先上效果图
上海市第六次全国人口普查
全国人口普查一次，不要问我为什么不找，我也没办法，摊手～
思路
申请使用百度地图API密钥
数据准备
分析数据
把地区改编成经纬度
画图
1. 申请使用百度地图API密钥
点击创建应用，应用名称随便取，IP白名单，写自己的本地IP，或者0.0.0.0/0 都可
image.png
点击提交，记住自己的密钥(AK)，后面有用。
2. 数据准备(xlsx格式)
3. 数据分析&4. 把地区改编成经纬度
我用python3.6
import json
from urllib.request import urlopen, quote
import xlrd
# 打开xlsx
book =xlrd.open_workbook("/Users/chengkai/Desktop/file/learn/project/sh_population/sh_population.xlsx")
# 打开sheet1
sh = book.sheet_by_index(0)
# 待拼接的url(不完整的url)
url = 'http://api./geocoder/v2/'
ak = '你自己的密钥'
# 遍历每一行，为什么从1开始呢，因为0是标题行，不需要
for i in range(1, sh.nrows):
# 各个地区前面加上‘上海市’，保证后面检索到的所有经纬度都是上海市的地区，而不是别的省市的
city ='上海市'+sh.cell_value(i,0)
# 取第二列所有人口
population = sh.cell_value(i,1)
# 因为出现中文，所以转换一下格式
add = quote(city)
# 以 json 的格式输出
output = 'json'
# URL 正式拼接，这一句画，下面还会详解解释
uri = url + '?' + 'address=' + add + '&output=' + output + '&ak=' + ak
req = urlopen(uri)
# 传入的字符串，需要解码
res = req.read().decode()
# 写成json 字典的形式
temp = json.loads(res)
# 提取经度
lng = temp['result']['location']['lng']
# 提取纬度
lat = temp['result']['location']['lat']
# 写成新的字典
str_temp = '{"lat":' + str(lat) + ',"lng":' + str(lng) + ',"count":' + str(population) +'},'
print(str_temp)
注释一，url拼接
仔细观察url 不一样的地方就是地区
看到下面的字典知道经纬度是怎么一层层提取了把
image.png
image.png
最后结果
{"lat":31.227203440768868,"lng":121.49607206403445,"count":429891.0},
{"lat":31.213348379555082,"lng":121.48123797847695,"count":248779.0},
{"lat":31.169152089592195,"lng":121.44623500472937,"count":1085130.0},
{"lat":31.213301496813617,"lng":121.3876161086648,"count":690571.0},
{"lat":31.23538080348789,"lng":121.45475555700204,"count":246788.0},
{"lat":31.263742929075534,"lng":121.39844294374956,"count":1288881.0},
{"lat":31.288044465926138,"lng":121.4577688102147,"count":830476.0},
{"lat":31.28249722898657,"lng":121.49191854079479,"count":852476.0},
{"lat":31.304510479541904,"lng":121.5357165996346,"count":1313222.0},
{"lat":31.093537540382123,"lng":121.42502428093465,"count":2429372.0},
{"lat":31.398622694466777,"lng":121.40904121844942,"count":1904886.0},
{"lat":31.36433805543363,"lng":121.25101353755592,"count":1471231.0},
{"lat":31.23089534913395,"lng":121.6384813140922,"count":5044430.0},
{"lat":30.83508077708232,"lng":121.24840817975154,"count":732410.0},
{"lat":31.021244628098586,"lng":121.22679050142115,"count":1582398.0},
{"lat":31.130862397996967,"lng":121.09142524282201,"count":1081022.0},
{"lat":30.915122452605868,"lng":121.56064167963345,"count":1083463.0},
{"lat":31.633564930802045,"lng":121.5353975435439,"count":703722.0},
5. 画图
复制粘贴下面的代码写到html文件
1 改成你的密钥
3 把下面的var points 的内容和上面上海市人口的内容替换
2 选一个地图的中心点，我选择黄浦区作为我的中心点
4 下面的代码还有很多参数值得研究，有时间的读者不妨研究一下，可以留言相互学习哈
image.png
如果写如密钥报错的话，可以用v=1.4版本的，因为这版本不需要密钥
热力图功能示例
ul,li{list-style: none;margin:0;padding:0;float:left;}
html{height:100%}
body{height:100%;margin:0px;padding:0px;font-family:"微软雅黑";}
#container{height:500px;width:100%;}
#r-result{width:100%;}
var map = new BMap.Map("container"); // 创建地图实例
var point = new BMap.Point(121.44623500472937, 31.169152089592195);
map.centerAndZoom(point,15); // 初始化地图，设置中心点坐标和地图级别
map.enableScrollWheelZoom(); // 允许滚轮缩放
var points =[{"lat":31.227203440768868,"lng":121.49607206403445,"count":429891.0},
{"lat":31.213348379555082,"lng":121.48123797847695,"count":248779.0},
{"lat":31.169152089592195,"lng":121.44623500472937,"count":1085130.0},
{"lat":31.213301496813617,"lng":121.3876161086648,"count":690571.0},
{"lat":31.23538080348789,"lng":121.45475555700204,"count":246788.0},
{"lat":31.263742929075534,"lng":121.39844294374956,"count":1288881.0},
{"lat":31.288044465926138,"lng":121.4577688102147,"count":830476.0},
{"lat":31.28249722898657,"lng":121.49191854079479,"count":852476.0},
{"lat":31.304510479541904,"lng":121.5357165996346,"count":1313222.0},
{"lat":31.093537540382123,"lng":121.42502428093465,"count":2429372.0},
{"lat":31.398622694466777,"lng":121.40904121844942,"count":1904886.0},
{"lat":31.36433805543363,"lng":121.25101353755592,"count":1471231.0},
{"lat":31.23089534913395,"lng":121.6384813140922,"count":5044430.0},
{"lat":30.83508077708232,"lng":121.24840817975154,"count":732410.0},
{"lat":31.021244628098586,"lng":121.22679050142115,"count":1582398.0},
{"lat":31.130862397996967,"lng":121.09142524282201,"count":1081022.0},
{"lat":30.915122452605868,"lng":121.56064167963345,"count":1083463.0},
{"lat":31.633564930802045,"lng":121.5353975435439,"count":703722.0},
];
if(!isSupportCanvas()){
alert('热力图目前只支持有canvas支持的浏览器,您所使用的浏览器不能使用热力图功能~')
}
//详细的参数,可以查看heatmap.js的文档 /pa7/heatmap.js/blob/master/README.md
//参数说明如下:
/* visible 热力图是否显示,默认为true
* opacity 热力的透明度,1-100
* radius 势力图的每个点的半径大小
* gradient {JSON} 热力图的渐变区间 . gradient如下所示
* {
.2:'rgb(0, 255, 255)',
.5:'rgb(0, 110, 255)',
.8:'rgb(100, 0, 255)'
}
其中 key 表示插值的位置, 0~1.
value 为颜色值.
*/
heatmapOverlay = new BMapLib.HeatmapOverlay({"radius":50});
map.addOverlay(heatmapOverlay);
heatmapOverlay.setDataSet({data:points,max:100});
//是否显示热力图
function openHeatmap(){
heatmapOverlay.show();
}
function closeHeatmap(){
heatmapOverlay.hide();
}
closeHeatmap();
function setGradient(){
/*格式如下所示:
{
0:'rgb(102, 255, 0)',
.5:'rgb(255, 170, 0)',
1:'rgb(255, 0, 0)'
}*/
var gradient = {};
var colors = document.querySelectorAll("input[type='color']");
colors = [].slice.call(colors,0);
colors.forEach(function(ele){
gradient[ele.getAttribute("data-key")] = ele.value;
});
heatmapOverlay.setOptions({"gradient":gradient});
}
//判断浏览区是否支持canvas
function isSupportCanvas(){
var elem = document.createElement('canvas');
return !!(elem.getContext && elem.getContext('2d'));
}
最后用浏览器打开html 文件，会看到最前面的镇楼图，祝君好运～！
