【Python】【Web.py】python调用html【问题：echart图标调用html上未显示】
code调用123.html和echarts.min.js文件
code.py
import web
import execjs urls = (
'/hello', 'hello',
)
app = web.application(urls, globals()) class hello:
def GET(self):
jsstr = get_js()
ctx = execjs.compile(jsstr) # 加载JS文件
return open('123.html', encoding='utf-8') ''''''
def get_js():
f = open("echarts.min.js", 'r', encoding='utf-8') # 打开JS文件
line = f.readline()
htmlstr = ''
while line:
htmlstr = htmlstr+line
line = f.readline()
return htmlstr if __name__ == "__main__":
app.run()
同目录下放123.html
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<title>小屁琦</title>
<script type="text/javascript" src='echarts.min.js'></script>
<link href="https://cdn.bootcss.com/bootstrap/3.3.7/css/bootstrap.min.css" rel="stylesheet"> <!-- 可选的Bootstrap主题文件（一般不使用） -->
<!-- <script src="https://cdn.bootcss.com/bootstrap/3.3.7/css/bootstrap-theme.min.css"></script>--> <!-- jQuery文件。务必在bootstrap.min.js 之前引入 -->
<script src="https://cdn.bootcss.com/jquery/2.1.1/jquery.min.js"></script> <!-- 最新的 Bootstrap 核心 JavaScript 文件 -->
<script src="https://cdn.bootcss.com/bootstrap/3.3.7/js/bootstrap.min.js"></script> <body> <div class="container">
<div class="row clearfix">
<div class="col-md-12 column">
<nav class="navbar navbar-default" role="navigation">
<div class="navbar-header">
<button type="button" class="navbar-toggle" data-toggle="collapse" data-target="#bs-example-navbar-collapse-1"> <span class="sr-only">Toggle navigation</span><span class="icon-bar"></span><span class="icon-bar"></span><span class="icon-bar"></span></button> <a class="navbar-brand" href="#">Brand</a>
</div> <div class="collapse navbar-collapse" id="bs-example-navbar-collapse-1">
<ul class="nav navbar-nav">
<li class="active">
<a href="#">Link</a>
</li>
<li>
<a href="#">Link</a>
</li>
<li class="dropdown">
<a href="#" class="dropdown-toggle" data-toggle="dropdown">Dropdown<strong class="caret"></strong></a>
<ul class="dropdown-menu">
<li>
<a href="#">Action</a>
</li>
<li>
<a href="#">Another action</a>
</li>
<li>
<a href="#">Something else here</a>
</li>
<li class="divider">
</li>
<li>
<a href="#">Separated link</a>
</li>
<li class="divider">
</li>
<li>
<a href="#">One more separated link</a>
</li>
</ul>
</li>
</ul>
<form class="navbar-form navbar-left" role="search">
<div class="form-group">
<input type="text" class="form-control" />
</div> <button type="submit" class="btn btn-default">Submit</button>
</form>
<ul class="nav navbar-nav navbar-right">
<li>
<a href="#">Link</a>
</li>
<li class="dropdown">
<a href="#" class="dropdown-toggle" data-toggle="dropdown">Dropdown<strong class="caret"></strong></a>
<ul class="dropdown-menu">
<li>
<a href="#">Action</a>
</li>
<li>
<a href="#">Another action</a>
</li>
<li>
<a href="#">Something else here</a>
</li>
<li class="divider">
</li>
<li>
<a href="#">Separated link</a>
</li>
</ul>
</li>
</ul>
</div> </nav>
<div class="jumbotron">
<h1>
Hello, 小郭琦!
</h1>
<p>
你干啥那
</p>
<p>
<a class="btn btn-primary btn-large" href="#">Learn more</a>
</p>
</div>
<table class="table">
<thead>
<tr>
<th>
编号
</th>
<th>
产品
</th>
<th>
交付时间
</th>
<th>
状态
</th>
</tr>
</thead>
<tbody>
<tr>
<td>
1
</td>
<td>
TB - Monthly
</td>
<td>
01/04/2012
</td>
<td>
Default
</td>
</tr>
<tr class="success">
<td>
1
</td>
<td>
TB - Monthly
</td>
<td>
01/04/2012
</td>
<td>
Approved
</td>
</tr>
<tr class="error">
<td>
2
</td>
<td>
TB - Monthly
</td>
<td>
02/04/2012
</td>
<td>
Declined
</td>
</tr>
<tr class="warning">
<td>
3
</td>
<td>
TB - Monthly
</td>
<td>
03/04/2012
</td>
<td>
Pending
</td>
</tr>
<tr class="info">
<td>
4
</td>
<td>
TB - Monthly
</td>
<td>
04/04/2012
</td>
<td>
Call in to confirm
</td>
</tr>
</tbody>
</table>
</div>
</div>
<div class="row clearfix">
<div class="col-md-12 column">
<ul class="pagination">
<li>
<a href="#">Prev</a>
</li>
<li>
<a href="#">1</a>
</li>
<li>
<a href="#">2</a>
</li>
<li>
<a href="#">3</a>
</li>
<li>
<a href="#">4</a>
</li>
<li>
<a href="#">5</a>
</li>
<li>
<a href="#">Next</a>
</li>
</ul>
</div>
</div>
<div class="row clearfix">
<div class="col-md-6 column">
<div id="chart1" style="width:480px;height:480px;margin-top:60px"></div>
</div>
<div class="col-md-6 column">
<div id="chart2" style="width:600px;height:600px;"></div>
</div>
</div>
<div class="row clearfix">
<div class="col-md-6 column">
<div id="chart4" style="width:550px;height:480px;margin-top:60px"></div>
</div>
<div class="col-md-6 column">
<div id="chart3" style="width:600px;height:480px;margin-top:60px"></div>
</div>
</div>
</div>
</body>
<script type="text/javascript">
// 初始化图表标签
var myChart1 = echarts.init(document.getElementById('chart1'));
var options1 ={
backgroundColor: '#2c343c', title: {
text: 'Customized Pie',
left: 'center',
top: 20,
textStyle: {
color: '#ccc'
}
}, tooltip : {
trigger: 'item',
formatter: "{a} <br/>{b} : {c} ({d}%)"
}, visualMap: {
show: false,
min: 80,
max: 600,
inRange: {
colorLightness: [0, 1]
}
},
series : [
{
name:'访问来源',
type:'pie',
radius : '55%',
center: ['50%', '50%'],
data:[
{value:335, name:'直接访问'},
{value:310, name:'邮件营销'},
{value:274, name:'联盟广告'},
{value:235, name:'视频广告'},
{value:400, name:'搜索引擎'}
].sort(function (a, b) { return a.value - b.value; }),
roseType: 'radius',
label: {
normal: {
textStyle: {
color: 'rgba(255, 255, 255, 0.3)'
}
}
},
labelLine: {
normal: {
lineStyle: {
color: 'rgba(255, 255, 255, 0.3)'
},
smooth: 0.2,
length: 10,
length2: 20
}
},
itemStyle: {
normal: {
color: '#c23531',
shadowBlur: 200,
shadowColor: 'rgba(0, 0, 0, 0.5)'
}
}, animationType: 'scale',
animationEasing: 'elasticOut',
animationDelay: function (idx) {
return Math.random() * 200;
}
}
]
};
myChart1.setOption(options1); var myChart2 = echarts.init(document.getElementById('chart2'));
var options2 ={
title : {
text: '某地区蒸发量和降水量',
subtext: '纯属虚构'
},
tooltip : {
trigger: 'axis'
},
legend: {
data:['蒸发量','降水量']
},
toolbox: {
show : true,
feature : {
dataView : {show: true, readOnly: false},
magicType : {show: true, type: ['line', 'bar']},
restore : {show: true},
saveAsImage : {show: true}
}
},
calculable : true,
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']
}
],
yAxis : [
{
type : 'value'
}
],
series : [
{
name:'蒸发量',
type:'bar',
data:[2.0, 4.9, 7.0, 23.2, 25.6, 76.7, 135.6, 162.2, 32.6, 20.0, 6.4, 3.3],
markPoint : {
data : [
{type : 'max', name: '最大值'},
{type : 'min', name: '最小值'}
]
},
markLine : {
data : [
{type : 'average', name: '平均值'}
]
}
},
{
name:'降水量',
type:'bar',
data:[2.6, 5.9, 9.0, 26.4, 28.7, 70.7, 175.6, 182.2, 48.7, 18.8, 6.0, 2.3],
markPoint : {
data : [
{name : '年最高', value : 182.2, xAxis: 7, yAxis: 183},
{name : '年最低', value : 2.3, xAxis: 11, yAxis: 3}
]
},
markLine : {
data : [
{type : 'average', name : '平均值'}
]
}
}
]
};
myChart2.setOption(options2); var myChart3 = echarts.init(document.getElementById('chart3'));
var options3 ={
title: {
text: '折线图堆叠'
},
tooltip: {
trigger: 'axis'
},
legend: {
data:['邮件营销','联盟广告','视频广告','直接访问','搜索引擎']
},
grid: {
left: '3%',
right: '4%',
bottom: '3%',
containLabel: true
},
toolbox: {
feature: {
saveAsImage: {}
}
},
xAxis: {
type: 'category',
boundaryGap: false,
data: ['周一','周二','周三','周四','周五','周六','周日']
},
yAxis: {
type: 'value'
},
series: [
{
name:'邮件营销',
type:'line',
stack: '总量',
data:[120, 132, 101, 134, 90, 230, 210]
},
{
name:'联盟广告',
type:'line',
stack: '总量',
data:[220, 182, 191, 234, 290, 330, 310]
},
{
name:'视频广告',
type:'line',
stack: '总量',
data:[150, 232, 201, 154, 190, 330, 410]
},
{
name:'直接访问',
type:'line',
stack: '总量',
data:[320, 332, 301, 334, 390, 330, 320]
},
{
name:'搜索引擎',
type:'line',
stack: '总量',
data:[820, 932, 901, 934, 1290, 1330, 1320]
}
]
};
myChart3.setOption(options3); var myChart4 = echarts.init(document.getElementById('chart4'));
var options4 = {
title : {
text: '男性女性身高体重分布',
subtext: '抽样调查来自: Heinz 2003'
},
grid: {
left: '3%',
right: '7%',
bottom: '3%',
containLabel: true
},
tooltip : {
// trigger: 'axis',
showDelay : 0,
formatter : function (params) {
if (params.value.length > 1) {
return params.seriesName + ' :<br/>'
+ params.value[0] + 'cm '
+ params.value[1] + 'kg ';
}
else {
return params.seriesName + ' :<br/>'
+ params.name + ' : '
+ params.value + 'kg ';
}
},
axisPointer:{
show: true,
type : 'cross',
lineStyle: {
type : 'dashed',
width : 1
}
}
},
toolbox: {
feature: {
dataZoom: {},
brush: {
type: ['rect', 'polygon', 'clear']
}
}
},
brush: {
},
legend: {
data: ['女性','男性'],
left: 'center'
},
xAxis : [
{
type : 'value',
scale:true,
axisLabel : {
formatter: '{value} cm'
},
splitLine: {
show: false
}
}
],
yAxis : [
{
type : 'value',
scale:true,
axisLabel : {
formatter: '{value} kg'
},
splitLine: {
show: false
}
}
],
series : [
{
name:'女性',
type:'scatter',
data: [[161.2, 51.6], [167.5, 59.0], [159.5, 49.2], [157.0, 63.0], [155.8, 53.6],
[170.0, 59.0], [159.1, 47.6], [166.0, 69.8], [176.2, 66.8], [160.2, 75.2],
[172.5, 55.2], [170.9, 54.2], [172.9, 62.5], [153.4, 42.0], [160.0, 50.0],
[147.2, 49.8], [168.2, 49.2], [175.0, 73.2], [157.0, 47.8], [167.6, 68.8],
[159.5, 50.6], [175.0, 82.5], [166.8, 57.2], [176.5, 87.8], [170.2, 72.8],
[174.0, 54.5], [173.0, 59.8], [179.9, 67.3], [170.5, 67.8], [160.0, 47.0],
[154.4, 46.2], [162.0, 55.0], [176.5, 83.0], [160.0, 54.4], [152.0, 45.8],
[162.1, 53.6], [170.0, 73.2], [160.2, 52.1], [161.3, 67.9], [166.4, 56.6],
[168.9, 62.3], [163.8, 58.5], [167.6, 54.5], [160.0, 50.2], [161.3, 60.3],
[167.6, 58.3], [165.1, 56.2], [160.0, 50.2], [170.0, 72.9], [157.5, 59.8],
[167.6, 61.0], [160.7, 69.1], [163.2, 55.9], [152.4, 46.5], [157.5, 54.3],
[168.3, 54.8], [180.3, 60.7], [165.5, 60.0], [165.0, 62.0], [164.5, 60.3],
[156.0, 52.7], [160.0, 74.3], [163.0, 62.0], [165.7, 73.1], [161.0, 80.0],
[162.0, 54.7], [166.0, 53.2], [174.0, 75.7], [172.7, 61.1], [167.6, 55.7],
[151.1, 48.7], [164.5, 52.3], [163.5, 50.0], [152.0, 59.3], [169.0, 62.5],
[164.0, 55.7], [161.2, 54.8], [155.0, 45.9], [170.0, 70.6], [176.2, 67.2],
[170.0, 69.4], [162.5, 58.2], [170.3, 64.8], [164.1, 71.6], [169.5, 52.8],
[163.2, 59.8], [154.5, 49.0], [159.8, 50.0], [173.2, 69.2], [170.0, 55.9],
[161.4, 63.4], [169.0, 58.2], [166.2, 58.6], [159.4, 45.7], [162.5, 52.2],
[159.0, 48.6], [162.8, 57.8], [159.0, 55.6], [179.8, 66.8], [162.9, 59.4],
[161.0, 53.6], [151.1, 73.2], [168.2, 53.4], [168.9, 69.0], [173.2, 58.4],
[171.8, 56.2], [178.0, 70.6], [164.3, 59.8], [163.0, 72.0], [168.5, 65.2],
[166.8, 56.6], [172.7, 105.2], [163.5, 51.8], [169.4, 63.4], [167.8, 59.0],
[159.5, 47.6], [167.6, 63.0], [161.2, 55.2], [160.0, 45.0], [163.2, 54.0],
[162.2, 50.2], [161.3, 60.2], [149.5, 44.8], [157.5, 58.8], [163.2, 56.4],
[172.7, 62.0], [155.0, 49.2], [156.5, 67.2], [164.0, 53.8], [160.9, 54.4],
[162.8, 58.0], [167.0, 59.8], [160.0, 54.8], [160.0, 43.2], [168.9, 60.5],
[158.2, 46.4], [156.0, 64.4], [160.0, 48.8], [167.1, 62.2], [158.0, 55.5],
[167.6, 57.8], [156.0, 54.6], [162.1, 59.2], [173.4, 52.7], [159.8, 53.2],
[170.5, 64.5], [159.2, 51.8], [157.5, 56.0], [161.3, 63.6], [162.6, 63.2],
[160.0, 59.5], [168.9, 56.8], [165.1, 64.1], [162.6, 50.0], [165.1, 72.3],
[166.4, 55.0], [160.0, 55.9], [152.4, 60.4], [170.2, 69.1], [162.6, 84.5],
[170.2, 55.9], [158.8, 55.5], [172.7, 69.5], [167.6, 76.4], [162.6, 61.4],
[167.6, 65.9], [156.2, 58.6], [175.2, 66.8], [172.1, 56.6], [162.6, 58.6],
[160.0, 55.9], [165.1, 59.1], [182.9, 81.8], [166.4, 70.7], [165.1, 56.8],
[177.8, 60.0], [165.1, 58.2], [175.3, 72.7], [154.9, 54.1], [158.8, 49.1],
[172.7, 75.9], [168.9, 55.0], [161.3, 57.3], [167.6, 55.0], [165.1, 65.5],
[175.3, 65.5], [157.5, 48.6], [163.8, 58.6], [167.6, 63.6], [165.1, 55.2],
[165.1, 62.7], [168.9, 56.6], [162.6, 53.9], [164.5, 63.2], [176.5, 73.6],
[168.9, 62.0], [175.3, 63.6], [159.4, 53.2], [160.0, 53.4], [170.2, 55.0],
[162.6, 70.5], [167.6, 54.5], [162.6, 54.5], [160.7, 55.9], [160.0, 59.0],
[157.5, 63.6], [162.6, 54.5], [152.4, 47.3], [170.2, 67.7], [165.1, 80.9],
[172.7, 70.5], [165.1, 60.9], [170.2, 63.6], [170.2, 54.5], [170.2, 59.1],
[161.3, 70.5], [167.6, 52.7], [167.6, 62.7], [165.1, 86.3], [162.6, 66.4],
[152.4, 67.3], [168.9, 63.0], [170.2, 73.6], [175.2, 62.3], [175.2, 57.7],
[160.0, 55.4], [165.1, 104.1], [174.0, 55.5], [170.2, 77.3], [160.0, 80.5],
[167.6, 64.5], [167.6, 72.3], [167.6, 61.4], [154.9, 58.2], [162.6, 81.8],
[175.3, 63.6], [171.4, 53.4], [157.5, 54.5], [165.1, 53.6], [160.0, 60.0],
[174.0, 73.6], [162.6, 61.4], [174.0, 55.5], [162.6, 63.6], [161.3, 60.9],
[156.2, 60.0], [149.9, 46.8], [169.5, 57.3], [160.0, 64.1], [175.3, 63.6],
[169.5, 67.3], [160.0, 75.5], [172.7, 68.2], [162.6, 61.4], [157.5, 76.8],
[176.5, 71.8], [164.4, 55.5], [160.7, 48.6], [174.0, 66.4], [163.8, 67.3]
],
markArea: {
silent: true,
itemStyle: {
normal: {
color: 'transparent',
borderWidth: 1,
borderType: 'dashed'
}
},
data: [[{
name: '女性分布区间',
xAxis: 'min',
yAxis: 'min'
}, {
xAxis: 'max',
yAxis: 'max'
}]]
},
markPoint : {
data : [
{type : 'max', name: '最大值'},
{type : 'min', name: '最小值'}
]
},
markLine : {
lineStyle: {
normal: {
type: 'solid'
}
},
data : [
{type : 'average', name: '平均值'},
{ xAxis: 160 }
]
}
},
{
name:'男性',
type:'scatter',
data: [[174.0, 65.6], [175.3, 71.8], [193.5, 80.7], [186.5, 72.6], [187.2, 78.8],
[181.5, 74.8], [184.0, 86.4], [184.5, 78.4], [175.0, 62.0], [184.0, 81.6],
[180.0, 76.6], [177.8, 83.6], [192.0, 90.0], [176.0, 74.6], [174.0, 71.0],
[184.0, 79.6], [192.7, 93.8], [171.5, 70.0], [173.0, 72.4], [176.0, 85.9],
[176.0, 78.8], [180.5, 77.8], [172.7, 66.2], [176.0, 86.4], [173.5, 81.8],
[178.0, 89.6], [180.3, 82.8], [180.3, 76.4], [164.5, 63.2], [173.0, 60.9],
[183.5, 74.8], [175.5, 70.0], [188.0, 72.4], [189.2, 84.1], [172.8, 69.1],
[170.0, 59.5], [182.0, 67.2], [170.0, 61.3], [177.8, 68.6], [184.2, 80.1],
[186.7, 87.8], [171.4, 84.7], [172.7, 73.4], [175.3, 72.1], [180.3, 82.6],
[182.9, 88.7], [188.0, 84.1], [177.2, 94.1], [172.1, 74.9], [167.0, 59.1],
[169.5, 75.6], [174.0, 86.2], [172.7, 75.3], [182.2, 87.1], [164.1, 55.2],
[163.0, 57.0], [171.5, 61.4], [184.2, 76.8], [174.0, 86.8], [174.0, 72.2],
[177.0, 71.6], [186.0, 84.8], [167.0, 68.2], [171.8, 66.1], [182.0, 72.0],
[167.0, 64.6], [177.8, 74.8], [164.5, 70.0], [192.0, 101.6], [175.5, 63.2],
[171.2, 79.1], [181.6, 78.9], [167.4, 67.7], [181.1, 66.0], [177.0, 68.2],
[174.5, 63.9], [177.5, 72.0], [170.5, 56.8], [182.4, 74.5], [197.1, 90.9],
[180.1, 93.0], [175.5, 80.9], [180.6, 72.7], [184.4, 68.0], [175.5, 70.9],
[180.6, 72.5], [177.0, 72.5], [177.1, 83.4], [181.6, 75.5], [176.5, 73.0],
[175.0, 70.2], [174.0, 73.4], [165.1, 70.5], [177.0, 68.9], [192.0, 102.3],
[176.5, 68.4], [169.4, 65.9], [182.1, 75.7], [179.8, 84.5], [175.3, 87.7],
[184.9, 86.4], [177.3, 73.2], [167.4, 53.9], [178.1, 72.0], [168.9, 55.5],
[157.2, 58.4], [180.3, 83.2], [170.2, 72.7], [177.8, 64.1], [172.7, 72.3],
[165.1, 65.0], [186.7, 86.4], [165.1, 65.0], [174.0, 88.6], [175.3, 84.1],
[185.4, 66.8], [177.8, 75.5], [180.3, 93.2], [180.3, 82.7], [177.8, 58.0],
[177.8, 79.5], [177.8, 78.6], [177.8, 71.8], [177.8, 116.4], [163.8, 72.2],
[188.0, 83.6], [198.1, 85.5], [175.3, 90.9], [166.4, 85.9], [190.5, 89.1],
[166.4, 75.0], [177.8, 77.7], [179.7, 86.4], [172.7, 90.9], [190.5, 73.6],
[185.4, 76.4], [168.9, 69.1], [167.6, 84.5], [175.3, 64.5], [170.2, 69.1],
[190.5, 108.6], [177.8, 86.4], [190.5, 80.9], [177.8, 87.7], [184.2, 94.5],
[176.5, 80.2], [177.8, 72.0], [180.3, 71.4], [171.4, 72.7], [172.7, 84.1],
[172.7, 76.8], [177.8, 63.6], [177.8, 80.9], [182.9, 80.9], [170.2, 85.5],
[167.6, 68.6], [175.3, 67.7], [165.1, 66.4], [185.4, 102.3], [181.6, 70.5],
[172.7, 95.9], [190.5, 84.1], [179.1, 87.3], [175.3, 71.8], [170.2, 65.9],
[193.0, 95.9], [171.4, 91.4], [177.8, 81.8], [177.8, 96.8], [167.6, 69.1],
[167.6, 82.7], [180.3, 75.5], [182.9, 79.5], [176.5, 73.6], [186.7, 91.8],
[188.0, 84.1], [188.0, 85.9], [177.8, 81.8], [174.0, 82.5], [177.8, 80.5],
[171.4, 70.0], [185.4, 81.8], [185.4, 84.1], [188.0, 90.5], [188.0, 91.4],
[182.9, 89.1], [176.5, 85.0], [175.3, 69.1], [175.3, 73.6], [188.0, 80.5],
[188.0, 82.7], [175.3, 86.4], [170.5, 67.7], [179.1, 92.7], [177.8, 93.6],
[175.3, 70.9], [182.9, 75.0], [170.8, 93.2], [188.0, 93.2], [180.3, 77.7],
[177.8, 61.4], [185.4, 94.1], [168.9, 75.0], [185.4, 83.6], [180.3, 85.5],
[174.0, 73.9], [167.6, 66.8], [182.9, 87.3], [160.0, 72.3], [180.3, 88.6],
[167.6, 75.5], [186.7, 101.4], [175.3, 91.1], [175.3, 67.3], [175.9, 77.7],
[175.3, 81.8], [179.1, 75.5], [181.6, 84.5], [177.8, 76.6], [182.9, 85.0],
[177.8, 102.5], [184.2, 77.3], [179.1, 71.8], [176.5, 87.9], [188.0, 94.3],
[174.0, 70.9], [167.6, 64.5], [170.2, 77.3], [167.6, 72.3], [188.0, 87.3],
[174.0, 80.0], [176.5, 82.3], [180.3, 73.6], [167.6, 74.1], [188.0, 85.9],
[180.3, 73.2], [167.6, 76.3], [183.0, 65.9], [183.0, 90.9], [179.1, 89.1],
[170.2, 62.3], [177.8, 82.7], [179.1, 79.1], [190.5, 98.2], [177.8, 84.1],
[180.3, 83.2], [180.3, 83.2]
],
markArea: {
silent: true,
itemStyle: {
normal: {
color: 'transparent',
borderWidth: 1,
borderType: 'dashed'
}
},
data: [[{
name: '男性分布区间',
xAxis: 'min',
yAxis: 'min'
}, {
xAxis: 'max',
yAxis: 'max'
}]]
},
markPoint : {
data : [
{type : 'max', name: '最大值'},
{type : 'min', name: '最小值'}
]
},
markLine : {
lineStyle: {
normal: {
type: 'solid'
}
},
data : [
{type : 'average', name: '平均值'},
{ xAxis: 170 }
]
}
}
]
}; myChart4.setOption(options4); </script>
</html>
同目录下放 echarts.min.js文件
-------------------------------------------------------------------------------------------------------------
运行效果：
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