[Python] Simplify arrow_to_pandas DateOffset handling for nanoseconds/milliseconds

Describe the enhancement requested

When dropping support for older pandas we discussed whether the following code could be simplified:

arrow/python/pyarrow/src/arrow/python/arrow_to_pandas.cc

Lines 1286 to 1320 in 97b8678

    
           template <typename Type> 
        
           enable_if_t<std::is_same<Type, MonthDayNanoIntervalType>::value, Status> Visit( 
        
               const Type& type) { 
        
             OwnedRef args(PyTuple_New(0)); 
        
             OwnedRef kwargs(PyDict_New()); 
        
             RETURN_IF_PYERROR(); 
        
             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)); 
        
               *out = 
        
                   PyObject_Call(internal::BorrowPandasDataOffsetType(), args.obj(), kwargs.obj()); 
        
               RETURN_IF_PYERROR(); 
        
               return Status::OK(); 
        
             }; 
        
             return ConvertAsPyObjects<MonthDayNanoIntervalType>(options, data, to_date_offset, 
        
                                                                 out_values); 
        
           }

Link to description:
#50444 (comment)

It seems it could be with something like:

$ git diff
diff --git a/python/pyarrow/src/arrow/python/arrow_to_pandas.cc b/python/pyarrow/src/arrow/python/arrow_to_pandas.cc
index 348d352a04..581da12577 100644
--- a/python/pyarrow/src/arrow/python/arrow_to_pandas.cc
+++ b/python/pyarrow/src/arrow/python/arrow_to_pandas.cc
@@ -1292,24 +1292,10 @@ 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));
       *out =
           PyObject_Call(internal::BorrowPandasDataOffsetType(), args.obj(), kwargs.obj());
       RETURN_IF_PYERROR();

but as shared on the PR comment it might cause a UX change. Nowadays we don't roundtrip hours/minutes on DateOffset, we show microseconds and nanoseconds. With a change like the above we will be consistent and we would show, Month/Day/Nano instead of Month/Day/Microseconds/Nano.

This issue is to track this code simplifaction.

Component(s)

Python

Issue resolved by pull request 50465
#50465

apacheGH-50464: [C++][Python] Simplify arrow_to_pandas DateOffset han…

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[Python] Simplify arrow_to_pandas DateOffset handling for nanoseconds/milliseconds #50464

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	template <typename Type>
	enable_if_t<std::is_same<Type, MonthDayNanoIntervalType>::value, Status> Visit(
	const Type& type) {
	OwnedRef args(PyTuple_New(0));
	OwnedRef kwargs(PyDict_New());
	RETURN_IF_PYERROR();
	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));
	*out =
	PyObject_Call(internal::BorrowPandasDataOffsetType(), args.obj(), kwargs.obj());
	RETURN_IF_PYERROR();
	return Status::OK();
	};
	return ConvertAsPyObjects<MonthDayNanoIntervalType>(options, data, to_date_offset,
	out_values);
	}

[Python] Simplify arrow_to_pandas DateOffset handling for nanoseconds/milliseconds #50464

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Describe the enhancement requested

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raulcd commented on Jul 23, 2026

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