一、引入模块

import requests
import re
import json
import csv
import pandas as pd
from pyecharts.charts import Map
from pyecharts import options as opts

二、数据采集-爬虫

网址
url = 'https://voice.baidu.com/act/newpneumonia/newpneumonia/?from=osari_aladin_banner&city=%E7%BE%8E%E5%9B%BD-%E7%BE%8E%E5%9B%BD'
防盗链
headers = {'user-agent': 'Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/92.0.4515.131 Safari/537.36 SLBrowser/8.0.0.5261 SLBChan/25'}

with open('人数.csv', mode='a', encoding='utf-8', newline='') as f:
        csv_writer = csv.writer(f)
        csv_writer.writerow(['地点', '确诊人数', 'confirmed', 'curConfirmRelative', 'crued', 'died'])
        
rest = requests.get(url=url, headers=headers)
data_html = rest.text
正则表达式
json_str = re.findall('"component":\[(.*)\],', data_html)[0]
# json解析数据
json_dict = json.loads(json_str)
caseList = json_dict['caseList']

# 循环遍历提取数据
for case in caseList:
    area = case['area']  #省份
    curConfirm = case['curConfirm']  #总确诊人数
    confirmed = case['confirmed']  #确诊人数
    curConfirmRelative = case['curConfirmRelative']  #确诊人数
    crued = case['crued']   #治愈人数
    died = case['died']   #死亡人数
    with open('人数.csv', mode='a', encoding='utf-8', newline='') as f:
        csv_writer = csv.writer(f)
        csv_writer.writerow([area, curConfirm, confirmed, curConfirmRelative, crued, died])

三、数据可视化

df = pd.read_csv('人数.csv')
china_map = (
    Map()
        .add('现确诊', [list(i) for i in zip(df['地点'].values.tolist(), df['确诊人数'].values.tolist())], 'china')
        .set_global_opts(
        title_opts=opts.TitleOpts(title='各地区确诊人数'),
        visualmap_opts=opts.VisualMapOpts(max_=200, is_inverse=True)
        )
)
china_map.render_notebook()

四、可视化效果显示