checkDataQuality: checkDataQuality

In dataQualityR: Performs variable level data quality checks and generates summary statistics

Description

The function takes in a data frame object, runs data quality checks on each variable, generates summary statistics, and outputs two csv files containing the data quality report – one for numeric variables and the other for categorical variables

Usage

checkDataQuality(data,  
				 out.file.num, 
				 out.file.cat,
				 numeric.cutoff = -1)

Arguments

data	An object of class data.frame
out.file.num	Filename for saving data quality report of numeric variables
out.file.cat	Filename for saving data quality report of categoric variables
numeric.cutoff	The minimum number of unique values needed for a numeric variable to be treated as continous. This feature is included to account for binary or multi-category variables, with small number of unique values, which are stored as numeric. Default is -1 which does not place any cut-off and all numeric variables are treated as continuous

Value

Returns csv files stored directly on disk

Author(s)

Madhav Kumar and Shreyes Upadhyay

Examples

data(crx)
num.file <- paste(tempdir(), "/dq_num.csv", sep= "")
cat.file <- paste(tempdir(), "/dq_cat.csv", sep= "")
checkDataQuality(data= crx, out.file.num= num.file, out.file.cat= cat.file)

dataQualityR documentation built on May 2, 2019, 11:12 a.m.