How to Fix Pyecharts Map Visualization Issues with COVID Data in Python

Introduction

In response to a follower's question about a Pyecharts map that displayed no data, the author explains the issue and shares the original code.

Original Code

# Visualization part
import pandas as pd
from pyecharts.charts import Map, Page
from pyecharts import options as opts

# Set column alignment
pd.set_option('display.unicode.ambiguous_as_wide', True)
pd.set_option('display.unicode.east_asian_width', True)
# Open file
df = pd.read_excel('D:\python-base\python\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)

data3 = df['当前确诊']
data3_list = list(data3)

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)
# Generate render.html
page.render()
# After rendering, comment out page.render() and resize HTML
Page.save_resize_html("render.html", cfg_file="chart_config.json", dest="my_test.html")

Revised Code

# Visualization part
import pandas as pd
from pyecharts.charts import Map, Page
from pyecharts import options as opts

# Set column alignment
pd.set_option('display.unicode.ambiguous_as_wide', True)
pd.set_option('display.unicode.east_asian_width', True)
# Open file
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)

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)
# Generate render.html
page.render()
# After rendering, comment out page.render() and resize HTML
Page.save_resize_html("render.html", cfg_file="chart_config.json", dest="my_test.html")

The revised code correctly normalizes province names, fixes the data alignment, and the map now displays the COVID‑19 statistics as intended.

Conclusion

This article demonstrates how to troubleshoot a Pyecharts map visualization problem by cleaning the source data and adjusting the Python code, providing a practical solution for developers working with data visualization in Python.