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kailai 2022-01-11 16:39:58 +08:00
parent e71dade89a
commit 7c1d8f095f
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# personalTravelMap
# Python之绘制个人足迹地图
前两年，足迹地图小程序风靡朋友圈，一时间大家都流行晒自己的旅行地图。但是，笔者最近体验了好几款足迹地图的小程序，发现这些小程序虽然号称是足迹地图，但最多只是展示到省级别，无法精确到市级别，因此，笔者周末花了点时间，用Python来绘制自己的个人足迹地图，可以精确到市级别。
  下面的部分，笔者将介绍如何简单地来绘制个人足迹地图。
  首先我们需要安装以下Python的第三方模块:
```python
echarts-china-cities-pypkg==0.0.9
echarts-china-provinces-pypkg==0.0.3
pyecharts==1.6.2
PyYAML==5.3.1
```
本项目的完整结构如下：
![完整的项目结构](https://img-blog.csdnimg.cn/20200531105908178.png?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2pjbGlhbjkx,size_16,color_FFFFFF,t_70)
我们在项目中采用YAML文件来配置自己旅行过的省以及省下面的市，笔者的配置文件如下：
```tcl
北京:
- 延庆区
- 昌平区
- 海淀区
- 东城区
- 西城区
- 大兴区
- 朝阳区
上海:
- 嘉定区
- 青浦区
- 松江区
- 宝山区
- 闵行区
- 奉贤区
- 浦东新区
- 崇明区
- 徐汇区
- 黄浦区
- 静安区
- 杨浦区
- 虹口区
- 金山区
- 长宁区
- 普陀区
天津:
- 滨海新区
- 南开区
- 河西区
- 和平区
河北:
- 保定市
- 廊坊市
山东:
- 烟台市
- 青岛市
江苏:
- 南京市
- 苏州市
- 扬州市
- 镇江市
- 无锡市
浙江:
- 杭州市
- 绍兴市
- 宁波市
- 舟山市
- 湖州市
- 嘉兴市
- 台州市
- 金华市
江西:
- 南昌市
- 九江市
安徽:
- 黄山市
湖北:
- 武汉市
湖南:
- 长沙市
海南:
- 海口市
- 三亚市
四川:
- 成都市
广东:
- 湛江市
```
接着我们利用Python脚本来生成足迹地图。先是全国地图，用于显示省和直辖市的情况，`china_map.py`的代码如下：
```python
# -*- coding: utf-8 -*-
# author: Jclian91
# place: Pudong Shanghai
# time: 2020/5/31 9:21 上午
# 绘制个人足迹地图：全国范围
import yaml
from pyecharts.charts import Map
from pyecharts import options as opts
# 省和直辖市
with open("travel_config.yml", 'r', encoding='utf-8') as ymlfile:
province_city_dict = yaml.safe_load(ymlfile)
province_dict = dict(zip(province_city_dict.keys(), [1]*len(province_city_dict.keys())))
print(province_dict)
# maptype='china' 只显示全国直辖市和省级
map = Map(init_opts=opts.InitOpts(width='1200px', height='800px'))
map.set_global_opts(
title_opts=opts.TitleOpts(title="个人足迹地图"),
visualmap_opts=opts.VisualMapOpts(max_=1, is_piecewise=True,
pieces=[
{"max": 1, "min": 1, "label": "去过", "color": "#4EA397"},
{"max": 0, "min": 0, "label": "未去过", "color": "#FFFFFF"},
]) #最大数据范围，分段
)
map.add("个人足迹地图", data_pair=province_dict.items(), maptype="china", is_roam=True)
map.render('全国.html')
```
运行上述脚本，会生成`全国.html`。为了保证图片居中显示，我们对该HTML中的下面一行：
```html
<div id="a438407081634ceab6af1c965034ae16" class="chart-container" style="width:1200px; height:800px;"></div>
```
的样式（style）增加如下内容：
```html
margin:auto;top:30px
```
全国范围的足迹地图效果图如下：
![个人足迹地图——全国](https://img-blog.csdnimg.cn/20200531110511512.png?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2pjbGlhbjkx,size_16,color_FFFFFF,t_70#pic_center)
接着，我们来生成每个省市的足迹地图，利用`province_map.py`脚本，代码如下：
```python
# -*- coding: utf-8 -*-
# author: Jclian91
# place: Pudong Shanghai
# time: 2020/5/31 10:01 上午
# 绘制个人足迹地图：省市范围
import yaml
from pyecharts.charts import Map
from pyecharts import options as opts
# 省和直辖市下面的市
with open("travel_config.yml", 'r', encoding='utf-8') as ymlfile:
province_city_dict = yaml.safe_load(ymlfile)
for province, cities in province_city_dict.items():
map = Map(init_opts=opts.InitOpts(width='1200px', height='800px'))
map.set_global_opts(
title_opts=opts.TitleOpts(title="个人足迹地图-%s" % province),
visualmap_opts=opts.VisualMapOpts(max_=1, is_piecewise=True,
pieces=[
{"max": 1, "min": 1, "label": "去过", "color": "#4EA397"},
{"max": 0, "min": 0, "label": "未去过", "color": "#FFFFFF"},
]) #最大数据范围，分段
)
city_dict = dict(zip(cities, [1]*len(cities)))
map.add("个人足迹地图-%s" % province, data_pair=city_dict.items(), maptype=province, is_roam=True)
map.render('./provinces/%s.html' % province)
print("生成个人足迹地图-%s 成功" % province)
```
这时，会在`provinces`目录下生成每个省或者直辖市的足迹地图，我们分别对每个HTML进行修改，保证图片居中。我们在这里只展示三个省市的情况：
![个人足迹地区——海南](https://img-blog.csdnimg.cn/20200531110800239.png?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2pjbGlhbjkx,size_16,color_FFFFFF,t_70#pic_center)
![个人足迹地图——江苏](https://img-blog.csdnimg.cn/20200531110819229.png?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2pjbGlhbjkx,size_16,color_FFFFFF,t_70#pic_center)
![个人足迹地图——浙江](https://img-blog.csdnimg.cn/20200531110836218.png?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2pjbGlhbjkx,size_16,color_FFFFFF,t_70#pic_center)
最后一步，也是最为关键的一步，就是我们要打通全国足迹地图和每个省市足迹地图的联系，也就是说，我们点击全国足迹地图上去过的省份，那么可以点击进去查看该省市下的足迹地图情况，比如说去过哪些市。
  对此，我们修改生成的全国.html文件，假设该地图的图像句柄为chart_a438407081634ceab6af1c965034ae16，那么在最后的<script>对中添加内容如下：（确保点击去过的省份，可以查看该省市的足迹地图）
```html
chart_a438407081634ceab6af1c965034ae16.on('click', function (param){
var selected = param.name;
if (selected) {
switch(selected){
case '北京':
location.href = "provinces/北京.html";
break;
case '上海':
location.href = "provinces/上海.html";
break;
case '天津':
location.href = "provinces/天津.html";
break;
case '四川':
location.href = "provinces/四川.html";
break;
case '安徽':
location.href = "provinces/安徽.html";
break;
case '山东':
location.href = "provinces/山东.html";
break;
case '江苏':
location.href = "provinces/江苏.html";
break;
case '江西':
location.href = "provinces/江西.html";
break;
case '河北':
location.href = "provinces/河北.html";
break;
case '浙江':
location.href = "provinces/浙江.html";
break;
case '海南':
location.href = "provinces/海南.html";
break;
case '湖北':
location.href = "provinces/湖北.html";
break;
case '湖南':
location.href = "provinces/湖南.html";
break;
case '广东':
location.href = "provinces/广东.html";
break;
default:
break;
}
}
});
```
前两年，足迹地图小程序风靡朋友圈，一时间大家都流行晒自己的旅行地图。但是，笔者最近体验了好几款足迹地图的小程序，发现这些小程序虽然号称是足迹地图，但最多只是展示到省级别，无法精确到市级别，因此，笔者周末花了点时间，用Python来绘制自己的个人足迹地图，可以精确到市级别。

28
china_map.py Normal file
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@ -0,0 +1,28 @@
# -*- coding: utf-8 -*-
# author: Jclian91
# place: Pudong Shanghai
# time: 2020/5/31 9:21 上午
# 绘制个人足迹地图：全国范围
import yaml
from pyecharts.charts import Map
from pyecharts import options as opts
# 省和直辖市
with open("travel_config.yml", 'r', encoding='utf-8') as ymlfile:
province_city_dict = yaml.safe_load(ymlfile)
province_dict = dict(zip(province_city_dict.keys(), [1]*len(province_city_dict.keys())))
print(province_dict)
# maptype='china' 只显示全国直辖市和省级
map = Map(init_opts=opts.InitOpts(width='1200px', height='800px'))
map.set_global_opts(
title_opts=opts.TitleOpts(title="个人足迹地图"),
visualmap_opts=opts.VisualMapOpts(max_=1, is_piecewise=True,
pieces=[
{"max": 1, "min": 1, "label": "去过", "color": "#4EA397"},
{"max": 0, "min": 0, "label": "未去过", "color": "#FFFFFF"},
]) #最大数据范围，分段
)
map.add("个人足迹地图", data_pair=province_dict.items(), maptype="china", is_roam=True)
map.render('全国.html')

29
province_map.py Normal file
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@ -0,0 +1,29 @@
# -*- coding: utf-8 -*-
# author: Jclian91
# place: Pudong Shanghai
# time: 2020/5/31 10:01 上午
# 绘制个人足迹地图：省市范围
import yaml
from pyecharts.charts import Map
from pyecharts import options as opts
# 省和直辖市下面的市
with open("travel_config.yml", 'r', encoding='utf-8') as ymlfile:
province_city_dict = yaml.safe_load(ymlfile)
for province, cities in province_city_dict.items():
map = Map(init_opts=opts.InitOpts(width='1200px', height='800px'))
map.set_global_opts(
title_opts=opts.TitleOpts(title="个人足迹地图-%s" % province),
visualmap_opts=opts.VisualMapOpts(max_=1, is_piecewise=True,
pieces=[
{"max": 1, "min": 1, "label": "去过", "color": "#4EA397"},
{"max": 0, "min": 0, "label": "未去过", "color": "#FFFFFF"},
]) #最大数据范围，分段
)
city_dict = dict(zip(cities, [1]*len(cities)))
map.add("个人足迹地图-%s" % province, data_pair=city_dict.items(), maptype=province, is_roam=True)
map.render('./provinces/%s.html' % province)
print("生成个人足迹地图-%s 成功" % province)

205
provinces/上海.html Normal file
View File

@ -0,0 +1,205 @@
<!DOCTYPE html>
<html>
<head>
<meta charset="UTF-8">
<title>Awesome-pyecharts</title>
<script type="text/javascript" src="https://assets.pyecharts.org/assets/echarts.min.js"></script>
<script type="text/javascript" src="https://assets.pyecharts.org/assets/maps/shanghai.js"></script>
</head>
<body>
<div id="a32e71822f104ce38e57b57a8d206341" class="chart-container" style="width:1200px; height:800px;margin:auto;top:30px"></div>
<script>
var chart_a32e71822f104ce38e57b57a8d206341 = echarts.init(
document.getElementById('a32e71822f104ce38e57b57a8d206341'), 'white', {renderer: 'canvas'});
var option_a32e71822f104ce38e57b57a8d206341 = {
"animation": true,
"animationThreshold": 2000,
"animationDuration": 1000,
"animationEasing": "cubicOut",
"animationDelay": 0,
"animationDurationUpdate": 300,
"animationEasingUpdate": "cubicOut",
"animationDelayUpdate": 0,
"color": [
"#c23531",
"#2f4554",
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],
"series": [
{
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"label": {
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"margin": 8
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{
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],
"roam": true,
"zoom": 1,
"showLegendSymbol": true,
"emphasis": {}
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"legend": [
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],
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},
"show": true,
"padding": 5,
"itemGap": 10,
"itemWidth": 25,
"itemHeight": 14
}
],
"tooltip": {
"show": true,
"trigger": "item",
"triggerOn": "mousemove|click",
"axisPointer": {
"type": "line"
},
"textStyle": {
"fontSize": 14
},
"borderWidth": 0
},
"title": [
{
"text": "\u4e2a\u4eba\u8db3\u8ff9\u5730\u56fe-\u4e0a\u6d77",
"padding": 5,
"itemGap": 10
}
],
"visualMap": {
"show": true,
"type": "piecewise",
"min": 0,
"max": 1,
"inRange": {
"color": [
"#50a3ba",
"#eac763",
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"calculable": true,
"inverse": false,
"splitNumber": 5,
"orient": "vertical",
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"itemWidth": 20,
"itemHeight": 14,
"borderWidth": 0,
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{
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chart_a32e71822f104ce38e57b57a8d206341.setOption(option_a32e71822f104ce38e57b57a8d206341);
</script>
</body>
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173
provinces/北京.html Normal file
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@ -0,0 +1,173 @@
<!DOCTYPE html>
<html>
<head>
<meta charset="UTF-8">
<title>Awesome-pyecharts</title>
<script type="text/javascript" src="https://assets.pyecharts.org/assets/echarts.min.js"></script>
<script type="text/javascript" src="https://assets.pyecharts.org/assets/maps/beijing.js"></script>
</head>
<body>
<div id="deba5c2f2abd46fbae2d5a180ccb83ef" class="chart-container" style="width:1200px; height:800px;margin:auto;top:30px"></div>
<script>
var chart_deba5c2f2abd46fbae2d5a180ccb83ef = echarts.init(
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</script>
</body>
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145
provinces/四川.html Normal file
View File

@ -0,0 +1,145 @@
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<html>
<head>
<meta charset="UTF-8">
<title>Awesome-pyecharts</title>
<script type="text/javascript" src="https://assets.pyecharts.org/assets/echarts.min.js"></script>
<script type="text/javascript" src="https://assets.pyecharts.org/assets/maps/sichuan.js"></script>
</head>
<body>
<div id="10e7f81aeef542d5a61e169ba019356c" class="chart-container" style="width:1200px; height:800px;margin:auto;top:30px"></div>
<script>
var chart_10e7f81aeef542d5a61e169ba019356c = echarts.init(
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var option_10e7f81aeef542d5a61e169ba019356c = {
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"#fab27b",
"#2a5caa",
"#444693",
"#726930",
"#b2d235",
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"#ac6767",
"#1d953f",
"#6950a1",
"#918597"
],
"series": [
{
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"name": "\u4e2a\u4eba\u8db3\u8ff9\u5730\u56fe-\u56db\u5ddd",
"label": {
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"position": "top",
"margin": 8
},
"mapType": "\u56db\u5ddd",
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"axisPointer": {
"type": "line"
},
"textStyle": {
"fontSize": 14
},
"borderWidth": 0
},
"title": [
{
"text": "\u4e2a\u4eba\u8db3\u8ff9\u5730\u56fe-\u6e56\u5357",
"padding": 5,
"itemGap": 10
}
],
"visualMap": {
"show": true,
"type": "piecewise",
"min": 0,
"max": 1,
"inRange": {
"color": [
"#50a3ba",
"#eac763",
"#d94e5d"
]
},
"calculable": true,
"inverse": false,
"splitNumber": 5,
"orient": "vertical",
"showLabel": true,
"itemWidth": 20,
"itemHeight": 14,
"borderWidth": 0,
"pieces": [
{
"max": 1,
"min": 1,
"label": "\u53bb\u8fc7",
"color": "#4EA397"
},
{
"max": 0,
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"label": "\u672a\u53bb\u8fc7",
"color": "#FFFFFF"
}
]
}
};
chart_9f6b5cb89e8849609beeb81032133299.setOption(option_9f6b5cb89e8849609beeb81032133299);
</script>
</body>
</html>

4
requirements.txt Normal file
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pyecharts==1.6.2
PyYAML==5.3.1
echarts-china-cities-pypkg==0.0.9
echarts-china-provinces-pypkg==0.0.

68
travel_config.yml Normal file
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北京:
- 延庆区
- 昌平区
- 海淀区
- 东城区
- 西城区
- 大兴区
- 朝阳区
- 丰台区
上海:
- 嘉定区
- 青浦区
- 松江区
- 宝山区
- 闵行区
- 奉贤区
- 浦东新区
- 崇明区
- 徐汇区
- 黄浦区
- 静安区
- 杨浦区
- 虹口区
- 金山区
- 长宁区
- 普陀区
天津:
- 滨海新区
- 南开区
- 河西区
- 和平区
河北:
- 保定市
- 廊坊市
山东:
- 烟台市
- 青岛市
江苏:
- 南京市
- 苏州市
- 扬州市
- 镇江市
- 无锡市
浙江:
- 杭州市
- 绍兴市
- 宁波市
- 舟山市
- 湖州市
- 嘉兴市
- 台州市
- 金华市
江西:
- 南昌市
- 九江市
安徽:
- 黄山市
湖北:
- 武汉市
湖南:
- 长沙市
海南:
- 海口市
- 三亚市
四川:
- 成都市
广东:
- 湛江市

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249
全国.html Normal file
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<!DOCTYPE html>
<html>
<head>
<meta charset="UTF-8">
<title>Awesome-pyecharts</title>
<script type="text/javascript" src="https://assets.pyecharts.org/assets/echarts.min.js"></script>
<script type="text/javascript" src="https://assets.pyecharts.org/assets/maps/china.js"></script>
</head>
<body>
<div id="a438407081634ceab6af1c965034ae16" class="chart-container" style="width:1200px; height:800px;margin:auto;top:30px"></div>
<script>
var chart_a438407081634ceab6af1c965034ae16 = echarts.init(
document.getElementById('a438407081634ceab6af1c965034ae16'), 'white', {renderer: 'canvas'});
var option_a438407081634ceab6af1c965034ae16 = {
"animation": true,
"animationThreshold": 2000,
"animationDuration": 1000,
"animationEasing": "cubicOut",
"animationDelay": 0,
"animationDurationUpdate": 300,
"animationEasingUpdate": "cubicOut",
"animationDelayUpdate": 0,
"color": [
"#c23531",
"#2f4554",
"#61a0a8",
"#d48265",
"#749f83",
"#ca8622",
"#bda29a",
"#6e7074",
"#546570",
"#c4ccd3",
"#f05b72",
"#ef5b9c",
"#f47920",
"#905a3d",
"#fab27b",
"#2a5caa",
"#444693",
"#726930",
"#b2d235",
"#6d8346",
"#ac6767",
"#1d953f",
"#6950a1",
"#918597"
],
"series": [
{
"type": "map",
"name": "\u4e2a\u4eba\u8db3\u8ff9\u5730\u56fe",
"label": {
"show": true,
"position": "top",
"margin": 8
},
"mapType": "china",
"data": [
{
"name": "\u5317\u4eac",
"value": 1
},
{
"name": "\u4e0a\u6d77",
"value": 1
},
{
"name": "\u5929\u6d25",
"value": 1
},
{
"name": "\u6cb3\u5317",
"value": 1
},
{
"name": "\u5c71\u4e1c",
"value": 1
},
{
"name": "\u6c5f\u82cf",
"value": 1
},
{
"name": "\u6d59\u6c5f",
"value": 1
},
{
"name": "\u6c5f\u897f",
"value": 1
},
{
"name": "\u5b89\u5fbd",
"value": 1
},
{
"name": "\u6e56\u5317",
"value": 1
},
{
"name": "\u6e56\u5357",
"value": 1
},
{
"name": "\u6d77\u5357",
"value": 1
},
{
"name": "\u56db\u5ddd",
"value": 1
},
{
"name": "\u5e7f\u4e1c",
"value": 1
}
],
"roam": true,
"zoom": 1,
"showLegendSymbol": true,
"emphasis": {}
}
],
"legend": [
{
"data": [
"\u4e2a\u4eba\u8db3\u8ff9\u5730\u56fe"
],
"selected": {
"\u4e2a\u4eba\u8db3\u8ff9\u5730\u56fe": true
},
"show": true,
"padding": 5,
"itemGap": 10,
"itemWidth": 25,
"itemHeight": 14
}
],
"tooltip": {
"show": true,
"trigger": "item",
"triggerOn": "mousemove|click",
"axisPointer": {
"type": "line"
},
"textStyle": {
"fontSize": 14
},
"borderWidth": 0
},
"title": [
{
"text": "\u4e2a\u4eba\u8db3\u8ff9\u5730\u56fe",
"padding": 5,
"itemGap": 10
}
],
"visualMap": {
"show": true,
"type": "piecewise",
"min": 0,
"max": 1,
"inRange": {
"color": [
"#50a3ba",
"#eac763",
"#d94e5d"
]
},
"calculable": true,
"inverse": false,
"splitNumber": 5,
"orient": "vertical",
"showLabel": true,
"itemWidth": 20,
"itemHeight": 14,
"borderWidth": 0,
"pieces": [
{
"max": 1,
"min": 1,
"label": "\u53bb\u8fc7",
"color": "#4EA397"
},
{
"max": 0,
"min": 0,
"label": "\u672a\u53bb\u8fc7",
"color": "#FFFFFF"
}
]
}
};
chart_a438407081634ceab6af1c965034ae16.setOption(option_a438407081634ceab6af1c965034ae16);
chart_a438407081634ceab6af1c965034ae16.on('click', function (param){
var selected = param.name;
if (selected) {
switch(selected){
case '北京':
location.href = "provinces/北京.html";
break;
case '上海':
location.href = "provinces/上海.html";
break;
case '天津':
location.href = "provinces/天津.html";
break;
case '四川':
location.href = "provinces/四川.html";
break;
case '安徽':
location.href = "provinces/安徽.html";
break;
case '山东':
location.href = "provinces/山东.html";
break;
case '江苏':
location.href = "provinces/江苏.html";
break;
case '江西':
location.href = "provinces/江西.html";
break;
case '河北':
location.href = "provinces/河北.html";
break;
case '浙江':
location.href = "provinces/浙江.html";
break;
case '海南':
location.href = "provinces/海南.html";
break;
case '湖北':
location.href = "provinces/湖北.html";
break;
case '湖南':
location.href = "provinces/湖南.html";
break;
case '广东':
location.href = "provinces/广东.html";
break;
default:
break;
}
}
});
</script>
</body>
</html>