Germany: SK Baden-Baden (Baden-Württemberg)¶

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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 10:19:09 CEST
In [2]:
%config InlineBackend.figure_formats = ['svg']
from oscovida import *
In [3]:
overview(country="Germany", subregion="SK Baden-Baden", weeks=5);
2023-03-07T10:19:23.452954 image/svg+xml Matplotlib v3.7.1, https://matplotlib.org/ 30 Jan 06 Feb 13 Feb 20 Feb 27 Feb 06 Mar 75 75 100 100 125 125 150 150 7-day incidence rate (per 100K people) 57.6 SK Baden-Baden, 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 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-SK Baden-Baden new deaths (rolling 7d mean) Germany-SK Baden-Baden new deaths 30 Jan 06 Feb 13 Feb 20 Feb 27 Feb 06 Mar 0.75 0.75 1.00 1.00 1.25 1.25 1.50 1.50 R & growth factor (based on cases) Germany-SK Baden-Baden cases daily growth factor Germany-SK Baden-Baden cases daily growth factor (rolling mean) Germany-SK Baden-Baden 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-SK Baden-Baden deaths daily growth factor Germany-SK Baden-Baden deaths daily growth factor (rolling mean) Germany-SK Baden-Baden estimated R (using deaths) 30 Jan 06 Feb 13 Feb 20 Feb 27 Feb 06 Mar 0 1000 2000 3000 4000 cases doubling time [days] Germany-SK Baden-Baden doubling time cases (rolling mean) 0.00 11.11 22.21 daily change Germany-SK Baden-Baden new cases (rolling 7d mean) Germany-SK Baden-Baden new cases 0.000 0.233 0.467 0.700 0.933
In [4]:
overview(country="Germany", subregion="SK Baden-Baden");
2023-03-07T10:19:43.443053 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) 57.6 SK Baden-Baden, 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 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 0.75 0.75 1.00 1.00 1.25 1.25 1.50 1.50 R & growth factor (based on cases) Germany-SK Baden-Baden cases daily growth factor Germany-SK Baden-Baden cases daily growth factor (rolling mean) Germany-SK Baden-Baden 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-SK Baden-Baden deaths daily growth factor Germany-SK Baden-Baden deaths daily growth factor (rolling mean) Germany-SK Baden-Baden estimated R (using deaths) May 20 Sep 20 Jan 21 May 21 Sep 21 Jan 22 May 22 Sep 22 Jan 23 0 1000 2000 3000 4000 cases doubling time [days] Germany-SK Baden-Baden doubling time cases (rolling mean) Germany-SK Baden-Baden doubling time deaths (rolling mean) 0.0 55.5 111.1 166.6 222.1 daily change Germany-SK Baden-Baden new cases (rolling 7d mean) Germany-SK Baden-Baden new cases 0.000 1.111 2.221 3.332 4.442 daily change Germany-SK Baden-Baden new deaths (rolling 7d mean) Germany-SK Baden-Baden new deaths 0.0 21.5 43.0 64.5 86.0 deaths doubling time [days]
In [5]:
compare_plot(country="Germany", subregion="SK Baden-Baden", dates="2020-03-15:");
2023-03-07T10:22:04.877299 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 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: SK Baden-Baden SK Baden-Baden 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 SK Baden-Baden Bayern Berlin Bremen Hamburg Hessen Nordrhein-Westfalen Sachsen-Anhalt
In [6]:
# load the data
cases, deaths = germany_get_region(landkreis="SK Baden-Baden")

# get population of the region for future normalisation:
inhabitants = population(country="Germany", subregion="SK Baden-Baden")
print(f'Population of country="Germany", subregion="SK Baden-Baden": {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="SK Baden-Baden": 55527 people
Out[6]:
total cases daily new cases total deaths daily new deaths
date
2023-03-06 23922 7 136 0
2023-03-03 23915 5 136 0
2023-03-02 23910 6 136 0
2023-03-01 23904 8 136 0
2023-02-28 23896 6 136 0
2023-02-27 23890 33 136 0
2023-02-24 23857 8 136 0
2023-02-23 23849 12 136 0
2023-02-22 23837 14 136 0
2023-02-21 23823 18 136 0
2023-02-20 23805 22 136 0
2023-02-17 23783 13 136 0
2023-02-16 23770 8 136 0
2023-02-15 23762 14 136 0
2023-02-14 23748 18 136 0
2023-02-13 23730 29 136 0
2023-02-10 23701 8 136 0
2023-02-09 23693 4 136 0
2023-02-08 23689 6 136 0
2023-02-07 23683 16 136 0
2023-02-06 23667 9 136 0
2023-02-03 23658 8 136 0
2023-02-02 23650 8 136 0
2023-02-01 23642 10 136 0
2023-01-31 23632 10 136 0
2023-01-30 23622 12 136 0
2023-01-27 23610 5 136 0
2023-01-26 23605 6 136 0
2023-01-25 23599 4 136 0
2023-01-24 23595 13 136 0
2023-01-23 23582 7 136 0
2023-01-20 23575 8 136 0
2023-01-19 23567 6 136 0
2023-01-18 23561 11 136 1
2023-01-17 23550 13 135 0
2023-01-16 23537 11 135 1
2023-01-13 23526 9 134 0
2023-01-12 23517 6 134 0
2023-01-11 23511 9 134 0
2023-01-10 23502 11 134 0
2023-01-09 23491 18 134 1
2023-01-05 23473 4 133 0
2023-01-04 23469 10 133 0
2023-01-03 23459 19 133 0
2023-01-02 23440 17 133 0
2022-12-30 23423 15 133 1
2022-12-29 23408 22 132 0
2022-12-28 23386 47 132 1
2022-12-27 23339 47 131 1
2022-12-23 23292 20 130 0
2022-12-22 23272 29 130 2
2022-12-21 23243 29 128 0
2022-12-20 23214 29 128 1
2022-12-19 23185 32 127 3
2022-12-16 23153 18 124 0
2022-12-15 23135 16 124 0
2022-12-14 23119 16 124 0
2022-12-13 23103 21 124 0
2022-12-12 23082 23 124 0
2022-12-09 23059 17 124 0
2022-12-08 23042 15 124 0
2022-12-07 23027 18 124 0
2022-12-06 23009 15 124 0
2022-12-05 22994 25 124 0
2022-12-02 22969 14 124 0
2022-12-01 22955 14 124 0
2022-11-30 22941 10 124 0
2022-11-29 22931 17 124 0
2022-11-28 22914 26 124 0
2022-11-25 22888 5 124 0
2022-11-24 22883 6 124 0
2022-11-23 22877 15 124 0
2022-11-22 22862 19 124 0
2022-11-21 22843 22 124 0
2022-11-18 22821 13 124 1
2022-11-17 22808 15 123 0
2022-11-16 22793 10 123 1
2022-11-15 22783 21 122 0
2022-11-14 22762 24 122 0
2022-11-11 22738 20 122 0
2022-11-10 22718 19 122 0
2022-11-09 22699 33 122 1
2022-11-08 22666 36 121 1
2022-11-07 22630 41 120 0
2022-11-04 22589 18 120 1
2022-11-03 22571 29 119 0
2022-11-02 22542 27 119 0
2022-10-31 22515 44 119 1
2022-10-28 22471 34 118 0
2022-10-27 22437 42 118 0
2022-10-26 22395 42 118 1
2022-10-25 22353 51 117 0
2022-10-24 22302 62 117 1
2022-10-21 22240 45 116 0
2022-10-20 22195 40 116 0
2022-10-19 22155 71 116 1
2022-10-18 22084 122 115 0
2022-10-17 21962 85 115 0
2022-10-14 21877 56 115 1
2022-10-13 21821 55 114 1
2022-10-12 21766 86 113 1
2022-10-11 21680 108 112 0
2022-10-10 21572 115 112 0
2022-10-07 21457 72 112 0
2022-10-06 21385 91 112 0
2022-10-05 21294 113 112 1
2022-10-04 21181 105 111 0
2022-09-30 21076 49 111 0
2022-09-29 21027 43 111 0
2022-09-28 20984 65 111 0
2022-09-27 20919 65 111 0
2022-09-26 20854 62 111 0
2022-09-23 20792 34 111 0
2022-09-22 20758 23 111 0
2022-09-21 20735 34 111 0
2022-09-20 20701 30 111 0
2022-09-19 20671 37 111 0
2022-09-16 20634 16 111 0
2022-09-15 20618 13 111 0
2022-09-14 20605 20 111 0
2022-09-13 20585 28 111 0
2022-09-12 20557 28 111 1
2022-09-09 20529 15 110 0
2022-09-08 20514 15 110 0
2022-09-07 20499 15 110 0
2022-09-06 20484 27 110 0
2022-09-05 20457 24 110 0
2022-09-02 20433 21 110 0
2022-09-01 20412 14 110 0
2022-08-31 20398 20 110 0
2022-08-30 20378 37 110 0
2022-08-29 20341 40 110 0
2022-08-26 20301 15 110 0
2022-08-25 20286 27 110 0
2022-08-24 20259 18 110 0
2022-08-23 20241 35 110 0
2022-08-22 20206 28 110 0
2022-08-19 20178 18 110 0
2022-08-18 20160 24 110 0
2022-08-17 20136 33 110 0
2022-08-16 20103 45 110 1
2022-08-15 20058 37 109 0
2022-08-12 20021 30 109 0
2022-08-11 19991 27 109 1
2022-08-10 19964 35 108 0
2022-08-09 19929 53 108 0
2022-08-08 19876 40 108 0
2022-08-05 19836 37 108 0
2022-08-04 19799 37 108 0
2022-08-03 19762 40 108 0
2022-08-02 19722 71 108 0
2022-08-01 19651 67 108 0
2022-07-29 19584 45 108 0
2022-07-28 19539 44 108 0
2022-07-27 19495 55 108 0
2022-07-26 19440 106 108 0
2022-07-25 19334 125 108 0
2022-07-22 19209 65 108 0
2022-07-21 19144 55 108 0
2022-07-20 19089 98 108 0
2022-07-19 18991 147 108 0
2022-07-18 18844 141 108 1
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2021-05-20 1995 5 63 0
2021-05-19 1990 5 63 0
2021-05-18 1985 4 63 0
2021-05-15 1981 8 63 0
2021-05-14 1973 2 63 0
2021-05-13 1971 8 63 1
2021-05-12 1963 12 62 0
2021-05-11 1951 7 62 0
2021-05-10 1944 2 62 0
2021-05-08 1942 8 62 1
2021-05-07 1934 6 61 0
2021-05-06 1928 15 61 0
2021-05-05 1913 13 61 1
2021-05-04 1900 27 60 0
2021-05-01 1873 5 60 0
2021-04-30 1868 8 60 0
2021-04-29 1860 12 60 0
2021-04-28 1848 21 60 0
2021-04-27 1827 20 60 0
2021-04-26 1807 1 60 0
2021-04-24 1806 17 60 0
2021-04-23 1789 17 60 1
2021-04-22 1772 14 59 0
2021-04-21 1758 15 59 1
2021-04-20 1743 37 58 0
2021-04-19 1706 6 58 0
2021-04-18 1700 1 58 0
2021-04-17 1699 12 58 0
2021-04-16 1687 18 58 0
2021-04-15 1669 9 58 0
2021-04-14 1660 13 58 0
2021-04-13 1647 13 58 1
2021-04-12 1634 3 57 0
2021-04-10 1631 17 57 1
2021-04-09 1614 9 56 1
2021-04-08 1605 12 55 0
2021-04-07 1593 33 55 1
2021-04-06 1560 1 54 0
2021-04-04 1559 3 54 0
2021-04-03 1556 2 54 0
2021-04-02 1554 15 54 0
2021-04-01 1539 20 54 1
2021-03-31 1519 12 53 0
2021-03-30 1507 21 53 1
2021-03-29 1486 7 52 1
2021-03-28 1479 9 51 1
2021-03-27 1470 4 50 0
2021-03-26 1466 17 50 0
2021-03-25 1449 17 50 0
2021-03-24 1432 16 50 0
2021-03-23 1416 18 50 1
2021-03-22 1398 1 49 0
2021-03-21 1397 1 49 0
2021-03-20 1396 10 49 0
2021-03-19 1386 16 49 0
2021-03-18 1370 12 49 0
2021-03-17 1358 7 49 0
2021-03-16 1351 22 49 0
2021-03-15 1329 2 49 0
2021-03-14 1327 2 49 0
2021-03-13 1325 4 49 0
2021-03-12 1321 10 49 0
2021-03-11 1311 4 49 0
2021-03-10 1307 8 49 0
2021-03-09 1299 6 49 0
2021-03-08 1293 2 49 0
2021-03-05 1291 2 49 0
2021-03-04 1289 7 49 1
2021-03-03 1282 8 48 0
2021-03-02 1274 5 48 0
2021-02-27 1269 4 48 1
2021-02-26 1265 3 47 0
2021-02-25 1262 4 47 0
2021-02-24 1258 10 47 0
2021-02-23 1248 13 47 0
2021-02-22 1235 2 47 0
2021-02-21 1233 1 47 1
2021-02-20 1232 3 46 0
2021-02-19 1229 4 46 0
2021-02-18 1225 5 46 0
2021-02-16 1220 2 46 0
2021-02-14 1218 1 46 0
2021-02-13 1217 5 46 0
2021-02-12 1212 4 46 0
2021-02-11 1208 3 46 0
2021-02-10 1205 4 46 0
2021-02-09 1201 5 46 0
2021-02-08 1196 1 46 0
2021-02-06 1195 1 46 0
2021-02-05 1194 4 46 0
2021-02-04 1190 2 46 0
2021-02-03 1188 2 46 0
2021-02-02 1186 7 46 0
2021-02-01 1179 1 46 0
2021-01-31 1178 2 46 0
2021-01-30 1176 4 46 0
2021-01-29 1172 1 46 0
2021-01-28 1171 5 46 0
2021-01-27 1166 1 46 0
2021-01-26 1165 3 46 0
2021-01-23 1162 1 46 0
2021-01-22 1161 3 46 0
2021-01-21 1158 8 46 0
2021-01-20 1150 3 46 0
2021-01-19 1147 7 46 0
2021-01-18 1140 6 46 0
2021-01-17 1134 6 46 0
2021-01-16 1128 3 46 0
2021-01-15 1125 5 46 0
2021-01-14 1120 4 46 0
2021-01-13 1116 8 46 1
2021-01-12 1108 15 45 0
2021-01-11 1093 11 45 0
2021-01-10 1082 1 45 0
2021-01-09 1081 4 45 0
2021-01-08 1077 10 45 3
2021-01-07 1067 4 42 0
2021-01-06 1063 11 42 0
2021-01-05 1052 12 42 0
2021-01-04 1040 7 42 0
2021-01-03 1033 5 42 0
2021-01-02 1028 6 42 0
2021-01-01 1022 3 42 0
2020-12-31 1019 20 42 1
2020-12-30 999 18 41 0
2020-12-29 981 17 41 0
2020-12-28 964 10 41 1
2020-12-27 954 6 40 1
2020-12-26 948 18 39 4
2020-12-25 930 1 35 0
2020-12-24 929 3 35 0
2020-12-23 926 7 35 0
2020-12-22 919 8 35 1
2020-12-21 911 9 34 0
2020-12-20 902 8 34 2
2020-12-19 894 6 32 0
2020-12-18 888 12 32 0
2020-12-17 876 22 32 1
2020-12-16 854 6 31 0
2020-12-15 848 10 31 0
2020-12-14 838 21 31 1
2020-12-13 817 13 30 0
2020-12-12 804 7 30 0
2020-12-11 797 14 30 0
2020-12-10 783 10 30 1
2020-12-09 773 22 29 0
2020-12-08 751 12 29 0
2020-12-07 739 20 29 2
2020-12-06 719 11 27 0
2020-12-05 708 1 27 0
2020-12-04 707 18 27 0
2020-12-03 689 3 27 0
2020-12-02 686 11 27 1
2020-12-01 675 8 26 1
2020-11-30 667 8 25 0
2020-11-29 659 5 25 0
2020-11-28 654 7 25 0
2020-11-27 647 6 25 0
2020-11-26 641 17 25 1
2020-11-25 624 13 24 0
2020-11-24 611 8 24 0
2020-11-23 603 5 24 0
2020-11-22 598 10 24 0
2020-11-21 588 11 24 0
2020-11-20 577 11 24 0
2020-11-19 566 19 24 0
2020-11-18 547 11 24 0
2020-11-17 536 19 24 0
2020-11-16 517 7 24 0
2020-11-14 510 2 24 0
2020-11-13 508 8 24 0
2020-11-12 500 8 24 1
2020-11-11 492 13 23 0
2020-11-10 479 5 23 0
2020-11-09 474 2 23 0
2020-11-08 472 10 23 0
2020-11-07 462 5 23 0
2020-11-06 457 10 23 0
2020-11-05 447 21 23 1
2020-11-04 426 13 22 0
2020-11-03 413 6 22 0
2020-11-02 407 1 22 0
2020-10-31 406 17 22 0
2020-10-30 389 12 22 0
2020-10-29 377 6 22 0
2020-10-28 371 18 22 0
2020-10-27 353 8 22 0
2020-10-26 345 13 22 0
2020-10-25 332 3 22 1
2020-10-24 329 3 21 0
2020-10-23 326 7 21 0
2020-10-22 319 3 21 1
2020-10-21 316 12 20 0
2020-10-20 304 9 20 0
2020-10-19 295 3 20 0
2020-10-18 292 5 20 0
2020-10-17 287 7 20 0
2020-10-16 280 5 20 0
2020-10-15 275 5 20 0
2020-10-14 270 3 20 0
2020-10-13 267 8 20 0
2020-10-12 259 4 20 0
2020-10-11 255 6 20 0
2020-10-10 249 4 20 0
2020-10-09 245 4 20 0
2020-10-08 241 5 20 0
2020-10-07 236 2 20 0
2020-10-06 234 1 20 1
2020-10-05 233 1 19 0
2020-10-04 232 1 19 0
2020-09-30 231 1 19 0
2020-09-29 230 1 19 0
2020-09-26 229 1 19 0
2020-09-24 228 2 19 0
2020-09-22 226 3 19 0
2020-09-19 223 1 19 0
2020-09-18 222 1 19 0
2020-09-17 221 1 19 0
2020-09-13 220 1 19 0
2020-09-12 219 1 19 0
2020-09-11 218 1 19 0
2020-09-10 217 2 19 0
2020-09-09 215 5 19 0
2020-09-08 210 2 19 0
2020-09-07 208 1 19 0
2020-09-01 207 4 19 0
2020-08-27 203 4 19 0
2020-08-26 199 2 19 0
2020-08-22 197 1 19 0
2020-08-21 196 2 19 0
2020-08-20 194 2 19 0
2020-08-17 192 2 19 0
2020-08-14 190 1 19 0
2020-08-06 189 2 19 0
2020-07-03 187 2 19 0
2020-06-06 185 1 19 0
2020-05-13 184 1 19 0
2020-05-12 183 1 19 0
2020-05-01 182 2 19 0
2020-04-30 180 2 19 0
2020-04-29 178 1 19 0
2020-04-26 177 1 19 0
2020-04-25 176 1 19 0
2020-04-23 175 2 19 0
2020-04-22 173 5 19 0
2020-04-21 168 1 19 0
2020-04-20 167 1 19 0
2020-04-19 166 1 19 0
2020-04-18 165 1 19 0
2020-04-17 164 1 19 0
2020-04-16 163 9 19 1
2020-04-15 154 8 18 0
2020-04-13 146 1 18 1
2020-04-12 145 5 17 0
2020-04-11 140 1 17 1
2020-04-10 139 4 16 0
2020-04-09 135 6 16 2
2020-04-08 129 6 14 0
2020-04-07 123 11 14 5
2020-04-05 112 3 9 0
2020-04-04 109 1 9 1
2020-04-03 108 8 8 1
2020-04-02 100 9 7 1
2020-04-01 91 2 6 0
2020-03-31 89 9 6 1
2020-03-30 80 8 5 0
2020-03-29 72 4 5 0
2020-03-28 68 14 5 0
2020-03-27 54 11 5 0
2020-03-26 43 4 5 0
2020-03-25 39 2 5 1
2020-03-24 37 4 4 1
2020-03-22 33 8 3 0
2020-03-21 25 3 3 0
2020-03-20 22 3 3 0
2020-03-19 19 3 3 0
2020-03-18 16 3 3 0
2020-03-17 13 1 3 0
2020-03-16 12 7 3 3
2020-03-15 5 1 0 0
2020-03-13 4 1 0 0
2020-03-11 3 1 0 0
2020-03-10 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: 0:03:18.176739