def roll(*args, **kwargs):
    """
    Calculates a given statistic across a rolling time period.

    Parameters
    ----------
    returns : pd.Series or np.ndarray
        Daily returns of the strategy, noncumulative.
        - See full explanation in :func:`~empyrical.stats.cum_returns`.
    factor_returns (optional): float / series
        Benchmark return to compare returns against.
    function:
        the function to run for each rolling window.
    window (keyword): int
        the number of periods included in each calculation.
    (other keywords): other keywords that are required to be passed to the
        function in the 'function' argument may also be passed in.

    Returns
    -------
    np.ndarray, pd.Series
        depends on input type
        ndarray(s) ==> ndarray
        Series(s) ==> pd.Series

        A Series or ndarray of the results of the stat across the rolling
        window.

    """
    func = kwargs.pop('function')
    window = kwargs.pop('window')
    if len(args) > 2:
        raise ValueError("Cannot pass more than 2 return sets")

    if len(args) == 2:
        if not isinstance(args[0], type(args[1])):
            raise ValueError("The two returns arguments are not the same.")

    if isinstance(args[0], np.ndarray):
        return _roll_ndarray(func, window, *args, **kwargs)
    return _roll_pandas(func, window, *args, **kwargs)
Calculates a given statistic across a rolling time period.

    Parameters
    ----------
    returns : pd.Series or np.ndarray
        Daily returns of the strategy, noncumulative.
        - See full explanation in :func:`~empyrical.stats.cum_returns`.
    factor_returns (optional): float / series
        Benchmark return to compare returns against.
    function:
        the function to run for each rolling window.
    window (keyword): int
        the number of periods included in each calculation.
    (other keywords): other keywords that are required to be passed to the
        function in the 'function' argument may also be passed in.

    Returns
    -------
    np.ndarray, pd.Series
        depends on input type
        ndarray(s) ==> ndarray
        Series(s) ==> pd.Series

        A Series or ndarray of the results of the stat across the rolling
        window.