Cоnsider the fоllоwing preprocessing pipeline: from skleаrn.pipeline import Pipelinefrom skleаrn.compose import ColumnTrаnsformerfrom sklearn.preprocessing import StandardScaler, OneHotEncoderpipeline = Pipeline([ ('preprocess', ColumnTransformer([ ('scaler', StandardScaler(), ['height', 'weight']), ('encoder', OneHotEncoder(), ['gender']) ], remainder='drop'))]) Suppose your DataFrame df has three columns: height and weight (both numeric) gender with exactly three possible categories: 'M', 'F', and 'O' After running X_transformed = pipeline.fit_transform(df), how many columns will X_transformed have?