散点图也可以叫做热点图、地理分布图等。
目标
画一个地图，上面星星点点的一些表示数据的热点。没想到这么简单的一个事儿，小坑无数，diss下百度。
基于百度地图的散点图
也就是scatter与bmap结合。主要参考官网的地理/地图例子，把那个矩形给去掉了。
先写html，说明见注释。
基于百度地图的散点图
首先，ECharts官网已经不提供地图文件直接下载了，只能采用与百度地图结合的形式。
image.png
其他都好说，引入bmap.js真是费周折。先从Echarts官网的最下面的扩展百度地图点进去，跳转到github，直接下载使用。
控制台报错Uncaught SyntaxError: Unexpected token
image.png
你倒是告诉我，哪来的min版本？
后来阴差阳错，在这个地址下载了min版本才可用了。
js代码没什么好说的，参考了百度地图以及Echarts的官网。
$(function () {
var mp = new BMap.Map("scatter-bmap");
mp.centerAndZoom(new BMap.Point(116.3964,39.9093), 10);
mp.enableScrollWheelZoom();
var canvasLayer = new BMap.CanvasLayer({
update: update
});
function update() {
var ctx = this.canvas.getContext("2d");
if (!ctx) {
return;
}
ctx.clearRect(0, 0, ctx.canvas.width, ctx.canvas.height);
var temp = {};
ctx.fillStyle = "rgba(50, 50, 255, 0.7)";
ctx.beginPath();
var data = [
new BMap.Point(116.297047,39.979542),
new BMap.Point(116.321768,39.88748),
new BMap.Point(116.494243,39.956539)
];
for (var i = 0, len = data.length; i < len; i++) {
var pixel = mp.pointToPixel(data[i]);
ctx.fillRect(pixel.x, pixel.y, 30, 30);
}
}
mp.addOverlay(canvasLayer);
// 初始化echarts示例mapChart
var mapChart = echarts.init(document.getElementById('scatter-bmap'));
var data = [
{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}
];
var geoCoordMap = {
'海门':[121.15,31.89],
'鄂尔多斯':[109.781327,39.608266],
'招远':[120.38,37.35],
'舟山':[122.207216,29.985295],
'齐齐哈尔':[123.97,47.33],
'盐城':[120.13,33.38],
'赤峰':[118.87,42.28],
'青岛':[120.33,36.07],
'乳山':[121.52,36.89],
'金昌':[102.188043,38.59],
'泉州':[118.58,24.93],
'莱西':[120.53,36.86],
'日照':[119.46,35.42],
'胶南':[119.97,35.88],
'南通':[121.05,32.08],
'拉萨':[91.11,29.97],
'云浮':[112.02,22.93],
'梅州':[116.1,24.55],
'文登':[122.05,37.2],
'上海':[121.48,31.22],
'攀枝花':[101.718637,26.582347],
'威海':[122.1,37.5],
'承德':[117.93,40.97],
'厦门':[118.1,24.46],
'汕尾':[115.375279,22.786211],
'潮州':[116.63,23.68],
'丹东':[124.37,40.13],
'太仓':[121.1,31.45],
'曲靖':[103.79,25.51],
'烟台':[121.39,37.52],
'福州':[119.3,26.08],
'瓦房店':[121.979603,39.627114],
'即墨':[120.45,36.38],
'抚顺':[123.97,41.97],
'玉溪':[102.52,24.35],
'张家口':[114.87,40.82],
'阳泉':[113.57,37.85],
'莱州':[119.942327,37.177017],
'湖州':[120.1,30.86],
'汕头':[116.69,23.39],
'昆山':[120.95,31.39],
'宁波':[121.56,29.86],
'湛江':[110.359377,21.270708],
'揭阳':[116.35,23.55],
'荣成':[122.41,37.16],
'连云港':[119.16,34.59],
'葫芦岛':[120.836932,40.711052],
'常熟':[120.74,31.64],
'东莞':[113.75,23.04],
'河源':[114.68,23.73],
'淮安':[119.15,33.5],
'泰州':[119.9,32.49],
'南宁':[108.33,22.84],
'营口':[122.18,40.65],
'惠州':[114.4,23.09],
'江阴':[120.26,31.91],
'蓬莱':[120.75,37.8],
'韶关':[113.62,24.84],
'嘉峪关':[98.289152,39.77313],
'广州':[113.23,23.16],
'延安':[109.47,36.6],
'太原':[112.53,37.87],
'清远':[113.01,23.7],
'中山':[113.38,22.52],
'昆明':[102.73,25.04],
'寿光':[118.73,36.86],
'盘锦':[122.070714,41.119997],
'长治':[113.08,36.18],
'深圳':[114.07,22.62],
'珠海':[113.52,22.3],
'宿迁':[118.3,33.96],
'咸阳':[108.72,34.36],
'铜川':[109.11,35.09],
'平度':[119.97,36.77],
'佛山':[113.11,23.05],
'海口':[110.35,20.02],
'江门':[113.06,22.61],
'章丘':[117.53,36.72],
'肇庆':[112.44,23.05],
'大连':[121.62,38.92],
'临汾':[111.5,36.08],
'吴江':[120.63,31.16],
'石嘴山':[106.39,39.04],
'沈阳':[123.38,41.8],
'苏州':[120.62,31.32],
'茂名':[110.88,21.68],
'嘉兴':[120.76,30.77],
'长春':[125.35,43.88],
'胶州':[120.03336,36.264622],
'银川':[106.27,38.47],
'张家港':[120.555821,31.875428],
'三门峡':[111.19,34.76],
'锦州':[121.15,41.13],
'南昌':[115.89,28.68],
'柳州':[109.4,24.33],
'三亚':[109.511909,18.252847],
'自贡':[104.778442,29.33903],
'吉林':[126.57,43.87],
'阳江':[111.95,21.85],
'泸州':[105.39,28.91],
'西宁':[101.74,36.56],
'宜宾':[104.56,29.77],
'呼和浩特':[111.65,40.82],
'成都':[104.06,30.67],
'大同':[113.3,40.12],
'镇江':[119.44,32.2],
'桂林':[110.28,25.29],
'张家界':[110.479191,29.117096],
'宜兴':[119.82,31.36],
'北海':[109.12,21.49],
'西安':[108.95,34.27],
'金坛':[119.56,31.74],
'东营':[118.49,37.46],
'牡丹江':[129.58,44.6],
'遵义':[106.9,27.7],
'绍兴':[120.58,30.01],
'扬州':[119.42,32.39],
'常州':[119.95,31.79],
'潍坊':[119.1,36.62],
'重庆':[106.54,29.59],
'台州':[121.420757,28.656386],
'南京':[118.78,32.04],
'滨州':[118.03,37.36],
'贵阳':[106.71,26.57],
'无锡':[120.29,31.59],
'本溪':[123.73,41.3],
'克拉玛依':[84.77,45.59],
'渭南':[109.5,34.52],
'马鞍山':[118.48,31.56],
'宝鸡':[107.15,34.38],
'焦作':[113.21,35.24],
'句容':[119.16,31.95],
'北京':[116.46,39.92],
'徐州':[117.2,34.26],
'衡水':[115.72,37.72],
'包头':[110,40.58],
'绵阳':[104.73,31.48],
'乌鲁木齐':[87.68,43.77],
'枣庄':[117.57,34.86],
'杭州':[120.19,30.26],
'淄博':[118.05,36.78],
'鞍山':[122.85,41.12],
'溧阳':[119.48,31.43],
'库尔勒':[86.06,41.68],
'安阳':[114.35,36.1],
'开封':[114.35,34.79],
'济南':[117,36.65],
'德阳':[104.37,31.13],
'温州':[120.65,28.01],
'九江':[115.97,29.71],
'邯郸':[114.47,36.6],
'临安':[119.72,30.23],
'兰州':[103.73,36.03],
'沧州':[116.83,38.33],
'临沂':[118.35,35.05],
'南充':[106.110698,30.837793],
'天津':[117.2,39.13],
'富阳':[119.95,30.07],
'泰安':[117.13,36.18],
'诸暨':[120.23,29.71],
'郑州':[113.65,34.76],
'哈尔滨':[126.63,45.75],
'聊城':[115.97,36.45],
'芜湖':[118.38,31.33],
'唐山':[118.02,39.63],
'平顶山':[113.29,33.75],
'邢台':[114.48,37.05],
'德州':[116.29,37.45],
'济宁':[116.59,35.38],
'荆州':[112.239741,30.335165],
'宜昌':[111.3,30.7],
'义乌':[120.06,29.32],
'丽水':[119.92,28.45],
'洛阳':[112.44,34.7],
'秦皇岛':[119.57,39.95],
'株洲':[113.16,27.83],
'石家庄':[114.48,38.03],
'莱芜':[117.67,36.19],
'常德':[111.69,29.05],
'保定':[115.48,38.85],
'湘潭':[112.91,27.87],
'金华':[119.64,29.12],
'岳阳':[113.09,29.37],
'长沙':[113,28.21],
'衢州':[118.88,28.97],
'廊坊':[116.7,39.53],
'菏泽':[115.480656,35.23375],
'合肥':[117.27,31.86],
'武汉':[114.31,30.52],
'大庆':[125.03,46.58]
};
var convertData = function (data) {
var res = [];
for (var i = 0; i < data.length; i++) {
var geoCoord = geoCoordMap[data[i].name];
if (geoCoord) {
res.push({
name: data[i].name,
value: geoCoord.concat(data[i].value)
});
}
}
return res;
};
option = {
title: {
text: '全国空气质量',
subtext: 'data from PM25.in',
sublink: 'http://www.pm25.in',
left: 'center',
textStyle: {
color: '#fff'
}
},
tooltip : {
trigger: 'item'
},
bmap: {
center: [104.114129, 37.550339],
zoom: 5,
roam: true,
mapStyle: {
styleJson: [
{
"featureType": "water",
"elementType": "all",
"stylers": {
"color": "#044161"
}
},
{
"featureType": "land",
"elementType": "all",
"stylers": {
"color": "#004981"
}
},
{
"featureType": "boundary",
"elementType": "geometry",
"stylers": {
"color": "#064f85"
}
},
{
"featureType": "railway",
"elementType": "all",
"stylers": {
"visibility": "off"
}
},
{
"featureType": "highway",
"elementType": "geometry",
"stylers": {
"color": "#004981"
}
},
{
"featureType": "highway",
"elementType": "geometry.fill",
"stylers": {
"color": "#005b96",
"lightness": 1
}
},
{
"featureType": "highway",
"elementType": "labels",
"stylers": {
"visibility": "off"
}
},
{
"featureType": "arterial",
"elementType": "geometry",
"stylers": {
"color": "#004981"
}
},
{
"featureType": "arterial",
"elementType": "geometry.fill",
"stylers": {
"color": "#00508b"
}
},
{
"featureType": "poi",
"elementType": "all",
"stylers": {
"visibility": "off"
}
},
{
"featureType": "green",
"elementType": "all",
"stylers": {
"color": "#056197",
"visibility": "off"
}
},
{
"featureType": "subway",
"elementType": "all",
"stylers": {
"visibility": "off"
}
},
{
"featureType": "manmade",
"elementType": "all",
"stylers": {
"visibility": "off"
}
},
{
"featureType": "local",
"elementType": "all",
"stylers": {
"visibility": "off"
}
},
{
"featureType": "arterial",
"elementType": "labels",
"stylers": {
"visibility": "off"
}
},
{
"featureType": "boundary",
"elementType": "geometry.fill",
"stylers": {
"color": "#029fd4"
}
},
{
"featureType": "building",
"elementType": "all",
"stylers": {
"color": "#1a5787"
}
},
{
"featureType": "label",
"elementType": "all",
"stylers": {
"visibility": "off"
}
}
]
}
},
series : [
{
name: '医院数量',
type: 'scatter',
coordinateSystem: 'bmap',
data: convertData(data),
symbolSize: function (val) {
return val[2] / 10;
},
label: {
normal: {
formatter: '{b}',
position: 'right',
show: false
},
emphasis: {
show: true
}
},
itemStyle: {
normal: {
color: '#ddb926'
}
}
},
{
name: 'Top 5',
type: 'effectScatter',
coordinateSystem: 'bmap',
data: convertData(data.sort(function (a, b) {
return b.value - a.value;
}).slice(0, 6)),
symbolSize: function (val) {
return val[2] / 10;
},
showEffectOn: 'emphasis',
rippleEffect: {
brushType: 'stroke'
},
hoverAnimation: true,
label: {
normal: {
formatter: '{b}',
position: 'right',
show: true
}
},
itemStyle: {
normal: {
color: '#f4e925',
shadowBlur: 10,
shadowColor: '#333'
}
},
zlevel: 1
}
]
};
mapChart.setOption(option);
});
效果见图。
image.png
基于地图文件的GL散点图
也就是scatterGL与map文件结合，主要参考官网这个例子。恶心的是，上一个例子，百度告诉我地图文件不能用了，要跟百度地图结合，然后这个例子还是用的地图文件，就没人好好维护下前后对的上么？只能自己多次尝试踩坑。
先写html，去除了bmap相关文件，引入了gl库以及地图文件。
基于地图文件的GL散点图
地图文件去哪里下载呢？github的这个，我试过，好像是不能用的。阴差阳错的在这个文章里找到一个
下载了，可用，感恩。
官网的GL散点图例子的数据采用异步加载一个全世界gps信息什么的数据，有点复杂，自己研究发现，其实数据做出经纬度数值对数组就行了。
$(function () {
var mapScatter = echarts.init(document.getElementById('scatter-gl'));
var option = {
backgroundColor: '#000',
title: {
text: '我的GL散点图',
left: 'center',
textStyle: {
color: '#fff'
}
},
geo: {
map: 'china',
roam: true,
label: {
emphasis: {
show: false
}
},
silent: true,
itemStyle: {
normal: {
areaColor: '#323c48',
borderColor: '#111'
},
emphasis: {
areaColor: '#2a333d'
}
}
},
series: [{
name: '弱',
type: 'scatterGL',
progressive: 1e6,
coordinateSystem: 'geo',
symbolSize: 1,
zoomScale: 0.002,
blendMode: 'lighter',
large: true,
itemStyle: {
color: 'rgb(20, 15, 2)'
},
postEffect: {
enable: true
},
silent: true,
dimensions: ['lng', 'lat'],
data: [[116.37187, 39.9769], [116.47187, 40.0769], [116.57187, 40.1769], [116.67187, 40.2769], [116.77187, 40.3769], [116.87187, 40.4769], [116.97187, 40.5769], [117.07187, 40.6769], [117.17187, 40.7769], [117.27187, 40.8769], [117.37187, 40.9769], [117.47187, 41.0769], [117.57187, 41.1769], [117.67187, 41.2769], [117.77187, 41.3769], [117.87187, 41.4769], [117.97187, 41.5769], [118.07187, 41.6769], [118.17187, 41.7769], [118.27187, 41.8769], [118.37187, 41.9769], [118.47187, 42.0769], [118.57187, 42.1769], [118.67187, 42.2769], [118.77187, 42.3769], [118.87187, 42.4769], [118.97187, 42.5769], [119.07187, 42.6769], [119.17187, 42.7769], [119.27187, 42.8769], [119.37187, 42.9769], [119.47187, 43.0769], [119.57187, 43.1769], [119.67187, 43.2769], [119.77187, 43.3769], [119.87187, 43.4769], [119.97187, 43.5769], [120.07187, 43.6769], [120.17187, 43.7769], [120.27187, 43.8769], [120.37187, 43.9769], [120.47187, 44.0769], [120.57187, 44.1769], [120.67187, 44.2769], [120.77187, 44.3769], [120.87187, 44.4769], [120.97187, 44.5769], [121.07187, 44.6769], [121.17187, 44.7769], [121.27187, 44.8769], [121.37187, 44.9769], [121.47187, 45.0769], [121.57187, 45.1769], [121.67187, 45.2769], [121.77187, 45.3769], [121.87187, 45.4769], [121.97187, 45.5769], [122.07187, 45.6769], [122.17187, 45.7769], [122.27187, 45.8769], [122.37187, 45.9769], [122.47187, 46.0769], [122.57187, 46.1769], [122.67187, 46.2769], [122.77187, 46.3769], [122.87187, 46.4769], [122.97187, 46.5769], [123.07187, 46.6769], [123.17187, 46.7769], [123.27187, 46.8769], [123.37187, 46.9769], [123.47187, 47.0769], [123.57187, 47.1769], [123.67187, 47.2769], [123.77187, 47.3769], [123.87187, 47.4769], [123.97187, 47.5769], [124.07187, 47.6769], [124.17187, 47.7769], [124.27187, 47.8769], [124.37187, 47.9769], [124.47187, 48.0769], [124.57187, 48.1769], [124.67187, 48.2769], [124.77187, 48.3769], [124.87187, 48.4769], [124.97187, 48.5769], [125.07187, 48.6769], [125.17187, 48.7769], [125.27187, 48.8769], [125.37187, 48.9769], [125.47187, 49.0769], [125.57187, 49.1769], [125.67187, 49.2769], [125.77187, 49.3769], [125.87187, 49.4769], [125.97187, 49.5769], [126.07187, 49.6769], [126.17187, 49.7769], [126.27187, 49.8769]]
}]
};
mapScatter.setOption(option);
});
看散点效果，有一道黄色的斜线，看到了吗？
image.png
总结
采用百度地图会调用api、渲染、加载、还有配额等等，有点繁琐。
采用地图文件比较简洁，就是显示的地图信息很少，就一些轮廓。
第一个例子是scatter基于bmap，第二个例子是scatterGL基于map文件；我觉得换一下也是可以的，读者可以尝试。
