implement TimedeltaArray asm8, to_timedelta64

pandas/core/arrays/datetimes.py

@@ -707,6 +707,22 @@ def tz_localize(self, tz, ambiguous='raise', errors='raise'):
     # ----------------------------------------------------------------
     # Conversion Methods - Vectorized analogues of Timestamp methods
 
+    def to_datetime64(self):
+        """
+        Return numpy datetime64[ns] representation of self.  For timezone-aware
+        cases, the returned array represents UTC timestamps.
+
+        Returns
+        -------
+        ndarray[datetime64[ns]]
+        """
+        return self.asi8.view('M8[ns]')
+
+    @property
+    def asm8(self):
+        """Vectorized analogue of Timestamp.asm8"""
+        return self.to_datetime64()
+
     def to_pydatetime(self):
         """
         Return Datetime Array/Index as object ndarray of datetime.datetime

pandas/core/arrays/timedeltas.py

@@ -355,6 +355,31 @@ def to_pytimedelta(self):
         """
         return tslibs.ints_to_pytimedelta(self.asi8)
 
+    def to_timedelta64(self):
+        """
+        Return numpy array with timedelta64[ns] dtype
+
+        Returns
+        -------
+        ndarray[timedelta64[ns]]
+
+        Notes
+        -----
+        This returns a view on self, not a copy.
+
+        See also
+        --------
+        Timedelta.to_timedelta64
+        """
+        return self.asi8.view('m8[ns]')
+
+    @property
+    def asm8(self):
+        """
+        Vectorized analogue of Timedelta.asm8
+        """
+        return self.to_timedelta64()
+
     days = _field_accessor("days", "days",
                            " Number of days for each element. ")
     seconds = _field_accessor("seconds", "seconds",

pandas/tests/arrays/test_datetimelike.py

@@ -106,6 +106,30 @@ def test_to_period(self, datetime_index, freqstr):
         #  an EA-specific tm.assert_ function
         tm.assert_index_equal(pd.Index(result), pd.Index(expected))
 
+    def test_asm8(self, datetime_index):
+        dti = datetime_index
+        arr = DatetimeArrayMixin(dti)
+
+        expected = np.array([x.asm8 for x in dti], dtype='M8[ns]')
+
+        result = dti.asm8
+        tm.assert_numpy_array_equal(result, expected)
+
+        result = arr.asm8
+        tm.assert_numpy_array_equal(result, expected)
+
+    def test_to_datetime64(self, datetime_index):
+        dti = datetime_index
+        arr = DatetimeArrayMixin(dti)
+
+        expected = np.array([x.asm8 for x in dti], dtype='M8[ns]')
+
+        result = dti.to_datetime64()
+        tm.assert_numpy_array_equal(result, expected)
+
+        result = arr.to_datetime64()
+        tm.assert_numpy_array_equal(result, expected)
+
     @pytest.mark.parametrize('propname', pd.DatetimeIndex._bool_ops)
     def test_bool_properties(self, datetime_index, propname):
         # in this case _bool_ops is just `is_leap_year`
@@ -148,6 +172,30 @@ def test_astype_object(self):
         assert asobj.dtype == 'O'
         assert list(asobj) == list(tdi)
 
+    def test_asm8(self):
+        tdi = pd.TimedeltaIndex(['1 Hour', '3 Hours'])
+        arr = TimedeltaArrayMixin(tdi)
+
+        expected = np.array([3600, 10800], dtype='m8[ns]') * 1e9
+
+        result = tdi.asm8
+        tm.assert_numpy_array_equal(result, expected)
+
+        result = arr.asm8
+        tm.assert_numpy_array_equal(result, expected)
+
+    def test_to_timedelta64(self):
+        tdi = pd.TimedeltaIndex(['1 Hour', '3 Hours'])
+        arr = TimedeltaArrayMixin(tdi)
+
+        expected = np.array([3600, 10800], dtype='m8[ns]') * 1e9
+
+        result = tdi.to_timedelta64()
+        tm.assert_numpy_array_equal(result, expected)
+
+        result = arr.to_timedelta64()
+        tm.assert_numpy_array_equal(result, expected)
+
     def test_to_pytimedelta(self, timedelta_index):
         tdi = timedelta_index
         arr = TimedeltaArrayMixin(tdi)