Python：爬取全国各省疫情数据并在地图显示

代码：

import requests
import pymysql
import json
from pyecharts import options as opts
from pyecharts.charts import Map
 
def create():
 
    # 连接数据库
    db = pymysql.connect(host = 'localhost', user = 'root', password ='258000', database = 'yiqing',charset='utf8')
 
    # 使用 cursor() 方法创建一个游标对象 cursor
    cursor = db.cursor()
 
    # 使用 execute() 方法执行 SQL，如果表存在则删除
    cursor.execute("DROP TABLE IF EXISTS proyiqing")
 
    # 使用预处理语句创建表
    sql = """CREATE TABLE proyiqing (
            Id INT PRIMARY KEY AUTO_INCREMENT,
            update_time varCHAR(255),
            provinse varchar(255),
            today_confirm varchar(255),
            total_confirm varchar(255),
            now_confirm varchar(255),
            total_dead varchar(255),
            total_heal varchar(255))"""
    #update_time,provinse,today_confirm,total_confirm,now_confirm,total_dead,total_heal
    cursor.execute(sql)
 
    #关闭数据库连接
    db.close()
 
def insert(value):
 
    # 连接数据库
    db = pymysql.connect(host = 'localhost', user = 'root', password ='258000', database = 'yiqing',charset='utf8')
 
    # 使用 execute() 方法执行 SQL，如果表存在则删除
    cursor = db.cursor()
 
    # 使用预处理语句插入数据
    sql = "INSERT INTO proyiqing(update_time,provinse,today_confirm,total_confirm,now_confirm,total_dead,total_heal) VALUES ( %s,%s,%s,%s,%s,%s,%s)"
    #update_time,provinse,today_confirm,total_confirm,now_confirm,total_dead,total_heal
 
    try:
        cursor.execute(sql, value)
        db.commit()
        print('插入数据成功')
    except:
        db.rollback()
        print("插入数据失败")
    db.close()
 
create()  # 创建表
 
#目标网站
url = 'https://view.inews.qq.com/g2/getOnsInfo?name=disease_h5'
headers = {
      'user-agent': 'Mozilla/5.0 (Linux; Android 6.0; Nexus 5 Build/MRA58N) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/78.0.3904.108 Mobile Safari/537.36'
    }
 
#请求资源，获取相应内容
r = requests.get(url, headers)
 
# 将响应信息进行json格式化
res = json.loads(r.text)
data = json.loads(res['data'])
 
#世界疫情
lists = ['截至时间：' + str(data['lastUpdateTime']) + '\n'
        '全国确诊人数：' + str(data['chinaTotal']['confirm']) + '\n'
        '今日新增确诊：' + str(data['chinaAdd']['confirm']) + '\n'
        '全国疑似：' + str(data['chinaTotal']['suspect']) + '\n'
        '今日新增疑似：' + str(data['chinaAdd']['suspect']) + '\n'
        '全国治愈：' + str(data['chinaTotal']['heal']) + '\n'
        '今日新增治愈：' + str(data['chinaAdd']['heal']) + '\n'
        '全国死亡：' + str(data['chinaTotal']['dead']) + '\n'
        '今日新增死亡：' + str( data['chinaAdd']['dead']) + '\n']
result = ''.join(lists)
with open('疫情查询.txt', 'w+', encoding="utf-8") as f:
        f.write(result + '\n')
 
#更新时间
update_time = data['lastUpdateTime']
 
#保存全国各省现有确诊数据
province_detals = []
confirm_detals = []
 
#省份疫情
for pro in data['areaTree'][0]['children']:
        provinse = pro["name"]   #省名
        today_confirm = pro["today"]["confirm"]
        total_confirm = pro["total"]["confirm"]
        now_confirm = pro["total"]["nowConfirm"]
        total_dead = pro["total"]["dead"]
        total_heal = pro["total"]["heal"]
        province_detals.append(provinse)
        confirm_detals.append(now_confirm)
        #insert((update_time,provinse,today_confirm,total_confirm,now_confirm,total_dead,total_heal))#存入数据库
 
#建立一一对应关系
data_zip = zip(province_detals,confirm_detals)
data_list = list(data_zip)
 
#可视化 matplot 和 pyechart
map = Map(opts.InitOpts(width='1900px',height='800px')).add(series_name="中国疫情分布",
                data_pair=data_list,#输入数据
                maptype="china",#地图类型
                is_map_symbol_show=False#显示标记
)
 
#不显示国家名称
map.set_series_opts(label_opts=opts.LabelOpts(is_show=False))
 
#设置全局配置项
map.set_global_opts(title_opts=opts.TitleOpts(title="中国疫情情况"),#设置图标题
                    visualmap_opts=opts.VisualMapOpts(
                        is_piecewise=True,
                        pieces=[
                        {"min":1,"max": 10},
                        {"min": 10, "max": 20},
                        {"min": 20, "max": 30},
                        {"min": 30, "max": 40},
                        {"min": 40, "max": 50},
                        {"min": 50, "max": 60},
                        {"min": 60, "max": 70},
                        {"min": 70, "max": 80},
                        {"min": 80, "max": 90},
                        {"min": 90, "max": 100},
                        {"min": 100}]
                    )) #显示图例
map.render("中国疫情分布情况.html")

效果：