조한균_0_메달_데이터_분석(실습).ipynb

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  "metadata": {
    "colab": {
      "provenance": [],
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/JoHanGyun/python.if/blob/main/%EC%A1%B0%ED%95%9C%EA%B7%A0_0_%EB%A9%94%EB%8B%AC_%EB%8D%B0%EC%9D%B4%ED%84%B0_%EB%B6%84%EC%84%9D(%EC%8B%A4%EC%8A%B5).ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#🥇 **올림픽 메달 분석하기**"
      ],
      "metadata": {
        "id": "5QIcmX7sUK9s"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "###**※ <u>Colab에서 한글 사용을 위한 사전 작업</u> ※**\n",
        "- 코랩에서 한글을 사용하려면 런타임을 실행중인 가상머신(VM)에 한글폰트를 설치해야 한다.\n",
        "- 설치가 완료되면 최상위 디렉터리에서 usr/share/fonts 밑에 폰트가 추가된다.\n",
        "- 폰트의 설치가 완료된 후에는 <u>런타임을 재시작해야 설치된 폰트를 정상적으로 사용</u>할 수 있다. <br>\n",
        "<font color='tomato'>★ 재시작 방법 : [런타임] > [런타임 재시작]</font>"
      ],
      "metadata": {
        "id": "EW37lfb8I-yh"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# 한글 나눔글꼴을 설치하기 위한 셸 명령어 실행, 실행 후 런타임 재시작\n",
        "!sudo apt-get install -y fonts-nanum\n",
        "!sudo fc-cache -fv\n",
        "!rm ~/.cache/matplotlib -rf"
      ],
      "metadata": {
        "id": "-hZsDMiwakvI",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "5cf9d1e0-03d3-4be2-d4c8-3980c316bf90"
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Reading package lists... Done\n",
            "Building dependency tree... Done\n",
            "Reading state information... Done\n",
            "fonts-nanum is already the newest version (20200506-1).\n",
            "0 upgraded, 0 newly installed, 0 to remove and 16 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: 12 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": "markdown",
      "source": [
        "###**※ <u>반복 가능한 객체와 enumerate() 함수</u> ※**\n",
        "- enumerate()는 리스트(튜플, 문자열)의 인덱스와 요소를 포함하는 enumerate 객체를 반환한다.\n",
        "- enumerate 객체는 반복 가능한(iterable) 객체로, for문에서 사용할 수 있다. (Ex. 리스트, 튜플, 문자열, range, enumerate)\n",
        "- 리스트의 요소를 반복할 때 현재 인덱스가 몇번째인지 확인해야 하는 경우 사용한다."
      ],
      "metadata": {
        "id": "6AFkY-42Hg7o"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "fruits =['사과', '키위', '바나나']"
      ],
      "metadata": {
        "id": "7crBE9ifIpBL"
      },
      "execution_count": 1,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# enumerate() 함수 반환값 살펴보기\n",
        "print(enumerate(fruits))"
      ],
      "metadata": {
        "id": "IzZ4C-aTIrX_",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "c142873e-9c4f-4d4e-eab1-e664e5ba0803"
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<enumerate object at 0x7c3e60200d80>\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# enumerate() 함수 반환값의 타입 살펴보기\n",
        "print(type(enumerate(fruits)))"
      ],
      "metadata": {
        "id": "5pPq9oxUI-6g",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "6a2bb2bd-b3c0-438d-86ef-6e651394e7ce"
      },
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'enumerate'>\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# enumerate() 함수 반환값을 리스트로 변환하여 살펴보기\n",
        "print(list(enumerate(fruits)))"
      ],
      "metadata": {
        "id": "jbTcEY28Isw8",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "f716c8d3-572d-452a-ea72-583bd887ef72"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[(0, '사과'), (1, '키위'), (2, '바나나')]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# for문에서 enumerate() 함수 사용하기\n",
        "for i, val in enumerate(fruits):\n",
        "  print(f'{i}번째 요소는 {val}')"
      ],
      "metadata": {
        "id": "9ozXx0sVIxuF",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "f7362c2a-7fc8-45e7-ee35-9ddc50c99f08"
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0번째 요소는 사과\n",
            "1번째 요소는 키위\n",
            "2번째 요소는 바나나\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "위 코드를 enumerate()를 사용하지 않고 다른 방법으로 해결해보자."
      ],
      "metadata": {
        "id": "NqdUJzD94tB_"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# 인덱스와 과일이름 함께 출력하기\n",
        "for i in range(len(fruits)):\n",
        "  print(i,\"번째 요소는\",fruits[i])"
      ],
      "metadata": {
        "id": "0_XaqKGa4qRv",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "baae821a-b415-48d6-ac8c-a8c7c26b253c"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0 번째 요소는 사과\n",
            "1 번째 요소는 키위\n",
            "2 번째 요소는 바나나\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "for val in fruits:\n",
        "  print(f'{i}번째 요소는 {val}')\n",
        "  i+=1"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Me2ywL7sODXg",
        "outputId": "b7c8fbf1-90e7-42a2-960b-909275a75658"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "1번째 요소는 사과\n",
            "2번째 요소는 키위\n",
            "3번째 요소는 바나나\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "###**▶ 파이썬 리스트 복습하기**\n",
        "> 데이터 분석 실습에서 분석할 데이터는 주로 리스트로 취급하여 처리할 것이다. <br>\n",
        "앞으로의 실습을 위해 파이썬의 리스트와 반복문을 복습해보자."
      ],
      "metadata": {
        "id": "6BmSN_7WwEIP"
      }
    },
    {
      "cell_type": "markdown",
      "source": [],
      "metadata": {
        "id": "NLfPtOD-1JBm"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "1. 올림픽 메달 획득 현황을 나타내는 2차원 리스트 \"medals\"을 만들어보자.<br>\n",
        " - 리스트의 요소는 각각 국가명, 금메달, 은메달, 동메달의 개수를 의미한다. (예) 미국은 금 46개, 은 37개, 동 38개 획득\n",
        "  - 요소의 순서는 해당 국가의 올림픽 종합 순위에 따라 정렬되어 있다."
      ],
      "metadata": {
        "id": "VEhbzg5j8S7T"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "medals = [['미국', 46, 37, 38], ['영국', 27, 23, 17], ['중국', 26, 18, 26], ['러시아', 19, 18, 19], ['독일', 17, 10, 15], ['일본', 12, 8, 21], ['프랑스', 10, 18, 14], ['대한민국', 9, 3, 9]]"
      ],
      "metadata": {
        "id": "5vsr4DNRBGT7"
      },
      "execution_count": 14,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "2. 국가별로 획득한 전체 메달 수를 국가별 리스트의 마지막 요소로 추가해보자. (※ sum(리스트) : 리스트의 모든 요소의 총합)"
      ],
      "metadata": {
        "id": "cxZiEjmbjGJF"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "for row in medals:\n",
        "  row.append(sum(row[1:]))"
      ],
      "metadata": {
        "id": "LE7gAZN1DL7E"
      },
      "execution_count": 15,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "3. 종합 순위를 국가별 리스트의 첫번째 요소로 추가해보자.\n"
      ],
      "metadata": {
        "id": "DRk1oaCGjkPP"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "for i, row in enumerate(medals):\n",
        "  row.insert(0,i+1)"
      ],
      "metadata": {
        "id": "Zazahs0rDWYA"
      },
      "execution_count": 16,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "4. 다음 코드의 실행결과를 예상해보자.\n"
      ],
      "metadata": {
        "id": "XnreJIqc66i6"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "medals"
      ],
      "metadata": {
        "id": "UYfEWRbR8SVF",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "c5829025-0457-4c9d-a265-4f49a26ac17b"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[[1, '미국', 46, 37, 38, 121],\n",
              " [2, '영국', 27, 23, 17, 67],\n",
              " [3, '중국', 26, 18, 26, 70],\n",
              " [4, '러시아', 19, 18, 19, 56],\n",
              " [5, '독일', 17, 10, 15, 42],\n",
              " [6, '일본', 12, 8, 21, 41],\n",
              " [7, '프랑스', 10, 18, 14, 42],\n",
              " [8, '대한민국', 9, 3, 9, 21]]"
            ]
          },
          "metadata": {},
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "medals[0]"
      ],
      "metadata": {
        "id": "iZV_L0DZ8VMw",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "5df10a78-8a1d-49f1-b85c-2396961020b2"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['미국', 46, 37, 38, 121]"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "medals[0][1]"
      ],
      "metadata": {
        "id": "NZNJ8_PV8Wwa",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "3561b1b0-9af7-459b-fee4-979f27b5f0a4"
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "46"
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "5. 나라이름만 뽑아서 리스트 \"nation\"을 만들어보자."
      ],
      "metadata": {
        "id": "WK-I15xDukhV"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "nation = []\n",
        "for row in medals:\n",
        "  nation.append(row[1])\n",
        "print(f'국가: {nation}')"
      ],
      "metadata": {
        "id": "0BTfk-B7BdvD",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "0a602cd5-dabe-40ff-bbbc-e5469fa9303f"
      },
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "국가: ['미국', '영국', '중국', '러시아', '독일', '일본', '프랑스', '대한민국']\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "6. 나라별 금메달, 은메달, 동메달 개수를 뽑아서 리스트 \"gold\", \"silver\", \"bronze\"를 만들어보자."
      ],
      "metadata": {
        "id": "7xtSJFyDvGLm"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "gold, silver, bronze = [], [], []\n",
        "for row in medals:\n",
        "  gold.append(row[2])\n",
        "  silver.append(row[3])\n",
        "  bronze.append(row[4])\n",
        "print(f'금메달 개수: {gold}')\n",
        "print(f'은메달 개수: {silver}')\n",
        "print(f'동메달 개수: {bronze}')"
      ],
      "metadata": {
        "id": "gsfr6W6ju5yY",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "081baaea-0897-4221-c209-7c6bdc0568c5"
      },
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "금메달 개수: [46, 27, 26, 19, 17, 12, 10, 9]\n",
            "은메달 개수: [37, 23, 18, 18, 10, 8, 18, 3]\n",
            "동메달 개수: [38, 17, 26, 19, 15, 21, 14, 9]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "###**▶ 파이썬 데이터 시각화 맛보기**\n",
        "> [맷플롯립(Matplotlib)](https://matplotlib.org/)은 파이썬에서 가장 많이 사용되는 데이터 시각화 패키지이다. <br>\n",
        "맷플롯립을 이용해 앞에서 생성한 올림픽 메달 데이터를 그래프로 그려보자."
      ],
      "metadata": {
        "id": "5FZlnZjhwR5T"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "<u>＃준비작업 1. 맷플롯립(Matplotlib) 임포트 하기</u><br>\n",
        "외부 모듈에 정의된 함수, 클래스, 변수 등에 접근하려면 해당 모듈을 먼저 임포트 해야한다.<br>\n",
        "맷플롯립의 서브 패키지인 [파이플롯(pyplot)](https://matplotlib.org/stable/api/pyplot_summary.html)을 plt 라는 이름으로 임포트 해보자."
      ],
      "metadata": {
        "id": "Mc-PuJhkKwIy"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Matplotlib 임포트\n",
        "import matplotlib.pyplot as plt"
      ],
      "metadata": {
        "id": "tfaDnfcEx2xP"
      },
      "execution_count": 11,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "<u>＃준비작업 2. 한글 사용 설정하기</u><br>\n",
        "맷플롯립은 기본적으로는 한글을 지원하지 않기 때문에 시스템에 설치된 한글 폰트를 사용하도록 별도로 지정해주는 작업이 필요하다.\n",
        "- 시스템에 폰트 설치하기\n",
        "- 맷플롯립에서 사용할 커스텀 폰트 설정하기\n",
        "\n",
        "폰트 첫 번째 셀에서 이미 설치했기 때문에 여기서는 맷플롯립 설정부터 시작한다.\n"
      ],
      "metadata": {
        "id": "MVEr8a4oMhWr"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Matplotlib에서 사용할 폰트를 설치한 나눔글꼴로 설정\n",
        "plt.rc('font', family='NanumBarunGothic')"
      ],
      "metadata": {
        "id": "tJkvJz3VamUK"
      },
      "execution_count": 12,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "나라별 획득한 금메달의 개수를 꺾은선 그래프로 그려보자.\n",
        "- title() : 도표(axes)의 제목을 설정하는 함수\n",
        "- plot() : 데이터(x, y)를 도표(axes)에 선 또는 점으로 추가하는 함수\n",
        "- legend() : 도표(axes)에 범례를 추가하는 함수\n",
        "- show() : 그림(figure)을 화면에 보여주는 함수"
      ],
      "metadata": {
        "id": "pLUd7p0FiTUS"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# 도표(axes)의 제목 설정하기 (나라별 금메달 개수)\n",
        "plt.title(\"나라별 금메달 개수\")\n",
        "# 꺾은선 그래프 그리기\n",
        "plt.plot(nation,gold,color='gold',marker='o',label='금메달')\n",
        "# 범례 추가하기\n",
        "plt.legend()\n",
        "# 그래프 보여주기\n",
        "plt.show()"
      ],
      "metadata": {
        "id": "CUx_JjKuJlQG",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 451
        },
        "outputId": "70b2eba6-681c-4dc5-c6e8-916350effc05"
      },
      "execution_count": 26,
      "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": [
        "나라별 획득한 은메달의 개수를 꺾은선 그래프로 그려보자."
      ],
      "metadata": {
        "id": "JQSaaPAWy81K"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# 도표(axes)의 제목 설정하기 (나라별 은메달 개수)\n",
        "plt.title(\"나라별 은메달 개수\")\n",
        "# 꺾은선 그래프 그리기\n",
        "plt.plot(nation,silver,color='gray',label='은메달')\n",
        "# 범례 추가하기\n",
        "plt.legend()\n",
        "# 그래프 보여주기\n",
        "plt.show()"
      ],
      "metadata": {
        "id": "p4E-rBrHwmxB",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 451
        },
        "outputId": "7a8fd01b-3dc9-40dd-85de-36d7e1109504"
      },
      "execution_count": 31,
      "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": [
        "나라별 획득한 동메달의 개수를 꺾은선 그래프로 그려보자."
      ],
      "metadata": {
        "id": "oJWuAEllzBEo"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# 도표(axes)의 제목 설정하기 (나라별 동메달 개수)\n",
        "plt.title(\"나라별 동메달 개수\")\n",
        "# 꺾은선 그래프 그리기\n",
        "plt.plot(nation,bronze,color='orange',label='동메달')\n",
        "# 범례 추가하기\n",
        "plt.legend()\n",
        "# 그래프 보여주기\n",
        "plt.show()"
      ],
      "metadata": {
        "id": "tSGKlZXYKSzP",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 451
        },
        "outputId": "e0502fa3-00d5-4f80-cbc6-b2c88eaeadc1"
      },
      "execution_count": 33,
      "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": [
        "나라별 획득한 세 종류 메달의 개수를 나타낸 꺾은선 그래프를 한 도표에 그려보자."
      ],
      "metadata": {
        "id": "ysBjW0ESzBfe"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# 도표(axes)의 제목 설정하기 (나라별 메달 개수)\n",
        "plt.title(\"나라별 메달 개수\")\n",
        "# 꺾은선 그래프 그리기\n",
        "plt.plot(nation,gold,color='gold',label='금메달')\n",
        "plt.plot(nation,silver,color='gray',label='은메달')\n",
        "plt.plot(nation,bronze,color='orange',label='동메달')\n",
        "# 범례 추가하기\n",
        "plt.legend()\n",
        "# 그래프 보여주기\n",
        "plt.show()"
      ],
      "metadata": {
        "id": "Uvtb2EWTNeye",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 451
        },
        "outputId": "4f97dac5-bd2a-4c86-9b28-c02795bc3dd5"
      },
      "execution_count": 35,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    }
  ]
}