Germany: LK Göttingen (Niedersachsen)

• 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 13:07:38 CEST

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

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

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

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

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

# get population of the region for future normalisation:
inhabitants = population(country="Germany", subregion="LK Göttingen")
print(f'Population of country="Germany", subregion="LK Göttingen": {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 Göttingen": 323661 people

	total cases	daily new cases	total deaths	daily new deaths
date
2023-03-06	155117	30	525	0
2023-03-04	155087	41	525	0
2023-03-03	155046	38	525	0
2023-03-02	155008	49	525	0
2023-03-01	154959	74	525	0
2023-02-28	154885	106	525	0
2023-02-27	154779	49	525	0
2023-02-26	154730	17	525	0
2023-02-25	154713	64	525	0
2023-02-24	154649	67	525	0
2023-02-23	154582	84	525	0
2023-02-22	154498	105	525	1
2023-02-21	154393	117	524	0
2023-02-20	154276	81	524	1
2023-02-19	154195	24	523	0
2023-02-18	154171	57	523	0
2023-02-17	154114	59	523	0
2023-02-16	154055	100	523	0
2023-02-15	153955	64	523	0
2023-02-14	153891	120	523	1
2023-02-13	153771	87	522	2
2023-02-11	153684	31	520	0
2023-02-10	153653	61	520	0
2023-02-09	153592	52	520	0
2023-02-08	153540	74	520	0
2023-02-07	153466	121	520	0
2023-02-06	153345	65	520	0
2023-02-04	153280	44	520	0
2023-02-03	153236	61	520	1
2023-02-02	153175	70	519	0
2023-02-01	153105	87	519	0
2023-01-31	153018	151	519	0
2023-01-30	152867	93	519	0
2023-01-28	152774	67	519	0
2023-01-27	152707	64	519	0
2023-01-26	152643	65	519	0
2023-01-25	152578	78	519	0
2023-01-24	152500	127	519	0
2023-01-23	152373	84	519	0
2023-01-21	152289	35	519	0
2023-01-20	152254	37	519	0
2023-01-19	152217	63	519	1
2023-01-18	152154	77	518	0
2023-01-17	152077	90	518	0
2023-01-16	151987	173	518	0
2023-01-13	151814	29	518	0
2023-01-12	151785	103	518	0
2023-01-11	151682	156	518	2
2023-01-10	151526	178	516	0
2023-01-09	151348	224	516	0
2023-01-07	151124	50	516	0
2023-01-06	151074	91	516	1
2023-01-05	150983	139	515	3
2023-01-04	150844	158	512	0
2023-01-03	150686	323	512	0
2023-01-02	150363	366	512	1
2022-12-30	149997	156	511	0
2022-12-29	149841	159	511	0
2022-12-28	149682	221	511	0
2022-12-27	149461	338	511	2
2022-12-25	149123	44	509	0
2022-12-23	149079	254	509	2
2022-12-22	148825	274	507	1
2022-12-21	148551	390	506	2
2022-12-20	148161	217	504	1
2022-12-19	147944	392	503	2
2022-12-16	147552	170	501	0
2022-12-15	147382	199	501	2
2022-12-14	147183	223	499	2
2022-12-13	146960	302	497	0
2022-12-12	146658	537	497	3
2022-12-08	146121	187	494	0
2022-12-07	145934	286	494	2
2022-12-06	145648	264	492	0
2022-12-05	145384	388	492	1
2022-12-02	144996	118	491	0
2022-12-01	144878	201	491	3
2022-11-30	144677	216	488	0
2022-11-29	144461	266	488	0
2022-11-28	144195	285	488	0
2022-11-27	143910	7	488	0
2022-11-26	143903	12	488	0
2022-11-25	143891	230	488	0
2022-11-24	143661	221	488	0
2022-11-23	143440	165	488	0
2022-11-22	143275	279	488	0
2022-11-21	142996	218	488	0
2022-11-18	142778	157	488	0
2022-11-17	142621	158	488	0
2022-11-16	142463	196	488	0
2022-11-15	142267	270	488	0
2022-11-14	141997	215	488	2
2022-11-13	141782	2	486	0
2022-11-12	141780	8	486	0
2022-11-11	141772	167	486	1
2022-11-10	141605	199	485	0
2022-11-09	141406	212	485	1
2022-11-08	141194	297	484	0
2022-11-07	140897	326	484	1
2022-11-05	140571	9	483	0
2022-11-04	140562	215	483	0
2022-11-03	140347	245	483	0
2022-11-02	140102	499	483	0
2022-11-01	139603	521	483	1
2022-10-29	139082	2	482	0
2022-10-28	139080	240	482	0
2022-10-27	138840	359	482	1
2022-10-26	138481	397	481	1
2022-10-25	138084	484	480	0
2022-10-24	137600	534	480	0
2022-10-23	137066	3	480	0
2022-10-22	137063	35	480	0
2022-10-21	137028	471	480	1
2022-10-20	136557	344	479	3
2022-10-19	136213	572	476	0
2022-10-18	135641	767	476	0
2022-10-17	134874	884	476	2
2022-10-16	133990	1	474	0
2022-10-15	133989	7	474	0
2022-10-14	133982	363	474	2
2022-10-13	133619	652	472	1
2022-10-12	132967	653	471	0
2022-10-11	132314	699	471	1
2022-10-10	131615	906	470	4
2022-10-08	130709	31	466	0
2022-10-07	130678	827	466	2
2022-10-06	129851	1548	464	3
2022-10-05	128303	688	461	1
2022-10-04	127615	741	460	3
2022-10-02	126874	9	457	0
2022-10-01	126865	23	457	0
2022-09-30	126842	354	457	2
2022-09-29	126488	358	455	1
2022-09-28	126130	341	454	1
2022-09-27	125789	469	453	0
2022-09-26	125320	316	453	2
2022-09-24	125004	29	451	0
2022-09-23	124975	274	451	0
2022-09-22	124701	189	451	0
2022-09-21	124512	228	451	0
2022-09-20	124284	273	451	1
2022-09-19	124011	231	450	2
2022-09-18	123780	10	448	0
2022-09-17	123770	8	448	0
2022-09-16	123762	165	448	0
2022-09-15	123597	141	448	0
2022-09-14	123456	215	448	0
2022-09-13	123241	255	448	2
2022-09-12	122986	259	446	1
2022-09-11	122727	11	445	0
2022-09-09	122716	207	445	0
2022-09-08	122509	142	445	0
2022-09-07	122367	210	445	1
2022-09-06	122157	246	444	0
2022-09-05	121911	224	444	0
2022-09-04	121687	5	444	0
2022-09-03	121682	1	444	0
2022-09-02	121681	142	444	0
2022-09-01	121539	163	444	0
2022-08-31	121376	170	444	0
2022-08-30	121206	254	444	1
2022-08-29	120952	254	443	1
2022-08-28	120698	21	442	0
2022-08-27	120677	9	442	0
2022-08-26	120668	139	442	0
2022-08-25	120529	164	442	0
2022-08-24	120365	194	442	0
2022-08-23	120171	329	442	0
2022-08-22	119842	303	442	1
2022-08-21	119539	2	441	0
2022-08-20	119537	1	441	0
2022-08-19	119536	191	441	0
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2022-08-16	118886	307	441	1
2022-08-15	118579	385	440	1
2022-08-14	118194	8	439	0
2022-08-13	118186	2	439	0
2022-08-12	118184	236	439	0
2022-08-11	117948	280	439	0
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2022-08-01	115599	433	436	3
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2022-07-21	112311	544	425	0
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2020-03-23	78	11	0	0
2020-03-22	67	4	0	0
2020-03-21	63	10	0	0
2020-03-20	53	8	0	0
2020-03-19	45	7	0	0
2020-03-18	38	19	0	0
2020-03-17	19	5	0	0
2020-03-16	14	4	0	0
2020-03-15	10	2	0	0
2020-03-14	8	2	0	0
2020-03-13	6	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: 0:03:10.454703