Germany: LK Mainz-Bingen (Rheinland-Pfalz)¶

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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 14:47:52 CEST
In [2]:
%config InlineBackend.figure_formats = ['svg']
from oscovida import *
In [3]:
overview(country="Germany", subregion="LK Mainz-Bingen", weeks=5);
2023-03-07T14:48:08.185321 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) 121.0 LK Mainz-Bingen, 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 0.0 0.1 0.2 0.3 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 1.4 1.4 R & growth factor (based on cases) Germany-LK Mainz-Bingen cases daily growth factor Germany-LK Mainz-Bingen cases daily growth factor (rolling mean) Germany-LK Mainz-Bingen 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 Mainz-Bingen deaths daily growth factor Germany-LK Mainz-Bingen deaths daily growth factor (rolling mean) Germany-LK Mainz-Bingen 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 Mainz-Bingen doubling time cases (rolling mean) 0.0 42.5 85.0 127.5 daily change Germany-LK Mainz-Bingen new cases (rolling 7d mean) Germany-LK Mainz-Bingen new cases 0.000 0.212 0.425 0.637 0.850 daily change Germany-LK Mainz-Bingen new deaths (rolling 7d mean) Germany-LK Mainz-Bingen new deaths 0.000 0.323 0.645 0.968
In [4]:
overview(country="Germany", subregion="LK Mainz-Bingen");
2023-03-07T14:48:23.537809 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) 121.0 LK Mainz-Bingen, 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 0 200 400 600 daily change normalised per 100K May 20 Sep 20 Jan 21 May 21 Sep 21 Jan 22 May 22 Sep 22 Jan 23 0 2 4 6 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 1.4 1.4 R & growth factor (based on cases) Germany-LK Mainz-Bingen cases daily growth factor Germany-LK Mainz-Bingen cases daily growth factor (rolling mean) Germany-LK Mainz-Bingen 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 Mainz-Bingen deaths daily growth factor Germany-LK Mainz-Bingen deaths daily growth factor (rolling mean) Germany-LK Mainz-Bingen estimated R (using deaths) May 20 Sep 20 Jan 21 May 21 Sep 21 Jan 22 May 22 Sep 22 Jan 23 0 20000 40000 60000 cases doubling time [days] Germany-LK Mainz-Bingen doubling time cases (rolling mean) Germany-LK Mainz-Bingen doubling time deaths (rolling mean) 0 425 850 1275 daily change Germany-LK Mainz-Bingen new cases (rolling 7d mean) Germany-LK Mainz-Bingen new cases 0.00 4.25 8.50 12.75 daily change Germany-LK Mainz-Bingen new deaths (rolling 7d mean) Germany-LK Mainz-Bingen new deaths 0.0 78.4 156.8 235.2 deaths doubling time [days]
In [5]:
compare_plot(country="Germany", subregion="LK Mainz-Bingen", dates="2020-03-15:");
2023-03-07T14:50:50.927305 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 Mainz-Bingen LK Mainz-Bingen 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 Mainz-Bingen Bayern Berlin Bremen Hamburg Hessen Nordrhein-Westfalen Sachsen-Anhalt
In [6]:
# load the data
cases, deaths = germany_get_region(landkreis="LK Mainz-Bingen")

# get population of the region for future normalisation:
inhabitants = population(country="Germany", subregion="LK Mainz-Bingen")
print(f'Population of country="Germany", subregion="LK Mainz-Bingen": {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 Mainz-Bingen": 212420 people
Out[6]:
total cases daily new cases total deaths daily new deaths
date
2023-03-06 99900 11 332 0
2023-03-03 99889 25 332 0
2023-03-02 99864 28 332 0
2023-03-01 99836 82 332 0
2023-02-28 99754 111 332 1
2023-02-27 99643 164 331 0
2023-02-24 99479 66 331 0
2023-02-23 99413 151 331 0
2023-02-22 99262 43 331 0
2023-02-21 99219 148 331 0
2023-02-17 99071 51 331 1
2023-02-16 99020 62 330 0
2023-02-15 98958 73 330 0
2023-02-14 98885 107 330 0
2023-02-13 98778 74 330 0
2023-02-10 98704 67 330 0
2023-02-09 98637 43 330 0
2023-02-08 98594 51 330 0
2023-02-07 98543 83 330 0
2023-02-06 98460 71 330 0
2023-02-03 98389 42 330 0
2023-02-02 98347 52 330 0
2023-02-01 98295 38 330 0
2023-01-31 98257 66 330 0
2023-01-30 98191 53 330 0
2023-01-27 98138 31 330 0
2023-01-26 98107 31 330 0
2023-01-25 98076 39 330 0
2023-01-24 98037 33 330 0
2023-01-23 98004 45 330 0
2023-01-20 97959 20 330 0
2023-01-19 97939 32 330 0
2023-01-18 97907 32 330 0
2023-01-17 97875 40 330 0
2023-01-16 97835 51 330 0
2023-01-13 97784 31 330 0
2023-01-12 97753 16 330 0
2023-01-11 97737 37 330 2
2023-01-10 97700 53 328 0
2023-01-09 97647 81 328 1
2023-01-06 97566 44 327 0
2023-01-05 97522 114 327 0
2023-01-04 97408 197 327 2
2023-01-03 97211 262 325 1
2023-01-02 96949 212 324 0
2022-12-30 96737 1 324 0
2022-12-29 96736 3 324 0
2022-12-27 96733 3 324 0
2022-12-23 96730 79 324 0
2022-12-22 96651 88 324 0
2022-12-21 96563 118 324 0
2022-12-20 96445 105 324 0
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2022-12-16 96185 88 324 0
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2022-12-12 95818 155 324 0
2022-12-09 95663 76 324 2
2022-12-08 95587 71 322 0
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2022-12-02 95165 65 322 1
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2022-11-25 94715 96 320 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: 0:04:22.153828