Germany: LK Kassel (Hessen)¶

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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 12:51:50 CEST
In [2]:
%config InlineBackend.figure_formats = ['svg']
from oscovida import *
In [3]:
overview(country="Germany", subregion="LK Kassel", weeks=5);
2023-03-07T12:52:03.311586 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) 108.7 LK Kassel, 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 0.8 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 Kassel cases daily growth factor Germany-LK Kassel cases daily growth factor (rolling mean) Germany-LK Kassel 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 Kassel deaths daily growth factor Germany-LK Kassel deaths daily growth factor (rolling mean) Germany-LK Kassel 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 Kassel doubling time cases (rolling mean) Germany-LK Kassel doubling time deaths (rolling mean) 0.0 23.7 47.5 71.2 94.9 daily change Germany-LK Kassel new cases (rolling 7d mean) Germany-LK Kassel new cases 0.000 0.475 0.949 1.424 1.898 daily change Germany-LK Kassel new deaths (rolling 7d mean) Germany-LK Kassel new deaths 0.0 108.5 217.0 325.4 deaths doubling time [days]
In [4]:
overview(country="Germany", subregion="LK Kassel");
2023-03-07T12:52:22.605533 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 0 500 500 1000 1000 1500 1500 2000 2000 7-day incidence rate (per 100K people) 108.7 LK Kassel, 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 0.8 0.8 1.0 1.0 1.2 1.2 1.4 1.4 R & growth factor (based on cases) Germany-LK Kassel cases daily growth factor Germany-LK Kassel cases daily growth factor (rolling mean) Germany-LK Kassel 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 Kassel deaths daily growth factor Germany-LK Kassel deaths daily growth factor (rolling mean) Germany-LK Kassel 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 Kassel doubling time cases (rolling mean) Germany-LK Kassel doubling time deaths (rolling mean) 0 237 475 712 949 daily change Germany-LK Kassel new cases (rolling 7d mean) Germany-LK Kassel new cases 0.000 2.373 4.745 7.118 daily change Germany-LK Kassel new deaths (rolling 7d mean) Germany-LK Kassel new deaths 0.0 137.1 274.3 411.4 deaths doubling time [days]
In [5]:
compare_plot(country="Germany", subregion="LK Kassel", dates="2020-03-15:");
2023-03-07T12:54:53.727890 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 Kassel LK Kassel 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 Kassel Bayern Berlin Bremen Hamburg Hessen Nordrhein-Westfalen Sachsen-Anhalt
In [6]:
# load the data
cases, deaths = germany_get_region(landkreis="LK Kassel")

# get population of the region for future normalisation:
inhabitants = population(country="Germany", subregion="LK Kassel")
print(f'Population of country="Germany", subregion="LK Kassel": {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 Kassel": 237268 people
Out[6]:
total cases daily new cases total deaths daily new deaths
date
2023-03-06 98442 41 392 0
2023-03-03 98401 63 392 0
2023-03-02 98338 21 392 0
2023-03-01 98317 41 392 0
2023-02-28 98276 92 392 0
2023-02-27 98184 73 392 0
2023-02-24 98111 55 392 0
2023-02-23 98056 74 392 0
2023-02-22 97982 54 392 0
2023-02-21 97928 67 392 0
2023-02-20 97861 108 392 0
2023-02-17 97753 54 392 1
2023-02-16 97699 73 391 0
2023-02-15 97626 80 391 2
2023-02-14 97546 90 389 0
2023-02-13 97456 76 389 0
2023-02-10 97380 33 389 2
2023-02-09 97347 63 387 0
2023-02-08 97284 42 387 0
2023-02-07 97242 55 387 0
2023-02-06 97187 63 387 0
2023-02-03 97124 38 387 0
2023-02-02 97086 35 387 0
2023-02-01 97051 41 387 0
2023-01-31 97010 76 387 0
2023-01-30 96934 46 387 0
2023-01-27 96888 19 387 0
2023-01-26 96869 32 387 0
2023-01-25 96837 46 387 0
2023-01-24 96791 57 387 0
2023-01-23 96734 37 387 0
2023-01-20 96697 13 387 0
2023-01-19 96684 27 387 0
2023-01-18 96657 22 387 0
2023-01-17 96635 41 387 0
2023-01-16 96594 48 387 2
2023-01-13 96546 23 385 0
2023-01-12 96523 21 385 0
2023-01-11 96502 65 385 1
2023-01-10 96437 77 384 0
2023-01-09 96360 76 384 0
2023-01-06 96284 45 384 1
2023-01-05 96239 54 383 0
2023-01-04 96185 61 383 0
2023-01-03 96124 143 383 1
2023-01-02 95981 73 382 0
2022-12-30 95908 40 382 0
2022-12-29 95868 94 382 0
2022-12-28 95774 98 382 0
2022-12-27 95676 190 382 1
2022-12-23 95486 74 381 0
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2022-12-21 95249 140 381 0
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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: 0:03:12.037330