
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 14:17:46 CEST


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


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


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


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


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

# get population of the region for future normalisation:
inhabitants = population(country="Germany", subregion="SK Dortmund")
print(f'Population of country="Germany", subregion="SK Dortmund": {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 Dortmund": 586852 people


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: 0:03:20.543150

Germany: SK Dortmund (Nordrhein-Westfalen)¶

Explore the data in your web browser¶

Acknowledgements:¶

	total cases	daily new cases	total deaths	daily new deaths
date
2023-03-03	260099	58	701	0
2023-03-02	260041	65	701	0
2023-03-01	259976	150	701	0
2023-02-28	259826	214	701	0
2023-02-27	259612	231	701	2
2023-02-24	259381	127	699	0
2023-02-23	259254	156	699	0
2023-02-22	259098	209	699	0
2023-02-21	258889	187	699	1
2023-02-20	258702	149	698	1
2023-02-17	258553	119	697	1
2023-02-16	258434	143	696	1
2023-02-15	258291	169	695	0
2023-02-14	258122	168	695	0
2023-02-13	257954	154	695	1
2023-02-10	257800	80	694	0
2023-02-09	257720	131	694	0
2023-02-08	257589	115	694	0
2023-02-07	257474	124	694	0
2023-02-06	257350	159	694	0
2023-02-03	257191	91	694	0
2023-02-02	257100	132	694	0
2023-02-01	256968	165	694	0
2023-01-31	256803	162	694	0
2023-01-30	256641	181	694	0
2023-01-27	256460	102	694	1
2023-01-26	256358	134	693	0
2023-01-25	256224	114	693	1
2023-01-24	256110	121	692	0
2023-01-23	255989	138	692	0
2023-01-20	255851	56	692	0
2023-01-19	255795	74	692	0
2023-01-18	255721	79	692	1
2023-01-17	255642	87	691	1
2023-01-16	255555	146	690	0
2023-01-13	255409	73	690	0
2023-01-12	255336	98	690	1
2023-01-11	255238	100	689	1
2023-01-10	255138	205	688	0