as_character(x, ...)

to_character(x, ...)

## S3 method for class 'data.frame'
as_character(
  x,
  ...,
  add.non.labelled = FALSE,
  prefix = FALSE,
  var.label = NULL,
  drop.na = TRUE,
  drop.levels = FALSE,
  keep.labels = FALSE
)

as_label(x, ...)

to_label(x, ...)

## S3 method for class 'data.frame'
as_label(
  x,
  ...,
  add.non.labelled = FALSE,
  prefix = FALSE,
  var.label = NULL,
  drop.na = TRUE,
  drop.levels = FALSE,
  keep.labels = FALSE
)

data(efc)
print(get_labels(efc)['c161sex'])
head(efc$c161sex)
head(as_label(efc$c161sex))

print(get_labels(efc)['e42dep'])
table(efc$e42dep)
table(as_label(efc$e42dep))

head(efc$e42dep)
head(as_label(efc$e42dep))

# structure of numeric values won't be changed
# by this function, it only applies to labelled vectors
# (typically categorical or factor variables)

str(efc$e17age)
str(as_label(efc$e17age))


# factor with non-numeric levels
as_label(factor(c("a", "b", "c")))

# factor with non-numeric levels, prefixed
x <- factor(c("a", "b", "c"))
x <- set_labels(x, labels = c("ape", "bear", "cat"))
as_label(x, prefix = TRUE)


# create vector
x <- c(1, 2, 3, 2, 4, NA)
# add less labels than values
x <- set_labels(
  x,
  labels = c("yes", "maybe", "no"),
  force.labels = FALSE,
  force.values = FALSE
)

# convert to label w/o non-labelled values
as_label(x)

# convert to label, including non-labelled values
as_label(x, add.non.labelled = TRUE)


# create labelled integer, with missing flag
if (require("haven")) {
  x <- labelled(
    c(1:3, tagged_na("a", "c", "z"), 4:1, 2:3),
    c("Agreement" = 1, "Disagreement" = 4, "First" = tagged_na("c"),
      "Refused" = tagged_na("a"), "Not home" = tagged_na("z"))
  )

  # to labelled factor, with missing labels
  as_label(x, drop.na = FALSE)

  # to labelled factor, missings removed
  as_label(x, drop.na = TRUE)

  # keep missings, and use non-labelled values as well
  as_label(x, add.non.labelled = TRUE, drop.na = FALSE)
}

# convert labelled character to factor
dummy <- c("M", "F", "F", "X")
dummy <- set_labels(
  dummy,
  labels = c(`M` = "Male", `F` = "Female", `X` = "Refused")
)
get_labels(dummy,, "p")
as_label(dummy)

# drop unused factor levels, but preserve variable label
x <- factor(c("a", "b", "c"), levels = c("a", "b", "c", "d"))
x <- set_labels(x, labels = c("ape", "bear", "cat"))
set_label(x) <- "A factor!"
x
as_label(x, drop.levels = TRUE)

# change variable label
as_label(x, var.label = "New variable label!", drop.levels = TRUE)


# convert to numeric and back again, preserving label attributes
# *and* values in numeric vector
x <- c(0, 1, 0, 4)
x <- set_labels(x, labels = c(`null` = 0, `one` = 1, `four` = 4))

# to factor
as_label(x)

# to factor, back to numeric - values are 1, 2 and 3,
# instead of original 0, 1 and 4
as_numeric(as_label(x))

# preserve label-attributes when converting to factor, use these attributes
# to restore original numeric values when converting back to numeric
as_numeric(as_label(x, keep.labels = TRUE), use.labels = TRUE)


# easily coerce specific variables in a data frame to factor
# and keep other variables, with their class preserved
as_label(efc, e42dep, e16sex, c172code)