Germany: LK Dithmarschen (Schleswig-Holstein)¶

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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 15:45:57 CEST
In [2]:
%config InlineBackend.figure_formats = ['svg']
from oscovida import *
In [3]:
overview(country="Germany", subregion="LK Dithmarschen", weeks=5);
2023-03-07T15:46:12.263025 image/svg+xml Matplotlib v3.7.1, https://matplotlib.org/ 30 Jan 06 Feb 13 Feb 20 Feb 27 Feb 06 Mar 40 40 60 60 80 80 7-day incidence rate (per 100K people) 57.5 LK Dithmarschen, 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 15 20 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 Dithmarschen new deaths (rolling 7d mean) Germany-LK Dithmarschen new deaths 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 Dithmarschen cases daily growth factor Germany-LK Dithmarschen cases daily growth factor (rolling mean) Germany-LK Dithmarschen 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 Dithmarschen deaths daily growth factor Germany-LK Dithmarschen deaths daily growth factor (rolling mean) Germany-LK Dithmarschen estimated R (using deaths) 30 Jan 06 Feb 13 Feb 20 Feb 27 Feb 06 Mar 0 2000 4000 6000 cases doubling time [days] Germany-LK Dithmarschen doubling time cases (rolling mean) 0.0 6.7 13.4 20.1 26.8 daily change Germany-LK Dithmarschen new cases (rolling 7d mean) Germany-LK Dithmarschen new cases 0.000 0.304 0.608 0.912
In [4]:
overview(country="Germany", subregion="LK Dithmarschen");
2023-03-07T15:46:30.778239 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) 57.5 LK Dithmarschen, 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 0 100 200 300 400 daily change normalised per 100K May 20 Sep 20 Jan 21 May 21 Sep 21 Jan 22 May 22 Sep 22 Jan 23 0 1 2 3 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 Dithmarschen cases daily growth factor Germany-LK Dithmarschen cases daily growth factor (rolling mean) Germany-LK Dithmarschen 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 Dithmarschen deaths daily growth factor Germany-LK Dithmarschen deaths daily growth factor (rolling mean) Germany-LK Dithmarschen 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 6000 8000 cases doubling time [days] Germany-LK Dithmarschen doubling time cases (rolling mean) Germany-LK Dithmarschen doubling time deaths (rolling mean) 0.0 134.0 267.9 401.9 535.9 daily change Germany-LK Dithmarschen new cases (rolling 7d mean) Germany-LK Dithmarschen new cases 0.000 1.340 2.679 4.019 daily change Germany-LK Dithmarschen new deaths (rolling 7d mean) Germany-LK Dithmarschen new deaths 0.0 21.8 43.6 65.5 87.3 deaths doubling time [days]
In [5]:
compare_plot(country="Germany", subregion="LK Dithmarschen", dates="2020-03-15:");
2023-03-07T15:49:03.219774 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 Dithmarschen LK Dithmarschen 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 Dithmarschen Bayern Berlin Bremen Hamburg Hessen Nordrhein-Westfalen Sachsen-Anhalt
In [6]:
# load the data
cases, deaths = germany_get_region(landkreis="LK Dithmarschen")

# get population of the region for future normalisation:
inhabitants = population(country="Germany", subregion="LK Dithmarschen")
print(f'Population of country="Germany", subregion="LK Dithmarschen": {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 Dithmarschen": 133969 people
Out[6]:
total cases daily new cases total deaths daily new deaths
date
2023-03-06 53969 14 126 0
2023-03-03 53955 4 126 0
2023-03-02 53951 5 126 0
2023-03-01 53946 26 126 0
2023-02-28 53920 28 126 0
2023-02-27 53892 29 126 0
2023-02-24 53863 25 126 0
2023-02-23 53838 13 126 0
2023-02-22 53825 12 126 0
2023-02-21 53813 27 126 0
2023-02-20 53786 18 126 0
2023-02-17 53768 6 126 0
2023-02-16 53762 13 126 0
2023-02-15 53749 13 126 0
2023-02-14 53736 19 126 0
2023-02-13 53717 16 126 0
2023-02-10 53701 10 126 0
2023-02-09 53691 6 126 0
2023-02-08 53685 15 126 0
2023-02-07 53670 18 126 0
2023-02-06 53652 19 126 0
2023-02-03 53633 15 126 0
2023-02-02 53618 16 126 0
2023-02-01 53602 10 126 0
2023-01-31 53592 22 126 0
2023-01-30 53570 10 126 0
2023-01-27 53560 5 126 0
2023-01-26 53555 4 126 0
2023-01-25 53551 14 126 0
2023-01-24 53537 14 126 0
2023-01-23 53523 9 126 0
2023-01-20 53514 9 126 0
2023-01-19 53505 7 126 0
2023-01-18 53498 12 126 0
2023-01-17 53486 20 126 0
2023-01-16 53466 32 126 0
2023-01-13 53434 17 126 0
2023-01-12 53417 12 126 1
2023-01-11 53405 17 125 0
2023-01-10 53388 34 125 0
2023-01-09 53354 28 125 0
2023-01-06 53326 29 125 0
2023-01-05 53297 26 125 0
2023-01-04 53271 44 125 1
2023-01-03 53227 56 124 0
2023-01-02 53171 42 124 0
2022-12-30 53129 45 124 0
2022-12-29 53084 48 124 0
2022-12-28 53036 86 124 0
2022-12-27 52950 114 124 0
2022-12-23 52836 82 124 0
2022-12-22 52754 85 124 0
2022-12-21 52669 101 124 0
2022-12-20 52568 113 124 0
2022-12-19 52455 110 124 0
2022-12-16 52345 68 124 0
2022-12-15 52277 82 124 1
2022-12-14 52195 102 123 1
2022-12-13 52093 95 122 0
2022-12-12 51998 128 122 1
2022-12-09 51870 67 121 0
2022-12-08 51803 59 121 0
2022-12-07 51744 63 121 1
2022-12-06 51681 68 120 0
2022-12-05 51613 90 120 0
2022-12-02 51523 56 120 0
2022-12-01 51467 50 120 0
2022-11-30 51417 50 120 0
2022-11-29 51367 77 120 0
2022-11-28 51290 46 120 0
2022-11-25 51244 24 120 0
2022-11-24 51220 37 120 0
2022-11-23 51183 43 120 0
2022-11-22 51140 49 120 0
2022-11-21 51091 38 120 0
2022-11-18 51053 40 120 0
2022-11-17 51013 35 120 0
2022-11-16 50978 50 120 0
2022-11-15 50928 103 120 0
2022-11-14 50825 100 120 0
2022-11-11 50725 61 120 0
2022-11-10 50664 71 120 0
2022-11-09 50593 76 120 0
2022-11-08 50517 102 120 0
2022-11-07 50415 89 120 1
2022-11-04 50326 60 119 0
2022-11-03 50266 105 119 0
2022-11-02 50161 131 119 0
2022-11-01 50030 160 119 0
2022-10-28 49870 85 119 0
2022-10-27 49785 102 119 0
2022-10-26 49683 104 119 0
2022-10-25 49579 173 119 0
2022-10-24 49406 168 119 0
2022-10-21 49238 102 119 0
2022-10-20 49136 73 119 0
2022-10-19 49063 107 119 0
2022-10-18 48956 163 119 0
2022-10-17 48793 198 119 0
2022-10-14 48595 111 119 0
2022-10-13 48484 125 119 1
2022-10-12 48359 158 118 0
2022-10-11 48201 206 118 0
2022-10-10 47995 231 118 0
2022-10-07 47764 136 118 0
2022-10-06 47628 219 118 0
2022-10-05 47409 206 118 1
2022-10-04 47203 244 117 1
2022-09-30 46959 127 116 0
2022-09-29 46832 100 116 0
2022-09-28 46732 105 116 0
2022-09-27 46627 137 116 3
2022-09-26 46490 125 113 1
2022-09-24 46365 1 112 0
2022-09-23 46364 51 112 0
2022-09-22 46313 70 112 0
2022-09-21 46243 63 112 0
2022-09-20 46180 89 112 0
2022-09-19 46091 69 112 0
2022-09-16 46022 50 112 0
2022-09-15 45972 55 112 0
2022-09-14 45917 55 112 0
2022-09-13 45862 103 112 0
2022-09-12 45759 83 112 0
2022-09-09 45676 42 112 0
2022-09-08 45634 63 112 0
2022-09-07 45571 52 112 0
2022-09-06 45519 89 112 0
2022-09-05 45430 53 112 0
2022-09-02 45377 37 112 0
2022-09-01 45340 62 112 0
2022-08-31 45278 60 112 0
2022-08-30 45218 96 112 0
2022-08-29 45122 78 112 0
2022-08-26 45044 60 112 0
2022-08-25 44984 62 112 0
2022-08-24 44922 66 112 0
2022-08-23 44856 105 112 0
2022-08-22 44751 99 112 0
2022-08-19 44652 95 112 0
2022-08-18 44557 115 112 0
2022-08-17 44442 89 112 0
2022-08-16 44353 197 112 0
2022-08-15 44156 134 112 0
2022-08-12 44022 91 112 0
2022-08-11 43931 128 112 0
2022-08-10 43803 129 112 0
2022-08-09 43674 170 112 0
2022-08-08 43504 126 112 1
2022-08-05 43378 88 111 0
2022-08-04 43290 111 111 0
2022-08-03 43179 108 111 0
2022-08-02 43071 166 111 0
2022-08-01 42905 134 111 0
2022-07-29 42771 99 111 0
2022-07-28 42672 102 111 0
2022-07-27 42570 147 111 0
2022-07-26 42423 181 111 0
2022-07-25 42242 180 111 0
2022-07-22 42062 93 111 0
2022-07-21 41969 112 111 0
2022-07-20 41857 134 111 0
2022-07-19 41723 215 111 0
2022-07-18 41508 186 111 0
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2022-07-13 41093 138 110 1
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2022-07-11 40748 174 109 2
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2022-07-01 39706 174 107 0
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2022-06-23 38335 209 107 0
2022-06-22 38126 239 107 0
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2022-06-20 37597 378 107 1
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2022-06-15 36819 252 106 0
2022-06-14 36567 269 106 0
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2022-06-09 35793 162 106 0
2022-06-08 35631 148 106 0
2022-06-07 35483 237 106 0
2022-06-03 35246 68 106 0
2022-06-02 35178 88 106 0
2022-06-01 35090 143 106 0
2022-05-31 34947 109 106 0
2022-05-30 34838 143 106 0
2022-05-27 34695 95 106 0
2022-05-25 34600 66 106 0
2022-05-24 34534 64 106 0
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2022-05-16 33922 225 105 0
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2022-05-11 33453 165 105 1
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2022-05-09 33080 100 103 0
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2022-05-06 32770 162 103 0
2022-05-05 32608 163 103 1
2022-05-04 32445 211 102 0
2022-05-03 32234 283 102 0
2022-05-02 31951 121 102 0
2022-05-01 31830 117 102 0
2022-04-30 31713 203 102 1
2022-04-29 31510 153 101 0
2022-04-28 31357 232 101 0
2022-04-27 31125 266 101 0
2022-04-26 30859 291 101 2
2022-04-25 30568 175 99 0
2022-04-24 30393 113 99 0
2022-04-23 30280 278 99 1
2022-04-22 30002 289 98 0
2022-04-21 29713 296 98 0
2022-04-20 29417 411 98 0
2022-04-19 29006 182 98 0
2022-04-18 28824 211 98 1
2022-04-17 28613 167 97 0
2022-04-16 28446 228 97 0
2022-04-15 28218 215 97 0
2022-04-14 28003 326 97 0
2022-04-13 27677 333 97 0
2022-04-12 27344 295 97 0
2022-04-11 27049 199 97 0
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2021-07-24 2000 2 53 0
2021-07-23 1998 2 53 0
2021-07-22 1996 3 53 0
2021-07-21 1993 3 53 0
2021-07-20 1990 5 53 0
2021-07-19 1985 1 53 0
2021-07-18 1984 1 53 0
2021-07-17 1983 3 53 0
2021-07-16 1980 1 53 0
2021-07-13 1979 1 53 0
2021-07-09 1978 1 53 0
2021-06-28 1977 1 53 0
2021-06-20 1976 1 53 0
2021-06-09 1975 2 53 0
2021-06-04 1973 1 53 0
2021-06-03 1972 1 53 0
2021-06-02 1971 8 53 1
2021-06-01 1963 1 52 0
2021-05-30 1962 2 52 0
2021-05-27 1960 1 52 0
2021-05-26 1959 9 52 0
2021-05-24 1950 3 52 0
2021-05-23 1947 3 52 1
2021-05-22 1944 1 51 0
2021-05-21 1943 1 51 0
2021-05-19 1942 2 51 0
2021-05-18 1940 3 51 0
2021-05-17 1937 1 51 0
2021-05-16 1936 3 51 0
2021-05-15 1933 6 51 0
2021-05-14 1927 7 51 3
2021-05-13 1920 3 48 1
2021-05-12 1917 4 47 0
2021-05-11 1913 4 47 0
2021-05-10 1909 4 47 0
2021-05-09 1905 2 47 0
2021-05-08 1903 8 47 0
2021-05-07 1895 3 47 0
2021-05-06 1892 11 47 0
2021-05-05 1881 13 47 0
2021-05-04 1868 13 47 1
2021-05-03 1855 5 46 0
2021-05-02 1850 4 46 0
2021-05-01 1846 9 46 1
2021-04-30 1837 8 45 0
2021-04-29 1829 7 45 0
2021-04-28 1822 6 45 0
2021-04-27 1816 14 45 1
2021-04-26 1802 6 44 1
2021-04-25 1796 8 43 0
2021-04-24 1788 18 43 0
2021-04-23 1770 18 43 0
2021-04-22 1752 13 43 0
2021-04-21 1739 24 43 0
2021-04-20 1715 18 43 0
2021-04-19 1697 5 43 0
2021-04-18 1692 6 43 0
2021-04-17 1686 11 43 0
2021-04-16 1675 14 43 0
2021-04-15 1661 13 43 0
2021-04-14 1648 9 43 1
2021-04-13 1639 24 42 0
2021-04-12 1615 4 42 0
2021-04-11 1611 16 42 0
2021-04-10 1595 17 42 0
2021-04-09 1578 17 42 0
2021-04-08 1561 3 42 0
2021-04-07 1558 6 42 0
2021-04-06 1552 7 42 0
2021-04-05 1545 4 42 0
2021-04-04 1541 4 42 0
2021-04-03 1537 13 42 0
2021-04-02 1524 6 42 0
2021-04-01 1518 3 42 0
2021-03-31 1515 7 42 0
2021-03-30 1508 11 42 0
2021-03-29 1497 5 42 0
2021-03-28 1492 3 42 0
2021-03-27 1489 10 42 0
2021-03-26 1479 12 42 0
2021-03-25 1467 2 42 0
2021-03-24 1465 6 42 0
2021-03-23 1459 11 42 0
2021-03-22 1448 10 42 0
2021-03-21 1438 5 42 0
2021-03-20 1433 20 42 0
2021-03-19 1413 5 42 0
2021-03-18 1408 13 42 0
2021-03-17 1395 12 42 0
2021-03-16 1383 8 42 0
2021-03-15 1375 6 42 0
2021-03-14 1369 1 42 0
2021-03-13 1368 10 42 0
2021-03-12 1358 7 42 0
2021-03-11 1351 4 42 0
2021-03-10 1347 1 42 0
2021-03-09 1346 3 42 1
2021-03-07 1343 1 41 0
2021-03-06 1342 1 41 0
2021-03-05 1341 5 41 0
2021-03-04 1336 6 41 0
2021-03-03 1330 7 41 0
2021-03-02 1323 5 41 1
2021-03-01 1318 2 40 0
2021-02-28 1316 2 40 0
2021-02-27 1314 2 40 0
2021-02-25 1312 1 40 0
2021-02-24 1311 3 40 0
2021-02-23 1308 4 40 0
2021-02-21 1304 1 40 0
2021-02-19 1303 1 40 0
2021-02-18 1302 6 40 0
2021-02-17 1296 3 40 0
2021-02-16 1293 6 40 0
2021-02-15 1287 1 40 0
2021-02-13 1286 2 40 0
2021-02-12 1284 3 40 0
2021-02-11 1281 8 40 0
2021-02-10 1273 4 40 0
2021-02-09 1269 4 40 0
2021-02-08 1265 1 40 0
2021-02-07 1264 2 40 0
2021-02-06 1262 2 40 0
2021-02-05 1260 3 40 0
2021-02-04 1257 3 40 0
2021-02-03 1254 6 40 0
2021-02-02 1248 4 40 0
2021-01-31 1244 2 40 0
2021-01-30 1242 5 40 0
2021-01-29 1237 5 40 0
2021-01-28 1232 6 40 0
2021-01-27 1226 2 40 0
2021-01-26 1224 13 40 0
2021-01-25 1211 2 40 0
2021-01-24 1209 4 40 0
2021-01-23 1205 23 40 0
2021-01-22 1182 11 40 0
2021-01-21 1171 19 40 2
2021-01-20 1152 12 38 0
2021-01-19 1140 11 38 0
2021-01-18 1129 3 38 0
2021-01-17 1126 5 38 1
2021-01-16 1121 7 37 0
2021-01-15 1114 7 37 0
2021-01-14 1107 17 37 1
2021-01-13 1090 13 36 0
2021-01-12 1077 8 36 0
2021-01-11 1069 26 36 0
2021-01-10 1043 5 36 0
2021-01-09 1038 10 36 0
2021-01-08 1028 10 36 0
2021-01-07 1018 4 36 0
2021-01-06 1014 14 36 2
2021-01-05 1000 14 34 0
2021-01-04 986 2 34 0
2021-01-03 984 9 34 0
2021-01-02 975 7 34 0
2021-01-01 968 9 34 1
2020-12-31 959 12 33 0
2020-12-30 947 22 33 1
2020-12-29 925 6 32 0
2020-12-28 919 8 32 1
2020-12-27 911 10 31 2
2020-12-26 901 4 29 1
2020-12-25 897 6 28 0
2020-12-24 891 7 28 0
2020-12-23 884 14 28 1
2020-12-22 870 13 27 0
2020-12-21 857 4 27 0
2020-12-20 853 8 27 0
2020-12-19 845 4 27 0
2020-12-18 841 28 27 5
2020-12-17 813 18 22 1
2020-12-16 795 10 21 1
2020-12-15 785 12 20 0
2020-12-14 773 3 20 0
2020-12-13 770 3 20 0
2020-12-12 767 17 20 0
2020-12-11 750 16 20 0
2020-12-10 734 24 20 0
2020-12-09 710 11 20 2
2020-12-08 699 12 18 1
2020-12-07 687 15 17 0
2020-12-06 672 16 17 1
2020-12-05 656 6 16 0
2020-12-04 650 8 16 0
2020-12-03 642 15 16 0
2020-12-02 627 9 16 0
2020-12-01 618 7 16 0
2020-11-30 611 3 16 0
2020-11-29 608 3 16 0
2020-11-28 605 3 16 0
2020-11-27 602 10 16 0
2020-11-26 592 6 16 0
2020-11-25 586 16 16 1
2020-11-24 570 4 15 0
2020-11-23 566 3 15 0
2020-11-22 563 7 15 0
2020-11-21 556 4 15 0
2020-11-20 552 6 15 0
2020-11-19 546 12 15 0
2020-11-18 534 11 15 0
2020-11-17 523 10 15 0
2020-11-16 513 5 15 0
2020-11-15 508 2 15 0
2020-11-14 506 9 15 0
2020-11-13 497 9 15 0
2020-11-12 488 7 15 0
2020-11-11 481 15 15 0
2020-11-10 466 1 15 0
2020-11-09 465 8 15 0
2020-11-08 457 1 15 0
2020-11-07 456 6 15 0
2020-11-06 450 11 15 0
2020-11-05 439 16 15 1
2020-11-04 423 6 14 1
2020-11-03 417 4 13 0
2020-11-02 413 6 13 1
2020-11-01 407 2 12 0
2020-10-31 405 9 12 0
2020-10-30 396 8 12 0
2020-10-29 388 18 12 1
2020-10-28 370 5 11 0
2020-10-27 365 13 11 1
2020-10-26 352 2 10 0
2020-10-25 350 3 10 0
2020-10-24 347 7 10 0
2020-10-23 340 14 10 0
2020-10-22 326 12 10 0
2020-10-21 314 7 10 0
2020-10-20 307 14 10 2
2020-10-19 293 13 8 0
2020-10-16 280 5 8 1
2020-10-15 275 13 7 1
2020-10-14 262 7 6 0
2020-10-13 255 2 6 0
2020-10-12 253 1 6 0
2020-10-11 252 2 6 0
2020-10-10 250 1 6 0
2020-10-09 249 2 6 0
2020-10-08 247 3 6 0
2020-10-07 244 6 6 0
2020-10-06 238 13 6 0
2020-10-04 225 10 6 0
2020-10-01 215 1 6 0
2020-09-30 214 2 6 0
2020-09-29 212 1 6 0
2020-09-27 211 2 6 0
2020-09-26 209 2 6 0
2020-09-25 207 4 6 0
2020-09-24 203 13 6 0
2020-09-23 190 6 6 0
2020-09-21 184 1 6 0
2020-09-20 183 6 6 0
2020-09-17 177 2 6 0
2020-09-15 175 5 6 0
2020-09-12 170 1 6 0
2020-09-09 169 11 6 0
2020-09-07 158 2 6 0
2020-09-03 156 3 6 0
2020-08-30 153 1 6 0
2020-08-26 152 1 6 0
2020-08-25 151 1 6 0
2020-08-23 150 2 6 0
2020-08-18 148 1 6 0
2020-08-15 147 5 6 0
2020-08-14 142 2 6 0
2020-08-12 140 1 6 0
2020-08-11 139 10 6 0
2020-08-10 129 1 6 0
2020-08-05 128 1 6 0
2020-08-04 127 1 6 0
2020-08-03 126 2 6 0
2020-08-01 124 3 6 0
2020-07-31 121 2 6 0
2020-07-30 119 2 6 0
2020-07-29 117 7 6 0
2020-07-28 110 12 6 0
2020-07-27 98 8 6 0
2020-07-26 90 1 6 0
2020-07-25 89 5 6 0
2020-07-24 84 2 6 1
2020-07-22 82 3 5 0
2020-07-21 79 1 5 0
2020-07-08 78 1 5 0
2020-07-03 77 1 5 0
2020-07-01 76 1 5 0
2020-06-30 75 1 5 0
2020-06-29 74 1 5 0
2020-06-24 73 1 5 0
2020-06-20 72 1 5 0
2020-06-18 71 6 5 0
2020-06-16 65 1 5 0
2020-06-12 64 1 5 1
2020-06-10 63 1 4 0
2020-06-07 62 1 4 0
2020-06-05 61 1 4 0
2020-05-05 60 4 4 0
2020-05-04 56 1 4 0
2020-04-28 55 1 4 1
2020-04-14 54 1 3 0
2020-04-12 53 1 3 0
2020-04-11 52 1 3 0
2020-04-09 51 2 3 1
2020-04-08 49 6 2 0
2020-04-07 43 2 2 0
2020-04-05 41 1 2 0
2020-04-04 40 2 2 0
2020-04-03 38 4 2 0
2020-04-02 34 4 2 0
2020-04-01 30 2 2 1
2020-03-31 28 1 1 0
2020-03-30 27 3 1 0
2020-03-27 24 3 1 0
2020-03-26 21 2 1 0
2020-03-25 19 2 1 0
2020-03-24 17 1 1 1
2020-03-23 16 1 0 0
2020-03-20 15 3 0 0
2020-03-19 12 1 0 0
2020-03-18 11 5 0 0
2020-03-15 6 5 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: 0:03:16.550328