Germany: SK Berlin Neukölln (Berlin)

• Homepage of project: https://oscovida.github.io
• Plots are explained at http://oscovida.github.io/plots.html
• Execute this Jupyter Notebook using myBinder

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 12:06:07 CEST

%config InlineBackend.figure_formats = ['svg']
from oscovida import *

overview(country="Germany", subregion="SK Berlin Neukölln", weeks=5);

overview(country="Germany", subregion="SK Berlin Neukölln");

compare_plot(country="Germany", subregion="SK Berlin Neukölln", dates="2020-03-15:");

# load the data
cases, deaths = germany_get_region(landkreis="SK Berlin Neukölln")

# get population of the region for future normalisation:
inhabitants = population(country="Germany", subregion="SK Berlin Neukölln")
print(f'Population of country="Germany", subregion="SK Berlin Neukölln": {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 Berlin Neukölln": 320204 people

	total cases	daily new cases	total deaths	daily new deaths
date
2023-03-06	127656	18	568	0
2023-03-05	127638	11	568	0
2023-03-04	127627	7	568	0
2023-03-03	127620	18	568	0
2023-03-02	127602	16	568	0
...	...	...	...	...
2020-03-12	16	7	0	0
2020-03-11	9	4	0	0
2020-03-10	5	1	0	0
2020-03-09	4	2	0	0
2020-03-03	2	1	0	0

1002 rows × 4 columns

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)

---

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.

# to force a fresh download of data, run "clear_cache()"

print(f"Notebook execution took: {datetime.datetime.now()-start}")

Notebook execution took: 0:02:55.976557