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GH-50464: [C++][Python] Simplify arrow_to_pandas DateOffset handling for nanoseconds/milliseconds #50465

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GH-50464: [C++][Python] Simplify arrow_to_pandas DateOffset handling for nanoseconds/milliseconds #50465

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GH-50464: [C++][Python] Simplify arrow_to_pandas DateOffset handling …
raulcd Jul 10, 2026
fee35da
Changes on roundtripping, we roundtrip Month Day Nanoseconds but not …
raulcd Jul 10, 2026
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17 changes: 2 additions & 15 deletions python/pyarrow/src/arrow/python/arrow_to_pandas.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -1292,24 +1292,11 @@ struct ObjectWriterVisitor {
auto to_date_offset = [&](const MonthDayNanoIntervalType::MonthDayNanos& interval,
PyObject** out) {
ARROW_DCHECK(internal::BorrowPandasDataOffsetType() != nullptr);
// DateOffset objects do not add nanoseconds component to pd.Timestamp.
// as of Pandas 1.3.3
// (https://github.com/pandas-dev/pandas/issues/43892).
// So convert microseconds and remainder to preserve data
// but give users more expected results.
int64_t microseconds = interval.nanoseconds / 1000;
int64_t nanoseconds;
if (interval.nanoseconds >= 0) {
nanoseconds = interval.nanoseconds % 1000;
} else {
nanoseconds = -((-interval.nanoseconds) % 1000);
}

PyDict_SetItemString(kwargs.obj(), "months", PyLong_FromLong(interval.months));
PyDict_SetItemString(kwargs.obj(), "days", PyLong_FromLong(interval.days));
PyDict_SetItemString(kwargs.obj(), "microseconds",
PyLong_FromLongLong(microseconds));
PyDict_SetItemString(kwargs.obj(), "nanoseconds", PyLong_FromLongLong(nanoseconds));
PyDict_SetItemString(kwargs.obj(), "nanoseconds",
PyLong_FromLongLong(interval.nanoseconds));
Comment on lines 1296 to +1299
*out =
PyObject_Call(internal::BorrowPandasDataOffsetType(), args.obj(), kwargs.obj());
RETURN_IF_PYERROR();
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12 changes: 5 additions & 7 deletions python/pyarrow/tests/test_array.py
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Expand Up @@ -2762,11 +2762,10 @@ def test_interval_array_from_relativedelta():
assert arr.equals(expected)
assert arr.to_pandas().tolist() == [
None, DateOffset(months=13, days=8,
microseconds=(
nanoseconds=(
datetime.timedelta(seconds=1, microseconds=1,
minutes=1, hours=1) //
datetime.timedelta(microseconds=1)),
nanoseconds=0)]
datetime.timedelta(microseconds=1)) * 1000)]
with pytest.raises(ValueError):
pa.array([DateOffset(years=((1 << 32) // 12), months=100)])
with pytest.raises(ValueError):
Expand Down Expand Up @@ -2814,12 +2813,11 @@ def test_interval_array_from_dateoffset():
assert arr.equals(expected)
expected_from_pandas = [
None, DateOffset(months=13, days=8,
microseconds=(
nanoseconds=(
datetime.timedelta(seconds=1, microseconds=1,
minutes=1, hours=1) //
datetime.timedelta(microseconds=1)),
nanoseconds=1),
DateOffset(months=0, days=0, microseconds=0, nanoseconds=0)]
datetime.timedelta(microseconds=1) * 1000) + 1),
DateOffset(months=0, days=0, nanoseconds=0)]

assert arr.to_pandas().tolist() == expected_from_pandas

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3 changes: 1 addition & 2 deletions python/pyarrow/tests/test_pandas.py
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Expand Up @@ -1733,8 +1733,7 @@ def test_month_day_nano_interval(self):
from pandas.tseries.offsets import DateOffset
df = pd.DataFrame({
'date_offset': [None,
DateOffset(days=3600, months=3600, microseconds=3,
nanoseconds=600)]
DateOffset(days=3600, months=3600, nanoseconds=3600)]
})
schema = pa.schema([('date_offset', pa.month_day_nano_interval())])
_check_pandas_roundtrip(
Expand Down
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