def test_features_numerical_features_no_target(
feature_list, target, expected, data_classification_balanced, feature_descriptor
):
"""Testing if .numerical_features() returns correct values when drop_target = True (without Target feature name)."""
X, y = data_classification_balanced
f = Features(X, y, feature_descriptor)
f._numerical_features = feature_list
f.target = target
actual = f.numerical_features(drop_target=True)
assert actual == expected
def test_features_numerical_features_exclude_transformed(
data_classification_balanced, feature_descriptor, transformed_features
):
"""Testing if returning numerical features list with transformed columns excluded works properly."""
col_list = ["Height", "Price"]
X, y = data_classification_balanced
f = Features(X, y, feature_descriptor, transformed_features)
actual_result = f.numerical_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