데이터분석_3주차_아파트실거래가분석_I(나영훈).ipynb

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        "<a href=\"https://colab.research.google.com/github/younghoonNa/pythonDT/blob/main/%EB%8D%B0%EC%9D%B4%ED%84%B0%EB%B6%84%EC%84%9D_3%EC%A3%BC%EC%B0%A8_%EC%95%84%ED%8C%8C%ED%8A%B8%EC%8B%A4%EA%B1%B0%EB%9E%98%EA%B0%80%EB%B6%84%EC%84%9D_I(%EB%82%98%EC%98%81%ED%9B%88).ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!wget http://49.247.133.7/2020-seoul-apt-price.csv\n",
        "!wget http://49.247.133.7/loc_code.xlsx"
      ],
      "metadata": {
        "id": "fJFY74xg6aIn",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "a3c45ffe-39d4-4260-8c9d-49a2ffd0850a"
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "--2021-12-30 01:29:02--  http://49.247.133.7/2020-seoul-apt-price.csv\n",
            "Connecting to 49.247.133.7:80... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 5531058 (5.3M) [text/csv]\n",
            "Saving to: ‘2020-seoul-apt-price.csv’\n",
            "\n",
            "2020-seoul-apt-pric 100%[===================>]   5.27M  2.18MB/s    in 2.4s    \n",
            "\n",
            "2021-12-30 01:29:05 (2.18 MB/s) - ‘2020-seoul-apt-price.csv’ saved [5531058/5531058]\n",
            "\n",
            "--2021-12-30 01:29:05--  http://49.247.133.7/loc_code.xlsx\n",
            "Connecting to 49.247.133.7:80... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 11114 (11K) [application/vnd.openxmlformats-officedocument.spreadsheetml.sheet]\n",
            "Saving to: ‘loc_code.xlsx’\n",
            "\n",
            "loc_code.xlsx       100%[===================>]  10.85K  --.-KB/s    in 0s      \n",
            "\n",
            "2021-12-30 01:29:05 (228 MB/s) - ‘loc_code.xlsx’ saved [11114/11114]\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {
        "id": "hc5DGsD2hQ8Q"
      },
      "outputs": [],
      "source": [
        "import pandas as pd\n",
        "import numpy as np"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ckWUt0ejhQ8W"
      },
      "source": [
        "# 1. 법정동 코드 가공"
      ]
    },
    {
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      "execution_count": 4,
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              "      <th>0</th>\n",
              "      <td>서울특별시</td>\n",
              "      <td>종로구</td>\n",
              "      <td>11110</td>\n",
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              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>서울특별시</td>\n",
              "      <td>중구</td>\n",
              "      <td>11140</td>\n",
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              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>서울특별시</td>\n",
              "      <td>용산구</td>\n",
              "      <td>11170</td>\n",
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              "      <th>3</th>\n",
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              "      <td>성동구</td>\n",
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              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>서울특별시</td>\n",
              "      <td>광진구</td>\n",
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            "text/plain": [
              "     시도명 시군구명   지역코드\n",
              "0  서울특별시  종로구  11110\n",
              "1  서울특별시   중구  11140\n",
              "2  서울특별시  용산구  11170\n",
              "3  서울특별시  성동구  11200\n",
              "4  서울특별시  광진구  11215"
            ]
          },
          "metadata": {},
          "execution_count": 4
        }
      ],
      "source": [
        "# loc_code.xlsx 파일을 읽어 locCode 변수에 저장하세요.\n",
        "locCode = pd.read_excel('loc_code.xlsx')\n",
        "locCode.head()"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "locCode"
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        "id": "uTCTttdcAJ1N",
        "outputId": "6f31f1ad-7095-4786-e8ba-789cc5510d5e"
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "      <td>용산구</td>\n",
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              "      <td>성동구</td>\n",
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              "      <th>4</th>\n",
              "      <td>서울특별시</td>\n",
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              "      <th>261</th>\n",
              "      <td>경상남도</td>\n",
              "      <td>함양군</td>\n",
              "      <td>48870</td>\n",
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              "    <tr>\n",
              "      <th>262</th>\n",
              "      <td>경상남도</td>\n",
              "      <td>거창군</td>\n",
              "      <td>48880</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>263</th>\n",
              "      <td>경상남도</td>\n",
              "      <td>합천군</td>\n",
              "      <td>48890</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>264</th>\n",
              "      <td>제주특별자치도</td>\n",
              "      <td>제주시</td>\n",
              "      <td>50110</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>265</th>\n",
              "      <td>제주특별자치도</td>\n",
              "      <td>서귀포시</td>\n",
              "      <td>50130</td>\n",
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              "<p>266 rows × 3 columns</p>\n",
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              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
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            "text/plain": [
              "         시도명  시군구명   지역코드\n",
              "0      서울특별시   종로구  11110\n",
              "1      서울특별시    중구  11140\n",
              "2      서울특별시   용산구  11170\n",
              "3      서울특별시   성동구  11200\n",
              "4      서울특별시   광진구  11215\n",
              "..       ...   ...    ...\n",
              "261     경상남도   함양군  48870\n",
              "262     경상남도   거창군  48880\n",
              "263     경상남도   합천군  48890\n",
              "264  제주특별자치도   제주시  50110\n",
              "265  제주특별자치도  서귀포시  50130\n",
              "\n",
              "[266 rows x 3 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 5
        }
      ]
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              "      <th></th>\n",
              "      <th>시도명</th>\n",
              "      <th>시군구명</th>\n",
              "      <th>지역코드</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>서울특별시</td>\n",
              "      <td>종로구</td>\n",
              "      <td>11110</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>서울특별시</td>\n",
              "      <td>중구</td>\n",
              "      <td>11140</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>서울특별시</td>\n",
              "      <td>용산구</td>\n",
              "      <td>11170</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>서울특별시</td>\n",
              "      <td>성동구</td>\n",
              "      <td>11200</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>서울특별시</td>\n",
              "      <td>광진구</td>\n",
              "      <td>11215</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>서울특별시</td>\n",
              "      <td>동대문구</td>\n",
              "      <td>11230</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>서울특별시</td>\n",
              "      <td>중랑구</td>\n",
              "      <td>11260</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>서울특별시</td>\n",
              "      <td>성북구</td>\n",
              "      <td>11290</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>서울특별시</td>\n",
              "      <td>강북구</td>\n",
              "      <td>11305</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>서울특별시</td>\n",
              "      <td>도봉구</td>\n",
              "      <td>11320</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>서울특별시</td>\n",
              "      <td>노원구</td>\n",
              "      <td>11350</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>서울특별시</td>\n",
              "      <td>은평구</td>\n",
              "      <td>11380</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>서울특별시</td>\n",
              "      <td>서대문구</td>\n",
              "      <td>11410</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>서울특별시</td>\n",
              "      <td>마포구</td>\n",
              "      <td>11440</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>서울특별시</td>\n",
              "      <td>양천구</td>\n",
              "      <td>11470</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>서울특별시</td>\n",
              "      <td>강서구</td>\n",
              "      <td>11500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>서울특별시</td>\n",
              "      <td>구로구</td>\n",
              "      <td>11530</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>서울특별시</td>\n",
              "      <td>금천구</td>\n",
              "      <td>11545</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>서울특별시</td>\n",
              "      <td>영등포구</td>\n",
              "      <td>11560</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>서울특별시</td>\n",
              "      <td>동작구</td>\n",
              "      <td>11590</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>서울특별시</td>\n",
              "      <td>관악구</td>\n",
              "      <td>11620</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>서울특별시</td>\n",
              "      <td>서초구</td>\n",
              "      <td>11650</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>서울특별시</td>\n",
              "      <td>강남구</td>\n",
              "      <td>11680</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23</th>\n",
              "      <td>서울특별시</td>\n",
              "      <td>송파구</td>\n",
              "      <td>11710</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24</th>\n",
              "      <td>서울특별시</td>\n",
              "      <td>강동구</td>\n",
              "      <td>11740</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-22a81800-e0aa-4a51-b288-425dd762d9db')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-22a81800-e0aa-4a51-b288-425dd762d9db button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-22a81800-e0aa-4a51-b288-425dd762d9db');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "      시도명  시군구명   지역코드\n",
              "0   서울특별시   종로구  11110\n",
              "1   서울특별시    중구  11140\n",
              "2   서울특별시   용산구  11170\n",
              "3   서울특별시   성동구  11200\n",
              "4   서울특별시   광진구  11215\n",
              "5   서울특별시  동대문구  11230\n",
              "6   서울특별시   중랑구  11260\n",
              "7   서울특별시   성북구  11290\n",
              "8   서울특별시   강북구  11305\n",
              "9   서울특별시   도봉구  11320\n",
              "10  서울특별시   노원구  11350\n",
              "11  서울특별시   은평구  11380\n",
              "12  서울특별시  서대문구  11410\n",
              "13  서울특별시   마포구  11440\n",
              "14  서울특별시   양천구  11470\n",
              "15  서울특별시   강서구  11500\n",
              "16  서울특별시   구로구  11530\n",
              "17  서울특별시   금천구  11545\n",
              "18  서울특별시  영등포구  11560\n",
              "19  서울특별시   동작구  11590\n",
              "20  서울특별시   관악구  11620\n",
              "21  서울특별시   서초구  11650\n",
              "22  서울특별시   강남구  11680\n",
              "23  서울특별시   송파구  11710\n",
              "24  서울특별시   강동구  11740"
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ],
      "source": [
        "# 위 데이터 중 서울특별시에 소속된 데이터만 추출하세요\n",
        "# 추출은 시도명, 시군구명, 지역코드로 한정하세요\n",
        "loc_Seoul = locCode.loc[locCode['시도명'] == '서울특별시', :]\n",
        "loc_Seoul"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "O0-XTfNwhQ8Y"
      },
      "source": [
        "# 2. 실거래가 데이터 가공"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "JRzs2vxbhQ8Y",
        "outputId": "85c22d9d-eecb-40d8-b4ae-8d990eb49bb0"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "  <div id=\"df-0662e0cf-321d-4d00-b8c9-6fe41f2ac8d7\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <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>건축년도</th>\n",
              "      <th>거래년도</th>\n",
              "      <th>거래월</th>\n",
              "      <th>거래일자</th>\n",
              "      <th>법정동</th>\n",
              "      <th>거래금액</th>\n",
              "      <th>아파트이름</th>\n",
              "      <th>전용면적</th>\n",
              "      <th>지번</th>\n",
              "      <th>지역코드</th>\n",
              "      <th>층</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2007</td>\n",
              "      <td>2020</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>필운동</td>\n",
              "      <td>100,000</td>\n",
              "      <td>신동아블루아광화문의 꿈</td>\n",
              "      <td>111.97</td>\n",
              "      <td>254</td>\n",
              "      <td>11110</td>\n",
              "      <td>6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2008</td>\n",
              "      <td>2020</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>사직동</td>\n",
              "      <td>162,000</td>\n",
              "      <td>광화문풍림스페이스본(106동)</td>\n",
              "      <td>163.33</td>\n",
              "      <td>9-1</td>\n",
              "      <td>11110</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1994</td>\n",
              "      <td>2020</td>\n",
              "      <td>1</td>\n",
              "      <td>6</td>\n",
              "      <td>내수동</td>\n",
              "      <td>88,000</td>\n",
              "      <td>세종로대우</td>\n",
              "      <td>109.91</td>\n",
              "      <td>167</td>\n",
              "      <td>11110</td>\n",
              "      <td>11</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2004</td>\n",
              "      <td>2020</td>\n",
              "      <td>1</td>\n",
              "      <td>9</td>\n",
              "      <td>내수동</td>\n",
              "      <td>130,000</td>\n",
              "      <td>킹스매너</td>\n",
              "      <td>194.43</td>\n",
              "      <td>110-15</td>\n",
              "      <td>11110</td>\n",
              "      <td>4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2003</td>\n",
              "      <td>2020</td>\n",
              "      <td>1</td>\n",
              "      <td>20</td>\n",
              "      <td>내수동</td>\n",
              "      <td>149,000</td>\n",
              "      <td>경희궁 파크팰리스</td>\n",
              "      <td>148.09</td>\n",
              "      <td>95</td>\n",
              "      <td>11110</td>\n",
              "      <td>8</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-0662e0cf-321d-4d00-b8c9-6fe41f2ac8d7')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-0662e0cf-321d-4d00-b8c9-6fe41f2ac8d7 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-0662e0cf-321d-4d00-b8c9-6fe41f2ac8d7');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "   건축년도  거래년도  거래월  거래일자   법정동  ...             아파트이름    전용면적      지번   지역코드   층\n",
              "0  2007  2020    1     3   필운동  ...      신동아블루아광화문의 꿈  111.97     254  11110   6\n",
              "1  2008  2020    1     2   사직동  ...  광화문풍림스페이스본(106동)  163.33     9-1  11110   2\n",
              "2  1994  2020    1     6   내수동  ...             세종로대우  109.91     167  11110  11\n",
              "3  2004  2020    1     9   내수동  ...              킹스매너  194.43  110-15  11110   4\n",
              "4  2003  2020    1    20   내수동  ...         경희궁 파크팰리스  148.09      95  11110   8\n",
              "\n",
              "[5 rows x 11 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ],
      "source": [
        "# 2020-seoul-apt-price.csv 파일을 읽어 apt 변수에 저장하세요. encoding 옵션은 'cp949'로 설정합니다.\n",
        "apt = pd.read_csv('2020-seoul-apt-price.csv', encoding = 'cp949')\n",
        "\n",
        "apt.head()"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "apt"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "id": "BR-Yb8bQA2Zc",
        "outputId": "46916b9e-2045-4441-ced4-d92ad56a6058"
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "  <div id=\"df-c1b2540e-a56b-48e0-b7d8-ea61651cfc7a\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <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>건축년도</th>\n",
              "      <th>거래년도</th>\n",
              "      <th>거래월</th>\n",
              "      <th>거래일자</th>\n",
              "      <th>법정동</th>\n",
              "      <th>거래금액</th>\n",
              "      <th>아파트이름</th>\n",
              "      <th>전용면적</th>\n",
              "      <th>지번</th>\n",
              "      <th>지역코드</th>\n",
              "      <th>층</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2007</td>\n",
              "      <td>2020</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>필운동</td>\n",
              "      <td>100,000</td>\n",
              "      <td>신동아블루아광화문의 꿈</td>\n",
              "      <td>111.97</td>\n",
              "      <td>254</td>\n",
              "      <td>11110</td>\n",
              "      <td>6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2008</td>\n",
              "      <td>2020</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>사직동</td>\n",
              "      <td>162,000</td>\n",
              "      <td>광화문풍림스페이스본(106동)</td>\n",
              "      <td>163.33</td>\n",
              "      <td>9-1</td>\n",
              "      <td>11110</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1994</td>\n",
              "      <td>2020</td>\n",
              "      <td>1</td>\n",
              "      <td>6</td>\n",
              "      <td>내수동</td>\n",
              "      <td>88,000</td>\n",
              "      <td>세종로대우</td>\n",
              "      <td>109.91</td>\n",
              "      <td>167</td>\n",
              "      <td>11110</td>\n",
              "      <td>11</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2004</td>\n",
              "      <td>2020</td>\n",
              "      <td>1</td>\n",
              "      <td>9</td>\n",
              "      <td>내수동</td>\n",
              "      <td>130,000</td>\n",
              "      <td>킹스매너</td>\n",
              "      <td>194.43</td>\n",
              "      <td>110-15</td>\n",
              "      <td>11110</td>\n",
              "      <td>4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2003</td>\n",
              "      <td>2020</td>\n",
              "      <td>1</td>\n",
              "      <td>20</td>\n",
              "      <td>내수동</td>\n",
              "      <td>149,000</td>\n",
              "      <td>경희궁 파크팰리스</td>\n",
              "      <td>148.09</td>\n",
              "      <td>95</td>\n",
              "      <td>11110</td>\n",
              "      <td>8</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>80971</th>\n",
              "      <td>2011</td>\n",
              "      <td>2020</td>\n",
              "      <td>12</td>\n",
              "      <td>21</td>\n",
              "      <td>강일동</td>\n",
              "      <td>115,000</td>\n",
              "      <td>고덕리엔파크2단지</td>\n",
              "      <td>84.83</td>\n",
              "      <td>717</td>\n",
              "      <td>11740</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>80972</th>\n",
              "      <td>2009</td>\n",
              "      <td>2020</td>\n",
              "      <td>12</td>\n",
              "      <td>26</td>\n",
              "      <td>강일동</td>\n",
              "      <td>109,000</td>\n",
              "      <td>강일리버파크3단지</td>\n",
              "      <td>84.53</td>\n",
              "      <td>674</td>\n",
              "      <td>11740</td>\n",
              "      <td>7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>80973</th>\n",
              "      <td>2009</td>\n",
              "      <td>2020</td>\n",
              "      <td>12</td>\n",
              "      <td>26</td>\n",
              "      <td>강일동</td>\n",
              "      <td>107,000</td>\n",
              "      <td>강일리버파크4단지</td>\n",
              "      <td>84.83</td>\n",
              "      <td>673</td>\n",
              "      <td>11740</td>\n",
              "      <td>10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>80974</th>\n",
              "      <td>2009</td>\n",
              "      <td>2020</td>\n",
              "      <td>12</td>\n",
              "      <td>31</td>\n",
              "      <td>강일동</td>\n",
              "      <td>111,000</td>\n",
              "      <td>강일리버파크4단지</td>\n",
              "      <td>84.74</td>\n",
              "      <td>673</td>\n",
              "      <td>11740</td>\n",
              "      <td>12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>80975</th>\n",
              "      <td>2009</td>\n",
              "      <td>2020</td>\n",
              "      <td>12</td>\n",
              "      <td>31</td>\n",
              "      <td>강일동</td>\n",
              "      <td>104,000</td>\n",
              "      <td>강일리버파크9단지</td>\n",
              "      <td>84.74</td>\n",
              "      <td>699</td>\n",
              "      <td>11740</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>80976 rows × 11 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-c1b2540e-a56b-48e0-b7d8-ea61651cfc7a')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-c1b2540e-a56b-48e0-b7d8-ea61651cfc7a button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-c1b2540e-a56b-48e0-b7d8-ea61651cfc7a');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "       건축년도  거래년도  거래월  거래일자   법정동  ...             아파트이름    전용면적      지번   지역코드   층\n",
              "0      2007  2020    1     3   필운동  ...      신동아블루아광화문의 꿈  111.97     254  11110   6\n",
              "1      2008  2020    1     2   사직동  ...  광화문풍림스페이스본(106동)  163.33     9-1  11110   2\n",
              "2      1994  2020    1     6   내수동  ...             세종로대우  109.91     167  11110  11\n",
              "3      2004  2020    1     9   내수동  ...              킹스매너  194.43  110-15  11110   4\n",
              "4      2003  2020    1    20   내수동  ...         경희궁 파크팰리스  148.09      95  11110   8\n",
              "...     ...   ...  ...   ...   ...  ...               ...     ...     ...    ...  ..\n",
              "80971  2011  2020   12    21   강일동  ...         고덕리엔파크2단지   84.83     717  11740   5\n",
              "80972  2009  2020   12    26   강일동  ...         강일리버파크3단지   84.53     674  11740   7\n",
              "80973  2009  2020   12    26   강일동  ...         강일리버파크4단지   84.83     673  11740  10\n",
              "80974  2009  2020   12    31   강일동  ...         강일리버파크4단지   84.74     673  11740  12\n",
              "80975  2009  2020   12    31   강일동  ...         강일리버파크9단지   84.74     699  11740   5\n",
              "\n",
              "[80976 rows x 11 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 9,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5RUYdZKHhQ8Z",
        "outputId": "8e72bb70-8976-4a54-c66d-18b4e16842c4"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['건축년도', '거래년도', '거래월', '거래일자', '법정동', '거래금액', '아파트이름', '전용면적', '지번',\n",
              "       '지역코드', '층'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ],
      "source": [
        "# 실거래가 데이터의 컬럼명을 출력하세요\n",
        "apt.columns"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 10,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "qJqflim2hQ8Z",
        "outputId": "0a5264e0-f732-46a4-c0e6-e19b0d761b58"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(80976, 11)"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ],
      "source": [
        "# 데이터의 크기를 조회하세요 (shape)\n",
        "apt.shape"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 11,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "a7d2N-oxhQ8Z",
        "outputId": "47a85e70-4c30-4dc7-e999-41e3410d4541"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "건축년도      0\n",
              "거래년도      0\n",
              "거래월       0\n",
              "거래일자      0\n",
              "법정동       0\n",
              "거래금액      0\n",
              "아파트이름     0\n",
              "전용면적      0\n",
              "지번       25\n",
              "지역코드      0\n",
              "층         0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ],
      "source": [
        "# 각 열 별로 누락 데이터가 있는지 확인하세요\n",
        "apt.isna().sum()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 12,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Nfx7_8xfifBy",
        "outputId": "ee12834a-9850-4210-ee5f-21e7333b2d0f"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "건축년도     0\n",
              "거래년도     0\n",
              "거래월      0\n",
              "거래일자     0\n",
              "법정동      0\n",
              "거래금액     0\n",
              "아파트이름    0\n",
              "전용면적     0\n",
              "지번       0\n",
              "지역코드     0\n",
              "층        0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ],
      "source": [
        "# 누락 데이터를 제거하세요.(누락데이터가 하나라도 포함된 행은 삭제합니다.)\n",
        "apt = apt.dropna()\n",
        "#apt.dropna(inplaec=True)\n",
        "apt.isna().sum()"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# object 타입인 '거래금액' 열을 정수 (int64)로 변경하세요\n",
        "# 거래금액 컬럼의 ,를 제거 후 정수로 변경하세요.\n",
        "# df['컬럼명'].str.replace(변경전, 변경후)\n",
        "apt['거래금액'] = apt['거래금액'].str.replace(',', '').astype('int64')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "886_DuZpCbYi",
        "outputId": "3ac904c0-a2cb-41d6-c10e-1ce9038c0a4e"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:4: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  after removing the cwd from sys.path.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# 데이터의 정보를 출력하여 '거래금액' 열의 타입이 변경됐는지 확인하세요\n",
        "apt.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "tiZo4gk0BZza",
        "outputId": "ff822fef-731c-44cc-e071-83edc41326ea"
      },
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "Int64Index: 80951 entries, 0 to 80975\n",
            "Data columns (total 11 columns):\n",
            " #   Column  Non-Null Count  Dtype  \n",
            "---  ------  --------------  -----  \n",
            " 0   건축년도    80951 non-null  int64  \n",
            " 1   거래년도    80951 non-null  int64  \n",
            " 2   거래월     80951 non-null  int64  \n",
            " 3   거래일자    80951 non-null  int64  \n",
            " 4   법정동     80951 non-null  object \n",
            " 5   거래금액    80951 non-null  int64  \n",
            " 6   아파트이름   80951 non-null  object \n",
            " 7   전용면적    80951 non-null  float64\n",
            " 8   지번      80951 non-null  object \n",
            " 9   지역코드    80951 non-null  int64  \n",
            " 10  층       80951 non-null  int64  \n",
            "dtypes: float64(1), int64(7), object(3)\n",
            "memory usage: 7.4+ MB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# apt['거래금액'] = pd.to_numeric(apt['거래금액'], errors = 'ignore')\n",
        "# apt.info()"
      ],
      "metadata": {
        "id": "SXJ-AorPBeUW"
      },
      "execution_count": 16,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# 데이터의 정보를 출력하여 '거래금액' 열의 타입이 변경됐는지 확인하세요\n",
        "apt.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "d9h5OHkoCIUj",
        "outputId": "7e1575c4-2d75-4cbe-d5be-f75b52441460"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "\n",
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              "      <th></th>\n",
              "      <th>건축년도</th>\n",
              "      <th>거래년도</th>\n",
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              "  </thead>\n",
              "  <tbody>\n",
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              "      <th>0</th>\n",
              "      <td>2007</td>\n",
              "      <td>2020</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>필운동</td>\n",
              "      <td>100000</td>\n",
              "      <td>신동아블루아광화문의 꿈</td>\n",
              "      <td>111.97</td>\n",
              "      <td>254</td>\n",
              "      <td>11110</td>\n",
              "      <td>6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2008</td>\n",
              "      <td>2020</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>사직동</td>\n",
              "      <td>162000</td>\n",
              "      <td>광화문풍림스페이스본(106동)</td>\n",
              "      <td>163.33</td>\n",
              "      <td>9-1</td>\n",
              "      <td>11110</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1994</td>\n",
              "      <td>2020</td>\n",
              "      <td>1</td>\n",
              "      <td>6</td>\n",
              "      <td>내수동</td>\n",
              "      <td>88000</td>\n",
              "      <td>세종로대우</td>\n",
              "      <td>109.91</td>\n",
              "      <td>167</td>\n",
              "      <td>11110</td>\n",
              "      <td>11</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2004</td>\n",
              "      <td>2020</td>\n",
              "      <td>1</td>\n",
              "      <td>9</td>\n",
              "      <td>내수동</td>\n",
              "      <td>130000</td>\n",
              "      <td>킹스매너</td>\n",
              "      <td>194.43</td>\n",
              "      <td>110-15</td>\n",
              "      <td>11110</td>\n",
              "      <td>4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2003</td>\n",
              "      <td>2020</td>\n",
              "      <td>1</td>\n",
              "      <td>20</td>\n",
              "      <td>내수동</td>\n",
              "      <td>149000</td>\n",
              "      <td>경희궁 파크팰리스</td>\n",
              "      <td>148.09</td>\n",
              "      <td>95</td>\n",
              "      <td>11110</td>\n",
              "      <td>8</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-b1be8d8a-f54f-43e6-8968-58941045e74c')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "\n",
              "    .colab-df-convert:hover {\n",
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              "\n",
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              "        const buttonEl =\n",
              "          document.querySelector('#df-b1be8d8a-f54f-43e6-8968-58941045e74c button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-b1be8d8a-f54f-43e6-8968-58941045e74c');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
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              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "   건축년도  거래년도  거래월  거래일자   법정동  ...             아파트이름    전용면적      지번   지역코드   층\n",
              "0  2007  2020    1     3   필운동  ...      신동아블루아광화문의 꿈  111.97     254  11110   6\n",
              "1  2008  2020    1     2   사직동  ...  광화문풍림스페이스본(106동)  163.33     9-1  11110   2\n",
              "2  1994  2020    1     6   내수동  ...             세종로대우  109.91     167  11110  11\n",
              "3  2004  2020    1     9   내수동  ...              킹스매너  194.43  110-15  11110   4\n",
              "4  2003  2020    1    20   내수동  ...         경희궁 파크팰리스  148.09      95  11110   8\n",
              "\n",
              "[5 rows x 11 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# # 데이터의 정보를 출력하여 '거래금액' 열의 타입이 변경됐는지 확인하세요 >> 위에서 해결\n",
        "# apt['거래금액'] = pd.to_numeric(apt['거래금액'], errors = 'ignore')\n",
        "# apt.info()"
      ],
      "metadata": {
        "id": "jXV-s6BEE_Mp"
      },
      "execution_count": 18,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# '전용면적' 열을 이용하여 '전용면적(평)' 열을 추가하세요\n",
        "# 변환 공식: 전용면적/3.306\n",
        "# '전용면적(평)'의 값은 round 함수를 활용하여 소수점 둘째자리까지만 표기합니다.\n",
        "# Ex) round(아파트 전용면적컬럼 데이터, 반올림자리수 )\n",
        "\n",
        "apt['전용면적(평)'] = round(apt['전용면적'] , 2)\n",
        "apt.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 310
        },
        "id": "07XO18OECgwz",
        "outputId": "a39f5632-7d35-4622-dcf7-f20851f47d55"
      },
      "execution_count": 31,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n"
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              "      <th>건축년도</th>\n",
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              "      <th>아파트이름</th>\n",
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              "      <th>지번</th>\n",
              "      <th>지역코드</th>\n",
              "      <th>층</th>\n",
              "      <th>반기</th>\n",
              "      <th>전용면적(평)</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2007</td>\n",
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              "      <td>1</td>\n",
              "      <td>3</td>\n",
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              "      <td>254</td>\n",
              "      <td>11110</td>\n",
              "      <td>6</td>\n",
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              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2008</td>\n",
              "      <td>2020</td>\n",
              "      <td>1</td>\n",
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              "      <td>사직동</td>\n",
              "      <td>162000</td>\n",
              "      <td>광화문풍림스페이스본(106동)</td>\n",
              "      <td>163.33</td>\n",
              "      <td>9-1</td>\n",
              "      <td>11110</td>\n",
              "      <td>2</td>\n",
              "      <td>상반기</td>\n",
              "      <td>163.33</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1994</td>\n",
              "      <td>2020</td>\n",
              "      <td>1</td>\n",
              "      <td>6</td>\n",
              "      <td>내수동</td>\n",
              "      <td>88000</td>\n",
              "      <td>세종로대우</td>\n",
              "      <td>109.91</td>\n",
              "      <td>167</td>\n",
              "      <td>11110</td>\n",
              "      <td>11</td>\n",
              "      <td>상반기</td>\n",
              "      <td>109.91</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2004</td>\n",
              "      <td>2020</td>\n",
              "      <td>1</td>\n",
              "      <td>9</td>\n",
              "      <td>내수동</td>\n",
              "      <td>130000</td>\n",
              "      <td>킹스매너</td>\n",
              "      <td>194.43</td>\n",
              "      <td>110-15</td>\n",
              "      <td>11110</td>\n",
              "      <td>4</td>\n",
              "      <td>상반기</td>\n",
              "      <td>194.43</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2003</td>\n",
              "      <td>2020</td>\n",
              "      <td>1</td>\n",
              "      <td>20</td>\n",
              "      <td>내수동</td>\n",
              "      <td>149000</td>\n",
              "      <td>경희궁 파크팰리스</td>\n",
              "      <td>148.09</td>\n",
              "      <td>95</td>\n",
              "      <td>11110</td>\n",
              "      <td>8</td>\n",
              "      <td>상반기</td>\n",
              "      <td>148.09</td>\n",
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              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-fa9d16bb-cd7f-4ac0-a3ca-f370629f2cef')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-fa9d16bb-cd7f-4ac0-a3ca-f370629f2cef button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-fa9d16bb-cd7f-4ac0-a3ca-f370629f2cef');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "   건축년도  거래년도  거래월  거래일자   법정동    거래금액  ...    전용면적      지번   지역코드   층   반기 전용면적(평)\n",
              "0  2007  2020    1     3   필운동  100000  ...  111.97     254  11110   6  상반기  111.97\n",
              "1  2008  2020    1     2   사직동  162000  ...  163.33     9-1  11110   2  상반기  163.33\n",
              "2  1994  2020    1     6   내수동   88000  ...  109.91     167  11110  11  상반기  109.91\n",
              "3  2004  2020    1     9   내수동  130000  ...  194.43  110-15  11110   4  상반기  194.43\n",
              "4  2003  2020    1    20   내수동  149000  ...  148.09      95  11110   8  상반기  148.09\n",
              "\n",
              "[5 rows x 13 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 31
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# 아래 코드의 <조건> 부분을 완성하여(불리언 인덱싱),\n",
        "# '거래월'이 7월 전이면 상반기, \n",
        "# 7월 이후면 하반기로 설정되는 '반기' 열을 추가하세요\n",
        "apt['반기'] = 0\n",
        "apt.loc[apt['거래월'] < 7 , '반기'] = \"상반기\"\n",
        "apt.loc[apt['거래월'] >= 7 , '반기'] = \"하반기\""
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "QZbuuQwrDaQq",
        "outputId": "efbea9f9-21ee-4594-90fd-a1bb9aa47e86"
      },
      "execution_count": 32,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:4: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  after removing the cwd from sys.path.\n",
            "/usr/local/lib/python3.7/dist-packages/pandas/core/indexing.py:1763: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  isetter(loc, value)\n",
            "/usr/local/lib/python3.7/dist-packages/pandas/core/indexing.py:1763: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  isetter(loc, value)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "apt.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "GjnBWrp4Eca9",
        "outputId": "3501b4ae-5585-4ad8-ba7b-a4471f925385"
      },
      "execution_count": 33,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "\n",
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              "      <th></th>\n",
              "      <th>건축년도</th>\n",
              "      <th>거래년도</th>\n",
              "      <th>거래월</th>\n",
              "      <th>거래일자</th>\n",
              "      <th>법정동</th>\n",
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              "      <th>아파트이름</th>\n",
              "      <th>전용면적</th>\n",
              "      <th>지번</th>\n",
              "      <th>지역코드</th>\n",
              "      <th>층</th>\n",
              "      <th>반기</th>\n",
              "      <th>전용면적(평)</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2007</td>\n",
              "      <td>2020</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>필운동</td>\n",
              "      <td>100000</td>\n",
              "      <td>신동아블루아광화문의 꿈</td>\n",
              "      <td>111.97</td>\n",
              "      <td>254</td>\n",
              "      <td>11110</td>\n",
              "      <td>6</td>\n",
              "      <td>상반기</td>\n",
              "      <td>111.97</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2008</td>\n",
              "      <td>2020</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>사직동</td>\n",
              "      <td>162000</td>\n",
              "      <td>광화문풍림스페이스본(106동)</td>\n",
              "      <td>163.33</td>\n",
              "      <td>9-1</td>\n",
              "      <td>11110</td>\n",
              "      <td>2</td>\n",
              "      <td>상반기</td>\n",
              "      <td>163.33</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1994</td>\n",
              "      <td>2020</td>\n",
              "      <td>1</td>\n",
              "      <td>6</td>\n",
              "      <td>내수동</td>\n",
              "      <td>88000</td>\n",
              "      <td>세종로대우</td>\n",
              "      <td>109.91</td>\n",
              "      <td>167</td>\n",
              "      <td>11110</td>\n",
              "      <td>11</td>\n",
              "      <td>상반기</td>\n",
              "      <td>109.91</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2004</td>\n",
              "      <td>2020</td>\n",
              "      <td>1</td>\n",
              "      <td>9</td>\n",
              "      <td>내수동</td>\n",
              "      <td>130000</td>\n",
              "      <td>킹스매너</td>\n",
              "      <td>194.43</td>\n",
              "      <td>110-15</td>\n",
              "      <td>11110</td>\n",
              "      <td>4</td>\n",
              "      <td>상반기</td>\n",
              "      <td>194.43</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2003</td>\n",
              "      <td>2020</td>\n",
              "      <td>1</td>\n",
              "      <td>20</td>\n",
              "      <td>내수동</td>\n",
              "      <td>149000</td>\n",
              "      <td>경희궁 파크팰리스</td>\n",
              "      <td>148.09</td>\n",
              "      <td>95</td>\n",
              "      <td>11110</td>\n",
              "      <td>8</td>\n",
              "      <td>상반기</td>\n",
              "      <td>148.09</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-a85c567d-4291-4c36-9017-5c7751fabd80')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
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              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
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              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-a85c567d-4291-4c36-9017-5c7751fabd80 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-a85c567d-4291-4c36-9017-5c7751fabd80');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "   건축년도  거래년도  거래월  거래일자   법정동    거래금액  ...    전용면적      지번   지역코드   층   반기 전용면적(평)\n",
              "0  2007  2020    1     3   필운동  100000  ...  111.97     254  11110   6  상반기  111.97\n",
              "1  2008  2020    1     2   사직동  162000  ...  163.33     9-1  11110   2  상반기  163.33\n",
              "2  1994  2020    1     6   내수동   88000  ...  109.91     167  11110  11  상반기  109.91\n",
              "3  2004  2020    1     9   내수동  130000  ...  194.43  110-15  11110   4  상반기  194.43\n",
              "4  2003  2020    1    20   내수동  149000  ...  148.09      95  11110   8  상반기  148.09\n",
              "\n",
              "[5 rows x 13 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 33
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 34,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 310
        },
        "id": "k64W4machQ8c",
        "outputId": "401a733a-7388-41d8-fa78-35e4d30513f2",
        "scrolled": true
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:2: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n"
          ]
        },
        {
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          "data": {
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              "\n",
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              "      <th>거래월</th>\n",
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              "      <td>111.97</td>\n",
              "      <td>254</td>\n",
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              "      <td>6</td>\n",
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              "      <th>1</th>\n",
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              "      <td>사직동</td>\n",
              "      <td>162000</td>\n",
              "      <td>광화문풍림스페이스본(106동)</td>\n",
              "      <td>163.33</td>\n",
              "      <td>9-1</td>\n",
              "      <td>11110</td>\n",
              "      <td>2</td>\n",
              "      <td>상반기</td>\n",
              "      <td>163.33</td>\n",
              "      <td>991.856977</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1994</td>\n",
              "      <td>2020</td>\n",
              "      <td>1</td>\n",
              "      <td>6</td>\n",
              "      <td>내수동</td>\n",
              "      <td>88000</td>\n",
              "      <td>세종로대우</td>\n",
              "      <td>109.91</td>\n",
              "      <td>167</td>\n",
              "      <td>11110</td>\n",
              "      <td>11</td>\n",
              "      <td>상반기</td>\n",
              "      <td>109.91</td>\n",
              "      <td>800.655081</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2004</td>\n",
              "      <td>2020</td>\n",
              "      <td>1</td>\n",
              "      <td>9</td>\n",
              "      <td>내수동</td>\n",
              "      <td>130000</td>\n",
              "      <td>킹스매너</td>\n",
              "      <td>194.43</td>\n",
              "      <td>110-15</td>\n",
              "      <td>11110</td>\n",
              "      <td>4</td>\n",
              "      <td>상반기</td>\n",
              "      <td>194.43</td>\n",
              "      <td>668.621098</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2003</td>\n",
              "      <td>2020</td>\n",
              "      <td>1</td>\n",
              "      <td>20</td>\n",
              "      <td>내수동</td>\n",
              "      <td>149000</td>\n",
              "      <td>경희궁 파크팰리스</td>\n",
              "      <td>148.09</td>\n",
              "      <td>95</td>\n",
              "      <td>11110</td>\n",
              "      <td>8</td>\n",
              "      <td>상반기</td>\n",
              "      <td>148.09</td>\n",
              "      <td>1006.144912</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-1867a4c4-b9dd-4f96-b018-f66d7399fb61')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-1867a4c4-b9dd-4f96-b018-f66d7399fb61 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-1867a4c4-b9dd-4f96-b018-f66d7399fb61');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "   건축년도  거래년도  거래월  거래일자   법정동  ...   지역코드   층   반기 전용면적(평)       평당거래금액\n",
              "0  2007  2020    1     3   필운동  ...  11110   6  상반기  111.97   893.096365\n",
              "1  2008  2020    1     2   사직동  ...  11110   2  상반기  163.33   991.856977\n",
              "2  1994  2020    1     6   내수동  ...  11110  11  상반기  109.91   800.655081\n",
              "3  2004  2020    1     9   내수동  ...  11110   4  상반기  194.43   668.621098\n",
              "4  2003  2020    1    20   내수동  ...  11110   8  상반기  148.09  1006.144912\n",
              "\n",
              "[5 rows x 14 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 34
        }
      ],
      "source": [
        "# '전용면적(평)' 열을 이용하여 '평당거래금액' 열을 생성합니다.\n",
        "apt['평당거래금액'] = apt['거래금액'] /apt['전용면적(평)']\n",
        "apt.head()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "VNNWdxO_hQ8c"
      },
      "source": [
        "# 3. 데이터 프레임 결합"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# '지역코드'를 기준으로 겹치는 지역 코드만 고려하여 법정동 코드 데이터 프레임과 \n",
        "# 아파트 실거래가 데이터 프레임을 결합합니다.\n",
        "\n",
        "df = pd.merge(apt, loc_Seoul, on = '지역코드',how = 'inner') \n",
        "df.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "m4nPly0AFta5",
        "outputId": "a920cb07-7e19-4671-e25c-9318544cba99"
      },
      "execution_count": 35,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "\n",
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              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>건축년도</th>\n",
              "      <th>거래년도</th>\n",
              "      <th>거래월</th>\n",
              "      <th>거래일자</th>\n",
              "      <th>법정동</th>\n",
              "      <th>거래금액</th>\n",
              "      <th>아파트이름</th>\n",
              "      <th>전용면적</th>\n",
              "      <th>지번</th>\n",
              "      <th>지역코드</th>\n",
              "      <th>층</th>\n",
              "      <th>반기</th>\n",
              "      <th>전용면적(평)</th>\n",
              "      <th>평당거래금액</th>\n",
              "      <th>시도명</th>\n",
              "      <th>시군구명</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2007</td>\n",
              "      <td>2020</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>필운동</td>\n",
              "      <td>100000</td>\n",
              "      <td>신동아블루아광화문의 꿈</td>\n",
              "      <td>111.97</td>\n",
              "      <td>254</td>\n",
              "      <td>11110</td>\n",
              "      <td>6</td>\n",
              "      <td>상반기</td>\n",
              "      <td>111.97</td>\n",
              "      <td>893.096365</td>\n",
              "      <td>서울특별시</td>\n",
              "      <td>종로구</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2008</td>\n",
              "      <td>2020</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>사직동</td>\n",
              "      <td>162000</td>\n",
              "      <td>광화문풍림스페이스본(106동)</td>\n",
              "      <td>163.33</td>\n",
              "      <td>9-1</td>\n",
              "      <td>11110</td>\n",
              "      <td>2</td>\n",
              "      <td>상반기</td>\n",
              "      <td>163.33</td>\n",
              "      <td>991.856977</td>\n",
              "      <td>서울특별시</td>\n",
              "      <td>종로구</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1994</td>\n",
              "      <td>2020</td>\n",
              "      <td>1</td>\n",
              "      <td>6</td>\n",
              "      <td>내수동</td>\n",
              "      <td>88000</td>\n",
              "      <td>세종로대우</td>\n",
              "      <td>109.91</td>\n",
              "      <td>167</td>\n",
              "      <td>11110</td>\n",
              "      <td>11</td>\n",
              "      <td>상반기</td>\n",
              "      <td>109.91</td>\n",
              "      <td>800.655081</td>\n",
              "      <td>서울특별시</td>\n",
              "      <td>종로구</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2004</td>\n",
              "      <td>2020</td>\n",
              "      <td>1</td>\n",
              "      <td>9</td>\n",
              "      <td>내수동</td>\n",
              "      <td>130000</td>\n",
              "      <td>킹스매너</td>\n",
              "      <td>194.43</td>\n",
              "      <td>110-15</td>\n",
              "      <td>11110</td>\n",
              "      <td>4</td>\n",
              "      <td>상반기</td>\n",
              "      <td>194.43</td>\n",
              "      <td>668.621098</td>\n",
              "      <td>서울특별시</td>\n",
              "      <td>종로구</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2003</td>\n",
              "      <td>2020</td>\n",
              "      <td>1</td>\n",
              "      <td>20</td>\n",
              "      <td>내수동</td>\n",
              "      <td>149000</td>\n",
              "      <td>경희궁 파크팰리스</td>\n",
              "      <td>148.09</td>\n",
              "      <td>95</td>\n",
              "      <td>11110</td>\n",
              "      <td>8</td>\n",
              "      <td>상반기</td>\n",
              "      <td>148.09</td>\n",
              "      <td>1006.144912</td>\n",
              "      <td>서울특별시</td>\n",
              "      <td>종로구</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-20a5abe4-ba55-4e41-a629-2d761fbe0c1e')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-20a5abe4-ba55-4e41-a629-2d761fbe0c1e button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-20a5abe4-ba55-4e41-a629-2d761fbe0c1e');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "   건축년도  거래년도  거래월  거래일자   법정동  ...   반기 전용면적(평)       평당거래금액    시도명  시군구명\n",
              "0  2007  2020    1     3   필운동  ...  상반기  111.97   893.096365  서울특별시   종로구\n",
              "1  2008  2020    1     2   사직동  ...  상반기  163.33   991.856977  서울특별시   종로구\n",
              "2  1994  2020    1     6   내수동  ...  상반기  109.91   800.655081  서울특별시   종로구\n",
              "3  2004  2020    1     9   내수동  ...  상반기  194.43   668.621098  서울특별시   종로구\n",
              "4  2003  2020    1    20   내수동  ...  상반기  148.09  1006.144912  서울특별시   종로구\n",
              "\n",
              "[5 rows x 16 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 35
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 36,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "AoQz30BPhQ8c",
        "outputId": "ffe257cd-f310-4f92-9874-50c2810cde73",
        "scrolled": true
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "\n",
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              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>건축년도</th>\n",
              "      <th>거래년도</th>\n",
              "      <th>거래월</th>\n",
              "      <th>거래일자</th>\n",
              "      <th>법정동</th>\n",
              "      <th>거래금액</th>\n",
              "      <th>아파트이름</th>\n",
              "      <th>전용면적</th>\n",
              "      <th>지번</th>\n",
              "      <th>층</th>\n",
              "      <th>반기</th>\n",
              "      <th>전용면적(평)</th>\n",
              "      <th>평당거래금액</th>\n",
              "      <th>시도명</th>\n",
              "      <th>시군구명</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2007</td>\n",
              "      <td>2020</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>필운동</td>\n",
              "      <td>100000</td>\n",
              "      <td>신동아블루아광화문의 꿈</td>\n",
              "      <td>111.97</td>\n",
              "      <td>254</td>\n",
              "      <td>6</td>\n",
              "      <td>상반기</td>\n",
              "      <td>111.97</td>\n",
              "      <td>893.096365</td>\n",
              "      <td>서울특별시</td>\n",
              "      <td>종로구</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2008</td>\n",
              "      <td>2020</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>사직동</td>\n",
              "      <td>162000</td>\n",
              "      <td>광화문풍림스페이스본(106동)</td>\n",
              "      <td>163.33</td>\n",
              "      <td>9-1</td>\n",
              "      <td>2</td>\n",
              "      <td>상반기</td>\n",
              "      <td>163.33</td>\n",
              "      <td>991.856977</td>\n",
              "      <td>서울특별시</td>\n",
              "      <td>종로구</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1994</td>\n",
              "      <td>2020</td>\n",
              "      <td>1</td>\n",
              "      <td>6</td>\n",
              "      <td>내수동</td>\n",
              "      <td>88000</td>\n",
              "      <td>세종로대우</td>\n",
              "      <td>109.91</td>\n",
              "      <td>167</td>\n",
              "      <td>11</td>\n",
              "      <td>상반기</td>\n",
              "      <td>109.91</td>\n",
              "      <td>800.655081</td>\n",
              "      <td>서울특별시</td>\n",
              "      <td>종로구</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2004</td>\n",
              "      <td>2020</td>\n",
              "      <td>1</td>\n",
              "      <td>9</td>\n",
              "      <td>내수동</td>\n",
              "      <td>130000</td>\n",
              "      <td>킹스매너</td>\n",
              "      <td>194.43</td>\n",
              "      <td>110-15</td>\n",
              "      <td>4</td>\n",
              "      <td>상반기</td>\n",
              "      <td>194.43</td>\n",
              "      <td>668.621098</td>\n",
              "      <td>서울특별시</td>\n",
              "      <td>종로구</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2003</td>\n",
              "      <td>2020</td>\n",
              "      <td>1</td>\n",
              "      <td>20</td>\n",
              "      <td>내수동</td>\n",
              "      <td>149000</td>\n",
              "      <td>경희궁 파크팰리스</td>\n",
              "      <td>148.09</td>\n",
              "      <td>95</td>\n",
              "      <td>8</td>\n",
              "      <td>상반기</td>\n",
              "      <td>148.09</td>\n",
              "      <td>1006.144912</td>\n",
              "      <td>서울특별시</td>\n",
              "      <td>종로구</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
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              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-ca396ad1-61e7-4cf2-a3e7-4de8e17ea593')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
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              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
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              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
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              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-ca396ad1-61e7-4cf2-a3e7-4de8e17ea593 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-ca396ad1-61e7-4cf2-a3e7-4de8e17ea593');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "   건축년도  거래년도  거래월  거래일자   법정동  ...   반기 전용면적(평)       평당거래금액    시도명  시군구명\n",
              "0  2007  2020    1     3   필운동  ...  상반기  111.97   893.096365  서울특별시   종로구\n",
              "1  2008  2020    1     2   사직동  ...  상반기  163.33   991.856977  서울특별시   종로구\n",
              "2  1994  2020    1     6   내수동  ...  상반기  109.91   800.655081  서울특별시   종로구\n",
              "3  2004  2020    1     9   내수동  ...  상반기  194.43   668.621098  서울특별시   종로구\n",
              "4  2003  2020    1    20   내수동  ...  상반기  148.09  1006.144912  서울특별시   종로구\n",
              "\n",
              "[5 rows x 15 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 36
        }
      ],
      "source": [
        "# '지역코드' 열은 더이상 필요 없으므로 삭제합니다.\n",
        "df = df.drop('지역코드', axis = 1)\n",
        "df.head()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 37,
      "metadata": {
        "id": "QEHT87p1uPYa"
      },
      "outputs": [],
      "source": [
        "# 완성된 데이터의 재사용성을 위해 파일로 저장합니다.\n",
        "# 파일 이름은 '2020년 서울시 아파트 실거래가_merge.csv',\n",
        "# encoding은 'cp949'\n",
        "# index는 제외하고 저장하세요.\n",
        "df.to_csv('2020년 서울시 아파트 실거래가_merge.csv', index=False, encoding='cp949')"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "A3Sb_UNuhQ8c"
      },
      "source": [
        "# 4. 데이터 분석"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 38,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "Gr_rNMKZhQ8d",
        "outputId": "2a27ae96-f8e7-4d7b-86f0-54b646364175",
        "scrolled": true
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "          const element = document.querySelector('#df-38229400-05e2-4af3-94c4-8ae4d94613e8');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "       건축년도  거래년도  거래월  거래일자   법정동  ...   반기 전용면적(평)       평당거래금액    시도명  시군구명\n",
              "69087  1982  2020    3     4   개포동  ...  상반기   56.57  5471.097755  서울특별시   강남구\n",
              "68882  1982  2020    2    17   개포동  ...  상반기   58.08  5423.553719  서울특별시   강남구\n",
              "69097  1982  2020    3    19   개포동  ...  상반기   50.38  5240.174672  서울특별시   강남구\n",
              "68890  1982  2020    2    20   개포동  ...  상반기   50.64  5134.281201  서울특별시   강남구\n",
              "69088  1982  2020    3     6   개포동  ...  상반기   41.98  4835.636017  서울특별시   강남구\n",
              "\n",
              "[5 rows x 15 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 38
        }
      ],
      "source": [
        "# 2020년에 거래된 평당거래금액이 높은 5개의 거래를 출력합니다.\n",
        "df.sort_values('평당거래금액', ascending=False).head()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 39,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "X1yV2yw3hQ8d",
        "outputId": "0b912bae-dba5-443f-8ab3-e4fccafa8aca"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "  <div id=\"df-e777fa44-37c4-4c8f-b230-fc4596c77f0f\">\n",
              "    <div class=\"colab-df-container\">\n",
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              "<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",
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              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>건축년도</th>\n",
              "      <th>거래년도</th>\n",
              "      <th>거래월</th>\n",
              "      <th>거래일자</th>\n",
              "      <th>법정동</th>\n",
              "      <th>거래금액</th>\n",
              "      <th>아파트이름</th>\n",
              "      <th>전용면적</th>\n",
              "      <th>지번</th>\n",
              "      <th>층</th>\n",
              "      <th>반기</th>\n",
              "      <th>전용면적(평)</th>\n",
              "      <th>평당거래금액</th>\n",
              "      <th>시도명</th>\n",
              "      <th>시군구명</th>\n",
              "    </tr>\n",
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              "      <th>1907</th>\n",
              "      <td>2011</td>\n",
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              "      <td>18</td>\n",
              "      <td>한남동</td>\n",
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              "      <td>240.230</td>\n",
              "      <td>810</td>\n",
              "      <td>4</td>\n",
              "      <td>상반기</td>\n",
              "      <td>240.23</td>\n",
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              "      <td>서울특별시</td>\n",
              "      <td>용산구</td>\n",
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              "    <tr>\n",
              "      <th>2351</th>\n",
              "      <td>2011</td>\n",
              "      <td>2020</td>\n",
              "      <td>6</td>\n",
              "      <td>29</td>\n",
              "      <td>한남동</td>\n",
              "      <td>660000</td>\n",
              "      <td>한남더힐</td>\n",
              "      <td>240.305</td>\n",
              "      <td>810</td>\n",
              "      <td>3</td>\n",
              "      <td>상반기</td>\n",
              "      <td>240.30</td>\n",
              "      <td>2746.566792</td>\n",
              "      <td>서울특별시</td>\n",
              "      <td>용산구</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1906</th>\n",
              "      <td>2011</td>\n",
              "      <td>2020</td>\n",
              "      <td>2</td>\n",
              "      <td>17</td>\n",
              "      <td>한남동</td>\n",
              "      <td>660000</td>\n",
              "      <td>한남더힐</td>\n",
              "      <td>240.230</td>\n",
              "      <td>810</td>\n",
              "      <td>5</td>\n",
              "      <td>상반기</td>\n",
              "      <td>240.23</td>\n",
              "      <td>2747.367107</td>\n",
              "      <td>서울특별시</td>\n",
              "      <td>용산구</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2333</th>\n",
              "      <td>2011</td>\n",
              "      <td>2020</td>\n",
              "      <td>6</td>\n",
              "      <td>10</td>\n",
              "      <td>한남동</td>\n",
              "      <td>670000</td>\n",
              "      <td>한남더힐</td>\n",
              "      <td>240.305</td>\n",
              "      <td>810</td>\n",
              "      <td>2</td>\n",
              "      <td>상반기</td>\n",
              "      <td>240.30</td>\n",
              "      <td>2788.181440</td>\n",
              "      <td>서울특별시</td>\n",
              "      <td>용산구</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1981</th>\n",
              "      <td>2011</td>\n",
              "      <td>2020</td>\n",
              "      <td>4</td>\n",
              "      <td>27</td>\n",
              "      <td>한남동</td>\n",
              "      <td>730000</td>\n",
              "      <td>한남더힐</td>\n",
              "      <td>240.305</td>\n",
              "      <td>810</td>\n",
              "      <td>-1</td>\n",
              "      <td>상반기</td>\n",
              "      <td>240.30</td>\n",
              "      <td>3037.869330</td>\n",
              "      <td>서울특별시</td>\n",
              "      <td>용산구</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
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              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-e777fa44-37c4-4c8f-b230-fc4596c77f0f')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
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              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
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              "      display: none;\n",
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              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-e777fa44-37c4-4c8f-b230-fc4596c77f0f button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-e777fa44-37c4-4c8f-b230-fc4596c77f0f');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
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              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "      건축년도  거래년도  거래월  거래일자   법정동  ...   반기 전용면적(평)       평당거래금액    시도명  시군구명\n",
              "1907  2011  2020    2    18   한남동  ...  상반기  240.23  2684.926945  서울특별시   용산구\n",
              "2351  2011  2020    6    29   한남동  ...  상반기  240.30  2746.566792  서울특별시   용산구\n",
              "1906  2011  2020    2    17   한남동  ...  상반기  240.23  2747.367107  서울특별시   용산구\n",
              "2333  2011  2020    6    10   한남동  ...  상반기  240.30  2788.181440  서울특별시   용산구\n",
              "1981  2011  2020    4    27   한남동  ...  상반기  240.30  3037.869330  서울특별시   용산구\n",
              "\n",
              "[5 rows x 15 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 39
        }
      ],
      "source": [
        "# 불리언 인덱싱을 사용해서 2020년 상반기 데이터를 뽑아내고,\n",
        "# 거래 금액이 높은 5개의 거래를 출력합니다.\n",
        "df.loc[df['반기'] == '상반기', :].sort_values('거래금액').tail()"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# groupby를 사용하여, 시군구 별 거래 금액의 합계와 평균 금액을 구하고\n",
        "# 거래 금액의 평균이 높은 순서대로 정렬합니다.\n",
        "pd.DataFrame(df.groupby('시군구명')['거래금액'].agg(['sum', 'mean'])).sort_values('mean', ascending=False)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 864
        },
        "id": "YtCR6jIbIu2_",
        "outputId": "7259ad8c-e9b3-4946-fea2-9952c0f70828"
      },
      "execution_count": 40,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
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              "      <th></th>\n",
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              "    <tr>\n",
              "      <th>광진구</th>\n",
              "      <td>132848700</td>\n",
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              "      <td>278445244</td>\n",
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              "    <tr>\n",
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              "    <tr>\n",
              "      <th>중구</th>\n",
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              "      <td>299456715</td>\n",
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              "      <th>동대문구</th>\n",
              "      <td>218203716</td>\n",
              "      <td>70776.424262</td>\n",
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              "    <tr>\n",
              "      <th>성북구</th>\n",
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              "      <td>68592.357778</td>\n",
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              "    <tr>\n",
              "      <th>강서구</th>\n",
              "      <td>383205183</td>\n",
              "      <td>67763.958090</td>\n",
              "    </tr>\n",
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              "      <th>은평구</th>\n",
              "      <td>206762892</td>\n",
              "      <td>62466.130514</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>관악구</th>\n",
              "      <td>159871672</td>\n",
              "      <td>62182.680669</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>강북구</th>\n",
              "      <td>117543500</td>\n",
              "      <td>55840.142518</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>구로구</th>\n",
              "      <td>265591417</td>\n",
              "      <td>54536.225257</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>노원구</th>\n",
              "      <td>454525680</td>\n",
              "      <td>52166.381269</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>중랑구</th>\n",
              "      <td>139125390</td>\n",
              "      <td>50701.672741</td>\n",
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              "    <tr>\n",
              "      <th>금천구</th>\n",
              "      <td>76984085</td>\n",
              "      <td>47113.883109</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>도봉구</th>\n",
              "      <td>199920400</td>\n",
              "      <td>45727.447392</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-d66e7070-d432-49f8-9933-1966a57ec334')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "        \n",
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              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
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              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
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              "\n",
              "    .colab-df-convert:hover {\n",
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              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
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              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-d66e7070-d432-49f8-9933-1966a57ec334 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-d66e7070-d432-49f8-9933-1966a57ec334');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
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              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "            sum           mean\n",
              "시군구명                          \n",
              "강남구   655663087  180523.977698\n",
              "서초구   550608694  174519.395880\n",
              "용산구   219369564  150769.459794\n",
              "송파구   583141519  130369.219539\n",
              "성동구   331737193  113725.468975\n",
              "광진구   132848700  106791.559486\n",
              "마포구   278445244  101252.816000\n",
              "동작구   275499081   97487.289809\n",
              "중구     90528205   92187.581466\n",
              "영등포구  299456715   89657.699102\n",
              "양천구   298352977   88874.881442\n",
              "강동구   346750637   83695.543567\n",
              "종로구    62110771   82924.927904\n",
              "서대문구  213228968   78624.250737\n",
              "동대문구  218203716   70776.424262\n",
              "성북구   285275616   68592.357778\n",
              "강서구   383205183   67763.958090\n",
              "은평구   206762892   62466.130514\n",
              "관악구   159871672   62182.680669\n",
              "강북구   117543500   55840.142518\n",
              "구로구   265591417   54536.225257\n",
              "노원구   454525680   52166.381269\n",
              "중랑구   139125390   50701.672741\n",
              "금천구    76984085   47113.883109\n",
              "도봉구   199920400   45727.447392"
            ]
          },
          "metadata": {},
          "execution_count": 40
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# 거래월과 시군구별 거래량(거래 건 수)을 피벗테이블로 표현하세요\n",
        "pv_table = df.pivot_table(index='시군구명', values='거래금액',  columns='거래월', aggfunc='size')\n",
        "pv_table"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 864
        },
        "id": "GqFvAhdWN9ha",
        "outputId": "f124c741-51f7-483f-b4d4-187a22102a11"
      },
      "execution_count": 45,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "  <div id=\"df-5fa75616-8235-4ccf-b617-5485d2872660\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <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>거래월</th>\n",
              "      <th>1</th>\n",
              "      <th>2</th>\n",
              "      <th>3</th>\n",
              "      <th>4</th>\n",
              "      <th>5</th>\n",
              "      <th>6</th>\n",
              "      <th>7</th>\n",
              "      <th>8</th>\n",
              "      <th>9</th>\n",
              "      <th>10</th>\n",
              "      <th>11</th>\n",
              "      <th>12</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>시군구명</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>강남구</th>\n",
              "      <td>131</td>\n",
              "      <td>237</td>\n",
              "      <td>135</td>\n",
              "      <td>145</td>\n",
              "      <td>331</td>\n",
              "      <td>789</td>\n",
              "      <td>365</td>\n",
              "      <td>227</td>\n",
              "      <td>177</td>\n",
              "      <td>215</td>\n",
              "      <td>418</td>\n",
              "      <td>462</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>강동구</th>\n",
              "      <td>336</td>\n",
              "      <td>392</td>\n",
              "      <td>165</td>\n",
              "      <td>127</td>\n",
              "      <td>317</td>\n",
              "      <td>871</td>\n",
              "      <td>558</td>\n",
              "      <td>314</td>\n",
              "      <td>200</td>\n",
              "      <td>195</td>\n",
              "      <td>328</td>\n",
              "      <td>340</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>강북구</th>\n",
              "      <td>313</td>\n",
              "      <td>262</td>\n",
              "      <td>161</td>\n",
              "      <td>99</td>\n",
              "      <td>132</td>\n",
              "      <td>371</td>\n",
              "      <td>207</td>\n",
              "      <td>95</td>\n",
              "      <td>78</td>\n",
              "      <td>122</td>\n",
              "      <td>107</td>\n",
              "      <td>158</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>강서구</th>\n",
              "      <td>425</td>\n",
              "      <td>459</td>\n",
              "      <td>247</td>\n",
              "      <td>188</td>\n",
              "      <td>327</td>\n",
              "      <td>1128</td>\n",
              "      <td>956</td>\n",
              "      <td>413</td>\n",
              "      <td>303</td>\n",
              "      <td>330</td>\n",
              "      <td>456</td>\n",
              "      <td>423</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>관악구</th>\n",
              "      <td>235</td>\n",
              "      <td>296</td>\n",
              "      <td>178</td>\n",
              "      <td>139</td>\n",
              "      <td>165</td>\n",
              "      <td>503</td>\n",
              "      <td>298</td>\n",
              "      <td>116</td>\n",
              "      <td>116</td>\n",
              "      <td>128</td>\n",
              "      <td>179</td>\n",
              "      <td>218</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>광진구</th>\n",
              "      <td>63</td>\n",
              "      <td>113</td>\n",
              "      <td>52</td>\n",
              "      <td>40</td>\n",
              "      <td>79</td>\n",
              "      <td>229</td>\n",
              "      <td>194</td>\n",
              "      <td>93</td>\n",
              "      <td>76</td>\n",
              "      <td>72</td>\n",
              "      <td>105</td>\n",
              "      <td>128</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>구로구</th>\n",
              "      <td>443</td>\n",
              "      <td>574</td>\n",
              "      <td>310</td>\n",
              "      <td>229</td>\n",
              "      <td>356</td>\n",
              "      <td>864</td>\n",
              "      <td>551</td>\n",
              "      <td>257</td>\n",
              "      <td>219</td>\n",
              "      <td>234</td>\n",
              "      <td>463</td>\n",
              "      <td>370</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>금천구</th>\n",
              "      <td>125</td>\n",
              "      <td>185</td>\n",
              "      <td>176</td>\n",
              "      <td>53</td>\n",
              "      <td>99</td>\n",
              "      <td>228</td>\n",
              "      <td>174</td>\n",
              "      <td>89</td>\n",
              "      <td>67</td>\n",
              "      <td>67</td>\n",
              "      <td>116</td>\n",
              "      <td>255</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>노원구</th>\n",
              "      <td>815</td>\n",
              "      <td>1154</td>\n",
              "      <td>625</td>\n",
              "      <td>371</td>\n",
              "      <td>621</td>\n",
              "      <td>1722</td>\n",
              "      <td>927</td>\n",
              "      <td>381</td>\n",
              "      <td>308</td>\n",
              "      <td>395</td>\n",
              "      <td>620</td>\n",
              "      <td>774</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>도봉구</th>\n",
              "      <td>367</td>\n",
              "      <td>563</td>\n",
              "      <td>308</td>\n",
              "      <td>199</td>\n",
              "      <td>280</td>\n",
              "      <td>845</td>\n",
              "      <td>604</td>\n",
              "      <td>200</td>\n",
              "      <td>147</td>\n",
              "      <td>204</td>\n",
              "      <td>301</td>\n",
              "      <td>354</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>동대문구</th>\n",
              "      <td>287</td>\n",
              "      <td>343</td>\n",
              "      <td>172</td>\n",
              "      <td>121</td>\n",
              "      <td>215</td>\n",
              "      <td>529</td>\n",
              "      <td>387</td>\n",
              "      <td>200</td>\n",
              "      <td>154</td>\n",
              "      <td>162</td>\n",
              "      <td>230</td>\n",
              "      <td>283</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>동작구</th>\n",
              "      <td>208</td>\n",
              "      <td>278</td>\n",
              "      <td>118</td>\n",
              "      <td>50</td>\n",
              "      <td>148</td>\n",
              "      <td>535</td>\n",
              "      <td>483</td>\n",
              "      <td>217</td>\n",
              "      <td>146</td>\n",
              "      <td>152</td>\n",
              "      <td>215</td>\n",
              "      <td>276</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>마포구</th>\n",
              "      <td>182</td>\n",
              "      <td>211</td>\n",
              "      <td>112</td>\n",
              "      <td>63</td>\n",
              "      <td>162</td>\n",
              "      <td>491</td>\n",
              "      <td>469</td>\n",
              "      <td>209</td>\n",
              "      <td>164</td>\n",
              "      <td>180</td>\n",
              "      <td>261</td>\n",
              "      <td>246</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>서대문구</th>\n",
              "      <td>227</td>\n",
              "      <td>271</td>\n",
              "      <td>137</td>\n",
              "      <td>87</td>\n",
              "      <td>186</td>\n",
              "      <td>491</td>\n",
              "      <td>377</td>\n",
              "      <td>180</td>\n",
              "      <td>157</td>\n",
              "      <td>167</td>\n",
              "      <td>200</td>\n",
              "      <td>232</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>서초구</th>\n",
              "      <td>121</td>\n",
              "      <td>178</td>\n",
              "      <td>116</td>\n",
              "      <td>94</td>\n",
              "      <td>212</td>\n",
              "      <td>545</td>\n",
              "      <td>431</td>\n",
              "      <td>275</td>\n",
              "      <td>199</td>\n",
              "      <td>232</td>\n",
              "      <td>322</td>\n",
              "      <td>430</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>성동구</th>\n",
              "      <td>206</td>\n",
              "      <td>284</td>\n",
              "      <td>151</td>\n",
              "      <td>76</td>\n",
              "      <td>176</td>\n",
              "      <td>646</td>\n",
              "      <td>386</td>\n",
              "      <td>204</td>\n",
              "      <td>143</td>\n",
              "      <td>142</td>\n",
              "      <td>223</td>\n",
              "      <td>280</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>성북구</th>\n",
              "      <td>448</td>\n",
              "      <td>521</td>\n",
              "      <td>241</td>\n",
              "      <td>174</td>\n",
              "      <td>258</td>\n",
              "      <td>843</td>\n",
              "      <td>566</td>\n",
              "      <td>245</td>\n",
              "      <td>140</td>\n",
              "      <td>160</td>\n",
              "      <td>263</td>\n",
              "      <td>300</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>송파구</th>\n",
              "      <td>221</td>\n",
              "      <td>359</td>\n",
              "      <td>146</td>\n",
              "      <td>138</td>\n",
              "      <td>347</td>\n",
              "      <td>1134</td>\n",
              "      <td>560</td>\n",
              "      <td>281</td>\n",
              "      <td>225</td>\n",
              "      <td>229</td>\n",
              "      <td>367</td>\n",
              "      <td>466</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>양천구</th>\n",
              "      <td>241</td>\n",
              "      <td>313</td>\n",
              "      <td>168</td>\n",
              "      <td>113</td>\n",
              "      <td>249</td>\n",
              "      <td>688</td>\n",
              "      <td>491</td>\n",
              "      <td>198</td>\n",
              "      <td>151</td>\n",
              "      <td>178</td>\n",
              "      <td>245</td>\n",
              "      <td>322</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>영등포구</th>\n",
              "      <td>307</td>\n",
              "      <td>348</td>\n",
              "      <td>146</td>\n",
              "      <td>122</td>\n",
              "      <td>241</td>\n",
              "      <td>602</td>\n",
              "      <td>420</td>\n",
              "      <td>207</td>\n",
              "      <td>154</td>\n",
              "      <td>206</td>\n",
              "      <td>265</td>\n",
              "      <td>322</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>용산구</th>\n",
              "      <td>103</td>\n",
              "      <td>80</td>\n",
              "      <td>37</td>\n",
              "      <td>31</td>\n",
              "      <td>125</td>\n",
              "      <td>260</td>\n",
              "      <td>178</td>\n",
              "      <td>108</td>\n",
              "      <td>103</td>\n",
              "      <td>125</td>\n",
              "      <td>141</td>\n",
              "      <td>164</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>은평구</th>\n",
              "      <td>313</td>\n",
              "      <td>355</td>\n",
              "      <td>203</td>\n",
              "      <td>175</td>\n",
              "      <td>235</td>\n",
              "      <td>548</td>\n",
              "      <td>491</td>\n",
              "      <td>194</td>\n",
              "      <td>150</td>\n",
              "      <td>180</td>\n",
              "      <td>224</td>\n",
              "      <td>242</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>종로구</th>\n",
              "      <td>65</td>\n",
              "      <td>57</td>\n",
              "      <td>43</td>\n",
              "      <td>27</td>\n",
              "      <td>55</td>\n",
              "      <td>115</td>\n",
              "      <td>97</td>\n",
              "      <td>49</td>\n",
              "      <td>34</td>\n",
              "      <td>76</td>\n",
              "      <td>64</td>\n",
              "      <td>67</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>중구</th>\n",
              "      <td>84</td>\n",
              "      <td>93</td>\n",
              "      <td>62</td>\n",
              "      <td>35</td>\n",
              "      <td>55</td>\n",
              "      <td>164</td>\n",
              "      <td>140</td>\n",
              "      <td>71</td>\n",
              "      <td>52</td>\n",
              "      <td>71</td>\n",
              "      <td>76</td>\n",
              "      <td>79</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>중랑구</th>\n",
              "      <td>237</td>\n",
              "      <td>364</td>\n",
              "      <td>207</td>\n",
              "      <td>136</td>\n",
              "      <td>220</td>\n",
              "      <td>469</td>\n",
              "      <td>343</td>\n",
              "      <td>156</td>\n",
              "      <td>103</td>\n",
              "      <td>154</td>\n",
              "      <td>159</td>\n",
              "      <td>196</td>\n",
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              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-5fa75616-8235-4ccf-b617-5485d2872660')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "    .colab-df-container {\n",
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              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
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              "\n",
              "    .colab-df-convert:hover {\n",
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              "\n",
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              "\n",
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              "\n",
              "      <script>\n",
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              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-5fa75616-8235-4ccf-b617-5485d2872660');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
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              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "거래월    1     2    3    4    5     6    7    8    9    10   11   12\n",
              "시군구명                                                              \n",
              "강남구   131   237  135  145  331   789  365  227  177  215  418  462\n",
              "강동구   336   392  165  127  317   871  558  314  200  195  328  340\n",
              "강북구   313   262  161   99  132   371  207   95   78  122  107  158\n",
              "강서구   425   459  247  188  327  1128  956  413  303  330  456  423\n",
              "관악구   235   296  178  139  165   503  298  116  116  128  179  218\n",
              "광진구    63   113   52   40   79   229  194   93   76   72  105  128\n",
              "구로구   443   574  310  229  356   864  551  257  219  234  463  370\n",
              "금천구   125   185  176   53   99   228  174   89   67   67  116  255\n",
              "노원구   815  1154  625  371  621  1722  927  381  308  395  620  774\n",
              "도봉구   367   563  308  199  280   845  604  200  147  204  301  354\n",
              "동대문구  287   343  172  121  215   529  387  200  154  162  230  283\n",
              "동작구   208   278  118   50  148   535  483  217  146  152  215  276\n",
              "마포구   182   211  112   63  162   491  469  209  164  180  261  246\n",
              "서대문구  227   271  137   87  186   491  377  180  157  167  200  232\n",
              "서초구   121   178  116   94  212   545  431  275  199  232  322  430\n",
              "성동구   206   284  151   76  176   646  386  204  143  142  223  280\n",
              "성북구   448   521  241  174  258   843  566  245  140  160  263  300\n",
              "송파구   221   359  146  138  347  1134  560  281  225  229  367  466\n",
              "양천구   241   313  168  113  249   688  491  198  151  178  245  322\n",
              "영등포구  307   348  146  122  241   602  420  207  154  206  265  322\n",
              "용산구   103    80   37   31  125   260  178  108  103  125  141  164\n",
              "은평구   313   355  203  175  235   548  491  194  150  180  224  242\n",
              "종로구    65    57   43   27   55   115   97   49   34   76   64   67\n",
              "중구     84    93   62   35   55   164  140   71   52   71   76   79\n",
              "중랑구   237   364  207  136  220   469  343  156  103  154  159  196"
            ]
          },
          "metadata": {},
          "execution_count": 45
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 43,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "id": "ZV3OBsGihQ8g",
        "outputId": "2e19c239-ad64-4739-a5f7-242cbb4a5b0d",
        "scrolled": true
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "\n",
              "  <div id=\"df-1e2538f3-bf78-407d-852b-4301428500ad\">\n",
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>건축년도</th>\n",
              "      <th>거래년도</th>\n",
              "      <th>거래월</th>\n",
              "      <th>거래일자</th>\n",
              "      <th>법정동</th>\n",
              "      <th>거래금액</th>\n",
              "      <th>아파트이름</th>\n",
              "      <th>전용면적</th>\n",
              "      <th>지번</th>\n",
              "      <th>층</th>\n",
              "      <th>반기</th>\n",
              "      <th>전용면적(평)</th>\n",
              "      <th>평당거래금액</th>\n",
              "      <th>시도명</th>\n",
              "      <th>시군구명</th>\n",
              "    </tr>\n",
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              "  <tbody>\n",
              "    <tr>\n",
              "      <th>68703</th>\n",
              "      <td>2003</td>\n",
              "      <td>2020</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
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              "      <td>20200</td>\n",
              "      <td>우림루미아트1</td>\n",
              "      <td>24.0000</td>\n",
              "      <td>706-11</td>\n",
              "      <td>8</td>\n",
              "      <td>상반기</td>\n",
              "      <td>24.00</td>\n",
              "      <td>841.666667</td>\n",
              "      <td>서울특별시</td>\n",
              "      <td>강남구</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>68704</th>\n",
              "      <td>2004</td>\n",
              "      <td>2020</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>역삼동</td>\n",
              "      <td>77000</td>\n",
              "      <td>현대하이츠</td>\n",
              "      <td>99.2200</td>\n",
              "      <td>775-15</td>\n",
              "      <td>4</td>\n",
              "      <td>상반기</td>\n",
              "      <td>99.22</td>\n",
              "      <td>776.053215</td>\n",
              "      <td>서울특별시</td>\n",
              "      <td>강남구</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>68705</th>\n",
              "      <td>1996</td>\n",
              "      <td>2020</td>\n",
              "      <td>1</td>\n",
              "      <td>4</td>\n",
              "      <td>역삼동</td>\n",
              "      <td>39500</td>\n",
              "      <td>한스빌(836)</td>\n",
              "      <td>41.9500</td>\n",
              "      <td>836</td>\n",
              "      <td>11</td>\n",
              "      <td>상반기</td>\n",
              "      <td>41.95</td>\n",
              "      <td>941.597139</td>\n",
              "      <td>서울특별시</td>\n",
              "      <td>강남구</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>68706</th>\n",
              "      <td>1998</td>\n",
              "      <td>2020</td>\n",
              "      <td>1</td>\n",
              "      <td>6</td>\n",
              "      <td>역삼동</td>\n",
              "      <td>148800</td>\n",
              "      <td>동부센트레빌</td>\n",
              "      <td>59.8200</td>\n",
              "      <td>716</td>\n",
              "      <td>21</td>\n",
              "      <td>상반기</td>\n",
              "      <td>59.82</td>\n",
              "      <td>2487.462387</td>\n",
              "      <td>서울특별시</td>\n",
              "      <td>강남구</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>68707</th>\n",
              "      <td>2002</td>\n",
              "      <td>2020</td>\n",
              "      <td>1</td>\n",
              "      <td>6</td>\n",
              "      <td>역삼동</td>\n",
              "      <td>56000</td>\n",
              "      <td>트레벨</td>\n",
              "      <td>33.4800</td>\n",
              "      <td>766-8</td>\n",
              "      <td>4</td>\n",
              "      <td>상반기</td>\n",
              "      <td>33.48</td>\n",
              "      <td>1672.640382</td>\n",
              "      <td>서울특별시</td>\n",
              "      <td>강남구</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>72330</th>\n",
              "      <td>1995</td>\n",
              "      <td>2020</td>\n",
              "      <td>12</td>\n",
              "      <td>30</td>\n",
              "      <td>도곡동</td>\n",
              "      <td>195000</td>\n",
              "      <td>럭키(963)</td>\n",
              "      <td>84.9700</td>\n",
              "      <td>963</td>\n",
              "      <td>3</td>\n",
              "      <td>하반기</td>\n",
              "      <td>84.97</td>\n",
              "      <td>2294.927622</td>\n",
              "      <td>서울특별시</td>\n",
              "      <td>강남구</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>72331</th>\n",
              "      <td>2006</td>\n",
              "      <td>2020</td>\n",
              "      <td>12</td>\n",
              "      <td>30</td>\n",
              "      <td>도곡동</td>\n",
              "      <td>365000</td>\n",
              "      <td>도곡렉슬</td>\n",
              "      <td>134.9023</td>\n",
              "      <td>527</td>\n",
              "      <td>3</td>\n",
              "      <td>하반기</td>\n",
              "      <td>134.90</td>\n",
              "      <td>2705.707932</td>\n",
              "      <td>서울특별시</td>\n",
              "      <td>강남구</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>72332</th>\n",
              "      <td>2001</td>\n",
              "      <td>2020</td>\n",
              "      <td>12</td>\n",
              "      <td>31</td>\n",
              "      <td>도곡동</td>\n",
              "      <td>290000</td>\n",
              "      <td>삼성래미안</td>\n",
              "      <td>122.8100</td>\n",
              "      <td>91-5</td>\n",
              "      <td>17</td>\n",
              "      <td>하반기</td>\n",
              "      <td>122.81</td>\n",
              "      <td>2361.371224</td>\n",
              "      <td>서울특별시</td>\n",
              "      <td>강남구</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>72333</th>\n",
              "      <td>2004</td>\n",
              "      <td>2020</td>\n",
              "      <td>12</td>\n",
              "      <td>31</td>\n",
              "      <td>도곡동</td>\n",
              "      <td>208000</td>\n",
              "      <td>아카데미스위트1</td>\n",
              "      <td>122.0700</td>\n",
              "      <td>467-7</td>\n",
              "      <td>18</td>\n",
              "      <td>하반기</td>\n",
              "      <td>122.07</td>\n",
              "      <td>1703.940362</td>\n",
              "      <td>서울특별시</td>\n",
              "      <td>강남구</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>72334</th>\n",
              "      <td>2006</td>\n",
              "      <td>2020</td>\n",
              "      <td>12</td>\n",
              "      <td>31</td>\n",
              "      <td>도곡동</td>\n",
              "      <td>90000</td>\n",
              "      <td>SK허브프리모</td>\n",
              "      <td>67.5700</td>\n",
              "      <td>953-1</td>\n",
              "      <td>5</td>\n",
              "      <td>하반기</td>\n",
              "      <td>67.57</td>\n",
              "      <td>1331.952050</td>\n",
              "      <td>서울특별시</td>\n",
              "      <td>강남구</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>3632 rows × 15 columns</p>\n",
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              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-1e2538f3-bf78-407d-852b-4301428500ad');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "       건축년도  거래년도  거래월  거래일자   법정동  ...   반기 전용면적(평)       평당거래금액    시도명  시군구명\n",
              "68703  2003  2020    1     3   역삼동  ...  상반기   24.00   841.666667  서울특별시   강남구\n",
              "68704  2004  2020    1     3   역삼동  ...  상반기   99.22   776.053215  서울특별시   강남구\n",
              "68705  1996  2020    1     4   역삼동  ...  상반기   41.95   941.597139  서울특별시   강남구\n",
              "68706  1998  2020    1     6   역삼동  ...  상반기   59.82  2487.462387  서울특별시   강남구\n",
              "68707  2002  2020    1     6   역삼동  ...  상반기   33.48  1672.640382  서울특별시   강남구\n",
              "...     ...   ...  ...   ...   ...  ...  ...     ...          ...    ...   ...\n",
              "72330  1995  2020   12    30   도곡동  ...  하반기   84.97  2294.927622  서울특별시   강남구\n",
              "72331  2006  2020   12    30   도곡동  ...  하반기  134.90  2705.707932  서울특별시   강남구\n",
              "72332  2001  2020   12    31   도곡동  ...  하반기  122.81  2361.371224  서울특별시   강남구\n",
              "72333  2004  2020   12    31   도곡동  ...  하반기  122.07  1703.940362  서울특별시   강남구\n",
              "72334  2006  2020   12    31   도곡동  ...  하반기   67.57  1331.952050  서울특별시   강남구\n",
              "\n",
              "[3632 rows x 15 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 43
        }
      ],
      "source": [
        "# 시군구가 강남구인 데이터를 추출하세요\n",
        "gangnam = df.loc[df['시군구명'] == '강남구' , :]\n",
        "gangnam"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 46,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 237
        },
        "id": "lscl8qxfhQ8h",
        "outputId": "9edff277-aab4-4196-e7de-9a569e8f946e"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "  <div id=\"df-af78c56c-bc68-46e9-9928-3d9fe83fe1bb\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <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>거래금액</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>아파트이름</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>효성빌라 청담101(A동)</th>\n",
              "      <td>620000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>상지리츠빌 카일룸</th>\n",
              "      <td>565400.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>청담 어퍼하우스</th>\n",
              "      <td>519500.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>한양8(81동한개동)</th>\n",
              "      <td>491600.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>아펠바움</th>\n",
              "      <td>480000.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-af78c56c-bc68-46e9-9928-3d9fe83fe1bb')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-af78c56c-bc68-46e9-9928-3d9fe83fe1bb button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-af78c56c-bc68-46e9-9928-3d9fe83fe1bb');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "                    거래금액\n",
              "아파트이름                   \n",
              "효성빌라 청담101(A동)  620000.0\n",
              "상지리츠빌 카일룸       565400.0\n",
              "청담 어퍼하우스        519500.0\n",
              "한양8(81동한개동)     491600.0\n",
              "아펠바움            480000.0"
            ]
          },
          "metadata": {},
          "execution_count": 46
        }
      ],
      "source": [
        "# 강남구의 아파트 단지별 평균 거래 금액을 계산 후 상위 5개를 출력합니다.\n",
        "pd.DataFrame(gangnam.groupby(['아파트이름'])['거래금액'].mean()).sort_values('거래금액', ascending=False).head()"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# pv_gangnam = pd.DataFrame(gangnam.groupby(['법정동', '거래월'])['거래금액'].mean()).sort_values('거래금액', ascending=False)\n",
        "# pv_gangnam = round(pv_gangnam, 2)\n",
        "# pv_gangnam"
      ],
      "metadata": {
        "id": "5I27FaZkPyst"
      },
      "execution_count": 50,
      "outputs": []
    },
    {
      "cell_type": "code",
      "execution_count": 49,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 518
        },
        "id": "yVU2Ncm9hQ8h",
        "outputId": "67a03f73-183e-42d3-93b5-624be267232b",
        "scrolled": true
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "  <div id=\"df-bc1e75ed-2ef2-475a-bcbb-158ca8fa171b\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <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>거래월</th>\n",
              "      <th>1</th>\n",
              "      <th>2</th>\n",
              "      <th>3</th>\n",
              "      <th>4</th>\n",
              "      <th>5</th>\n",
              "      <th>6</th>\n",
              "      <th>7</th>\n",
              "      <th>8</th>\n",
              "      <th>9</th>\n",
              "      <th>10</th>\n",
              "      <th>11</th>\n",
              "      <th>12</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>법정동</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>개포동</th>\n",
              "      <td>161583.33</td>\n",
              "      <td>181135.39</td>\n",
              "      <td>182202.38</td>\n",
              "      <td>151500.00</td>\n",
              "      <td>154590.62</td>\n",
              "      <td>174853.68</td>\n",
              "      <td>189583.33</td>\n",
              "      <td>189905.88</td>\n",
              "      <td>168650.00</td>\n",
              "      <td>176572.22</td>\n",
              "      <td>202102.94</td>\n",
              "      <td>182220.97</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>논현동</th>\n",
              "      <td>125244.44</td>\n",
              "      <td>94079.17</td>\n",
              "      <td>82958.33</td>\n",
              "      <td>129000.00</td>\n",
              "      <td>123490.00</td>\n",
              "      <td>102197.19</td>\n",
              "      <td>127952.38</td>\n",
              "      <td>143922.22</td>\n",
              "      <td>104214.29</td>\n",
              "      <td>123139.90</td>\n",
              "      <td>122465.33</td>\n",
              "      <td>120650.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>대치동</th>\n",
              "      <td>226214.29</td>\n",
              "      <td>204231.43</td>\n",
              "      <td>229107.69</td>\n",
              "      <td>213302.94</td>\n",
              "      <td>224888.64</td>\n",
              "      <td>239325.19</td>\n",
              "      <td>134910.53</td>\n",
              "      <td>241285.71</td>\n",
              "      <td>213444.44</td>\n",
              "      <td>255983.33</td>\n",
              "      <td>186921.05</td>\n",
              "      <td>241755.50</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>도곡동</th>\n",
              "      <td>214590.00</td>\n",
              "      <td>196096.88</td>\n",
              "      <td>153986.96</td>\n",
              "      <td>268472.22</td>\n",
              "      <td>204930.77</td>\n",
              "      <td>212941.96</td>\n",
              "      <td>202180.31</td>\n",
              "      <td>185057.58</td>\n",
              "      <td>214572.22</td>\n",
              "      <td>225534.62</td>\n",
              "      <td>238560.34</td>\n",
              "      <td>214466.15</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>삼성동</th>\n",
              "      <td>186000.00</td>\n",
              "      <td>168476.19</td>\n",
              "      <td>186737.50</td>\n",
              "      <td>168555.56</td>\n",
              "      <td>184210.00</td>\n",
              "      <td>153213.93</td>\n",
              "      <td>136028.12</td>\n",
              "      <td>188533.33</td>\n",
              "      <td>200200.00</td>\n",
              "      <td>140814.29</td>\n",
              "      <td>136419.00</td>\n",
              "      <td>132126.11</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>세곡동</th>\n",
              "      <td>114200.00</td>\n",
              "      <td>112340.00</td>\n",
              "      <td>114666.67</td>\n",
              "      <td>134000.00</td>\n",
              "      <td>117700.00</td>\n",
              "      <td>119713.33</td>\n",
              "      <td>125711.54</td>\n",
              "      <td>132112.50</td>\n",
              "      <td>145875.00</td>\n",
              "      <td>142250.00</td>\n",
              "      <td>137500.00</td>\n",
              "      <td>136807.69</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>수서동</th>\n",
              "      <td>100200.00</td>\n",
              "      <td>101650.00</td>\n",
              "      <td>115416.67</td>\n",
              "      <td>135187.50</td>\n",
              "      <td>118167.86</td>\n",
              "      <td>115238.24</td>\n",
              "      <td>134742.42</td>\n",
              "      <td>126939.44</td>\n",
              "      <td>134692.08</td>\n",
              "      <td>152166.67</td>\n",
              "      <td>133840.29</td>\n",
              "      <td>135176.92</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>신사동</th>\n",
              "      <td>106571.43</td>\n",
              "      <td>106750.00</td>\n",
              "      <td>103900.00</td>\n",
              "      <td>89625.00</td>\n",
              "      <td>82925.00</td>\n",
              "      <td>117333.33</td>\n",
              "      <td>113571.43</td>\n",
              "      <td>123500.00</td>\n",
              "      <td>92000.00</td>\n",
              "      <td>261333.33</td>\n",
              "      <td>254500.00</td>\n",
              "      <td>264625.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>압구정동</th>\n",
              "      <td>290333.33</td>\n",
              "      <td>247100.00</td>\n",
              "      <td>315600.00</td>\n",
              "      <td>264792.50</td>\n",
              "      <td>275707.89</td>\n",
              "      <td>275994.90</td>\n",
              "      <td>319265.62</td>\n",
              "      <td>353037.50</td>\n",
              "      <td>285805.56</td>\n",
              "      <td>320208.33</td>\n",
              "      <td>293886.67</td>\n",
              "      <td>309497.44</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>역삼동</th>\n",
              "      <td>82457.50</td>\n",
              "      <td>111055.71</td>\n",
              "      <td>127842.86</td>\n",
              "      <td>144370.59</td>\n",
              "      <td>96955.89</td>\n",
              "      <td>153598.12</td>\n",
              "      <td>134801.85</td>\n",
              "      <td>123852.14</td>\n",
              "      <td>168400.00</td>\n",
              "      <td>130562.69</td>\n",
              "      <td>154048.78</td>\n",
              "      <td>148110.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>율현동</th>\n",
              "      <td>130000.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>일원동</th>\n",
              "      <td>167666.67</td>\n",
              "      <td>174800.00</td>\n",
              "      <td>155500.00</td>\n",
              "      <td>147000.00</td>\n",
              "      <td>150923.08</td>\n",
              "      <td>163279.41</td>\n",
              "      <td>146721.74</td>\n",
              "      <td>183029.41</td>\n",
              "      <td>178250.00</td>\n",
              "      <td>186423.08</td>\n",
              "      <td>167857.89</td>\n",
              "      <td>201248.28</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>자곡동</th>\n",
              "      <td>146000.00</td>\n",
              "      <td>146100.00</td>\n",
              "      <td>156666.67</td>\n",
              "      <td>143000.00</td>\n",
              "      <td>150166.67</td>\n",
              "      <td>152268.75</td>\n",
              "      <td>158450.00</td>\n",
              "      <td>144861.11</td>\n",
              "      <td>102600.00</td>\n",
              "      <td>93380.30</td>\n",
              "      <td>92769.70</td>\n",
              "      <td>103645.74</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>청담동</th>\n",
              "      <td>112760.00</td>\n",
              "      <td>178641.67</td>\n",
              "      <td>197311.11</td>\n",
              "      <td>201355.56</td>\n",
              "      <td>195215.38</td>\n",
              "      <td>199548.94</td>\n",
              "      <td>86071.43</td>\n",
              "      <td>106875.00</td>\n",
              "      <td>226428.57</td>\n",
              "      <td>192414.29</td>\n",
              "      <td>202190.91</td>\n",
              "      <td>272846.15</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-bc1e75ed-2ef2-475a-bcbb-158ca8fa171b')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "      \n",
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              "      gap: 12px;\n",
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              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
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              "    .colab-df-convert:hover {\n",
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              "      background-color: #3B4455;\n",
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              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
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              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-bc1e75ed-2ef2-475a-bcbb-158ca8fa171b');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
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              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "거래월           1          2          3   ...         10         11         12\n",
              "법정동                                     ...                                 \n",
              " 개포동   161583.33  181135.39  182202.38  ...  176572.22  202102.94  182220.97\n",
              " 논현동   125244.44   94079.17   82958.33  ...  123139.90  122465.33  120650.00\n",
              " 대치동   226214.29  204231.43  229107.69  ...  255983.33  186921.05  241755.50\n",
              " 도곡동   214590.00  196096.88  153986.96  ...  225534.62  238560.34  214466.15\n",
              " 삼성동   186000.00  168476.19  186737.50  ...  140814.29  136419.00  132126.11\n",
              " 세곡동   114200.00  112340.00  114666.67  ...  142250.00  137500.00  136807.69\n",
              " 수서동   100200.00  101650.00  115416.67  ...  152166.67  133840.29  135176.92\n",
              " 신사동   106571.43  106750.00  103900.00  ...  261333.33  254500.00  264625.00\n",
              " 압구정동  290333.33  247100.00  315600.00  ...  320208.33  293886.67  309497.44\n",
              " 역삼동    82457.50  111055.71  127842.86  ...  130562.69  154048.78  148110.00\n",
              " 율현동   130000.00       0.00       0.00  ...       0.00       0.00       0.00\n",
              " 일원동   167666.67  174800.00  155500.00  ...  186423.08  167857.89  201248.28\n",
              " 자곡동   146000.00  146100.00  156666.67  ...   93380.30   92769.70  103645.74\n",
              " 청담동   112760.00  178641.67  197311.11  ...  192414.29  202190.91  272846.15\n",
              "\n",
              "[14 rows x 12 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 49
        }
      ],
      "source": [
        "# 피벗 테이블 이용하여 강남구의 거래월과 법정동의 평균거래금액을 계산합니다. (NA는 0으로 치환합니다.)\n",
        "# 완성된 피벗 테이블 뒤에\n",
        "# pivot_table( ... ).round(반올림자리수)\n",
        "# 형태로 소수점 둘째자리까지 출력합니다.\n",
        "# 거래월과 시군구별 거래량(거래 건 수)을 피벗테이블로 표현하세요\n",
        "pv_gang_table = gangnam.pivot_table(values='거래금액', index='법정동', columns='거래월', aggfunc = 'mean').fillna(0).round(2)\n",
        "pv_gang_table"
      ]
    }
  ],
  "metadata": {
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      "collapsed_sections": [
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        "O0-XTfNwhQ8Y",
        "VNNWdxO_hQ8c"
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      "name": "데이터분석_3주차 아파트 실거래가 분석 I(나영훈).ipynb",
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