Create Interactive COVID‑19 Maps and Timelines with Python pyecharts

Hello, I am a Python advanced user sharing a visualization project that turns Baidu's real‑time pandemic data into province‑level maps and a carousel animation.

Preface

A student asked for help with a visualization assignment, which led to this tutorial based on a reference article about creating stunning migration and carousel maps with pyecharts.

Data Source

The data comes from Baidu's real‑time pandemic big‑data report.

Implementation Process

Newly Confirmed Cases

Code and resulting map:

from pyecharts.charts import Map, Timeline
from pyecharts import options as opts

# 准数据
shanxi_city = ["西安市", "延安市", "咸阳市", "渭南市", "安康市", "汉中市", "宝鸡市", "铜川市", "商洛市", "榆林市", "韩城市", "杨凌示范区"]
shanxi_data = [46, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]

# 绘制陕西疫情地图
map = (
    Map()
    .add('陕西省', [(i, j) for i, j in zip(shanxi_city, shanxi_data)], '陕西')
    .set_global_opts(title_opts=opts.TitleOpts(title='陕西省新增感染病例疫情图'), visualmap_opts=opts.VisualMapOpts(max_=50, is_piecewise=True))
)

# 渲染数据
map.render('陕西省新增感染病例疫情图.html')

Existing Cases

Same code with updated data; result:

Cumulative Cases

Same code with cumulative data; result:

Recovered Cases

Same code with recovered data; result:

Death Cases

Same code with death data; result:

Carousel

Code to combine the maps into a timeline carousel:

from pyecharts.charts import Map, Timeline
from pyecharts import options as opts

# 1. 准数据
shanxi_city = ["西安市", "延安市", "咸阳市", "渭南市", "安康市", "汉中市", "宝鸡市", "铜川市", "商洛市", "榆林市", "韩城市", "杨凌示范区"]
xinzeng = [46, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
xianyou = [1747, 13, 11, 1, 0, 0, 0, 0, 0, 0, 0, 0]
leiji = [2094, 21, 31, 18, 26, 26, 13, 8, 7, 3, 1, 1]
zhiyu = [304, 8, 20, 17, 26, 26, 13, 8, 7, 3, 1, 1]
siwang = [3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]

# 2. 绘制新增疫情地图：格式一
map1 = (
    Map(init_opts=opts.InitOpts(width="700px", height="300px", theme="blue"))
    .add('新增病例', [(i, j) for i, j in zip(shanxi_city, xinzeng)], '陕西')
    .set_global_opts(visualmap_opts=opts.VisualMapOpts(max_=50))
)

# 3. 绘制现有疫情地图：格式二
map2 = (
    Map()
    .add('现有病例', [(i, j) for i, j in zip(shanxi_city, xianyou)], '陕西')
    .set_global_opts(visualmap_opts=opts.VisualMapOpts(max_=1750, is_piecewise=True))
)

# 4. 绘制累计疫情地图：格式三
map3 = (
    Map()
    .add('累计病例', [(i, j) for i, j in zip(shanxi_city, leiji)], '陕西')
    .set_global_opts(visualmap_opts=opts.VisualMapOpts(max_=2100, is_piecewise=True))
)

# 5. 绘制治愈疫情地图：格式四
map4 = (
    Map()
    .add('治愈病例', [(i, j) for i, j in zip(shanxi_city, zhiyu)], '陕西')
    .set_global_opts(visualmap_opts=opts.VisualMapOpts(max_=310, is_piecewise=True))
)

# 6. 绘制死亡疫情地图：格式五
map5 = (
    Map()
    .add('死亡病例', [(i, j) for i, j in zip(shanxi_city, siwang)], '陕西')
    .set_global_opts(visualmap_opts=opts.VisualMapOpts(max_=3, is_piecewise=True))
)

# 7. 创建组合类对象
timeline = Timeline(init_opts=opts.InitOpts(width='720px', height='350px'))

# 8. 在组合对象中添加需要组合的图表对象
timeline.add(chart=map1, time_point="陕西省新增病例疫情图")
 timeline.add(chart=map2, time_point="陕西省现有病例疫情图")
 timeline.add(chart=map3, time_point="陕西省累计病例疫情图")
 timeline.add(chart=map4, time_point="陕西省治愈病例疫情图")
 timeline.add(chart=map5, time_point="陕西省死亡病例疫情图")
 timeline.add_schema(is_auto_play=True, play_interval=2000)

# 9. 渲染数据
timeline.render('陕西省疫情轮播图.html')

Summary

This article demonstrates how to obtain Baidu’s real‑time pandemic data and use Python’s pyecharts library to create province‑level maps and an animated carousel for various case categories.