def METHOD_NAME(dataset):
    assert len(dataset.features) == 22
    assert len(dataset.predictors) == 21
    _assert_target(dataset.target, "problems", ["no", "yes"])
    assert all([p.data_type == 'number' for p in dataset.predictors])
    assert all([p.values is None for p in dataset.predictors])
    assert not any([p.has_missing_values for p in dataset.predictors])
    assert dataset.train.X.dtypes.apply(lambda dt: pd.api.types.is_numeric_dtype(dt)).all()
    assert len(dataset.train.X.select_dtypes(include=['float']).columns) == 18
    assert len(dataset.train.X.select_dtypes(include=['uint8']).columns) == 3
    assert pd.api.types.is_categorical_dtype(dataset.train.y.dtypes.iloc[0])