Skip to content

BUG: Fixes regression in Series.pow with all-NA double[pyarrow] values in in pandas 3.x #62572

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 2 commits into from
Oct 5, 2025
+10 −1
Merged

BUG: Fixes regression in Series.pow with all-NA double[pyarrow] values in in pandas 3.x #62572

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
d923031
BUG: Fixes regression in Series.pow with all-NA double[pyarrow] value…
fandimeng-fm Oct 4, 2025
08bfc5b
Remove release note from v3.0.0.rst
fandimeng-fm Oct 4, 2025
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
2 changes: 1 addition & 1 deletion pandas/core/arrays/arrow/array.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -1051,7 +1051,7 @@ def _arith_method(self, other, op) -> Self | npt.NDArray[np.object_]:
result = self._evaluate_op_method(other, op, ARROW_ARITHMETIC_FUNCS)
if is_nan_na() and result.dtype.kind == "f":
parr = result._pa_array
mask = pc.is_nan(parr).to_numpy()
mask = pc.is_nan(parr).fill_null(False).to_numpy()
arr = pc.replace_with_mask(parr, mask, pa.scalar(None, type=parr.type))
result = type(self)(arr)
return result
Expand Down
9 changes: 9 additions & 0 deletions pandas/tests/extension/test_arrow.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -3691,3 +3691,12 @@ def test_setitem_float_nan_is_na(using_nan_is_na):
ser[2] = np.nan
assert isinstance(ser[2], float)
assert np.isnan(ser[2])


def test_pow_with_all_na_float():
# GH#62520

s = pd.Series([None, None], dtype="float64[pyarrow]")
result = s.pow(2)
expected = pd.Series([pd.NA, pd.NA], dtype="float64[pyarrow]")
tm.assert_series_equal(result, expected)
Loading