作者:Python进阶者
来源:Python爬虫与数据挖掘
前几天有个粉丝【Lethe】问了一道Pyecharts可视化的问题,如下图所示。
后来原始数据和代码都给到了,需要帮忙看看。
下面是她自己的代码,如下所示:
# 可视化部分 import pandas as pd from pyecharts.charts import Map, Page from pyecharts import options as opts # 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('D:python-basepython实训项目文档国内疫情统计表1.xlsx')
locations = [location for location in df['省']]
values = [value for value in df['当前确诊']]
datas1 = list(zip(locations, values))
data2 = df['省']
data2_list = list(data2) # print(data2_list) data3 = df['当前确诊']
data3_list = list(data3) # print(data3_list) data4 = df['疑似确诊']
data4_list = list(data4)
data5 = df['累计确诊']
data5_list = list(data5)
data6 = df['死亡人数']
data6_list = list(data6)
data7 = df['治愈人数']
data7_list = list(data7)
a = (
Map()
.add("当前确诊", datas1, "china")
.set_global_opts(
title_opts=opts.TitleOpts(),
visualmap_opts=opts.VisualMapOpts(max_=100),
)
)
b = (
Map()
.add("疑似确诊", [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("累计确诊", [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("死亡人数", [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("治愈人数", [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()这行注释掉 # 然后循行这下面 '''
Page.save_resize_html("render.html",
cfg_file="chart_config.json",
dest="my_test.html")
'''
后来【此类生物】修改了下代码,顺利解决了问题,代码如下所示。
# 可视化部分 import pandas as pd from pyecharts.charts import Map, Page from pyecharts import options as opts # 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('国内疫情统计表1.xlsx')
locations = [] for location in df['省']: if "广西" in location:
location = "广西" if "新疆" in location:
location = "新疆" if "宁夏" in location:
location = "宁夏" if "西藏" in location:
location = "西藏" if "内蒙古" in location:
location = "内蒙古" else:
location = location.strip("省市")
locations.append(location)
values = [value for value in df['当前确诊']]
print(values, locations)
datas1 = list(zip(locations, values)) # data2 = locations
data2_list = list(data2)
print(data2_list)
data3 = df['当前确诊']
data3_list = list(data3) # print(data3_list) data4 = df['疑似确诊']
data4_list = list(data4)
data5 = df['累计确诊']
data5_list = list(data5)
data6 = df['死亡人数']
data6_list = list(data6)
data7 = df['治愈人数']
data7_list = list(data7) # # # a = (
Map()
.add("当前确诊", datas1, "china")
.set_global_opts(
title_opts=opts.TitleOpts(),
visualmap_opts=opts.VisualMapOpts(max_=100),
)
) # # # b = (
Map()
.add("疑似确诊", [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("累计确诊", [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("死亡人数", [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("治愈人数", [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()这行注释掉 # 然后循行这下面 '''
Page.save_resize_html("render.html",
cfg_file="chart_config.json",
dest="my_test.html")
'''
顺利解决问题。
其实就是数据处理的问题,关于这个之前有写过文章,惊!Pyecharts作图,发现无数据展示?,感兴趣的可以看下,看完之后就一目了然了。
如果有遇到问题,随时联系我解决,欢迎加入我的Python学习交流群。
大家好,我是Python进阶者。这篇文章主要盘点了一道Pyecharts作图的问题,文中针对该问题给出了具体的解析和代码实现,帮助粉丝顺利解决了问题。
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