<!DOCTYPE HTML>
<html>
<head>
<meta charset="utf-8"><link rel="icon" href="https://jscdn.com.cn/highcharts/images/favicon.ico">
<meta name="viewport" content="width=device-width, initial-scale=1">
<style>
/* css 代码 */
</style>
<script src="https://code.highcharts.com.cn/highcharts/highcharts.js"></script>
<script src="https://code.highcharts.com.cn/highcharts/modules/exporting.js"></script>
<script src="https://code.highcharts.com.cn/highcharts/modules/oldie.js"></script>
<script src="https://img.hcharts.cn/highcharts-plugins/highcharts-zh_CN.js"></script>
</head>
<body>
<div id="container" style="min-width:400px;height:400px"></div>
<script>
// JS 代码
</script>
</body>
</html>
1、基础柱状图
option = {
xAxis: {
type: 'category',
data: ['Mon', 'Tue', 'Wed', 'Thu', 'Fri', 'Sat', 'Sun']
},
yAxis: {
type: 'value'
},
series: [{
data: [120, 200, 150, 80, 70, 110, 130],
type: 'bar'
}]
};
2、基础柱状图
var chart = Highcharts.chart('container',{
chart: {
type: 'column'
},
title: {
text: '月平均降雨量'
},
subtitle: {
text: '数据来源: WorldClimate.com'
},
xAxis: {
categories: [
'一月','二月','三月','四月','五月','六月','七月','八月','九月','十月','十一月','十二月'
],
crosshair: true
},
yAxis: {
min: 0,
title: {
text: '降雨量 (mm)'
}
},
tooltip: {
// head + 每个 point + footer 拼接成完整的 table
headerFormat: '<span style="font-size:10px">{point.key}</span><table>',
pointFormat: '<tr><td style="color:{series.color};padding:0">{series.name}: </td>' +
'<td style="padding:0"><b>{point.y:.1f} mm</b></td></tr>',
footerFormat: '</table>',
shared: true,
useHTML: true
},
plotOptions: {
column: {
borderWidth: 0
}
},
series: [{
name: '东京',
data: [49.9, 71.5, 106.4, 129.2, 144.0, 176.0, 135.6, 148.5, 216.4, 194.1, 95.6, 54.4]
}, {
name: '纽约',
data: [83.6, 78.8, 98.5, 93.4, 106.0, 84.5, 105.0, 104.3, 91.2, 83.5, 106.6, 92.3]
}, {
name: '伦敦',
data: [48.9, 38.8, 39.3, 41.4, 47.0, 48.3, 59.0, 59.6, 52.4, 65.2, 59.3, 51.2]
}, {
name: '柏林',
data: [42.4, 33.2, 34.5, 39.7, 52.6, 75.5, 57.4, 60.4, 47.6, 39.1, 46.8, 51.1]
}]
});
3、基础条形图
var chart = Highcharts.chart('container', {
chart: {
type: 'bar'
},
title: {
text: '各洲不同时间的人口条形图'
},
subtitle: {
text: '数据来源: Wikipedia.org'
},
xAxis: {
categories: ['非洲', '美洲', '亚洲', '欧洲', '大洋洲'],
title: {
text: null
}
},
yAxis: {
min: 0,
title: {
text: '人口总量 (百万)',
align: 'high'
},
labels: {
overflow: 'justify'
}
},
tooltip: {
valueSuffix: ' 百万'
},
plotOptions: {
bar: {
dataLabels: {
enabled: true,
allowOverlap: true // 允许数据标签重叠
}
}
},
legend: {
layout: 'vertical',
align: 'right',
verticalAlign: 'top',
x: -40,
y: 100,
floating: true,
borderWidth: 1,
backgroundColor: ((Highcharts.theme && Highcharts.theme.legendBackgroundColor) || '#FFFFFF'),
shadow: true
},
series: [{
name: '1800 年',
data: [107, 31, 635, 203, 2]
}, {
name: '1900 年',
data: [133, 156, 947, 408, 6]
}, {
name: '2008 年',
data: [973, 914, 4054, 732, 34]
}]
});
4、人口金字塔
var categories = ['0-4', '5-9', '10-14', '15-19',
'20-24', '25-29', '30-34', '35-39', '40-44',
'45-49', '50-54', '55-59', '60-64', '65-69',
'70-74', '75-79', '80-84', '85-89', '90-94',
'95-99', '100 + '];
var chart = Highcharts.chart('container', {
chart: {
type: 'bar'
},
title: {
text: '2015 年德国人口金字塔'
},
subtitle: {
useHTML: true,
text: '数据来源: <a href="http://populationpyramid.net/germany/2015/">1950 ~ 2100 年世界人口金字塔</a>'
},
xAxis: [{
categories: categories,
reversed: false,
labels: {
step: 1
}
}, {
// 显示在右侧的镜像 xAxis （通过 linkedTo 与第一个 xAxis 关联）
opposite: true,
reversed: false,
categories: categories,
linkedTo: 0,
labels: {
step: 1
}
}],
yAxis: {
title: {
text: null
},
labels: {
formatter: function () {
return (Math.abs(this.value) / 1000000) + 'M';
}
},
min: -4000000,
max: 4000000
},
plotOptions: {
series: {
stacking: 'normal'
}
},
tooltip: {
formatter: function () {
return '<b>' + this.series.name + ', age ' + this.point.category + '</b><br/>' +
'人口: ' + Highcharts.numberFormat(Math.abs(this.point.y), 0);
}
},
series: [{
name: '男',
data: [-1746181, -1884428, -2089758, -2222362, -2537431, -2507081, -2443179,
-2664537, -3556505, -3680231, -3143062, -2721122, -2229181, -2227768,
-2176300, -1329968, -836804, -354784, -90569, -28367, -3878]
}, {
name: '女',
data: [1656154, 1787564, 1981671, 2108575, 2403438, 2366003, 2301402, 2519874,
3360596, 3493473, 3050775, 2759560, 2304444, 2426504, 2568938, 1785638,
1447162, 1005011, 330870, 130632, 21208]
}]
});