ENH: don't silently ignore dtype in NaT/Timestamp/Timedelta to_numpy

doc/source/whatsnew/v1.4.0.rst

@@ -210,6 +210,8 @@ Other enhancements
 - :meth:`read_excel` now accepts a ``decimal`` argument that allow the user to specify the decimal point when parsing string columns to numeric (:issue:`14403`)
 - :meth:`.GroupBy.mean` now supports `Numba <http://numba.pydata.org/>`_ execution with the ``engine`` keyword (:issue:`43731`)
 - :meth:`Timestamp.isoformat`, now handles the ``timespec`` argument from the base :class:``datetime`` class (:issue:`26131`)
+- :meth:`NaT.to_numpy` ``dtype`` argument is now respected, so ``np.timedelta64`` can be returned (:issue:`44460`)
+-
 
 .. ---------------------------------------------------------------------------
 

pandas/_libs/tslibs/nattype.pyi

@@ -18,7 +18,9 @@ class NaTType(datetime):
     value: np.int64
     def asm8(self) -> np.datetime64: ...
     def to_datetime64(self) -> np.datetime64: ...
-    def to_numpy(self, dtype=..., copy: bool = ...) -> np.datetime64: ...
+    def to_numpy(
+        self, dtype=..., copy: bool = ...
+    ) -> np.datetime64 | np.timedelta64: ...
     @property
     def is_leap_year(self) -> bool: ...
     @property

pandas/_libs/tslibs/nattype.pyx

@@ -258,19 +258,20 @@ cdef class _NaT(datetime):
         """
         return np.datetime64('NaT', "ns")
 
-    def to_numpy(self, dtype=None, copy=False) -> np.datetime64:
+    def to_numpy(self, dtype=None, copy=False) -> np.datetime64 | np.timedelta64:
         """
-        Convert the Timestamp to a NumPy datetime64.
+        Convert the Timestamp to a NumPy datetime64 or timedelta64.
 
         .. versionadded:: 0.25.0
 
-        This is an alias method for `Timestamp.to_datetime64()`. The dtype and
-        copy parameters are available here only for compatibility. Their values
+        With the default 'dtype', this is an alias method for `NaT.to_datetime64()`.
+
+        The copy parameter is available here only for compatibility. Its value
         will not affect the return value.
 
         Returns
         -------
-        numpy.datetime64
+        numpy.datetime64 or numpy.timedelta64
 
         See Also
         --------
@@ -286,7 +287,22 @@ cdef class _NaT(datetime):
 
         >>> pd.NaT.to_numpy()
         numpy.datetime64('NaT')
+
+        >>> pd.NaT.to_numpy("m8[ns]")
+        numpy.timedelta64('NaT','ns')
         """
+        if dtype is not None:
+            # GH#44460
+            dtype = np.dtype(dtype)
+            if dtype.kind == "M":
+                return np.datetime64("NaT").astype(dtype)
+            elif dtype.kind == "m":
+                return np.timedelta64("NaT").astype(dtype)
+            else:
+                raise ValueError(
+                    "NaT.to_numpy dtype must be a datetime64 dtype, timedelta64 "
+                    "dtype, or None."
+                )
         return self.to_datetime64()
 
     def __repr__(self) -> str:

pandas/_libs/tslibs/timedeltas.pyx

@@ -929,6 +929,10 @@ cdef class _Timedelta(timedelta):
         --------
         Series.to_numpy : Similar method for Series.
         """
+        if dtype is not None or copy is not False:
+            raise ValueError(
+                "Timedelta.to_numpy dtype and copy arguments are ignored"
+            )
         return self.to_timedelta64()
 
     def view(self, dtype):

pandas/_libs/tslibs/timestamps.pyx

@@ -934,6 +934,10 @@ cdef class _Timestamp(ABCTimestamp):
         >>> pd.NaT.to_numpy()
         numpy.datetime64('NaT')
         """
+        if dtype is not None or copy is not False:
+            raise ValueError(
+                "Timestamp.to_numpy dtype and copy arguments are ignored."
+            )
         return self.to_datetime64()
 
     def to_period(self, freq=None):

pandas/tests/scalar/test_nat.py

@@ -330,6 +330,11 @@ def test_nat_doc_strings(compare):
     if klass == Timestamp and method == "isoformat":
         return
 
+    if method == "to_numpy":
+        # GH#44460 can return either dt64 or td64 depending on dtype,
+        #  different docstring is intentional
+        return
+
     nat_doc = getattr(NaT, method).__doc__
     assert klass_doc == nat_doc
 
@@ -511,6 +516,22 @@ def test_to_numpy_alias():
 
     assert isna(expected) and isna(result)
 
+    # GH#44460
+    result = NaT.to_numpy("M8[s]")
+    assert isinstance(result, np.datetime64)
+    assert result.dtype == "M8[s]"
+
+    result = NaT.to_numpy("m8[ns]")
+    assert isinstance(result, np.timedelta64)
+    assert result.dtype == "m8[ns]"
+
+    result = NaT.to_numpy("m8[s]")
+    assert isinstance(result, np.timedelta64)
+    assert result.dtype == "m8[s]"
+
+    with pytest.raises(ValueError, match="NaT.to_numpy dtype must be a "):
+        NaT.to_numpy(np.int64)
+
 
 @pytest.mark.parametrize(
     "other",

pandas/tests/scalar/timedelta/test_timedelta.py

@@ -317,6 +317,13 @@ def test_to_numpy_alias(self):
         td = Timedelta("10m7s")
         assert td.to_timedelta64() == td.to_numpy()
 
+        # GH#44460
+        msg = "dtype and copy arguments are ignored"
+        with pytest.raises(ValueError, match=msg):
+            td.to_numpy("m8[s]")
+        with pytest.raises(ValueError, match=msg):
+            td.to_numpy(copy=True)
+
     @pytest.mark.parametrize(
         "freq,s1,s2",
         [

pandas/tests/scalar/timestamp/test_timestamp.py

@@ -619,6 +619,13 @@ def test_to_numpy_alias(self):
         ts = Timestamp(datetime.now())
         assert ts.to_datetime64() == ts.to_numpy()
 
+        # GH#44460
+        msg = "dtype and copy arguments are ignored"
+        with pytest.raises(ValueError, match=msg):
+            ts.to_numpy("M8[s]")
+        with pytest.raises(ValueError, match=msg):
+            ts.to_numpy(copy=True)
+
 
 class SubDatetime(datetime):
     pass