I am making a pipeline with sklearn to handle my dataset, when trying to use OneHotEncoder (to transform not-numeric attributes into numeric ones) as one of pipeline's step - it returns the wrong shape size array.

The shape of original dataset is (8693, 14) and final dataset returned using pipeline must have the same size. Generally if I don't use OneHotEncoder in pipeline - it returns normal shape size array, but when I add it - shape is ruined and it's wrong.

Can you help please? Already tried OneHotEncoder parameters, 'toarray' method, 'resize' method and they do not solve the problem.

CodePudding user response：

OneHotEncoder creates one column per category, to map a categorical/string column to a number you can use OrdinalEncoder instead.