4장_판다스_데이터_분석_(4.6).ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "441442eb",
   "metadata": {},
   "source": [
    "# 데이터프레임 합성"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "ac4ecd04",
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>고객번호</th>\n",
       "      <th>이름</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1001</td>\n",
       "      <td>둘리</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1002</td>\n",
       "      <td>도우너</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1003</td>\n",
       "      <td>또치</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1004</td>\n",
       "      <td>길동</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1005</td>\n",
       "      <td>희동</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1006</td>\n",
       "      <td>마이콜</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>1007</td>\n",
       "      <td>영희</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   고객번호   이름\n",
       "0  1001   둘리\n",
       "1  1002  도우너\n",
       "2  1003   또치\n",
       "3  1004   길동\n",
       "4  1005   희동\n",
       "5  1006  마이콜\n",
       "6  1007   영희"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "df1 = pd.DataFrame({\n",
    "    '고객번호': [1001, 1002, 1003, 1004, 1005, 1006, 1007], \n",
    "    '이름': ['둘리', '도우너', '또치', '길동', '희동', '마이콜', '영희']\n",
    "}, columns = ['고객번호', '이름'])\n",
    "\n",
    "df1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "a624870c",
   "metadata": {},
   "outputs": [
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       "      <th>금액</th>\n",
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       "  </thead>\n",
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       "      <th>0</th>\n",
       "      <td>1001</td>\n",
       "      <td>10000</td>\n",
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       "      <th>1</th>\n",
       "      <td>1001</td>\n",
       "      <td>20000</td>\n",
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       "      <th>2</th>\n",
       "      <td>1005</td>\n",
       "      <td>15000</td>\n",
       "    </tr>\n",
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       "      <th>3</th>\n",
       "      <td>1006</td>\n",
       "      <td>5000</td>\n",
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       "      <th>4</th>\n",
       "      <td>1008</td>\n",
       "      <td>100000</td>\n",
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       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1001</td>\n",
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      "text/plain": [
       "   고객번호      금액\n",
       "0  1001   10000\n",
       "1  1001   20000\n",
       "2  1005   15000\n",
       "3  1006    5000\n",
       "4  1008  100000\n",
       "5  1001   30000"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2 = pd.DataFrame({\n",
    "    '고객번호': [1001, 1001, 1005, 1006, 1008, 1001],\n",
    "    '금액': [10000, 20000, 15000, 5000, 100000, 30000]\n",
    "}, columns=['고객번호', '금액'])\n",
    "df2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "9f1eb57e",
   "metadata": {},
   "outputs": [
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       "      <th>금액</th>\n",
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       "      <td>1001</td>\n",
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       "      <td>10000</td>\n",
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       "      <td>1001</td>\n",
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       "      <td>30000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1005</td>\n",
       "      <td>희동</td>\n",
       "      <td>15000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1006</td>\n",
       "      <td>마이콜</td>\n",
       "      <td>5000</td>\n",
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      "text/plain": [
       "   고객번호   이름     금액\n",
       "0  1001   둘리  10000\n",
       "1  1001   둘리  20000\n",
       "2  1001   둘리  30000\n",
       "3  1005   희동  15000\n",
       "4  1006  마이콜   5000"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.merge(df1, df2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "87fd1b83",
   "metadata": {},
   "outputs": [
    {
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       "      <th>고객번호</th>\n",
       "      <th>이름</th>\n",
       "      <th>금액</th>\n",
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       "      <td>1001</td>\n",
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       "      <th>3</th>\n",
       "      <td>1002</td>\n",
       "      <td>도우너</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1003</td>\n",
       "      <td>또치</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1004</td>\n",
       "      <td>길동</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>1005</td>\n",
       "      <td>희동</td>\n",
       "      <td>15000.0</td>\n",
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       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1006</td>\n",
       "      <td>마이콜</td>\n",
       "      <td>5000.0</td>\n",
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       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1007</td>\n",
       "      <td>영희</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>1008</td>\n",
       "      <td>NaN</td>\n",
       "      <td>100000.0</td>\n",
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      ],
      "text/plain": [
       "   고객번호   이름        금액\n",
       "0  1001   둘리   10000.0\n",
       "1  1001   둘리   20000.0\n",
       "2  1001   둘리   30000.0\n",
       "3  1002  도우너       NaN\n",
       "4  1003   또치       NaN\n",
       "5  1004   길동       NaN\n",
       "6  1005   희동   15000.0\n",
       "7  1006  마이콜    5000.0\n",
       "8  1007   영희       NaN\n",
       "9  1008  NaN  100000.0"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.merge(df1, df2, how = 'outer')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "c8975daf",
   "metadata": {},
   "outputs": [
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       "      <th>품종</th>\n",
       "      <th>꽃잎길이</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>setosa</td>\n",
       "      <td>1.4</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>setosa</td>\n",
       "      <td>1.3</td>\n",
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       "      <td>virginica</td>\n",
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       "          품종  꽃잎길이\n",
       "0     setosa   1.4\n",
       "1     setosa   1.3\n",
       "2  virginica   1.5\n",
       "3  virginica   1.3"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1 = pd.DataFrame({\n",
    "    '품종': ['setosa', 'setosa', 'virginica', 'virginica'],\n",
    "    '꽃잎길이': [1.4, 1.3, 1.5, 1.3]},\n",
    "    columns=['품종', '꽃잎길이'])\n",
    "df1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "7e32c2e4",
   "metadata": {},
   "outputs": [
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       "      <td>virginica</td>\n",
       "      <td>0.5</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>versicolor</td>\n",
       "      <td>0.3</td>\n",
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       "</table>\n",
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      ],
      "text/plain": [
       "           품종  꽃잎너비\n",
       "0      setosa   0.4\n",
       "1   virginica   0.3\n",
       "2   virginica   0.5\n",
       "3  versicolor   0.3"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2 = pd.DataFrame({\n",
    "    '품종': ['setosa', 'virginica', 'virginica', 'versicolor'],\n",
    "    '꽃잎너비': [0.4, 0.3, 0.5, 0.3]},\n",
    "    columns=['품종', '꽃잎너비'])\n",
    "df2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "18b4e985",
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    "scrolled": true
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   "outputs": [
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>setosa</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>virginica</td>\n",
       "      <td>1.5</td>\n",
       "      <td>0.3</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>virginica</td>\n",
       "      <td>1.5</td>\n",
       "      <td>0.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>virginica</td>\n",
       "      <td>1.3</td>\n",
       "      <td>0.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>virginica</td>\n",
       "      <td>1.3</td>\n",
       "      <td>0.5</td>\n",
       "    </tr>\n",
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       "</table>\n",
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      ],
      "text/plain": [
       "          품종  꽃잎길이  꽃잎너비\n",
       "0     setosa   1.4   0.4\n",
       "1     setosa   1.3   0.4\n",
       "2  virginica   1.5   0.3\n",
       "3  virginica   1.5   0.5\n",
       "4  virginica   1.3   0.3\n",
       "5  virginica   1.3   0.5"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.merge(df1, df2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "399b5eb4",
   "metadata": {},
   "outputs": [
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       "      <th>고객명</th>\n",
       "      <th>날짜</th>\n",
       "      <th>데이터</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>춘향</td>\n",
       "      <td>2018-01-01</td>\n",
       "      <td>20000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>춘향</td>\n",
       "      <td>2018-01-02</td>\n",
       "      <td>30000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>몽룡</td>\n",
       "      <td>2018-01-01</td>\n",
       "      <td>100000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  고객명          날짜     데이터\n",
       "0  춘향  2018-01-01   20000\n",
       "1  춘향  2018-01-02   30000\n",
       "2  몽룡  2018-01-01  100000"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1 = pd.DataFrame({\n",
    "    '고객명': ['춘향', '춘향', '몽룡'],\n",
    "    '날짜': ['2018-01-01', '2018-01-02', '2018-01-01'],\n",
    "    '데이터': ['20000', '30000', '100000']})\n",
    "df1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "c353f30e",
   "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",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>고객명</th>\n",
       "      <th>데이터</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>춘향</td>\n",
       "      <td>여자</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>몽룡</td>\n",
       "      <td>남자</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  고객명 데이터\n",
       "0  춘향  여자\n",
       "1  몽룡  남자"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2 = pd.DataFrame({\n",
    "    '고객명': ['춘향', '몽룡'],\n",
    "    '데이터': ['여자', '남자']})\n",
    "df2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "c8b79b24",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>고객명</th>\n",
       "      <th>날짜</th>\n",
       "      <th>데이터_x</th>\n",
       "      <th>데이터_y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>춘향</td>\n",
       "      <td>2018-01-01</td>\n",
       "      <td>20000</td>\n",
       "      <td>여자</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>춘향</td>\n",
       "      <td>2018-01-02</td>\n",
       "      <td>30000</td>\n",
       "      <td>여자</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>몽룡</td>\n",
       "      <td>2018-01-01</td>\n",
       "      <td>100000</td>\n",
       "      <td>남자</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  고객명          날짜   데이터_x 데이터_y\n",
       "0  춘향  2018-01-01   20000    여자\n",
       "1  춘향  2018-01-02   30000    여자\n",
       "2  몽룡  2018-01-01  100000    남자"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.merge(df1, df2, on = \"고객명\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "efb968f9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>이름</th>\n",
       "      <th>성적</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>영희</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>철수</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>철수</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   이름  성적\n",
       "0  영희   1\n",
       "1  철수   2\n",
       "2  철수   3"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1 = pd.DataFrame({\n",
    "    '이름': ['영희', '철수', '철수'],\n",
    "    '성적': [1, 2, 3]})\n",
    "df1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "133adf27",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe thead th {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>성명</th>\n",
       "      <th>성적2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>영희</td>\n",
       "      <td>4</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>영희</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>철수</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   성명  성적2\n",
       "0  영희    4\n",
       "1  영희    5\n",
       "2  철수    6"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2 = pd.DataFrame({\n",
    "    '성명': ['영희', '영희', '철수'],\n",
    "    '성적2': [4, 5, 6]})\n",
    "df2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "8727baa2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>이름</th>\n",
       "      <th>성적</th>\n",
       "      <th>성명</th>\n",
       "      <th>성적2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>영희</td>\n",
       "      <td>1</td>\n",
       "      <td>영희</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>영희</td>\n",
       "      <td>1</td>\n",
       "      <td>영희</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>철수</td>\n",
       "      <td>2</td>\n",
       "      <td>철수</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>철수</td>\n",
       "      <td>3</td>\n",
       "      <td>철수</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   이름  성적  성명  성적2\n",
       "0  영희   1  영희    4\n",
       "1  영희   1  영희    5\n",
       "2  철수   2  철수    6\n",
       "3  철수   3  철수    6"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.merge(df1, df2, left_on = '이름', right_on = '성명')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "15e4bc4c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>도시</th>\n",
       "      <th>연도</th>\n",
       "      <th>인구</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>서울</td>\n",
       "      <td>2000</td>\n",
       "      <td>9853972</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>서울</td>\n",
       "      <td>2005</td>\n",
       "      <td>9762546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>서울</td>\n",
       "      <td>2010</td>\n",
       "      <td>9631482</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>부산</td>\n",
       "      <td>2000</td>\n",
       "      <td>3655437</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>부산</td>\n",
       "      <td>2005</td>\n",
       "      <td>3512547</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   도시    연도       인구\n",
       "0  서울  2000  9853972\n",
       "1  서울  2005  9762546\n",
       "2  서울  2010  9631482\n",
       "3  부산  2000  3655437\n",
       "4  부산  2005  3512547"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1 = pd.DataFrame({\n",
    "    '도시': ['서울', '서울', '서울', '부산', '부산'],\n",
    "    '연도': [2000, 2005, 2010, 2000, 2005],\n",
    "    '인구': [9853972, 9762546, 9631482, 3655437, 3512547]})\n",
    "df1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "4a77220e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>데이터1</th>\n",
       "      <th>데이터2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">부산</th>\n",
       "      <th>2000</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005</th>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">서울</th>\n",
       "      <th>2000</th>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005</th>\n",
       "      <td>6</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010</th>\n",
       "      <td>8</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015</th>\n",
       "      <td>10</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         데이터1  데이터2\n",
       "부산 2000     0     1\n",
       "   2005     2     3\n",
       "서울 2000     4     5\n",
       "   2005     6     7\n",
       "   2010     8     9\n",
       "   2015    10    11"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2 = pd.DataFrame(\n",
    "    np.arange(12).reshape((6, 2)),\n",
    "    index=[['부산', '부산', '서울', '서울', '서울', '서울'],\n",
    "           [2000, 2005, 2000, 2005, 2010, 2015]],\n",
    "    columns=['데이터1', '데이터2'])\n",
    "df2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "2acf2876",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
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       "      <th>도시</th>\n",
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       "      <th>인구</th>\n",
       "      <th>데이터1</th>\n",
       "      <th>데이터2</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
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       "      <td>2000</td>\n",
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       "      <th>1</th>\n",
       "      <td>서울</td>\n",
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       "      <td>9762546</td>\n",
       "      <td>6</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>서울</td>\n",
       "      <td>2010</td>\n",
       "      <td>9631482</td>\n",
       "      <td>8</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>부산</td>\n",
       "      <td>2000</td>\n",
       "      <td>3655437</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>부산</td>\n",
       "      <td>2005</td>\n",
       "      <td>3512547</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   도시    연도       인구  데이터1  데이터2\n",
       "0  서울  2000  9853972     4     5\n",
       "1  서울  2005  9762546     6     7\n",
       "2  서울  2010  9631482     8     9\n",
       "3  부산  2000  3655437     0     1\n",
       "4  부산  2005  3512547     2     3"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.merge(df1, df2, left_on = ['도시', '연도'], right_index = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "c30caf20",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <td>4.0</td>\n",
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       "    <tr>\n",
       "      <th>e</th>\n",
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       "      <td>6.0</td>\n",
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       "    서울   부산\n",
       "a  1.0  2.0\n",
       "c  3.0  4.0\n",
       "e  5.0  6.0"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
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   "source": [
    "df1 = pd.DataFrame(\n",
    "    [[1., 2.], [3., 4.], [5., 6.]],\n",
    "    index=['a', 'c', 'e'],\n",
    "    columns=['서울', '부산'])\n",
    "df1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "0903e1e8",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>대구</th>\n",
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       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>b</th>\n",
       "      <td>7.0</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>c</th>\n",
       "      <td>9.0</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>d</th>\n",
       "      <td>11.0</td>\n",
       "      <td>12.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>e</th>\n",
       "      <td>13.0</td>\n",
       "      <td>14.0</td>\n",
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       "  </tbody>\n",
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      "text/plain": [
       "     대구    광주\n",
       "b   7.0   8.0\n",
       "c   9.0  10.0\n",
       "d  11.0  12.0\n",
       "e  13.0  14.0"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2 = pd.DataFrame(\n",
    "    [[7., 8.], [9., 10.], [11., 12.], [13, 14]],\n",
    "    index=['b', 'c', 'd', 'e'],\n",
    "    columns=['대구', '광주'])\n",
    "df2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "8220e74c",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>b</th>\n",
       "      <td>NaN</td>\n",
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       "      <td>7.0</td>\n",
       "      <td>8.0</td>\n",
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       "      <th>c</th>\n",
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       "      <th>d</th>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>e</th>\n",
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       "      <td>13.0</td>\n",
       "      <td>14.0</td>\n",
       "    </tr>\n",
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       "</table>\n",
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      "text/plain": [
       "    서울   부산    대구    광주\n",
       "a  1.0  2.0   NaN   NaN\n",
       "b  NaN  NaN   7.0   8.0\n",
       "c  3.0  4.0   9.0  10.0\n",
       "d  NaN  NaN  11.0  12.0\n",
       "e  5.0  6.0  13.0  14.0"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.merge(df1, df2, how = 'outer', left_index=True, right_index=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "f5e31d24",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>e</th>\n",
       "      <td>5.0</td>\n",
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      ],
      "text/plain": [
       "    서울   부산    대구    광주\n",
       "a  1.0  2.0   NaN   NaN\n",
       "b  NaN  NaN   7.0   8.0\n",
       "c  3.0  4.0   9.0  10.0\n",
       "d  NaN  NaN  11.0  12.0\n",
       "e  5.0  6.0  13.0  14.0"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1.join(df2, how = 'outer')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "6526aa08",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[array([70,  9, 63, 54, 16]),\n",
       " array([59, 31, 50, 39, 66]),\n",
       " array([94, 72, 83, 73, 18]),\n",
       " array([85, 32,  1, 92, 66]),\n",
       " array([38, 79, 95, 17, 92])]"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data1 = []\n",
    "\n",
    "for i in range(5):\n",
    "    data1.append(np.random.randint(1,101, size = 5))\n",
    "    \n",
    "data1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "b8301640",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[array([ 83,  60, 101,  98,  14]),\n",
       " array([94, 65, 84, 22, 55]),\n",
       " array([83, 77, 11, 79, 77]),\n",
       " array([51, 86, 76, 47, 12]),\n",
       " array([ 42, 100,  38,  42,  69])]"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data2 = []\n",
    "\n",
    "for i in range(5):\n",
    "    data2.append(np.random.randint(1,102, size = 5))\n",
    "    \n",
    "data2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "9a729d0a",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>5</th>\n",
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      "text/plain": [
       "   국어  영어  수학  과학  사회\n",
       "1  70   9  63  54  16\n",
       "2  59  31  50  39  66\n",
       "3  94  72  83  73  18\n",
       "4  85  32   1  92  66\n",
       "5  38  79  95  17  92"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1 = pd.DataFrame(data1, \n",
    "                   index = [1,2,3,4,5], \n",
    "                   columns = [\"국어\", \"영어\", \"수학\", \"과학\", \"사회\"])\n",
    "df1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "bfc39873",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
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       "    국어   영어   수리  과학  사회\n",
       "6   83   60  101  98  14\n",
       "7   94   65   84  22  55\n",
       "8   83   77   11  79  77\n",
       "9   51   86   76  47  12\n",
       "10  42  100   38  42  69"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2 = pd.DataFrame(data2, \n",
    "                   index = [6,7,8,9,10], \n",
    "                   columns = [\"국어\", \"영어\", '수리', \"과학\", \"사회\"])\n",
    "df2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "512a2209",
   "metadata": {},
   "outputs": [
    {
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       "      <th>3</th>\n",
       "      <td>85</td>\n",
       "      <td>32</td>\n",
       "      <td>1.0</td>\n",
       "      <td>92</td>\n",
       "      <td>66</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>38</td>\n",
       "      <td>79</td>\n",
       "      <td>95.0</td>\n",
       "      <td>17</td>\n",
       "      <td>92</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>83</td>\n",
       "      <td>60</td>\n",
       "      <td>NaN</td>\n",
       "      <td>98</td>\n",
       "      <td>14</td>\n",
       "      <td>101.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>94</td>\n",
       "      <td>65</td>\n",
       "      <td>NaN</td>\n",
       "      <td>22</td>\n",
       "      <td>55</td>\n",
       "      <td>84.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>83</td>\n",
       "      <td>77</td>\n",
       "      <td>NaN</td>\n",
       "      <td>79</td>\n",
       "      <td>77</td>\n",
       "      <td>11.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>51</td>\n",
       "      <td>86</td>\n",
       "      <td>NaN</td>\n",
       "      <td>47</td>\n",
       "      <td>12</td>\n",
       "      <td>76.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>42</td>\n",
       "      <td>100</td>\n",
       "      <td>NaN</td>\n",
       "      <td>42</td>\n",
       "      <td>69</td>\n",
       "      <td>38.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   국어   영어    수학  과학  사회     수리\n",
       "0  70    9  63.0  54  16    NaN\n",
       "1  59   31  50.0  39  66    NaN\n",
       "2  94   72  83.0  73  18    NaN\n",
       "3  85   32   1.0  92  66    NaN\n",
       "4  38   79  95.0  17  92    NaN\n",
       "5  83   60   NaN  98  14  101.0\n",
       "6  94   65   NaN  22  55   84.0\n",
       "7  83   77   NaN  79  77   11.0\n",
       "8  51   86   NaN  47  12   76.0\n",
       "9  42  100   NaN  42  69   38.0"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.merge(df1, df2, how = \"outer\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "2aacbab2",
   "metadata": {},
   "outputs": [],
   "source": [
    "s1 = pd.Series([0, 1], index=['A', 'B'])\n",
    "s2 = pd.Series([2, 3, 4], index=['A', 'B', 'C'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "2f190824",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "A    0\n",
       "B    1\n",
       "dtype: int64"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "c7f4fcc6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "A    2\n",
       "B    3\n",
       "C    4\n",
       "dtype: int64"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "id": "13e9e8b7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "A    0\n",
       "B    1\n",
       "A    2\n",
       "B    3\n",
       "C    4\n",
       "dtype: int64"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.concat([s1, s2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "id": "f0e4cdaf",
   "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>데이터1</th>\n",
       "      <th>데이터2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>a</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>b</th>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>c</th>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   데이터1  데이터2\n",
       "a     0     1\n",
       "b     2     3\n",
       "c     4     5"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1 = pd.DataFrame(\n",
    "    np.arange(6).reshape(3, 2),\n",
    "    index=['a', 'b', 'c'],\n",
    "    columns=['데이터1', '데이터2'])\n",
    "df1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "id": "0bcf5c00",
   "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>데이터3</th>\n",
       "      <th>데이터4</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>a</th>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>c</th>\n",
       "      <td>7</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   데이터3  데이터4\n",
       "a     5     6\n",
       "c     7     8"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2 = pd.DataFrame(\n",
    "    5 + np.arange(4).reshape(2, 2),\n",
    "    index=['a', 'c'],\n",
    "    columns=['데이터3', '데이터4'])\n",
    "df2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "id": "321c97d3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .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>데이터1</th>\n",
       "      <th>데이터2</th>\n",
       "      <th>데이터3</th>\n",
       "      <th>데이터4</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>a</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>b</th>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>c</th>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>7.0</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   데이터1  데이터2  데이터3  데이터4\n",
       "a     0     1   5.0   6.0\n",
       "b     2     3   NaN   NaN\n",
       "c     4     5   7.0   8.0"
      ]
     },
     "execution_count": 88,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.concat([df1, df2], axis = 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "id": "d3c32683",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[array([11, 53]),\n",
       " array([77, 95]),\n",
       " array([ 2, 14]),\n",
       " array([93, 77]),\n",
       " array([75, 47]),\n",
       " array([34, 42])]"
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data1 = []\n",
    "\n",
    "for i in range(6):\n",
    "    data1.append(np.random.randint(1,101, size = 2))\n",
    "data1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "id": "db42b23a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[array([36, 87]),\n",
       " array([ 1, 46]),\n",
       " array([60, 54]),\n",
       " array([49, 82]),\n",
       " array([90, 11]),\n",
       " array([35, 96])]"
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data2 = []\n",
    "\n",
    "for i in range(6):\n",
    "    data2.append(np.random.randint(1,101, size = 2))\n",
    "data2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "id": "b4991662",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        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",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1월</th>\n",
       "      <td>11</td>\n",
       "      <td>53</td>\n",
       "      <td>-42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2월</th>\n",
       "      <td>77</td>\n",
       "      <td>95</td>\n",
       "      <td>-18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3월</th>\n",
       "      <td>2</td>\n",
       "      <td>14</td>\n",
       "      <td>-12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4월</th>\n",
       "      <td>93</td>\n",
       "      <td>77</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5월</th>\n",
       "      <td>75</td>\n",
       "      <td>47</td>\n",
       "      <td>28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6월</th>\n",
       "      <td>34</td>\n",
       "      <td>42</td>\n",
       "      <td>-8</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    매출  비용  이익\n",
       "1월  11  53 -42\n",
       "2월  77  95 -18\n",
       "3월   2  14 -12\n",
       "4월  93  77  16\n",
       "5월  75  47  28\n",
       "6월  34  42  -8"
      ]
     },
     "execution_count": 97,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1 = pd.DataFrame(data1, columns = [\"매출\", \"비용\"], \n",
    "                   index = ['1월', '2월', '3월', '4월', '5월', '6월'])\n",
    "df1[\"이익\"] = df1[\"매출\"] - df1[\"비용\"]\n",
    "df1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "id": "fe76e353",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    .dataframe tbody tr th {\n",
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       "\n",
       "    .dataframe thead th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
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       "    <tr style=\"text-align: right;\">\n",
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       "      <th>매출</th>\n",
       "      <th>비용</th>\n",
       "      <th>이익</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>7월</th>\n",
       "      <td>36</td>\n",
       "      <td>87</td>\n",
       "      <td>-51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8월</th>\n",
       "      <td>1</td>\n",
       "      <td>46</td>\n",
       "      <td>-45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9월</th>\n",
       "      <td>60</td>\n",
       "      <td>54</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10월</th>\n",
       "      <td>49</td>\n",
       "      <td>82</td>\n",
       "      <td>-33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11월</th>\n",
       "      <td>90</td>\n",
       "      <td>11</td>\n",
       "      <td>79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12월</th>\n",
       "      <td>35</td>\n",
       "      <td>96</td>\n",
       "      <td>-61</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     매출  비용  이익\n",
       "7월   36  87 -51\n",
       "8월    1  46 -45\n",
       "9월   60  54   6\n",
       "10월  49  82 -33\n",
       "11월  90  11  79\n",
       "12월  35  96 -61"
      ]
     },
     "execution_count": 98,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2 = pd.DataFrame(data2, columns = [\"매출\", \"비용\"], \n",
    "                   index = ['7월', '8월', '9월', '10월', '11월', '12월'])\n",
    "df2[\"이익\"] = df2[\"매출\"] - df2[\"비용\"]\n",
    "df2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "id": "6216dbec",
   "metadata": {},
   "outputs": [],
   "source": [
    "df3 = pd.concat([df1, df2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "id": "cbaed41e",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th>이익</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1월</th>\n",
       "      <td>11</td>\n",
       "      <td>53</td>\n",
       "      <td>-42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2월</th>\n",
       "      <td>77</td>\n",
       "      <td>95</td>\n",
       "      <td>-18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3월</th>\n",
       "      <td>2</td>\n",
       "      <td>14</td>\n",
       "      <td>-12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4월</th>\n",
       "      <td>93</td>\n",
       "      <td>77</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5월</th>\n",
       "      <td>75</td>\n",
       "      <td>47</td>\n",
       "      <td>28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6월</th>\n",
       "      <td>34</td>\n",
       "      <td>42</td>\n",
       "      <td>-8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7월</th>\n",
       "      <td>36</td>\n",
       "      <td>87</td>\n",
       "      <td>-51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8월</th>\n",
       "      <td>1</td>\n",
       "      <td>46</td>\n",
       "      <td>-45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9월</th>\n",
       "      <td>60</td>\n",
       "      <td>54</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10월</th>\n",
       "      <td>49</td>\n",
       "      <td>82</td>\n",
       "      <td>-33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11월</th>\n",
       "      <td>90</td>\n",
       "      <td>11</td>\n",
       "      <td>79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12월</th>\n",
       "      <td>35</td>\n",
       "      <td>96</td>\n",
       "      <td>-61</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     매출  비용  이익\n",
       "1월   11  53 -42\n",
       "2월   77  95 -18\n",
       "3월    2  14 -12\n",
       "4월   93  77  16\n",
       "5월   75  47  28\n",
       "6월   34  42  -8\n",
       "7월   36  87 -51\n",
       "8월    1  46 -45\n",
       "9월   60  54   6\n",
       "10월  49  82 -33\n",
       "11월  90  11  79\n",
       "12월  35  96 -61"
      ]
     },
     "execution_count": 101,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "id": "67d4cbcd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        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>매출</th>\n",
       "      <th>비용</th>\n",
       "      <th>이익</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1월</th>\n",
       "      <td>11</td>\n",
       "      <td>53</td>\n",
       "      <td>-42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2월</th>\n",
       "      <td>77</td>\n",
       "      <td>95</td>\n",
       "      <td>-18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3월</th>\n",
       "      <td>2</td>\n",
       "      <td>14</td>\n",
       "      <td>-12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4월</th>\n",
       "      <td>93</td>\n",
       "      <td>77</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5월</th>\n",
       "      <td>75</td>\n",
       "      <td>47</td>\n",
       "      <td>28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6월</th>\n",
       "      <td>34</td>\n",
       "      <td>42</td>\n",
       "      <td>-8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7월</th>\n",
       "      <td>36</td>\n",
       "      <td>87</td>\n",
       "      <td>-51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8월</th>\n",
       "      <td>1</td>\n",
       "      <td>46</td>\n",
       "      <td>-45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9월</th>\n",
       "      <td>60</td>\n",
       "      <td>54</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10월</th>\n",
       "      <td>49</td>\n",
       "      <td>82</td>\n",
       "      <td>-33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11월</th>\n",
       "      <td>90</td>\n",
       "      <td>11</td>\n",
       "      <td>79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12월</th>\n",
       "      <td>35</td>\n",
       "      <td>96</td>\n",
       "      <td>-61</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>총실적</th>\n",
       "      <td>563</td>\n",
       "      <td>704</td>\n",
       "      <td>-141</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      매출   비용   이익\n",
       "1월    11   53  -42\n",
       "2월    77   95  -18\n",
       "3월     2   14  -12\n",
       "4월    93   77   16\n",
       "5월    75   47   28\n",
       "6월    34   42   -8\n",
       "7월    36   87  -51\n",
       "8월     1   46  -45\n",
       "9월    60   54    6\n",
       "10월   49   82  -33\n",
       "11월   90   11   79\n",
       "12월   35   96  -61\n",
       "총실적  563  704 -141"
      ]
     },
     "execution_count": 117,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df3.loc['총실적'] = df3.sum()\n",
    "df3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d1240c48",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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