정규_3주차_pandas심화.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Pandas (2)\n",
    "제가 생각하기에, 케이스 스터디를 제외하고 코딩부 수업에서 가장 중요한 부분이 이 부분인 듯합니다.\n",
    "\n",
    "여러분들이 파이썬을 쓰시면서 가장 많이, 그리고 가장 요긴하게 다룰 내용들 대부분이 이번 내용에 들어 있습니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Bitcoin</th>\n",
       "      <th>Ethereum</th>\n",
       "      <th>Litecoin</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Jul 27, 2023</th>\n",
       "      <td>29190.0</td>\n",
       "      <td>1859.03</td>\n",
       "      <td>90.47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jul 26, 2023</th>\n",
       "      <td>29352.2</td>\n",
       "      <td>1872.00</td>\n",
       "      <td>90.66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jul 25, 2023</th>\n",
       "      <td>29228.6</td>\n",
       "      <td>1857.67</td>\n",
       "      <td>89.45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jul 24, 2023</th>\n",
       "      <td>29178.1</td>\n",
       "      <td>1850.04</td>\n",
       "      <td>89.14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jul 23, 2023</th>\n",
       "      <td>30085.9</td>\n",
       "      <td>1888.85</td>\n",
       "      <td>93.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jul 31, 2022</th>\n",
       "      <td>23303.4</td>\n",
       "      <td>1680.00</td>\n",
       "      <td>59.77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jul 30, 2022</th>\n",
       "      <td>23634.2</td>\n",
       "      <td>1695.97</td>\n",
       "      <td>60.40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jul 29, 2022</th>\n",
       "      <td>23774.3</td>\n",
       "      <td>1720.77</td>\n",
       "      <td>60.62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jul 28, 2022</th>\n",
       "      <td>23850.0</td>\n",
       "      <td>1726.01</td>\n",
       "      <td>63.47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jul 27, 2022</th>\n",
       "      <td>22958.3</td>\n",
       "      <td>1636.01</td>\n",
       "      <td>59.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>366 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              Bitcoin  Ethereum  Litecoin\n",
       "Date                                     \n",
       "Jul 27, 2023  29190.0   1859.03     90.47\n",
       "Jul 26, 2023  29352.2   1872.00     90.66\n",
       "Jul 25, 2023  29228.6   1857.67     89.45\n",
       "Jul 24, 2023  29178.1   1850.04     89.14\n",
       "Jul 23, 2023  30085.9   1888.85     93.15\n",
       "...               ...       ...       ...\n",
       "Jul 31, 2022  23303.4   1680.00     59.77\n",
       "Jul 30, 2022  23634.2   1695.97     60.40\n",
       "Jul 29, 2022  23774.3   1720.77     60.62\n",
       "Jul 28, 2022  23850.0   1726.01     63.47\n",
       "Jul 27, 2022  22958.3   1636.01     59.00\n",
       "\n",
       "[366 rows x 3 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#thousands 옵션은 천 단위 인자를 인식할 수 있도록 알려 주는 역할을 합니다. 이를 지정하지 않으면 숫자 사이에 쉽표가 껴 있는 것으로 보고 string으로 처리하는 문제가 발생합니다.\n",
    "coins=pd.read_csv(\"/Users/yihoon-j/Documents/fr/2학기 교안 작업/Coin.csv\", thousands=\",\",index_col=0)\n",
    "coins"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 불리언 인덱싱\n",
    "불리언 연산은 수식이나 조건을 충족하면 1로, 아니라면 0으로 하는 연산을 의미하며, 이를 응용한 인덱싱을 불리언 인덱싱이라 합니다.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Date\n",
       "Jul 27, 2023    False\n",
       "Jul 26, 2023    False\n",
       "Jul 25, 2023    False\n",
       "Jul 24, 2023    False\n",
       "Jul 23, 2023    False\n",
       "                ...  \n",
       "Jul 31, 2022    False\n",
       "Jul 30, 2022    False\n",
       "Jul 29, 2022    False\n",
       "Jul 28, 2022    False\n",
       "Jul 27, 2022    False\n",
       "Name: Bitcoin, Length: 366, dtype: bool"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#불리언 인덱싱을 위해서는 먼저 조건을 찾아야 합니다. True, False로 반환되는 조건을 먼저 만들어 봅시다.\n",
    "coins['Bitcoin']>31000 #'Bitcoin' 컬럼의 값이 31000보다 큰지 확인하여, 그렇다면 True를, 아니라면 False를 반환합니다.\n",
    "#열이 많기 때문에 처음 다섯 행과 끝 다섯 행만 출력되어 있습니다."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**참고**\n",
    "\n",
    "True는 1에, False는 0에 해당되는 값입니다.\n",
    "\n",
    "앞서 사용한 조건문에서는 True가 총 두 개 반환됩니다 (출력되는 않았지만요).\n",
    "\n",
    "따라서 저 조건문의 `sum()`을 수행하면 2가 반환됩니다.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(coins['Bitcoin']>31000).sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "이제 불리언 인덱싱을 수행해 보겠습니다.\n",
    "\n",
    "앞서 2주차 수업에서 데이터프레임의 인덱싱을 어떻게 하는지 보았습니다.\n",
    "\n",
    "앞서서 한 것처럼 loc, iloc를 사용하는 것이 아니라, True에 해당하는 행만을 반환하는 방식으로 불리언 인덱싱을 수행합니다.\n",
    "\n",
    "매 행을 조건과 비교하여 True인 행만 반환해 주는 형태입니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "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>Bitcoin</th>\n",
       "      <th>Ethereum</th>\n",
       "      <th>Litecoin</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Jul 13, 2023</th>\n",
       "      <td>31466.1</td>\n",
       "      <td>2004.77</td>\n",
       "      <td>101.84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jul 03, 2023</th>\n",
       "      <td>31151.3</td>\n",
       "      <td>1955.56</td>\n",
       "      <td>107.28</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              Bitcoin  Ethereum  Litecoin\n",
       "Date                                     \n",
       "Jul 13, 2023  31466.1   2004.77    101.84\n",
       "Jul 03, 2023  31151.3   1955.56    107.28"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "coins[coins['Bitcoin']>31000]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## drop\n",
    "\n",
    "값을 삭제할 때 사용합니다.\n",
    "\n",
    "`axis=0` 옵션으로 행을 (default),\n",
    "\n",
    "`axis=1` 옵션으로 열을 삭제합니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "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>Ethereum</th>\n",
       "      <th>Litecoin</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Jul 27, 2023</th>\n",
       "      <td>1859.03</td>\n",
       "      <td>90.47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jul 26, 2023</th>\n",
       "      <td>1872.00</td>\n",
       "      <td>90.66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jul 25, 2023</th>\n",
       "      <td>1857.67</td>\n",
       "      <td>89.45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jul 24, 2023</th>\n",
       "      <td>1850.04</td>\n",
       "      <td>89.14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jul 23, 2023</th>\n",
       "      <td>1888.85</td>\n",
       "      <td>93.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jul 31, 2022</th>\n",
       "      <td>1680.00</td>\n",
       "      <td>59.77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jul 30, 2022</th>\n",
       "      <td>1695.97</td>\n",
       "      <td>60.40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jul 29, 2022</th>\n",
       "      <td>1720.77</td>\n",
       "      <td>60.62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jul 28, 2022</th>\n",
       "      <td>1726.01</td>\n",
       "      <td>63.47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jul 27, 2022</th>\n",
       "      <td>1636.01</td>\n",
       "      <td>59.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>366 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              Ethereum  Litecoin\n",
       "Date                            \n",
       "Jul 27, 2023   1859.03     90.47\n",
       "Jul 26, 2023   1872.00     90.66\n",
       "Jul 25, 2023   1857.67     89.45\n",
       "Jul 24, 2023   1850.04     89.14\n",
       "Jul 23, 2023   1888.85     93.15\n",
       "...                ...       ...\n",
       "Jul 31, 2022   1680.00     59.77\n",
       "Jul 30, 2022   1695.97     60.40\n",
       "Jul 29, 2022   1720.77     60.62\n",
       "Jul 28, 2022   1726.01     63.47\n",
       "Jul 27, 2022   1636.01     59.00\n",
       "\n",
       "[366 rows x 2 columns]"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "coins.drop(['Bitcoin', 'Etherium'], axis=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## sort\n",
    "\n",
    "데이터프레임을 정렬합니다.\n",
    "\n",
    "`sort_index` 인덱스를 기준으로 정렬\n",
    "\n",
    "`sort_values` 컬럼을 기준으로 정렬"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "coins.sort_index().loc[::30] #정렬이 어떻게 이루어지는지 쉽게 보여드리기 위해 30개 즉 한 달 간격으로 row를 건너뛰면서 출력하였습니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "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>Bitcoin</th>\n",
       "      <th>Ethereum</th>\n",
       "      <th>Litecoin</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Sep 30, 2022</th>\n",
       "      <td>19423.0</td>\n",
       "      <td>1328.73</td>\n",
       "      <td>53.49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Oct 31, 2022</th>\n",
       "      <td>20496.3</td>\n",
       "      <td>1572.89</td>\n",
       "      <td>55.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Oct 01, 2022</th>\n",
       "      <td>19311.9</td>\n",
       "      <td>1311.80</td>\n",
       "      <td>52.92</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Nov 01, 2022</th>\n",
       "      <td>20483.5</td>\n",
       "      <td>1579.64</td>\n",
       "      <td>55.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>May 02, 2023</th>\n",
       "      <td>28669.1</td>\n",
       "      <td>1869.74</td>\n",
       "      <td>88.13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mar 03, 2023</th>\n",
       "      <td>22354.4</td>\n",
       "      <td>1568.89</td>\n",
       "      <td>90.54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jun 03, 2023</th>\n",
       "      <td>27072.0</td>\n",
       "      <td>1892.05</td>\n",
       "      <td>96.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jul 05, 2023</th>\n",
       "      <td>30512.8</td>\n",
       "      <td>1910.43</td>\n",
       "      <td>102.54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jan 06, 2023</th>\n",
       "      <td>16950.9</td>\n",
       "      <td>1269.14</td>\n",
       "      <td>75.93</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Feb 04, 2023</th>\n",
       "      <td>23323.8</td>\n",
       "      <td>1666.90</td>\n",
       "      <td>98.47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dec 05, 2022</th>\n",
       "      <td>16966.5</td>\n",
       "      <td>1259.56</td>\n",
       "      <td>80.18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Aug 06, 2022</th>\n",
       "      <td>22944.2</td>\n",
       "      <td>1690.27</td>\n",
       "      <td>60.81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Apr 06, 2023</th>\n",
       "      <td>28036.7</td>\n",
       "      <td>1872.35</td>\n",
       "      <td>90.97</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              Bitcoin  Ethereum  Litecoin\n",
       "Date                                     \n",
       "Sep 30, 2022  19423.0   1328.73     53.49\n",
       "Oct 31, 2022  20496.3   1572.89     55.04\n",
       "Oct 01, 2022  19311.9   1311.80     52.92\n",
       "Nov 01, 2022  20483.5   1579.64     55.12\n",
       "May 02, 2023  28669.1   1869.74     88.13\n",
       "Mar 03, 2023  22354.4   1568.89     90.54\n",
       "Jun 03, 2023  27072.0   1892.05     96.02\n",
       "Jul 05, 2023  30512.8   1910.43    102.54\n",
       "Jan 06, 2023  16950.9   1269.14     75.93\n",
       "Feb 04, 2023  23323.8   1666.90     98.47\n",
       "Dec 05, 2022  16966.5   1259.56     80.18\n",
       "Aug 06, 2022  22944.2   1690.27     60.81\n",
       "Apr 06, 2023  28036.7   1872.35     90.97"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "coins.sort_index(ascending=False).loc[::30] #ascending 옵션을 명시하지 않을 경우 오름차순 정렬됩니다. False라고 명시해 주어야만 내림차순 정렬됩니다.\n",
    "\n",
    "\n",
    "#인덱스 포맷이 문자형으로 인식되기 때문에 알파벳 순(Apr - Aug - Dec - ...)으로 정렬된다.\n",
    "#날짜 순으로 정렬하는건 뒤에서 다시 다룰게요!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "여러 개의 값을 기준으로 정렬할 때는 정렬할 값들을 []로 묶어 줍니다. 첫 번째 값을 기준으로 먼저 정렬하고, 그 다음 두 번째 값을 기준으로 정렬하고,... 의 형태로 정렬됩니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "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>Bitcoin</th>\n",
       "      <th>Ethereum</th>\n",
       "      <th>Litecoin</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Nov 21, 2022</th>\n",
       "      <td>15776.2</td>\n",
       "      <td>1107.46</td>\n",
       "      <td>61.34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Nov 09, 2022</th>\n",
       "      <td>15886.9</td>\n",
       "      <td>1100.84</td>\n",
       "      <td>50.62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Nov 28, 2022</th>\n",
       "      <td>16211.7</td>\n",
       "      <td>1167.73</td>\n",
       "      <td>73.90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Nov 22, 2022</th>\n",
       "      <td>16212.9</td>\n",
       "      <td>1139.74</td>\n",
       "      <td>70.61</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Nov 20, 2022</th>\n",
       "      <td>16286.7</td>\n",
       "      <td>1142.88</td>\n",
       "      <td>62.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jun 23, 2023</th>\n",
       "      <td>30679.4</td>\n",
       "      <td>1891.97</td>\n",
       "      <td>91.27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jun 27, 2023</th>\n",
       "      <td>30689.1</td>\n",
       "      <td>1889.51</td>\n",
       "      <td>88.07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jul 04, 2023</th>\n",
       "      <td>30768.4</td>\n",
       "      <td>1936.19</td>\n",
       "      <td>104.18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jul 03, 2023</th>\n",
       "      <td>31151.3</td>\n",
       "      <td>1955.56</td>\n",
       "      <td>107.28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jul 13, 2023</th>\n",
       "      <td>31466.1</td>\n",
       "      <td>2004.77</td>\n",
       "      <td>101.84</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>366 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              Bitcoin  Ethereum  Litecoin\n",
       "Date                                     \n",
       "Nov 21, 2022  15776.2   1107.46     61.34\n",
       "Nov 09, 2022  15886.9   1100.84     50.62\n",
       "Nov 28, 2022  16211.7   1167.73     73.90\n",
       "Nov 22, 2022  16212.9   1139.74     70.61\n",
       "Nov 20, 2022  16286.7   1142.88     62.10\n",
       "...               ...       ...       ...\n",
       "Jun 23, 2023  30679.4   1891.97     91.27\n",
       "Jun 27, 2023  30689.1   1889.51     88.07\n",
       "Jul 04, 2023  30768.4   1936.19    104.18\n",
       "Jul 03, 2023  31151.3   1955.56    107.28\n",
       "Jul 13, 2023  31466.1   2004.77    101.84\n",
       "\n",
       "[366 rows x 3 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "coins.sort_values(['Bitcoin', 'Ethereum'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## rename\n",
    "\n",
    "행/열 이름 바꾸기"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "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>BTC</th>\n",
       "      <th>ETH</th>\n",
       "      <th>LTC</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Jul 27, 2023</th>\n",
       "      <td>29190.0</td>\n",
       "      <td>1859.03</td>\n",
       "      <td>90.47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jul 26, 2023</th>\n",
       "      <td>29352.2</td>\n",
       "      <td>1872.00</td>\n",
       "      <td>90.66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jul 25, 2023</th>\n",
       "      <td>29228.6</td>\n",
       "      <td>1857.67</td>\n",
       "      <td>89.45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jul 24, 2023</th>\n",
       "      <td>29178.1</td>\n",
       "      <td>1850.04</td>\n",
       "      <td>89.14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jul 23, 2023</th>\n",
       "      <td>30085.9</td>\n",
       "      <td>1888.85</td>\n",
       "      <td>93.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jul 31, 2022</th>\n",
       "      <td>23303.4</td>\n",
       "      <td>1680.00</td>\n",
       "      <td>59.77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jul 30, 2022</th>\n",
       "      <td>23634.2</td>\n",
       "      <td>1695.97</td>\n",
       "      <td>60.40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jul 29, 2022</th>\n",
       "      <td>23774.3</td>\n",
       "      <td>1720.77</td>\n",
       "      <td>60.62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jul 28, 2022</th>\n",
       "      <td>23850.0</td>\n",
       "      <td>1726.01</td>\n",
       "      <td>63.47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jul 27, 2022</th>\n",
       "      <td>22958.3</td>\n",
       "      <td>1636.01</td>\n",
       "      <td>59.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>366 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                  BTC      ETH    LTC\n",
       "Date                                 \n",
       "Jul 27, 2023  29190.0  1859.03  90.47\n",
       "Jul 26, 2023  29352.2  1872.00  90.66\n",
       "Jul 25, 2023  29228.6  1857.67  89.45\n",
       "Jul 24, 2023  29178.1  1850.04  89.14\n",
       "Jul 23, 2023  30085.9  1888.85  93.15\n",
       "...               ...      ...    ...\n",
       "Jul 31, 2022  23303.4  1680.00  59.77\n",
       "Jul 30, 2022  23634.2  1695.97  60.40\n",
       "Jul 29, 2022  23774.3  1720.77  60.62\n",
       "Jul 28, 2022  23850.0  1726.01  63.47\n",
       "Jul 27, 2022  22958.3  1636.01  59.00\n",
       "\n",
       "[366 rows x 3 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "coins.rename(columns={'Bitcoin':'BTC', 'Ethereum':'ETH', 'Litecoin':'LTC'})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## pivot\n",
    "데이터프레임에서의 피봇은 Column을 Row로 혹은 반대로 전환(pivot)하는 것을 뜻합니다.\n",
    "\n",
    "원래는 피봇이 무엇인지 보여 드린 후 피봇의 역방향 처리 (특별히 정해진 이름은 없습니다만 저는 reverse pivot이라 부르겠습니다)를 보여드리는 게 맞는데,\n",
    "\n",
    "제가 일하면서 맞닥뜨린 실제 데이터들은 reverse pivot할 일들이 훨씬 많은 듯해서, 순서를 바꿔서 보여 드리겠습니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "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>COINS</th>\n",
       "      <th>PRICE</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Jul 27, 2023</th>\n",
       "      <td>Bitcoin</td>\n",
       "      <td>29190.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jul 27, 2023</th>\n",
       "      <td>Ethereum</td>\n",
       "      <td>1859.03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jul 27, 2023</th>\n",
       "      <td>Litecoin</td>\n",
       "      <td>90.47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jul 26, 2023</th>\n",
       "      <td>Bitcoin</td>\n",
       "      <td>29352.20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jul 26, 2023</th>\n",
       "      <td>Ethereum</td>\n",
       "      <td>1872.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jul 26, 2023</th>\n",
       "      <td>Litecoin</td>\n",
       "      <td>90.66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jul 25, 2023</th>\n",
       "      <td>Bitcoin</td>\n",
       "      <td>29228.60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jul 25, 2023</th>\n",
       "      <td>Ethereum</td>\n",
       "      <td>1857.67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jul 25, 2023</th>\n",
       "      <td>Litecoin</td>\n",
       "      <td>89.45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jul 24, 2023</th>\n",
       "      <td>Bitcoin</td>\n",
       "      <td>29178.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jul 24, 2023</th>\n",
       "      <td>Ethereum</td>\n",
       "      <td>1850.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jul 24, 2023</th>\n",
       "      <td>Litecoin</td>\n",
       "      <td>89.14</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 COINS     PRICE\n",
       "Date                            \n",
       "Jul 27, 2023   Bitcoin  29190.00\n",
       "Jul 27, 2023  Ethereum   1859.03\n",
       "Jul 27, 2023  Litecoin     90.47\n",
       "Jul 26, 2023   Bitcoin  29352.20\n",
       "Jul 26, 2023  Ethereum   1872.00\n",
       "Jul 26, 2023  Litecoin     90.66\n",
       "Jul 25, 2023   Bitcoin  29228.60\n",
       "Jul 25, 2023  Ethereum   1857.67\n",
       "Jul 25, 2023  Litecoin     89.45\n",
       "Jul 24, 2023   Bitcoin  29178.10\n",
       "Jul 24, 2023  Ethereum   1850.04\n",
       "Jul 24, 2023  Litecoin     89.14"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#reverse pivot (stack)\n",
    "coins_piv=coins.stack().reset_index(name='PRICE').rename(columns={'level_1':'COINS'}).set_index('Date')\n",
    "coins_piv.head(12)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "행 단위로 나열되어 있던 각 코인의 가격이 열 단위로 길게 정렬되었죠?\n",
    "```\n",
    "TMI:\n",
    "이러한 연산은 보통 데이터를 데이터베이스에 저장할 때 사용합니다.\n",
    "데이터베이스에서 새로운 열을 추가하는 것은 행을 추가하는 것과 비교하면 매우 큰 비용이 발생하기 때문입니다.\n",
    "따라서 이 때 최대한 열을 줄이고 행을 늘리는 방법을 사용합니다.\n",
    "```\n",
    "\n",
    "보시면 코드가 상당히 복잡한데, 물론 이걸 알아두면 좋지만, 솔직히 저도 쓰고 맨날 까먹는 코드입니다.\n",
    "그냥 '이런 게 있구나'하고 기억해 두셨다가, 필요한 상황이 닥쳤을 때 복붙해서 써먹으시면 충분합니다."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "한편, pivot은 방금 살펴본 reverse pivot의 반대 방향 연산입니다.\n",
    "\n",
    "피봇 함수는 상대적으로 간단하기 때문에 알아 두시면 좋습니다.\n",
    "\n",
    "데이터가 어떤 형태로 들어가야 하는지를 잘 고민해 보고,\n",
    "\n",
    "컬럼에는 무엇이 있어야 하는지, 그리고 표의 값은 무엇이 되어야 하는지를 각각 `columns`, `values` 인자에 지정해 줍니다.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "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>COINS</th>\n",
       "      <th>Bitcoin</th>\n",
       "      <th>Ethereum</th>\n",
       "      <th>Litecoin</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Apr 01, 2023</th>\n",
       "      <td>28456.1</td>\n",
       "      <td>1820.78</td>\n",
       "      <td>92.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Apr 02, 2023</th>\n",
       "      <td>28198.3</td>\n",
       "      <td>1795.01</td>\n",
       "      <td>92.81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Apr 03, 2023</th>\n",
       "      <td>27802.1</td>\n",
       "      <td>1810.77</td>\n",
       "      <td>92.98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Apr 04, 2023</th>\n",
       "      <td>28164.4</td>\n",
       "      <td>1870.52</td>\n",
       "      <td>92.53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Apr 05, 2023</th>\n",
       "      <td>28173.5</td>\n",
       "      <td>1908.96</td>\n",
       "      <td>92.67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sep 26, 2022</th>\n",
       "      <td>19225.7</td>\n",
       "      <td>1337.06</td>\n",
       "      <td>53.43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sep 27, 2022</th>\n",
       "      <td>19081.0</td>\n",
       "      <td>1328.23</td>\n",
       "      <td>52.65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sep 28, 2022</th>\n",
       "      <td>19411.0</td>\n",
       "      <td>1337.37</td>\n",
       "      <td>53.28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sep 29, 2022</th>\n",
       "      <td>19593.0</td>\n",
       "      <td>1336.08</td>\n",
       "      <td>53.96</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sep 30, 2022</th>\n",
       "      <td>19423.0</td>\n",
       "      <td>1328.73</td>\n",
       "      <td>53.49</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>366 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "COINS         Bitcoin  Ethereum  Litecoin\n",
       "Date                                     \n",
       "Apr 01, 2023  28456.1   1820.78     92.56\n",
       "Apr 02, 2023  28198.3   1795.01     92.81\n",
       "Apr 03, 2023  27802.1   1810.77     92.98\n",
       "Apr 04, 2023  28164.4   1870.52     92.53\n",
       "Apr 05, 2023  28173.5   1908.96     92.67\n",
       "...               ...       ...       ...\n",
       "Sep 26, 2022  19225.7   1337.06     53.43\n",
       "Sep 27, 2022  19081.0   1328.23     52.65\n",
       "Sep 28, 2022  19411.0   1337.37     53.28\n",
       "Sep 29, 2022  19593.0   1336.08     53.96\n",
       "Sep 30, 2022  19423.0   1328.73     53.49\n",
       "\n",
       "[366 rows x 3 columns]"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#pivot\n",
    "coins_piv.pivot(columns='COINS', values='PRICE')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## describe\n",
    "수치형 컬럼의 여러 정보를 반환합니다. 데이터의 분포를 빠르게 파악할 때 유용합니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count     366.000000\n",
       "mean     1607.971503\n",
       "std       251.177637\n",
       "min      1100.840000\n",
       "25%      1335.457500\n",
       "50%      1639.290000\n",
       "75%      1838.852500\n",
       "max      2119.290000\n",
       "Name: Ethereum, dtype: float64"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "coins['Ethereum'].describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## shift\n",
    "데이터프레임을 특정 Row만큼 뒤로/앞으로 당길 때 사용합니다.\n",
    "\n",
    "한 개의 데이터프레임 안에서 과거 값/미래 값을 현재 값과 매치해야 할 때 사용할 수 있습니다.\n",
    "\n",
    "예를 들어, 3일 후의 주가를 예측해야 할 경우 예측에 사용되는 값들을 `shift(-3)`하여, 3일 이전의 값을 환율과 매칭시켜 학습 모델에 집어넣을 수 있습니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Date\n",
       "Jul 27, 2023    29228.6\n",
       "Jul 26, 2023    29178.1\n",
       "Jul 25, 2023    30085.9\n",
       "Jul 24, 2023    29788.9\n",
       "Jul 23, 2023    29903.1\n",
       "                 ...   \n",
       "Jul 31, 2022    23774.3\n",
       "Jul 30, 2022    23850.0\n",
       "Jul 29, 2022    22958.3\n",
       "Jul 28, 2022        NaN\n",
       "Jul 27, 2022        NaN\n",
       "Name: Bitcoin, Length: 366, dtype: float64"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "coins['Bitcoin'].shift(-2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## groupby\n",
    "데이터를 특정 열/인덱스를 기준으로 집계합니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "#데이터프레임으로 이것저것 가공을 많이 했기 때문에, 원본 파일을 새로 다시 한 번 불러오겠습니다.\n",
    "coins=pd.read_csv(\"/Users/yihoon-j/Documents/fr/2학기 교안 작업/Coin.csv\", thousands=\",\",index_col=0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "집계를 위해서는 집계가 가능하도록 공통되는 값이 존재하는 열/인덱스가 필요하기 때문에, 먼저 인덱스를 만들어주는 작업을 수행하겠습니다.\n",
    "\n",
    "아직 우리가 배우지 않은 내용들이 많기 때문에, 일단은 \"이 코드가 월 번호, 주 번호를 만드는 연산이구나\"하고만 넘어가 주세요.\n",
    "\n",
    "해당 코드는 날짜 자료형을 다루면서 다시 설명해드리겠습니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "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>Date</th>\n",
       "      <th>Bitcoin</th>\n",
       "      <th>Ethereum</th>\n",
       "      <th>Litecoin</th>\n",
       "      <th>Month</th>\n",
       "      <th>Week</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Jul 27, 2023</td>\n",
       "      <td>29190.0</td>\n",
       "      <td>1859.03</td>\n",
       "      <td>90.47</td>\n",
       "      <td>202307</td>\n",
       "      <td>202330</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Jul 26, 2023</td>\n",
       "      <td>29352.2</td>\n",
       "      <td>1872.00</td>\n",
       "      <td>90.66</td>\n",
       "      <td>202307</td>\n",
       "      <td>202330</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Jul 25, 2023</td>\n",
       "      <td>29228.6</td>\n",
       "      <td>1857.67</td>\n",
       "      <td>89.45</td>\n",
       "      <td>202307</td>\n",
       "      <td>202330</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Jul 24, 2023</td>\n",
       "      <td>29178.1</td>\n",
       "      <td>1850.04</td>\n",
       "      <td>89.14</td>\n",
       "      <td>202307</td>\n",
       "      <td>202330</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Jul 23, 2023</td>\n",
       "      <td>30085.9</td>\n",
       "      <td>1888.85</td>\n",
       "      <td>93.15</td>\n",
       "      <td>202307</td>\n",
       "      <td>202329</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>361</th>\n",
       "      <td>Jul 31, 2022</td>\n",
       "      <td>23303.4</td>\n",
       "      <td>1680.00</td>\n",
       "      <td>59.77</td>\n",
       "      <td>202207</td>\n",
       "      <td>202230</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>362</th>\n",
       "      <td>Jul 30, 2022</td>\n",
       "      <td>23634.2</td>\n",
       "      <td>1695.97</td>\n",
       "      <td>60.40</td>\n",
       "      <td>202207</td>\n",
       "      <td>202230</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>363</th>\n",
       "      <td>Jul 29, 2022</td>\n",
       "      <td>23774.3</td>\n",
       "      <td>1720.77</td>\n",
       "      <td>60.62</td>\n",
       "      <td>202207</td>\n",
       "      <td>202230</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>364</th>\n",
       "      <td>Jul 28, 2022</td>\n",
       "      <td>23850.0</td>\n",
       "      <td>1726.01</td>\n",
       "      <td>63.47</td>\n",
       "      <td>202207</td>\n",
       "      <td>202230</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>365</th>\n",
       "      <td>Jul 27, 2022</td>\n",
       "      <td>22958.3</td>\n",
       "      <td>1636.01</td>\n",
       "      <td>59.00</td>\n",
       "      <td>202207</td>\n",
       "      <td>202230</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>366 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             Date  Bitcoin  Ethereum  Litecoin   Month    Week\n",
       "0    Jul 27, 2023  29190.0   1859.03     90.47  202307  202330\n",
       "1    Jul 26, 2023  29352.2   1872.00     90.66  202307  202330\n",
       "2    Jul 25, 2023  29228.6   1857.67     89.45  202307  202330\n",
       "3    Jul 24, 2023  29178.1   1850.04     89.14  202307  202330\n",
       "4    Jul 23, 2023  30085.9   1888.85     93.15  202307  202329\n",
       "..            ...      ...       ...       ...     ...     ...\n",
       "361  Jul 31, 2022  23303.4   1680.00     59.77  202207  202230\n",
       "362  Jul 30, 2022  23634.2   1695.97     60.40  202207  202230\n",
       "363  Jul 29, 2022  23774.3   1720.77     60.62  202207  202230\n",
       "364  Jul 28, 2022  23850.0   1726.01     63.47  202207  202230\n",
       "365  Jul 27, 2022  22958.3   1636.01     59.00  202207  202230\n",
       "\n",
       "[366 rows x 6 columns]"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import datetime\n",
    "coins=coins.reset_index()\n",
    "coins['Month']=coins['Date'].apply(lambda x: datetime.datetime.strptime(x, \"%b %d, %Y\").strftime('%Y%m')) #각 날짜의 월 번호 만들기\n",
    "coins['Week']=coins['Date'].apply(lambda x: datetime.datetime.strptime(x, \"%b %d, %Y\").strftime('%Y%W')) #각 날짜의 주 번호 만들기\n",
    "coins"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "groupby()안에는 집계 대상이 되는 컬럼명을, 그 뒤에는 집계 함수를 지정합니다.\n",
    "\n",
    "집계 함수는 진짜 정말 많은데.. 제일 많이 쓰는 건 `mean()` `median()` `min()` `max()` `std()` 정도는 다들 지난 학기에 보셨을 거고,\n",
    "\n",
    "추가로 `ohlc()`를 한번 다뤄 볼게요"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-5-a25d8ff13365>:1: FutureWarning: The default value of numeric_only in DataFrameGroupBy.mean is deprecated. In a future version, numeric_only will default to False. Either specify numeric_only or select only columns which should be valid for the function.\n",
      "  coins.groupby('Month').mean()\n"
     ]
    },
    {
     "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>Bitcoin</th>\n",
       "      <th>Ethereum</th>\n",
       "      <th>Litecoin</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Month</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>202207</th>\n",
       "      <td>23504.040000</td>\n",
       "      <td>1691.752000</td>\n",
       "      <td>60.652000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202208</th>\n",
       "      <td>22353.016129</td>\n",
       "      <td>1698.932258</td>\n",
       "      <td>58.368710</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202209</th>\n",
       "      <td>19794.286667</td>\n",
       "      <td>1483.870667</td>\n",
       "      <td>56.574000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202210</th>\n",
       "      <td>19647.096774</td>\n",
       "      <td>1367.231935</td>\n",
       "      <td>53.162903</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202211</th>\n",
       "      <td>17591.980000</td>\n",
       "      <td>1297.642000</td>\n",
       "      <td>65.468333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202212</th>\n",
       "      <td>16942.287097</td>\n",
       "      <td>1236.584194</td>\n",
       "      <td>71.682581</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202301</th>\n",
       "      <td>20242.125806</td>\n",
       "      <td>1466.301935</td>\n",
       "      <td>84.329355</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202302</th>\n",
       "      <td>23292.742857</td>\n",
       "      <td>1624.176071</td>\n",
       "      <td>96.256786</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202303</th>\n",
       "      <td>25079.564516</td>\n",
       "      <td>1672.958710</td>\n",
       "      <td>85.623226</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202304</th>\n",
       "      <td>28842.470000</td>\n",
       "      <td>1916.051333</td>\n",
       "      <td>91.974333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202305</th>\n",
       "      <td>27489.090323</td>\n",
       "      <td>1844.672258</td>\n",
       "      <td>87.235161</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202306</th>\n",
       "      <td>27758.550000</td>\n",
       "      <td>1818.483333</td>\n",
       "      <td>85.422667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202307</th>\n",
       "      <td>30167.870370</td>\n",
       "      <td>1896.790370</td>\n",
       "      <td>96.396296</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Bitcoin     Ethereum   Litecoin\n",
       "Month                                       \n",
       "202207  23504.040000  1691.752000  60.652000\n",
       "202208  22353.016129  1698.932258  58.368710\n",
       "202209  19794.286667  1483.870667  56.574000\n",
       "202210  19647.096774  1367.231935  53.162903\n",
       "202211  17591.980000  1297.642000  65.468333\n",
       "202212  16942.287097  1236.584194  71.682581\n",
       "202301  20242.125806  1466.301935  84.329355\n",
       "202302  23292.742857  1624.176071  96.256786\n",
       "202303  25079.564516  1672.958710  85.623226\n",
       "202304  28842.470000  1916.051333  91.974333\n",
       "202305  27489.090323  1844.672258  87.235161\n",
       "202306  27758.550000  1818.483333  85.422667\n",
       "202307  30167.870370  1896.790370  96.396296"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "coins.groupby('Month').mean()\n",
    "#집계가 불가능한 Date컬럼은 출력되지 않음\n",
    "#참고로 여기 뜨는 FutureWarning은 \"나중에는 문법 업데이트 돼서 안 될 수도 있다\"는 의미입니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "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=\"4\" halign=\"left\">Bitcoin</th>\n",
       "      <th colspan=\"4\" halign=\"left\">Ethereum</th>\n",
       "      <th colspan=\"4\" halign=\"left\">Litecoin</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Month</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",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>202207</th>\n",
       "      <td>23303.4</td>\n",
       "      <td>23850.0</td>\n",
       "      <td>22958.3</td>\n",
       "      <td>22958.3</td>\n",
       "      <td>1680.00</td>\n",
       "      <td>1726.01</td>\n",
       "      <td>1636.01</td>\n",
       "      <td>1636.01</td>\n",
       "      <td>59.77</td>\n",
       "      <td>63.47</td>\n",
       "      <td>59.00</td>\n",
       "      <td>59.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202208</th>\n",
       "      <td>20043.9</td>\n",
       "      <td>24442.5</td>\n",
       "      <td>19550.2</td>\n",
       "      <td>23271.2</td>\n",
       "      <td>1555.12</td>\n",
       "      <td>1983.50</td>\n",
       "      <td>1426.25</td>\n",
       "      <td>1630.10</td>\n",
       "      <td>53.81</td>\n",
       "      <td>63.80</td>\n",
       "      <td>52.67</td>\n",
       "      <td>59.47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202209</th>\n",
       "      <td>19423.0</td>\n",
       "      <td>22395.3</td>\n",
       "      <td>18489.0</td>\n",
       "      <td>20126.1</td>\n",
       "      <td>1328.73</td>\n",
       "      <td>1774.38</td>\n",
       "      <td>1247.74</td>\n",
       "      <td>1585.48</td>\n",
       "      <td>53.49</td>\n",
       "      <td>63.28</td>\n",
       "      <td>51.14</td>\n",
       "      <td>57.55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202210</th>\n",
       "      <td>20496.3</td>\n",
       "      <td>20809.8</td>\n",
       "      <td>19042.9</td>\n",
       "      <td>19311.9</td>\n",
       "      <td>1572.89</td>\n",
       "      <td>1619.69</td>\n",
       "      <td>1274.57</td>\n",
       "      <td>1311.80</td>\n",
       "      <td>55.04</td>\n",
       "      <td>56.62</td>\n",
       "      <td>50.39</td>\n",
       "      <td>52.92</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202211</th>\n",
       "      <td>17163.9</td>\n",
       "      <td>21301.6</td>\n",
       "      <td>15776.2</td>\n",
       "      <td>20483.5</td>\n",
       "      <td>1294.41</td>\n",
       "      <td>1645.01</td>\n",
       "      <td>1100.84</td>\n",
       "      <td>1579.64</td>\n",
       "      <td>79.15</td>\n",
       "      <td>79.15</td>\n",
       "      <td>50.62</td>\n",
       "      <td>55.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202212</th>\n",
       "      <td>16537.4</td>\n",
       "      <td>17796.4</td>\n",
       "      <td>16441.3</td>\n",
       "      <td>16972.0</td>\n",
       "      <td>1195.67</td>\n",
       "      <td>1320.76</td>\n",
       "      <td>1166.70</td>\n",
       "      <td>1276.05</td>\n",
       "      <td>70.08</td>\n",
       "      <td>80.18</td>\n",
       "      <td>63.40</td>\n",
       "      <td>77.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202301</th>\n",
       "      <td>23125.1</td>\n",
       "      <td>23753.1</td>\n",
       "      <td>16618.4</td>\n",
       "      <td>16618.4</td>\n",
       "      <td>1585.27</td>\n",
       "      <td>1659.98</td>\n",
       "      <td>1200.52</td>\n",
       "      <td>1200.52</td>\n",
       "      <td>94.14</td>\n",
       "      <td>94.88</td>\n",
       "      <td>70.91</td>\n",
       "      <td>70.91</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202302</th>\n",
       "      <td>23130.5</td>\n",
       "      <td>24839.5</td>\n",
       "      <td>21635.0</td>\n",
       "      <td>23725.6</td>\n",
       "      <td>1604.69</td>\n",
       "      <td>1703.27</td>\n",
       "      <td>1505.84</td>\n",
       "      <td>1642.10</td>\n",
       "      <td>93.79</td>\n",
       "      <td>102.85</td>\n",
       "      <td>91.07</td>\n",
       "      <td>100.33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202303</th>\n",
       "      <td>28473.7</td>\n",
       "      <td>28473.7</td>\n",
       "      <td>20156.7</td>\n",
       "      <td>23642.2</td>\n",
       "      <td>1821.62</td>\n",
       "      <td>1821.62</td>\n",
       "      <td>1426.75</td>\n",
       "      <td>1666.09</td>\n",
       "      <td>89.57</td>\n",
       "      <td>97.85</td>\n",
       "      <td>69.22</td>\n",
       "      <td>97.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202304</th>\n",
       "      <td>29252.1</td>\n",
       "      <td>30472.5</td>\n",
       "      <td>27264.8</td>\n",
       "      <td>28456.1</td>\n",
       "      <td>1868.88</td>\n",
       "      <td>2119.29</td>\n",
       "      <td>1795.01</td>\n",
       "      <td>1820.78</td>\n",
       "      <td>88.14</td>\n",
       "      <td>101.77</td>\n",
       "      <td>85.33</td>\n",
       "      <td>92.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202305</th>\n",
       "      <td>27216.1</td>\n",
       "      <td>29513.2</td>\n",
       "      <td>26328.4</td>\n",
       "      <td>28077.6</td>\n",
       "      <td>1873.63</td>\n",
       "      <td>1993.33</td>\n",
       "      <td>1794.71</td>\n",
       "      <td>1830.75</td>\n",
       "      <td>90.45</td>\n",
       "      <td>93.79</td>\n",
       "      <td>77.78</td>\n",
       "      <td>86.76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202306</th>\n",
       "      <td>30472.9</td>\n",
       "      <td>30689.1</td>\n",
       "      <td>25129.5</td>\n",
       "      <td>26819.0</td>\n",
       "      <td>1933.80</td>\n",
       "      <td>1933.80</td>\n",
       "      <td>1650.96</td>\n",
       "      <td>1861.77</td>\n",
       "      <td>108.66</td>\n",
       "      <td>108.66</td>\n",
       "      <td>73.17</td>\n",
       "      <td>94.18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202307</th>\n",
       "      <td>29190.0</td>\n",
       "      <td>31466.1</td>\n",
       "      <td>29178.1</td>\n",
       "      <td>30586.8</td>\n",
       "      <td>1859.03</td>\n",
       "      <td>2004.77</td>\n",
       "      <td>1848.36</td>\n",
       "      <td>1924.53</td>\n",
       "      <td>90.47</td>\n",
       "      <td>113.35</td>\n",
       "      <td>89.14</td>\n",
       "      <td>107.34</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Bitcoin                            Ethereum                    \\\n",
       "           open     high      low    close     open     high      low   \n",
       "Month                                                                   \n",
       "202207  23303.4  23850.0  22958.3  22958.3  1680.00  1726.01  1636.01   \n",
       "202208  20043.9  24442.5  19550.2  23271.2  1555.12  1983.50  1426.25   \n",
       "202209  19423.0  22395.3  18489.0  20126.1  1328.73  1774.38  1247.74   \n",
       "202210  20496.3  20809.8  19042.9  19311.9  1572.89  1619.69  1274.57   \n",
       "202211  17163.9  21301.6  15776.2  20483.5  1294.41  1645.01  1100.84   \n",
       "202212  16537.4  17796.4  16441.3  16972.0  1195.67  1320.76  1166.70   \n",
       "202301  23125.1  23753.1  16618.4  16618.4  1585.27  1659.98  1200.52   \n",
       "202302  23130.5  24839.5  21635.0  23725.6  1604.69  1703.27  1505.84   \n",
       "202303  28473.7  28473.7  20156.7  23642.2  1821.62  1821.62  1426.75   \n",
       "202304  29252.1  30472.5  27264.8  28456.1  1868.88  2119.29  1795.01   \n",
       "202305  27216.1  29513.2  26328.4  28077.6  1873.63  1993.33  1794.71   \n",
       "202306  30472.9  30689.1  25129.5  26819.0  1933.80  1933.80  1650.96   \n",
       "202307  29190.0  31466.1  29178.1  30586.8  1859.03  2004.77  1848.36   \n",
       "\n",
       "                Litecoin                         \n",
       "          close     open    high    low   close  \n",
       "Month                                            \n",
       "202207  1636.01    59.77   63.47  59.00   59.00  \n",
       "202208  1630.10    53.81   63.80  52.67   59.47  \n",
       "202209  1585.48    53.49   63.28  51.14   57.55  \n",
       "202210  1311.80    55.04   56.62  50.39   52.92  \n",
       "202211  1579.64    79.15   79.15  50.62   55.12  \n",
       "202212  1276.05    70.08   80.18  63.40   77.56  \n",
       "202301  1200.52    94.14   94.88  70.91   70.91  \n",
       "202302  1642.10    93.79  102.85  91.07  100.33  \n",
       "202303  1666.09    89.57   97.85  69.22   97.85  \n",
       "202304  1820.78    88.14  101.77  85.33   92.56  \n",
       "202305  1830.75    90.45   93.79  77.78   86.76  \n",
       "202306  1861.77   108.66  108.66  73.17   94.18  \n",
       "202307  1924.53    90.47  113.35  89.14  107.34  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#ohlc: 시가, 고가, 저가, 종가를 한꺼번에 계산\n",
    "coins_ohlc=coins.drop(['Date', 'Week'], axis=1).groupby('Month').ohlc() #ohlc는 숫자형 자료형을 기준으로만 집계가 가능합니다\n",
    "coins_ohlc"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "어라? 컬럼이 이중으로 바뀌어 버렸네요. 컬럼 레벨을 하나로 낮춰 봅시다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "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>Bitcoin_open</th>\n",
       "      <th>Bitcoin_high</th>\n",
       "      <th>Bitcoin_low</th>\n",
       "      <th>Bitcoin_close</th>\n",
       "      <th>Ethereum_open</th>\n",
       "      <th>Ethereum_high</th>\n",
       "      <th>Ethereum_low</th>\n",
       "      <th>Ethereum_close</th>\n",
       "      <th>Litecoin_open</th>\n",
       "      <th>Litecoin_high</th>\n",
       "      <th>Litecoin_low</th>\n",
       "      <th>Litecoin_close</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Month</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",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>202207</th>\n",
       "      <td>23303.4</td>\n",
       "      <td>23850.0</td>\n",
       "      <td>22958.3</td>\n",
       "      <td>22958.3</td>\n",
       "      <td>1680.00</td>\n",
       "      <td>1726.01</td>\n",
       "      <td>1636.01</td>\n",
       "      <td>1636.01</td>\n",
       "      <td>59.77</td>\n",
       "      <td>63.47</td>\n",
       "      <td>59.00</td>\n",
       "      <td>59.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202208</th>\n",
       "      <td>20043.9</td>\n",
       "      <td>24442.5</td>\n",
       "      <td>19550.2</td>\n",
       "      <td>23271.2</td>\n",
       "      <td>1555.12</td>\n",
       "      <td>1983.50</td>\n",
       "      <td>1426.25</td>\n",
       "      <td>1630.10</td>\n",
       "      <td>53.81</td>\n",
       "      <td>63.80</td>\n",
       "      <td>52.67</td>\n",
       "      <td>59.47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202209</th>\n",
       "      <td>19423.0</td>\n",
       "      <td>22395.3</td>\n",
       "      <td>18489.0</td>\n",
       "      <td>20126.1</td>\n",
       "      <td>1328.73</td>\n",
       "      <td>1774.38</td>\n",
       "      <td>1247.74</td>\n",
       "      <td>1585.48</td>\n",
       "      <td>53.49</td>\n",
       "      <td>63.28</td>\n",
       "      <td>51.14</td>\n",
       "      <td>57.55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202210</th>\n",
       "      <td>20496.3</td>\n",
       "      <td>20809.8</td>\n",
       "      <td>19042.9</td>\n",
       "      <td>19311.9</td>\n",
       "      <td>1572.89</td>\n",
       "      <td>1619.69</td>\n",
       "      <td>1274.57</td>\n",
       "      <td>1311.80</td>\n",
       "      <td>55.04</td>\n",
       "      <td>56.62</td>\n",
       "      <td>50.39</td>\n",
       "      <td>52.92</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202211</th>\n",
       "      <td>17163.9</td>\n",
       "      <td>21301.6</td>\n",
       "      <td>15776.2</td>\n",
       "      <td>20483.5</td>\n",
       "      <td>1294.41</td>\n",
       "      <td>1645.01</td>\n",
       "      <td>1100.84</td>\n",
       "      <td>1579.64</td>\n",
       "      <td>79.15</td>\n",
       "      <td>79.15</td>\n",
       "      <td>50.62</td>\n",
       "      <td>55.12</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Bitcoin_open  Bitcoin_high  Bitcoin_low  Bitcoin_close  Ethereum_open  \\\n",
       "Month                                                                           \n",
       "202207       23303.4       23850.0      22958.3        22958.3        1680.00   \n",
       "202208       20043.9       24442.5      19550.2        23271.2        1555.12   \n",
       "202209       19423.0       22395.3      18489.0        20126.1        1328.73   \n",
       "202210       20496.3       20809.8      19042.9        19311.9        1572.89   \n",
       "202211       17163.9       21301.6      15776.2        20483.5        1294.41   \n",
       "\n",
       "        Ethereum_high  Ethereum_low  Ethereum_close  Litecoin_open  \\\n",
       "Month                                                                \n",
       "202207        1726.01       1636.01         1636.01          59.77   \n",
       "202208        1983.50       1426.25         1630.10          53.81   \n",
       "202209        1774.38       1247.74         1585.48          53.49   \n",
       "202210        1619.69       1274.57         1311.80          55.04   \n",
       "202211        1645.01       1100.84         1579.64          79.15   \n",
       "\n",
       "        Litecoin_high  Litecoin_low  Litecoin_close  \n",
       "Month                                                \n",
       "202207          63.47         59.00           59.00  \n",
       "202208          63.80         52.67           59.47  \n",
       "202209          63.28         51.14           57.55  \n",
       "202210          56.62         50.39           52.92  \n",
       "202211          79.15         50.62           55.12  "
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#list comprehension이라는 기법 응용한 컬럼 grade down기법인데, 복붙해서 사용합시다~\n",
    "coins_ohlc.columns=['_'.join(col) for col in coins_ohlc.columns]\n",
    "coins_ohlc.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "집계 기준, 집계 함수 각각을 여러 개로 설정할 수도 있습니다.\n",
    "이때는 `agg()`를 사용하여 여러 개의 집계 옵션을 지정해 줍니다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/_x/6zxfdhhj0cn8q6l5rd4411y80000gn/T/ipykernel_83917/1837553109.py:1: FutureWarning: ['Date'] did not aggregate successfully. If any error is raised this will raise in a future version of pandas. Drop these columns/ops to avoid this warning.\n",
      "  coins.groupby(['Month', 'Week']).agg(['mean', 'ohlc'])\n"
     ]
    },
    {
     "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></th>\n",
       "      <th colspan=\"5\" halign=\"left\">Bitcoin</th>\n",
       "      <th colspan=\"5\" halign=\"left\">Ethereum</th>\n",
       "      <th colspan=\"5\" halign=\"left\">Litecoin</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>mean</th>\n",
       "      <th colspan=\"4\" halign=\"left\">ohlc</th>\n",
       "      <th>mean</th>\n",
       "      <th colspan=\"4\" halign=\"left\">ohlc</th>\n",
       "      <th>mean</th>\n",
       "      <th colspan=\"4\" halign=\"left\">ohlc</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>Bitcoin</th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>Ethereum</th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>Litecoin</th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Month</th>\n",
       "      <th>Week</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",
       "      <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>202207</th>\n",
       "      <th>202230</th>\n",
       "      <td>23504.040000</td>\n",
       "      <td>23303.4</td>\n",
       "      <td>23850.0</td>\n",
       "      <td>22958.3</td>\n",
       "      <td>22958.3</td>\n",
       "      <td>1691.752000</td>\n",
       "      <td>1680.00</td>\n",
       "      <td>1726.01</td>\n",
       "      <td>1636.01</td>\n",
       "      <td>1636.01</td>\n",
       "      <td>60.652000</td>\n",
       "      <td>59.77</td>\n",
       "      <td>63.47</td>\n",
       "      <td>59.00</td>\n",
       "      <td>59.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">202208</th>\n",
       "      <th>202231</th>\n",
       "      <td>23017.200000</td>\n",
       "      <td>23175.3</td>\n",
       "      <td>23308.2</td>\n",
       "      <td>22612.1</td>\n",
       "      <td>23271.2</td>\n",
       "      <td>1659.267143</td>\n",
       "      <td>1700.29</td>\n",
       "      <td>1737.71</td>\n",
       "      <td>1606.94</td>\n",
       "      <td>1630.10</td>\n",
       "      <td>59.910000</td>\n",
       "      <td>61.11</td>\n",
       "      <td>62.48</td>\n",
       "      <td>57.75</td>\n",
       "      <td>59.47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202232</th>\n",
       "      <td>24000.742857</td>\n",
       "      <td>24302.8</td>\n",
       "      <td>24442.5</td>\n",
       "      <td>23146.7</td>\n",
       "      <td>23816.3</td>\n",
       "      <td>1870.170000</td>\n",
       "      <td>1935.10</td>\n",
       "      <td>1983.50</td>\n",
       "      <td>1702.80</td>\n",
       "      <td>1778.42</td>\n",
       "      <td>62.151429</td>\n",
       "      <td>63.13</td>\n",
       "      <td>63.80</td>\n",
       "      <td>59.17</td>\n",
       "      <td>62.63</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202233</th>\n",
       "      <td>22569.642857</td>\n",
       "      <td>21517.2</td>\n",
       "      <td>24101.7</td>\n",
       "      <td>20831.3</td>\n",
       "      <td>24101.7</td>\n",
       "      <td>1751.567143</td>\n",
       "      <td>1618.25</td>\n",
       "      <td>1900.25</td>\n",
       "      <td>1575.60</td>\n",
       "      <td>1900.25</td>\n",
       "      <td>58.010000</td>\n",
       "      <td>55.48</td>\n",
       "      <td>61.29</td>\n",
       "      <td>54.03</td>\n",
       "      <td>60.69</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202234</th>\n",
       "      <td>20814.014286</td>\n",
       "      <td>19550.2</td>\n",
       "      <td>21565.4</td>\n",
       "      <td>19550.2</td>\n",
       "      <td>21416.3</td>\n",
       "      <td>1581.258571</td>\n",
       "      <td>1426.25</td>\n",
       "      <td>1695.37</td>\n",
       "      <td>1426.25</td>\n",
       "      <td>1626.75</td>\n",
       "      <td>55.194286</td>\n",
       "      <td>53.38</td>\n",
       "      <td>57.24</td>\n",
       "      <td>52.67</td>\n",
       "      <td>57.24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">202307</th>\n",
       "      <th>202326</th>\n",
       "      <td>30602.250000</td>\n",
       "      <td>30617.7</td>\n",
       "      <td>30617.7</td>\n",
       "      <td>30586.8</td>\n",
       "      <td>30586.8</td>\n",
       "      <td>1931.050000</td>\n",
       "      <td>1937.57</td>\n",
       "      <td>1937.57</td>\n",
       "      <td>1924.53</td>\n",
       "      <td>1924.53</td>\n",
       "      <td>110.345000</td>\n",
       "      <td>113.35</td>\n",
       "      <td>113.35</td>\n",
       "      <td>107.34</td>\n",
       "      <td>107.34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202327</th>\n",
       "      <td>30449.671429</td>\n",
       "      <td>30166.9</td>\n",
       "      <td>31151.3</td>\n",
       "      <td>29913.1</td>\n",
       "      <td>31151.3</td>\n",
       "      <td>1892.807143</td>\n",
       "      <td>1862.91</td>\n",
       "      <td>1955.56</td>\n",
       "      <td>1848.36</td>\n",
       "      <td>1955.56</td>\n",
       "      <td>100.071429</td>\n",
       "      <td>95.12</td>\n",
       "      <td>107.28</td>\n",
       "      <td>95.12</td>\n",
       "      <td>107.28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202328</th>\n",
       "      <td>30533.757143</td>\n",
       "      <td>30235.5</td>\n",
       "      <td>31466.1</td>\n",
       "      <td>30235.5</td>\n",
       "      <td>30415.3</td>\n",
       "      <td>1918.185714</td>\n",
       "      <td>1922.45</td>\n",
       "      <td>2004.77</td>\n",
       "      <td>1871.86</td>\n",
       "      <td>1880.42</td>\n",
       "      <td>96.338571</td>\n",
       "      <td>92.87</td>\n",
       "      <td>101.84</td>\n",
       "      <td>92.87</td>\n",
       "      <td>96.76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202329</th>\n",
       "      <td>29927.871429</td>\n",
       "      <td>30085.9</td>\n",
       "      <td>30139.7</td>\n",
       "      <td>29788.9</td>\n",
       "      <td>30139.7</td>\n",
       "      <td>1890.792857</td>\n",
       "      <td>1888.85</td>\n",
       "      <td>1911.24</td>\n",
       "      <td>1866.25</td>\n",
       "      <td>1911.24</td>\n",
       "      <td>92.488571</td>\n",
       "      <td>93.15</td>\n",
       "      <td>94.10</td>\n",
       "      <td>91.58</td>\n",
       "      <td>92.18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202330</th>\n",
       "      <td>29237.225000</td>\n",
       "      <td>29190.0</td>\n",
       "      <td>29352.2</td>\n",
       "      <td>29178.1</td>\n",
       "      <td>29178.1</td>\n",
       "      <td>1859.685000</td>\n",
       "      <td>1859.03</td>\n",
       "      <td>1872.00</td>\n",
       "      <td>1850.04</td>\n",
       "      <td>1850.04</td>\n",
       "      <td>89.930000</td>\n",
       "      <td>90.47</td>\n",
       "      <td>90.66</td>\n",
       "      <td>89.14</td>\n",
       "      <td>89.14</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>63 rows × 15 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                    Bitcoin                                         Ethereum  \\\n",
       "                       mean     ohlc                                    mean   \n",
       "                    Bitcoin     open     high      low    close     Ethereum   \n",
       "Month  Week                                                                    \n",
       "202207 202230  23504.040000  23303.4  23850.0  22958.3  22958.3  1691.752000   \n",
       "202208 202231  23017.200000  23175.3  23308.2  22612.1  23271.2  1659.267143   \n",
       "       202232  24000.742857  24302.8  24442.5  23146.7  23816.3  1870.170000   \n",
       "       202233  22569.642857  21517.2  24101.7  20831.3  24101.7  1751.567143   \n",
       "       202234  20814.014286  19550.2  21565.4  19550.2  21416.3  1581.258571   \n",
       "...                     ...      ...      ...      ...      ...          ...   \n",
       "202307 202326  30602.250000  30617.7  30617.7  30586.8  30586.8  1931.050000   \n",
       "       202327  30449.671429  30166.9  31151.3  29913.1  31151.3  1892.807143   \n",
       "       202328  30533.757143  30235.5  31466.1  30235.5  30415.3  1918.185714   \n",
       "       202329  29927.871429  30085.9  30139.7  29788.9  30139.7  1890.792857   \n",
       "       202330  29237.225000  29190.0  29352.2  29178.1  29178.1  1859.685000   \n",
       "\n",
       "                                                     Litecoin                  \\\n",
       "                  ohlc                                   mean    ohlc           \n",
       "                  open     high      low    close    Litecoin    open    high   \n",
       "Month  Week                                                                     \n",
       "202207 202230  1680.00  1726.01  1636.01  1636.01   60.652000   59.77   63.47   \n",
       "202208 202231  1700.29  1737.71  1606.94  1630.10   59.910000   61.11   62.48   \n",
       "       202232  1935.10  1983.50  1702.80  1778.42   62.151429   63.13   63.80   \n",
       "       202233  1618.25  1900.25  1575.60  1900.25   58.010000   55.48   61.29   \n",
       "       202234  1426.25  1695.37  1426.25  1626.75   55.194286   53.38   57.24   \n",
       "...                ...      ...      ...      ...         ...     ...     ...   \n",
       "202307 202326  1937.57  1937.57  1924.53  1924.53  110.345000  113.35  113.35   \n",
       "       202327  1862.91  1955.56  1848.36  1955.56  100.071429   95.12  107.28   \n",
       "       202328  1922.45  2004.77  1871.86  1880.42   96.338571   92.87  101.84   \n",
       "       202329  1888.85  1911.24  1866.25  1911.24   92.488571   93.15   94.10   \n",
       "       202330  1859.03  1872.00  1850.04  1850.04   89.930000   90.47   90.66   \n",
       "\n",
       "                               \n",
       "                               \n",
       "                  low   close  \n",
       "Month  Week                    \n",
       "202207 202230   59.00   59.00  \n",
       "202208 202231   57.75   59.47  \n",
       "       202232   59.17   62.63  \n",
       "       202233   54.03   60.69  \n",
       "       202234   52.67   57.24  \n",
       "...               ...     ...  \n",
       "202307 202326  107.34  107.34  \n",
       "       202327   95.12  107.28  \n",
       "       202328   92.87   96.76  \n",
       "       202329   91.58   92.18  \n",
       "       202330   89.14   89.14  \n",
       "\n",
       "[63 rows x 15 columns]"
      ]
     },
     "execution_count": 144,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "coins.groupby(['Month', 'Week']).agg(['mean', 'ohlc'])"
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": "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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## join\n",
    "두 개의 데이터프레임을 하나로 병합합니다.\n",
    "\n",
    "![image.png](attachment:image.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "실제 데이터를 사용하는 것보다는 간단한 데이터프레임으로 직접 확인하는 게 더 이해가 잘 될 거 같아서, 데이터프레임 간단히 만들어서 확인해 볼게요."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "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>PER</th>\n",
       "      <th>PBR</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ㄱㄱ전자</th>\n",
       "      <td>5.3</td>\n",
       "      <td>1.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ㄱㄱ중공업</th>\n",
       "      <td>11.4</td>\n",
       "      <td>0.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ㄱㄱ솔루션</th>\n",
       "      <td>3.3</td>\n",
       "      <td>2.1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        PER  PBR\n",
       "ㄱㄱ전자    5.3  1.2\n",
       "ㄱㄱ중공업  11.4  0.7\n",
       "ㄱㄱ솔루션   3.3  2.1"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#ㄱㄱ그룹 계열사 재무제표\n",
    "df1=pd.DataFrame({'PER':[5.3,11.4, 3.3], 'PBR':[1.2, 0.7, 2.1]}, index=['ㄱㄱ전자', 'ㄱㄱ중공업', 'ㄱㄱ솔루션'])\n",
    "df1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "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>직원수</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ㄱㄱ중공업</th>\n",
       "      <td>5천</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ㄴㄴ중공업</th>\n",
       "      <td>16천</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ㄷㄷ중공업</th>\n",
       "      <td>20천</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       직원수\n",
       "ㄱㄱ중공업   5천\n",
       "ㄴㄴ중공업  16천\n",
       "ㄷㄷ중공업  20천"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#중공업 상장사 직원 수 비교\n",
    "df2=pd.DataFrame({'직원수':['5천','16천', '20천']}, index=['ㄱㄱ중공업', 'ㄴㄴ중공업', 'ㄷㄷ중공업'])\n",
    "df2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "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>PER</th>\n",
       "      <th>PBR</th>\n",
       "      <th>직원수</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ㄱㄱ전자</th>\n",
       "      <td>5.3</td>\n",
       "      <td>1.2</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ㄱㄱ중공업</th>\n",
       "      <td>11.4</td>\n",
       "      <td>0.7</td>\n",
       "      <td>5천</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ㄱㄱ솔루션</th>\n",
       "      <td>3.3</td>\n",
       "      <td>2.1</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        PER  PBR  직원수\n",
       "ㄱㄱ전자    5.3  1.2  NaN\n",
       "ㄱㄱ중공업  11.4  0.7   5천\n",
       "ㄱㄱ솔루션   3.3  2.1  NaN"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1.join(df2,how='left') #inner(default), outer, left, default"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**참고**\n",
    "- 세 개 이상의 데이터프레임을 붙일 때는 데이터프레임들을`[]`로 묶어서 합칩니다. `df1.join([df2,df3,df4], how='inner']` 이런 식으로!\n",
    "- 이때 left join시 가장 왼쪽 인덱스를 기준으로 조인되며, right join은 불가합니다.\n",
    "- 조인되었을 때 동일한 이름의 열이 있으면 조인이 수행되지 않습니다."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "base",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.16"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}