Germany: SK Bremen (Bremen)

• 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 12:20:49 CEST

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

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

overview(country="Germany", subregion="SK Bremen");

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

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

# get population of the region for future normalisation:
inhabitants = population(country="Germany", subregion="SK Bremen")
print(f'Population of country="Germany", subregion="SK Bremen": {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 Bremen": 563290 people

	total cases	daily new cases	total deaths	daily new deaths
date
2023-03-06	249621	55	720	2
2023-03-03	249566	11	718	0
2023-03-02	249555	69	718	0
2023-03-01	249486	154	718	0
2023-02-28	249332	158	718	0
...	...	...	...	...
2020-03-11	31	11	0	0
2020-03-10	20	10	0	0
2020-03-09	10	6	0	0
2020-03-03	4	2	0	0
2020-03-02	2	1	0	0

1047 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: 0:03:04.041444