assertr: assertr: Assertive programming for R analysis pipeline.

In lorenzwalthert/assertr: Assertive Programming for R Analysis Pipelines

Description

The assertr package supplies a suite of functions designed to verify assumptions about data early in an analysis pipeline.

Details

See the assertr vignette or the documentation for more information
> vignette("assertr")

You may also want to read the documentation for the function that assertr provides:

• assert

• verify

• insist

• assert_rows

• insist_rows

• not_na

• in_set

• num_row_NAs

• maha_dist

• within_bounds

• within_n_sds

• within_n_mads

Examples

library(magrittr)     # for the piping operator
library(dplyr)

# this confirms that
  # - that the dataset contains more than 10 observations
  # - that the column for 'miles per gallon' (mpg) is a positive number
  # - that the column for 'miles per gallon' (mpg) does not contain a datum
  #   that is outside 4 standard deviations from its mean, and
  # - that the am and vs columns (automatic/manual and v/straight engine,
  #    respectively) contain 0s and 1s only
  # - each row contains at most 2 NAs
  # - each row's mahalanobis distance is within 10 median absolute deviations of
  #   all the distance (for outlier detection)

mtcars %>%
  verify(nrow(.) > 10) %>%
  verify(mpg > 0) %>%
  insist(within_n_sds(4), mpg) %>%
  assert(in_set(0,1), am, vs) %>%
  assert_rows(num_row_NAs, within_bounds(0,2), everything()) %>%
  insist_rows(maha_dist, within_n_mads(10), everything()) %>%
  group_by(cyl) %>%
  summarise(avg.mpg=mean(mpg))

lorenzwalthert/assertr documentation built on May 20, 2019, 4:06 p.m.