
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 12:44:40 CEST


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


overview(country="Germany", subregion="LK Marburg-Biedenkopf", weeks=5);


overview(country="Germany", subregion="LK Marburg-Biedenkopf");


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


# load the data
cases, deaths = germany_get_region(landkreis="LK Marburg-Biedenkopf")

# get population of the region for future normalisation:
inhabitants = population(country="Germany", subregion="LK Marburg-Biedenkopf")
print(f'Population of country="Germany", subregion="LK Marburg-Biedenkopf": {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 Marburg-Biedenkopf": 246097 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: 0:02:59.766702

Germany: LK Marburg-Biedenkopf (Hessen)¶

Explore the data in your web browser¶

Acknowledgements:¶

	total cases	daily new cases	total deaths	daily new deaths
date
2023-03-06	122762	10	479	0
2023-03-05	122752	7	479	0
2023-03-04	122745	7	479	0
2023-03-03	122738	33	479	0
2023-03-02	122705	30	479	0
2023-03-01	122675	113	479	0
2023-02-28	122562	99	479	1
2023-02-27	122463	83	478	0
2023-02-26	122380	39	478	0
2023-02-25	122341	25	478	0
2023-02-24	122316	103	478	0
2023-02-23	122213	180	478	0
2023-02-22	122033	56	478	0
2023-02-21	121977	60	478	0
2023-02-20	121917	81	478	0
2023-02-19	121836	34	478	0
2023-02-18	121802	23	478	0
2023-02-17	121779	93	478	1
2023-02-16	121686	77	477	0
2023-02-15	121609	71	477	0
2023-02-14	121538	105	477	0
2023-02-13	121433	91	477	0
2023-02-12	121342	21	477	0
2023-02-11	121321	21	477	0
2023-02-10	121300	54	477	0
2023-02-09	121246	43	477	0
2023-02-08	121203	47	477	0
2023-02-07	121156	46	477	0
2023-02-06	121110	90	477	0
2023-02-05	121020	16	477	0
2023-02-04	121004	18	477	0
2023-02-03	120986	57	477	0
2023-02-02	120929	35	477	0
2023-02-01	120894	35	477	0
2023-01-31	120859	43	477	0
2023-01-30	120816	47	477	0
2023-01-29	120769	16	477	0
2023-01-28	120753	18	477	0
2023-01-27	120735	34	477	0