\\n6\\n]   \n",
       "21613  [\\n, 5, \\n]  [\\n103 kW (140 hp)\\n]    [\\n998 cc\\n]  [\\n6\\n]   \n",
       "26740  [\\n, 4, \\n]  [\\n110 kW (150 hp)\\n]  [\\n1,984 cc\\n]  [\\n6\\n]   \n",
       "10426  [\\n, 5, \\n]    [\\n51 kW (69 hp)\\n]  [\\n1,242 cc\\n]  [\\n5\\n]   \n",
       "3800           NaN  [\\n103 kW (140 hp)\\n]             NaN      NaN   \n",
       "28360  [\\n, 5, \\n]  [\\n173 kW (235 hp)\\n]  [\\n1,969 cc\\n]      NaN   \n",
       "\n",
       "          CO₂-emissions       Manufacturer colour       Drivetrain Cylinders  \\\n",
       "12345               NaN                       NaN  [\\n, Front, \\n]   [\\n4\\n]   \n",
       "5343   160 g/km (comb.)                       NaN              NaN   [\\n4\\n]   \n",
       "20337  121 g/km (comb.)                Silver (m)  [\\n, Front, \\n]   [\\n4\\n]   \n",
       "13024               NaN                     Negro  [\\n, Front, \\n]   [\\n4\\n]   \n",
       "23242  108 g/km (comb.)  Magnetic-grau (metallic)  [\\n, Front, \\n]   [\\n3\\n]   \n",
       "21613               NaN               AZUL CHROME  [\\n, Front, \\n]   [\\n3\\n]   \n",
       "26740  169 g/km (comb.)            Caspian blue /              NaN   [\\n5\\n]   \n",
       "10426               NaN                       NaN              NaN       NaN   \n",
       "3800                NaN                      Gris              NaN       NaN   \n",
       "28360  139 g/km (comb.)     ONYX BLACK / Metallic    [\\n, 4WD, \\n]       NaN   \n",
       "\n",
       "                                        Fuel consumption  \\\n",
       "12345  [[4.3 l/100 km (comb.)], [5 l/100 km (city)], ...   \n",
       "5343   [[6.9 l/100 km (comb.)], [9.1 l/100 km (city)]...   \n",
       "20337  [[5.3 l/100 km (comb.)], [6.6 l/100 km (city)]...   \n",
       "13024  [[6.8 l/100 km (comb.)], [8.5 l/100 km (city)]...   \n",
       "23242  [[4.8 l/100 km (comb.)], [5.9 l/100 km (city)]...   \n",
       "21613  [[4.5 l/100 km (comb.)], [5.8 l/100 km (city)]...   \n",
       "26740  [[6.4 l/100 km (comb.)], [8.7 l/100 km (city)]...   \n",
       "10426                                                NaN   \n",
       "3800                                                 NaN   \n",
       "28360  [[5.3 l/100 km (comb.)], [6.1 l/100 km (city)]...   \n",
       "\n",
       "                               \\nComfort & Convenience\\n  \\\n",
       "12345  [Cruise control, Electrical side mirrors, Mult...   \n",
       "5343   [Air conditioning, Automatic climate control, ...   \n",
       "20337  [Air conditioning, Armrest, Cruise control, El...   \n",
       "13024  [Air conditioning, Automatic climate control, ...   \n",
       "23242  [Electrical side mirrors, Electrically heated ...   \n",
       "21613  [Air conditioning, Automatic climate control, ...   \n",
       "26740  [Air conditioning, Armrest, Automatic climate ...   \n",
       "10426  [Air conditioning, Air suspension, Automatic c...   \n",
       "3800                                                 NaN   \n",
       "28360  [Air conditioning, Air suspension, Armrest, Au...   \n",
       "\n",
       "                               \\nEntertainment & Media\\n  \\\n",
       "12345                     [Bluetooth, On-board computer]   \n",
       "5343   [Bluetooth, CD player, Hands-free equipment, O...   \n",
       "20337  [Bluetooth, CD player, Digital radio, Hands-fr...   \n",
       "13024                     [Bluetooth, On-board computer]   \n",
       "23242  [Android Auto, Apple CarPlay, Bluetooth, Digit...   \n",
       "21613                                              [USB]   \n",
       "26740  [Bluetooth, CD player, Hands-free equipment, M...   \n",
       "10426  [Android Auto, Apple CarPlay, Bluetooth, CD pl...   \n",
       "3800                                                 NaN   \n",
       "28360  [Android Auto, Apple CarPlay, Bluetooth, CD pl...   \n",
       "\n",
       "                                   \\nSafety & Security\\n  \\\n",
       "12345  [ABS, Central door lock, Fog lights, Isofix, P...   \n",
       "5343   [ABS, Adaptive Cruise Control, Central door lo...   \n",
       "20337  [ABS, Central door lock, Daytime running light...   \n",
       "13024  [ABS, Central door lock, Fog lights, Isofix, P...   \n",
       "23242  [ABS, Central door lock, Daytime running light...   \n",
       "21613  [ABS, Central door lock, Driver-side airbag, E...   \n",
       "26740  [ABS, Adaptive headlights, Central door lock w...   \n",
       "10426  [ABS, Alarm system, Central door lock, Central...   \n",
       "3800                                                 NaN   \n",
       "28360  [ABS, Adaptive Cruise Control, Adaptive headli...   \n",
       "\n",
       "                                              \\nExtras\\n    Empty weight  \\\n",
       "12345                                     [Alloy wheels]  [\\n1,372 kg\\n]   \n",
       "5343    [Alloy wheels, Spare tyre, Spoiler, Sport seats]  [\\n1,148 kg\\n]   \n",
       "20337                              [Catalytic Converter]             NaN   \n",
       "13024                   [Alloy wheels, Sport suspension]  [\\n1,466 kg\\n]   \n",
       "23242  [Alloy wheels, Catalytic Converter, Roof rack,...  [\\n1,383 kg\\n]   \n",
       "21613                   [Alloy wheels, Sport suspension]  [\\n1,101 kg\\n]   \n",
       "26740                                     [Alloy wheels]             NaN   \n",
       "10426  [Alloy wheels (16\"), Ambient lighting, Emergen...             NaN   \n",
       "3800                                                 NaN             NaN   \n",
       "28360  [Alloy wheels, Ambient lighting, Automatically...             NaN   \n",
       "\n",
       "               Model code General inspection Last service  \\\n",
       "12345                 NaN                NaN          NaN   \n",
       "5343                  NaN            06/2023      06/2022   \n",
       "20337  [\\n, 1329/ALO, \\n]            12/2021          NaN   \n",
       "13024                 NaN                NaN          NaN   \n",
       "23242  [\\n, 8566/BPP, \\n]                NaN          NaN   \n",
       "21613                 NaN                NaN          NaN   \n",
       "26740  [\\n, 9101/ATK, \\n]                New          NaN   \n",
       "10426                 NaN                NaN          NaN   \n",
       "3800                  NaN                NaN          NaN   \n",
       "28360                 NaN                New          NaN   \n",
       "\n",
       "      Full service history Non-smoker vehicle Emission class  \\\n",
       "12345                  NaN                NaN            NaN   \n",
       "5343                   Yes                Yes         Euro 5   \n",
       "20337                  NaN                NaN   Euro 6d-TEMP   \n",
       "13024                  NaN                NaN            NaN   \n",
       "23242                  Yes                NaN         Euro 6   \n",
       "21613                  NaN                NaN            NaN   \n",
       "26740                  Yes                Yes         Euro 5   \n",
       "10426                  NaN                NaN            NaN   \n",
       "3800                   NaN                NaN            NaN   \n",
       "28360                  Yes                Yes         Euro 6   \n",
       "\n",
       "      Emissions sticker Upholstery colour    Upholstery  Production date  \\\n",
       "12345               NaN               NaN           NaN              NaN   \n",
       "5343                NaN             Black  Full leather              NaN   \n",
       "20337               NaN               NaN         Cloth          2018.00   \n",
       "13024               NaN               NaN           NaN              NaN   \n",
       "23242               NaN               NaN         Cloth              NaN   \n",
       "21613               NaN               NaN           NaN              NaN   \n",
       "26740         4 (Green)             Black  Full leather              NaN   \n",
       "10426               NaN             Black  Part leather              NaN   \n",
       "3800                NaN               NaN           NaN              NaN   \n",
       "28360         4 (Green)             Black  Full leather              NaN   \n",
       "\n",
       "                  Previous owner Other fuel types Power consumption  \\\n",
       "12345                        NaN              NaN               NaN   \n",
       "5343                         NaN              NaN               NaN   \n",
       "20337  [[14,337 km, 12/2018], 1]              NaN               NaN   \n",
       "13024                        NaN              NaN               NaN   \n",
       "23242  [[26,600 km, 04/2020], 1]              NaN               NaN   \n",
       "21613                        NaN              NaN               NaN   \n",
       "26740  [[97,865 km, 06/2013], 1]              NaN               NaN   \n",
       "10426                        NaN              NaN               NaN   \n",
       "3800                         NaN              NaN               NaN   \n",
       "28360  [[76,500 km, 06/2017], 1]              NaN               NaN   \n",
       "\n",
       "      Energy efficiency class  \\\n",
       "12345                     NaN   \n",
       "5343                      NaN   \n",
       "20337                       A   \n",
       "13024                     NaN   \n",
       "23242                       A   \n",
       "21613                     NaN   \n",
       "26740                       B   \n",
       "10426                     NaN   \n",
       "3800                      NaN   \n",
       "28360                     NaN   \n",
       "\n",
       "                                          CO₂-efficiency  \\\n",
       "12345                                                NaN   \n",
       "5343                                                 NaN   \n",
       "20337  Calculated on basis of measured CO₂-emissions ...   \n",
       "13024                                                NaN   \n",
       "23242  Calculated on basis of measured CO₂-emissions ...   \n",
       "21613                                                NaN   \n",
       "26740  Calculated on basis of measured CO₂-emissions ...   \n",
       "10426                                                NaN   \n",
       "3800                                                 NaN   \n",
       "28360                                                NaN   \n",
       "\n",
       "      Fuel consumption (WLTP) CO₂-emissions (WLTP) Available from  \\\n",
       "12345                     NaN                  NaN            NaN   \n",
       "5343                      NaN                  NaN            NaN   \n",
       "20337                     NaN                  NaN            NaN   \n",
       "13024                     NaN                  NaN            NaN   \n",
       "23242                     NaN                  NaN            NaN   \n",
       "21613                     NaN                  NaN            NaN   \n",
       "26740                     NaN                  NaN            NaN   \n",
       "10426                     NaN                  NaN            NaN   \n",
       "3800                      NaN                  NaN            NaN   \n",
       "28360                     NaN                  NaN            NaN   \n",
       "\n",
       "      Taxi or rental car Availability Last timing belt change  \\\n",
       "12345                NaN          NaN                     NaN   \n",
       "5343                 NaN          NaN                 06/2021   \n",
       "20337                NaN          NaN                     NaN   \n",
       "13024                NaN          NaN                     NaN   \n",
       "23242                NaN          NaN                     NaN   \n",
       "21613                NaN          NaN                     NaN   \n",
       "26740                NaN          NaN                     NaN   \n",
       "10426                NaN          NaN                     NaN   \n",
       "3800                 NaN          NaN                     NaN   \n",
       "28360                NaN          NaN                     NaN   \n",
       "\n",
       "      Electric Range (WLTP) Power consumption (WLTP) Battery Ownership  \n",
       "12345                   NaN                      NaN               NaN  \n",
       "5343                    NaN                      NaN               NaN  \n",
       "20337                   NaN                      NaN               NaN  \n",
       "13024                   NaN                      NaN               NaN  \n",
       "23242                   NaN                      NaN               NaN  \n",
       "21613                   NaN                      NaN               NaN  \n",
       "26740                   NaN                      NaN               NaN  \n",
       "10426                   NaN                      NaN               NaN  \n",
       "3800                    NaN                      NaN               NaN  \n",
       "28360                   NaN                      NaN               NaN  "
      ]
     },
     "execution_count": 152,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df0.sample(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 154,
   "id": "a45373e3-a06f-4ad3-bbea-6124e22cfcb4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(29480, 58)"
      ]
     },
     "execution_count": 154,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 156,
   "id": "b6741439-dc76-49fa-8d0a-5094b7df6cc0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 29480 entries, 0 to 29479\n",
      "Data columns (total 58 columns):\n",
      " #   Column                    Non-Null Count  Dtype  \n",
      "---  ------                    --------------  -----  \n",
      " 0   make_model                28630 non-null  object \n",
      " 1   short_description         28630 non-null  object \n",
      " 2   make                      28630 non-null  object \n",
      " 3   model                     28630 non-null  object \n",
      " 4   location                  28630 non-null  object \n",
      " 5   price                     28630 non-null  object \n",
      " 6   Body type                 28630 non-null  object \n",
      " 7   Type                      28630 non-null  object \n",
      " 8   Doors                     28271 non-null  object \n",
      " 9   Country version           16889 non-null  object \n",
      " 10  Offer number              23100 non-null  object \n",
      " 11  Warranty                  15784 non-null  object \n",
      " 12  Mileage                   28629 non-null  object \n",
      " 13  First registration        28628 non-null  object \n",
      " 14  Gearbox                   28382 non-null  object \n",
      " 15  Fuel type                 26843 non-null  object \n",
      " 16  Colour                    26906 non-null  object \n",
      " 17  Paint                     14495 non-null  object \n",
      " 18  desc                      28047 non-null  object \n",
      " 19  seller                    28630 non-null  object \n",
      " 20  Seats                     25505 non-null  object \n",
      " 21  Power                     28058 non-null  object \n",
      " 22  Engine size               27227 non-null  object \n",
      " 23  Gears                     18954 non-null  object \n",
      " 24  CO₂-emissions             18594 non-null  object \n",
      " 25  Manufacturer colour       21787 non-null  object \n",
      " 26  Drivetrain                16893 non-null  object \n",
      " 27  Cylinders                 18852 non-null  object \n",
      " 28  Fuel consumption          23385 non-null  object \n",
      " 29  \n",
      "Comfort & Convenience\n",
      "   25433 non-null  object \n",
      " 30  \n",
      "Entertainment & Media\n",
      "   23644 non-null  object \n",
      " 31  \n",
      "Safety & Security\n",
      "       25415 non-null  object \n",
      " 32  \n",
      "Extras\n",
      "                  23480 non-null  object \n",
      " 33  Empty weight              17758 non-null  object \n",
      " 34  Model code                8367 non-null   object \n",
      " 35  General inspection        12254 non-null  object \n",
      " 36  Last service              2003 non-null   object \n",
      " 37  Full service history      12565 non-null  object \n",
      " 38  Non-smoker vehicle        11594 non-null  object \n",
      " 39  Emission class            17859 non-null  object \n",
      " 40  Emissions sticker         9414 non-null   object \n",
      " 41  Upholstery colour         14569 non-null  object \n",
      " 42  Upholstery                18610 non-null  object \n",
      " 43  Production date           5908 non-null   float64\n",
      " 44  Previous owner            14015 non-null  object \n",
      " 45  Other fuel types          2313 non-null   object \n",
      " 46  Power consumption         515 non-null    object \n",
      " 47  Energy efficiency class   7804 non-null   object \n",
      " 48  CO₂-efficiency            7804 non-null   object \n",
      " 49  Fuel consumption (WLTP)   100 non-null    object \n",
      " 50  CO₂-emissions (WLTP)      116 non-null    object \n",
      " 51  Available from            393 non-null    object \n",
      " 52  Taxi or rental car        422 non-null    object \n",
      " 53  Availability              301 non-null    object \n",
      " 54  Last timing belt change   572 non-null    object \n",
      " 55  Electric Range (WLTP)     16 non-null     object \n",
      " 56  Power consumption (WLTP)  16 non-null     object \n",
      " 57  Battery Ownership         7 non-null      object \n",
      "dtypes: float64(1), object(57)\n",
      "memory usage: 13.0+ MB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 160,
   "id": "3e314933-452c-4f9c-ab8c-005203e59c0a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>make_model</th>\n",
       "      <th>short_description</th>\n",
       "      <th>make</th>\n",
       "      <th>model</th>\n",
       "      <th>location</th>\n",
       "      <th>price</th>\n",
       "      <th>Body type</th>\n",
       "      <th>Type</th>\n",
       "      <th>Doors</th>\n",
       "      <th>Country version</th>\n",
       "      <th>Offer number</th>\n",
       "      <th>Warranty</th>\n",
       "      <th>Mileage</th>\n",
       "      <th>First registration</th>\n",
       "      <th>Gearbox</th>\n",
       "      <th>Fuel type</th>\n",
       "      <th>Colour</th>\n",
       "      <th>Paint</th>\n",
       "      <th>desc</th>\n",
       "      <th>seller</th>\n",
       "      <th>Seats</th>\n",
       "      <th>Power</th>\n",
       "      <th>Engine size</th>\n",
       "      <th>Gears</th>\n",
       "      <th>CO₂-emissions</th>\n",
       "      <th>Manufacturer colour</th>\n",
       "      <th>Drivetrain</th>\n",
       "      <th>Cylinders</th>\n",
       "      <th>Fuel consumption</th>\n",
       "      <th>\\nComfort &amp; Convenience\\n</th>\n",
       "      <th>\\nEntertainment &amp; Media\\n</th>\n",
       "      <th>\\nSafety &amp; Security\\n</th>\n",
       "      <th>\\nExtras\\n</th>\n",
       "      <th>Empty weight</th>\n",
       "      <th>Model code</th>\n",
       "      <th>General inspection</th>\n",
       "      <th>Last service</th>\n",
       "      <th>Full service history</th>\n",
       "      <th>Non-smoker vehicle</th>\n",
       "      <th>Emission class</th>\n",
       "      <th>Emissions sticker</th>\n",
       "      <th>Upholstery colour</th>\n",
       "      <th>Upholstery</th>\n",
       "      <th>Previous owner</th>\n",
       "      <th>Other fuel types</th>\n",
       "      <th>Power consumption</th>\n",
       "      <th>Energy efficiency class</th>\n",
       "      <th>CO₂-efficiency</th>\n",
       "      <th>Fuel consumption (WLTP)</th>\n",
       "      <th>CO₂-emissions (WLTP)</th>\n",
       "      <th>Available from</th>\n",
       "      <th>Taxi or rental car</th>\n",
       "      <th>Availability</th>\n",
       "      <th>Last timing belt change</th>\n",
       "      <th>Electric Range (WLTP)</th>\n",
       "      <th>Power consumption (WLTP)</th>\n",
       "      <th>Battery Ownership</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
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       "      <td>&lt;class 'float'&gt;</td>\n",
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       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'str'&gt;</td>\n",
       "      <td>&lt;class 'str'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>&lt;class 'str'&gt;</td>\n",
       "      <td>&lt;class 'str'&gt;</td>\n",
       "      <td>&lt;class 'str'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'str'&gt;</td>\n",
       "      <td>&lt;class 'str'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'str'&gt;</td>\n",
       "      <td>&lt;class 'str'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'str'&gt;</td>\n",
       "      <td>&lt;class 'str'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'str'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'str'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>&lt;class 'str'&gt;</td>\n",
       "      <td>&lt;class 'str'&gt;</td>\n",
       "      <td>&lt;class 'str'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'str'&gt;</td>\n",
       "      <td>&lt;class 'str'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'str'&gt;</td>\n",
       "      <td>&lt;class 'str'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'str'&gt;</td>\n",
       "      <td>&lt;class 'str'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'str'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'str'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>&lt;class 'str'&gt;</td>\n",
       "      <td>&lt;class 'str'&gt;</td>\n",
       "      <td>&lt;class 'str'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'str'&gt;</td>\n",
       "      <td>&lt;class 'str'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'str'&gt;</td>\n",
       "      <td>&lt;class 'str'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'str'&gt;</td>\n",
       "      <td>&lt;class 'str'&gt;</td>\n",
       "      <td>&lt;class 'str'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'str'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</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",
       "      <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",
       "      <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>29475</th>\n",
       "      <td>&lt;class 'str'&gt;</td>\n",
       "      <td>&lt;class 'str'&gt;</td>\n",
       "      <td>&lt;class 'str'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'str'&gt;</td>\n",
       "      <td>&lt;class 'str'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'str'&gt;</td>\n",
       "      <td>&lt;class 'str'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'str'&gt;</td>\n",
       "      <td>&lt;class 'str'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'str'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'str'&gt;</td>\n",
       "      <td>&lt;class 'str'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'str'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'str'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'str'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29476</th>\n",
       "      <td>&lt;class 'str'&gt;</td>\n",
       "      <td>&lt;class 'str'&gt;</td>\n",
       "      <td>&lt;class 'str'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'str'&gt;</td>\n",
       "      <td>&lt;class 'str'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'str'&gt;</td>\n",
       "      <td>&lt;class 'str'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'str'&gt;</td>\n",
       "      <td>&lt;class 'str'&gt;</td>\n",
       "      <td>&lt;class 'str'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'str'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'str'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'str'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'str'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'str'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29477</th>\n",
       "      <td>&lt;class 'str'&gt;</td>\n",
       "      <td>&lt;class 'str'&gt;</td>\n",
       "      <td>&lt;class 'str'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'str'&gt;</td>\n",
       "      <td>&lt;class 'str'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'float'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'str'&gt;</td>\n",
       "      <td>&lt;class 'str'&gt;</td>\n",
       "      <td>&lt;class 'list'&gt;</td>\n",
       "      <td>&lt;class 'str'&gt;</td>\n",
       "      <td>&lt;class 'str'&gt;</td>\n",
       "      <td>&lt;class 'str'&gt;</td>\n",
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       "    <tr>\n",
       "      <th>29479</th>\n",
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       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>29480 rows × 57 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            make_model short_description             make            model  \\\n",
       "0        <class 'str'>     <class 'str'>    <class 'str'>   <class 'list'>   \n",
       "1        <class 'str'>     <class 'str'>    <class 'str'>   <class 'list'>   \n",
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       "3        <class 'str'>     <class 'str'>    <class 'str'>   <class 'list'>   \n",
       "4        <class 'str'>     <class 'str'>    <class 'str'>   <class 'list'>   \n",
       "...                ...               ...              ...              ...   \n",
       "29475    <class 'str'>     <class 'str'>    <class 'str'>   <class 'list'>   \n",
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       "29479  <class 'float'>   <class 'float'>  <class 'float'>  <class 'float'>   \n",
       "\n",
       "              location            price        Body type             Type  \\\n",
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       "...                ...              ...              ...              ...   \n",
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       "\n",
       "                 Doors  Country version     Offer number         Warranty  \\\n",
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       "\n",
       "               Mileage First registration          Gearbox        Fuel type  \\\n",
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       "\n",
       "                 Seats            Power      Engine size            Gears  \\\n",
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       "\n",
       "         CO₂-emissions Manufacturer colour       Drivetrain        Cylinders  \\\n",
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       "\n",
       "      Fuel consumption \\nComfort & Convenience\\n \\nEntertainment & Media\\n  \\\n",
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       "\n",
       "      \\nSafety & Security\\n       \\nExtras\\n     Empty weight  \\\n",
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       "\n",
       "      Full service history Non-smoker vehicle   Emission class  \\\n",
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       "\n",
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       "\n",
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       "\n",
       "        CO₂-efficiency Fuel consumption (WLTP) CO₂-emissions (WLTP)  \\\n",
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       "4      <class 'float'>         <class 'float'>      <class 'float'>   \n",
       "...                ...                     ...                  ...   \n",
       "29475  <class 'float'>         <class 'float'>      <class 'float'>   \n",
       "29476  <class 'float'>         <class 'float'>      <class 'float'>   \n",
       "29477  <class 'float'>         <class 'float'>      <class 'float'>   \n",
       "29478  <class 'float'>         <class 'float'>      <class 'float'>   \n",
       "29479  <class 'float'>         <class 'float'>      <class 'float'>   \n",
       "\n",
       "        Available from Taxi or rental car     Availability  \\\n",
       "0      <class 'float'>    <class 'float'>  <class 'float'>   \n",
       "1      <class 'float'>    <class 'float'>  <class 'float'>   \n",
       "2      <class 'float'>    <class 'float'>  <class 'float'>   \n",
       "3      <class 'float'>    <class 'float'>  <class 'float'>   \n",
       "4      <class 'float'>    <class 'float'>  <class 'float'>   \n",
       "...                ...                ...              ...   \n",
       "29475  <class 'float'>    <class 'float'>  <class 'float'>   \n",
       "29476  <class 'float'>    <class 'float'>  <class 'float'>   \n",
       "29477  <class 'float'>    <class 'float'>  <class 'float'>   \n",
       "29478  <class 'float'>    <class 'float'>  <class 'float'>   \n",
       "29479  <class 'float'>    <class 'float'>  <class 'float'>   \n",
       "\n",
       "      Last timing belt change Electric Range (WLTP) Power consumption (WLTP)  \\\n",
       "0             <class 'float'>       <class 'float'>          <class 'float'>   \n",
       "1             <class 'float'>       <class 'float'>          <class 'float'>   \n",
       "2             <class 'float'>       <class 'float'>          <class 'float'>   \n",
       "3             <class 'float'>       <class 'float'>          <class 'float'>   \n",
       "4             <class 'float'>       <class 'float'>          <class 'float'>   \n",
       "...                       ...                   ...                      ...   \n",
       "29475         <class 'float'>       <class 'float'>          <class 'float'>   \n",
       "29476         <class 'float'>       <class 'float'>          <class 'float'>   \n",
       "29477         <class 'float'>       <class 'float'>          <class 'float'>   \n",
       "29478         <class 'float'>       <class 'float'>          <class 'float'>   \n",
       "29479         <class 'float'>       <class 'float'>          <class 'float'>   \n",
       "\n",
       "      Battery Ownership  \n",
       "0       <class 'float'>  \n",
       "1       <class 'float'>  \n",
       "2       <class 'float'>  \n",
       "3       <class 'float'>  \n",
       "4       <class 'float'>  \n",
       "...                 ...  \n",
       "29475   <class 'float'>  \n",
       "29476   <class 'float'>  \n",
       "29477   <class 'float'>  \n",
       "29478   <class 'float'>  \n",
       "29479   <class 'float'>  \n",
       "\n",
       "[29480 rows x 57 columns]"
      ]
     },
     "execution_count": 160,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.select_dtypes(include = ['object']).applymap(type)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "id": "2107aa47-99d4-44d5-9cb2-c3baffcf3e0b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['make_model', 'short_description', 'make', 'model', 'location', 'price',\n",
       "       'Body type', 'Type', 'Doors', 'Country version', 'Offer number',\n",
       "       'Warranty', 'Mileage', 'First registration', 'Gearbox', 'Fuel type',\n",
       "       'Colour', 'Paint', 'desc', 'seller', 'Seats', 'Power', 'Engine size',\n",
       "       'Gears', 'CO₂-emissions', 'Manufacturer colour', 'Drivetrain',\n",
       "       'Cylinders', 'Fuel consumption', '\\nComfort & Convenience\\n',\n",
       "       '\\nEntertainment & Media\\n', '\\nSafety & Security\\n', '\\nExtras\\n',\n",
       "       'Empty weight', 'Model code', 'General inspection', 'Last service',\n",
       "       'Full service history', 'Non-smoker vehicle', 'Emission class',\n",
       "       'Emissions sticker', 'Upholstery colour', 'Upholstery',\n",
       "       'Production date', 'Previous owner', 'Other fuel types',\n",
       "       'Power consumption', 'Energy efficiency class', 'CO₂-efficiency',\n",
       "       'Fuel consumption (WLTP)', 'CO₂-emissions (WLTP)', 'Available from',\n",
       "       'Taxi or rental car', 'Availability', 'Last timing belt change',\n",
       "       'Electric Range (WLTP)', 'Power consumption (WLTP)',\n",
       "       'Battery Ownership'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 164,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Examination of column names \n",
    "df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 166,
   "id": "194def17-7f06-48de-b4f7-7ea3a6c499e4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['\\nComfort & Convenience\\n',\n",
       " '\\nEntertainment & Media\\n',\n",
       " '\\nExtras\\n',\n",
       " '\\nSafety & Security\\n',\n",
       " 'Availability',\n",
       " 'Available from',\n",
       " 'Battery Ownership',\n",
       " 'Body type',\n",
       " 'CO₂-efficiency',\n",
       " 'CO₂-emissions',\n",
       " 'CO₂-emissions (WLTP)',\n",
       " 'Colour',\n",
       " 'Country version',\n",
       " 'Cylinders',\n",
       " 'Doors',\n",
       " 'Drivetrain',\n",
       " 'Electric Range (WLTP)',\n",
       " 'Emission class',\n",
       " 'Emissions sticker',\n",
       " 'Empty weight',\n",
       " 'Energy efficiency class',\n",
       " 'Engine size',\n",
       " 'First registration',\n",
       " 'Fuel consumption',\n",
       " 'Fuel consumption (WLTP)',\n",
       " 'Fuel type',\n",
       " 'Full service history',\n",
       " 'Gearbox',\n",
       " 'Gears',\n",
       " 'General inspection',\n",
       " 'Last service',\n",
       " 'Last timing belt change',\n",
       " 'Manufacturer colour',\n",
       " 'Mileage',\n",
       " 'Model code',\n",
       " 'Non-smoker vehicle',\n",
       " 'Offer number',\n",
       " 'Other fuel types',\n",
       " 'Paint',\n",
       " 'Power',\n",
       " 'Power consumption',\n",
       " 'Power consumption (WLTP)',\n",
       " 'Previous owner',\n",
       " 'Production date',\n",
       " 'Seats',\n",
       " 'Taxi or rental car',\n",
       " 'Type',\n",
       " 'Upholstery',\n",
       " 'Upholstery colour',\n",
       " 'Warranty',\n",
       " 'desc',\n",
       " 'location',\n",
       " 'make',\n",
       " 'make_model',\n",
       " 'model',\n",
       " 'price',\n",
       " 'seller',\n",
       " 'short_description']"
      ]
     },
     "execution_count": 166,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sorted(df.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 172,
   "id": "b5931ac9-18dd-4768-b81c-4880ea28669b",
   "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>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>make_model</th>\n",
       "      <td>Mercedes-Benz A 160</td>\n",
       "      <td>Mercedes-Benz EQE 350</td>\n",
       "      <td>Mercedes-Benz A 45 AMG</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>short_description</th>\n",
       "      <td>CDi</td>\n",
       "      <td>350+</td>\n",
       "      <td>S 4Matic+ 8G-DCT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>make</th>\n",
       "      <td>\\nMercedes-Benz\\n</td>\n",
       "      <td>\\nMercedes-Benz\\n</td>\n",
       "      <td>\\nMercedes-Benz\\n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>model</th>\n",
       "      <td>[\\n, A 160 ,\\n]</td>\n",
       "      <td>[\\n, EQE 350 ,\\n]</td>\n",
       "      <td>[\\n, A 45 AMG ,\\n]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>location</th>\n",
       "      <td>P.I. EL PALMAR C/FORJA 6,  11500 PUERTO DE SAN...</td>\n",
       "      <td>APARTADO DE CORREOS 1032,  26140 LOGROÑO, ES</td>\n",
       "      <td>PORT. TARRACO, MOLL DE LLEVANT, Nº 5, LOC. 6-8...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>price</th>\n",
       "      <td>€ 16,950.-</td>\n",
       "      <td>€ 80,900.-</td>\n",
       "      <td>€ 69,900.-</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>body_type</th>\n",
       "      <td>[\\n, Compact, \\n]</td>\n",
       "      <td>[\\n, Compact, \\n]</td>\n",
       "      <td>[\\n, Compact, \\n]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>type</th>\n",
       "      <td>[\\n, Used, \\n]</td>\n",
       "      <td>[\\n, Pre-registered, \\n]</td>\n",
       "      <td>[\\n, Used, \\n]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>doors</th>\n",
       "      <td>[\\n, 5, \\n]</td>\n",
       "      <td>[\\n, 4, \\n]</td>\n",
       "      <td>[\\n, 5, \\n]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>country_version</th>\n",
       "      <td>[\\n, Spain, \\n]</td>\n",
       "      <td>[\\n, Spain, \\n]</td>\n",
       "      <td>[\\n, Spain, \\n]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>offer_number</th>\n",
       "      <td>[\\n, 7468157, \\n]</td>\n",
       "      <td>[\\n, 7054863, \\n]</td>\n",
       "      <td>[\\n, 7410454, \\n]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>warranty</th>\n",
       "      <td>[\\n, 24 months, \\n]</td>\n",
       "      <td>[\\n, 24 months, \\n]</td>\n",
       "      <td>[\\n, 12 months, \\n]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mileage</th>\n",
       "      <td>120,200 km</td>\n",
       "      <td>5,000 km</td>\n",
       "      <td>18,900 km</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>first_registration</th>\n",
       "      <td>06/2016</td>\n",
       "      <td>06/2022</td>\n",
       "      <td>07/2020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>gearbox</th>\n",
       "      <td>[\\nManual\\n]</td>\n",
       "      <td>[\\nAutomatic\\n]</td>\n",
       "      <td>[\\nAutomatic\\n]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fuel_type</th>\n",
       "      <td>Diesel</td>\n",
       "      <td>Electric</td>\n",
       "      <td>Gasoline</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>colour</th>\n",
       "      <td>Black</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Grey</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>paint</th>\n",
       "      <td>Metallic</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>desc</th>\n",
       "      <td>[ , Precio al contado: 16950 euros,  ,  , Vehí...</td>\n",
       "      <td>[ , Precio al contado: 88900 euros,  , AUTO OJ...</td>\n",
       "      <td>[Gris MANUFAKTUR mountaingrau magno,  , Linea/...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>seller</th>\n",
       "      <td>Dealer</td>\n",
       "      <td>Dealer</td>\n",
       "      <td>Dealer</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>seats</th>\n",
       "      <td>NaN</td>\n",
       "      <td>[\\n, 5, \\n]</td>\n",
       "      <td>[\\n, 5, \\n]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>power</th>\n",
       "      <td>NaN</td>\n",
       "      <td>[\\n215 kW (292 hp)\\n]</td>\n",
       "      <td>[\\n310 kW (421 hp)\\n]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>engine_size</th>\n",
       "      <td>NaN</td>\n",
       "      <td>[\\n1 cc\\n]</td>\n",
       "      <td>[\\n1,991 cc\\n]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>gears</th>\n",
       "      <td>NaN</td>\n",
       "      <td>[\\n9\\n]</td>\n",
       "      <td>[\\n8\\n]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>co_emissions</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0 g/km (comb.)</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>manufacturer_colour</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Negro Obsidiana</td>\n",
       "      <td>Mountaingrau magno</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>drivetrain</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[\\n, 4WD, \\n]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cylinders</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[\\n4\\n]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fuel_consumption</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[[8.4 l/100 km (comb.)], [10.9 l/100 km (city)...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>comfort_&amp;_convenience</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>entertainment_&amp;_media</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>safety_&amp;_security</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>extras</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>empty_weight</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>model_code</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>general_inspection</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>last_service</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>full_service_history</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>non_smoker_vehicle</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>emission_class</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>emissions_sticker</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>upholstery_colour</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>upholstery</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>production_date</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>previous_owner</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>other_fuel_types</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>power_consumption</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>energy_efficiency_class</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>co_efficiency</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fuel_consumption_wltp</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>co_emissions_wltp</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>available_from</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>taxi_or_rental_car</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>availability</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>last_timing_belt_change</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>electric_range_wltp</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>power_consumption_wltp</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>battery_ownership</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                                         0  \\\n",
       "make_model                                             Mercedes-Benz A 160   \n",
       "short_description                                                      CDi   \n",
       "make                                                     \\nMercedes-Benz\\n   \n",
       "model                                                      [\\n, A 160 ,\\n]   \n",
       "location                 P.I. EL PALMAR C/FORJA 6,  11500 PUERTO DE SAN...   \n",
       "price                                                           € 16,950.-   \n",
       "body_type                                                [\\n, Compact, \\n]   \n",
       "type                                                        [\\n, Used, \\n]   \n",
       "doors                                                          [\\n, 5, \\n]   \n",
       "country_version                                            [\\n, Spain, \\n]   \n",
       "offer_number                                             [\\n, 7468157, \\n]   \n",
       "warranty                                               [\\n, 24 months, \\n]   \n",
       "mileage                                                         120,200 km   \n",
       "first_registration                                                 06/2016   \n",
       "gearbox                                                       [\\nManual\\n]   \n",
       "fuel_type                                                           Diesel   \n",
       "colour                                                               Black   \n",
       "paint                                                             Metallic   \n",
       "desc                     [ , Precio al contado: 16950 euros,  ,  , Vehí...   \n",
       "seller                                                              Dealer   \n",
       "seats                                                                  NaN   \n",
       "power                                                                  NaN   \n",
       "engine_size                                                            NaN   \n",
       "gears                                                                  NaN   \n",
       "co_emissions                                                           NaN   \n",
       "manufacturer_colour                                                    NaN   \n",
       "drivetrain                                                             NaN   \n",
       "cylinders                                                              NaN   \n",
       "fuel_consumption                                                       NaN   \n",
       "comfort_&_convenience                                                  NaN   \n",
       "entertainment_&_media                                                  NaN   \n",
       "safety_&_security                                                      NaN   \n",
       "extras                                                                 NaN   \n",
       "empty_weight                                                           NaN   \n",
       "model_code                                                             NaN   \n",
       "general_inspection                                                     NaN   \n",
       "last_service                                                           NaN   \n",
       "full_service_history                                                   NaN   \n",
       "non_smoker_vehicle                                                     NaN   \n",
       "emission_class                                                         NaN   \n",
       "emissions_sticker                                                      NaN   \n",
       "upholstery_colour                                                      NaN   \n",
       "upholstery                                                             NaN   \n",
       "production_date                                                        NaN   \n",
       "previous_owner                                                         NaN   \n",
       "other_fuel_types                                                       NaN   \n",
       "power_consumption                                                      NaN   \n",
       "energy_efficiency_class                                                NaN   \n",
       "co_efficiency                                                          NaN   \n",
       "fuel_consumption_wltp                                                  NaN   \n",
       "co_emissions_wltp                                                      NaN   \n",
       "available_from                                                         NaN   \n",
       "taxi_or_rental_car                                                     NaN   \n",
       "availability                                                           NaN   \n",
       "last_timing_belt_change                                                NaN   \n",
       "electric_range_wltp                                                    NaN   \n",
       "power_consumption_wltp                                                 NaN   \n",
       "battery_ownership                                                      NaN   \n",
       "\n",
       "                                                                         1  \\\n",
       "make_model                                           Mercedes-Benz EQE 350   \n",
       "short_description                                                     350+   \n",
       "make                                                     \\nMercedes-Benz\\n   \n",
       "model                                                    [\\n, EQE 350 ,\\n]   \n",
       "location                      APARTADO DE CORREOS 1032,  26140 LOGROÑO, ES   \n",
       "price                                                           € 80,900.-   \n",
       "body_type                                                [\\n, Compact, \\n]   \n",
       "type                                              [\\n, Pre-registered, \\n]   \n",
       "doors                                                          [\\n, 4, \\n]   \n",
       "country_version                                            [\\n, Spain, \\n]   \n",
       "offer_number                                             [\\n, 7054863, \\n]   \n",
       "warranty                                               [\\n, 24 months, \\n]   \n",
       "mileage                                                           5,000 km   \n",
       "first_registration                                                 06/2022   \n",
       "gearbox                                                    [\\nAutomatic\\n]   \n",
       "fuel_type                                                         Electric   \n",
       "colour                                                                 NaN   \n",
       "paint                                                                  NaN   \n",
       "desc                     [ , Precio al contado: 88900 euros,  , AUTO OJ...   \n",
       "seller                                                              Dealer   \n",
       "seats                                                          [\\n, 5, \\n]   \n",
       "power                                                [\\n215 kW (292 hp)\\n]   \n",
       "engine_size                                                     [\\n1 cc\\n]   \n",
       "gears                                                              [\\n9\\n]   \n",
       "co_emissions                                                0 g/km (comb.)   \n",
       "manufacturer_colour                                        Negro Obsidiana   \n",
       "drivetrain                                                             NaN   \n",
       "cylinders                                                              NaN   \n",
       "fuel_consumption                                                       NaN   \n",
       "comfort_&_convenience                                                  NaN   \n",
       "entertainment_&_media                                                  NaN   \n",
       "safety_&_security                                                      NaN   \n",
       "extras                                                                 NaN   \n",
       "empty_weight                                                           NaN   \n",
       "model_code                                                             NaN   \n",
       "general_inspection                                                     NaN   \n",
       "last_service                                                           NaN   \n",
       "full_service_history                                                   NaN   \n",
       "non_smoker_vehicle                                                     NaN   \n",
       "emission_class                                                         NaN   \n",
       "emissions_sticker                                                      NaN   \n",
       "upholstery_colour                                                      NaN   \n",
       "upholstery                                                             NaN   \n",
       "production_date                                                        NaN   \n",
       "previous_owner                                                         NaN   \n",
       "other_fuel_types                                                       NaN   \n",
       "power_consumption                                                      NaN   \n",
       "energy_efficiency_class                                                NaN   \n",
       "co_efficiency                                                          NaN   \n",
       "fuel_consumption_wltp                                                  NaN   \n",
       "co_emissions_wltp                                                      NaN   \n",
       "available_from                                                         NaN   \n",
       "taxi_or_rental_car                                                     NaN   \n",
       "availability                                                           NaN   \n",
       "last_timing_belt_change                                                NaN   \n",
       "electric_range_wltp                                                    NaN   \n",
       "power_consumption_wltp                                                 NaN   \n",
       "battery_ownership                                                      NaN   \n",
       "\n",
       "                                                                         2  \n",
       "make_model                                          Mercedes-Benz A 45 AMG  \n",
       "short_description                                         S 4Matic+ 8G-DCT  \n",
       "make                                                     \\nMercedes-Benz\\n  \n",
       "model                                                   [\\n, A 45 AMG ,\\n]  \n",
       "location                 PORT. TARRACO, MOLL DE LLEVANT, Nº 5, LOC. 6-8...  \n",
       "price                                                           € 69,900.-  \n",
       "body_type                                                [\\n, Compact, \\n]  \n",
       "type                                                        [\\n, Used, \\n]  \n",
       "doors                                                          [\\n, 5, \\n]  \n",
       "country_version                                            [\\n, Spain, \\n]  \n",
       "offer_number                                             [\\n, 7410454, \\n]  \n",
       "warranty                                               [\\n, 12 months, \\n]  \n",
       "mileage                                                          18,900 km  \n",
       "first_registration                                                 07/2020  \n",
       "gearbox                                                    [\\nAutomatic\\n]  \n",
       "fuel_type                                                         Gasoline  \n",
       "colour                                                                Grey  \n",
       "paint                                                                  NaN  \n",
       "desc                     [Gris MANUFAKTUR mountaingrau magno,  , Linea/...  \n",
       "seller                                                              Dealer  \n",
       "seats                                                          [\\n, 5, \\n]  \n",
       "power                                                [\\n310 kW (421 hp)\\n]  \n",
       "engine_size                                                 [\\n1,991 cc\\n]  \n",
       "gears                                                              [\\n8\\n]  \n",
       "co_emissions                                                           NaN  \n",
       "manufacturer_colour                                     Mountaingrau magno  \n",
       "drivetrain                                                   [\\n, 4WD, \\n]  \n",
       "cylinders                                                          [\\n4\\n]  \n",
       "fuel_consumption         [[8.4 l/100 km (comb.)], [10.9 l/100 km (city)...  \n",
       "comfort_&_convenience                                                  NaN  \n",
       "entertainment_&_media                                                  NaN  \n",
       "safety_&_security                                                      NaN  \n",
       "extras                                                                 NaN  \n",
       "empty_weight                                                           NaN  \n",
       "model_code                                                             NaN  \n",
       "general_inspection                                                     NaN  \n",
       "last_service                                                           NaN  \n",
       "full_service_history                                                   NaN  \n",
       "non_smoker_vehicle                                                     NaN  \n",
       "emission_class                                                         NaN  \n",
       "emissions_sticker                                                      NaN  \n",
       "upholstery_colour                                                      NaN  \n",
       "upholstery                                                             NaN  \n",
       "production_date                                                        NaN  \n",
       "previous_owner                                                         NaN  \n",
       "other_fuel_types                                                       NaN  \n",
       "power_consumption                                                      NaN  \n",
       "energy_efficiency_class                                                NaN  \n",
       "co_efficiency                                                          NaN  \n",
       "fuel_consumption_wltp                                                  NaN  \n",
       "co_emissions_wltp                                                      NaN  \n",
       "available_from                                                         NaN  \n",
       "taxi_or_rental_car                                                     NaN  \n",
       "availability                                                           NaN  \n",
       "last_timing_belt_change                                                NaN  \n",
       "electric_range_wltp                                                    NaN  \n",
       "power_consumption_wltp                                                 NaN  \n",
       "battery_ownership                                                      NaN  "
      ]
     },
     "execution_count": 172,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Renaming Column Names\n",
    "\n",
    "from skimpy import clean_columns\n",
    "\n",
    "df = clean_columns(df)\n",
    "df.head(3).T\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 174,
   "id": "9c686afd-8771-4d22-8ae0-5a6eff594139",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['make_model', 'short_description', 'make', 'model', 'location', 'price',\n",
       "       'Body type', 'Type', 'Doors', 'Country version', 'Offer number',\n",
       "       'Warranty', 'Mileage', 'First registration', 'Gearbox', 'Fuel type',\n",
       "       'Colour', 'Paint', 'desc', 'seller', 'Seats', 'Power', 'Engine size',\n",
       "       'Gears', 'CO₂-emissions', 'Manufacturer colour', 'Drivetrain',\n",
       "       'Cylinders', 'Fuel consumption', '\\nComfort & Convenience\\n',\n",
       "       '\\nEntertainment & Media\\n', '\\nSafety & Security\\n', '\\nExtras\\n',\n",
       "       'Empty weight', 'Model code', 'General inspection', 'Last service',\n",
       "       'Full service history', 'Non-smoker vehicle', 'Emission class',\n",
       "       'Emissions sticker', 'Upholstery colour', 'Upholstery',\n",
       "       'Production date', 'Previous owner', 'Other fuel types',\n",
       "       'Power consumption', 'Energy efficiency class', 'CO₂-efficiency',\n",
       "       'Fuel consumption (WLTP)', 'CO₂-emissions (WLTP)', 'Available from',\n",
       "       'Taxi or rental car', 'Availability', 'Last timing belt change',\n",
       "       'Electric Range (WLTP)', 'Power consumption (WLTP)',\n",
       "       'Battery Ownership'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 174,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df0.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 176,
   "id": "20149922-91bc-4a16-8c4f-b666ea3b0350",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['availability',\n",
       " 'available_from',\n",
       " 'battery_ownership',\n",
       " 'body_type',\n",
       " 'co_efficiency',\n",
       " 'co_emissions',\n",
       " 'co_emissions_wltp',\n",
       " 'colour',\n",
       " 'comfort_&_convenience',\n",
       " 'country_version',\n",
       " 'cylinders',\n",
       " 'desc',\n",
       " 'doors',\n",
       " 'drivetrain',\n",
       " 'electric_range_wltp',\n",
       " 'emission_class',\n",
       " 'emissions_sticker',\n",
       " 'empty_weight',\n",
       " 'energy_efficiency_class',\n",
       " 'engine_size',\n",
       " 'entertainment_&_media',\n",
       " 'extras',\n",
       " 'first_registration',\n",
       " 'fuel_consumption',\n",
       " 'fuel_consumption_wltp',\n",
       " 'fuel_type',\n",
       " 'full_service_history',\n",
       " 'gearbox',\n",
       " 'gears',\n",
       " 'general_inspection',\n",
       " 'last_service',\n",
       " 'last_timing_belt_change',\n",
       " 'location',\n",
       " 'make',\n",
       " 'make_model',\n",
       " 'manufacturer_colour',\n",
       " 'mileage',\n",
       " 'model',\n",
       " 'model_code',\n",
       " 'non_smoker_vehicle',\n",
       " 'offer_number',\n",
       " 'other_fuel_types',\n",
       " 'paint',\n",
       " 'power',\n",
       " 'power_consumption',\n",
       " 'power_consumption_wltp',\n",
       " 'previous_owner',\n",
       " 'price',\n",
       " 'production_date',\n",
       " 'safety_&_security',\n",
       " 'seats',\n",
       " 'seller',\n",
       " 'short_description',\n",
       " 'taxi_or_rental_car',\n",
       " 'type',\n",
       " 'upholstery',\n",
       " 'upholstery_colour',\n",
       " 'warranty']"
      ]
     },
     "execution_count": 176,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "columns_sorted = sorted(df.columns)\n",
    "columns_sorted"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 178,
   "id": "23d396d1-ade4-465d-8507-25660fce5e6f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">╭──────────────────────────────────────────────── skimpy summary ─────────────────────────────────────────────────╮\n",
       "│ <span style=\"font-style: italic\">         Data Summary         </span> <span style=\"font-style: italic\">      Data Types       </span>                                                          │\n",
       "│ ┏━━━━━━━━━━━━━━━━━━━┳━━━━━━━━┓ ┏━━━━━━━━━━━━━┳━━━━━━━┓                                                          │\n",
       "│ ┃<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\"> dataframe         </span>┃<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\"> Values </span>┃ ┃<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\"> Column Type </span>┃<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\"> Count </span>┃                                                          │\n",
       "│ ┡━━━━━━━━━━━━━━━━━━━╇━━━━━━━━┩ ┡━━━━━━━━━━━━━╇━━━━━━━┩                                                          │\n",
       "│ │ Number of rows    │ 29480  │ │ string      │ 32    │                                                          │\n",
       "│ │ Number of columns │ 33     │ │ float64     │ 1     │                                                          │\n",
       "│ └───────────────────┴────────┘ └─────────────┴───────┘                                                          │\n",
       "│ <span style=\"font-style: italic\">                                                    number                                                    </span>  │\n",
       "│ ┏━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━┳━━━━━━━┳━━━━━━━━━┳━━━━━━━┳━━━━━━━┳━━━━━━━┳━━━━━━━┳━━━━━━━┳━━━━━━━━┓  │\n",
       "│ ┃<span style=\"font-weight: bold\"> column_name         </span>┃<span style=\"font-weight: bold\"> NA      </span>┃<span style=\"font-weight: bold\"> NA %    </span>┃<span style=\"font-weight: bold\"> mean  </span>┃<span style=\"font-weight: bold\"> sd      </span>┃<span style=\"font-weight: bold\"> p0    </span>┃<span style=\"font-weight: bold\"> p25   </span>┃<span style=\"font-weight: bold\"> p50   </span>┃<span style=\"font-weight: bold\"> p75   </span>┃<span style=\"font-weight: bold\"> p100  </span>┃<span style=\"font-weight: bold\"> hist   </span>┃  │\n",
       "│ ┡━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━╇━━━━━━━╇━━━━━━━━━╇━━━━━━━╇━━━━━━━╇━━━━━━━╇━━━━━━━╇━━━━━━━╇━━━━━━━━┩  │\n",
       "│ │ <span style=\"color: #af87ff; text-decoration-color: #af87ff\">production_date    </span> │ <span style=\"color: #008080; text-decoration-color: #008080\">  23572</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">  79.96</span> │ <span style=\"color: #008080; text-decoration-color: #008080\"> 2018</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">  6.493</span> │ <span style=\"color: #008080; text-decoration-color: #008080\"> 1954</span> │ <span style=\"color: #008080; text-decoration-color: #008080\"> 2018</span> │ <span style=\"color: #008080; text-decoration-color: #008080\"> 2019</span> │ <span style=\"color: #008080; text-decoration-color: #008080\"> 2021</span> │ <span style=\"color: #008080; text-decoration-color: #008080\"> 2022</span> │ <span style=\"color: #008000; text-decoration-color: #008000\">     ▇</span> │  │\n",
       "│ └─────────────────────┴─────────┴─────────┴───────┴─────────┴───────┴───────┴───────┴───────┴───────┴────────┘  │\n",
       "│ <span style=\"font-style: italic\">                                                    string                                                    </span>  │\n",
       "│ ┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━┳━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━┓  │\n",
       "│ ┃<span style=\"font-weight: bold\"> column_name                        </span>┃<span style=\"font-weight: bold\"> NA         </span>┃<span style=\"font-weight: bold\"> NA %       </span>┃<span style=\"font-weight: bold\"> words per row          </span>┃<span style=\"font-weight: bold\"> total words        </span>┃  │\n",
       "│ ┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━╇━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━┩  │\n",
       "│ │ <span style=\"color: #af87ff; text-decoration-color: #af87ff\">make_model                        </span> │ <span style=\"color: #008080; text-decoration-color: #008080\">       850</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">      2.88</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">                   2.1</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">             61645</span> │  │\n",
       "│ │ <span style=\"color: #af87ff; text-decoration-color: #af87ff\">short_description                 </span> │ <span style=\"color: #008080; text-decoration-color: #008080\">       850</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">      2.88</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">                   5.1</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">            150035</span> │  │\n",
       "│ │ <span style=\"color: #af87ff; text-decoration-color: #af87ff\">make                              </span> │ <span style=\"color: #008080; text-decoration-color: #008080\">       850</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">      2.88</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">                  0.97</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">             28630</span> │  │\n",
       "│ │ <span style=\"color: #af87ff; text-decoration-color: #af87ff\">location                          </span> │ <span style=\"color: #008080; text-decoration-color: #008080\">       850</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">      2.88</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">                   7.3</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">            214201</span> │  │\n",
       "│ │ <span style=\"color: #af87ff; text-decoration-color: #af87ff\">price                             </span> │ <span style=\"color: #008080; text-decoration-color: #008080\">       850</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">      2.88</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">                   1.9</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">             57260</span> │  │\n",
       "│ │ <span style=\"color: #af87ff; text-decoration-color: #af87ff\">mileage                           </span> │ <span style=\"color: #008080; text-decoration-color: #008080\">       851</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">      2.89</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">                   1.9</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">             57258</span> │  │\n",
       "│ │ <span style=\"color: #af87ff; text-decoration-color: #af87ff\">first_registration                </span> │ <span style=\"color: #008080; text-decoration-color: #008080\">       852</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">      2.89</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">                  0.97</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">             28628</span> │  │\n",
       "│ │ <span style=\"color: #af87ff; text-decoration-color: #af87ff\">fuel_type                         </span> │ <span style=\"color: #008080; text-decoration-color: #008080\">      2637</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">      8.95</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">                   1.6</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">             47219</span> │  │\n",
       "│ │ <span style=\"color: #af87ff; text-decoration-color: #af87ff\">colour                            </span> │ <span style=\"color: #008080; text-decoration-color: #008080\">      2574</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">      8.73</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">                  0.91</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">             26906</span> │  │\n",
       "│ │ <span style=\"color: #af87ff; text-decoration-color: #af87ff\">paint                             </span> │ <span style=\"color: #008080; text-decoration-color: #008080\">     14985</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">     50.83</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">                  0.49</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">             14495</span> │  │\n",
       "│ │ <span style=\"color: #af87ff; text-decoration-color: #af87ff\">seller                            </span> │ <span style=\"color: #008080; text-decoration-color: #008080\">       850</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">      2.88</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">                     1</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">             30942</span> │  │\n",
       "│ │ <span style=\"color: #af87ff; text-decoration-color: #af87ff\">co_emissions                      </span> │ <span style=\"color: #008080; text-decoration-color: #008080\">     10886</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">     36.93</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">                   1.9</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">             55800</span> │  │\n",
       "│ │ <span style=\"color: #af87ff; text-decoration-color: #af87ff\">manufacturer_colour               </span> │ <span style=\"color: #008080; text-decoration-color: #008080\">      7693</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">      26.1</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">                   1.4</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">             40514</span> │  │\n",
       "│ │ <span style=\"color: #af87ff; text-decoration-color: #af87ff\">general_inspection                </span> │ <span style=\"color: #008080; text-decoration-color: #008080\">     17226</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">     58.43</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">                  0.42</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">             12254</span> │  │\n",
       "│ │ <span style=\"color: #af87ff; text-decoration-color: #af87ff\">last_service                      </span> │ <span style=\"color: #008080; text-decoration-color: #008080\">     27477</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">     93.21</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">                 0.068</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">              2003</span> │  │\n",
       "│ │ <span style=\"color: #af87ff; text-decoration-color: #af87ff\">full_service_history              </span> │ <span style=\"color: #008080; text-decoration-color: #008080\">     16915</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">     57.38</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">                  0.43</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">             12565</span> │  │\n",
       "│ │ <span style=\"color: #af87ff; text-decoration-color: #af87ff\">non_smoker_vehicle                </span> │ <span style=\"color: #008080; text-decoration-color: #008080\">     17886</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">     60.67</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">                  0.39</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">             11594</span> │  │\n",
       "│ │ <span style=\"color: #af87ff; text-decoration-color: #af87ff\">emission_class                    </span> │ <span style=\"color: #008080; text-decoration-color: #008080\">     11621</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">     39.42</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">                   1.2</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">             35718</span> │  │\n",
       "│ │ <span style=\"color: #af87ff; text-decoration-color: #af87ff\">emissions_sticker                 </span> │ <span style=\"color: #008080; text-decoration-color: #008080\">     20066</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">     68.07</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">                  0.64</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">             19004</span> │  │\n",
       "│ │ <span style=\"color: #af87ff; text-decoration-color: #af87ff\">upholstery_colour                 </span> │ <span style=\"color: #008080; text-decoration-color: #008080\">     14911</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">     50.58</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">                  0.49</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">             14569</span> │  │\n",
       "│ │ <span style=\"color: #af87ff; text-decoration-color: #af87ff\">upholstery                        </span> │ <span style=\"color: #008080; text-decoration-color: #008080\">     10870</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">     36.87</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">                  0.91</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">             26884</span> │  │\n",
       "│ │ <span style=\"color: #af87ff; text-decoration-color: #af87ff\">other_fuel_types                  </span> │ <span style=\"color: #008080; text-decoration-color: #008080\">     27167</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">     92.15</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">                 0.079</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">              2315</span> │  │\n",
       "│ │ <span style=\"color: #af87ff; text-decoration-color: #af87ff\">power_consumption                 </span> │ <span style=\"color: #008080; text-decoration-color: #008080\">     28965</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">     98.25</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">                  0.07</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">              2060</span> │  │\n",
       "│ │ <span style=\"color: #af87ff; text-decoration-color: #af87ff\">energy_efficiency_class           </span> │ <span style=\"color: #008080; text-decoration-color: #008080\">     21676</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">     73.53</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">                  0.26</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">              7804</span> │  │\n",
       "│ │ <span style=\"color: #af87ff; text-decoration-color: #af87ff\">co_efficiency                     </span> │ <span style=\"color: #008080; text-decoration-color: #008080\">     21676</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">     73.53</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">                   3.7</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">            109256</span> │  │\n",
       "│ │ <span style=\"color: #af87ff; text-decoration-color: #af87ff\">fuel_consumption_wltp             </span> │ <span style=\"color: #008080; text-decoration-color: #008080\">     29380</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">     99.66</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">                  0.01</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">               300</span> │  │\n",
       "│ │ <span style=\"color: #af87ff; text-decoration-color: #af87ff\">co_emissions_wltp                 </span> │ <span style=\"color: #008080; text-decoration-color: #008080\">     29364</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">     99.61</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">                 0.012</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">               348</span> │  │\n",
       "│ │ <span style=\"color: #af87ff; text-decoration-color: #af87ff\">taxi_or_rental_car                </span> │ <span style=\"color: #008080; text-decoration-color: #008080\">     29058</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">     98.57</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">                 0.014</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">               422</span> │  │\n",
       "│ │ <span style=\"color: #af87ff; text-decoration-color: #af87ff\">last_timing_belt_change           </span> │ <span style=\"color: #008080; text-decoration-color: #008080\">     28908</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">     98.06</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">                 0.019</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">               572</span> │  │\n",
       "│ │ <span style=\"color: #af87ff; text-decoration-color: #af87ff\">electric_range_wltp               </span> │ <span style=\"color: #008080; text-decoration-color: #008080\">     29464</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">     99.95</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">                0.0023</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">                68</span> │  │\n",
       "│ │ <span style=\"color: #af87ff; text-decoration-color: #af87ff\">power_consumption_wltp            </span> │ <span style=\"color: #008080; text-decoration-color: #008080\">     29464</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">     99.95</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">                0.0016</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">                48</span> │  │\n",
       "│ │ <span style=\"color: #af87ff; text-decoration-color: #af87ff\">battery_ownership                 </span> │ <span style=\"color: #008080; text-decoration-color: #008080\">     29473</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">     99.98</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">               0.00024</span> │ <span style=\"color: #008080; text-decoration-color: #008080\">                 7</span> │  │\n",
       "│ └────────────────────────────────────┴────────────┴────────────┴────────────────────────┴────────────────────┘  │\n",
       "╰────────────────────────────────────────────────────── End ──────────────────────────────────────────────────────╯\n",
       "</pre>\n"
      ],
      "text/plain": [
       "╭──────────────────────────────────────────────── skimpy summary ─────────────────────────────────────────────────╮\n",
       "│ \u001b[3m         Data Summary         \u001b[0m \u001b[3m      Data Types       \u001b[0m                                                          │\n",
       "│ ┏━━━━━━━━━━━━━━━━━━━┳━━━━━━━━┓ ┏━━━━━━━━━━━━━┳━━━━━━━┓                                                          │\n",
       "│ ┃\u001b[1;36m \u001b[0m\u001b[1;36mdataframe        \u001b[0m\u001b[1;36m \u001b[0m┃\u001b[1;36m \u001b[0m\u001b[1;36mValues\u001b[0m\u001b[1;36m \u001b[0m┃ ┃\u001b[1;36m \u001b[0m\u001b[1;36mColumn Type\u001b[0m\u001b[1;36m \u001b[0m┃\u001b[1;36m \u001b[0m\u001b[1;36mCount\u001b[0m\u001b[1;36m \u001b[0m┃                                                          │\n",
       "│ ┡━━━━━━━━━━━━━━━━━━━╇━━━━━━━━┩ ┡━━━━━━━━━━━━━╇━━━━━━━┩                                                          │\n",
       "│ │ Number of rows    │ 29480  │ │ string      │ 32    │                                                          │\n",
       "│ │ Number of columns │ 33     │ │ float64     │ 1     │                                                          │\n",
       "│ └───────────────────┴────────┘ └─────────────┴───────┘                                                          │\n",
       "│ \u001b[3m                                                    number                                                    \u001b[0m  │\n",
       "│ ┏━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━┳━━━━━━━┳━━━━━━━━━┳━━━━━━━┳━━━━━━━┳━━━━━━━┳━━━━━━━┳━━━━━━━┳━━━━━━━━┓  │\n",
       "│ ┃\u001b[1m \u001b[0m\u001b[1mcolumn_name        \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mNA     \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mNA %   \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mmean \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1msd     \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mp0   \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mp25  \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mp50  \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mp75  \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mp100 \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mhist  \u001b[0m\u001b[1m \u001b[0m┃  │\n",
       "│ ┡━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━╇━━━━━━━╇━━━━━━━━━╇━━━━━━━╇━━━━━━━╇━━━━━━━╇━━━━━━━╇━━━━━━━╇━━━━━━━━┩  │\n",
       "│ │ \u001b[38;5;141mproduction_date    \u001b[0m │ \u001b[36m  23572\u001b[0m │ \u001b[36m  79.96\u001b[0m │ \u001b[36m 2018\u001b[0m │ \u001b[36m  6.493\u001b[0m │ \u001b[36m 1954\u001b[0m │ \u001b[36m 2018\u001b[0m │ \u001b[36m 2019\u001b[0m │ \u001b[36m 2021\u001b[0m │ \u001b[36m 2022\u001b[0m │ \u001b[32m     ▇\u001b[0m │  │\n",
       "│ └─────────────────────┴─────────┴─────────┴───────┴─────────┴───────┴───────┴───────┴───────┴───────┴────────┘  │\n",
       "│ \u001b[3m                                                    string                                                    \u001b[0m  │\n",
       "│ ┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━┳━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━┓  │\n",
       "│ ┃\u001b[1m \u001b[0m\u001b[1mcolumn_name                       \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mNA        \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mNA %      \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mwords per row         \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mtotal words       \u001b[0m\u001b[1m \u001b[0m┃  │\n",
       "│ ┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━╇━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━┩  │\n",
       "│ │ \u001b[38;5;141mmake_model                        \u001b[0m │ \u001b[36m       850\u001b[0m │ \u001b[36m      2.88\u001b[0m │ \u001b[36m                   2.1\u001b[0m │ \u001b[36m             61645\u001b[0m │  │\n",
       "│ │ \u001b[38;5;141mshort_description                 \u001b[0m │ \u001b[36m       850\u001b[0m │ \u001b[36m      2.88\u001b[0m │ \u001b[36m                   5.1\u001b[0m │ \u001b[36m            150035\u001b[0m │  │\n",
       "│ │ \u001b[38;5;141mmake                              \u001b[0m │ \u001b[36m       850\u001b[0m │ \u001b[36m      2.88\u001b[0m │ \u001b[36m                  0.97\u001b[0m │ \u001b[36m             28630\u001b[0m │  │\n",
       "│ │ \u001b[38;5;141mlocation                          \u001b[0m │ \u001b[36m       850\u001b[0m │ \u001b[36m      2.88\u001b[0m │ \u001b[36m                   7.3\u001b[0m │ \u001b[36m            214201\u001b[0m │  │\n",
       "│ │ \u001b[38;5;141mprice                             \u001b[0m │ \u001b[36m       850\u001b[0m │ \u001b[36m      2.88\u001b[0m │ \u001b[36m                   1.9\u001b[0m │ \u001b[36m             57260\u001b[0m │  │\n",
       "│ │ \u001b[38;5;141mmileage                           \u001b[0m │ \u001b[36m       851\u001b[0m │ \u001b[36m      2.89\u001b[0m │ \u001b[36m                   1.9\u001b[0m │ \u001b[36m             57258\u001b[0m │  │\n",
       "│ │ \u001b[38;5;141mfirst_registration                \u001b[0m │ \u001b[36m       852\u001b[0m │ \u001b[36m      2.89\u001b[0m │ \u001b[36m                  0.97\u001b[0m │ \u001b[36m             28628\u001b[0m │  │\n",
       "│ │ \u001b[38;5;141mfuel_type                         \u001b[0m │ \u001b[36m      2637\u001b[0m │ \u001b[36m      8.95\u001b[0m │ \u001b[36m                   1.6\u001b[0m │ \u001b[36m             47219\u001b[0m │  │\n",
       "│ │ \u001b[38;5;141mcolour                            \u001b[0m │ \u001b[36m      2574\u001b[0m │ \u001b[36m      8.73\u001b[0m │ \u001b[36m                  0.91\u001b[0m │ \u001b[36m             26906\u001b[0m │  │\n",
       "│ │ \u001b[38;5;141mpaint                             \u001b[0m │ \u001b[36m     14985\u001b[0m │ \u001b[36m     50.83\u001b[0m │ \u001b[36m                  0.49\u001b[0m │ \u001b[36m             14495\u001b[0m │  │\n",
       "│ │ \u001b[38;5;141mseller                            \u001b[0m │ \u001b[36m       850\u001b[0m │ \u001b[36m      2.88\u001b[0m │ \u001b[36m                     1\u001b[0m │ \u001b[36m             30942\u001b[0m │  │\n",
       "│ │ \u001b[38;5;141mco_emissions                      \u001b[0m │ \u001b[36m     10886\u001b[0m │ \u001b[36m     36.93\u001b[0m │ \u001b[36m                   1.9\u001b[0m │ \u001b[36m             55800\u001b[0m │  │\n",
       "│ │ \u001b[38;5;141mmanufacturer_colour               \u001b[0m │ \u001b[36m      7693\u001b[0m │ \u001b[36m      26.1\u001b[0m │ \u001b[36m                   1.4\u001b[0m │ \u001b[36m             40514\u001b[0m │  │\n",
       "│ │ \u001b[38;5;141mgeneral_inspection                \u001b[0m │ \u001b[36m     17226\u001b[0m │ \u001b[36m     58.43\u001b[0m │ \u001b[36m                  0.42\u001b[0m │ \u001b[36m             12254\u001b[0m │  │\n",
       "│ │ \u001b[38;5;141mlast_service                      \u001b[0m │ \u001b[36m     27477\u001b[0m │ \u001b[36m     93.21\u001b[0m │ \u001b[36m                 0.068\u001b[0m │ \u001b[36m              2003\u001b[0m │  │\n",
       "│ │ \u001b[38;5;141mfull_service_history              \u001b[0m │ \u001b[36m     16915\u001b[0m │ \u001b[36m     57.38\u001b[0m │ \u001b[36m                  0.43\u001b[0m │ \u001b[36m             12565\u001b[0m │  │\n",
       "│ │ \u001b[38;5;141mnon_smoker_vehicle                \u001b[0m │ \u001b[36m     17886\u001b[0m │ \u001b[36m     60.67\u001b[0m │ \u001b[36m                  0.39\u001b[0m │ \u001b[36m             11594\u001b[0m │  │\n",
       "│ │ \u001b[38;5;141memission_class                    \u001b[0m │ \u001b[36m     11621\u001b[0m │ \u001b[36m     39.42\u001b[0m │ \u001b[36m                   1.2\u001b[0m │ \u001b[36m             35718\u001b[0m │  │\n",
       "│ │ \u001b[38;5;141memissions_sticker                 \u001b[0m │ \u001b[36m     20066\u001b[0m │ \u001b[36m     68.07\u001b[0m │ \u001b[36m                  0.64\u001b[0m │ \u001b[36m             19004\u001b[0m │  │\n",
       "│ │ \u001b[38;5;141mupholstery_colour                 \u001b[0m │ \u001b[36m     14911\u001b[0m │ \u001b[36m     50.58\u001b[0m │ \u001b[36m                  0.49\u001b[0m │ \u001b[36m             14569\u001b[0m │  │\n",
       "│ │ \u001b[38;5;141mupholstery                        \u001b[0m │ \u001b[36m     10870\u001b[0m │ \u001b[36m     36.87\u001b[0m │ \u001b[36m                  0.91\u001b[0m │ \u001b[36m             26884\u001b[0m │  │\n",
       "│ │ \u001b[38;5;141mother_fuel_types                  \u001b[0m │ \u001b[36m     27167\u001b[0m │ \u001b[36m     92.15\u001b[0m │ \u001b[36m                 0.079\u001b[0m │ \u001b[36m              2315\u001b[0m │  │\n",
       "│ │ \u001b[38;5;141mpower_consumption                 \u001b[0m │ \u001b[36m     28965\u001b[0m │ \u001b[36m     98.25\u001b[0m │ \u001b[36m                  0.07\u001b[0m │ \u001b[36m              2060\u001b[0m │  │\n",
       "│ │ \u001b[38;5;141menergy_efficiency_class           \u001b[0m │ \u001b[36m     21676\u001b[0m │ \u001b[36m     73.53\u001b[0m │ \u001b[36m                  0.26\u001b[0m │ \u001b[36m              7804\u001b[0m │  │\n",
       "│ │ \u001b[38;5;141mco_efficiency                     \u001b[0m │ \u001b[36m     21676\u001b[0m │ \u001b[36m     73.53\u001b[0m │ \u001b[36m                   3.7\u001b[0m │ \u001b[36m            109256\u001b[0m │  │\n",
       "│ │ \u001b[38;5;141mfuel_consumption_wltp             \u001b[0m │ \u001b[36m     29380\u001b[0m │ \u001b[36m     99.66\u001b[0m │ \u001b[36m                  0.01\u001b[0m │ \u001b[36m               300\u001b[0m │  │\n",
       "│ │ \u001b[38;5;141mco_emissions_wltp                 \u001b[0m │ \u001b[36m     29364\u001b[0m │ \u001b[36m     99.61\u001b[0m │ \u001b[36m                 0.012\u001b[0m │ \u001b[36m               348\u001b[0m │  │\n",
       "│ │ \u001b[38;5;141mtaxi_or_rental_car                \u001b[0m │ \u001b[36m     29058\u001b[0m │ \u001b[36m     98.57\u001b[0m │ \u001b[36m                 0.014\u001b[0m │ \u001b[36m               422\u001b[0m │  │\n",
       "│ │ \u001b[38;5;141mlast_timing_belt_change           \u001b[0m │ \u001b[36m     28908\u001b[0m │ \u001b[36m     98.06\u001b[0m │ \u001b[36m                 0.019\u001b[0m │ \u001b[36m               572\u001b[0m │  │\n",
       "│ │ \u001b[38;5;141melectric_range_wltp               \u001b[0m │ \u001b[36m     29464\u001b[0m │ \u001b[36m     99.95\u001b[0m │ \u001b[36m                0.0023\u001b[0m │ \u001b[36m                68\u001b[0m │  │\n",
       "│ │ \u001b[38;5;141mpower_consumption_wltp            \u001b[0m │ \u001b[36m     29464\u001b[0m │ \u001b[36m     99.95\u001b[0m │ \u001b[36m                0.0016\u001b[0m │ \u001b[36m                48\u001b[0m │  │\n",
       "│ │ \u001b[38;5;141mbattery_ownership                 \u001b[0m │ \u001b[36m     29473\u001b[0m │ \u001b[36m     99.98\u001b[0m │ \u001b[36m               0.00024\u001b[0m │ \u001b[36m                 7\u001b[0m │  │\n",
       "│ └────────────────────────────────────┴────────────┴────────────┴────────────────────────┴────────────────────┘  │\n",
       "╰────────────────────────────────────────────────────── End ──────────────────────────────────────────────────────╯\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "skim(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 184,
   "id": "262ecfdd-d402-432e-8c96-a0d032caf7a5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "make_model                   850\n",
       "short_description            850\n",
       "make                         850\n",
       "model                        850\n",
       "location                     850\n",
       "price                        850\n",
       "body_type                    850\n",
       "type                         850\n",
       "doors                       1209\n",
       "country_version            12591\n",
       "offer_number                6380\n",
       "warranty                   13696\n",
       "mileage                      851\n",
       "first_registration           852\n",
       "gearbox                     1098\n",
       "fuel_type                   2637\n",
       "colour                      2574\n",
       "paint                      14985\n",
       "desc                        1433\n",
       "seller                       850\n",
       "seats                       3975\n",
       "power                       1422\n",
       "engine_size                 2253\n",
       "gears                      10526\n",
       "co_emissions               10886\n",
       "manufacturer_colour         7693\n",
       "drivetrain                 12587\n",
       "cylinders                  10628\n",
       "fuel_consumption            6095\n",
       "comfort_&_convenience       4047\n",
       "entertainment_&_media       5836\n",
       "safety_&_security           4065\n",
       "extras                      6000\n",
       "empty_weight               11722\n",
       "model_code                 21113\n",
       "general_inspection         17226\n",
       "last_service               27477\n",
       "full_service_history       16915\n",
       "non_smoker_vehicle         17886\n",
       "emission_class             11621\n",
       "emissions_sticker          20066\n",
       "upholstery_colour          14911\n",
       "upholstery                 10870\n",
       "production_date            23572\n",
       "previous_owner             15465\n",
       "other_fuel_types           27167\n",
       "power_consumption          28965\n",
       "energy_efficiency_class    21676\n",
       "co_efficiency              21676\n",
       "fuel_consumption_wltp      29380\n",
       "co_emissions_wltp          29364\n",
       "available_from             29087\n",
       "taxi_or_rental_car         29058\n",
       "availability               29179\n",
       "last_timing_belt_change    28908\n",
       "electric_range_wltp        29464\n",
       "power_consumption_wltp     29464\n",
       "battery_ownership          29473\n",
       "dtype: int64"
      ]
     },
     "execution_count": 184,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    " # examination of missing values\n",
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 188,
   "id": "b591c629-47cf-4ce0-9afc-1236c4285636",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "make_model                 2.88\n",
       "short_description          2.88\n",
       "make                       2.88\n",
       "model                      2.88\n",
       "location                   2.88\n",
       "price                      2.88\n",
       "body_type                  2.88\n",
       "type                       2.88\n",
       "doors                      4.10\n",
       "country_version           42.71\n",
       "offer_number              21.64\n",
       "warranty                  46.46\n",
       "mileage                    2.89\n",
       "first_registration         2.89\n",
       "gearbox                    3.72\n",
       "fuel_type                  8.95\n",
       "colour                     8.73\n",
       "paint                     50.83\n",
       "desc                       4.86\n",
       "seller                     2.88\n",
       "seats                     13.48\n",
       "power                      4.82\n",
       "engine_size                7.64\n",
       "gears                     35.71\n",
       "co_emissions              36.93\n",
       "manufacturer_colour       26.10\n",
       "drivetrain                42.70\n",
       "cylinders                 36.05\n",
       "fuel_consumption          20.68\n",
       "comfort_&_convenience     13.73\n",
       "entertainment_&_media     19.80\n",
       "safety_&_security         13.79\n",
       "extras                    20.35\n",
       "empty_weight              39.76\n",
       "model_code                71.62\n",
       "general_inspection        58.43\n",
       "last_service              93.21\n",
       "full_service_history      57.38\n",
       "non_smoker_vehicle        60.67\n",
       "emission_class            39.42\n",
       "emissions_sticker         68.07\n",
       "upholstery_colour         50.58\n",
       "upholstery                36.87\n",
       "production_date           79.96\n",
       "previous_owner            52.46\n",
       "other_fuel_types          92.15\n",
       "power_consumption         98.25\n",
       "energy_efficiency_class   73.53\n",
       "co_efficiency             73.53\n",
       "fuel_consumption_wltp     99.66\n",
       "co_emissions_wltp         99.61\n",
       "available_from            98.67\n",
       "taxi_or_rental_car        98.57\n",
       "availability              98.98\n",
       "last_timing_belt_change   98.06\n",
       "electric_range_wltp       99.95\n",
       "power_consumption_wltp    99.95\n",
       "battery_ownership         99.98\n",
       "dtype: float64"
      ]
     },
     "execution_count": 188,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().sum()*100 / df.shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 200,
   "id": "d5281526-b7a1-4c07-bb6f-5ce3af4b7535",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "model_code                71.62\n",
       "last_service              93.21\n",
       "production_date           79.96\n",
       "other_fuel_types          92.15\n",
       "power_consumption         98.25\n",
       "energy_efficiency_class   73.53\n",
       "co_efficiency             73.53\n",
       "fuel_consumption_wltp     99.66\n",
       "co_emissions_wltp         99.61\n",
       "available_from            98.67\n",
       "taxi_or_rental_car        98.57\n",
       "availability              98.98\n",
       "last_timing_belt_change   98.06\n",
       "electric_range_wltp       99.95\n",
       "power_consumption_wltp    99.95\n",
       "battery_ownership         99.98\n",
       "dtype: float64"
      ]
     },
     "execution_count": 200,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Dropping columns which have missing values more than %70\n",
    "\n",
    "def df_nans(df, limit):\n",
    "    missing = df.isnull().sum()*100 / df.shape[0]\n",
    "    return missing.loc[lambda x : x >= limit]\n",
    "\n",
    "def column_nans(serial):\n",
    "    # display percentage of nans in a Series\n",
    "    return serial.isnull().sum()*100 / serial.shape[0]\n",
    "\n",
    "df_nans(df, 70)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 202,
   "id": "29129de0-42c1-4828-8efe-377a880fc91f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['model_code', 'last_service', 'production_date', 'other_fuel_types',\n",
       "       'power_consumption', 'energy_efficiency_class', 'co_efficiency',\n",
       "       'fuel_consumption_wltp', 'co_emissions_wltp', 'available_from',\n",
       "       'taxi_or_rental_car', 'availability', 'last_timing_belt_change',\n",
       "       'electric_range_wltp', 'power_consumption_wltp', 'battery_ownership'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 202,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "drop_columns = df_nans(df, 70).index\n",
    "drop_columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 204,
   "id": "c47e7a0b-badb-41a6-aed6-5e040cc1a7e9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(29480, 58)"
      ]
     },
     "execution_count": 204,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 206,
   "id": "84faf65e-84ba-46a2-b53a-3e563fefb58b",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.drop(drop_columns, axis=1, inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 208,
   "id": "ceb6a869-73bc-4ace-997b-3ca068d57979",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(29480, 42)"
      ]
     },
     "execution_count": 208,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 218,
   "id": "6c6ae567-00ee-43b9-9de9-7aed9927b6ba",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Dropping redundant columns\n",
    "\n",
    "df.drop(columns = ['make_model', 'offer_number', 'seller', 'previous_owner', 'non_smoker_vehicle', 'empty_weight', 'emission_class', 'emissions_sticker', 'location', 'country_version','short_description'], inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 220,
   "id": "b454fbf2-120f-4542-a508-e3bb82ba4ffa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(29480, 31)"
      ]
     },
     "execution_count": 220,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 244,
   "id": "8d35ed15-53c2-4f85-b345-53a17da6b368",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['make', 'model', 'price', 'body_type', 'type', 'doors', 'warranty',\n",
       "       'mileage', 'first_registration', 'gearbox', 'fuel_type', 'colour',\n",
       "       'paint', 'desc', 'seats', 'power', 'engine_size', 'gears',\n",
       "       'co_emissions', 'manufacturer_colour', 'drivetrain', 'cylinders',\n",
       "       'fuel_consumption', 'comfort_&_convenience', 'entertainment_&_media',\n",
       "       'safety_&_security', 'extras', 'general_inspection',\n",
       "       'full_service_history', 'upholstery_colour', 'upholstery'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 244,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 228,
   "id": "35f2858d-affb-49a9-a632-a4e04065a926",
   "metadata": {},
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "unhashable type: 'list'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "Cell \u001b[1;32mIn[228], line 3\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[38;5;66;03m# Dropping duplicates\u001b[39;00m\n\u001b[1;32m----> 3\u001b[0m duplicates \u001b[38;5;241m=\u001b[39m df[df\u001b[38;5;241m.\u001b[39mduplicated()]\n",
      "File \u001b[1;32m~\\anaconda3\\Lib\\site-packages\\pandas\\core\\frame.py:6958\u001b[0m, in \u001b[0;36mDataFrame.duplicated\u001b[1;34m(self, subset, keep)\u001b[0m\n\u001b[0;32m   6956\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m   6957\u001b[0m     vals \u001b[38;5;241m=\u001b[39m (col\u001b[38;5;241m.\u001b[39mvalues \u001b[38;5;28;01mfor\u001b[39;00m name, col \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mitems() \u001b[38;5;28;01mif\u001b[39;00m name \u001b[38;5;129;01min\u001b[39;00m subset)\n\u001b[1;32m-> 6958\u001b[0m     labels, shape \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mmap\u001b[39m(\u001b[38;5;28mlist\u001b[39m, \u001b[38;5;28mzip\u001b[39m(\u001b[38;5;241m*\u001b[39m\u001b[38;5;28mmap\u001b[39m(f, vals)))\n\u001b[0;32m   6960\u001b[0m     ids \u001b[38;5;241m=\u001b[39m get_group_index(labels, \u001b[38;5;28mtuple\u001b[39m(shape), sort\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m, xnull\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m)\n\u001b[0;32m   6961\u001b[0m     result \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_constructor_sliced(duplicated(ids, keep), index\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mindex)\n",
      "File \u001b[1;32m~\\anaconda3\\Lib\\site-packages\\pandas\\core\\frame.py:6926\u001b[0m, in \u001b[0;36mDataFrame.duplicated.<locals>.f\u001b[1;34m(vals)\u001b[0m\n\u001b[0;32m   6925\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mf\u001b[39m(vals) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m \u001b[38;5;28mtuple\u001b[39m[np\u001b[38;5;241m.\u001b[39mndarray, \u001b[38;5;28mint\u001b[39m]:\n\u001b[1;32m-> 6926\u001b[0m     labels, shape \u001b[38;5;241m=\u001b[39m algorithms\u001b[38;5;241m.\u001b[39mfactorize(vals, size_hint\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mlen\u001b[39m(\u001b[38;5;28mself\u001b[39m))\n\u001b[0;32m   6927\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m labels\u001b[38;5;241m.\u001b[39mastype(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mi8\u001b[39m\u001b[38;5;124m\"\u001b[39m, copy\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m), \u001b[38;5;28mlen\u001b[39m(shape)\n",
      "File \u001b[1;32m~\\anaconda3\\Lib\\site-packages\\pandas\\core\\algorithms.py:795\u001b[0m, in \u001b[0;36mfactorize\u001b[1;34m(values, sort, use_na_sentinel, size_hint)\u001b[0m\n\u001b[0;32m    792\u001b[0m             \u001b[38;5;66;03m# Don't modify (potentially user-provided) array\u001b[39;00m\n\u001b[0;32m    793\u001b[0m             values \u001b[38;5;241m=\u001b[39m np\u001b[38;5;241m.\u001b[39mwhere(null_mask, na_value, values)\n\u001b[1;32m--> 795\u001b[0m     codes, uniques \u001b[38;5;241m=\u001b[39m factorize_array(\n\u001b[0;32m    796\u001b[0m         values,\n\u001b[0;32m    797\u001b[0m         use_na_sentinel\u001b[38;5;241m=\u001b[39muse_na_sentinel,\n\u001b[0;32m    798\u001b[0m         size_hint\u001b[38;5;241m=\u001b[39msize_hint,\n\u001b[0;32m    799\u001b[0m     )\n\u001b[0;32m    801\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m sort \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(uniques) \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m0\u001b[39m:\n\u001b[0;32m    802\u001b[0m     uniques, codes \u001b[38;5;241m=\u001b[39m safe_sort(\n\u001b[0;32m    803\u001b[0m         uniques,\n\u001b[0;32m    804\u001b[0m         codes,\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m    807\u001b[0m         verify\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m,\n\u001b[0;32m    808\u001b[0m     )\n",
      "File \u001b[1;32m~\\anaconda3\\Lib\\site-packages\\pandas\\core\\algorithms.py:595\u001b[0m, in \u001b[0;36mfactorize_array\u001b[1;34m(values, use_na_sentinel, size_hint, na_value, mask)\u001b[0m\n\u001b[0;32m    592\u001b[0m hash_klass, values \u001b[38;5;241m=\u001b[39m _get_hashtable_algo(values)\n\u001b[0;32m    594\u001b[0m table \u001b[38;5;241m=\u001b[39m hash_klass(size_hint \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(values))\n\u001b[1;32m--> 595\u001b[0m uniques, codes \u001b[38;5;241m=\u001b[39m table\u001b[38;5;241m.\u001b[39mfactorize(\n\u001b[0;32m    596\u001b[0m     values,\n\u001b[0;32m    597\u001b[0m     na_sentinel\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m,\n\u001b[0;32m    598\u001b[0m     na_value\u001b[38;5;241m=\u001b[39mna_value,\n\u001b[0;32m    599\u001b[0m     mask\u001b[38;5;241m=\u001b[39mmask,\n\u001b[0;32m    600\u001b[0m     ignore_na\u001b[38;5;241m=\u001b[39muse_na_sentinel,\n\u001b[0;32m    601\u001b[0m )\n\u001b[0;32m    603\u001b[0m \u001b[38;5;66;03m# re-cast e.g. i8->dt64/td64, uint8->bool\u001b[39;00m\n\u001b[0;32m    604\u001b[0m uniques \u001b[38;5;241m=\u001b[39m _reconstruct_data(uniques, original\u001b[38;5;241m.\u001b[39mdtype, original)\n",
      "File \u001b[1;32mpandas\\\\_libs\\\\hashtable_class_helper.pxi:7281\u001b[0m, in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.factorize\u001b[1;34m()\u001b[0m\n",
      "File \u001b[1;32mpandas\\\\_libs\\\\hashtable_class_helper.pxi:7195\u001b[0m, in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable._unique\u001b[1;34m()\u001b[0m\n",
      "\u001b[1;31mTypeError\u001b[0m: unhashable type: 'list'"
     ]
    }
   ],
   "source": [
    "# Dropping duplicates\n",
    "\n",
    "duplicates = df[df.duplicated()]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 252,
   "id": "34aa3f42-cb57-43f5-b2e3-932f4f140383",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "make\n",
       "\\nVolvo\\n            3659\n",
       "\\nMercedes-Benz\\n    2398\n",
       "\\nOpel\\n             2385\n",
       "\\nPeugeot\\n          2360\n",
       "\\nRenault\\n          2351\n",
       "\\nFiat\\n             2338\n",
       "\\nFord\\n             2324\n",
       "\\nNissan\\n           2064\n",
       "\\nToyota\\n           2038\n",
       "\\nHyundai\\n          1867\n",
       "\\nSEAT\\n             1743\n",
       "\\nSkoda\\n            1566\n",
       "\\nDacia\\n            1537\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 252,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['make'].duplicated(keep=False)]['make'].value_counts(dropna=True)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 254,
   "id": "3019ea3c-1bac-41bf-ac68-aff2053f4448",
   "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>make</th>\n",
       "      <th>model</th>\n",
       "      <th>price</th>\n",
       "      <th>body_type</th>\n",
       "      <th>type</th>\n",
       "      <th>doors</th>\n",
       "      <th>warranty</th>\n",
       "      <th>mileage</th>\n",
       "      <th>first_registration</th>\n",
       "      <th>gearbox</th>\n",
       "      <th>fuel_type</th>\n",
       "      <th>colour</th>\n",
       "      <th>paint</th>\n",
       "      <th>desc</th>\n",
       "      <th>seats</th>\n",
       "      <th>power</th>\n",
       "      <th>engine_size</th>\n",
       "      <th>gears</th>\n",
       "      <th>co_emissions</th>\n",
       "      <th>manufacturer_colour</th>\n",
       "      <th>drivetrain</th>\n",
       "      <th>cylinders</th>\n",
       "      <th>fuel_consumption</th>\n",
       "      <th>comfort_&amp;_convenience</th>\n",
       "      <th>entertainment_&amp;_media</th>\n",
       "      <th>safety_&amp;_security</th>\n",
       "      <th>extras</th>\n",
       "      <th>general_inspection</th>\n",
       "      <th>full_service_history</th>\n",
       "      <th>upholstery_colour</th>\n",
       "      <th>upholstery</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [make, model, price, body_type, type, doors, warranty, mileage, first_registration, gearbox, fuel_type, colour, paint, desc, seats, power, engine_size, gears, co_emissions, manufacturer_colour, drivetrain, cylinders, fuel_consumption, comfort_&_convenience, entertainment_&_media, safety_&_security, extras, general_inspection, full_service_history, upholstery_colour, upholstery]\n",
       "Index: []"
      ]
     },
     "execution_count": 254,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.astype(str)['make'] == 'Volvo']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 256,
   "id": "ebbc2c03-92fb-42f9-b424-f5e84acd6657",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Series([], dtype: bool)"
      ]
     },
     "execution_count": 256,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['make'] == 'Volvo'].astype(str).duplicated(keep=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 258,
   "id": "da98fbee-ea09-44a9-be6f-b08b4e30a5d5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Series([], Name: count, dtype: int64)"
      ]
     },
     "execution_count": 258,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['make'] == 'Volvo'].astype(str).duplicated(keep=False).value_counts(dropna=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 264,
   "id": "a57abdbc-ec56-4829-8fb8-35568d5a25d9",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Cleaning the columns one by one \n",
    "\n",
    "def first_looking(df, col):\n",
    "    print(\"column name    : \", col)\n",
    "    print(\"--------------------------------\")\n",
    "    print(\"per_of_nulls   : \", \"%\", round(df[col].isnull().sum() * 100 / df.shape[0], 2))\n",
    "    print(\"num_of_nulls   : \", df[col].isnull().sum())\n",
    "    print(\"num_of_uniques : \", df[col].astype(str).nunique())\n",
    "    print(\"shape_of_df    : \", df.shape)\n",
    "    print(\"--------------------------------\")\n",
    "    print(df[col].value_counts(dropna=False))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 266,
   "id": "d8eed078-b08e-4905-bc23-55ade9f4aa76",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "column name    :  price\n",
      "--------------------------------\n",
      "per_of_nulls   :  % 2.88\n",
      "num_of_nulls   :  850\n",
      "num_of_uniques :  5022\n",
      "shape_of_df    :  (29480, 31)\n",
      "--------------------------------\n",
      "price\n",
      "NaN           850\n",
      "€ 14,990.-    222\n",
      "€ 12,990.-    219\n",
      "€ 16,990.-    186\n",
      "€ 19,990.-    166\n",
      "             ... \n",
      "€ 19,112.-      1\n",
      "€ 30,465.-      1\n",
      "€ 18,461.-      1\n",
      "€ 22,649.-      1\n",
      "€ 4,440.-       1\n",
      "Name: count, Length: 5022, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "first_looking(df, \"price\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 268,
   "id": "deb75276-ce13-40f8-a6da-bf05592b5915",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 268,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"price\"].isnull().any()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 270,
   "id": "161a9a94-5776-414a-8014-a26400e1be5c",
   "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>make</th>\n",
       "      <th>model</th>\n",
       "      <th>price</th>\n",
       "      <th>body_type</th>\n",
       "      <th>type</th>\n",
       "      <th>doors</th>\n",
       "      <th>warranty</th>\n",
       "      <th>mileage</th>\n",
       "      <th>first_registration</th>\n",
       "      <th>gearbox</th>\n",
       "      <th>fuel_type</th>\n",
       "      <th>colour</th>\n",
       "      <th>paint</th>\n",
       "      <th>desc</th>\n",
       "      <th>seats</th>\n",
       "      <th>power</th>\n",
       "      <th>engine_size</th>\n",
       "      <th>gears</th>\n",
       "      <th>co_emissions</th>\n",
       "      <th>manufacturer_colour</th>\n",
       "      <th>drivetrain</th>\n",
       "      <th>cylinders</th>\n",
       "      <th>fuel_consumption</th>\n",
       "      <th>comfort_&amp;_convenience</th>\n",
       "      <th>entertainment_&amp;_media</th>\n",
       "      <th>safety_&amp;_security</th>\n",
       "      <th>extras</th>\n",
       "      <th>general_inspection</th>\n",
       "      <th>full_service_history</th>\n",
       "      <th>upholstery_colour</th>\n",
       "      <th>upholstery</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>11025</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12579</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9609</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29314</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16642</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29335</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23922</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29366</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24656</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20318</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21108</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17118</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17373</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8931</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25423</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13353</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12375</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3408</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11676</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27173</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      make model price body_type type doors warranty mileage  \\\n",
       "11025  NaN   NaN   NaN       NaN  NaN   NaN      NaN     NaN   \n",
       "12579  NaN   NaN   NaN       NaN  NaN   NaN      NaN     NaN   \n",
       "9609   NaN   NaN   NaN       NaN  NaN   NaN      NaN     NaN   \n",
       "29314  NaN   NaN   NaN       NaN  NaN   NaN      NaN     NaN   \n",
       "16642  NaN   NaN   NaN       NaN  NaN   NaN      NaN     NaN   \n",
       "29335  NaN   NaN   NaN       NaN  NaN   NaN      NaN     NaN   \n",
       "23922  NaN   NaN   NaN       NaN  NaN   NaN      NaN     NaN   \n",
       "29366  NaN   NaN   NaN       NaN  NaN   NaN      NaN     NaN   \n",
       "24656  NaN   NaN   NaN       NaN  NaN   NaN      NaN     NaN   \n",
       "20318  NaN   NaN   NaN       NaN  NaN   NaN      NaN     NaN   \n",
       "21108  NaN   NaN   NaN       NaN  NaN   NaN      NaN     NaN   \n",
       "17118  NaN   NaN   NaN       NaN  NaN   NaN      NaN     NaN   \n",
       "17373  NaN   NaN   NaN       NaN  NaN   NaN      NaN     NaN   \n",
       "8931   NaN   NaN   NaN       NaN  NaN   NaN      NaN     NaN   \n",
       "25423  NaN   NaN   NaN       NaN  NaN   NaN      NaN     NaN   \n",
       "13353  NaN   NaN   NaN       NaN  NaN   NaN      NaN     NaN   \n",
       "12375  NaN   NaN   NaN       NaN  NaN   NaN      NaN     NaN   \n",
       "3408   NaN   NaN   NaN       NaN  NaN   NaN      NaN     NaN   \n",
       "11676  NaN   NaN   NaN       NaN  NaN   NaN      NaN     NaN   \n",
       "27173  NaN   NaN   NaN       NaN  NaN   NaN      NaN     NaN   \n",
       "\n",
       "      first_registration gearbox fuel_type colour paint desc seats power  \\\n",
       "11025                NaN     NaN       NaN    NaN   NaN  NaN   NaN   NaN   \n",
       "12579                NaN     NaN       NaN    NaN   NaN  NaN   NaN   NaN   \n",
       "9609                 NaN     NaN       NaN    NaN   NaN  NaN   NaN   NaN   \n",
       "29314                NaN     NaN       NaN    NaN   NaN  NaN   NaN   NaN   \n",
       "16642                NaN     NaN       NaN    NaN   NaN  NaN   NaN   NaN   \n",
       "29335                NaN     NaN       NaN    NaN   NaN  NaN   NaN   NaN   \n",
       "23922                NaN     NaN       NaN    NaN   NaN  NaN   NaN   NaN   \n",
       "29366                NaN     NaN       NaN    NaN   NaN  NaN   NaN   NaN   \n",
       "24656                NaN     NaN       NaN    NaN   NaN  NaN   NaN   NaN   \n",
       "20318                NaN     NaN       NaN    NaN   NaN  NaN   NaN   NaN   \n",
       "21108                NaN     NaN       NaN    NaN   NaN  NaN   NaN   NaN   \n",
       "17118                NaN     NaN       NaN    NaN   NaN  NaN   NaN   NaN   \n",
       "17373                NaN     NaN       NaN    NaN   NaN  NaN   NaN   NaN   \n",
       "8931                 NaN     NaN       NaN    NaN   NaN  NaN   NaN   NaN   \n",
       "25423                NaN     NaN       NaN    NaN   NaN  NaN   NaN   NaN   \n",
       "13353                NaN     NaN       NaN    NaN   NaN  NaN   NaN   NaN   \n",
       "12375                NaN     NaN       NaN    NaN   NaN  NaN   NaN   NaN   \n",
       "3408                 NaN     NaN       NaN    NaN   NaN  NaN   NaN   NaN   \n",
       "11676                NaN     NaN       NaN    NaN   NaN  NaN   NaN   NaN   \n",
       "27173                NaN     NaN       NaN    NaN   NaN  NaN   NaN   NaN   \n",
       "\n",
       "      engine_size gears co_emissions manufacturer_colour drivetrain cylinders  \\\n",
       "11025         NaN   NaN          NaN                 NaN        NaN       NaN   \n",
       "12579         NaN   NaN          NaN                 NaN        NaN       NaN   \n",
       "9609          NaN   NaN          NaN                 NaN        NaN       NaN   \n",
       "29314         NaN   NaN          NaN                 NaN        NaN       NaN   \n",
       "16642         NaN   NaN          NaN                 NaN        NaN       NaN   \n",
       "29335         NaN   NaN          NaN                 NaN        NaN       NaN   \n",
       "23922         NaN   NaN          NaN                 NaN        NaN       NaN   \n",
       "29366         NaN   NaN          NaN                 NaN        NaN       NaN   \n",
       "24656         NaN   NaN          NaN                 NaN        NaN       NaN   \n",
       "20318         NaN   NaN          NaN                 NaN        NaN       NaN   \n",
       "21108         NaN   NaN          NaN                 NaN        NaN       NaN   \n",
       "17118         NaN   NaN          NaN                 NaN        NaN       NaN   \n",
       "17373         NaN   NaN          NaN                 NaN        NaN       NaN   \n",
       "8931          NaN   NaN          NaN                 NaN        NaN       NaN   \n",
       "25423         NaN   NaN          NaN                 NaN        NaN       NaN   \n",
       "13353         NaN   NaN          NaN                 NaN        NaN       NaN   \n",
       "12375         NaN   NaN          NaN                 NaN        NaN       NaN   \n",
       "3408          NaN   NaN          NaN                 NaN        NaN       NaN   \n",
       "11676         NaN   NaN          NaN                 NaN        NaN       NaN   \n",
       "27173         NaN   NaN          NaN                 NaN        NaN       NaN   \n",
       "\n",
       "      fuel_consumption comfort_&_convenience entertainment_&_media  \\\n",
       "11025              NaN                   NaN                   NaN   \n",
       "12579              NaN                   NaN                   NaN   \n",
       "9609               NaN                   NaN                   NaN   \n",
       "29314              NaN                   NaN                   NaN   \n",
       "16642              NaN                   NaN                   NaN   \n",
       "29335              NaN                   NaN                   NaN   \n",
       "23922              NaN                   NaN                   NaN   \n",
       "29366              NaN                   NaN                   NaN   \n",
       "24656              NaN                   NaN                   NaN   \n",
       "20318              NaN                   NaN                   NaN   \n",
       "21108              NaN                   NaN                   NaN   \n",
       "17118              NaN                   NaN                   NaN   \n",
       "17373              NaN                   NaN                   NaN   \n",
       "8931               NaN                   NaN                   NaN   \n",
       "25423              NaN                   NaN                   NaN   \n",
       "13353              NaN                   NaN                   NaN   \n",
       "12375              NaN                   NaN                   NaN   \n",
       "3408               NaN                   NaN                   NaN   \n",
       "11676              NaN                   NaN                   NaN   \n",
       "27173              NaN                   NaN                   NaN   \n",
       "\n",
       "      safety_&_security extras general_inspection full_service_history  \\\n",
       "11025               NaN    NaN                NaN                  NaN   \n",
       "12579               NaN    NaN                NaN                  NaN   \n",
       "9609                NaN    NaN                NaN                  NaN   \n",
       "29314               NaN    NaN                NaN                  NaN   \n",
       "16642               NaN    NaN                NaN                  NaN   \n",
       "29335               NaN    NaN                NaN                  NaN   \n",
       "23922               NaN    NaN                NaN                  NaN   \n",
       "29366               NaN    NaN                NaN                  NaN   \n",
       "24656               NaN    NaN                NaN                  NaN   \n",
       "20318               NaN    NaN                NaN                  NaN   \n",
       "21108               NaN    NaN                NaN                  NaN   \n",
       "17118               NaN    NaN                NaN                  NaN   \n",
       "17373               NaN    NaN                NaN                  NaN   \n",
       "8931                NaN    NaN                NaN                  NaN   \n",
       "25423               NaN    NaN                NaN                  NaN   \n",
       "13353               NaN    NaN                NaN                  NaN   \n",
       "12375               NaN    NaN                NaN                  NaN   \n",
       "3408                NaN    NaN                NaN                  NaN   \n",
       "11676               NaN    NaN                NaN                  NaN   \n",
       "27173               NaN    NaN                NaN                  NaN   \n",
       "\n",
       "      upholstery_colour upholstery  \n",
       "11025               NaN        NaN  \n",
       "12579               NaN        NaN  \n",
       "9609                NaN        NaN  \n",
       "29314               NaN        NaN  \n",
       "16642               NaN        NaN  \n",
       "29335               NaN        NaN  \n",
       "23922               NaN        NaN  \n",
       "29366               NaN        NaN  \n",
       "24656               NaN        NaN  \n",
       "20318               NaN        NaN  \n",
       "21108               NaN        NaN  \n",
       "17118               NaN        NaN  \n",
       "17373               NaN        NaN  \n",
       "8931                NaN        NaN  \n",
       "25423               NaN        NaN  \n",
       "13353               NaN        NaN  \n",
       "12375               NaN        NaN  \n",
       "3408                NaN        NaN  \n",
       "11676               NaN        NaN  \n",
       "27173               NaN        NaN  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Price feature/column has 850 NaN values.\n"
     ]
    }
   ],
   "source": [
    "display(df[df[\"price\"].isnull()].sample(20))\n",
    "\n",
    "price_nans = df[\"price\"].isnull().sum()\n",
    "\n",
    "print(f\"Price feature/column has {price_nans} NaN values.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 272,
   "id": "1785a6b1-b203-4a62-9959-f8c302d48b49",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0        € 16,950.-\n",
       "1        € 80,900.-\n",
       "2        € 69,900.-\n",
       "3        € 46,990.-\n",
       "4        € 16,800.-\n",
       "            ...    \n",
       "29475     € 5,499.-\n",
       "29476     € 7,300.-\n",
       "29477    € 29,900.-\n",
       "29478     € 4,440.-\n",
       "29479           NaN\n",
       "Name: price, Length: 29480, dtype: object"
      ]
     },
     "execution_count": 272,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['price']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 274,
   "id": "a0f83a31-36f0-41f5-b191-c7aed081dc82",
   "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>0</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>16,950</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>80,900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>69,900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>46,990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>16,800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29475</th>\n",
       "      <td>5,499</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29476</th>\n",
       "      <td>7,300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29477</th>\n",
       "      <td>29,900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29478</th>\n",
       "      <td>4,440</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29479</th>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>29480 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            0\n",
       "0      16,950\n",
       "1      80,900\n",
       "2      69,900\n",
       "3      46,990\n",
       "4      16,800\n",
       "...       ...\n",
       "29475   5,499\n",
       "29476   7,300\n",
       "29477  29,900\n",
       "29478   4,440\n",
       "29479     NaN\n",
       "\n",
       "[29480 rows x 1 columns]"
      ]
     },
     "execution_count": 274,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['price'].astype(str).str.extract('(\\d+.\\d+)')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 280,
   "id": "a7c88db5-59c6-46c9-8424-8477bdf46e9c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       16950.00\n",
       "1       80900.00\n",
       "2       69900.00\n",
       "3       46990.00\n",
       "4       16800.00\n",
       "          ...   \n",
       "29475    5499.00\n",
       "29476    7300.00\n",
       "29477   29900.00\n",
       "29478    4440.00\n",
       "29479        NaN\n",
       "Name: price, Length: 29480, dtype: float64"
      ]
     },
     "execution_count": 280,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['price'] = df['price'].astype(str).str.extract('(\\d+.\\d+)')\n",
    "df['price'] = df['price'].str.replace(\",\", \"\").astype(float)\n",
    "df['price'] "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 282,
   "id": "9fb884a1-5aec-4654-b706-62cfccd61815",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "46990.0"
      ]
     },
     "execution_count": 282,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.price[3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 284,
   "id": "d9cea48d-6db2-4a73-bbd6-f8b9ef24e1b1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "850"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "(29480, 31)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(df.price.isnull().sum())\n",
    "display(df.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 286,
   "id": "469f9370-bbb9-4cb8-940b-fb3e3d029a55",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.dropna(how='all', inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 290,
   "id": "dc24f6a3-e5a1-47bf-8784-4415fef68666",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "(28630, 31)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(df.price.isnull().sum())\n",
    "display(df.shape)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 292,
   "id": "30a07f68-4ce1-42c8-b410-5cda1cf62c59",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    28630.00\n",
       "mean     23470.66\n",
       "std      23953.50\n",
       "min        490.00\n",
       "25%      11990.00\n",
       "50%      17979.00\n",
       "75%      27990.00\n",
       "max     999999.00\n",
       "Name: price, dtype: float64"
      ]
     },
     "execution_count": 292,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['price'].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 294,
   "id": "4826ae5a-f5c8-4e28-b5cf-b7dcab9deabd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# create box plot\n",
    "sns.boxplot(df.price)\n",
    "\n",
    "# format tick labels\n",
    "plt.ticklabel_format(style='plain', axis='y')  \n",
    "\n",
    "# display plot\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 296,
   "id": "3c39cfd2-5d8f-4910-baf5-1753b394972d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.distplot(df.price)\n",
    "plt.ticklabel_format(style='plain'); \n",
    "\n",
    "# fig, ax = plt.subplots(figsize=(15, 6))\n",
    "# ax.hist(df.price, bins=50);\n",
    "# df.price.hist(bins=100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 300,
   "id": "62c4b56d-06e8-4df2-bd0a-eb5f9182d032",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "column name    :  make\n",
      "--------------------------------\n",
      "per_of_nulls   :  % 0.0\n",
      "num_of_nulls   :  0\n",
      "num_of_uniques :  13\n",
      "shape_of_df    :  (28630, 31)\n",
      "--------------------------------\n",
      "make\n",
      "\\nVolvo\\n            3659\n",
      "\\nMercedes-Benz\\n    2398\n",
      "\\nOpel\\n             2385\n",
      "\\nPeugeot\\n          2360\n",
      "\\nRenault\\n          2351\n",
      "\\nFiat\\n             2338\n",
      "\\nFord\\n             2324\n",
      "\\nNissan\\n           2064\n",
      "\\nToyota\\n           2038\n",
      "\\nHyundai\\n          1867\n",
      "\\nSEAT\\n             1743\n",
      "\\nSkoda\\n            1566\n",
      "\\nDacia\\n            1537\n",
      "Name: count, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "first_looking(df, \"make\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 302,
   "id": "c3dab232-e4e3-4a21-8c1d-f9d352ac219a",
   "metadata": {},
   "outputs": [],
   "source": [
    "df[\"make\"] = df.make.str.strip('\\n')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 304,
   "id": "9b97aa19-8598-4ebe-adb4-684ad09f59e3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "make\n",
       "Volvo            3659\n",
       "Mercedes-Benz    2398\n",
       "Opel             2385\n",
       "Peugeot          2360\n",
       "Renault          2351\n",
       "Fiat             2338\n",
       "Ford             2324\n",
       "Nissan           2064\n",
       "Toyota           2038\n",
       "Hyundai          1867\n",
       "SEAT             1743\n",
       "Skoda            1566\n",
       "Dacia            1537\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 304,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.make.value_counts(dropna=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 306,
   "id": "e0e211d4-0b46-47e6-8045-bf15d29e1f80",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "column name    :  model\n",
      "--------------------------------\n",
      "per_of_nulls   :  % 0.0\n",
      "num_of_nulls   :  0\n",
      "num_of_uniques :  594\n",
      "shape_of_df    :  (28630, 31)\n",
      "--------------------------------\n",
      "model\n",
      "[\\n, Megane ,\\n]        863\n",
      "[\\n, Leon ,\\n]          787\n",
      "[\\n, V40 ,\\n]           740\n",
      "[\\n, Sandero ,\\n]       730\n",
      "[\\n, i30 ,\\n]           706\n",
      "                       ... \n",
      "[\\n, GLA 35 AMG ,\\n]      1\n",
      "[\\n, G 55 AMG ,\\n]        1\n",
      "[\\n, Ariya ,\\n]           1\n",
      "[\\n, 105 ,\\n]             1\n",
      "[\\n, 244 ,\\n]             1\n",
      "Name: count, Length: 594, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "first_looking(df,\"model\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 314,
   "id": "9e573dd6-0b3b-40d0-88ac-afcd51c0b313",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'A 35 AMG'"
      ]
     },
     "execution_count": 314,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"model\"][3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 310,
   "id": "de8d158a-9547-45b7-b660-6dce333b9655",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0           A 160\n",
       "1         EQE 350\n",
       "2        A 45 AMG\n",
       "3        A 35 AMG\n",
       "4        A 45 AMG\n",
       "           ...   \n",
       "29474         S90\n",
       "29475         S40\n",
       "29476         C30\n",
       "29477         S90\n",
       "29478         S80\n",
       "Name: model, Length: 28630, dtype: object"
      ]
     },
     "execution_count": 310,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['model'] = df['model'].explode().str.strip(\"\\n, \")\n",
    "df['model']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 316,
   "id": "00deb87c-aa44-472e-9cda-642e5a52cf0d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "model\n",
       "Megane        863\n",
       "Leon          787\n",
       "V40           740\n",
       "Sandero       730\n",
       "i30           706\n",
       "             ... \n",
       "GLA 35 AMG      1\n",
       "G 55 AMG        1\n",
       "Ariya           1\n",
       "105             1\n",
       "244             1\n",
       "Name: count, Length: 594, dtype: int64"
      ]
     },
     "execution_count": 316,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.model.value_counts(dropna=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 318,
   "id": "f8a86ccf-e717-474a-9a50-3cfa1c4363a3",
   "metadata": {},
   "outputs": [
    {
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       "      <th>model</th>\n",
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       "      <th>4717</th>\n",
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       "      <th>23437</th>\n",
       "      <td>Ford</td>\n",
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       "      <th>16832</th>\n",
       "      <td>Dacia</td>\n",
       "      <td>Sandero</td>\n",
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       "    <tr>\n",
       "      <th>28389</th>\n",
       "      <td>Volvo</td>\n",
       "      <td>V60</td>\n",
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       "    <tr>\n",
       "      <th>22380</th>\n",
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       "      <th>29434</th>\n",
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       "    <tr>\n",
       "      <th>25204</th>\n",
       "      <td>Hyundai</td>\n",
       "      <td></td>\n",
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       "    <tr>\n",
       "      <th>9717</th>\n",
       "      <td>Fiat</td>\n",
       "      <td>500 Abarth</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14074</th>\n",
       "      <td>Skoda</td>\n",
       "      <td>Rapid/Spaceback</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6599</th>\n",
       "      <td>Renault</td>\n",
       "      <td>Talisman</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19255</th>\n",
       "      <td>Nissan</td>\n",
       "      <td>Micra</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26538</th>\n",
       "      <td>Volvo</td>\n",
       "      <td>C70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4358</th>\n",
       "      <td>Opel</td>\n",
       "      <td>Astra</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7013</th>\n",
       "      <td>Renault</td>\n",
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       "    <tr>\n",
       "      <th>20822</th>\n",
       "      <td>Nissan</td>\n",
       "      <td>Qashqai</td>\n",
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       "    <tr>\n",
       "      <th>12631</th>\n",
       "      <td>SEAT</td>\n",
       "      <td>Ateca</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16470</th>\n",
       "      <td>Dacia</td>\n",
       "      <td>Lodgy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19118</th>\n",
       "      <td>Toyota</td>\n",
       "      <td>Aygo X</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9507</th>\n",
       "      <td>Peugeot</td>\n",
       "      <td>Boxer</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          make            model\n",
       "4717      Opel            Astra\n",
       "23437     Ford            Focus\n",
       "10647     Fiat        Barchetta\n",
       "16832    Dacia          Sandero\n",
       "28389    Volvo              V60\n",
       "22380     Ford          Mustang\n",
       "29434    Volvo              V40\n",
       "25204  Hyundai                 \n",
       "9717      Fiat       500 Abarth\n",
       "14074    Skoda  Rapid/Spaceback\n",
       "6599   Renault         Talisman\n",
       "19255   Nissan            Micra\n",
       "26538    Volvo              C70\n",
       "4358      Opel            Astra\n",
       "7013   Renault             Clio\n",
       "20822   Nissan          Qashqai\n",
       "12631     SEAT            Ateca\n",
       "16470    Dacia            Lodgy\n",
       "19118   Toyota           Aygo X\n",
       "9507   Peugeot            Boxer"
      ]
     },
     "execution_count": 318,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[['make', 'model']].sample(20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 320,
   "id": "35d522cf-edbb-4c5e-91d4-75b9e0f33cec",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 320,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.model.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 322,
   "id": "2cc40c1c-f6f8-4213-bbf2-5e98b21bcb12",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "model\n",
       "False    28354\n",
       "True       276\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 322,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['model'].str.contains(r'^\\s*$').value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 324,
   "id": "8d696c12-8644-42b9-a28d-e4b1b273501c",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "276"
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     "metadata": {},
     "output_type": "display_data"
    },
    {
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       "      <th>922</th>\n",
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       "    <tr>\n",
       "      <th>1229</th>\n",
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       "      <td></td>\n",
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       "    <tr>\n",
       "      <th>1275</th>\n",
       "      <td>Mercedes-Benz</td>\n",
       "      <td></td>\n",
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       "    <tr>\n",
       "      <th>1294</th>\n",
       "      <td>Mercedes-Benz</td>\n",
       "      <td></td>\n",
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       "    <tr>\n",
       "      <th>1820</th>\n",
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       "      <th>1974</th>\n",
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       "      <td>Mercedes-Benz</td>\n",
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       "      <td>Mercedes-Benz</td>\n",
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       "      <th>2122</th>\n",
       "      <td>Mercedes-Benz</td>\n",
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       "    <tr>\n",
       "      <th>2186</th>\n",
       "      <td>Mercedes-Benz</td>\n",
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       "      <th>2234</th>\n",
       "      <td>Mercedes-Benz</td>\n",
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       "      <td>Mercedes-Benz</td>\n",
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       "      <th>2373</th>\n",
       "      <td>Mercedes-Benz</td>\n",
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       "    <tr>\n",
       "      <th>2917</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
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       "    <tr>\n",
       "      <th>2921</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
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       "    <tr>\n",
       "      <th>2923</th>\n",
       "      <td>Opel</td>\n",
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       "      <th>2924</th>\n",
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       "    <tr>\n",
       "      <th>2926</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
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       "    <tr>\n",
       "      <th>2927</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2928</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
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       "    <tr>\n",
       "      <th>2931</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
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       "    <tr>\n",
       "      <th>2932</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
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       "    <tr>\n",
       "      <th>2933</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
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       "    <tr>\n",
       "      <th>2934</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2936</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2939</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2942</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2943</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2944</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2945</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2948</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2949</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2950</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2951</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2952</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2953</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2954</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2958</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2959</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2960</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2961</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2962</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2964</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2965</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2966</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2967</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2968</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2969</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2970</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2971</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2972</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2973</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2974</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2975</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2976</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2978</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2979</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2980</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2981</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2982</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2983</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2984</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2985</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2987</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2989</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2990</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2991</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2992</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2993</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2995</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2996</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2997</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2998</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2999</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3000</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3001</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3002</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3003</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3004</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3005</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3006</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3007</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3009</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3010</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3011</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3012</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3013</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3015</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3016</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3017</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3018</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3019</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3020</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3021</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3022</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3023</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3024</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3025</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3026</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3028</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3029</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3030</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3031</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3032</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3033</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3034</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3035</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3037</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3039</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3040</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3041</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3042</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3043</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3044</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3367</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3387</th>\n",
       "      <td>Opel</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5196</th>\n",
       "      <td>Renault</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5323</th>\n",
       "      <td>Renault</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5324</th>\n",
       "      <td>Renault</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5408</th>\n",
       "      <td>Renault</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5610</th>\n",
       "      <td>Renault</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5626</th>\n",
       "      <td>Renault</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5660</th>\n",
       "      <td>Renault</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5745</th>\n",
       "      <td>Renault</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6079</th>\n",
       "      <td>Renault</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6102</th>\n",
       "      <td>Renault</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6118</th>\n",
       "      <td>Renault</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6127</th>\n",
       "      <td>Renault</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6132</th>\n",
       "      <td>Renault</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6639</th>\n",
       "      <td>Renault</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6723</th>\n",
       "      <td>Renault</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6745</th>\n",
       "      <td>Renault</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7837</th>\n",
       "      <td>Peugeot</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8106</th>\n",
       "      <td>Peugeot</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9190</th>\n",
       "      <td>Peugeot</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9196</th>\n",
       "      <td>Peugeot</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9360</th>\n",
       "      <td>Peugeot</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9762</th>\n",
       "      <td>Fiat</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9995</th>\n",
       "      <td>Fiat</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10095</th>\n",
       "      <td>Fiat</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10104</th>\n",
       "      <td>Fiat</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10145</th>\n",
       "      <td>Fiat</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10319</th>\n",
       "      <td>Fiat</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10430</th>\n",
       "      <td>Fiat</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10431</th>\n",
       "      <td>Fiat</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10474</th>\n",
       "      <td>Fiat</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10475</th>\n",
       "      <td>Fiat</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10477</th>\n",
       "      <td>Fiat</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10480</th>\n",
       "      <td>Fiat</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10488</th>\n",
       "      <td>Fiat</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10494</th>\n",
       "      <td>Fiat</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10511</th>\n",
       "      <td>Fiat</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10526</th>\n",
       "      <td>Fiat</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10571</th>\n",
       "      <td>Fiat</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10579</th>\n",
       "      <td>Fiat</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10600</th>\n",
       "      <td>Fiat</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10631</th>\n",
       "      <td>Fiat</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10632</th>\n",
       "      <td>Fiat</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10657</th>\n",
       "      <td>Fiat</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10660</th>\n",
       "      <td>Fiat</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10728</th>\n",
       "      <td>Fiat</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11228</th>\n",
       "      <td>Fiat</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11252</th>\n",
       "      <td>Fiat</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11346</th>\n",
       "      <td>Fiat</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11707</th>\n",
       "      <td>Fiat</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12072</th>\n",
       "      <td>SEAT</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12395</th>\n",
       "      <td>SEAT</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12410</th>\n",
       "      <td>SEAT</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13151</th>\n",
       "      <td>SEAT</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15138</th>\n",
       "      <td>Skoda</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15422</th>\n",
       "      <td>Dacia</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15464</th>\n",
       "      <td>Dacia</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15465</th>\n",
       "      <td>Dacia</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16537</th>\n",
       "      <td>Dacia</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16846</th>\n",
       "      <td>Dacia</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17455</th>\n",
       "      <td>Toyota</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17466</th>\n",
       "      <td>Toyota</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17467</th>\n",
       "      <td>Toyota</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17478</th>\n",
       "      <td>Toyota</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17507</th>\n",
       "      <td>Toyota</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17514</th>\n",
       "      <td>Toyota</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17560</th>\n",
       "      <td>Toyota</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17837</th>\n",
       "      <td>Toyota</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17839</th>\n",
       "      <td>Toyota</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18071</th>\n",
       "      <td>Toyota</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18253</th>\n",
       "      <td>Toyota</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18270</th>\n",
       "      <td>Toyota</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18327</th>\n",
       "      <td>Toyota</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18512</th>\n",
       "      <td>Toyota</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18524</th>\n",
       "      <td>Toyota</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18577</th>\n",
       "      <td>Toyota</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19591</th>\n",
       "      <td>Nissan</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19594</th>\n",
       "      <td>Nissan</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19597</th>\n",
       "      <td>Nissan</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19759</th>\n",
       "      <td>Nissan</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19904</th>\n",
       "      <td>Nissan</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19940</th>\n",
       "      <td>Nissan</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19946</th>\n",
       "      <td>Nissan</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19991</th>\n",
       "      <td>Nissan</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20004</th>\n",
       "      <td>Nissan</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20008</th>\n",
       "      <td>Nissan</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20020</th>\n",
       "      <td>Nissan</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20031</th>\n",
       "      <td>Nissan</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21893</th>\n",
       "      <td>Ford</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21898</th>\n",
       "      <td>Ford</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21915</th>\n",
       "      <td>Ford</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21917</th>\n",
       "      <td>Ford</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21920</th>\n",
       "      <td>Ford</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21931</th>\n",
       "      <td>Ford</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21932</th>\n",
       "      <td>Ford</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21947</th>\n",
       "      <td>Ford</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21954</th>\n",
       "      <td>Ford</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21960</th>\n",
       "      <td>Ford</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21967</th>\n",
       "      <td>Ford</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21968</th>\n",
       "      <td>Ford</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21979</th>\n",
       "      <td>Ford</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22043</th>\n",
       "      <td>Ford</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22052</th>\n",
       "      <td>Ford</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22268</th>\n",
       "      <td>Ford</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22531</th>\n",
       "      <td>Ford</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22556</th>\n",
       "      <td>Ford</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22787</th>\n",
       "      <td>Ford</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23758</th>\n",
       "      <td>Hyundai</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24707</th>\n",
       "      <td>Hyundai</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24733</th>\n",
       "      <td>Hyundai</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24734</th>\n",
       "      <td>Hyundai</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24740</th>\n",
       "      <td>Hyundai</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24752</th>\n",
       "      <td>Hyundai</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24784</th>\n",
       "      <td>Hyundai</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24814</th>\n",
       "      <td>Hyundai</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25204</th>\n",
       "      <td>Hyundai</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25205</th>\n",
       "      <td>Hyundai</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25222</th>\n",
       "      <td>Hyundai</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25315</th>\n",
       "      <td>Hyundai</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25316</th>\n",
       "      <td>Hyundai</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25360</th>\n",
       "      <td>Hyundai</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26739</th>\n",
       "      <td>Volvo</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27062</th>\n",
       "      <td>Volvo</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27124</th>\n",
       "      <td>Volvo</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27130</th>\n",
       "      <td>Volvo</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27185</th>\n",
       "      <td>Volvo</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27191</th>\n",
       "      <td>Volvo</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27235</th>\n",
       "      <td>Volvo</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27283</th>\n",
       "      <td>Volvo</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27301</th>\n",
       "      <td>Volvo</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27318</th>\n",
       "      <td>Volvo</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27324</th>\n",
       "      <td>Volvo</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27379</th>\n",
       "      <td>Volvo</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27385</th>\n",
       "      <td>Volvo</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27429</th>\n",
       "      <td>Volvo</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27477</th>\n",
       "      <td>Volvo</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27495</th>\n",
       "      <td>Volvo</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27622</th>\n",
       "      <td>Volvo</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27638</th>\n",
       "      <td>Volvo</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27681</th>\n",
       "      <td>Volvo</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28020</th>\n",
       "      <td>Volvo</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28036</th>\n",
       "      <td>Volvo</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28079</th>\n",
       "      <td>Volvo</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                make model\n",
       "162    Mercedes-Benz      \n",
       "184    Mercedes-Benz      \n",
       "186    Mercedes-Benz      \n",
       "211    Mercedes-Benz      \n",
       "213    Mercedes-Benz      \n",
       "226    Mercedes-Benz      \n",
       "319    Mercedes-Benz      \n",
       "427    Mercedes-Benz      \n",
       "442    Mercedes-Benz      \n",
       "471    Mercedes-Benz      \n",
       "474    Mercedes-Benz      \n",
       "608    Mercedes-Benz      \n",
       "642    Mercedes-Benz      \n",
       "643    Mercedes-Benz      \n",
       "651    Mercedes-Benz      \n",
       "766    Mercedes-Benz      \n",
       "856    Mercedes-Benz      \n",
       "861    Mercedes-Benz      \n",
       "922    Mercedes-Benz      \n",
       "1229   Mercedes-Benz      \n",
       "1275   Mercedes-Benz      \n",
       "1294   Mercedes-Benz      \n",
       "1820   Mercedes-Benz      \n",
       "1974   Mercedes-Benz      \n",
       "2035   Mercedes-Benz      \n",
       "2116   Mercedes-Benz      \n",
       "2122   Mercedes-Benz      \n",
       "2186   Mercedes-Benz      \n",
       "2234   Mercedes-Benz      \n",
       "2337   Mercedes-Benz      \n",
       "2373   Mercedes-Benz      \n",
       "2917            Opel      \n",
       "2921            Opel      \n",
       "2923            Opel      \n",
       "2924            Opel      \n",
       "2926            Opel      \n",
       "2927            Opel      \n",
       "2928            Opel      \n",
       "2931            Opel      \n",
       "2932            Opel      \n",
       "2933            Opel      \n",
       "2934            Opel      \n",
       "2936            Opel      \n",
       "2939            Opel      \n",
       "2942            Opel      \n",
       "2943            Opel      \n",
       "2944            Opel      \n",
       "2945            Opel      \n",
       "2948            Opel      \n",
       "2949            Opel      \n",
       "2950            Opel      \n",
       "2951            Opel      \n",
       "2952            Opel      \n",
       "2953            Opel      \n",
       "2954            Opel      \n",
       "2958            Opel      \n",
       "2959            Opel      \n",
       "2960            Opel      \n",
       "2961            Opel      \n",
       "2962            Opel      \n",
       "2964            Opel      \n",
       "2965            Opel      \n",
       "2966            Opel      \n",
       "2967            Opel      \n",
       "2968            Opel      \n",
       "2969            Opel      \n",
       "2970            Opel      \n",
       "2971            Opel      \n",
       "2972            Opel      \n",
       "2973            Opel      \n",
       "2974            Opel      \n",
       "2975            Opel      \n",
       "2976            Opel      \n",
       "2978            Opel      \n",
       "2979            Opel      \n",
       "2980            Opel      \n",
       "2981            Opel      \n",
       "2982            Opel      \n",
       "2983            Opel      \n",
       "2984            Opel      \n",
       "2985            Opel      \n",
       "2987            Opel      \n",
       "2989            Opel      \n",
       "2990            Opel      \n",
       "2991            Opel      \n",
       "2992            Opel      \n",
       "2993            Opel      \n",
       "2995            Opel      \n",
       "2996            Opel      \n",
       "2997            Opel      \n",
       "2998            Opel      \n",
       "2999            Opel      \n",
       "3000            Opel      \n",
       "3001            Opel      \n",
       "3002            Opel      \n",
       "3003            Opel      \n",
       "3004            Opel      \n",
       "3005            Opel      \n",
       "3006            Opel      \n",
       "3007            Opel      \n",
       "3009            Opel      \n",
       "3010            Opel      \n",
       "3011            Opel      \n",
       "3012            Opel      \n",
       "3013            Opel      \n",
       "3015            Opel      \n",
       "3016            Opel      \n",
       "3017            Opel      \n",
       "3018            Opel      \n",
       "3019            Opel      \n",
       "3020            Opel      \n",
       "3021            Opel      \n",
       "3022            Opel      \n",
       "3023            Opel      \n",
       "3024            Opel      \n",
       "3025            Opel      \n",
       "3026            Opel      \n",
       "3028            Opel      \n",
       "3029            Opel      \n",
       "3030            Opel      \n",
       "3031            Opel      \n",
       "3032            Opel      \n",
       "3033            Opel      \n",
       "3034            Opel      \n",
       "3035            Opel      \n",
       "3037            Opel      \n",
       "3039            Opel      \n",
       "3040            Opel      \n",
       "3041            Opel      \n",
       "3042            Opel      \n",
       "3043            Opel      \n",
       "3044            Opel      \n",
       "3367            Opel      \n",
       "3387            Opel      \n",
       "5196         Renault      \n",
       "5323         Renault      \n",
       "5324         Renault      \n",
       "5408         Renault      \n",
       "5610         Renault      \n",
       "5626         Renault      \n",
       "5660         Renault      \n",
       "5745         Renault      \n",
       "6079         Renault      \n",
       "6102         Renault      \n",
       "6118         Renault      \n",
       "6127         Renault      \n",
       "6132         Renault      \n",
       "6639         Renault      \n",
       "6723         Renault      \n",
       "6745         Renault      \n",
       "7837         Peugeot      \n",
       "8106         Peugeot      \n",
       "9190         Peugeot      \n",
       "9196         Peugeot      \n",
       "9360         Peugeot      \n",
       "9762            Fiat      \n",
       "9995            Fiat      \n",
       "10095           Fiat      \n",
       "10104           Fiat      \n",
       "10145           Fiat      \n",
       "10319           Fiat      \n",
       "10430           Fiat      \n",
       "10431           Fiat      \n",
       "10474           Fiat      \n",
       "10475           Fiat      \n",
       "10477           Fiat      \n",
       "10480           Fiat      \n",
       "10488           Fiat      \n",
       "10494           Fiat      \n",
       "10511           Fiat      \n",
       "10526           Fiat      \n",
       "10571           Fiat      \n",
       "10579           Fiat      \n",
       "10600           Fiat      \n",
       "10631           Fiat      \n",
       "10632           Fiat      \n",
       "10657           Fiat      \n",
       "10660           Fiat      \n",
       "10728           Fiat      \n",
       "11228           Fiat      \n",
       "11252           Fiat      \n",
       "11346           Fiat      \n",
       "11707           Fiat      \n",
       "12072           SEAT      \n",
       "12395           SEAT      \n",
       "12410           SEAT      \n",
       "13151           SEAT      \n",
       "15138          Skoda      \n",
       "15422          Dacia      \n",
       "15464          Dacia      \n",
       "15465          Dacia      \n",
       "16537          Dacia      \n",
       "16846          Dacia      \n",
       "17455         Toyota      \n",
       "17466         Toyota      \n",
       "17467         Toyota      \n",
       "17478         Toyota      \n",
       "17507         Toyota      \n",
       "17514         Toyota      \n",
       "17560         Toyota      \n",
       "17837         Toyota      \n",
       "17839         Toyota      \n",
       "18071         Toyota      \n",
       "18253         Toyota      \n",
       "18270         Toyota      \n",
       "18327         Toyota      \n",
       "18512         Toyota      \n",
       "18524         Toyota      \n",
       "18577         Toyota      \n",
       "19591         Nissan      \n",
       "19594         Nissan      \n",
       "19597         Nissan      \n",
       "19759         Nissan      \n",
       "19904         Nissan      \n",
       "19940         Nissan      \n",
       "19946         Nissan      \n",
       "19991         Nissan      \n",
       "20004         Nissan      \n",
       "20008         Nissan      \n",
       "20020         Nissan      \n",
       "20031         Nissan      \n",
       "21893           Ford      \n",
       "21898           Ford      \n",
       "21915           Ford      \n",
       "21917           Ford      \n",
       "21920           Ford      \n",
       "21931           Ford      \n",
       "21932           Ford      \n",
       "21947           Ford      \n",
       "21954           Ford      \n",
       "21960           Ford      \n",
       "21967           Ford      \n",
       "21968           Ford      \n",
       "21979           Ford      \n",
       "22043           Ford      \n",
       "22052           Ford      \n",
       "22268           Ford      \n",
       "22531           Ford      \n",
       "22556           Ford      \n",
       "22787           Ford      \n",
       "23758        Hyundai      \n",
       "24707        Hyundai      \n",
       "24733        Hyundai      \n",
       "24734        Hyundai      \n",
       "24740        Hyundai      \n",
       "24752        Hyundai      \n",
       "24784        Hyundai      \n",
       "24814        Hyundai      \n",
       "25204        Hyundai      \n",
       "25205        Hyundai      \n",
       "25222        Hyundai      \n",
       "25315        Hyundai      \n",
       "25316        Hyundai      \n",
       "25360        Hyundai      \n",
       "26739          Volvo      \n",
       "27062          Volvo      \n",
       "27124          Volvo      \n",
       "27130          Volvo      \n",
       "27185          Volvo      \n",
       "27191          Volvo      \n",
       "27235          Volvo      \n",
       "27283          Volvo      \n",
       "27301          Volvo      \n",
       "27318          Volvo      \n",
       "27324          Volvo      \n",
       "27379          Volvo      \n",
       "27385          Volvo      \n",
       "27429          Volvo      \n",
       "27477          Volvo      \n",
       "27495          Volvo      \n",
       "27622          Volvo      \n",
       "27638          Volvo      \n",
       "27681          Volvo      \n",
       "28020          Volvo      \n",
       "28036          Volvo      \n",
       "28079          Volvo      "
      ]
     },
     "execution_count": 324,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "display((df[df['model'].str.contains(r'^\\s*$')][ \"model\"]).count())\n",
    "\n",
    "df[df['model'].str.contains(r'^\\s*$')][[\"make\", \"model\"]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 326,
   "id": "675d1d03-15d7-49c7-827e-ba38a528a03f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0        [ , Precio al contado: 16950 euros,  ,  , Vehí...\n",
       "1        [ , Precio al contado: 88900 euros,  , AUTO OJ...\n",
       "2        [Gris MANUFAKTUR mountaingrau magno,  , Linea/...\n",
       "3        [ , Precio al contado: 48990 euros,  ,  , BONI...\n",
       "4        [ , Precio al contado: 17400 euros,  , Vehícul...\n",
       "                               ...                        \n",
       "29474    [ , Precio al contado: 41400 euros,  , Os pres...\n",
       "29475    [Een goed rijdende auto met APK + NAP + Elektr...\n",
       "29476    [*** VOLVO C30 2011 TRES PROPRE EN PARFAIT ETA...\n",
       "29477    [Bekijk deze auto in unieke 360 graden present...\n",
       "29478    [YOUNGTIMER !, Bedrijfsinformatie, NEEM VOOR U...\n",
       "Name: desc, Length: 28630, dtype: object"
      ]
     },
     "execution_count": 326,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"desc\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 328,
   "id": "79b1d569-acf2-4a08-b27a-037a556a5e2b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "column name    :  desc\n",
      "--------------------------------\n",
      "per_of_nulls   :  % 2.04\n",
      "num_of_nulls   :  583\n",
      "num_of_uniques :  23242\n",
      "shape_of_df    :  (28630, 31)\n",
      "--------------------------------\n",
      "desc\n",
      "NaN                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                  583\n",
      "[]                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                    88\n",
      "[Genaue Angaben zu der Serienausstattung, finden Sie auf unsere Homepage., Gerne nehmen wir Ihr Aktuelles Fahrzeug zurück!, Der Verkäufer übernimmt keine Haftung für Tipp und Datenübermittlungsfehler., Angeführte Ausstattungen sind ggfs. gesondert vor Ort zu prüfen., Alle Angaben in den Inseraten sind unverbindlich und ohne Gewähr.,  , Dacia Jogger TCe 110 Extreme+ 7-Sitzer,  , Sonderausstattung,  , City-Paket,  , - elektrische Parkbremse, - erhöhte Mittelkonsole, - Einparkhilfe vorne und hinten, - Rückfahrkamera, - Toter-Winkel-Warner,  , Sitzheizung für Vordersitze,  , Klimaautomatik,  , Scheiben hinten abgedunkelt,  , 7-Sitzer,  , Serienausstattung,  ,  , Eco LED-Scheinwerfer,  , Reserverad,  , Notbremsassistent,  , ECO-Mode,  , 12V Steckdose,  , Klapptische für zweite Sitzreihe,  , El. Parkbremse,  , Sonnenblenden mit Make-up-Spiegel,  , Beifahrersonnenblende mit Make-up-Spiegel,  , Fahrersitz höhenverstellbar,  , Lenkrad höhen- und längsverstellbar,  , Rücksitzbank 60/40 umklappbar,  , Servolenkung,  , Zentralverriegelung,  , El. Fensterheber vorne und hinten,  , El. Seitenspiegel,  , Schlüssellose Zentralverriegelung,  , Armlehne,  , Lenkrad in Lederoptik mit Multifunktion,  , Dachreling modular,  , Leichtmetallfelgen in schwarz mit Sommerreifen,  , Reifendruck-Kontrolle,  , Dacia Media Nav Multimediasystem,  , DAB-Radio,  , MP3 fähig,  , Bluetooth,  , USB-Anschluss,  , Touchscreen,  , CarPlay,  , Android Auto,  , Sprachsteuerung,  , Navigationssystem,  , Tempomat,  , Freisprecheinrichtung,  , Bordcomputer Check-Control,  , Geschwindigkeitsbegrenzungsanlage, ...]                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                           51\n",
      "[Ref.  4236LFG,            OCASIONPLUS, SÓLO ESTE MES MEJOR PRECIO GARANTIZADO, COMPRA CON TOTAL CONFIANZA - 15 DÍAS O 1000 KMs DE PRUEBA, OCASIONPLUS - Nº1 Calidad/Precio, 5000 COCHES - 50 centros en toda la península , Elige tu coche y te lo llevamos a tu provincia, Hasta 2350€ de descuento en este coche, ADEMÁS HACEMOS FINANCIACIONES A MEDIDA, PREGÚNTANOS!!, Equipamiento destacado: Techo panorámico, Tapicería de piel, Asistente de aparcamiento, Navegador, Encendido automático de faros, Arranque por botón, Start/Stop automático, Control de velocidad, Volante multifunción, Bluetooth, Aire Acondicionado (Climatizador), Control de tracción, Llantas de aleación (18\")., - Garantía total 1 año, con cobertura nacional, ampliable a 24 meses., - Certificado de Kilómetros y ausencia de golpes estructurales., - Sobrevaloramos tu coche en operaciones de cambio. Tásalo ahora en ocasionplus.com, - Entregamos cualquier coche en cualquier centro por 100€, - Abierto Domingo y Festivos.,  , Extras,  ,  , Equipamiento destacado seleccionado por el usuario,  ,  , - Llantas de aleación de 18\", - Techo panorámico, - Navegador, - Start/Stop automático, - Control de velocidad, - Volante multifunción, - Bluetooth, - Control de tracción, - Climatizador, - Llantas de aleación, - Aire Acondicionado, - Tapicería de piel, - Asistente de aparcamiento, - Encendido automático de faros, - Arranque por botón, See more]                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                     34\n",
      "[ , Precio al contado: 15200 euros,  , Ref.  6710KJS,            \"OCASIONPLUS, SÓLO ESTE MES MEJOR PRECIO GARANTIZADO, COMPRA CON TOTAL CONFIANZA - 15 DÍAS O 1000 KMs DE PRUEBA, OCASIONPLUS - Nº1 Calidad/Precio, 5000 COCHES - 50 centros en toda la península , Elige tu coche y te lo llevamos a tu provincia, Hasta 1382€ de descuento en este coche, Precio oferta financiado: 13818€ (202€/mes) financiando la totalidad a un plazo mínimo de 60 meses, Precio al contado: 15200€ ADEMÁS HACEMOS FINANCIACIONES A MEDIDA, PREGÚNTANOS!!\", Equipamiento destacado: Faros traseros led, Bluetooth, Arranque por botón, Aire Acondicionado (Climatizador), Isofix, Llantas de aleación (16\")., - Coche Nacional., - Garantía total 1 año, con cobertura nacional, ampliable a 24 meses., - Certificado de Kilómetros y ausencia de golpes estructurales., - Sobrevaloramos tu coche en operaciones de cambio. Tásalo ahora en ocasionplus.com, - Entregamos cualquier coche en cualquier centro por 100€, - Abierto Domingo y Festivos.,  , Extras,  ,  , Equipamiento destacado seleccionado por el usuario,  ,  , - Bluetooth, - Climatizador, - Llantas de aleación, - Aire Acondicionado, - Llantas de aleación de 16\", - Faros traseros led, - Isofi, x- Arranque por botón,  , Condiciones de la financiación,  , \"OCASIONPLUS, SÓLO ESTE MES MEJOR PRECIO GARANTIZADO, COMPRA CON TOTAL CONFIANZA - 15 DÍAS O 1000 KMs DE PRUEBA, OCASIONPLUS - Nº1 Calidad/Precio, 5000 COCHES - 50 centros en toda la península , Elige tu coche y te lo llevamos a tu provincia, Hasta 1382€ de descuento en este coche, Precio oferta financiado: 13818€ (202€/mes) financiando la totalidad a un plazo mínimo de 60 meses, Precio al contado: 15200€ ADEMÁS HACEMOS FINANCIACIONES A MEDIDA, PREGÚNTANOS!!\", See more]                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                               34\n",
      "                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                    ... \n",
      "[PEUGEOT 3008 BUSINESS 3008 1.6 BlueHDi 120ch S&S EAT6 Active Business]                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                1\n",
      "[ , Precio al contado: 27900 euros,  , Concesionario oficial Peugeot en Valencia con más de 50 Años de experiencia. Vehículo revisado en más de 100 puntos con el programa Spoticar de Peugeot. Posibilidad de financiar hasta 120 meses sin entrada. Garantizado 12 meses ampliable hasta 36 meses. Gestionamos también su seguro de coche a los mejores precios. Vehículo publicado con 3.400-€ de descuento al financiar con nuestra entidad financiera colaboradora una cantidad mínima de 10.000.-€ a 60 meses y entregando coche de más de 10 años., Este anuncio no es contractual y está sujeto a las condiciones de la campaña mensual. Le animamos, a consultar condiciones., EQUIPAMIENTOS:, Asientos de tela (material principal) y de cuero sintético (material secundario), Navegador con datos vía memoria interna/disco duro y pantalla a color de 10,0 \" con información en 3D y con voz, control mediante pantalla táctil y información de tráfico 25,4 y 36, Volante multi-función revestido de cuero ajustable en altura y en profundidad,  , Condiciones de la financiación,  , Consultar condiciones de financiación en este anuncio o contactando con el anunciante, See more]                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                  1\n",
      "[Concessionaria Burnout che fa parte della Community NON PRENDERMI PER IL CHILOMETRO e da più di 10 anni sul mercato E' LIETA DI PRESENTARVI . Stupenda Peugeot 5008 1.6 hdi 120 cv 7 posti , Vettura tagliandata, garantita ,sanificata e ricondizionamento interni., SCOPRITE I NOSTRI VANTAGGI USATO GARANTITO E RICONDIZIONATO , * POSSIBILITA' PERMUTA USATO CON USATO, * FINANZIAMENTI PERSONALIZZATI. , * POSSIBILITA' DI ESTENDERE LA GARANZIA A 24 / 36 / 48 MESI , Optional:, specchi elettrici , Apple Car play, Cruise control, Completa cronologia tagliandi, vetri elettrici, Sensore pioggia , sensore luci, Unico proprietario, Sensori di parcheggio, E tanto altro ancora, Ci scusiamo per l'inconveniente ma a causa della non uniformità dei dati pubblicati dai diversi portali,vi invitiamo a verificare le caratteristiche dello specifico veicolo , * I nostri Consulenti sono a Sua disposizione tutti i giorni, dal lunedì al sabato, dalle 9.00 alle19 , WhatsApp Messenger  3473007167, See more]                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                          1\n",
      "[Equipements supplémentaires : 2 sieges escamotables et extractibles pour les passagers du 3eme rang, Acces et demarrage mains libres, Accoudoir central AV a ouverture papillon, avec compartiment de rangement eclaire et refrigerable, Aide graphique et sonore au stationnement AR, Aide graphique et sonore au stationnement AV, Air conditionne automatique bi-zone avec aerateurs aux places AR, Airbags frontaux conducteur et passager adaptatifs (passager neutralisable par cle), airbags lateraux conducteur et passager AV, airbags rideaux de tete aux places AV et AR, Appuis-tete a securite optimisee reglables en hauteur sur les sieges conducteur et passager AV ainsi que sur les places laterales AR, Avertisseur de temps de conduite, Barres de toit longitudinales profilee en Aluminium, Boite a gants floquee et eclairee, Boitiers de retroviseurs exterieurs dans la couleur de la carrosserie, Calandre avec jonc peripherique et ailettes chromes, Ceintures de securite 3 points a enrouleur (x2) au 3eme rang, Ceintures de securite 3 points a enrouleur (x3) au 2eme rang, avec pretensionneurs et limiteurs d'effort aux places laterales, Ceintures de securite AV 3 points a enrouleur, reglables en hauteur avec pretensionneurs et limiteurs d'effort, Commande de verrouillage a distance (2 plips), Console centrale AV avec 2 porte-gobelets, Controle dynamique de stabilite CDS avec antipatinage electronique ASR, Decors de planche de bord et panneaux de portes en maille 'Brumeo', Decors interieurs (baguettes de planche de bord et panneaux de portes, enjoliveur de console) chromes, Detection de sous-gonflage indirecte, Direction assistee electrique, colonne de direction reglable en hauteur et profondeur (mecanique), Ecran tactile capacitif 8' et 'Toggles Switches', Enjoliveur d'arc de pavillon en inox, Enjoliveur de seuil d'entree de coffre chrome, Enjoliveur en inox sur les protecteurs de bas de portes, Essuie-vitre AR avec enclenchement automatique en marche AR, Essuie-vitre AV avec systeme de lavage 'Magic Wash', Fixations pour 3 sieges enfants suivant norme ISOFIX aux places du 2eme rang, Fonction 'Mirror Screen', Frein de stationnement electrique avec aide au demarrage en pente, Indicateur de rapport conseille, Inserts d'ailes AV chromes, Jantes alliage 18' 'Detroit' bi-ton diamantees, Kit de depannage de pneumatique : compresseur 12 volts, flacon de produit de colmatage, anneau de remorquage, deux cales de roue, manivelle de frein de stationnement electrique, Leve-vitres AR electriques et sequentiels avec antipincement, Leve-vitres AV electriques et sequentiels avec antipincement, Lunette AR chauffante avec antennes serigraphiees, Miroirs de courtoisie eclaires, Nouveau Peugeot i-Cockpit : combine tete haute numerique reconfigurable et volant compact multi-fonctions, Pack City 1, Pack Eclairage d'ambiance, Pack Safety Plus, Pack Visibilite, Passages de roues rapportes noirs, Peugeot Connect, Plafonnier AV avec spots de lecture (x2) et plafonniers a extinction temporisee aux 2eme et 3eme rangs, Poches/filets aumonieres au dos des sieges AV, Poignees de maintien (x4) retractables avec frein (crochets pour cintres aux places AR), Poignees de portes couleur carrosserie, Prise 12V (x3 : zone connectique, AR de console et coffre), Prise USB (dans la zone connectique), Projecteurs antibrouillard halogenes, Projecteurs halogenes a l'AV avec feux diurnes a LED, Radio 6 HP, bi-tuner compatible MP3 et connectivite Bluetooth (audio streaming, kit mains libres), avec commandes au volant, ecran tactile capacitif 8', Reconnaissance des panneaux de vitesse et preconisation de vitesse, Regulateur / Limiteur de vitesse, Retroviseurs exterieurs electriques degivrants, Retroviseurs exterieurs rabattables electriquement avec eclairage d'accueil a LED, Retroviseurs indexes a la marche AR, Rideaux pare-soleil (x2) pour les passagers du 2eme rang, Sabots de pare-chocs AV gris metallise, Securite enfants electrique des vitres AR, Sellerie TEP & Tissu 'Evron', Sieg, See more]      1\n",
      "[YOUNGTIMER !, Bedrijfsinformatie, NEEM VOOR U WILT KOMEN KIJKEN NAAR EEN AUTO TELEFONISCH CONTACT MET ONS OP 0162-313775 (optie 2) U BENT VAN HARTE WELKOM VOOR PROEFRIT! DINSDAG ALLEEN OP AFSPRAAK! , Overige informatie: Inruil, financiering, garantie of nieuwe apk zijn bespreekbaar. Inruil van uw auto, bus, bestelwagen,vrachtwagen , camper, caravan, boot, graafmachines tractoren of andere industriële equipment is mogelijk! Overdekte showroom 2500 M2 met 100 occasions op voorraad! Ons adres is Lage Ham 106 in Dongen. Openingstijden: Maandag: 9:00-18.00 Dinsdag: ALLEEN OP AFSPRAAK  woensdag t/m vrijdag: 09.00 t/m 18.00 zaterdag 09.00 t/m 14.00. Wij zijn bereikbaar op 0162-313 775 Verdere informatie: WWW.FOCD.NL. Voor informatie over afwijkende openingstijden wat betreft feestdagen kunt u terecht op onze home pagina van WWW.FOCD.NL, Meer informatie, Algemene informatie, Modeljaar: , 2001, Prestaties, Acceleratie (0-100): , 8,9 s, Topsnelheid: , 225 km/u, Maten, Afmetingen (LxBxH): , 482 x 183 x 145 cm, Wielbasis: , 279 cm, Gewichten, Laadvermogen: , 517 kg, GVW: , 2.090 kg, Max. trekgewicht: , 1.800 kg,  (ongeremd 500 kg), Financiële informatie, BTW/marge: , BTW niet verrekenbaar voor ondernemers (margeregeling), Motorrijtuigenbelasting: , € 230 - € 261,  per kwartaal, Aanvullende opties en accessoires, Exterieur, Metaalkleur vernis of parelmoerlak, Buitenspiegels elektrisch verstel- en verwarmbaar, Buitenspiegels in carrosseriekleur, Elektronische remkrachtverdeling, koplampreiniging, Trekhaak afneembaar, Infotainment, Navigatiesysteem en autotelefoon, Interieur, Achterbank verwarmd, Armsteun achter, Armsteun voor, Elektrische ramen voor en achter, Elektrisch rolgordijn voor achterruit, Elektrisch verstelbare bestuurdersstoel, Hoofdsteunen voor en achter, Houtafwerking interieur, Lendesteunen (verstelbaar), Stuur verstelbaar, Voorstoelen in hoogte verstelbaar, Voorstoelen verwarmd, Veiligheid, Airbag(s) hoofd voor, Alarm klasse 1(startblokkering), Alarm klasse 3, Side Impact Protection System, See more]                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                  1\n",
      "Name: count, Length: 23242, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "first_looking(df, \"desc\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 332,
   "id": "d307e79e-d7e4-4fe4-94bb-5aebc82589ad",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(28630, 31)"
      ]
     },
     "execution_count": 332,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 336,
   "id": "7e1cad57-bbb0-4c62-b07e-1483d0156e28",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.drop('desc', axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 338,
   "id": "837d662d-6e19-4a44-b02f-532c99939e3c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(28630, 30)"
      ]
     },
     "execution_count": 338,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 340,
   "id": "36203a7c-a6e3-4a4e-8598-047b249ab0f2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "column name    :  body_type\n",
      "--------------------------------\n",
      "per_of_nulls   :  % 0.0\n",
      "num_of_nulls   :  0\n",
      "num_of_uniques :  6\n",
      "shape_of_df    :  (28630, 30)\n",
      "--------------------------------\n",
      "body_type\n",
      "[\\n, Station wagon, \\n]       5448\n",
      "[\\n, Off-Road/Pick-up, \\n]    5415\n",
      "[\\n, Compact, \\n]             5387\n",
      "[\\n, Sedan, \\n]               5043\n",
      "[\\n, Coupe, \\n]               4009\n",
      "[\\n, Convertible, \\n]         3328\n",
      "Name: count, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "first_looking(df, 'body_type')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 342,
   "id": "5e18b201-c488-43b3-a6fb-06259359dd55",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0        Compact\n",
       "1        Compact\n",
       "2        Compact\n",
       "3        Compact\n",
       "4        Compact\n",
       "          ...   \n",
       "29474      Sedan\n",
       "29475      Sedan\n",
       "29476      Sedan\n",
       "29477      Sedan\n",
       "29478      Sedan\n",
       "Name: body_type, Length: 28630, dtype: object"
      ]
     },
     "execution_count": 342,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['body_type'] = df['body_type'].explode().str.strip(\"\\n, \")\n",
    "df['body_type']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 344,
   "id": "db66311b-c50f-4bb4-acb5-abbb7c0571d2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "body_type\n",
       "Station wagon       5448\n",
       "Off-Road/Pick-up    5415\n",
       "Compact             5387\n",
       "Sedan               5043\n",
       "Coupe               4009\n",
       "Convertible         3328\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 344,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"body_type\"].value_counts(dropna=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 346,
   "id": "abdcc18a-c0b0-46ec-b4dc-6702649fb24b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "column name    :  type\n",
      "--------------------------------\n",
      "per_of_nulls   :  % 0.0\n",
      "num_of_nulls   :  0\n",
      "num_of_uniques :  4\n",
      "shape_of_df    :  (28630, 30)\n",
      "--------------------------------\n",
      "type\n",
      "[\\n, Used, \\n]              25251\n",
      "[\\n, Demonstration, \\n]      1433\n",
      "[\\n, Pre-registered, \\n]     1377\n",
      "[\\n, Employee's car, \\n]      569\n",
      "Name: count, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "first_looking(df, 'type')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 348,
   "id": "4407d9db-0c7f-4fee-a860-ab895faab9df",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0                  Used\n",
       "1        Pre-registered\n",
       "2                  Used\n",
       "3                  Used\n",
       "4                  Used\n",
       "              ...      \n",
       "29474              Used\n",
       "29475              Used\n",
       "29476              Used\n",
       "29477              Used\n",
       "29478              Used\n",
       "Name: type, Length: 28630, dtype: object"
      ]
     },
     "execution_count": 348,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['type'] = df['type'].explode().str.strip(\"\\n, \")\n",
    "df['type']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 350,
   "id": "00f9ee80-2cde-45f0-b854-4edbb202f682",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "type\n",
       "Used              25251\n",
       "Demonstration      1433\n",
       "Pre-registered     1377\n",
       "Employee's car      569\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 350,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.type.value_counts(dropna=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 352,
   "id": "a71df82d-5e56-4419-9f9e-f4e6a698797c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "column name    :  doors\n",
      "--------------------------------\n",
      "per_of_nulls   :  % 1.25\n",
      "num_of_nulls   :  359\n",
      "num_of_uniques :  7\n",
      "shape_of_df    :  (28630, 30)\n",
      "--------------------------------\n",
      "doors\n",
      "[\\n, 5, \\n]    17481\n",
      "[\\n, 2, \\n]     5523\n",
      "[\\n, 4, \\n]     3001\n",
      "[\\n, 3, \\n]     2259\n",
      "NaN              359\n",
      "[\\n, 6, \\n]        5\n",
      "[\\n, 1, \\n]        2\n",
      "Name: count, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "first_looking(df, \"doors\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 354,
   "id": "8107058b-f065-4ed5-989e-6e05967bd64c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0        5\n",
       "1        4\n",
       "2        5\n",
       "3        5\n",
       "4        5\n",
       "        ..\n",
       "29474    4\n",
       "29475    4\n",
       "29476    3\n",
       "29477    4\n",
       "29478    4\n",
       "Name: doors, Length: 28630, dtype: object"
      ]
     },
     "execution_count": 354,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['doors'].explode().str.strip(\"\\n, \")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 356,
   "id": "d10d5b32-c94b-498c-be71-252fc21d1ba0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       5.00\n",
       "1       4.00\n",
       "2       5.00\n",
       "3       5.00\n",
       "4       5.00\n",
       "        ... \n",
       "29474   4.00\n",
       "29475   4.00\n",
       "29476   3.00\n",
       "29477   4.00\n",
       "29478   4.00\n",
       "Name: doors, Length: 28630, dtype: float64"
      ]
     },
     "execution_count": 356,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['doors'] = df['doors'].explode().str.strip(\"\\n, \")\n",
    "df['doors'] = pd.to_numeric(df['doors'])\n",
    "df['doors']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 358,
   "id": "711bcd99-1676-46d4-9907-2b806b6bd8a8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "doors\n",
       "5.00    17481\n",
       "2.00     5523\n",
       "4.00     3001\n",
       "3.00     2259\n",
       "NaN       359\n",
       "6.00        5\n",
       "1.00        2\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 358,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.doors.value_counts(dropna=False)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 360,
   "id": "e7775f6f-7415-4b54-8533-3644b17f2081",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "column name    :  warranty\n",
      "--------------------------------\n",
      "per_of_nulls   :  % 44.87\n",
      "num_of_nulls   :  12846\n",
      "num_of_uniques :  66\n",
      "shape_of_df    :  (28630, 30)\n",
      "--------------------------------\n",
      "warranty\n",
      "NaN                     12846\n",
      "[\\n, 12 months, \\n]      9545\n",
      "[\\n, Yes, \\n]            2319\n",
      "[\\n, 24 months, \\n]      1515\n",
      "[\\n, 60 months, \\n]       968\n",
      "[\\n, 6 months, \\n]        398\n",
      "[\\n, 36 months, \\n]       257\n",
      "[\\n, 3 months, \\n]        185\n",
      "[\\n, 0 months, \\n]        133\n",
      "[\\n, 48 months, \\n]        78\n",
      "[\\n, 84 months, \\n]        47\n",
      "[\\n, 72 months, \\n]        40\n",
      "[\\n, 13 months, \\n]        22\n",
      "[\\n, 8 months, \\n]         19\n",
      "[\\n, 18 months, \\n]        15\n",
      "[\\n, 1 months, \\n]         15\n",
      "[\\n, 15 months, \\n]        13\n",
      "[\\n, 14 months, \\n]        13\n",
      "[\\n, 16 months, \\n]        13\n",
      "[\\n, 30 months, \\n]        12\n",
      "[\\n, 34 months, \\n]        11\n",
      "[\\n, 21 months, \\n]        11\n",
      "[\\n, 33 months, \\n]        11\n",
      "[\\n, 32 months, \\n]         9\n",
      "[\\n, 20 months, \\n]         9\n",
      "[\\n, 23 months, \\n]         9\n",
      "[\\n, 19 months, \\n]         9\n",
      "[\\n, 17 months, \\n]         9\n",
      "[\\n, 35 months, \\n]         8\n",
      "[\\n, 28 months, \\n]         8\n",
      "[\\n, 50 months, \\n]         6\n",
      "[\\n, 22 months, \\n]         6\n",
      "[\\n, 42 months, \\n]         5\n",
      "[\\n, 31 months, \\n]         4\n",
      "[\\n, 26 months, \\n]         4\n",
      "[\\n, 52 months, \\n]         4\n",
      "[\\n, 47 months, \\n]         4\n",
      "[\\n, 9 months, \\n]          4\n",
      "[\\n, 25 months, \\n]         3\n",
      "[\\n, 58 months, \\n]         3\n",
      "[\\n, 11 months, \\n]         3\n",
      "[\\n, 27 months, \\n]         3\n",
      "[\\n, 45 months, \\n]         2\n",
      "[\\n, 53 months, \\n]         2\n",
      "[\\n, 10 months, \\n]         2\n",
      "[\\n, 57 months, \\n]         2\n",
      "[\\n, 51 months, \\n]         2\n",
      "[\\n, 29 months, \\n]         2\n",
      "[\\n, 2 months, \\n]          2\n",
      "[\\n, 80 months, \\n]         2\n",
      "[\\n, 90 months, \\n]         2\n",
      "[\\n, 7 months, \\n]          2\n",
      "[\\n, 46 months, \\n]         1\n",
      "[\\n, 117 months, \\n]        1\n",
      "[\\n, 43 months, \\n]         1\n",
      "[\\n, 65 months, \\n]         1\n",
      "[\\n, 39 months, \\n]         1\n",
      "[\\n, 142 months, \\n]        1\n",
      "[\\n, 110 months, \\n]        1\n",
      "[\\n, 37 months, \\n]         1\n",
      "[\\n, 49 months, \\n]         1\n",
      "[\\n, 55 months, \\n]         1\n",
      "[\\n, 99 months, \\n]         1\n",
      "[\\n, 122 months, \\n]        1\n",
      "[\\n, 44 months, \\n]         1\n",
      "[\\n, 4 months, \\n]          1\n",
      "Name: count, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "first_looking(df, \"warranty\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 362,
   "id": "19eac033-de05-4d7f-af1a-ec34e969fec0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       24.00\n",
       "1       24.00\n",
       "2       12.00\n",
       "3       12.00\n",
       "4       12.00\n",
       "         ... \n",
       "29474   12.00\n",
       "29475     NaN\n",
       "29476   13.00\n",
       "29477   12.00\n",
       "29478     NaN\n",
       "Name: warranty, Length: 28630, dtype: float64"
      ]
     },
     "execution_count": 362,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"warranty\"] = df.warranty.apply(lambda x : x[0] if type(x)==list else x)\n",
    "\n",
    "df[\"warranty\"] = df.warranty.str.extract('(\\d{1,4})').astype(\"float\") # str.extract('(\\d+)')\n",
    "df[\"warranty\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 364,
   "id": "79c2c964-fefd-4989-9965-9b3424b2d83e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "warranty\n",
       "NaN       15165\n",
       "12.00      9545\n",
       "24.00      1515\n",
       "60.00       968\n",
       "6.00        398\n",
       "36.00       257\n",
       "3.00        185\n",
       "0.00        133\n",
       "48.00        78\n",
       "84.00        47\n",
       "72.00        40\n",
       "13.00        22\n",
       "8.00         19\n",
       "18.00        15\n",
       "1.00         15\n",
       "15.00        13\n",
       "14.00        13\n",
       "16.00        13\n",
       "30.00        12\n",
       "34.00        11\n",
       "21.00        11\n",
       "33.00        11\n",
       "32.00         9\n",
       "20.00         9\n",
       "23.00         9\n",
       "19.00         9\n",
       "17.00         9\n",
       "35.00         8\n",
       "28.00         8\n",
       "50.00         6\n",
       "22.00         6\n",
       "42.00         5\n",
       "31.00         4\n",
       "26.00         4\n",
       "52.00         4\n",
       "47.00         4\n",
       "9.00          4\n",
       "25.00         3\n",
       "58.00         3\n",
       "11.00         3\n",
       "27.00         3\n",
       "45.00         2\n",
       "53.00         2\n",
       "10.00         2\n",
       "57.00         2\n",
       "51.00         2\n",
       "29.00         2\n",
       "2.00          2\n",
       "80.00         2\n",
       "90.00         2\n",
       "7.00          2\n",
       "46.00         1\n",
       "117.00        1\n",
       "43.00         1\n",
       "65.00         1\n",
       "39.00         1\n",
       "142.00        1\n",
       "110.00        1\n",
       "37.00         1\n",
       "49.00         1\n",
       "55.00         1\n",
       "99.00         1\n",
       "122.00        1\n",
       "44.00         1\n",
       "4.00          1\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 364,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.warranty.value_counts(dropna=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 366,
   "id": "48ec1952-fba3-457d-9694-8446ad5d2467",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "column name    :  mileage\n",
      "--------------------------------\n",
      "per_of_nulls   :  % 0.0\n",
      "num_of_nulls   :  1\n",
      "num_of_uniques :  14184\n",
      "shape_of_df    :  (28630, 30)\n",
      "--------------------------------\n",
      "mileage\n",
      "10 km         586\n",
      "1 km          172\n",
      "50 km         133\n",
      "100 km        119\n",
      "5,000 km      118\n",
      "             ... \n",
      "141,589 km      1\n",
      "59,821 km       1\n",
      "123,500 km      1\n",
      "29,781 km       1\n",
      "230,047 km      1\n",
      "Name: count, Length: 14184, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "first_looking(df, \"mileage\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 368,
   "id": "26bee8ed-1fbc-4e48-913d-0bd094366c8a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       120200.00\n",
       "1         5000.00\n",
       "2        18900.00\n",
       "3        18995.00\n",
       "4       197000.00\n",
       "           ...   \n",
       "29474    40345.00\n",
       "29475   145000.00\n",
       "29476    96000.00\n",
       "29477    94343.00\n",
       "29478   230047.00\n",
       "Name: mileage, Length: 28630, dtype: float64"
      ]
     },
     "execution_count": 368,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"mileage\"] = df.mileage.str.replace(',', '').str.extract('(\\d{1,8})').astype('float')\n",
    "df[\"mileage\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 370,
   "id": "ebf5b2b9-032a-4da2-8107-2b4a4b989da0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "mileage\n",
       "10.00        586\n",
       "1.00         172\n",
       "50.00        133\n",
       "100.00       119\n",
       "5000.00      118\n",
       "            ... \n",
       "141589.00      1\n",
       "59821.00       1\n",
       "123500.00      1\n",
       "29781.00       1\n",
       "230047.00      1\n",
       "Name: count, Length: 14184, dtype: int64"
      ]
     },
     "execution_count": 370,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.mileage.value_counts(dropna=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 372,
   "id": "c6f360c9-d360-4a99-a92d-1dd46b8d4351",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "column name    :  first_registration\n",
      "--------------------------------\n",
      "per_of_nulls   :  % 0.01\n",
      "num_of_nulls   :  2\n",
      "num_of_uniques :  656\n",
      "shape_of_df    :  (28630, 30)\n",
      "--------------------------------\n",
      "first_registration\n",
      "08/2022    454\n",
      "06/2022    428\n",
      "05/2019    420\n",
      "06/2019    418\n",
      "07/2019    416\n",
      "          ... \n",
      "06/1967      1\n",
      "06/1980      1\n",
      "09/1970      1\n",
      "06/1963      1\n",
      "10/1979      1\n",
      "Name: count, Length: 656, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "first_looking(df, \"first_registration\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 374,
   "id": "38f7ad02-5155-49fe-815e-ae94c084273d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0        2016\n",
       "1        2022\n",
       "2        2020\n",
       "3        2020\n",
       "4        2015\n",
       "         ... \n",
       "29474    2019\n",
       "29475    2004\n",
       "29476    2011\n",
       "29477    2017\n",
       "29478    2002\n",
       "Name: first_registration, Length: 28630, dtype: object"
      ]
     },
     "execution_count": 374,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['first_registration'].str.extract('.*(\\d{4})', expand=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 376,
   "id": "7d06c670-3005-4057-a265-b587ca732f75",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0        2016\n",
       "1        2022\n",
       "2        2020\n",
       "3        2020\n",
       "4        2015\n",
       "         ... \n",
       "29474    2019\n",
       "29475    2004\n",
       "29476    2011\n",
       "29477    2017\n",
       "29478    2002\n",
       "Name: first_registration, Length: 28630, dtype: object"
      ]
     },
     "execution_count": 376,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['first_registration'].str[-4:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 378,
   "id": "1942b5c9-2861-4363-a30f-712f719a581e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       2016.00\n",
       "1       2022.00\n",
       "2       2020.00\n",
       "3       2020.00\n",
       "4       2015.00\n",
       "          ...  \n",
       "29474   2019.00\n",
       "29475   2004.00\n",
       "29476   2011.00\n",
       "29477   2017.00\n",
       "29478   2002.00\n",
       "Name: first_registration, Length: 28630, dtype: float64"
      ]
     },
     "execution_count": 378,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['first_registration'] = df['first_registration'].str[-4:].astype('float')\n",
    "df['first_registration']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 380,
   "id": "f68a768a-b456-4423-ac0b-a7c77234f0e0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "first_registration\n",
       "2019.00    3667\n",
       "2018.00    3492\n",
       "2022.00    3086\n",
       "2021.00    2870\n",
       "2020.00    2473\n",
       "2017.00    2426\n",
       "2016.00    1486\n",
       "2015.00    1237\n",
       "2014.00     936\n",
       "2013.00     703\n",
       "2012.00     655\n",
       "2011.00     642\n",
       "2010.00     559\n",
       "2007.00     492\n",
       "2008.00     441\n",
       "2009.00     424\n",
       "2006.00     395\n",
       "2005.00     287\n",
       "2004.00     247\n",
       "2003.00     211\n",
       "2001.00     191\n",
       "2002.00     187\n",
       "2000.00     160\n",
       "1999.00     144\n",
       "1998.00      91\n",
       "1997.00      81\n",
       "1994.00      80\n",
       "1995.00      78\n",
       "1996.00      71\n",
       "1991.00      62\n",
       "1992.00      60\n",
       "1993.00      55\n",
       "1990.00      54\n",
       "1966.00      41\n",
       "1967.00      34\n",
       "1988.00      33\n",
       "1965.00      32\n",
       "1973.00      29\n",
       "1972.00      29\n",
       "1968.00      27\n",
       "1987.00      26\n",
       "1978.00      23\n",
       "1986.00      22\n",
       "1989.00      20\n",
       "1970.00      19\n",
       "1971.00      18\n",
       "1985.00      18\n",
       "1969.00      17\n",
       "1979.00      17\n",
       "1983.00      16\n",
       "1975.00      14\n",
       "1977.00      13\n",
       "1964.00      11\n",
       "1976.00      11\n",
       "1982.00      11\n",
       "1984.00      10\n",
       "1981.00       9\n",
       "1963.00       9\n",
       "1974.00       9\n",
       "1962.00       8\n",
       "1961.00       7\n",
       "1980.00       6\n",
       "1955.00       6\n",
       "1954.00       4\n",
       "1958.00       4\n",
       "1957.00       4\n",
       "1960.00       4\n",
       "1932.00       3\n",
       "1937.00       2\n",
       "1959.00       2\n",
       "1900.00       2\n",
       "1953.00       2\n",
       "1930.00       2\n",
       "NaN           2\n",
       "1952.00       2\n",
       "2025.00       1\n",
       "1933.00       1\n",
       "1946.00       1\n",
       "1956.00       1\n",
       "2023.00       1\n",
       "1929.00       1\n",
       "1950.00       1\n",
       "1928.00       1\n",
       "2202.00       1\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 380,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"first_registration\"].value_counts(dropna=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 384,
   "id": "09d1ab29-b929-4c79-b9ce-b0a114063dc5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "column name    :  first_registration\n",
      "--------------------------------\n",
      "per_of_nulls   :  % 0.01\n",
      "num_of_nulls   :  2\n",
      "num_of_uniques :  84\n",
      "shape_of_df    :  (28630, 30)\n",
      "--------------------------------\n",
      "first_registration\n",
      "2019.00    3667\n",
      "2018.00    3492\n",
      "2022.00    3086\n",
      "2021.00    2870\n",
      "2020.00    2473\n",
      "2017.00    2426\n",
      "2016.00    1486\n",
      "2015.00    1237\n",
      "2014.00     936\n",
      "2013.00     703\n",
      "2012.00     655\n",
      "2011.00     642\n",
      "2010.00     559\n",
      "2007.00     492\n",
      "2008.00     441\n",
      "2009.00     424\n",
      "2006.00     395\n",
      "2005.00     287\n",
      "2004.00     247\n",
      "2003.00     211\n",
      "2001.00     191\n",
      "2002.00     187\n",
      "2000.00     160\n",
      "1999.00     144\n",
      "1998.00      91\n",
      "1997.00      81\n",
      "1994.00      80\n",
      "1995.00      78\n",
      "1996.00      71\n",
      "1991.00      62\n",
      "1992.00      60\n",
      "1993.00      55\n",
      "1990.00      54\n",
      "1966.00      41\n",
      "1967.00      34\n",
      "1988.00      33\n",
      "1965.00      32\n",
      "1973.00      29\n",
      "1972.00      29\n",
      "1968.00      27\n",
      "1987.00      26\n",
      "1978.00      23\n",
      "1986.00      22\n",
      "1989.00      20\n",
      "1970.00      19\n",
      "1971.00      18\n",
      "1985.00      18\n",
      "1969.00      17\n",
      "1979.00      17\n",
      "1983.00      16\n",
      "1975.00      14\n",
      "1977.00      13\n",
      "1964.00      11\n",
      "1976.00      11\n",
      "1982.00      11\n",
      "1984.00      10\n",
      "1981.00       9\n",
      "1963.00       9\n",
      "1974.00       9\n",
      "1962.00       8\n",
      "1961.00       7\n",
      "1980.00       6\n",
      "1955.00       6\n",
      "1954.00       4\n",
      "1958.00       4\n",
      "1957.00       4\n",
      "1960.00       4\n",
      "1932.00       3\n",
      "1937.00       2\n",
      "1959.00       2\n",
      "1900.00       2\n",
      "1953.00       2\n",
      "1930.00       2\n",
      "NaN           2\n",
      "1952.00       2\n",
      "2025.00       1\n",
      "1933.00       1\n",
      "1946.00       1\n",
      "1956.00       1\n",
      "2023.00       1\n",
      "1929.00       1\n",
      "1950.00       1\n",
      "1928.00       1\n",
      "2202.00       1\n",
      "Name: count, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "first_looking(df, 'first_registration')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 394,
   "id": "a5bea65c-0a2c-4ee5-9a62-526da4076599",
   "metadata": {},
   "outputs": [
    {
     "ename": "AttributeError",
     "evalue": "Can only use .str accessor with string values!",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
      "Cell \u001b[1;32mIn[394], line 1\u001b[0m\n\u001b[1;32m----> 1\u001b[0m df[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mfirst_registration\u001b[39m\u001b[38;5;124m'\u001b[39m] \u001b[38;5;241m=\u001b[39m df[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mfirst_registration\u001b[39m\u001b[38;5;124m'\u001b[39m]\u001b[38;5;241m.\u001b[39mstr[\u001b[38;5;241m-\u001b[39m\u001b[38;5;241m4\u001b[39m:]\u001b[38;5;241m.\u001b[39mastype(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mfloat\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[0;32m      2\u001b[0m df[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mfirst_registration\u001b[39m\u001b[38;5;124m'\u001b[39m]\n",
      "File \u001b[1;32m~\\anaconda3\\Lib\\site-packages\\pandas\\core\\generic.py:6299\u001b[0m, in \u001b[0;36mNDFrame.__getattr__\u001b[1;34m(self, name)\u001b[0m\n\u001b[0;32m   6292\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m (\n\u001b[0;32m   6293\u001b[0m     name \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_internal_names_set\n\u001b[0;32m   6294\u001b[0m     \u001b[38;5;129;01mand\u001b[39;00m name \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_metadata\n\u001b[0;32m   6295\u001b[0m     \u001b[38;5;129;01mand\u001b[39;00m name \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_accessors\n\u001b[0;32m   6296\u001b[0m     \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_info_axis\u001b[38;5;241m.\u001b[39m_can_hold_identifiers_and_holds_name(name)\n\u001b[0;32m   6297\u001b[0m ):\n\u001b[0;32m   6298\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m[name]\n\u001b[1;32m-> 6299\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mobject\u001b[39m\u001b[38;5;241m.\u001b[39m\u001b[38;5;21m__getattribute__\u001b[39m(\u001b[38;5;28mself\u001b[39m, name)\n",
      "File \u001b[1;32m~\\anaconda3\\Lib\\site-packages\\pandas\\core\\accessor.py:224\u001b[0m, in \u001b[0;36mCachedAccessor.__get__\u001b[1;34m(self, obj, cls)\u001b[0m\n\u001b[0;32m    221\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m obj \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m    222\u001b[0m     \u001b[38;5;66;03m# we're accessing the attribute of the class, i.e., Dataset.geo\u001b[39;00m\n\u001b[0;32m    223\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_accessor\n\u001b[1;32m--> 224\u001b[0m accessor_obj \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_accessor(obj)\n\u001b[0;32m    225\u001b[0m \u001b[38;5;66;03m# Replace the property with the accessor object. Inspired by:\u001b[39;00m\n\u001b[0;32m    226\u001b[0m \u001b[38;5;66;03m# https://www.pydanny.com/cached-property.html\u001b[39;00m\n\u001b[0;32m    227\u001b[0m \u001b[38;5;66;03m# We need to use object.__setattr__ because we overwrite __setattr__ on\u001b[39;00m\n\u001b[0;32m    228\u001b[0m \u001b[38;5;66;03m# NDFrame\u001b[39;00m\n\u001b[0;32m    229\u001b[0m \u001b[38;5;28mobject\u001b[39m\u001b[38;5;241m.\u001b[39m\u001b[38;5;21m__setattr__\u001b[39m(obj, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_name, accessor_obj)\n",
      "File \u001b[1;32m~\\anaconda3\\Lib\\site-packages\\pandas\\core\\strings\\accessor.py:191\u001b[0m, in \u001b[0;36mStringMethods.__init__\u001b[1;34m(self, data)\u001b[0m\n\u001b[0;32m    188\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m__init__\u001b[39m(\u001b[38;5;28mself\u001b[39m, data) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m    189\u001b[0m     \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mpandas\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mcore\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01marrays\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mstring_\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m StringDtype\n\u001b[1;32m--> 191\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_inferred_dtype \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_validate(data)\n\u001b[0;32m    192\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_is_categorical \u001b[38;5;241m=\u001b[39m \u001b[38;5;28misinstance\u001b[39m(data\u001b[38;5;241m.\u001b[39mdtype, CategoricalDtype)\n\u001b[0;32m    193\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_is_string \u001b[38;5;241m=\u001b[39m \u001b[38;5;28misinstance\u001b[39m(data\u001b[38;5;241m.\u001b[39mdtype, StringDtype)\n",
      "File \u001b[1;32m~\\anaconda3\\Lib\\site-packages\\pandas\\core\\strings\\accessor.py:245\u001b[0m, in \u001b[0;36mStringMethods._validate\u001b[1;34m(data)\u001b[0m\n\u001b[0;32m    242\u001b[0m inferred_dtype \u001b[38;5;241m=\u001b[39m lib\u001b[38;5;241m.\u001b[39minfer_dtype(values, skipna\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m)\n\u001b[0;32m    244\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m inferred_dtype \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;129;01min\u001b[39;00m allowed_types:\n\u001b[1;32m--> 245\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mAttributeError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mCan only use .str accessor with string values!\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[0;32m    246\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m inferred_dtype\n",
      "\u001b[1;31mAttributeError\u001b[0m: Can only use .str accessor with string values!"
     ]
    }
   ],
   "source": [
    "df['first_registration'] = df['first_registration'].str[-4:].astype('float')\n",
    "df['first_registration']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 396,
   "id": "81830e6b-6266-4542-8d05-cca16733019d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "column name    :  gearbox\n",
      "--------------------------------\n",
      "per_of_nulls   :  % 0.87\n",
      "num_of_nulls   :  248\n",
      "num_of_uniques :  4\n",
      "shape_of_df    :  (28630, 30)\n",
      "--------------------------------\n",
      "gearbox\n",
      "[\\nManual\\n]            17023\n",
      "[\\nAutomatic\\n]         11287\n",
      "NaN                       248\n",
      "[\\nSemi-automatic\\n]       72\n",
      "Name: count, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "first_looking(df,\"gearbox\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 404,
   "id": "e89f51df-609e-4f9a-83b0-b7743e9cebe9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0           Manual\n",
       "1        Automatic\n",
       "2        Automatic\n",
       "3        Automatic\n",
       "4        Automatic\n",
       "           ...    \n",
       "29474    Automatic\n",
       "29475    Automatic\n",
       "29476       Manual\n",
       "29477    Automatic\n",
       "29478    Automatic\n",
       "Name: gearbox, Length: 28630, dtype: object"
      ]
     },
     "execution_count": 404,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['gearbox'] = df['gearbox'].astype(str).str.strip(\"['\\\\n']\").str.extract(\"(\\D+)\")\n",
    "df['gearbox']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 406,
   "id": "85d2b409-2b9a-41b0-ac29-a4afeaba3878",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "gearbox\n",
       "Manual            17023\n",
       "Automatic         11287\n",
       "a                   248\n",
       "Semi-automatic       72\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 406,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.gearbox.value_counts(dropna=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 408,
   "id": "74593786-2ff3-426b-b4c9-77d59247b5eb",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['gearbox'].replace('a', np.nan, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 410,
   "id": "c7f62070-7738-4caa-9b2a-c36b95fe394a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "gearbox\n",
       "Manual            17023\n",
       "Automatic         11287\n",
       "NaN                 248\n",
       "Semi-automatic       72\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 410,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.gearbox.value_counts(dropna=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "535513ad-d203-4141-a658-a55f43f357bf",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f9847b41-1a48-4470-80f9-7d981a6bca09",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "df.to_csv('Cleaned_autoscout.csv)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2ff1fefa-8269-4997-9c7f-bb33ef836b26",
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   "outputs": [],
   "source": []
  },
  {
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   "execution_count": null,
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   "outputs": [],
   "source": []
  },
  {
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   "execution_count": null,
   "id": "29cc2d61-2212-4324-a7c8-e15b265b6364",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "be182c94-ef2b-426e-ac20-1aedcd250739",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6a820308-59f6-4fa6-84e8-4f3f4f4150ae",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d474affe-f2a2-4f7e-9f58-42c9e0e9426d",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
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   "execution_count": null,
   "id": "fa5a6095-be24-4e02-8261-70c4999ba9f6",
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   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "63c54034-a9f6-4007-b200-f4a90c29108a",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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