Germany: SK Mülheim a.d.Ruhr (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 14:24:40 CEST

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

overview(country="Germany", subregion="SK Mülheim a.d.Ruhr", weeks=5);

overview(country="Germany", subregion="SK Mülheim a.d.Ruhr");

compare_plot(country="Germany", subregion="SK Mülheim a.d.Ruhr", dates="2020-03-15:");

# load the data
cases, deaths = germany_get_region(landkreis="SK Mülheim a.d.Ruhr")

# get population of the region for future normalisation:
inhabitants = population(country="Germany", subregion="SK Mülheim a.d.Ruhr")
print(f'Population of country="Germany", subregion="SK Mülheim a.d.Ruhr": {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 Mülheim a.d.Ruhr": 170739 people

	total cases	daily new cases	total deaths	daily new deaths
date
2023-03-06	67436	5	459	0
2023-03-05	67431	5	459	0
2023-03-04	67426	4	459	0
2023-03-03	67422	28	459	0
2023-03-02	67394	41	459	0
2023-03-01	67353	31	459	0
2023-02-28	67322	77	459	0
2023-02-27	67245	47	459	0
2023-02-26	67198	8	459	0
2023-02-25	67190	29	459	0
2023-02-24	67161	50	459	0
2023-02-23	67111	98	459	1
2023-02-22	67013	52	458	2
2023-02-21	66961	58	456	0
2023-02-20	66903	26	456	0
2023-02-19	66877	10	456	1
2023-02-18	66867	16	455	0
2023-02-17	66851	63	455	0
2023-02-16	66788	60	455	1
2023-02-15	66728	74	454	0
2023-02-14	66654	79	454	1
2023-02-13	66575	53	453	0
2023-02-12	66522	14	453	0
2023-02-11	66508	29	453	0
2023-02-10	66479	37	453	0
2023-02-09	66442	45	453	0
2023-02-08	66397	41	453	0
2023-02-07	66356	63	453	0
2023-02-06	66293	49	453	1
2023-02-05	66244	9	452	0
2023-02-04	66235	22	452	0
2023-02-03	66213	31	452	0
2023-02-02	66182	25	452	0
2023-02-01	66157	33	452	0
2023-01-31	66124	67	452	0
2023-01-30	66057	34	452	0
2023-01-29	66023	15	452	0
2023-01-28	66008	17	452	0
2023-01-27	65991	26	452	0
2023-01-26	65965	35	452	0
2023-01-25	65930	52	452	1
2023-01-24	65878	46	451	0
2023-01-23	65832	73	451	0
2023-01-22	65759	16	451	0
2023-01-20	65743	16	451	0
2023-01-19	65727	19	451	0
2023-01-18	65708	41	451	0
2023-01-17	65667	50	451	0
2023-01-16	65617	27	451	0
2023-01-13	65590	13	451	0
2023-01-12	65577	12	451	1
2023-01-11	65565	24	450	0
2023-01-10	65541	49	450	0
2023-01-09	65492	39	450	0
2023-01-08	65453	17	450	0
2023-01-07	65436	20	450	0
2023-01-06	65416	18	450	1
2023-01-05	65398	51	449	1
2023-01-04	65347	57	448	0
2023-01-03	65290	65	448	1
2023-01-02	65225	63	447	1
2023-01-01	65162	19	446	0
2022-12-31	65143	31	446	0
2022-12-30	65112	96	446	0
2022-12-29	65016	82	446	1
2022-12-28	64934	129	445	1
2022-12-27	64805	163	444	1
2022-12-25	64642	1	443	0
2022-12-24	64641	13	443	0
2022-12-23	64628	63	443	0
2022-12-22	64565	117	443	0
2022-12-21	64448	163	443	0
2022-12-20	64285	172	443	0
2022-12-19	64113	109	443	1
2022-12-18	64004	16	442	0
2022-12-17	63988	16	442	0
2022-12-16	63972	67	442	2
2022-12-15	63905	88	440	1
2022-12-14	63817	189	439	1
2022-12-13	63628	118	438	1
2022-12-12	63510	101	437	1
2022-12-11	63409	19	436	0
2022-12-10	63390	32	436	0
2022-12-09	63358	49	436	0
2022-12-08	63309	56	436	1
2022-12-07	63253	64	435	0
2022-12-06	63189	106	435	1
2022-12-05	63083	48	434	0
2022-12-04	63035	13	434	0
2022-12-03	63022	17	434	0
2022-12-02	63005	49	434	0
2022-12-01	62956	54	434	0
2022-11-30	62902	49	434	0
2022-11-29	62853	86	434	0
2022-11-28	62767	56	434	0
2022-11-27	62711	11	434	0
2022-11-26	62700	41	434	0
2022-11-25	62659	56	434	1
2022-11-24	62603	58	433	0
2022-11-23	62545	77	433	0
2022-11-22	62468	72	433	0
2022-11-21	62396	66	433	0
2022-11-20	62330	6	433	1
2022-11-19	62324	28	432	0
2022-11-18	62296	79	432	5
2022-11-17	62217	79	427	1
2022-11-16	62138	64	426	2
2022-11-15	62074	96	424	0
2022-11-14	61978	87	424	2
2022-11-13	61891	15	422	0
2022-11-12	61876	25	422	0
2022-11-11	61851	61	422	0
2022-11-10	61790	65	422	2
2022-11-09	61725	93	420	1
2022-11-08	61632	119	419	1
2022-11-07	61513	113	418	3
2022-11-06	61400	10	415	0
2022-11-05	61390	18	415	0
2022-11-04	61372	70	415	1
2022-11-03	61302	139	414	0
2022-11-02	61163	132	414	2
2022-11-01	61031	43	412	0
2022-10-31	60988	161	412	0
2022-10-30	60827	16	412	0
2022-10-29	60811	47	412	0
2022-10-28	60764	85	412	1
2022-10-27	60679	118	411	0
2022-10-26	60561	184	411	1
2022-10-25	60377	183	410	2
2022-10-24	60194	192	408	2
2022-10-23	60002	37	406	1
2022-10-22	59965	63	405	1
2022-10-21	59902	117	404	2
2022-10-20	59785	177	402	0
2022-10-19	59608	229	402	0
2022-10-18	59379	264	402	0
2022-10-17	59115	215	402	0
2022-10-16	58900	36	402	1
2022-10-15	58864	78	401	1
2022-10-14	58786	139	400	1
2022-10-13	58647	207	399	2
2022-10-12	58440	197	397	0
2022-10-11	58243	303	397	0
2022-10-10	57940	145	397	1
2022-10-09	57795	13	396	0
2022-10-08	57782	41	396	0
2022-10-07	57741	168	396	1
2022-10-06	57573	153	395	1
2022-10-05	57420	259	394	3
2022-10-04	57161	161	391	0
2022-10-03	57000	32	391	0
2022-10-02	56968	18	391	0
2022-10-01	56950	52	391	0
2022-09-30	56898	96	391	1
2022-09-29	56802	86	390	0
2022-09-28	56716	134	390	0
2022-09-27	56582	165	390	2
2022-09-26	56417	140	388	0
2022-09-25	56277	19	388	0
2022-09-24	56258	22	388	0
2022-09-23	56236	65	388	0
2022-09-22	56171	70	388	0
2022-09-21	56101	91	388	0
2022-09-20	56010	106	388	0
2022-09-19	55904	70	388	0
2022-09-18	55834	4	388	0
2022-09-17	55830	20	388	0
2022-09-16	55810	46	388	0
2022-09-15	55764	51	388	2
2022-09-14	55713	54	386	0
2022-09-13	55659	129	386	0
2022-09-12	55530	114	386	0
2022-09-11	55416	22	386	0
2022-09-10	55394	20	386	0
2022-09-09	55374	67	386	2
2022-09-08	55307	75	384	0
2022-09-07	55232	91	384	0
2022-09-06	55141	100	384	0
2022-09-05	55041	50	384	0
2022-09-04	54991	10	384	0
2022-09-03	54981	17	384	0
2022-09-02	54964	57	384	0
2022-09-01	54907	80	384	0
2022-08-31	54827	55	384	2
2022-08-30	54772	103	382	0
2022-08-29	54669	94	382	0
2022-08-28	54575	9	382	0
2022-08-27	54566	39	382	0
2022-08-26	54527	73	382	0
2022-08-25	54454	111	382	0
2022-08-24	54343	77	382	0
2022-08-23	54266	154	382	1
2022-08-22	54112	108	381	1
2022-08-21	54004	18	380	0
2022-08-20	53986	65	380	0
2022-08-19	53921	106	380	0
2022-08-18	53815	114	380	0
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2022-08-11	53139	135	379	0
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2022-08-08	52675	145	379	1
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2022-08-05	52471	82	378	0
2022-08-04	52389	158	378	2
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2022-08-02	52113	187	375	0
2022-08-01	51926	136	375	1
2022-07-31	51790	37	374	0
2022-07-30	51753	25	374	0
2022-07-29	51728	113	374	1
2022-07-28	51615	172	373	0
2022-07-27	51443	192	373	3
2022-07-26	51251	246	370	1
2022-07-25	51005	222	369	1
2022-07-24	50783	30	368	0
2022-07-23	50753	52	368	1
2022-07-22	50701	92	367	0
2022-07-21	50609	131	367	2
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2022-07-19	50312	161	365	0
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2022-07-08	48854	231	363	0
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2020-03-25	51	3	0	0
2020-03-24	48	6	0	0
2020-03-23	42	8	0	0
2020-03-21	34	4	0	0
2020-03-20	30	5	0	0
2020-03-19	25	9	0	0
2020-03-18	16	3	0	0
2020-03-17	13	3	0	0
2020-03-16	10	2	0	0
2020-03-13	8	3	0	0
2020-03-12	5	1	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: 0:03:34.566727