Germany: SK Bottrop (Nordrhein-Westfalen)

• 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 14:17:55 CEST

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

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

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

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

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

# get population of the region for future normalisation:
inhabitants = population(country="Germany", subregion="SK Bottrop")
print(f'Population of country="Germany", subregion="SK Bottrop": {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 Bottrop": 117311 people

	total cases	daily new cases	total deaths	daily new deaths
date
2023-03-03	49546	22	226	0
2023-03-02	49524	14	226	0
2023-03-01	49510	32	226	0
2023-02-28	49478	34	226	0
2023-02-27	49444	49	226	0
2023-02-24	49395	30	226	0
2023-02-23	49365	50	226	0
2023-02-22	49315	24	226	0
2023-02-21	49291	72	226	2
2023-02-17	49219	20	224	0
2023-02-16	49199	32	224	0
2023-02-15	49167	30	224	0
2023-02-14	49137	51	224	0
2023-02-13	49086	34	224	0
2023-02-10	49052	14	224	0
2023-02-09	49038	35	224	0
2023-02-08	49003	37	224	0
2023-02-07	48966	28	224	0
2023-02-06	48938	39	224	0
2023-02-05	48899	1	224	0
2023-02-03	48898	16	224	0
2023-02-02	48882	17	224	0
2023-02-01	48865	36	224	0
2023-01-31	48829	46	224	0
2023-01-30	48783	43	224	1
2023-01-27	48740	23	223	0
2023-01-26	48717	24	223	0
2023-01-25	48693	33	223	0
2023-01-24	48660	41	223	0
2023-01-23	48619	35	223	0
2023-01-20	48584	18	223	0
2023-01-19	48566	16	223	0
2023-01-18	48550	18	223	0
2023-01-17	48532	29	223	0
2023-01-16	48503	50	223	0
2023-01-13	48453	13	223	0
2023-01-12	48440	18	223	0
2023-01-11	48422	34	223	0
2023-01-10	48388	29	223	0
2023-01-09	48359	52	223	0
2023-01-06	48307	39	223	1
2023-01-05	48268	50	222	0
2023-01-04	48218	37	222	0
2023-01-03	48181	51	222	1
2023-01-02	48130	68	221	0
2022-12-30	48062	74	221	0
2022-12-29	47988	89	221	2
2022-12-28	47899	52	219	0
2022-12-27	47847	67	219	0
2022-12-23	47780	80	219	0
2022-12-22	47700	92	219	0
2022-12-21	47608	73	219	0
2022-12-20	47535	114	219	2
2022-12-19	47421	115	217	1
2022-12-16	47306	63	216	0
2022-12-15	47243	75	216	1
2022-12-14	47168	49	215	0
2022-12-13	47119	106	215	0
2022-12-12	47013	100	215	1
2022-12-09	46913	107	214	0
2022-12-08	46806	41	214	0
2022-12-07	46765	63	214	0
2022-12-06	46702	80	214	2
2022-12-05	46622	25	212	0
2022-12-04	46597	1	212	0
2022-12-03	46596	2	212	0
2022-12-02	46594	1	212	0
2022-12-01	46593	3	212	0
2022-11-30	46590	23	212	0
2022-11-29	46567	57	212	0
2022-11-28	46510	37	212	0
2022-11-27	46473	9	212	0
2022-11-26	46464	15	212	0
2022-11-25	46449	43	212	0
2022-11-24	46406	32	212	0
2022-11-23	46374	51	212	0
2022-11-22	46323	54	212	0
2022-11-21	46269	49	212	1
2022-11-20	46220	18	211	0
2022-11-19	46202	26	211	0
2022-11-18	46176	41	211	0
2022-11-17	46135	47	211	1
2022-11-16	46088	51	210	2
2022-11-15	46037	71	208	0
2022-11-14	45966	57	208	0
2022-11-13	45909	12	208	0
2022-11-12	45897	46	208	0
2022-11-11	45851	54	208	0
2022-11-10	45797	57	208	0
2022-11-09	45740	64	208	0
2022-11-08	45676	74	208	0
2022-11-07	45602	80	208	1
2022-11-06	45522	27	207	0
2022-11-05	45495	36	207	0
2022-11-04	45459	66	207	0
2022-11-03	45393	76	207	0
2022-11-02	45317	58	207	0
2022-11-01	45259	74	207	0
2022-10-31	45185	87	207	1
2022-10-30	45098	36	206	0
2022-10-29	45062	56	206	0
2022-10-28	45006	76	206	0
2022-10-27	44930	107	206	1
2022-10-26	44823	123	205	1
2022-10-25	44700	150	204	0
2022-10-24	44550	68	204	0
2022-10-23	44482	81	204	1
2022-10-22	44401	59	203	0
2022-10-21	44342	110	203	1
2022-10-20	44232	129	202	0
2022-10-19	44103	178	202	0
2022-10-18	43925	170	202	0
2022-10-17	43755	141	202	0
2022-10-16	43614	42	202	0
2022-10-15	43572	74	202	0
2022-10-14	43498	135	202	0
2022-10-13	43363	100	202	0
2022-10-12	43263	187	202	0
2022-10-11	43076	173	202	0
2022-10-10	42903	87	202	0
2022-10-09	42816	35	202	0
2022-10-08	42781	99	202	0
2022-10-07	42682	187	202	0
2022-10-06	42495	162	202	0
2022-10-05	42333	171	202	0
2022-10-04	42162	96	202	0
2022-10-03	42066	35	202	0
2022-10-02	42031	12	202	0
2022-10-01	42019	64	202	0
2022-09-30	41955	98	202	0
2022-09-29	41857	73	202	0
2022-09-28	41784	90	202	0
2022-09-27	41694	95	202	0
2022-09-26	41599	84	202	1
2022-09-25	41515	19	201	0
2022-09-24	41496	34	201	0
2022-09-23	41462	56	201	0
2022-09-22	41406	38	201	0
2022-09-21	41368	70	201	0
2022-09-20	41298	45	201	0
2022-09-19	41253	45	201	0
2022-09-18	41208	22	201	0
2022-09-17	41186	18	201	0
2022-09-16	41168	40	201	0
2022-09-15	41128	54	201	0
2022-09-14	41074	41	201	0
2022-09-13	41033	63	201	0
2022-09-12	40970	36	201	0
2022-09-11	40934	26	201	0
2022-09-10	40908	29	201	0
2022-09-09	40879	42	201	0
2022-09-08	40837	47	201	0
2022-09-07	40790	58	201	0
2022-09-06	40732	75	201	0
2022-09-05	40657	48	201	0
2022-09-04	40609	13	201	0
2022-09-03	40596	34	201	1
2022-09-02	40562	54	200	0
2022-09-01	40508	53	200	0
2022-08-31	40455	78	200	0
2022-08-30	40377	73	200	0
2022-08-29	40304	52	200	0
2022-08-28	40252	17	200	0
2022-08-27	40235	35	200	0
2022-08-26	40200	59	200	0
2022-08-25	40141	56	200	0
2022-08-24	40085	71	200	0
2022-08-23	40014	87	200	0
2022-08-22	39927	72	200	0
2022-08-21	39855	10	200	1
2022-08-20	39845	55	199	0
2022-08-19	39790	59	199	0
2022-08-18	39731	64	199	0
2022-08-17	39667	88	199	0
2022-08-16	39579	62	199	0
2022-08-15	39517	83	199	0
2022-08-14	39434	19	199	0
2022-08-13	39415	43	199	0
2022-08-12	39372	65	199	0
2022-08-11	39307	95	199	0
2022-08-10	39212	88	199	0
2022-08-09	39124	98	199	0
2022-08-08	39026	84	199	0
2022-08-07	38942	31	199	1
2022-08-06	38911	55	198	0
2022-08-05	38856	62	198	0
2022-08-04	38794	84	198	1
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2022-08-02	38626	129	197	3
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2022-07-29	38326	80	194	0
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2022-07-27	38168	84	194	1
2022-07-26	38084	102	193	1
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2022-07-24	37893	58	192	1
2022-07-23	37835	72	191	0
2022-07-22	37763	83	191	1
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2022-06-24	34478	86	184	0
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2020-03-18	10	5	1	1
2020-03-17	5	1	0	0
2020-03-15	4	1	0	0
2020-03-11	3	2	0	0

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: 0:03:28.059949