Germany: LK Freising (Bayern)¶

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In [1]:
import datetime
import time

start = datetime.datetime.now()
print(f"Notebook executed on: {start.strftime('%d/%m/%Y %H:%M:%S%Z')} {time.tzname[time.daylight]}")

Notebook executed on: 07/03/2023 10:48:04 CEST
In [2]:
%config InlineBackend.figure_formats = ['svg']
from oscovida import *
In [3]:
overview(country="Germany", subregion="LK Freising", weeks=5);
2023-03-07T10:48:17.851827 image/svg+xml Matplotlib v3.7.1, https://matplotlib.org/ 30 Jan 06 Feb 13 Feb 20 Feb 27 Feb 06 Mar 60 60 80 80 100 100 120 120 7-day incidence rate (per 100K people) 54.7 LK Freising, Germany, last 5 weeks, last data point from 2023-03-06 30 Jan 06 Feb 13 Feb 20 Feb 27 Feb 06 Mar 0 10 20 30 daily change normalised per 100K 30 Jan 06 Feb 13 Feb 20 Feb 27 Feb 06 Mar 0.00 0.00 0.05 0.05 0.10 0.10 daily change Germany-LK Freising new deaths (rolling 7d mean) Germany-LK Freising new deaths 30 Jan 06 Feb 13 Feb 20 Feb 27 Feb 06 Mar 0.6 0.6 0.8 0.8 1.0 1.0 1.2 1.2 R & growth factor (based on cases) Germany-LK Freising cases daily growth factor Germany-LK Freising cases daily growth factor (rolling mean) Germany-LK Freising estimated R (using cases) 30 Jan 06 Feb 13 Feb 20 Feb 27 Feb 06 Mar 0.8 0.8 0.9 0.9 1.0 1.0 1.1 1.1 1.2 1.2 R & growth factor (based on deaths) Germany-LK Freising deaths daily growth factor Germany-LK Freising deaths daily growth factor (rolling mean) Germany-LK Freising estimated R (using deaths) 30 Jan 06 Feb 13 Feb 20 Feb 27 Feb 06 Mar 0 2000 4000 6000 cases doubling time [days] Germany-LK Freising doubling time cases (rolling mean) 0.00 18.11 36.23 54.34 daily change Germany-LK Freising new cases (rolling 7d mean) Germany-LK Freising new cases 0.000 0.260 0.521 0.781
In [4]:
overview(country="Germany", subregion="LK Freising");
2023-03-07T10:48:34.976870 image/svg+xml Matplotlib v3.7.1, https://matplotlib.org/ Jan 20 May 20 Sep 20 Jan 21 May 21 Sep 21 Jan 22 May 22 Sep 22 Jan 23 0 0 1000 1000 2000 2000 7-day incidence rate (per 100K people) 54.7 LK Freising, Germany, last data point from 2023-03-06 Jan 20 May 20 Sep 20 Jan 21 May 21 Sep 21 Jan 22 May 22 Sep 22 Jan 23 0 200 400 600 daily change normalised per 100K Jan 20 May 20 Sep 20 Jan 21 May 21 Sep 21 Jan 22 May 22 Sep 22 Jan 23 0 1 2 3 daily change normalised per 100K Jan 20 May 20 Sep 20 Jan 21 May 21 Sep 21 Jan 22 May 22 Sep 22 Jan 23 0.6 0.6 0.8 0.8 1.0 1.0 1.2 1.2 R & growth factor (based on cases) Germany-LK Freising cases daily growth factor Germany-LK Freising cases daily growth factor (rolling mean) Germany-LK Freising estimated R (using cases) Jan 20 May 20 Sep 20 Jan 21 May 21 Sep 21 Jan 22 May 22 Sep 22 Jan 23 0.8 0.8 0.9 0.9 1.0 1.0 1.1 1.1 1.2 1.2 R & growth factor (based on deaths) Germany-LK Freising deaths daily growth factor Germany-LK Freising deaths daily growth factor (rolling mean) Germany-LK Freising estimated R (using deaths) Jan 20 May 20 Sep 20 Jan 21 May 21 Sep 21 Jan 22 May 22 Sep 22 Jan 23 0 2000 4000 6000 cases doubling time [days] Germany-LK Freising doubling time cases (rolling mean) Germany-LK Freising doubling time deaths (rolling mean) 0 362 725 1087 daily change Germany-LK Freising new cases (rolling 7d mean) Germany-LK Freising new cases 0.000 1.811 3.623 5.434 daily change Germany-LK Freising new deaths (rolling 7d mean) Germany-LK Freising new deaths 0.0 47.8 95.7 143.5 deaths doubling time [days]
In [5]:
compare_plot(country="Germany", subregion="LK Freising", dates="2020-03-15:");
2023-03-07T10:51:18.648090 image/svg+xml Matplotlib v3.7.1, https://matplotlib.org/ 2020-05 2020-09 2021-01 2021-05 2021-09 2022-01 2022-05 2022-09 2023-01 0.1 0.1 1 1 10 10 100 100 daily new cases (rolling 7-day mean) normalised by 100K people Daily cases (top) and deaths (below) for Germany: LK Freising LK Freising Bayern Berlin Bremen Hamburg Hessen Nordrhein-Westfalen Sachsen-Anhalt 2020-05 2020-09 2021-01 2021-05 2021-09 2022-01 2022-05 2022-09 2023-01 0.001 0.001 0.01 0.01 0.1 0.1 1 1 daily new deaths (rolling 7-day mean) normalised by 100K people LK Freising Bayern Berlin Bremen Hamburg Hessen Nordrhein-Westfalen Sachsen-Anhalt
In [6]:
# load the data
cases, deaths = germany_get_region(landkreis="LK Freising")

# get population of the region for future normalisation:
inhabitants = population(country="Germany", subregion="LK Freising")
print(f'Population of country="Germany", subregion="LK Freising": {inhabitants} people')

# compose into one table
table = compose_dataframe_summary(cases, deaths)

# show tables with up to 1000 rows
pd.set_option("display.max_rows", 1000)

# display the table
table

Population of country="Germany", subregion="LK Freising": 181144 people
Out[6]:
total cases daily new cases total deaths daily new deaths
date
2023-03-06 91396 2 258 0
2023-03-05 91394 2 258 0
2023-03-04 91392 3 258 0
2023-03-03 91389 9 258 0
2023-03-02 91380 9 258 0
... ... ... ... ...
2020-03-07 26 3 0 0
2020-03-06 23 19 0 0
2020-03-05 4 1 0 0
2020-03-04 3 1 0 0
2020-03-01 2 1 0 0

1006 rows × 4 columns

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Acknowledgements:¶

  • Johns Hopkins University provides data for countries
  • Robert Koch Institute provides data for within Germany
  • Atlo Team for gathering and providing data from Hungary (https://atlo.team/koronamonitor/)
  • Open source and scientific computing community for the data tools
  • Github for hosting repository and html files
  • Project Jupyter for the Notebook and binder service
  • The H2020 project Photon and Neutron Open Science Cloud (PaNOSC)
In [7]:
print(f"Download of data from Johns Hopkins university: cases at {fetch_cases_last_execution()} and "
      f"deaths at {fetch_deaths_last_execution()}.")

Download of data from Johns Hopkins university: cases at 07/03/2023 09:31:22 and deaths at 07/03/2023 09:31:21.
In [8]:
# to force a fresh download of data, run "clear_cache()"
In [9]:
print(f"Notebook execution took: {datetime.datetime.now()-start}")

Notebook execution took: 0:03:37.702971