Germany: LK Rhön-Grabfeld (Bayern)¶

  • Homepage of project: https://oscovida.github.io
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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 11:22:00 CEST
In [2]:
%config InlineBackend.figure_formats = ['svg']
from oscovida import *
In [3]:
overview(country="Germany", subregion="LK Rhön-Grabfeld", weeks=5);
2023-03-07T11:22:16.828931 image/svg+xml Matplotlib v3.7.1, https://matplotlib.org/ 30 Jan 06 Feb 13 Feb 20 Feb 27 Feb 06 Mar 100 100 150 150 200 200 250 250 7-day incidence rate (per 100K people) 183.9 LK Rhön-Grabfeld, Germany, last 5 weeks, last data point from 2023-03-06 30 Jan 06 Feb 13 Feb 20 Feb 27 Feb 06 Mar 0 20 40 60 daily change normalised per 100K 30 Jan 06 Feb 13 Feb 20 Feb 27 Feb 06 Mar 0 2 4 daily change normalised per 100K 30 Jan 06 Feb 13 Feb 20 Feb 27 Feb 06 Mar 0.8 0.8 1.0 1.0 1.2 1.2 1.4 1.4 R & growth factor (based on cases) Germany-LK Rhön-Grabfeld cases daily growth factor Germany-LK Rhön-Grabfeld cases daily growth factor (rolling mean) Germany-LK Rhön-Grabfeld estimated R (using cases) 30 Jan 06 Feb 13 Feb 20 Feb 27 Feb 06 Mar 1 1 2 2 3 3 4 4 5 5 R & growth factor (based on deaths) Germany-LK Rhön-Grabfeld deaths daily growth factor Germany-LK Rhön-Grabfeld deaths daily growth factor (rolling mean) Germany-LK Rhön-Grabfeld estimated R (using deaths) 30 Jan 06 Feb 13 Feb 20 Feb 27 Feb 06 Mar 0 1000 2000 3000 cases doubling time [days] Germany-LK Rhön-Grabfeld doubling time cases (rolling mean) Germany-LK Rhön-Grabfeld doubling time deaths (rolling mean) 0.00 15.88 31.75 47.63 daily change Germany-LK Rhön-Grabfeld new cases (rolling 7d mean) Germany-LK Rhön-Grabfeld new cases 0.000 1.588 3.175 daily change Germany-LK Rhön-Grabfeld new deaths (rolling 7d mean) Germany-LK Rhön-Grabfeld new deaths 0.0 92.2 184.5 276.7 deaths doubling time [days]
In [4]:
overview(country="Germany", subregion="LK Rhön-Grabfeld");
2023-03-07T11:22:33.611418 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 7-day incidence rate (per 100K people) 183.9 LK Rhön-Grabfeld, 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 5 10 15 daily change normalised per 100K May 20 Sep 20 Jan 21 May 21 Sep 21 Jan 22 May 22 Sep 22 Jan 23 0.8 0.8 1.0 1.0 1.2 1.2 1.4 1.4 R & growth factor (based on cases) Germany-LK Rhön-Grabfeld cases daily growth factor Germany-LK Rhön-Grabfeld cases daily growth factor (rolling mean) Germany-LK Rhön-Grabfeld estimated R (using cases) May 20 Sep 20 Jan 21 May 21 Sep 21 Jan 22 May 22 Sep 22 Jan 23 1 1 2 2 3 3 4 4 5 5 R & growth factor (based on deaths) Germany-LK Rhön-Grabfeld deaths daily growth factor Germany-LK Rhön-Grabfeld deaths daily growth factor (rolling mean) Germany-LK Rhön-Grabfeld estimated R (using deaths) May 20 Sep 20 Jan 21 May 21 Sep 21 Jan 22 May 22 Sep 22 Jan 23 0 2000 4000 cases doubling time [days] Germany-LK Rhön-Grabfeld doubling time cases (rolling mean) Germany-LK Rhön-Grabfeld doubling time deaths (rolling mean) 0.0 158.8 317.5 476.3 daily change Germany-LK Rhön-Grabfeld new cases (rolling 7d mean) Germany-LK Rhön-Grabfeld new cases 0.00 3.97 7.94 11.91 daily change Germany-LK Rhön-Grabfeld new deaths (rolling 7d mean) Germany-LK Rhön-Grabfeld new deaths 0.0 62.5 125.1 deaths doubling time [days]
In [5]:
compare_plot(country="Germany", subregion="LK Rhön-Grabfeld", dates="2020-03-15:");
2023-03-07T11:41:14.721109 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 Rhön-Grabfeld LK Rhön-Grabfeld 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 Rhön-Grabfeld Bayern Berlin Bremen Hamburg Hessen Nordrhein-Westfalen Sachsen-Anhalt
In [6]:
# load the data
cases, deaths = germany_get_region(landkreis="LK Rhön-Grabfeld")

# get population of the region for future normalisation:
inhabitants = population(country="Germany", subregion="LK Rhön-Grabfeld")
print(f'Population of country="Germany", subregion="LK Rhön-Grabfeld": {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 Rhön-Grabfeld": 79376 people
Out[6]:
total cases daily new cases total deaths daily new deaths
date
2023-03-06 44086 25 185 0
2023-03-03 44061 13 185 0
2023-03-02 44048 19 185 0
2023-03-01 44029 49 185 0
2023-02-28 43980 40 185 0
2023-02-27 43940 41 185 1
2023-02-24 43899 34 184 0
2023-02-23 43865 47 184 0
2023-02-22 43818 28 184 0
2023-02-21 43790 9 184 1
2023-02-20 43781 61 183 4
2023-02-17 43720 23 179 0
2023-02-16 43697 15 179 0
2023-02-15 43682 19 179 0
2023-02-14 43663 22 179 0
2023-02-13 43641 21 179 0
2023-02-10 43620 28 179 0
2023-02-09 43592 6 179 0
2023-02-08 43586 29 179 0
2023-02-07 43557 22 179 0
2023-02-06 43535 37 179 0
2023-02-03 43498 16 179 0
2023-02-02 43482 13 179 0
2023-02-01 43469 20 179 0
2023-01-31 43449 19 179 0
2023-01-30 43430 15 179 1
2023-01-27 43415 36 178 0
2023-01-26 43379 5 178 0
2023-01-25 43374 19 178 0
2023-01-24 43355 10 178 0
2023-01-23 43345 16 178 0
2023-01-20 43329 13 178 1
2023-01-19 43316 6 177 1
2023-01-18 43310 12 176 0
2023-01-17 43298 9 176 0
2023-01-16 43289 14 176 0
2023-01-13 43275 19 176 0
2023-01-12 43256 3 176 0
2023-01-11 43253 24 176 0
2023-01-10 43229 15 176 0
2023-01-09 43214 7 176 0
2023-01-06 43207 43 176 0
2023-01-05 43164 24 176 0
2023-01-04 43140 29 176 0
2023-01-03 43111 18 176 0
2023-01-02 43093 36 176 0
2022-12-30 43057 12 176 0
2022-12-29 43045 29 176 0
2022-12-28 43016 18 176 0
2022-12-27 42998 18 176 0
2022-12-23 42980 8 176 0
2022-12-22 42972 27 176 0
2022-12-21 42945 14 176 0
2022-12-20 42931 18 176 1
2022-12-19 42913 19 175 0
2022-12-16 42894 15 175 0
2022-12-15 42879 11 175 0
2022-12-14 42868 21 175 0
2022-12-13 42847 10 175 0
2022-12-12 42837 20 175 0
2022-12-09 42817 13 175 0
2022-12-08 42804 11 175 0
2022-12-07 42793 11 175 0
2022-12-06 42782 19 175 0
2022-12-05 42763 22 175 1
2022-12-02 42741 17 174 0
2022-12-01 42724 25 174 0
2022-11-30 42699 18 174 0
2022-11-29 42681 17 174 0
2022-11-28 42664 12 174 0
2022-11-25 42652 11 174 0
2022-11-24 42641 14 174 0
2022-11-23 42627 24 174 0
2022-11-22 42603 19 174 0
2022-11-21 42584 15 174 0
2022-11-18 42569 18 174 0
2022-11-17 42551 14 174 0
2022-11-16 42537 19 174 0
2022-11-15 42518 23 174 0
2022-11-14 42495 35 174 0
2022-11-11 42460 50 174 0
2022-11-10 42410 11 174 0
2022-11-09 42399 23 174 0
2022-11-08 42376 57 174 0
2022-11-07 42319 42 174 0
2022-11-04 42277 51 174 0
2022-11-03 42226 26 174 0
2022-11-02 42200 76 174 0
2022-10-31 42124 67 174 0
2022-10-28 42057 70 174 0
2022-10-27 41987 76 174 1
2022-10-26 41911 97 173 0
2022-10-25 41814 162 173 0
2022-10-24 41652 94 173 0
2022-10-21 41558 126 173 1
2022-10-20 41432 84 172 0
2022-10-19 41348 171 172 0
2022-10-18 41177 201 172 0
2022-10-17 40976 243 172 0
2022-10-14 40733 164 172 0
2022-10-13 40569 126 172 0
2022-10-12 40443 238 172 0
2022-10-11 40205 246 172 0
2022-10-10 39959 279 172 0
2022-10-07 39680 261 172 0
2022-10-06 39419 183 172 0
2022-10-05 39236 133 172 1
2022-10-04 39103 289 171 0
2022-09-30 38814 125 171 0
2022-09-29 38689 114 171 1
2022-09-28 38575 121 170 1
2022-09-27 38454 113 169 1
2022-09-26 38341 81 168 0
2022-09-23 38260 47 168 0
2022-09-22 38213 38 168 0
2022-09-21 38175 47 168 0
2022-09-20 38128 64 168 0
2022-09-19 38064 75 168 0
2022-09-16 37989 43 168 0
2022-09-15 37946 60 168 0
2022-09-14 37886 27 168 0
2022-09-13 37859 38 168 0
2022-09-12 37821 53 168 1
2022-09-09 37768 23 167 0
2022-09-08 37745 16 167 0
2022-09-07 37729 47 167 0
2022-09-06 37682 51 167 0
2022-09-05 37631 43 167 0
2022-09-02 37588 33 167 0
2022-09-01 37555 17 167 0
2022-08-31 37538 34 167 0
2022-08-30 37504 43 167 0
2022-08-29 37461 49 167 0
2022-08-26 37412 30 167 0
2022-08-25 37382 40 167 0
2022-08-24 37342 43 167 0
2022-08-23 37299 32 167 0
2022-08-22 37267 56 167 0
2022-08-19 37211 32 167 0
2022-08-18 37179 52 167 0
2022-08-17 37127 31 167 0
2022-08-16 37096 102 167 0
2022-08-12 36994 39 167 0
2022-08-11 36955 53 167 0
2022-08-10 36902 74 167 0
2022-08-09 36828 67 167 0
2022-08-08 36761 76 167 0
2022-08-05 36685 69 167 0
2022-08-04 36616 31 167 0
2022-08-03 36585 126 167 0
2022-08-02 36459 88 167 0
2022-08-01 36371 115 167 2
2022-07-29 36256 124 165 1
2022-07-28 36132 104 164 0
2022-07-27 36028 146 164 0
2022-07-26 35882 177 164 0
2022-07-25 35705 186 164 1
2022-07-22 35519 147 163 0
2022-07-21 35372 99 163 0
2022-07-20 35273 241 163 0
2022-07-19 35032 158 163 0
2022-07-18 34874 198 163 0
2022-07-15 34676 127 163 1
2022-07-14 34549 137 162 0
2022-07-13 34412 159 162 1
2022-07-12 34253 140 161 0
2022-07-11 34113 168 161 0
2022-07-08 33945 128 161 0
2022-07-07 33817 136 161 0
2022-07-06 33681 122 161 0
2022-07-05 33559 125 161 0
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2022-07-01 33264 51 161 0
2022-06-30 33213 192 161 0
2022-06-29 33021 104 161 0
2022-06-28 32917 71 161 0
2022-06-27 32846 121 161 0
2022-06-24 32725 40 161 0
2022-06-23 32685 159 161 0
2022-06-22 32526 121 161 0
2022-06-21 32405 78 161 0
2022-06-20 32327 87 161 0
2022-06-17 32240 90 161 0
2022-06-15 32150 74 161 0
2022-06-14 32076 73 161 0
2022-06-13 32003 84 161 1
2022-06-10 31919 72 160 0
2022-06-09 31847 92 160 0
2022-06-08 31755 59 160 0
2022-06-07 31696 123 160 0
2022-06-03 31573 35 160 0
2022-06-02 31538 41 160 0
2022-06-01 31497 47 160 1
2022-05-31 31450 70 159 0
2022-05-30 31380 77 159 0
2022-05-27 31303 69 159 0
2022-05-25 31234 52 159 0
2022-05-24 31182 58 159 1
2022-05-23 31124 67 158 0
2022-05-20 31057 55 158 0
2022-05-19 31002 76 158 0
2022-05-18 30926 66 158 0
2022-05-17 30860 88 158 0
2022-05-16 30772 96 158 0
2022-05-13 30676 38 158 0
2022-05-12 30638 48 158 0
2022-05-11 30590 153 158 0
2022-05-10 30437 90 158 0
2022-05-09 30347 205 158 0
2022-05-06 30142 12 158 0
2022-05-05 30130 79 158 0
2022-05-04 30051 125 158 0
2022-05-03 29926 123 158 0
2022-05-02 29803 150 158 0
2022-04-29 29653 84 158 0
2022-04-28 29569 91 158 1
2022-04-27 29478 221 157 1
2022-04-26 29257 195 156 0
2022-04-25 29062 86 156 2
2022-04-23 28976 109 154 0
2022-04-22 28867 38 154 0
2022-04-21 28829 301 154 0
2022-04-20 28528 174 154 1
2022-04-19 28354 132 153 0
2022-04-18 28222 135 153 0
2022-04-15 28087 125 153 0
2022-04-14 27962 178 153 1
2022-04-13 27784 190 152 0
2022-04-12 27594 221 152 0
2022-04-11 27373 81 152 0
2022-04-09 27292 154 152 1
2022-04-08 27138 218 151 0
2022-04-07 26920 213 151 0
2022-04-06 26707 269 151 0
2022-04-05 26438 281 151 0
2022-04-04 26157 266 151 0
2022-04-02 25891 231 151 1
2022-04-01 25660 263 150 0
2022-03-31 25397 365 150 0
2022-03-30 25032 357 150 2
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2022-03-28 24377 251 148 1
2022-03-26 24126 274 147 1
2022-03-25 23852 268 146 0
2022-03-24 23584 296 146 3
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2022-03-22 22931 467 142 2
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2022-01-04 7926 131 126 0
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2022-01-02 7763 9 126 0
2021-12-31 7754 37 126 0
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2021-12-29 7683 59 126 1
2021-12-28 7624 77 125 0
2021-12-27 7547 13 125 0
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2021-06-10 3531 1 89 0
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2021-06-03 3524 4 89 0
2021-06-02 3520 4 89 0
2021-06-01 3516 7 89 0
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2021-05-28 3507 3 89 1
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2021-05-05 3299 16 88 1
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2021-05-03 3242 1 87 0
2021-05-01 3241 6 87 0
2021-04-30 3235 16 87 0
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2021-04-27 3169 36 87 1
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2021-04-22 3095 22 86 0
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2021-04-19 3000 6 85 1
2021-04-17 2994 1 84 0
2021-04-16 2993 32 84 1
2021-04-15 2961 24 83 0
2021-04-14 2937 54 83 2
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2021-04-12 2826 6 81 0
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2021-04-09 2805 49 80 0
2021-04-08 2756 32 80 0
2021-04-07 2724 43 80 0
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2021-04-05 2640 5 80 2
2021-04-03 2635 3 78 0
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2021-04-01 2594 38 77 1
2021-03-31 2556 26 76 2
2021-03-30 2530 51 74 0
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2021-03-24 2412 31 73 1
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2021-03-22 2338 4 72 0
2021-03-21 2334 2 72 0
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2021-03-18 2297 13 70 0
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2021-02-27 2133 1 67 0
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2021-02-17 2078 4 67 0
2021-02-16 2074 14 67 0
2021-02-15 2060 2 67 0
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2021-02-11 2045 12 67 1
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2021-02-08 2013 7 66 1
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2021-02-04 1983 1 64 0
2021-02-03 1982 5 64 0
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2021-01-31 1943 1 63 0
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2021-01-25 1883 17 62 1
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2021-01-22 1863 2 61 0
2021-01-21 1861 31 61 0
2021-01-20 1830 10 61 0
2021-01-19 1820 25 61 1
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2021-01-16 1766 3 60 0
2021-01-15 1763 15 60 0
2021-01-14 1748 10 60 0
2021-01-13 1738 45 60 4
2021-01-12 1693 26 56 1
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2021-01-05 1598 47 54 1
2021-01-04 1551 11 53 1
2021-01-03 1540 14 52 0
2021-01-02 1526 11 52 1
2020-12-31 1515 37 51 3
2020-12-30 1478 19 48 0
2020-12-29 1459 69 48 13
2020-12-28 1390 28 35 0
2020-12-27 1362 4 35 0
2020-12-26 1358 14 35 0
2020-12-24 1344 16 35 1
2020-12-23 1328 36 34 2
2020-12-22 1292 68 32 7
2020-12-21 1224 9 25 2
2020-12-20 1215 2 23 0
2020-12-19 1213 14 23 0
2020-12-18 1199 18 23 1
2020-12-17 1181 25 22 0
2020-12-16 1156 18 22 0
2020-12-15 1138 25 22 0
2020-12-14 1113 5 22 1
2020-12-13 1108 1 21 0
2020-12-12 1107 9 21 0
2020-12-11 1098 17 21 0
2020-12-10 1081 15 21 1
2020-12-09 1066 27 20 0
2020-12-08 1039 41 20 1
2020-12-07 998 15 19 1
2020-12-06 983 2 18 0
2020-12-05 981 7 18 0
2020-12-04 974 30 18 0
2020-12-03 944 17 18 0
2020-12-02 927 23 18 0
2020-12-01 904 19 18 0
2020-11-29 885 5 18 0
2020-11-28 880 8 18 0
2020-11-27 872 14 18 0
2020-11-26 858 29 18 1
2020-11-25 829 24 17 0
2020-11-24 805 52 17 0
2020-11-23 753 26 17 2
2020-11-22 727 3 15 0
2020-11-20 724 40 15 0
2020-11-19 684 17 15 1
2020-11-18 667 24 14 0
2020-11-17 643 12 14 0
2020-11-16 631 8 14 1
2020-11-15 623 4 13 0
2020-11-13 619 33 13 0
2020-11-12 586 15 13 0
2020-11-11 571 16 13 0
2020-11-10 555 14 13 0
2020-11-09 541 24 13 0
2020-11-06 517 22 13 0
2020-11-05 495 12 13 0
2020-11-04 483 22 13 1
2020-11-03 461 15 12 0
2020-11-02 446 9 12 1
2020-10-31 437 13 11 0
2020-10-30 424 8 11 0
2020-10-29 416 29 11 0
2020-10-28 387 2 11 1
2020-10-27 385 9 10 0
2020-10-26 376 7 10 0
2020-10-23 369 17 10 0
2020-10-22 352 11 10 0
2020-10-21 341 8 10 0
2020-10-20 333 5 10 0
2020-10-19 328 4 10 0
2020-10-16 324 4 10 0
2020-10-14 320 2 10 0
2020-10-13 318 1 10 0
2020-10-12 317 2 10 0
2020-10-09 315 2 10 0
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2020-10-06 305 1 10 0
2020-10-05 304 1 10 0
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2020-09-30 298 15 10 2
2020-09-29 283 7 8 0
2020-09-28 276 2 8 0
2020-09-26 274 4 8 0
2020-09-25 270 10 8 0
2020-09-24 260 3 8 0
2020-09-23 257 6 8 0
2020-09-22 251 8 8 0
2020-09-19 243 16 8 0
2020-09-18 227 4 8 0
2020-09-16 223 2 8 0
2020-09-15 221 1 8 0
2020-09-14 220 1 8 0
2020-09-09 219 1 8 0
2020-09-08 218 2 8 0
2020-09-04 216 1 8 0
2020-09-03 215 1 8 0
2020-09-02 214 1 8 0
2020-08-31 213 1 8 0
2020-08-24 212 3 8 0
2020-08-13 209 4 8 0
2020-08-12 205 1 8 0
2020-08-10 204 1 8 0
2020-08-05 203 1 8 0
2020-08-04 202 1 8 0
2020-08-03 201 2 8 0
2020-07-10 199 1 8 0
2020-07-07 198 1 8 0
2020-07-06 197 1 8 0
2020-06-29 196 1 8 0
2020-06-11 195 1 8 0
2020-06-04 194 1 8 0
2020-05-30 193 1 8 0
2020-05-26 192 2 8 0
2020-05-23 190 1 8 0
2020-05-20 189 2 8 0
2020-05-19 187 1 8 0
2020-05-09 186 1 8 0
2020-05-07 185 1 8 0
2020-05-03 184 1 8 0
2020-05-02 183 1 8 0
2020-04-30 182 2 8 0
2020-04-28 180 6 8 0
2020-04-27 174 2 8 0
2020-04-26 172 1 8 0
2020-04-25 171 7 8 1
2020-04-24 164 5 7 0
2020-04-23 159 8 7 0
2020-04-22 151 5 7 0
2020-04-21 146 4 7 0
2020-04-20 142 4 7 2
2020-04-19 138 4 5 0
2020-04-18 134 2 5 0
2020-04-17 132 2 5 0
2020-04-16 130 1 5 0
2020-04-15 129 5 5 0
2020-04-14 124 5 5 0
2020-04-13 119 1 5 0
2020-04-12 118 6 5 0
2020-04-11 112 3 5 0
2020-04-10 109 7 5 0
2020-04-09 102 5 5 0
2020-04-08 97 15 5 2
2020-04-07 82 3 3 1
2020-04-06 79 2 2 0
2020-04-05 77 2 2 0
2020-04-04 75 9 2 1
2020-04-03 66 8 1 0
2020-04-02 58 7 1 0
2020-04-01 51 6 1 0
2020-03-31 45 5 1 0
2020-03-30 40 2 1 0
2020-03-29 38 2 1 1
2020-03-28 36 3 0 0
2020-03-27 33 3 0 0
2020-03-26 30 6 0 0
2020-03-25 24 3 0 0
2020-03-24 21 3 0 0
2020-03-23 18 4 0 0
2020-03-22 14 1 0 0
2020-03-21 13 3 0 0
2020-03-20 10 2 0 0
2020-03-19 8 5 0 0
2020-03-17 3 1 0 0
2020-03-16 2 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: 0:19:44.084322