Hungary: Nógrád¶

  • Homepage of project: https://oscovida.github.io
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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="Nógrád", weeks=5);
2023-03-07T16:42:05.466964 image/svg+xml Matplotlib v3.7.1, https://matplotlib.org/ 21 Nov 28 Nov 05 Dec 12 Dec 19 Dec 60 60 80 80 7-day incidence rate Nógrád, Hungary, last 5 weeks, last data point from 2022-12-21 21 Nov 28 Nov 05 Dec 12 Dec 19 Dec 0 0 20 20 40 40 60 60 80 80 daily change Hungary-Nógrád new cases (rolling 7d mean) Hungary-Nógrád 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 0.75 0.75 1.00 1.00 1.25 1.25 1.50 1.50 1.75 1.75 R & growth factor (based on cases) Hungary-Nógrád cases daily growth factor Hungary-Nógrád cases daily growth factor (rolling mean) Hungary-Nógrád 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 2000 2000 4000 4000 cases doubling time [days]
In [4]:
overview(country="Hungary", region="Nógrád");
2023-03-07T16:42:10.093530 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 94.0 Nógrád, 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 0 200 200 400 400 600 600 800 800 daily change Hungary-Nógrád new cases (rolling 7d mean) Hungary-Nógrád 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 0.75 0.75 1.00 1.00 1.25 1.25 1.50 1.50 1.75 1.75 R & growth factor (based on cases) Hungary-Nógrád cases daily growth factor Hungary-Nógrád cases daily growth factor (rolling mean) Hungary-Nógrád 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 5000 5000 10000 10000 15000 15000 20000 20000 cases doubling time [days]
In [5]:
compare_plot(country="Hungary", region="Nógrád");

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

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="Nógrád")

# get population of the region for future normalisation:
inhabitants = population(country="Hungary", region="Nógrád")
print(f'Population of country="Hungary", region="Nógrád": {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="Nógrád": None people
Out[6]:
total cases daily new cases
Dátum
2022-12-21 46441 94
2022-12-14 46347 79
2022-12-07 46268 92
2022-11-30 46176 76
2022-11-23 46100 44
2022-11-16 46056 50
2022-11-09 46006 158
2022-10-26 45848 146
2022-10-19 45702 163
2022-10-12 45539 206
2022-10-05 45333 212
2022-09-28 45121 167
2022-09-21 44954 252
2022-09-14 44702 218
2022-09-07 44484 231
2022-08-31 44253 311
2022-08-24 43942 406
2022-08-17 43536 353
2022-08-10 43183 344
2022-08-03 42839 367
2022-07-27 42472 298
2022-07-20 42174 110
2022-07-13 42064 79
2022-07-06 41985 56
2022-06-29 41929 44
2022-06-22 41885 14
2022-06-15 41871 45
2022-06-08 41826 41
2022-06-01 41785 39
2022-05-25 41746 50
2022-05-18 41696 82
2022-05-11 41614 112
2022-05-02 41502 54
2022-04-28 41448 23
2022-04-27 41425 60
2022-04-26 41365 25
2022-04-25 41340 49
2022-04-22 41291 44
2022-04-21 41247 38
2022-04-20 41209 11
2022-04-19 41198 60
2022-04-14 41138 36
2022-04-13 41102 35
2022-04-12 41067 17
2022-04-11 41050 88
2022-04-08 40962 75
2022-04-06 40887 37
2022-04-05 40850 95
2022-04-01 40755 35
2022-03-31 40720 43
2022-03-30 40677 35
2022-03-29 40642 23
2022-03-28 40619 92
2022-03-25 40527 29
2022-03-24 40498 37
2022-03-23 40461 36
2022-03-22 40425 18
2022-03-21 40407 86
2022-03-18 40321 55
2022-03-17 40266 29
2022-03-16 40237 112
2022-03-11 40125 48
2022-03-10 40077 57
2022-03-09 40020 48
2022-03-08 39972 26
2022-03-07 39946 140
2022-03-04 39806 53
2022-03-03 39753 71
2022-03-02 39682 96
2022-03-01 39586 37
2022-02-28 39549 192
2022-02-25 39357 108
2022-02-24 39249 147
2022-02-23 39102 155
2022-02-22 38947 40
2022-02-21 38907 296
2022-02-18 38611 191
2022-02-17 38420 224
2022-02-16 38196 250
2022-02-15 37946 50
2022-02-14 37896 492
2022-02-11 37404 248
2022-02-10 37156 291
2022-02-09 36865 358
2022-02-08 36507 73
2022-02-07 36434 771
2022-02-04 35663 404
2022-02-03 35259 416
2022-02-02 34843 384
2022-02-01 34459 141
2022-01-31 34318 866
2022-01-28 33452 355
2022-01-27 33097 336
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2022-01-25 32486 89
2022-01-24 32397 697
2022-01-21 31700 267
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2022-01-17 30888 250
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2022-01-07 29948 112
2022-01-06 29836 132
2022-01-05 29704 98
2022-01-04 29606 39
2022-01-03 29567 120
2021-12-31 29447 57
2021-12-30 29390 73
2021-12-29 29317 59
2021-12-28 29258 21
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2021-12-23 29105 90
2021-12-22 29015 77
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2021-12-13 28316 306
2021-12-10 28010 151
2021-12-09 27859 157
2021-12-08 27702 203
2021-12-07 27499 67
2021-12-06 27432 533
2021-12-03 26899 151
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2020-04-27 23 0
2020-04-26 23 0
2020-04-25 23 0
2020-04-24 23 0
2020-04-23 23 0
2020-04-22 23 0
2020-04-21 23 1
2020-04-20 22 0
2020-04-19 22 2
2020-04-18 20 0
2020-04-17 20 1
2020-04-16 19 0
2020-04-15 19 0
2020-04-14 19 0
2020-04-13 19 1
2020-04-12 18 1
2020-04-11 17 5
2020-04-10 12 0
2020-04-09 12 0
2020-04-08 12 1
2020-04-07 11 1
2020-04-06 10 0
2020-04-05 10 2
2020-04-04 8 1
2020-04-03 7 1
2020-04-02 6 1
2020-04-01 5 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: 0:00:09.901218