to_timedelta with ints result unit try to match input unit

Author: jbrockmendel

pandas/core/arrays/timedeltas.py

@@ -1205,7 +1205,9 @@ def _ints_to_td64ns(data, unit: str = "ns") -> tuple[np.ndarray, bool]:
         dtype_str = f"timedelta64[{unit}]"
         data = data.view(dtype_str)
 
-        data = astype_overflowsafe(data, dtype=TD64NS_DTYPE)
+        new_dtype = get_supported_dtype(data.dtype)
+        if new_dtype != data.dtype:
+            data = astype_overflowsafe(data, dtype=new_dtype)
 
         # the astype conversion makes a copy, so we can avoid re-copying later
         copy_made = True

pandas/tests/groupby/methods/test_quantile.py

@@ -363,15 +363,14 @@ def test_groupby_quantile_allNA_column(dtype):
 
 def test_groupby_timedelta_quantile():
     # GH: 29485
-    df = DataFrame(
-        {"value": pd.to_timedelta(np.arange(4), unit="s"), "group": [1, 1, 2, 2]}
-    )
+    tdi = pd.to_timedelta(np.arange(4), unit="s").as_unit("us")
+    df = DataFrame({"value": tdi, "group": [1, 1, 2, 2]})
     result = df.groupby("group").quantile(0.99)
     expected = DataFrame(
         {
             "value": [
-                pd.Timedelta("0 days 00:00:00.990000").as_unit("ns"),
-                pd.Timedelta("0 days 00:00:02.990000").as_unit("ns"),
+                pd.Timedelta("0 days 00:00:00.990000"),
+                pd.Timedelta("0 days 00:00:02.990000"),
             ]
         },
         index=Index([1, 2], name="group"),

pandas/tests/io/json/test_pandas.py

@@ -1156,7 +1156,8 @@ def test_timedelta(self):
 
         with tm.assert_produces_warning(Pandas4Warning, match=msg):
             json = frame.to_json()
-        tm.assert_frame_equal(frame, read_json(StringIO(json)).apply(converter))
+        result = read_json(StringIO(json)).apply(converter)
+        tm.assert_frame_equal(frame.astype("m8[ms]"), result)
 
     def test_timedelta2(self):
         frame = DataFrame(

pandas/tests/scalar/timedelta/test_constructors.py

@@ -155,9 +155,14 @@ def test_unit_deprecated(self, unit, unit_depr):
     def test_unit_parser(self, unit, np_unit, wrapper):
         # validate all units, GH 6855, GH 21762
         # array-likes
+        if wrapper is list:
+            # we go through _objects_to_td64ns which hasn't yet been updated
+            exp_unit = "ns"
+        else:
+            exp_unit = np_unit if np_unit not in ["W", "D", "m"] else "s"
         expected = TimedeltaIndex(
             [np.timedelta64(i, np_unit) for i in np.arange(5).tolist()],
-            dtype="m8[ns]",
+            dtype=f"m8[{exp_unit}]",
         )
 
         result = to_timedelta(wrapper(range(5)), unit=unit)

pandas/tests/tools/test_to_datetime.py

@@ -2111,7 +2111,7 @@ def test_dataframe_field_aliases_column_subset(self, df, cache, unit):
         result = to_datetime(df[list(unit.keys())].rename(columns=unit), cache=cache)
         expected = Series(
             [Timestamp("20150204 06:58:10"), Timestamp("20160305 07:59:11")],
-            dtype="M8[ns]",
+            dtype="M8[us]",
         )
         tm.assert_series_equal(result, expected)
 

pandas/tests/tools/test_to_timedelta.py

@@ -121,7 +121,7 @@ def test_to_timedelta_units_dtypes(self, dtype, unit):
         # arrays of various dtypes
         arr = np.array([1] * 5, dtype=dtype)
         result = to_timedelta(arr, unit=unit)
-        exp_dtype = "m8[ns]" if dtype == "int64" else "m8[s]"
+        exp_dtype = "m8[s]"
         expected = TimedeltaIndex([np.timedelta64(1, unit)] * 5, dtype=exp_dtype)
         tm.assert_index_equal(result, expected)
 
@@ -277,7 +277,7 @@ def test_to_timedelta_coerce_strings_unit(self):
     )
     def test_to_timedelta_nullable_int64_dtype(self, expected_val, result_val):
         # GH 35574
-        expected = Series([timedelta(days=1), expected_val], dtype="m8[ns]")
+        expected = Series([timedelta(days=1), expected_val], dtype="m8[s]")
         result = to_timedelta(Series([1, result_val], dtype="Int64"), unit="days")
 
         tm.assert_series_equal(result, expected)