Hungary: Pest¶

  • Homepage of project: https://oscovida.github.io
  • Plots are explained at http://oscovida.github.io/plots.html
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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 16:42:02 CEST
In [2]:
%config InlineBackend.figure_formats = ['svg']
from oscovida import *
In [3]:
overview(country="Hungary", region="Pest", weeks=5);
2023-03-07T16:42:05.957165 image/svg+xml Matplotlib v3.7.1, https://matplotlib.org/ 21 Nov 28 Nov 05 Dec 12 Dec 19 Dec 600 600 700 700 800 800 7-day incidence rate Pest, Hungary, last 5 weeks, last data point from 2022-12-21 21 Nov 28 Nov 05 Dec 12 Dec 19 Dec 0 0 200 200 400 400 600 600 800 800 daily change Hungary-Pest new cases (rolling 7d mean) Hungary-Pest new cases 21 Nov 28 Nov 05 Dec 12 Dec 19 Dec No data available to plot daily change in deaths 21 Nov 28 Nov 05 Dec 12 Dec 19 Dec 0.8 0.8 1.0 1.0 1.2 1.2 1.4 1.4 R & growth factor (based on cases) Hungary-Pest cases daily growth factor Hungary-Pest cases daily growth factor (rolling mean) Hungary-Pest estimated R (using cases) 21 Nov 28 Nov 05 Dec 12 Dec 19 Dec No data available to plot R & growth factor (based on deaths) 21 Nov 28 Nov 05 Dec 12 Dec 19 Dec 0 0 1000 1000 2000 2000 3000 3000 cases doubling time [days]
In [4]:
overview(country="Hungary", region="Pest");
2023-03-07T16:42:10.349713 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 5000 5000 10000 10000 15000 15000 7-day incidence rate 779.0 Pest, Hungary, last data point from 2022-12-21 May 20 Sep 20 Jan 21 May 21 Sep 21 Jan 22 May 22 Sep 22 Jan 23 0 0 2000 2000 4000 4000 6000 6000 daily change Hungary-Pest new cases (rolling 7d mean) Hungary-Pest new cases May 20 Sep 20 Jan 21 May 21 Sep 21 Jan 22 May 22 Sep 22 Jan 23 No data available to plot daily change in deaths 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) Hungary-Pest cases daily growth factor Hungary-Pest cases daily growth factor (rolling mean) Hungary-Pest estimated R (using cases) May 20 Sep 20 Jan 21 May 21 Sep 21 Jan 22 May 22 Sep 22 Jan 23 No data available to plot R & growth factor (based on deaths) May 20 Sep 20 Jan 21 May 21 Sep 21 Jan 22 May 22 Sep 22 Jan 23 0 0 10000 10000 20000 20000 30000 30000 cases doubling time [days]
In [5]:
compare_plot(country="Hungary", region="Pest");

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
Cell In[5], line 1
----> 1 compare_plot(country="Hungary", region="Pest");

File /tank/oscovida/work/oscovida.github.io/oscovida.github.io/.venv/lib/python3.9/site-packages/oscovida/oscovida.py:1976, in compare_plot(country, region, subregion, savefig, normalise, dates, align)
   1974 if normalise:
   1975     _population = population(country=country, region=region, subregion=subregion)
-> 1976     c *= 100000 / _population
   1977     d *= 100000 / _population
   1979 if not subregion and not region:    # i.e. not a region of Germany

TypeError: unsupported operand type(s) for /: 'int' and 'NoneType'
In [6]:
# load the data
cases, deaths = get_region_hungary(county="Pest")

# get population of the region for future normalisation:
inhabitants = population(country="Hungary", region="Pest")
print(f'Population of country="Hungary", region="Pest": {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="Hungary", region="Pest": None people
Out[6]:
total cases daily new cases
Dátum
2022-12-21 292300 779
2022-12-14 291521 796
2022-12-07 290725 762
2022-11-30 289963 586
2022-11-23 289377 534
2022-11-16 288843 543
2022-11-09 288300 1398
2022-10-26 286902 1101
2022-10-19 285801 1381
2022-10-12 284420 1457
2022-10-05 282963 1320
2022-09-28 281643 1104
2022-09-21 280539 1218
2022-09-14 279321 1173
2022-09-07 278148 1106
2022-08-31 277042 1343
2022-08-24 275699 1498
2022-08-17 274201 1718
2022-08-10 272483 2141
2022-08-03 270342 2880
2022-07-27 267462 1830
2022-07-20 265632 1448
2022-07-13 264184 1221
2022-07-06 262963 743
2022-06-29 262220 520
2022-06-22 261700 303
2022-06-15 261397 234
2022-06-08 261163 235
2022-06-01 260928 278
2022-05-25 260650 459
2022-05-18 260191 688
2022-05-11 259503 926
2022-05-02 258577 536
2022-04-28 258041 259
2022-04-27 257782 324
2022-04-26 257458 160
2022-04-25 257298 504
2022-04-22 256794 300
2022-04-21 256494 449
2022-04-20 256045 177
2022-04-19 255868 768
2022-04-14 255100 316
2022-04-13 254784 371
2022-04-12 254413 219
2022-04-11 254194 591
2022-04-08 253603 646
2022-04-06 252957 393
2022-04-05 252564 720
2022-04-01 251844 291
2022-03-31 251553 311
2022-03-30 251242 416
2022-03-29 250826 173
2022-03-28 250653 653
2022-03-25 250000 310
2022-03-24 249690 297
2022-03-23 249393 369
2022-03-22 249024 176
2022-03-21 248848 628
2022-03-18 248220 393
2022-03-17 247827 151
2022-03-16 247676 555
2022-03-11 247121 237
2022-03-10 246884 270
2022-03-09 246614 296
2022-03-08 246318 125
2022-03-07 246193 644
2022-03-04 245549 268
2022-03-03 245281 484
2022-03-02 244797 356
2022-03-01 244441 205
2022-02-28 244236 987
2022-02-25 243249 457
2022-02-24 242792 544
2022-02-23 242248 693
2022-02-22 241555 279
2022-02-21 241276 1436
2022-02-18 239840 711
2022-02-17 239129 900
2022-02-16 238229 1007
2022-02-15 237222 481
2022-02-14 236741 2339
2022-02-11 234402 1220
2022-02-10 233182 1573
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2022-02-08 229836 889
2022-02-07 228947 4016
2022-02-04 224931 1967
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2022-02-02 220749 2729
2022-02-01 218020 1199
2022-01-31 216821 5879
2022-01-28 210942 2297
2022-01-27 208645 2698
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2022-01-25 202605 1339
2022-01-24 201266 6382
2022-01-21 194884 2480
2022-01-20 192404 2641
2022-01-19 189763 2976
2022-01-18 186787 1293
2022-01-17 185494 3733
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2022-01-12 178336 1575
2022-01-11 176761 591
2022-01-10 176170 2302
2022-01-07 173868 1060
2022-01-06 172808 1049
2022-01-05 171759 837
2022-01-04 170922 337
2022-01-03 170585 774
2021-12-31 169811 466
2021-12-30 169345 504
2021-12-29 168841 435
2021-12-28 168406 148
2021-12-27 168258 1029
2021-12-23 167229 519
2021-12-22 166710 516
2021-12-21 166194 262
2021-12-20 165932 1374
2021-12-17 164558 546
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2021-11-09 126579 656
2021-11-08 125923 1956
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2020-06-04 567 4
2020-06-03 563 0
2020-06-02 563 9
2020-06-01 554 2
2020-05-31 552 2
2020-05-30 550 3
2020-05-29 547 6
2020-05-28 541 6
2020-05-27 535 4
2020-05-26 531 4
2020-05-25 527 2
2020-05-24 525 9
2020-05-23 516 6
2020-05-22 510 10
2020-05-21 500 4
2020-05-20 496 10
2020-05-19 486 10
2020-05-18 476 3
2020-05-17 473 6
2020-05-16 467 7
2020-05-15 460 1
2020-05-14 459 3
2020-05-13 456 11
2020-05-12 445 7
2020-05-11 438 4
2020-05-10 434 10
2020-05-09 424 4
2020-05-08 420 6
2020-05-07 414 4
2020-05-06 410 8
2020-05-05 402 1
2020-05-04 401 1
2020-05-03 400 6
2020-05-02 394 14
2020-05-01 380 5
2020-04-30 375 7
2020-04-29 368 10
2020-04-28 358 6
2020-04-27 352 2
2020-04-26 350 11
2020-04-25 339 10
2020-04-24 329 12
2020-04-23 317 12
2020-04-22 305 12
2020-04-21 293 7
2020-04-20 286 8
2020-04-19 278 14
2020-04-18 264 5
2020-04-17 259 10
2020-04-16 249 15
2020-04-15 234 14
2020-04-14 220 6
2020-04-13 214 -1
2020-04-12 215 16
2020-04-11 199 5
2020-04-10 194 11
2020-04-09 183 19
2020-04-08 164 11
2020-04-07 153 11
2020-04-06 142 0
2020-04-05 142 8
2020-04-04 134 10
2020-04-03 124 2
2020-04-02 122 24
2020-04-01 98 9

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: 0:00:09.884974