sjlabelled (version 1.0.14)

get_labels: 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, include.values = NULL,
  include.non.labelled = NULL)

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, include.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, include.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

# NOT RUN {
# 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)

# }