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Sparse array cumsum leads to infinite recursion 62669 #62703

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813d76e
added condition to avoid max recursion depth
Oct 15, 2025
a3ff481
added condition to avoid max recursion depth
Oct 15, 2025
c550eac
added entry in rst file
Oct 15, 2025
bc75673
added test cases
Oct 15, 2025
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1 change: 1 addition & 0 deletions doc/source/whatsnew/v3.0.0.rst
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Original file line number Diff line number Diff line change
Expand Up @@ -1169,6 +1169,7 @@ Sparse
- Bug in :class:`SparseDtype` for equal comparison with na fill value. (:issue:`54770`)
- Bug in :meth:`DataFrame.sparse.from_spmatrix` which hard coded an invalid ``fill_value`` for certain subtypes. (:issue:`59063`)
- Bug in :meth:`DataFrame.sparse.to_dense` which ignored subclassing and always returned an instance of :class:`DataFrame` (:issue:`59913`)
- Bug in :meth:`cumsum` for integer arrays Calling SparseArray.cumsum caused max recursion depth error. (:issue:`62669`)

ExtensionArray
^^^^^^^^^^^^^^
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3 changes: 3 additions & 0 deletions pandas/core/arrays/sparse/array.py
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Expand Up @@ -1571,6 +1571,9 @@ def cumsum(self, axis: AxisInt = 0, *args, **kwargs) -> SparseArray:
raise ValueError(f"axis(={axis}) out of bounds")

if not self._null_fill_value:
if isinstance(self, SparseArray) and self.fill_value == 0:
# special case where we can avoid max recursion depth
return SparseArray(self.to_dense().cumsum())
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This fix seems to specific. Additionally especially for the open issue, it doesn't appear to_dense is needed

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@santhoshbethi santhoshbethi Oct 15, 2025 •
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Yeah, This fix is very specific to given use case.

       ` if isinstance(self, SparseArray) and self.fill_value == 0:
            # special case where we can avoid max recursion depth
            return SparseArray(self.cumsum())

If I don't add I am getting sameError: maximum recursion depth exceeded`

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I think the fix being specific is fine. It is basically using the same "trick" that the code was previously using for float arrays with nan fill, which was that if it is non-nan fill, densify and resparse so now the fill is nan, and call .cumsum() again. So it recurses once. This trick broke for integer arrays because when you do the densify and reparsing, the default fill is 0. This fix now catches that case ensuring that int arrays also only recurse once.

return SparseArray(self.to_dense()).cumsum()

return SparseArray(
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14 changes: 14 additions & 0 deletions pandas/tests/arrays/sparse/test_array.py
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Expand Up @@ -363,6 +363,20 @@ def test_setting_fill_value_fillna_still_works():
tm.assert_numpy_array_equal(result, expected)


def test_cumsum_integer_no_recursion():
# GH 62669: RecursionError in integer SparseArray.cumsum
arr = SparseArray([1, 2, 3])
result = arr.cumsum()
expected = SparseArray([1, 3, 6])
tm.assert_sp_array_equal(result, expected)

# Also test with some zeros interleaved
arr2 = SparseArray([0, 1, 0, 2])
result2 = arr2.cumsum()
expected2 = SparseArray([0, 1, 1, 3])
tm.assert_sp_array_equal(result2, expected2)


def test_setting_fill_value_updates():
arr = SparseArray([0.0, np.nan], fill_value=0)
arr.fill_value = np.nan
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