```py
        >>> from datasets import load_dataset
        >>> ds = load_dataset("rotten_tomatoes", streaming=True)
        >>> ds = ds.rename_columns({"text": "movie_review", "label": "rating"})
        >>> next(iter(ds["train"]))
        {'movie_review': 'the rock is destined to be the 21st century\'s new " conan " and that he\'s going to make a splash even greater than arnold schwarzenegger , jean-claud van damme or steven segal .',
         'rating': 1}
        ```
        """
        return IterableDatasetDict(
            {k: dataset.rename_columns(column_mapping=column_mapping) for k, dataset in self.items()}
        )

    def remove_columns(self, column_names: Union[str, List[str]]) -> "IterableDatasetDict":
        """
        Remove one or several column(s) in the dataset and the features associated to them.
        The removal is done on-the-fly on the examples when iterating over the dataset.
        The removal is applied to all the datasets of the dataset dictionary.