# Depth of Decision Tree

If there are only categorical variables in the dataset, will the depth of the decision tree be equal to the number of attributes? If not, can a value be split again?

First of all, it might be less than number of attributes when one of your attributes lose importance when others have been used due to some kind of dependence among them. Depending on the implementation, it might be larger also when branching is done like "Blue/Not Blue" at each level. But, typically, each categorical feature is handled in a single node (level), so you'll probably have depth $$\leq$$ number of features.