R/assertr.R

In lorenzwalthert/assertr: Assertive Programming for R Analysis Pipelines

#' assertr: Assertive programming for R analysis pipeline.
#'
#' The assertr package supplies a suite of functions designed to verify
#' assumptions about data early in an analysis pipeline.
#'
#' See the assertr vignette or the documentation for more information \cr
#' > \code{vignette("assertr")}
#'
#' You may also want to read the documentation for the function that
#' \code{assertr} provides:
#' \itemize{
#'   \item \code{\link{assert}}
#'   \item \code{\link{verify}}
#'   \item \code{\link{insist}}
#'   \item \code{\link{assert_rows}}
#'   \item \code{\link{insist_rows}}
#'   \item \code{\link{not_na}}
#'   \item \code{\link{in_set}}
#'   \item \code{\link{num_row_NAs}}
#'   \item \code{\link{maha_dist}}
#'   \item \code{\link{within_bounds}}
#'   \item \code{\link{within_n_sds}}
#'   \item \code{\link{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))
#'
#'
#' @docType package
#' @name assertr
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