python爬取国内疫情数据并生成地图

效果展示

直接上代码

获取国内疫情数据

from selenium import webdriver
import os
from time import sleep
import xlwt

bookwork = xlwt.Workbook(encoding='utf-8')
sheetbook = bookwork.add_sheet('国内疫情数据')

title = ['地区','现有确诊','累计确诊','治愈','死亡']
for i in range(len(title)):
    sheetbook.write(0,i,title[i])
    # 限制图片加载
options = webdriver.ChromeOptions()
prefs = {
        'profile.default_content_setting_values': {
            'images': 2,   #限制图片加载
            'permissions.default.stylesheet': 2,    #限制css样式加载
            # 'javascript':2
        }
    }
options.add_experimental_option('prefs', prefs)
options.add_argument('headless')      #设置无浏览器界面运行
driver = webdriver.Chrome(chrome_options=options)

link = 'https://news.qq.com/zt2020/page/feiyan.htm#/?nojump=1'
driver.get(link)
sleep(3)
time = driver.find_element_by_xpath('//*[@id="app"]/div[2]/div[3]/div[1]/div[2]/p/span').text
print(time)
time = time.split(' ')
time = time[0]
print(time)
dir = driver.find_element_by_id('listWraper')

table = driver.find_elements_by_xpath('//*[@id="listWraper"]/table[2]/tbody')
print(len(table))

num = 1
for i in table:
    name = i.find_element_by_tag_name('th').text
    td = i.find_elements_by_tag_name('td')
    current = td[0].find_element_by_tag_name('p').text
    history = td[1].find_element_by_tag_name('p').text
    head = td[2].find_element_by_tag_name('p').text
    dead = td[3].find_element_by_tag_name('p').text
    sheetbook.write(num,0,name)
    sheetbook.write(num, 1,current )
    sheetbook.write(num, 2,history)
    sheetbook.write(num, 3,head)
    sheetbook.write(num, 4,dead)
    print(name,current,history,head,dead)
    num = num + 1
bookwork.save(time[5:]+'国内疫情数据.xlsx')
print('更新完成')
driver.quit()   #关闭浏览器

生成地图

# V1 版本开始支持链式调用
#coding = utf-8
from pyecharts import options as opts
from pyecharts.charts import Map
from pyecharts.globals import ThemeType  # 主题
from snapshot_selenium import snapshot as driver
from pyecharts.render import make_snapshot
import xlrd


filename = '06-10国内疫情数据.xlsx'
file = xlrd.open_workbook(filename)
sheet = file.sheet_by_name('国内疫情数据')
cityname = sheet.col_values(0)  # 获取城市名
number = sheet.col_values(1)  # 获取城市现有确诊人数
data = []
for i in range(1, len(cityname)):
    list = []
    list.append(cityname[i])
    list.append(number[i])
    data.append(list)

# 设置地图参数
map = (
    Map(init_opts=opts.InitOpts(bg_color="#FFFAFA", theme=ThemeType.ESSOS, width=1000))
        .add("现存确诊人数", data)
        .set_global_opts(
        title_opts=opts.TitleOpts(title=filename[0:5] + "国内数据的疫情图"),
        visualmap_opts=opts.VisualMapOpts(
            is_piecewise=True,  # 设置是否为分段显示
            # 自定义的每一段的范围，以及每一段的文字，以及每一段的特别的样式。例如：
            pieces=[
                {"min": 400, "label": '>400人', "color": "#eb2f06"},
                {"min": 300, "max": 400, "label": '300-400人', "color": "#FF3030"},  # 不指定 max，表示 max 为无限大（Infinity）。
                {"min": 150, "max": 300, "label": '150-300人', "color": "#FF4500"},
                {"min": 100, "max": 150, "label": '100-150人', "color": "#FF7F50"},
                {"min": 50, "max": 100, "label": '50-100人', "color": "#FFA500"},
                {"min": 1, "max": 50, "label": '1-50人', "color": "#FFDEAD"},
            ],
            # 两端的文本，如['High', 'Low']。
            range_text=['高', '低'],
        ),
    )
)
make_snapshot(driver, map.render('F:/CODE/爬虫/可视化疫情2/中国疫情人数地图.html'), "F:/CODE/爬虫/可视化疫情2/chinese_map.png")