Assignment of column via .loc for numpy non-ns datetimes (#27928)

Author: inmoonlight

doc/source/whatsnew/v0.25.2.rst

@@ -52,7 +52,6 @@ Indexing
 -
 -
 -
--
 
 Missing
 ^^^^^^^

doc/source/whatsnew/v1.0.0.rst

@@ -170,6 +170,7 @@ Indexing
 
 - Bug in assignment using a reverse slicer (:issue:`26939`)
 - Bug in reindexing a :meth:`PeriodIndex` with another type of index that contained a `Period` (:issue:`28323`) (:issue:`28337`)
+- Fix assignment of column via `.loc` with numpy non-ns datetime type (:issue:`27395`)
 
 Missing
 ^^^^^^^

pandas/core/dtypes/cast.py

@@ -1029,7 +1029,10 @@ def maybe_cast_to_datetime(value, dtype, errors="raise"):
             )
 
             if is_datetime64 and not is_dtype_equal(dtype, _NS_DTYPE):
-                if dtype.name in ("datetime64", "datetime64[ns]"):
+
+                # pandas supports dtype whose granularity is less than [ns]
+                # e.g., [ps], [fs], [as]
+                if dtype <= np.dtype("M8[ns]"):
                     if dtype.name == "datetime64":
                         raise ValueError(msg.format(dtype=dtype.name))
                     dtype = _NS_DTYPE
@@ -1047,7 +1050,10 @@ def maybe_cast_to_datetime(value, dtype, errors="raise"):
                     value = [value]
 
             elif is_timedelta64 and not is_dtype_equal(dtype, _TD_DTYPE):
-                if dtype.name in ("timedelta64", "timedelta64[ns]"):
+
+                # pandas supports dtype whose granularity is less than [ns]
+                # e.g., [ps], [fs], [as]
+                if dtype <= np.dtype("m8[ns]"):
                     if dtype.name == "timedelta64":
                         raise ValueError(msg.format(dtype=dtype.name))
                     dtype = _TD_DTYPE

pandas/tests/indexing/test_loc.py

@@ -690,6 +690,28 @@ def test_loc_setitem_consistency_slice_column_len(self):
         )
         tm.assert_series_equal(df[("Respondent", "Duration")], expected)
 
+    @pytest.mark.parametrize("unit", ["Y", "M", "D", "h", "m", "s", "ms", "us"])
+    def test_loc_assign_non_ns_datetime(self, unit):
+        # GH 27395, non-ns dtype assignment via .loc should work
+        # and return the same result when using simple assignment
+        df = DataFrame(
+            {
+                "timestamp": [
+                    np.datetime64("2017-02-11 12:41:29"),
+                    np.datetime64("1991-11-07 04:22:37"),
+                ]
+            }
+        )
+
+        df.loc[:, unit] = df.loc[:, "timestamp"].values.astype(
+            "datetime64[{unit}]".format(unit=unit)
+        )
+        df["expected"] = df.loc[:, "timestamp"].values.astype(
+            "datetime64[{unit}]".format(unit=unit)
+        )
+        expected = Series(df.loc[:, "expected"], name=unit)
+        tm.assert_series_equal(df.loc[:, unit], expected)
+
     def test_loc_setitem_frame(self):
         df = self.frame_labels