README.md

Plot COVID-19 data on the city of Kassel. Data source is the city's own dedicated website which was scraped from a bot who posted changes in IRC. These changes have then been scraped again using some regexes:

echo 'day,time,county,total,total_rel,recovered,recovered_rel,infected,infected_rel,dead,dead_rel' > covid-ks-$(date -I).csv
grep -E 'Kassel (Stadt|Land):.+tot$' ~/.weechat/logs/irc.freenode.\#flipdot.weechatlog | sed -re 's/(,|\[psa\]|insgesamt|genesen|infiziert|tot|\)|\+|Kassel)//g' -e 's/@flipbot//' -e 's/(: )/ /g' -e 's/Stadt/0/' -e 's/Land/1/g' -e 's/(\s|\t|\(| )+/,/g' -e 's/,$//' >> covid-ks-$(date -I).csv

To see interactive plots, download the necessary libraries first:

pip install --user pandas matplotlib

After successful installation run the downloaded Python script in the same folder that the csv file resides in:

python3 covid-ks.py

covid-ks-2020-05-09.csv

covid-ks.py

#!/usr/bin/env python3
import pylab as plt
import pandas as pd
import matplotlib.dates as mdates

interest = {
    'infected': 'Infiziert',
    'recovered': 'Genesen',
    'dead': 'Gestorben',
}
areas = {
    0: 'Kassel Stadt',
    1: 'Kassel Land',
}

formatter = mdates.DateFormatter('%Y-%b-%d')
df = pd.read_csv('covid-ks-2020-05-09.csv', parse_dates={'date': [0, 1]})
fig, ax = plt.subplots(len(interest), sharex=True)

for i, (k_i, l_i) in enumerate(interest.items()):
    for k_a, l_a in areas.items():
        ax[i].plot(df[df.county == k_a].date, df[df.county == k_a][k_i], label=l_a)
    ax[i].set_title(l_i)
    ax[i].xaxis_date()
    ax[i].xaxis.set_major_formatter(formatter)
    ax[i].legend()
plt.show()