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BUG: RuntimeWarning from np.ndarray.astype when converting large int64[pyarrow] values #62709

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BUG: RuntimeWarning from np.ndarray.astype when converting large int64[pyarrow] values #62709

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4959b78
fix np.ndarray.astype runtimewarning
matiaslindgren Oct 16, 2025
7a0282a
update whatsnew
matiaslindgren Oct 16, 2025
aa4ab61
fix precommit
matiaslindgren Oct 16, 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 @@ -1002,6 +1002,7 @@ Numeric
Conversion
^^^^^^^^^^
- Bug in :meth:`DataFrame.astype` not casting ``values`` for Arrow-based dictionary dtype correctly (:issue:`58479`)
- Bug in :meth:`DataFrame.convert_dtypes` with ``dtype_backend='pyarrow'`` for large ``int64`` values (:issue:`58485`)
- Bug in :meth:`DataFrame.update` bool dtype being converted to object (:issue:`55509`)
- Bug in :meth:`Series.astype` might modify read-only array inplace when casting to a string dtype (:issue:`57212`)
- Bug in :meth:`Series.convert_dtypes` and :meth:`DataFrame.convert_dtypes` removing timezone information for objects with :class:`ArrowDtype` (:issue:`60237`)
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4 changes: 2 additions & 2 deletions pandas/core/dtypes/cast.py
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Expand Up @@ -960,7 +960,7 @@ def convert_dtypes(
if len(arr) < len(input_array) and not is_nan_na():
# In the presence of NaNs, we cannot convert to IntegerDtype
pass
elif (arr.astype(int) == arr).all():
elif np.array_equal(arr, np.trunc(arr), equal_nan=True):
inferred_dtype = target_int_dtype
else:
inferred_dtype = input_array.dtype
Expand All @@ -987,7 +987,7 @@ def convert_dtypes(
if len(arr) < len(input_array) and not is_nan_na():
# In the presence of NaNs, we can't convert to IntegerDtype
inferred_dtype = inferred_float_dtype
elif (arr.astype(int) == arr).all():
elif np.array_equal(arr, np.trunc(arr)):
inferred_dtype = pandas_dtype_func("Int64")
else:
inferred_dtype = inferred_float_dtype
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27 changes: 27 additions & 0 deletions pandas/tests/frame/methods/test_convert_dtypes.py
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Expand Up @@ -228,3 +228,30 @@ def test_convert_dtype_pyarrow_timezone_preserve(self):
result = df.convert_dtypes(dtype_backend="pyarrow")
expected = df.copy()
tm.assert_frame_equal(result, expected)

def test_convert_dtype_pyarrow_int64_limits_warning(self):
# GH 58485
pytest.importorskip("pyarrow")
data = {
"a": [
-9223372036854775808,
4611686018427387904,
9223372036854775807,
None,
],
"b": [
-9223372036854775808,
4611686018427387904,
9223372036854775807,
None,
],
"c": [
-9223372036854775808,
4611686018427387904,
9223372036854775807,
None,
],
}
result = pd.DataFrame(data).convert_dtypes(dtype_backend="pyarrow")
expected = pd.DataFrame(data, dtype="int64[pyarrow]")
tm.assert_frame_equal(result, expected)
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