01_2_데이터변환.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 데이터 불러오기"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: numpy.ufunc size changed, may indicate binary incompatibility. Expected 192 from C header, got 216 from PyObject\n",
      "  return f(*args, **kwds)\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "df=pd.read_csv('heart.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Age</th>\n",
       "      <th>Sex</th>\n",
       "      <th>ChestPain</th>\n",
       "      <th>RestBP</th>\n",
       "      <th>Chol</th>\n",
       "      <th>Fbs</th>\n",
       "      <th>RestECG</th>\n",
       "      <th>MaxHR</th>\n",
       "      <th>ExAng</th>\n",
       "      <th>Oldpeak</th>\n",
       "      <th>Slope</th>\n",
       "      <th>Ca</th>\n",
       "      <th>Thal</th>\n",
       "      <th>AHD</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>63</td>\n",
       "      <td>1</td>\n",
       "      <td>typical</td>\n",
       "      <td>145</td>\n",
       "      <td>233</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>150</td>\n",
       "      <td>0</td>\n",
       "      <td>2.3</td>\n",
       "      <td>3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>fixed</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>67</td>\n",
       "      <td>1</td>\n",
       "      <td>asymptomatic</td>\n",
       "      <td>160</td>\n",
       "      <td>286</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>108</td>\n",
       "      <td>1</td>\n",
       "      <td>1.5</td>\n",
       "      <td>2</td>\n",
       "      <td>3.0</td>\n",
       "      <td>normal</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>67</td>\n",
       "      <td>1</td>\n",
       "      <td>asymptomatic</td>\n",
       "      <td>120</td>\n",
       "      <td>229</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>129</td>\n",
       "      <td>1</td>\n",
       "      <td>2.6</td>\n",
       "      <td>2</td>\n",
       "      <td>2.0</td>\n",
       "      <td>reversable</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>37</td>\n",
       "      <td>1</td>\n",
       "      <td>nonanginal</td>\n",
       "      <td>130</td>\n",
       "      <td>250</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>187</td>\n",
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       "      <td>3</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>No</td>\n",
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       "      <th>4</th>\n",
       "      <td>41</td>\n",
       "      <td>0</td>\n",
       "      <td>nontypical</td>\n",
       "      <td>130</td>\n",
       "      <td>204</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>172</td>\n",
       "      <td>0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>normal</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>298</th>\n",
       "      <td>45</td>\n",
       "      <td>1</td>\n",
       "      <td>typical</td>\n",
       "      <td>110</td>\n",
       "      <td>264</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>132</td>\n",
       "      <td>0</td>\n",
       "      <td>1.2</td>\n",
       "      <td>2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>reversable</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>299</th>\n",
       "      <td>68</td>\n",
       "      <td>1</td>\n",
       "      <td>asymptomatic</td>\n",
       "      <td>144</td>\n",
       "      <td>193</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>141</td>\n",
       "      <td>0</td>\n",
       "      <td>3.4</td>\n",
       "      <td>2</td>\n",
       "      <td>2.0</td>\n",
       "      <td>reversable</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>300</th>\n",
       "      <td>57</td>\n",
       "      <td>1</td>\n",
       "      <td>asymptomatic</td>\n",
       "      <td>130</td>\n",
       "      <td>131</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>115</td>\n",
       "      <td>1</td>\n",
       "      <td>1.2</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "      <td>reversable</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>301</th>\n",
       "      <td>57</td>\n",
       "      <td>0</td>\n",
       "      <td>nontypical</td>\n",
       "      <td>130</td>\n",
       "      <td>236</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>174</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "      <td>normal</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>302</th>\n",
       "      <td>38</td>\n",
       "      <td>1</td>\n",
       "      <td>nonanginal</td>\n",
       "      <td>138</td>\n",
       "      <td>175</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>173</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>normal</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>303 rows × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Age  Sex     ChestPain  RestBP  Chol  Fbs  RestECG  MaxHR  ExAng  \\\n",
       "0     63    1       typical     145   233    1        2    150      0   \n",
       "1     67    1  asymptomatic     160   286    0        2    108      1   \n",
       "2     67    1  asymptomatic     120   229    0        2    129      1   \n",
       "3     37    1    nonanginal     130   250    0        0    187      0   \n",
       "4     41    0    nontypical     130   204    0        2    172      0   \n",
       "..   ...  ...           ...     ...   ...  ...      ...    ...    ...   \n",
       "298   45    1       typical     110   264    0        0    132      0   \n",
       "299   68    1  asymptomatic     144   193    1        0    141      0   \n",
       "300   57    1  asymptomatic     130   131    0        0    115      1   \n",
       "301   57    0    nontypical     130   236    0        2    174      0   \n",
       "302   38    1    nonanginal     138   175    0        0    173      0   \n",
       "\n",
       "     Oldpeak  Slope   Ca        Thal  AHD  \n",
       "0        2.3      3  0.0       fixed   No  \n",
       "1        1.5      2  3.0      normal  Yes  \n",
       "2        2.6      2  2.0  reversable  Yes  \n",
       "3        3.5      3  0.0      normal   No  \n",
       "4        1.4      1  0.0      normal   No  \n",
       "..       ...    ...  ...         ...  ...  \n",
       "298      1.2      2  0.0  reversable  Yes  \n",
       "299      3.4      2  2.0  reversable  Yes  \n",
       "300      1.2      2  1.0  reversable  Yes  \n",
       "301      0.0      2  1.0      normal  Yes  \n",
       "302      0.0      1  NaN      normal   No  \n",
       "\n",
       "[303 rows x 14 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Age</th>\n",
       "      <th>Sex</th>\n",
       "      <th>RestBP</th>\n",
       "      <th>Chol</th>\n",
       "      <th>Fbs</th>\n",
       "      <th>RestECG</th>\n",
       "      <th>MaxHR</th>\n",
       "      <th>ExAng</th>\n",
       "      <th>Oldpeak</th>\n",
       "      <th>Slope</th>\n",
       "      <th>Ca</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>297.000000</td>\n",
       "      <td>297.000000</td>\n",
       "      <td>297.000000</td>\n",
       "      <td>297.000000</td>\n",
       "      <td>297.000000</td>\n",
       "      <td>297.000000</td>\n",
       "      <td>297.000000</td>\n",
       "      <td>297.000000</td>\n",
       "      <td>297.000000</td>\n",
       "      <td>297.000000</td>\n",
       "      <td>297.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>54.542088</td>\n",
       "      <td>0.676768</td>\n",
       "      <td>131.693603</td>\n",
       "      <td>247.350168</td>\n",
       "      <td>0.144781</td>\n",
       "      <td>0.996633</td>\n",
       "      <td>149.599327</td>\n",
       "      <td>0.326599</td>\n",
       "      <td>1.055556</td>\n",
       "      <td>1.602694</td>\n",
       "      <td>0.676768</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>9.049736</td>\n",
       "      <td>0.468500</td>\n",
       "      <td>17.762806</td>\n",
       "      <td>51.997583</td>\n",
       "      <td>0.352474</td>\n",
       "      <td>0.994914</td>\n",
       "      <td>22.941562</td>\n",
       "      <td>0.469761</td>\n",
       "      <td>1.166123</td>\n",
       "      <td>0.618187</td>\n",
       "      <td>0.938965</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>29.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>94.000000</td>\n",
       "      <td>126.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>71.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>48.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>120.000000</td>\n",
       "      <td>211.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>133.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>56.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>130.000000</td>\n",
       "      <td>243.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>153.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.800000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>61.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>140.000000</td>\n",
       "      <td>276.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>166.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.600000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>77.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>200.000000</td>\n",
       "      <td>564.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>202.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>6.200000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>3.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              Age         Sex      RestBP        Chol         Fbs     RestECG  \\\n",
       "count  297.000000  297.000000  297.000000  297.000000  297.000000  297.000000   \n",
       "mean    54.542088    0.676768  131.693603  247.350168    0.144781    0.996633   \n",
       "std      9.049736    0.468500   17.762806   51.997583    0.352474    0.994914   \n",
       "min     29.000000    0.000000   94.000000  126.000000    0.000000    0.000000   \n",
       "25%     48.000000    0.000000  120.000000  211.000000    0.000000    0.000000   \n",
       "50%     56.000000    1.000000  130.000000  243.000000    0.000000    1.000000   \n",
       "75%     61.000000    1.000000  140.000000  276.000000    0.000000    2.000000   \n",
       "max     77.000000    1.000000  200.000000  564.000000    1.000000    2.000000   \n",
       "\n",
       "            MaxHR       ExAng     Oldpeak       Slope          Ca  \n",
       "count  297.000000  297.000000  297.000000  297.000000  297.000000  \n",
       "mean   149.599327    0.326599    1.055556    1.602694    0.676768  \n",
       "std     22.941562    0.469761    1.166123    0.618187    0.938965  \n",
       "min     71.000000    0.000000    0.000000    1.000000    0.000000  \n",
       "25%    133.000000    0.000000    0.000000    1.000000    0.000000  \n",
       "50%    153.000000    0.000000    0.800000    2.000000    0.000000  \n",
       "75%    166.000000    1.000000    1.600000    2.000000    1.000000  \n",
       "max    202.000000    1.000000    6.200000    3.000000    3.000000  "
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Age          0\n",
       "Sex          0\n",
       "ChestPain    0\n",
       "RestBP       0\n",
       "Chol         0\n",
       "Fbs          0\n",
       "RestECG      0\n",
       "MaxHR        0\n",
       "ExAng        0\n",
       "Oldpeak      0\n",
       "Slope        0\n",
       "Ca           4\n",
       "Thal         2\n",
       "AHD          0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 누락치 제거\n",
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 누락치 제거\n",
    "df=df.dropna(axis=0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Categorical Data 변환하기"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Age</th>\n",
       "      <th>Sex</th>\n",
       "      <th>ChestPain</th>\n",
       "      <th>RestBP</th>\n",
       "      <th>Chol</th>\n",
       "      <th>Fbs</th>\n",
       "      <th>RestECG</th>\n",
       "      <th>MaxHR</th>\n",
       "      <th>ExAng</th>\n",
       "      <th>Oldpeak</th>\n",
       "      <th>Slope</th>\n",
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       "      <th>Thal</th>\n",
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       "  </thead>\n",
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       "      <th>0</th>\n",
       "      <td>63</td>\n",
       "      <td>1</td>\n",
       "      <td>typical</td>\n",
       "      <td>145</td>\n",
       "      <td>233</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>150</td>\n",
       "      <td>0</td>\n",
       "      <td>2.3</td>\n",
       "      <td>3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>fixed</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>67</td>\n",
       "      <td>1</td>\n",
       "      <td>asymptomatic</td>\n",
       "      <td>160</td>\n",
       "      <td>286</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>108</td>\n",
       "      <td>1</td>\n",
       "      <td>1.5</td>\n",
       "      <td>2</td>\n",
       "      <td>3.0</td>\n",
       "      <td>normal</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>67</td>\n",
       "      <td>1</td>\n",
       "      <td>asymptomatic</td>\n",
       "      <td>120</td>\n",
       "      <td>229</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>129</td>\n",
       "      <td>1</td>\n",
       "      <td>2.6</td>\n",
       "      <td>2</td>\n",
       "      <td>2.0</td>\n",
       "      <td>reversable</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>37</td>\n",
       "      <td>1</td>\n",
       "      <td>nonanginal</td>\n",
       "      <td>130</td>\n",
       "      <td>250</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>187</td>\n",
       "      <td>0</td>\n",
       "      <td>3.5</td>\n",
       "      <td>3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>normal</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>41</td>\n",
       "      <td>0</td>\n",
       "      <td>nontypical</td>\n",
       "      <td>130</td>\n",
       "      <td>204</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>172</td>\n",
       "      <td>0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>normal</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Age  Sex     ChestPain  RestBP  Chol  Fbs  RestECG  MaxHR  ExAng  Oldpeak  \\\n",
       "0   63    1       typical     145   233    1        2    150      0      2.3   \n",
       "1   67    1  asymptomatic     160   286    0        2    108      1      1.5   \n",
       "2   67    1  asymptomatic     120   229    0        2    129      1      2.6   \n",
       "3   37    1    nonanginal     130   250    0        0    187      0      3.5   \n",
       "4   41    0    nontypical     130   204    0        2    172      0      1.4   \n",
       "\n",
       "   Slope   Ca        Thal  AHD  \n",
       "0      3  0.0       fixed   No  \n",
       "1      2  3.0      normal  Yes  \n",
       "2      2  2.0  reversable  Yes  \n",
       "3      3  0.0      normal   No  \n",
       "4      1  0.0      normal   No  "
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "# get_dummies를 이용해 변환\n",
    "df2=pd.get_dummies(df,columns=['Sex','ChestPain','Thal','AHD'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr>\n",
       "      <th>301</th>\n",
       "      <td>57</td>\n",
       "      <td>130</td>\n",
       "      <td>236</td>\n",
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       "      <td>2</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "<p>297 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Age  RestBP  Chol  Fbs  RestECG  MaxHR  ExAng  Oldpeak  Slope   Ca  ...  \\\n",
       "0     63     145   233    1        2    150      0      2.3      3  0.0  ...   \n",
       "1     67     160   286    0        2    108      1      1.5      2  3.0  ...   \n",
       "2     67     120   229    0        2    129      1      2.6      2  2.0  ...   \n",
       "3     37     130   250    0        0    187      0      3.5      3  0.0  ...   \n",
       "4     41     130   204    0        2    172      0      1.4      1  0.0  ...   \n",
       "..   ...     ...   ...  ...      ...    ...    ...      ...    ...  ...  ...   \n",
       "297   57     140   241    0        0    123      1      0.2      2  0.0  ...   \n",
       "298   45     110   264    0        0    132      0      1.2      2  0.0  ...   \n",
       "299   68     144   193    1        0    141      0      3.4      2  2.0  ...   \n",
       "300   57     130   131    0        0    115      1      1.2      2  1.0  ...   \n",
       "301   57     130   236    0        2    174      0      0.0      2  1.0  ...   \n",
       "\n",
       "     Sex_1  ChestPain_asymptomatic  ChestPain_nonanginal  \\\n",
       "0        1                       0                     0   \n",
       "1        1                       1                     0   \n",
       "2        1                       1                     0   \n",
       "3        1                       0                     1   \n",
       "4        0                       0                     0   \n",
       "..     ...                     ...                   ...   \n",
       "297      0                       1                     0   \n",
       "298      1                       0                     0   \n",
       "299      1                       1                     0   \n",
       "300      1                       1                     0   \n",
       "301      0                       0                     0   \n",
       "\n",
       "     ChestPain_nontypical  ChestPain_typical  Thal_fixed  Thal_normal  \\\n",
       "0                       0                  1           1            0   \n",
       "1                       0                  0           0            1   \n",
       "2                       0                  0           0            0   \n",
       "3                       0                  0           0            1   \n",
       "4                       1                  0           0            1   \n",
       "..                    ...                ...         ...          ...   \n",
       "297                     0                  0           0            0   \n",
       "298                     0                  1           0            0   \n",
       "299                     0                  0           0            0   \n",
       "300                     0                  0           0            0   \n",
       "301                     1                  0           0            1   \n",
       "\n",
       "     Thal_reversable  AHD_No  AHD_Yes  \n",
       "0                  0       1        0  \n",
       "1                  0       0        1  \n",
       "2                  1       0        1  \n",
       "3                  0       1        0  \n",
       "4                  0       1        0  \n",
       "..               ...     ...      ...  \n",
       "297                1       0        1  \n",
       "298                1       0        1  \n",
       "299                1       0        1  \n",
       "300                1       0        1  \n",
       "301                0       0        1  \n",
       "\n",
       "[297 rows x 21 columns]"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Age', 'RestBP', 'Chol', 'Fbs', 'RestECG', 'MaxHR', 'ExAng', 'Oldpeak',\n",
       "       'Slope', 'Ca', 'Sex_0', 'Sex_1', 'ChestPain_asymptomatic',\n",
       "       'ChestPain_nonanginal', 'ChestPain_nontypical', 'ChestPain_typical',\n",
       "       'Thal_fixed', 'Thal_normal', 'Thal_reversable', 'AHD_No', 'AHD_Yes'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 데이터 표준화"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {
    "tags": []
   },
   "outputs": [
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       "      <th>2</th>\n",
       "      <td>8</td>\n",
       "      <td>318.0</td>\n",
       "      <td>150.0</td>\n",
       "      <td>3436.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>70</td>\n",
       "      <td>1</td>\n",
       "      <td>18.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>8</td>\n",
       "      <td>304.0</td>\n",
       "      <td>150.0</td>\n",
       "      <td>3433.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>70</td>\n",
       "      <td>1</td>\n",
       "      <td>16.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>8</td>\n",
       "      <td>302.0</td>\n",
       "      <td>140.0</td>\n",
       "      <td>3449.0</td>\n",
       "      <td>10.5</td>\n",
       "      <td>70</td>\n",
       "      <td>1</td>\n",
       "      <td>17.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>387</th>\n",
       "      <td>4</td>\n",
       "      <td>140.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>2790.0</td>\n",
       "      <td>15.6</td>\n",
       "      <td>82</td>\n",
       "      <td>1</td>\n",
       "      <td>27.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>388</th>\n",
       "      <td>4</td>\n",
       "      <td>97.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>2130.0</td>\n",
       "      <td>24.6</td>\n",
       "      <td>82</td>\n",
       "      <td>2</td>\n",
       "      <td>44.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>389</th>\n",
       "      <td>4</td>\n",
       "      <td>135.0</td>\n",
       "      <td>84.0</td>\n",
       "      <td>2295.0</td>\n",
       "      <td>11.6</td>\n",
       "      <td>82</td>\n",
       "      <td>1</td>\n",
       "      <td>32.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>390</th>\n",
       "      <td>4</td>\n",
       "      <td>120.0</td>\n",
       "      <td>79.0</td>\n",
       "      <td>2625.0</td>\n",
       "      <td>18.6</td>\n",
       "      <td>82</td>\n",
       "      <td>1</td>\n",
       "      <td>28.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>391</th>\n",
       "      <td>4</td>\n",
       "      <td>119.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>2720.0</td>\n",
       "      <td>19.4</td>\n",
       "      <td>82</td>\n",
       "      <td>1</td>\n",
       "      <td>31.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>392 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     cylinders  displacement  horsepower  weight  acceleration  model_year  \\\n",
       "0            8         307.0       130.0  3504.0          12.0          70   \n",
       "1            8         350.0       165.0  3693.0          11.5          70   \n",
       "2            8         318.0       150.0  3436.0          11.0          70   \n",
       "3            8         304.0       150.0  3433.0          12.0          70   \n",
       "4            8         302.0       140.0  3449.0          10.5          70   \n",
       "..         ...           ...         ...     ...           ...         ...   \n",
       "387          4         140.0        86.0  2790.0          15.6          82   \n",
       "388          4          97.0        52.0  2130.0          24.6          82   \n",
       "389          4         135.0        84.0  2295.0          11.6          82   \n",
       "390          4         120.0        79.0  2625.0          18.6          82   \n",
       "391          4         119.0        82.0  2720.0          19.4          82   \n",
       "\n",
       "     origin   mpg  \n",
       "0         1  18.0  \n",
       "1         1  15.0  \n",
       "2         1  18.0  \n",
       "3         1  16.0  \n",
       "4         1  17.0  \n",
       "..      ...   ...  \n",
       "387       1  27.0  \n",
       "388       2  44.0  \n",
       "389       1  32.0  \n",
       "390       1  28.0  \n",
       "391       1  31.0  \n",
       "\n",
       "[392 rows x 8 columns]"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df=pd.read_csv('auto.csv')\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>cylinders</th>\n",
       "      <th>displacement</th>\n",
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       "      <th>acceleration</th>\n",
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       "      <th>2</th>\n",
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       "      <th>3</th>\n",
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       "      <td>-0.715726</td>\n",
       "      <td>-0.953992</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1.482053</td>\n",
       "      <td>1.028134</td>\n",
       "      <td>0.923085</td>\n",
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       "      <td>-0.479835</td>\n",
       "      <td>-0.220842</td>\n",
       "      <td>0.021267</td>\n",
       "      <td>1.634321</td>\n",
       "      <td>-0.715726</td>\n",
       "      <td>0.455359</td>\n",
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       "    <tr>\n",
       "      <th>388</th>\n",
       "      <td>-0.862911</td>\n",
       "      <td>-0.930889</td>\n",
       "      <td>-1.363154</td>\n",
       "      <td>-0.997859</td>\n",
       "      <td>3.283479</td>\n",
       "      <td>1.634321</td>\n",
       "      <td>0.525711</td>\n",
       "      <td>2.633448</td>\n",
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       "    <tr>\n",
       "      <th>389</th>\n",
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       "      <td>-0.567753</td>\n",
       "      <td>-0.531795</td>\n",
       "      <td>-0.803605</td>\n",
       "      <td>-1.428605</td>\n",
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       "      <td>-0.715726</td>\n",
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       "      <th>390</th>\n",
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       "      <td>0.583482</td>\n",
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       "      <th>391</th>\n",
       "      <td>-0.862911</td>\n",
       "      <td>-0.720653</td>\n",
       "      <td>-0.583754</td>\n",
       "      <td>-0.303253</td>\n",
       "      <td>1.398646</td>\n",
       "      <td>1.634321</td>\n",
       "      <td>-0.715726</td>\n",
       "      <td>0.967851</td>\n",
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       "</table>\n",
       "<p>392 rows × 8 columns</p>\n",
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      "text/plain": [
       "     cylinders  displacement  horsepower    weight  acceleration  model_year  \\\n",
       "0     1.482053      1.075915    0.663285  0.619748     -1.283618   -1.623241   \n",
       "1     1.482053      1.486832    1.572585  0.842258     -1.464852   -1.623241   \n",
       "2     1.482053      1.181033    1.182885  0.539692     -1.646086   -1.623241   \n",
       "3     1.482053      1.047246    1.182885  0.536160     -1.283618   -1.623241   \n",
       "4     1.482053      1.028134    0.923085  0.554997     -1.827320   -1.623241   \n",
       "..         ...           ...         ...       ...           ...         ...   \n",
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       "388  -0.862911     -0.930889   -1.363154 -0.997859      3.283479    1.634321   \n",
       "389  -0.862911     -0.567753   -0.531795 -0.803605     -1.428605    1.634321   \n",
       "390  -0.862911     -0.711097   -0.661694 -0.415097      1.108671    1.634321   \n",
       "391  -0.862911     -0.720653   -0.583754 -0.303253      1.398646    1.634321   \n",
       "\n",
       "       origin       mpg  \n",
       "0   -0.715726 -0.697747  \n",
       "1   -0.715726 -1.082115  \n",
       "2   -0.715726 -0.697747  \n",
       "3   -0.715726 -0.953992  \n",
       "4   -0.715726 -0.825870  \n",
       "..        ...       ...  \n",
       "387 -0.715726  0.455359  \n",
       "388  0.525711  2.633448  \n",
       "389 -0.715726  1.095974  \n",
       "390 -0.715726  0.583482  \n",
       "391 -0.715726  0.967851  \n",
       "\n",
       "[392 rows x 8 columns]"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 표준화\n",
    "df=(df-df.mean())/df.std()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## SKlearn을 이용한 전처리"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [],
   "source": [
    "df=pd.read_csv('auto.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 1.48394702,  1.07728956,  0.66413273, ..., -1.62531533,\n",
       "        -0.71664105, -0.69863841],\n",
       "       [ 1.48394702,  1.48873169,  1.57459447, ..., -1.62531533,\n",
       "        -0.71664105, -1.08349824],\n",
       "       [ 1.48394702,  1.1825422 ,  1.18439658, ..., -1.62531533,\n",
       "        -0.71664105, -0.69863841],\n",
       "       ...,\n",
       "       [-0.86401356, -0.56847897, -0.53247413, ...,  1.63640964,\n",
       "        -0.71664105,  1.09737414],\n",
       "       [-0.86401356, -0.7120053 , -0.66254009, ...,  1.63640964,\n",
       "        -0.71664105,  0.5842277 ],\n",
       "       [-0.86401356, -0.72157372, -0.58450051, ...,  1.63640964,\n",
       "        -0.71664105,  0.96908753]])"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.preprocessing import StandardScaler, MinMaxScaler\n",
    "## 정규화 (평균0, 표준편차0으로 스케일링)\n",
    "scaler = StandardScaler()\n",
    "output = scaler.fit_transform(df)\n",
    "output"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>model_year</th>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1.483947</td>\n",
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       "      <td>-1.083498</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1.483947</td>\n",
       "      <td>1.182542</td>\n",
       "      <td>1.184397</td>\n",
       "      <td>0.540382</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1.483947</td>\n",
       "      <td>1.048584</td>\n",
       "      <td>1.184397</td>\n",
       "      <td>0.536845</td>\n",
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       "      <td>-0.716641</td>\n",
       "      <td>-0.955212</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1.483947</td>\n",
       "      <td>1.029447</td>\n",
       "      <td>0.924265</td>\n",
       "      <td>0.555706</td>\n",
       "      <td>-1.829655</td>\n",
       "      <td>-1.625315</td>\n",
       "      <td>-0.716641</td>\n",
       "      <td>-0.826925</td>\n",
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       "    <tr>\n",
       "      <th>...</th>\n",
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       "      <th>387</th>\n",
       "      <td>-0.864014</td>\n",
       "      <td>-0.520637</td>\n",
       "      <td>-0.480448</td>\n",
       "      <td>-0.221125</td>\n",
       "      <td>0.021294</td>\n",
       "      <td>1.636410</td>\n",
       "      <td>-0.716641</td>\n",
       "      <td>0.455941</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>388</th>\n",
       "      <td>-0.864014</td>\n",
       "      <td>-0.932079</td>\n",
       "      <td>-1.364896</td>\n",
       "      <td>-0.999134</td>\n",
       "      <td>3.287676</td>\n",
       "      <td>1.636410</td>\n",
       "      <td>0.526382</td>\n",
       "      <td>2.636813</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>389</th>\n",
       "      <td>-0.864014</td>\n",
       "      <td>-0.568479</td>\n",
       "      <td>-0.532474</td>\n",
       "      <td>-0.804632</td>\n",
       "      <td>-1.430430</td>\n",
       "      <td>1.636410</td>\n",
       "      <td>-0.716641</td>\n",
       "      <td>1.097374</td>\n",
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       "    <tr>\n",
       "      <th>390</th>\n",
       "      <td>-0.864014</td>\n",
       "      <td>-0.712005</td>\n",
       "      <td>-0.662540</td>\n",
       "      <td>-0.415627</td>\n",
       "      <td>1.110088</td>\n",
       "      <td>1.636410</td>\n",
       "      <td>-0.716641</td>\n",
       "      <td>0.584228</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>391</th>\n",
       "      <td>-0.864014</td>\n",
       "      <td>-0.721574</td>\n",
       "      <td>-0.584501</td>\n",
       "      <td>-0.303641</td>\n",
       "      <td>1.400433</td>\n",
       "      <td>1.636410</td>\n",
       "      <td>-0.716641</td>\n",
       "      <td>0.969088</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>392 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     cylinders  displacement  horsepower    weight  acceleration  model_year  \\\n",
       "0     1.483947      1.077290    0.664133  0.620540     -1.285258   -1.625315   \n",
       "1     1.483947      1.488732    1.574594  0.843334     -1.466724   -1.625315   \n",
       "2     1.483947      1.182542    1.184397  0.540382     -1.648189   -1.625315   \n",
       "3     1.483947      1.048584    1.184397  0.536845     -1.285258   -1.625315   \n",
       "4     1.483947      1.029447    0.924265  0.555706     -1.829655   -1.625315   \n",
       "..         ...           ...         ...       ...           ...         ...   \n",
       "387  -0.864014     -0.520637   -0.480448 -0.221125      0.021294    1.636410   \n",
       "388  -0.864014     -0.932079   -1.364896 -0.999134      3.287676    1.636410   \n",
       "389  -0.864014     -0.568479   -0.532474 -0.804632     -1.430430    1.636410   \n",
       "390  -0.864014     -0.712005   -0.662540 -0.415627      1.110088    1.636410   \n",
       "391  -0.864014     -0.721574   -0.584501 -0.303641      1.400433    1.636410   \n",
       "\n",
       "       origin       mpg  \n",
       "0   -0.716641 -0.698638  \n",
       "1   -0.716641 -1.083498  \n",
       "2   -0.716641 -0.698638  \n",
       "3   -0.716641 -0.955212  \n",
       "4   -0.716641 -0.826925  \n",
       "..        ...       ...  \n",
       "387 -0.716641  0.455941  \n",
       "388  0.526382  2.636813  \n",
       "389 -0.716641  1.097374  \n",
       "390 -0.716641  0.584228  \n",
       "391 -0.716641  0.969088  \n",
       "\n",
       "[392 rows x 8 columns]"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.DataFrame(output, columns=df.columns)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Polynomial Term 추가하기"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\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>X</th>\n",
       "      <th>y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.542312</td>\n",
       "      <td>4.216289</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.541676</td>\n",
       "      <td>2.874347</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-2.344561</td>\n",
       "      <td>11.687971</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1.220562</td>\n",
       "      <td>0.512072</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2.011580</td>\n",
       "      <td>-3.117803</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>995</th>\n",
       "      <td>-1.378233</td>\n",
       "      <td>10.731244</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>996</th>\n",
       "      <td>-0.154483</td>\n",
       "      <td>4.602639</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>997</th>\n",
       "      <td>-0.097741</td>\n",
       "      <td>3.282276</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>998</th>\n",
       "      <td>-1.309402</td>\n",
       "      <td>9.394069</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>999</th>\n",
       "      <td>-0.225035</td>\n",
       "      <td>3.260692</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1000 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            X          y\n",
       "0    0.542312   4.216289\n",
       "1    0.541676   2.874347\n",
       "2   -2.344561  11.687971\n",
       "3    1.220562   0.512072\n",
       "4    2.011580  -3.117803\n",
       "..        ...        ...\n",
       "995 -1.378233  10.731244\n",
       "996 -0.154483   4.602639\n",
       "997 -0.097741   3.282276\n",
       "998 -1.309402   9.394069\n",
       "999 -0.225035   3.260692\n",
       "\n",
       "[1000 rows x 2 columns]"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df=pd.read_csv('simple.csv')\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [],
   "source": [
    "## 객체 생성\n",
    "from sklearn.preprocessing import PolynomialFeatures\n",
    "transformer = PolynomialFeatures(degree=2, interaction_only=True)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[  1.        ,   0.54231199,   4.21628949,   2.28654434],\n",
       "       [  1.        ,   0.54167552,   2.87434682,   1.55696331],\n",
       "       [  1.        ,  -2.34456094,  11.68797089, -27.40315998],\n",
       "       ...,\n",
       "       [  1.        ,  -0.09774062,   3.28227568,  -0.32081166],\n",
       "       [  1.        ,  -1.30940196,   9.39406861, -12.30061187],\n",
       "       [  1.        ,  -0.22503533,   3.26069231,  -0.73377097]])"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## 데이터 변환\n",
    "output=transformer.fit_transform(df)\n",
    "output # Array형태\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['1', 'X', 'y', 'X y']"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## 열이름 붙이기\n",
    "columns = transformer.get_feature_names(df.columns)\n",
    "columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>1</th>\n",
       "      <th>X</th>\n",
       "      <th>y</th>\n",
       "      <th>X y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.542312</td>\n",
       "      <td>4.216289</td>\n",
       "      <td>2.286544</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.541676</td>\n",
       "      <td>2.874347</td>\n",
       "      <td>1.556963</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1.0</td>\n",
       "      <td>-2.344561</td>\n",
       "      <td>11.687971</td>\n",
       "      <td>-27.403160</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1.0</td>\n",
       "      <td>1.220562</td>\n",
       "      <td>0.512072</td>\n",
       "      <td>0.625016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1.0</td>\n",
       "      <td>2.011580</td>\n",
       "      <td>-3.117803</td>\n",
       "      <td>-6.271710</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>995</th>\n",
       "      <td>1.0</td>\n",
       "      <td>-1.378233</td>\n",
       "      <td>10.731244</td>\n",
       "      <td>-14.790157</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>996</th>\n",
       "      <td>1.0</td>\n",
       "      <td>-0.154483</td>\n",
       "      <td>4.602639</td>\n",
       "      <td>-0.711027</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>997</th>\n",
       "      <td>1.0</td>\n",
       "      <td>-0.097741</td>\n",
       "      <td>3.282276</td>\n",
       "      <td>-0.320812</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>998</th>\n",
       "      <td>1.0</td>\n",
       "      <td>-1.309402</td>\n",
       "      <td>9.394069</td>\n",
       "      <td>-12.300612</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>999</th>\n",
       "      <td>1.0</td>\n",
       "      <td>-0.225035</td>\n",
       "      <td>3.260692</td>\n",
       "      <td>-0.733771</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1000 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       1         X          y        X y\n",
       "0    1.0  0.542312   4.216289   2.286544\n",
       "1    1.0  0.541676   2.874347   1.556963\n",
       "2    1.0 -2.344561  11.687971 -27.403160\n",
       "3    1.0  1.220562   0.512072   0.625016\n",
       "4    1.0  2.011580  -3.117803  -6.271710\n",
       "..   ...       ...        ...        ...\n",
       "995  1.0 -1.378233  10.731244 -14.790157\n",
       "996  1.0 -0.154483   4.602639  -0.711027\n",
       "997  1.0 -0.097741   3.282276  -0.320812\n",
       "998  1.0 -1.309402   9.394069 -12.300612\n",
       "999  1.0 -0.225035   3.260692  -0.733771\n",
       "\n",
       "[1000 rows x 4 columns]"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## 다시 데이터프레임으로\n",
    "pd.DataFrame(output,columns=columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>1</th>\n",
       "      <th>X</th>\n",
       "      <th>y</th>\n",
       "      <th>X^2</th>\n",
       "      <th>X y</th>\n",
       "      <th>y^2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.542312</td>\n",
       "      <td>4.216289</td>\n",
       "      <td>0.294102</td>\n",
       "      <td>2.286544</td>\n",
       "      <td>17.777097</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.541676</td>\n",
       "      <td>2.874347</td>\n",
       "      <td>0.293412</td>\n",
       "      <td>1.556963</td>\n",
       "      <td>8.261870</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1.0</td>\n",
       "      <td>-2.344561</td>\n",
       "      <td>11.687971</td>\n",
       "      <td>5.496966</td>\n",
       "      <td>-27.403160</td>\n",
       "      <td>136.608663</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1.0</td>\n",
       "      <td>1.220562</td>\n",
       "      <td>0.512072</td>\n",
       "      <td>1.489772</td>\n",
       "      <td>0.625016</td>\n",
       "      <td>0.262218</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1.0</td>\n",
       "      <td>2.011580</td>\n",
       "      <td>-3.117803</td>\n",
       "      <td>4.046454</td>\n",
       "      <td>-6.271710</td>\n",
       "      <td>9.720696</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>995</th>\n",
       "      <td>1.0</td>\n",
       "      <td>-1.378233</td>\n",
       "      <td>10.731244</td>\n",
       "      <td>1.899527</td>\n",
       "      <td>-14.790157</td>\n",
       "      <td>115.159608</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>996</th>\n",
       "      <td>1.0</td>\n",
       "      <td>-0.154483</td>\n",
       "      <td>4.602639</td>\n",
       "      <td>0.023865</td>\n",
       "      <td>-0.711027</td>\n",
       "      <td>21.184289</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>997</th>\n",
       "      <td>1.0</td>\n",
       "      <td>-0.097741</td>\n",
       "      <td>3.282276</td>\n",
       "      <td>0.009553</td>\n",
       "      <td>-0.320812</td>\n",
       "      <td>10.773334</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>998</th>\n",
       "      <td>1.0</td>\n",
       "      <td>-1.309402</td>\n",
       "      <td>9.394069</td>\n",
       "      <td>1.714533</td>\n",
       "      <td>-12.300612</td>\n",
       "      <td>88.248525</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>999</th>\n",
       "      <td>1.0</td>\n",
       "      <td>-0.225035</td>\n",
       "      <td>3.260692</td>\n",
       "      <td>0.050641</td>\n",
       "      <td>-0.733771</td>\n",
       "      <td>10.632114</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1000 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       1         X          y       X^2        X y         y^2\n",
       "0    1.0  0.542312   4.216289  0.294102   2.286544   17.777097\n",
       "1    1.0  0.541676   2.874347  0.293412   1.556963    8.261870\n",
       "2    1.0 -2.344561  11.687971  5.496966 -27.403160  136.608663\n",
       "3    1.0  1.220562   0.512072  1.489772   0.625016    0.262218\n",
       "4    1.0  2.011580  -3.117803  4.046454  -6.271710    9.720696\n",
       "..   ...       ...        ...       ...        ...         ...\n",
       "995  1.0 -1.378233  10.731244  1.899527 -14.790157  115.159608\n",
       "996  1.0 -0.154483   4.602639  0.023865  -0.711027   21.184289\n",
       "997  1.0 -0.097741   3.282276  0.009553  -0.320812   10.773334\n",
       "998  1.0 -1.309402   9.394069  1.714533 -12.300612   88.248525\n",
       "999  1.0 -0.225035   3.260692  0.050641  -0.733771   10.632114\n",
       "\n",
       "[1000 rows x 6 columns]"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## 한번에\n",
    "transformer = PolynomialFeatures(degree=2, interaction_only=False)\n",
    "output=transformer.fit_transform(df)\n",
    "columns = transformer.get_feature_names(df.columns)\n",
    "pd.DataFrame(output,columns=columns)"
   ]
  }
 ],
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