
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 12:28:10 CEST


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


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


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


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


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

# get population of the region for future normalisation:
inhabitants = population(country="Germany", subregion="LK Fulda")
print(f'Population of country="Germany", subregion="LK Fulda": {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 Fulda": 223572 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: 0:03:04.874483

Germany: LK Fulda (Hessen)¶

Explore the data in your web browser¶

Acknowledgements:¶

	total cases	daily new cases	total deaths	daily new deaths
date
2023-03-06	135437	16	425	1
2023-03-05	135421	5	424	0
2023-03-04	135416	5	424	0
2023-03-03	135411	26	424	0
2023-03-02	135385	29	424	0
2023-03-01	135356	27	424	0
2023-02-28	135329	161	424	0
2023-02-27	135168	150	424	0
2023-02-26	135018	69	424	0
2023-02-25	134949	97	424	0
2023-02-24	134852	176	424	0
2023-02-23	134676	160	424	1
2023-02-22	134516	173	423	0
2023-02-21	134343	147	423	0
2023-02-20	134196	152	423	0
2023-02-19	134044	93	423	0
2023-02-18	133951	86	423	1
2023-02-17	133865	123	422	0
2023-02-16	133742	146	422	0
2023-02-15	133596	157	422	0
2023-02-14	133439	153	422	0
2023-02-13	133286	136	422	0
2023-02-12	133150	67	422	0
2023-02-11	133083	63	422	0
2023-02-10	133020	96	422	0
2023-02-09	132924	109	422	0
2023-02-08	132815	126	422	0
2023-02-07	132689	119	422	0
2023-02-06	132570	132	422	0
2023-02-05	132438	47	422	0
2023-02-04	132391	45	422	0
2023-02-03	132346	93	422	0
2023-02-02	132253	102	422	0
2023-02-01	132151	91	422	0
2023-01-31	132060	97	422	0
2023-01-30	131963	97	422	0
2023-01-29	131866	38	422	0
2023-01-28	131828	39	422	0
2023-01-27	131789	67	422	0