dmhw_1.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "source": [
    "# Datamining hw #1"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%% md\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "outputs": [
    {
     "data": {
      "text/plain": "                                           model  price  age_08_04  mfg_month  \\\n0  TOYOTA Corolla 2.0 D4D HATCHB TERRA 2/3-Doors  13500         23         10   \n1  TOYOTA Corolla 2.0 D4D HATCHB TERRA 2/3-Doors  13750         23         10   \n2  TOYOTA Corolla 2.0 D4D HATCHB TERRA 2/3-Doors  13950         24          9   \n3  TOYOTA Corolla 2.0 D4D HATCHB TERRA 2/3-Doors  14950         26          7   \n4    TOYOTA Corolla 2.0 D4D HATCHB SOL 2/3-Doors  13750         30          3   \n\n   mfg_year     km fuel_type  hp  met_color   color  ...  powered_windows  \\\n0      2002  46986    Diesel  90          1    Blue  ...                1   \n1      2002  72937    Diesel  90          1  Silver  ...                0   \n2      2002  41711    Diesel  90          1    Blue  ...                0   \n3      2002  48000    Diesel  90          0   Black  ...                0   \n4      2002  38500    Diesel  90          0   Black  ...                1   \n\n   power_steering  radio  mistlamps  sport_model  backseat_divider  \\\n0               1      0          0            0                 1   \n1               1      0          0            0                 1   \n2               1      0          0            0                 1   \n3               1      0          0            0                 1   \n4               1      0          1            0                 1   \n\n   metallic_rim  radio_cassette  parking_assistant  tow_bar  \n0             0               0                  0        0  \n1             0               0                  0        0  \n2             0               0                  0        0  \n3             0               0                  0        0  \n4             0               0                  0        0  \n\n[5 rows x 38 columns]",
      "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>model</th>\n      <th>price</th>\n      <th>age_08_04</th>\n      <th>mfg_month</th>\n      <th>mfg_year</th>\n      <th>km</th>\n      <th>fuel_type</th>\n      <th>hp</th>\n      <th>met_color</th>\n      <th>color</th>\n      <th>...</th>\n      <th>powered_windows</th>\n      <th>power_steering</th>\n      <th>radio</th>\n      <th>mistlamps</th>\n      <th>sport_model</th>\n      <th>backseat_divider</th>\n      <th>metallic_rim</th>\n      <th>radio_cassette</th>\n      <th>parking_assistant</th>\n      <th>tow_bar</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>TOYOTA Corolla 2.0 D4D HATCHB TERRA 2/3-Doors</td>\n      <td>13500</td>\n      <td>23</td>\n      <td>10</td>\n      <td>2002</td>\n      <td>46986</td>\n      <td>Diesel</td>\n      <td>90</td>\n      <td>1</td>\n      <td>Blue</td>\n      <td>...</td>\n      <td>1</td>\n      <td>1</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>1</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>TOYOTA Corolla 2.0 D4D HATCHB TERRA 2/3-Doors</td>\n      <td>13750</td>\n      <td>23</td>\n      <td>10</td>\n      <td>2002</td>\n      <td>72937</td>\n      <td>Diesel</td>\n      <td>90</td>\n      <td>1</td>\n      <td>Silver</td>\n      <td>...</td>\n      <td>0</td>\n      <td>1</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>1</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>TOYOTA Corolla 2.0 D4D HATCHB TERRA 2/3-Doors</td>\n      <td>13950</td>\n      <td>24</td>\n      <td>9</td>\n      <td>2002</td>\n      <td>41711</td>\n      <td>Diesel</td>\n      <td>90</td>\n      <td>1</td>\n      <td>Blue</td>\n      <td>...</td>\n      <td>0</td>\n      <td>1</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>1</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>TOYOTA Corolla 2.0 D4D HATCHB TERRA 2/3-Doors</td>\n      <td>14950</td>\n      <td>26</td>\n      <td>7</td>\n      <td>2002</td>\n      <td>48000</td>\n      <td>Diesel</td>\n      <td>90</td>\n      <td>0</td>\n      <td>Black</td>\n      <td>...</td>\n      <td>0</td>\n      <td>1</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>1</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>TOYOTA Corolla 2.0 D4D HATCHB SOL 2/3-Doors</td>\n      <td>13750</td>\n      <td>30</td>\n      <td>3</td>\n      <td>2002</td>\n      <td>38500</td>\n      <td>Diesel</td>\n      <td>90</td>\n      <td>0</td>\n      <td>Black</td>\n      <td>...</td>\n      <td>1</td>\n      <td>1</td>\n      <td>0</td>\n      <td>1</td>\n      <td>0</td>\n      <td>1</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n  </tbody>\n</table>\n<p>5 rows × 38 columns</p>\n</div>"
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# fuel type 변수와 Color 변수를 가변수로 변환\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "toyota_df = pd.read_csv('C:/Users/User/Desktop/대학/23-1/ToyotaCorolla.csv')\n",
    "toyota_df.head()"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 1436 entries, 0 to 1435\n",
      "Data columns (total 38 columns):\n",
      " #   Column             Non-Null Count  Dtype \n",
      "---  ------             --------------  ----- \n",
      " 0   model              1436 non-null   object\n",
      " 1   price              1436 non-null   int64 \n",
      " 2   age_08_04          1436 non-null   int64 \n",
      " 3   mfg_month          1436 non-null   int64 \n",
      " 4   mfg_year           1436 non-null   int64 \n",
      " 5   km                 1436 non-null   int64 \n",
      " 6   fuel_type          1436 non-null   object\n",
      " 7   hp                 1436 non-null   int64 \n",
      " 8   met_color          1436 non-null   int64 \n",
      " 9   color              1436 non-null   object\n",
      " 10  automatic          1436 non-null   int64 \n",
      " 11  cc                 1436 non-null   int64 \n",
      " 12  doors              1436 non-null   int64 \n",
      " 13  cylinders          1436 non-null   int64 \n",
      " 14  gears              1436 non-null   int64 \n",
      " 15  quarterly_tax      1436 non-null   int64 \n",
      " 16  weight             1436 non-null   int64 \n",
      " 17  mfr_guarantee      1436 non-null   int64 \n",
      " 18  bovag_guarantee    1436 non-null   int64 \n",
      " 19  guarantee_period   1436 non-null   int64 \n",
      " 20  abs                1436 non-null   int64 \n",
      " 21  airbag_1           1436 non-null   int64 \n",
      " 22  airbag_2           1436 non-null   int64 \n",
      " 23  airco              1436 non-null   int64 \n",
      " 24  automatic_airco    1436 non-null   int64 \n",
      " 25  boardcomputer      1436 non-null   int64 \n",
      " 26  cd_player          1436 non-null   int64 \n",
      " 27  central_lock       1436 non-null   int64 \n",
      " 28  powered_windows    1436 non-null   int64 \n",
      " 29  power_steering     1436 non-null   int64 \n",
      " 30  radio              1436 non-null   int64 \n",
      " 31  mistlamps          1436 non-null   int64 \n",
      " 32  sport_model        1436 non-null   int64 \n",
      " 33  backseat_divider   1436 non-null   int64 \n",
      " 34  metallic_rim       1436 non-null   int64 \n",
      " 35  radio_cassette     1436 non-null   int64 \n",
      " 36  parking_assistant  1436 non-null   int64 \n",
      " 37  tow_bar            1436 non-null   int64 \n",
      "dtypes: int64(35), object(3)\n",
      "memory usage: 426.4+ KB\n"
     ]
    }
   ],
   "source": [
    "toyota_df.info()"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "outputs": [
    {
     "data": {
      "text/plain": "Index(['model', 'price', 'age_08_04', 'mfg_month', 'mfg_year', 'km',\n       'fuel_type', 'hp', 'met_color', 'color', 'automatic', 'cc', 'doors',\n       'cylinders', 'gears', 'quarterly_tax', 'weight', 'mfr_guarantee',\n       'bovag_guarantee', 'guarantee_period', 'abs', 'airbag_1', 'airbag_2',\n       'airco', 'automatic_airco', 'boardcomputer', 'cd_player',\n       'central_lock', 'powered_windows', 'power_steering', 'radio',\n       'mistlamps', 'sport_model', 'backseat_divider', 'metallic_rim',\n       'radio_cassette', 'parking_assistant', 'tow_bar'],\n      dtype='object')"
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "toyota_df.columns"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "outputs": [
    {
     "data": {
      "text/plain": "array(['Diesel', 'Petrol', 'CNG'], dtype=object)"
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "toyota_df['fuel_type'].unique()"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "object\n",
      "Index(['CNG', 'Diesel', 'Petrol'], dtype='object')\n",
      "category\n"
     ]
    }
   ],
   "source": [
    "# fuel_type 열은 factor 이기 때문에 data type 변경\n",
    "print(toyota_df.fuel_type.dtype)\n",
    "toyota_df.fuel_type = toyota_df.fuel_type.astype('category')\n",
    "print(toyota_df.fuel_type.cat.categories)\n",
    "print(toyota_df.fuel_type.dtype)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "outputs": [
    {
     "data": {
      "text/plain": "array(['Blue', 'Silver', 'Black', 'White', 'Grey', 'Red', 'Green',\n       'Yellow', 'Violet', 'Beige'], dtype=object)"
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "toyota_df['color'].unique()"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "object\n",
      "Index(['Beige', 'Black', 'Blue', 'Green', 'Grey', 'Red', 'Silver', 'Violet',\n",
      "       'White', 'Yellow'],\n",
      "      dtype='object')\n",
      "category\n"
     ]
    }
   ],
   "source": [
    "print(toyota_df.color.dtype)\n",
    "toyota_df.color = toyota_df.color.astype('category')\n",
    "print(toyota_df.color.cat.categories)\n",
    "print(toyota_df.color.dtype)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "outputs": [
    {
     "data": {
      "text/plain": "                                           model  price  age_08_04  mfg_month  \\\n0  TOYOTA Corolla 2.0 D4D HATCHB TERRA 2/3-Doors  13500         23         10   \n1  TOYOTA Corolla 2.0 D4D HATCHB TERRA 2/3-Doors  13750         23         10   \n2  TOYOTA Corolla 2.0 D4D HATCHB TERRA 2/3-Doors  13950         24          9   \n3  TOYOTA Corolla 2.0 D4D HATCHB TERRA 2/3-Doors  14950         26          7   \n4    TOYOTA Corolla 2.0 D4D HATCHB SOL 2/3-Doors  13750         30          3   \n\n   mfg_year     km  hp  met_color  automatic    cc  ...  color_Beige  \\\n0      2002  46986  90          1          0  2000  ...            0   \n1      2002  72937  90          1          0  2000  ...            0   \n2      2002  41711  90          1          0  2000  ...            0   \n3      2002  48000  90          0          0  2000  ...            0   \n4      2002  38500  90          0          0  2000  ...            0   \n\n   color_Black  color_Blue  color_Green  color_Grey  color_Red  color_Silver  \\\n0            0           1            0           0          0             0   \n1            0           0            0           0          0             1   \n2            0           1            0           0          0             0   \n3            1           0            0           0          0             0   \n4            1           0            0           0          0             0   \n\n   color_Violet  color_White  color_Yellow  \n0             0            0             0  \n1             0            0             0  \n2             0            0             0  \n3             0            0             0  \n4             0            0             0  \n\n[5 rows x 49 columns]",
      "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>model</th>\n      <th>price</th>\n      <th>age_08_04</th>\n      <th>mfg_month</th>\n      <th>mfg_year</th>\n      <th>km</th>\n      <th>hp</th>\n      <th>met_color</th>\n      <th>automatic</th>\n      <th>cc</th>\n      <th>...</th>\n      <th>color_Beige</th>\n      <th>color_Black</th>\n      <th>color_Blue</th>\n      <th>color_Green</th>\n      <th>color_Grey</th>\n      <th>color_Red</th>\n      <th>color_Silver</th>\n      <th>color_Violet</th>\n      <th>color_White</th>\n      <th>color_Yellow</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>TOYOTA Corolla 2.0 D4D HATCHB TERRA 2/3-Doors</td>\n      <td>13500</td>\n      <td>23</td>\n      <td>10</td>\n      <td>2002</td>\n      <td>46986</td>\n      <td>90</td>\n      <td>1</td>\n      <td>0</td>\n      <td>2000</td>\n      <td>...</td>\n      <td>0</td>\n      <td>0</td>\n      <td>1</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>TOYOTA Corolla 2.0 D4D HATCHB TERRA 2/3-Doors</td>\n      <td>13750</td>\n      <td>23</td>\n      <td>10</td>\n      <td>2002</td>\n      <td>72937</td>\n      <td>90</td>\n      <td>1</td>\n      <td>0</td>\n      <td>2000</td>\n      <td>...</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>1</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>TOYOTA Corolla 2.0 D4D HATCHB TERRA 2/3-Doors</td>\n      <td>13950</td>\n      <td>24</td>\n      <td>9</td>\n      <td>2002</td>\n      <td>41711</td>\n      <td>90</td>\n      <td>1</td>\n      <td>0</td>\n      <td>2000</td>\n      <td>...</td>\n      <td>0</td>\n      <td>0</td>\n      <td>1</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>TOYOTA Corolla 2.0 D4D HATCHB TERRA 2/3-Doors</td>\n      <td>14950</td>\n      <td>26</td>\n      <td>7</td>\n      <td>2002</td>\n      <td>48000</td>\n      <td>90</td>\n      <td>0</td>\n      <td>0</td>\n      <td>2000</td>\n      <td>...</td>\n      <td>0</td>\n      <td>1</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>TOYOTA Corolla 2.0 D4D HATCHB SOL 2/3-Doors</td>\n      <td>13750</td>\n      <td>30</td>\n      <td>3</td>\n      <td>2002</td>\n      <td>38500</td>\n      <td>90</td>\n      <td>0</td>\n      <td>0</td>\n      <td>2000</td>\n      <td>...</td>\n      <td>0</td>\n      <td>1</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n  </tbody>\n</table>\n<p>5 rows × 49 columns</p>\n</div>"
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 더미 변수 만들기\n",
    "toyota_df = pd.get_dummies(toyota_df, columns = ['fuel_type', 'color'])\n",
    "toyota_df.head()"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "trainData :  (718, 49)\n",
      "validData :  (431, 49)\n",
      "testData :  (287, 49)\n"
     ]
    }
   ],
   "source": [
    "# 학습/검증/시험 데이터 분할 5:3:2\n",
    "from sklearn.model_selection import train_test_split\n",
    "trainData, temp = train_test_split(toyota_df, test_size = 0.5, random_state = 25)\n",
    "validData = toyota_df.drop(trainData.index).sample(frac = 0.6, random_state = 25)\n",
    "testData = toyota_df.drop(trainData.index).drop(validData.index)\n",
    "\n",
    "print('trainData : ', trainData.shape)\n",
    "print('validData : ', validData.shape)\n",
    "print('testData : ', testData.shape)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "* 학습 데이터 : 모델 구축 시 사용하는 데이터\n",
    "* 검증 데이터 : 모델 구축 후 검증을 위해 사용하는 데이터\n",
    "* 평가 데이터 : 모델 구축 후 새로운 데이터에 대한 성능을 평가하는 데이터"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%% md\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "outputs": [],
   "source": [
    "# 학습 데이터 준비\n",
    "X_train = trainData.drop(['model', 'price'], axis=1)\n",
    "y_train = trainData['price']"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "outputs": [
    {
     "data": {
      "text/plain": "LinearRegression()",
      "text/html": "<style>#sk-container-id-7 {color: black;background-color: white;}#sk-container-id-7 pre{padding: 0;}#sk-container-id-7 div.sk-toggleable {background-color: white;}#sk-container-id-7 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-7 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-7 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-7 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-7 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-7 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-7 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-7 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-7 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-7 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-7 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-7 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-7 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-7 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-7 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-7 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-7 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-7 div.sk-item {position: relative;z-index: 1;}#sk-container-id-7 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-7 div.sk-item::before, #sk-container-id-7 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-7 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-7 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-7 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-7 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-7 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-7 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-7 div.sk-label-container {text-align: center;}#sk-container-id-7 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-7 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-7\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>LinearRegression()</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-7\" type=\"checkbox\" checked><label for=\"sk-estimator-id-7\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">LinearRegression</label><div class=\"sk-toggleable__content\"><pre>LinearRegression()</pre></div></div></div></div></div>"
     },
     "execution_count": 125,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 모델 학습\n",
    "from sklearn.linear_model import LinearRegression\n",
    "model = LinearRegression()\n",
    "model.fit(X_train, y_train)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Validation Score: 0.6432923135007729\n"
     ]
    }
   ],
   "source": [
    "# 검증 데이터 준비\n",
    "X_val = validData.drop(['model', 'price'], axis=1)\n",
    "y_val = validData['price']\n",
    "\n",
    "# 검증 데이터로 성능 평가\n",
    "score = model.score(X_val, y_val)\n",
    "print('Validation Score:', score)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Test Score: 0.9370602399008361\n"
     ]
    }
   ],
   "source": [
    "# 테스트 데이터 준비\n",
    "X_test = testData.drop(['model', 'price'], axis=1)\n",
    "y_test =testData['price']\n",
    "\n",
    "# 테스트 데이터로 성능 평가\n",
    "score = model.score(X_test, y_test)\n",
    "print('Test Score:', score)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 128,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy: 0.9370602399008361\n"
     ]
    }
   ],
   "source": [
    "# 예측\n",
    "y_pred = model.predict(X_test)\n",
    "\n",
    "# 결과 출력\n",
    "print('Accuracy:', model.score(X_test, y_test))"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "### 검증 데이터와 테스트 데이터에서 모델의 성능이 어느 정도인지를 알 수 있음\n",
    "### 선형 회귀 모델의 score 함수는 결정 계수(R squared) 값을 반환하며, 1에 가까울수록 모델의 예측 성능이 좋다는 것을 의미"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%% md\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "outputs": [],
   "source": [
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 1000x800 with 2 Axes>",
      "image/png": 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\n"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# heatmap으로 상관관계 시각화\n",
    "plt.figure(figsize = (10,8))\n",
    "sns.heatmap(toyota_df.drop(['cylinders','color_Beige','color_Black','color_Blue','color_Grey','color_White','color_Silver','color_Violet','color_Yellow','color_Red','color_Green'],axis = 1).corr(), cmap = 'coolwarm')\n",
    "plt.title('Correlation Matrix Heatmap')\n",
    "plt.show()"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 1000x800 with 1 Axes>",
      "image/png": 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\n"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 가변수로 변환된 데이터에서 color 간 Price 분포 시각화\n",
    "plt.figure(figsize=(10, 8))\n",
    "sns.boxplot(data=toyota_df, y='price', x='color_Blue')\n",
    "plt.title('Price Distribution by Color')\n",
    "plt.xticks([0, 1], ['Not Blue', 'Blue'])\n",
    "plt.show()"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 1000x800 with 1 Axes>",
      "image/png": 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\n"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 가변수로 변환된 데이터에서 fuel_type 간 Price 분포 시각화\n",
    "plt.figure(figsize=(10, 8))\n",
    "sns.boxplot(data=toyota_df, y='price', x='fuel_type_Diesel')\n",
    "plt.title('Price Distribution by Fuel Type')\n",
    "plt.xticks([0, 1], ['Petrol', 'Diesel'])\n",
    "plt.show()"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "* Diesel 차량이 Petrol 차량보다 가격이 높은 것으로 나타났으며, Blue 차량이 Not Blue 차량보다 가격이 높은 것으로 나타남"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%% md\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 1000x800 with 1 Axes>",
      "image/png": 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\n"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 가변수로 변환된 데이터에서 fuel_type 간 Age_08_04 분포 시각화\n",
    "plt.figure(figsize=(10, 8))\n",
    "sns.boxplot(data=toyota_df, y='age_08_04', x='fuel_type_Diesel')\n",
    "plt.title('Age Distribution by Fuel Type')\n",
    "plt.xticks([0, 1], ['Petrol', 'Diesel'])\n",
    "plt.show()"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 1000x800 with 1 Axes>",
      "image/png": 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\n"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 가변수로 변환된 데이터에서 color 간 Age_08_04 분포 시각화\n",
    "plt.figure(figsize=(10, 8))\n",
    "sns.boxplot(data=toyota_df, y='age_08_04', x='color_Blue')\n",
    "plt.title('Age Distribution by Color')\n",
    "plt.xticks([0, 1], ['Not Blue', 'Blue'])\n",
    "plt.show()"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "* Diesel 차량이 Petrol 차량보다 연식이 낮은 것으로 나타났으며, 또한 Blue 차량이 Not Blue 차량보다 연식이 높은 것으로 나타남"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%% md\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
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