Create a simple chart showing the development of the COVID-19 7 day incidence score in your city

README.md

7 day incidence development chart

A Python script that creates a simple chart showing the development of the COVID-19 7 day incidence in your city (or cities of interest).

Data is taken from lgl.bayern.de so it works only for cities in Bayern, Germany.

How to use

Run the script with the names of the cities you want to have charted:

$ ./chart.py 'Erlangen' 'Fürth Stadt' 'Nürnberg Stadt'

The script should run every day so you see you the 7 day incidence is developing over time.

The script generates chart.png that contains the chart.

chart.py

#!/usr/bin/env python3

import json
import matplotlib.pyplot as plt
import re
import requests
import sys

from datetime import datetime, timedelta
from lxml import etree, html as lxmlhtml
from os import path


def extract_date(html):
    pattern = b'<script>var publikationsDatum = "'
    pos = html.find(pattern)
    if pos < 0:
        return None
    pos += len(pattern)
    date = html[pos:pos + 10].decode('utf-8')
    return datetime.strptime(date, '%d.%m.%Y')


def file_name_for_date(date):
    return date.strftime('%Y%m%d')


def fetch(cities):
    html = requests.get(
        'https://www.lgl.bayern.de/gesundheit/infektionsschutz/infektionskrankheiten_a_z/coronavirus/karte_coronavirus/'
    ).content
    date = extract_date(html)
    if date is None:
        return None
    file_name = file_name_for_date(date)
    tree = lxmlhtml.fromstring(html)
    stats = {}
    for city in cities:
        for td in tree.xpath(
            '//table[@id="tableLandkreise"]/tr/td[text() = "%s"]' % (city, ),
        ):
            tr = td.getparent()
            name = tr.xpath('td[1]')[0].text_content()
            total = tr.xpath('td[2]')[0].text_content()
            change = tr.xpath('td[3]')[0].text_content()
            if change == '-':
                change = '0'
            seven = tr.xpath('td[6]')[0].text_content()
            stats[name] = {
                'total': int(total.replace('.', '')),
                'change': int(change.strip('()').replace(' ', '')),
                'seven': float(seven.replace(',', '.')),
            }
    with open(file_name, 'w') as f:
        json.dump(stats, f)
    return date


def main(cities):
    if not cities or len(cities) < 1:
        cities = ['Fürth Stadt', 'Nürnberg Stadt']
    date = fetch(cities)
    if date is None:
        return
    days = []
    changes = {}
    for i in range(-6, 1):
        d = date + timedelta(days=i)
        file_name = file_name_for_date(d)
        if path.isfile(file_name):
            with open(file_name) as f:
                stats = json.load(f)
                days.append(d.strftime('%a %d'))
                for city in cities:
                    if city not in changes:
                        changes[city] = []
                    changes[city].append(stats[city]['seven'])
    for city in cities:
        plt.plot(days, changes[city], marker='o', label=city)
    plt.legend()
    plt.title('Entwicklung 7 Tage Inzidenz pro 100.000 Einwohner')
    plt.xlabel('Datum')
    plt.ylabel('Inzidenz')
    plt.savefig('chart.png')


if __name__ == '__main__':
    main(sys.argv[1:])