Python爬虫爬取疫情数据并可视化展示

import requests      # 发送网络请求模块
import json
import pprint        # 格式化输出模块
import pandas as pd  # 数据分析当中一个非常重要的模块

url = 'https://view.inews.qq.com/g2/getOnsInfo?name=disease_h5&_=1638361138568'
response = requests.get(url, verify=False)

json_data = response.json()['data']

json_data = json.loads(json_data)
china_data = json_data['areaTree'][0]['children'] # 列表
data_set = []
for i in china_data:
    data_dict = {}
    # 地区名称
    data_dict['province'] = i['name']
    # 新增确认
    data_dict['nowConfirm'] = i['total']['nowConfirm']
    # 死亡人数
    data_dict['dead'] = i['total']['dead']
    # 治愈人数
    data_dict['heal'] = i['total']['heal']
    # 死亡率
    data_dict['deadRate'] = i['total']['deadRate']
    # 治愈率
    data_dict['healRate'] = i['total']['healRate']
    data_set.append(data_dict)

df = pd.DataFrame(data_set)
df.to_csv('data.csv')

from pyecharts import options as opts
from pyecharts.charts import Bar,Line,Pie,Map,Grid

df2 = df.sort_values(by=['nowConfirm'],ascending=False)[:9]
df2

line = (
    Line()
    .add_xaxis(list(df['province'].values))
    .add_yaxis("治愈率", df['healRate'].values.tolist())
    .add_yaxis("死亡率", df['deadRate'].values.tolist())
    .set_global_opts(
        title_opts=opts.TitleOpts(title="死亡率与治愈率"),

    )
)
line.render_notebook()

bar = (
    Bar()
    .add_xaxis(list(df['province'].values)[:6])
    .add_yaxis("死亡", df['dead'].values.tolist()[:6])
    .add_yaxis("治愈", df['heal'].values.tolist()[:6])
    .set_global_opts(
        title_opts=opts.TitleOpts(title="各地区确诊人数与死亡人数情况"),
        datazoom_opts=[opts.DataZoomOpts()],
        )
)
bar.render_notebook()