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Call audit_cols_minimal() within your audit() methods for the output of consistency test mapper functions such as grim_map(). It will create a tibble with the three minimal, required columns:

  1. incons_cases counts the inconsistent cases, i.e., the number of rows in the mapper's output where "consistency" is FALSE.

  2. all_cases is the total number of rows in the mapper's output.

  3. incons_rate is the ratio of incons_cases to all_cases.

You can still add other columns to this tibble. Either way, make sure to name your method correctly. See examples.


audit_cols_minimal(data, name_test)



Data frame returned by a mapper function, such as grim_map().


String (length 1). Short, plain-text name of the consistency test, such as "GRIM". Only needed for a potential alert.


A tibble (data frame) with the columns listed above.

See also

For context, see vignette("consistency-tests-in-depth"). In case you don't call audit_cols_minimal(), you should call check_audit_special().


# For a mapper function called `schlim_map()`
# that applies a test called SCHLIM and returns
# a data frame with the `"scr_schlim_map"` class:
audit.scr_schlim_map <- function(data) {
  audit_cols_minimal(data, name_test = "SCHLIM")

# If you like, add other summary columns
# with `dplyr::mutate()` or similar.