02_Pandas_연습문제(05~07).ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 연습문제 1\n",
    "5명의 학생의 국어, 영어, 수학 점수를 나타내는 데이터프레임을 다음과 같이 만든다.  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1) 학생 이름을 나타내는 열을 포함시키지 않고 데이터프레임 df_score1 을 생성한 후,  \n",
    "df_score1.index 속성에 학생 이름을 나타내는 열을 지정하여 인덱스를 지정한다.  \n",
    "reset_index 명령으로 이 인덱스 열을 명령으로 일반 데이터열로 바꾸여  \n",
    "데이터프레임 df_score2을 만든다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "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>국어</th>\n",
       "      <th>영어</th>\n",
       "      <th>수학</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>이름</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>김길동</th>\n",
       "      <td>100</td>\n",
       "      <td>80</td>\n",
       "      <td>80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>이길동</th>\n",
       "      <td>80</td>\n",
       "      <td>70</td>\n",
       "      <td>90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>박길동</th>\n",
       "      <td>90</td>\n",
       "      <td>90</td>\n",
       "      <td>70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>최길동</th>\n",
       "      <td>80</td>\n",
       "      <td>100</td>\n",
       "      <td>60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>한길동</th>\n",
       "      <td>70</td>\n",
       "      <td>60</td>\n",
       "      <td>50</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      국어   영어  수학\n",
       "이름               \n",
       "김길동  100   80  80\n",
       "이길동   80   70  90\n",
       "박길동   90   90  70\n",
       "최길동   80  100  60\n",
       "한길동   70   60  50"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_score1 = pd.DataFrame({'국어':[100,80,90,80,70],\n",
    "                          '영어':[80,70,90,100,60],\n",
    "                          '수학':[80,90,70,60,50]})\n",
    "df_score1.index = ['김길동','이길동','박길동','최길동','한길동']\n",
    "df_score1.index.name = '이름'\n",
    "df_score1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>이름</th>\n",
       "      <th>국어</th>\n",
       "      <th>영어</th>\n",
       "      <th>수학</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>김길동</td>\n",
       "      <td>100</td>\n",
       "      <td>80</td>\n",
       "      <td>80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>이길동</td>\n",
       "      <td>80</td>\n",
       "      <td>70</td>\n",
       "      <td>90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>박길동</td>\n",
       "      <td>90</td>\n",
       "      <td>90</td>\n",
       "      <td>70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>최길동</td>\n",
       "      <td>80</td>\n",
       "      <td>100</td>\n",
       "      <td>60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>한길동</td>\n",
       "      <td>70</td>\n",
       "      <td>60</td>\n",
       "      <td>50</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    이름   국어   영어  수학\n",
       "0  김길동  100   80  80\n",
       "1  이길동   80   70  90\n",
       "2  박길동   90   90  70\n",
       "3  최길동   80  100  60\n",
       "4  한길동   70   60  50"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_score2 = df_score1.reset_index()\n",
    "df_score2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "2) 학생 이름을 나타내는 열이 일반 데이터 열을 포함하는 데이터프레임 df_score2에  \n",
    "set_index 명령을 적용하여 다시 학생 이름을 나타내는 열을 인덱스로 변경한다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>국어</th>\n",
       "      <th>영어</th>\n",
       "      <th>수학</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>이름</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>김길동</th>\n",
       "      <td>100</td>\n",
       "      <td>80</td>\n",
       "      <td>80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>이길동</th>\n",
       "      <td>80</td>\n",
       "      <td>70</td>\n",
       "      <td>90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>박길동</th>\n",
       "      <td>90</td>\n",
       "      <td>90</td>\n",
       "      <td>70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>최길동</th>\n",
       "      <td>80</td>\n",
       "      <td>100</td>\n",
       "      <td>60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>한길동</th>\n",
       "      <td>70</td>\n",
       "      <td>60</td>\n",
       "      <td>50</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      국어   영어  수학\n",
       "이름               \n",
       "김길동  100   80  80\n",
       "이길동   80   70  90\n",
       "박길동   90   90  70\n",
       "최길동   80  100  60\n",
       "한길동   70   60  50"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_score2.set_index('이름', inplace = True)\n",
    "df_score2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 연습 문제 2\n",
    "A반 학생 5명과 B반 학생 5명의 국어, 영어, 수학 점수를 나타내는 데이터프레임을 만든다."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1) \"반\", \"번호\", \"국어\", \"영어\", \"수학\" 을 열로 가지는 데이터프레임 df_score3을 만든다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th>국어</th>\n",
       "      <th>영어</th>\n",
       "      <th>수학</th>\n",
       "      <th>번호</th>\n",
       "      <th>반</th>\n",
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       "      <th>0</th>\n",
       "      <td>100</td>\n",
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       "      <td>A</td>\n",
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       "      <th>1</th>\n",
       "      <td>80</td>\n",
       "      <td>70</td>\n",
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       "      <td>2</td>\n",
       "      <td>A</td>\n",
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       "      <th>2</th>\n",
       "      <td>90</td>\n",
       "      <td>90</td>\n",
       "      <td>70</td>\n",
       "      <td>3</td>\n",
       "      <td>A</td>\n",
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       "      <th>3</th>\n",
       "      <td>80</td>\n",
       "      <td>100</td>\n",
       "      <td>60</td>\n",
       "      <td>4</td>\n",
       "      <td>A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>50</td>\n",
       "      <td>90</td>\n",
       "      <td>90</td>\n",
       "      <td>5</td>\n",
       "      <td>A</td>\n",
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      "text/plain": [
       "    국어   영어  수학  번호  반\n",
       "0  100   80  80   1  A\n",
       "1   80   70  90   2  A\n",
       "2   90   90  70   3  A\n",
       "3   80  100  60   4  A\n",
       "4   50   90  90   5  A"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_score3 = pd.DataFrame({'국어':[100,80,90,80,50,80,85,90,95,50],\n",
    "                          '영어':[80,70,90,100,90,100,90,95,70,60], \n",
    "                          '수학':[80,90,70,60,90,60,80,85,90,100],\n",
    "                          '번호':[1,2,3,4,5,1,2,3,4,5], \n",
    "                          '반':['A','A','A','A','A','B','B','B','B','B']})\n",
    "df_score3.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "2) df_score3을 변형하여 1차 행 인덱스로 \"반\"을 2차 행 인덱스로  \n",
    "\"번호\"을 가지는 데이터프레임 df_score4을 만든다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th></th>\n",
       "      <th>과목</th>\n",
       "      <th>국어</th>\n",
       "      <th>영어</th>\n",
       "      <th>수학</th>\n",
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       "      <th rowspan=\"5\" valign=\"top\">A</th>\n",
       "      <th>1</th>\n",
       "      <td>100</td>\n",
       "      <td>80</td>\n",
       "      <td>80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>80</td>\n",
       "      <td>70</td>\n",
       "      <td>90</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>90</td>\n",
       "      <td>90</td>\n",
       "      <td>70</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>80</td>\n",
       "      <td>100</td>\n",
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       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>50</td>\n",
       "      <td>90</td>\n",
       "      <td>90</td>\n",
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       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">B</th>\n",
       "      <th>1</th>\n",
       "      <td>80</td>\n",
       "      <td>100</td>\n",
       "      <td>60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>85</td>\n",
       "      <td>90</td>\n",
       "      <td>80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>90</td>\n",
       "      <td>95</td>\n",
       "      <td>85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>95</td>\n",
       "      <td>70</td>\n",
       "      <td>90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>50</td>\n",
       "      <td>60</td>\n",
       "      <td>100</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "과목     국어   영어   수학\n",
       "반 번호               \n",
       "A 1   100   80   80\n",
       "  2    80   70   90\n",
       "  3    90   90   70\n",
       "  4    80  100   60\n",
       "  5    50   90   90\n",
       "B 1    80  100   60\n",
       "  2    85   90   80\n",
       "  3    90   95   85\n",
       "  4    95   70   90\n",
       "  5    50   60  100"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_score4 = df_score3.set_index(['반','번호'])\n",
    "df_score4.columns.name = '과목'\n",
    "df_score4"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "3) 데이터 프레임 df_score4에 각 학생의 평균을 나타내는 행을 오른쪽에 추가한다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th rowspan=\"5\" valign=\"top\">A</th>\n",
       "      <th>1</th>\n",
       "      <td>100</td>\n",
       "      <td>80</td>\n",
       "      <td>80</td>\n",
       "      <td>86.67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>80</td>\n",
       "      <td>70</td>\n",
       "      <td>90</td>\n",
       "      <td>80.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>90</td>\n",
       "      <td>90</td>\n",
       "      <td>70</td>\n",
       "      <td>83.33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>80</td>\n",
       "      <td>100</td>\n",
       "      <td>60</td>\n",
       "      <td>80.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>50</td>\n",
       "      <td>90</td>\n",
       "      <td>90</td>\n",
       "      <td>76.67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">B</th>\n",
       "      <th>1</th>\n",
       "      <td>80</td>\n",
       "      <td>100</td>\n",
       "      <td>60</td>\n",
       "      <td>80.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>85</td>\n",
       "      <td>90</td>\n",
       "      <td>80</td>\n",
       "      <td>85.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>90</td>\n",
       "      <td>95</td>\n",
       "      <td>85</td>\n",
       "      <td>90.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>95</td>\n",
       "      <td>70</td>\n",
       "      <td>90</td>\n",
       "      <td>85.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>50</td>\n",
       "      <td>60</td>\n",
       "      <td>100</td>\n",
       "      <td>70.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "과목     국어   영어   수학     평균\n",
       "반 번호                      \n",
       "A 1   100   80   80  86.67\n",
       "  2    80   70   90  80.00\n",
       "  3    90   90   70  83.33\n",
       "  4    80  100   60  80.00\n",
       "  5    50   90   90  76.67\n",
       "B 1    80  100   60  80.00\n",
       "  2    85   90   80  85.00\n",
       "  3    90   95   85  90.00\n",
       "  4    95   70   90  85.00\n",
       "  5    50   60  100  70.00"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_score4['평균'] = (df_score4.mean(axis=1)).round(2)\n",
    "df_score4"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "4) df_score3을 변형하여 행 인덱스로 \"번호\"를, 1차 열 인덱스로  \n",
    "\"국어\", \"영어\", \"수학\"을, 2차 열 인덱스로 \"반\"을 가지는 데이터프레임 df_score5을 만든다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "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 tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr:last-of-type th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"2\" halign=\"left\">국어</th>\n",
       "      <th colspan=\"2\" halign=\"left\">영어</th>\n",
       "      <th colspan=\"2\" halign=\"left\">수학</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>반</th>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>번호</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>100</td>\n",
       "      <td>80</td>\n",
       "      <td>80</td>\n",
       "      <td>100</td>\n",
       "      <td>80</td>\n",
       "      <td>60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>80</td>\n",
       "      <td>85</td>\n",
       "      <td>70</td>\n",
       "      <td>90</td>\n",
       "      <td>90</td>\n",
       "      <td>80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>90</td>\n",
       "      <td>90</td>\n",
       "      <td>90</td>\n",
       "      <td>95</td>\n",
       "      <td>70</td>\n",
       "      <td>85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>80</td>\n",
       "      <td>95</td>\n",
       "      <td>100</td>\n",
       "      <td>70</td>\n",
       "      <td>60</td>\n",
       "      <td>90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>50</td>\n",
       "      <td>50</td>\n",
       "      <td>90</td>\n",
       "      <td>60</td>\n",
       "      <td>90</td>\n",
       "      <td>100</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     국어       영어       수학     \n",
       "반     A   B    A    B   A    B\n",
       "번호                            \n",
       "1   100  80   80  100  80   60\n",
       "2    80  85   70   90  90   80\n",
       "3    90  90   90   95  70   85\n",
       "4    80  95  100   70  60   90\n",
       "5    50  50   90   60  90  100"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_score5 = df_score3.set_index(['반','번호'])\n",
    "df_score5 = df_score5.unstack('반')\n",
    "df_score5"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "5) 데이터 프레임 df_score5에 각 반별 각 과목의 평균을 나타내는 행을 아래에 추가한다"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "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 tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr:last-of-type th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"2\" halign=\"left\">국어</th>\n",
       "      <th colspan=\"2\" halign=\"left\">영어</th>\n",
       "      <th colspan=\"2\" halign=\"left\">수학</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>반</th>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>번호</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>100.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>60.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>80.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>80.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>90.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>95.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>85.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>80.0</td>\n",
       "      <td>95.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>90.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>평균</th>\n",
       "      <td>80.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>78.0</td>\n",
       "      <td>83.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       국어           영어           수학       \n",
       "반       A     B      A      B     A      B\n",
       "번호                                        \n",
       "1   100.0  80.0   80.0  100.0  80.0   60.0\n",
       "2    80.0  85.0   70.0   90.0  90.0   80.0\n",
       "3    90.0  90.0   90.0   95.0  70.0   85.0\n",
       "4    80.0  95.0  100.0   70.0  60.0   90.0\n",
       "5    50.0  50.0   90.0   60.0  90.0  100.0\n",
       "평균   80.0  80.0   86.0   83.0  78.0   83.0"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_score5.loc['평균',:] = df_score5.mean()\n",
    "df_score5"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 연습 문제 3\n",
    "두 개의 데이터프레임을 만들고 merge 명령으로 합친다.  \n",
    "단 데이터프레임은 다음 조건을 만족해야 한다.\n",
    "- 각각 5 x 5 이상의 크기를 가진다.\n",
    "- 공통 열을 하나 이상 가진다. 다만 공통 열의 이름은 서로 다르다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "scrolled": true
   },
   "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>BackNo</th>\n",
       "      <th>Name</th>\n",
       "      <th>Position</th>\n",
       "      <th>HighSchool</th>\n",
       "      <th>Height</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>7</td>\n",
       "      <td>송광민</td>\n",
       "      <td>내야수</td>\n",
       "      <td>공주고</td>\n",
       "      <td>184</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>50</td>\n",
       "      <td>이성열</td>\n",
       "      <td>내야수</td>\n",
       "      <td>순천효천고</td>\n",
       "      <td>185</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>43</td>\n",
       "      <td>정은원</td>\n",
       "      <td>내야수</td>\n",
       "      <td>인천고</td>\n",
       "      <td>177</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>8</td>\n",
       "      <td>정근우</td>\n",
       "      <td>외야수</td>\n",
       "      <td>부산고</td>\n",
       "      <td>172</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>25</td>\n",
       "      <td>최진행</td>\n",
       "      <td>외야수</td>\n",
       "      <td>덕수정보고</td>\n",
       "      <td>188</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   BackNo Name Position HighSchool  Height\n",
       "0       7  송광민      내야수        공주고     184\n",
       "1      50  이성열      내야수      순천효천고     185\n",
       "2      43  정은원      내야수        인천고     177\n",
       "3       8  정근우      외야수        부산고     172\n",
       "4      25  최진행      외야수      덕수정보고     188"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "eagles = pd.DataFrame({\n",
    "    'BackNo': [7,50,43,8,25],\n",
    "    'Name': ['송광민','이성열','정은원','정근우','최진행'],\n",
    "    'Position': ['내야수','내야수','내야수','외야수','외야수'],\n",
    "    'HighSchool': ['공주고','순천효천고','인천고','부산고','덕수정보고'],\n",
    "    'Height': [184,185,177,172,188]})\n",
    "eagles"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "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>선수명</th>\n",
       "      <th>타율</th>\n",
       "      <th>출루율</th>\n",
       "      <th>장타율</th>\n",
       "      <th>OPS</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>송광민</td>\n",
       "      <td>0.204</td>\n",
       "      <td>0.358</td>\n",
       "      <td>0.384</td>\n",
       "      <td>0.742</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>정근우</td>\n",
       "      <td>0.319</td>\n",
       "      <td>0.336</td>\n",
       "      <td>0.393</td>\n",
       "      <td>0.729</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>최진행</td>\n",
       "      <td>0.227</td>\n",
       "      <td>0.354</td>\n",
       "      <td>0.432</td>\n",
       "      <td>0.786</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>이성열</td>\n",
       "      <td>0.230</td>\n",
       "      <td>0.309</td>\n",
       "      <td>0.379</td>\n",
       "      <td>0.688</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>정은원</td>\n",
       "      <td>0.310</td>\n",
       "      <td>0.339</td>\n",
       "      <td>0.383</td>\n",
       "      <td>0.722</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   선수명     타율    출루율    장타율    OPS\n",
       "0  송광민  0.204  0.358  0.384  0.742\n",
       "1  정근우  0.319  0.336  0.393  0.729\n",
       "2  최진행  0.227  0.354  0.432  0.786\n",
       "3  이성열  0.230  0.309  0.379  0.688\n",
       "4  정은원  0.310  0.339  0.383  0.722"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "players = pd.DataFrame({\n",
    "    '선수명': ['송광민','정근우','최진행','이성열','정은원'],\n",
    "    '타율': np.random.uniform(0.2, 0.32, 5).round(3),\n",
    "    '출루율': np.random.uniform(0.3, 0.4, 5).round(3),\n",
    "    '장타율': np.random.uniform(0.36, 0.45, 5).round(3)\n",
    "})\n",
    "players['OPS'] = players['출루율'] + players['장타율']\n",
    "players"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "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>BackNo</th>\n",
       "      <th>Name</th>\n",
       "      <th>Position</th>\n",
       "      <th>HighSchool</th>\n",
       "      <th>Height</th>\n",
       "      <th>선수명</th>\n",
       "      <th>타율</th>\n",
       "      <th>출루율</th>\n",
       "      <th>장타율</th>\n",
       "      <th>OPS</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>7</td>\n",
       "      <td>송광민</td>\n",
       "      <td>내야수</td>\n",
       "      <td>공주고</td>\n",
       "      <td>184</td>\n",
       "      <td>송광민</td>\n",
       "      <td>0.204</td>\n",
       "      <td>0.358</td>\n",
       "      <td>0.384</td>\n",
       "      <td>0.742</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>50</td>\n",
       "      <td>이성열</td>\n",
       "      <td>내야수</td>\n",
       "      <td>순천효천고</td>\n",
       "      <td>185</td>\n",
       "      <td>이성열</td>\n",
       "      <td>0.230</td>\n",
       "      <td>0.309</td>\n",
       "      <td>0.379</td>\n",
       "      <td>0.688</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>43</td>\n",
       "      <td>정은원</td>\n",
       "      <td>내야수</td>\n",
       "      <td>인천고</td>\n",
       "      <td>177</td>\n",
       "      <td>정은원</td>\n",
       "      <td>0.310</td>\n",
       "      <td>0.339</td>\n",
       "      <td>0.383</td>\n",
       "      <td>0.722</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>8</td>\n",
       "      <td>정근우</td>\n",
       "      <td>외야수</td>\n",
       "      <td>부산고</td>\n",
       "      <td>172</td>\n",
       "      <td>정근우</td>\n",
       "      <td>0.319</td>\n",
       "      <td>0.336</td>\n",
       "      <td>0.393</td>\n",
       "      <td>0.729</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>25</td>\n",
       "      <td>최진행</td>\n",
       "      <td>외야수</td>\n",
       "      <td>덕수정보고</td>\n",
       "      <td>188</td>\n",
       "      <td>최진행</td>\n",
       "      <td>0.227</td>\n",
       "      <td>0.354</td>\n",
       "      <td>0.432</td>\n",
       "      <td>0.786</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   BackNo Name Position HighSchool  Height  선수명     타율    출루율    장타율    OPS\n",
       "0       7  송광민      내야수        공주고     184  송광민  0.204  0.358  0.384  0.742\n",
       "1      50  이성열      내야수      순천효천고     185  이성열  0.230  0.309  0.379  0.688\n",
       "2      43  정은원      내야수        인천고     177  정은원  0.310  0.339  0.383  0.722\n",
       "3       8  정근우      외야수        부산고     172  정근우  0.319  0.336  0.393  0.729\n",
       "4      25  최진행      외야수      덕수정보고     188  최진행  0.227  0.354  0.432  0.786"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.merge(eagles, players, left_on='Name', right_on='선수명')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 연습 문제 4\n",
    "어느 회사의 전반기(1월 ~ 6월) 실적을 나타내는 데이터프레임과 후반기(7월 ~ 12월) 실적을  \n",
    "나타내는 데이터프레임을 만든 뒤 합친다. 실적 정보는 \"매출\", \"비용\", \"이익\" 으로 이루어진다.  \n",
    "- (이익 = 매출 - 비용)  \n",
    "  \n",
    "또한 1년간의 총 실적을 마지막 행으로 덧붙인다.  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "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>매출</th>\n",
       "      <th>비용</th>\n",
       "      <th>이익</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>월</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1월</th>\n",
       "      <td>405000</td>\n",
       "      <td>349504</td>\n",
       "      <td>55496</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2월</th>\n",
       "      <td>506030</td>\n",
       "      <td>203953</td>\n",
       "      <td>302077</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3월</th>\n",
       "      <td>904035</td>\n",
       "      <td>542039</td>\n",
       "      <td>361996</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4월</th>\n",
       "      <td>403524</td>\n",
       "      <td>603495</td>\n",
       "      <td>-199971</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5월</th>\n",
       "      <td>382940</td>\n",
       "      <td>320435</td>\n",
       "      <td>62505</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6월</th>\n",
       "      <td>942334</td>\n",
       "      <td>342346</td>\n",
       "      <td>599988</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        매출      비용      이익\n",
       "월                         \n",
       "1월  405000  349504   55496\n",
       "2월  506030  203953  302077\n",
       "3월  904035  542039  361996\n",
       "4월  403524  603495 -199971\n",
       "5월  382940  320435   62505\n",
       "6월  942334  342346  599988"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "firstHalf = pd.DataFrame({'월': ['1월','2월','3월','4월','5월','6월'],\n",
    "                   '매출': [405000,506030,904035,403524,382940,942334],\n",
    "                   '비용': [349504,203953,542039,603495,320435,342346]})\n",
    "firstHalf['이익'] = firstHalf['매출'] - firstHalf['비용']\n",
    "firstHalf = firstHalf.set_index(\"월\")\n",
    "firstHalf"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 연습 문제 5\n",
    "key1의 값을 기준으로 data1의 값을 분류하여 합계를 구한 결과를  \n",
    "시리즈가 아닌 데이터프레임으로 구한다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "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>key1</th>\n",
       "      <th>key2</th>\n",
       "      <th>data1</th>\n",
       "      <th>data2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>A</td>\n",
       "      <td>one</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>A</td>\n",
       "      <td>two</td>\n",
       "      <td>2</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>B</td>\n",
       "      <td>one</td>\n",
       "      <td>3</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>B</td>\n",
       "      <td>two</td>\n",
       "      <td>4</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>A</td>\n",
       "      <td>one</td>\n",
       "      <td>5</td>\n",
       "      <td>50</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  key1 key2  data1  data2\n",
       "0    A  one      1     10\n",
       "1    A  two      2     20\n",
       "2    B  one      3     30\n",
       "3    B  two      4     40\n",
       "4    A  one      5     50"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2 = pd.DataFrame({\n",
    "    'key1': ['A', 'A', 'B', 'B', 'A'],\n",
    "    'key2': ['one', 'two', 'one', 'two', 'one'],\n",
    "    'data1': [1, 2, 3, 4, 5],\n",
    "    'data2': [10, 20, 30, 40, 50]\n",
    "})\n",
    "df2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "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>data1</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>key1</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>A</th>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B</th>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      data1\n",
       "key1       \n",
       "A         8\n",
       "B         7"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2.groupby(df2.key1).sum()[[\"data1\"]]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 연습 문제 6\n",
    "붓꽃(iris) 데이터에서 붓꽃 종(species)별로 꽃잎길이(sepal_length),  \n",
    "꽃잎폭(sepal_width) 등의 평균을 구하라.  \n",
    "만약 붓꽃 종(species)이 표시되지 않았을 때 이 수치들을 이용하여  \n",
    "붓꽃 종을 찾아낼 수 있을지 생각하라."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "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>sepal_length</th>\n",
       "      <th>sepal_width</th>\n",
       "      <th>petal_length</th>\n",
       "      <th>petal_width</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>species</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>setosa</th>\n",
       "      <td>5.006</td>\n",
       "      <td>3.428</td>\n",
       "      <td>1.462</td>\n",
       "      <td>0.246</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>versicolor</th>\n",
       "      <td>5.936</td>\n",
       "      <td>2.770</td>\n",
       "      <td>4.260</td>\n",
       "      <td>1.326</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>virginica</th>\n",
       "      <td>6.588</td>\n",
       "      <td>2.974</td>\n",
       "      <td>5.552</td>\n",
       "      <td>2.026</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            sepal_length  sepal_width  petal_length  petal_width\n",
       "species                                                         \n",
       "setosa             5.006        3.428         1.462        0.246\n",
       "versicolor         5.936        2.770         4.260        1.326\n",
       "virginica          6.588        2.974         5.552        2.026"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "iris = sns.load_dataset(\"iris\")\n",
    "iris.groupby(iris.species).mean()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 연습 문제 7\n",
    "팁의 비율이 요일과 점심/저녁 여부, 인원수에 어떤 영향을 받는지 살펴본다.  \n",
    "어떤 요인이 가장 크게 작용하는지 판단할 수 있는 방법이 있는가?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "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>total_bill</th>\n",
       "      <th>tip</th>\n",
       "      <th>sex</th>\n",
       "      <th>smoker</th>\n",
       "      <th>day</th>\n",
       "      <th>time</th>\n",
       "      <th>size</th>\n",
       "      <th>tip_pct</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>239</th>\n",
       "      <td>29.03</td>\n",
       "      <td>5.92</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sat</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>3</td>\n",
       "      <td>20.39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>240</th>\n",
       "      <td>27.18</td>\n",
       "      <td>2.00</td>\n",
       "      <td>Female</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Sat</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "      <td>7.36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>241</th>\n",
       "      <td>22.67</td>\n",
       "      <td>2.00</td>\n",
       "      <td>Male</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Sat</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "      <td>8.82</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>242</th>\n",
       "      <td>17.82</td>\n",
       "      <td>1.75</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sat</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "      <td>9.82</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>243</th>\n",
       "      <td>18.78</td>\n",
       "      <td>3.00</td>\n",
       "      <td>Female</td>\n",
       "      <td>No</td>\n",
       "      <td>Thur</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "      <td>15.97</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     total_bill   tip     sex smoker   day    time  size  tip_pct\n",
       "239       29.03  5.92    Male     No   Sat  Dinner     3    20.39\n",
       "240       27.18  2.00  Female    Yes   Sat  Dinner     2     7.36\n",
       "241       22.67  2.00    Male    Yes   Sat  Dinner     2     8.82\n",
       "242       17.82  1.75    Male     No   Sat  Dinner     2     9.82\n",
       "243       18.78  3.00  Female     No  Thur  Dinner     2    15.97"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "tips = sns.load_dataset(\"tips\")\n",
    "tips['tip_pct'] = (tips['tip'] / tips['total_bill'] * 100).round(2)\n",
    "tips.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "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",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>tip_pct</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>day</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Thur</th>\n",
       "      <td>16.126452</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Fri</th>\n",
       "      <td>16.991579</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sat</th>\n",
       "      <td>15.314598</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sun</th>\n",
       "      <td>16.689605</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        tip_pct\n",
       "day            \n",
       "Thur  16.126452\n",
       "Fri   16.991579\n",
       "Sat   15.314598\n",
       "Sun   16.689605"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tips.pivot_table('tip_pct','day')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "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>tip_pct</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>time</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Lunch</th>\n",
       "      <td>16.411765</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dinner</th>\n",
       "      <td>15.951477</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          tip_pct\n",
       "time             \n",
       "Lunch   16.411765\n",
       "Dinner  15.951477"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tips.pivot_table('tip_pct','time')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>tip_pct</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>size</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>21.727500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>16.571410</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>15.214737</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>14.594865</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>14.152000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>15.620000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        tip_pct\n",
       "size           \n",
       "1     21.727500\n",
       "2     16.571410\n",
       "3     15.214737\n",
       "4     14.594865\n",
       "5     14.152000\n",
       "6     15.620000"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tips.pivot_table('tip_pct','size')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
       "    .dataframe thead tr:last-of-type th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th colspan=\"8\" halign=\"left\">tip_pct</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>size</th>\n",
       "      <th>day</th>\n",
       "      <th>time</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">1</th>\n",
       "      <th>Thur</th>\n",
       "      <th>Lunch</th>\n",
       "      <td>1.0</td>\n",
       "      <td>18.170000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>18.17</td>\n",
       "      <td>18.1700</td>\n",
       "      <td>18.17</td>\n",
       "      <td>18.1700</td>\n",
       "      <td>18.17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Fri</th>\n",
       "      <th>Lunch</th>\n",
       "      <td>1.0</td>\n",
       "      <td>22.380000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>22.38</td>\n",
       "      <td>22.3800</td>\n",
       "      <td>22.38</td>\n",
       "      <td>22.3800</td>\n",
       "      <td>22.38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sat</th>\n",
       "      <th>Dinner</th>\n",
       "      <td>2.0</td>\n",
       "      <td>23.180000</td>\n",
       "      <td>13.279465</td>\n",
       "      <td>13.79</td>\n",
       "      <td>18.4850</td>\n",
       "      <td>23.18</td>\n",
       "      <td>27.8750</td>\n",
       "      <td>32.57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"6\" valign=\"top\">2</th>\n",
       "      <th rowspan=\"2\" valign=\"top\">Thur</th>\n",
       "      <th>Lunch</th>\n",
       "      <td>47.0</td>\n",
       "      <td>16.401277</td>\n",
       "      <td>3.770712</td>\n",
       "      <td>7.86</td>\n",
       "      <td>13.9800</td>\n",
       "      <td>15.38</td>\n",
       "      <td>19.1950</td>\n",
       "      <td>26.63</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dinner</th>\n",
       "      <td>1.0</td>\n",
       "      <td>15.970000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15.97</td>\n",
       "      <td>15.9700</td>\n",
       "      <td>15.97</td>\n",
       "      <td>15.9700</td>\n",
       "      <td>15.97</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">Fri</th>\n",
       "      <th>Lunch</th>\n",
       "      <td>5.0</td>\n",
       "      <td>18.196000</td>\n",
       "      <td>5.285431</td>\n",
       "      <td>11.77</td>\n",
       "      <td>15.3700</td>\n",
       "      <td>18.09</td>\n",
       "      <td>19.8200</td>\n",
       "      <td>25.93</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dinner</th>\n",
       "      <td>11.0</td>\n",
       "      <td>16.267273</td>\n",
       "      <td>4.741030</td>\n",
       "      <td>10.36</td>\n",
       "      <td>13.3750</td>\n",
       "      <td>14.66</td>\n",
       "      <td>18.4500</td>\n",
       "      <td>26.35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sat</th>\n",
       "      <th>Dinner</th>\n",
       "      <td>53.0</td>\n",
       "      <td>15.528679</td>\n",
       "      <td>5.039191</td>\n",
       "      <td>3.56</td>\n",
       "      <td>12.9400</td>\n",
       "      <td>15.52</td>\n",
       "      <td>18.8400</td>\n",
       "      <td>29.20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sun</th>\n",
       "      <th>Dinner</th>\n",
       "      <td>39.0</td>\n",
       "      <td>18.086410</td>\n",
       "      <td>10.824426</td>\n",
       "      <td>5.94</td>\n",
       "      <td>12.1050</td>\n",
       "      <td>16.63</td>\n",
       "      <td>20.2900</td>\n",
       "      <td>71.03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">3</th>\n",
       "      <th>Thur</th>\n",
       "      <th>Lunch</th>\n",
       "      <td>4.0</td>\n",
       "      <td>14.460000</td>\n",
       "      <td>7.065942</td>\n",
       "      <td>7.30</td>\n",
       "      <td>8.9875</td>\n",
       "      <td>14.58</td>\n",
       "      <td>20.0525</td>\n",
       "      <td>21.38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Fri</th>\n",
       "      <th>Lunch</th>\n",
       "      <td>1.0</td>\n",
       "      <td>18.770000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>18.77</td>\n",
       "      <td>18.7700</td>\n",
       "      <td>18.77</td>\n",
       "      <td>18.7700</td>\n",
       "      <td>18.77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sat</th>\n",
       "      <th>Dinner</th>\n",
       "      <td>18.0</td>\n",
       "      <td>15.142222</td>\n",
       "      <td>4.429456</td>\n",
       "      <td>5.64</td>\n",
       "      <td>12.8725</td>\n",
       "      <td>15.35</td>\n",
       "      <td>17.9900</td>\n",
       "      <td>23.07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sun</th>\n",
       "      <th>Dinner</th>\n",
       "      <td>15.0</td>\n",
       "      <td>15.266000</td>\n",
       "      <td>4.358894</td>\n",
       "      <td>7.18</td>\n",
       "      <td>13.2650</td>\n",
       "      <td>16.05</td>\n",
       "      <td>17.0350</td>\n",
       "      <td>22.77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">4</th>\n",
       "      <th>Thur</th>\n",
       "      <th>Lunch</th>\n",
       "      <td>5.0</td>\n",
       "      <td>14.552000</td>\n",
       "      <td>3.121437</td>\n",
       "      <td>11.60</td>\n",
       "      <td>12.1300</td>\n",
       "      <td>14.71</td>\n",
       "      <td>14.8400</td>\n",
       "      <td>19.48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Fri</th>\n",
       "      <th>Dinner</th>\n",
       "      <td>1.0</td>\n",
       "      <td>11.770000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11.77</td>\n",
       "      <td>11.7700</td>\n",
       "      <td>11.77</td>\n",
       "      <td>11.7700</td>\n",
       "      <td>11.77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sat</th>\n",
       "      <th>Dinner</th>\n",
       "      <td>13.0</td>\n",
       "      <td>13.828462</td>\n",
       "      <td>4.610869</td>\n",
       "      <td>7.75</td>\n",
       "      <td>10.2500</td>\n",
       "      <td>13.62</td>\n",
       "      <td>18.6200</td>\n",
       "      <td>20.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sun</th>\n",
       "      <th>Dinner</th>\n",
       "      <td>18.0</td>\n",
       "      <td>15.317222</td>\n",
       "      <td>4.390685</td>\n",
       "      <td>8.15</td>\n",
       "      <td>12.6425</td>\n",
       "      <td>14.97</td>\n",
       "      <td>16.9700</td>\n",
       "      <td>28.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">5</th>\n",
       "      <th>Thur</th>\n",
       "      <th>Lunch</th>\n",
       "      <td>1.0</td>\n",
       "      <td>12.140000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12.14</td>\n",
       "      <td>12.1400</td>\n",
       "      <td>12.14</td>\n",
       "      <td>12.1400</td>\n",
       "      <td>12.14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sat</th>\n",
       "      <th>Dinner</th>\n",
       "      <td>1.0</td>\n",
       "      <td>10.660000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.66</td>\n",
       "      <td>10.6600</td>\n",
       "      <td>10.66</td>\n",
       "      <td>10.6600</td>\n",
       "      <td>10.66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sun</th>\n",
       "      <th>Dinner</th>\n",
       "      <td>3.0</td>\n",
       "      <td>15.986667</td>\n",
       "      <td>8.864583</td>\n",
       "      <td>6.57</td>\n",
       "      <td>11.8950</td>\n",
       "      <td>17.22</td>\n",
       "      <td>20.6950</td>\n",
       "      <td>24.17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">6</th>\n",
       "      <th>Thur</th>\n",
       "      <th>Lunch</th>\n",
       "      <td>3.0</td>\n",
       "      <td>17.366667</td>\n",
       "      <td>2.885833</td>\n",
       "      <td>14.09</td>\n",
       "      <td>16.2850</td>\n",
       "      <td>18.48</td>\n",
       "      <td>19.0050</td>\n",
       "      <td>19.53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sun</th>\n",
       "      <th>Dinner</th>\n",
       "      <td>1.0</td>\n",
       "      <td>10.380000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.38</td>\n",
       "      <td>10.3800</td>\n",
       "      <td>10.38</td>\n",
       "      <td>10.3800</td>\n",
       "      <td>10.38</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 tip_pct                                               \\\n",
       "                   count       mean        std    min      25%    50%   \n",
       "size day  time                                                          \n",
       "1    Thur Lunch      1.0  18.170000        NaN  18.17  18.1700  18.17   \n",
       "     Fri  Lunch      1.0  22.380000        NaN  22.38  22.3800  22.38   \n",
       "     Sat  Dinner     2.0  23.180000  13.279465  13.79  18.4850  23.18   \n",
       "2    Thur Lunch     47.0  16.401277   3.770712   7.86  13.9800  15.38   \n",
       "          Dinner     1.0  15.970000        NaN  15.97  15.9700  15.97   \n",
       "     Fri  Lunch      5.0  18.196000   5.285431  11.77  15.3700  18.09   \n",
       "          Dinner    11.0  16.267273   4.741030  10.36  13.3750  14.66   \n",
       "     Sat  Dinner    53.0  15.528679   5.039191   3.56  12.9400  15.52   \n",
       "     Sun  Dinner    39.0  18.086410  10.824426   5.94  12.1050  16.63   \n",
       "3    Thur Lunch      4.0  14.460000   7.065942   7.30   8.9875  14.58   \n",
       "     Fri  Lunch      1.0  18.770000        NaN  18.77  18.7700  18.77   \n",
       "     Sat  Dinner    18.0  15.142222   4.429456   5.64  12.8725  15.35   \n",
       "     Sun  Dinner    15.0  15.266000   4.358894   7.18  13.2650  16.05   \n",
       "4    Thur Lunch      5.0  14.552000   3.121437  11.60  12.1300  14.71   \n",
       "     Fri  Dinner     1.0  11.770000        NaN  11.77  11.7700  11.77   \n",
       "     Sat  Dinner    13.0  13.828462   4.610869   7.75  10.2500  13.62   \n",
       "     Sun  Dinner    18.0  15.317222   4.390685   8.15  12.6425  14.97   \n",
       "5    Thur Lunch      1.0  12.140000        NaN  12.14  12.1400  12.14   \n",
       "     Sat  Dinner     1.0  10.660000        NaN  10.66  10.6600  10.66   \n",
       "     Sun  Dinner     3.0  15.986667   8.864583   6.57  11.8950  17.22   \n",
       "6    Thur Lunch      3.0  17.366667   2.885833  14.09  16.2850  18.48   \n",
       "     Sun  Dinner     1.0  10.380000        NaN  10.38  10.3800  10.38   \n",
       "\n",
       "                                  \n",
       "                      75%    max  \n",
       "size day  time                    \n",
       "1    Thur Lunch   18.1700  18.17  \n",
       "     Fri  Lunch   22.3800  22.38  \n",
       "     Sat  Dinner  27.8750  32.57  \n",
       "2    Thur Lunch   19.1950  26.63  \n",
       "          Dinner  15.9700  15.97  \n",
       "     Fri  Lunch   19.8200  25.93  \n",
       "          Dinner  18.4500  26.35  \n",
       "     Sat  Dinner  18.8400  29.20  \n",
       "     Sun  Dinner  20.2900  71.03  \n",
       "3    Thur Lunch   20.0525  21.38  \n",
       "     Fri  Lunch   18.7700  18.77  \n",
       "     Sat  Dinner  17.9900  23.07  \n",
       "     Sun  Dinner  17.0350  22.77  \n",
       "4    Thur Lunch   14.8400  19.48  \n",
       "     Fri  Dinner  11.7700  11.77  \n",
       "     Sat  Dinner  18.6200  20.56  \n",
       "     Sun  Dinner  16.9700  28.05  \n",
       "5    Thur Lunch   12.1400  12.14  \n",
       "     Sat  Dinner  10.6600  10.66  \n",
       "     Sun  Dinner  20.6950  24.17  \n",
       "6    Thur Lunch   19.0050  19.53  \n",
       "     Sun  Dinner  10.3800  10.38  "
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tips.groupby([\"size\",\"day\", \"time\"])[[\"tip_pct\"]].describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 연습 문제 8\n",
    "타이타닉 승객 데이터를 이용하여 다음 분석을 실시하라. 데이터는 다음과 같이 받을 수 있다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>survived</th>\n",
       "      <th>pclass</th>\n",
       "      <th>sex</th>\n",
       "      <th>age</th>\n",
       "      <th>sibsp</th>\n",
       "      <th>parch</th>\n",
       "      <th>fare</th>\n",
       "      <th>embarked</th>\n",
       "      <th>class</th>\n",
       "      <th>who</th>\n",
       "      <th>adult_male</th>\n",
       "      <th>deck</th>\n",
       "      <th>embark_town</th>\n",
       "      <th>alive</th>\n",
       "      <th>alone</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>male</td>\n",
       "      <td>22.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>7.2500</td>\n",
       "      <td>S</td>\n",
       "      <td>Third</td>\n",
       "      <td>man</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Southampton</td>\n",
       "      <td>no</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>38.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>71.2833</td>\n",
       "      <td>C</td>\n",
       "      <td>First</td>\n",
       "      <td>woman</td>\n",
       "      <td>False</td>\n",
       "      <td>C</td>\n",
       "      <td>Cherbourg</td>\n",
       "      <td>yes</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>female</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7.9250</td>\n",
       "      <td>S</td>\n",
       "      <td>Third</td>\n",
       "      <td>woman</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Southampton</td>\n",
       "      <td>yes</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>35.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>53.1000</td>\n",
       "      <td>S</td>\n",
       "      <td>First</td>\n",
       "      <td>woman</td>\n",
       "      <td>False</td>\n",
       "      <td>C</td>\n",
       "      <td>Southampton</td>\n",
       "      <td>yes</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>male</td>\n",
       "      <td>35.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8.0500</td>\n",
       "      <td>S</td>\n",
       "      <td>Third</td>\n",
       "      <td>man</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Southampton</td>\n",
       "      <td>no</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   survived  pclass     sex   age  sibsp  parch     fare embarked  class  \\\n",
       "0         0       3    male  22.0      1      0   7.2500        S  Third   \n",
       "1         1       1  female  38.0      1      0  71.2833        C  First   \n",
       "2         1       3  female  26.0      0      0   7.9250        S  Third   \n",
       "3         1       1  female  35.0      1      0  53.1000        S  First   \n",
       "4         0       3    male  35.0      0      0   8.0500        S  Third   \n",
       "\n",
       "     who  adult_male deck  embark_town alive  alone  \n",
       "0    man        True  NaN  Southampton    no  False  \n",
       "1  woman       False    C    Cherbourg   yes  False  \n",
       "2  woman       False  NaN  Southampton   yes   True  \n",
       "3  woman       False    C  Southampton   yes  False  \n",
       "4    man        True  NaN  Southampton    no   True  "
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic = sns.load_dataset(\"titanic\")\n",
    "titanic.describe()\n",
    "titanic.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1) qcut 명령으로 세 개의 나이 그룹을 만든다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\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>survived</th>\n",
       "      <th>pclass</th>\n",
       "      <th>sex</th>\n",
       "      <th>age</th>\n",
       "      <th>sibsp</th>\n",
       "      <th>parch</th>\n",
       "      <th>fare</th>\n",
       "      <th>embarked</th>\n",
       "      <th>class</th>\n",
       "      <th>who</th>\n",
       "      <th>adult_male</th>\n",
       "      <th>deck</th>\n",
       "      <th>embark_town</th>\n",
       "      <th>alive</th>\n",
       "      <th>alone</th>\n",
       "      <th>age_group</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>male</td>\n",
       "      <td>22.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>7.2500</td>\n",
       "      <td>S</td>\n",
       "      <td>Third</td>\n",
       "      <td>man</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Southampton</td>\n",
       "      <td>no</td>\n",
       "      <td>False</td>\n",
       "      <td>young</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>38.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>71.2833</td>\n",
       "      <td>C</td>\n",
       "      <td>First</td>\n",
       "      <td>woman</td>\n",
       "      <td>False</td>\n",
       "      <td>C</td>\n",
       "      <td>Cherbourg</td>\n",
       "      <td>yes</td>\n",
       "      <td>False</td>\n",
       "      <td>old</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>female</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7.9250</td>\n",
       "      <td>S</td>\n",
       "      <td>Third</td>\n",
       "      <td>woman</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Southampton</td>\n",
       "      <td>yes</td>\n",
       "      <td>True</td>\n",
       "      <td>middle</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>35.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>53.1000</td>\n",
       "      <td>S</td>\n",
       "      <td>First</td>\n",
       "      <td>woman</td>\n",
       "      <td>False</td>\n",
       "      <td>C</td>\n",
       "      <td>Southampton</td>\n",
       "      <td>yes</td>\n",
       "      <td>False</td>\n",
       "      <td>old</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>male</td>\n",
       "      <td>35.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8.0500</td>\n",
       "      <td>S</td>\n",
       "      <td>Third</td>\n",
       "      <td>man</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Southampton</td>\n",
       "      <td>no</td>\n",
       "      <td>True</td>\n",
       "      <td>old</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   survived  pclass     sex   age  sibsp  parch     fare embarked  class  \\\n",
       "0         0       3    male  22.0      1      0   7.2500        S  Third   \n",
       "1         1       1  female  38.0      1      0  71.2833        C  First   \n",
       "2         1       3  female  26.0      0      0   7.9250        S  Third   \n",
       "3         1       1  female  35.0      1      0  53.1000        S  First   \n",
       "4         0       3    male  35.0      0      0   8.0500        S  Third   \n",
       "\n",
       "     who  adult_male deck  embark_town alive  alone age_group  \n",
       "0    man        True  NaN  Southampton    no  False     young  \n",
       "1  woman       False    C    Cherbourg   yes  False       old  \n",
       "2  woman       False  NaN  Southampton   yes   True    middle  \n",
       "3  woman       False    C  Southampton   yes  False       old  \n",
       "4    man        True  NaN  Southampton    no   True       old  "
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic['age_group'] = pd.qcut(titanic.age, 3, labels = ['young','middle','old'])\n",
    "titanic.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "2) 성별, 선실, 나이 그룹에 의한 생존율을 데이터프레임으로 계산한다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\n",
       "\n",
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       "        text-align: right;\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>age_group</th>\n",
       "      <th>young</th>\n",
       "      <th>middle</th>\n",
       "      <th>old</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sex</th>\n",
       "      <th>pclass</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">female</th>\n",
       "      <th>1</th>\n",
       "      <td>0.954545</td>\n",
       "      <td>0.947368</td>\n",
       "      <td>0.977273</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.909091</td>\n",
       "      <td>0.857143</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.508475</td>\n",
       "      <td>0.481481</td>\n",
       "      <td>0.250000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">male</th>\n",
       "      <th>1</th>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.347826</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.357143</td>\n",
       "      <td>0.076923</td>\n",
       "      <td>0.062500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.158879</td>\n",
       "      <td>0.195652</td>\n",
       "      <td>0.055556</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "age_group         young    middle       old\n",
       "sex    pclass                              \n",
       "female 1       0.954545  0.947368  0.977273\n",
       "       2       1.000000  0.909091  0.857143\n",
       "       3       0.508475  0.481481  0.250000\n",
       "male   1       0.500000  0.500000  0.347826\n",
       "       2       0.357143  0.076923  0.062500\n",
       "       3       0.158879  0.195652  0.055556"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic.pivot_table('survived', ['sex','pclass'], 'age_group', aggfunc='mean')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "3) 행에는 성별 및 나이 그룹에 대한 다중 인덱스를 사용하고 열에는 선실 인덱스를 사용한다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>pclass</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sex</th>\n",
       "      <th>age_group</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">female</th>\n",
       "      <th>young</th>\n",
       "      <td>0.954545</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.508475</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>middle</th>\n",
       "      <td>0.947368</td>\n",
       "      <td>0.909091</td>\n",
       "      <td>0.481481</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>old</th>\n",
       "      <td>0.977273</td>\n",
       "      <td>0.857143</td>\n",
       "      <td>0.250000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">male</th>\n",
       "      <th>young</th>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.357143</td>\n",
       "      <td>0.158879</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>middle</th>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.076923</td>\n",
       "      <td>0.195652</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>old</th>\n",
       "      <td>0.347826</td>\n",
       "      <td>0.062500</td>\n",
       "      <td>0.055556</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "pclass                   1         2         3\n",
       "sex    age_group                              \n",
       "female young      0.954545  1.000000  0.508475\n",
       "       middle     0.947368  0.909091  0.481481\n",
       "       old        0.977273  0.857143  0.250000\n",
       "male   young      0.500000  0.357143  0.158879\n",
       "       middle     0.500000  0.076923  0.195652\n",
       "       old        0.347826  0.062500  0.055556"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic.pivot_table('survived', ['sex', 'age_group'], 'pclass', aggfunc='mean')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "4) 성별 및 선실에 의한 생존율을 피봇 데이터 형태로 만든다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "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>pclass</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sex</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>female</th>\n",
       "      <td>0.968085</td>\n",
       "      <td>0.921053</td>\n",
       "      <td>0.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>male</th>\n",
       "      <td>0.368852</td>\n",
       "      <td>0.157407</td>\n",
       "      <td>0.135447</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "pclass         1         2         3\n",
       "sex                                 \n",
       "female  0.968085  0.921053  0.500000\n",
       "male    0.368852  0.157407  0.135447"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic.pivot_table('survived', 'sex', 'pclass', aggfunc='mean')"
   ]
  }
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