Germany: LK Emsland (Niedersachsen)¶

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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 13:07:34 CEST
In [2]:
%config InlineBackend.figure_formats = ['svg']
from oscovida import *
In [3]:
overview(country="Germany", subregion="LK Emsland", weeks=5);
2023-03-07T13:07:50.285548 image/svg+xml Matplotlib v3.7.1, https://matplotlib.org/ 30 Jan 06 Feb 13 Feb 20 Feb 27 Feb 06 Mar 100 100 150 150 200 200 7-day incidence rate (per 100K people) 89.3 LK Emsland, 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 40 daily change normalised per 100K 30 Jan 06 Feb 13 Feb 20 Feb 27 Feb 06 Mar 0.0 0.1 0.2 0.3 daily change normalised per 100K 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 Emsland cases daily growth factor Germany-LK Emsland cases daily growth factor (rolling mean) Germany-LK Emsland estimated R (using cases) 30 Jan 06 Feb 13 Feb 20 Feb 27 Feb 06 Mar 0 0 1 1 2 2 3 3 4 4 R & growth factor (based on deaths) Germany-LK Emsland deaths daily growth factor Germany-LK Emsland deaths daily growth factor (rolling mean) Germany-LK Emsland estimated R (using deaths) 30 Jan 06 Feb 13 Feb 20 Feb 27 Feb 06 Mar 0 2000 4000 cases doubling time [days] Germany-LK Emsland doubling time cases (rolling mean) 0.0 33.1 66.3 99.4 132.6 daily change Germany-LK Emsland new cases (rolling 7d mean) Germany-LK Emsland new cases 0.000 0.331 0.663 0.994 daily change Germany-LK Emsland new deaths (rolling 7d mean) Germany-LK Emsland new deaths 0.000 0.388 0.776
In [4]:
overview(country="Germany", subregion="LK Emsland");
2023-03-07T13:08:05.190120 image/svg+xml Matplotlib v3.7.1, https://matplotlib.org/ May 20 Sep 20 Jan 21 May 21 Sep 21 Jan 22 May 22 Sep 22 Jan 23 0 0 1000 1000 2000 2000 3000 3000 7-day incidence rate (per 100K people) 89.3 LK Emsland, Germany, last data point from 2023-03-06 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 May 20 Sep 20 Jan 21 May 21 Sep 21 Jan 22 May 22 Sep 22 Jan 23 0.0 0.5 1.0 1.5 2.0 daily change normalised per 100K 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 Emsland cases daily growth factor Germany-LK Emsland cases daily growth factor (rolling mean) Germany-LK Emsland estimated R (using cases) May 20 Sep 20 Jan 21 May 21 Sep 21 Jan 22 May 22 Sep 22 Jan 23 0 0 1 1 2 2 3 3 4 4 R & growth factor (based on deaths) Germany-LK Emsland deaths daily growth factor Germany-LK Emsland deaths daily growth factor (rolling mean) Germany-LK Emsland estimated R (using deaths) May 20 Sep 20 Jan 21 May 21 Sep 21 Jan 22 May 22 Sep 22 Jan 23 0 5000 10000 15000 cases doubling time [days] Germany-LK Emsland doubling time cases (rolling mean) Germany-LK Emsland doubling time deaths (rolling mean) 0 663 1326 1988 daily change Germany-LK Emsland new cases (rolling 7d mean) Germany-LK Emsland new cases 0.000 1.657 3.314 4.971 6.628 daily change Germany-LK Emsland new deaths (rolling 7d mean) Germany-LK Emsland new deaths 0.0 173.7 347.3 521.0 deaths doubling time [days]
In [5]:
compare_plot(country="Germany", subregion="LK Emsland", dates="2020-03-15:");
2023-03-07T13:10:15.841560 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 Emsland LK Emsland 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 Emsland Bayern Berlin Bremen Hamburg Hessen Nordrhein-Westfalen Sachsen-Anhalt
In [6]:
# load the data
cases, deaths = germany_get_region(landkreis="LK Emsland")

# get population of the region for future normalisation:
inhabitants = population(country="Germany", subregion="LK Emsland")
print(f'Population of country="Germany", subregion="LK Emsland": {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 Emsland": 331397 people
Out[6]:
total cases daily new cases total deaths daily new deaths
date
2023-03-06 194732 9 467 0
2023-03-05 194723 9 467 0
2023-03-04 194714 16 467 0
2023-03-03 194698 48 467 0
2023-03-02 194650 28 467 0
... ... ... ... ...
2020-03-14 19 10 1 0
2020-03-13 9 5 1 0
2020-03-12 4 1 1 1
2020-03-11 3 1 0 0
2020-03-10 2 1 0 0

1026 rows × 4 columns

Explore the data in your web browser¶

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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: 0:02:49.177855