dummy_vars: Create dummy variables for all categorical/factor variables...

In predRupdate: Prediction Model Validation and Updating

Create dummy variables for all categorical/factor variables in a data.frame

Description

Create dummy/indicator variables for all categorical variables in a data.frame. Can be used as a pre-processing step before calling other functions within the package.

Usage

dummy_vars(df)

Arguments

df	a data.frame on which to make dummy variables for each categorical/factor variable, based on contrasts.

Value

a data.frame matching df but where each categorical variable in df is replaced with indicator variables. All combinations of the indicator/dummy variable are returned. Naming convention of the new dummy variables is variable_level. For example, a factor variable in df named "colour" with levels "red", "green" and "purple" will be replaced with three columns (the new dummy variables), named colour_red, colour_green and colour_purple.

See Also

pred_input_info

Examples

dummy_vars(data.frame("Colour" = factor(sample(c("red",
                                                 "azure",
                                                 "green",
                                                 "white"),
                                              500,
                                              replace = TRUE))))

predRupdate documentation built on Sept. 11, 2024, 5:34 p.m.