Germany: LK Potsdam-Mittelmark (Brandenburg)

• 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 12:20:49 CEST

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

overview(country="Germany", subregion="LK Potsdam-Mittelmark", weeks=5);

overview(country="Germany", subregion="LK Potsdam-Mittelmark");

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

# load the data
cases, deaths = germany_get_region(landkreis="LK Potsdam-Mittelmark")

# get population of the region for future normalisation:
inhabitants = population(country="Germany", subregion="LK Potsdam-Mittelmark")
print(f'Population of country="Germany", subregion="LK Potsdam-Mittelmark": {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 Potsdam-Mittelmark": 219521 people

	total cases	daily new cases	total deaths	daily new deaths
date
2023-03-06	96678	7	347	0
2023-03-04	96671	8	347	0
2023-03-03	96663	9	347	0
2023-03-02	96654	15	347	0
2023-03-01	96639	32	347	0
2023-02-28	96607	41	347	0
2023-02-27	96566	41	347	0
2023-02-26	96525	1	347	0
2023-02-25	96524	1	347	0
2023-02-24	96523	25	347	0
2023-02-23	96498	38	347	0
2023-02-22	96460	40	347	0
2023-02-21	96420	33	347	0
2023-02-20	96387	19	347	0
2023-02-19	96368	1	347	0
2023-02-18	96367	1	347	0
2023-02-17	96366	13	347	0
2023-02-16	96353	30	347	0
2023-02-15	96323	41	347	0
2023-02-14	96282	28	347	0
2023-02-13	96254	29	347	1
2023-02-12	96225	1	346	0
2023-02-11	96224	18	346	0
2023-02-10	96206	21	346	0
2023-02-09	96185	39	346	0
2023-02-08	96146	26	346	0
2023-02-07	96120	44	346	0
2023-02-06	96076	36	346	1
2023-02-03	96040	27	345	0
2023-02-02	96013	25	345	0
2023-02-01	95988	43	345	0
2023-01-31	95945	21	345	0
2023-01-30	95924	28	345	0
2023-01-28	95896	9	345	0
2023-01-27	95887	26	345	1
2023-01-26	95861	23	344	0
2023-01-25	95838	31	344	0
2023-01-24	95807	27	344	0
2023-01-23	95780	22	344	1
2023-01-21	95758	13	343	0
2023-01-20	95745	26	343	0
2023-01-19	95719	20	343	0
2023-01-18	95699	25	343	0
2023-01-17	95674	45	343	1
2023-01-16	95629	23	342	0
2023-01-15	95606	3	342	0
2023-01-14	95603	8	342	0
2023-01-13	95595	20	342	0
2023-01-12	95575	19	342	0
2023-01-11	95556	48	342	0
2023-01-10	95508	42	342	1
2023-01-09	95466	38	341	0
2023-01-08	95428	2	341	0
2023-01-07	95426	15	341	0
2023-01-06	95411	46	341	0
2023-01-05	95365	55	341	1
2023-01-04	95310	58	340	0
2023-01-03	95252	106	340	0
2023-01-02	95146	52	340	2
2023-01-01	95094	6	338	1
2022-12-31	95088	19	337	1
2022-12-30	95069	122	336	0
2022-12-29	94947	108	336	0
2022-12-28	94839	119	336	2
2022-12-27	94720	111	334	0
2022-12-26	94609	6	334	0
2022-12-25	94603	37	334	0
2022-12-24	94566	13	334	0
2022-12-23	94553	59	334	0
2022-12-22	94494	94	334	0
2022-12-21	94400	121	334	1
2022-12-20	94279	167	333	1
2022-12-19	94112	122	332	0
2022-12-18	93990	8	332	0
2022-12-17	93982	22	332	0
2022-12-16	93960	138	332	1
2022-12-15	93822	110	331	0
2022-12-14	93712	165	331	0
2022-12-13	93547	188	331	1
2022-12-12	93359	198	330	0
2022-12-11	93161	5	330	0
2022-12-10	93156	15	330	0
2022-12-09	93141	111	330	0
2022-12-08	93030	150	330	0
2022-12-07	92880	152	330	1
2022-12-06	92728	211	329	0
2022-12-05	92517	216	329	1
2022-12-03	92301	7	328	0
2022-12-02	92294	117	328	0
2022-12-01	92177	176	328	1
2022-11-30	92001	166	327	0
2022-11-29	91835	136	327	0
2022-11-28	91699	140	327	0
2022-11-27	91559	25	327	0
2022-11-26	91534	35	327	1
2022-11-25	91499	79	326	0
2022-11-24	91420	129	326	0
2022-11-23	91291	122	326	0
2022-11-22	91169	141	326	0
2022-11-21	91028	120	326	0
2022-11-20	90908	20	326	0
2022-11-19	90888	10	326	0
2022-11-18	90878	115	326	0
2022-11-17	90763	61	326	0
2022-11-16	90702	79	326	0
2022-11-15	90623	105	326	1
2022-11-14	90518	88	325	0
2022-11-13	90430	17	325	0
2022-11-12	90413	12	325	0
2022-11-11	90401	106	325	0
2022-11-10	90295	92	325	1
2022-11-09	90203	119	324	0
2022-11-08	90084	110	324	0
2022-11-07	89974	106	324	1
2022-11-06	89868	19	323	0
2022-11-05	89849	49	323	0
2022-11-04	89800	98	323	0
2022-11-03	89702	125	323	0
2022-11-02	89577	163	323	0
2022-11-01	89414	126	323	0
2022-10-31	89288	17	323	0
2022-10-30	89271	16	323	0
2022-10-29	89255	40	323	1
2022-10-28	89215	147	322	0
2022-10-27	89068	113	322	0
2022-10-26	88955	203	322	0
2022-10-25	88752	260	322	0
2022-10-24	88492	171	322	0
2022-10-23	88321	9	322	0
2022-10-22	88312	109	322	0
2022-10-21	88203	177	322	0
2022-10-20	88026	252	322	0
2022-10-19	87774	362	322	0
2022-10-18	87412	351	322	1
2022-10-17	87061	361	321	1
2022-10-16	86700	18	320	0
2022-10-15	86682	111	320	0
2022-10-14	86571	211	320	0
2022-10-13	86360	341	320	0
2022-10-12	86019	378	320	1
2022-10-11	85641	375	319	1
2022-10-10	85266	309	318	0
2022-10-09	84957	44	318	0
2022-10-08	84913	68	318	2
2022-10-07	84845	402	316	1
2022-10-06	84443	446	315	1
2022-10-05	83997	387	314	1
2022-10-04	83610	227	313	0
2022-10-03	83383	5	313	0
2022-10-02	83378	5	313	0
2022-10-01	83373	14	313	0
2022-09-30	83359	186	313	0
2022-09-29	83173	173	313	0
2022-09-28	83000	284	313	0
2022-09-27	82716	309	313	1
2022-09-26	82407	263	312	0
2022-09-25	82144	8	312	0
2022-09-24	82136	2	312	0
2022-09-23	82134	123	312	1
2022-09-22	82011	124	311	0
2022-09-21	81887	184	311	1
2022-09-20	81703	202	310	0
2022-09-19	81501	186	310	0
2022-09-18	81315	3	310	1
2022-09-17	81312	4	309	0
2022-09-16	81308	85	309	0
2022-09-15	81223	124	309	0
2022-09-14	81099	197	309	0
2022-09-13	80902	198	309	0
2022-09-12	80704	113	309	1
2022-09-11	80591	12	308	0
2022-09-10	80579	23	308	0
2022-09-09	80556	126	308	0
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2022-09-06	80122	222	308	0
2022-09-05	79900	131	308	0
2022-09-04	79769	2	308	0
2022-09-03	79767	1	308	0
2022-09-02	79766	129	308	0
2022-09-01	79637	96	308	0
2022-08-31	79541	101	308	0
2022-08-30	79440	197	308	0
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2022-08-23	78751	172	307	0
2022-08-22	78579	164	307	0
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2020-03-25	58	18	0	0
2020-03-24	40	4	0	0
2020-03-23	36	8	0	0
2020-03-22	28	2	0	0
2020-03-21	26	5	0	0
2020-03-20	21	4	0	0
2020-03-19	17	3	0	0
2020-03-18	14	4	0	0
2020-03-17	10	3	0	0
2020-03-15	7	2	0	0
2020-03-13	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: 0:02:59.820079