ENH: Handle generic timestamp dtypes with Series

We only use the nanosecond frequency, so generic
timestamp frequencies should be interpreted with
the nanosecond frequency.

xref gh-15524 (comment).

doc/source/whatsnew/v0.20.0.txt

@@ -320,6 +320,7 @@ Other Enhancements
 ^^^^^^^^^^^^^^^^^^
 
 - Integration with the ``feather-format``, including a new top-level ``pd.read_feather()`` and ``DataFrame.to_feather()`` method, see :ref:`here <io.feather>`.
+- The ``Series`` constructor will now accept timestamp dtypes that do not specify frequency like ``np.datetime64`` (:issue:`15524`)
 - ``Series.str.replace()`` now accepts a callable, as replacement, which is passed to ``re.sub`` (:issue:`15055`)
 - ``Series.str.replace()`` now accepts a compiled regular expression as a pattern (:issue:`15446`)
 

pandas/core/internals.py

@@ -492,6 +492,14 @@ def _astype(self, dtype, copy=False, errors='raise', values=None,
                 return self.copy()
             return self
 
+        # numpy arrays don't handle generic timestamp dtypes well. Since
+        # we only use the nanosecond frequency, interpret generic timestamp
+        # dtypes as nanosecond frequency.
+        if dtype.name == "datetime64":
+            dtype = np.dtype('M8[ns]')
+        elif dtype.name == "timedelta64":
+            dtype = np.dtype('m8[ns]')
+
         if klass is None:
             if dtype == np.object_:
                 klass = ObjectBlock

pandas/tests/series/test_constructors.py

@@ -839,3 +839,27 @@ def test_constructor_cast_object(self):
         s = Series(date_range('1/1/2000', periods=10), dtype=object)
         exp = Series(date_range('1/1/2000', periods=10))
         tm.assert_series_equal(s, exp)
+
+    def test_constructor_generic_timestamp(self):
+        # see gh-15524
+        dtype = np.timedelta64
+        s = Series([], dtype=dtype)
+
+        self.assertTrue(s.empty)
+        self.assertEqual(s.dtype, 'm8[ns]')
+
+        dtype = np.datetime64
+        s = Series([], dtype=dtype)
+
+        self.assertTrue(s.empty)
+        self.assertEqual(s.dtype, 'M8[ns]')
+
+        # These timestamps have the wrong frequencies,
+        # so an Exception should be raised now.
+        msg = "cannot convert timedeltalike"
+        with tm.assertRaisesRegexp(TypeError, msg):
+            Series([], dtype='m8[ps]')
+
+        msg = "cannot convert datetimelike"
+        with tm.assertRaisesRegexp(TypeError, msg):
+            Series([], dtype='M8[ps]')

pandas/tests/series/test_dtypes.py

@@ -153,6 +153,31 @@ def test_astype_dict(self):
         self.assertRaises(KeyError, s.astype, {'abc': str, 'def': str})
         self.assertRaises(KeyError, s.astype, {0: str})
 
+    def test_astype_generic_timestamp(self):
+        # see gh-15524
+        data = [1]
+
+        s = Series(data)
+        dtype = np.datetime64
+        result = s.astype(dtype)
+        expected = Series(data, dtype=dtype)
+        assert_series_equal(result, expected)
+
+        s = Series(data)
+        dtype = np.timedelta64
+        result = s.astype(dtype)
+        expected = Series(data, dtype=dtype)
+        assert_series_equal(result, expected)
+
+    def test_astype_empty_constructor_equality(self):
+        # see gh-15524
+
+        for dtype in np.typecodes['All']:
+            if dtype != 'V':  # not supported
+                init_empty = Series([], dtype=dtype)
+                astype_empty = Series([]).astype(dtype)
+                assert_series_equal(init_empty, astype_empty)
+
     def test_complexx(self):
         # GH4819
         # complex access for ndarray compat

pandas/types/cast.py

@@ -855,7 +855,7 @@ def maybe_cast_to_datetime(value, dtype, errors='raise'):
 
             # force the dtype if needed
             if is_datetime64 and not is_dtype_equal(dtype, _NS_DTYPE):
-                if dtype.name == 'datetime64[ns]':
+                if dtype.name in ('datetime64', 'datetime64[ns]'):
                     dtype = _NS_DTYPE
                 else:
                     raise TypeError("cannot convert datetimelike to "
@@ -869,7 +869,7 @@ 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 == 'timedelta64[ns]':
+                if dtype.name in ('timedelta64', 'timedelta64[ns]'):
                     dtype = _TD_DTYPE
                 else:
                     raise TypeError("cannot convert timedeltalike to "