第四周总结

这周学了一下Python爬取数据，是入门级别 

这是一小部分练习代码

import time

import json

import requests

import jsonpath

from pyecharts.charts import Map

import pyecharts.options as opts

import io

import sys

sys.stdout = io.TextIOWrapper(sys.stdout.buffer,encoding='utf-8')

 

# 全国疫情地区分布(各省确诊病例)

def catch_cn_disease_dis():

    timestamp = '%d'%int(time.time()*1000)

    url_area = ('https://view.inews.qq.com/g2/getOnsInfo?name=disease_h5'

               '&callback=&_=') + timestamp

    world_data = json.loads(requests.get(url=url_area).json()['data'])

    china_data = jsonpath.jsonpath(world_data,

                                   expr='$.areaTree[0].children[*]')

    ls_province_names = jsonpath.jsonpath(china_data, expr='$[*].name')

    ls_confirm_vals = jsonpath.jsonpath(china_data, expr='$[*].total.confirm')

    ls_province_confirm = list(zip(ls_province_names, ls_confirm_vals,))

    return ls_province_confirm, world_data

 

 

 

 

ls_province_cfm, dic_world_data = catch_cn_disease_dis()

print(ls_province_cfm)

 

 

# 绘制全国疫情地图

def map_cn_disease_dis() -> Map:

    c = (

        Map()

        .add('中国', ls_province_cfm, 'china')

        .set_global_opts(

            title_opts=opts.TitleOpts(title='全国新型冠状病毒疫情地图（确诊数）'),

            visualmap_opts=opts.VisualMapOpts(is_show=True,

                                              split_number=6,

                                              is_piecewise=True,  # 是否为分段型

                                              pos_top='center',

                                              pieces=[

                                                   {'min': 10000, 'color': '#7f1818'},  #不指定 max

                                                   {'min': 1000, 'max': 10000},

                                                   {'min': 500, 'max': 999},

                                                   {'min': 100, 'max': 499},

                                                   {'min': 10, 'max': 99},

                                                   {'min': 0, 'max': 5} ],

                                              ),

        )

    )

    return c

map_cn_disease_dis().render('全国疫情地图.htm