mariposa (version 0.7.3)

var_label: Get or Set Variable Labels

Description

Retrieves or assigns variable labels (the "label" attribute) on vectors or data frame columns. Variable labels describe what a variable measures (e.g., "Age of respondent") and are commonly used in survey data imported from SPSS, Stata, or SAS.

The function operates in two modes:

• GET mode: Called with bare variable names or no ... arguments, returns existing labels.

• SET mode: Called with name = "label" pairs, assigns labels to variables and returns the modified data.

Usage

var_label(data, ...)

Value

• GET mode (vector input): A single character string (the label), or NULL if no label exists.

• GET mode (data frame input): A named character vector of labels. Variables without labels return NA.

• SET mode: The modified data frame (invisibly), with labels assigned.

Arguments

data

A data frame, tibble, or a single vector.

...

In GET mode: unquoted variable names (tidyselect supported). If empty, returns labels for all variables. In SET mode: named pairs where the name is a variable and the value is the label string. Use NULL to remove a label.

Details

Variable labels are stored as the "label" attribute on each column, which is the standard used by the haven package for SPSS/Stata/SAS imports. These labels are preserved by mariposa's codebook(), frequency(), and describe() functions.

When to Use This

Use var_label() when you:

• Want to inspect what variables measure in imported survey data

• Need to add labels to manually created data before using codebook() or write_spss()

• Want to update or correct labels after import

See Also

val_labels() for value labels, codebook() for viewing all metadata, copy_labels() for preserving labels after dplyr operations

Other labels: copy_labels(), drop_labels(), find_var(), set_na(), to_character(), to_label(), to_labelled(), to_numeric(), unlabel(), val_labels()

Examples

# GET: retrieve all variable labels
var_label(survey_data)

# GET: specific variables
var_label(survey_data, age, gender)

# GET: from a single vector
var_label(survey_data$age)

# SET: assign labels
data <- var_label(survey_data,
  age = "Age of respondent",
  gender = "Gender identity"
)

# REMOVE: set to NULL
data <- var_label(data, age = NULL)