```py
        >>> from datasets import load_dataset, ClassLabel
        >>> ds = load_dataset("rotten_tomatoes", streaming=True)
        >>> ds["train"].features
        {'label': ClassLabel(names=['neg', 'pos'], id=None),
         'text': Value(dtype='string', id=None)}
        >>> ds = ds.cast_column('label', ClassLabel(names=['bad', 'good']))
        >>> ds["train"].features
        {'label': ClassLabel(names=['bad', 'good'], id=None),
         'text': Value(dtype='string', id=None)}
        ```
        """
        return IterableDatasetDict(
            {k: dataset.cast_column(column=column, feature=feature) for k, dataset in self.items()}
        )

    def cast(
        self,
        features: Features,
    ) -> "IterableDatasetDict":
        """
        Cast the dataset to a new set of features.
        The type casting is applied to all the datasets of the dataset dictionary.