def _aligned_series(*many_series):
    """
    Return a new list of series containing the data in the input series, but
    with their indices aligned. NaNs will be filled in for missing values.

    Parameters
    ----------
    *many_series
        The series to align.

    Returns
    -------
    aligned_series : iterable[array-like]
        A new list of series containing the data in the input series, but
        with their indices aligned. NaNs will be filled in for missing values.

    """
    head = many_series[0]
    tail = many_series[1:]
    n = len(head)
    if (isinstance(head, np.ndarray) and
            all(len(s) == n and isinstance(s, np.ndarray) for s in tail)):
        # optimization: ndarrays of the same length are already aligned
        return many_series

    # dataframe has no ``itervalues``
    return (
        v
        for _, v in iteritems(pd.concat(map(_to_pandas, many_series), axis=1))
    )
def _aligned_series ( * many_series ) : head = many_series [ 0 ] tail = many_series [ 1 : ] n = len ( head ) if ( isinstance ( head , np . ndarray ) and all ( len ( s ) == n and isinstance ( s , np . ndarray ) for s in tail ) ) : return many_series return ( v for _ , v in iteritems ( pd . concat ( map ( _to_pandas , many_series ) , axis = 1 ) ) )
Return a new list of series containing the data in the input series, but
    with their indices aligned. NaNs will be filled in for missing values.

    Parameters
    ----------
    *many_series
        The series to align.

    Returns
    -------
    aligned_series : iterable[array-like]
        A new list of series containing the data in the input series, but
        with their indices aligned. NaNs will be filled in for missing values.