rki-covid19csv-parser

A small python module to work with the RKI_Covid19.csv files issued by the German RKI (Robert Koch Institut) on a daily basis.

Installation:

pip install rki-covid19csv-parser

Usage:

First steps:

Initialize the parser and load data from the RKI_Covid19.csv file. Because of the daily increasing file size this process can take a while.

import rki_covid19csv_parser
  
covid_cases = rki_covid19csv_parser.covid_cases()

covid_cases.load_rki_csv('path/to/csv')

Speeding up the loading process:

Once you have loaded the csv file it's possible to save the processed data to a file. This can speed up the process of loading the data significantly if you whish to run your script more than once.

#save file.
covid_cases.save_toFile('desired/path')

#load file.
covid_cases.load_fromFile('path/to/saved/file')

Get the covid19 data:

Supported methods:

A description of the parameters can be found below.

method	description	returns
cumCases(date, region_id, date_type)	cumulated covid19 cases	Filter object
cumDeaths(date, region_id, date_type)	cumulated covid19 deaths	Filter object
newCases(date, region_id, date_type)	new covid19 cases	Filter object
newDeaths(date, region_id, date_type)	new covid19 deaths	Filter object
newCasesTimespan(date, region_id, date_type, timespan)	new covid19 cases in period	Filter object
newDeathsTimespan(date, region_id, date_type, timespan)	new covid19 deaths in period	Filter object
activeCases(date, region_id, date_type, days_infectious)	active covid19 cases	Filter object
sevenDayCaserate(date, region_id, date_type)	new covid19 cases in 7-days	Filter object
sevenDayIncidence(date, region_id, date_type)	new covid19 cases per 100k people in 7-days	Filter object
deathRate(date, region_id, days_infectious)	death rate (activeCases/newDeaths)	Filter object

Parameters:

parameter	type	description	example
date	str in iso-format, datetime.date obj, datetime.datetime obj	The desired date.	'2020-06-01 00:00:00'
region_id	str	A list of region-ids can be found here.	'0'
date_type	str	The date type to use. Meldedatum or Refdatum	'Meldedatum'
timespan	int	Number of last days to be included in calculation.	3
days_infectious	int	Number of days a case is considered as active.	14

Get your covid19 data in shape:

Each of the methods mentioned above returns an objct of the class Filter. You can use the following methods to get the data into your desired shape.

method	description	returns
values()	raw data	ndarray
by_cases(raw, decimals)	absolute number of cases	dict
by_age(frequency, decimals)	cases sorted into agegroups	dict
by_gender(frequency, decimals)	cases sorted by gender	dict
by_ageandgener(frequency, decimals)	cases sorted by age and gender	dict

parameter	input type	description	example
frequency	str	weather you want the absolute or relative number of cases	'absolute'
decimals	int	number of decimals	3
raw	bool	True to get raw values	True

Examples:

cases = covid_cases.cumCases(date='2021-04-29 00:00:00', region_id='01001', date_type='Meldedatum').by_gender(frequency='absolute')
print(cases)
>>> {'M': 1200, 'W': 1400, 'unbekannt': 130}

Example values!