Create Dummy Variables (One-Hot Encoding)

Creates 0/1 dummy variables from categorical variables. Column names are derived from value labels when available, making results readable for SPSS-style data.

Unlike model.matrix(), to_dummy() uses value labels for column naming and handles haven_labelled vectors correctly.

Usage

to_dummy(data, ..., suffix = "val", ref = NULL, append = TRUE)

Arguments

data

A data frame or vector. When a data frame is passed, use ... to select variables.

...

Variables to dummy-code (tidyselect). Only used when data is a data frame.

suffix

How to name dummy columns: "val" (default) uses the raw value (e.g., gender_1), "label" uses the value label (e.g., gender_Male).

ref

A value to use as reference category (omitted from output). If NULL (default), all categories get a dummy variable. Set to a specific value for n-1 coding (e.g., for regression).

append

If TRUE (default), the dummy columns are appended to the original data frame. If FALSE, only the dummy columns are returned. Ignored when data is a vector.

Value

If append = TRUE (default), the original data frame with dummy columns appended. If append = FALSE, a tibble with only the dummy columns. For vector input, always a tibble of dummy columns.

Details

Column Naming

With suffix = "val": {varname}_{value} (e.g., gender_1, gender_2). With suffix = "label": {varname}_{label} where labels are cleaned (spaces replaced with _, special characters removed).

Reference Category

For regression, you typically need n-1 dummy variables. Set ref to the value of the reference category to omit it.

See also

rec() for general recoding, to_label() for converting to factor

Other recode: rec()

Examples

library(dplyr)
data(survey_data)

# Create dummies and append to data (default)
data <- to_dummy(survey_data, gender)

# Use labels for column names
data <- to_dummy(survey_data, gender, suffix = "label")

# n-1 dummies with reference category
data <- to_dummy(survey_data, gender, ref = 1)

# Multiple variables
data <- to_dummy(survey_data, gender, education, suffix = "label")

# Return only the dummy columns (without original data)
dummies <- to_dummy(survey_data, gender, append = FALSE)