check_cols_empty: Check for empty columns

In Sage-Bionetworks/dccvalidator: Metadata Validation for Data Coordinating Centers

Check for empty columns

Description

Check for empty columns in the data and warn (or fail) if present. The function takes in a list of required column names that are not tested for emptiness. This is due to the existing function check_cols_complete(), which ensures that the required columns are complete. By ignoring the required columns in check_cols_empty(), there are no duplicated results for the same column in the event that a required column was also empty.

Usage

check_cols_empty(
  data,
  empty_values = c(NA, ""),
  required_cols = NULL,
  strict = FALSE,
  success_msg = "No columns are empty",
  fail_msg = "Some columns are completely empty"
)

Arguments

data	Data to check
empty_values	Values that are considered empty. Defaults to NA and "".
required_cols	A character vector of the required columns to check for completeness.
strict	If FALSE, return a "check_warn" object; if TRUE, return a "check_fail" object
success_msg	Message indicating the check succeeded.
fail_msg	Message indicating the check failed.

Value

A condition object indicating whether the data contains columns that are empty.

Examples

dat <- data.frame(specimenID = c("x", "y"), organ = c(NA, NA))
check_cols_empty(dat)

Sage-Bionetworks/dccvalidator documentation built on May 7, 2022, 10:32 a.m.