lecture6.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "id": "HQS2UZY1bFnh"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "Bad key savefig.frameon in file /home/bang/anaconda3/lib/python3.8/site-packages/matplotlib/mpl-data/stylelib/_classic_test.mplstyle, line 421 ('savefig.frameon : True')\n",
      "You probably need to get an updated matplotlibrc file from\n",
      "https://github.com/matplotlib/matplotlib/blob/v3.4.2/matplotlibrc.template\n",
      "or from the matplotlib source distribution\n",
      "\n",
      "Bad key verbose.level in file /home/bang/anaconda3/lib/python3.8/site-packages/matplotlib/mpl-data/stylelib/_classic_test.mplstyle, line 472 ('verbose.level  : silent      # one of silent, helpful, debug, debug-annoying')\n",
      "You probably need to get an updated matplotlibrc file from\n",
      "https://github.com/matplotlib/matplotlib/blob/v3.4.2/matplotlibrc.template\n",
      "or from the matplotlib source distribution\n",
      "\n",
      "Bad key verbose.fileo in file /home/bang/anaconda3/lib/python3.8/site-packages/matplotlib/mpl-data/stylelib/_classic_test.mplstyle, line 473 ('verbose.fileo  : sys.stdout  # a log filename, sys.stdout or sys.stderr')\n",
      "You probably need to get an updated matplotlibrc file from\n",
      "https://github.com/matplotlib/matplotlib/blob/v3.4.2/matplotlibrc.template\n",
      "or from the matplotlib source distribution\n",
      "In /home/bang/anaconda3/lib/python3.8/site-packages/matplotlib/mpl-data/stylelib/_classic_test.mplstyle: \n",
      "The text.latex.preview rcparam was deprecated in Matplotlib 3.3 and will be removed two minor releases later.\n",
      "In /home/bang/anaconda3/lib/python3.8/site-packages/matplotlib/mpl-data/stylelib/_classic_test.mplstyle: \n",
      "The mathtext.fallback_to_cm rcparam was deprecated in Matplotlib 3.3 and will be removed two minor releases later.\n",
      "In /home/bang/anaconda3/lib/python3.8/site-packages/matplotlib/mpl-data/stylelib/_classic_test.mplstyle: Support for setting the 'mathtext.fallback_to_cm' rcParam is deprecated since 3.3 and will be removed two minor releases later; use 'mathtext.fallback : 'cm' instead.\n",
      "In /home/bang/anaconda3/lib/python3.8/site-packages/matplotlib/mpl-data/stylelib/_classic_test.mplstyle: \n",
      "The validate_bool_maybe_none function was deprecated in Matplotlib 3.3 and will be removed two minor releases later.\n",
      "In /home/bang/anaconda3/lib/python3.8/site-packages/matplotlib/mpl-data/stylelib/_classic_test.mplstyle: \n",
      "The savefig.jpeg_quality rcparam was deprecated in Matplotlib 3.3 and will be removed two minor releases later.\n",
      "In /home/bang/anaconda3/lib/python3.8/site-packages/matplotlib/mpl-data/stylelib/_classic_test.mplstyle: \n",
      "The keymap.all_axes rcparam was deprecated in Matplotlib 3.3 and will be removed two minor releases later.\n",
      "In /home/bang/anaconda3/lib/python3.8/site-packages/matplotlib/mpl-data/stylelib/_classic_test.mplstyle: \n",
      "The animation.avconv_path rcparam was deprecated in Matplotlib 3.3 and will be removed two minor releases later.\n",
      "In /home/bang/anaconda3/lib/python3.8/site-packages/matplotlib/mpl-data/stylelib/_classic_test.mplstyle: \n",
      "The animation.avconv_args rcparam was deprecated in Matplotlib 3.3 and will be removed two minor releases later.\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "CRu9j1LVbm67"
   },
   "source": [
    "# Cars93 data\n",
    "In this lab, we would like to explore data about 93 number of vehicles."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 312
    },
    "id": "XURptut9Y0Au",
    "outputId": "dbdf0687-9045-489d-fecf-a86cbfc89feb"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Manufacturer</th>\n",
       "      <th>Model</th>\n",
       "      <th>Type</th>\n",
       "      <th>Min.Price</th>\n",
       "      <th>Price</th>\n",
       "      <th>Max.Price</th>\n",
       "      <th>MPG.city</th>\n",
       "      <th>MPG.highway</th>\n",
       "      <th>AirBags</th>\n",
       "      <th>DriveTrain</th>\n",
       "      <th>...</th>\n",
       "      <th>Passengers</th>\n",
       "      <th>Length</th>\n",
       "      <th>Wheelbase</th>\n",
       "      <th>Width</th>\n",
       "      <th>Turn.circle</th>\n",
       "      <th>Rear.seat.room</th>\n",
       "      <th>Luggage.room</th>\n",
       "      <th>Weight</th>\n",
       "      <th>Origin</th>\n",
       "      <th>Make</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Acura</td>\n",
       "      <td>Integra</td>\n",
       "      <td>Small</td>\n",
       "      <td>12.9</td>\n",
       "      <td>15.9</td>\n",
       "      <td>18.8</td>\n",
       "      <td>25.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>None</td>\n",
       "      <td>Front</td>\n",
       "      <td>...</td>\n",
       "      <td>5.0</td>\n",
       "      <td>177.0</td>\n",
       "      <td>102.0</td>\n",
       "      <td>68.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>26.5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2705.0</td>\n",
       "      <td>non-USA</td>\n",
       "      <td>Acura Integra</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Legend</td>\n",
       "      <td>Midsize</td>\n",
       "      <td>29.2</td>\n",
       "      <td>33.9</td>\n",
       "      <td>38.7</td>\n",
       "      <td>18.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>Driver &amp; Passenger</td>\n",
       "      <td>Front</td>\n",
       "      <td>...</td>\n",
       "      <td>5.0</td>\n",
       "      <td>195.0</td>\n",
       "      <td>115.0</td>\n",
       "      <td>71.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>3560.0</td>\n",
       "      <td>non-USA</td>\n",
       "      <td>Acura Legend</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Audi</td>\n",
       "      <td>90</td>\n",
       "      <td>Compact</td>\n",
       "      <td>25.9</td>\n",
       "      <td>29.1</td>\n",
       "      <td>32.3</td>\n",
       "      <td>20.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>Driver only</td>\n",
       "      <td>Front</td>\n",
       "      <td>...</td>\n",
       "      <td>5.0</td>\n",
       "      <td>180.0</td>\n",
       "      <td>102.0</td>\n",
       "      <td>67.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>3375.0</td>\n",
       "      <td>non-USA</td>\n",
       "      <td>Audi 90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Audi</td>\n",
       "      <td>100</td>\n",
       "      <td>Midsize</td>\n",
       "      <td>NaN</td>\n",
       "      <td>37.7</td>\n",
       "      <td>44.6</td>\n",
       "      <td>19.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>Driver &amp; Passenger</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>6.0</td>\n",
       "      <td>193.0</td>\n",
       "      <td>106.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>37.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>3405.0</td>\n",
       "      <td>non-USA</td>\n",
       "      <td>Audi 100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>BMW</td>\n",
       "      <td>535i</td>\n",
       "      <td>Midsize</td>\n",
       "      <td>NaN</td>\n",
       "      <td>30.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>22.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Rear</td>\n",
       "      <td>...</td>\n",
       "      <td>4.0</td>\n",
       "      <td>186.0</td>\n",
       "      <td>109.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>39.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>3640.0</td>\n",
       "      <td>non-USA</td>\n",
       "      <td>BMW 535i</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 27 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "  Manufacturer    Model     Type  Min.Price  Price  Max.Price  MPG.city  \\\n",
       "0        Acura  Integra    Small       12.9   15.9       18.8      25.0   \n",
       "1          NaN   Legend  Midsize       29.2   33.9       38.7      18.0   \n",
       "2         Audi       90  Compact       25.9   29.1       32.3      20.0   \n",
       "3         Audi      100  Midsize        NaN   37.7       44.6      19.0   \n",
       "4          BMW     535i  Midsize        NaN   30.0        NaN      22.0   \n",
       "\n",
       "   MPG.highway             AirBags DriveTrain  ... Passengers  Length  \\\n",
       "0         31.0                None      Front  ...        5.0   177.0   \n",
       "1         25.0  Driver & Passenger      Front  ...        5.0   195.0   \n",
       "2         26.0         Driver only      Front  ...        5.0   180.0   \n",
       "3         26.0  Driver & Passenger        NaN  ...        6.0   193.0   \n",
       "4         30.0                 NaN       Rear  ...        4.0   186.0   \n",
       "\n",
       "   Wheelbase  Width  Turn.circle Rear.seat.room  Luggage.room  Weight  \\\n",
       "0      102.0   68.0         37.0           26.5           NaN  2705.0   \n",
       "1      115.0   71.0         38.0           30.0          15.0  3560.0   \n",
       "2      102.0   67.0         37.0           28.0          14.0  3375.0   \n",
       "3      106.0    NaN         37.0           31.0          17.0  3405.0   \n",
       "4      109.0   69.0         39.0           27.0          13.0  3640.0   \n",
       "\n",
       "    Origin           Make  \n",
       "0  non-USA  Acura Integra  \n",
       "1  non-USA   Acura Legend  \n",
       "2  non-USA        Audi 90  \n",
       "3  non-USA       Audi 100  \n",
       "4  non-USA       BMW 535i  \n",
       "\n",
       "[5 rows x 27 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv('https://raw.githubusercontent.com/selva86/datasets/master/Cars93_miss.csv')\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "cuLySvTcL4AB"
   },
   "source": [
    "# Drop Missing Value"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "XjFrpry9MAgM",
    "outputId": "36c885d3-1a55-42c8-abd9-97bc63502361"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 20 entries, 2 to 90\n",
      "Data columns (total 27 columns):\n",
      " #   Column              Non-Null Count  Dtype  \n",
      "---  ------              --------------  -----  \n",
      " 0   Manufacturer        20 non-null     object \n",
      " 1   Model               20 non-null     object \n",
      " 2   Type                20 non-null     object \n",
      " 3   Min.Price           20 non-null     float64\n",
      " 4   Price               20 non-null     float64\n",
      " 5   Max.Price           20 non-null     float64\n",
      " 6   MPG.city            20 non-null     float64\n",
      " 7   MPG.highway         20 non-null     float64\n",
      " 8   AirBags             20 non-null     object \n",
      " 9   DriveTrain          20 non-null     object \n",
      " 10  Cylinders           20 non-null     object \n",
      " 11  EngineSize          20 non-null     float64\n",
      " 12  Horsepower          20 non-null     float64\n",
      " 13  RPM                 20 non-null     float64\n",
      " 14  Rev.per.mile        20 non-null     float64\n",
      " 15  Man.trans.avail     20 non-null     object \n",
      " 16  Fuel.tank.capacity  20 non-null     float64\n",
      " 17  Passengers          20 non-null     float64\n",
      " 18  Length              20 non-null     float64\n",
      " 19  Wheelbase           20 non-null     float64\n",
      " 20  Width               20 non-null     float64\n",
      " 21  Turn.circle         20 non-null     float64\n",
      " 22  Rear.seat.room      20 non-null     float64\n",
      " 23  Luggage.room        20 non-null     float64\n",
      " 24  Weight              20 non-null     float64\n",
      " 25  Origin              20 non-null     object \n",
      " 26  Make                20 non-null     object \n",
      "dtypes: float64(18), object(9)\n",
      "memory usage: 4.4+ KB\n"
     ]
    }
   ],
   "source": [
    "dfNoMissing = df.dropna()\n",
    "dfNoMissing.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "4_l3u1ncbd8K"
   },
   "source": [
    "# Scaling\n",
    "**[TODO]** Rescale the numeric attribute using z-score. You can use Scikit-learn or Pandas."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>Min.Price</th>\n",
       "      <th>Price</th>\n",
       "      <th>Max.Price</th>\n",
       "      <th>MPG.city</th>\n",
       "      <th>MPG.highway</th>\n",
       "      <th>EngineSize</th>\n",
       "      <th>Horsepower</th>\n",
       "      <th>RPM</th>\n",
       "      <th>Rev.per.mile</th>\n",
       "      <th>Fuel.tank.capacity</th>\n",
       "      <th>Passengers</th>\n",
       "      <th>Length</th>\n",
       "      <th>Wheelbase</th>\n",
       "      <th>Width</th>\n",
       "      <th>Turn.circle</th>\n",
       "      <th>Rear.seat.room</th>\n",
       "      <th>Luggage.room</th>\n",
       "      <th>Weight</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.714462</td>\n",
       "      <td>1.909199</td>\n",
       "      <td>2.006788</td>\n",
       "      <td>-0.689169</td>\n",
       "      <td>-1.030448</td>\n",
       "      <td>0.085718</td>\n",
       "      <td>0.936406</td>\n",
       "      <td>0.468046</td>\n",
       "      <td>0.088902</td>\n",
       "      <td>0.255073</td>\n",
       "      <td>-0.074744</td>\n",
       "      <td>-0.060346</td>\n",
       "      <td>-0.108605</td>\n",
       "      <td>-0.256332</td>\n",
       "      <td>-0.318616</td>\n",
       "      <td>-0.154074</td>\n",
       "      <td>-0.209020</td>\n",
       "      <td>0.684456</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1.194212</td>\n",
       "      <td>1.083765</td>\n",
       "      <td>0.954326</td>\n",
       "      <td>-1.550630</td>\n",
       "      <td>-1.284879</td>\n",
       "      <td>2.571534</td>\n",
       "      <td>1.139696</td>\n",
       "      <td>-1.952883</td>\n",
       "      <td>-1.807669</td>\n",
       "      <td>2.118481</td>\n",
       "      <td>1.420127</td>\n",
       "      <td>2.008662</td>\n",
       "      <td>1.791984</td>\n",
       "      <td>2.195540</td>\n",
       "      <td>1.897842</td>\n",
       "      <td>0.808890</td>\n",
       "      <td>2.229546</td>\n",
       "      <td>1.934368</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.469014</td>\n",
       "      <td>0.334759</td>\n",
       "      <td>0.200537</td>\n",
       "      <td>-1.335265</td>\n",
       "      <td>-1.030448</td>\n",
       "      <td>1.971509</td>\n",
       "      <td>0.885583</td>\n",
       "      <td>-1.630093</td>\n",
       "      <td>-1.748401</td>\n",
       "      <td>2.118481</td>\n",
       "      <td>1.420127</td>\n",
       "      <td>1.893717</td>\n",
       "      <td>1.791984</td>\n",
       "      <td>1.972642</td>\n",
       "      <td>1.066670</td>\n",
       "      <td>0.423704</td>\n",
       "      <td>1.881179</td>\n",
       "      <td>1.600487</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-0.082767</td>\n",
       "      <td>-0.123815</td>\n",
       "      <td>-0.155025</td>\n",
       "      <td>-0.043073</td>\n",
       "      <td>-0.521585</td>\n",
       "      <td>0.257153</td>\n",
       "      <td>0.148656</td>\n",
       "      <td>-0.338930</td>\n",
       "      <td>-0.286461</td>\n",
       "      <td>-0.019856</td>\n",
       "      <td>1.420127</td>\n",
       "      <td>0.112071</td>\n",
       "      <td>0.162908</td>\n",
       "      <td>-0.033435</td>\n",
       "      <td>0.789613</td>\n",
       "      <td>0.808890</td>\n",
       "      <td>-0.209020</td>\n",
       "      <td>0.187915</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2.282008</td>\n",
       "      <td>1.970342</td>\n",
       "      <td>1.608559</td>\n",
       "      <td>-0.689169</td>\n",
       "      <td>-1.030448</td>\n",
       "      <td>0.514307</td>\n",
       "      <td>0.301124</td>\n",
       "      <td>-0.661721</td>\n",
       "      <td>-0.889017</td>\n",
       "      <td>-0.019856</td>\n",
       "      <td>1.420127</td>\n",
       "      <td>1.261520</td>\n",
       "      <td>0.977446</td>\n",
       "      <td>0.189463</td>\n",
       "      <td>1.620785</td>\n",
       "      <td>2.927411</td>\n",
       "      <td>0.836080</td>\n",
       "      <td>1.018336</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Min.Price     Price  Max.Price  MPG.city  MPG.highway  EngineSize  \\\n",
       "0   1.714462  1.909199   2.006788 -0.689169    -1.030448    0.085718   \n",
       "1   1.194212  1.083765   0.954326 -1.550630    -1.284879    2.571534   \n",
       "2   0.469014  0.334759   0.200537 -1.335265    -1.030448    1.971509   \n",
       "3  -0.082767 -0.123815  -0.155025 -0.043073    -0.521585    0.257153   \n",
       "4   2.282008  1.970342   1.608559 -0.689169    -1.030448    0.514307   \n",
       "\n",
       "   Horsepower       RPM  Rev.per.mile  Fuel.tank.capacity  Passengers  \\\n",
       "0    0.936406  0.468046      0.088902            0.255073   -0.074744   \n",
       "1    1.139696 -1.952883     -1.807669            2.118481    1.420127   \n",
       "2    0.885583 -1.630093     -1.748401            2.118481    1.420127   \n",
       "3    0.148656 -0.338930     -0.286461           -0.019856    1.420127   \n",
       "4    0.301124 -0.661721     -0.889017           -0.019856    1.420127   \n",
       "\n",
       "     Length  Wheelbase     Width  Turn.circle  Rear.seat.room  Luggage.room  \\\n",
       "0 -0.060346  -0.108605 -0.256332    -0.318616       -0.154074     -0.209020   \n",
       "1  2.008662   1.791984  2.195540     1.897842        0.808890      2.229546   \n",
       "2  1.893717   1.791984  1.972642     1.066670        0.423704      1.881179   \n",
       "3  0.112071   0.162908 -0.033435     0.789613        0.808890     -0.209020   \n",
       "4  1.261520   0.977446  0.189463     1.620785        2.927411      0.836080   \n",
       "\n",
       "     Weight  \n",
       "0  0.684456  \n",
       "1  1.934368  \n",
       "2  1.600487  \n",
       "3  0.187915  \n",
       "4  1.018336  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.preprocessing import StandardScaler\n",
    "# filter data with numeric attirbute\n",
    "dfNumeric = dfNoMissing.select_dtypes(include='number')\n",
    "\n",
    "# create a scaler object\n",
    "stdScaler = StandardScaler()\n",
    "\n",
    "# fit and transform the data\n",
    "dfStd = pd.DataFrame(stdScaler.fit_transform(dfNumeric), columns = dfNumeric.columns)\n",
    "\n",
    "dfStd.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "rqFHrx48PIb7"
   },
   "source": [
    "# Encoding\n",
    "Filter categorical attribute and remove unnessary attribute using `.drop()` \n",
    "* unnessary attribute: `Manufacturer`,\t`Model`, `Make`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 205
    },
    "id": "AfXu-r0WQFb9",
    "outputId": "5e842ee7-295e-47ad-a5ab-174d92880bdf"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
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       "    }\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>Type</th>\n",
       "      <th>AirBags</th>\n",
       "      <th>DriveTrain</th>\n",
       "      <th>Cylinders</th>\n",
       "      <th>Man.trans.avail</th>\n",
       "      <th>Origin</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Compact</td>\n",
       "      <td>Driver only</td>\n",
       "      <td>Front</td>\n",
       "      <td>6</td>\n",
       "      <td>Yes</td>\n",
       "      <td>non-USA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Large</td>\n",
       "      <td>Driver only</td>\n",
       "      <td>Rear</td>\n",
       "      <td>6</td>\n",
       "      <td>No</td>\n",
       "      <td>USA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Large</td>\n",
       "      <td>Driver only</td>\n",
       "      <td>Rear</td>\n",
       "      <td>8</td>\n",
       "      <td>No</td>\n",
       "      <td>USA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Compact</td>\n",
       "      <td>Driver &amp; Passenger</td>\n",
       "      <td>Front</td>\n",
       "      <td>4</td>\n",
       "      <td>No</td>\n",
       "      <td>USA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Large</td>\n",
       "      <td>Driver only</td>\n",
       "      <td>Front</td>\n",
       "      <td>6</td>\n",
       "      <td>No</td>\n",
       "      <td>USA</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Type             AirBags DriveTrain Cylinders Man.trans.avail   Origin\n",
       "2   Compact         Driver only      Front         6             Yes  non-USA\n",
       "7     Large         Driver only       Rear         6              No      USA\n",
       "17    Large         Driver only       Rear         8              No      USA\n",
       "20  Compact  Driver & Passenger      Front         4              No      USA\n",
       "21    Large         Driver only      Front         6              No      USA"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfFilter = dfNoMissing.select_dtypes(exclude='number').drop(\n",
    "    columns=['Manufacturer', 'Model', 'Make'])\n",
    "dfFilter.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "jzdYHOQJUbWz"
   },
   "source": [
    "**[TODO]** Encode remaining categorical attiribute into numeric attribute using label encoding."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
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       "    }\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>Type</th>\n",
       "      <th>AirBags</th>\n",
       "      <th>DriveTrain</th>\n",
       "      <th>Cylinders</th>\n",
       "      <th>Man.trans.avail</th>\n",
       "      <th>Origin</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Type  AirBags  DriveTrain  Cylinders  Man.trans.avail  Origin\n",
       "0     0        1           1          2                1       1\n",
       "1     1        1           2          2                0       0\n",
       "2     1        1           2          3                0       0\n",
       "3     0        0           1          1                0       0\n",
       "4     1        1           1          2                0       0"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.preprocessing import LabelEncoder\n",
    "\n",
    "# create a encoder object\n",
    "enc = LabelEncoder()\n",
    "\n",
    "# create empthy dataframe \n",
    "dfEnc = pd.DataFrame()\n",
    "\n",
    "# fill up data frame with encoded attribute using iteration\n",
    "for col in dfFilter.columns:\n",
    "    dfEnc[col] = enc.fit_transform(dfNoMissing[col])\n",
    "\n",
    "dfEnc.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Ub3POiYeaHWL"
   },
   "source": [
    "Merge `df_enc` and `df_std`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 695
    },
    "id": "78ABYZ_6ZUJc",
    "outputId": "cd715824-f84b-4d5e-b974-a173f0749c55"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\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>Type</th>\n",
       "      <th>AirBags</th>\n",
       "      <th>DriveTrain</th>\n",
       "      <th>Cylinders</th>\n",
       "      <th>Man.trans.avail</th>\n",
       "      <th>Origin</th>\n",
       "      <th>Min.Price</th>\n",
       "      <th>Price</th>\n",
       "      <th>Max.Price</th>\n",
       "      <th>MPG.city</th>\n",
       "      <th>...</th>\n",
       "      <th>Rev.per.mile</th>\n",
       "      <th>Fuel.tank.capacity</th>\n",
       "      <th>Passengers</th>\n",
       "      <th>Length</th>\n",
       "      <th>Wheelbase</th>\n",
       "      <th>Width</th>\n",
       "      <th>Turn.circle</th>\n",
       "      <th>Rear.seat.room</th>\n",
       "      <th>Luggage.room</th>\n",
       "      <th>Weight</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1.714462</td>\n",
       "      <td>1.909199</td>\n",
       "      <td>2.006788</td>\n",
       "      <td>-0.689169</td>\n",
       "      <td>...</td>\n",
       "      <td>0.088902</td>\n",
       "      <td>0.255073</td>\n",
       "      <td>-0.074744</td>\n",
       "      <td>-0.060346</td>\n",
       "      <td>-0.108605</td>\n",
       "      <td>-0.256332</td>\n",
       "      <td>-0.318616</td>\n",
       "      <td>-0.154074</td>\n",
       "      <td>-0.209020</td>\n",
       "      <td>0.684456</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.194212</td>\n",
       "      <td>1.083765</td>\n",
       "      <td>0.954326</td>\n",
       "      <td>-1.550630</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.807669</td>\n",
       "      <td>2.118481</td>\n",
       "      <td>1.420127</td>\n",
       "      <td>2.008662</td>\n",
       "      <td>1.791984</td>\n",
       "      <td>2.195540</td>\n",
       "      <td>1.897842</td>\n",
       "      <td>0.808890</td>\n",
       "      <td>2.229546</td>\n",
       "      <td>1.934368</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.469014</td>\n",
       "      <td>0.334759</td>\n",
       "      <td>0.200537</td>\n",
       "      <td>-1.335265</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.748401</td>\n",
       "      <td>2.118481</td>\n",
       "      <td>1.420127</td>\n",
       "      <td>1.893717</td>\n",
       "      <td>1.791984</td>\n",
       "      <td>1.972642</td>\n",
       "      <td>1.066670</td>\n",
       "      <td>0.423704</td>\n",
       "      <td>1.881179</td>\n",
       "      <td>1.600487</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.082767</td>\n",
       "      <td>-0.123815</td>\n",
       "      <td>-0.155025</td>\n",
       "      <td>-0.043073</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.286461</td>\n",
       "      <td>-0.019856</td>\n",
       "      <td>1.420127</td>\n",
       "      <td>0.112071</td>\n",
       "      <td>0.162908</td>\n",
       "      <td>-0.033435</td>\n",
       "      <td>0.789613</td>\n",
       "      <td>0.808890</td>\n",
       "      <td>-0.209020</td>\n",
       "      <td>0.187915</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2.282008</td>\n",
       "      <td>1.970342</td>\n",
       "      <td>1.608559</td>\n",
       "      <td>-0.689169</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.889017</td>\n",
       "      <td>-0.019856</td>\n",
       "      <td>1.420127</td>\n",
       "      <td>1.261520</td>\n",
       "      <td>0.977446</td>\n",
       "      <td>0.189463</td>\n",
       "      <td>1.620785</td>\n",
       "      <td>2.927411</td>\n",
       "      <td>0.836080</td>\n",
       "      <td>1.018336</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>-1.123268</td>\n",
       "      <td>-0.674105</td>\n",
       "      <td>-0.240359</td>\n",
       "      <td>1.249118</td>\n",
       "      <td>...</td>\n",
       "      <td>0.533410</td>\n",
       "      <td>-0.875191</td>\n",
       "      <td>-0.074744</td>\n",
       "      <td>-0.405181</td>\n",
       "      <td>-0.651630</td>\n",
       "      <td>-0.479229</td>\n",
       "      <td>-0.595673</td>\n",
       "      <td>-0.731853</td>\n",
       "      <td>-1.254119</td>\n",
       "      <td>-1.164730</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>-1.296685</td>\n",
       "      <td>-1.316109</td>\n",
       "      <td>-1.278598</td>\n",
       "      <td>1.249118</td>\n",
       "      <td>...</td>\n",
       "      <td>0.938407</td>\n",
       "      <td>-1.272310</td>\n",
       "      <td>-0.074744</td>\n",
       "      <td>-0.750015</td>\n",
       "      <td>-1.194656</td>\n",
       "      <td>-1.147922</td>\n",
       "      <td>-0.872730</td>\n",
       "      <td>-0.924445</td>\n",
       "      <td>-1.254119</td>\n",
       "      <td>-1.079120</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>-1.202094</td>\n",
       "      <td>-1.270252</td>\n",
       "      <td>-1.292821</td>\n",
       "      <td>1.249118</td>\n",
       "      <td>...</td>\n",
       "      <td>0.266705</td>\n",
       "      <td>-0.875191</td>\n",
       "      <td>-1.569614</td>\n",
       "      <td>-0.979905</td>\n",
       "      <td>-0.787387</td>\n",
       "      <td>-0.479229</td>\n",
       "      <td>-1.149787</td>\n",
       "      <td>-0.539260</td>\n",
       "      <td>0.487713</td>\n",
       "      <td>-1.113364</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>-0.650313</td>\n",
       "      <td>-0.765820</td>\n",
       "      <td>-0.837702</td>\n",
       "      <td>1.033753</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.029634</td>\n",
       "      <td>-0.478071</td>\n",
       "      <td>-0.074744</td>\n",
       "      <td>-0.520126</td>\n",
       "      <td>-0.651630</td>\n",
       "      <td>-0.479229</td>\n",
       "      <td>-0.595673</td>\n",
       "      <td>-0.731853</td>\n",
       "      <td>-0.557386</td>\n",
       "      <td>-0.916460</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>-0.114297</td>\n",
       "      <td>-0.016814</td>\n",
       "      <td>0.072534</td>\n",
       "      <td>0.603023</td>\n",
       "      <td>...</td>\n",
       "      <td>0.533410</td>\n",
       "      <td>-0.172594</td>\n",
       "      <td>-0.074744</td>\n",
       "      <td>0.169544</td>\n",
       "      <td>0.027151</td>\n",
       "      <td>0.189463</td>\n",
       "      <td>0.512556</td>\n",
       "      <td>0.423704</td>\n",
       "      <td>-0.209020</td>\n",
       "      <td>-0.008989</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.019706</td>\n",
       "      <td>-0.261388</td>\n",
       "      <td>-0.467919</td>\n",
       "      <td>-0.904534</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.997675</td>\n",
       "      <td>0.591097</td>\n",
       "      <td>-0.074744</td>\n",
       "      <td>1.031630</td>\n",
       "      <td>1.384715</td>\n",
       "      <td>1.081053</td>\n",
       "      <td>-0.041559</td>\n",
       "      <td>-0.154074</td>\n",
       "      <td>0.139347</td>\n",
       "      <td>1.086825</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>-0.319245</td>\n",
       "      <td>-0.139101</td>\n",
       "      <td>0.015645</td>\n",
       "      <td>0.172292</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.207437</td>\n",
       "      <td>-0.050404</td>\n",
       "      <td>-0.074744</td>\n",
       "      <td>-0.002874</td>\n",
       "      <td>0.027151</td>\n",
       "      <td>-0.256332</td>\n",
       "      <td>0.512556</td>\n",
       "      <td>0.038519</td>\n",
       "      <td>-0.209020</td>\n",
       "      <td>0.127988</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.319245</td>\n",
       "      <td>-0.475389</td>\n",
       "      <td>-0.595921</td>\n",
       "      <td>0.172292</td>\n",
       "      <td>...</td>\n",
       "      <td>0.286461</td>\n",
       "      <td>-0.264237</td>\n",
       "      <td>-0.074744</td>\n",
       "      <td>0.399434</td>\n",
       "      <td>0.027151</td>\n",
       "      <td>-0.256332</td>\n",
       "      <td>0.235499</td>\n",
       "      <td>-0.154074</td>\n",
       "      <td>-0.209020</td>\n",
       "      <td>-0.111722</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.059119</td>\n",
       "      <td>0.288902</td>\n",
       "      <td>0.484986</td>\n",
       "      <td>-0.904534</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.681580</td>\n",
       "      <td>0.132882</td>\n",
       "      <td>-0.074744</td>\n",
       "      <td>0.801741</td>\n",
       "      <td>0.705933</td>\n",
       "      <td>0.858155</td>\n",
       "      <td>0.789613</td>\n",
       "      <td>0.038519</td>\n",
       "      <td>0.487713</td>\n",
       "      <td>0.812871</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.689726</td>\n",
       "      <td>1.190765</td>\n",
       "      <td>1.594337</td>\n",
       "      <td>-0.904534</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.323648</td>\n",
       "      <td>0.591097</td>\n",
       "      <td>1.420127</td>\n",
       "      <td>-0.232763</td>\n",
       "      <td>1.113202</td>\n",
       "      <td>1.303950</td>\n",
       "      <td>1.343727</td>\n",
       "      <td>0.808890</td>\n",
       "      <td>1.184446</td>\n",
       "      <td>0.889921</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>-1.217859</td>\n",
       "      <td>-1.254966</td>\n",
       "      <td>-1.235931</td>\n",
       "      <td>2.110579</td>\n",
       "      <td>...</td>\n",
       "      <td>1.264380</td>\n",
       "      <td>-2.097097</td>\n",
       "      <td>-1.569614</td>\n",
       "      <td>-2.014409</td>\n",
       "      <td>-1.737681</td>\n",
       "      <td>-1.816614</td>\n",
       "      <td>-1.703902</td>\n",
       "      <td>-1.887409</td>\n",
       "      <td>-1.602486</td>\n",
       "      <td>-1.592782</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>-0.713374</td>\n",
       "      <td>-0.872820</td>\n",
       "      <td>-0.979927</td>\n",
       "      <td>0.387657</td>\n",
       "      <td>...</td>\n",
       "      <td>2.252177</td>\n",
       "      <td>-0.050404</td>\n",
       "      <td>-0.074744</td>\n",
       "      <td>-0.347708</td>\n",
       "      <td>-0.787387</td>\n",
       "      <td>-0.702127</td>\n",
       "      <td>-0.872730</td>\n",
       "      <td>-0.346667</td>\n",
       "      <td>0.139347</td>\n",
       "      <td>-0.830849</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>-0.997147</td>\n",
       "      <td>-1.147965</td>\n",
       "      <td>-1.235931</td>\n",
       "      <td>0.387657</td>\n",
       "      <td>...</td>\n",
       "      <td>0.622312</td>\n",
       "      <td>-1.119572</td>\n",
       "      <td>-1.569614</td>\n",
       "      <td>-1.037378</td>\n",
       "      <td>-1.330412</td>\n",
       "      <td>-1.147922</td>\n",
       "      <td>-1.149787</td>\n",
       "      <td>-0.924445</td>\n",
       "      <td>-1.602486</td>\n",
       "      <td>-1.258902</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.405953</td>\n",
       "      <td>0.518189</td>\n",
       "      <td>0.598765</td>\n",
       "      <td>-0.473804</td>\n",
       "      <td>...</td>\n",
       "      <td>0.889017</td>\n",
       "      <td>0.743836</td>\n",
       "      <td>-0.074744</td>\n",
       "      <td>-0.060346</td>\n",
       "      <td>0.027151</td>\n",
       "      <td>-0.256332</td>\n",
       "      <td>-0.872730</td>\n",
       "      <td>1.194075</td>\n",
       "      <td>-0.209020</td>\n",
       "      <td>0.016694</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1.241507</td>\n",
       "      <td>1.022621</td>\n",
       "      <td>0.783657</td>\n",
       "      <td>-1.119899</td>\n",
       "      <td>...</td>\n",
       "      <td>0.296339</td>\n",
       "      <td>0.743836</td>\n",
       "      <td>-1.569614</td>\n",
       "      <td>-1.267268</td>\n",
       "      <td>-0.787387</td>\n",
       "      <td>-0.479229</td>\n",
       "      <td>-0.595673</td>\n",
       "      <td>-0.924445</td>\n",
       "      <td>0.139347</td>\n",
       "      <td>-0.282943</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>20 rows × 24 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    Type  AirBags  DriveTrain  Cylinders  Man.trans.avail  Origin  Min.Price  \\\n",
       "0      0        1           1          2                1       1   1.714462   \n",
       "1      1        1           2          2                0       0   1.194212   \n",
       "2      1        1           2          3                0       0   0.469014   \n",
       "3      0        0           1          1                0       0  -0.082767   \n",
       "4      1        1           1          2                0       0   2.282008   \n",
       "5      3        2           1          1                1       0  -1.123268   \n",
       "6      3        2           1          1                1       1  -1.296685   \n",
       "7      3        2           1          1                1       1  -1.202094   \n",
       "8      3        2           1          1                1       1  -0.650313   \n",
       "9      0        1           1          1                1       1  -0.114297   \n",
       "10     2        2           2          2                0       0  -0.019706   \n",
       "11     0        1           1          1                1       1  -0.319245   \n",
       "12     0        2           1          1                0       0  -0.319245   \n",
       "13     2        2           1          2                1       0   0.059119   \n",
       "14     1        0           1          2                0       0   0.689726   \n",
       "15     3        2           0          0                1       1  -1.217859   \n",
       "16     3        2           0          1                1       1  -0.713374   \n",
       "17     3        2           1          1                1       1  -0.997147   \n",
       "18     0        2           1          1                1       1   0.405953   \n",
       "19     4        2           1          2                1       1   1.241507   \n",
       "\n",
       "       Price  Max.Price  MPG.city  ...  Rev.per.mile  Fuel.tank.capacity  \\\n",
       "0   1.909199   2.006788 -0.689169  ...      0.088902            0.255073   \n",
       "1   1.083765   0.954326 -1.550630  ...     -1.807669            2.118481   \n",
       "2   0.334759   0.200537 -1.335265  ...     -1.748401            2.118481   \n",
       "3  -0.123815  -0.155025 -0.043073  ...     -0.286461           -0.019856   \n",
       "4   1.970342   1.608559 -0.689169  ...     -0.889017           -0.019856   \n",
       "5  -0.674105  -0.240359  1.249118  ...      0.533410           -0.875191   \n",
       "6  -1.316109  -1.278598  1.249118  ...      0.938407           -1.272310   \n",
       "7  -1.270252  -1.292821  1.249118  ...      0.266705           -0.875191   \n",
       "8  -0.765820  -0.837702  1.033753  ...     -0.029634           -0.478071   \n",
       "9  -0.016814   0.072534  0.603023  ...      0.533410           -0.172594   \n",
       "10 -0.261388  -0.467919 -0.904534  ...     -0.997675            0.591097   \n",
       "11 -0.139101   0.015645  0.172292  ...     -0.207437           -0.050404   \n",
       "12 -0.475389  -0.595921  0.172292  ...      0.286461           -0.264237   \n",
       "13  0.288902   0.484986 -0.904534  ...     -0.681580            0.132882   \n",
       "14  1.190765   1.594337 -0.904534  ...     -1.323648            0.591097   \n",
       "15 -1.254966  -1.235931  2.110579  ...      1.264380           -2.097097   \n",
       "16 -0.872820  -0.979927  0.387657  ...      2.252177           -0.050404   \n",
       "17 -1.147965  -1.235931  0.387657  ...      0.622312           -1.119572   \n",
       "18  0.518189   0.598765 -0.473804  ...      0.889017            0.743836   \n",
       "19  1.022621   0.783657 -1.119899  ...      0.296339            0.743836   \n",
       "\n",
       "    Passengers    Length  Wheelbase     Width  Turn.circle  Rear.seat.room  \\\n",
       "0    -0.074744 -0.060346  -0.108605 -0.256332    -0.318616       -0.154074   \n",
       "1     1.420127  2.008662   1.791984  2.195540     1.897842        0.808890   \n",
       "2     1.420127  1.893717   1.791984  1.972642     1.066670        0.423704   \n",
       "3     1.420127  0.112071   0.162908 -0.033435     0.789613        0.808890   \n",
       "4     1.420127  1.261520   0.977446  0.189463     1.620785        2.927411   \n",
       "5    -0.074744 -0.405181  -0.651630 -0.479229    -0.595673       -0.731853   \n",
       "6    -0.074744 -0.750015  -1.194656 -1.147922    -0.872730       -0.924445   \n",
       "7    -1.569614 -0.979905  -0.787387 -0.479229    -1.149787       -0.539260   \n",
       "8    -0.074744 -0.520126  -0.651630 -0.479229    -0.595673       -0.731853   \n",
       "9    -0.074744  0.169544   0.027151  0.189463     0.512556        0.423704   \n",
       "10   -0.074744  1.031630   1.384715  1.081053    -0.041559       -0.154074   \n",
       "11   -0.074744 -0.002874   0.027151 -0.256332     0.512556        0.038519   \n",
       "12   -0.074744  0.399434   0.027151 -0.256332     0.235499       -0.154074   \n",
       "13   -0.074744  0.801741   0.705933  0.858155     0.789613        0.038519   \n",
       "14    1.420127 -0.232763   1.113202  1.303950     1.343727        0.808890   \n",
       "15   -1.569614 -2.014409  -1.737681 -1.816614    -1.703902       -1.887409   \n",
       "16   -0.074744 -0.347708  -0.787387 -0.702127    -0.872730       -0.346667   \n",
       "17   -1.569614 -1.037378  -1.330412 -1.147922    -1.149787       -0.924445   \n",
       "18   -0.074744 -0.060346   0.027151 -0.256332    -0.872730        1.194075   \n",
       "19   -1.569614 -1.267268  -0.787387 -0.479229    -0.595673       -0.924445   \n",
       "\n",
       "    Luggage.room    Weight  \n",
       "0      -0.209020  0.684456  \n",
       "1       2.229546  1.934368  \n",
       "2       1.881179  1.600487  \n",
       "3      -0.209020  0.187915  \n",
       "4       0.836080  1.018336  \n",
       "5      -1.254119 -1.164730  \n",
       "6      -1.254119 -1.079120  \n",
       "7       0.487713 -1.113364  \n",
       "8      -0.557386 -0.916460  \n",
       "9      -0.209020 -0.008989  \n",
       "10      0.139347  1.086825  \n",
       "11     -0.209020  0.127988  \n",
       "12     -0.209020 -0.111722  \n",
       "13      0.487713  0.812871  \n",
       "14      1.184446  0.889921  \n",
       "15     -1.602486 -1.592782  \n",
       "16      0.139347 -0.830849  \n",
       "17     -1.602486 -1.258902  \n",
       "18     -0.209020  0.016694  \n",
       "19      0.139347 -0.282943  \n",
       "\n",
       "[20 rows x 24 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfProcessed = pd.concat((dfEnc, dfStd), axis=1)\n",
    "dfProcessed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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   "name": "lecture6.ipynb",
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  "kernelspec": {
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   "language": "python",
   "name": "python3"
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   "name": "python",
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