1、前言
Hello！这篇文章是基于我上篇【Vue3实现百度地图可视化】的“续作”。在导入地图成功后，基于全国地图绘制各个地市销量散点图，最终效果如下：
上一篇地址传送门：juejin.cn/post/726559…
2、基本步骤
- mapStyle自定义地图样式
- 定制标题
- 定制散点
- 数据整合
- 实现Top5涟漪特效
上一篇文章中，最后效果如下，我们会在此基础上进行进一步的绘制。
3、配置项基本代码结构
// mounted生命周期函数中加载配置项
mounted() {
this.mapOptions = {
// 标题定制
title: { ... },
bmap: {
...
// mapStyle自定义地图样式
mapStyle: {
styleJson: [...],
},
},
tooltip: {...},
series: [
// 散点图配置项
{
type: "scatter",
...
},
// Top5波纹散点图配置项
{
type: "effectScatter",
...
},
],
};
},
4、mapStyle自定义地图样式
1、mapStyle介绍：mapStyle是bmap中的一个属性，用于定义地图的样式，mapStyle属性接受一个字符串，该字符串是一个JSON对象的字符串styleJson，styleJson是一个数组对象，每个对象定义了不同类型的地图元素的样式，如水域、陆地等。
2、注：因为涉及修改的地图元素样式较多，这里只呈现部分主要的代码，最后会附上完整代码
局部代码如下：
bmap: {
mapStyle: {
// 数组对象，每个对象定义一个地图元素样式
styleJson: [
// 部分代码
{
featureType: "water",
elementType: "all",
stylers: {
color: "#d1d1d1",
},
},
{
featureType: "land",
elementType: "all",
stylers: {
color: "#f3f3f3",
},
},
// 其他地图元素样式
... ...
]
}
}
5、定制标题
1、标题定制涉及【主标题、副标题内容及样式】、【标题位置】这两个方面。
2、如需了解更具体的配置项，可参考EChart官方的配置项手册。
title: {
text: "外卖销售数据大盘",
subtext: "销售趋势统计",
subtextStyle: {
color: "#999",
},
left: "center",
top: 10,
},
6、定制散点
1、定义两个散点的测试数据
const testPoint = [
{
name: "海门", // 地市
value: [121.15, 31.89, 80], // 经度、纬度、销售量
},
{
name: "南京",
value: [118.78, 32.04, 150],
},
];
2、高德和百度的坐标系统是不一样的，百度是bmap，下面的配置项都是在series下的属性。
3、coordinateSystem: 'bmap',使用百度坐标系统。
4、encode: { value:2 } value值的定制，将数组下标为2的值作为value值，定制后tooltip显示销售量而不再是纬度。
5、symbolSize: (value) => {} 回调函数根据value[2] 的值定制点的大小
6、label 标记
6.1、position: right 标记的位置
6.2、show: false label的show属性先设为false，鼠标hover到点上才展示标记，在emphasis中设为true
6.3、formatter: (val) => {} 回调函数对展示数据的定制
7、emphasis: { label: true } 鼠标移入，展示label
scatter散点图完整配置代码
series: [
{
type: "scatter",
name: "销售额",
coordinateSystem: "bmap",
data: testPoint,
// value值的定制
encode: {
value: 2,
},
// 定制点的大小
symbolSize: function (value) {
return value[2] / 10;
},
// 点的颜色
itemStyle: {
color: "purple",
},
label: {
show: false,
// 标记的位置
position: "right",
// 展示内容
formatter: (val) => {
return `${val.name} - ${val.value[2]}`;
},
textStyle: {
color: "purple",
},
},
emphasis: {
// 鼠标移入，展示label
label: {
show: true,
},
},
}]
7、数据整合
7.1、数据定义
上一步是使用的测试数据testPoint，这一步使用真实数据，现在提供了两组数据cityCount和cityCoord
cityCount数组对象：每一项为城市名称name + value销售量 { "name": "海门", "value": 9 }
cityCoord数组对象：每一项为城市名称name + position经纬度坐标系 { "name": "海门", "position": [121.15, 31.89] }
需求就是将数组项中的对象拼接成下面的格式
{
name: "海门",
value: [121.15, 31.89, 9],
},
7.2、数据整合
定义convertData方法，该方法会返回整合后的新数组 --> 方法中遍历cityCount --> 在循环体中通过cityCoord.find()去匹配name相同的项 --> 如匹配成功，则合并。
// 合并两个数组
const convertData = function () {
const result = [];
// 遍历cityCount数组
cityCount.forEach((cityCountItem) => {
// 查找cityCoord数组中与当前cityCountItem相匹配的项
const matchItem = cityCoord.find(
(item) => cityCountItem.name === item.name
);
// 如果找到了匹配的项，则将其合并成新的对象，并加入到result中
if (matchItem) {
result.push({
name: cityCountItem.name,
value: [...matchItem.position, cityCountItem.value],
});
}
});
return result;
};
8、实现Top5涟漪特效
1、定义第二个series：effectScatter
2、data的值：根据convertData的value属性中的第二项数组项销售量对convertData进行降序排列
3、然后再截取数组项前5项
最后完整的代码：
<template>
<v-chart :option="mapOptions"></v-chart>
</template>
<script>
import "echarts/extension/bmap/bmap";
// const testPoint = [
// {
// name: "海门", // 地市
// value: [121.15, 31.89, 80], // 经度、纬度、销售量
// },
// {
// name: "南京",
// value: [118.78, 32.04, 150],
// },
// ];
// { "name": "海门", "value": 9 },
const cityCount = [
{ name: "海门", value: 9 },
{ name: "鄂尔多斯", value: 12 },
{ name: "招远", value: 12 },
{ name: "舟山", value: 12 },
{ name: "齐齐哈尔", value: 14 },
{ name: "盐城", value: 15 },
{ name: "赤峰", value: 16 },
{ name: "青岛", value: 18 },
{ name: "乳山", value: 18 },
{ name: "金昌", value: 19 },
{ name: "泉州", value: 21 },
{ name: "莱西", value: 21 },
{ name: "日照", value: 21 },
{ name: "胶南", value: 22 },
{ name: "南通", value: 23 },
{ name: "拉萨", value: 24 },
{ name: "云浮", value: 24 },
{ name: "梅州", value: 25 },
{ name: "文登", value: 25 },
{ name: "上海", value: 25 },
{ name: "攀枝花", value: 25 },
{ name: "威海", value: 25 },
{ name: "承德", value: 25 },
{ name: "厦门", value: 26 },
{ name: "汕尾", value: 26 },
{ name: "潮州", value: 26 },
{ name: "丹东", value: 27 },
{ name: "太仓", value: 27 },
{ name: "曲靖", value: 27 },
{ name: "烟台", value: 28 },
{ name: "福州", value: 29 },
{ name: "瓦房店", value: 30 },
{ name: "即墨", value: 30 },
{ name: "抚顺", value: 31 },
{ name: "玉溪", value: 31 },
{ name: "张家口", value: 31 },
{ name: "阳泉", value: 31 },
{ name: "莱州", value: 32 },
{ name: "湖州", value: 32 },
{ name: "汕头", value: 32 },
{ name: "昆山", value: 33 },
{ name: "宁波", value: 33 },
{ name: "湛江", value: 33 },
{ name: "揭阳", value: 34 },
{ name: "荣成", value: 34 },
{ name: "连云港", value: 35 },
{ name: "葫芦岛", value: 35 },
{ name: "常熟", value: 36 },
{ name: "东莞", value: 36 },
{ name: "河源", value: 36 },
{ name: "淮安", value: 36 },
{ name: "泰州", value: 36 },
{ name: "南宁", value: 37 },
{ name: "营口", value: 37 },
{ name: "惠州", value: 37 },
{ name: "江阴", value: 37 },
{ name: "蓬莱", value: 37 },
{ name: "韶关", value: 38 },
{ name: "嘉峪关", value: 38 },
{ name: "广州", value: 38 },
{ name: "延安", value: 38 },
{ name: "太原", value: 39 },
{ name: "清远", value: 39 },
{ name: "中山", value: 39 },
{ name: "昆明", value: 39 },
{ name: "寿光", value: 40 },
{ name: "盘锦", value: 40 },
{ name: "长治", value: 41 },
{ name: "深圳", value: 41 },
{ name: "珠海", value: 42 },
{ name: "宿迁", value: 43 },
{ name: "咸阳", value: 43 },
{ name: "铜川", value: 44 },
{ name: "平度", value: 44 },
{ name: "佛山", value: 44 },
{ name: "海口", value: 44 },
{ name: "江门", value: 45 },
{ name: "章丘", value: 45 },
{ name: "肇庆", value: 46 },
{ name: "大连", value: 47 },
{ name: "临汾", value: 47 },
{ name: "吴江", value: 47 },
{ name: "石嘴山", value: 49 },
{ name: "沈阳", value: 50 },
{ name: "苏州", value: 50 },
{ name: "茂名", value: 50 },
{ name: "嘉兴", value: 51 },
{ name: "长春", value: 51 },
{ name: "胶州", value: 52 },
{ name: "银川", value: 52 },
{ name: "张家港", value: 52 },
{ name: "三门峡", value: 53 },
{ name: "锦州", value: 54 },
{ name: "南昌", value: 54 },
{ name: "柳州", value: 54 },
{ name: "三亚", value: 54 },
{ name: "自贡", value: 56 },
{ name: "吉林", value: 56 },
{ name: "阳江", value: 57 },
{ name: "泸州", value: 57 },
{ name: "西宁", value: 57 },
{ name: "宜宾", value: 58 },
{ name: "呼和浩特", value: 58 },
{ name: "成都", value: 58 },
{ name: "大同", value: 58 },
{ name: "镇江", value: 59 },
{ name: "桂林", value: 59 },
{ name: "张家界", value: 59 },
{ name: "宜兴", value: 59 },
{ name: "北海", value: 60 },
{ name: "西安", value: 61 },
{ name: "金坛", value: 62 },
{ name: "东营", value: 62 },
{ name: "牡丹江", value: 63 },
{ name: "遵义", value: 63 },
{ name: "绍兴", value: 63 },
{ name: "扬州", value: 64 },
{ name: "常州", value: 64 },
{ name: "潍坊", value: 65 },
{ name: "重庆", value: 66 },
{ name: "台州", value: 67 },
{ name: "南京", value: 67 },
{ name: "滨州", value: 70 },
{ name: "贵阳", value: 71 },
{ name: "无锡", value: 71 },
{ name: "本溪", value: 71 },
{ name: "克拉玛依", value: 72 },
{ name: "渭南", value: 72 },
{ name: "马鞍山", value: 72 },
{ name: "宝鸡", value: 72 },
{ name: "焦作", value: 75 },
{ name: "句容", value: 75 },
{ name: "北京", value: 79 },
{ name: "徐州", value: 79 },
{ name: "衡水", value: 80 },
{ name: "包头", value: 80 },
{ name: "绵阳", value: 80 },
{ name: "乌鲁木齐", value: 84 },
{ name: "枣庄", value: 84 },
{ name: "杭州", value: 84 },
{ name: "淄博", value: 85 },
{ name: "鞍山", value: 86 },
{ name: "溧阳", value: 86 },
{ name: "库尔勒", value: 86 },
{ name: "安阳", value: 90 },
{ name: "开封", value: 90 },
{ name: "济南", value: 92 },
{ name: "德阳", value: 93 },
{ name: "温州", value: 95 },
{ name: "九江", value: 96 },
{ name: "邯郸", value: 98 },
{ name: "临安", value: 99 },
{ name: "兰州", value: 99 },
{ name: "沧州", value: 100 },
{ name: "临沂", value: 103 },
{ name: "南充", value: 104 },
{ name: "天津", value: 105 },
{ name: "富阳", value: 106 },
{ name: "泰安", value: 112 },
{ name: "诸暨", value: 112 },
{ name: "郑州", value: 113 },
{ name: "哈尔滨", value: 114 },
{ name: "聊城", value: 116 },
{ name: "芜湖", value: 117 },
{ name: "唐山", value: 119 },
{ name: "平顶山", value: 119 },
{ name: "邢台", value: 119 },
{ name: "德州", value: 120 },
{ name: "济宁", value: 120 },
{ name: "荆州", value: 127 },
{ name: "宜昌", value: 130 },
{ name: "义乌", value: 132 },
{ name: "丽水", value: 133 },
{ name: "洛阳", value: 134 },
{ name: "秦皇岛", value: 136 },
{ name: "株洲", value: 143 },
{ name: "石家庄", value: 147 },
{ name: "莱芜", value: 148 },
{ name: "常德", value: 152 },
{ name: "保定", value: 153 },
{ name: "湘潭", value: 154 },
{ name: "金华", value: 157 },
{ name: "岳阳", value: 169 },
{ name: "长沙", value: 175 },
{ name: "衢州", value: 177 },
{ name: "廊坊", value: 193 },
{ name: "菏泽", value: 194 },
{ name: "合肥", value: 229 },
{ name: "武汉", value: 273 },
{ name: "大庆", value: 279 },
];
// { "name": "海门", "position": [121.15, 31.89] }
const cityCoord = [
{ name: "海门", position: [121.15, 31.89] },
{ name: "鄂尔多斯", position: [109.781327, 39.608266] },
{ name: "招远", position: [120.38, 37.35] },
{ name: "舟山", position: [122.207216, 29.985295] },
{ name: "齐齐哈尔", position: [123.97, 47.33] },
{ name: "盐城", position: [120.13, 33.38] },
{ name: "赤峰", position: [118.87, 42.28] },
{ name: "青岛", position: [120.33, 36.07] },
{ name: "乳山", position: [121.52, 36.89] },
{ name: "金昌", position: [102.19, 38.52] },
{ name: "泉州", position: [118.58, 24.93] },
{ name: "莱西", position: [120.53, 36.86] },
{ name: "日照", position: [119.46, 35.42] },
{ name: "胶南", position: [119.97, 35.88] },
{ name: "南通", position: [121.05, 32.08] },
{ name: "拉萨", position: [91.11, 29.97] },
{ name: "云浮", position: [112.02, 22.93] },
{ name: "梅州", position: [116.1, 24.55] },
{ name: "文登", position: [122.05, 37.21] },
{ name: "上海", position: [121.48, 31.22] },
{ name: "攀枝花", position: [101.718637, 26.582347] },
{ name: "威海", position: [122.1, 37.51] },
{ name: "承德", position: [117.93, 40.97] },
{ name: "厦门", position: [118.1, 24.46] },
{ name: "汕尾", position: [115.38, 22.79] },
{ name: "潮州", position: [116.63, 23.68] },
{ name: "丹东", position: [124.37, 40.13] },
{ name: "太仓", position: [121.1, 31.45] },
{ name: "曲靖", position: [103.79, 25.51] },
{ name: "烟台", position: [121.39, 37.52] },
{ name: "福州", position: [119.3, 26.08] },
{ name: "瓦房店", position: [121.979603, 39.627114] },
{ name: "即墨", position: [120.45, 36.38] },
{ name: "抚顺", position: [123.97, 41.97] },
{ name: "玉溪", position: [102.52, 24.35] },
{ name: "张家口", position: [114.87, 40.82] },
{ name: "阳泉", position: [113.57, 37.85] },
{ name: "莱州", position: [119.94, 37.177] },
{ name: "湖州", position: [120.1, 30.86] },
{ name: "汕头", position: [116.69, 23.39] },
{ name: "昆山", position: [120.95, 31.39] },
{ name: "宁波", position: [121.56, 29.86] },
{ name: "湛江", position: [110.36, 21.27] },
{ name: "揭阳", position: [116.35, 23.55] },
{ name: "荣成", position: [122.41, 37.16] },
{ name: "连云港", position: [119.16, 34.59] },
{ name: "葫芦岛", position: [120.836932, 40.711052] },
{ name: "常熟", position: [120.74, 31.64] },
{ name: "东莞", position: [113.75, 23.04] },
{ name: "河源", position: [114.68, 23.73] },
{ name: "淮安", position: [119.15, 33.51] },
{ name: "泰州", position: [119.9, 32.49] },
{ name: "南宁", position: [108.33, 22.84] },
{ name: "营口", position: [122.18, 40.65] },
{ name: "惠州", position: [114.4, 23.09] },
{ name: "江阴", position: [120.26, 31.91] },
{ name: "蓬莱", position: [120.75, 37.8] },
{ name: "韶关", position: [113.62, 24.84] },
{ name: "嘉峪关", position: [98.289, 39.77] },
{ name: "广州", position: [113.23, 23.16] },
{ name: "延安", position: [109.47, 36.6] },
{ name: "太原", position: [112.53, 37.87] },
{ name: "清远", position: [113.01, 23.7] },
{ name: "中山", position: [113.38, 22.52] },
{ name: "昆明", position: [102.73, 25.04] },
{ name: "寿光", position: [118.73, 36.86] },
{ name: "盘锦", position: [122.07, 41.12] },
{ name: "长治", position: [113.08, 36.18] },
{ name: "深圳", position: [114.07, 22.62] },
{ name: "珠海", position: [113.52, 22.31] },
{ name: "宿迁", position: [118.31, 33.96] },
{ name: "咸阳", position: [108.72, 34.36] },
{ name: "铜川", position: [109.11, 35.09] },
{ name: "平度", position: [119.97, 36.77] },
{ name: "佛山", position: [113.11, 23.05] },
{ name: "海口", position: [110.35, 20.02] },
{ name: "江门", position: [113.06, 22.61] },
{ name: "章丘", position: [117.53, 36.72] },
{ name: "肇庆", position: [112.44, 23.05] },
{ name: "大连", position: [121.62, 38.92] },
{ name: "临汾", position: [111.51, 36.08] },
{ name: "吴江", position: [120.63, 31.16] },
{ name: "石嘴山", position: [106.39, 39.04] },
{ name: "沈阳", position: [123.38, 41.81] },
{ name: "苏州", position: [120.62, 31.32] },
{ name: "茂名", position: [110.88, 21.68] },
{ name: "嘉兴", position: [120.76, 30.77] },
{ name: "长春", position: [125.35, 43.88] },
{ name: "胶州", position: [120.03, 36.26] },
{ name: "银川", position: [106.27, 38.47] },
{ name: "张家港", position: [120.555821, 31.875428] },
{ name: "三门峡", position: [111.19, 34.76] },
{ name: "锦州", position: [121.15, 41.13] },
{ name: "南昌", position: [115.89, 28.68] },
{ name: "柳州", position: [109.41, 24.33] },
{ name: "三亚", position: [109.51, 18.25] },
{ name: "自贡", position: [104.78, 29.33] },
{ name: "吉林", position: [126.57, 43.87] },
{ name: "阳江", position: [111.95, 21.85] },
{ name: "泸州", position: [105.39, 28.91] },
{ name: "西宁", position: [101.74, 36.56] },
{ name: "宜宾", position: [104.56, 29.77] },
{ name: "呼和浩特", position: [111.65, 40.82] },
{ name: "成都", position: [104.06, 30.67] },
{ name: "大同", position: [113.3, 40.12] },
{ name: "镇江", position: [119.44, 32.2] },
{ name: "桂林", position: [110.28, 25.29] },
{ name: "张家界", position: [110.48, 29.12] },
{ name: "宜兴", position: [119.82, 31.36] },
{ name: "北海", position: [109.12, 21.49] },
{ name: "西安", position: [108.95, 34.27] },
{ name: "金坛", position: [119.56, 31.74] },
{ name: "东营", position: [118.49, 37.46] },
{ name: "牡丹江", position: [129.58, 44.6] },
{ name: "遵义", position: [106.91, 27.71] },
{ name: "绍兴", position: [120.58, 30.01] },
{ name: "扬州", position: [119.42, 32.39] },
{ name: "常州", position: [119.95, 31.79] },
{ name: "潍坊", position: [119.1, 36.62] },
{ name: "重庆", position: [106.54, 29.59] },
{ name: "台州", position: [121.42, 28.66] },
{ name: "南京", position: [118.78, 32.04] },
{ name: "滨州", position: [118.03, 37.36] },
{ name: "贵阳", position: [106.71, 26.57] },
{ name: "无锡", position: [120.29, 31.59] },
{ name: "本溪", position: [123.73, 41.3] },
{ name: "克拉玛依", position: [84.77, 45.59] },
{ name: "渭南", position: [109.5, 34.52] },
{ name: "马鞍", position: [118.48, 31.56] },
{ name: "宝鸡", position: [107.15, 34.38] },
{ name: "焦作", position: [113.21, 35.24] },
{ name: "句容", position: [119.16, 31.95] },
{ name: "北京", position: [116.46, 39.92] },
{ name: "徐州", position: [117.2, 34.26] },
{ name: "衡水", position: [115.72, 37.72] },
{ name: "包头", position: [110.01, 40.58] },
{ name: "绵阳", position: [104.73, 31.48] },
{ name: "乌鲁木齐", position: [87.68, 43.77] },
{ name: "枣庄", position: [117.57, 34.86] },
{ name: "杭州", position: [120.19, 30.26] },
{ name: "淄博", position: [118.05, 36.78] },
{ name: "鞍山", position: [122.85, 41.12] },
{ name: "溧阳", position: [119.48, 31.43] },
{ name: "库尔勒", position: [86.061, 41.68] },
{ name: "安阳", position: [114.35, 36.11] },
{ name: "开封", position: [114.35, 34.79] },
{ name: "济南", position: [117.01, 36.65] },
{ name: "德阳", position: [104.37, 31.13] },
{ name: "温州", position: [120.65, 28.01] },
{ name: "九江", position: [115.97, 29.71] },
{ name: "邯郸", position: [114.47, 36.6] },
{ name: "临安", position: [119.72, 30.23] },
{ name: "兰州", position: [103.73, 36.03] },
{ name: "沧州", position: [116.83, 38.33] },
{ name: "临沂", position: [118.35, 35.05] },
{ name: "南充", position: [106.11, 30.84] },
{ name: "天津", position: [117.21, 39.13] },
{ name: "富阳", position: [119.95, 30.07] },
{ name: "泰安", position: [117.13, 36.18] },
{ name: "诸暨", position: [120.23, 29.71] },
{ name: "郑州", position: [113.65, 34.76] },
{ name: "哈尔滨", position: [126.63, 45.75] },
{ name: "聊城", position: [115.97, 36.45] },
{ name: "芜湖", position: [118.38, 31.33] },
{ name: "唐山", position: [118.02, 39.63] },
{ name: "平顶山", position: [113.29, 33.75] },
{ name: "邢台", position: [114.48, 37.05] },
{ name: "德州", position: [116.29, 37.45] },
{ name: "济宁", position: [116.59, 35.38] },
{ name: "荆州", position: [112.239741, 30.335165] },
{ name: "宜昌", position: [111.3, 30.7] },
{ name: "义乌", position: [120.06, 29.32] },
{ name: "丽水", position: [119.92, 28.45] },
{ name: "洛阳", position: [112.44, 34.7] },
{ name: "秦皇岛", position: [119.57, 39.95] },
{ name: "株洲", position: [113.16, 27.83] },
{ name: "石家庄", position: [114.48, 38.03] },
{ name: "莱芜", position: [117.67, 36.19] },
{ name: "常德", position: [111.69, 29.05] },
{ name: "保定", position: [115.48, 38.85] },
{ name: "湘潭", position: [112.91, 27.87] },
{ name: "金华", position: [119.64, 29.12] },
{ name: "岳阳", position: [113.09, 29.37] },
{ name: "长沙", position: [113.01, 28.21] },
{ name: "衢州", position: [118.88, 28.97] },
{ name: "廊坊", position: [116.7, 39.53] },
{ name: "菏泽", position: [115.48, 35.23] },
{ name: "合肥", position: [117.27, 31.86] },
{ name: "武汉", position: [114.31, 30.52] },
{ name: "大庆", position: [125.03, 46.58] },
];
// 合并两个数组
const convertData = function () {
const result = [];
// 遍历cityCount数组
cityCount.forEach((cityCountItem) => {
// 查找cityCoord数组中与当前cityCountItem相匹配的项
const matchItem = cityCoord.find(
(item) => cityCountItem.name === item.name
);
// 如果找到了匹配的项，则将其合并成新的对象，并加入到result中
if (matchItem) {
result.push({
name: cityCountItem.name,
value: [...matchItem.position, cityCountItem.value],
});
}
});
return result;
};
export default {
name: "BMap",
data() {
return {
mapOptions: {},
};
},
mounted() {
this.mapOptions = {
title: {
text: "外卖销售数据大盘",
subtext: "销售趋势统计",
subtextStyle: {
color: "#999",
},
sublink: "https://www.imooc.com/",
left: "center",
top: 10,
},
bmap: {
// 地图中心点（经纬度）
center: [104, 38],
// 缩放比例
zoom: 5,
// 是否允许缩放
roam: false,
// 地图定制
mapStyle: {
styleJson: [
{
featureType: "water",
elementType: "all",
stylers: {
color: "#d1d1d1",
},
},
{
featureType: "land",
elementType: "all",
stylers: {
color: "#f3f3f3",
},
},
{
featureType: "railway",
elementType: "all",
stylers: {
visibility: "off",
},
},
{
featureType: "highway",
elementType: "all",
stylers: {
color: "#fdfdfd",
},
},
{
featureType: "highway",
elementType: "labels",
stylers: {
visibility: "off",
},
},
{
featureType: "arterial",
elementType: "geometry",
stylers: {
color: "#fefefe",
},
},
{
featureType: "arterial",
elementType: "geometry.fill",
stylers: {
color: "#fefefe",
},
},
{
featureType: "poi",
elementType: "all",
stylers: {
visibility: "off",
},
},
{
featureType: "green",
elementType: "all",
stylers: {
visibility: "off",
},
},
{
featureType: "subway",
elementType: "all",
stylers: {
visibility: "off",
},
},
{
featureType: "manmade",
elementType: "all",
stylers: {
color: "#d1d1d1",
},
},
{
featureType: "local",
elementType: "all",
stylers: {
color: "#d1d1d1",
},
},
{
featureType: "arterial",
elementType: "labels",
stylers: {
visibility: "off",
},
},
{
featureType: "boundary",
elementType: "all",
stylers: {
color: "#fefefe",
},
},
{
featureType: "building",
elementType: "all",
stylers: {
color: "#d1d1d1",
},
},
{
featureType: "label",
elementType: "labels.text.fill",
stylers: {
color: "#999999",
},
},
],
},
},
tooltip: {
backgroundColor: "rgba(0, 0, 0, 0.5)",
borderWidth: 0,
textStyle: {
color: "#fff",
fontWeight: "normal",
},
},
series: [
// 散点图
{
type: "scatter",
name: "销售额",
coordinateSystem: "bmap",
data: convertData(),
// value值的定制
encode: {
value: 2,
},
// 定制点的大小
symbolSize: function (value) {
return value[2] / 10;
},
// 点的颜色
itemStyle: {
color: "purple",
},
label: {
show: false,
// 标记的位置
position: "right",
// 展示内容
formatter: (val) => {
return `${val.name} - ${val.value[2]}`;
},
textStyle: {
color: "purple",
},
},
emphasis: {
// 鼠标移入，展示label
label: {
show: true,
},
},
},
// Top5波纹散点图
{
type: "effectScatter",
name: "Top",
coordinateSystem: "bmap",
data: convertData()
.sort((a, b) => b.value[2] - a.value[2])
.slice(0, 5),
// value值的定制
encode: {
value: 2,
},
// 定制点的大小
symbolSize: function (value) {
return value[2] / 10;
},
// 涟漪特效配置
rippleEffect: {
brushType: "stroke",
},
// 点的颜色
itemStyle: {
color: "purple",
// 点的阴影
shadowColor: "rgba{0, 0, 0, .5}",
shadowBlur: 10,
},
label: {
show: false,
// 标记的位置
position: "right",
// 展示内容
formatter: (val) => {
return `${val.name} - ${val.value[2]}`;
},
textStyle: {
color: "purple",
},
},
emphasis: {
// 鼠标移入，展示label
label: {
show: true,
},
},
},
],
};
},
};
</script>
<style lang="scss">
.echarts {
margin: 20px;
width: 840px !important;
height: 680px !important;
}
.anchorBL {
display: none;
}
</style>
这样，全国地图的销量分布散点图就完成了！觉得有干货或者喜欢的话麻烦您动动手，点个赞吧~！
