Germany: LK Sömmerda (Thüringen)¶

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In [1]:
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 16:09:35 CEST
In [2]:
%config InlineBackend.figure_formats = ['svg']
from oscovida import *
In [3]:
overview(country="Germany", subregion="LK Sömmerda", weeks=5);
2023-03-07T16:09:46.417557 image/svg+xml Matplotlib v3.7.1, https://matplotlib.org/ 30 Jan 06 Feb 13 Feb 20 Feb 27 Feb 06 Mar 30 30 40 40 50 50 7-day incidence rate (per 100K people) 27.6 LK Sömmerda, Germany, last 5 weeks, last data point from 2023-03-06 30 Jan 06 Feb 13 Feb 20 Feb 27 Feb 06 Mar 0 5 10 daily change normalised per 100K 30 Jan 06 Feb 13 Feb 20 Feb 27 Feb 06 Mar −0.050 −0.050 −0.025 −0.025 0.000 0.000 0.025 0.025 0.050 0.050 daily change Germany-LK Sömmerda new deaths (rolling 7d mean) Germany-LK Sömmerda new deaths 30 Jan 06 Feb 13 Feb 20 Feb 27 Feb 06 Mar 0.6 0.6 0.8 0.8 1.0 1.0 1.2 1.2 1.4 1.4 R & growth factor (based on cases) Germany-LK Sömmerda cases daily growth factor Germany-LK Sömmerda cases daily growth factor (rolling mean) Germany-LK Sömmerda estimated R (using cases) 30 Jan 06 Feb 13 Feb 20 Feb 27 Feb 06 Mar 0.8 0.8 0.9 0.9 1.0 1.0 1.1 1.1 1.2 1.2 R & growth factor (based on deaths) Germany-LK Sömmerda deaths daily growth factor Germany-LK Sömmerda deaths daily growth factor (rolling mean) Germany-LK Sömmerda estimated R (using deaths) 30 Jan 06 Feb 13 Feb 20 Feb 27 Feb 06 Mar 0 2500 5000 7500 10000 cases doubling time [days] Germany-LK Sömmerda doubling time cases (rolling mean) 0.00 3.44 6.87 daily change Germany-LK Sömmerda new cases (rolling 7d mean) Germany-LK Sömmerda new cases 0.000 0.208 0.416 0.623 0.831
In [4]:
overview(country="Germany", subregion="LK Sömmerda");
2023-03-07T16:10:04.503527 image/svg+xml Matplotlib v3.7.1, https://matplotlib.org/ May 20 Sep 20 Jan 21 May 21 Sep 21 Jan 22 May 22 Sep 22 Jan 23 0 0 1000 1000 2000 2000 3000 3000 7-day incidence rate (per 100K people) 27.6 LK Sömmerda, Germany, last data point from 2023-03-06 May 20 Sep 20 Jan 21 May 21 Sep 21 Jan 22 May 22 Sep 22 Jan 23 0 200 400 600 daily change normalised per 100K May 20 Sep 20 Jan 21 May 21 Sep 21 Jan 22 May 22 Sep 22 Jan 23 0 2 4 daily change normalised per 100K May 20 Sep 20 Jan 21 May 21 Sep 21 Jan 22 May 22 Sep 22 Jan 23 0.6 0.6 0.8 0.8 1.0 1.0 1.2 1.2 1.4 1.4 R & growth factor (based on cases) Germany-LK Sömmerda cases daily growth factor Germany-LK Sömmerda cases daily growth factor (rolling mean) Germany-LK Sömmerda estimated R (using cases) May 20 Sep 20 Jan 21 May 21 Sep 21 Jan 22 May 22 Sep 22 Jan 23 0.8 0.8 0.9 0.9 1.0 1.0 1.1 1.1 1.2 1.2 R & growth factor (based on deaths) Germany-LK Sömmerda deaths daily growth factor Germany-LK Sömmerda deaths daily growth factor (rolling mean) Germany-LK Sömmerda estimated R (using deaths) May 20 Sep 20 Jan 21 May 21 Sep 21 Jan 22 May 22 Sep 22 Jan 23 0 5000 10000 cases doubling time [days] Germany-LK Sömmerda doubling time cases (rolling mean) Germany-LK Sömmerda doubling time deaths (rolling mean) 0.0 137.4 274.9 412.3 daily change Germany-LK Sömmerda new cases (rolling 7d mean) Germany-LK Sömmerda new cases 0.000 1.374 2.749 daily change Germany-LK Sömmerda new deaths (rolling 7d mean) Germany-LK Sömmerda new deaths 0.0 78.4 156.9 deaths doubling time [days]
In [5]:
compare_plot(country="Germany", subregion="LK Sömmerda", dates="2020-03-15:");
2023-03-07T16:11:53.801957 image/svg+xml Matplotlib v3.7.1, https://matplotlib.org/ 2020-05 2020-09 2021-01 2021-05 2021-09 2022-01 2022-05 2022-09 2023-01 0.1 0.1 1 1 10 10 100 100 daily new cases (rolling 7-day mean) normalised by 100K people Daily cases (top) and deaths (below) for Germany: LK Sömmerda LK Sömmerda Bayern Berlin Bremen Hamburg Hessen Nordrhein-Westfalen Sachsen-Anhalt 2020-05 2020-09 2021-01 2021-05 2021-09 2022-01 2022-05 2022-09 2023-01 0.001 0.001 0.01 0.01 0.1 0.1 1 1 daily new deaths (rolling 7-day mean) normalised by 100K people LK Sömmerda Bayern Berlin Bremen Hamburg Hessen Nordrhein-Westfalen Sachsen-Anhalt
In [6]:
# load the data
cases, deaths = germany_get_region(landkreis="LK Sömmerda")

# get population of the region for future normalisation:
inhabitants = population(country="Germany", subregion="LK Sömmerda")
print(f'Population of country="Germany", subregion="LK Sömmerda": {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 Sömmerda": 68717 people
Out[6]:
total cases daily new cases total deaths daily new deaths
date
2023-03-06 27726 3 269 0
2023-03-03 27723 2 269 0
2023-03-02 27721 4 269 0
2023-02-28 27717 10 269 0
2023-02-27 27707 7 269 0
2023-02-24 27700 3 269 0
2023-02-23 27697 10 269 0
2023-02-22 27687 9 269 0
2023-02-21 27678 3 269 0
2023-02-20 27675 10 269 0
2023-02-17 27665 6 269 0
2023-02-16 27659 9 269 0
2023-02-15 27650 1 269 0
2023-02-14 27649 6 269 0
2023-02-13 27643 4 269 0
2023-02-10 27639 5 269 0
2023-02-09 27634 1 269 0
2023-02-08 27633 6 269 0
2023-02-07 27627 5 269 0
2023-02-06 27622 5 269 0
2023-02-03 27617 5 269 0
2023-02-02 27612 6 269 0
2023-02-01 27606 2 269 0
2023-01-31 27604 3 269 0
2023-01-30 27601 4 269 0
2023-01-27 27597 6 269 0
2023-01-26 27591 5 269 0
2023-01-25 27586 1 269 0
2023-01-24 27585 3 269 0
2023-01-23 27582 4 269 0
2023-01-20 27578 2 269 0
2023-01-19 27576 4 269 0
2023-01-18 27572 4 269 0
2023-01-17 27568 3 269 0
2023-01-16 27565 8 269 0
2023-01-13 27557 4 269 0
2023-01-12 27553 4 269 0
2023-01-11 27549 10 269 0
2023-01-10 27539 16 269 0
2023-01-09 27523 6 269 0
2023-01-06 27517 9 269 0
2023-01-05 27508 19 269 0
2023-01-04 27489 20 269 2
2023-01-03 27469 7 267 0
2023-01-02 27462 10 267 0
2022-12-30 27452 7 267 0
2022-12-29 27445 8 267 1
2022-12-28 27437 14 266 0
2022-12-27 27423 11 266 0
2022-12-23 27412 7 266 0
2022-12-22 27405 19 266 0
2022-12-21 27386 14 266 1
2022-12-20 27372 13 265 0
2022-12-19 27359 16 265 0
2022-12-16 27343 20 265 1
2022-12-15 27323 13 264 0
2022-12-14 27310 17 264 0
2022-12-13 27293 12 264 0
2022-12-12 27281 20 264 1
2022-12-09 27261 25 263 0
2022-12-08 27236 18 263 2
2022-12-07 27218 18 261 2
2022-12-06 27200 11 259 0
2022-12-03 27189 1 259 0
2022-12-02 27188 22 259 0
2022-12-01 27166 10 259 0
2022-11-30 27156 12 259 0
2022-11-29 27144 24 259 0
2022-11-28 27120 4 259 0
2022-11-27 27116 1 259 0
2022-11-26 27115 2 259 0
2022-11-25 27113 20 259 0
2022-11-24 27093 21 259 0
2022-11-23 27072 19 259 1
2022-11-21 27053 2 258 0
2022-11-20 27051 1 258 0
2022-11-19 27050 2 258 1
2022-11-18 27048 22 257 0
2022-11-17 27026 20 257 0
2022-11-16 27006 23 257 0
2022-11-15 26983 25 257 0
2022-11-14 26958 20 257 0
2022-11-13 26938 1 257 0
2022-11-11 26937 14 257 0
2022-11-10 26923 9 257 0
2022-11-09 26914 15 257 0
2022-11-08 26899 33 257 0
2022-11-07 26866 20 257 0
2022-11-06 26846 1 257 0
2022-11-05 26845 2 257 0
2022-11-04 26843 27 257 0
2022-11-03 26816 32 257 0
2022-11-02 26784 20 257 0
2022-11-01 26764 58 257 1
2022-10-31 26706 7 256 0
2022-10-30 26699 2 256 0
2022-10-29 26697 3 256 0
2022-10-28 26694 30 256 1
2022-10-27 26664 43 255 0
2022-10-26 26621 63 255 0
2022-10-25 26558 49 255 0
2022-10-24 26509 63 255 0
2022-10-23 26446 3 255 0
2022-10-22 26443 30 255 0
2022-10-21 26413 28 255 0
2022-10-20 26385 39 255 0
2022-10-19 26346 63 255 0
2022-10-18 26283 67 255 0
2022-10-17 26216 74 255 0
2022-10-16 26142 4 255 0
2022-10-15 26138 2 255 0
2022-10-14 26136 60 255 0
2022-10-13 26076 38 255 1
2022-10-12 26038 82 254 0
2022-10-11 25956 65 254 0
2022-10-10 25891 87 254 0
2022-10-09 25804 3 254 0
2022-10-08 25801 7 254 0
2022-10-07 25794 84 254 0
2022-10-06 25710 80 254 0
2022-10-05 25630 100 254 0
2022-10-04 25530 39 254 0
2022-10-02 25491 4 254 0
2022-10-01 25487 8 254 0
2022-09-30 25479 44 254 0
2022-09-29 25435 19 254 0
2022-09-28 25416 41 254 1
2022-09-27 25375 63 253 0
2022-09-26 25312 53 253 1
2022-09-25 25259 2 252 1
2022-09-24 25257 9 251 0
2022-09-23 25248 32 251 0
2022-09-22 25216 36 251 0
2022-09-21 25180 27 251 0
2022-09-20 25153 8 251 0
2022-09-19 25145 10 251 0
2022-09-18 25135 1 251 0
2022-09-17 25134 3 251 0
2022-09-16 25131 20 251 0
2022-09-15 25111 23 251 0
2022-09-14 25088 24 251 0
2022-09-13 25064 24 251 0
2022-09-12 25040 38 251 1
2022-09-10 25002 3 250 0
2022-09-09 24999 11 250 0
2022-09-08 24988 22 250 0
2022-09-07 24966 13 250 0
2022-09-06 24953 20 250 0
2022-09-05 24933 6 250 0
2022-09-03 24927 6 250 0
2022-09-02 24921 9 250 0
2022-09-01 24912 10 250 0
2022-08-31 24902 22 250 0
2022-08-30 24880 8 250 0
2022-08-29 24872 18 250 0
2022-08-27 24854 4 250 0
2022-08-26 24850 11 250 0
2022-08-25 24839 7 250 0
2022-08-24 24832 13 250 0
2022-08-23 24819 31 250 0
2022-08-22 24788 19 250 0
2022-08-20 24769 7 250 0
2022-08-19 24762 16 250 0
2022-08-18 24746 17 250 0
2022-08-17 24729 30 250 1
2022-08-16 24699 17 249 0
2022-08-15 24682 30 249 0
2022-08-13 24652 9 249 0
2022-08-12 24643 27 249 0
2022-08-11 24616 4 249 0
2022-08-10 24612 33 249 0
2022-08-09 24579 10 249 0
2022-08-08 24569 31 249 0
2022-08-06 24538 4 249 0
2022-08-05 24534 12 249 0
2022-08-04 24522 27 249 0
2022-08-03 24495 21 249 0
2022-08-02 24474 24 249 0
2022-08-01 24450 36 249 0
2022-07-31 24414 2 249 0
2022-07-30 24412 5 249 0
2022-07-29 24407 26 249 0
2022-07-28 24381 20 249 1
2022-07-27 24361 44 248 1
2022-07-26 24317 47 247 0
2022-07-25 24270 42 247 0
2022-07-24 24228 8 247 1
2022-07-23 24220 6 246 1
2022-07-22 24214 36 245 0
2022-07-21 24178 27 245 0
2022-07-20 24151 33 245 0
2022-07-19 24118 45 245 0
2022-07-18 24073 39 245 0
2022-07-17 24034 3 245 0
2022-07-16 24031 5 245 0
2022-07-15 24026 34 245 0
2022-07-14 23992 34 245 0
2022-07-13 23958 44 245 1
2022-07-12 23914 46 244 0
2022-07-11 23868 31 244 0
2022-07-10 23837 2 244 0
2022-07-09 23835 9 244 0
2022-07-08 23826 17 244 0
2022-07-07 23809 23 244 0
2022-07-06 23786 14 244 0
2022-07-05 23772 35 244 0
2022-07-04 23737 30 244 0
2022-07-03 23707 6 244 0
2022-07-02 23701 7 244 0
2022-07-01 23694 19 244 1
2022-06-30 23675 10 243 0
2022-06-29 23665 22 243 0
2022-06-28 23643 27 243 0
2022-06-27 23616 50 243 0
2022-06-26 23566 2 243 0
2022-06-25 23564 6 243 0
2022-06-24 23558 15 243 0
2022-06-23 23543 24 243 0
2022-06-22 23519 19 243 0
2022-06-21 23500 26 243 0
2022-06-20 23474 22 243 0
2022-06-19 23452 3 243 0
2022-06-18 23449 6 243 0
2022-06-17 23443 21 243 0
2022-06-16 23422 16 243 0
2022-06-15 23406 21 243 0
2022-06-14 23385 24 243 0
2022-06-13 23361 18 243 0
2022-06-12 23343 1 243 0
2022-06-11 23342 7 243 0
2022-06-10 23335 7 243 0
2022-06-09 23328 20 243 0
2022-06-08 23308 8 243 0
2022-06-07 23300 18 243 0
2022-06-05 23282 1 243 0
2022-06-04 23281 4 243 0
2022-06-03 23277 3 243 0
2022-06-02 23274 5 243 0
2022-06-01 23269 4 243 0
2022-05-31 23265 9 243 0
2022-05-30 23256 9 243 0
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2021-06-02 4150 5 140 0
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2021-05-31 4139 2 140 0
2021-05-29 4137 3 140 0
2021-05-28 4134 8 140 2
2021-05-27 4126 4 138 0
2021-05-26 4122 12 138 0
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2021-05-24 4102 3 138 1
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2021-05-20 4076 12 137 0
2021-05-19 4064 24 137 0
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2021-05-17 4016 7 137 1
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2021-05-11 3942 11 136 1
2021-05-10 3931 10 135 0
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2021-05-07 3884 17 134 0
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2021-05-05 3847 25 134 1
2021-05-04 3822 33 133 0
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2021-05-02 3778 8 133 0
2021-05-01 3770 11 133 1
2021-04-30 3759 24 132 0
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2021-04-28 3699 23 132 0
2021-04-27 3676 19 132 0
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2021-04-24 3626 40 132 1
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2021-04-22 3550 43 128 0
2021-04-21 3507 36 128 0
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2021-04-19 3421 35 125 0
2021-04-18 3386 14 125 0
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2021-04-15 3329 57 124 4
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2021-04-13 3234 37 119 0
2021-04-12 3197 29 119 0
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2021-04-10 3151 18 119 0
2021-04-09 3133 35 119 0
2021-04-08 3098 38 119 0
2021-04-07 3060 35 119 0
2021-04-06 3025 16 119 0
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2021-03-20 2592 16 110 0
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2021-03-18 2536 30 110 1
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2021-03-12 2410 22 107 1
2021-03-11 2388 24 106 0
2021-03-10 2364 19 106 0
2021-03-09 2345 12 106 0
2021-03-08 2333 3 106 0
2021-03-07 2330 18 106 3
2021-03-06 2312 13 103 0
2021-03-05 2299 11 103 0
2021-03-04 2288 16 103 0
2021-03-03 2272 13 103 0
2021-03-02 2259 22 103 1
2021-03-01 2237 3 102 0
2021-02-28 2234 8 102 0
2021-02-27 2226 15 102 0
2021-02-26 2211 11 102 0
2021-02-25 2200 13 102 0
2021-02-24 2187 56 102 3
2021-02-23 2131 13 99 0
2021-02-22 2118 3 99 0
2021-02-21 2115 8 99 2
2021-02-20 2107 14 97 0
2021-02-19 2093 21 97 0
2021-02-18 2072 23 97 2
2021-02-17 2049 4 95 0
2021-02-16 2045 16 95 0
2021-02-15 2029 2 95 0
2021-02-14 2027 1 95 0
2021-02-13 2026 12 95 3
2021-02-12 2014 15 92 1
2021-02-11 1999 11 91 1
2021-02-10 1988 9 90 1
2021-02-09 1979 6 89 2
2021-02-07 1973 2 87 1
2021-02-06 1971 14 86 0
2021-02-05 1957 16 86 1
2021-02-04 1941 21 85 2
2021-02-03 1920 20 83 2
2021-02-02 1900 18 81 1
2021-02-01 1882 9 80 1
2021-01-31 1873 7 79 0
2021-01-30 1866 13 79 0
2021-01-29 1853 13 79 0
2021-01-28 1840 17 79 0
2021-01-27 1823 24 79 1
2021-01-26 1799 32 78 1
2021-01-25 1767 9 77 0
2021-01-24 1758 6 77 0
2021-01-23 1752 11 77 0
2021-01-22 1741 25 77 0
2021-01-21 1716 19 77 3
2021-01-20 1697 17 74 0
2021-01-19 1680 29 74 2
2021-01-18 1651 3 72 0
2021-01-17 1648 11 72 0
2021-01-16 1637 29 72 1
2021-01-15 1608 15 71 0
2021-01-14 1593 25 71 1
2021-01-13 1568 42 70 3
2021-01-12 1526 47 67 4
2021-01-11 1479 10 63 1
2021-01-10 1469 1 62 0
2021-01-09 1468 16 62 1
2021-01-08 1452 41 61 2
2021-01-07 1411 50 59 2
2021-01-06 1361 42 57 1
2021-01-05 1319 39 56 1
2021-01-04 1280 4 55 2
2021-01-03 1276 2 53 0
2021-01-02 1274 9 53 1
2021-01-01 1265 26 52 3
2020-12-31 1239 39 49 2
2020-12-30 1200 65 47 3
2020-12-29 1135 46 44 2
2020-12-28 1089 13 42 1
2020-12-27 1076 6 41 1
2020-12-26 1070 7 40 0
2020-12-25 1063 9 40 1
2020-12-24 1054 25 39 0
2020-12-23 1029 36 39 2
2020-12-22 993 34 37 0
2020-12-21 959 11 37 1
2020-12-20 948 9 36 0
2020-12-19 939 22 36 1
2020-12-18 917 33 35 1
2020-12-17 884 32 34 0
2020-12-16 852 28 34 3
2020-12-15 824 23 31 2
2020-12-14 801 1 29 0
2020-12-13 800 22 29 1
2020-12-12 778 1 28 0
2020-12-11 777 32 28 2
2020-12-10 745 16 26 1
2020-12-09 729 15 25 1
2020-12-08 714 18 24 1
2020-12-07 696 14 23 0
2020-12-06 682 1 23 0
2020-12-05 681 14 23 1
2020-12-04 667 26 22 3
2020-12-03 641 19 19 0
2020-12-02 622 18 19 0
2020-12-01 604 23 19 0
2020-11-30 581 4 19 0
2020-11-29 577 4 19 1
2020-11-28 573 12 18 1
2020-11-27 561 38 17 1
2020-11-26 523 37 16 1
2020-11-25 486 25 15 0
2020-11-24 461 16 15 4
2020-11-23 445 7 11 1
2020-11-22 438 12 10 0
2020-11-21 426 12 10 0
2020-11-20 414 49 10 3
2020-11-19 365 14 7 0
2020-11-18 351 11 7 0
2020-11-17 340 16 7 0
2020-11-16 324 9 7 0
2020-11-15 315 11 7 0
2020-11-14 304 2 7 0
2020-11-13 302 8 7 0
2020-11-12 294 29 7 3
2020-11-11 265 6 4 0
2020-11-10 259 10 4 0
2020-11-09 249 4 4 0
2020-11-08 245 2 4 0
2020-11-07 243 3 4 0
2020-11-06 240 5 4 0
2020-11-05 235 7 4 0
2020-11-04 228 3 4 0
2020-11-03 225 8 4 0
2020-11-02 217 4 4 0
2020-10-31 213 6 4 0
2020-10-30 207 6 4 0
2020-10-29 201 5 4 0
2020-10-28 196 7 4 1
2020-10-27 189 7 3 0
2020-10-26 182 4 3 0
2020-10-24 178 7 3 0
2020-10-23 171 10 3 0
2020-10-22 161 12 3 0
2020-10-21 149 12 3 0
2020-10-20 137 8 3 1
2020-10-19 129 1 2 0
2020-10-18 128 1 2 0
2020-10-17 127 10 2 0
2020-10-16 117 15 2 0
2020-10-15 102 7 2 0
2020-10-14 95 4 2 0
2020-10-13 91 7 2 0
2020-10-12 84 6 2 0
2020-10-11 78 1 2 0
2020-10-10 77 3 2 1
2020-10-09 74 5 1 0
2020-10-08 69 3 1 0
2020-10-06 66 1 1 0
2020-10-03 65 1 1 0
2020-10-02 64 1 1 0
2020-10-01 63 1 1 0
2020-09-23 62 1 1 0
2020-09-21 61 1 1 0
2020-09-18 60 1 1 0
2020-09-14 59 1 1 0
2020-09-11 58 1 1 0
2020-09-10 57 1 1 0
2020-09-04 56 1 1 0
2020-09-02 55 1 1 0
2020-08-29 54 1 1 0
2020-08-27 53 1 1 0
2020-08-26 52 1 1 0
2020-08-25 51 2 1 0
2020-08-21 49 2 1 0
2020-08-14 47 1 1 0
2020-08-12 46 1 1 0
2020-08-11 45 1 1 0
2020-08-06 44 1 1 0
2020-07-30 43 1 1 0
2020-07-26 42 1 1 0
2020-07-16 41 1 1 0
2020-07-14 40 1 1 0
2020-07-11 39 1 1 0
2020-06-30 38 1 1 0
2020-05-01 37 1 1 0
2020-04-21 36 3 1 0
2020-04-16 33 1 1 0
2020-04-09 32 1 1 0
2020-04-08 31 1 1 0
2020-04-07 30 1 1 0
2020-04-05 29 1 1 1
2020-04-02 28 2 0 0
2020-04-01 26 3 0 0
2020-03-31 23 1 0 0
2020-03-27 22 3 0 0
2020-03-26 19 6 0 0
2020-03-25 13 4 0 0
2020-03-24 9 1 0 0
2020-03-23 8 2 0 0
2020-03-22 6 2 0 0
2020-03-21 4 1 0 0
2020-03-20 3 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)
In [7]:
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.
In [8]:
# to force a fresh download of data, run "clear_cache()"
In [9]:
print(f"Notebook execution took: {datetime.datetime.now()-start}")

Notebook execution took: 0:02:27.018953