rki-covid19csv-parser 1.0.2

A simple module to work with the RKI_COVID19.csv files issued by the Robert-Koch-Institut in Germany.

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
kumFälle(date, region_id, date_type)	cumulated covid19 cases	Filter object
kumTodesfälle(date, region_id, date_type)	cumulated covid19 deaths	Filter object
neueFälle(date, region_id, date_type)	new covid19 cases	Filter object
neueTodesfälle(date, region_id, date_type)	new covid19 deaths	Filter object
neueFälleZeitraum(date, region_id, date_type, timespan)	new covid19 cases in period	Filter object
neueTodesfälleZeitraum(date, region_id, date_type, timespan)	new covid19 deaths in period	Filter object

Parameters:

parameter	input type	description	example
date	str	The desired date in the iso format	'2020-06-01 00:00:00'
region_id	str	The region_id of the desired region. A list 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

Filter class:

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
by_cases()	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

Examples:

cases = covid_cases.kumFälle(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!