ReadCleanExploreDataset.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "1f942412",
   "metadata": {},
   "outputs": [],
   "source": [
    "import sklearn\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "import datetime\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "0e60622d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.23.2\n"
     ]
    }
   ],
   "source": [
    "print(sklearn.__version__)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "ab1ec7f9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1.2.4\n"
     ]
    }
   ],
   "source": [
    "print(pd.__version__)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "05dd1a49",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1.19.5\n"
     ]
    }
   ],
   "source": [
    "print(np.__version__)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "fa0f4ea5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Model</th>\n",
       "      <th>MPG</th>\n",
       "      <th>Cylinders</th>\n",
       "      <th>Displacement</th>\n",
       "      <th>Horsepower</th>\n",
       "      <th>Weight</th>\n",
       "      <th>Acceleration</th>\n",
       "      <th>Year</th>\n",
       "      <th>Origin</th>\n",
       "      <th>bore</th>\n",
       "      <th>stroke</th>\n",
       "      <th>compression-ratio</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>chevrolet chevelle malibu</td>\n",
       "      <td>18.0</td>\n",
       "      <td>8</td>\n",
       "      <td>307</td>\n",
       "      <td>130</td>\n",
       "      <td>3504</td>\n",
       "      <td>12</td>\n",
       "      <td>1970[1975]</td>\n",
       "      <td>US; Detroit, Michigan</td>\n",
       "      <td>3.47</td>\n",
       "      <td>2.68</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>buick skylark 320</td>\n",
       "      <td>15.0</td>\n",
       "      <td>8</td>\n",
       "      <td>350</td>\n",
       "      <td>165</td>\n",
       "      <td>3693</td>\n",
       "      <td>11.5</td>\n",
       "      <td>1970</td>\n",
       "      <td>US]</td>\n",
       "      <td>3.47</td>\n",
       "      <td>2.68</td>\n",
       "      <td>?</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>plymouth satellite</td>\n",
       "      <td>18.0</td>\n",
       "      <td>?</td>\n",
       "      <td>318</td>\n",
       "      <td>150</td>\n",
       "      <td>3436</td>\n",
       "      <td>11</td>\n",
       "      <td>1970, 1976</td>\n",
       "      <td>US</td>\n",
       "      <td>2.68</td>\n",
       "      <td>3.47</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>amc rebel sst</td>\n",
       "      <td>16.0</td>\n",
       "      <td>8</td>\n",
       "      <td>304</td>\n",
       "      <td>150</td>\n",
       "      <td>3433</td>\n",
       "      <td>12</td>\n",
       "      <td>1970</td>\n",
       "      <td>US</td>\n",
       "      <td>3.19</td>\n",
       "      <td>3.40</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ford torino</td>\n",
       "      <td>17.0</td>\n",
       "      <td>8</td>\n",
       "      <td>302</td>\n",
       "      <td>140</td>\n",
       "      <td>3449</td>\n",
       "      <td>10.5</td>\n",
       "      <td>1970-1972</td>\n",
       "      <td>US]</td>\n",
       "      <td>3.19</td>\n",
       "      <td>3.40</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       Model   MPG Cylinders Displacement  Horsepower Weight  \\\n",
       "0  chevrolet chevelle malibu  18.0         8          307         130   3504   \n",
       "1          buick skylark 320  15.0         8          350         165   3693   \n",
       "2         plymouth satellite  18.0         ?          318         150   3436   \n",
       "3              amc rebel sst  16.0         8          304         150   3433   \n",
       "4                ford torino  17.0         8          302         140   3449   \n",
       "\n",
       "  Acceleration        Year                 Origin  bore  stroke  \\\n",
       "0           12  1970[1975]  US; Detroit, Michigan  3.47    2.68   \n",
       "1         11.5        1970                    US]  3.47    2.68   \n",
       "2           11  1970, 1976                     US  2.68    3.47   \n",
       "3           12        1970                     US  3.19    3.40   \n",
       "4         10.5   1970-1972                    US]  3.19    3.40   \n",
       "\n",
       "  compression-ratio  \n",
       "0                 9  \n",
       "1                 ?  \n",
       "2                 9  \n",
       "3                10  \n",
       "4                 8  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "automobile_df = pd.read_csv('datasets/cars.csv')\n",
    "automobile_df.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "71ae47cf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(394, 12)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "automobile_df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "6a71a3d2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Model</th>\n",
       "      <th>MPG</th>\n",
       "      <th>Cylinders</th>\n",
       "      <th>Displacement</th>\n",
       "      <th>Horsepower</th>\n",
       "      <th>Weight</th>\n",
       "      <th>Acceleration</th>\n",
       "      <th>Year</th>\n",
       "      <th>Origin</th>\n",
       "      <th>bore</th>\n",
       "      <th>stroke</th>\n",
       "      <th>compression-ratio</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>chevrolet chevelle malibu</td>\n",
       "      <td>18.0</td>\n",
       "      <td>8</td>\n",
       "      <td>307</td>\n",
       "      <td>130</td>\n",
       "      <td>3504</td>\n",
       "      <td>12</td>\n",
       "      <td>1970[1975]</td>\n",
       "      <td>US; Detroit, Michigan</td>\n",
       "      <td>3.47</td>\n",
       "      <td>2.68</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>buick skylark 320</td>\n",
       "      <td>15.0</td>\n",
       "      <td>8</td>\n",
       "      <td>350</td>\n",
       "      <td>165</td>\n",
       "      <td>3693</td>\n",
       "      <td>11.5</td>\n",
       "      <td>1970</td>\n",
       "      <td>US]</td>\n",
       "      <td>3.47</td>\n",
       "      <td>2.68</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>plymouth satellite</td>\n",
       "      <td>18.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>318</td>\n",
       "      <td>150</td>\n",
       "      <td>3436</td>\n",
       "      <td>11</td>\n",
       "      <td>1970, 1976</td>\n",
       "      <td>US</td>\n",
       "      <td>2.68</td>\n",
       "      <td>3.47</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>amc rebel sst</td>\n",
       "      <td>16.0</td>\n",
       "      <td>8</td>\n",
       "      <td>304</td>\n",
       "      <td>150</td>\n",
       "      <td>3433</td>\n",
       "      <td>12</td>\n",
       "      <td>1970</td>\n",
       "      <td>US</td>\n",
       "      <td>3.19</td>\n",
       "      <td>3.40</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ford torino</td>\n",
       "      <td>17.0</td>\n",
       "      <td>8</td>\n",
       "      <td>302</td>\n",
       "      <td>140</td>\n",
       "      <td>3449</td>\n",
       "      <td>10.5</td>\n",
       "      <td>1970-1972</td>\n",
       "      <td>US]</td>\n",
       "      <td>3.19</td>\n",
       "      <td>3.40</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       Model   MPG Cylinders Displacement  Horsepower Weight  \\\n",
       "0  chevrolet chevelle malibu  18.0         8          307         130   3504   \n",
       "1          buick skylark 320  15.0         8          350         165   3693   \n",
       "2         plymouth satellite  18.0       NaN          318         150   3436   \n",
       "3              amc rebel sst  16.0         8          304         150   3433   \n",
       "4                ford torino  17.0         8          302         140   3449   \n",
       "\n",
       "  Acceleration        Year                 Origin  bore  stroke  \\\n",
       "0           12  1970[1975]  US; Detroit, Michigan  3.47    2.68   \n",
       "1         11.5        1970                    US]  3.47    2.68   \n",
       "2           11  1970, 1976                     US  2.68    3.47   \n",
       "3           12        1970                     US  3.19    3.40   \n",
       "4         10.5   1970-1972                    US]  3.19    3.40   \n",
       "\n",
       "  compression-ratio  \n",
       "0                 9  \n",
       "1               NaN  \n",
       "2                 9  \n",
       "3                10  \n",
       "4                 8  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "automobile_df = automobile_df.replace('?', np.nan)\n",
    "automobile_df.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "ca8f3c7e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Model                0\n",
       "MPG                  9\n",
       "Cylinders            2\n",
       "Displacement         1\n",
       "Horsepower           0\n",
       "Weight               1\n",
       "Acceleration         1\n",
       "Year                 0\n",
       "Origin               0\n",
       "bore                 0\n",
       "stroke               0\n",
       "compression-ratio    2\n",
       "dtype: int64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "automobile_df.isna().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "41c0fdc6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Model                0\n",
       "MPG                  0\n",
       "Cylinders            2\n",
       "Displacement         1\n",
       "Horsepower           0\n",
       "Weight               1\n",
       "Acceleration         1\n",
       "Year                 0\n",
       "Origin               0\n",
       "bore                 0\n",
       "stroke               0\n",
       "compression-ratio    2\n",
       "dtype: int64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "automobile_df['MPG'] = automobile_df['MPG'].fillna(automobile_df['MPG'].mean())\n",
    "automobile_df.isna().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8306798f",
   "metadata": {},
   "source": [
    "We can drop Not a number (NaN) records if we think that there are only few records having missing data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "d70aea5e",
   "metadata": {},
   "outputs": [],
   "source": [
    "automobile_df = automobile_df.dropna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "004af604",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(387, 12)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "automobile_df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "6e97bf63",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Model                0\n",
       "MPG                  0\n",
       "Cylinders            0\n",
       "Displacement         0\n",
       "Horsepower           0\n",
       "Weight               0\n",
       "Acceleration         0\n",
       "Year                 0\n",
       "Origin               0\n",
       "bore                 0\n",
       "stroke               0\n",
       "compression-ratio    0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "automobile_df.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "143046ee",
   "metadata": {},
   "source": [
    "Dataset has no missing values now"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "cabde09e",
   "metadata": {},
   "outputs": [],
   "source": [
    "automobile_df.drop(['Model'],axis=1,inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "a312cbfd",
   "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>MPG</th>\n",
       "      <th>Cylinders</th>\n",
       "      <th>Displacement</th>\n",
       "      <th>Horsepower</th>\n",
       "      <th>Weight</th>\n",
       "      <th>Acceleration</th>\n",
       "      <th>Year</th>\n",
       "      <th>Origin</th>\n",
       "      <th>bore</th>\n",
       "      <th>stroke</th>\n",
       "      <th>compression-ratio</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>157</th>\n",
       "      <td>14.0</td>\n",
       "      <td>8</td>\n",
       "      <td>351</td>\n",
       "      <td>148</td>\n",
       "      <td>4657</td>\n",
       "      <td>13.5</td>\n",
       "      <td>1975</td>\n",
       "      <td>US</td>\n",
       "      <td>3.19</td>\n",
       "      <td>3.03</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>230</th>\n",
       "      <td>16.0</td>\n",
       "      <td>8</td>\n",
       "      <td>351</td>\n",
       "      <td>149</td>\n",
       "      <td>4335</td>\n",
       "      <td>14.5</td>\n",
       "      <td>1977</td>\n",
       "      <td>US</td>\n",
       "      <td>3.58</td>\n",
       "      <td>2.87</td>\n",
       "      <td>8.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>373</th>\n",
       "      <td>31.0</td>\n",
       "      <td>4</td>\n",
       "      <td>91</td>\n",
       "      <td>68</td>\n",
       "      <td>1970</td>\n",
       "      <td>17.6</td>\n",
       "      <td>1982</td>\n",
       "      <td>Japan</td>\n",
       "      <td>2.97</td>\n",
       "      <td>3.23</td>\n",
       "      <td>9.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>346</th>\n",
       "      <td>34.7</td>\n",
       "      <td>4</td>\n",
       "      <td>105</td>\n",
       "      <td>63</td>\n",
       "      <td>2215</td>\n",
       "      <td>14.9</td>\n",
       "      <td>1981</td>\n",
       "      <td>US</td>\n",
       "      <td>3.03</td>\n",
       "      <td>3.15</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>223</th>\n",
       "      <td>17.5</td>\n",
       "      <td>6</td>\n",
       "      <td>250</td>\n",
       "      <td>110</td>\n",
       "      <td>3520</td>\n",
       "      <td>16.4</td>\n",
       "      <td>1977</td>\n",
       "      <td>US</td>\n",
       "      <td>3.78</td>\n",
       "      <td>3.15</td>\n",
       "      <td>9.5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      MPG Cylinders Displacement  Horsepower Weight Acceleration  Year Origin  \\\n",
       "157  14.0         8          351         148   4657         13.5  1975     US   \n",
       "230  16.0         8          351         149   4335         14.5  1977     US   \n",
       "373  31.0         4           91          68   1970         17.6  1982  Japan   \n",
       "346  34.7         4          105          63   2215         14.9  1981     US   \n",
       "223  17.5         6          250         110   3520         16.4  1977     US   \n",
       "\n",
       "     bore  stroke compression-ratio  \n",
       "157  3.19    3.03                 9  \n",
       "230  3.58    2.87               8.8  \n",
       "373  2.97    3.23               9.4  \n",
       "346  3.03    3.15                 9  \n",
       "223  3.78    3.15               9.5  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "automobile_df.sample(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "b16f8c25",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>MPG</th>\n",
       "      <th>Cylinders</th>\n",
       "      <th>Displacement</th>\n",
       "      <th>Horsepower</th>\n",
       "      <th>Weight</th>\n",
       "      <th>Acceleration</th>\n",
       "      <th>Year</th>\n",
       "      <th>Origin</th>\n",
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       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>18.000000</td>\n",
       "      <td>8</td>\n",
       "      <td>307</td>\n",
       "      <td>130</td>\n",
       "      <td>3504</td>\n",
       "      <td>12</td>\n",
       "      <td>1970[1975]</td>\n",
       "      <td>US; Detroit, Michigan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>16.000000</td>\n",
       "      <td>8</td>\n",
       "      <td>304</td>\n",
       "      <td>150</td>\n",
       "      <td>3433</td>\n",
       "      <td>12</td>\n",
       "      <td>1970</td>\n",
       "      <td>US</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>17.000000</td>\n",
       "      <td>8</td>\n",
       "      <td>302</td>\n",
       "      <td>140</td>\n",
       "      <td>3449</td>\n",
       "      <td>10.5</td>\n",
       "      <td>1970-1972</td>\n",
       "      <td>US]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>14.000000</td>\n",
       "      <td>8</td>\n",
       "      <td>454</td>\n",
       "      <td>220</td>\n",
       "      <td>4354</td>\n",
       "      <td>9</td>\n",
       "      <td>1970[1975]</td>\n",
       "      <td>US; Detroit, Michigan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>23.551429</td>\n",
       "      <td>8</td>\n",
       "      <td>440</td>\n",
       "      <td>215</td>\n",
       "      <td>4312</td>\n",
       "      <td>8.5</td>\n",
       "      <td>1970</td>\n",
       "      <td>US</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         MPG Cylinders Displacement  Horsepower Weight Acceleration  \\\n",
       "0  18.000000         8          307         130   3504           12   \n",
       "3  16.000000         8          304         150   3433           12   \n",
       "4  17.000000         8          302         140   3449         10.5   \n",
       "6  14.000000         8          454         220   4354            9   \n",
       "7  23.551429         8          440         215   4312          8.5   \n",
       "\n",
       "         Year                 Origin  \n",
       "0  1970[1975]  US; Detroit, Michigan  \n",
       "3        1970                     US  \n",
       "4   1970-1972                    US]  \n",
       "6  1970[1975]  US; Detroit, Michigan  \n",
       "7        1970                     US  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "automobile_df.drop(['bore','stroke','compression-ratio'],inplace=True,axis=1)\n",
    "automobile_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fb06107e",
   "metadata": {},
   "source": [
    "Removed not important columns in the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "b6e0a575",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True     351\n",
       "False     36\n",
       "Name: Year, dtype: int64"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "automobile_df['Year'].str.isnumeric().value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "0bade677",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0          1970[1975]\n",
       "4           1970-1972\n",
       "6          1970[1975]\n",
       "30      1971[1973]971\n",
       "35         1971[1973]\n",
       "40         1971[1973]\n",
       "44         1971[1973]\n",
       "49         1971[1973]\n",
       "56         1972[1973]\n",
       "61         1972[1973]\n",
       "65         1972[1973]\n",
       "68         1972[1973]\n",
       "73         1972[1973]\n",
       "75            1972-73\n",
       "79            1972-73\n",
       "82            1972-73\n",
       "96          1973-1974\n",
       "97         1973, 1974\n",
       "102    1973, 19741973\n",
       "105        1973, 1974\n",
       "108        1973, 1974\n",
       "112        1973, 1974\n",
       "115        1973, 1974\n",
       "126        1974, 1975\n",
       "131        1974, 1975\n",
       "134        1974, 1975\n",
       "137        1974, 1975\n",
       "139    1974, 19751974\n",
       "142        1974, 1975\n",
       "365         1982-1985\n",
       "374         1982-1985\n",
       "380         1982-1985\n",
       "383         1982-1985\n",
       "387         1982-1985\n",
       "389         1982-1985\n",
       "391         1982-1985\n",
       "Name: Year, dtype: object"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "automobile_df['Year'].loc[automobile_df['Year'].str.isnumeric() == False ]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "81f665a3",
   "metadata": {},
   "source": [
    "As the year is type of object type we can extract the year with regular expression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "e3357ab0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    1970\n",
       "3    1970\n",
       "4    1970\n",
       "6    1970\n",
       "7    1970\n",
       "Name: Year, dtype: object"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "extract = automobile_df['Year'].str.extract(r'(\\d{4})', expand=False)\n",
    "extract.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "a9c08dd6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      1970\n",
       "3      1970\n",
       "4      1970\n",
       "6      1970\n",
       "7      1970\n",
       "       ... \n",
       "389    1982\n",
       "390    1982\n",
       "391    1982\n",
       "392    1982\n",
       "393    1982\n",
       "Name: Year, Length: 387, dtype: object"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "extract"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "276e70cf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dtype('int64')"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "automobile_df['Year'] = pd.to_numeric(extract)\n",
    "automobile_df['Year'].dtype"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "f4a54fa4",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>Cylinders</th>\n",
       "      <th>Displacement</th>\n",
       "      <th>Horsepower</th>\n",
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       "      <th>3</th>\n",
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       "      <td>140</td>\n",
       "      <td>3449</td>\n",
       "      <td>10.5</td>\n",
       "      <td>1970</td>\n",
       "      <td>US]</td>\n",
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       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>14.000000</td>\n",
       "      <td>8</td>\n",
       "      <td>454</td>\n",
       "      <td>220</td>\n",
       "      <td>4354</td>\n",
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       "      <td>1970</td>\n",
       "      <td>US; Detroit, Michigan</td>\n",
       "    </tr>\n",
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       "      <td>23.551429</td>\n",
       "      <td>8</td>\n",
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       "      <td>215</td>\n",
       "      <td>4312</td>\n",
       "      <td>8.5</td>\n",
       "      <td>1970</td>\n",
       "      <td>US</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         MPG Cylinders Displacement  Horsepower Weight Acceleration  Year  \\\n",
       "0  18.000000         8          307         130   3504           12  1970   \n",
       "3  16.000000         8          304         150   3433           12  1970   \n",
       "4  17.000000         8          302         140   3449         10.5  1970   \n",
       "6  14.000000         8          454         220   4354            9  1970   \n",
       "7  23.551429         8          440         215   4312          8.5  1970   \n",
       "\n",
       "                  Origin  \n",
       "0  US; Detroit, Michigan  \n",
       "3                     US  \n",
       "4                    US]  \n",
       "6  US; Detroit, Michigan  \n",
       "7                     US  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "automobile_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "fb18f53b",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>4</td>\n",
       "      <td>91</td>\n",
       "      <td>67</td>\n",
       "      <td>1965</td>\n",
       "      <td>15</td>\n",
       "      <td>Japan</td>\n",
       "      <td>39</td>\n",
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       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>25.0</td>\n",
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       "      <td>95</td>\n",
       "      <td>2228</td>\n",
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       "    <tr>\n",
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       "      <td>14.0</td>\n",
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       "      <td>US</td>\n",
       "      <td>47</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "      MPG Cylinders Displacement  Horsepower Weight Acceleration  \\\n",
       "178  25.0         4          121         115   2671         13.5   \n",
       "106  18.0         6          232         100   2789           15   \n",
       "379  38.0         4           91          67   1965           15   \n",
       "31   25.0         4          113          95   2228           14   \n",
       "136  14.0         8          318         150   4457         13.5   \n",
       "\n",
       "            Origin  Age  \n",
       "178         Europe   46  \n",
       "106             US   48  \n",
       "379          Japan   39  \n",
       "31   Japan; Aichi]   50  \n",
       "136             US   47  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "automobile_df['Age'] = datetime.datetime.now().year - automobile_df['Year']\n",
    "automobile_df.drop(['Year'],axis=1, inplace=True)\n",
    "automobile_df.sample(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "8375aa07",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "MPG             float64\n",
       "Cylinders        object\n",
       "Displacement     object\n",
       "Horsepower        int64\n",
       "Weight           object\n",
       "Acceleration     object\n",
       "Origin           object\n",
       "Age               int64\n",
       "dtype: object"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "automobile_df.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "06437b85",
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'f' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-24-a9fcd54b25e7>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mf\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m: name 'f' is not defined"
     ]
    }
   ],
   "source": [
    "f"
   ]
  }
 ],
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