11.2.1.이상치 처리.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 필요한 패키지 설치\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "\n",
    "plt.rcParams['figure.dpi'] = 300"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>HeartDisease</th>\n",
       "      <th>BMI</th>\n",
       "      <th>Smoking</th>\n",
       "      <th>AlcoholDrinking</th>\n",
       "      <th>Stroke</th>\n",
       "      <th>PhysicalHealth</th>\n",
       "      <th>MentalHealth</th>\n",
       "      <th>DiffWalking</th>\n",
       "      <th>Sex</th>\n",
       "      <th>AgeCategory</th>\n",
       "      <th>Race</th>\n",
       "      <th>Diabetic</th>\n",
       "      <th>PhysicalActivity</th>\n",
       "      <th>GenHealth</th>\n",
       "      <th>SleepTime</th>\n",
       "      <th>Asthma</th>\n",
       "      <th>KidneyDisease</th>\n",
       "      <th>SkinCancer</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>No</td>\n",
       "      <td>16.60</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>3.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>No</td>\n",
       "      <td>Female</td>\n",
       "      <td>55-59</td>\n",
       "      <td>White</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Very good</td>\n",
       "      <td>5.0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>No</td>\n",
       "      <td>20.34</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>No</td>\n",
       "      <td>Female</td>\n",
       "      <td>80 or older</td>\n",
       "      <td>White</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Very good</td>\n",
       "      <td>7.0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>No</td>\n",
       "      <td>26.58</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>20.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>No</td>\n",
       "      <td>Male</td>\n",
       "      <td>65-69</td>\n",
       "      <td>White</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Fair</td>\n",
       "      <td>8.0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>No</td>\n",
       "      <td>24.21</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>No</td>\n",
       "      <td>Female</td>\n",
       "      <td>75-79</td>\n",
       "      <td>White</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Good</td>\n",
       "      <td>6.0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>No</td>\n",
       "      <td>23.71</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>28.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Female</td>\n",
       "      <td>40-44</td>\n",
       "      <td>White</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Very good</td>\n",
       "      <td>8.0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  HeartDisease    BMI Smoking AlcoholDrinking Stroke  PhysicalHealth  \\\n",
       "0           No  16.60     Yes              No     No             3.0   \n",
       "1           No  20.34      No              No    Yes             0.0   \n",
       "2           No  26.58     Yes              No     No            20.0   \n",
       "3           No  24.21      No              No     No             0.0   \n",
       "4           No  23.71      No              No     No            28.0   \n",
       "\n",
       "   MentalHealth DiffWalking     Sex  AgeCategory   Race Diabetic  \\\n",
       "0          30.0          No  Female        55-59  White      Yes   \n",
       "1           0.0          No  Female  80 or older  White       No   \n",
       "2          30.0          No    Male        65-69  White      Yes   \n",
       "3           0.0          No  Female        75-79  White       No   \n",
       "4           0.0         Yes  Female        40-44  White       No   \n",
       "\n",
       "  PhysicalActivity  GenHealth  SleepTime Asthma KidneyDisease SkinCancer  \n",
       "0              Yes  Very good        5.0    Yes            No        Yes  \n",
       "1              Yes  Very good        7.0     No            No         No  \n",
       "2              Yes       Fair        8.0    Yes            No         No  \n",
       "3               No       Good        6.0     No            No        Yes  \n",
       "4              Yes  Very good        8.0     No            No         No  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 데이터 불러오기\n",
    "# https://www.kaggle.com/datasets/kamilpytlak/personal-key-indicators-of-heart-disease\n",
    "df = pd.read_csv(\"datasets/heart_2020_cleaned.csv\")\n",
    "\n",
    "# 데이터 샘플 확인\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    319795.000000\n",
       "mean         28.325399\n",
       "std           6.356100\n",
       "min          12.020000\n",
       "25%          24.030000\n",
       "50%          27.340000\n",
       "75%          31.420000\n",
       "max          94.850000\n",
       "Name: BMI, dtype: float64"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# BMI 컬럼의 분포 확인\n",
    "\n",
    "df['BMI'].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 2400x1800 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# BMI 컬럼의 박스플롯 시각화를 통한 이상치 확인\n",
    "\n",
    "plt.figure(figsize = (8, 6))\n",
    "sns.boxplot(y = 'BMI', data = df)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "count    319795.000000\n",
      "mean         28.325399\n",
      "std           6.356100\n",
      "min          12.020000\n",
      "25%          24.030000\n",
      "50%          27.340000\n",
      "75%          31.420000\n",
      "max          94.850000\n",
      "Name: BMI, dtype: float64\n",
      "count    318477.000000\n",
      "mean         28.193173\n",
      "std           6.010014\n",
      "min          12.020000\n",
      "25%          24.020000\n",
      "50%          27.320000\n",
      "75%          31.320000\n",
      "max          53.590000\n",
      "Name: BMI, dtype: float64\n"
     ]
    }
   ],
   "source": [
    "# BMI 컬럼의 이상치 제거 (IQR*3)\n",
    "\n",
    "# Q!, Q3 범위 정의\n",
    "Q1 = df['BMI'].quantile(0.25)\n",
    "Q3 = df['BMI'].quantile(0.75)\n",
    "IQR = Q3 - Q1    #IQR 범위. \n",
    "rev_range = 3  # 제거 범위 조절 변수 설정\n",
    "\n",
    "# 이상치 범위 설정\n",
    "filter = (df['BMI'] >= Q1 - rev_range * IQR) & (df['BMI'] <= Q3 + rev_range *IQR)\n",
    "df_rmv = df.loc[filter]\n",
    "print(df['BMI'].describe())\n",
    "print(df_rmv['BMI'].describe())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 2400x1800 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 이상치 제거 후 박스플롯 시각화\n",
    "\n",
    "plt.figure(figsize = (8, 6))\n",
    "sns.boxplot(y = 'BMI', data = df_rmv)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 이상치 IQR*3 값으로 대치\n",
    "\n",
    "# 이상치 대치 함수 설정\n",
    "def replace_outlier(value):\n",
    "    Q1 = df['BMI'].quantile(0.25)\n",
    "    Q3 = df['BMI'].quantile(0.75)\n",
    "    IQR = Q3 - Q1    #IQR 범위. \n",
    "    rev_range = 3  # 제거 범위 조절 변수 설정\n",
    "\n",
    "    if ((value < (Q1 - rev_range * IQR))): \n",
    "        value = Q1 - rev_range * IQR\n",
    "    if ((value > (Q3 + rev_range * IQR))): \n",
    "        value = Q3 + rev_range * IQR\n",
    "#         value = df['BMI'].median() # 중앙값 대치\n",
    "    return value\n",
    "df['BMI'] = df['BMI'].apply(replace_outlier)\n",
    "\n",
    "print(df['BMI'].describe())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 이상치 대치 후 박스플롯 시각화\n",
    "\n",
    "plt.figure(figsize = (8, 6))\n",
    "sns.boxplot(y = 'BMI', data = df)\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}