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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 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))
    )