Germany: LK Erzgebirgskreis (Sachsen)¶

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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 15:36:34 CEST
In [2]:
%config InlineBackend.figure_formats = ['svg']
from oscovida import *
In [3]:
overview(country="Germany", subregion="LK Erzgebirgskreis", weeks=5);
2023-03-07T15:36:49.412885 image/svg+xml Matplotlib v3.7.1, https://matplotlib.org/ 30 Jan 06 Feb 13 Feb 20 Feb 27 Feb 06 Mar 35 35 40 40 45 45 50 50 7-day incidence rate (per 100K people) 43.8 LK Erzgebirgskreis, 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 0.0 0.1 0.2 0.3 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 R & growth factor (based on cases) Germany-LK Erzgebirgskreis cases daily growth factor Germany-LK Erzgebirgskreis cases daily growth factor (rolling mean) Germany-LK Erzgebirgskreis estimated R (using cases) 30 Jan 06 Feb 13 Feb 20 Feb 27 Feb 06 Mar 0.0 0.0 0.5 0.5 1.0 1.0 R & growth factor (based on deaths) Germany-LK Erzgebirgskreis deaths daily growth factor Germany-LK Erzgebirgskreis deaths daily growth factor (rolling mean) Germany-LK Erzgebirgskreis 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 Erzgebirgskreis doubling time cases (rolling mean) 0.00 16.43 32.87 daily change Germany-LK Erzgebirgskreis new cases (rolling 7d mean) Germany-LK Erzgebirgskreis new cases 0.000 0.329 0.657 0.986 daily change Germany-LK Erzgebirgskreis new deaths (rolling 7d mean) Germany-LK Erzgebirgskreis new deaths 0.000 0.211 0.422 0.633 0.844
In [4]:
overview(country="Germany", subregion="LK Erzgebirgskreis");
2023-03-07T15:37:04.831816 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) 43.8 LK Erzgebirgskreis, 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 0.0 2.5 5.0 7.5 10.0 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 R & growth factor (based on cases) Germany-LK Erzgebirgskreis cases daily growth factor Germany-LK Erzgebirgskreis cases daily growth factor (rolling mean) Germany-LK Erzgebirgskreis estimated R (using cases) May 20 Sep 20 Jan 21 May 21 Sep 21 Jan 22 May 22 Sep 22 Jan 23 0.0 0.0 0.5 0.5 1.0 1.0 R & growth factor (based on deaths) Germany-LK Erzgebirgskreis deaths daily growth factor Germany-LK Erzgebirgskreis deaths daily growth factor (rolling mean) Germany-LK Erzgebirgskreis estimated R (using deaths) May 20 Sep 20 Jan 21 May 21 Sep 21 Jan 22 May 22 Sep 22 Jan 23 0 20000 40000 cases doubling time [days] Germany-LK Erzgebirgskreis doubling time cases (rolling mean) Germany-LK Erzgebirgskreis doubling time deaths (rolling mean) 0 657 1315 1972 daily change Germany-LK Erzgebirgskreis new cases (rolling 7d mean) Germany-LK Erzgebirgskreis new cases 0.00 8.22 16.43 24.65 32.87 daily change Germany-LK Erzgebirgskreis new deaths (rolling 7d mean) Germany-LK Erzgebirgskreis new deaths 0 841 1682 deaths doubling time [days]
In [5]:
compare_plot(country="Germany", subregion="LK Erzgebirgskreis", dates="2020-03-15:");
2023-03-07T15:39:35.206415 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 Erzgebirgskreis LK Erzgebirgskreis 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 Erzgebirgskreis Bayern Berlin Bremen Hamburg Hessen Nordrhein-Westfalen Sachsen-Anhalt
In [6]:
# load the data
cases, deaths = germany_get_region(landkreis="LK Erzgebirgskreis")

# get population of the region for future normalisation:
inhabitants = population(country="Germany", subregion="LK Erzgebirgskreis")
print(f'Population of country="Germany", subregion="LK Erzgebirgskreis": {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 Erzgebirgskreis": 328695 people
Out[6]:
total cases daily new cases total deaths daily new deaths
date
2023-03-06 161765 26 1830 0
2023-03-03 161739 38 1830 0
2023-03-02 161701 17 1830 0
2023-03-01 161684 16 1830 0
2023-02-28 161668 47 1830 0
2023-02-27 161621 35 1830 0
2023-02-24 161586 22 1830 0
2023-02-23 161564 28 1830 0
2023-02-22 161536 24 1830 0
2023-02-21 161512 35 1830 0
2023-02-20 161477 49 1830 0
2023-02-17 161428 29 1830 0
2023-02-16 161399 13 1830 0
2023-02-15 161386 27 1830 0
2023-02-14 161359 34 1830 0
2023-02-13 161325 28 1830 0
2023-02-10 161297 9 1830 0
2023-02-09 161288 23 1830 0
2023-02-08 161265 15 1830 0
2023-02-07 161250 35 1830 0
2023-02-06 161215 29 1830 1
2023-02-03 161186 7 1829 0
2023-02-02 161179 31 1829 0
2023-02-01 161148 8 1829 0
2023-01-31 161140 32 1829 0
2023-01-30 161108 37 1829 0
2023-01-27 161071 63 1829 0
2023-01-26 161008 9 1829 0
2023-01-25 160999 34 1829 0
2023-01-24 160965 11 1829 0
2023-01-23 160954 19 1829 0
2023-01-20 160935 10 1829 0
2023-01-19 160925 25 1829 0
2023-01-18 160900 17 1829 0
2023-01-17 160883 23 1829 0
2023-01-16 160860 26 1829 0
2023-01-13 160834 16 1829 0
2023-01-12 160818 31 1829 0
2023-01-11 160787 30 1829 0
2023-01-10 160757 41 1829 0
2023-01-09 160716 43 1829 0
2023-01-06 160673 29 1829 0
2023-01-05 160644 39 1829 0
2023-01-04 160605 42 1829 0
2023-01-03 160563 94 1829 2
2023-01-02 160469 71 1827 1
2022-12-30 160398 40 1826 0
2022-12-29 160358 73 1826 0
2022-12-28 160285 69 1826 1
2022-12-27 160216 137 1825 2
2022-12-23 160079 39 1823 0
2022-12-22 160040 85 1823 1
2022-12-21 159955 118 1822 0
2022-12-20 159837 120 1822 1
2022-12-19 159717 182 1821 5
2022-12-17 159535 1 1816 0
2022-12-16 159534 109 1816 1
2022-12-15 159425 77 1815 0
2022-12-14 159348 160 1815 2
2022-12-13 159188 123 1813 3
2022-12-12 159065 173 1810 2
2022-12-09 158892 64 1808 3
2022-12-08 158828 153 1805 1
2022-12-07 158675 146 1804 0
2022-12-06 158529 101 1804 1
2022-12-05 158428 177 1803 5
2022-12-04 158251 1 1798 0
2022-12-02 158250 84 1798 1
2022-12-01 158166 53 1797 0
2022-11-30 158113 101 1797 1
2022-11-29 158012 125 1796 0
2022-11-28 157887 113 1796 1
2022-11-25 157774 71 1795 2
2022-11-24 157703 64 1793 0
2022-11-23 157639 104 1793 2
2022-11-22 157535 73 1791 0
2022-11-21 157462 120 1791 0
2022-11-18 157342 103 1791 1
2022-11-17 157239 90 1790 0
2022-11-15 157149 135 1790 0
2022-11-14 157014 118 1790 0
2022-11-11 156896 84 1790 1
2022-11-10 156812 83 1789 0
2022-11-09 156729 60 1789 1
2022-11-08 156669 170 1788 2
2022-11-07 156499 126 1786 0
2022-11-04 156373 106 1786 0
2022-11-03 156267 133 1786 0
2022-11-02 156134 203 1786 1
2022-11-01 155931 213 1785 2
2022-10-28 155718 90 1783 0
2022-10-27 155628 159 1783 2
2022-10-26 155469 199 1781 1
2022-10-25 155270 254 1780 2
2022-10-24 155016 303 1778 2
2022-10-21 154713 191 1776 0
2022-10-20 154522 245 1776 2
2022-10-19 154277 226 1774 1
2022-10-18 154051 390 1773 1
2022-10-17 153661 442 1772 2
2022-10-14 153219 194 1770 0
2022-10-13 153025 349 1770 3
2022-10-12 152676 376 1767 3
2022-10-11 152300 436 1764 0
2022-10-10 151864 639 1764 2
2022-10-07 151225 335 1762 0
2022-10-06 150890 493 1762 1
2022-10-05 150397 568 1761 4
2022-10-04 149829 548 1757 3
2022-09-30 149281 216 1754 0
2022-09-29 149065 319 1754 1
2022-09-28 148746 391 1753 0
2022-09-27 148355 499 1753 1
2022-09-26 147856 469 1752 2
2022-09-23 147387 230 1750 1
2022-09-22 147157 264 1749 0
2022-09-21 146893 321 1749 0
2022-09-20 146572 258 1749 0
2022-09-19 146314 306 1749 5
2022-09-16 146008 119 1744 1
2022-09-15 145889 219 1743 1
2022-09-14 145670 166 1742 0
2022-09-13 145504 244 1742 0
2022-09-12 145260 238 1742 0
2022-09-11 145022 1 1742 0
2022-09-09 145021 118 1742 1
2022-09-08 144903 157 1741 0
2022-09-07 144746 181 1741 1
2022-09-06 144565 178 1740 0
2022-09-05 144387 217 1740 1
2022-09-02 144170 130 1739 1
2022-09-01 144040 113 1738 0
2022-08-31 143927 161 1738 0
2022-08-30 143766 182 1738 0
2022-08-29 143584 193 1738 1
2022-08-26 143391 99 1737 0
2022-08-25 143292 99 1737 0
2022-08-24 143193 146 1737 0
2022-08-23 143047 255 1737 0
2022-08-22 142792 219 1737 1
2022-08-20 142573 1 1736 0
2022-08-19 142572 98 1736 1
2022-08-18 142474 157 1735 1
2022-08-17 142317 127 1734 1
2022-08-16 142190 225 1733 3
2022-08-15 141965 204 1730 2
2022-08-13 141761 1 1728 0
2022-08-12 141760 106 1728 0
2022-08-11 141654 112 1728 0
2022-08-10 141542 142 1728 0
2022-08-09 141400 223 1728 0
2022-08-08 141177 233 1728 3
2022-08-05 140944 130 1725 2
2022-08-04 140814 170 1723 0
2022-08-03 140644 192 1723 1
2022-08-02 140452 336 1722 1
2022-08-01 140116 276 1721 3
2022-07-29 139840 156 1718 0
2022-07-28 139684 245 1718 3
2022-07-27 139439 276 1715 2
2022-07-26 139163 504 1713 0
2022-07-25 138659 430 1713 4
2022-07-22 138229 203 1709 1
2022-07-21 138026 456 1708 2
2022-07-20 137570 252 1706 0
2022-07-19 137318 469 1706 1
2022-07-18 136849 401 1705 2
2022-07-15 136448 197 1703 1
2022-07-14 136251 253 1702 0
2022-07-13 135998 170 1702 0
2022-07-12 135828 387 1702 1
2022-07-11 135441 259 1701 1
2022-07-08 135182 149 1700 0
2022-07-07 135033 184 1700 0
2022-07-06 134849 290 1700 0
2022-07-05 134559 130 1700 1
2022-07-04 134429 187 1699 0
2022-07-01 134242 171 1699 0
2022-06-30 134071 160 1699 1
2022-06-29 133911 171 1698 3
2022-06-28 133740 219 1695 0
2022-06-27 133521 128 1695 0
2022-06-24 133393 130 1695 0
2022-06-23 133263 111 1695 1
2022-06-22 133152 121 1694 0
2022-06-21 133031 128 1694 2
2022-06-20 132903 141 1692 1
2022-06-17 132762 90 1691 0
2022-06-16 132672 95 1691 0
2022-06-15 132577 90 1691 0
2022-06-14 132487 126 1691 1
2022-06-13 132361 149 1690 0
2022-06-10 132212 85 1690 0
2022-06-09 132127 155 1690 0
2022-06-08 131972 90 1690 0
2022-06-07 131882 127 1690 0
2022-06-03 131755 67 1690 0
2022-06-02 131688 65 1690 0
2022-06-01 131623 60 1690 0
2022-05-31 131563 118 1690 0
2022-05-30 131445 115 1690 0
2022-05-27 131330 4 1690 0
2022-05-25 131326 62 1690 0
2022-05-24 131264 97 1690 0
2022-05-23 131167 80 1690 0
2022-05-20 131087 50 1690 0
2022-05-19 131037 66 1690 0
2022-05-18 130971 86 1690 1
2022-05-17 130885 120 1689 0
2022-05-16 130765 110 1689 0
2022-05-14 130655 8 1689 0
2022-05-13 130647 76 1689 0
2022-05-12 130571 118 1689 0
2022-05-11 130453 168 1689 0
2022-05-10 130285 133 1689 0
2022-05-09 130152 135 1689 0
2022-05-06 130017 126 1689 0
2022-05-05 129891 127 1689 1
2022-05-04 129764 181 1688 0
2022-05-03 129583 277 1688 2
2022-05-02 129306 169 1686 2
2022-04-30 129137 47 1684 0
2022-04-29 129090 143 1684 0
2022-04-28 128947 149 1684 1
2022-04-27 128798 180 1683 1
2022-04-26 128618 343 1682 0
2022-04-25 128275 324 1682 4
2022-04-24 127951 1 1678 0
2022-04-23 127950 58 1678 0
2022-04-22 127892 205 1678 1
2022-04-21 127687 374 1677 1
2022-04-20 127313 461 1676 5
2022-04-19 126852 552 1671 3
2022-04-14 126300 346 1668 3
2022-04-13 125954 381 1665 2
2022-04-12 125573 557 1663 1
2022-04-11 125016 317 1662 0
2022-04-09 124699 305 1662 1
2022-04-08 124394 397 1661 2
2022-04-07 123997 429 1659 1
2022-04-06 123568 537 1658 2
2022-04-05 123031 815 1656 4
2022-04-04 122216 408 1652 6
2022-04-03 121808 3 1646 0
2022-04-02 121805 462 1646 2
2022-04-01 121343 689 1644 4
2022-03-31 120654 976 1640 4
2022-03-30 119678 745 1636 1
2022-03-29 118933 1233 1635 3
2022-03-28 117700 1111 1632 6
2022-03-27 116589 16 1626 0
2022-03-26 116573 753 1626 5
2022-03-25 115820 957 1621 6
2022-03-24 114863 1476 1615 3
2022-03-23 113387 1620 1612 3
2022-03-22 111767 1987 1609 5
2022-03-21 109780 1703 1604 7
2022-03-20 108077 24 1597 0
2022-03-19 108053 697 1597 0
2022-03-18 107356 1506 1597 4
2022-03-17 105850 2092 1593 5
2022-03-16 103758 1713 1588 5
2022-03-15 102045 1838 1583 6
2022-03-14 100207 1781 1577 4
2022-03-13 98426 22 1573 2
2022-03-12 98404 1167 1571 2
2022-03-11 97237 1157 1569 5
2022-03-10 96080 1597 1564 8
2022-03-09 94483 1392 1556 4
2022-03-08 93091 1549 1552 1
2022-03-07 91542 898 1551 5
2022-03-06 90644 13 1546 0
2022-03-05 90631 811 1546 3
2022-03-04 89820 896 1543 1
2022-03-03 88924 859 1542 4
2022-03-02 88065 1352 1538 0
2022-03-01 86713 1330 1538 2
2022-02-28 85383 622 1536 1
2022-02-27 84761 3 1535 0
2022-02-26 84758 753 1535 3
2022-02-25 84005 673 1532 0
2022-02-24 83332 831 1532 1
2022-02-23 82501 1085 1531 4
2022-02-22 81416 1031 1527 0
2022-02-21 80385 482 1527 4
2022-02-20 79903 62 1523 0
2022-02-19 79841 716 1523 2
2022-02-18 79125 522 1521 2
2022-02-17 78603 754 1519 2
2022-02-16 77849 775 1517 0
2022-02-15 77074 937 1517 0
2022-02-14 76137 590 1517 3
2022-02-13 75547 5 1514 0
2022-02-12 75542 497 1514 0
2022-02-11 75045 539 1514 1
2022-02-10 74506 639 1513 0
2022-02-09 73867 542 1513 1
2022-02-08 73325 864 1512 3
2022-02-07 72461 300 1509 1
2022-02-05 72161 352 1508 3
2022-02-04 71809 299 1505 0
2022-02-03 71510 370 1505 1
2022-02-02 71140 283 1504 0
2022-02-01 70857 459 1504 0
2022-01-31 70398 132 1504 0
2022-01-29 70266 174 1504 0
2022-01-28 70092 157 1504 0
2022-01-27 69935 163 1504 1
2022-01-26 69772 152 1503 0
2022-01-25 69620 252 1503 0
2022-01-24 69368 61 1503 0
2022-01-23 69307 1 1503 0
2022-01-22 69306 122 1503 1
2022-01-21 69184 93 1502 0
2022-01-20 69091 83 1502 0
2022-01-19 69008 87 1502 1
2022-01-18 68921 124 1501 0
2022-01-17 68797 73 1501 1
2022-01-15 68724 82 1500 1
2022-01-14 68642 70 1499 0
2022-01-13 68572 95 1499 2
2022-01-12 68477 74 1497 1
2022-01-11 68403 119 1496 1
2022-01-10 68284 68 1495 1
2022-01-08 68216 85 1494 0
2022-01-07 68131 65 1494 3
2022-01-06 68066 122 1491 1
2022-01-05 67944 127 1490 1
2022-01-04 67817 365 1489 4
2022-01-03 67452 132 1485 3
2022-01-01 67320 1 1482 0
2021-12-31 67319 204 1482 2
2021-12-30 67115 153 1480 3
2021-12-29 66962 248 1477 1
2021-12-28 66714 320 1476 5
2021-12-27 66394 144 1471 4
2021-12-25 66250 1 1467 0
2021-12-24 66249 192 1467 5
2021-12-23 66057 220 1462 5
2021-12-22 65837 318 1457 3
2021-12-21 65519 480 1454 7
2021-12-20 65039 198 1447 6
2021-12-18 64841 232 1441 4
2021-12-17 64609 315 1437 9
2021-12-16 64294 408 1428 2
2021-12-15 63886 482 1426 13
2021-12-14 63404 656 1413 8
2021-12-13 62748 306 1405 7
2021-12-12 62442 3 1398 1
2021-12-11 62439 454 1397 7
2021-12-10 61985 451 1390 7
2021-12-09 61534 759 1383 7
2021-12-08 60775 750 1376 5
2021-12-07 60025 869 1371 9
2021-12-06 59156 405 1362 13
2021-12-04 58751 749 1349 11
2021-12-03 58002 800 1338 8
2021-12-02 57202 898 1330 16
2021-12-01 56304 965 1314 10
2021-11-30 55339 912 1304 14
2021-11-29 54427 932 1290 12
2021-11-28 53495 225 1278 2
2021-11-27 53270 692 1276 11
2021-11-26 52578 965 1265 15
2021-11-25 51613 1305 1250 13
2021-11-24 50308 1632 1237 34
2021-11-23 48676 1278 1203 13
2021-11-22 47398 1082 1190 10
2021-11-21 46316 275 1180 7
2021-11-20 46041 703 1173 3
2021-11-19 45338 1174 1170 21
2021-11-18 44164 664 1149 16
2021-11-17 43500 830 1133 10
2021-11-16 42670 820 1123 9
2021-11-15 41850 639 1114 9
2021-11-14 41211 11 1105 0
2021-11-13 41200 164 1105 4
2021-11-12 41036 698 1101 3
2021-11-11 40338 740 1098 17
2021-11-10 39598 527 1081 12
2021-11-09 39071 405 1069 2
2021-11-08 38666 258 1067 5
2021-11-06 38408 245 1062 5
2021-11-05 38163 287 1057 4
2021-11-04 37876 376 1053 6
2021-11-03 37500 196 1047 2
2021-11-02 37304 338 1045 9
2021-11-01 36966 300 1036 7
2021-10-30 36666 43 1029 0
2021-10-29 36623 238 1029 5
2021-10-28 36385 240 1024 6
2021-10-27 36145 222 1018 5
2021-10-26 35923 313 1013 1
2021-10-25 35610 53 1012 6
2021-10-23 35557 198 1006 5
2021-10-22 35359 219 1001 4
2021-10-21 35140 163 997 4
2021-10-20 34977 150 993 2
2021-10-19 34827 226 991 4
2021-10-18 34601 48 987 3
2021-10-17 34553 10 984 0
2021-10-16 34543 113 984 2
2021-10-15 34430 120 982 1
2021-10-14 34310 96 981 3
2021-10-13 34214 118 978 5
2021-10-12 34096 166 973 3
2021-10-11 33930 46 970 5
2021-10-09 33884 71 965 0
2021-10-08 33813 69 965 0
2021-10-07 33744 79 965 0
2021-10-06 33665 106 965 1
2021-10-05 33559 121 964 1
2021-10-04 33438 30 963 2
2021-10-02 33408 51 961 1
2021-10-01 33357 59 960 0
2021-09-30 33298 63 960 0
2021-09-29 33235 66 960 0
2021-09-28 33169 107 960 1
2021-09-27 33062 35 959 2
2021-09-25 33027 59 957 0
2021-09-24 32968 52 957 0
2021-09-23 32916 33 957 0
2021-09-22 32883 47 957 0
2021-09-21 32836 71 957 2
2021-09-20 32765 20 955 0
2021-09-18 32745 61 955 1
2021-09-17 32684 27 954 1
2021-09-16 32657 31 953 1
2021-09-15 32626 36 952 0
2021-09-14 32590 52 952 1
2021-09-13 32538 16 951 0
2021-09-12 32522 4 951 1
2021-09-11 32518 27 950 1
2021-09-10 32491 25 949 1
2021-09-09 32466 30 948 0
2021-09-08 32436 29 948 0
2021-09-07 32407 42 948 0
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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: 0:03:29.203108