Apply Labels

Apply Labels

apply_labels(
  data,
  dict,
  from = "value",
  to = "value_label",
  by = "variable",
  names_from = "variable",
  names_to = "variable_label",
  dataset_name = NULL,
  ...
)

Arguments

data	dataset to apply labeling on.
dict	dictionary to use for application of labeling.
from	a column name or position defining words or keys to be replaced
to	a column name or position defining replacement values
by	character or integer - which column in dict defines the columns in data corresponding to each section of the dict. Defaults to "variable".
names_from	column name or position defining where to match names from. Defaults to "variable".
names_to	column name or position defining replacements for names(data). Defaults to "variable_label".
dataset_name	(optional) name of dataset to filter dict by
...	Passed to match_df

Value

a labelled, display friendly tibble

Examples

dictionary <- data.frame(
  var = c(rep("x1", 2),
          rep("x2", 3),
          rep("x3", 5)),
  var_lab = c(rep("Column 1", 2),
              rep("Column 2", 3),
              rep("Column 3", 5)),
  val = c(c(TRUE, FALSE),
          c(1:3),
          letters[1:5]),
  val_lab = c(c("YES", "NO"),
              paste0("Group ", c(1:3)),
              paste0("Area ", LETTERS[1:5]))
)

dat <- data.frame(
  "x1" = rep(c(TRUE, FALSE), 15),
  "x2" = rep(c(1:3), 10),
  "x3" = rep(letters[1:5], 6)
)

apply_labels(dat,
             dictionary,
             from = "val",
             to = "val_lab",
             by = "var",
             names_from = "var",
             names_to = "var_lab")
#>    Column 1 Column 2 Column 3
#> 1       YES  Group 1   Area A
#> 2        NO  Group 2   Area B
#> 3       YES  Group 3   Area C
#> 4        NO  Group 1   Area D
#> 5       YES  Group 2   Area E
#> 6        NO  Group 3   Area A
#> 7       YES  Group 1   Area B
#> 8        NO  Group 2   Area C
#> 9       YES  Group 3   Area D
#> 10       NO  Group 1   Area E
#> 11      YES  Group 2   Area A
#> 12       NO  Group 3   Area B
#> 13      YES  Group 1   Area C
#> 14       NO  Group 2   Area D
#> 15      YES  Group 3   Area E
#> 16       NO  Group 1   Area A
#> 17      YES  Group 2   Area B
#> 18       NO  Group 3   Area C
#> 19      YES  Group 1   Area D
#> 20       NO  Group 2   Area E
#> 21      YES  Group 3   Area A
#> 22       NO  Group 1   Area B
#> 23      YES  Group 2   Area C
#> 24       NO  Group 3   Area D
#> 25      YES  Group 1   Area E
#> 26       NO  Group 2   Area A
#> 27      YES  Group 3   Area B
#> 28       NO  Group 1   Area C
#> 29      YES  Group 2   Area D
#> 30       NO  Group 3   Area E