R/check_any_lab_atts.R

In labelr: Label Data Frames, Variables, and Values

#' Check Whether Data Frame Has Any labelr Attributes
#'
#' @description
#' `check_any_lab_atts` returns FALSE if your data.frame has no labelr-generated
#' meta-data attributes (still) associated with it (at all or of a specific
#' sub-type), and TRUE if it does.
#'
#' @details
#' By default (labs = "any"), this function looks to see if your data.frame's
#' attributes includes any attribute with a name containing the substring
#' "frame.lab", "name.labs", "val.labs", and/or "factor." These are the core
#' substrings of the label meta-data attributes that labelr creates and
#' manipulates. If you wish to narrow your search for a specific labelr,
#' attribute, you may supply this as a character (sub)string (e.g.,
#' check_any_lab_atts(df, "val.labs.cyl") to see if the variable "cyl"
#' has variable value label meta-data). But make sure that your second argument
#' is meaningful (e.g., check_any_lab_atts(iris, "row.") will return TRUE
#' true based on the presence of a standard "row.names" attribute, which has
#' nothing to do with labels.
#'
#' @param data the data.frame you are checking for the presence (or absence)
#' of labelr meta-data.
#' @param labs which label meta-data you are looking for. Default of "any"
#' will look for types "frame.lab", "name.labs", "val.labs", and "factor."
#' (period is part of the substring), which are the core labelr meta-data.
#' To search more narrowly, you can try things like labs = "val.labs",
#' labs="name.labs", etc.
#' @return TRUE if any instance of the default or user-specified meta-data
#' attribute is found, FALSE if not.
#' @export
#' @examples
#' # make toy demographic (gender, raceth, etc.) data set
#' set.seed(555)
#' df <- make_demo_data(n = 1000) # another labelr:: function
#' # let's add variable VALUE labels for variable "raceth"
#' df <- add_val_labs(df,
#'   vars = "raceth", vals = c(1:7),
#'   labs = c("White", "Black", "Hispanic", "Asian", "AIAN", "Multi", "Other"),
#'   max.unique.vals = 50
#' )
#'
#' check_any_lab_atts(df)
check_any_lab_atts <- function(data, labs = "any") {
  all_labs <- c("name.labs", "val.labs", "factor.", "frame.lab")
  if (labs == "any") labs <- all_labs

  lab_atts <- FALSE
  for (i in seq_along(labs)) {
    this_att <- labs[i]
    lab_atts[i] <- any(grepl(this_att, names(attributes(data))))
  }

  labs_check_res <- any(lab_atts)
  return(labs_check_res)
}