Making a real-time data map of the coronavirus in Python

4 min readFeb 12, 2020

The daily data change of the epidemic affects the hearts of millions of people. How I hope that the news of the epidemic being overcome will come as soon as I wake up.

The first thing I wake up every morning is to look at the changes in the number of confirmed patients. I believe that many of my friends are the same as me. I am a programmer, and I have made such a small program at home, which generates data distribution maps in real-time through Python, which can be the whole country or each province. Technology sharing, we fight the epidemic together.

(The data taken from the website may not be very accurate, mainly for technology sharing, but also forgive me)

National Data Map

Hubei Province

Zhejiang Province

Let’s take a look at the code with everyone!

Here with the help of pyecharts

1.First import the required modules

import requests
import json
import refrom pyecharts.charts 
import Mapfrom pyecharts 
import options

Import these modules from the command line

Import module

pip3 install requests

pip3 install json

pip3 install re

pip3 install pyecharts

In addition to the above modules need to be imported.

In turn, it is a global map, a provincial map of China, a city map of China, a county map of China, and a map of China’s regions.

Map import as needed

pip3 install echarts-countries-pypkg

pip3 install echarts-china-provinces-pypkg

pip3 install echarts-china-cities-pypkg

pip3 install echarts-china-counties-pypkg

pip3 install echarts-china-misc-pypkg

2. Get data-process data;

#send request, collect data

result= requests.get('https://interface.sina.cn/news/wap/fymap2020_data.d.json?1580097300739&&callback=sinajp_1580097300873005379567841634181')

# handle the data

json_str = re.search("\(+([^)]*)\)+", result.text).group(1)html = f"{json_str}"table = json.loads(f"{html}")

3. Generate maps, explained in detail later;

province_data = [] # loop to read the data for each province

for province in table['data']['list']: province_data.append((province['name'], province['value'])) city_data = []

#get data for each city

for city in province['city']:

city_data.append((city['mapName'], city['conNum']))

map_province = Map()

map_province.set_global_opts(title_opts=options.TitleOpts(title=province['name'] + "实时疫情图-确诊人数：" + province['value']), v visualmap_opts=options.VisualMapOpts(is_piecewise=True,

pieces=[ {"min": 1000, "label": '>1000人', "color": "#6F171F"}, {"min": 500, "max": 1000, "label": '500-1000人', "color": "#C92C34"}, {"min": 100, "max": 499, "label": '100-499人', "color": "#E35B52"}, {"min": 10, "max": 99, "label": '10-99人', "color": "#F39E86"}, {"min": 1, "max": 9, "label": '1-9人', "color": "#FDEBD0"}]))

map_province.add("确诊", city_data, maptype = province['name'])

map_province.render(province['name'] + ".html")

map_country = Map()

map_country.set_global_opts(title_opts=options.TitleOpts(title="中国实时疫情图-确诊人数：" + table['data']["gntotal"]),

visualmap_opts=options.VisualMapOpts(is_piecewise=True,

map_country.add("确诊", province_data, maptype="china")

map_country.render("country.html") """#world地图，没有详细去完善了，有兴趣的可以试试。 data=[] for country in table['data']['worldlist']: data.append((country['name'], country['value']))print(data) map_country = Map()map_country.set_global_opts(title_opts=options.TitleOpts(title="世界实时疫情图"), visualmap_opts=options.VisualMapOpts(max_=1000))map_country.add("确诊", data, maptype="world")map_country.render("world.html")

# generate the HTML file """

print("complete！！！")

Part of the code explained:

(1)

#Add province data to the list

province_data.append ((province [‘name’], province [‘value’]))

Take out the corresponding value in the data and add it to province_data.

(2)

title_opts = options.TitleOpts (title = “A”)

A is the red framed part of the generated map.