
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 11:21:58 CEST


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


overview(country="Germany", subregion="LK Rosenheim", weeks=5);


overview(country="Germany", subregion="LK Rosenheim");


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


# load the data
cases, deaths = germany_get_region(landkreis="LK Rosenheim")

# get population of the region for future normalisation:
inhabitants = population(country="Germany", subregion="LK Rosenheim")
print(f'Population of country="Germany", subregion="LK Rosenheim": {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 Rosenheim": 263367 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: 0:02:41.487370

Germany: LK Rosenheim (Bayern)¶

Explore the data in your web browser¶

Acknowledgements:¶

	total cases	daily new cases	total deaths	daily new deaths
date
2023-03-06	146894	33	838	0
2023-03-03	146861	22	838	0
2023-03-02	146839	45	838	0
2023-03-01	146794	93	838	0
2023-02-28	146701	69	838	0
2023-02-27	146632	92	838	0
2023-02-24	146540	55	838	0
2023-02-23	146485	56	838	0
2023-02-22	146429	69	838	0
2023-02-21	146360	58	838	0
2023-02-20	146302	69	838	0
2023-02-17	146233	42	838	0
2023-02-16	146191	48	838	0
2023-02-15	146143	58	838	0
2023-02-14	146085	64	838	0
2023-02-13	146021	83	838	0
2023-02-10	145938	51	838	0
2023-02-09	145887	49	838	0
2023-02-08	145838	62	838	0
2023-02-07	145776	58	838	0
2023-02-06	145718	58	838	0
2023-02-03	145660	39	838	0
2023-02-02	145621	47	838	0
2023-02-01	145574	53	838	0
2023-01-31	145521	63	838	1
2023-01-30	145458	43	837	0
2023-01-27	145415	22	837	0
2023-01-26	145393	34	837	0
2023-01-25	145359	68	837	0
2023-01-24	145291	33	837	0
2023-01-23	145258	47	837	0
2023-01-20	145211	20	837	0
2023-01-19	145191	22	837	0
2023-01-18	145169	36	837	0
2023-01-17	145133	35	837	0
2023-01-16	145098	40	837	0
2023-01-13	145058	48	837	1
2023-01-12	145010	20	836	1
2023-01-11	144990	112	835	0