Germany: LK Neckar-Odenwald-Kreis (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 10:01:30 CEST
In [2]:
%config InlineBackend.figure_formats = ['svg']
from oscovida import *
In [3]:
overview(country="Germany", subregion="LK Neckar-Odenwald-Kreis", weeks=5);
2023-03-07T10:01:45.278360 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 7-day incidence rate (per 100K people) 109.8 LK Neckar-Odenwald-Kreis, 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 0.2 0.4 0.6 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 Neckar-Odenwald-Kreis cases daily growth factor Germany-LK Neckar-Odenwald-Kreis cases daily growth factor (rolling mean) Germany-LK Neckar-Odenwald-Kreis estimated R (using cases) 30 Jan 06 Feb 13 Feb 20 Feb 27 Feb 06 Mar 0.0 0.0 0.5 0.5 1.0 1.0 R & growth factor (based on deaths) Germany-LK Neckar-Odenwald-Kreis deaths daily growth factor Germany-LK Neckar-Odenwald-Kreis deaths daily growth factor (rolling mean) Germany-LK Neckar-Odenwald-Kreis 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 Neckar-Odenwald-Kreis doubling time cases (rolling mean) 0.0 28.8 57.6 86.4 daily change Germany-LK Neckar-Odenwald-Kreis new cases (rolling 7d mean) Germany-LK Neckar-Odenwald-Kreis new cases 0.000 0.288 0.576 0.864 daily change Germany-LK Neckar-Odenwald-Kreis new deaths (rolling 7d mean) Germany-LK Neckar-Odenwald-Kreis new deaths 0.000 0.263 0.526 0.790
In [4]:
overview(country="Germany", subregion="LK Neckar-Odenwald-Kreis");
2023-03-07T10:02:59.946952 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) 109.8 LK Neckar-Odenwald-Kreis, 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 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 R & growth factor (based on cases) Germany-LK Neckar-Odenwald-Kreis cases daily growth factor Germany-LK Neckar-Odenwald-Kreis cases daily growth factor (rolling mean) Germany-LK Neckar-Odenwald-Kreis estimated R (using cases) May 20 Sep 20 Jan 21 May 21 Sep 21 Jan 22 May 22 Sep 22 Jan 23 0.0 0.0 0.5 0.5 1.0 1.0 R & growth factor (based on deaths) Germany-LK Neckar-Odenwald-Kreis deaths daily growth factor Germany-LK Neckar-Odenwald-Kreis deaths daily growth factor (rolling mean) Germany-LK Neckar-Odenwald-Kreis 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-LK Neckar-Odenwald-Kreis doubling time cases (rolling mean) Germany-LK Neckar-Odenwald-Kreis doubling time deaths (rolling mean) 0.0 287.9 575.7 daily change Germany-LK Neckar-Odenwald-Kreis new cases (rolling 7d mean) Germany-LK Neckar-Odenwald-Kreis new cases 0.00 2.88 5.76 8.64 daily change Germany-LK Neckar-Odenwald-Kreis new deaths (rolling 7d mean) Germany-LK Neckar-Odenwald-Kreis new deaths 0.0 70.1 140.1 210.2 280.2 deaths doubling time [days]
In [5]:
compare_plot(country="Germany", subregion="LK Neckar-Odenwald-Kreis", dates="2020-03-15:");
2023-03-07T10:05:04.284735 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 Neckar-Odenwald-Kreis LK Neckar-Odenwald-Kreis 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 Neckar-Odenwald-Kreis Bayern Berlin Bremen Hamburg Hessen Nordrhein-Westfalen Sachsen-Anhalt
In [6]:
# load the data
cases, deaths = germany_get_region(landkreis="LK Neckar-Odenwald-Kreis")

# get population of the region for future normalisation:
inhabitants = population(country="Germany", subregion="LK Neckar-Odenwald-Kreis")
print(f'Population of country="Germany", subregion="LK Neckar-Odenwald-Kreis": {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 Neckar-Odenwald-Kreis": 143929 people
Out[6]:
total cases daily new cases total deaths daily new deaths
date
2023-03-06 71660 26 236 0
2023-03-03 71634 9 236 0
2023-03-02 71625 7 236 0
2023-03-01 71618 52 236 0
2023-02-28 71566 64 236 0
2023-02-27 71502 90 236 0
2023-02-24 71412 64 236 0
2023-02-23 71348 40 236 0
2023-02-22 71308 67 236 0
2023-02-21 71241 53 236 0
2023-02-20 71188 44 236 0
2023-02-17 71144 33 236 0
2023-02-16 71111 43 236 0
2023-02-15 71068 50 236 0
2023-02-14 71018 49 236 0
2023-02-13 70969 51 236 0
2023-02-10 70918 30 236 0
2023-02-09 70888 41 236 0
2023-02-08 70847 41 236 0
2023-02-07 70806 57 236 0
2023-02-06 70749 48 236 0
2023-02-03 70701 24 236 1
2023-02-02 70677 27 235 0
2023-02-01 70650 23 235 0
2023-01-31 70627 37 235 0
2023-01-30 70590 31 235 0
2023-01-27 70559 22 235 0
2023-01-26 70537 20 235 0
2023-01-25 70517 22 235 0
2023-01-24 70495 26 235 0
2023-01-23 70469 27 235 1
2023-01-20 70442 6 234 1
2023-01-19 70436 12 233 0
2023-01-18 70424 22 233 0
2023-01-17 70402 23 233 0
2023-01-16 70379 23 233 0
2023-01-13 70356 15 233 0
2023-01-12 70341 13 233 0
2023-01-11 70328 32 233 0
2023-01-10 70296 41 233 0
2023-01-09 70255 36 233 0
2023-01-05 70219 41 233 0
2023-01-04 70178 30 233 0
2023-01-03 70148 29 233 0
2023-01-02 70119 65 233 0
2022-12-30 70054 35 233 0
2022-12-29 70019 41 233 0
2022-12-28 69978 22 233 0
2022-12-27 69956 66 233 1
2022-12-23 69890 59 232 2
2022-12-22 69831 36 230 1
2022-12-21 69795 76 229 0
2022-12-20 69719 79 229 0
2022-12-19 69640 37 229 0
2022-12-16 69603 28 229 0
2022-12-15 69575 39 229 0
2022-12-14 69536 51 229 0
2022-12-13 69485 45 229 0
2022-12-12 69440 42 229 0
2022-12-09 69398 23 229 0
2022-12-08 69375 34 229 0
2022-12-07 69341 35 229 0
2022-12-06 69306 56 229 0
2022-12-05 69250 37 229 0
2022-12-02 69213 29 229 0
2022-12-01 69184 38 229 0
2022-11-30 69146 33 229 0
2022-11-29 69113 35 229 0
2022-11-28 69078 46 229 0
2022-11-25 69032 17 229 0
2022-11-24 69015 40 229 0
2022-11-23 68975 43 229 0
2022-11-22 68932 34 229 0
2022-11-21 68898 65 229 0
2022-11-18 68833 30 229 0
2022-11-17 68803 26 229 0
2022-11-16 68777 50 229 0
2022-11-15 68727 68 229 0
2022-11-14 68659 53 229 0
2022-11-11 68606 33 229 0
2022-11-10 68573 52 229 0
2022-11-09 68521 48 229 0
2022-11-08 68473 61 229 0
2022-11-07 68412 132 229 0
2022-11-04 68280 78 229 0
2022-11-03 68202 41 229 0
2022-11-02 68161 101 229 0
2022-10-31 68060 176 229 1
2022-10-28 67884 33 228 1
2022-10-27 67851 84 227 0
2022-10-26 67767 138 227 0
2022-10-25 67629 100 227 0
2022-10-24 67529 227 227 0
2022-10-21 67302 71 227 0
2022-10-20 67231 158 227 0
2022-10-19 67073 185 227 0
2022-10-18 66888 276 227 0
2022-10-17 66612 406 227 0
2022-10-14 66206 186 227 0
2022-10-13 66020 202 227 0
2022-10-12 65818 325 227 0
2022-10-11 65493 289 227 0
2022-10-10 65204 494 227 0
2022-10-07 64710 226 227 0
2022-10-06 64484 256 227 1
2022-10-05 64228 263 226 0
2022-10-04 63965 351 226 0
2022-09-30 63614 181 226 0
2022-09-29 63433 237 226 0
2022-09-28 63196 236 226 0
2022-09-27 62960 207 226 0
2022-09-26 62753 251 226 1
2022-09-23 62502 95 225 0
2022-09-22 62407 79 225 1
2022-09-21 62328 136 224 0
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2022-09-07 61502 59 224 0
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2022-07-25 58485 462 222 2
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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: 0:06:00.727408