BUG: to_datetime re-parsing Arrow-backed objects

doc/source/whatsnew/v2.1.0.rst

@@ -315,11 +315,11 @@ Datetimelike
 ^^^^^^^^^^^^
 - :meth:`DatetimeIndex.map` with ``na_action="ignore"`` now works as expected. (:issue:`51644`)
 - Bug in :func:`date_range` when ``freq`` was a :class:`DateOffset` with ``nanoseconds`` (:issue:`46877`)
+- Bug in :func:`to_datetime` converting :class:`Series` or :class:`DataFrame` containing :class:`arrays.ArrowExtensionArray` of ``pyarrow`` timestamps to numpy datetimes (:issue:`52545`)
 - Bug in :meth:`Timestamp.round` with values close to the implementation bounds returning incorrect results instead of raising ``OutOfBoundsDatetime`` (:issue:`51494`)
 - Bug in :meth:`arrays.DatetimeArray.map` and :meth:`DatetimeIndex.map`, where the supplied callable operated array-wise instead of element-wise (:issue:`51977`)
 - Bug in constructing a :class:`Series` or :class:`DataFrame` from a datetime or timedelta scalar always inferring nanosecond resolution instead of inferring from the input (:issue:`52212`)
 - Bug in parsing datetime strings with weekday but no day e.g. "2023 Sept Thu" incorrectly raising ``AttributeError`` instead of ``ValueError`` (:issue:`52659`)
--
 
 Timedelta
 ^^^^^^^^^

pandas/core/tools/datetimes.py

@@ -57,7 +57,10 @@
     is_list_like,
     is_numeric_dtype,
 )
-from pandas.core.dtypes.dtypes import DatetimeTZDtype
+from pandas.core.dtypes.dtypes import (
+    ArrowDtype,
+    DatetimeTZDtype,
+)
 from pandas.core.dtypes.generic import (
     ABCDataFrame,
     ABCSeries,
@@ -400,6 +403,16 @@ def _convert_listlike_datetimes(
             arg = arg.tz_convert(None).tz_localize("utc")
         return arg
 
+    elif isinstance(arg_dtype, ArrowDtype) and arg_dtype.kind == "M":
+        # TODO: Combine with above if DTI/DTA supports Arrow timestamps
+        if utc:
+            import pyarrow as pa
+
+            # array attribute has to exist since arg is Index/Series at this point
+            arg_arr = arg.array._pa_array
+            arg._pa_array = arg_arr.cast(pa.timestamp(arg_arr.type.unit, "utc"))
+        return arg
+
     elif lib.is_np_dtype(arg_dtype, "M"):
         arg_dtype = cast(np.dtype, arg_dtype)
         if not is_supported_unit(get_unit_from_dtype(arg_dtype)):

pandas/tests/tools/test_to_datetime.py

@@ -933,6 +933,19 @@ def test_to_datetime_dtarr(self, tz):
         result = to_datetime(arr)
         assert result is arr
 
+    @pytest.mark.parametrize("utc", [True, False])
+    @pytest.mark.parametrize("tz", [None, "US/Central"])
+    def test_to_datetime_arrow(self, tz, utc):
+        pa = pytest.importorskip("pyarrow")
+
+        dti = date_range("1965-04-03", periods=19, freq="2W", tz=tz)
+        dti_arrow = dti.astype(pd.ArrowDtype(pa.timestamp(unit="ns")))
+
+        result = to_datetime(dti_arrow, utc=utc)
+        expected = to_datetime(dti, utc=utc).astype("timestamp[ns][pyarrow]")
+        assert result is dti_arrow
+        tm.assert_index_equal(result, expected, exact=False)
+
     def test_to_datetime_pydatetime(self):
         actual = to_datetime(datetime(2008, 1, 15))
         assert actual == datetime(2008, 1, 15)