python可视化-疫情监控图（1）地图，柱形图

#需要导入的库
from pyecharts import options as opts
from pyecharts.charts import Geo
from pyecharts.globals import ChartType, SymbolType
from pyecharts.charts import Map
import pandas as pd
from pyecharts.charts import Bar
from pyecharts.globals import ThemeType

from pyecharts.charts import Map,Page

数据集：https://www.cnblogs.com/qi-6666/p/15525301.html

或：https://files.cnblogs.com/files/blogs/673788/data.zip?t=1636387982&download=true

地图部分

# 设置列对齐
pd.set_option('display.unicode.ambiguous_as_wide', True)
pd.set_option('display.unicode.east_asian_width', True)
# 打开文件
df = pd.read_excel('china.xlsx')
# 对省份进行统计
data2 = df['省份']
data2_list = list(data2)
data3 = df['累计确诊']
data3_list = list(data3)
data4 = df['死亡']
data4_list = list(data4)
data5 = df ['治愈']
data5_list = list(data5)

c = (
    Map(init_opts=opts.InitOpts(width='600px',height='400px',theme=ThemeType.DARK))
        .add("治愈", [list(z) for z in zip(data2_list, data5_list)], "china")
        .set_global_opts(
        title_opts=opts.TitleOpts(),
        visualmap_opts=opts.VisualMapOpts(max_=200),
    )
)



datamap=[list(z) for z in zip(data2_list, data4_list)]
datamap
pieces = [
    {'max':1,'label':'0','color':'#F5D5C0','symbol':None},
    {'min':1,'max':9,'latel':'1-9','color':'#F5AB7B'},
    {'min':10,'max':99,'latel':'10-99','color':'#EC803A'},
    {'min':100,'max':999,'latel':'100-999','color':'#F2632E'},
    {'min':1000,'max':9999,'latel':'1000-9999','color':'#F0640A'},
    {'min':10000,'label':'>=10000','color':'#E32721'}
]
map=(
    Map(init_opts=opts.InitOpts(width='600px',height='400px',theme=ThemeType.DARK))
#     Map()
    .add("死亡",
        maptype="china",
         data_pair=datamap,
         zoom=1.3,
         is_map_symbol_show=False
        )
    .set_global_opts(#title_opts=opts.TitleOpts(title="死亡"),
                     visualmap_opts=opts.VisualMapOpts(is_piecewise=True,pieces=pieces)
                    )
    .add("",
          maptype="china",
         data_pair=[['安徽',0],['江西',0],['重庆',0],['甘肃',0],['海南',0],['贵州',0],['宁夏',0],['青海',0],['西藏',0]],
         itemstyle_opts=opts.ItemStyleOpts(color="red")
    
    )
)
map.render_notebook()

柱形图部分

 

a2=data2['地区']
b2=data2['自愈']
c2=['英国','巴西','美国','印度']
d2=[140206,607125,764161,457221]
d3=[39713,15268,84276,14323]
# result = data.groupby(by=['地区','自愈'])

from pyecharts import options as opts
from pyecharts.charts import Bar
from pyecharts.globals import ThemeType
bar = (
    Bar(init_opts=opts.InitOpts(width='600px',height='400px',theme=ThemeType.DARK))
    .add_xaxis(c2)
    .add_yaxis('新增确诊',d3)
    .add_yaxis('死亡',d2)
    
    .set_colors([ '#76dd0f','#ff8080'])
#     .legend(loc='upper legt')#'#ff8080'
    .set_global_opts(visualmap_opts=opts.VisualMapOpts(pos_left='80%', pos_bottom=10, pos_right='30%'))
    .set_global_opts(title_opts=opts.TitleOpts(title="新确和死亡人数")
                    )
)

bar.render_notebook()

 

最终结果（本页面只是一部分的代码，数据的爬取和其他图片的呈现请点击主页查看）

 

 

 

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