Germany: LK Traunstein (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 11:28:53 CEST
In [2]:
%config InlineBackend.figure_formats = ['svg']
from oscovida import *
In [3]:
overview(country="Germany", subregion="LK Traunstein", weeks=5);
2023-03-07T11:29:10.748960 image/svg+xml Matplotlib v3.7.1, https://matplotlib.org/ 30 Jan 06 Feb 13 Feb 20 Feb 27 Feb 06 Mar 40 40 60 60 80 80 100 100 7-day incidence rate (per 100K people) 40.3 LK Traunstein, Germany, last 5 weeks, last data point from 2023-03-06 30 Jan 06 Feb 13 Feb 20 Feb 27 Feb 06 Mar 0 5 10 15 20 daily change normalised per 100K 30 Jan 06 Feb 13 Feb 20 Feb 27 Feb 06 Mar 0.0 0.2 0.4 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 Traunstein cases daily growth factor Germany-LK Traunstein cases daily growth factor (rolling mean) Germany-LK Traunstein estimated R (using cases) 30 Jan 06 Feb 13 Feb 20 Feb 27 Feb 06 Mar 0 0 2 2 4 4 6 6 R & growth factor (based on deaths) Germany-LK Traunstein deaths daily growth factor Germany-LK Traunstein deaths daily growth factor (rolling mean) Germany-LK Traunstein estimated R (using deaths) 30 Jan 06 Feb 13 Feb 20 Feb 27 Feb 06 Mar 0 2500 5000 7500 10000 cases doubling time [days] Germany-LK Traunstein doubling time cases (rolling mean) 0.00 8.92 17.84 26.77 35.69 daily change Germany-LK Traunstein new cases (rolling 7d mean) Germany-LK Traunstein new cases 0.000 0.357 0.714 daily change Germany-LK Traunstein new deaths (rolling 7d mean) Germany-LK Traunstein new deaths 0.000 0.230 0.460 0.689 0.919
In [4]:
overview(country="Germany", subregion="LK Traunstein");
2023-03-07T11:29:30.169439 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 May 23 0 0 1000 1000 2000 2000 3000 3000 7-day incidence rate (per 100K people) 40.3 LK Traunstein, 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 May 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 May 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 May 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 Traunstein cases daily growth factor Germany-LK Traunstein cases daily growth factor (rolling mean) Germany-LK Traunstein estimated R (using cases) Jan 20 May 20 Sep 20 Jan 21 May 21 Sep 21 Jan 22 May 22 Sep 22 Jan 23 May 23 0 0 2 2 4 4 6 6 R & growth factor (based on deaths) Germany-LK Traunstein deaths daily growth factor Germany-LK Traunstein deaths daily growth factor (rolling mean) Germany-LK Traunstein estimated R (using deaths) Jan 20 May 20 Sep 20 Jan 21 May 21 Sep 21 Jan 22 May 22 Sep 22 Jan 23 May 23 0 2500 5000 7500 10000 cases doubling time [days] Germany-LK Traunstein doubling time cases (rolling mean) Germany-LK Traunstein doubling time deaths (rolling mean) 0 357 714 1071 daily change Germany-LK Traunstein new cases (rolling 7d mean) Germany-LK Traunstein new cases 0.000 1.784 3.569 5.353 daily change Germany-LK Traunstein new deaths (rolling 7d mean) Germany-LK Traunstein new deaths 0.0 85.4 170.8 256.2 341.6 deaths doubling time [days]
In [5]:
compare_plot(country="Germany", subregion="LK Traunstein", dates="2020-03-15:");
2023-03-07T11:32:10.588703 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 Traunstein LK Traunstein 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 Traunstein Bayern Berlin Bremen Hamburg Hessen Nordrhein-Westfalen Sachsen-Anhalt
In [6]:
# load the data
cases, deaths = germany_get_region(landkreis="LK Traunstein")

# get population of the region for future normalisation:
inhabitants = population(country="Germany", subregion="LK Traunstein")
print(f'Population of country="Germany", subregion="LK Traunstein": {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 Traunstein": 178447 people
Out[6]:
total cases daily new cases total deaths daily new deaths
date
2023-03-06 100282 9 424 0
2023-03-05 100273 1 424 0
2023-03-03 100272 7 424 0
2023-03-02 100265 18 424 0
2023-03-01 100247 10 424 0
... ... ... ... ...
2020-03-14 10 2 0 0
2020-03-13 8 1 0 0
2020-03-11 7 3 0 0
2020-02-06 4 1 0 0
2020-02-04 3 1 0 0

1022 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: 0:03:38.846948