Germany: LK Paderborn (Nordrhein-Westfalen)¶

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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: 26/01/2023 14:07:45 CEST
In [2]:
%config InlineBackend.figure_formats = ['svg']
from oscovida import *
In [3]:
overview(country="Germany", subregion="LK Paderborn", weeks=5);
2023-01-26T14:08:01.711617 image/svg+xml Matplotlib v3.6.3, https://matplotlib.org/ 26 Dec 02 Jan 09 Jan 16 Jan 23 Jan 100 100 200 200 7-day incidence rate (per 100K people) 54.3 LK Paderborn, Germany, last 5 weeks, last data point from 2023-01-25 26 Dec 02 Jan 09 Jan 16 Jan 23 Jan 0 20 40 60 daily change normalised per 100K 26 Dec 02 Jan 09 Jan 16 Jan 23 Jan 0.0 0.2 0.4 0.6 daily change normalised per 100K 26 Dec 02 Jan 09 Jan 16 Jan 23 Jan 0.6 0.6 0.8 0.8 1.0 1.0 1.2 1.2 R & growth factor (based on cases) Germany-LK Paderborn cases daily growth factor Germany-LK Paderborn cases daily growth factor (rolling mean) Germany-LK Paderborn estimated R (using cases) 26 Dec 02 Jan 09 Jan 16 Jan 23 Jan 1 1 2 2 3 3 4 4 R & growth factor (based on deaths) Germany-LK Paderborn deaths daily growth factor Germany-LK Paderborn deaths daily growth factor (rolling mean) Germany-LK Paderborn estimated R (using deaths) 26 Dec 02 Jan 09 Jan 16 Jan 23 Jan 0 1000 2000 3000 4000 cases doubling time [days] Germany-LK Paderborn doubling time cases (rolling mean) 0.0 61.9 123.8 185.6 daily change Germany-LK Paderborn new cases (rolling 7d mean) Germany-LK Paderborn new cases 0.000 0.619 1.238 1.856 daily change Germany-LK Paderborn new deaths (rolling 7d mean) Germany-LK Paderborn new deaths 0.00 0.24 0.48 0.72 0.96
In [4]:
overview(country="Germany", subregion="LK Paderborn");
In [5]:
compare_plot(country="Germany", subregion="LK Paderborn", dates="2020-03-15:");
2023-01-26T14:10:39.906721 image/svg+xml Matplotlib v3.6.3, 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 Paderborn LK Paderborn 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 Paderborn Bayern Berlin Bremen Hamburg Hessen Nordrhein-Westfalen Sachsen-Anhalt
In [6]:
# load the data
cases, deaths = germany_get_region(landkreis="LK Paderborn")

# get population of the region for future normalisation:
inhabitants = population(country="Germany", subregion="LK Paderborn")
print(f'Population of country="Germany", subregion="LK Paderborn": {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 Paderborn": 309380 people
Out[6]:
total cases daily new cases total deaths daily new deaths
date
2023-01-25 120840 31 254 0
2023-01-24 120809 49 254 0
2023-01-23 120760 43 254 0
2023-01-20 120717 21 254 0
2023-01-19 120696 24 254 0
2023-01-18 120672 30 254 0
2023-01-17 120642 43 254 0
2023-01-16 120599 33 254 1
2023-01-13 120566 21 253 0
2023-01-12 120545 72 253 0
2023-01-11 120473 24 253 0
2023-01-10 120449 54 253 0
2023-01-09 120395 93 253 0
2023-01-06 120302 71 253 1
2023-01-05 120231 93 252 1
2023-01-04 120138 80 251 0
2023-01-03 120058 98 251 0
2023-01-02 119960 113 251 0
2022-12-30 119847 56 251 0
2022-12-29 119791 126 251 2
2022-12-28 119665 135 249 0
2022-12-27 119530 216 249 0
2022-12-23 119314 101 249 0
2022-12-22 119213 240 249 0
2022-12-21 118973 161 249 2
2022-12-20 118812 145 247 1
2022-12-19 118667 139 246 0
2022-12-17 118528 64 246 0
2022-12-16 118464 121 246 0
2022-12-15 118343 93 246 0
2022-12-14 118250 128 246 1
2022-12-13 118122 171 245 0
2022-12-12 117951 149 245 0
2022-12-10 117802 50 245 0
2022-12-09 117752 50 245 1
2022-12-08 117702 178 244 1
2022-12-07 117524 130 243 0
2022-12-06 117394 144 243 1
2022-12-05 117250 115 242 0
2022-12-03 117135 59 242 0
2022-12-02 117076 148 242 0
2022-12-01 116928 69 242 0
2022-11-30 116859 184 242 0
2022-11-29 116675 131 242 0
2022-11-28 116544 97 242 1
2022-11-26 116447 123 241 0
2022-11-25 116324 87 241 0
2022-11-24 116237 105 241 0
2022-11-23 116132 207 241 0
2022-11-22 115925 149 241 0
2022-11-21 115776 187 241 2
2022-11-18 115589 86 239 0
2022-11-17 115503 112 239 0
2022-11-16 115391 118 239 0
2022-11-15 115273 150 239 0
2022-11-14 115123 124 239 0
2022-11-12 114999 68 239 0
2022-11-11 114931 170 239 1
2022-11-10 114761 107 238 0
2022-11-09 114654 254 238 0
2022-11-08 114400 184 238 1
2022-11-07 114216 171 237 0
2022-11-05 114045 139 237 0
2022-11-04 113906 242 237 1
2022-11-03 113664 284 236 0
2022-11-02 113380 331 236 0
2022-10-31 113049 356 236 0
2022-10-29 112693 128 236 0
2022-10-28 112565 195 236 0
2022-10-27 112370 400 236 0
2022-10-26 111970 305 236 1
2022-10-25 111665 319 235 0
2022-10-24 111346 269 235 1
2022-10-22 111077 197 234 0
2022-10-21 110880 327 234 0
2022-10-20 110553 206 234 0
2022-10-19 110347 459 234 2
2022-10-18 109888 358 232 0
2022-10-17 109530 336 232 0
2022-10-15 109194 71 232 0
2022-10-14 109123 362 232 0
2022-10-13 108761 526 232 0
2022-10-12 108235 170 232 0
2022-10-11 108065 426 232 0
2022-10-10 107639 136 232 0
2022-10-08 107503 211 232 0
2022-10-07 107292 374 232 0
2022-10-06 106918 281 232 0
2022-10-05 106637 468 232 0
2022-10-04 106169 140 232 0
2022-10-01 106029 114 232 0
2022-09-30 105915 168 232 0
2022-09-29 105747 85 232 0
2022-09-28 105662 293 232 0
2022-09-27 105369 162 232 0
2022-09-26 105207 203 232 0
2022-09-23 105004 125 232 0
2022-09-22 104879 82 232 0
2022-09-21 104797 83 232 0
2022-09-20 104714 120 232 0
2022-09-19 104594 125 232 0
2022-09-17 104469 26 232 0
2022-09-16 104443 40 232 0
2022-09-15 104403 144 232 0
2022-09-14 104259 126 232 0
2022-09-13 104133 96 232 0
2022-09-12 104037 100 232 0
2022-09-10 103937 73 232 0
2022-09-09 103864 47 232 0
2022-09-08 103817 157 232 0
2022-09-07 103660 106 232 0
2022-09-06 103554 161 232 0
2022-09-05 103393 55 232 0
2022-09-03 103338 63 232 0
2022-09-02 103275 121 232 0
2022-09-01 103154 85 232 0
2022-08-31 103069 234 232 1
2022-08-30 102835 130 231 0
2022-08-29 102705 196 231 1
2022-08-27 102509 89 230 0
2022-08-26 102420 110 230 0
2022-08-25 102310 200 230 0
2022-08-24 102110 154 230 0
2022-08-23 101956 191 230 0
2022-08-22 101765 196 230 0
2022-08-20 101569 114 230 0
2022-08-19 101455 242 230 0
2022-08-18 101213 162 230 0
2022-08-17 101051 372 230 0
2022-08-16 100679 235 230 0
2022-08-15 100444 336 230 1
2022-08-13 100108 48 229 0
2022-08-12 100060 289 229 0
2022-08-11 99771 212 229 0
2022-08-10 99559 519 229 0
2022-08-09 99040 235 229 0
2022-08-08 98805 347 229 0
2022-08-06 98458 152 229 0
2022-08-05 98306 275 229 0
2022-08-04 98031 490 229 0
2022-08-03 97541 323 229 0
2022-08-02 97218 289 229 1
2022-08-01 96929 207 228 1
2022-07-30 96722 188 227 0
2022-07-29 96534 118 227 1
2022-07-28 96416 212 226 1
2022-07-27 96204 418 225 0
2022-07-26 95786 278 225 0
2022-07-25 95508 318 225 0
2022-07-23 95190 126 225 0
2022-07-22 95064 223 225 0
2022-07-21 94841 460 225 0
2022-07-20 94381 271 225 0
2022-07-19 94110 381 225 0
2022-07-18 93729 365 225 1
2022-07-16 93364 129 224 0
2022-07-15 93235 370 224 0
2022-07-14 92865 219 224 0
2022-07-13 92646 504 224 1
2022-07-12 92142 273 223 0
2022-07-11 91869 370 223 0
2022-07-09 91499 120 223 0
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2022-07-07 91232 432 223 0
2022-07-06 90800 349 223 0
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2022-06-26 87018 1 223 0
2022-06-25 87017 163 223 0
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