Germany: LK Steinfurt (Nordrhein-Westfalen)¶

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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 14:09:41 CEST
In [2]:
%config InlineBackend.figure_formats = ['svg']
from oscovida import *
In [3]:
overview(country="Germany", subregion="LK Steinfurt", weeks=5);
2023-03-07T14:10:00.567357 image/svg+xml Matplotlib v3.7.1, https://matplotlib.org/ 30 Jan 06 Feb 13 Feb 20 Feb 27 Feb 06 Mar 100 100 150 150 200 200 250 250 7-day incidence rate (per 100K people) 140.2 LK Steinfurt, Germany, last 5 weeks, last data point from 2023-03-06 30 Jan 06 Feb 13 Feb 20 Feb 27 Feb 06 Mar 0 20 40 60 daily change normalised per 100K 30 Jan 06 Feb 13 Feb 20 Feb 27 Feb 06 Mar 0.00 0.05 0.10 0.15 0.20 daily change normalised per 100K 30 Jan 06 Feb 13 Feb 20 Feb 27 Feb 06 Mar 0.8 0.8 1.0 1.0 1.2 1.2 1.4 1.4 R & growth factor (based on cases) Germany-LK Steinfurt cases daily growth factor Germany-LK Steinfurt cases daily growth factor (rolling mean) Germany-LK Steinfurt 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 Steinfurt deaths daily growth factor Germany-LK Steinfurt deaths daily growth factor (rolling mean) Germany-LK Steinfurt estimated R (using deaths) 30 Jan 06 Feb 13 Feb 20 Feb 27 Feb 06 Mar 0 1000 2000 3000 cases doubling time [days] Germany-LK Steinfurt doubling time cases (rolling mean) 0.0 90.0 180.1 270.1 daily change Germany-LK Steinfurt new cases (rolling 7d mean) Germany-LK Steinfurt new cases 0.000 0.225 0.450 0.675 0.900 daily change Germany-LK Steinfurt new deaths (rolling 7d mean) Germany-LK Steinfurt new deaths 0.000 0.288 0.576 0.863
In [4]:
overview(country="Germany", subregion="LK Steinfurt");
2023-03-07T14:10:18.188666 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 7-day incidence rate (per 100K people) 140.2 LK Steinfurt, 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 0 100 200 300 400 daily change normalised per 100K May 20 Sep 20 Jan 21 May 21 Sep 21 Jan 22 May 22 Sep 22 Jan 23 0 1 2 daily change normalised per 100K May 20 Sep 20 Jan 21 May 21 Sep 21 Jan 22 May 22 Sep 22 Jan 23 0.8 0.8 1.0 1.0 1.2 1.2 1.4 1.4 R & growth factor (based on cases) Germany-LK Steinfurt cases daily growth factor Germany-LK Steinfurt cases daily growth factor (rolling mean) Germany-LK Steinfurt 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 Steinfurt deaths daily growth factor Germany-LK Steinfurt deaths daily growth factor (rolling mean) Germany-LK Steinfurt estimated R (using deaths) May 20 Sep 20 Jan 21 May 21 Sep 21 Jan 22 May 22 Sep 22 Jan 23 0 2500 5000 7500 10000 cases doubling time [days] Germany-LK Steinfurt doubling time cases (rolling mean) Germany-LK Steinfurt doubling time deaths (rolling mean) 0 450 900 1351 1801 daily change Germany-LK Steinfurt new cases (rolling 7d mean) Germany-LK Steinfurt new cases 0.0 4.5 9.0 daily change Germany-LK Steinfurt new deaths (rolling 7d mean) Germany-LK Steinfurt new deaths 0.0 125.2 250.3 375.5 500.6 deaths doubling time [days]
In [5]:
compare_plot(country="Germany", subregion="LK Steinfurt", dates="2020-03-15:");
2023-03-07T14:12:35.967647 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 Steinfurt LK Steinfurt 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 Steinfurt Bayern Berlin Bremen Hamburg Hessen Nordrhein-Westfalen Sachsen-Anhalt
In [6]:
# load the data
cases, deaths = germany_get_region(landkreis="LK Steinfurt")

# get population of the region for future normalisation:
inhabitants = population(country="Germany", subregion="LK Steinfurt")
print(f'Population of country="Germany", subregion="LK Steinfurt": {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 Steinfurt": 450176 people
Out[6]:
total cases daily new cases total deaths daily new deaths
date
2023-03-06 214980 68 530 0
2023-03-03 214912 38 530 0
2023-03-02 214874 57 530 0
2023-03-01 214817 184 530 0
2023-02-28 214633 284 530 0
... ... ... ... ...
2020-03-16 29 20 0 0
2020-03-12 9 3 0 0
2020-03-11 6 2 0 0
2020-03-10 4 2 0 0
2020-03-08 2 1 0 0

1038 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: 0:03:07.576344