# Buggy code
def _reindex_non_unique(self, target):
    """
    Create a new index with target's values (move/add/delete values as
    necessary) use with non-unique Index and a possibly non-unique target.

    Parameters
    ----------
    target : an iterable

    Returns
    -------
    new_index : pd.Index
        Resulting index.
    indexer : np.ndarray or None
        Indices of output values in original index.

    """
    target = ensure_index(target)
    if len(target) == 0:
        # GH#13691
        return self[:0], np.array([], dtype=np.intp), None

    indexer, missing = self.get_indexer_non_unique(target)
    check = indexer != -1
    new_labels = self.take(indexer[check])
    new_indexer = None

    if len(missing):
        length = np.arange(len(indexer))

        missing = ensure_platform_int(missing)
        missing_labels = target.take(missing)
        missing_indexer = ensure_int64(length[~check])
        cur_labels = self.take(indexer[check]).values
        cur_indexer = ensure_int64(length[check])

        new_labels = np.empty((len(indexer),), dtype=object)
        new_labels[cur_indexer] = cur_labels
        new_labels[missing_indexer] = missing_labels

        # a unique indexer
        if target.is_unique:
            # see GH5553, make sure we use the right indexer
            new_indexer = np.arange(len(indexer))
            new_indexer[cur_indexer] = np.arange(len(cur_labels))
            new_indexer[missing_indexer] = -1

        # we have a non_unique selector, need to use the original
        # indexer here
        else:
            # need to retake to have the same size as the indexer
            indexer[~check] = -1

            # reset the new indexer to account for the new size
            new_indexer = np.arange(len(self.take(indexer)))
            new_indexer[~check] = -1

    if isinstance(self, ABCMultiIndex):
        new_index = type(self).from_tuples(new_labels, names=self.names)
    else:
        new_index = Index(new_labels, name=self.name)
    return new_index, indexer, new_indexer


# Traceback (IndexError)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "C:\Users\mboling\Anaconda3\envs\pandastest\lib\site-packages\pandas\util\_decorators.py", line 312, in wrapper
return func(*args, **kwargs)
File "C:\Users\mboling\Anaconda3\envs\pandastest\lib\site-packages\pandas\core\frame.py", line 4173, in reindex
return super().reindex(**kwargs)
File "C:\Users\mboling\Anaconda3\envs\pandastest\lib\site-packages\pandas\core\generic.py", line 4806, in reindex
return self._reindex_axes(
File "C:\Users\mboling\Anaconda3\envs\pandastest\lib\site-packages\pandas\core\frame.py", line 4013, in _reindex_axes
frame = frame._reindex_columns(
File "C:\Users\mboling\Anaconda3\envs\pandastest\lib\site-packages\pandas\core\frame.py", line 4055, in _reindex_columns
new_columns, indexer = self.columns.reindex(
File "C:\Users\mboling\Anaconda3\envs\pandastest\lib\site-packages\pandas\core\indexes\category.py", line 448, in reindex
new_target, indexer, _ = result._reindex_non_unique(np.array(target))
File "C:\Users\mboling\Anaconda3\envs\pandastest\lib\site-packages\pandas\core\indexes\base.py", line 3589, in _reindex_non_unique
new_indexer = np.arange(len(self.take(indexer)))
File "C:\Users\mboling\Anaconda3\envs\pandastest\lib\site-packages\pandas\core\indexes\base.py", line 751, in take
taken = algos.take(
File "C:\Users\mboling\Anaconda3\envs\pandastest\lib\site-packages\pandas\core\algorithms.py", line 1657, in take
result = arr.take(indices, axis=axis)
IndexError: cannot do a non-empty take from an empty axes.

# Fixed code
def _reindex_non_unique(self, target):
    """
    Create a new index with target's values (move/add/delete values as
    necessary) use with non-unique Index and a possibly non-unique target.

    Parameters
    ----------
    target : an iterable

    Returns
    -------
    new_index : pd.Index
        Resulting index.
    indexer : np.ndarray or None
        Indices of output values in original index.

    """
    target = ensure_index(target)
    if len(target) == 0:
        # GH#13691
        return self[:0], np.array([], dtype=np.intp), None

    indexer, missing = self.get_indexer_non_unique(target)
    check = indexer != -1
    new_labels = self.take(indexer[check])
    new_indexer = None

    if len(missing):
        length = np.arange(len(indexer))

        missing = ensure_platform_int(missing)
        missing_labels = target.take(missing)
        missing_indexer = ensure_int64(length[~check])
        cur_labels = self.take(indexer[check]).values
        cur_indexer = ensure_int64(length[check])

        new_labels = np.empty((len(indexer),), dtype=object)
        new_labels[cur_indexer] = cur_labels
        new_labels[missing_indexer] = missing_labels

        # GH#38906
        if not len(self):
            new_indexer = np.arange(0)

        # a unique indexer
        elif target.is_unique:
            # see GH5553, make sure we use the right indexer
            new_indexer = np.arange(len(indexer))
            new_indexer[cur_indexer] = np.arange(len(cur_labels))
            new_indexer[missing_indexer] = -1

        # we have a non_unique selector, need to use the original
        # indexer here
        else:
            # need to retake to have the same size as the indexer
            indexer[~check] = -1

            # reset the new indexer to account for the new size
            new_indexer = np.arange(len(self.take(indexer)))
            new_indexer[~check] = -1

    if isinstance(self, ABCMultiIndex):
        new_index = type(self).from_tuples(new_labels, names=self.names)
    else:
        new_index = Index(new_labels, name=self.name)
    return new_index, indexer, new_indexer