Does Decision tree classifier calculate entropies before transforming categorical features using OneHotEncoder or transformation should be done
It's not totally clear to me what is your main question but here are a few points which might help you:


Like any regular classifier, a decision tree classifier does not transform the features. It's up to the user if they want to apply any transformation before calling the classifier.
Standard decision tree classifiers can deal with features which have multiple values.


Afaik training a decision tree model using a library classifier is not going to help you much understanding how the model is calculated, it's just going to give you the result. You could try to code your own implementation if you want.