BUG: to_timedelta/datetime with numeric ArrowExtensionArray

doc/source/whatsnew/v2.0.1.rst

@@ -20,7 +20,7 @@ Fixed regressions
 
 Bug fixes
 ~~~~~~~~~
--
+- Bug in :func:`to_datetime` and :func:`to_timedelta` when trying to convert numeric data with a :class:`ArrowDtype` (:issue:`52425`)
 
 .. ---------------------------------------------------------------------------
 .. _whatsnew_201.other:

pandas/core/arrays/datetimelike.py

@@ -127,6 +127,7 @@
     NDArrayBackedExtensionArray,
     ravel_compat,
 )
+from pandas.core.arrays.arrow.array import ArrowExtensionArray
 from pandas.core.arrays.base import ExtensionArray
 from pandas.core.arrays.integer import IntegerArray
 import pandas.core.common as com
@@ -2209,10 +2210,14 @@ def ensure_arraylike_for_datetimelike(data, copy: bool, cls_name: str):
     else:
         data = extract_array(data, extract_numpy=True)
 
-    if isinstance(data, IntegerArray):
+    if isinstance(data, IntegerArray) or (
+        isinstance(data, ArrowExtensionArray) and data.dtype.kind in "iu"
+    ):
         data = data.to_numpy("int64", na_value=iNaT)
         copy = False
-    elif not isinstance(data, (np.ndarray, ExtensionArray)):
+    elif not isinstance(data, (np.ndarray, ExtensionArray)) or isinstance(
+        data, ArrowExtensionArray
+    ):
         # GH#24539 e.g. xarray, dask object
         data = np.asarray(data)
 

pandas/tests/tools/test_to_datetime.py

@@ -3586,3 +3586,12 @@ def test_ignoring_unknown_tz_deprecated():
     with tm.assert_produces_warning(FutureWarning):
         res = to_datetime([dtstr])
     tm.assert_index_equal(res, to_datetime([dtstr[:-5]]))
+
+
+def test_from_numeric_arrow_dtype(any_numeric_ea_dtype):
+    # GH 52425
+    pytest.importorskip("pyarrow")
+    ser = Series([1, 2], dtype=f"{any_numeric_ea_dtype.lower()}[pyarrow]")
+    result = to_datetime(ser)
+    expected = Series([1, 2], dtype="datetime64[ns]")
+    tm.assert_series_equal(result, expected)

pandas/tests/tools/test_to_timedelta.py

@@ -287,3 +287,12 @@ def test_to_timedelta_numeric_ea(self, any_numeric_ea_dtype):
         result = to_timedelta(ser)
         expected = Series([pd.Timedelta(1, unit="ns"), pd.NaT])
         tm.assert_series_equal(result, expected)
+
+
+def test_from_numeric_arrow_dtype(any_numeric_ea_dtype):
+    # GH 52425
+    pytest.importorskip("pyarrow")
+    ser = Series([1, 2], dtype=f"{any_numeric_ea_dtype.lower()}[pyarrow]")
+    result = to_timedelta(ser)
+    expected = Series([1, 2], dtype="timedelta64[ns]")
+    tm.assert_series_equal(result, expected)