# Buggy code
def __init__(
    self,
    data=None,
    index=None,
    sparse_index=None,
    kind="block",
    fill_value=None,
    name=None,
    dtype=None,
    copy=False,
    fastpath=False,
):
    # we are called internally, so short-circuit
    if fastpath:
        # data is an ndarray, index is defined

        if not isinstance(data, SingleBlockManager):
            data = SingleBlockManager(data, index, fastpath=True)
        if copy:
            data = data.copy()

    else:
        if data is None:
            data = []

        if isinstance(data, Series) and name is None:
            name = data.name

        is_sparse_array = isinstance(data, SparseArray)
        if fill_value is None:
            if is_sparse_array:
                fill_value = data.fill_value
            else:
                fill_value = nan

        if is_sparse_array:
            if isinstance(data, SparseSeries) and index is None:
                index = data.index.view()
            elif index is not None:
                assert len(index) == len(data)

            sparse_index = data.sp_index
            data = np.asarray(data)

        elif isinstance(data, SparseSeries):
            if index is None:
                index = data.index.view()

            # extract the SingleBlockManager
            data = data._data

        elif isinstance(data, (Series, dict)):
            if index is None:
                index = data.index.view()

            data = Series(data)
            data, sparse_index = make_sparse(data, kind=kind, fill_value=fill_value)

        elif isinstance(data, (tuple, list, np.ndarray)):
            # array-like
            if sparse_index is None:
                data, sparse_index = make_sparse(data, kind=kind, fill_value=fill_value)
            else:
                assert len(data) == sparse_index.npoints

        elif isinstance(data, SingleBlockManager):
            if dtype is not None:
                data = data.astype(dtype)
            if index is None:
                index = data.index.view()
            else:
                data = data.reindex(index, copy=False)

        else:
            length = len(index)

            if data == fill_value or (isnull(data) and isnull(fill_value)):
                if kind == "block":
                    sparse_index = BlockIndex(length, [], [])
                else:
                    sparse_index = IntIndex(length, [])
                data = np.array([])

            else:
                if kind == "block":
                    locs, lens = ([0], [length]) if length else ([], [])
                    sparse_index = BlockIndex(length, locs, lens)
                else:
                    sparse_index = IntIndex(length, index)
                v = data
                data = np.empty(length)
                data.fill(v)

        if index is None:
            index = com._default_index(sparse_index.length)
        index = _ensure_index(index)

        # create/copy the manager
        if isinstance(data, SingleBlockManager):
            if copy:
                data = data.copy()
        else:
            # create a sparse array
            if not isinstance(data, SparseArray):
                data = SparseArray(
                    data,
                    sparse_index=sparse_index,
                    fill_value=fill_value,
                    dtype=dtype,
                    copy=copy,
                )

            data = SingleBlockManager(data, index)

    generic.NDFrame.__init__(self, data)

    self.index = index
    self.name = name


# Traceback (TypeError)
Traceback (most recent call last):
File "/Users/bryan/anaconda3/lib/python3.5/site-packages/pandas/sparse/series.py", line 420, in _get_values
fastpath=True).__finalize__(self)
File "/Users/bryan/anaconda3/lib/python3.5/site-packages/pandas/sparse/series.py", line 222, in __init__
self.index = index
File "/Users/bryan/anaconda3/lib/python3.5/site-packages/pandas/core/generic.py", line 2685, in __setattr__
return object.__setattr__(self, name, value)
File "pandas/src/properties.pyx", line 65, in pandas.lib.AxisProperty.__set__ (pandas/lib.c:44748)
File "/Users/bryan/anaconda3/lib/python3.5/site-packages/pandas/core/series.py", line 274, in _set_axis
labels = _ensure_index(labels)
File "/Users/bryan/anaconda3/lib/python3.5/site-packages/pandas/indexes/base.py", line 3409, in _ensure_index
return Index(index_like)
File "/Users/bryan/anaconda3/lib/python3.5/site-packages/pandas/indexes/base.py", line 268, in __new__
cls._scalar_data_error(data)
File "/Users/bryan/anaconda3/lib/python3.5/site-packages/pandas/indexes/base.py", line 483, in _scalar_data_error
repr(data)))
TypeError: Index(...) must be called with a collection of some kind, None was passed

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/Users/bryan/anaconda3/lib/python3.5/site-packages/pandas/core/base.py", line 46, in __str__
return self.__unicode__()
File "/Users/bryan/anaconda3/lib/python3.5/site-packages/pandas/sparse/series.py", line 306, in __unicode__
series_rep = Series.__unicode__(self)
File "/Users/bryan/anaconda3/lib/python3.5/site-packages/pandas/core/series.py", line 984, in __unicode__
max_rows=max_rows)
File "/Users/bryan/anaconda3/lib/python3.5/site-packages/pandas/core/series.py", line 1025, in to_string
dtype=dtype, name=name, max_rows=max_rows)
File "/Users/bryan/anaconda3/lib/python3.5/site-packages/pandas/core/series.py", line 1052, in _get_repr
max_rows=max_rows)
File "/Users/bryan/anaconda3/lib/python3.5/site-packages/pandas/formats/format.py", line 145, in __init__
self._chk_truncate()
File "/Users/bryan/anaconda3/lib/python3.5/site-packages/pandas/formats/format.py", line 158, in _chk_truncate
series = concat((series.iloc[:row_num],
File "/Users/bryan/anaconda3/lib/python3.5/site-packages/pandas/core/indexing.py", line 1296, in __getitem__
return self._getitem_axis(key, axis=0)
File "/Users/bryan/anaconda3/lib/python3.5/site-packages/pandas/core/indexing.py", line 1587, in _getitem_axis
return self._get_slice_axis(key, axis=axis)
File "/Users/bryan/anaconda3/lib/python3.5/site-packages/pandas/core/indexing.py", line 1579, in _get_slice_axis
return self._slice(slice_obj, axis=axis, kind='iloc')
File "/Users/bryan/anaconda3/lib/python3.5/site-packages/pandas/core/indexing.py", line 99, in _slice
return self.obj._slice(obj, axis=axis, kind=kind)
File "/Users/bryan/anaconda3/lib/python3.5/site-packages/pandas/core/series.py", line 578, in _slice
return self._get_values(slobj)
File "/Users/bryan/anaconda3/lib/python3.5/site-packages/pandas/sparse/series.py", line 422, in _get_values
return self[indexer]
File "/Users/bryan/anaconda3/lib/python3.5/site-packages/pandas/sparse/series.py", line 396, in __getitem__
return self._get_val_at(self.index.get_loc(key))
File "/Users/bryan/anaconda3/lib/python3.5/site-packages/pandas/sparse/series.py", line 392, in _get_val_at
return self.block.values._get_val_at(loc)
File "/Users/bryan/anaconda3/lib/python3.5/site-packages/pandas/sparse/array.py", line 308, in _get_val_at
if loc < 0:
ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()

# Fixed code
def __init__(
    self,
    data=None,
    index=None,
    sparse_index=None,
    kind="block",
    fill_value=None,
    name=None,
    dtype=None,
    copy=False,
    fastpath=False,
):
    # we are called internally, so short-circuit
    if fastpath:
        # data is an ndarray, index is defined

        if not isinstance(data, SingleBlockManager):
            data = SingleBlockManager(data, index, fastpath=True)
        if copy:
            data = data.copy()

    else:
        if data is None:
            data = []

        if isinstance(data, Series) and name is None:
            name = data.name

        is_sparse_array = isinstance(data, SparseArray)
        if fill_value is None:
            if is_sparse_array:
                fill_value = data.fill_value
            else:
                fill_value = np.nan

        if is_sparse_array:
            if isinstance(data, SparseSeries) and index is None:
                index = data.index.view()
            elif index is not None:
                assert len(index) == len(data)

            sparse_index = data.sp_index
            data = np.asarray(data)

        elif isinstance(data, SparseSeries):
            if index is None:
                index = data.index.view()

            # extract the SingleBlockManager
            data = data._data

        elif isinstance(data, (Series, dict)):
            if index is None:
                index = data.index.view()

            data = Series(data)
            data, sparse_index = make_sparse(data, kind=kind, fill_value=fill_value)

        elif isinstance(data, (tuple, list, np.ndarray)):
            # array-like
            if sparse_index is None:
                data, sparse_index = make_sparse(data, kind=kind, fill_value=fill_value)
            else:
                assert len(data) == sparse_index.npoints

        elif isinstance(data, SingleBlockManager):
            if dtype is not None:
                data = data.astype(dtype)
            if index is None:
                index = data.index.view()
            else:
                data = data.reindex(index, copy=False)

        else:
            length = len(index)

            if data == fill_value or (isnull(data) and isnull(fill_value)):
                if kind == "block":
                    sparse_index = BlockIndex(length, [], [])
                else:
                    sparse_index = IntIndex(length, [])
                data = np.array([])

            else:
                if kind == "block":
                    locs, lens = ([0], [length]) if length else ([], [])
                    sparse_index = BlockIndex(length, locs, lens)
                else:
                    sparse_index = IntIndex(length, index)
                v = data
                data = np.empty(length)
                data.fill(v)

        if index is None:
            index = com._default_index(sparse_index.length)
        index = _ensure_index(index)

        # create/copy the manager
        if isinstance(data, SingleBlockManager):
            if copy:
                data = data.copy()
        else:
            # create a sparse array
            if not isinstance(data, SparseArray):
                data = SparseArray(
                    data,
                    sparse_index=sparse_index,
                    fill_value=fill_value,
                    dtype=dtype,
                    copy=copy,
                )

            data = SingleBlockManager(data, index)

    generic.NDFrame.__init__(self, data)

    self.index = index
    self.name = name