2.5.데이터 결합.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 데이터 결합\n",
    "R과 다른점 : 결합하려는 데이터프레임의 행과 열의 개수가 맞지 않아도 NaN값이 채워짐\n",
    "## 행결합\n",
    "### 데이터프레임 붙이기 : pd.concat()\n",
    "\n",
    "\n",
    "    행인덱스와 열인덱스가 다른 데이터프레임 합치기     \n",
    "    * pd.concat([df1, df2, ...], axis=0)     \n",
    "    ignore_index=True를 붙이면 인덱스 재배열 가능"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "\n",
    "customer1 = pd.DataFrame({'id':['c01', 'c02', 'c03', 'c04'],\n",
    "                        'last_name':[\"Lee\",\"Kim\",\"Choi\",\"Park\"]},\n",
    "                        index = [0,1, 2,3])\n",
    "\n",
    "customer2 = pd.DataFrame({'Id':['c05','c06','c07'],\n",
    "                         'Last_name':['Lim', 'Bae', 'Kim'],\n",
    "                         'age':[23, 34, 45]},\n",
    "                        index = [0, 1, 2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>last_name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>c01</td>\n",
       "      <td>Lee</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>c02</td>\n",
       "      <td>Kim</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>c03</td>\n",
       "      <td>Choi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>c04</td>\n",
       "      <td>Park</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "    id last_name\n",
       "0  c01       Lee\n",
       "1  c02       Kim\n",
       "2  c03      Choi\n",
       "3  c04      Park"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "customer1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Id</th>\n",
       "      <th>Last_name</th>\n",
       "      <th>age</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>c05</td>\n",
       "      <td>Lim</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>c06</td>\n",
       "      <td>Bae</td>\n",
       "      <td>34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>c07</td>\n",
       "      <td>Kim</td>\n",
       "      <td>45</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      "text/plain": [
       "    Id Last_name  age\n",
       "0  c05       Lim   23\n",
       "1  c06       Bae   34\n",
       "2  c07       Kim   45"
      ]
     },
     "execution_count": 3,
     "metadata": {},
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   ],
   "source": [
    "customer2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "customer2.columns =['id','last_name','age']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
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       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>last_name</th>\n",
       "      <th>age</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>c05</td>\n",
       "      <td>Lim</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>c06</td>\n",
       "      <td>Bae</td>\n",
       "      <td>34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>c07</td>\n",
       "      <td>Kim</td>\n",
       "      <td>45</td>\n",
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      "text/plain": [
       "    id last_name  age\n",
       "0  c05       Lim   23\n",
       "1  c06       Bae   34\n",
       "2  c07       Kim   45"
      ]
     },
     "execution_count": 5,
     "metadata": {},
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    "customer2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
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       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>last_name</th>\n",
       "      <th>age</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>c01</td>\n",
       "      <td>Lee</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>c02</td>\n",
       "      <td>Kim</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>c03</td>\n",
       "      <td>Choi</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>c04</td>\n",
       "      <td>Park</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>c05</td>\n",
       "      <td>Lim</td>\n",
       "      <td>23.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>c06</td>\n",
       "      <td>Bae</td>\n",
       "      <td>34.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>c07</td>\n",
       "      <td>Kim</td>\n",
       "      <td>45.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      "text/plain": [
       "    id last_name   age\n",
       "0  c01       Lee   NaN\n",
       "1  c02       Kim   NaN\n",
       "2  c03      Choi   NaN\n",
       "3  c04      Park   NaN\n",
       "0  c05       Lim  23.0\n",
       "1  c06       Bae  34.0\n",
       "2  c07       Kim  45.0"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# default 값으로 axis=0이 적용되어 행방향으로 데이터프레임을 붙임     \n",
    "# customer1에는 age열이 없으므로 NaN값이 채워짐      \n",
    "\n",
    "pd.concat([customer1,customer2])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "customer = pd.concat([customer1,customer2]).reset_index(drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
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       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>last_name</th>\n",
       "      <th>age</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>c01</td>\n",
       "      <td>Lee</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>c02</td>\n",
       "      <td>Kim</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>c03</td>\n",
       "      <td>Choi</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>c04</td>\n",
       "      <td>Park</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>c05</td>\n",
       "      <td>Lim</td>\n",
       "      <td>23.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>c06</td>\n",
       "      <td>Bae</td>\n",
       "      <td>34.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>c07</td>\n",
       "      <td>Kim</td>\n",
       "      <td>45.0</td>\n",
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      "text/plain": [
       "    id last_name   age\n",
       "0  c01       Lee   NaN\n",
       "1  c02       Kim   NaN\n",
       "2  c03      Choi   NaN\n",
       "3  c04      Park   NaN\n",
       "4  c05       Lim  23.0\n",
       "5  c06       Bae  34.0\n",
       "6  c07       Kim  45.0"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "customer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>last_name</th>\n",
       "      <th>age</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>c01</td>\n",
       "      <td>Lee</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>c02</td>\n",
       "      <td>Kim</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>c03</td>\n",
       "      <td>Choi</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>c04</td>\n",
       "      <td>Park</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>c05</td>\n",
       "      <td>Lim</td>\n",
       "      <td>23.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>c06</td>\n",
       "      <td>Bae</td>\n",
       "      <td>34.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>c07</td>\n",
       "      <td>Kim</td>\n",
       "      <td>45.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      "text/plain": [
       "    id last_name   age\n",
       "0  c01       Lee   NaN\n",
       "1  c02       Kim   NaN\n",
       "2  c03      Choi   NaN\n",
       "3  c04      Park   NaN\n",
       "4  c05       Lim  23.0\n",
       "5  c06       Bae  34.0\n",
       "6  c07       Kim  45.0"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## reset_index를 쓰지 않고 바로 인덱스 재배열 하는 방법\n",
    "\n",
    "result = pd.concat([customer1, customer2],ignore_index=True)\n",
    "result"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 열결합"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 데이터프레임 붙이기 : pd.concat()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "행인덱스와 열인덱스가 다른 데이터프레임 합치기     \n",
    "* pd.concat([df1, df2, ...], axis=1)     \n",
    "    \n",
    "axis=1은 열방향으로 데이터프레임을 붙임     \n",
    "customer2에는 index 3행이 없으므로 NaN값이 채워짐      "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>last_name</th>\n",
       "      <th>age</th>\n",
       "      <th>id</th>\n",
       "      <th>last_name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>c05</td>\n",
       "      <td>Lim</td>\n",
       "      <td>23.0</td>\n",
       "      <td>c01</td>\n",
       "      <td>Lee</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>c06</td>\n",
       "      <td>Bae</td>\n",
       "      <td>34.0</td>\n",
       "      <td>c02</td>\n",
       "      <td>Kim</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>c07</td>\n",
       "      <td>Kim</td>\n",
       "      <td>45.0</td>\n",
       "      <td>c03</td>\n",
       "      <td>Choi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>c04</td>\n",
       "      <td>Park</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    id last_name   age   id last_name\n",
       "0  c05       Lim  23.0  c01       Lee\n",
       "1  c06       Bae  34.0  c02       Kim\n",
       "2  c07       Kim  45.0  c03      Choi\n",
       "3  NaN       NaN   NaN  c04      Park"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result2 = pd.concat([customer2,customer1], axis=1)\n",
    "result2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 시리즈를 데이터프레임에 붙이기 : pd.concat()\n",
    "시리즈 객체를 생성할 때 name은, 이 시리즈가 데이터프레임이 결합되었을 때의 열이름을 나타냄"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "grade = pd.Series(['A', 'B', 'C','A', 'D', 'C', 'B'], name='grade')\n",
    "grade2 = pd.Series(['A', 'B', 'C','A', 'D', 'C'], name='grade')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "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>grade</th>\n",
       "      <th>grade</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>A</td>\n",
       "      <td>A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>B</td>\n",
       "      <td>B</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>C</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>A</td>\n",
       "      <td>A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>D</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>C</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>B</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  grade grade\n",
       "0     A     A\n",
       "1     B     B\n",
       "2     C     C\n",
       "3     A     A\n",
       "4     D     D\n",
       "5     C     C\n",
       "6     B   NaN"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result3 = pd.concat([grade, grade2], axis=1)\n",
    "result3"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 시리즈끼리 붙이기 : pd.concat()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "    e   g\n",
      "0  e0  g0\n",
      "1  e1  g1\n",
      "2  e2  g2\n",
      "3  e3  g3\n",
      "<class 'pandas.core.frame.DataFrame'> \n",
      "\n",
      "0    e0\n",
      "1    e1\n",
      "2    e2\n",
      "3    e3\n",
      "4    g0\n",
      "5    g1\n",
      "6    g2\n",
      "7    g3\n",
      "dtype: object\n",
      "<class 'pandas.core.series.Series'>\n"
     ]
    }
   ],
   "source": [
    "sr1 = pd.Series(['e0','e1','e2','e3'], name = 'e')\n",
    "sr2 = pd.Series(['g0','g1','g2','g3'], name = 'g')\n",
    "\n",
    "# 열방향으로 시리즈를 연결하면 데이터프레임이 됨\n",
    "result4 = pd.concat([sr1, sr2], axis=1) \n",
    "print(result4)\n",
    "print(type(result4), '\\n')\n",
    "\n",
    "#행방향으로 시리즈를 연결하면 시리즈 타입 유지\n",
    "result5 = pd.concat([sr1, sr2], ignore_index=True)\n",
    "print(result5)\n",
    "print(type(result5))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## merge\n",
    "두 데이터프레임에 존재하는 고유값(Key)를 기준으로 병합\n",
    "* pd.merge(df_left, df_right, how='inner', on=None) 이 default\n",
    "\n",
    "    how에 들어갈 수 있는 매개변수 : 'inner' , 'outer', 'left', 'right'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "id_name = pd.DataFrame({'ID' : ['c01', 'c02', 'c03', 'c04', 'c05', 'c06', 'c07'],\n",
    "                       'last_name': ['Lee', 'Kim', 'Choi', 'Park','Lim','Bae','Kim']})\n",
    "id_number = pd.DataFrame({'id' : ['c03', 'c04', 'c05', 'c06', 'c07', 'c08', 'c09'],\n",
    "                         'number' : [3, 1, 0, 7, 3, 4, 1]})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "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>ID</th>\n",
       "      <th>last_name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>c01</td>\n",
       "      <td>Lee</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>c02</td>\n",
       "      <td>Kim</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>c03</td>\n",
       "      <td>Choi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>c04</td>\n",
       "      <td>Park</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>c05</td>\n",
       "      <td>Lim</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>c06</td>\n",
       "      <td>Bae</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>c07</td>\n",
       "      <td>Kim</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    ID last_name\n",
       "0  c01       Lee\n",
       "1  c02       Kim\n",
       "2  c03      Choi\n",
       "3  c04      Park\n",
       "4  c05       Lim\n",
       "5  c06       Bae\n",
       "6  c07       Kim"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "id_name"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "id_number.columns = ['ID','number']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "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>ID</th>\n",
       "      <th>number</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>c03</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>c04</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>c05</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>c06</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>c07</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>c08</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>c09</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    ID  number\n",
       "0  c03       3\n",
       "1  c04       1\n",
       "2  c05       0\n",
       "3  c06       7\n",
       "4  c07       3\n",
       "5  c08       4\n",
       "6  c09       1"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "id_number"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "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>ID</th>\n",
       "      <th>last_name</th>\n",
       "      <th>ID</th>\n",
       "      <th>number</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>c01</td>\n",
       "      <td>Lee</td>\n",
       "      <td>c03</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>c02</td>\n",
       "      <td>Kim</td>\n",
       "      <td>c04</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>c03</td>\n",
       "      <td>Choi</td>\n",
       "      <td>c05</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>c04</td>\n",
       "      <td>Park</td>\n",
       "      <td>c06</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>c05</td>\n",
       "      <td>Lim</td>\n",
       "      <td>c07</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>c06</td>\n",
       "      <td>Bae</td>\n",
       "      <td>c08</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>c07</td>\n",
       "      <td>Kim</td>\n",
       "      <td>c09</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    ID last_name   ID  number\n",
       "0  c01       Lee  c03       3\n",
       "1  c02       Kim  c04       1\n",
       "2  c03      Choi  c05       0\n",
       "3  c04      Park  c06       7\n",
       "4  c05       Lim  c07       3\n",
       "5  c06       Bae  c08       4\n",
       "6  c07       Kim  c09       1"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.concat([id_name,id_number],axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "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>ID</th>\n",
       "      <th>last_name</th>\n",
       "      <th>number</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>c03</td>\n",
       "      <td>Choi</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>c04</td>\n",
       "      <td>Park</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>c05</td>\n",
       "      <td>Lim</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>c06</td>\n",
       "      <td>Bae</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>c07</td>\n",
       "      <td>Kim</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>c08</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>c09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    ID last_name  number\n",
       "0  c03      Choi       3\n",
       "1  c04      Park       1\n",
       "2  c05       Lim       0\n",
       "3  c06       Bae       7\n",
       "4  c07       Kim       3\n",
       "5  c08       NaN       4\n",
       "6  c09       NaN       1"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.merge(id_name,id_number,how='right',on='ID')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "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>ID</th>\n",
       "      <th>last_name</th>\n",
       "      <th>number</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>c03</td>\n",
       "      <td>Choi</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>c04</td>\n",
       "      <td>Park</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>c05</td>\n",
       "      <td>Lim</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>c06</td>\n",
       "      <td>Bae</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>c07</td>\n",
       "      <td>Kim</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    ID last_name  number\n",
       "0  c03      Choi       3\n",
       "1  c04      Park       1\n",
       "2  c05       Lim       0\n",
       "3  c06       Bae       7\n",
       "4  c07       Kim       3"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.merge(id_name, id_number,how='inner',on='ID')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 미션!! 아래의 과제를 수행하고 댓글에 올려주세요!!! "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 컬럼을 기준으로 두 테이블이 모두 공통된 값을 가지고 있는 경우에만 두 데이터(id_name, id_number)를 병합해보세요.\n",
    "# inner join "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 공통된 값이 없는 경우에도 데이터가 출력되도록 id 칼럼을 기준으로 두 데이터의 모든 행을 병합해보세요.\n",
    "# Outer Join"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# id 칼럼을 기준으로 두 데이터를 병합하는데, \n",
    "# 기준칼럼에 공통 값이 없는 경우에는 id_number 데이터를 기준으로 병합해보세요. \n",
    "# Right Outer Join에 해당\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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