Germany: LK Ravensburg (Baden-Württemberg)¶

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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 10:01:02 CEST
In [2]:
%config InlineBackend.figure_formats = ['svg']
from oscovida import *
In [3]:
overview(country="Germany", subregion="LK Ravensburg", weeks=5);
2023-03-07T10:01:17.958728 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 7-day incidence rate (per 100K people) 34.5 LK Ravensburg, 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 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 Ravensburg cases daily growth factor Germany-LK Ravensburg cases daily growth factor (rolling mean) Germany-LK Ravensburg 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 Ravensburg deaths daily growth factor Germany-LK Ravensburg deaths daily growth factor (rolling mean) Germany-LK Ravensburg 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 Ravensburg doubling time cases (rolling mean) 0.0 28.7 57.4 daily change Germany-LK Ravensburg new cases (rolling 7d mean) Germany-LK Ravensburg new cases 0.000 0.287 0.574 0.861 daily change Germany-LK Ravensburg new deaths (rolling 7d mean) Germany-LK Ravensburg new deaths 0.000 0.230 0.461 0.691 0.922
In [4]:
overview(country="Germany", subregion="LK Ravensburg");
2023-03-07T10:01:35.831365 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) 34.5 LK Ravensburg, 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 3 daily change normalised per 100K May 20 Sep 20 Jan 21 May 21 Sep 21 Jan 22 May 22 Sep 22 Jan 23 0.6 0.6 0.8 0.8 1.0 1.0 1.2 1.2 R & growth factor (based on cases) Germany-LK Ravensburg cases daily growth factor Germany-LK Ravensburg cases daily growth factor (rolling mean) Germany-LK Ravensburg 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 Ravensburg deaths daily growth factor Germany-LK Ravensburg deaths daily growth factor (rolling mean) Germany-LK Ravensburg 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 Ravensburg doubling time cases (rolling mean) Germany-LK Ravensburg doubling time deaths (rolling mean) 0 287 574 861 1148 daily change Germany-LK Ravensburg new cases (rolling 7d mean) Germany-LK Ravensburg new cases 0.00 2.87 5.74 8.61 daily change Germany-LK Ravensburg new deaths (rolling 7d mean) Germany-LK Ravensburg new deaths 0.0 69.2 138.4 207.7 deaths doubling time [days]
In [5]:
compare_plot(country="Germany", subregion="LK Ravensburg", dates="2020-03-15:");
2023-03-07T10:02:48.162858 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 Ravensburg LK Ravensburg 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 Ravensburg Bayern Berlin Bremen Hamburg Hessen Nordrhein-Westfalen Sachsen-Anhalt
In [6]:
# load the data
cases, deaths = germany_get_region(landkreis="LK Ravensburg")

# get population of the region for future normalisation:
inhabitants = population(country="Germany", subregion="LK Ravensburg")
print(f'Population of country="Germany", subregion="LK Ravensburg": {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 Ravensburg": 287011 people
Out[6]:
total cases daily new cases total deaths daily new deaths
date
2023-03-06 130748 15 241 0
2023-03-03 130733 7 241 0
2023-03-02 130726 9 241 0
2023-03-01 130717 29 241 0
2023-02-28 130688 39 241 0
2023-02-27 130649 78 241 0
2023-02-25 130571 2 241 0
2023-02-24 130569 28 241 0
2023-02-23 130541 46 241 0
2023-02-22 130495 40 241 0
2023-02-21 130455 65 241 0
2023-02-20 130390 36 241 0
2023-02-17 130354 35 241 0
2023-02-16 130319 30 241 0
2023-02-15 130289 22 241 0
2023-02-14 130267 64 241 1
2023-02-13 130203 57 240 0
2023-02-10 130146 28 240 0
2023-02-09 130118 25 240 0
2023-02-08 130093 39 240 0
2023-02-07 130054 39 240 0
2023-02-06 130015 61 240 0
2023-02-04 129954 1 240 0
2023-02-03 129953 25 240 0
2023-02-02 129928 21 240 0
2023-02-01 129907 39 240 0
2023-01-31 129868 50 240 1
2023-01-30 129818 48 239 0
2023-01-27 129770 13 239 0
2023-01-26 129757 16 239 0
2023-01-25 129741 29 239 0
2023-01-24 129712 25 239 0
2023-01-23 129687 32 239 0
2023-01-20 129655 16 239 0
2023-01-19 129639 19 239 0
2023-01-18 129620 28 239 0
2023-01-17 129592 38 239 1
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2023-01-12 129505 18 237 0
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2023-01-10 129461 37 237 0
2023-01-09 129424 57 237 0
2023-01-06 129367 1 237 0
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2023-01-03 129295 58 237 1
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2022-12-28 129121 70 235 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: 0:02:02.796416