공영주차장 데이터 시각화.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "source": [
        "# 한글 설치 코드 : 설치 후 런타임 다시 시작\n",
        "!sudo apt-get install -y fonts-nanum\n",
        "!sudo fc-cache -fv\n",
        "!rm ~/.cache/matplotlib -rf"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "NLKT8SStERhN",
        "outputId": "1dff09cc-9a74-4f65-b121-b09edee2c195"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "Building dependency tree       \n",
            "Reading state information... Done\n",
            "fonts-nanum is already the newest version (20180306-3).\n",
            "0 upgraded, 0 newly installed, 0 to remove and 24 not upgraded.\n",
            "/usr/share/fonts: caching, new cache contents: 0 fonts, 1 dirs\n",
            "/usr/share/fonts/truetype: caching, new cache contents: 0 fonts, 3 dirs\n",
            "/usr/share/fonts/truetype/humor-sans: caching, new cache contents: 1 fonts, 0 dirs\n",
            "/usr/share/fonts/truetype/liberation: caching, new cache contents: 16 fonts, 0 dirs\n",
            "/usr/share/fonts/truetype/nanum: caching, new cache contents: 10 fonts, 0 dirs\n",
            "/usr/local/share/fonts: caching, new cache contents: 0 fonts, 0 dirs\n",
            "/root/.local/share/fonts: skipping, no such directory\n",
            "/root/.fonts: skipping, no such directory\n",
            "/usr/share/fonts/truetype: skipping, looped directory detected\n",
            "/usr/share/fonts/truetype/humor-sans: skipping, looped directory detected\n",
            "/usr/share/fonts/truetype/liberation: skipping, looped directory detected\n",
            "/usr/share/fonts/truetype/nanum: skipping, looped directory detected\n",
            "/var/cache/fontconfig: cleaning cache directory\n",
            "/root/.cache/fontconfig: not cleaning non-existent cache directory\n",
            "/root/.fontconfig: not cleaning non-existent cache directory\n",
            "fc-cache: succeeded\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install squarify"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "JAa3sYxVZ-6W",
        "outputId": "95f4dad1-2a19-4f13-e327-e667a406d4ca"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Requirement already satisfied: squarify in /usr/local/lib/python3.10/dist-packages (0.4.3)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### 파이차트 수정해야 할 것"
      ],
      "metadata": {
        "id": "ueEUW7skafuY"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt\n",
        "import squarify\n",
        "\n",
        "# 데이터 생성\n",
        "sizes = [15, 30, 45, 10]\n",
        "labels = [\"group A\", \"group B\", \"group C\", \"group D\"]\n",
        "colors = [\"red\", \"green\", \"blue\", \"yellow\"]\n",
        "\n",
        "# 트리맵 생성\n",
        "squarify.plot(sizes=sizes, label=labels, color=colors)\n",
        "\n",
        "# 트리맵 레이아웃 설정\n",
        "plt.axis('off')\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 406
        },
        "id": "Lt1aOcyPaLQF",
        "outputId": "281ad502-9940-49ea-bf06-4791a4b98f64"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt\n",
        "\n",
        "# 데이터프레임에서 단속동별 빈도를 구합니다.\n",
        "freq = df.groupby('단속동')['위반내용'].count()\n",
        "\n",
        "# 파이차트를 그립니다.\n",
        "plt.pie(freq, labels=freq.index, autopct='%.1f%%', startangle=90)\n",
        "plt.rcParams['font.family'] = 'NanumBarunGothic'\n",
        "plt.axis('equal')\n",
        "plt.show()"
      ],
      "metadata": {
        "id": "ITA5C8jNZrCa",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 420
        },
        "outputId": "f9147f3e-23b2-47a0-cd67-411f92fdaf87"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### 데이터 불러오기"
      ],
      "metadata": {
        "id": "3ARVvePxak5O"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "from google.colab import drive\n",
        "\n",
        "drive.mount('/content/drive')\n",
        "\n",
        "# 데이터 불러오기\n",
        "filename = \"/content/drive/MyDrive/[03팀] 김가경, 김수민, 민채원/code/Gwangjingu_parking_total.csv\"\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "iixCETADc3De",
        "outputId": "48267f4c-8ba6-4b5e-bde4-4a61af1f8e3b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount(\"/content/drive\", force_remount=True).\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# 데이터 불러오기\n",
        "df = pd.read_csv(filename, encoding='cp949')\n",
        "df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "id": "DQPQeri2epaA",
        "outputId": "ab4253b7-bb92-48fd-a78c-d8d48b92015d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                       단속일시   단속원금  단속동               단속장소           위반내용  \\\n",
              "0          2015-01-01 06:44  40000  화양동              119-4          주정차금지   \n",
              "1          2015-01-01 07:01  40000  화양동          건대입구1번출구앞    32조내지 34조위반   \n",
              "2          2015-01-01 07:24  50000  구의동        동서울터미널 주차장앞    32조내지 34조위반   \n",
              "3          2015-01-01 08:00  40000  화양동          건대입구1번출구앞    32조내지 34조위반   \n",
              "4          2015-01-01 08:15  40000  화양동          건대입구1번출구앞    32조내지 34조위반   \n",
              "...                     ...    ...  ...                ...            ...   \n",
              "490926  2023-02-28 20:43:00  32000  군자동               군자빌딩  주정차금지(황색실선)구역   \n",
              "490927  2023-02-28 21:23:00   8000  자양동  서울 광진구 자양동 659-32             보도   \n",
              "490928  2023-02-28 21:38:00  32000  화양동     서울 광진구 능동로 154             보도   \n",
              "490929  2023-02-28 22:36:00  32000  자양동   서울 광진구 자양동 12-10            교차로   \n",
              "490930  2023-02-28 23:19:00  32000  자양동              02-02           횡단보도   \n",
              "\n",
              "        견인지시     데이터기준일자  \n",
              "0       견인처리  2022-06-10  \n",
              "1        미견인  2022-06-10  \n",
              "2        미견인  2022-06-10  \n",
              "3        미견인  2022-06-10  \n",
              "4        미견인  2022-06-10  \n",
              "...      ...         ...  \n",
              "490926   미견인         NaN  \n",
              "490927   미견인         NaN  \n",
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              "490929   미견인         NaN  \n",
              "490930   미견인         NaN  \n",
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            ]
          },
          "metadata": {},
          "execution_count": 66
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### 빈도분석"
      ],
      "metadata": {
        "id": "ATjLuNGoc1mz"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# 데이터 불러오기\n",
        "df1 = pd.read_csv(filename, encoding='cp949', usecols=['위반내용','단속동', '단속장소'])\n",
        "df1"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "id": "8Iep5tHudOjV",
        "outputId": "9e7a7e5b-96ca-409f-be1a-09fe33974a45"
      },
      "execution_count": null,
      "outputs": [
        {
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              "        단속동               단속장소           위반내용\n",
              "0       화양동              119-4          주정차금지\n",
              "1       화양동          건대입구1번출구앞    32조내지 34조위반\n",
              "2       구의동        동서울터미널 주차장앞    32조내지 34조위반\n",
              "3       화양동          건대입구1번출구앞    32조내지 34조위반\n",
              "4       화양동          건대입구1번출구앞    32조내지 34조위반\n",
              "...     ...                ...            ...\n",
              "490926  군자동               군자빌딩  주정차금지(황색실선)구역\n",
              "490927  자양동  서울 광진구 자양동 659-32             보도\n",
              "490928  화양동     서울 광진구 능동로 154             보도\n",
              "490929  자양동   서울 광진구 자양동 12-10            교차로\n",
              "490930  자양동              02-02           횡단보도\n",
              "\n",
              "[490931 rows x 3 columns]"
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              "\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",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 67
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### 위반내용"
      ],
      "metadata": {
        "id": "vmThSLmNGHvK"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "violation_count = df['위반내용'].value_counts()\n",
        "violation_count"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "vdA8OjmKPJcl",
        "outputId": "c608dcdb-e1d4-46cd-c4f0-9d805da6e8b4"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "주차금지(황색점선)구역     122562\n",
              "주정차금지(황색실선)구역     52743\n",
              "주정차위반             48225\n",
              "교통소통장애            46375\n",
              "32조내지 34조위반       45891\n",
              "보도                42775\n",
              "주정차금지             27807\n",
              "횡단보도              22686\n",
              "주차방법위반            16810\n",
              "버스정류소             11541\n",
              "도로 모퉁이             9430\n",
              "도로교통법 제32조         9214\n",
              "안전지대               7856\n",
              "보도주차               7040\n",
              "소화전                3802\n",
              "교차로                3167\n",
              "버스정류장              1686\n",
              "어린이보호구역            1602\n",
              "안전지대사방             1431\n",
              "주차구획선외 주차          1334\n",
              "주정차금지구역            1050\n",
              "모퉁이                 976\n",
              "보차도                 910\n",
              "특별구역                670\n",
              "소통장해                601\n",
              "통학로                 407\n",
              "건널목                 296\n",
              "이중주차                293\n",
              "건널목,횡단보도            270\n",
              "소방기계 비치장소           240\n",
              "황색실선,황색점선           194\n",
              "소방차(긴급차량)통행장애       191\n",
              "유턴지역                173\n",
              "소화전,소방용기기           121\n",
              "교차로,모퉁이             113\n",
              "도로교통법 제34조          110\n",
              "보도막음                 54\n",
              "중앙선                  51\n",
              "일방통행                 51\n",
              "민원신고                 37\n",
              "도로공사구역               31\n",
              "이면도로주차               28\n",
              "32조위반                26\n",
              "터널                   22\n",
              "화재경보기                 9\n",
              "차도                    8\n",
              "다리                    5\n",
              "교차로,횡단보도,보도           5\n",
              "교통장애                  4\n",
              "공사구역                  2\n",
              "기타                    2\n",
              "도로교통법 제33조            2\n",
              "라인밖                   1\n",
              "거주자우선                 1\n",
              "Name: 위반내용, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 68
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# 위반내용 빈도 분석\n",
        "violation_count = df1['위반내용'].value_counts()\n",
        "#print(violation_count)\n",
        "violation_count = violation_count.head(10)\n",
        "\n",
        "# 위반내용 빈도 시각화\n",
        "plt.rcParams['font.family'] = 'NanumBarunGothic'\n",
        "violation_count.plot(kind='pie',colors = ['#F8B9C5','#B1D8B7','#D3E0C9','#FDE9A8','#D6BDD6','#A2C9D9','#D1D1D1','#FFB347','#E6A8D7','#77DD77'])\n",
        "plt.title('주정차 위반내용 상위 10개')\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 427
        },
        "id": "V5vSEh8jdWX3",
        "outputId": "34d01c80-9ae9-4643-c0b2-f60555eba019"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "colors = ['#F8B9C5','#B1D8B7','#D3E0C9','#FDE9A8','#D6BDD6','#A2C9D9','#D1D1D1','#FFB347','#E6A8D7','#77DD77']\n",
        "\n",
        "plt.pie(violation_count, labels=violation_count.index,colors=colors, autopct='%.1f%%', textprops={'fontsize': 10})\n",
        "plt.axis('equal')\n",
        "plt.title('주정차 위반내용 상위 10개', fontsize=14)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 435
        },
        "id": "gnoNt5leHcvW",
        "outputId": "6335fcf4-4e46-4975-941d-fd15a23e37eb"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### 단속장소"
      ],
      "metadata": {
        "id": "f5hPNF7TGMub"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "리젠트오피스텔 건너편      8256 -> 구의동 /\n",
        "동서울터미널 주차장앞      7856 ->강변역로 50 /\n",
        "지너스타워 주차장 앞      7655 -> 구의동 /\n",
        "건대입구1번출구앞        6822 -> 화양동 /\n",
        "건대분수광장 건너편       6538 -> 화양동 /\n",
        "아차산로             6173 -> 광장동 /\n",
        "건대역약국앞           5973 -> 화양동 /\n",
        "능동로              5643 -> 능동 /\n",
        "구의동 웰츠타워         5291 -> 구의동 /\n",
        "군자역 5번가구할인매장앞    5286 -> 능동"
      ],
      "metadata": {
        "id": "VDxylxX-SK1w"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# 단속장소 빈도 분석\n",
        "location_count = df1['단속장소'].value_counts()\n",
        "print(location_count.head(20))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "CZZI3Go0p93W",
        "outputId": "dde316b6-9766-4f82-8078-91c033751577"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "리젠트오피스텔 건너편      8256\n",
            "동서울터미널 주차장앞      7856\n",
            "지너스타워 주차장 앞      7655\n",
            "건대입구1번출구앞        6822\n",
            "건대분수광장 건너편       6538\n",
            "아차산로             6173\n",
            "건대역약국앞           5973\n",
            "능동로              5643\n",
            "구의동 웰츠타워         5291\n",
            "군자역 5번가구할인매장앞    5286\n",
            "중곡지구대 앞          5003\n",
            "우리은행 앞           4697\n",
            "올포유 앞            4567\n",
            "리젠트오피스텔건너편       3725\n",
            "파리바게트앞           3713\n",
            "건대역약국 앞          3347\n",
            "MB모터스            3300\n",
            "광나루로             3174\n",
            "건대입구 1번 출구 앞     3153\n",
            "MB모터스 옆          2842\n",
            "Name: 단속장소, dtype: int64\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### 단속동"
      ],
      "metadata": {
        "id": "cTIJQGTGGPSh"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# 단속동 컬럼에서 공백 제거\n",
        "df['단속동'] = df['단속동'].str.replace(' ', '')"
      ],
      "metadata": {
        "id": "Y9n7OfgMMDt8"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print(location_count.head(10))\n",
        "print(location_count[1])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "LknzZ5o6N71b",
        "outputId": "6d22a448-82cb-4ced-9213-89f6d124f9fb"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "리젠트오피스텔 건너편      8256\n",
            "동서울터미널 주차장앞      7856\n",
            "지너스타워 주차장 앞      7655\n",
            "건대입구1번출구앞        6822\n",
            "건대분수광장 건너편       6538\n",
            "아차산로             6173\n",
            "건대역약국앞           5973\n",
            "능동로              5643\n",
            "구의동 웰츠타워         5291\n",
            "군자역 5번가구할인매장앞    5286\n",
            "Name: 단속장소, dtype: int64\n",
            "7856\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# 단속동 빈도 분석\n",
        "location_count = df['단속동'].value_counts()\n",
        "location_count = location_count.head(10)\n",
        "print(location_count)\n",
        "print(location_count.shape)\n",
        "# 단속동 빈도 시각화\n",
        "import matplotlib.pyplot as plt\n",
        "plt.rcParams['font.family'] = 'NanumBarunGothic'\n",
        "colors = ['#FFB9B8', 'gray','gray','gray','gray','gray','gray','gray','gray','gray']\n",
        "location_count.plot(kind='bar',rot=0, color = colors)\n",
        "plt.title('주정차 단속 다발 상위 10개 동')\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 671
        },
        "id": "NeoXIgq-MPVH",
        "outputId": "bcd45c0c-ce8d-4957-cc0a-3557d42c6771"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "구의동     117190\n",
            "자양동      92292\n",
            "중곡동      81379\n",
            "화양동      50312\n",
            "광장동      44613\n",
            "군자동      35167\n",
            "능동       18351\n",
            "아차산로      5757\n",
            "능동로       4040\n",
            "광나루로      2040\n",
            "Name: 단속동, dtype: int64\n",
            "(10,)\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(df1['단속동'].unique())"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "exEJZH5rTI1u",
        "outputId": "1682b5ec-aa40-4e3e-be77-6f7f4d11ba24"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "['화양동' '구의동' '능동' '중곡동' '자양동' '군자동' '광장동' '능  동' '노유동' '모진동' '자양번영로2길'\n",
            " '뚝섬로46길' '자양번영로' '자양로' '아차산로' '동일로' '군자로' '능동로31길' '뚝섬로64길' '뚝섬로41길'\n",
            " '면목로' '천호대로' '광나루로' '천호대로118길' '뚝섬로34길' '자양로33길' '능동로1길' '능동로' '천호대로137길'\n",
            " '용마산로' '영화사로' '뚝섬로32길' '용마산로8나길' '뚝섬로' '동일로18길' '광나루로15길' '동일로4길' '긴고랑로'\n",
            " '아차산로76길' '자양로43길' '능동로24길' '천호대로116길' '군자로15길' '동일로52길' '군자로10길' '구의강변로'\n",
            " '광장로' '긴고랑로19길' '능동로4길' '뚝섬로58길' '광나루로30길' '자양로39길' '천호대로130길' '자양로4길'\n",
            " '영화사로16길' '용마산로22길' '능동로19길' '아차산로69길' '자양로13길' '능동로16길' '자양로44길'\n",
            " '광나루로56길' '광나루로44길' '아차산로39길' '뚝섬로66길' '천호대로131길' '자양로30길' '아차산로33길'\n",
            " '구의로' '뚝섬로23길' '군자로9길' '동일로24길' '군자로2길' '아차산로60길' '아차산로75길' '긴고랑로7길'\n",
            " '천호대로136길' '능동로13길' '아차산로49길' '천호대로111길' '자양로50길' '자양번영로4길' '동일로76길'\n",
            " '능동로59길' '긴고랑로40길' '자양강변길' '자양로40길' '아차산로27길' '자양로53길' '워커힐로' '영화사로20길'\n",
            " '광나루로52길' '광장로1다길' '자양번영로1길' '구의로4길' '뚝섬로56길' '능동로11길' '자양로23가길' '자양로21길'\n",
            " '답십리로86길' '동일로30길' '능동로3길' '아차산로23길' '긴고랑로10길' '뚝섬로24길' '자양번영로11길'\n",
            " '구의강변로1길' '광장로7길' '광나루로54길' '답십리로' '광나루로30나길' '광장로1길' '능동로36길' '아차산로73길'\n",
            " '동일로22길' '아차산로21길' '영화사로11길' '강변역로' '아차산로28길' '뚝섬로40길' '군자로12길' '동일로28길'\n",
            " '자양로5길' '능동로26길' '광나루로24길' '동일로70길' '아차산로70길' '뚝섬로52길' '뚝섬로36길'\n",
            " '천호대로141길' '능동로32길' '강변역로4길' '아차산로59길' '용마산로33길' '능동로40길' '영화사로3길'\n",
            " '동일로20길' '능동로38길' '자양로19길' '천호대로119길' '자양로37길' '뚝섬로22길' '아차산로66길' '시민신고웹'\n",
            " '천호대로104나길' '뚝섬로37길' '자양로13가길' '능동로3다길' '능동로48길' '자양로7길' '자양로18길' '능동로6길'\n",
            " '자양로9길' '아차산로76가길' '아차산로78길' '아차산로34길' '긴고랑로13길' '자양로52길' '용마산로25길'\n",
            " '자양로4나길' '용마산로24길' '용마산로28길' '자양로3가길' '아차산로78가길' '영화사로13길' '천호대로115길'\n",
            " '능동로17길' '광나루로18길' '천호대로127길' '자양로51길' '뚝섬로33길' '자양로3길' '뚝섬로26길'\n",
            " '천호대로129길' '뚝섬로52라길' '능동로34길' '긴고랑로22길' '용마산로30길' '자양로26길' '자양번영로6길'\n",
            " '긴고랑로16길' '면목로16길' '동일로26길' '용마산로6길' '긴고랑로46가길' '천호대로114길' '천호대로112길'\n",
            " '천호대로107길' '천호대로104길' '뚝섬로45길' '능동로27가길' '군자로5길' '능동로29가길' '광나루로30가길'\n",
            " '아차산로58길' '영화사로9길' '구의강변로3가길' '용마산로4길' '천호대로102길' '자양로54길' '뚝섬로52마길'\n",
            " '동일로56라길' '아차산로30길' '답십리로84길' '아차산로36길' '구의로6길' '긴고랑로30길' '천호대로134길'\n",
            " '아차산로44길' '뚝섬로48길' '능동로50길' '용마산로2길' '광장로5길' '강변북로' '면목로13길' '뚝섬로54길'\n",
            " '동일로48길' '면목로5길' '자양번영로7길' '능동로10길' '용마산로8가길' '천호대로121길' '자양로2길' '자양로47길'\n",
            " '광나루로46길' '아차산로45길' '용마산로7길' '용마산로1길' '긴고랑로33길' '뚝섬로57가길' '아차산로63길'\n",
            " '자양로6길' '구천면로' '동일로56나길' '뚝섬로50길' '긴고랑로4길' '동일로76나길' '뚝섬로52다길' '천호대로113길'\n",
            " '자양로45길' '뚝섬로30길' '뚝섬로56가길' '아차산로25길' '아차산로41가길' '광나루로30다길' '광나루로12길'\n",
            " '자양로41길' '천호대로143길' '답십리로82길' '용마산로5길' '광나루로37길' '영화사로9가길' '뚝섬로35길'\n",
            " '천호대로124길' '자양로44나길' '능동로51길' '긴고랑로44길' '동일로66길' '뚝섬로31길' '긴고랑로1길'\n",
            " '군자로6길' '군자로7길' '아차산로41길' '능동로5길' '뚝섬로23가길' '천호대로123길' '용마산로3길'\n",
            " '천호대로117길' '긴고랑로6길' '용마산로28다길' '영화사로7길' '아차산로51길' '광장로1가길' '천호대로110길'\n",
            " '동일로72길' '용마산로12길' '동일로10다길' '동일로76가길' '능동로23길' '능동로9길' '구의강변로3길' '능동로7길'\n",
            " '용마산로32길' '구의강변로5길' '동일로60길' '동일로12길' '뚝섬로62길' '능동로30길' '자양번영로5길'\n",
            " '아차산로22길' '영화사로3가길' '자양로11길' '능동로35길' '능동로3마길' '구의로14길' '광나루로17길'\n",
            " '아차산로44가길' '광나루로14길' '용마산로8길' '천호대로101길' '능동로21길' '능동로42길' '뚝섬로49길'\n",
            " '자양번영로3길' '뚝섬로27길' '아차산로40길' '군자로3길' '답십리로78길' '용마산로16길' '동일로2길' '광장로1나길'\n",
            " '영화사로16가길' '자양로42길' '천호대로138길' '뚝섬로44길' '긴고랑로46길' '면목로17길' '동일로4가길'\n",
            " '뚝섬로51길' '자양로32길' '능동로49길' '아차산로55길' '자양번영로3가길' '뚝섬로36가길' '광나루로35길'\n",
            " '용마산로20길' '용마산로14길' '면목로12길' '아차산로26길' '성내천로23길' '자양로23길' '아차산로53길'\n",
            " '아차산로65길' '광나루로16길' '뚝섬로59길' '자양로22길' '광나루로38길' '긴고랑로36길' '동일로16길'\n",
            " '아차산로31길' '구의강변로7길' '광나루로19길' '천호대로125길' '천호대로120길' '동일로80길' '아차산로61길'\n",
            " '능동로27길' '자양로28가길' '동일로68길' '능동로53길' '뚝섬로57길' '광나루로43길' '뚝섬로47길'\n",
            " '뚝섬로32가길' '광나루로20가길' '자양로35길' '천호대로122길' '뚝섬로52가길' '긴고랑로8길' '광나루로36길'\n",
            " '동일로50길' '능동로41길' '아차산로42길' '아차산로29길' '능동로27나길' '면목로7길' '동일로34길' '구의로1길'\n",
            " '광나루로40길' '용마산로18길' '동일로56가길' '자양번영로13길' '광나루로20길' '광장로3길' '동일로56길'\n",
            " '긴고랑로39길' '뚝섬로43길' '뚝섬로55길' '구의로12길' '능동로3가길' '뚝섬로31가길' '아차산로24길'\n",
            " '자양번영로8길' '동일로18가길' '긴고랑로26길' '긴고랑로29길' '능동로48가길' '동일로18나길' '긴고랑로46나길'\n",
            " '긴고랑로47길' '긴고랑로20길' '동일로54길' '자양로15길' '능동로37길' '자양로44가길' '영화사로16나길'\n",
            " '아차산로58가길' '광나루로50길' '군자로17길' '광나루로39길' '자양번영로12길' '자양로48길' '뚝섬로22가길'\n",
            " '긴고랑로31길' '능동로29길' '자양로25길' '아차산로32길' '군자로4길' '천호대로140길' '자양번영로3다길'\n",
            " '자양로38길' '자양로28길' '자양로49길' '긴고랑로14길' '군자로13길' '긴고랑로12길' '답십리로76길'\n",
            " '자양로50가길' '아차산로57길' '능동로39길' '긴고랑로5길' '자양로46길' '답십리로88길' '뚝섬로29길'\n",
            " '긴고랑로17길' '천호대로109길' '뚝섬로67가길' '답십리로80길' '뚝섬로52나길' '자양로36길' '자양로13다길'\n",
            " '뚝섬로30가길' '긴고랑로45길' '긴고랑로38길' '용마산로10길' '구의로16길' '자양로23나길' '동일로62길'\n",
            " '아차산로46길' '영화사로3나길' '긴고랑로9길' '능동로25길' '광장로9길' '광나루로26길' '자양로16길' '동일로78길'\n",
            " '긴고랑로11길' '동일로40길' '동일로6길' '뚝섬로67길' '자양로13나길' '동일로8길' '능동로55길' '긴고랑로15길'\n",
            " '자양번영로3나길' '동일로58길' '긴고랑로2길' '면목로1길' '용마산로21길' '동일로38길' '아차산로46가길'\n",
            " '용마산로29길' '동일로74길' '구의로3길' '광나루로22나길' '강변역로2길' '능동로15길' '용마산로28가길'\n",
            " '동일로56다길' '용마산로27길' '능동로47길' '자양번영로10길' '광나루로22길' '영화사로5길' '뚝섬로25가길'\n",
            " '광나루로13길' '능동로44길' '아차산로39가길' '긴고랑로42길' '면목로11길' '동일로10길' '동일로14길'\n",
            " '뚝섬로58가길' '용마산로8마길' '면목로9길' '용마산로34길' '동일로64길' '능동로43길' '광나루로48길'\n",
            " '용마산로8다길' '천호대로132길']\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "### 단속동 전처리 ###\n",
        "\n",
        "# 단속동 공백 제거\n",
        "df1['단속동'] = df1['단속동'].str.replace(' ', '')"
      ],
      "metadata": {
        "id": "UGOoPRgL-U68"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print(df1['단속동'].unique())"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7X4nPWbfWFMW",
        "outputId": "13503931-1c92-4ebb-aebe-7614dbf69ddd"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "['화양동' '구의동' '능동' '중곡동' '자양동' '군자동' '광장동' '노유동' '모진동' '자양번영로' '뚝섬로' '자양로'\n",
            " '아차산로' '동일로' '군자로' '능동로' '면목로' '천호대로' '광나루로' '용마산로' '영화사로' '긴고랑로' '구의강변로'\n",
            " '광장로' '구의로' '자양강변길' '워커힐로' '답십리로' '강변역로' '시민신고웹' '강변북로' '구천면로' '성내천로']\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import re\n",
        "\n",
        "pattern = r'(.로).+길'\n",
        "for i in range (len(df1['단속동'])):\n",
        "  df1['단속동'][i] = re.sub(pattern, r'\\1',df1['단속동'][i])\n",
        "\n",
        "print(df1)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "jJJhh0PZRPu0",
        "outputId": "b90a6ed6-4c7d-4ec8-ebb8-2244b11e5156"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "        단속동               단속장소           위반내용\n",
            "0       화양동              119-4          주정차금지\n",
            "1       화양동          건대입구1번출구앞    32조내지 34조위반\n",
            "2       구의동        동서울터미널 주차장앞    32조내지 34조위반\n",
            "3       화양동          건대입구1번출구앞    32조내지 34조위반\n",
            "4       화양동          건대입구1번출구앞    32조내지 34조위반\n",
            "...     ...                ...            ...\n",
            "490926  군자동               군자빌딩  주정차금지(황색실선)구역\n",
            "490927  자양동  서울 광진구 자양동 659-32             보도\n",
            "490928  화양동     서울 광진구 능동로 154             보도\n",
            "490929  자양동   서울 광진구 자양동 12-10            교차로\n",
            "490930  자양동              02-02           횡단보도\n",
            "\n",
            "[490931 rows x 3 columns]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import re\n",
        "# 정규 표현식 : 동일로26길 -> 동일로\n",
        "pattern = r'(.로).+길'\n",
        "# 주소 변경\n",
        "for i in range (len(df1['단속동'])):\n",
        "  df1['단속동'][i] = re.sub(pattern, r'\\1',df1['단속동'][i])\n",
        "\n",
        "print(df1)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8nXex0TAHzkv",
        "outputId": "f4c99b2b-d844-4747-ce99-41559eeb65fa"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "        단속동               단속장소           위반내용\n",
            "0       화양동              119-4          주정차금지\n",
            "1       화양동          건대입구1번출구앞    32조내지 34조위반\n",
            "2       구의동        동서울터미널 주차장앞    32조내지 34조위반\n",
            "3       화양동          건대입구1번출구앞    32조내지 34조위반\n",
            "4       화양동          건대입구1번출구앞    32조내지 34조위반\n",
            "...     ...                ...            ...\n",
            "490926  군자동               군자빌딩  주정차금지(황색실선)구역\n",
            "490927  자양동  서울 광진구 자양동 659-32             보도\n",
            "490928  화양동     서울 광진구 능동로 154             보도\n",
            "490929  자양동   서울 광진구 자양동 12-10            교차로\n",
            "490930  자양동              02-02           횡단보도\n",
            "\n",
            "[490931 rows x 3 columns]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# 단속동 빈도 분석\n",
        "location_count = df1['단속동'].value_counts()\n",
        "print(location_count.head(7))\n",
        "print(location_count.shape)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "4GsC176cJufi",
        "outputId": "4224ae13-9eae-4e86-af85-d52a44cec8dd"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "구의동    117190\n",
            "자양동     92292\n",
            "중곡동     81379\n",
            "화양동     50312\n",
            "광장동     44613\n",
            "군자동     35167\n",
            "능동      18351\n",
            "Name: 단속동, dtype: int64\n",
            "(33,)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# 예시 데이터 생성\n",
        "count = pd.Series([117190, 92292, 81379, 50312, 44613, 35167, 18351], index=['구의동', '자양동', '중곡동', '화양동', '광장동', '군자동', '능동'])\n",
        "\n",
        "# Series를 DataFrame으로 변환하고 인덱스를 컬럼으로 변경\n",
        "location_count = count.to_frame().reset_index()\n",
        "\n",
        "# 컬럼 이름 지정\n",
        "location_count.columns = ['단속동', '단속건수']\n",
        "\n",
        "# 출력\n",
        "print(location_count)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "MFOh97DoYGh7",
        "outputId": "2685f762-8765-4145-f8f5-2fe15b913cba"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "   단속동    단속건수\n",
            "0  구의동  117190\n",
            "1  자양동   92292\n",
            "2  중곡동   81379\n",
            "3  화양동   50312\n",
            "4  광장동   44613\n",
            "5  군자동   35167\n",
            "6   능동   18351\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# # 단속동 빈도 분석\n",
        "# location_count = df1['단속동'].value_counts()\n",
        "# print(location_count)"
      ],
      "metadata": {
        "id": "mTc-wiWzdWtG"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "### 지도 시각화(단속동 빈도 분석)"
      ],
      "metadata": {
        "id": "xvytgvmylowQ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import folium\n",
        "from folium.plugins import MarkerCluster"
      ],
      "metadata": {
        "id": "-C7lu9ukWHgf"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# 데이터 불러오기\n",
        "where = \"/content/drive/MyDrive/[03팀] 김가경, 김수민, 민채원/code/GwangjinGu_latilong.csv\"\n",
        "# 데이터 불러오기\n",
        "data = pd.read_csv(where, encoding='utf-8')\n",
        "data = data[data['시군구'] == '광진구']\n",
        "data = data.rename(columns={'읍면동/구': '단속동'})\n",
        "data"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 645
        },
        "id": "3NCXwctUolp7",
        "outputId": "088d5ea8-9102-4acc-fe9c-568b495797e1"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "        시도  시군구    단속동  읍/면/리/동   리         위도          경도\n",
              "556  서울특별시  광진구    NaN      NaN NaN  37.538617  127.082375\n",
              "557  서울특별시  광진구    자양동      NaN NaN  37.534508  127.082438\n",
              "558  서울특별시  광진구    구의동      NaN NaN  37.542492  127.085676\n",
              "559  서울특별시  광진구    중곡동      NaN NaN  37.560675  127.080038\n",
              "560  서울특별시  광진구  구의제3동      NaN NaN  37.538071  127.092020\n",
              "561  서울특별시  광진구  구의제2동      NaN NaN  37.547248  127.089911\n",
              "562  서울특별시  광진구  구의제1동      NaN NaN  37.542492  127.085676\n",
              "563  서울특별시  광진구  자양제4동      NaN NaN  37.534112  127.066297\n",
              "564  서울특별시  광진구  자양제3동      NaN NaN  37.533842  127.072913\n",
              "565  서울특별시  광진구  자양제2동      NaN NaN  37.528825  127.084438\n",
              "566  서울특별시  광진구  자양제1동      NaN NaN  37.534508  127.082438\n",
              "567  서울특별시  광진구    광장동      NaN NaN  37.546892  127.103025\n",
              "568  서울특별시  광진구     능동      NaN NaN  37.553780  127.080499\n",
              "569  서울특별시  광진구  중곡제4동      NaN NaN  37.559086  127.089454\n",
              "570  서울특별시  광진구  중곡제3동      NaN NaN  37.568808  127.080174\n",
              "571  서울특별시  광진구  중곡제2동      NaN NaN  37.560308  127.081487\n",
              "572  서울특별시  광진구  중곡제1동      NaN NaN  37.560675  127.080038\n",
              "573  서울특별시  광진구    군자동      NaN NaN  37.555122  127.075837\n",
              "574  서울특별시  광진구    화양동      NaN NaN  37.546542  127.071315"
            ],
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              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>시도</th>\n",
              "      <th>시군구</th>\n",
              "      <th>단속동</th>\n",
              "      <th>읍/면/리/동</th>\n",
              "      <th>리</th>\n",
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              "  </thead>\n",
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              "      <td>37.534508</td>\n",
              "      <td>127.082438</td>\n",
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              "      <th>558</th>\n",
              "      <td>서울특별시</td>\n",
              "      <td>광진구</td>\n",
              "      <td>구의동</td>\n",
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              "      <td>37.542492</td>\n",
              "      <td>127.085676</td>\n",
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              "    <tr>\n",
              "      <th>559</th>\n",
              "      <td>서울특별시</td>\n",
              "      <td>광진구</td>\n",
              "      <td>중곡동</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>37.560675</td>\n",
              "      <td>127.080038</td>\n",
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              "      <th>560</th>\n",
              "      <td>서울특별시</td>\n",
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              "      <td>구의제3동</td>\n",
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              "      <td>NaN</td>\n",
              "      <td>37.538071</td>\n",
              "      <td>127.092020</td>\n",
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              "    <tr>\n",
              "      <th>561</th>\n",
              "      <td>서울특별시</td>\n",
              "      <td>광진구</td>\n",
              "      <td>구의제2동</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>37.547248</td>\n",
              "      <td>127.089911</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>562</th>\n",
              "      <td>서울특별시</td>\n",
              "      <td>광진구</td>\n",
              "      <td>구의제1동</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>37.542492</td>\n",
              "      <td>127.085676</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>563</th>\n",
              "      <td>서울특별시</td>\n",
              "      <td>광진구</td>\n",
              "      <td>자양제4동</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>37.534112</td>\n",
              "      <td>127.066297</td>\n",
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              "    <tr>\n",
              "      <th>564</th>\n",
              "      <td>서울특별시</td>\n",
              "      <td>광진구</td>\n",
              "      <td>자양제3동</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>37.533842</td>\n",
              "      <td>127.072913</td>\n",
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              "      <th>565</th>\n",
              "      <td>서울특별시</td>\n",
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              "      <td>NaN</td>\n",
              "      <td>37.528825</td>\n",
              "      <td>127.084438</td>\n",
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              "    <tr>\n",
              "      <th>566</th>\n",
              "      <td>서울특별시</td>\n",
              "      <td>광진구</td>\n",
              "      <td>자양제1동</td>\n",
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              "      <td>NaN</td>\n",
              "      <td>37.534508</td>\n",
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              "      <th>571</th>\n",
              "      <td>서울특별시</td>\n",
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              "      <td>중곡제2동</td>\n",
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              "      <td>NaN</td>\n",
              "      <td>37.560308</td>\n",
              "      <td>127.081487</td>\n",
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              "      <th>572</th>\n",
              "      <td>서울특별시</td>\n",
              "      <td>광진구</td>\n",
              "      <td>중곡제1동</td>\n",
              "      <td>NaN</td>\n",
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              "      <td>37.560675</td>\n",
              "      <td>127.080038</td>\n",
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              "      <td>37.546542</td>\n",
              "      <td>127.071315</td>\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
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              "    [theme=dark] .colab-df-convert:hover {\n",
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              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-23ec96e7-ab9c-4f5f-9fe1-f4f0c125d5d1');\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",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# 단속동df, 위도/경도df -> merge\n",
        "merged_df = pd.merge(data,location_count, on='단속동', how='left')\n",
        "merged_df = merged_df[['단속동','단속건수','위도','경도']]\n",
        "merged_df = merged_df.dropna(subset=['단속건수'])\n",
        "merged_df = merged_df.sort_values(by = '단속건수', ascending = False)\n",
        "merged_df['단속건수'] = merged_df['단속건수'].astype(int)\n",
        "merged_df = merged_df.reset_index(drop=True) #인덱스 0부터 시작하게\n",
        "merged_df"
      ],
      "metadata": {
        "id": "zAybq0-G1v5e",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 269
        },
        "outputId": "770092e5-663b-4ed6-973f-337d0d64c353"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   단속동    단속건수         위도          경도\n",
              "0  구의동  117190  37.542492  127.085676\n",
              "1  자양동   92292  37.534508  127.082438\n",
              "2  중곡동   81379  37.560675  127.080038\n",
              "3  화양동   50312  37.546542  127.071315\n",
              "4  광장동   44613  37.546892  127.103025\n",
              "5  군자동   35167  37.555122  127.075837\n",
              "6   능동   18351  37.553780  127.080499"
            ],
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              "\n",
              "  <div id=\"df-efef0cca-7097-430d-af6b-3fe9c45c2146\">\n",
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              "      <div>\n",
              "<style scoped>\n",
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>단속동</th>\n",
              "      <th>단속건수</th>\n",
              "      <th>위도</th>\n",
              "      <th>경도</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>구의동</td>\n",
              "      <td>117190</td>\n",
              "      <td>37.542492</td>\n",
              "      <td>127.085676</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>자양동</td>\n",
              "      <td>92292</td>\n",
              "      <td>37.534508</td>\n",
              "      <td>127.082438</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>중곡동</td>\n",
              "      <td>81379</td>\n",
              "      <td>37.560675</td>\n",
              "      <td>127.080038</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>화양동</td>\n",
              "      <td>50312</td>\n",
              "      <td>37.546542</td>\n",
              "      <td>127.071315</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>광장동</td>\n",
              "      <td>44613</td>\n",
              "      <td>37.546892</td>\n",
              "      <td>127.103025</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>군자동</td>\n",
              "      <td>35167</td>\n",
              "      <td>37.555122</td>\n",
              "      <td>127.075837</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>능동</td>\n",
              "      <td>18351</td>\n",
              "      <td>37.553780</td>\n",
              "      <td>127.080499</td>\n",
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              "  </tbody>\n",
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              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
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              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-efef0cca-7097-430d-af6b-3fe9c45c2146 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-efef0cca-7097-430d-af6b-3fe9c45c2146');\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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            ]
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          "metadata": {},
          "execution_count": 38
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install selenium"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "wO8LwAdCbma8",
        "outputId": "d243bd50-9ee6-4010-b5bd-87fd2db2f55d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Collecting selenium\n",
            "  Downloading selenium-4.9.0-py3-none-any.whl (6.5 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m6.5/6.5 MB\u001b[0m \u001b[31m50.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting trio~=0.17\n",
            "  Downloading trio-0.22.0-py3-none-any.whl (384 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m384.9/384.9 kB\u001b[0m \u001b[31m32.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: certifi>=2021.10.8 in /usr/local/lib/python3.10/dist-packages (from selenium) (2022.12.7)\n",
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            "Collecting trio-websocket~=0.9\n",
            "  Downloading trio_websocket-0.10.2-py3-none-any.whl (17 kB)\n",
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            "Requirement already satisfied: attrs>=19.2.0 in /usr/local/lib/python3.10/dist-packages (from trio~=0.17->selenium) (23.1.0)\n",
            "Collecting async-generator>=1.9\n",
            "  Downloading async_generator-1.10-py3-none-any.whl (18 kB)\n",
            "Requirement already satisfied: sortedcontainers in /usr/local/lib/python3.10/dist-packages (from trio~=0.17->selenium) (2.4.0)\n",
            "Collecting outcome\n",
            "  Downloading outcome-1.2.0-py2.py3-none-any.whl (9.7 kB)\n",
            "Collecting wsproto>=0.14\n",
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            "Requirement already satisfied: PySocks!=1.5.7,<2.0,>=1.5.6 in /usr/local/lib/python3.10/dist-packages (from urllib3[socks]~=1.26->selenium) (1.7.1)\n",
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            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m58.3/58.3 kB\u001b[0m \u001b[31m7.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hInstalling collected packages: outcome, h11, async-generator, wsproto, trio, trio-websocket, selenium\n",
            "Successfully installed async-generator-1.10 h11-0.14.0 outcome-1.2.0 selenium-4.9.0 trio-0.22.0 trio-websocket-0.10.2 wsproto-1.2.0\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from collections import defaultdict\n",
        "import time\n",
        "# 광진구 좌표\n",
        "GwangjinGu = merged_df.loc[:,['위도','경도']]\n",
        "lst = GwangjinGu.values.tolist() # DF -> list\n",
        "\n",
        "# 광진구 중심 좌표\n",
        "center = [ 37.538617,127.082375]\n",
        "m = folium.Map(location=center,titles = 'GwangjinGu', zoom_start=13)\n",
        "\n",
        "# 단속건수 범위 구하기\n",
        "min_count = merged_df['단속건수'].min()\n",
        "max_count = merged_df['단속건수'].max()\n",
        "diff_count = max_count - min_count\n",
        "\n",
        "# 원을 표시하고 빈도수에 따라 원의 크기를 조절\n",
        "for i in range(len(merged_df)):\n",
        "    count = merged_df.loc[i, '단속건수']\n",
        "    normalized_count = (count - min_count) / diff_count  # 단속건수를 0~1 사이로 정규화\n",
        "    radius = normalized_count * 80 + 5  # 원의 크기는 빈도수와 비례하도록 조절\n",
        "    color = f'#{int(255*normalized_count):02x}0000'  # 원의 색상은 빈도수에 따라 변화하도록 조절\n",
        "    folium.CircleMarker(location=lst[i],\n",
        "                        radius=radius,\n",
        "                        color=color,\n",
        "                        fill_color=color).add_to(m)\n",
        "    folium.Marker(location=lst[i],  # 동 이름 표시\n",
        "                  icon=folium.Icon(color='green',icon='mapbox'),\n",
        "                  tooltip=merged_df.loc[i, '단속동']).add_to(m)\n",
        "\n",
        "m.save('map.html')\n",
        "m"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 395
        },
        "id": "5nkr7hP4lsNL",
        "outputId": "644f458c-9be9-4029-a625-cfdc1dbf99e9"
      },
      "execution_count": null,
      "outputs": [
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          "output_type": "execute_result",
          "data": {
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              "                &quot;https://{s}.tile.openstreetmap.org/{z}/{x}/{y}.png&quot;,\n",
              "                {&quot;attribution&quot;: &quot;Data by \\u0026copy; \\u003ca target=\\&quot;_blank\\&quot; href=\\&quot;http://openstreetmap.org\\&quot;\\u003eOpenStreetMap\\u003c/a\\u003e, under \\u003ca target=\\&quot;_blank\\&quot; href=\\&quot;http://www.openstreetmap.org/copyright\\&quot;\\u003eODbL\\u003c/a\\u003e.&quot;, &quot;detectRetina&quot;: false, &quot;maxNativeZoom&quot;: 18, &quot;maxZoom&quot;: 18, &quot;minZoom&quot;: 0, &quot;noWrap&quot;: false, &quot;opacity&quot;: 1, &quot;subdomains&quot;: &quot;abc&quot;, &quot;tms&quot;: false}\n",
              "            ).addTo(map_1b11a4770f103598b9976cfbd9f86db3);\n",
              "        \n",
              "    \n",
              "            var circle_marker_d9c2e210b68cecd164d1a561790e59fe = L.circleMarker(\n",
              "                [37.534508, 127.082438],\n",
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              "    \n",
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              "                [37.534508, 127.082438],\n",
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              "            var icon_c69ac03f64aad7340955f20195510b2e = L.AwesomeMarkers.icon(\n",
              "                {&quot;extraClasses&quot;: &quot;fa-rotate-0&quot;, &quot;icon&quot;: &quot;mapbox&quot;, &quot;iconColor&quot;: &quot;white&quot;, &quot;markerColor&quot;: &quot;green&quot;, &quot;prefix&quot;: &quot;glyphicon&quot;}\n",
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              "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;#ff0000&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: true, &quot;fillColor&quot;: &quot;#ff0000&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 85.0, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
              "            ).addTo(map_1b11a4770f103598b9976cfbd9f86db3);\n",
              "        \n",
              "    \n",
              "            var marker_a199daadab37a7577d54d4e92aa4fa33 = L.marker(\n",
              "                [37.5424917, 127.0856756],\n",
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              "            ).addTo(map_1b11a4770f103598b9976cfbd9f86db3);\n",
              "        \n",
              "    \n",
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              "                {&quot;extraClasses&quot;: &quot;fa-rotate-0&quot;, &quot;icon&quot;: &quot;mapbox&quot;, &quot;iconColor&quot;: &quot;white&quot;, &quot;markerColor&quot;: &quot;green&quot;, &quot;prefix&quot;: &quot;glyphicon&quot;}\n",
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              "            ).addTo(map_1b11a4770f103598b9976cfbd9f86db3);\n",
              "        \n",
              "    \n",
              "            var marker_af8aa365978680dcb98069af9c5b8542 = L.marker(\n",
              "                [37.560675, 127.080038],\n",
              "                {}\n",
              "            ).addTo(map_1b11a4770f103598b9976cfbd9f86db3);\n",
              "        \n",
              "    \n",
              "            var icon_aeb664357e28bd640b5c806d7462d2c6 = L.AwesomeMarkers.icon(\n",
              "                {&quot;extraClasses&quot;: &quot;fa-rotate-0&quot;, &quot;icon&quot;: &quot;mapbox&quot;, &quot;iconColor&quot;: &quot;white&quot;, &quot;markerColor&quot;: &quot;green&quot;, &quot;prefix&quot;: &quot;glyphicon&quot;}\n",
              "            );\n",
              "            marker_af8aa365978680dcb98069af9c5b8542.setIcon(icon_aeb664357e28bd640b5c806d7462d2c6);\n",
              "        \n",
              "    \n",
              "            marker_af8aa365978680dcb98069af9c5b8542.bindTooltip(\n",
              "                `&lt;div&gt;\n",
              "                     중곡동\n",
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              "        \n",
              "    \n",
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              "        \n",
              "    \n",
              "            var marker_fc307c898dbac7ffd778725372e03c92 = L.marker(\n",
              "                [37.546892, 127.103025],\n",
              "                {}\n",
              "            ).addTo(map_1b11a4770f103598b9976cfbd9f86db3);\n",
              "        \n",
              "    \n",
              "            var icon_a58cf21be1cf97eb3ded8ca58cbc8ded = L.AwesomeMarkers.icon(\n",
              "                {&quot;extraClasses&quot;: &quot;fa-rotate-0&quot;, &quot;icon&quot;: &quot;mapbox&quot;, &quot;iconColor&quot;: &quot;white&quot;, &quot;markerColor&quot;: &quot;green&quot;, &quot;prefix&quot;: &quot;glyphicon&quot;}\n",
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              "                `&lt;div&gt;\n",
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              "            ).addTo(map_1b11a4770f103598b9976cfbd9f86db3);\n",
              "        \n",
              "    \n",
              "            var marker_9c777f605ca7ef7c82ad30ef563a68a9 = L.marker(\n",
              "                [37.5537803, 127.0804994],\n",
              "                {}\n",
              "            ).addTo(map_1b11a4770f103598b9976cfbd9f86db3);\n",
              "        \n",
              "    \n",
              "            var icon_4ea7807f9cef3385468f2f1591de7efa = L.AwesomeMarkers.icon(\n",
              "                {&quot;extraClasses&quot;: &quot;fa-rotate-0&quot;, &quot;icon&quot;: &quot;mapbox&quot;, &quot;iconColor&quot;: &quot;white&quot;, &quot;markerColor&quot;: &quot;green&quot;, &quot;prefix&quot;: &quot;glyphicon&quot;}\n",
              "            );\n",
              "            marker_9c777f605ca7ef7c82ad30ef563a68a9.setIcon(icon_4ea7807f9cef3385468f2f1591de7efa);\n",
              "        \n",
              "    \n",
              "            marker_9c777f605ca7ef7c82ad30ef563a68a9.bindTooltip(\n",
              "                `&lt;div&gt;\n",
              "                     능동\n",
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              "                {&quot;sticky&quot;: true}\n",
              "            );\n",
              "        \n",
              "    \n",
              "            var circle_marker_08fb3626c3ec020425c34db0db22c248 = L.circleMarker(\n",
              "                [37.5551217, 127.0758373],\n",
              "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;#2b0000&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: true, &quot;fillColor&quot;: &quot;#2b0000&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 18.610821639231478, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
              "            ).addTo(map_1b11a4770f103598b9976cfbd9f86db3);\n",
              "        \n",
              "    \n",
              "            var marker_d9d9e0ceeec1fbe6d6f77e7239dfb133 = L.marker(\n",
              "                [37.5551217, 127.0758373],\n",
              "                {}\n",
              "            ).addTo(map_1b11a4770f103598b9976cfbd9f86db3);\n",
              "        \n",
              "    \n",
              "            var icon_7aef5a58cd3211e18bcd62c85ad13f10 = L.AwesomeMarkers.icon(\n",
              "                {&quot;extraClasses&quot;: &quot;fa-rotate-0&quot;, &quot;icon&quot;: &quot;mapbox&quot;, &quot;iconColor&quot;: &quot;white&quot;, &quot;markerColor&quot;: &quot;green&quot;, &quot;prefix&quot;: &quot;glyphicon&quot;}\n",
              "            );\n",
              "            marker_d9d9e0ceeec1fbe6d6f77e7239dfb133.setIcon(icon_7aef5a58cd3211e18bcd62c85ad13f10);\n",
              "        \n",
              "    \n",
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              "                `&lt;div&gt;\n",
              "                     군자동\n",
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              "                {&quot;sticky&quot;: true}\n",
              "            );\n",
              "        \n",
              "    \n",
              "            var circle_marker_864896413ba64f7ddf42a97793a50e71 = L.circleMarker(\n",
              "                [37.5465421, 127.0713152],\n",
              "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;#520000&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: true, &quot;fillColor&quot;: &quot;#520000&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 30.869140723803355, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
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              "        \n",
              "    \n",
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              "                `&lt;div&gt;\n",
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            ]
          },
          "metadata": {},
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### 인구수 시각화"
      ],
      "metadata": {
        "id": "HRe31xefoF6H"
      }
    },
    {
      "cell_type": "markdown",
      "source": [],
      "metadata": {
        "id": "XpvQcP2kCtZr"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "# 데이터 불러오기\n",
        "filename = \"/content/drive/MyDrive/[03팀] 김가경, 김수민, 민채원/code/Gwangjin-Gu Population of March.csv\"\n",
        "# 데이터 불러오기\n",
        "population = pd.read_csv(filename, encoding='cp949')\n",
        "print(population)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "jSdOlDTLnI4j",
        "outputId": "405a3d47-753f-45ff-fb24-fd2a3f866634"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "     행정기관       합계        남        여\n",
            "0     광진구  336,801  162,209  174,592\n",
            "1     화양동   23,450   11,171   12,279\n",
            "2     군자동   19,340    9,576    9,764\n",
            "3   중곡제1동   15,453    7,364    8,089\n",
            "4   중곡제2동   20,856    9,828   11,028\n",
            "5   중곡제3동   15,913    7,861    8,052\n",
            "6   중곡제4동   27,866   13,623   14,243\n",
            "7      능동   11,163    5,131    6,032\n",
            "8     광장동   34,044   16,468   17,576\n",
            "9   자양제1동   22,007   10,710   11,297\n",
            "10  자양제2동   23,802   11,546   12,256\n",
            "11  자양제3동   27,457   13,117   14,340\n",
            "12  자양제4동   17,989    8,964    9,025\n",
            "13  구의제1동   23,424   11,181   12,243\n",
            "14  구의제2동   25,864   12,385   13,479\n",
            "15  구의제3동   28,173   13,284   14,889\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "population['합계'] = population['합계'].apply(lambda x: int(x.replace(',', '')))\n",
        "population['남'] = population['남'].apply(lambda x: int(x.replace(',', '')))\n",
        "population['여'] = population['여'].apply(lambda x: int(x.replace(',', '')))\n"
      ],
      "metadata": {
        "id": "v4lwkttLw_DS"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# 행정기관 전처리 : 앞 두글자가 같은 경우 그룹화\n",
        "population['행정기관'] = population['행정기관'].str[:2]\n",
        "grouped_population = population.groupby('행정기관', as_index=False).sum()\n",
        "grouped_population = grouped_population.sort_values(by='합계',ascending = False)\n",
        "grouped_population = grouped_population.drop([1])\n",
        "# 결과 확인\n",
        "print(grouped_population)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "QM5W6StWofsy",
        "outputId": "6a2bf7b5-874a-4779-f16d-e12955561bd5"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "  행정기관     합계      남      여\n",
            "5   자양  91255  44337  46918\n",
            "6   중곡  80088  38676  41412\n",
            "2   구의  77461  36850  40611\n",
            "0   광장  34044  16468  17576\n",
            "7   화양  23450  11171  12279\n",
            "3   군자  19340   9576   9764\n",
            "4   능동  11163   5131   6032\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt\n",
        "colors = ['#BBDEFB','#FFD1DC']\n",
        "grouped_population = grouped_population.set_index('행정기관')\n",
        "ax = grouped_population[['남', '여']].plot(title = '행정기관 별 인구수',kind='bar', color = colors, stacked=True)\n",
        "ax.set_xlabel('행정기관')\n",
        "ax.set_ylabel('인구수')\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 481
        },
        "id": "plFxGZCLvI6z",
        "outputId": "ec22bc5f-0356-44f5-ed32-7e8219f08213"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "grouped_population.to_csv('population.csv', index=True)"
      ],
      "metadata": {
        "id": "DivkmXBkz4EP"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "dt = pivot_table[(~pivot_table==0).all(axis=1)]"
      ],
      "metadata": {
        "id": "PNCVoy0cuUyJ"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print(dt)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "qFQ43W5QtgfU",
        "outputId": "e98783fc-db6a-410d-e76b-0fa12b525175"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Empty DataFrame\n",
            "Columns: [32조내지 34조위반, 32조위반, 거주자우선, 건널목, 건널목,횡단보도, 공사구역, 교차로, 교차로,모퉁이, 교차로,횡단보도,보도, 교통소통장애, 교통장애, 기타, 다리, 도로 모퉁이, 도로공사구역, 도로교통법 제32조, 도로교통법 제33조, 도로교통법 제34조, 라인밖, 모퉁이, 민원신고, 버스정류소, 버스정류장, 보도, 보도막음, 보도주차, 보차도, 소방기계 비치장소, 소방차(긴급차량)통행장애, 소통장해, 소화전, 소화전,소방용기기, 안전지대, 안전지대사방, 어린이보호구역, 유턴지역, 이면도로주차, 이중주차, 일방통행, 주정차금지, 주정차금지(황색실선)구역, 주정차금지구역, 주정차위반, 주차구획선외 주차, 주차금지(황색점선)구역, 주차방법위반, 중앙선, 차도, 터널, 통학로, 특별구역, 화재경보기, 황색실선,황색점선, 횡단보도]\n",
            "Index: []\n",
            "\n",
            "[0 rows x 54 columns]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pivot_table"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 759
        },
        "id": "YI59SqYizhGW",
        "outputId": "b29dc218-89a3-46e7-e2d9-0767c72e44f5"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "위반내용      32조내지 34조위반  32조위반  거주자우선  건널목  건널목,횡단보도  공사구역  교차로  교차로,모퉁이  \\\n",
              "단속동                                                                      \n",
              "강변북로                0      0      0    0         0     0    0        0   \n",
              "강변역로                0      0      0    0         0     0    0        0   \n",
              "강변역로2길              0      0      0    0         0     0    0        0   \n",
              "강변역로4길              0      0      0    0         0     0    5        0   \n",
              "광나루로                0      1      0    0         3     0    0        0   \n",
              "...               ...    ...    ...  ...       ...   ...  ...      ...   \n",
              "천호대로138길            0      0      0    0         0     0    0        0   \n",
              "천호대로140길            0      0      0    0         0     0    0        0   \n",
              "천호대로141길            0      0      0    0         0     0    0        0   \n",
              "천호대로143길            0      0      0    0         0     0    0        0   \n",
              "화양동              9551      0      0    5         5     0  352        7   \n",
              "\n",
              "위반내용      교차로,횡단보도,보도  교통소통장애  ...  주차금지(황색점선)구역  주차방법위반  중앙선  차도  터널  통학로  \\\n",
              "단속동                            ...                                           \n",
              "강변북로                0      11  ...             2       6    0   0   0    0   \n",
              "강변역로                0      15  ...             9      11    0   0   0    0   \n",
              "강변역로2길              0       0  ...             0       1    0   0   0    0   \n",
              "강변역로4길              0      90  ...            39      45    0   0   0    0   \n",
              "광나루로                0     485  ...           563     232    0   0   0    0   \n",
              "...               ...     ...  ...           ...     ...  ...  ..  ..  ...   \n",
              "천호대로138길            0      21  ...            23      47    0   0   0    0   \n",
              "천호대로140길            0       0  ...             0       1    0   0   0    0   \n",
              "천호대로141길            0      22  ...             9       1    0   0   0    0   \n",
              "천호대로143길            0       4  ...             4       0    0   0   0    0   \n",
              "화양동                 0    3901  ...          7656     880    0   2   5    2   \n",
              "\n",
              "위반내용      특별구역  화재경보기  황색실선,황색점선  횡단보도  \n",
              "단속동                                     \n",
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              "광나루로         0      0          0    93  \n",
              "...        ...    ...        ...   ...  \n",
              "천호대로138길     0      0          0    10  \n",
              "천호대로140길     0      0          0     3  \n",
              "천호대로141길     0      0          0     0  \n",
              "천호대로143길     0      0          0     0  \n",
              "화양동         22      0          9  2766  \n",
              "\n",
              "[491 rows x 54 columns]"
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              "      <th></th>\n",
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              "      <th>강변역로</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>15</td>\n",
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              "      <td>0</td>\n",
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              "      <th>강변역로2길</th>\n",
              "      <td>0</td>\n",
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              "      <th>강변역로4길</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
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              "      <th>광나루로</th>\n",
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              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <th>천호대로138길</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
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              "    <tr>\n",
              "      <th>천호대로140길</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "    <tr>\n",
              "      <th>천호대로141길</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
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              "    <tr>\n",
              "      <th>천호대로143길</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <th>화양동</th>\n",
              "      <td>9551</td>\n",
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              "      <td>5</td>\n",
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              "      <td>7</td>\n",
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              "      <td>22</td>\n",
              "      <td>0</td>\n",
              "      <td>9</td>\n",
              "      <td>2766</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>491 rows × 54 columns</p>\n",
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              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-7e70f96c-30cc-4338-868c-28615e22da4d')\"\n",
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              "    .colab-df-convert {\n",
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              "\n",
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              "          document.querySelector('#df-7e70f96c-30cc-4338-868c-28615e22da4d button.colab-df-convert');\n",
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              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-7e70f96c-30cc-4338-868c-28615e22da4d');\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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              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 107
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pivot_table['합계'] = pivot_table.iloc[:,:54].sum(axis = 1)\n",
        "pivot_table = pivot_table.sort_values('합계',ascending = False)\n",
        "pivot_table = pivot_table.head(10)"
      ],
      "metadata": {
        "id": "4RofD6yAyOoo"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "pivot_table"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 676
        },
        "id": "i_burj4qzmue",
        "outputId": "160dd3cc-2ab4-490b-9287-96c61b413cb0"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "위반내용  32조내지 34조위반  32조위반  거주자우선  건널목  건널목,횡단보도  공사구역  교차로  교차로,모퉁이  \\\n",
              "단속동                                                                  \n",
              "구의동         15927      0      0   49        16     2  435       14   \n",
              "자양동          7428      1      0   60        16     0  752       26   \n",
              "중곡동          9130      0      0  129        16     0  611       22   \n",
              "화양동          9551      0      0    5         5     0  352        7   \n",
              "광장동           958      0      0   30        13     0  548       14   \n",
              "군자동          2021      0      0    8         6     0  282        9   \n",
              "능동            876      0      0    9         1     0  117        4   \n",
              "아차산로            0      1      0    1        25     0    2        0   \n",
              "능동로             0      0      0    1         8     0    2        1   \n",
              "능  동            0      0      0    0         0     0    4        0   \n",
              "\n",
              "위반내용  교차로,횡단보도,보도  교통소통장애  ...  주차방법위반  중앙선  차도  터널  통학로  특별구역  화재경보기  \\\n",
              "단속동                        ...                                          \n",
              "구의동             0    9338  ...    1076    4   2   4  115   112      3   \n",
              "자양동             0    8823  ...    1985    9   1   4  116   173      2   \n",
              "중곡동             0    4456  ...     597    0   0   2  104    54      0   \n",
              "화양동             0    3901  ...     880    0   2   5    2    22      0   \n",
              "광장동             0    4853  ...    1661    1   2   0   57   269      1   \n",
              "군자동             0    1842  ...    1014   37   0   1   13    38      0   \n",
              "능동              0    1868  ...     129    0   1   1    0     2      0   \n",
              "아차산로            1    1054  ...    1342    0   0   3    0     0      0   \n",
              "능동로             0     972  ...     482    0   0   2    0     0      0   \n",
              "능  동            0       0  ...      20    0   0   0    0     0      0   \n",
              "\n",
              "위반내용  황색실선,황색점선  횡단보도      합계  \n",
              "단속동                            \n",
              "구의동          64  3698  117190  \n",
              "자양동          60  6900   92292  \n",
              "중곡동          26  2990   81379  \n",
              "화양동           9  2766   50312  \n",
              "광장동          17  1656   44613  \n",
              "군자동          18  1121   35167  \n",
              "능동            0    86   15709  \n",
              "아차산로          0   247    5757  \n",
              "능동로           0   107    4040  \n",
              "능  동          0     7    2642  \n",
              "\n",
              "[10 rows x 55 columns]"
            ],
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              "\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th>위반내용</th>\n",
              "      <th>32조내지 34조위반</th>\n",
              "      <th>32조위반</th>\n",
              "      <th>거주자우선</th>\n",
              "      <th>건널목</th>\n",
              "      <th>건널목,횡단보도</th>\n",
              "      <th>공사구역</th>\n",
              "      <th>교차로</th>\n",
              "      <th>교차로,모퉁이</th>\n",
              "      <th>교차로,횡단보도,보도</th>\n",
              "      <th>교통소통장애</th>\n",
              "      <th>...</th>\n",
              "      <th>주차방법위반</th>\n",
              "      <th>중앙선</th>\n",
              "      <th>차도</th>\n",
              "      <th>터널</th>\n",
              "      <th>통학로</th>\n",
              "      <th>특별구역</th>\n",
              "      <th>화재경보기</th>\n",
              "      <th>황색실선,황색점선</th>\n",
              "      <th>횡단보도</th>\n",
              "      <th>합계</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>단속동</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <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>구의동</th>\n",
              "      <td>15927</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>49</td>\n",
              "      <td>16</td>\n",
              "      <td>2</td>\n",
              "      <td>435</td>\n",
              "      <td>14</td>\n",
              "      <td>0</td>\n",
              "      <td>9338</td>\n",
              "      <td>...</td>\n",
              "      <td>1076</td>\n",
              "      <td>4</td>\n",
              "      <td>2</td>\n",
              "      <td>4</td>\n",
              "      <td>115</td>\n",
              "      <td>112</td>\n",
              "      <td>3</td>\n",
              "      <td>64</td>\n",
              "      <td>3698</td>\n",
              "      <td>117190</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>자양동</th>\n",
              "      <td>7428</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>60</td>\n",
              "      <td>16</td>\n",
              "      <td>0</td>\n",
              "      <td>752</td>\n",
              "      <td>26</td>\n",
              "      <td>0</td>\n",
              "      <td>8823</td>\n",
              "      <td>...</td>\n",
              "      <td>1985</td>\n",
              "      <td>9</td>\n",
              "      <td>1</td>\n",
              "      <td>4</td>\n",
              "      <td>116</td>\n",
              "      <td>173</td>\n",
              "      <td>2</td>\n",
              "      <td>60</td>\n",
              "      <td>6900</td>\n",
              "      <td>92292</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>중곡동</th>\n",
              "      <td>9130</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>129</td>\n",
              "      <td>16</td>\n",
              "      <td>0</td>\n",
              "      <td>611</td>\n",
              "      <td>22</td>\n",
              "      <td>0</td>\n",
              "      <td>4456</td>\n",
              "      <td>...</td>\n",
              "      <td>597</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>104</td>\n",
              "      <td>54</td>\n",
              "      <td>0</td>\n",
              "      <td>26</td>\n",
              "      <td>2990</td>\n",
              "      <td>81379</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>화양동</th>\n",
              "      <td>9551</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>5</td>\n",
              "      <td>5</td>\n",
              "      <td>0</td>\n",
              "      <td>352</td>\n",
              "      <td>7</td>\n",
              "      <td>0</td>\n",
              "      <td>3901</td>\n",
              "      <td>...</td>\n",
              "      <td>880</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>5</td>\n",
              "      <td>2</td>\n",
              "      <td>22</td>\n",
              "      <td>0</td>\n",
              "      <td>9</td>\n",
              "      <td>2766</td>\n",
              "      <td>50312</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>광장동</th>\n",
              "      <td>958</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>30</td>\n",
              "      <td>13</td>\n",
              "      <td>0</td>\n",
              "      <td>548</td>\n",
              "      <td>14</td>\n",
              "      <td>0</td>\n",
              "      <td>4853</td>\n",
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              "      <td>1661</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>57</td>\n",
              "      <td>269</td>\n",
              "      <td>1</td>\n",
              "      <td>17</td>\n",
              "      <td>1656</td>\n",
              "      <td>44613</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>군자동</th>\n",
              "      <td>2021</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>8</td>\n",
              "      <td>6</td>\n",
              "      <td>0</td>\n",
              "      <td>282</td>\n",
              "      <td>9</td>\n",
              "      <td>0</td>\n",
              "      <td>1842</td>\n",
              "      <td>...</td>\n",
              "      <td>1014</td>\n",
              "      <td>37</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>13</td>\n",
              "      <td>38</td>\n",
              "      <td>0</td>\n",
              "      <td>18</td>\n",
              "      <td>1121</td>\n",
              "      <td>35167</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>능동</th>\n",
              "      <td>876</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>9</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>117</td>\n",
              "      <td>4</td>\n",
              "      <td>0</td>\n",
              "      <td>1868</td>\n",
              "      <td>...</td>\n",
              "      <td>129</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>86</td>\n",
              "      <td>15709</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>아차산로</th>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>25</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1054</td>\n",
              "      <td>...</td>\n",
              "      <td>1342</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>247</td>\n",
              "      <td>5757</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>능동로</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>8</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>972</td>\n",
              "      <td>...</td>\n",
              "      <td>482</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>107</td>\n",
              "      <td>4040</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>능  동</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>20</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>7</td>\n",
              "      <td>2642</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>10 rows × 55 columns</p>\n",
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              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
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              "  "
            ]
          },
          "metadata": {},
          "execution_count": 115
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_sub = df[['단속동', '위반내용']]\n",
        "grouped = df_sub.groupby(['단속동', '위반내용']).size().reset_index(name='counts')\n",
        "pivot_table = grouped.pivot_table(index='단속동', columns='위반내용', values='counts', fill_value=0)\n",
        "import seaborn as sns\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "sns.heatmap(pivot_table, cmap='Blues')\n",
        "plt.show()\n"
      ],
      "metadata": {
        "id": "Nnkzb_9vj17V",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 590
        },
        "outputId": "bc517471-84ef-4646-ac10-41013c0ccadf"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "Ja8lz8m4xD4w"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}