1.引入echarts.js文件（github下载地址：github.com/apache/echa…）
2.准备一个呈现图标的盒子
3.初始化echarts的实例对象
4.准备配置项（配置项官方文档:echarts.apache.org/zh/option.h…）
5.把配置项设置给echarts实例对象

<!DOCTYPE html>
<html lang="en">
<head>
  <meta charset="UTF-8">
  <meta http-equiv="X-UA-Compatible" content="IE=edge">
  <meta name="viewport" content="width=device-width, initial-scale=1.0">
  <title>Echarts快速入门</title>
  <!-- 1.引入echarts.js文件 -->
  <script src="./js/echarts.min.js"></script>
</head>
<body>
  <!-- 2.准备一个呈现图标的盒子 -->
    <div style="width: 300px; height: 300px;"></div>
    <script>
  // 3.初始化echarts的实例对象
        let mCharts = echarts.init(document.querySelector('div'));
  // 4.准备配置项
        let option = {
          xAxis: {
            type: 'category',
            data: ['小明','小红','小王']
          },
          yAxis: {
            type: 'value'
          },
          series: [
            {
              name: '语文',
              type: 'bar',
              data: [70,92,78]
            }
          ]
        }
  // 5.把配置项设置给echarts实例对象 -->
        mCharts.setOption(option);
    </script>
</body>
</html>

2.ECharts常用图表

1.柱状图
2.折线图
3.散点图
4.饼图
5.地图
6.雷达图
7.仪表盘图

使用场景

2.0 通用配置

标题：title
- 文字样式
  - textStyle
- 标题边框
  - borderWidth
  - borderColor
  - borderRadius
- 标题位置
  - left
  - right
  - top
  - bottom
提示：tooltip (提示框组件：用于配置鼠标滑过或点击图标时的显示框)
- 触发类型：trigger
  - 可选值（item和axis）
    - item : 当鼠标只有在柱状图里面点击或划过才会显示
    - axis: 鼠标在柱状图所在坐表轴上都可
- 触发时机： triggerOn
  - 可选值（mouseover和click）
- 格式化： formatter
  - 字符串模板回调函数
工具按钮：toolbox（ECharts提供的工具栏，内置有导出图片，数据视图，动态类型切换，数据区域缩放，重置五个工具）
图例：legend（用于筛选系列，需要和series配合使用）
- legend中的data是一个数组
- legend中的data的值需要和series数组中某组数据中的name值一样

2.1柱状图

常见效果：

标记：最大值，最小值，平均值（markPoint markLine）
显示：数值显示，柱宽度，横向柱状图（label barWidth）

<!DOCTYPE html>
<html lang="en">
<head>
  <meta charset="UTF-8">
  <meta http-equiv="X-UA-Compatible" content="IE=edge">
  <meta name="viewport" content="width=device-width, initial-scale=1.0">
  <title>柱状图</title>
  <script src="./js/echarts.min.js"></script>
</head>
<body>
  <div style="width: 500px; height: 500px;"></div>
  <script>
    let myCharts = echarts.init(document.querySelector('div'))
    let option = {
      xAxis: {
        type: 'category',
        data: ['张三','李四','王五','闰土']
      },
      yAxis: {
        type: 'value'
      },
      series: [
        {
          name: '语文',
          type: 'bar',
          markPoint: {
            data: [
              {
                type: 'max',
                name: '最大值'
              },
              {
                type: 'min',
                name: '最小值'
              }
            ]
          },
          markLine: {
            data: [
              {
                type: 'average',
                name: '平均值'
              }
            ]
          },
          label: {
            show: true
          },
          barWidth: '50%',
          data: [85,56,68,98]
        }
      ]
    }
    myCharts.setOption(option);
  </script>
</body>
</html>

2.2折线图

常见效果

标记：最大值，最小值，平均值，标注区间
- markPoint markLine markArea
线条控制：平滑，风格
- smooth lineStyle
填充风格
- areaStyle
紧挨边缘
- boundaryGap
缩放：脱离0值比例
- scale
堆叠图
- stack

<!DOCTYPE html>
<html lang="en">
<head>
  <meta charset="UTF-8">
  <meta http-equiv="X-UA-Compatible" content="IE=edge">
  <meta name="viewport" content="width=device-width, initial-scale=1.0">
  <title>折线图</title>
  <script src="./js/echarts.min.js"></script>
</head>
<body>
    <div style="width: 500px; height: 500px;"></div>
    <script>
      let myCharts = echarts.init(document.querySelector('div'))
      let option = {
        xAxis: {
          type: 'category',
          data: ['1月','2月','3月','4月','5月','6月','7月','8月','9月','10月','11月','12月'],
          boundaryGap: false
        },
        yAxis: {
          type: 'value',
          scale: true
        },
        series: [
          {
            name: '康师傅销量',
            type: 'line',
            data: [3000,2800,900,1000,800,700,1400,1300,900,1000,800,600],
            markPoint: {
             data: [
             {
                type: 'max'
              },
              {
                type: 'min'
              }
             ]
            },
            markLine: {
              data: [
              {
                type: 'average'
              }
              ]
            },
            markArea: {
              data: [
                [
                  {
                    xAxis: '1月'
                  },
                  {
                    xAxis: '2月'
                  }
                ],
                [
                  {
                    xAxis: '8月'
                  },
                  {
                    xAxis: '9月'
                  }
                ]
              ]
            },
            smooth: true,
            lineStyle: {
              type: 'dotted',//solid dashed
              color: 'blue'
            },
            areaStyle: {
              color: 'red'
            }
          }
        ]
      }
      myCharts.setOption(option)
    </script>
</body>
</html>

2.3散点图

散点图可以帮助我们推断出变量间的相关性，比如身高和体重的关系。

实现步骤

ECharts最基本的代码结构
x轴的数据和y轴的数据：二维数组
- array: [ [身高1，体重1] ，[身高2，体重2]，……..]
图表类型
- 在series下设置type：‘scatter’
- xAxis和yAxis中的type都要设置成value

常见效果

气泡图效果
- 散点的大小不同： symbolSize
- 散点的颜色不同: itemStyle.color
涟漪动画效果
- type: ‘effectScatter’
- showEffectOn: ’emphasis’
- rippleEffect: {scale: 数值}

<!DOCTYPE html>
<html lang="en">

<head>
  <meta charset="UTF-8">
  <meta name="viewport" content="width=device-width, initial-scale=1.0">
  <meta http-equiv="X-UA-Compatible" content="ie=edge">
  <title>Document</title>
  <script src="./js/echarts.min.js"></script>
</head>

<body>
  <div style="width: 600px;height:400px"></div>
  <script>
    //1. ECharts最基本的代码结构
    //2. x轴和y轴数据 二维数组 [ [身高,体重],...   ]
    //3. 将type的值设置为scatter, x轴和y轴的type都是value
    var data = [{ "gender": "female", "height": 161.2, "weight": 51.6 }, { "gender": "female", "height": 167.5, "weight": 59 }, { "gender": "female", "height": 159.5, "weight": 49.2 }, { "gender": "female", "height": 157, "weight": 63 }, { "gender": "female", "height": 155.8, "weight": 53.6 }, { "gender": "female", "height": 170, "weight": 59 }, { "gender": "female", "height": 159.1, "weight": 47.6 }, { "gender": "female", "height": 166, "weight": 69.8 }, { "gender": "female", "height": 176.2, "weight": 66.8 }, { "gender": "female", "height": 160.2, "weight": 75.2 }, { "gender": "female", "height": 172.5, "weight": 55.2 }, { "gender": "female", "height": 170.9, "weight": 54.2 }, { "gender": "female", "height": 172.9, "weight": 62.5 }, { "gender": "female", "height": 153.4, "weight": 42 }, { "gender": "female", "height": 160, "weight": 50 }, { "gender": "female", "height": 147.2, "weight": 49.8 }, { "gender": "female", "height": 168.2, "weight": 49.2 }, { "gender": "female", "height": 175, "weight": 73.2 }, { "gender": "female", "height": 157, "weight": 47.8 }, { "gender": "female", "height": 167.6, "weight": 68.8 }, { "gender": "female", "height": 159.5, "weight": 50.6 }, { "gender": "female", "height": 175, "weight": 82.5 }, { "gender": "female", "height": 166.8, "weight": 57.2 }, { "gender": "female", "height": 176.5, "weight": 87.8 }, { "gender": "female", "height": 170.2, "weight": 72.8 }, { "gender": "female", "height": 174, "weight": 54.5 }, { "gender": "female", "height": 173, "weight": 59.8 }, { "gender": "female", "height": 179.9, "weight": 67.3 }, { "gender": "female", "height": 170.5, "weight": 67.8 }, { "gender": "female", "height": 160, "weight": 47 }, { "gender": "female", "height": 154.4, "weight": 46.2 }, { "gender": "female", "height": 162, "weight": 55 }, { "gender": "female", "height": 176.5, "weight": 83 }, { "gender": "female", "height": 160, "weight": 54.4 }, { "gender": "female", "height": 152, "weight": 45.8 }, { "gender": "female", "height": 162.1, "weight": 53.6 }, { "gender": "female", "height": 170, "weight": 73.2 }, { "gender": "female", "height": 160.2, "weight": 52.1 }, { "gender": "female", "height": 161.3, "weight": 67.9 }, { "gender": "female", "height": 166.4, "weight": 56.6 }, { "gender": "female", "height": 168.9, "weight": 62.3 }, { "gender": "female", "height": 163.8, "weight": 58.5 }, { "gender": "female", "height": 167.6, "weight": 54.5 }, { "gender": "female", "height": 160, "weight": 50.2 }, { "gender": "female", "height": 161.3, "weight": 60.3 }, { "gender": "female", "height": 167.6, "weight": 58.3 }, { "gender": "female", "height": 165.1, "weight": 56.2 }, { "gender": "female", "height": 160, "weight": 50.2 }, { "gender": "female", "height": 170, "weight": 72.9 }, { "gender": "female", "height": 157.5, "weight": 59.8 }, { "gender": "female", "height": 167.6, "weight": 61 }, { "gender": "female", "height": 160.7, "weight": 69.1 }, { "gender": "female", "height": 163.2, "weight": 55.9 }, { "gender": "female", "height": 152.4, "weight": 46.5 }, { "gender": "female", "height": 157.5, "weight": 54.3 }, { "gender": "female", "height": 168.3, "weight": 54.8 }, { "gender": "female", "height": 180.3, "weight": 60.7 }, { "gender": "female", "height": 165.5, "weight": 60 }, { "gender": "female", "height": 165, "weight": 62 }, { "gender": "female", "height": 164.5, "weight": 60.3 }, { "gender": "female", "height": 156, "weight": 52.7 }, { "gender": "female", "height": 160, "weight": 74.3 }, { "gender": "female", "height": 163, "weight": 62 }, { "gender": "female", "height": 165.7, "weight": 73.1 }, { "gender": "female", "height": 161, "weight": 80 }, { "gender": "female", "height": 162, "weight": 54.7 }, { "gender": "female", "height": 166, "weight": 53.2 }, { "gender": "female", "height": 174, "weight": 75.7 }, { "gender": "female", "height": 172.7, "weight": 61.1 }, { "gender": "female", "height": 167.6, "weight": 55.7 }, { "gender": "female", "height": 151.1, "weight": 48.7 }, { "gender": "female", "height": 164.5, "weight": 52.3 }, { "gender": "female", "height": 163.5, "weight": 50 }, { "gender": "female", "height": 152, "weight": 59.3 }, { "gender": "female", "height": 169, "weight": 62.5 }, { "gender": "female", "height": 164, "weight": 55.7 }, { "gender": "female", "height": 161.2, "weight": 54.8 }, { "gender": "female", "height": 155, "weight": 45.9 }, { "gender": "female", "height": 170, "weight": 70.6 }, { "gender": "female", "height": 176.2, "weight": 67.2 }, { "gender": "female", "height": 170, "weight": 69.4 }, { "gender": "female", "height": 162.5, "weight": 58.2 }, { "gender": "female", "height": 170.3, "weight": 64.8 }, { "gender": "female", "height": 164.1, "weight": 71.6 }, { "gender": "female", "height": 169.5, "weight": 52.8 }, { "gender": "female", "height": 163.2, "weight": 59.8 }, { "gender": "female", "height": 154.5, "weight": 49 }, { "gender": "female", "height": 159.8, "weight": 50 }, { "gender": "female", "height": 173.2, "weight": 69.2 }, { "gender": "female", "height": 170, "weight": 55.9 }, { "gender": "female", "height": 161.4, "weight": 63.4 }, { "gender": "female", "height": 169, "weight": 58.2 }, { "gender": "female", "height": 166.2, "weight": 58.6 }, { "gender": "female", "height": 159.4, "weight": 45.7 }, { "gender": "female", "height": 162.5, "weight": 52.2 }, { "gender": "female", "height": 159, "weight": 48.6 }, { "gender": "female", "height": 162.8, "weight": 57.8 }, { "gender": "female", "height": 159, "weight": 55.6 }, { "gender": "female", "height": 179.8, "weight": 66.8 }, { "gender": "female", "height": 162.9, "weight": 59.4 }, { "gender": "female", "height": 161, "weight": 53.6 }, { "gender": "female", "height": 151.1, "weight": 73.2 }, { "gender": "female", "height": 168.2, "weight": 53.4 }, { "gender": "female", "height": 168.9, "weight": 69 }, { "gender": "female", "height": 173.2, "weight": 58.4 }, { "gender": "female", "height": 171.8, "weight": 56.2 }, { "gender": "female", "height": 178, "weight": 70.6 }, { "gender": "female", "height": 164.3, "weight": 59.8 }, { "gender": "female", "height": 163, "weight": 72 }, { "gender": "female", "height": 168.5, "weight": 65.2 }, { "gender": "female", "height": 166.8, "weight": 56.6 }, { "gender": "female", "height": 172.7, "weight": 105.2 }, { "gender": "female", "height": 163.5, "weight": 51.8 }, { "gender": "female", "height": 169.4, "weight": 63.4 }, { "gender": "female", "height": 167.8, "weight": 59 }, { "gender": "female", "height": 159.5, "weight": 47.6 }, { "gender": "female", "height": 167.6, "weight": 63 }, { "gender": "female", "height": 161.2, "weight": 55.2 }, { "gender": "female", "height": 160, "weight": 45 }, { "gender": "female", "height": 163.2, "weight": 54 }, { "gender": "female", "height": 162.2, "weight": 50.2 }, { "gender": "female", "height": 161.3, "weight": 60.2 }, { "gender": "female", "height": 149.5, "weight": 44.8 }, { "gender": "female", "height": 157.5, "weight": 58.8 }, { "gender": "female", "height": 163.2, "weight": 56.4 }, { "gender": "female", "height": 172.7, "weight": 62 }, { "gender": "female", "height": 155, "weight": 49.2 }, { "gender": "female", "height": 156.5, "weight": 67.2 }, { "gender": "female", "height": 164, "weight": 53.8 }, { "gender": "female", "height": 160.9, "weight": 54.4 }, { "gender": "female", "height": 162.8, "weight": 58 }, { "gender": "female", "height": 167, "weight": 59.8 }, { "gender": "female", "height": 160, "weight": 54.8 }, { "gender": "female", "height": 160, "weight": 43.2 }, { "gender": "female", "height": 168.9, "weight": 60.5 }, { "gender": "female", "height": 158.2, "weight": 46.4 }, { "gender": "female", "height": 156, "weight": 64.4 }, { "gender": "female", "height": 160, "weight": 48.8 }, { "gender": "female", "height": 167.1, "weight": 62.2 }, { "gender": "female", "height": 158, "weight": 55.5 }, { "gender": "female", "height": 167.6, "weight": 57.8 }, { "gender": "female", "height": 156, "weight": 54.6 }, { "gender": "female", "height": 162.1, "weight": 59.2 }, { "gender": "female", "height": 173.4, "weight": 52.7 }, { "gender": "female", "height": 159.8, "weight": 53.2 }, { "gender": "female", "height": 170.5, "weight": 64.5 }, { "gender": "female", "height": 159.2, "weight": 51.8 }, { "gender": "female", "height": 157.5, "weight": 56 }, { "gender": "female", "height": 161.3, "weight": 63.6 }, { "gender": "female", "height": 162.6, "weight": 63.2 }, { "gender": "female", "height": 160, "weight": 59.5 }, { "gender": "female", "height": 168.9, "weight": 56.8 }, { "gender": "female", "height": 165.1, "weight": 64.1 }, { "gender": "female", "height": 162.6, "weight": 50 }, { "gender": "female", "height": 165.1, "weight": 72.3 }, { "gender": "female", "height": 166.4, "weight": 55 }, { "gender": "female", "height": 160, "weight": 55.9 }, { "gender": "female", "height": 152.4, "weight": 60.4 }, { "gender": "female", "height": 170.2, "weight": 69.1 }, { "gender": "female", "height": 162.6, "weight": 84.5 }, { "gender": "female", "height": 170.2, "weight": 55.9 }, { "gender": "female", "height": 158.8, "weight": 55.5 }, { "gender": "female", "height": 172.7, "weight": 69.5 }, { "gender": "female", "height": 167.6, "weight": 76.4 }, { "gender": "female", "height": 162.6, "weight": 61.4 }, { "gender": "female", "height": 167.6, "weight": 65.9 }, { "gender": "female", "height": 156.2, "weight": 58.6 }, { "gender": "female", "height": 175.2, "weight": 66.8 }, { "gender": "female", "height": 172.1, "weight": 56.6 }, { "gender": "female", "height": 162.6, "weight": 58.6 }, { "gender": "female", "height": 160, "weight": 55.9 }, { "gender": "female", "height": 165.1, "weight": 59.1 }, { "gender": "female", "height": 182.9, "weight": 81.8 }, { "gender": "female", "height": 166.4, "weight": 70.7 }, { "gender": "female", "height": 165.1, "weight": 56.8 }, { "gender": "female", "height": 177.8, "weight": 60 }, { "gender": "female", "height": 165.1, "weight": 58.2 }, { "gender": "female", "height": 175.3, "weight": 72.7 }, { "gender": "female", "height": 154.9, "weight": 54.1 }, { "gender": "female", "height": 158.8, "weight": 49.1 }, { "gender": "female", "height": 172.7, "weight": 75.9 }, { "gender": "female", "height": 168.9, "weight": 55 }, { "gender": "female", "height": 161.3, "weight": 57.3 }, { "gender": "female", "height": 167.6, "weight": 55 }, { "gender": "female", "height": 165.1, "weight": 65.5 }, { "gender": "female", "height": 175.3, "weight": 65.5 }, { "gender": "female", "height": 157.5, "weight": 48.6 }, { "gender": "female", "height": 163.8, "weight": 58.6 }, { "gender": "female", "height": 167.6, "weight": 63.6 }, { "gender": "female", "height": 165.1, "weight": 55.2 }, { "gender": "female", "height": 165.1, "weight": 62.7 }, { "gender": "female", "height": 168.9, "weight": 56.6 }, { "gender": "female", "height": 162.6, "weight": 53.9 }, { "gender": "female", "height": 164.5, "weight": 63.2 }, { "gender": "female", "height": 176.5, "weight": 73.6 }, { "gender": "female", "height": 168.9, "weight": 62 }, { "gender": "female", "height": 175.3, "weight": 63.6 }, { "gender": "female", "height": 159.4, "weight": 53.2 }, { "gender": "female", "height": 160, "weight": 53.4 }, { "gender": "female", "height": 170.2, "weight": 55 }, { "gender": "female", "height": 162.6, "weight": 70.5 }, { "gender": "female", "height": 167.6, "weight": 54.5 }, { "gender": "female", "height": 162.6, "weight": 54.5 }, { "gender": "female", "height": 160.7, "weight": 55.9 }, { "gender": "female", "height": 160, "weight": 59 }, { "gender": "female", "height": 157.5, "weight": 63.6 }, { "gender": "female", "height": 162.6, "weight": 54.5 }, { "gender": "female", "height": 152.4, "weight": 47.3 }, { "gender": "female", "height": 170.2, "weight": 67.7 }, { "gender": "female", "height": 165.1, "weight": 80.9 }, { "gender": "female", "height": 172.7, "weight": 70.5 }, { "gender": "female", "height": 165.1, "weight": 60.9 }, { "gender": "female", "height": 170.2, "weight": 63.6 }, { "gender": "female", "height": 170.2, "weight": 54.5 }, { "gender": "female", "height": 170.2, "weight": 59.1 }, { "gender": "female", "height": 161.3, "weight": 70.5 }, { "gender": "female", "height": 167.6, "weight": 52.7 }, { "gender": "female", "height": 167.6, "weight": 62.7 }, { "gender": "female", "height": 165.1, "weight": 86.3 }, { "gender": "female", "height": 162.6, "weight": 66.4 }, { "gender": "female", "height": 152.4, "weight": 67.3 }, { "gender": "female", "height": 168.9, "weight": 63 }, { "gender": "female", "height": 170.2, "weight": 73.6 }, { "gender": "female", "height": 175.2, "weight": 62.3 }, { "gender": "female", "height": 175.2, "weight": 57.7 }, { "gender": "female", "height": 160, "weight": 55.4 }, { "gender": "female", "height": 165.1, "weight": 104.1 }, { "gender": "female", "height": 174, "weight": 55.5 }, { "gender": "female", "height": 170.2, "weight": 77.3 }, { "gender": "female", "height": 160, "weight": 80.5 }, { "gender": "female", "height": 167.6, "weight": 64.5 }, { "gender": "female", "height": 167.6, "weight": 72.3 }, { "gender": "female", "height": 167.6, "weight": 61.4 }, { "gender": "female", "height": 154.9, "weight": 58.2 }, { "gender": "female", "height": 162.6, "weight": 81.8 }, { "gender": "female", "height": 175.3, "weight": 63.6 }, { "gender": "female", "height": 171.4, "weight": 53.4 }, { "gender": "female", "height": 157.5, "weight": 54.5 }, { "gender": "female", "height": 165.1, "weight": 53.6 }, { "gender": "female", "height": 160, "weight": 60 }, { "gender": "female", "height": 174, "weight": 73.6 }, { "gender": "female", "height": 162.6, "weight": 61.4 }, { "gender": "female", "height": 174, "weight": 55.5 }, { "gender": "female", "height": 162.6, "weight": 63.6 }, { "gender": "female", "height": 161.3, "weight": 60.9 }, { "gender": "female", "height": 156.2, "weight": 60 }, { "gender": "female", "height": 149.9, "weight": 46.8 }, { "gender": "female", "height": 169.5, "weight": 57.3 }, { "gender": "female", "height": 160, "weight": 64.1 }, { "gender": "female", "height": 175.3, "weight": 63.6 }, { "gender": "female", "height": 169.5, "weight": 67.3 }, { "gender": "female", "height": 160, "weight": 75.5 }, { "gender": "female", "height": 172.7, "weight": 68.2 }, { "gender": "female", "height": 162.6, "weight": 61.4 }, { "gender": "female", "height": 157.5, "weight": 76.8 }, { "gender": "female", "height": 176.5, "weight": 71.8 }, { "gender": "female", "height": 164.4, "weight": 55.5 }, { "gender": "female", "height": 160.7, "weight": 48.6 }, { "gender": "female", "height": 174, "weight": 66.4 }, { "gender": "female", "height": 163.8, "weight": 67.3 }, { "gender": "male", "height": 174, "weight": 65.6 }, { "gender": "male", "height": 175.3, "weight": 71.8 }, { "gender": "male", "height": 193.5, "weight": 80.7 }, { "gender": "male", "height": 186.5, "weight": 72.6 }, { "gender": "male", "height": 187.2, "weight": 78.8 }, { "gender": "male", "height": 181.5, "weight": 74.8 }, { "gender": "male", "height": 184, "weight": 86.4 }, { "gender": "male", "height": 184.5, "weight": 78.4 }, { "gender": "male", "height": 175, "weight": 62 }, { "gender": "male", "height": 184, "weight": 81.6 }, { "gender": "male", "height": 180, "weight": 76.6 }, { "gender": "male", "height": 177.8, "weight": 83.6 }, { "gender": "male", "height": 192, "weight": 90 }, { "gender": "male", "height": 176, "weight": 74.6 }, { "gender": "male", "height": 174, "weight": 71 }, { "gender": "male", "height": 184, "weight": 79.6 }, { "gender": "male", "height": 192.7, "weight": 93.8 }, { "gender": "male", "height": 171.5, "weight": 70 }, { "gender": "male", "height": 173, "weight": 72.4 }, { "gender": "male", "height": 176, "weight": 85.9 }, { "gender": "male", "height": 176, "weight": 78.8 }, { "gender": "male", "height": 180.5, "weight": 77.8 }, { "gender": "male", "height": 172.7, "weight": 66.2 }, { "gender": "male", "height": 176, "weight": 86.4 }, { "gender": "male", "height": 173.5, "weight": 81.8 }, { "gender": "male", "height": 178, "weight": 89.6 }, { "gender": "male", "height": 180.3, "weight": 82.8 }, { "gender": "male", "height": 180.3, "weight": 76.4 }, { "gender": "male", "height": 164.5, "weight": 63.2 }, { "gender": "male", "height": 173, "weight": 60.9 }, { "gender": "male", "height": 183.5, "weight": 74.8 }, { "gender": "male", "height": 175.5, "weight": 70 }, { "gender": "male", "height": 188, "weight": 72.4 }, { "gender": "male", "height": 189.2, "weight": 84.1 }, { "gender": "male", "height": 172.8, "weight": 69.1 }, { "gender": "male", "height": 170, "weight": 59.5 }, { "gender": "male", "height": 182, "weight": 67.2 }, { "gender": "male", "height": 170, "weight": 61.3 }, { "gender": "male", "height": 177.8, "weight": 68.6 }, { "gender": "male", "height": 184.2, "weight": 80.1 }, { "gender": "male", "height": 186.7, "weight": 87.8 }, { "gender": "male", "height": 171.4, "weight": 84.7 }, { "gender": "male", "height": 172.7, "weight": 73.4 }, { "gender": "male", "height": 175.3, "weight": 72.1 }, { "gender": "male", "height": 180.3, "weight": 82.6 }, { "gender": "male", "height": 182.9, "weight": 88.7 }, { "gender": "male", "height": 188, "weight": 84.1 }, { "gender": "male", "height": 177.2, "weight": 94.1 }, { "gender": "male", "height": 172.1, "weight": 74.9 }, { "gender": "male", "height": 167, "weight": 59.1 }, { "gender": "male", "height": 169.5, "weight": 75.6 }, { "gender": "male", "height": 174, "weight": 86.2 }, { "gender": "male", "height": 172.7, "weight": 75.3 }, { "gender": "male", "height": 182.2, "weight": 87.1 }, { "gender": "male", "height": 164.1, "weight": 55.2 }, { "gender": "male", "height": 163, "weight": 57 }, { "gender": "male", "height": 171.5, "weight": 61.4 }, { "gender": "male", "height": 184.2, "weight": 76.8 }, { "gender": "male", "height": 174, "weight": 86.8 }, { "gender": "male", "height": 174, "weight": 72.2 }, { "gender": "male", "height": 177, "weight": 71.6 }, { "gender": "male", "height": 186, "weight": 84.8 }, { "gender": "male", "height": 167, "weight": 68.2 }, { "gender": "male", "height": 171.8, "weight": 66.1 }, { "gender": "male", "height": 182, "weight": 72 }, { "gender": "male", "height": 167, "weight": 64.6 }, { "gender": "male", "height": 177.8, "weight": 74.8 }, { "gender": "male", "height": 164.5, "weight": 70 }, { "gender": "male", "height": 192, "weight": 101.6 }, { "gender": "male", "height": 175.5, "weight": 63.2 }, { "gender": "male", "height": 171.2, "weight": 79.1 }, { "gender": "male", "height": 181.6, "weight": 78.9 }, { "gender": "male", "height": 167.4, "weight": 67.7 }, { "gender": "male", "height": 181.1, "weight": 66 }, { "gender": "male", "height": 177, "weight": 68.2 }, { "gender": "male", "height": 174.5, "weight": 63.9 }, { "gender": "male", "height": 177.5, "weight": 72 }, { "gender": "male", "height": 170.5, "weight": 56.8 }, { "gender": "male", "height": 182.4, "weight": 74.5 }, { "gender": "male", "height": 197.1, "weight": 90.9 }, { "gender": "male", "height": 180.1, "weight": 93 }, { "gender": "male", "height": 175.5, "weight": 80.9 }, { "gender": "male", "height": 180.6, "weight": 72.7 }, { "gender": "male", "height": 184.4, "weight": 68 }, { "gender": "male", "height": 175.5, "weight": 70.9 }, { "gender": "male", "height": 180.6, "weight": 72.5 }, { "gender": "male", "height": 177, "weight": 72.5 }, { "gender": "male", "height": 177.1, "weight": 83.4 }, { "gender": "male", "height": 181.6, "weight": 75.5 }, { "gender": "male", "height": 176.5, "weight": 73 }, { "gender": "male", "height": 175, "weight": 70.2 }, { "gender": "male", "height": 174, "weight": 73.4 }, { "gender": "male", "height": 165.1, "weight": 70.5 }, { "gender": "male", "height": 177, "weight": 68.9 }, { "gender": "male", "height": 192, "weight": 102.3 }, { "gender": "male", "height": 176.5, "weight": 68.4 }, { "gender": "male", "height": 169.4, "weight": 65.9 }, { "gender": "male", "height": 182.1, "weight": 75.7 }, { "gender": "male", "height": 179.8, "weight": 84.5 }, { "gender": "male", "height": 175.3, "weight": 87.7 }, { "gender": "male", "height": 184.9, "weight": 86.4 }, { "gender": "male", "height": 177.3, "weight": 73.2 }, { "gender": "male", "height": 167.4, "weight": 53.9 }, { "gender": "male", "height": 178.1, "weight": 72 }, { "gender": "male", "height": 168.9, "weight": 55.5 }, { "gender": "male", "height": 157.2, "weight": 58.4 }, { "gender": "male", "height": 180.3, "weight": 83.2 }, { "gender": "male", "height": 170.2, "weight": 72.7 }, { "gender": "male", "height": 177.8, "weight": 64.1 }, { "gender": "male", "height": 172.7, "weight": 72.3 }, { "gender": "male", "height": 165.1, "weight": 65 }, { "gender": "male", "height": 186.7, "weight": 86.4 }, { "gender": "male", "height": 165.1, "weight": 65 }, { "gender": "male", "height": 174, "weight": 88.6 }, { "gender": "male", "height": 175.3, "weight": 84.1 }, { "gender": "male", "height": 185.4, "weight": 66.8 }, { "gender": "male", "height": 177.8, "weight": 75.5 }, { "gender": "male", "height": 180.3, "weight": 93.2 }, { "gender": "male", "height": 180.3, "weight": 82.7 }, { "gender": "male", "height": 177.8, "weight": 58 }, { "gender": "male", "height": 177.8, "weight": 79.5 }, { "gender": "male", "height": 177.8, "weight": 78.6 }, { "gender": "male", "height": 177.8, "weight": 71.8 }, { "gender": "male", "height": 177.8, "weight": 116.4 }, { "gender": "male", "height": 163.8, "weight": 72.2 }, { "gender": "male", "height": 188, "weight": 83.6 }, { "gender": "male", "height": 198.1, "weight": 85.5 }, { "gender": "male", "height": 175.3, "weight": 90.9 }, { "gender": "male", "height": 166.4, "weight": 85.9 }, { "gender": "male", "height": 190.5, "weight": 89.1 }, { "gender": "male", "height": 166.4, "weight": 75 }, { "gender": "male", "height": 177.8, "weight": 77.7 }, { "gender": "male", "height": 179.7, "weight": 86.4 }, { "gender": "male", "height": 172.7, "weight": 90.9 }, { "gender": "male", "height": 190.5, "weight": 73.6 }, { "gender": "male", "height": 185.4, "weight": 76.4 }, { "gender": "male", "height": 168.9, "weight": 69.1 }, { "gender": "male", "height": 167.6, "weight": 84.5 }, { "gender": "male", "height": 175.3, "weight": 64.5 }, { "gender": "male", "height": 170.2, "weight": 69.1 }, { "gender": "male", "height": 190.5, "weight": 108.6 }, { "gender": "male", "height": 177.8, "weight": 86.4 }, { "gender": "male", "height": 190.5, "weight": 80.9 }, { "gender": "male", "height": 177.8, "weight": 87.7 }, { "gender": "male", "height": 184.2, "weight": 94.5 }, { "gender": "male", "height": 176.5, "weight": 80.2 }, { "gender": "male", "height": 177.8, "weight": 72 }, { "gender": "male", "height": 180.3, "weight": 71.4 }, { "gender": "male", "height": 171.4, "weight": 72.7 }, { "gender": "male", "height": 172.7, "weight": 84.1 }, { "gender": "male", "height": 172.7, "weight": 76.8 }, { "gender": "male", "height": 177.8, "weight": 63.6 }, { "gender": "male", "height": 177.8, "weight": 80.9 }, { "gender": "male", "height": 182.9, "weight": 80.9 }, { "gender": "male", "height": 170.2, "weight": 85.5 }, { "gender": "male", "height": 167.6, "weight": 68.6 }, { "gender": "male", "height": 175.3, "weight": 67.7 }, { "gender": "male", "height": 165.1, "weight": 66.4 }, { "gender": "male", "height": 185.4, "weight": 102.3 }, { "gender": "male", "height": 181.6, "weight": 70.5 }, { "gender": "male", "height": 172.7, "weight": 95.9 }, { "gender": "male", "height": 190.5, "weight": 84.1 }, { "gender": "male", "height": 179.1, "weight": 87.3 }, { "gender": "male", "height": 175.3, "weight": 71.8 }, { "gender": "male", "height": 170.2, "weight": 65.9 }, { "gender": "male", "height": 193, "weight": 95.9 }, { "gender": "male", "height": 171.4, "weight": 91.4 }, { "gender": "male", "height": 177.8, "weight": 81.8 }, { "gender": "male", "height": 177.8, "weight": 96.8 }, { "gender": "male", "height": 167.6, "weight": 69.1 }, { "gender": "male", "height": 167.6, "weight": 82.7 }, { "gender": "male", "height": 180.3, "weight": 75.5 }, { "gender": "male", "height": 182.9, "weight": 79.5 }, { "gender": "male", "height": 176.5, "weight": 73.6 }, { "gender": "male", "height": 186.7, "weight": 91.8 }, { "gender": "male", "height": 188, "weight": 84.1 }, { "gender": "male", "height": 188, "weight": 85.9 }, { "gender": "male", "height": 177.8, "weight": 81.8 }, { "gender": "male", "height": 174, "weight": 82.5 }, { "gender": "male", "height": 177.8, "weight": 80.5 }, { "gender": "male", "height": 171.4, "weight": 70 }, { "gender": "male", "height": 185.4, "weight": 81.8 }, { "gender": "male", "height": 185.4, "weight": 84.1 }, { "gender": "male", "height": 188, "weight": 90.5 }, { "gender": "male", "height": 188, "weight": 91.4 }, { "gender": "male", "height": 182.9, "weight": 89.1 }, { "gender": "male", "height": 176.5, "weight": 85 }, { "gender": "male", "height": 175.3, "weight": 69.1 }, { "gender": "male", "height": 175.3, "weight": 73.6 }, { "gender": "male", "height": 188, "weight": 80.5 }, { "gender": "male", "height": 188, "weight": 82.7 }, { "gender": "male", "height": 175.3, "weight": 86.4 }, { "gender": "male", "height": 170.5, "weight": 67.7 }, { "gender": "male", "height": 179.1, "weight": 92.7 }, { "gender": "male", "height": 177.8, "weight": 93.6 }, { "gender": "male", "height": 175.3, "weight": 70.9 }, { "gender": "male", "height": 182.9, "weight": 75 }, { "gender": "male", "height": 170.8, "weight": 93.2 }, { "gender": "male", "height": 188, "weight": 93.2 }, { "gender": "male", "height": 180.3, "weight": 77.7 }, { "gender": "male", "height": 177.8, "weight": 61.4 }, { "gender": "male", "height": 185.4, "weight": 94.1 }, { "gender": "male", "height": 168.9, "weight": 75 }, { "gender": "male", "height": 185.4, "weight": 83.6 }, { "gender": "male", "height": 180.3, "weight": 85.5 }, { "gender": "male", "height": 174, "weight": 73.9 }, { "gender": "male", "height": 167.6, "weight": 66.8 }, { "gender": "male", "height": 182.9, "weight": 87.3 }, { "gender": "male", "height": 160, "weight": 72.3 }, { "gender": "male", "height": 180.3, "weight": 88.6 }, { "gender": "male", "height": 167.6, "weight": 75.5 }, { "gender": "male", "height": 186.7, "weight": 101.4 }, { "gender": "male", "height": 175.3, "weight": 91.1 }, { "gender": "male", "height": 175.3, "weight": 67.3 }, { "gender": "male", "height": 175.9, "weight": 77.7 }, { "gender": "male", "height": 175.3, "weight": 81.8 }, { "gender": "male", "height": 179.1, "weight": 75.5 }, { "gender": "male", "height": 181.6, "weight": 84.5 }, { "gender": "male", "height": 177.8, "weight": 76.6 }, { "gender": "male", "height": 182.9, "weight": 85 }, { "gender": "male", "height": 177.8, "weight": 102.5 }, { "gender": "male", "height": 184.2, "weight": 77.3 }, { "gender": "male", "height": 179.1, "weight": 71.8 }, { "gender": "male", "height": 176.5, "weight": 87.9 }, { "gender": "male", "height": 188, "weight": 94.3 }, { "gender": "male", "height": 174, "weight": 70.9 }, { "gender": "male", "height": 167.6, "weight": 64.5 }, { "gender": "male", "height": 170.2, "weight": 77.3 }, { "gender": "male", "height": 167.6, "weight": 72.3 }, { "gender": "male", "height": 188, "weight": 87.3 }, { "gender": "male", "height": 174, "weight": 80 }, { "gender": "male", "height": 176.5, "weight": 82.3 }, { "gender": "male", "height": 180.3, "weight": 73.6 }, { "gender": "male", "height": 167.6, "weight": 74.1 }, { "gender": "male", "height": 188, "weight": 85.9 }, { "gender": "male", "height": 180.3, "weight": 73.2 }, { "gender": "male", "height": 167.6, "weight": 76.3 }, { "gender": "male", "height": 183, "weight": 65.9 }, { "gender": "male", "height": 183, "weight": 90.9 }, { "gender": "male", "height": 179.1, "weight": 89.1 }, { "gender": "male", "height": 170.2, "weight": 62.3 }, { "gender": "male", "height": 177.8, "weight": 82.7 }, { "gender": "male", "height": 179.1, "weight": 79.1 }, { "gender": "male", "height": 190.5, "weight": 98.2 }, { "gender": "male", "height": 177.8, "weight": 84.1 }, { "gender": "male", "height": 180.3, "weight": 83.2 }, { "gender": "male", "height": 180.3, "weight": 83.2 }]
    var axisData = []
    for (var i = 0; i < data.length; i++) {
      var height = data[i].height
      var weight = data[i].weight
      var newArr = [height, weight]
      axisData.push(newArr)
    }
    console.log(axisData)
    var mCharts = echarts.init(document.querySelector("div"))
    var option = {
      xAxis: {
        type: 'value',
        scale: true
      },
      yAxis: {
        type: 'value',
        scale: true
      },
      series: [
        {
          // type: 'scatter',
          type: 'effectScatter', // 指明图表为带涟漪动画的散点图
          showEffectOn: 'emphasis', // 出现涟漪动画的时机 render emphasis
          rippleEffect: {
            scale: 10 // 涟漪动画时, 散点的缩放比例
          },
          data: axisData,
          // symbolSize: 30
          symbolSize: function (arg) { // 控制散点的大小
            // console.log(arg)
            var height = arg[0] / 100
            var weight = arg[1]
            // bmi = 体重kg / (身高m*身高m)   大于28,就代表肥胖
            var bmi = weight / (height * height)
            if (bmi > 28) {
              return 20
            }
            return 5
          },
          itemStyle: { // 控制散点的样式
            color: function (arg) {
              // console.log(arg)
              var height = arg.data[0] / 100
              var weight = arg.data[1]
              // bmi = 体重kg / (身高m*身高m)   大于28,就代表肥胖
              var bmi = weight / (height * height)
              if (bmi > 28) {
                return 'red'
              }
              return 'green'
            }
          }
        }
      ]
    }
    mCharts.setOption(option)
  </script>
</body>

</html>

直角坐标系

直角系坐标图标：柱状图，折线图，散点图

直角坐标系中的常用配置

配置1：网格 grid
- grid是用来控制直角坐标系的布局和大小，x轴和y轴就是在grid的基础上进行绘制的
  - 显示grid ： show
  - grid的边框： boderWidth，borderColor
  - grid的大小和位置： left ，right , top ,bottom,width,height
配置2：坐标轴 axis
- 坐标轴分为x轴和y轴
- 一个grid中最多有两种位置的x轴和y轴
  - 坐标轴类型type：
    - value: 数值轴，自动会从series中读取目标数据
    - category：类目轴，该类型必须通过配合data设置类目数据使用
  - 显示位置position：
    - xAxis: 可取值为top或bottom
    - yAxis：可以取值为left或right
配置3：区域缩放 dataZoom
- dataZoom用于区域缩放，对数据范围进行过滤，x轴和y轴都可以拥有。
- dataZoom是一个数组，意味着可以配置多个区域缩放器。
  - 类型： type
    - slider：滑块
    - inside：内置，依靠鼠标滚轮或者双击缩放
  - 指明产生作用的轴：
    - xAxisIndex：设置缩放组件设置的是哪一个x轴，一般写0即可
    - yAxisIndex: 设置缩放组件设置的是哪一个y轴，一般写0即可
  - 指明初始状态的缩放情况：
    - start: 数据窗口的起始百分比
    - end: 数据窗口的结束百分比

1.网格grid
<!DOCTYPE html>
<html lang="en">

<head>
  <meta charset="UTF-8">
  <meta name="viewport" content="width=device-width, initial-scale=1.0">
  <meta http-equiv="X-UA-Compatible" content="ie=edge">
  <title>Document</title>
  <script src="lib/echarts.min.js"></script>
</head>

<body>
  <div style="width: 600px;height:400px"></div>
  <script>
    var mCharts = echarts.init(document.querySelector("div"))
    var xDataArr = ['张三', '李四', '王五', '闰土', '小明', '茅台', '二妞', '大强']
    var yDataArr = [88, 92, 63, 77, 94, 80, 72, 86]
    var option = {
      grid: { // 坐标轴容器
        show: true, // 是否可见
        borderWidth: 10, // 边框的宽度
        borderColor: 'red', // 边框的颜色
        left: 120, // 边框的位置
        top: 120,
        width: 300, // 边框的大小
        height: 150
      },
      xAxis: {
        type: 'category',
        data: xDataArr
      },
      yAxis: {
        type: 'value'
      },
      series: [
        {
          name: '语文',
          type: 'bar',
          markPoint: {
            data: [
              {
                type: 'max', name: '最大值'
              },{
                type: 'min', name: '最小值'
              }
            ]
          },
          markLine: {
            data: [
              {
                type: 'average', name: '平均值'
              }
            ]
          },
          label: {
            show: true,
            rotate: 60,
            position: 'top'
          },
          barWidth: '30%',
          data: yDataArr
        }
      ]
    }
    mCharts.setOption(option)
  </script>
</body>
</html>

2.坐标轴axis
<!DOCTYPE html>
<html lang="en">

<head>
  <meta charset="UTF-8">
  <meta name="viewport" content="width=device-width, initial-scale=1.0">
  <meta http-equiv="X-UA-Compatible" content="ie=edge">
  <title>Document</title>
  <script src="./js/echarts.min.js"></script>
</head>

<body>
  <div style="width: 600px;height:400px"></div>
  <script>
    var mCharts = echarts.init(document.querySelector("div"))
    var xDataArr = ['张三', '李四', '王五', '闰土', '小明', '茅台', '二妞', '大强']
    var yDataArr = [88, 92, 63, 77, 94, 80, 72, 86]
    var option = {
      grid: {
        show: true,
        borderColor: 'red',
      },
      xAxis: {
        type: 'category',
        data: xDataArr,
        position: 'top' // 控制坐标轴的位置
      },
      yAxis: {
        type: 'value',
        position: 'right' // 控制坐标轴的位置
      },
      series: [
        {
          name: '语文',
          type: 'bar',
          markPoint: {
            data: [
              {
                type: 'max', name: '最大值'
              },{
                type: 'min', name: '最小值'
              }
            ]
          },
          markLine: {
            data: [
              {
                type: 'average', name: '平均值'
              }
            ]
          },
          label: {
            show: true,
            rotate: 60,
            position: 'top'
          },
          barWidth: '30%',
          data: yDataArr
        }
      ]
    }
    mCharts.setOption(option)
  </script>
</body>
</html>

3. 区域缩放  dataZoom
<!DOCTYPE html>
<html lang="en">

<head>
  <meta charset="UTF-8">
  <meta name="viewport" content="width=device-width, initial-scale=1.0">
  <meta http-equiv="X-UA-Compatible" content="ie=edge">
  <title>Document</title>
  <script src="lib/echarts.min.js"></script>
</head>

<body>
  <div style="width: 600px;height:400px"></div>
  <script>
    var mCharts = echarts.init(document.querySelector("div"))
    var xDataArr = ['张三', '李四', '王五', '闰土', '小明', '茅台', '二妞', '大强']
    var yDataArr = [88, 92, 63, 77, 94, 80, 72, 86]
    var option = {
      dataZoom: [ // 控制区域缩放效果的实现
        {
          type: 'slider', // 缩放的类型  slide代表滑块  inside代表依靠鼠标滚轮
          // type: 'inside'
          xAxisIndex: 0
        },
        {
          type: 'slider',
          yAxisIndex: 0,
          start: 0, // 渲染完成后, 数据筛选的初始值, 百分比
          end: 80 // 渲染完成后, 数据筛选的结束值, 百分比
        }
      ],
      toolbox: {
        feature: {
          dataZoom: {}
        }
      },
      grid: {
        show: true,
        borderColor: 'red',
      },
      xAxis: {
        type: 'category',
        data: xDataArr
      },
      yAxis: {
        type: 'value'
      },
      series: [
        {
          name: '语文',
          type: 'bar',
          markPoint: {
            data: [
              {
                type: 'max', name: '最大值'
              },{
                type: 'min', name: '最小值'
              }
            ]
          },
          markLine: {
            data: [
              {
                type: 'average', name: '平均值'
              }
            ]
          },
          label: {
            show: true,
            rotate: 60,
            position: 'top'
          },
          barWidth: '30%',
          data: yDataArr
        }
      ]
    }
    mCharts.setOption(option)
  </script>
</body>
</html>

2.4饼图

实现步骤

ECharts最基本的代码结构
数据准备
图表类型：
- 在series下设置type: ‘pie’

常见效果

显示数值：
- label.formatter
饼图大小：
- radius： 20 (饼图半径)
- radius: ‘20% ‘（百分比参照的是盒子的长度和宽度中较小的那一部分的一半进行百分比设置）
- (圆环)radius: [‘50%’，‘75%’] （第0个元素代表的是内圆的半径，第一个元素代表的是外院的半径）
南丁格尔图：
- roseType： ‘radius’
选中效果：
- 选中模式： selectedMode： ‘single’/‘multiple’
- 选中偏移量： selectedOffset: 30

<!DOCTYPE html>
<html lang="en">

<head>
  <meta charset="UTF-8">
  <meta name="viewport" content="width=device-width, initial-scale=1.0">
  <meta http-equiv="X-UA-Compatible" content="ie=edge">
  <title>Document</title>
  <script src="./js/echarts.min.js"></script>
</head>

<body>
  <div style="width: 600px;height:400px"></div>
  <script>
    //1. ECharts最基本的代码结构
    //2. 准备数据[{name:???, value:??? },{}]
    //   淘宝: 11231  京东: 22673  唯品会: 6123  1号店: 8989   聚美优品: 6700
    //3. 将type的值设置为pie
    var mCharts = echarts.init(document.querySelector("div"))
    // pieData就是需要设置给饼图的数据, 数组,数组中包含一个又一个的对象, 每一个对象中, 需要有name和value
    var pieData = [
      {
        name: '淘宝',
        value: 11231
      },
      {
        name: '京东',
        value: 22673
      },
      {
        name: '唯品会',
        value: 6123
      },
      {
        name: '1号店',
        value: 8989
      },
      {
        name: '聚美优品',
        value: 6700
      }
    ]
    var option = {
      series: [
        {
          type: 'pie',
          data: pieData,
          label: { // 饼图文字的显示
            show: true, // 显示文字
            //formatter: 'hehe' // 决定文字显示的内容
            formatter: function(arg){
              // console.log(arg)
              return arg.name + '平台' + arg.value + '元\n' + arg.percent + '%'
            }
          },
          // radius: 20 // 饼图的半径
          // radius: '20%' // 百分比参照的是宽度和高度中较小的那一部分的一半来进行百分比设置
          // radius: ['50%', '75%'] // 第0个元素代表的是內圆的半径 第1个元素外圆的半径
          roseType: 'radius', // 南丁格尔图 饼图的每一个区域的半径是不同的
          // selectedMode: 'single' // 选中的效果,能够将选中的区域偏离圆点一小段距离
          selectedMode: 'multiple',
          selectedOffset: 30
        }
      ]
    }
    mCharts.setOption(option)
  </script>
</body>
</html>

2.5地图

地图图标的使用方式

百度API
- 需要申请百度地图ak
矢量地图
- 需要准备矢量地图数据

矢量地图的实现步骤

ECharts最基本的代码结构
准备中国的矢量地图的json文件，放到json/map/目录下china.json
使用Ajax获取china.json
- $.get(‘/json/map/china.json’, function (chinajson){});
在回调函数中往echarts全局对象中的注册地图的json数据
- echarts.registerMap(‘chinaMap’, chinajson)
在geo下设置
- type: ‘map’
- map: ‘chinaMap’

地图的常见配置

缩放拖动
- roam：boolean
名称显示
- label： {}
初始缩放比例
- zoom： Number
地图中心点
- center : []

<!DOCTYPE html>
<html lang="en">

<head>
  <meta charset="UTF-8">
  <meta name="viewport" content="width=device-width, initial-scale=1.0">
  <meta http-equiv="X-UA-Compatible" content="ie=edge">
  <title>Document</title>
  <script src="./js/echarts.min.js"></script>
  <script src="./js/jquery.js"></script>
</head>

<body>
  <div style="width: 600px;height:400px;border: 1px solid #f00"></div>

  <script>
    //1. ECharts最基本的代码结构
    //2. 准备中国地图的矢量数据
    //3. 使用Ajax获取矢量地图数据
    //4. 在Ajax的回调函数中注册地图矢量数据 echarts.registerMap('chinaMap', 矢量地图数据)
    //5. 配置geo的type为'map', map为'chinaMap' 
    var mCharts = echarts.init(document.querySelector("div"))
    $.get('/json/map/china.json', function (ret) {
      // ret 就是中国的各个省份的矢量地图数据
      // console.log(ret)
      echarts.registerMap('chinaMap', ret)
      var option = {
        geo: {
          type: 'map',
          map: 'chinaMap', // chinaMap需要和registerMap中的第一个参数保持一致
          roam: true, // 设置允许缩放以及拖动的效果
          label: {
            show: true // 展示标签
          },
          zoom: 1, // 设置初始化的缩放比例
          center: [87.617733, 43.792818] // 设置地图中心点的坐标
        }
      }
      mCharts.setOption(option)
    })

  </script>
</body>
</html>
(可能会产生跨域问题 ：  下载live Server插件 然后右键利用其打开就行)

常见效果

显示某个区域
- 加载该区域的矢量地图数据
- 通过registerMap注册到echarts全局对象中
- 指明geo配置下的type和map属性
- 通过zoom缩放该区域
- 通过center定位中心点
不同城市颜色不同
- 1.显示基本的中国地图
- 2.城市的空气质量数据设置个series
- 将series和geo关联起来
- 结合visualMap配合使用
地图和散点图结合
- 给series下增加新对象
- 准备好散点数据，设置给新对象的data
- 配置新对象的type为 effectScatter
- 让散点图使用地图坐标系统
  - coordinateSystem：‘geo’
- 让涟漪效果更加明显
  - rippleEffect： { scale ： 10}

1.不同城市颜色不同
<!DOCTYPE html>
<html lang="en">

<head>
  <meta charset="UTF-8">
  <meta name="viewport" content="width=device-width, initial-scale=1.0">
  <meta http-equiv="X-UA-Compatible" content="ie=edge">
  <title>Document</title>
  <script src="./js/echarts.min.js"></script>
  <script src="./js/jquery.js"></script>
</head>

<body>
  <div style="width: 600px;height:400px;border: 1px solid #f00"></div>

  <script>
    //1. 显示基本的中国地图
    //2. 将空气质量的数据设置给series下的对象
    //3. 将series下的数据和geo关联起来
    //4. 配置visualMap
    var airData = [
        { name: '北京', value: 39.92 },
        { name: '天津', value: 39.13 },
        { name: '上海', value: 31.22 },
        { name: '重庆', value: 66 },
        { name: '河北', value: 147 },
        { name: '河南', value: 113 },
        { name: '云南', value: 25.04 },
        { name: '辽宁', value: 50 },
        { name: '黑龙江', value: 114 },
        { name: '湖南', value: 175 },
        { name: '安徽', value: 117 },
        { name: '山东', value: 92 },
        { name: '新疆', value: 84 },
        { name: '江苏', value: 67 },
        { name: '浙江', value: 84 },
        { name: '江西', value: 96 },
        { name: '湖北', value: 273 },
        { name: '广西', value: 59 },
        { name: '甘肃', value: 99 },
        { name: '山西', value: 39 },
        { name: '内蒙古', value: 58 },
        { name: '陕西', value: 61 },
        { name: '吉林', value: 51 },
        { name: '福建', value: 29 },
        { name: '贵州', value: 71 },
        { name: '广东', value: 38 },
        { name: '青海', value: 57 },
        { name: '西藏', value: 24 },
        { name: '四川', value: 58 },
        { name: '宁夏', value: 52 },
        { name: '海南', value: 54 },
        { name: '台湾', value: 88 },
        { name: '香港', value: 66 },
        { name: '澳门', value: 77 },
        { name: '南海诸岛', value: 55 }
    ]
    var mCharts = echarts.init(document.querySelector("div"))
    $.get('json/map/china.json', function (ret) {
      // ret 就是中国的各个省份的矢量地图数据
      console.log(ret)
      echarts.registerMap('chinaMap', ret)
      var option = {
        geo: {
          type: 'map',
          map: 'chinaMap', // chinaMap需要和registerMap中的第一个参数保持一致
          roam: true, // 设置允许缩放以及拖动的效果
          label: {
            show: true // 展示标签
          }
        },
        series: [
          {
            data: airData,
            geoIndex: 0, // 将空气质量的数据和第0个geo配置关联在一起
            type: 'map'
          }
        ],
        visualMap: {
          min: 0,
          max: 300,
          inRange: {
            color: ['white', 'red'] // 控制颜色渐变的范围
          },
          calculable: true // 出现滑块
        }
      }
      mCharts.setOption(option)
    })

  </script>
</body>
</html>

2.地图和散点图结合
<!DOCTYPE html>
<html lang="en">

<head>
  <meta charset="UTF-8">
  <meta name="viewport" content="width=device-width, initial-scale=1.0">
  <meta http-equiv="X-UA-Compatible" content="ie=edge">
  <title>Document</title>
  <script src="js/echarts.min.js"></script>
  <script src="js/jquery.js"></script>
</head>

<body>
  <div style="width: 600px;height:400px;border: 1px solid #f00"></div>

  <script>
    //1. 给series下增加一个新的对象
    //2. 准备数据散点数据  , 配置给series下的另外一个对象
    //3. 配置series下的新对象的type值为effectScatter
    //4. 指明散点图的坐标系统为geo
    //5. 调整涟漪动画效果
    var airData = [
      { name: '北京', value: 39.92 },
      { name: '天津', value: 39.13 },
      { name: '上海', value: 31.22 },
      { name: '重庆', value: 66 },
      { name: '河北', value: 147 },
      { name: '河南', value: 113 },
      { name: '云南', value: 25.04 },
      { name: '辽宁', value: 50 },
      { name: '黑龙江', value: 114 },
      { name: '湖南', value: 175 },
      { name: '安徽', value: 117 },
      { name: '山东', value: 92 },
      { name: '新疆', value: 84 },
      { name: '江苏', value: 67 },
      { name: '浙江', value: 84 },
      { name: '江西', value: 96 },
      { name: '湖北', value: 273 },
      { name: '广西', value: 59 },
      { name: '甘肃', value: 99 },
      { name: '山西', value: 39 },
      { name: '内蒙古', value: 58 },
      { name: '陕西', value: 61 },
      { name: '吉林', value: 51 },
      { name: '福建', value: 29 },
      { name: '贵州', value: 71 },
      { name: '广东', value: 38 },
      { name: '青海', value: 57 },
      { name: '西藏', value: 24 },
      { name: '四川', value: 58 },
      { name: '宁夏', value: 52 },
      { name: '海南', value: 54 },
      { name: '台湾', value: 88 },
      { name: '香港', value: 66 },
      { name: '澳门', value: 77 },
      { name: '南海诸岛', value: 55 }
    ]
    var scatterData = [
      {
        value: [117.283042, 31.86119]
      }
    ]
    var mCharts = echarts.init(document.querySelector("div"))
    $.get('json/map/china.json', function (ret) {
      // ret 就是中国的各个省份的矢量地图数据
      console.log(ret)
      echarts.registerMap('chinaMap', ret)
      var option = {
        geo: {
          type: 'map',
          map: 'chinaMap', // chinaMap需要和registerMap中的第一个参数保持一致
          roam: true, // 设置允许缩放以及拖动的效果
          label: {
            show: true // 展示标签
          }
        },
        series: [
          {
            data: airData,
            geoIndex: 0, // 将空气质量的数据和第0个geo配置关联在一起
            type: 'map'
          },
          {
            data: scatterData, // 配置散点的坐标数据
            type: 'effectScatter',
            coordinateSystem: 'geo', // 指明散点使用的坐标系统  geo的坐标系统
            rippleEffect: {
              scale: 10 // 设置涟漪动画的缩放比例
            }
          }
        ],
        visualMap: {
          min: 0,
          max: 300,
          inRange: {
            color: ['white', 'red'] // 控制颜色渐变的范围
          },
          calculable: true // 出现滑块
        }
      }
      mCharts.setOption(option)
    })

  </script>
</body>
</html>

2.6雷达图

实现步骤

ECharts最基本的代码结构
定义各个维度的最大值
- radar.indicator：[ {name : ‘易用性’, max: 100},……..]
准备具体产品的数据
- data: [ { name : ‘华为’, value : [80,90,88,92,85]},……]
图表类型:
- 在series下设置type：rader

常用配置

显示数值
- label
区域面积
- areaStyle
绘制类型
- shape

<!DOCTYPE html>
<html lang="en">

<head>
  <meta charset="UTF-8">
  <meta name="viewport" content="width=device-width, initial-scale=1.0">
  <meta http-equiv="X-UA-Compatible" content="ie=edge">
  <title>Document</title>
  <script src="js/echarts.min.js"></script>
</head>

<body>
  <div style="width: 600px;height:400px"></div>
  <script>
    //1. ECharts最基本的代码结构
    //2. 定义各个维度的最大值, 通过radar属性配置
    //   易用性,功能,拍照,跑分,续航, 每个维度的最大值都是100
    //3. 准备产品数据, 设置给series下的data
    //   华为手机1: 80, 90, 80, 82, 90
    //   中兴手机1: 70, 82, 75, 70, 78
    //4. 将type的值设置为radar
    var mCharts = echarts.init(document.querySelector("div"))
    // 各个维度的最大值
    var dataMax = [
      {
        name: '易用性',
        max: 100
      },
      {
        name: '功能',
        max: 100
      },
      {
        name: '拍照',
        max: 100
      },
      {
        name: '跑分',
        max: 100
      },
      {
        name: '续航',
        max: 100
      }
    ]
    var option = {
      radar: { 
        indicator: dataMax, // 配置各个维度的最大值
        shape: 'polygon' // 配置雷达图最外层的图形 circle polygon
      },
      series: [
        {
          type: 'radar', // radar 此图表时一个雷达图
          label: { // 设置标签的样式
            show: true // 显示数值
          },
          areaStyle: {}, // 将每一个产品的雷达图形成阴影的面积
          data: [
            {
              name: '华为手机1',
              value: [80, 90, 80, 82, 90]
            },
            {
              name: '中兴手机1',
              value: [70, 82, 75, 70, 78]
            }
          ]
        }
      ]
    }
    mCharts.setOption(option)
  </script>
</body>

</html>

2.7仪表盘图

实现步骤

ECharts最基本的代码结构
准备数据，设置个series下的data
- data：【{value: 97}】
图表类型
- type: gauge

常用配置/效果

数值范围
- max
- min
多个指针
- 增加data中的数组元素
多个指针的颜色差异
- itemStyle

<!DOCTYPE html>
<html lang="en">

<head>
  <meta charset="UTF-8">
  <meta name="viewport" content="width=device-width, initial-scale=1.0">
  <meta http-equiv="X-UA-Compatible" content="ie=edge">
  <title>Document</title>
  <script src="js/echarts.min.js"></script>
</head>

<body>
  <div style="width: 600px;height:400px"></div>

  <script>
    //1. ECharts最基本的代码结构
    //2. 准备数据, 设置给series下的data
    //3. 将type的值设置为gauge
    var mCharts = echarts.init(document.querySelector("div"))
    var option = {
      series: [
        {
          type: 'gauge',
          data: [
            {
              value: 97,
              itemStyle: { // 指针的样式
                color: 'pink' // 指针的颜色
              }
            }, // 每一个对象就代表一个指针
            {
              value: 85,
              itemStyle: {
                color: 'green'
              }
            }
          ],
          min: 50 // min max 控制仪表盘数值范围
        }
      ]
    }
    mCharts.setOption(option)
  </script>
</body>

</html>

ECharts的高级使用

1.显示相关

1.1主题

内置主题
- ECharts中默认内置了两套主题：light，dark
- 在初始化对象方法init()中可以指明
  - let myECharts = echarts.init(dom,’light’);
  - let myECharts = echarts.init(dom,’dark’);
自定义主题
- 1.在主题编辑器中编辑主题（echarts.apache.org/zh/theme-bu…）
- 2.下载主题，是一个js文件
- 3.引入主题js文件
- 4.在init方法中使用该主题

1.内置dark主题
<!DOCTYPE html>
<html lang="en">

<head>
  <meta charset="UTF-8">
  <meta name="viewport" content="width=device-width, initial-scale=1.0">
  <meta http-equiv="X-UA-Compatible" content="ie=edge">
  <title>Document</title>
  <script src="js/echarts.min.js"></script>
</head>

<body>
  <div style="width: 600px;height:400px"></div>
  <script>
    // init方法有两个参数, 第一个参数代表是一个dom节点, 第二个参数, 代表你需要使用哪一套主题
    // 默认内置了两套主题 , light  dark
    var mCharts = echarts.init(document.querySelector("div"), 'dark')
    var xDataArr = ['张三', '李四', '王五', '闰土', '小明', '茅台', '二妞', '大强']
    var yDataArr = [88, 92, 63, 77, 94, 80, 72, 86]
    var option = {
      xAxis: {
        type: 'category',
        data: xDataArr
      },
      yAxis: {
        type: 'value'
      },
      series: [
        {
          type: 'bar',
          data: yDataArr,
          markPoint: {
            data: [
              {
                type: 'max', name: '最大值'
              },
              {
                type: 'min', name: '最小值'
              }
            ]
          },
          markLine: {
            data: [
              {
                type: 'average', name: '平均值'
              }
            ]
          },
          label: {
            show: true,
            rotate: 60
          },
          barWidth: '30%'
        }
      ]
    };
    mCharts.setOption(option)
  </script>
</body>
</html>

2.内置light主题
<!DOCTYPE html>
<html lang="en">

<head>
  <meta charset="UTF-8">
  <meta name="viewport" content="width=device-width, initial-scale=1.0">
  <meta http-equiv="X-UA-Compatible" content="ie=edge">
  <title>Document</title>
  <script src="js/echarts.min.js"></script>
</head>

<body>
  <div style="width: 600px;height:400px"></div>
  <script>
    // init方法有两个参数, 第一个参数代表是一个dom节点, 第二个参数, 代表你需要使用哪一套主题
    // 默认内置了两套主题 , light  dark
    var mCharts = echarts.init(document.querySelector("div"), 'light')
    var xDataArr = ['张三', '李四', '王五', '闰土', '小明', '茅台', '二妞', '大强']
    var yDataArr = [88, 92, 63, 77, 94, 80, 72, 86]
    var option = {
      xAxis: {
        type: 'category',
        data: xDataArr
      },
      yAxis: {
        type: 'value'
      },
      series: [
        {
          type: 'bar',
          data: yDataArr,
          markPoint: {
            data: [
              {
                type: 'max', name: '最大值'
              },
              {
                type: 'min', name: '最小值'
              }
            ]
          },
          markLine: {
            data: [
              {
                type: 'average', name: '平均值'
              }
            ]
          },
          label: {
            show: true,
            rotate: 60
          },
          barWidth: '30%'
        }
      ]
    };
    mCharts.setOption(option)
  </script>
</body>
</html>

3.自定义主题
<!DOCTYPE html>
<html lang="en">

<head>
  <meta charset="UTF-8">
  <meta name="viewport" content="width=device-width, initial-scale=1.0">
  <meta http-equiv="X-UA-Compatible" content="ie=edge">
  <title>Document</title>
  <script src="js/echarts.min.js"></script>
  <script src="theme/roma.js"></script>
</head>

<body>
  <div style="width: 600px;height:400px"></div>
  <script>
    // init方法有两个参数, 第一个参数代表是一个dom节点, 第二个参数, 代表你需要使用哪一套主题
    // 默认内置了两套主题 , light  dark
    var mCharts = echarts.init(document.querySelector("div"), 'roma')
    var xDataArr = ['张三', '李四', '王五', '闰土', '小明', '茅台', '二妞', '大强']
    var yDataArr = [88, 92, 63, 77, 94, 80, 72, 86]
    var option = {
      xAxis: {
        type: 'category',
        data: xDataArr
      },
      yAxis: {
        type: 'value'
      },
      series: [
        {
          type: 'bar',
          data: yDataArr,
          markPoint: {
            data: [
              {
                type: 'max', name: '最大值'
              },
              {
                type: 'min', name: '最小值'
              }
            ]
          },
          markLine: {
            data: [
              {
                type: 'average', name: '平均值'
              }
            ]
          },
          label: {
            show: true,
            rotate: 60
          },
          barWidth: '30%'
        }
      ]
    };
    mCharts.setOption(option)
  </script>
</body>
</html>

1.2调色盘

调色盘是一组颜色，图形，系列会自动从其中选择颜色。调色盘的作用遵循就近原则

主题调色盘
全局调色盘
- option: {color: [‘red’,’blue’,’green’]}
局部调色盘
- series: [{color: [‘green’,’red’]}]

颜色渐变：

线性渐变
径向渐变

1.3样式

直接样式
- itemStyle textStyle areaStyle lineStyle label
高亮样式
- 在emphasis中包裹 itemStyle textStyle areaStyle lineStyle label

<!DOCTYPE html>
<html lang="en">

<head>
  <meta charset="UTF-8">
  <meta name="viewport" content="width=device-width, initial-scale=1.0">
  <meta http-equiv="X-UA-Compatible" content="ie=edge">
  <title>Document</title>
  <script src="js/echarts.min.js"></script>
</head>


<body>
  <div style="width: 600px;height:400px"></div>
  <script>
    var mCharts = echarts.init(document.querySelector("div"))
    var option = {
      title: {
        text: '饼图的测试',
        textStyle: { // 控制标题的文字样式
          color: 'blue'
        }
      },
      series: [
        {
          type: 'pie',

          data: [{
            value: 11231,
            name: "淘宝",
            itemStyle: { // 控制淘宝这一区域的样式
              color: 'yellow'
            },
            label: {
              color: 'green'
            },
            emphasis: {
              itemStyle: { // 控制淘宝这一区域的样式
                color: 'pink'
              },
              label: {
                color: 'black'
              }
            }
          },
          {
            value: 22673,
            name: "京东"
          },
          {
            value: 6123,
            name: "唯品会",
          },
          {
            value: 8989,
            name: "1号店"
          },
          {
            value: 6700,
            name: "聚美优品"
          }]
        }
      ]
    }
    mCharts.setOption(option)
  </script>
</body>

</html>

1.4自适应

当浏览器的大小发生变化的时候，图表也能随之适配

1.监听窗口大小变化事件
2.在事件处理函数中调用ECharts实例对象的resize（）方法即可

<!DOCTYPE html>
<html lang="en">

<head>
  <meta charset="UTF-8">
  <meta name="viewport" content="width=device-width, initial-scale=1.0">
  <meta http-equiv="X-UA-Compatible" content="ie=edge">
  <title>Document</title>
  <script src="lib/echarts.min.js"></script>
</head>

<body>
  <div style="height:400px;border: 1px solid red"></div>
  <script>
    var mCharts = echarts.init(document.querySelector("div"))
    var xDataArr = ['张三', '李四', '王五', '闰土', '小明', '茅台', '二妞', '大强']
    var yDataArr = [88, 92, 63, 77, 94, 80, 72, 86]
    var option = {
      xAxis: {
        type: 'category',
        data: xDataArr
      },
      yAxis: {
        type: 'value'
      },
      series: [
        {
          type: 'bar',
          data: yDataArr,
          markPoint: {
            data: [
              {
                type: 'max', name: '最大值'
              },
              {
                type: 'min', name: '最小值'
              }
            ]
          },
          markLine: {
            data: [
              {
                type: 'average', name: '平均值'
              }
            ]
          },
          label: {
            show: true,
            rotate: 60
          },
          barWidth: '30%'
        }
      ]
    }
    mCharts.setOption(option)
    // 监听window窗口大小变化的事件
    window.onresize = function(){
      // console.log('window.onresize...')
      // 调用echarts实例对象的resize方法
      mCharts.resize()
    }
    // window.onresize = mCharts.resize

  </script>
</body>

</html>

2.动画的使用

2.1加载动画

ECharts已经内置好了加载数据的动画，我们只需要在合适的时机显示或隐藏即可

显示加载动画
- mCharts.showLoading()
隐藏加载动画
- mCharts.hideLoading()

<!DOCTYPE html>
<html lang="en">

<head>
  <meta charset="UTF-8">
  <meta name="viewport" content="width=device-width, initial-scale=1.0">
  <meta http-equiv="X-UA-Compatible" content="ie=edge">
  <title>Document</title>
  <script src="js/echarts.min.js"></script>
  <script src="js/jquery.js"></script>
</head>

<body>
  <div style="width: 600px;height:400px"></div>
  <script>
    // var data = 
    var mCharts = echarts.init(document.querySelector("div"))
    mCharts.showLoading() // 在获取数据之前, 显示加载动画
    $.get('data/test_data.json', function (ret) {
      mCharts.hideLoading() // 当服务器数据获取成功之后, 隐藏加载动画
      var axisData = []
      for (var i = 0; i < ret.length; i++) {
        var height = ret[i].height
        var weight = ret[i].weight
        var itemArr = [height, weight]
        axisData.push(itemArr)
      }
      console.log(axisData)
      var option = {
        xAxis: {
          type: 'value',
          scale: true
        },
        yAxis: {
          type: 'value',
          scale: true
        },
        series: [
          {
            type: 'effectScatter',
            data: axisData,
            symbolSize: function (arg) {
              // console.log(arg)
              var weight = arg[1]
              var height = arg[0] / 100
              // BMI > 28 肥胖
              // BMI: 体重/ 身高*身高     kg  m
              var bmi = weight / (height * height)
              if (bmi > 28) {
                return 20
              }
              return 5
            },
            itemStyle: {
              color: function (arg) {
                console.log(arg)
                var weight = arg.data[1]
                var height = arg.data[0] / 100
                var bmi = weight / (height * height)
                if (bmi > 28) {
                  return 'red'
                }
                return 'green'
              }
            },
            showEffectOn: 'emphasis',
            rippleEffect: {
              scale: 10
            }
          }
        ]
      };
      mCharts.setOption(option)
    })
  </script>
</body>
</html>

2.2增量动画

增量动画实现的方式

mCharts.setOption()
- 所有数据的更新都通过setOption实现
- 不用考虑数据产生了哪些变化
- ECharts会找到两组数据之间的差异然后通过合适的动画去表示数据的变化

<!DOCTYPE html>
<html lang="en">

<head>
  <meta charset="UTF-8">
  <meta name="viewport" content="width=device-width, initial-scale=1.0">
  <meta http-equiv="X-UA-Compatible" content="ie=edge">
  <title>Document</title>
  <script src="js/echarts.min.js"></script>
</head>

<body>
  <div style="width: 600px;height:400px"></div>
  <button id="modify">修改数据</button>
  <button id="add">增加数据</button>
  <script>
    var mCharts = echarts.init(document.querySelector("div"))
    var xDataArr = ['张三', '李四', '王五', '闰土', '小明', '茅台', '二妞', '大强']
    var yDataArr = [88, 92, 63, 77, 94, 80, 72, 86]
    var option = {
      xAxis: {
        type: 'category',
        data: xDataArr
      },
      yAxis: {
        type: 'value'
      },
      series: [
        {
          type: 'bar',
          data: yDataArr,
          markPoint: {
            data: [
              {
                type: 'max', name: '最大值'
              },
              {
                type: 'min', name: '最小值'
              }
            ]
          },
          markLine: {
            data: [
              {
                type: 'average', name: '平均值'
              }
            ]
          },
          label: {
            show: true,
            rotate: 60
          },
          barWidth: '30%'
        }
      ]
    }
    mCharts.setOption(option)

    var btnModify = document.querySelector('#modify')
    btnModify.onclick = function () {
      var newYDataArr = [68, 32, 99, 77, 94, 80, 72, 86]
      // setOption 可以设置多次
      // 新的option 和 旧的option
      // 新旧option的关系并不是相互覆盖的关系, 是相互整合的关系
      // 我们在设置新的option的时候, 只需要考虑到变化的部分就可以
      var option = {
        series: [
          {
            data: newYDataArr
          }
        ]
      }
      mCharts.setOption(option)
    }
    var btnAdd = document.querySelector('#add')
    btnAdd.onclick = function(){
      xDataArr.push('小明')
      yDataArr.push(90)
      var option = {
        xAxis: {
          data: xDataArr
        },
        series: [
          {
            data: yDataArr
          }
        ]
      }
      mCharts.setOption(option)
    }
  </script>
</body>

</html>

2.3动画的配置

动画常用配置项

开启动画
- animation: true
动画时长
- animationDuration: 5000
缓冲动画
- animationEasing: ‘bounceOut’
动画阈值
- animationThreshold: 8
- 单种形式的元素数量大于这个阈值时会关闭动画

<!DOCTYPE html>
<html lang="en">

<head>
  <meta charset="UTF-8">
  <meta name="viewport" content="width=device-width, initial-scale=1.0">
  <meta http-equiv="X-UA-Compatible" content="ie=edge">
  <title>Document</title>
  <script src="js/echarts.min.js"></script>
</head>

<body>
  <div style="width: 600px;height:400px"></div>
  <script>
    var mCharts = echarts.init(document.querySelector("div"))
    var xDataArr = ['张三', '李四', '王五', '闰土', '小明', '茅台', '二妞', '大强']
    var yDataArr = [88, 92, 63, 77, 94, 80, 72, 86]
    var option = {
      animation: true,  // 控制动画是否开启
      // animationDuration: 7000, // 动画的时长, 它是以毫秒为单位
      animationDuration: function(arg){
        console.log(arg)
        return 2000 * arg
      },
      animationEasing: 'bounceOut', // 缓动动画
      animationThreshold: 7, // 动画元素的阈值
      xAxis: {
        type: 'category',
        data: xDataArr
      },
      yAxis: {
        type: 'value'
      },
      series: [
        {
          type: 'bar',
          data: yDataArr,
          markPoint: {
            data: [
              {
                type: 'max', name: '最大值'
              },
              {
                type: 'min', name: '最小值'
              }
            ]
          },
          markLine: {
            data: [
              {
                type: 'average', name: '平均值'
              }
            ]
          },
          label: {
            show: true,
            rotate: 60
          },
          barWidth: '30%'
        }
      ]
    };
    mCharts.setOption(option)
  </script>
</body>
</html>

3.交互API

全局ECharts对象
- init
  - 初始化ECharts实例对象
  - 使用主题
- registerTheme
  - 注册主题
  - 只有注册过的主题，才能在init方法中使用主题
- registerMap
  - 注册地图数据
- connect
  - 一个页面中可以有多个独立的图表
  - 每一个图表对应一个ECharts实例对象
  - connect可以实现多图关联，传入联动目标为ECharts实例对象，可以为数组
    - 保存图片的自动拼接
    - 刷新按钮
    - 重置按钮
    - 提示框联动
    - 图例选择等
- geo组件使用地图数据
ECharts实例对象
- setOption
  - 设置或修改图表实例的配置项以及数据
  - 多次调用setOption方法
    - 合并新的配置和旧的配置，并不会覆盖
    - 适用场景：增量动画
- resize
  - 重新计算和绘制图表
  - 一般和window对象的resize事件结合使用
- on/off
  - 绑定和解绑事件处理函数
    - 鼠标事件
      - 常见事件： ‘click’ ‘dblclick’ ‘mousedown’ ‘mousemove’ ‘mouseup’等
      - 事件参数arg：和事件相关的数据信息
    - ECharts事件
      - 常见事件：’legendselectchanged’，’datazoom’，等
      - 事件参数arg：和事件相关的数据信息
- dispatchAction
  - 出发某些行为
  - 使用代码模拟用户的行为
- clear
  - 清空当前实例中的所有组件和图表
  - 清空之后可以再setOption
- dispose
  - 销毁实例
  - 无法再次调用setOption创建图表

1.全局ECharts对象
<!DOCTYPE html>
<html lang="en">

<head>
  <meta charset="UTF-8">
  <meta name="viewport" content="width=device-width, initial-scale=1.0">
  <meta http-equiv="X-UA-Compatible" content="ie=edge">
  <title>Document</title>
  <script src="js/echarts.min.js"></script>
  <script src="theme/rema.js"></script>
  <script src="js/jquery.js"></script>
</head>

<body>
  <div style="width: 600px;height:400px;border: 1px solid red"></div>
  <div style="width: 600px;height:400px;border: 1px solid green" id="div1"></div>
  <script>
    var mCharts = echarts.init(document.querySelector("div"), 'rema')
    var xDataArr = ['张三', '李四', '王五', '闰土', '小明', '茅台', '二妞', '大强']
    var yDataArr = [88, 92, 63, 77, 94, 80, 72, 86]
    var option = {
      toolbox: {
        feature: {
          saveAsImage: {}
        }
      },
      xAxis: {
        type: 'category',
        data: xDataArr
      },
      yAxis: {
        type: 'value'
      },
      series: [
        {
          type: 'bar',
          data: yDataArr,
          markPoint: {
            data: [
              {
                type: 'max', name: '最大值'
              },
              {
                type: 'min', name: '最小值'
              }
            ]
          },
          markLine: {
            data: [
              {
                type: 'average', name: '平均值'
              }
            ]
          },
          label: {
            show: true,
            rotate: 60
          },
          barWidth: '30%'
        }
      ]
    }
    mCharts.setOption(option)

    var mCharts2 = echarts.init(document.querySelector('#div1'))
    $.get('json/map/china.json', function(ret){
      echarts.registerMap('aa', ret)
      var option2 = {
        geo: {
          type: 'map',
          map: 'aa'
        }
      }
      mCharts2.setOption(option2)
      // echarts.connect([mCharts, mCharts2]) // 将柱状图和地图关联起来
    })
    

  </script>
</body>

</html>

2.ECharts实例对象
<!DOCTYPE html>
<html lang="en">

<head>
  <meta charset="UTF-8">
  <meta name="viewport" content="width=device-width, initial-scale=1.0">
  <meta http-equiv="X-UA-Compatible" content="ie=edge">
  <title>Document</title>
  <script src="js/echarts.min.js"></script>
  <script src="js/jquery.js"></script>
</head>

<body>
  <div style="width: 600px;height:400px"></div>
  <button id="btn1">触发行为</button>
  <button id="btn2">clear</button>
  <button id="btn3">setOption</button>
  <button id="btn4">dispose</button>
  <script>
    var mCharts = echarts.init(document.querySelector("div"))
    var pieData = [
      {
        value: 11231,
        name: "淘宝",
      },
      {
        value: 22673,
        name: "京东"
      },
      {
        value: 6123,
        name: "唯品会"
      },
      {
        value: 8989,
        name: "1号店"
      },
      {
        value: 6700,
        name: "聚美优品"
      }
    ]
    var option = {
      legend: {
        data: ['淘宝', '京东', '唯品会', '1号店', '聚美优品']
      },
      tooltip: {
        show: true
      },
      series: [
        {
          type: 'pie',
          data: pieData
        }
      ]
    }
    mCharts.setOption(option)
    mCharts.on('click', function (arg) {
      console.log(arg)
      console.log('click...')
    }) // 对事件进行监听

    mCharts.off('click') // 解绑click的事件

    mCharts.on('legendselectchanged', function (arg) {
      console.log(arg)
      console.log('legendselectchanged')
    })

    $('#btn1').click(function () {
      // 模拟用户的行为
      mCharts.dispatchAction({
        type: 'highlight',
        seriesIndex: 0, // 系列的索引
        dataIndex: 1 // 数据的索引
      })
      mCharts.dispatchAction({
        type: 'showTip',
        seriesIndex: 0,
        dataIndex: 2
      })
    })

    $('#btn2').click(function () {
      // 清空图表的实例
      mCharts.clear()
    })

    $('#btn3').click(function () {
      // 重新设置option
      mCharts.setOption(option)
    })

    $('#btn4').click(function () {
      // 销毁mCharts
      mCharts.dispose()
    })
  </script>
</body>

</html>

Koa2

Koa2快速上手

检查node环境
- node -v
安装Koa
- npm init -y
- npm install koa
创建并编写app.js文件
- 1.创建Koa对象
- 2.编写响应函数（中间件）
- 3.监听端口
启动服务
- npm app.js

开启掘金成长之旅！这是我参与「掘金日新计划 · 2 月更文挑战」的第 20 天，点击查看活动详情