expss (version 0.11.6)

var_lab: Set or get variable label

Description

These functions set/get/drop variable labels. For value labels see val_lab. For working with entire data.frame see apply_labels.

• var_lab returns variable label or NULL if label doesn't exist.

• var_lab<- set variable label.

• set_var_lab returns variable with label.

• unvr drops variable label.

• add_labelled_class Add missing 'labelled' class. This function is needed when you load SPSS data with packages which in some cases don't set 'labelled' class for variables with labels. For example, haven package doesn't set 'labelled' class for variables which have variable label but don't have value labels. Note that to use 'expss' with 'haven' you need to load 'expss' strictly after 'haven' to avoid conflicts.

Usage

var_lab(x, default = NULL)
var_lab(x) <- value
set_var_lab(x, value)
unvr(x)
drop_var_labs(x)
add_labelled_class(
  x,
  remove_classes = c("haven_labelled", "spss_labelled", "haven_labelled_spss",
    "vctrs_vctr")
)

Value

var_lab return variable label. If label doesn't exist it return NULL . var_lab<- and set_var_lab return variable (vector x) of class "labelled" with attribute "label" which equals submitted value.

Arguments

x

Variable. In the most cases it is numeric vector.

default

A character scalar. What we want to get from 'var_lab' if there is no variable label. NULL by default.

value

A character scalar - label for the variable x.

remove_classes

A character vector of classes which should be removed from the class attribute of the x.

Details

Variable label is stored in attribute "label" (attr(x,"label")). For preserving from dropping this attribute during some operations (such as c) variable class is set to "labelled". There are special methods of subsetting and concatenation for this class. To drop variable label use var_lab(var) <- NULL or unvr(var).

Examples

data(mtcars)
var_lab(mtcars$mpg) = "Miles/(US) gallon"
var_lab(mtcars$cyl) = "Number of cylinders"
var_lab(mtcars$disp) = "Displacement (cu.in.)"
var_lab(mtcars$hp) = "Gross horsepower"
var_lab(mtcars$drat) = "Rear axle ratio"
var_lab(mtcars$wt) = "Weight (lb/1000)"
var_lab(mtcars$qsec) = "1/4 mile time"
var_lab(mtcars$vs) = "V/S"
var_lab(mtcars$am) = "Transmission (0 = automatic, 1 = manual)"
val_lab(mtcars$am) = c(automatic = 0, manual=1)
var_lab(mtcars$gear) = "Number of forward gears"
var_lab(mtcars$carb) = "Number of carburetors"

fre(mtcars$am)

cross_mean(mtcars, list(mpg, disp, hp, qsec), list(total(), am))
 
if (FALSE) {
if(FALSE){ # to prevent execution
# you need to load packages strictly in this order to avoid conflicts
library(haven)
library(expss)
spss_data = haven::read_spss("spss_file.sav")
# add missing 'labelled' class
spss_data = add_labelled_class(spss_data) 
}
}