Custom transformer for sklearn Pipeline that alters both X and y

Question

I want to create my own transformer for use with the sklearn Pipeline. Hence I am creating a class that implements both fit and transform methods. The purpose of the transfo

Answer 1

Use "deep-copies" further on, down the pipeline and X, y remain protected

.fit() can first assign on each call deep-copy to new class-variables

self.X_without_NaNs = X.copy()
self.y_without_NaNs = y.copy()

and then reduce / transform these not to have more NaN-s than ordered by self.treshold