Germany: SK Regensburg (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 11:51:18 CEST
In [2]:
%config InlineBackend.figure_formats = ['svg']
from oscovida import *
In [3]:
overview(country="Germany", subregion="SK Regensburg", weeks=5);
2023-03-07T11:51:34.233746 image/svg+xml Matplotlib v3.7.1, https://matplotlib.org/ 30 Jan 06 Feb 13 Feb 20 Feb 27 Feb 06 Mar 100 100 120 120 140 140 160 160 7-day incidence rate (per 100K people) 99.6 SK Regensburg, 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 0.2 0.4 0.6 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 R & growth factor (based on cases) Germany-SK Regensburg cases daily growth factor Germany-SK Regensburg cases daily growth factor (rolling mean) Germany-SK Regensburg 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-SK Regensburg deaths daily growth factor Germany-SK Regensburg deaths daily growth factor (rolling mean) Germany-SK Regensburg 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-SK Regensburg doubling time cases (rolling mean) 0.00 15.35 30.71 46.06 61.42 daily change Germany-SK Regensburg new cases (rolling 7d mean) Germany-SK Regensburg new cases 0.000 0.307 0.614 0.921 daily change Germany-SK Regensburg new deaths (rolling 7d mean) Germany-SK Regensburg new deaths 0.000 0.256 0.513 0.769
In [4]:
overview(country="Germany", subregion="SK Regensburg");
2023-03-07T11:51:51.748820 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) 99.6 SK Regensburg, 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 0 250 500 750 1000 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 3 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 R & growth factor (based on cases) Germany-SK Regensburg cases daily growth factor Germany-SK Regensburg cases daily growth factor (rolling mean) Germany-SK Regensburg 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-SK Regensburg deaths daily growth factor Germany-SK Regensburg deaths daily growth factor (rolling mean) Germany-SK Regensburg estimated R (using deaths) May 20 Sep 20 Jan 21 May 21 Sep 21 Jan 22 May 22 Sep 22 Jan 23 0 2000 4000 6000 8000 cases doubling time [days] Germany-SK Regensburg doubling time cases (rolling mean) Germany-SK Regensburg doubling time deaths (rolling mean) 0 384 768 1152 1535 daily change Germany-SK Regensburg new cases (rolling 7d mean) Germany-SK Regensburg new cases 0.000 1.535 3.071 4.606 daily change Germany-SK Regensburg new deaths (rolling 7d mean) Germany-SK Regensburg new deaths 0.0 33.0 65.9 98.9 131.9 deaths doubling time [days]
In [5]:
compare_plot(country="Germany", subregion="SK Regensburg", dates="2020-03-15:");
2023-03-07T11:53:59.221007 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: SK Regensburg SK Regensburg 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 SK Regensburg Bayern Berlin Bremen Hamburg Hessen Nordrhein-Westfalen Sachsen-Anhalt
In [6]:
# load the data
cases, deaths = germany_get_region(landkreis="SK Regensburg")

# get population of the region for future normalisation:
inhabitants = population(country="Germany", subregion="SK Regensburg")
print(f'Population of country="Germany", subregion="SK Regensburg": {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="SK Regensburg": 153542 people
Out[6]:
total cases daily new cases total deaths daily new deaths
date
2023-03-06 76435 34 212 0
2023-03-03 76401 10 212 0
2023-03-02 76391 42 212 0
2023-03-01 76349 27 212 0
2023-02-28 76322 40 212 0
2023-02-27 76282 62 212 0
2023-02-24 76220 25 212 0
2023-02-23 76195 54 212 0
2023-02-22 76141 70 212 1
2023-02-21 76071 42 211 0
2023-02-20 76029 61 211 0
2023-02-17 75968 42 211 0
2023-02-16 75926 50 211 0
2023-02-15 75876 40 211 0
2023-02-14 75836 52 211 0
2023-02-13 75784 62 211 0
2023-02-10 75722 28 211 0
2023-02-09 75694 38 211 0
2023-02-08 75656 48 211 0
2023-02-07 75608 55 211 0
2023-02-06 75553 48 211 0
2023-02-03 75505 31 211 0
2023-02-02 75474 44 211 0
2023-02-01 75430 57 211 0
2023-01-31 75373 44 211 1
2023-01-30 75329 48 210 0
2023-01-27 75281 10 210 0
2023-01-26 75271 27 210 0
2023-01-25 75244 47 210 0
2023-01-24 75197 29 210 0
2023-01-23 75168 41 210 0
2023-01-20 75127 11 210 0
2023-01-19 75116 11 210 1
2023-01-18 75105 17 209 0
2023-01-17 75088 32 209 1
2023-01-16 75056 33 208 0
2023-01-14 75023 1 208 0
2023-01-13 75022 12 208 0
2023-01-12 75010 30 208 0
2023-01-11 74980 55 208 0
2023-01-10 74925 36 208 0
2023-01-09 74889 59 208 0
2023-01-05 74830 43 208 0
2023-01-04 74787 40 208 0
2023-01-03 74747 21 208 0
2023-01-02 74726 76 208 1
2022-12-30 74650 32 207 0
2022-12-29 74618 44 207 0
2022-12-28 74574 25 207 0
2022-12-27 74549 70 207 0
2022-12-23 74479 21 207 0
2022-12-22 74458 43 207 0
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2022-12-19 74315 56 207 1
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Explore the data in your web browser¶

  • If you want to execute this notebook, click here to use myBinder
  • and wait (~1 to 2 minutes)
  • Then press SHIFT+RETURN to advance code cell to code cell
  • See http://jupyter.org for more details on how to use Jupyter Notebook

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: 0:02:55.819902