04_pandas_02_dataframe.ipynb

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  "metadata": {
    "colab": {
      "name": "04_pandas_02_dataframe.ipynb",
      "provenance": [],
      "collapsed_sections": [
        "c1kVpPdfNRTZ",
        "CR5LSrBWNMD0",
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      "display_name": "Python 3.8.5 64-bit ('base': conda)",
      "name": "python3"
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    "language_info": {
      "name": "python",
      "version": ""
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/cybermin/2021_PNUAC_AIData/blob/main/04_pandas_02_dataframe.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "c91S0nenHIgF"
      },
      "source": [
        "# **DataFrame**\n",
        "+ 2차원 자료구조인 DataFrame는 행과 열이 있는 테이블 데이터\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "5PCO1T_6HkNU"
      },
      "source": [
        "## **pandas 라이브러리 추가**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TRAkQWf2HhxB"
      },
      "source": [
        "import pandas as pd"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "gUzx35xJMkFR"
      },
      "source": [
        "## 데이터프레임으로 변환\n",
        "* **pd.DataFrame()**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "c1kVpPdfNRTZ"
      },
      "source": [
        "###  리스트를 데이터프레임으로 변환"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "CIOZ77trF5l9"
      },
      "source": [
        "area = ['서울',\t'부산',\t'대구',\t'인천',\t'광주',\t'대전',\t'울산',\t'세종',\t'경기',\t'강원',\t'충북',\t'충남',\t'전북',\t'전남',\t'경북',\t'경남',\t'제주']\n",
        "pm25_avg = [20,13,15,20,19,16,14,18,20,14,19,23,23,14,15,13,14]\n",
        "pm25_max = [22,18,18,30,23,20,16,19,27,18,26,29,30,27,23,17,16]\n",
        "pm25_min = [16,10,11,12,15,12,11,17,13,9,14,19,14,10,8,9,11]"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 550
        },
        "id": "VVTw0bVSNedW",
        "outputId": "f09e0ca9-d430-4e94-8828-a8705347b5d9"
      },
      "source": [
        "#데이터 프레임 생성하기\n",
        " \n",
        "\n",
        "df"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
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              "    }\n",
              "\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>지역</th>\n",
              "      <th>평균</th>\n",
              "      <th>최대</th>\n",
              "      <th>최소</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>서울</td>\n",
              "      <td>20</td>\n",
              "      <td>22</td>\n",
              "      <td>16</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>부산</td>\n",
              "      <td>13</td>\n",
              "      <td>18</td>\n",
              "      <td>10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>대구</td>\n",
              "      <td>15</td>\n",
              "      <td>18</td>\n",
              "      <td>11</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>인천</td>\n",
              "      <td>20</td>\n",
              "      <td>30</td>\n",
              "      <td>12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>광주</td>\n",
              "      <td>19</td>\n",
              "      <td>23</td>\n",
              "      <td>15</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>대전</td>\n",
              "      <td>16</td>\n",
              "      <td>20</td>\n",
              "      <td>12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>울산</td>\n",
              "      <td>14</td>\n",
              "      <td>16</td>\n",
              "      <td>11</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>세종</td>\n",
              "      <td>18</td>\n",
              "      <td>19</td>\n",
              "      <td>17</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>경기</td>\n",
              "      <td>20</td>\n",
              "      <td>27</td>\n",
              "      <td>13</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>강원</td>\n",
              "      <td>14</td>\n",
              "      <td>18</td>\n",
              "      <td>9</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>충북</td>\n",
              "      <td>19</td>\n",
              "      <td>26</td>\n",
              "      <td>14</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>충남</td>\n",
              "      <td>23</td>\n",
              "      <td>29</td>\n",
              "      <td>19</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>전북</td>\n",
              "      <td>23</td>\n",
              "      <td>30</td>\n",
              "      <td>14</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>전남</td>\n",
              "      <td>14</td>\n",
              "      <td>27</td>\n",
              "      <td>10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>경북</td>\n",
              "      <td>15</td>\n",
              "      <td>23</td>\n",
              "      <td>8</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>경남</td>\n",
              "      <td>13</td>\n",
              "      <td>17</td>\n",
              "      <td>9</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>제주</td>\n",
              "      <td>14</td>\n",
              "      <td>16</td>\n",
              "      <td>11</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
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            "text/plain": [
              "    지역  평균  최대  최소\n",
              "0   서울  20  22  16\n",
              "1   부산  13  18  10\n",
              "2   대구  15  18  11\n",
              "3   인천  20  30  12\n",
              "4   광주  19  23  15\n",
              "5   대전  16  20  12\n",
              "6   울산  14  16  11\n",
              "7   세종  18  19  17\n",
              "8   경기  20  27  13\n",
              "9   강원  14  18   9\n",
              "10  충북  19  26  14\n",
              "11  충남  23  29  19\n",
              "12  전북  23  30  14\n",
              "13  전남  14  27  10\n",
              "14  경북  15  23   8\n",
              "15  경남  13  17   9\n",
              "16  제주  14  16  11"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
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        "id": "h4a2b73e33WN",
        "outputId": "f9a3d762-15e7-43e3-e8e9-e3a03d31da62"
      },
      "source": [
        "df['지역']"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0     서울\n",
              "1     부산\n",
              "2     대구\n",
              "3     인천\n",
              "4     광주\n",
              "5     대전\n",
              "6     울산\n",
              "7     세종\n",
              "8     경기\n",
              "9     강원\n",
              "10    충북\n",
              "11    충남\n",
              "12    전북\n",
              "13    전남\n",
              "14    경북\n",
              "15    경남\n",
              "16    제주\n",
              "Name: 지역, dtype: object"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "D2XPYMOe36Tl",
        "outputId": "5cc725d2-3d3b-4db5-e983-378332d5cebb"
      },
      "source": [
        "type(df['지역'])"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "pandas.core.series.Series"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "JS_gxUnAOHSE"
      },
      "source": [
        "## 외부 데이터 가져오기\n",
        "+ csv 읽기\n",
        " - 한글 파일명을 사용할 경우 : df = pd.read_csv(‘파일명‘, engine='python')\n",
        " - 파일 내용 한글이 깨지는 경우 : df = pd.read_csv(‘파일명‘, engine='python', encoding='cp949')\n",
        ">\n",
        "```\n",
        "df = pd.read_csv(‘파일명‘)\n",
        "```\n",
        "\n",
        "+ 엑셀 읽기\n",
        " - 한글 파일명을 사용할 경우 : df = pd.read_excel(‘파일명‘)\n",
        ">\n",
        "```\n",
        "df = pd.pd.read_excel(‘파일명‘)\n",
        "```"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 550
        },
        "id": "rgf7xNS2Owfw",
        "outputId": "84899483-f729-471f-b82f-8dde0d1efbdb"
      },
      "source": [
        "#지역별주간별_초미세먼지.csv 자료 가져오기\n",
        " \n",
        "df"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>지역</th>\n",
              "      <th>주간평균</th>\n",
              "      <th>최고값</th>\n",
              "      <th>최저값</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>서울</td>\n",
              "      <td>20</td>\n",
              "      <td>22</td>\n",
              "      <td>16</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>부산</td>\n",
              "      <td>13</td>\n",
              "      <td>18</td>\n",
              "      <td>10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>대구</td>\n",
              "      <td>15</td>\n",
              "      <td>18</td>\n",
              "      <td>11</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>인천</td>\n",
              "      <td>20</td>\n",
              "      <td>30</td>\n",
              "      <td>12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>광주</td>\n",
              "      <td>19</td>\n",
              "      <td>23</td>\n",
              "      <td>15</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>대전</td>\n",
              "      <td>16</td>\n",
              "      <td>20</td>\n",
              "      <td>12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>울산</td>\n",
              "      <td>14</td>\n",
              "      <td>16</td>\n",
              "      <td>11</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>세종</td>\n",
              "      <td>18</td>\n",
              "      <td>19</td>\n",
              "      <td>17</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>경기</td>\n",
              "      <td>20</td>\n",
              "      <td>27</td>\n",
              "      <td>13</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>강원</td>\n",
              "      <td>14</td>\n",
              "      <td>18</td>\n",
              "      <td>9</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>충북</td>\n",
              "      <td>19</td>\n",
              "      <td>26</td>\n",
              "      <td>14</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>충남</td>\n",
              "      <td>23</td>\n",
              "      <td>29</td>\n",
              "      <td>19</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>전북</td>\n",
              "      <td>23</td>\n",
              "      <td>30</td>\n",
              "      <td>14</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>전남</td>\n",
              "      <td>14</td>\n",
              "      <td>27</td>\n",
              "      <td>10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>경북</td>\n",
              "      <td>15</td>\n",
              "      <td>23</td>\n",
              "      <td>8</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>경남</td>\n",
              "      <td>13</td>\n",
              "      <td>17</td>\n",
              "      <td>9</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>제주</td>\n",
              "      <td>14</td>\n",
              "      <td>16</td>\n",
              "      <td>11</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   지역   주간평균   최고값   최저값 \n",
              "0   서울     20    22    16\n",
              "1   부산     13    18    10\n",
              "2   대구     15    18    11\n",
              "3   인천     20    30    12\n",
              "4   광주     19    23    15\n",
              "5   대전     16    20    12\n",
              "6   울산     14    16    11\n",
              "7   세종     18    19    17\n",
              "8   경기     20    27    13\n",
              "9   강원     14    18     9\n",
              "10  충북     19    26    14\n",
              "11  충남     23    29    19\n",
              "12  전북     23    30    14\n",
              "13  전남     14    27    10\n",
              "14  경북     15    23     8\n",
              "15  경남     13    17     9\n",
              "16  제주     14    16    11"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "2UfN4l5eRHfr"
      },
      "source": [
        "## 데이터프레임(DataFrame) 살펴보기\n",
        "* 데이터프레임의 정보 : **df.info()**\n",
        " - 데이터프레임에 대한 전반적인 정보\n",
        " - 데이터프레임을 구성하는 행과 열의 크기, 컬럼명, 컬럼을 구성하는 값의 자료형 등을 출력\n",
        "+ 데이터프레임의 크기 확인 : **df.shape 속성**\n",
        " - (행, 열) 크기를 확인하기\n",
        " - 행의 개수 : len(데이터프레임), len(.index), .shape[0]\n",
        " - 열의 개수 : len(.column), .shape[1]\n",
        "+ 데이터프레임의 원소의 총개수 : **df.size 속성**\n",
        "+ 데이터프레임 개수 확인 :**df.count()**\n",
        " - Null이 아닌 행의 개수 확인\n",
        " - axis='columns' : Null이 아닌 열의 개수 확인\n",
        "* 데이터프레임의 인덱스 \n",
        " + 열의 인덱스 : **df.colums**\n",
        " + 행의 인덱스 : **df.index**\n",
        " + **데이터프레임의 인덱스 변경**\n",
        "   - 열인덱스 명 변경 : df.column = [열명인덱스]\n",
        "   - 열항목 중 하나를 인덱스로 사용 : df.set_index(열명)\n",
        "   - 인덱스를 일반 데이터 열로 전환 : df.reset_index()"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "RPDi18n9SGRu",
        "outputId": "6518c99c-f04b-4a31-eb7b-9e9c53d68f7d"
      },
      "source": [
        "#데이터프레임의 정보\n",
        " "
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 17 entries, 0 to 16\n",
            "Data columns (total 4 columns):\n",
            " #   Column  Non-Null Count  Dtype \n",
            "---  ------  --------------  ----- \n",
            " 0   지역      17 non-null     object\n",
            " 1   주간평균    17 non-null     int64 \n",
            " 2   최고값     17 non-null     int64 \n",
            " 3   최저값     17 non-null     int64 \n",
            "dtypes: int64(3), object(1)\n",
            "memory usage: 672.0+ bytes\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6TsNgT0b3Js7",
        "outputId": "99300f78-e5cb-4039-a7e9-29c52b938415"
      },
      "source": [
        "#데이터프레임의 크기 확인\n",
        "print('데이터프레임 (행, 열) : ',  )\n",
        "print('데이터프레임 행 개수 len : ',   )\n",
        "print('데이터프레임 행 개수 len : ',   )\n",
        "print('데이터프레임 행 개수 shape : ',  )\n",
        "print('데이터프레임 열 개수 len : ',   )\n",
        "print('데이터프레임 열 개수 shape : ',   )"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "데이터프레임 (행, 열) :  (17, 4)\n",
            "데이터프레임 행 개수 len :  17\n",
            "데이터프레임 행 개수 len :  17\n",
            "데이터프레임 행 개수 shape :  17\n",
            "데이터프레임 열 개수 len :  4\n",
            "데이터프레임 열 개수 shape :  4\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "x820CTxf7sUS",
        "outputId": "f5f7db34-d916-4739-a30e-78c5cc669747"
      },
      "source": [
        "#데이터프레임 각 열의개수 확인\n",
        "print( )\n",
        "print('-'*20)\n",
        "print( )"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "지역       17\n",
            "주간평균     17\n",
            "최고값      17\n",
            "최저값      17\n",
            "dtype: int64\n",
            "--------------------\n",
            "0     4\n",
            "1     4\n",
            "2     4\n",
            "3     4\n",
            "4     4\n",
            "5     4\n",
            "6     4\n",
            "7     4\n",
            "8     4\n",
            "9     4\n",
            "10    4\n",
            "11    4\n",
            "12    4\n",
            "13    4\n",
            "14    4\n",
            "15    4\n",
            "16    4\n",
            "dtype: int64\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "-_PcsEFSDcsV",
        "outputId": "8c92486c-8cbc-4935-d69c-675d96f48e86"
      },
      "source": [
        "#데이터프레임의 원소의 총개수\n",
        "print( )"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "68\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "1VWiVWQ_SQtl",
        "outputId": "90542c38-3726-43f2-9d06-5b091a6c007d"
      },
      "source": [
        "#데이터프레임의 인덱스\n",
        "print('열인덱스 : ',  )\n",
        "print('행인덱스 :',  )"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "열인덱스 :  Index(['지역 ', '주간평균 ', '최고값 ', '최저값 '], dtype='object')\n",
            "행인덱스 : RangeIndex(start=0, stop=17, step=1)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "HTgaV9Y47zOt",
        "outputId": "dc706657-9dbd-40f2-f92f-cf4261e70af2"
      },
      "source": [
        "#각 문자열 요소에서 공백 제거\n",
        "lt = ['지역 ', '주간평균 ', '최고값 ', '최저값 ']\n",
        "lt = \n",
        "lt"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['지역', '주간평균', '최고값', '최저값']"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "DOgIflpZ7n8x",
        "outputId": "a3bc9b15-1b37-42eb-9ff4-91516606d9c4"
      },
      "source": [
        "df['지역 ']"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0     서울\n",
              "1     부산\n",
              "2     대구\n",
              "3     인천\n",
              "4     광주\n",
              "5     대전\n",
              "6     울산\n",
              "7     세종\n",
              "8     경기\n",
              "9     강원\n",
              "10    충북\n",
              "11    충남\n",
              "12    전북\n",
              "13    전남\n",
              "14    경북\n",
              "15    경남\n",
              "16    제주\n",
              "Name: 지역 , dtype: object"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "DxsgZnmASZ-V",
        "outputId": "90428054-b515-4366-d6c9-29dc80714407"
      },
      "source": [
        "#열명의 공백 제거 \n",
        " "
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['지역', '주간평균', '최고값', '최저값'], dtype='object')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "r__w0YOR8WD4",
        "outputId": "46b0920f-0c57-4b75-a5e5-4d2a939ff603"
      },
      "source": [
        "df['지역']"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0     서울\n",
              "1     부산\n",
              "2     대구\n",
              "3     인천\n",
              "4     광주\n",
              "5     대전\n",
              "6     울산\n",
              "7     세종\n",
              "8     경기\n",
              "9     강원\n",
              "10    충북\n",
              "11    충남\n",
              "12    전북\n",
              "13    전남\n",
              "14    경북\n",
              "15    경남\n",
              "16    제주\n",
              "Name: 지역, dtype: object"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 580
        },
        "id": "SI96LxJ1UTrM",
        "outputId": "0d15d652-91c9-4fe5-897d-1264d7f259b9"
      },
      "source": [
        "#지역 컬럼을 행 인덱스로 지정\n",
        " \n",
        "df"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>주간평균</th>\n",
              "      <th>최고값</th>\n",
              "      <th>최저값</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>지역</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>서울</th>\n",
              "      <td>20</td>\n",
              "      <td>22</td>\n",
              "      <td>16</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>부산</th>\n",
              "      <td>13</td>\n",
              "      <td>18</td>\n",
              "      <td>10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>대구</th>\n",
              "      <td>15</td>\n",
              "      <td>18</td>\n",
              "      <td>11</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>인천</th>\n",
              "      <td>20</td>\n",
              "      <td>30</td>\n",
              "      <td>12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>광주</th>\n",
              "      <td>19</td>\n",
              "      <td>23</td>\n",
              "      <td>15</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>대전</th>\n",
              "      <td>16</td>\n",
              "      <td>20</td>\n",
              "      <td>12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>울산</th>\n",
              "      <td>14</td>\n",
              "      <td>16</td>\n",
              "      <td>11</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>세종</th>\n",
              "      <td>18</td>\n",
              "      <td>19</td>\n",
              "      <td>17</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>경기</th>\n",
              "      <td>20</td>\n",
              "      <td>27</td>\n",
              "      <td>13</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>강원</th>\n",
              "      <td>14</td>\n",
              "      <td>18</td>\n",
              "      <td>9</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>충북</th>\n",
              "      <td>19</td>\n",
              "      <td>26</td>\n",
              "      <td>14</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>충남</th>\n",
              "      <td>23</td>\n",
              "      <td>29</td>\n",
              "      <td>19</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>전북</th>\n",
              "      <td>23</td>\n",
              "      <td>30</td>\n",
              "      <td>14</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>전남</th>\n",
              "      <td>14</td>\n",
              "      <td>27</td>\n",
              "      <td>10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>경북</th>\n",
              "      <td>15</td>\n",
              "      <td>23</td>\n",
              "      <td>8</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>경남</th>\n",
              "      <td>13</td>\n",
              "      <td>17</td>\n",
              "      <td>9</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>제주</th>\n",
              "      <td>14</td>\n",
              "      <td>16</td>\n",
              "      <td>11</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "    주간평균  최고값  최저값\n",
              "지역                \n",
              "서울    20   22   16\n",
              "부산    13   18   10\n",
              "대구    15   18   11\n",
              "인천    20   30   12\n",
              "광주    19   23   15\n",
              "대전    16   20   12\n",
              "울산    14   16   11\n",
              "세종    18   19   17\n",
              "경기    20   27   13\n",
              "강원    14   18    9\n",
              "충북    19   26   14\n",
              "충남    23   29   19\n",
              "전북    23   30   14\n",
              "전남    14   27   10\n",
              "경북    15   23    8\n",
              "경남    13   17    9\n",
              "제주    14   16   11"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6bZemWyo8zvB",
        "outputId": "791c72e3-74d5-421a-bfe1-0d1082cb416b"
      },
      "source": [
        "df.index"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['서울', '부산', '대구', '인천', '광주', '대전', '울산', '세종', '경기', '강원', '충북', '충남',\n",
              "       '전북', '전남', '경북', '경남', '제주'],\n",
              "      dtype='object', name='지역')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 550
        },
        "id": "4lb34DSsUm_8",
        "outputId": "de0d7b53-af05-4581-9a3e-2e66590074fb"
      },
      "source": [
        "#인덱스를 일반 데이터 열로 전환\n",
        " \n",
        "df"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>지역</th>\n",
              "      <th>주간평균</th>\n",
              "      <th>최고값</th>\n",
              "      <th>최저값</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>서울</td>\n",
              "      <td>20</td>\n",
              "      <td>22</td>\n",
              "      <td>16</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>부산</td>\n",
              "      <td>13</td>\n",
              "      <td>18</td>\n",
              "      <td>10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>대구</td>\n",
              "      <td>15</td>\n",
              "      <td>18</td>\n",
              "      <td>11</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>인천</td>\n",
              "      <td>20</td>\n",
              "      <td>30</td>\n",
              "      <td>12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>광주</td>\n",
              "      <td>19</td>\n",
              "      <td>23</td>\n",
              "      <td>15</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>대전</td>\n",
              "      <td>16</td>\n",
              "      <td>20</td>\n",
              "      <td>12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>울산</td>\n",
              "      <td>14</td>\n",
              "      <td>16</td>\n",
              "      <td>11</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>세종</td>\n",
              "      <td>18</td>\n",
              "      <td>19</td>\n",
              "      <td>17</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>경기</td>\n",
              "      <td>20</td>\n",
              "      <td>27</td>\n",
              "      <td>13</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>강원</td>\n",
              "      <td>14</td>\n",
              "      <td>18</td>\n",
              "      <td>9</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>충북</td>\n",
              "      <td>19</td>\n",
              "      <td>26</td>\n",
              "      <td>14</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>충남</td>\n",
              "      <td>23</td>\n",
              "      <td>29</td>\n",
              "      <td>19</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>전북</td>\n",
              "      <td>23</td>\n",
              "      <td>30</td>\n",
              "      <td>14</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>전남</td>\n",
              "      <td>14</td>\n",
              "      <td>27</td>\n",
              "      <td>10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>경북</td>\n",
              "      <td>15</td>\n",
              "      <td>23</td>\n",
              "      <td>8</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>경남</td>\n",
              "      <td>13</td>\n",
              "      <td>17</td>\n",
              "      <td>9</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>제주</td>\n",
              "      <td>14</td>\n",
              "      <td>16</td>\n",
              "      <td>11</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "    지역  주간평균  최고값  최저값\n",
              "0   서울    20   22   16\n",
              "1   부산    13   18   10\n",
              "2   대구    15   18   11\n",
              "3   인천    20   30   12\n",
              "4   광주    19   23   15\n",
              "5   대전    16   20   12\n",
              "6   울산    14   16   11\n",
              "7   세종    18   19   17\n",
              "8   경기    20   27   13\n",
              "9   강원    14   18    9\n",
              "10  충북    19   26   14\n",
              "11  충남    23   29   19\n",
              "12  전북    23   30   14\n",
              "13  전남    14   27   10\n",
              "14  경북    15   23    8\n",
              "15  경남    13   17    9\n",
              "16  제주    14   16   11"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "UO8Dw3XWxi97"
      },
      "source": [
        "## **데이터프레임 인덱싱(indexing)과 슬라이싱(slicing)**\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 225
        },
        "id": "kDu43olQ6-t_",
        "outputId": "26a3407a-2ebf-418d-b5c3-e5d5b7df3474"
      },
      "source": [
        "df = df.set_index('지역')\n",
        "df.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>주간평균</th>\n",
              "      <th>최고값</th>\n",
              "      <th>최저값</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>지역</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>서울</th>\n",
              "      <td>20</td>\n",
              "      <td>22</td>\n",
              "      <td>16</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>부산</th>\n",
              "      <td>13</td>\n",
              "      <td>18</td>\n",
              "      <td>10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>대구</th>\n",
              "      <td>15</td>\n",
              "      <td>18</td>\n",
              "      <td>11</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>인천</th>\n",
              "      <td>20</td>\n",
              "      <td>30</td>\n",
              "      <td>12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>광주</th>\n",
              "      <td>19</td>\n",
              "      <td>23</td>\n",
              "      <td>15</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "    주간평균  최고값  최저값\n",
              "지역                \n",
              "서울    20   22   16\n",
              "부산    13   18   10\n",
              "대구    15   18   11\n",
              "인천    20   30   12\n",
              "광주    19   23   15"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Cj62A7iA2MuH"
      },
      "source": [
        "### df[]\n",
        " + 특정 열 가져오기 : df[열인덱스], df[열인덱스 리스트]\n",
        " + 특정 행 가져오기 : df[시작행인덱스:종료행인덱스]  "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "y7CwJ-BjzTDe",
        "outputId": "9a76af0a-bada-4895-de03-9d6a19a7282f"
      },
      "source": [
        "#특정 열(주간평균) 가져오기\n",
        " "
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "지역\n",
              "서울    20\n",
              "부산    13\n",
              "대구    15\n",
              "인천    20\n",
              "광주    19\n",
              "대전    16\n",
              "울산    14\n",
              "세종    18\n",
              "경기    20\n",
              "강원    14\n",
              "충북    19\n",
              "충남    23\n",
              "전북    23\n",
              "전남    14\n",
              "경북    15\n",
              "경남    13\n",
              "제주    14\n",
              "Name: 주간평균, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 580
        },
        "id": "xCoa2WpIzZAn",
        "outputId": "3abfa97f-80d9-4075-90ef-07461fa05cb2"
      },
      "source": [
        "##특정 열(주간평균, 최저값) 가져오기\n",
        " "
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>주간평균</th>\n",
              "      <th>최저값</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>지역</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>서울</th>\n",
              "      <td>20</td>\n",
              "      <td>16</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>부산</th>\n",
              "      <td>13</td>\n",
              "      <td>10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>대구</th>\n",
              "      <td>15</td>\n",
              "      <td>11</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>인천</th>\n",
              "      <td>20</td>\n",
              "      <td>12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>광주</th>\n",
              "      <td>19</td>\n",
              "      <td>15</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>대전</th>\n",
              "      <td>16</td>\n",
              "      <td>12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>울산</th>\n",
              "      <td>14</td>\n",
              "      <td>11</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>세종</th>\n",
              "      <td>18</td>\n",
              "      <td>17</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>경기</th>\n",
              "      <td>20</td>\n",
              "      <td>13</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>강원</th>\n",
              "      <td>14</td>\n",
              "      <td>9</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>충북</th>\n",
              "      <td>19</td>\n",
              "      <td>14</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>충남</th>\n",
              "      <td>23</td>\n",
              "      <td>19</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>전북</th>\n",
              "      <td>23</td>\n",
              "      <td>14</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>전남</th>\n",
              "      <td>14</td>\n",
              "      <td>10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>경북</th>\n",
              "      <td>15</td>\n",
              "      <td>8</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>경남</th>\n",
              "      <td>13</td>\n",
              "      <td>9</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>제주</th>\n",
              "      <td>14</td>\n",
              "      <td>11</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "    주간평균  최저값\n",
              "지역           \n",
              "서울    20   16\n",
              "부산    13   10\n",
              "대구    15   11\n",
              "인천    20   12\n",
              "광주    19   15\n",
              "대전    16   12\n",
              "울산    14   11\n",
              "세종    18   17\n",
              "경기    20   13\n",
              "강원    14    9\n",
              "충북    19   14\n",
              "충남    23   19\n",
              "전북    23   14\n",
              "전남    14   10\n",
              "경북    15    8\n",
              "경남    13    9\n",
              "제주    14   11"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 22
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 166
        },
        "id": "Wm0TBqD42hKZ",
        "outputId": "8bee6650-b957-4f62-8ad6-8beb0a590bf1"
      },
      "source": [
        "#특정행(부산에서 인천까지) 가져오기\n",
        " "
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>주간평균</th>\n",
              "      <th>최고값</th>\n",
              "      <th>최저값</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>지역</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>부산</th>\n",
              "      <td>13</td>\n",
              "      <td>18</td>\n",
              "      <td>10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>대구</th>\n",
              "      <td>15</td>\n",
              "      <td>18</td>\n",
              "      <td>11</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>인천</th>\n",
              "      <td>20</td>\n",
              "      <td>30</td>\n",
              "      <td>12</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "    주간평균  최고값  최저값\n",
              "지역                \n",
              "부산    13   18   10\n",
              "대구    15   18   11\n",
              "인천    20   30   12"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "OQkafCZj21TB"
      },
      "source": [
        "### df.loc[행인덱스, 열인덱스]\n",
        "* 특정 열 가져오기 : df.loc[:, 열인덱스]\n",
        "* 특정 행 가져오기 : df.loc[행인덱스, :]\n",
        "* 특정 항목 가져오기 : df.loc[행인덱스, 열인덱스]"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "swVsCX2Z_xZd",
        "outputId": "129e02b6-f91d-469c-e5ed-aa11d016f0bd"
      },
      "source": [
        "df['최저값']"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "지역\n",
              "서울    16\n",
              "부산    10\n",
              "대구    11\n",
              "인천    12\n",
              "광주    15\n",
              "대전    12\n",
              "울산    11\n",
              "세종    17\n",
              "경기    13\n",
              "강원     9\n",
              "충북    14\n",
              "충남    19\n",
              "전북    14\n",
              "전남    10\n",
              "경북     8\n",
              "경남     9\n",
              "제주    11\n",
              "Name: 최저값, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ur3fWQue4mkE",
        "outputId": "4106064c-6eb1-4f85-edf8-128a306656e5"
      },
      "source": [
        "#loc 메소드로 특정 열(최저값) 가져오기\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "지역\n",
              "서울    16\n",
              "부산    10\n",
              "대구    11\n",
              "인천    12\n",
              "광주    15\n",
              "대전    12\n",
              "울산    11\n",
              "세종    17\n",
              "경기    13\n",
              "강원     9\n",
              "충북    14\n",
              "충남    19\n",
              "전북    14\n",
              "전남    10\n",
              "경북     8\n",
              "경남     9\n",
              "제주    11\n",
              "Name: 최저값, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 26
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 580
        },
        "id": "HlMs_CJfArKV",
        "outputId": "8973634d-7bb7-4c90-8492-7f69d2e41e7b"
      },
      "source": [
        "#loc 메소드로 특정 열(최저값) 가져와서 메소드를 사용하여 데이터프레임으로 변환\n",
        " "
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>최저값</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>지역</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>서울</th>\n",
              "      <td>16</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>부산</th>\n",
              "      <td>10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>대구</th>\n",
              "      <td>11</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>인천</th>\n",
              "      <td>12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>광주</th>\n",
              "      <td>15</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>대전</th>\n",
              "      <td>12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>울산</th>\n",
              "      <td>11</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>세종</th>\n",
              "      <td>17</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>경기</th>\n",
              "      <td>13</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>강원</th>\n",
              "      <td>9</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>충북</th>\n",
              "      <td>14</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>충남</th>\n",
              "      <td>19</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>전북</th>\n",
              "      <td>14</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>전남</th>\n",
              "      <td>10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>경북</th>\n",
              "      <td>8</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>경남</th>\n",
              "      <td>9</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>제주</th>\n",
              "      <td>11</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "    최저값\n",
              "지역     \n",
              "서울   16\n",
              "부산   10\n",
              "대구   11\n",
              "인천   12\n",
              "광주   15\n",
              "대전   12\n",
              "울산   11\n",
              "세종   17\n",
              "경기   13\n",
              "강원    9\n",
              "충북   14\n",
              "충남   19\n",
              "전북   14\n",
              "전남   10\n",
              "경북    8\n",
              "경남    9\n",
              "제주   11"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 580
        },
        "id": "goZEZ4z_AxCn",
        "outputId": "10e33607-2b87-4d41-bfc3-c4b74b01c502"
      },
      "source": [
        "#loc 메소드로 특정 열(최저값) 가져와서 메소드 없이 데이터프레임으로 변환\n",
        "df.loc[:, ['최저값']]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>최저값</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>지역</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>서울</th>\n",
              "      <td>16</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>부산</th>\n",
              "      <td>10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>대구</th>\n",
              "      <td>11</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>인천</th>\n",
              "      <td>12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>광주</th>\n",
              "      <td>15</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>대전</th>\n",
              "      <td>12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>울산</th>\n",
              "      <td>11</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>세종</th>\n",
              "      <td>17</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>경기</th>\n",
              "      <td>13</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>강원</th>\n",
              "      <td>9</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>충북</th>\n",
              "      <td>14</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>충남</th>\n",
              "      <td>19</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>전북</th>\n",
              "      <td>14</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>전남</th>\n",
              "      <td>10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>경북</th>\n",
              "      <td>8</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>경남</th>\n",
              "      <td>9</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>제주</th>\n",
              "      <td>11</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "    최저값\n",
              "지역     \n",
              "서울   16\n",
              "부산   10\n",
              "대구   11\n",
              "인천   12\n",
              "광주   15\n",
              "대전   12\n",
              "울산   11\n",
              "세종   17\n",
              "경기   13\n",
              "강원    9\n",
              "충북   14\n",
              "충남   19\n",
              "전북   14\n",
              "전남   10\n",
              "경북    8\n",
              "경남    9\n",
              "제주   11"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 580
        },
        "id": "pTfKZPju4s8N",
        "outputId": "55228f70-988d-4522-a82a-a4ec4d86d87f"
      },
      "source": [
        "#loc 메소드로 특정 열(주간평균, 최저값) 가져오기\n",
        " "
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>주간평균</th>\n",
              "      <th>최저값</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>지역</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>서울</th>\n",
              "      <td>20</td>\n",
              "      <td>16</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>부산</th>\n",
              "      <td>13</td>\n",
              "      <td>10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>대구</th>\n",
              "      <td>15</td>\n",
              "      <td>11</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>인천</th>\n",
              "      <td>20</td>\n",
              "      <td>12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>광주</th>\n",
              "      <td>19</td>\n",
              "      <td>15</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>대전</th>\n",
              "      <td>16</td>\n",
              "      <td>12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>울산</th>\n",
              "      <td>14</td>\n",
              "      <td>11</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>세종</th>\n",
              "      <td>18</td>\n",
              "      <td>17</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>경기</th>\n",
              "      <td>20</td>\n",
              "      <td>13</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>강원</th>\n",
              "      <td>14</td>\n",
              "      <td>9</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>충북</th>\n",
              "      <td>19</td>\n",
              "      <td>14</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>충남</th>\n",
              "      <td>23</td>\n",
              "      <td>19</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>전북</th>\n",
              "      <td>23</td>\n",
              "      <td>14</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>전남</th>\n",
              "      <td>14</td>\n",
              "      <td>10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>경북</th>\n",
              "      <td>15</td>\n",
              "      <td>8</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>경남</th>\n",
              "      <td>13</td>\n",
              "      <td>9</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>제주</th>\n",
              "      <td>14</td>\n",
              "      <td>11</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "    주간평균  최저값\n",
              "지역           \n",
              "서울    20   16\n",
              "부산    13   10\n",
              "대구    15   11\n",
              "인천    20   12\n",
              "광주    19   15\n",
              "대전    16   12\n",
              "울산    14   11\n",
              "세종    18   17\n",
              "경기    20   13\n",
              "강원    14    9\n",
              "충북    19   14\n",
              "충남    23   19\n",
              "전북    23   14\n",
              "전남    14   10\n",
              "경북    15    8\n",
              "경남    13    9\n",
              "제주    14   11"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 29
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 580
        },
        "id": "4LCD_xQ340Ai",
        "outputId": "70747d53-20a5-4693-e564-e3f7637b7aaf"
      },
      "source": [
        "#loc 메소드로 특정 열(주간평균에서 최저값까지) 가져오기\n",
        " "
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>주간평균</th>\n",
              "      <th>최고값</th>\n",
              "      <th>최저값</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>지역</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>서울</th>\n",
              "      <td>20</td>\n",
              "      <td>22</td>\n",
              "      <td>16</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>부산</th>\n",
              "      <td>13</td>\n",
              "      <td>18</td>\n",
              "      <td>10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>대구</th>\n",
              "      <td>15</td>\n",
              "      <td>18</td>\n",
              "      <td>11</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>인천</th>\n",
              "      <td>20</td>\n",
              "      <td>30</td>\n",
              "      <td>12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>광주</th>\n",
              "      <td>19</td>\n",
              "      <td>23</td>\n",
              "      <td>15</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>대전</th>\n",
              "      <td>16</td>\n",
              "      <td>20</td>\n",
              "      <td>12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>울산</th>\n",
              "      <td>14</td>\n",
              "      <td>16</td>\n",
              "      <td>11</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>세종</th>\n",
              "      <td>18</td>\n",
              "      <td>19</td>\n",
              "      <td>17</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>경기</th>\n",
              "      <td>20</td>\n",
              "      <td>27</td>\n",
              "      <td>13</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>강원</th>\n",
              "      <td>14</td>\n",
              "      <td>18</td>\n",
              "      <td>9</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>충북</th>\n",
              "      <td>19</td>\n",
              "      <td>26</td>\n",
              "      <td>14</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>충남</th>\n",
              "      <td>23</td>\n",
              "      <td>29</td>\n",
              "      <td>19</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>전북</th>\n",
              "      <td>23</td>\n",
              "      <td>30</td>\n",
              "      <td>14</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>전남</th>\n",
              "      <td>14</td>\n",
              "      <td>27</td>\n",
              "      <td>10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>경북</th>\n",
              "      <td>15</td>\n",
              "      <td>23</td>\n",
              "      <td>8</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>경남</th>\n",
              "      <td>13</td>\n",
              "      <td>17</td>\n",
              "      <td>9</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>제주</th>\n",
              "      <td>14</td>\n",
              "      <td>16</td>\n",
              "      <td>11</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "    주간평균  최고값  최저값\n",
              "지역                \n",
              "서울    20   22   16\n",
              "부산    13   18   10\n",
              "대구    15   18   11\n",
              "인천    20   30   12\n",
              "광주    19   23   15\n",
              "대전    16   20   12\n",
              "울산    14   16   11\n",
              "세종    18   19   17\n",
              "경기    20   27   13\n",
              "강원    14   18    9\n",
              "충북    19   26   14\n",
              "충남    23   29   19\n",
              "전북    23   30   14\n",
              "전남    14   27   10\n",
              "경북    15   23    8\n",
              "경남    13   17    9\n",
              "제주    14   16   11"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 106
        },
        "id": "PvhrPBZp49jO",
        "outputId": "bb86a629-0f6c-4688-a73d-4e7eb0da57d2"
      },
      "source": [
        "#특정 행(부산) 가져오기\n",
        " "
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>주간평균</th>\n",
              "      <th>최고값</th>\n",
              "      <th>최저값</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>지역</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>부산</th>\n",
              "      <td>13</td>\n",
              "      <td>18</td>\n",
              "      <td>10</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "    주간평균  최고값  최저값\n",
              "지역                \n",
              "부산    13   18   10"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 31
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 136
        },
        "id": "XAy3Zu3G5Pj3",
        "outputId": "d522b1af-d48d-4543-efd2-9dec6390410d"
      },
      "source": [
        "#특정 행(부산, 인천) 가져오기"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>주간평균</th>\n",
              "      <th>최고값</th>\n",
              "      <th>최저값</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>지역</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>부산</th>\n",
              "      <td>13</td>\n",
              "      <td>18</td>\n",
              "      <td>10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>인천</th>\n",
              "      <td>20</td>\n",
              "      <td>30</td>\n",
              "      <td>12</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "    주간평균  최고값  최저값\n",
              "지역                \n",
              "부산    13   18   10\n",
              "인천    20   30   12"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 32
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 166
        },
        "id": "fvfrg_sp5DjV",
        "outputId": "21590cb8-ad5c-46a8-94d0-55c4c68e8911"
      },
      "source": [
        "#특정 행(부산에서 인천까지) 가져오기"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>주간평균</th>\n",
              "      <th>최고값</th>\n",
              "      <th>최저값</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>지역</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>부산</th>\n",
              "      <td>13</td>\n",
              "      <td>18</td>\n",
              "      <td>10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>대구</th>\n",
              "      <td>15</td>\n",
              "      <td>18</td>\n",
              "      <td>11</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>인천</th>\n",
              "      <td>20</td>\n",
              "      <td>30</td>\n",
              "      <td>12</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "    주간평균  최고값  최저값\n",
              "지역                \n",
              "부산    13   18   10\n",
              "대구    15   18   11\n",
              "인천    20   30   12"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 33
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "JaH23lSz5U1q",
        "outputId": "6edaf01b-9728-414e-bd9e-177ac8057a65"
      },
      "source": [
        "#특정 항목(부산의 주간평균) 가져오기\n",
        " "
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "13"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 34
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 136
        },
        "id": "JzZvoYtp5d_X",
        "outputId": "093a7c60-28d0-4317-bf7b-eeb4eeaebd32"
      },
      "source": [
        "#특정 항목(부산과 인천의 주간평균과 최저값) 가져오기\n",
        " "
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>주간평균</th>\n",
              "      <th>최저값</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>지역</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>부산</th>\n",
              "      <td>13</td>\n",
              "      <td>10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>인천</th>\n",
              "      <td>20</td>\n",
              "      <td>12</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "    주간평균  최저값\n",
              "지역           \n",
              "부산    13   10\n",
              "인천    20   12"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 35
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 166
        },
        "id": "_Ec3ZWyu5kVA",
        "outputId": "8f60db26-e5ec-4c8d-8f6a-84131b7d5b31"
      },
      "source": [
        "#특정 항목(부산에서 인천까지의 주간평균에서 최저값까지) 가져오기"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>주간평균</th>\n",
              "      <th>최고값</th>\n",
              "      <th>최저값</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>지역</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>부산</th>\n",
              "      <td>13</td>\n",
              "      <td>18</td>\n",
              "      <td>10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>대구</th>\n",
              "      <td>15</td>\n",
              "      <td>18</td>\n",
              "      <td>11</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>인천</th>\n",
              "      <td>20</td>\n",
              "      <td>30</td>\n",
              "      <td>12</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "    주간평균  최고값  최저값\n",
              "지역                \n",
              "부산    13   18   10\n",
              "대구    15   18   11\n",
              "인천    20   30   12"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 36
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9vn-EO9V58vy"
      },
      "source": [
        "### df.iloc[행인덱스순서, 열인덱스순서]\n",
        "* 특정 열 가져오기 : df.loc[:, 열인덱스순서]\n",
        "* 특정 행 가져오기 : df.loc[행인덱스순서, :]\n",
        "* 특정 항목 가져오기 : df.loc[행인덱스순서, 열인덱스순서]"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "gO8u92nq6Wwe",
        "outputId": "fee2562e-aed0-4ba0-fae3-9d50b87df177"
      },
      "source": [
        "#특정 열 가져오기\n",
        "#df.loc[:, '최저값'] \n",
        "#iloc로 변경"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "지역\n",
              "서울    16\n",
              "부산    10\n",
              "대구    11\n",
              "인천    12\n",
              "광주    15\n",
              "대전    12\n",
              "울산    11\n",
              "세종    17\n",
              "경기    13\n",
              "강원     9\n",
              "충북    14\n",
              "충남    19\n",
              "전북    14\n",
              "전남    10\n",
              "경북     8\n",
              "경남     9\n",
              "제주    11\n",
              "Name: 최저값, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 37
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 580
        },
        "id": "JLqavk_Q6dSJ",
        "outputId": "3652e426-a498-4626-d7b9-46e85efed9c2"
      },
      "source": [
        "#df.loc[:, ['주간평균', '최저값']]\n",
        "#iloc로 변경"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>주간평균</th>\n",
              "      <th>최저값</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>지역</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>서울</th>\n",
              "      <td>20</td>\n",
              "      <td>16</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>부산</th>\n",
              "      <td>13</td>\n",
              "      <td>10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>대구</th>\n",
              "      <td>15</td>\n",
              "      <td>11</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>인천</th>\n",
              "      <td>20</td>\n",
              "      <td>12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>광주</th>\n",
              "      <td>19</td>\n",
              "      <td>15</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>대전</th>\n",
              "      <td>16</td>\n",
              "      <td>12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>울산</th>\n",
              "      <td>14</td>\n",
              "      <td>11</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>세종</th>\n",
              "      <td>18</td>\n",
              "      <td>17</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>경기</th>\n",
              "      <td>20</td>\n",
              "      <td>13</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>강원</th>\n",
              "      <td>14</td>\n",
              "      <td>9</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>충북</th>\n",
              "      <td>19</td>\n",
              "      <td>14</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>충남</th>\n",
              "      <td>23</td>\n",
              "      <td>19</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>전북</th>\n",
              "      <td>23</td>\n",
              "      <td>14</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>전남</th>\n",
              "      <td>14</td>\n",
              "      <td>10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>경북</th>\n",
              "      <td>15</td>\n",
              "      <td>8</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>경남</th>\n",
              "      <td>13</td>\n",
              "      <td>9</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>제주</th>\n",
              "      <td>14</td>\n",
              "      <td>11</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "    주간평균  최저값\n",
              "지역           \n",
              "서울    20   16\n",
              "부산    13   10\n",
              "대구    15   11\n",
              "인천    20   12\n",
              "광주    19   15\n",
              "대전    16   12\n",
              "울산    14   11\n",
              "세종    18   17\n",
              "경기    20   13\n",
              "강원    14    9\n",
              "충북    19   14\n",
              "충남    23   19\n",
              "전북    23   14\n",
              "전남    14   10\n",
              "경북    15    8\n",
              "경남    13    9\n",
              "제주    14   11"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 38
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 580
        },
        "id": "hiV1UrDQ6lNJ",
        "outputId": "cb315570-9f72-45b9-d178-d9e8aef20596"
      },
      "source": [
        "#df.loc[:, '주간평균':'최저값']\n",
        "#iloc로 변경"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>주간평균</th>\n",
              "      <th>최고값</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>지역</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>서울</th>\n",
              "      <td>20</td>\n",
              "      <td>22</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>부산</th>\n",
              "      <td>13</td>\n",
              "      <td>18</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>대구</th>\n",
              "      <td>15</td>\n",
              "      <td>18</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>인천</th>\n",
              "      <td>20</td>\n",
              "      <td>30</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>광주</th>\n",
              "      <td>19</td>\n",
              "      <td>23</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>대전</th>\n",
              "      <td>16</td>\n",
              "      <td>20</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>울산</th>\n",
              "      <td>14</td>\n",
              "      <td>16</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>세종</th>\n",
              "      <td>18</td>\n",
              "      <td>19</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>경기</th>\n",
              "      <td>20</td>\n",
              "      <td>27</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>강원</th>\n",
              "      <td>14</td>\n",
              "      <td>18</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>충북</th>\n",
              "      <td>19</td>\n",
              "      <td>26</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>충남</th>\n",
              "      <td>23</td>\n",
              "      <td>29</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>전북</th>\n",
              "      <td>23</td>\n",
              "      <td>30</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>전남</th>\n",
              "      <td>14</td>\n",
              "      <td>27</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>경북</th>\n",
              "      <td>15</td>\n",
              "      <td>23</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>경남</th>\n",
              "      <td>13</td>\n",
              "      <td>17</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>제주</th>\n",
              "      <td>14</td>\n",
              "      <td>16</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "    주간평균  최고값\n",
              "지역           \n",
              "서울    20   22\n",
              "부산    13   18\n",
              "대구    15   18\n",
              "인천    20   30\n",
              "광주    19   23\n",
              "대전    16   20\n",
              "울산    14   16\n",
              "세종    18   19\n",
              "경기    20   27\n",
              "강원    14   18\n",
              "충북    19   26\n",
              "충남    23   29\n",
              "전북    23   30\n",
              "전남    14   27\n",
              "경북    15   23\n",
              "경남    13   17\n",
              "제주    14   16"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 39
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "0eKovdGO6xxy",
        "outputId": "0c84fcce-dd49-4b74-d689-0eaa3f5cdb87"
      },
      "source": [
        "#특정 행 가져오기\n",
        "#df.loc['부산',:]\n",
        "#iloc로 변경"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "주간평균    13\n",
              "최고값     18\n",
              "최저값     10\n",
              "Name: 부산, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 40
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 136
        },
        "id": "fQt4kZCR63yx",
        "outputId": "46ea1f9c-549d-45ef-c6b8-514ba8bd368f"
      },
      "source": [
        "#df.loc[['부산', '인천'], :]\n",
        "#iloc로 변경"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>주간평균</th>\n",
              "      <th>최고값</th>\n",
              "      <th>최저값</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>지역</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>부산</th>\n",
              "      <td>13</td>\n",
              "      <td>18</td>\n",
              "      <td>10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>인천</th>\n",
              "      <td>20</td>\n",
              "      <td>30</td>\n",
              "      <td>12</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "    주간평균  최고값  최저값\n",
              "지역                \n",
              "부산    13   18   10\n",
              "인천    20   30   12"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 41
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 166
        },
        "id": "8sSgV4QzAGZS",
        "outputId": "d0be5d70-7c33-452c-e1de-b085c4f9ad46"
      },
      "source": [
        "#df.loc['부산':'인천', :]\n",
        "#iloc로 변경"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>주간평균</th>\n",
              "      <th>최고값</th>\n",
              "      <th>최저값</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>지역</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>부산</th>\n",
              "      <td>13</td>\n",
              "      <td>18</td>\n",
              "      <td>10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>대구</th>\n",
              "      <td>15</td>\n",
              "      <td>18</td>\n",
              "      <td>11</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>인천</th>\n",
              "      <td>20</td>\n",
              "      <td>30</td>\n",
              "      <td>12</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "    주간평균  최고값  최저값\n",
              "지역                \n",
              "부산    13   18   10\n",
              "대구    15   18   11\n",
              "인천    20   30   12"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 42
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "xweF6XzvAIVR",
        "outputId": "8f74a531-f111-4505-de46-674a1ef2aa67"
      },
      "source": [
        "#특정 항목 가져오기\n",
        "#df.loc['부산', '주간평균']\n",
        "#iloc로 변경"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "13"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 43
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 136
        },
        "id": "nhAX9CKmAJ0N",
        "outputId": "30189b66-2e0e-4d00-ce2a-02282a0af60f"
      },
      "source": [
        "#df.loc[['부산','인천'],['주간평균', '최저값']]\n",
        "#iloc로 변경"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>주간평균</th>\n",
              "      <th>최저값</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>지역</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>서울</th>\n",
              "      <td>20</td>\n",
              "      <td>16</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>인천</th>\n",
              "      <td>20</td>\n",
              "      <td>12</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "    주간평균  최저값\n",
              "지역           \n",
              "서울    20   16\n",
              "인천    20   12"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 44
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 166
        },
        "id": "V-HoJIUAAMm-",
        "outputId": "59ec9040-fb89-40fb-9f19-30992ca21f7e"
      },
      "source": [
        "#df.loc['부산':'인천','주간평균':'최저값']\n",
        "#iloc로 변경"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>주간평균</th>\n",
              "      <th>최고값</th>\n",
              "      <th>최저값</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>지역</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>부산</th>\n",
              "      <td>13</td>\n",
              "      <td>18</td>\n",
              "      <td>10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>대구</th>\n",
              "      <td>15</td>\n",
              "      <td>18</td>\n",
              "      <td>11</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>인천</th>\n",
              "      <td>20</td>\n",
              "      <td>30</td>\n",
              "      <td>12</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "    주간평균  최고값  최저값\n",
              "지역                \n",
              "부산    13   18   10\n",
              "대구    15   18   11\n",
              "인천    20   30   12"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 45
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "vvpKts0-Bd-U"
      },
      "source": [
        "## **데이터프레임(DataFrame) 기본 조회와 기초 통계 메소드**\n",
        "* head(n) : 상위 n개 조회, n생략 시 5개 조회\n",
        "+ tail(n) : 하위 n개 조회, n생략 시 5개 조회\n",
        "+ describe() : 요약 통계량 계산\n",
        "+ mean() : 평균\n",
        "+ max() : 최대\n",
        "+ min() : 최소\n",
        "+ std()  : 표준편차"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 136
        },
        "id": "Xl1QlqoKCdag",
        "outputId": "d80ec7a9-4d77-4eae-8c52-a069243058cd"
      },
      "source": [
        "df.head(2)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>주간평균</th>\n",
              "      <th>최고값</th>\n",
              "      <th>최저값</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>지역</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>서울</th>\n",
              "      <td>20</td>\n",
              "      <td>22</td>\n",
              "      <td>16</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>부산</th>\n",
              "      <td>13</td>\n",
              "      <td>18</td>\n",
              "      <td>10</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "    주간평균  최고값  최저값\n",
              "지역                \n",
              "서울    20   22   16\n",
              "부산    13   18   10"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 46
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 136
        },
        "id": "bSbGKI_8CdYN",
        "outputId": "b6346e59-75a9-4675-c0e7-91628300aa38"
      },
      "source": [
        "df.tail(2)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>주간평균</th>\n",
              "      <th>최고값</th>\n",
              "      <th>최저값</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>지역</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>경남</th>\n",
              "      <td>13</td>\n",
              "      <td>17</td>\n",
              "      <td>9</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>제주</th>\n",
              "      <td>14</td>\n",
              "      <td>16</td>\n",
              "      <td>11</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "    주간평균  최고값  최저값\n",
              "지역                \n",
              "경남    13   17    9\n",
              "제주    14   16   11"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 47
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 284
        },
        "id": "AFi0th9aCsbf",
        "outputId": "e299d9b2-dda5-4678-c40b-d3aaf5f90754"
      },
      "source": [
        "df.describe()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>주간평균</th>\n",
              "      <th>최고값</th>\n",
              "      <th>최저값</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>17.000000</td>\n",
              "      <td>17.000000</td>\n",
              "      <td>17.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>17.058824</td>\n",
              "      <td>22.294118</td>\n",
              "      <td>12.411765</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>3.399827</td>\n",
              "      <td>5.009550</td>\n",
              "      <td>3.063063</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>13.000000</td>\n",
              "      <td>16.000000</td>\n",
              "      <td>8.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>14.000000</td>\n",
              "      <td>18.000000</td>\n",
              "      <td>10.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>16.000000</td>\n",
              "      <td>22.000000</td>\n",
              "      <td>12.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>20.000000</td>\n",
              "      <td>27.000000</td>\n",
              "      <td>14.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>23.000000</td>\n",
              "      <td>30.000000</td>\n",
              "      <td>19.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "            주간평균        최고값        최저값\n",
              "count  17.000000  17.000000  17.000000\n",
              "mean   17.058824  22.294118  12.411765\n",
              "std     3.399827   5.009550   3.063063\n",
              "min    13.000000  16.000000   8.000000\n",
              "25%    14.000000  18.000000  10.000000\n",
              "50%    16.000000  22.000000  12.000000\n",
              "75%    20.000000  27.000000  14.000000\n",
              "max    23.000000  30.000000  19.000000"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 48
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "H_xl7uLIEn_c"
      },
      "source": [
        "## 자주사용되는 메소드\n",
        "+ 행열 전환 : df.T\n",
        "+ 정렬\n",
        " - 행열 인덱스 정렬 : df.sort_index(axis=n), n생략 또는 0:행, 1:열\n",
        " - 행렬 값 정렬 : df.sort_values()"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 580
        },
        "id": "Cij_DtKNgN-d",
        "outputId": "2a4ded0d-a0f9-4095-e2d9-832b59419806"
      },
      "source": [
        "df"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>주간평균</th>\n",
              "      <th>최고값</th>\n",
              "      <th>최저값</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>지역</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>서울</th>\n",
              "      <td>20</td>\n",
              "      <td>22</td>\n",
              "      <td>16</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>부산</th>\n",
              "      <td>13</td>\n",
              "      <td>18</td>\n",
              "      <td>10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>대구</th>\n",
              "      <td>15</td>\n",
              "      <td>18</td>\n",
              "      <td>11</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>인천</th>\n",
              "      <td>20</td>\n",
              "      <td>30</td>\n",
              "      <td>12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>광주</th>\n",
              "      <td>19</td>\n",
              "      <td>23</td>\n",
              "      <td>15</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>대전</th>\n",
              "      <td>16</td>\n",
              "      <td>20</td>\n",
              "      <td>12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>울산</th>\n",
              "      <td>14</td>\n",
              "      <td>16</td>\n",
              "      <td>11</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>세종</th>\n",
              "      <td>18</td>\n",
              "      <td>19</td>\n",
              "      <td>17</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>경기</th>\n",
              "      <td>20</td>\n",
              "      <td>27</td>\n",
              "      <td>13</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>강원</th>\n",
              "      <td>14</td>\n",
              "      <td>18</td>\n",
              "      <td>9</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>충북</th>\n",
              "      <td>19</td>\n",
              "      <td>26</td>\n",
              "      <td>14</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>충남</th>\n",
              "      <td>23</td>\n",
              "      <td>29</td>\n",
              "      <td>19</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>전북</th>\n",
              "      <td>23</td>\n",
              "      <td>30</td>\n",
              "      <td>14</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>전남</th>\n",
              "      <td>14</td>\n",
              "      <td>27</td>\n",
              "      <td>10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>경북</th>\n",
              "      <td>15</td>\n",
              "      <td>23</td>\n",
              "      <td>8</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>경남</th>\n",
              "      <td>13</td>\n",
              "      <td>17</td>\n",
              "      <td>9</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>제주</th>\n",
              "      <td>14</td>\n",
              "      <td>16</td>\n",
              "      <td>11</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "    주간평균  최고값  최저값\n",
              "지역                \n",
              "서울    20   22   16\n",
              "부산    13   18   10\n",
              "대구    15   18   11\n",
              "인천    20   30   12\n",
              "광주    19   23   15\n",
              "대전    16   20   12\n",
              "울산    14   16   11\n",
              "세종    18   19   17\n",
              "경기    20   27   13\n",
              "강원    14   18    9\n",
              "충북    19   26   14\n",
              "충남    23   29   19\n",
              "전북    23   30   14\n",
              "전남    14   27   10\n",
              "경북    15   23    8\n",
              "경남    13   17    9\n",
              "제주    14   16   11"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 49
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 136
        },
        "id": "SWJiNVmBBqh2",
        "outputId": "02f49db7-52b4-44b9-dbe4-91d352825e49"
      },
      "source": [
        "#행과 열 바꾸기"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>지역</th>\n",
              "      <th>서울</th>\n",
              "      <th>부산</th>\n",
              "      <th>대구</th>\n",
              "      <th>인천</th>\n",
              "      <th>광주</th>\n",
              "      <th>대전</th>\n",
              "      <th>울산</th>\n",
              "      <th>세종</th>\n",
              "      <th>경기</th>\n",
              "      <th>강원</th>\n",
              "      <th>충북</th>\n",
              "      <th>충남</th>\n",
              "      <th>전북</th>\n",
              "      <th>전남</th>\n",
              "      <th>경북</th>\n",
              "      <th>경남</th>\n",
              "      <th>제주</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>주간평균</th>\n",
              "      <td>20</td>\n",
              "      <td>13</td>\n",
              "      <td>15</td>\n",
              "      <td>20</td>\n",
              "      <td>19</td>\n",
              "      <td>16</td>\n",
              "      <td>14</td>\n",
              "      <td>18</td>\n",
              "      <td>20</td>\n",
              "      <td>14</td>\n",
              "      <td>19</td>\n",
              "      <td>23</td>\n",
              "      <td>23</td>\n",
              "      <td>14</td>\n",
              "      <td>15</td>\n",
              "      <td>13</td>\n",
              "      <td>14</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>최고값</th>\n",
              "      <td>22</td>\n",
              "      <td>18</td>\n",
              "      <td>18</td>\n",
              "      <td>30</td>\n",
              "      <td>23</td>\n",
              "      <td>20</td>\n",
              "      <td>16</td>\n",
              "      <td>19</td>\n",
              "      <td>27</td>\n",
              "      <td>18</td>\n",
              "      <td>26</td>\n",
              "      <td>29</td>\n",
              "      <td>30</td>\n",
              "      <td>27</td>\n",
              "      <td>23</td>\n",
              "      <td>17</td>\n",
              "      <td>16</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>최저값</th>\n",
              "      <td>16</td>\n",
              "      <td>10</td>\n",
              "      <td>11</td>\n",
              "      <td>12</td>\n",
              "      <td>15</td>\n",
              "      <td>12</td>\n",
              "      <td>11</td>\n",
              "      <td>17</td>\n",
              "      <td>13</td>\n",
              "      <td>9</td>\n",
              "      <td>14</td>\n",
              "      <td>19</td>\n",
              "      <td>14</td>\n",
              "      <td>10</td>\n",
              "      <td>8</td>\n",
              "      <td>9</td>\n",
              "      <td>11</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "지역    서울  부산  대구  인천  광주  대전  울산  세종  경기  강원  충북  충남  전북  전남  경북  경남  제주\n",
              "주간평균  20  13  15  20  19  16  14  18  20  14  19  23  23  14  15  13  14\n",
              "최고값   22  18  18  30  23  20  16  19  27  18  26  29  30  27  23  17  16\n",
              "최저값   16  10  11  12  15  12  11  17  13   9  14  19  14  10   8   9  11"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 50
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "GOBRXRIYgaA9",
        "outputId": "0ec7b463-bd01-4f2e-ea68-97362fce533a"
      },
      "source": [
        "#한글 폰트 사용설치\n",
        "%config InlineBackend.figure_format = 'retina'\n",
        "\n",
        "!apt -qq -y install fonts-nanum"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "fonts-nanum is already the newest version (20170925-1).\n",
            "The following package was automatically installed and is no longer required:\n",
            "  libnvidia-common-460\n",
            "Use 'apt autoremove' to remove it.\n",
            "0 upgraded, 0 newly installed, 0 to remove and 34 not upgraded.\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "k_tE7uvdCu5Y"
      },
      "source": [
        "import pandas as pd"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "JyBT3d_3gcPR"
      },
      "source": [
        "import matplotlib.pyplot as plt\n",
        " \n",
        "import matplotlib as mpl\n",
        "import matplotlib.font_manager as fm\n",
        "fontpath = '/usr/share/fonts/truetype/nanum/NanumBarunGothic.ttf'\n",
        "font = fm.FontProperties(fname=fontpath, size=9)\n",
        "plt.rc('font', family='NanumBarunGothic') \n",
        "mpl.font_manager._rebuild()\n",
        "\n",
        "import warnings\n",
        "warnings.filterwarnings('ignore')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 550
        },
        "id": "HXYI8OL8Cp7m",
        "outputId": "cdc6122c-530b-4a2a-8cc1-c268e04fbe60"
      },
      "source": [
        "#주간별 지역별주간별_초미세먼지.csv 데이터 가져오기\n",
        "df"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>지역</th>\n",
              "      <th>주간평균</th>\n",
              "      <th>최고값</th>\n",
              "      <th>최저값</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>서울</td>\n",
              "      <td>20</td>\n",
              "      <td>22</td>\n",
              "      <td>16</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>부산</td>\n",
              "      <td>13</td>\n",
              "      <td>18</td>\n",
              "      <td>10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>대구</td>\n",
              "      <td>15</td>\n",
              "      <td>18</td>\n",
              "      <td>11</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>인천</td>\n",
              "      <td>20</td>\n",
              "      <td>30</td>\n",
              "      <td>12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>광주</td>\n",
              "      <td>19</td>\n",
              "      <td>23</td>\n",
              "      <td>15</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>대전</td>\n",
              "      <td>16</td>\n",
              "      <td>20</td>\n",
              "      <td>12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>울산</td>\n",
              "      <td>14</td>\n",
              "      <td>16</td>\n",
              "      <td>11</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>세종</td>\n",
              "      <td>18</td>\n",
              "      <td>19</td>\n",
              "      <td>17</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>경기</td>\n",
              "      <td>20</td>\n",
              "      <td>27</td>\n",
              "      <td>13</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>강원</td>\n",
              "      <td>14</td>\n",
              "      <td>18</td>\n",
              "      <td>9</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>충북</td>\n",
              "      <td>19</td>\n",
              "      <td>26</td>\n",
              "      <td>14</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>충남</td>\n",
              "      <td>23</td>\n",
              "      <td>29</td>\n",
              "      <td>19</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>전북</td>\n",
              "      <td>23</td>\n",
              "      <td>30</td>\n",
              "      <td>14</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>전남</td>\n",
              "      <td>14</td>\n",
              "      <td>27</td>\n",
              "      <td>10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>경북</td>\n",
              "      <td>15</td>\n",
              "      <td>23</td>\n",
              "      <td>8</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>경남</td>\n",
              "      <td>13</td>\n",
              "      <td>17</td>\n",
              "      <td>9</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>제주</td>\n",
              "      <td>14</td>\n",
              "      <td>16</td>\n",
              "      <td>11</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   지역   주간평균   최고값   최저값 \n",
              "0   서울     20    22    16\n",
              "1   부산     13    18    10\n",
              "2   대구     15    18    11\n",
              "3   인천     20    30    12\n",
              "4   광주     19    23    15\n",
              "5   대전     16    20    12\n",
              "6   울산     14    16    11\n",
              "7   세종     18    19    17\n",
              "8   경기     20    27    13\n",
              "9   강원     14    18     9\n",
              "10  충북     19    26    14\n",
              "11  충남     23    29    19\n",
              "12  전북     23    30    14\n",
              "13  전남     14    27    10\n",
              "14  경북     15    23     8\n",
              "15  경남     13    17     9\n",
              "16  제주     14    16    11"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fClxsVoqCz_U"
      },
      "source": [
        "#지역으로 인덱스 변경\n",
        " "
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 225
        },
        "id": "lEFzRXkJC5vv",
        "outputId": "fe4d240d-7ade-4c5e-c663-9ba5f272030f"
      },
      "source": [
        "df.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>주간평균</th>\n",
              "      <th>최고값</th>\n",
              "      <th>최저값</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>지역</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>서울</th>\n",
              "      <td>20</td>\n",
              "      <td>22</td>\n",
              "      <td>16</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>부산</th>\n",
              "      <td>13</td>\n",
              "      <td>18</td>\n",
              "      <td>10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>대구</th>\n",
              "      <td>15</td>\n",
              "      <td>18</td>\n",
              "      <td>11</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>인천</th>\n",
              "      <td>20</td>\n",
              "      <td>30</td>\n",
              "      <td>12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>광주</th>\n",
              "      <td>19</td>\n",
              "      <td>23</td>\n",
              "      <td>15</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "     주간평균   최고값   최저값 \n",
              "지역                    \n",
              "서울      20    22    16\n",
              "부산      13    18    10\n",
              "대구      15    18    11\n",
              "인천      20    30    12\n",
              "광주      19    23    15"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 442
        },
        "id": "u0z6vc3EgP0s",
        "outputId": "3e2f6ae9-5975-479c-f8a8-bdf47784f73a"
      },
      "source": [
        "#데이터 프레임 그래프 그리기"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 720x504 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    }
  ]
}