pyecharts实现新冠肺炎疫情可视化并搭建BI数据大屏(Plus)

前几天写过一篇pyecharts实现新冠肺炎疫情可视化BI数据大屏，几天没看，今天又看了看，发现不能用了，因为TX页面改了，添加删除了一些东西(比如把确诊分为现存和累计等…)，所以我就又改了改，把新增的那些数据补了上去，还有就是把正中央的那个柱状图折线图混合改成了轮播图，这样看着更清晰，再者就是改了个名(原来叫 2019-nCov 我写了那篇文章那天WHO定名 COVID-19 我也就没改… 这是它的百度百科词条)

这是新的效果图:

（CSDN的GIF图最大只能3MB,所以你们就将就看看，看到那个东西会动就行…）

不说别的了，上新代码吧，还是复制可用的那种：

# 数据来源 [腾讯疫情实时追踪](https://news.qq.com/zt2020/page/feiyan.htm?from=timeline&isappinstalled=0)import json
import requests
import pandas as pd
from pyecharts.charts import *
from pyecharts import options as opts
from pyecharts.commons.utils import JsCode
from pyecharts.globals import ThemeType, ChartType
from bs4 import BeautifulSoup# 抓取数据
reponse = requests.get('https://view.inews.qq.com/g2/getOnsInfo?name=disease_h5').json()
data = json.loads(reponse['data'])
# 国内
lastUpdateTime = data['lastUpdateTime']chinaTotal = data['chinaTotal']
chinaTotal['累计确诊'] = chinaTotal['confirm']
chinaTotal['现有疑似'] = chinaTotal['suspect']
chinaTotal['累计死亡'] = chinaTotal['dead']
chinaTotal['累计治愈'] = chinaTotal['heal']
chinaTotal['现有确诊'] = chinaTotal['nowConfirm']
chinaTotal['现有重症'] = chinaTotal['nowSevere']
del chinaTotal['confirm']
del chinaTotal['suspect']
del chinaTotal['dead']
del chinaTotal['heal']
del chinaTotal['nowConfirm']
del chinaTotal['nowSevere']chinaAdd = data['chinaAdd']
chinaAdd['累计确诊新增'] = chinaAdd['confirm']
chinaAdd['现有疑似新增'] = data['chinaDayAddList'][-1]['suspect']
chinaAdd['累计死亡新增'] = chinaAdd['dead']
chinaAdd['累计治愈新增'] = chinaAdd['heal']
chinaAdd['现有确诊新增'] = chinaAdd['nowConfirm']
chinaAdd['现有重症新增'] = chinaAdd['nowSevere']
del chinaAdd['confirm']
del chinaAdd['suspect']
del chinaAdd['dead']
del chinaAdd['heal']
del chinaAdd['nowConfirm']
del chinaAdd['nowSevere']areaTree = data['areaTree']china_data = areaTree[0]['children']
china_list = []
for x in range(len(china_data)):province = china_data[x]['name']province_list = china_data[x]['children']for y in range(len(province_list)):city = province_list[y]['name']total = province_list[y]['total']today = province_list[y]['today']china_dict = {'province': province, 'city': city, 'total': total, 'today': today}china_list.append(china_dict)# 定义数据处理函数
def confirm(x):confirm = eval(str(x))['confirm']return confirmdef suspect(x):suspect = eval(str(x))['suspect']return suspectdef dead(x):dead = eval(str(x))['dead']return deaddef heal(x):heal = eval(str(x))['heal']return healdef deadRate(x):deadRate=eval(str(x))['deadRate']return deadRatedef healRate(x):healRate=eval(str(x))['healRate']return healRatechina_data = pd.DataFrame(china_list)
china_data.head()# 函数映射
china_data['confirm'] = china_data['total'].map(confirm)
china_data['suspect'] = china_data['total'].map(suspect)
china_data['dead'] = china_data['total'].map(dead)
china_data['heal'] = china_data['total'].map(heal)
china_data['deadRate']=china_data['total'].map(deadRate)
china_data['healRate']=china_data['total'].map(healRate)
china_data = china_data[["province", "city", "confirm", "suspect", "dead", "heal","deadRate","healRate"]]
china_data.head()
# 国际数据处理
global_data = pd.DataFrame(data['areaTree'])
global_data['confirm'] = global_data['total'].map(confirm)
global_data['suspect'] = global_data['total'].map(suspect)
global_data['dead'] = global_data['total'].map(dead)
global_data['heal'] = global_data['total'].map(heal)
global_data['deadRate']=global_data['total'].map(deadRate)
global_data['healRate']=global_data['total'].map(healRate)
world_name = pd.read_excel("世界各国中英文对照.xlsx")
global_data = pd.merge(global_data, world_name, left_on="name", right_on="中文", how="inner")
global_data = global_data[["name", "英文", "confirm", "suspect", "dead", "heal","deadRate","healRate"]]
global_data.head()
# 日数据处理
chinaDayList = pd.DataFrame(data['chinaDayList'])
chinaDayList = chinaDayList[['date', 'confirm', 'suspect', 'dead', 'heal']]
chinaDayList.head()# 日新增数据处理
chinaDayAddList = pd.DataFrame(data['chinaDayAddList'])
chinaDayAddList = chinaDayAddList[['date', 'confirm', 'suspect', 'dead', 'heal']]
chinaDayAddList.head()# 数据可视化# 饼图
total_pie = (Pie(init_opts=opts.InitOpts(theme=ThemeType.LIGHT,  bg_color="transparent")).add("", [list(z) for z in zip(chinaTotal.keys(), chinaTotal.values())],center=["50%", "60%"], radius=[75, 100]).add("", [list(z) for z in zip(chinaAdd.keys(), chinaAdd.values())],center=["50%", "60%"], radius=[0, 50]).set_global_opts(legend_opts=opts.LegendOpts(type_="scroll",textstyle_opts=opts.TextStyleOpts(color="#FFFFFF"))).set_series_opts(label_opts=opts.LabelOpts(formatter="{b}:{c}")))# 全球疫情地图
world_map = (Map(init_opts=opts.InitOpts(theme=ThemeType.WESTEROS)).add("", [list(z) for z in zip(list(global_data["英文"]), list(global_data["confirm"]))], "world",is_map_symbol_show=False).set_series_opts(label_opts=opts.LabelOpts(is_show=False),toolbox_opts=opts.ToolboxOpts(orient='vertical', pos_right="10%")).set_global_opts(visualmap_opts=opts.VisualMapOpts(is_piecewise=True, background_color="transparent",textstyle_opts=opts.TextStyleOpts(color="#F5FFFA"),pieces=[{"min": 101, "label": '>100', "color": "#893448"},{"min": 10, "max": 100, "label": '10-100',"color": "#fb8146"},{"min": 1, "max": 9, "label": '1-9',"color": "#fff2d1"},])))# 中国疫情地图绘制
# 数据处理
area_data = china_data.groupby("province")["confirm"].sum().reset_index()
area_data.columns = ["province", "confirm"]area_map = (Map(init_opts=opts.InitOpts(theme=ThemeType.WESTEROS)).add("", [list(z) for z in zip(list(area_data["province"]), list(area_data["confirm"]))], "china",is_map_symbol_show=False, label_opts=opts.LabelOpts(color="#fff"),tooltip_opts=opts.TooltipOpts(is_show=True), zoom=1.2, center=[105, 30]).set_series_opts(label_opts=opts.LabelOpts(is_show=False)).set_global_opts(title_opts=opts.TitleOpts(title="中国疫情分布图", pos_top='5%',title_textstyle_opts=opts.TextStyleOpts(color="#FF0000")),visualmap_opts=opts.VisualMapOpts(is_piecewise=True, pos_right=0, pos_bottom=0,textstyle_opts=opts.TextStyleOpts(color="#F5FFFA"),pieces=[{"min": 1001, "label": '>1000', "color": "#893448"},{"min": 500, "max": 1000, "label": '500-1000',"color": "#ff585e"},{"min": 101, "max": 499, "label": '101-499',"color": "#fb8146"},{"min": 10, "max": 100, "label": '10-100',"color": "#ffb248"},{"min": 0, "max": 9, "label": '0-9',"color": "#fff2d1"}])))city_data = china_data.groupby('city')['confirm'].sum().reset_index()
city_data.columns = ["city", "confirm"]def is_city(item):'''判断一个城市能否在Geo地图上被找到:param item: 城市名:return: T/F'''lists_1 = []lists_1.append(item)lists_2 = [10]geo = Geo()geo.add_schema(maptype="china")try:geo.add("确诊城市", [list(z) for z in zip(lists_1, lists_2)])return Trueexcept TypeError as e:return Falsecity_index = []
i = 0
for item in city_data['city']:if is_city(item) == False:city_index.append(i)i += 1for x in city_index:del (city_data['city'][x])del (city_data['confirm'][x])city_index_ = []
i = 0
for item in city_data['confirm']:if item > 1000:city_index_.append(i)i += 1serious_city = []  # 严重城市
serious_submit = []  # 严重人数
for y in city_index_:serious_city.append(list(city_data['city'])[y])serious_submit.append(list(city_data['confirm'])[y])list_1 = ["拉萨"]
list_2 = [1]area_heat_geo = (Geo(init_opts=opts.InitOpts(theme=ThemeType.WESTEROS, bg_color='transparent')).add_schema(maptype="china", zoom=1.2, center=[105, 30]).add("确诊城市", [list(z) for z in zip(list(city_data["city"]), list(city_data["confirm"]))], symbol_size=10).add("确诊城市", [list(z) for z in zip(list_1, list_2)], symbol_size=10)  # 孤独拉萨.add("确诊城市", [list(z) for z in zip(list(serious_city), list(serious_submit))],  # 感染者超1000的城市type_=ChartType.EFFECT_SCATTER, effect_opts=opts.EffectOpts(is_show=True, color="black",symbol_size=30, scale=4, period=1)).add("", [list(z) for z in zip(list(city_data["city"]), list(city_data["confirm"]))],type_=ChartType.HEATMAP).set_series_opts(label_opts=opts.LabelOpts(is_show=False)).set_global_opts(visualmap_opts=opts.VisualMapOpts(range_size=[0, 25, 50, 75, 100], max_=1000, orient='horizontal',pos_bottom=0),title_opts=opts.TitleOpts(title="中国疫情分布热图", pos_top='5%'),legend_opts=opts.LegendOpts(pos_bottom='10%', pos_left=0)))date = []  # 日期
confirmTotal = []  # 累计确诊
confirmAdd = []  # 新增确诊
suspectTotal = []  # 累计疑似
suspectAdd = []  # 新增疑似
deadTotal = []  # 累计死亡
deadAdd = []  # 新增死亡
healTotal = []  # 累计治愈
healAdd = []  # 新增治愈
deadRate = []  # 死亡率
healRate = []  # 治愈率
for j in data['chinaDayAddList']:confirmAdd.append(j['confirm'])suspectAdd.append(j['suspect'])deadAdd.append(j['dead'])healAdd.append(j['heal'])for k in data['chinaDayList']:date.append(k['date'])confirmTotal.append(k['confirm'])suspectTotal.append(k['suspect'])deadTotal.append(k['dead'])healTotal.append(k['heal'])deadRate.append(k['deadRate'])healRate.append(k['healRate'])line_1 = (Line(init_opts=opts.InitOpts(theme=ThemeType.DARK, bg_color="#333333")).add_xaxis(date).add_yaxis("累计确诊", confirmTotal, yaxis_index=1, is_smooth=True,tooltip_opts=opts.TooltipOpts(formatter="{a}:{c}")).set_series_opts(label_opts=opts.LabelOpts(is_show=False)).set_global_opts(yaxis_opts=opts.AxisOpts(axislabel_opts=opts.LabelOpts(formatter="{value}")),legend_opts=(opts.LegendOpts(textstyle_opts=opts.TextStyleOpts(color="white")))))
bar_1 = (Bar(init_opts=opts.InitOpts(theme=ThemeType.DARK, bg_color="#333333")).add_xaxis(date[7:]).add_yaxis("单日确诊", confirmAdd, tooltip_opts=opts.TooltipOpts(formatter="{a}:{c}")).extend_axis(yaxis=opts.AxisOpts(axislabel_opts=opts.LabelOpts(formatter="{value}"))).set_series_opts(label_opts=opts.LabelOpts(is_show=False)).set_global_opts(title_opts=opts.TitleOpts("确诊", pos_left='10%',title_textstyle_opts=opts.TextStyleOpts(color="white")),yaxis_opts=opts.AxisOpts(axislabel_opts=opts.LabelOpts(formatter="{value}")),legend_opts=(opts.LegendOpts(textstyle_opts=opts.TextStyleOpts(color="white"))))).overlap(line_1)line_2 = (Line(init_opts=opts.InitOpts(theme=ThemeType.LIGHT, bg_color="#333333")).add_xaxis(date).add_yaxis("累计疑似", suspectTotal, yaxis_index=1, is_smooth=True,tooltip_opts=opts.TooltipOpts(formatter="{a}:{c}")).set_series_opts(label_opts=opts.LabelOpts(is_show=False)).set_global_opts(yaxis_opts=opts.AxisOpts(axislabel_opts=opts.LabelOpts(formatter="{value}")),legend_opts=(opts.LegendOpts(textstyle_opts=opts.TextStyleOpts(color="white")))))bar_2 = (Bar(init_opts=opts.InitOpts(theme=ThemeType.LIGHT, bg_color="#333333")).add_xaxis(date[7:]).add_yaxis("单日疑似", suspectAdd, tooltip_opts=opts.TooltipOpts(formatter="{a}:{c}")).set_series_opts(label_opts=opts.LabelOpts(is_show=False)).set_global_opts(title_opts=opts.TitleOpts("疑似", pos_left='10%',title_textstyle_opts=opts.TextStyleOpts(color="white")),yaxis_opts=opts.AxisOpts(axislabel_opts=opts.LabelOpts(formatter="{value}")),legend_opts=(opts.LegendOpts(textstyle_opts=opts.TextStyleOpts(color="white"))))).overlap(line_2)line_3 = (Line(init_opts=opts.InitOpts(theme=ThemeType.DARK, bg_color="#333333")).add_xaxis(date).add_yaxis("累计死亡", deadTotal, yaxis_index=1, is_smooth=True, tooltip_opts=opts.TooltipOpts(formatter="{a}:{c}")).set_series_opts(label_opts=opts.LabelOpts(is_show=False)).set_global_opts(yaxis_opts=opts.AxisOpts(axislabel_opts=opts.LabelOpts(formatter="{value}")),legend_opts=(opts.LegendOpts(textstyle_opts=opts.TextStyleOpts(color="white")))))bar_3 = (Bar(init_opts=opts.InitOpts(theme=ThemeType.DARK, bg_color="#333333")).add_xaxis(date[7:]).add_yaxis("单日死亡", deadAdd, tooltip_opts=opts.TooltipOpts(formatter="{a}:{c}")).set_series_opts(label_opts=opts.LabelOpts(is_show=False)).set_global_opts(title_opts=opts.TitleOpts("死亡", pos_left='10%',title_textstyle_opts=opts.TextStyleOpts(color="white")),yaxis_opts=opts.AxisOpts(axislabel_opts=opts.LabelOpts(formatter="{value}")),legend_opts=(opts.LegendOpts(textstyle_opts=opts.TextStyleOpts(color="white"))))).overlap(line_3)line_4 = (Line(init_opts=opts.InitOpts(theme=ThemeType.ROMA, bg_color="#333333")).add_xaxis(date).add_yaxis("累计治愈", healTotal, yaxis_index=1, is_smooth=True, tooltip_opts=opts.TooltipOpts(formatter="{a}:{c}")).set_series_opts(label_opts=opts.LabelOpts(is_show=False)).set_global_opts(yaxis_opts=opts.AxisOpts(axislabel_opts=opts.LabelOpts(formatter="{value}")),legend_opts=(opts.LegendOpts(textstyle_opts=opts.TextStyleOpts(color="white")))))
bar_4 = (Bar(init_opts=opts.InitOpts(theme=ThemeType.ROMA, bg_color="#333333")).add_xaxis(date[7:]).add_yaxis("单日治愈", healAdd, tooltip_opts=opts.TooltipOpts(formatter="{a}:{c}")).set_series_opts(label_opts=opts.LabelOpts(is_show=False)).set_global_opts(title_opts=opts.TitleOpts("治愈",pos_left='10%',title_textstyle_opts=opts.TextStyleOpts(color="white")),yaxis_opts=opts.AxisOpts(axislabel_opts=opts.LabelOpts(formatter="{value}")),legend_opts=(opts.LegendOpts(textstyle_opts=opts.TextStyleOpts(color="white"))))).overlap(line_4)line = (Line(init_opts=opts.InitOpts(theme=ThemeType.CHALK, bg_color="#333333")).add_xaxis(date).add_yaxis("死亡率", deadRate, is_smooth=True, tooltip_opts=opts.TooltipOpts(formatter="{a}:{c}%")).set_series_opts(label_opts=opts.LabelOpts(is_show=False)).set_global_opts(title_opts=opts.TitleOpts("死亡/治愈率",pos_left='10%',title_textstyle_opts=opts.TextStyleOpts(color="white")),yaxis_opts=opts.AxisOpts(axislabel_opts=opts.LabelOpts(formatter="{value}")),legend_opts=(opts.LegendOpts(textstyle_opts=opts.TextStyleOpts(color="white")))))lines = (Line(init_opts=opts.InitOpts(theme=ThemeType.LIGHT, bg_color="#333333")).add_xaxis(date).add_yaxis("治愈率", healRate, is_smooth=True, tooltip_opts=opts.TooltipOpts(formatter="{a}:{c}%")).extend_axis(yaxis=opts.AxisOpts(axislabel_opts=opts.LabelOpts(formatter="{value}%"))).set_series_opts(label_opts=opts.LabelOpts(is_show=False)).set_global_opts(title_opts=opts.TitleOpts("死亡/治愈率", pos_left='10%',title_textstyle_opts=opts.TextStyleOpts(color="white")),yaxis_opts=opts.AxisOpts(axislabel_opts=opts.LabelOpts(formatter="{value}%")),legend_opts=(opts.LegendOpts(textstyle_opts=opts.TextStyleOpts(color="white"))))).overlap(line)tl = (Timeline(init_opts=opts.InitOpts(theme=ThemeType.WALDEN, bg_color="transparent")).add_schema(play_interval=5000, is_auto_play=True,width='70%',height='10%',pos_left='center',linestyle_opts=opts.LineStyleOpts(),label_opts=opts.LabelOpts(position='bottom',color="white")).add(bar_1, "确诊").add(bar_2, "疑似").add(bar_3, "死亡").add(bar_4, "治愈").add(lines, "死亡/治愈率"))big_title = (Pie().set_global_opts(title_opts=opts.TitleOpts(title="COVID-19",title_textstyle_opts=opts.TextStyleOpts(font_size=40, color='#FFFFFF',border_radius=True, border_color="white"),pos_top=0)))times = (Pie().set_global_opts(title_opts=opts.TitleOpts(subtitle=("截至 " + lastUpdateTime),subtitle_textstyle_opts=opts.TextStyleOpts(font_size=13, color='#FFFFFF'),pos_top=0))
)confirms = (Pie().set_global_opts(title_opts=opts.TitleOpts(title="确诊", pos_left='center', pos_top='center',subtitle="(现有)",item_gap=1,subtitle_textstyle_opts=opts.TextStyleOpts(color="#FFFFFF"),title_textstyle_opts=opts.TextStyleOpts(color='#FFFFFF'))))
confirms_people = (Pie().set_global_opts(title_opts=opts.TitleOpts(title=(str(chinaTotal['现有确诊']) + "   "),pos_top='15%', pos_left='center',subtitle=("         新增: " + str(chinaAdd['现有确诊新增'])),item_gap=1,title_textstyle_opts=opts.TextStyleOpts(color="#00FFFF",font_size=30),subtitle_textstyle_opts=opts.TextStyleOpts(color="#00BFFF"))))
suspects = (Pie().set_global_opts(title_opts=opts.TitleOpts(title="疑似", pos_left='center', pos_top='center',subtitle="(现有)",item_gap=1,subtitle_textstyle_opts=opts.TextStyleOpts(color="#FFFFFF"),title_textstyle_opts=opts.TextStyleOpts(color='#FFFFFF'))))
suspects_people = (Pie().set_global_opts(title_opts=opts.TitleOpts(title=(str(chinaTotal['现有疑似']) + "   "),pos_top='15%', pos_left='center',subtitle=("         新增 :" + str(chinaAdd['现有疑似新增'])),item_gap=1,title_textstyle_opts=opts.TextStyleOpts(color="#FF00FF",font_size=30),subtitle_textstyle_opts=opts.TextStyleOpts(color="#EE82EE"))))
deads = (Pie().set_global_opts(title_opts=opts.TitleOpts(title="死亡", pos_left='center', pos_top='center',subtitle="(累计)",item_gap=1,subtitle_textstyle_opts=opts.TextStyleOpts(color="#FFFFFF"),title_textstyle_opts=opts.TextStyleOpts(color='#FFFFFF'))))
deads_people = (Pie().set_global_opts(title_opts=opts.TitleOpts(title=(str(chinaTotal['累计死亡']) + "   "),pos_top='15%', pos_left='center',subtitle=("         新增 :" + str(chinaAdd['累计死亡新增'])),item_gap=1,title_textstyle_opts=opts.TextStyleOpts(color="#FF0000",font_size=30),subtitle_textstyle_opts=opts.TextStyleOpts(color="#F08080"))))
heals = (Pie().set_global_opts(title_opts=opts.TitleOpts(title="治愈", pos_left='center', pos_top='center',subtitle="(累计)",item_gap=1,subtitle_textstyle_opts=opts.TextStyleOpts(color="#FFFFFF"),title_textstyle_opts=opts.TextStyleOpts(color='#FFFFFF'))))
heals_people = (Pie().set_global_opts(title_opts=opts.TitleOpts(title=(str(chinaTotal['累计治愈']) + "   "),pos_top='15%', pos_left='center',subtitle=("         新增 :" + str(chinaAdd['累计治愈新增'])),item_gap=1,title_textstyle_opts=opts.TextStyleOpts(color="#00FF00",font_size=30),subtitle_textstyle_opts=opts.TextStyleOpts(color="#98FB98"))))sum=chinaTotal['现有确诊']+chinaTotal['现有疑似']+chinaTotal['累计死亡']+chinaTotal['累计治愈']
confirm_liquid = (Liquid().add("确诊比例", [chinaTotal['现有确诊'] / sum], tooltip_opts=opts.TooltipOpts(),label_opts=opts.LabelOpts(color="#00FFFF",font_size=15,formatter=JsCode("""function (param) {return (Math.floor(param.value * 10000) / 100) + '%';}"""),position="inside",),)
)suspect_liquid = (Liquid().add("疑似比例", [chinaTotal['现有疑似'] / sum], tooltip_opts=opts.TooltipOpts(),label_opts=opts.LabelOpts(color="#FF00FF",font_size=15,formatter=JsCode("""function (param) {return (Math.floor(param.value * 10000) / 100) + '%';}"""),position="inside",),)
)dead_liquid = (Liquid().add("死亡比例", [chinaTotal['累计死亡'] / sum], tooltip_opts=opts.TooltipOpts(),label_opts=opts.LabelOpts(color="#FF0000",font_size=15,formatter=JsCode("""function (param) {return (Math.floor(param.value * 10000) / 100) + '%';}"""),position="inside",),)
)heal_liquid = (Liquid().add("治愈比例", [chinaTotal['累计治愈'] / sum], tooltip_opts=opts.TooltipOpts(),label_opts=opts.LabelOpts(color="#00FF00",font_size=15,formatter=JsCode("""function (param) {return (Math.floor(param.value * 10000) / 100) + '%';}"""),position="inside",),)
)wc = (WordCloud().add("", [list(z) for z in zip(list(city_data["city"]), list(city_data["confirm"]))],word_gap=0, word_size_range=[10, 30]))# 图片汇总
# page = (Page(page_title="COVID-19",layout=Page.DraggablePageLayout)
page = (Page(page_title="COVID-19").add(total_pie).add(world_map).add(area_map).add(area_heat_geo)# .add(bar).add(tl).add(big_title).add(times).add(confirms).add(confirms_people).add(suspects).add(suspects_people).add(deads).add(deads_people).add(heals).add(heals_people).add(confirm_liquid).add(suspect_liquid).add(dead_liquid).add(heal_liquid).add(wc)).render('COVID-19 数据一览.html')with open("COVID-19 数据一览.html", "r+", encoding='utf-8') as html:html_bf = BeautifulSoup(html, 'lxml')divs = html_bf.select('.chart-container')divs[0]['style'] = "width:411px;height:303px;position:absolute;top:5px;left:0px;border-style:solid;border-color:#444444;border-width:0px;"divs[1]["style"] = "width:605px;height:274px;position:absolute;top:36px;left:333px;border-style:solid;border-color:#444444;border-width:0px;"divs[2]["style"] = "width:309px;height:405px;position:absolute;top:313px;left:961px;border-style:solid;border-color:#444444;border-width:0px;"divs[3]["style"] = "width:305px;height:405px;position:absolute;top:310px;left:0px;border-style:solid;border-color:#444444;border-width:0px;"divs[4]["style"] = "width:646px;height:304px;position:absolute;top:312px;left:312px;border-style:solid;border-color:#444444;border-width:0px;"divs[5]["style"] = "width:250px;height:55px;position:absolute;top:2px;left:440px;border-style:solid;border-color:#444444;border-width:0px;"divs[6]["style"] = "width:200px;height:30px;position:absolute;top:11px;left:675px;border-style:solid;border-color:#444444;border-width:0px;"divs[7]['style'] = "width:60px;height:75px;position:absolute;top:5px;left:1060px;border-style:solid;border-color:#DC143C;border-width:3px;border-radius:25px 0px 0px 0px"divs[8]["style"] = "width:130px;height:75px;position:absolute;top:5px;left:1120px;border-style:solid;border-color:#DC143C;border-width:3px;"divs[9]["style"] = "width:60px;height:75px;position:absolute;top:80px;left:1060px;border-style:solid;border-color:#DC143C;border-width:3px;"divs[10]["style"] = "width:130px;height:75px;position:absolute;top:80px;left:1120px;border-style:solid;border-color:#DC143C;border-width:3px;"divs[11]["style"] = "width:60px;height:75px;position:absolute;top:155px;left:1060px;border-style:solid;border-color:#DC143C;border-width:3px;"divs[12]["style"] = "width:130px;height:75px;position:absolute;top:155px;left:1120px;border-style:solid;border-color:#DC143C;border-width:3px;"divs[13]["style"] = "width:60px;height:75px;position:absolute;top:230px;left:1060px;border-style:solid;border-color:#DC143C;border-width:3px;"divs[14]["style"] = "width:130px;height:75px;position:absolute;top:230px;left:1120px;border-style:solid;border-color:#DC143C;border-width:3px;border-radius:0px 0px 25px 0px"divs[15]["style"] = "width:160px;height:160px;position:absolute;top:-35px;left:920px;border-style:solid;border-color:#444444;border-width:0px;"divs[16]["style"] = "width:160px;height:160px;position:absolute;top:40px;left:865px;border-style:solid;border-color:#444444;border-width:0px;"divs[17]["style"] = "width:160px;height:160px;position:absolute;top:115px;left:920px;border-style:solid;border-color:#444444;border-width:0px;"divs[18]["style"] = "width:160px;height:160px;position:absolute;top:188px;left:865px;border-style:solid;border-color:#444444;border-width:0px;"divs[19]["style"] = "width:1280px;height:120px;position:absolute;top:600px;left:0px;border-style:solid;border-color:#444444;border-width:0px;"body = html_bf.find("body")body["style"] = "background-color:#333333;"html_new = str(html_bf)html.seek(0, 0)html.truncate()html.write(html_new)html.close()

然后程序里面用到的 世界各国中英文对照.xlsx
链接：https://pan.baidu.com/s/1t4TjgEMPv8kzkvJY-h5ujA
提取码：8bvl

提取出来放到程序同名文件夹里就行了

PS:

腾讯又改页面了…

以前的每天的数据都消失了，这就没办法了啊，这些数据是我的BI数据大屏的灵魂啊，没了也没办法了，没有这些数据，搭建出来的BI也将会毫无意义。

但是，我又用pyecharts画了个pyecharts-Map3D实现新冠肺炎疫情全国数据立体可视化，效果还不错，有兴趣的可以看看😉

最新：基于Django+Pyecharts的COVID19新冠肺炎疫情监控面板

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