Task 5.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "7f8c73df",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "a31f68e9",
   "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>car_ID</th>\n",
       "      <th>symboling</th>\n",
       "      <th>CarName</th>\n",
       "      <th>fueltype</th>\n",
       "      <th>aspiration</th>\n",
       "      <th>doornumber</th>\n",
       "      <th>carbody</th>\n",
       "      <th>drivewheel</th>\n",
       "      <th>enginelocation</th>\n",
       "      <th>wheelbase</th>\n",
       "      <th>...</th>\n",
       "      <th>enginesize</th>\n",
       "      <th>fuelsystem</th>\n",
       "      <th>boreratio</th>\n",
       "      <th>stroke</th>\n",
       "      <th>compressionratio</th>\n",
       "      <th>horsepower</th>\n",
       "      <th>peakrpm</th>\n",
       "      <th>citympg</th>\n",
       "      <th>highwaympg</th>\n",
       "      <th>price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>alfa-romero giulia</td>\n",
       "      <td>gas</td>\n",
       "      <td>std</td>\n",
       "      <td>two</td>\n",
       "      <td>convertible</td>\n",
       "      <td>rwd</td>\n",
       "      <td>front</td>\n",
       "      <td>88.6</td>\n",
       "      <td>...</td>\n",
       "      <td>130</td>\n",
       "      <td>mpfi</td>\n",
       "      <td>3.47</td>\n",
       "      <td>2.68</td>\n",
       "      <td>9.0</td>\n",
       "      <td>111</td>\n",
       "      <td>5000</td>\n",
       "      <td>21</td>\n",
       "      <td>27</td>\n",
       "      <td>13495.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>alfa-romero stelvio</td>\n",
       "      <td>gas</td>\n",
       "      <td>std</td>\n",
       "      <td>two</td>\n",
       "      <td>convertible</td>\n",
       "      <td>rwd</td>\n",
       "      <td>front</td>\n",
       "      <td>88.6</td>\n",
       "      <td>...</td>\n",
       "      <td>130</td>\n",
       "      <td>mpfi</td>\n",
       "      <td>3.47</td>\n",
       "      <td>2.68</td>\n",
       "      <td>9.0</td>\n",
       "      <td>111</td>\n",
       "      <td>5000</td>\n",
       "      <td>21</td>\n",
       "      <td>27</td>\n",
       "      <td>16500.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>alfa-romero Quadrifoglio</td>\n",
       "      <td>gas</td>\n",
       "      <td>std</td>\n",
       "      <td>two</td>\n",
       "      <td>hatchback</td>\n",
       "      <td>rwd</td>\n",
       "      <td>front</td>\n",
       "      <td>94.5</td>\n",
       "      <td>...</td>\n",
       "      <td>152</td>\n",
       "      <td>mpfi</td>\n",
       "      <td>2.68</td>\n",
       "      <td>3.47</td>\n",
       "      <td>9.0</td>\n",
       "      <td>154</td>\n",
       "      <td>5000</td>\n",
       "      <td>19</td>\n",
       "      <td>26</td>\n",
       "      <td>16500.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>audi 100 ls</td>\n",
       "      <td>gas</td>\n",
       "      <td>std</td>\n",
       "      <td>four</td>\n",
       "      <td>sedan</td>\n",
       "      <td>fwd</td>\n",
       "      <td>front</td>\n",
       "      <td>99.8</td>\n",
       "      <td>...</td>\n",
       "      <td>109</td>\n",
       "      <td>mpfi</td>\n",
       "      <td>3.19</td>\n",
       "      <td>3.40</td>\n",
       "      <td>10.0</td>\n",
       "      <td>102</td>\n",
       "      <td>5500</td>\n",
       "      <td>24</td>\n",
       "      <td>30</td>\n",
       "      <td>13950.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>audi 100ls</td>\n",
       "      <td>gas</td>\n",
       "      <td>std</td>\n",
       "      <td>four</td>\n",
       "      <td>sedan</td>\n",
       "      <td>4wd</td>\n",
       "      <td>front</td>\n",
       "      <td>99.4</td>\n",
       "      <td>...</td>\n",
       "      <td>136</td>\n",
       "      <td>mpfi</td>\n",
       "      <td>3.19</td>\n",
       "      <td>3.40</td>\n",
       "      <td>8.0</td>\n",
       "      <td>115</td>\n",
       "      <td>5500</td>\n",
       "      <td>18</td>\n",
       "      <td>22</td>\n",
       "      <td>17450.0</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>200</th>\n",
       "      <td>201</td>\n",
       "      <td>-1</td>\n",
       "      <td>volvo 145e (sw)</td>\n",
       "      <td>gas</td>\n",
       "      <td>std</td>\n",
       "      <td>four</td>\n",
       "      <td>sedan</td>\n",
       "      <td>rwd</td>\n",
       "      <td>front</td>\n",
       "      <td>109.1</td>\n",
       "      <td>...</td>\n",
       "      <td>141</td>\n",
       "      <td>mpfi</td>\n",
       "      <td>3.78</td>\n",
       "      <td>3.15</td>\n",
       "      <td>9.5</td>\n",
       "      <td>114</td>\n",
       "      <td>5400</td>\n",
       "      <td>23</td>\n",
       "      <td>28</td>\n",
       "      <td>16845.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>201</th>\n",
       "      <td>202</td>\n",
       "      <td>-1</td>\n",
       "      <td>volvo 144ea</td>\n",
       "      <td>gas</td>\n",
       "      <td>turbo</td>\n",
       "      <td>four</td>\n",
       "      <td>sedan</td>\n",
       "      <td>rwd</td>\n",
       "      <td>front</td>\n",
       "      <td>109.1</td>\n",
       "      <td>...</td>\n",
       "      <td>141</td>\n",
       "      <td>mpfi</td>\n",
       "      <td>3.78</td>\n",
       "      <td>3.15</td>\n",
       "      <td>8.7</td>\n",
       "      <td>160</td>\n",
       "      <td>5300</td>\n",
       "      <td>19</td>\n",
       "      <td>25</td>\n",
       "      <td>19045.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202</th>\n",
       "      <td>203</td>\n",
       "      <td>-1</td>\n",
       "      <td>volvo 244dl</td>\n",
       "      <td>gas</td>\n",
       "      <td>std</td>\n",
       "      <td>four</td>\n",
       "      <td>sedan</td>\n",
       "      <td>rwd</td>\n",
       "      <td>front</td>\n",
       "      <td>109.1</td>\n",
       "      <td>...</td>\n",
       "      <td>173</td>\n",
       "      <td>mpfi</td>\n",
       "      <td>3.58</td>\n",
       "      <td>2.87</td>\n",
       "      <td>8.8</td>\n",
       "      <td>134</td>\n",
       "      <td>5500</td>\n",
       "      <td>18</td>\n",
       "      <td>23</td>\n",
       "      <td>21485.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>203</th>\n",
       "      <td>204</td>\n",
       "      <td>-1</td>\n",
       "      <td>volvo 246</td>\n",
       "      <td>diesel</td>\n",
       "      <td>turbo</td>\n",
       "      <td>four</td>\n",
       "      <td>sedan</td>\n",
       "      <td>rwd</td>\n",
       "      <td>front</td>\n",
       "      <td>109.1</td>\n",
       "      <td>...</td>\n",
       "      <td>145</td>\n",
       "      <td>idi</td>\n",
       "      <td>3.01</td>\n",
       "      <td>3.40</td>\n",
       "      <td>23.0</td>\n",
       "      <td>106</td>\n",
       "      <td>4800</td>\n",
       "      <td>26</td>\n",
       "      <td>27</td>\n",
       "      <td>22470.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>204</th>\n",
       "      <td>205</td>\n",
       "      <td>-1</td>\n",
       "      <td>volvo 264gl</td>\n",
       "      <td>gas</td>\n",
       "      <td>turbo</td>\n",
       "      <td>four</td>\n",
       "      <td>sedan</td>\n",
       "      <td>rwd</td>\n",
       "      <td>front</td>\n",
       "      <td>109.1</td>\n",
       "      <td>...</td>\n",
       "      <td>141</td>\n",
       "      <td>mpfi</td>\n",
       "      <td>3.78</td>\n",
       "      <td>3.15</td>\n",
       "      <td>9.5</td>\n",
       "      <td>114</td>\n",
       "      <td>5400</td>\n",
       "      <td>19</td>\n",
       "      <td>25</td>\n",
       "      <td>22625.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>205 rows × 26 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     car_ID  symboling                   CarName fueltype aspiration  \\\n",
       "0         1          3        alfa-romero giulia      gas        std   \n",
       "1         2          3       alfa-romero stelvio      gas        std   \n",
       "2         3          1  alfa-romero Quadrifoglio      gas        std   \n",
       "3         4          2               audi 100 ls      gas        std   \n",
       "4         5          2                audi 100ls      gas        std   \n",
       "..      ...        ...                       ...      ...        ...   \n",
       "200     201         -1           volvo 145e (sw)      gas        std   \n",
       "201     202         -1               volvo 144ea      gas      turbo   \n",
       "202     203         -1               volvo 244dl      gas        std   \n",
       "203     204         -1                 volvo 246   diesel      turbo   \n",
       "204     205         -1               volvo 264gl      gas      turbo   \n",
       "\n",
       "    doornumber      carbody drivewheel enginelocation  wheelbase  ...  \\\n",
       "0          two  convertible        rwd          front       88.6  ...   \n",
       "1          two  convertible        rwd          front       88.6  ...   \n",
       "2          two    hatchback        rwd          front       94.5  ...   \n",
       "3         four        sedan        fwd          front       99.8  ...   \n",
       "4         four        sedan        4wd          front       99.4  ...   \n",
       "..         ...          ...        ...            ...        ...  ...   \n",
       "200       four        sedan        rwd          front      109.1  ...   \n",
       "201       four        sedan        rwd          front      109.1  ...   \n",
       "202       four        sedan        rwd          front      109.1  ...   \n",
       "203       four        sedan        rwd          front      109.1  ...   \n",
       "204       four        sedan        rwd          front      109.1  ...   \n",
       "\n",
       "     enginesize  fuelsystem  boreratio  stroke compressionratio horsepower  \\\n",
       "0           130        mpfi       3.47    2.68              9.0        111   \n",
       "1           130        mpfi       3.47    2.68              9.0        111   \n",
       "2           152        mpfi       2.68    3.47              9.0        154   \n",
       "3           109        mpfi       3.19    3.40             10.0        102   \n",
       "4           136        mpfi       3.19    3.40              8.0        115   \n",
       "..          ...         ...        ...     ...              ...        ...   \n",
       "200         141        mpfi       3.78    3.15              9.5        114   \n",
       "201         141        mpfi       3.78    3.15              8.7        160   \n",
       "202         173        mpfi       3.58    2.87              8.8        134   \n",
       "203         145         idi       3.01    3.40             23.0        106   \n",
       "204         141        mpfi       3.78    3.15              9.5        114   \n",
       "\n",
       "     peakrpm citympg  highwaympg    price  \n",
       "0       5000      21          27  13495.0  \n",
       "1       5000      21          27  16500.0  \n",
       "2       5000      19          26  16500.0  \n",
       "3       5500      24          30  13950.0  \n",
       "4       5500      18          22  17450.0  \n",
       "..       ...     ...         ...      ...  \n",
       "200     5400      23          28  16845.0  \n",
       "201     5300      19          25  19045.0  \n",
       "202     5500      18          23  21485.0  \n",
       "203     4800      26          27  22470.0  \n",
       "204     5400      19          25  22625.0  \n",
       "\n",
       "[205 rows x 26 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv('Task 5 CarPrice_Assignment.csv')\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "2821015b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 205 entries, 0 to 204\n",
      "Data columns (total 26 columns):\n",
      " #   Column            Non-Null Count  Dtype  \n",
      "---  ------            --------------  -----  \n",
      " 0   car_ID            205 non-null    int64  \n",
      " 1   symboling         205 non-null    int64  \n",
      " 2   CarName           205 non-null    object \n",
      " 3   fueltype          205 non-null    object \n",
      " 4   aspiration        205 non-null    object \n",
      " 5   doornumber        205 non-null    object \n",
      " 6   carbody           205 non-null    object \n",
      " 7   drivewheel        205 non-null    object \n",
      " 8   enginelocation    205 non-null    object \n",
      " 9   wheelbase         205 non-null    float64\n",
      " 10  carlength         205 non-null    float64\n",
      " 11  carwidth          205 non-null    float64\n",
      " 12  carheight         205 non-null    float64\n",
      " 13  curbweight        205 non-null    int64  \n",
      " 14  enginetype        205 non-null    object \n",
      " 15  cylindernumber    205 non-null    object \n",
      " 16  enginesize        205 non-null    int64  \n",
      " 17  fuelsystem        205 non-null    object \n",
      " 18  boreratio         205 non-null    float64\n",
      " 19  stroke            205 non-null    float64\n",
      " 20  compressionratio  205 non-null    float64\n",
      " 21  horsepower        205 non-null    int64  \n",
      " 22  peakrpm           205 non-null    int64  \n",
      " 23  citympg           205 non-null    int64  \n",
      " 24  highwaympg        205 non-null    int64  \n",
      " 25  price             205 non-null    float64\n",
      "dtypes: float64(8), int64(8), object(10)\n",
      "memory usage: 41.8+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "4ef3d7d3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.duplicated().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "3c2d3289",
   "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>car_ID</th>\n",
       "      <th>symboling</th>\n",
       "      <th>wheelbase</th>\n",
       "      <th>carlength</th>\n",
       "      <th>carwidth</th>\n",
       "      <th>carheight</th>\n",
       "      <th>curbweight</th>\n",
       "      <th>enginesize</th>\n",
       "      <th>boreratio</th>\n",
       "      <th>stroke</th>\n",
       "      <th>compressionratio</th>\n",
       "      <th>horsepower</th>\n",
       "      <th>peakrpm</th>\n",
       "      <th>citympg</th>\n",
       "      <th>highwaympg</th>\n",
       "      <th>price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>205.000000</td>\n",
       "      <td>205.000000</td>\n",
       "      <td>205.000000</td>\n",
       "      <td>205.000000</td>\n",
       "      <td>205.000000</td>\n",
       "      <td>205.000000</td>\n",
       "      <td>205.000000</td>\n",
       "      <td>205.000000</td>\n",
       "      <td>205.000000</td>\n",
       "      <td>205.000000</td>\n",
       "      <td>205.000000</td>\n",
       "      <td>205.000000</td>\n",
       "      <td>205.000000</td>\n",
       "      <td>205.000000</td>\n",
       "      <td>205.000000</td>\n",
       "      <td>205.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>103.000000</td>\n",
       "      <td>0.834146</td>\n",
       "      <td>98.756585</td>\n",
       "      <td>174.049268</td>\n",
       "      <td>65.907805</td>\n",
       "      <td>53.724878</td>\n",
       "      <td>2555.565854</td>\n",
       "      <td>126.907317</td>\n",
       "      <td>3.329756</td>\n",
       "      <td>3.255415</td>\n",
       "      <td>10.142537</td>\n",
       "      <td>104.117073</td>\n",
       "      <td>5125.121951</td>\n",
       "      <td>25.219512</td>\n",
       "      <td>30.751220</td>\n",
       "      <td>13276.710571</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>59.322565</td>\n",
       "      <td>1.245307</td>\n",
       "      <td>6.021776</td>\n",
       "      <td>12.337289</td>\n",
       "      <td>2.145204</td>\n",
       "      <td>2.443522</td>\n",
       "      <td>520.680204</td>\n",
       "      <td>41.642693</td>\n",
       "      <td>0.270844</td>\n",
       "      <td>0.313597</td>\n",
       "      <td>3.972040</td>\n",
       "      <td>39.544167</td>\n",
       "      <td>476.985643</td>\n",
       "      <td>6.542142</td>\n",
       "      <td>6.886443</td>\n",
       "      <td>7988.852332</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>-2.000000</td>\n",
       "      <td>86.600000</td>\n",
       "      <td>141.100000</td>\n",
       "      <td>60.300000</td>\n",
       "      <td>47.800000</td>\n",
       "      <td>1488.000000</td>\n",
       "      <td>61.000000</td>\n",
       "      <td>2.540000</td>\n",
       "      <td>2.070000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>48.000000</td>\n",
       "      <td>4150.000000</td>\n",
       "      <td>13.000000</td>\n",
       "      <td>16.000000</td>\n",
       "      <td>5118.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>52.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>94.500000</td>\n",
       "      <td>166.300000</td>\n",
       "      <td>64.100000</td>\n",
       "      <td>52.000000</td>\n",
       "      <td>2145.000000</td>\n",
       "      <td>97.000000</td>\n",
       "      <td>3.150000</td>\n",
       "      <td>3.110000</td>\n",
       "      <td>8.600000</td>\n",
       "      <td>70.000000</td>\n",
       "      <td>4800.000000</td>\n",
       "      <td>19.000000</td>\n",
       "      <td>25.000000</td>\n",
       "      <td>7788.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>103.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>97.000000</td>\n",
       "      <td>173.200000</td>\n",
       "      <td>65.500000</td>\n",
       "      <td>54.100000</td>\n",
       "      <td>2414.000000</td>\n",
       "      <td>120.000000</td>\n",
       "      <td>3.310000</td>\n",
       "      <td>3.290000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>95.000000</td>\n",
       "      <td>5200.000000</td>\n",
       "      <td>24.000000</td>\n",
       "      <td>30.000000</td>\n",
       "      <td>10295.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>154.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>102.400000</td>\n",
       "      <td>183.100000</td>\n",
       "      <td>66.900000</td>\n",
       "      <td>55.500000</td>\n",
       "      <td>2935.000000</td>\n",
       "      <td>141.000000</td>\n",
       "      <td>3.580000</td>\n",
       "      <td>3.410000</td>\n",
       "      <td>9.400000</td>\n",
       "      <td>116.000000</td>\n",
       "      <td>5500.000000</td>\n",
       "      <td>30.000000</td>\n",
       "      <td>34.000000</td>\n",
       "      <td>16503.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>205.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>120.900000</td>\n",
       "      <td>208.100000</td>\n",
       "      <td>72.300000</td>\n",
       "      <td>59.800000</td>\n",
       "      <td>4066.000000</td>\n",
       "      <td>326.000000</td>\n",
       "      <td>3.940000</td>\n",
       "      <td>4.170000</td>\n",
       "      <td>23.000000</td>\n",
       "      <td>288.000000</td>\n",
       "      <td>6600.000000</td>\n",
       "      <td>49.000000</td>\n",
       "      <td>54.000000</td>\n",
       "      <td>45400.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           car_ID   symboling   wheelbase   carlength    carwidth   carheight  \\\n",
       "count  205.000000  205.000000  205.000000  205.000000  205.000000  205.000000   \n",
       "mean   103.000000    0.834146   98.756585  174.049268   65.907805   53.724878   \n",
       "std     59.322565    1.245307    6.021776   12.337289    2.145204    2.443522   \n",
       "min      1.000000   -2.000000   86.600000  141.100000   60.300000   47.800000   \n",
       "25%     52.000000    0.000000   94.500000  166.300000   64.100000   52.000000   \n",
       "50%    103.000000    1.000000   97.000000  173.200000   65.500000   54.100000   \n",
       "75%    154.000000    2.000000  102.400000  183.100000   66.900000   55.500000   \n",
       "max    205.000000    3.000000  120.900000  208.100000   72.300000   59.800000   \n",
       "\n",
       "        curbweight  enginesize   boreratio      stroke  compressionratio  \\\n",
       "count   205.000000  205.000000  205.000000  205.000000        205.000000   \n",
       "mean   2555.565854  126.907317    3.329756    3.255415         10.142537   \n",
       "std     520.680204   41.642693    0.270844    0.313597          3.972040   \n",
       "min    1488.000000   61.000000    2.540000    2.070000          7.000000   \n",
       "25%    2145.000000   97.000000    3.150000    3.110000          8.600000   \n",
       "50%    2414.000000  120.000000    3.310000    3.290000          9.000000   \n",
       "75%    2935.000000  141.000000    3.580000    3.410000          9.400000   \n",
       "max    4066.000000  326.000000    3.940000    4.170000         23.000000   \n",
       "\n",
       "       horsepower      peakrpm     citympg  highwaympg         price  \n",
       "count  205.000000   205.000000  205.000000  205.000000    205.000000  \n",
       "mean   104.117073  5125.121951   25.219512   30.751220  13276.710571  \n",
       "std     39.544167   476.985643    6.542142    6.886443   7988.852332  \n",
       "min     48.000000  4150.000000   13.000000   16.000000   5118.000000  \n",
       "25%     70.000000  4800.000000   19.000000   25.000000   7788.000000  \n",
       "50%     95.000000  5200.000000   24.000000   30.000000  10295.000000  \n",
       "75%    116.000000  5500.000000   30.000000   34.000000  16503.000000  \n",
       "max    288.000000  6600.000000   49.000000   54.000000  45400.000000  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "422e5565",
   "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>car_ID</th>\n",
       "      <th>symboling</th>\n",
       "      <th>CarName</th>\n",
       "      <th>fueltype</th>\n",
       "      <th>aspiration</th>\n",
       "      <th>doornumber</th>\n",
       "      <th>carbody</th>\n",
       "      <th>drivewheel</th>\n",
       "      <th>enginelocation</th>\n",
       "      <th>wheelbase</th>\n",
       "      <th>...</th>\n",
       "      <th>enginesize</th>\n",
       "      <th>fuelsystem</th>\n",
       "      <th>boreratio</th>\n",
       "      <th>stroke</th>\n",
       "      <th>compressionratio</th>\n",
       "      <th>horsepower</th>\n",
       "      <th>peakrpm</th>\n",
       "      <th>citympg</th>\n",
       "      <th>highwaympg</th>\n",
       "      <th>price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>205.000000</td>\n",
       "      <td>205.000000</td>\n",
       "      <td>205</td>\n",
       "      <td>205</td>\n",
       "      <td>205</td>\n",
       "      <td>205</td>\n",
       "      <td>205</td>\n",
       "      <td>205</td>\n",
       "      <td>205</td>\n",
       "      <td>205.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>205.000000</td>\n",
       "      <td>205</td>\n",
       "      <td>205.000000</td>\n",
       "      <td>205.000000</td>\n",
       "      <td>205.000000</td>\n",
       "      <td>205.000000</td>\n",
       "      <td>205.000000</td>\n",
       "      <td>205.000000</td>\n",
       "      <td>205.000000</td>\n",
       "      <td>205.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>unique</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>147</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <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>top</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>toyota corona</td>\n",
       "      <td>gas</td>\n",
       "      <td>std</td>\n",
       "      <td>four</td>\n",
       "      <td>sedan</td>\n",
       "      <td>fwd</td>\n",
       "      <td>front</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>mpfi</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <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>freq</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6</td>\n",
       "      <td>185</td>\n",
       "      <td>168</td>\n",
       "      <td>115</td>\n",
       "      <td>96</td>\n",
       "      <td>120</td>\n",
       "      <td>202</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>94</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <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>mean</th>\n",
       "      <td>103.000000</td>\n",
       "      <td>0.834146</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>98.756585</td>\n",
       "      <td>...</td>\n",
       "      <td>126.907317</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.329756</td>\n",
       "      <td>3.255415</td>\n",
       "      <td>10.142537</td>\n",
       "      <td>104.117073</td>\n",
       "      <td>5125.121951</td>\n",
       "      <td>25.219512</td>\n",
       "      <td>30.751220</td>\n",
       "      <td>13276.710571</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>59.322565</td>\n",
       "      <td>1.245307</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.021776</td>\n",
       "      <td>...</td>\n",
       "      <td>41.642693</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.270844</td>\n",
       "      <td>0.313597</td>\n",
       "      <td>3.972040</td>\n",
       "      <td>39.544167</td>\n",
       "      <td>476.985643</td>\n",
       "      <td>6.542142</td>\n",
       "      <td>6.886443</td>\n",
       "      <td>7988.852332</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>-2.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>86.600000</td>\n",
       "      <td>...</td>\n",
       "      <td>61.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.540000</td>\n",
       "      <td>2.070000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>48.000000</td>\n",
       "      <td>4150.000000</td>\n",
       "      <td>13.000000</td>\n",
       "      <td>16.000000</td>\n",
       "      <td>5118.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>52.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>94.500000</td>\n",
       "      <td>...</td>\n",
       "      <td>97.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.150000</td>\n",
       "      <td>3.110000</td>\n",
       "      <td>8.600000</td>\n",
       "      <td>70.000000</td>\n",
       "      <td>4800.000000</td>\n",
       "      <td>19.000000</td>\n",
       "      <td>25.000000</td>\n",
       "      <td>7788.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>103.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>97.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>120.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.310000</td>\n",
       "      <td>3.290000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>95.000000</td>\n",
       "      <td>5200.000000</td>\n",
       "      <td>24.000000</td>\n",
       "      <td>30.000000</td>\n",
       "      <td>10295.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>154.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>102.400000</td>\n",
       "      <td>...</td>\n",
       "      <td>141.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.580000</td>\n",
       "      <td>3.410000</td>\n",
       "      <td>9.400000</td>\n",
       "      <td>116.000000</td>\n",
       "      <td>5500.000000</td>\n",
       "      <td>30.000000</td>\n",
       "      <td>34.000000</td>\n",
       "      <td>16503.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>205.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>120.900000</td>\n",
       "      <td>...</td>\n",
       "      <td>326.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.940000</td>\n",
       "      <td>4.170000</td>\n",
       "      <td>23.000000</td>\n",
       "      <td>288.000000</td>\n",
       "      <td>6600.000000</td>\n",
       "      <td>49.000000</td>\n",
       "      <td>54.000000</td>\n",
       "      <td>45400.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>11 rows × 26 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            car_ID   symboling        CarName fueltype aspiration doornumber  \\\n",
       "count   205.000000  205.000000            205      205        205        205   \n",
       "unique         NaN         NaN            147        2          2          2   \n",
       "top            NaN         NaN  toyota corona      gas        std       four   \n",
       "freq           NaN         NaN              6      185        168        115   \n",
       "mean    103.000000    0.834146            NaN      NaN        NaN        NaN   \n",
       "std      59.322565    1.245307            NaN      NaN        NaN        NaN   \n",
       "min       1.000000   -2.000000            NaN      NaN        NaN        NaN   \n",
       "25%      52.000000    0.000000            NaN      NaN        NaN        NaN   \n",
       "50%     103.000000    1.000000            NaN      NaN        NaN        NaN   \n",
       "75%     154.000000    2.000000            NaN      NaN        NaN        NaN   \n",
       "max     205.000000    3.000000            NaN      NaN        NaN        NaN   \n",
       "\n",
       "       carbody drivewheel enginelocation   wheelbase  ...  enginesize  \\\n",
       "count      205        205            205  205.000000  ...  205.000000   \n",
       "unique       5          3              2         NaN  ...         NaN   \n",
       "top      sedan        fwd          front         NaN  ...         NaN   \n",
       "freq        96        120            202         NaN  ...         NaN   \n",
       "mean       NaN        NaN            NaN   98.756585  ...  126.907317   \n",
       "std        NaN        NaN            NaN    6.021776  ...   41.642693   \n",
       "min        NaN        NaN            NaN   86.600000  ...   61.000000   \n",
       "25%        NaN        NaN            NaN   94.500000  ...   97.000000   \n",
       "50%        NaN        NaN            NaN   97.000000  ...  120.000000   \n",
       "75%        NaN        NaN            NaN  102.400000  ...  141.000000   \n",
       "max        NaN        NaN            NaN  120.900000  ...  326.000000   \n",
       "\n",
       "        fuelsystem   boreratio      stroke compressionratio  horsepower  \\\n",
       "count          205  205.000000  205.000000       205.000000  205.000000   \n",
       "unique           8         NaN         NaN              NaN         NaN   \n",
       "top           mpfi         NaN         NaN              NaN         NaN   \n",
       "freq            94         NaN         NaN              NaN         NaN   \n",
       "mean           NaN    3.329756    3.255415        10.142537  104.117073   \n",
       "std            NaN    0.270844    0.313597         3.972040   39.544167   \n",
       "min            NaN    2.540000    2.070000         7.000000   48.000000   \n",
       "25%            NaN    3.150000    3.110000         8.600000   70.000000   \n",
       "50%            NaN    3.310000    3.290000         9.000000   95.000000   \n",
       "75%            NaN    3.580000    3.410000         9.400000  116.000000   \n",
       "max            NaN    3.940000    4.170000        23.000000  288.000000   \n",
       "\n",
       "            peakrpm     citympg  highwaympg         price  \n",
       "count    205.000000  205.000000  205.000000    205.000000  \n",
       "unique          NaN         NaN         NaN           NaN  \n",
       "top             NaN         NaN         NaN           NaN  \n",
       "freq            NaN         NaN         NaN           NaN  \n",
       "mean    5125.121951   25.219512   30.751220  13276.710571  \n",
       "std      476.985643    6.542142    6.886443   7988.852332  \n",
       "min     4150.000000   13.000000   16.000000   5118.000000  \n",
       "25%     4800.000000   19.000000   25.000000   7788.000000  \n",
       "50%     5200.000000   24.000000   30.000000  10295.000000  \n",
       "75%     5500.000000   30.000000   34.000000  16503.000000  \n",
       "max     6600.000000   49.000000   54.000000  45400.000000  \n",
       "\n",
       "[11 rows x 26 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe(include = 'all')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "2517feb4",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>CarName</th>\n",
       "      <th>fueltype</th>\n",
       "      <th>aspiration</th>\n",
       "      <th>doornumber</th>\n",
       "      <th>carbody</th>\n",
       "      <th>drivewheel</th>\n",
       "      <th>enginelocation</th>\n",
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       "      <td>two</td>\n",
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       "      <td>dohc</td>\n",
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       "      <td>mpfi</td>\n",
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       "    <tr>\n",
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       "      <td>alfa-romero stelvio</td>\n",
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       "    <tr>\n",
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       "      <td>alfa-romero Quadrifoglio</td>\n",
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       "      <td>mpfi</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>audi 100 ls</td>\n",
       "      <td>gas</td>\n",
       "      <td>std</td>\n",
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       "      <td>sedan</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>200</th>\n",
       "      <td>volvo 145e (sw)</td>\n",
       "      <td>gas</td>\n",
       "      <td>std</td>\n",
       "      <td>four</td>\n",
       "      <td>sedan</td>\n",
       "      <td>rwd</td>\n",
       "      <td>front</td>\n",
       "      <td>ohc</td>\n",
       "      <td>four</td>\n",
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       "      <td>volvo 144ea</td>\n",
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       "      <td>four</td>\n",
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       "      <td>front</td>\n",
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       "      <td>mpfi</td>\n",
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       "    <tr>\n",
       "      <th>202</th>\n",
       "      <td>volvo 244dl</td>\n",
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       "      <td>diesel</td>\n",
       "      <td>turbo</td>\n",
       "      <td>four</td>\n",
       "      <td>sedan</td>\n",
       "      <td>rwd</td>\n",
       "      <td>front</td>\n",
       "      <td>ohc</td>\n",
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       "      <td>idi</td>\n",
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       "      <th>204</th>\n",
       "      <td>volvo 264gl</td>\n",
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       "      <td>sedan</td>\n",
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       "      <td>front</td>\n",
       "      <td>ohc</td>\n",
       "      <td>four</td>\n",
       "      <td>mpfi</td>\n",
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      "text/plain": [
       "                      CarName fueltype aspiration doornumber      carbody  \\\n",
       "0          alfa-romero giulia      gas        std        two  convertible   \n",
       "1         alfa-romero stelvio      gas        std        two  convertible   \n",
       "2    alfa-romero Quadrifoglio      gas        std        two    hatchback   \n",
       "3                 audi 100 ls      gas        std       four        sedan   \n",
       "4                  audi 100ls      gas        std       four        sedan   \n",
       "..                        ...      ...        ...        ...          ...   \n",
       "200           volvo 145e (sw)      gas        std       four        sedan   \n",
       "201               volvo 144ea      gas      turbo       four        sedan   \n",
       "202               volvo 244dl      gas        std       four        sedan   \n",
       "203                 volvo 246   diesel      turbo       four        sedan   \n",
       "204               volvo 264gl      gas      turbo       four        sedan   \n",
       "\n",
       "    drivewheel enginelocation enginetype cylindernumber fuelsystem  \n",
       "0          rwd          front       dohc           four       mpfi  \n",
       "1          rwd          front       dohc           four       mpfi  \n",
       "2          rwd          front       ohcv            six       mpfi  \n",
       "3          fwd          front        ohc           four       mpfi  \n",
       "4          4wd          front        ohc           five       mpfi  \n",
       "..         ...            ...        ...            ...        ...  \n",
       "200        rwd          front        ohc           four       mpfi  \n",
       "201        rwd          front        ohc           four       mpfi  \n",
       "202        rwd          front       ohcv            six       mpfi  \n",
       "203        rwd          front        ohc            six        idi  \n",
       "204        rwd          front        ohc           four       mpfi  \n",
       "\n",
       "[205 rows x 10 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cat_col = df.select_dtypes(include = 'object')\n",
    "cat_col"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1cb09ffb",
   "metadata": {},
   "outputs": [],
   "source": [
    " "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "20cb5d7d",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
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       "  </tbody>\n",
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       "<p>205 rows × 16 columns</p>\n",
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      ],
      "text/plain": [
       "     car_ID  symboling  wheelbase  carlength  carwidth  carheight  curbweight  \\\n",
       "0         1          3       88.6      168.8      64.1       48.8        2548   \n",
       "1         2          3       88.6      168.8      64.1       48.8        2548   \n",
       "2         3          1       94.5      171.2      65.5       52.4        2823   \n",
       "3         4          2       99.8      176.6      66.2       54.3        2337   \n",
       "4         5          2       99.4      176.6      66.4       54.3        2824   \n",
       "..      ...        ...        ...        ...       ...        ...         ...   \n",
       "200     201         -1      109.1      188.8      68.9       55.5        2952   \n",
       "201     202         -1      109.1      188.8      68.8       55.5        3049   \n",
       "202     203         -1      109.1      188.8      68.9       55.5        3012   \n",
       "203     204         -1      109.1      188.8      68.9       55.5        3217   \n",
       "204     205         -1      109.1      188.8      68.9       55.5        3062   \n",
       "\n",
       "     enginesize  boreratio  stroke  compressionratio  horsepower  peakrpm  \\\n",
       "0           130       3.47    2.68               9.0         111     5000   \n",
       "1           130       3.47    2.68               9.0         111     5000   \n",
       "2           152       2.68    3.47               9.0         154     5000   \n",
       "3           109       3.19    3.40              10.0         102     5500   \n",
       "4           136       3.19    3.40               8.0         115     5500   \n",
       "..          ...        ...     ...               ...         ...      ...   \n",
       "200         141       3.78    3.15               9.5         114     5400   \n",
       "201         141       3.78    3.15               8.7         160     5300   \n",
       "202         173       3.58    2.87               8.8         134     5500   \n",
       "203         145       3.01    3.40              23.0         106     4800   \n",
       "204         141       3.78    3.15               9.5         114     5400   \n",
       "\n",
       "     citympg  highwaympg    price  \n",
       "0         21          27  13495.0  \n",
       "1         21          27  16500.0  \n",
       "2         19          26  16500.0  \n",
       "3         24          30  13950.0  \n",
       "4         18          22  17450.0  \n",
       "..       ...         ...      ...  \n",
       "200       23          28  16845.0  \n",
       "201       19          25  19045.0  \n",
       "202       18          23  21485.0  \n",
       "203       26          27  22470.0  \n",
       "204       19          25  22625.0  \n",
       "\n",
       "[205 rows x 16 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cont_col = df.select_dtypes(exclude = 'object')\n",
    "cont_col"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "30642e17",
   "metadata": {},
   "outputs": [],
   "source": [
    "q1 = cont_col.quantile(0.25)\n",
    "q3 = cont_col.quantile(0.75)\n",
    "iqr = q3-q1\n",
    "lower_bound = q1- 1.5*iqr\n",
    "upper_bound = q3 + 1.5*iqr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "cd99ec78",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "66"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "outliers = ((cont_col < lower_bound) | (cont_col > upper_bound)).any(axis = 1)\n",
    "outliers.sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "ec211a6b",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df[~outliers]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "5a1ca19d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(139, 26)"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "83c17b7f",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.preprocessing import LabelEncoder"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "b6c67086",
   "metadata": {},
   "outputs": [],
   "source": [
    "le = LabelEncoder()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "598f0324",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Administrator\\AppData\\Local\\Temp\\ipykernel_17512\\639738213.py:2: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df[col] = le.fit_transform(df[col])\n",
      "C:\\Users\\Administrator\\AppData\\Local\\Temp\\ipykernel_17512\\639738213.py:2: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df[col] = le.fit_transform(df[col])\n",
      "C:\\Users\\Administrator\\AppData\\Local\\Temp\\ipykernel_17512\\639738213.py:2: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df[col] = le.fit_transform(df[col])\n",
      "C:\\Users\\Administrator\\AppData\\Local\\Temp\\ipykernel_17512\\639738213.py:2: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df[col] = le.fit_transform(df[col])\n",
      "C:\\Users\\Administrator\\AppData\\Local\\Temp\\ipykernel_17512\\639738213.py:2: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df[col] = le.fit_transform(df[col])\n",
      "C:\\Users\\Administrator\\AppData\\Local\\Temp\\ipykernel_17512\\639738213.py:2: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df[col] = le.fit_transform(df[col])\n",
      "C:\\Users\\Administrator\\AppData\\Local\\Temp\\ipykernel_17512\\639738213.py:2: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df[col] = le.fit_transform(df[col])\n",
      "C:\\Users\\Administrator\\AppData\\Local\\Temp\\ipykernel_17512\\639738213.py:2: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df[col] = le.fit_transform(df[col])\n",
      "C:\\Users\\Administrator\\AppData\\Local\\Temp\\ipykernel_17512\\639738213.py:2: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df[col] = le.fit_transform(df[col])\n",
      "C:\\Users\\Administrator\\AppData\\Local\\Temp\\ipykernel_17512\\639738213.py:2: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df[col] = le.fit_transform(df[col])\n"
     ]
    },
    {
     "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",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>car_ID</th>\n",
       "      <th>symboling</th>\n",
       "      <th>CarName</th>\n",
       "      <th>fueltype</th>\n",
       "      <th>aspiration</th>\n",
       "      <th>doornumber</th>\n",
       "      <th>carbody</th>\n",
       "      <th>drivewheel</th>\n",
       "      <th>enginelocation</th>\n",
       "      <th>wheelbase</th>\n",
       "      <th>...</th>\n",
       "      <th>enginesize</th>\n",
       "      <th>fuelsystem</th>\n",
       "      <th>boreratio</th>\n",
       "      <th>stroke</th>\n",
       "      <th>compressionratio</th>\n",
       "      <th>horsepower</th>\n",
       "      <th>peakrpm</th>\n",
       "      <th>citympg</th>\n",
       "      <th>highwaympg</th>\n",
       "      <th>price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
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       "      <td>3</td>\n",
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       "      <td>8.7</td>\n",
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       "      <td>5300</td>\n",
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       "      <td>25</td>\n",
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       "    <tr>\n",
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       "      <td>3</td>\n",
       "      <td>3.58</td>\n",
       "      <td>2.87</td>\n",
       "      <td>8.8</td>\n",
       "      <td>134</td>\n",
       "      <td>5500</td>\n",
       "      <td>18</td>\n",
       "      <td>23</td>\n",
       "      <td>21485.0</td>\n",
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       "    <tr>\n",
       "      <th>204</th>\n",
       "      <td>205</td>\n",
       "      <td>-1</td>\n",
       "      <td>98</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>109.1</td>\n",
       "      <td>...</td>\n",
       "      <td>141</td>\n",
       "      <td>3</td>\n",
       "      <td>3.78</td>\n",
       "      <td>3.15</td>\n",
       "      <td>9.5</td>\n",
       "      <td>114</td>\n",
       "      <td>5400</td>\n",
       "      <td>19</td>\n",
       "      <td>25</td>\n",
       "      <td>22625.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>139 rows × 26 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     car_ID  symboling  CarName  fueltype  aspiration  doornumber  carbody  \\\n",
       "0         1          3        2         0           0           1        0   \n",
       "1         2          3        3         0           0           1        0   \n",
       "2         3          1        1         0           0           1        2   \n",
       "3         4          2        4         0           0           0        3   \n",
       "4         5          2        5         0           0           0        3   \n",
       "..      ...        ...      ...       ...         ...         ...      ...   \n",
       "199     200         -1       99         0           1           0        4   \n",
       "200     201         -1       95         0           0           0        3   \n",
       "201     202         -1       94         0           1           0        3   \n",
       "202     203         -1       96         0           0           0        3   \n",
       "204     205         -1       98         0           1           0        3   \n",
       "\n",
       "     drivewheel  enginelocation  wheelbase  ...  enginesize  fuelsystem  \\\n",
       "0             2               0       88.6  ...         130           3   \n",
       "1             2               0       88.6  ...         130           3   \n",
       "2             2               0       94.5  ...         152           3   \n",
       "3             1               0       99.8  ...         109           3   \n",
       "4             0               0       99.4  ...         136           3   \n",
       "..          ...             ...        ...  ...         ...         ...   \n",
       "199           2               0      104.3  ...         130           3   \n",
       "200           2               0      109.1  ...         141           3   \n",
       "201           2               0      109.1  ...         141           3   \n",
       "202           2               0      109.1  ...         173           3   \n",
       "204           2               0      109.1  ...         141           3   \n",
       "\n",
       "     boreratio  stroke  compressionratio  horsepower  peakrpm  citympg  \\\n",
       "0         3.47    2.68               9.0         111     5000       21   \n",
       "1         3.47    2.68               9.0         111     5000       21   \n",
       "2         2.68    3.47               9.0         154     5000       19   \n",
       "3         3.19    3.40              10.0         102     5500       24   \n",
       "4         3.19    3.40               8.0         115     5500       18   \n",
       "..         ...     ...               ...         ...      ...      ...   \n",
       "199       3.62    3.15               7.5         162     5100       17   \n",
       "200       3.78    3.15               9.5         114     5400       23   \n",
       "201       3.78    3.15               8.7         160     5300       19   \n",
       "202       3.58    2.87               8.8         134     5500       18   \n",
       "204       3.78    3.15               9.5         114     5400       19   \n",
       "\n",
       "     highwaympg    price  \n",
       "0            27  13495.0  \n",
       "1            27  16500.0  \n",
       "2            26  16500.0  \n",
       "3            30  13950.0  \n",
       "4            22  17450.0  \n",
       "..          ...      ...  \n",
       "199          22  18950.0  \n",
       "200          28  16845.0  \n",
       "201          25  19045.0  \n",
       "202          23  21485.0  \n",
       "204          25  22625.0  \n",
       "\n",
       "[139 rows x 26 columns]"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "for col in cat_col:\n",
    "    df[col] = le.fit_transform(df[col])\n",
    "    \n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "b35bdca8-47b9-42a7-9e07-a837c4d5b8a3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "147\n",
      "2\n",
      "2\n",
      "2\n",
      "5\n",
      "3\n",
      "2\n",
      "7\n",
      "7\n",
      "8\n"
     ]
    }
   ],
   "source": [
    "for cols in cat_col:\n",
    "    print(cat_col[cols].nunique())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "b532f3cd-406f-4e74-a923-5e3e012e101a",
   "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>CarName</th>\n",
       "      <th>fueltype</th>\n",
       "      <th>aspiration</th>\n",
       "      <th>doornumber</th>\n",
       "      <th>carbody</th>\n",
       "      <th>drivewheel</th>\n",
       "      <th>enginelocation</th>\n",
       "      <th>enginetype</th>\n",
       "      <th>cylindernumber</th>\n",
       "      <th>fuelsystem</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>alfa-romero giulia</td>\n",
       "      <td>gas</td>\n",
       "      <td>std</td>\n",
       "      <td>two</td>\n",
       "      <td>convertible</td>\n",
       "      <td>rwd</td>\n",
       "      <td>front</td>\n",
       "      <td>dohc</td>\n",
       "      <td>four</td>\n",
       "      <td>mpfi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>alfa-romero stelvio</td>\n",
       "      <td>gas</td>\n",
       "      <td>std</td>\n",
       "      <td>two</td>\n",
       "      <td>convertible</td>\n",
       "      <td>rwd</td>\n",
       "      <td>front</td>\n",
       "      <td>dohc</td>\n",
       "      <td>four</td>\n",
       "      <td>mpfi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>alfa-romero Quadrifoglio</td>\n",
       "      <td>gas</td>\n",
       "      <td>std</td>\n",
       "      <td>two</td>\n",
       "      <td>hatchback</td>\n",
       "      <td>rwd</td>\n",
       "      <td>front</td>\n",
       "      <td>ohcv</td>\n",
       "      <td>six</td>\n",
       "      <td>mpfi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>audi 100 ls</td>\n",
       "      <td>gas</td>\n",
       "      <td>std</td>\n",
       "      <td>four</td>\n",
       "      <td>sedan</td>\n",
       "      <td>fwd</td>\n",
       "      <td>front</td>\n",
       "      <td>ohc</td>\n",
       "      <td>four</td>\n",
       "      <td>mpfi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>audi 100ls</td>\n",
       "      <td>gas</td>\n",
       "      <td>std</td>\n",
       "      <td>four</td>\n",
       "      <td>sedan</td>\n",
       "      <td>4wd</td>\n",
       "      <td>front</td>\n",
       "      <td>ohc</td>\n",
       "      <td>five</td>\n",
       "      <td>mpfi</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>200</th>\n",
       "      <td>volvo 145e (sw)</td>\n",
       "      <td>gas</td>\n",
       "      <td>std</td>\n",
       "      <td>four</td>\n",
       "      <td>sedan</td>\n",
       "      <td>rwd</td>\n",
       "      <td>front</td>\n",
       "      <td>ohc</td>\n",
       "      <td>four</td>\n",
       "      <td>mpfi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>201</th>\n",
       "      <td>volvo 144ea</td>\n",
       "      <td>gas</td>\n",
       "      <td>turbo</td>\n",
       "      <td>four</td>\n",
       "      <td>sedan</td>\n",
       "      <td>rwd</td>\n",
       "      <td>front</td>\n",
       "      <td>ohc</td>\n",
       "      <td>four</td>\n",
       "      <td>mpfi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202</th>\n",
       "      <td>volvo 244dl</td>\n",
       "      <td>gas</td>\n",
       "      <td>std</td>\n",
       "      <td>four</td>\n",
       "      <td>sedan</td>\n",
       "      <td>rwd</td>\n",
       "      <td>front</td>\n",
       "      <td>ohcv</td>\n",
       "      <td>six</td>\n",
       "      <td>mpfi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>203</th>\n",
       "      <td>volvo 246</td>\n",
       "      <td>diesel</td>\n",
       "      <td>turbo</td>\n",
       "      <td>four</td>\n",
       "      <td>sedan</td>\n",
       "      <td>rwd</td>\n",
       "      <td>front</td>\n",
       "      <td>ohc</td>\n",
       "      <td>six</td>\n",
       "      <td>idi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>204</th>\n",
       "      <td>volvo 264gl</td>\n",
       "      <td>gas</td>\n",
       "      <td>turbo</td>\n",
       "      <td>four</td>\n",
       "      <td>sedan</td>\n",
       "      <td>rwd</td>\n",
       "      <td>front</td>\n",
       "      <td>ohc</td>\n",
       "      <td>four</td>\n",
       "      <td>mpfi</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>205 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                      CarName fueltype aspiration doornumber      carbody  \\\n",
       "0          alfa-romero giulia      gas        std        two  convertible   \n",
       "1         alfa-romero stelvio      gas        std        two  convertible   \n",
       "2    alfa-romero Quadrifoglio      gas        std        two    hatchback   \n",
       "3                 audi 100 ls      gas        std       four        sedan   \n",
       "4                  audi 100ls      gas        std       four        sedan   \n",
       "..                        ...      ...        ...        ...          ...   \n",
       "200           volvo 145e (sw)      gas        std       four        sedan   \n",
       "201               volvo 144ea      gas      turbo       four        sedan   \n",
       "202               volvo 244dl      gas        std       four        sedan   \n",
       "203                 volvo 246   diesel      turbo       four        sedan   \n",
       "204               volvo 264gl      gas      turbo       four        sedan   \n",
       "\n",
       "    drivewheel enginelocation enginetype cylindernumber fuelsystem  \n",
       "0          rwd          front       dohc           four       mpfi  \n",
       "1          rwd          front       dohc           four       mpfi  \n",
       "2          rwd          front       ohcv            six       mpfi  \n",
       "3          fwd          front        ohc           four       mpfi  \n",
       "4          4wd          front        ohc           five       mpfi  \n",
       "..         ...            ...        ...            ...        ...  \n",
       "200        rwd          front        ohc           four       mpfi  \n",
       "201        rwd          front        ohc           four       mpfi  \n",
       "202        rwd          front       ohcv            six       mpfi  \n",
       "203        rwd          front        ohc            six        idi  \n",
       "204        rwd          front        ohc           four       mpfi  \n",
       "\n",
       "[205 rows x 10 columns]"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cat_col"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "70145a40-1448-4dd2-a99a-1b60db2a4cb3",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\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>car_ID</th>\n",
       "      <th>symboling</th>\n",
       "      <th>CarName</th>\n",
       "      <th>fueltype</th>\n",
       "      <th>aspiration</th>\n",
       "      <th>doornumber</th>\n",
       "      <th>carbody</th>\n",
       "      <th>drivewheel</th>\n",
       "      <th>enginelocation</th>\n",
       "      <th>wheelbase</th>\n",
       "      <th>...</th>\n",
       "      <th>enginesize</th>\n",
       "      <th>fuelsystem</th>\n",
       "      <th>boreratio</th>\n",
       "      <th>stroke</th>\n",
       "      <th>compressionratio</th>\n",
       "      <th>horsepower</th>\n",
       "      <th>peakrpm</th>\n",
       "      <th>citympg</th>\n",
       "      <th>highwaympg</th>\n",
       "      <th>price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
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       "      <td>27</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
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       "      <td>19</td>\n",
       "      <td>26</td>\n",
       "      <td>16500.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
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       "      <td>13950.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>199</th>\n",
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       "      <td>2</td>\n",
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       "      <td>3</td>\n",
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       "      <td>22</td>\n",
       "      <td>18950.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>200</th>\n",
       "      <td>201</td>\n",
       "      <td>-1</td>\n",
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       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>109.1</td>\n",
       "      <td>...</td>\n",
       "      <td>141</td>\n",
       "      <td>3</td>\n",
       "      <td>3.78</td>\n",
       "      <td>3.15</td>\n",
       "      <td>9.5</td>\n",
       "      <td>114</td>\n",
       "      <td>5400</td>\n",
       "      <td>23</td>\n",
       "      <td>28</td>\n",
       "      <td>16845.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>201</th>\n",
       "      <td>202</td>\n",
       "      <td>-1</td>\n",
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       "      <td>2</td>\n",
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       "      <td>141</td>\n",
       "      <td>3</td>\n",
       "      <td>3.78</td>\n",
       "      <td>3.15</td>\n",
       "      <td>8.7</td>\n",
       "      <td>160</td>\n",
       "      <td>5300</td>\n",
       "      <td>19</td>\n",
       "      <td>25</td>\n",
       "      <td>19045.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202</th>\n",
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       "      <td>3</td>\n",
       "      <td>2</td>\n",
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       "      <td>109.1</td>\n",
       "      <td>...</td>\n",
       "      <td>173</td>\n",
       "      <td>3</td>\n",
       "      <td>3.58</td>\n",
       "      <td>2.87</td>\n",
       "      <td>8.8</td>\n",
       "      <td>134</td>\n",
       "      <td>5500</td>\n",
       "      <td>18</td>\n",
       "      <td>23</td>\n",
       "      <td>21485.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>204</th>\n",
       "      <td>205</td>\n",
       "      <td>-1</td>\n",
       "      <td>98</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "      <td>2</td>\n",
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       "      <td>141</td>\n",
       "      <td>3</td>\n",
       "      <td>3.78</td>\n",
       "      <td>3.15</td>\n",
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       "      <td>114</td>\n",
       "      <td>5400</td>\n",
       "      <td>19</td>\n",
       "      <td>25</td>\n",
       "      <td>22625.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>139 rows × 26 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     car_ID  symboling  CarName  fueltype  aspiration  doornumber  carbody  \\\n",
       "0         1          3        2         0           0           1        0   \n",
       "1         2          3        3         0           0           1        0   \n",
       "2         3          1        1         0           0           1        2   \n",
       "3         4          2        4         0           0           0        3   \n",
       "4         5          2        5         0           0           0        3   \n",
       "..      ...        ...      ...       ...         ...         ...      ...   \n",
       "199     200         -1       99         0           1           0        4   \n",
       "200     201         -1       95         0           0           0        3   \n",
       "201     202         -1       94         0           1           0        3   \n",
       "202     203         -1       96         0           0           0        3   \n",
       "204     205         -1       98         0           1           0        3   \n",
       "\n",
       "     drivewheel  enginelocation  wheelbase  ...  enginesize  fuelsystem  \\\n",
       "0             2               0       88.6  ...         130           3   \n",
       "1             2               0       88.6  ...         130           3   \n",
       "2             2               0       94.5  ...         152           3   \n",
       "3             1               0       99.8  ...         109           3   \n",
       "4             0               0       99.4  ...         136           3   \n",
       "..          ...             ...        ...  ...         ...         ...   \n",
       "199           2               0      104.3  ...         130           3   \n",
       "200           2               0      109.1  ...         141           3   \n",
       "201           2               0      109.1  ...         141           3   \n",
       "202           2               0      109.1  ...         173           3   \n",
       "204           2               0      109.1  ...         141           3   \n",
       "\n",
       "     boreratio  stroke  compressionratio  horsepower  peakrpm  citympg  \\\n",
       "0         3.47    2.68               9.0         111     5000       21   \n",
       "1         3.47    2.68               9.0         111     5000       21   \n",
       "2         2.68    3.47               9.0         154     5000       19   \n",
       "3         3.19    3.40              10.0         102     5500       24   \n",
       "4         3.19    3.40               8.0         115     5500       18   \n",
       "..         ...     ...               ...         ...      ...      ...   \n",
       "199       3.62    3.15               7.5         162     5100       17   \n",
       "200       3.78    3.15               9.5         114     5400       23   \n",
       "201       3.78    3.15               8.7         160     5300       19   \n",
       "202       3.58    2.87               8.8         134     5500       18   \n",
       "204       3.78    3.15               9.5         114     5400       19   \n",
       "\n",
       "     highwaympg    price  \n",
       "0            27  13495.0  \n",
       "1            27  16500.0  \n",
       "2            26  16500.0  \n",
       "3            30  13950.0  \n",
       "4            22  17450.0  \n",
       "..          ...      ...  \n",
       "199          22  18950.0  \n",
       "200          28  16845.0  \n",
       "201          25  19045.0  \n",
       "202          23  21485.0  \n",
       "204          25  22625.0  \n",
       "\n",
       "[139 rows x 26 columns]"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#df.drop(['car_ID', 'CarName'], inplace = True, axis = 1)\n",
    "#df.reset_index().drop(df.index, inplace = True, axis =1)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "7451f3dd",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.linear_model import LinearRegression\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.metrics import r2_score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "f3a6e5a2",
   "metadata": {},
   "outputs": [],
   "source": [
    "x = df.drop('price', axis =1)\n",
    "y = df.price"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "e5dce993-9060-4316-aaf7-f645afa5f028",
   "metadata": {},
   "outputs": [],
   "source": [
    "x_train,x_test, y_train,y_test = train_test_split(x,y, train_size = 0.8, random_state = 40)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "a1121a64-87b3-4dce-892d-d9f15c56a0d5",
   "metadata": {},
   "outputs": [],
   "source": [
    "linear_model = LinearRegression().fit(x_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "f15b0873-5567-4f0b-ba11-803632c85fed",
   "metadata": {},
   "outputs": [],
   "source": [
    "pred_y = linear_model.predict(x_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "de69e07d-34a8-46c3-a418-807c10efa7a0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.7993986132774007"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r2_score(y_test, pred_y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "id": "7ceaa650-6205-4355-97ce-54993eecb2b3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8406195960398886"
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "linear_model.score(x_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d70a3423-2351-4720-83e2-dbb701885476",
   "metadata": {},
   "outputs": [],
   "source": [
    " "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "979c1620-8f4d-40d0-8f86-3d58bc58a11e",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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