One-hot encoding

Turns a single-select nominal column with k categories into 0/1 indicator columns (one per category, named column = category). This lets a categorical variable be used as a regression predictor (regression accepts only numeric/ordinal inputs — see Regression).

• With Drop reference category on (default), one category is omitted (k − 1 columns) and becomes the baseline — the usual setup for regression.

• Turn it off to keep all k columns (useful for plain description).

A row with a missing value gets 0 in every indicator. The original column is left untouched and the indicators are inserted right after it.