to_dummy: Split (categorical) vectors into dummy variables

In sjmisc: Data and Variable Transformation Functions

Description

This function splits categorical or numeric vectors with more than two categories into 0/1-coded dummy variables.

Usage

to_dummy(x, ..., var.name = "name", suffix = c("numeric", "label"))

Arguments

x	A vector or data frame.
...	Optional, unquoted names of variables that should be selected for further processing. Required, if x is a data frame (and no vector) and only selected variables from x should be processed. You may also use functions like : or tidyselect's select-helpers. See 'Examples' or package-vignette.
var.name	Indicates how the new dummy variables are named. Use "name" to use the variable name or any other string that will be used as is. Only applies, if x is a vector. See 'Examples'.
suffix	Indicates which suffix will be added to each dummy variable. Use "numeric" to number dummy variables, e.g. x_1, x_2, x_3 etc. Use "label" to add value label, e.g. x_low, x_mid, x_high. May be abbreviated.

Value

A data frame with dummy variables for each category of x. The dummy coded variables are of type atomic.

Note

NA values will be copied from x, so each dummy variable has the same amount of NA's at the same position as x.

Examples

data(efc)
head(to_dummy(efc$e42dep))

# add value label as suffix to new variable name
head(to_dummy(efc$e42dep, suffix = "label"))

# use "dummy" as new variable name
head(to_dummy(efc$e42dep, var.name = "dummy"))

# create multiple dummies, append to data frame
to_dummy(efc, c172code, e42dep)

# pipe-workflow
library(dplyr)
efc %>%
  select(e42dep, e16sex, c172code) %>%
  to_dummy()

sjmisc documentation built on Dec. 11, 2021, 9:34 a.m.