sjlabelled (version 1.2.0)

set_label: Add variable label(s) to variables

Description

This function adds variable labels as attribute (named "label") to the variable x, resp. to a set of variables in a data frame or a list-object. var_labels() is intended for use within pipe-workflows and has a tidyverse-consistent syntax, including support for quasi-quotation (see 'Examples').

Usage

set_label(x, label)
set_label(x) <- value
var_labels(x, ...)

Arguments

x

Variable (vector), list of variables or a data frame where variables labels should be added as attribute. For var_labels(), x must be a data frame only.

label

If x is a vector (single variable), use a single character string with the variable label for x. If x is a data frame, use a vector with character labels of same length as ncol(x). Use label = "" to remove labels-attribute from x, resp. set any value of vector label to "" to remove specific variable label attributes from a data frame's variable.

value

See label.

...

Pairs of named vectors, where the name equals the variable name, which should be labelled, and the value is the new variable label.

Value

x, with variable label attribute(s), which contains the variable name(s); or with removed label-attribute if label = "".

See Also

See vignette Labelled Data and the sjlabelled-Package for more details; set_labels to manually set value labels or get_label to get variable labels.

Examples

# NOT RUN {
# manually set value and variable labels
dummy <- sample(1:4, 40, replace = TRUE)
dummy <- set_labels(dummy, labels = c("very low", "low", "mid", "hi"))
dummy <- set_label(dummy, label = "Dummy-variable")

# or use:
# set_label(dummy) <- "Dummy-variable"

# auto-detection of value labels by default, auto-detection of
# variable labels if argument "title" set to NULL.
# }
# NOT RUN {
library(sjPlot)
sjp.frq(dummy, title = NULL)
# }
# NOT RUN {
# Set variable labels for data frame
dummy <- data.frame(
  a = sample(1:4, 10, replace = TRUE),
  b = sample(1:4, 10, replace = TRUE),
  c = sample(1:4, 10, replace = TRUE)
)
dummy <- set_label(dummy, c("Variable A", "Variable B", "Variable C"))
str(dummy)

# remove one variable label
dummy <- set_label(dummy, c("Variable A", "", "Variable C"))
str(dummy)

# setting same variable labels to multiple vectors

# create a set of dummy variables
dummy1 <- sample(1:4, 40, replace = TRUE)
dummy2 <- sample(1:4, 40, replace = TRUE)
dummy3 <- sample(1:4, 40, replace = TRUE)
# put them in list-object
dummies <- list(dummy1, dummy2, dummy3)
# and set variable labels for all three dummies
dummies <- set_label(dummies, c("First Dummy", "2nd Dummy", "Third dummy"))
# see result...
get_label(dummies)


# use 'var_labels()' to set labels within a pipe-workflow, and
# when you need "tidyverse-consistent" api.
# Set variable labels for data frame
dummy <- data.frame(
  a = sample(1:4, 10, replace = TRUE),
  b = sample(1:4, 10, replace = TRUE),
  c = sample(1:4, 10, replace = TRUE)
)

library(magrittr)
dummy %>%
  var_labels(a = "First variable", c = "third variable") %>%
  get_label()

# with quasi-quotation
library(rlang)
v1 <- "First variable"
v2 <- "Third variable"
dummy %>%
  var_labels(a = !!v1, c = !!v2) %>%
  get_label()

x1 <- "a"
x2 <- "c"
dummy %>%
  var_labels(!!x1 := !!v1, !!x2 := !!v2) %>%
  get_label()

# }