get_labels: Retrieve value labels of labelled data

In sjlabelled: Labelled Data Utility Functions

Retrieve value labels of labelled data

Description

This function returns the value labels of labelled data.

Usage

get_labels(
  x,
  attr.only = FALSE,
  values = NULL,
  non.labelled = FALSE,
  drop.na = TRUE,
  drop.unused = FALSE
)

Arguments

x	A data frame with variables that have value label attributes (e.g. from an imported SPSS, SAS or STATA data set, via read_spss, read_sas or read_stata); a variable (vector) with value label attributes; or a list of variables with values label attributes. If x has no label attributes, factor levels are returned. See 'Examples'.
attr.only	Logical, if TRUE, labels are only searched for in the the vector's attributes; else, if attr.only = FALSE and x has no label attributes, factor levels or string values are returned. See 'Examples'.
values	String, indicating whether the values associated with the value labels are returned as well. If values = "as.name" (or values = "n"), values are set as names attribute of the returned object. If values = "as.prefix" (or values = "p"), values are included as prefix to each label. See 'Examples'.
non.labelled	Logical, if TRUE, values without labels will also be included in the returned labels (see fill_labels).
drop.na	Logical, whether labels of tagged NA values (see tagged_na()) should be included in the return value or not. By default, labelled (tagged) missing values are not returned. See get_na for more details on tagged NA values.
drop.unused	Logical, if TRUE, unused labels will be removed from the return value.

Value

Either a list with all value labels from all variables if x is a data.frame or list; a string with the value labels, if x is a variable; or NULL if no value label attribute was found.

See Also

See vignette Labelled Data and the sjlabelled-Package for more details; set_labels to manually set value labels, get_label to get variable labels and get_values to retrieve the values associated with value labels.

Examples

# import SPSS data set
# mydat <- read_spss("my_spss_data.sav")

# retrieve variable labels
# mydat.var <- get_label(mydat)

# retrieve value labels
# mydat.val <- get_labels(mydat)

data(efc)
get_labels(efc$e42dep)

# simple barplot
barplot(table(efc$e42dep))
# get value labels to annotate barplot
barplot(table(efc$e42dep),
        names.arg = get_labels(efc$e42dep),
        main = get_label(efc$e42dep))

# include associated values
get_labels(efc$e42dep, values = "as.name")

# include associated values
get_labels(efc$e42dep, values = "as.prefix")

# get labels from multiple variables
get_labels(list(efc$e42dep, efc$e16sex, efc$e15relat))


# create a dummy factor
f1 <- factor(c("hi", "low", "mid"))
# search for label attributes only
get_labels(f1, attr.only = TRUE)
# search for factor levels as well
get_labels(f1)

# same for character vectors
c1 <- c("higher", "lower", "mid")
# search for label attributes only
get_labels(c1, attr.only = TRUE)
# search for string values as well
get_labels(c1)


# 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.values = FALSE)
# get labels for labelled values only
get_labels(x)
# get labels for all values
get_labels(x, non.labelled = TRUE)


# get labels, including tagged NA values
library(haven)
x <- labelled(c(1:3, tagged_na("a", "c", "z"), 4:1),
              c("Agreement" = 1, "Disagreement" = 4, "First" = tagged_na("c"),
                "Refused" = tagged_na("a"), "Not home" = tagged_na("z")))
# get current NA values
x
get_labels(x, values = "n", drop.na = FALSE)


# create vector with unused labels
data(efc)
efc$e42dep <- set_labels(
  efc$e42dep,
  labels = c("independent" = 1, "dependent" = 4, "not used" = 5)
)
get_labels(efc$e42dep)
get_labels(efc$e42dep, drop.unused = TRUE)
get_labels(efc$e42dep, non.labelled = TRUE, drop.unused = TRUE)

sjlabelled documentation built on April 10, 2022, 5:05 p.m.