Germany: SK Hagen (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 14:25:53 CEST

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

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

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

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

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

# get population of the region for future normalisation:
inhabitants = population(country="Germany", subregion="SK Hagen")
print(f'Population of country="Germany", subregion="SK Hagen": {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 Hagen": 188713 people

	total cases	daily new cases	total deaths	daily new deaths
date
2023-03-06	84992	16	646	0
2023-03-03	84976	10	646	0
2023-03-02	84966	18	646	0
2023-03-01	84948	34	646	0
2023-02-28	84914	47	646	0
2023-02-27	84867	60	646	0
2023-02-24	84807	27	646	0
2023-02-23	84780	36	646	0
2023-02-22	84744	27	646	0
2023-02-21	84717	91	646	1
2023-02-20	84626	75	645	1
2023-02-17	84551	45	644	0
2023-02-16	84506	44	644	0
2023-02-15	84462	49	644	0
2023-02-14	84413	73	644	2
2023-02-13	84340	74	642	4
2023-02-10	84266	31	638	0
2023-02-09	84235	39	638	0
2023-02-08	84196	41	638	1
2023-02-07	84155	39	637	0
2023-02-06	84116	46	637	0
2023-02-03	84070	26	637	0
2023-02-02	84044	30	637	0
2023-02-01	84014	50	637	0
2023-01-31	83964	61	637	0
2023-01-30	83903	70	637	1
2023-01-27	83833	31	636	0
2023-01-26	83802	33	636	1
2023-01-25	83769	49	635	0
2023-01-24	83720	35	635	1
2023-01-23	83685	65	634	0
2023-01-20	83620	20	634	1
2023-01-19	83600	38	633	0
2023-01-18	83562	32	633	0
2023-01-17	83530	45	633	1
2023-01-16	83485	73	632	0
2023-01-13	83412	34	632	1
2023-01-12	83378	48	631	0
2023-01-11	83330	46	631	0
2023-01-10	83284	50	631	2
2023-01-09	83234	125	629	2
2023-01-06	83109	47	627	1
2023-01-05	83062	80	626	0
2023-01-04	82982	84	626	1
2023-01-03	82898	95	625	1
2023-01-02	82803	136	624	5
2022-12-30	82667	63	619	2
2022-12-29	82604	131	617	1
2022-12-28	82473	162	616	2
2022-12-27	82311	216	614	1
2022-12-26	82095	6	613	0
2022-12-23	82089	137	613	0
2022-12-22	81952	150	613	0
2022-12-21	81802	178	613	3
2022-12-20	81624	203	610	3
2022-12-19	81421	199	607	1
2022-12-16	81222	124	606	1
2022-12-15	81098	141	605	1
2022-12-14	80957	174	604	0
2022-12-13	80783	153	604	0
2022-12-12	80630	187	604	2
2022-12-09	80443	100	602	2
2022-12-08	80343	102	600	1
2022-12-07	80241	108	599	1
2022-12-06	80133	150	598	0
2022-12-05	79983	134	598	1
2022-12-04	79849	5	597	0
2022-12-02	79844	87	597	0
2022-12-01	79757	82	597	0
2022-11-30	79675	101	597	0
2022-11-29	79574	108	597	1
2022-11-28	79466	130	596	0
2022-11-25	79336	88	596	0
2022-11-24	79248	84	596	0
2022-11-23	79164	82	596	0
2022-11-22	79082	105	596	0
2022-11-21	78977	141	596	2
2022-11-18	78836	86	594	0
2022-11-17	78750	101	594	1
2022-11-16	78649	103	593	1
2022-11-15	78546	88	592	2
2022-11-14	78458	143	590	0
2022-11-11	78315	87	590	0
2022-11-10	78228	70	590	0
2022-11-09	78158	139	590	3
2022-11-08	78019	133	587	0
2022-11-07	77886	95	587	1
2022-11-04	77791	109	586	3
2022-11-03	77682	138	583	1
2022-11-02	77544	168	582	4
2022-11-01	77376	5	578	0
2022-10-31	77371	231	578	3
2022-10-28	77140	137	575	1
2022-10-27	77003	194	574	0
2022-10-26	76809	221	574	3
2022-10-25	76588	223	571	1
2022-10-24	76365	343	570	4
2022-10-21	76022	179	566	2
2022-10-20	75843	276	564	1
2022-10-19	75567	329	563	2
2022-10-18	75238	359	561	5
2022-10-17	74879	347	556	3
2022-10-16	74532	5	553	0
2022-10-15	74527	11	553	0
2022-10-14	74516	223	553	1
2022-10-13	74293	264	552	1
2022-10-12	74029	251	551	0
2022-10-11	73778	228	551	0
2022-10-10	73550	226	551	3
2022-10-09	73324	15	548	0
2022-10-08	73309	26	548	0
2022-10-07	73283	154	548	1
2022-10-06	73129	264	547	1
2022-10-05	72865	303	546	4
2022-10-04	72562	220	542	1
2022-10-02	72342	9	541	1
2022-09-30	72333	131	540	0
2022-09-29	72202	130	540	1
2022-09-28	72072	142	539	0
2022-09-27	71930	148	539	1
2022-09-26	71782	159	538	2
2022-09-23	71623	84	536	1
2022-09-22	71539	85	535	1
2022-09-21	71454	83	534	1
2022-09-20	71371	101	533	0
2022-09-19	71270	95	533	0
2022-09-16	71175	46	533	0
2022-09-15	71129	79	533	0
2022-09-14	71050	81	533	0
2022-09-13	70969	97	533	0
2022-09-12	70872	145	533	1
2022-09-09	70727	85	532	0
2022-09-08	70642	80	532	0
2022-09-07	70562	83	532	0
2022-09-06	70479	101	532	1
2022-09-05	70378	131	531	0
2022-09-04	70247	1	531	0
2022-09-02	70246	102	531	0
2022-09-01	70144	89	531	0
2022-08-31	70055	84	531	0
2022-08-30	69971	117	531	0
2022-08-29	69854	107	531	0
2022-08-26	69747	104	531	1
2022-08-25	69643	112	530	0
2022-08-24	69531	121	530	0
2022-08-23	69410	144	530	0
2022-08-22	69266	164	530	2
2022-08-19	69102	113	528	0
2022-08-18	68989	130	528	0
2022-08-17	68859	142	528	2
2022-08-16	68717	184	526	3
2022-08-15	68533	194	523	2
2022-08-12	68339	109	521	2
2022-08-11	68230	111	519	1
2022-08-10	68119	131	518	0
2022-08-09	67988	152	518	1
2022-08-08	67836	220	517	1
2022-08-07	67616	1	516	0
2022-08-05	67615	67	516	0
2022-08-04	67548	140	516	0
2022-08-03	67408	154	516	1
2022-08-02	67254	207	515	0
2022-08-01	67047	241	515	0
2022-07-29	66806	137	515	0
2022-07-28	66669	160	515	2
2022-07-27	66509	267	513	3
2022-07-26	66242	106	510	1
2022-07-25	66136	269	509	1
2022-07-22	65867	132	508	0
2022-07-21	65735	201	508	0
2022-07-20	65534	153	508	0
2022-07-19	65381	226	508	1
2022-07-18	65155	350	507	1
2022-07-17	64805	13	506	0
2022-07-16	64792	2	506	0
2022-07-15	64790	156	506	2
2022-07-14	64634	239	504	0
2022-07-13	64395	230	504	0
2022-07-12	64165	248	504	0
2022-07-11	63917	278	504	2
2022-07-10	63639	3	502	0
2022-07-08	63636	263	502	1
2022-07-07	63373	255	501	2
2022-07-06	63118	254	499	1
2022-07-05	62864	321	498	2
2022-07-04	62543	285	496	0
2022-07-03	62258	1	496	0
2022-07-02	62257	1	496	0
2022-07-01	62256	293	496	0
2022-06-30	61963	236	496	0
2022-06-29	61727	371	496	0
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2022-06-27	61007	267	496	0
2022-06-26	60740	2	496	0
2022-06-25	60738	1	496	0
2022-06-24	60737	202	496	0
2022-06-23	60535	192	496	1
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2022-06-20	59728	350	495	3
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2022-06-16	59245	3	492	0
2022-06-15	59242	177	492	0
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2022-06-08	58271	290	490	2
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2022-06-01	57673	101	488	0
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2022-05-27	57317	97	487	0
2022-05-25	57220	67	487	0
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2022-05-23	57045	153	487	0
2022-05-20	56892	80	487	0
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2022-05-18	56735	111	487	2
2022-05-17	56624	140	485	0
2022-05-16	56484	158	485	1
2022-05-13	56326	126	484	0
2022-05-12	56200	110	484	0
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2022-05-02	54776	260	482	1
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2022-04-27	54122	220	478	1
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2020-03-17	11	5	1	1
2020-03-16	6	1	0	0
2020-03-13	5	2	0	0
2020-03-10	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: 0:02:29.828574