Germany: LK Vogelsbergkreis (Hessen)¶

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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 12:44:37 CEST
In [2]:
%config InlineBackend.figure_formats = ['svg']
from oscovida import *
In [3]:
overview(country="Germany", subregion="LK Vogelsbergkreis", weeks=5);
2023-03-07T12:44:49.349751 image/svg+xml Matplotlib v3.7.1, https://matplotlib.org/ 30 Jan 06 Feb 13 Feb 20 Feb 27 Feb 06 Mar 150 150 200 200 250 250 7-day incidence rate (per 100K people) 151.4 LK Vogelsbergkreis, 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 80 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 Vogelsbergkreis new deaths (rolling 7d mean) Germany-LK Vogelsbergkreis 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 R & growth factor (based on cases) Germany-LK Vogelsbergkreis cases daily growth factor Germany-LK Vogelsbergkreis cases daily growth factor (rolling mean) Germany-LK Vogelsbergkreis 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 Vogelsbergkreis deaths daily growth factor Germany-LK Vogelsbergkreis deaths daily growth factor (rolling mean) Germany-LK Vogelsbergkreis estimated R (using deaths) 30 Jan 06 Feb 13 Feb 20 Feb 27 Feb 06 Mar 0 1000 2000 cases doubling time [days] Germany-LK Vogelsbergkreis doubling time cases (rolling mean) 0.0 21.1 42.3 63.4 84.5 daily change Germany-LK Vogelsbergkreis new cases (rolling 7d mean) Germany-LK Vogelsbergkreis new cases 0.000 0.376 0.752
In [4]:
overview(country="Germany", subregion="LK Vogelsbergkreis");
2023-03-07T12:45:04.513888 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 0 500 500 1000 1000 1500 1500 2000 2000 7-day incidence rate (per 100K people) 151.4 LK Vogelsbergkreis, 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 6 8 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 Vogelsbergkreis cases daily growth factor Germany-LK Vogelsbergkreis cases daily growth factor (rolling mean) Germany-LK Vogelsbergkreis 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 Vogelsbergkreis deaths daily growth factor Germany-LK Vogelsbergkreis deaths daily growth factor (rolling mean) Germany-LK Vogelsbergkreis 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 cases doubling time [days] Germany-LK Vogelsbergkreis doubling time cases (rolling mean) Germany-LK Vogelsbergkreis doubling time deaths (rolling mean) 0.0 211.3 422.7 634.0 daily change Germany-LK Vogelsbergkreis new cases (rolling 7d mean) Germany-LK Vogelsbergkreis new cases 0.00 2.11 4.23 6.34 8.45 daily change Germany-LK Vogelsbergkreis new deaths (rolling 7d mean) Germany-LK Vogelsbergkreis new deaths 0.0 26.7 53.5 80.2 deaths doubling time [days]
In [5]:
compare_plot(country="Germany", subregion="LK Vogelsbergkreis", dates="2020-03-15:");
2023-03-07T12:47:18.005429 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 Vogelsbergkreis LK Vogelsbergkreis 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 Vogelsbergkreis Bayern Berlin Bremen Hamburg Hessen Nordrhein-Westfalen Sachsen-Anhalt
In [6]:
# load the data
cases, deaths = germany_get_region(landkreis="LK Vogelsbergkreis")

# get population of the region for future normalisation:
inhabitants = population(country="Germany", subregion="LK Vogelsbergkreis")
print(f'Population of country="Germany", subregion="LK Vogelsbergkreis": {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 Vogelsbergkreis": 105671 people
Out[6]:
total cases daily new cases total deaths daily new deaths
date
2023-03-06 53202 25 131 0
2023-03-03 53177 24 131 0
2023-03-02 53153 12 131 0
2023-03-01 53141 41 131 0
2023-02-28 53100 58 131 0
2023-02-27 53042 91 131 0
2023-02-24 52951 35 131 0
2023-02-23 52916 70 131 0
2023-02-22 52846 43 131 0
2023-02-21 52803 62 131 0
2023-02-20 52741 54 131 0
2023-02-17 52687 29 131 0
2023-02-16 52658 40 131 0
2023-02-15 52618 40 131 0
2023-02-14 52578 59 131 0
2023-02-13 52519 55 131 0
2023-02-10 52464 13 131 0
2023-02-09 52451 23 131 0
2023-02-08 52428 30 131 0
2023-02-07 52398 57 131 0
2023-02-06 52341 62 131 0
2023-02-03 52279 22 131 0
2023-02-02 52257 23 131 0
2023-02-01 52234 31 131 0
2023-01-31 52203 42 131 0
2023-01-30 52161 44 131 0
2023-01-27 52117 16 131 0
2023-01-26 52101 13 131 0
2023-01-25 52088 18 131 0
2023-01-24 52070 21 131 0
2023-01-23 52049 32 131 0
2023-01-20 52017 12 131 0
2023-01-19 52005 16 131 0
2023-01-18 51989 16 131 0
2023-01-17 51973 23 131 0
2023-01-16 51950 29 131 0
2023-01-13 51921 15 131 0
2023-01-12 51906 20 131 0
2023-01-11 51886 32 131 0
2023-01-10 51854 29 131 0
2023-01-09 51825 47 131 0
2023-01-06 51778 6 131 0
2023-01-05 51772 46 131 0
2023-01-04 51726 46 131 0
2023-01-03 51680 45 131 0
2023-01-02 51635 85 131 0
2022-12-30 51550 31 131 0
2022-12-29 51519 91 131 0
2022-12-28 51428 49 131 0
2022-12-27 51379 125 131 0
2022-12-23 51254 42 131 0
2022-12-22 51212 71 131 0
2022-12-21 51141 71 131 0
2022-12-20 51070 46 131 0
2022-12-19 51024 70 131 0
2022-12-16 50954 24 131 0
2022-12-15 50930 37 131 0
2022-12-14 50893 62 131 0
2022-12-13 50831 47 131 0
2022-12-12 50784 67 131 0
2022-12-09 50717 21 131 0
2022-12-08 50696 51 131 0
2022-12-07 50645 43 131 0
2022-12-06 50602 73 131 0
2022-12-05 50529 9 131 0
2022-12-02 50520 20 131 0
2022-12-01 50500 50 131 0
2022-11-30 50450 29 131 0
2022-11-29 50421 58 131 0
2022-11-28 50363 71 131 0
2022-11-25 50292 47 131 0
2022-11-24 50245 50 131 0
2022-11-23 50195 54 131 0
2022-11-22 50141 46 131 0
2022-11-21 50095 64 131 0
2022-11-18 50031 40 131 0
2022-11-17 49991 30 131 0
2022-11-16 49961 68 131 0
2022-11-15 49893 40 131 0
2022-11-14 49853 99 131 0
2022-11-11 49754 49 131 0
2022-11-10 49705 51 131 0
2022-11-09 49654 49 131 0
2022-11-08 49605 80 131 0
2022-11-07 49525 82 131 0
2022-11-04 49443 36 131 0
2022-11-03 49407 74 131 0
2022-11-02 49333 109 131 0
2022-11-01 49224 79 131 0
2022-10-31 49145 171 131 0
2022-10-28 48974 64 131 0
2022-10-27 48910 96 131 0
2022-10-26 48814 72 131 0
2022-10-25 48742 198 131 0
2022-10-24 48544 253 131 0
2022-10-21 48291 160 131 0
2022-10-20 48131 145 131 0
2022-10-19 47986 306 131 0
2022-10-18 47680 145 131 0
2022-10-17 47535 388 131 0
2022-10-14 47147 184 131 0
2022-10-13 46963 246 131 0
2022-10-12 46717 334 131 0
2022-10-11 46383 181 131 0
2022-10-10 46202 542 131 0
2022-10-07 45660 127 131 0
2022-10-06 45533 484 131 0
2022-10-05 45049 216 131 0
2022-10-04 44833 352 131 2
2022-09-30 44481 77 129 0
2022-09-29 44404 175 129 0
2022-09-28 44229 245 129 0
2022-09-27 43984 123 129 0
2022-09-26 43861 194 129 0
2022-09-23 43667 69 129 0
2022-09-22 43598 61 129 0
2022-09-21 43537 89 129 0
2022-09-20 43448 95 129 0
2022-09-19 43353 141 129 1
2022-09-16 43212 48 128 0
2022-09-15 43164 67 128 0
2022-09-14 43097 57 128 1
2022-09-13 43040 83 127 0
2022-09-12 42957 84 127 0
2022-09-09 42873 34 127 0
2022-09-08 42839 37 127 0
2022-09-07 42802 74 127 0
2022-09-06 42728 76 127 0
2022-09-05 42652 80 127 0
2022-09-02 42572 48 127 0
2022-09-01 42524 32 127 0
2022-08-31 42492 91 127 0
2022-08-30 42401 38 127 0
2022-08-29 42363 92 127 0
2022-08-26 42271 28 127 0
2022-08-25 42243 40 127 0
2022-08-24 42203 55 127 0
2022-08-23 42148 76 127 0
2022-08-22 42072 147 127 0
2022-08-19 41925 56 127 0
2022-08-18 41869 83 127 0
2022-08-17 41786 122 127 0
2022-08-16 41664 94 127 0
2022-08-15 41570 150 127 0
2022-08-12 41420 54 127 0
2022-08-11 41366 139 127 0
2022-08-10 41227 146 127 0
2022-08-09 41081 70 127 0
2022-08-08 41011 139 127 0
2022-08-05 40872 41 127 0
2022-08-04 40831 97 127 0
2022-08-03 40734 179 127 0
2022-08-02 40555 120 127 0
2022-08-01 40435 211 127 0
2022-07-29 40224 77 127 0
2022-07-28 40147 145 127 0
2022-07-27 40002 212 127 0
2022-07-26 39790 256 127 1
2022-07-25 39534 392 126 0
2022-07-22 39142 100 126 0
2022-07-21 39042 209 126 0
2022-07-20 38833 326 126 0
2022-07-19 38507 270 126 0
2022-07-18 38237 384 126 0
2022-07-15 37853 152 126 0
2022-07-14 37701 224 126 0
2022-07-13 37477 255 126 0
2022-07-12 37222 278 126 0
2022-07-11 36944 376 126 0
2022-07-07 36568 220 126 0
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2022-07-01 35734 77 126 0
2022-06-30 35657 152 126 0
2022-06-29 35505 176 126 0
2022-06-28 35329 296 126 0
2022-06-27 35033 316 126 0
2022-06-24 34717 95 126 0
2022-06-23 34622 189 126 0
2022-06-22 34433 240 126 0
2022-06-21 34193 276 126 0
2022-06-20 33917 249 126 0
2022-06-17 33668 158 126 0
2022-06-15 33510 149 126 0
2022-06-14 33361 233 126 0
2022-06-13 33128 298 126 0
2022-06-10 32830 84 126 0
2022-06-09 32746 234 126 0
2022-06-08 32512 125 126 0
2022-06-07 32387 275 126 0
2022-06-03 32112 144 126 0
2022-06-02 31968 89 126 0
2022-06-01 31879 134 126 1
2022-05-31 31745 76 125 0
2022-05-30 31669 126 125 0
2022-05-27 31543 70 125 0
2022-05-25 31473 46 125 0
2022-05-24 31427 94 125 0
2022-05-23 31333 85 125 1
2022-05-20 31248 64 124 0
2022-05-19 31184 67 124 0
2022-05-18 31117 95 124 0
2022-05-17 31022 132 124 0
2022-05-16 30890 148 124 0
2022-05-13 30742 72 124 0
2022-05-12 30670 83 124 0
2022-05-11 30587 137 124 0
2022-05-10 30450 201 124 0
2022-05-09 30249 171 124 0
2022-05-06 30078 114 124 0
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2022-05-03 29720 251 124 0
2022-05-02 29469 324 124 0
2022-04-29 29145 123 124 0
2022-04-28 29022 182 124 0
2022-04-27 28840 285 124 0
2022-04-26 28555 363 124 0
2022-04-25 28192 404 124 0
2022-04-22 27788 178 124 0
2022-04-21 27610 545 124 1
2022-04-20 27065 450 123 0
2022-04-19 26615 752 123 0
2022-04-14 25863 247 123 0
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2022-04-08 24357 198 122 0
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2021-03-23 2758 19 100 1
2021-03-22 2739 5 99 1
2021-03-21 2734 8 98 0
2021-03-20 2726 20 98 0
2021-03-19 2706 6 98 0
2021-03-18 2700 10 98 0
2021-03-17 2690 18 98 0
2021-03-16 2672 15 98 0
2021-03-15 2657 2 98 0
2021-03-14 2655 4 98 0
2021-03-13 2651 12 98 0
2021-03-12 2639 4 98 0
2021-03-11 2635 9 98 0
2021-03-10 2626 7 98 0
2021-03-09 2619 9 98 0
2021-03-08 2610 1 98 0
2021-03-07 2609 2 98 0
2021-03-06 2607 6 98 0
2021-03-05 2601 4 98 0
2021-03-04 2597 5 98 0
2021-03-03 2592 4 98 0
2021-03-02 2588 9 98 1
2021-03-01 2579 9 97 0
2021-02-28 2570 1 97 0
2021-02-27 2569 5 97 0
2021-02-26 2564 9 97 0
2021-02-25 2555 13 97 0
2021-02-24 2542 6 97 0
2021-02-23 2536 16 97 0
2021-02-22 2520 2 97 0
2021-02-20 2518 15 97 0
2021-02-19 2503 3 97 0
2021-02-18 2500 10 97 0
2021-02-17 2490 7 97 1
2021-02-16 2483 18 96 0
2021-02-15 2465 6 96 0
2021-02-13 2459 12 96 0
2021-02-12 2447 9 96 0
2021-02-11 2438 10 96 1
2021-02-10 2428 10 95 0
2021-02-09 2418 9 95 0
2021-02-08 2409 2 95 1
2021-02-07 2407 3 94 1
2021-02-06 2404 13 93 0
2021-02-05 2391 9 93 1
2021-02-04 2382 13 92 0
2021-02-03 2369 22 92 0
2021-02-02 2347 9 92 1
2021-02-01 2338 3 91 0
2021-01-31 2335 10 91 0
2021-01-30 2325 2 91 0
2021-01-29 2323 14 91 1
2021-01-28 2309 18 90 0
2021-01-27 2291 25 90 1
2021-01-26 2266 16 89 0
2021-01-24 2250 2 89 0
2021-01-23 2248 14 89 1
2021-01-22 2234 8 88 0
2021-01-21 2226 40 88 2
2021-01-20 2186 23 86 0
2021-01-19 2163 23 86 0
2021-01-18 2140 4 86 0
2021-01-17 2136 6 86 1
2021-01-16 2130 24 85 0
2021-01-15 2106 31 85 1
2021-01-14 2075 34 84 2
2021-01-13 2041 39 82 1
2021-01-12 2002 33 81 2
2021-01-11 1969 10 79 0
2021-01-10 1959 5 79 1
2021-01-09 1954 25 78 0
2021-01-08 1929 39 78 2
2021-01-07 1890 82 76 9
2021-01-06 1808 65 67 0
2021-01-05 1743 53 67 1
2021-01-04 1690 19 66 1
2021-01-03 1671 5 65 1
2021-01-02 1666 18 64 1
2020-12-31 1648 59 63 1
2020-12-30 1589 48 62 0
2020-12-29 1541 36 62 0
2020-12-28 1505 9 62 2
2020-12-27 1496 19 60 2
2020-12-26 1477 12 58 1
2020-12-24 1465 37 57 1
2020-12-23 1428 63 56 5
2020-12-22 1365 36 51 2
2020-12-21 1329 12 49 0
2020-12-20 1317 10 49 1
2020-12-19 1307 26 48 0
2020-12-18 1281 48 48 0
2020-12-17 1233 65 48 2
2020-12-16 1168 92 46 4
2020-12-15 1076 48 42 4
2020-12-14 1028 8 38 1
2020-12-13 1020 12 37 0
2020-12-12 1008 31 37 0
2020-12-11 977 57 37 2
2020-12-10 920 37 35 1
2020-12-09 883 38 34 1
2020-12-08 845 30 33 2
2020-12-07 815 5 31 0
2020-12-06 810 3 31 0
2020-12-05 807 29 31 1
2020-12-04 778 15 30 1
2020-12-03 763 18 29 3
2020-12-02 745 18 26 0
2020-12-01 727 20 26 3
2020-11-30 707 14 23 0
2020-11-29 693 4 23 0
2020-11-28 689 9 23 1
2020-11-27 680 24 22 2
2020-11-26 656 24 20 2
2020-11-25 632 23 18 4
2020-11-24 609 15 14 1
2020-11-23 594 6 13 0
2020-11-22 588 5 13 1
2020-11-21 583 6 12 0
2020-11-20 577 20 12 0
2020-11-19 557 21 12 1
2020-11-18 536 24 11 0
2020-11-17 512 22 11 0
2020-11-16 490 10 11 0
2020-11-15 480 1 11 0
2020-11-14 479 7 11 0
2020-11-13 472 9 11 0
2020-11-12 463 24 11 1
2020-11-11 439 15 10 0
2020-11-10 424 9 10 2
2020-11-09 415 7 8 0
2020-11-08 408 3 8 0
2020-11-07 405 10 8 0
2020-11-06 395 12 8 0
2020-11-05 383 5 8 0
2020-11-04 378 11 8 0
2020-11-03 367 8 8 0
2020-11-02 359 4 8 0
2020-11-01 355 4 8 1
2020-10-31 351 15 7 0
2020-10-30 336 10 7 0
2020-10-29 326 13 7 0
2020-10-28 313 20 7 1
2020-10-27 293 8 6 0
2020-10-26 285 15 6 0
2020-10-25 270 2 6 0
2020-10-24 268 9 6 0
2020-10-23 259 9 6 0
2020-10-22 250 7 6 0
2020-10-21 243 9 6 0
2020-10-20 234 7 6 0
2020-10-19 227 12 6 0
2020-10-16 215 3 6 0
2020-10-15 212 7 6 0
2020-10-14 205 7 6 0
2020-10-13 198 1 6 0
2020-10-12 197 2 6 0
2020-10-09 195 1 6 0
2020-10-08 194 1 6 0
2020-10-07 193 1 6 0
2020-10-05 192 1 6 0
2020-10-01 191 2 6 0
2020-09-30 189 3 6 0
2020-09-28 186 4 6 0
2020-09-25 182 1 6 0
2020-09-23 181 1 6 0
2020-09-21 180 3 6 0
2020-09-17 177 2 6 0
2020-09-15 175 4 6 0
2020-09-14 171 1 6 0
2020-09-10 170 1 6 0
2020-09-08 169 2 6 0
2020-09-03 167 1 6 0
2020-09-02 166 1 6 0
2020-09-01 165 1 6 0
2020-08-31 164 1 6 0
2020-08-28 163 1 6 0
2020-08-25 162 1 6 0
2020-08-24 161 1 6 0
2020-08-21 160 6 6 0
2020-08-17 154 5 6 0
2020-08-06 149 4 6 0
2020-07-30 145 1 6 0
2020-07-29 144 4 6 0
2020-07-28 140 2 6 0
2020-07-27 138 3 6 1
2020-07-24 135 2 5 0
2020-07-23 133 2 5 0
2020-07-20 131 2 5 0
2020-07-17 129 1 5 0
2020-07-16 128 1 5 0
2020-07-15 127 1 5 0
2020-07-14 126 1 5 0
2020-07-10 125 2 5 0
2020-07-08 123 1 5 0
2020-07-03 122 1 5 0
2020-04-28 121 1 5 0
2020-04-25 120 1 5 0
2020-04-24 119 1 5 0
2020-04-23 118 1 5 0
2020-04-22 117 4 5 0
2020-04-21 113 3 5 0
2020-04-19 110 2 5 0
2020-04-18 108 2 5 0
2020-04-17 106 3 5 0
2020-04-16 103 1 5 1
2020-04-15 102 2 4 0
2020-04-10 100 4 4 0
2020-04-09 96 5 4 0
2020-04-08 91 6 4 0
2020-04-07 85 7 4 2
2020-04-05 78 2 2 0
2020-04-04 76 3 2 0
2020-04-03 73 4 2 0
2020-04-02 69 8 2 0
2020-04-01 61 3 2 0
2020-03-31 58 5 2 1
2020-03-29 53 2 1 0
2020-03-28 51 6 1 0
2020-03-27 45 4 1 0
2020-03-26 41 3 1 0
2020-03-25 38 7 1 0
2020-03-24 31 1 1 0
2020-03-23 30 6 1 0
2020-03-22 24 2 1 0
2020-03-21 22 5 1 0
2020-03-20 17 2 1 0
2020-03-19 15 3 1 0
2020-03-18 12 7 1 0
2020-03-17 5 1 1 0
2020-03-16 4 1 1 1
2020-03-13 3 1 0 0
2020-03-11 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: 0:03:12.899356