【爬虫+可视化】Python爬取疫情数据，并做可视化展示_mport requests # 用于发送网页请求 import pandas as ___

import requests
import pandas as pd
from pyecharts.charts import Bar, Line
from pyecharts import options as opts
 
# 获取数据
def get_data(url):
    response = requests.get(url)
    return response.json()
 
# 解析数据
def parse_data(data):
    records = data['records']
    provinces = [record['provinceName'] for record in records]
    confirmed_cases = [record['confirmedCount'] for record in records]
    suspected_cases = [record['suspectedCount'] for record in records]
    cured_cases = [record['curedCount'] for record in records]
    dead_cases = [record['deadCount'] for record in records]
    return provinces, confirmed_cases, suspected_cases, cured_cases, dead_cases
 
# 可视化数据
def visualize_data(provinces, confirmed_cases, suspected_cases, cured_cases, dead_cases):
    # 确诊变异情况柱状图
    bar = Bar()
    bar.add_xaxis(provinces)
    bar.add_yaxis("确诊", confirmed_cases)
    bar.add_yaxis("疑似", suspected_cases)
    bar.set_global_opts(title_opts=opts.TitleOpts(title="变异情况柱状图"))
    bar.render("变异情况.html")
 
    # 累计治愈和死亡情况折线图
    line = Line()
    line.add_xaxis(provinces)
    line.add_yaxis("治愈", cured_cases, is_smooth=True)
    line.add_yaxis("死亡", dead_cases, is_smooth=True)
    line.set_global_opts(title_opts=opts.TitleOpts(title="治愈与死亡累计折线图"))
    line.render("治愈与死亡.html")
 
# 主函数
def main():
    url = "https://api.inews.qq.com/newsqa/v1/automation/modules/list?modules=FAutoCountry,WomWorld,AiCountry,WomAboard,CountryOther,OverseaFightForecast,WomAboardForecast,GlobalFight,ChinaFight,FightAroundWorld,FightCountry,FightProvince,FightType,MasksSupplies,FightForecast,FightTips,FightAroundWorldForecast,CountryOtherForecast&_=1615366747766"
    data = get_data(url)
    provinces, confirmed_cases, suspected_cases, cured_cases, dead_cases = parse_data(data)
    visualize_data(provinces, confirmed_cases, suspected_cases, cured_cases, dead_cases)
 
if __name__ == "__main__":
    main()

这段代码使用了pyecharts库来创建图表，并且使用requests库来发送HTTP请求从网络上获取数据。首先定义了一个获取数据的函数，然后解析数据，并定义了一个可视化数据的函数。最后，在主函数中调用这些函数来完成数据的爬取和可视化展示。