Easy data validation with the validate package

By mark

The validate package is our attempt to make checking data against domain knowledge as easy as possible. Here is an example.

library(magrittr)
library(validate)

iris %>% check_that(
  Sepal.Width > 0.5 * Sepal.Length
  , mean(Sepal.Width) > 0
  , if ( Sepal.Width > 0.5*Sepal.Length) Sepal.Length > 10
) %>% summary()

#  rule items passes fails nNA error warning                                              expression
# 1   V1   150     66    84   0 FALSE   FALSE                        Sepal.Width > 0.5 * Sepal.Length
# 2   V2     1      1     0   0 FALSE   FALSE                                   mean(Sepal.Width) > 0
# 3   V3   150     84    66   0 FALSE   FALSE !(Sepal.Width > 0.5 * Sepal.Length) | Sepal.Length > 10

The summary gives an overview of the number of items checked. For an aggregated test, such as the one where we test the mean of a variable only one item is tested: the whole Sepal.Width column. The other rules are tested on each record in iris. Furthermore the number of items that pass, fail …read more

Source:: r-bloggers.com