sjmisc (version 2.7.7)

to_dummy: Split (categorical) vectors into dummy variables

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.

Examples

# NOT RUN {
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()

# }