Some calculations about the velocity of the Austrian vaccination campaign

impfungen_at.py

import pandas as pd
import matplotlib.pyplot as plt
import matplotlib.dates
import matplotlib.ticker
import seaborn as sns

# Get from https://info.gesundheitsministerium.gv.at/?re=opendata
bbg = pd.read_csv('timeline-bbg.csv', sep=';')
states = pd.read_csv('timeline-bundeslaendermeldungen.csv', sep=';')
states['BundeslandID'].replace(0, -1, inplace=True)

merged = bbg.merge(states, on=['Datum', 'BundeslandID'], how='outer', suffixes=('', '_y'))
merged['Name'].fillna(merged['Name_y'], inplace=True)
merged['Bevölkerung'].fillna(merged['Bevölkerung_y'], inplace=True)
merged.drop(['Name_y', 'Bevölkerung_y'], 'columns', inplace=True)
merged['ImpfungProAuslieferung'] = merged['GemeldeteImpfungenLaender'] / merged['Auslieferungen']
merged.sort_values(by='Datum', inplace=True)

events = merged.melt(
    id_vars=['Datum', 'BundeslandID', 'Name'],
    value_vars=['Auslieferungen', 'Bestellungen', 'GemeldeteImpfungenLaender'],
    var_name="event")
events.sort_values(by=['Datum', 'event'], inplace=True)

fig, ax = plt.subplots()
SEL = ('Steiermark', 'Oberösterreich', 'Niederösterreich')
sns.lineplot(x='Datum', y='value', style="event", hue="Name", data=events[events['Name'].isin(SEL)], ax=ax, style_order=['GemeldeteImpfungenLaender', 'Auslieferungen', 'Bestellungen'])
#sns.lineplot(x='Datum', y='ImpfungProAuslieferung', hue="Name", data=merged[merged['Name'].isin(SEL)])
ax.xaxis.set_major_locator(matplotlib.dates.WeekdayLocator(
    byweekday=matplotlib.dates.MO, interval=1))
ax.xaxis.set_major_formatter(matplotlib.dates.DateFormatter("KW%W"))
fig.autofmt_xdate()