Revert old change, ensure accounts for .unit

Author: mroeschke

pandas/core/arrays/_mixins.py

@@ -512,7 +512,9 @@ def _quantile(
         else:
             # e.g. test_quantile_empty we are empty integer dtype and res_values
             #  has floating dtype
-            return type(self)._from_sequence(res_values)  # type: ignore[call-arg]
+            # TODO: technically __init__ isn't defined here.
+            #  Should we raise NotImplementedError and handle this on NumpyEA?
+            return type(self)(res_values)  # type: ignore[call-arg]
 
     # ------------------------------------------------------------------------
     # numpy-like methods

pandas/core/arrays/datetimes.py

@@ -226,13 +226,16 @@ class DatetimeArray(dtl.TimelikeOps, dtl.DatelikeOps):
     """
 
     _typ = "datetimearray"
-    _internal_fill_value = np.datetime64("NaT", "ns")
     _recognized_scalars = (datetime, np.datetime64)
     _is_recognized_dtype: Callable[[DtypeObj], bool] = lambda x: lib.is_np_dtype(
         x, "M"
     ) or isinstance(x, DatetimeTZDtype)
     _infer_matches = ("datetime", "datetime64", "date")
 
+    @property
+    def _internal_fill_value(self) -> np.datetime64:
+        return np.datetime64("NaT", self.unit)
+
     @property
     def _scalar_type(self) -> type[Timestamp]:
         return Timestamp

pandas/core/arrays/timedeltas.py

@@ -154,11 +154,14 @@ class TimedeltaArray(dtl.TimelikeOps):
     """
 
     _typ = "timedeltaarray"
-    _internal_fill_value = np.timedelta64("NaT", "ns")
     _recognized_scalars = (timedelta, np.timedelta64, Tick)
     _is_recognized_dtype: Callable[[DtypeObj], bool] = lambda x: lib.is_np_dtype(x, "m")
     _infer_matches = ("timedelta", "timedelta64")
 
+    @property
+    def _internal_fill_value(self) -> np.timedelta64:
+        return np.timedelta64("NaT", self.unit)
+
     @property
     def _scalar_type(self) -> type[Timedelta]:
         return Timedelta