def test_features_categorical_features_no_target( feature_list, target, expected, data_classification_balanced, feature_descriptor ): """Testing if .categorical_features() returns correct values when drop_target = True (without Target feature name). """ X, y = data_classification_balanced f = Features(X, y, feature_descriptor) f._categorical_features = feature_list f.target = target actual = f.categorical_features(drop_target=True) assert actual == expected
def test_features_categorical_features_exclude_transformed( data_classification_balanced, feature_descriptor, transformed_features ): """Testing if returning categorical features list with transformed columns excluded works properly.""" col_list = ["AgeGroup", "bool", "Product", "Sex", "Target"] X, y = data_classification_balanced f = Features(X, y, feature_descriptor, transformed_features) actual_result = f.categorical_features(exclude_transformed=True) if transformed_features: expected_result = [feature for feature in col_list if feature not in transformed_features] else: expected_result = col_list assert actual_result == expected_result