作者：Python進(jìn)階者

來(lái)源：Python爬蟲(chóng)與數(shù)據(jù)挖掘

一、前言

前幾天有個(gè)粉絲【Lethe】問(wèn)了一道Pyecharts可視化的問(wèn)題，如下圖所示。

后來(lái)原始數(shù)據(jù)和代碼都給到了，需要幫忙看看。

二、實(shí)現(xiàn)過(guò)程

下面是她自己的代碼，如下所示：

# 可視化部分 import pandas as pd from pyecharts.charts import Map, Page from pyecharts import options as opts # 設(shè)置列對(duì)齊 pd.set_option('display.unicode.ambiguous_as_wide', True)
pd.set_option('display.unicode.east_asian_width', True) # 打開(kāi)文件 df = pd.read_excel('D:python-basepython實(shí)訓(xùn)項(xiàng)目文檔國(guó)內(nèi)疫情統(tǒng)計(jì)表1.xlsx')

locations = [location for location in df['省']]
values = [value for value in df['當(dāng)前確診']]
datas1 = list(zip(locations, values))

data2 = df['省']
data2_list = list(data2) # print(data2_list) data3 = df['當(dāng)前確診']
data3_list = list(data3) # print(data3_list) data4 = df['疑似確診']
data4_list = list(data4)

data5 = df['累計(jì)確診']
data5_list = list(data5)
data6 = df['死亡人數(shù)']
data6_list = list(data6)
data7 = df['治愈人數(shù)']
data7_list = list(data7)

a = (
    Map()
        .add("當(dāng)前確診", datas1, "china")
        .set_global_opts(
        title_opts=opts.TitleOpts(),
        visualmap_opts=opts.VisualMapOpts(max_=100),
    )
)

b = (
    Map()
        .add("疑似確診", [list(z) for z in zip(data2_list, data4_list)], "china")
        .set_global_opts(
        title_opts=opts.TitleOpts(),
        visualmap_opts=opts.VisualMapOpts(max_=200),
    )
)

c = (
    Map()
        .add("累計(jì)確診", [list(z) for z in zip(data2_list, data5_list)], "china")
        .set_global_opts(
        title_opts=opts.TitleOpts(),
        visualmap_opts=opts.VisualMapOpts(max_=200),
    )
)

d = (
    Map()
        .add("死亡人數(shù)", [list(z) for z in zip(data2_list, data6_list)], "china")
        .set_global_opts(
        title_opts=opts.TitleOpts(),
        visualmap_opts=opts.VisualMapOpts(max_=200),
    )
)

e = (
    Map()
        .add("治愈人數(shù)", [list(z) for z in zip(data2_list, data7_list)], "china")
        .set_global_opts(
        title_opts=opts.TitleOpts(),
        visualmap_opts=opts.VisualMapOpts(max_=200),
    )
)

page = Page(layout=Page.DraggablePageLayout)
page.add(
    a,
    b,
    c,
    d,
    e,
) # 先生成render.html文件 page.render() # 完成上一步之后把 page.render()這行注釋掉 # 然后循行這下面 '''
Page.save_resize_html("render.html",
    cfg_file="chart_config.json",
    dest="my_test.html")
''' 

后來(lái)【此類生物】修改了下代碼，順利解決了問(wèn)題，代碼如下所示。

# 可視化部分 import pandas as pd from pyecharts.charts import Map, Page from pyecharts import options as opts # 設(shè)置列對(duì)齊 pd.set_option('display.unicode.ambiguous_as_wide', True)
pd.set_option('display.unicode.east_asian_width', True) # 打開(kāi)文件 df = pd.read_excel('國(guó)內(nèi)疫情統(tǒng)計(jì)表1.xlsx')
locations = [] for location in df['省']: if "廣西" in location:
        location = "廣西" if "新疆" in location:
        location = "新疆" if "寧夏" in location:
        location = "寧夏" if "西藏" in location:
        location = "西藏" if "內(nèi)蒙古" in location:
        location = "內(nèi)蒙古" else:
        location = location.strip("省市")
    locations.append(location)

values = [value for value in df['當(dāng)前確診']]
print(values, locations)
datas1 = list(zip(locations, values)) # data2 = locations
data2_list = list(data2)
print(data2_list)

data3 = df['當(dāng)前確診']
data3_list = list(data3) # print(data3_list) data4 = df['疑似確診']
data4_list = list(data4)

data5 = df['累計(jì)確診']
data5_list = list(data5)
data6 = df['死亡人數(shù)']
data6_list = list(data6)
data7 = df['治愈人數(shù)']
data7_list = list(data7) # # # a = (
    Map()
        .add("當(dāng)前確診", datas1, "china")
        .set_global_opts(
        title_opts=opts.TitleOpts(),
        visualmap_opts=opts.VisualMapOpts(max_=100),
    )
) # # # b = (
    Map()
        .add("疑似確診", [list(z) for z in zip(data2_list, data4_list)], "china")
        .set_global_opts(
        title_opts=opts.TitleOpts(),
        visualmap_opts=opts.VisualMapOpts(max_=200),
    )
)

c = (
    Map()
        .add("累計(jì)確診", [list(z) for z in zip(data2_list, data5_list)], "china")
        .set_global_opts(
        title_opts=opts.TitleOpts(),
        visualmap_opts=opts.VisualMapOpts(max_=200),
    )
)

d = (
    Map()
        .add("死亡人數(shù)", [list(z) for z in zip(data2_list, data6_list)], "china")
        .set_global_opts(
        title_opts=opts.TitleOpts(),
        visualmap_opts=opts.VisualMapOpts(max_=200),
    )
)

e = (
    Map()
        .add("治愈人數(shù)", [list(z) for z in zip(data2_list, data7_list)], "china")
        .set_global_opts(
        title_opts=opts.TitleOpts(),
        visualmap_opts=opts.VisualMapOpts(max_=200),
    )
)

page = Page(layout=Page.DraggablePageLayout)
page.add(
    a,
    b,
    c,
    d,
    e,
) # 先生成render.html文件 page.render() # 完成上一步之后把 page.render()這行注釋掉 # 然后循行這下面 '''
Page.save_resize_html("render.html",
    cfg_file="chart_config.json",
    dest="my_test.html")
''' 

順利解決問(wèn)題。

其實(shí)就是數(shù)據(jù)處理的問(wèn)題，關(guān)于這個(gè)之前有寫(xiě)過(guò)文章，驚！Pyecharts作圖，發(fā)現(xiàn)無(wú)數(shù)據(jù)展示？，感興趣的可以看下，看完之后就一目了然了。

如果有遇到問(wèn)題，隨時(shí)聯(lián)系我解決，歡迎加入我的Python學(xué)習(xí)交流群。

三、總結(jié)

大家好，我是Python進(jìn)階者。這篇文章主要盤(pán)點(diǎn)了一道Pyecharts作圖的問(wèn)題，文中針對(duì)該問(wèn)題給出了具體的解析和代碼實(shí)現(xiàn)，幫助粉絲順利解決了問(wèn)題。