Disable M8 in nanops

Closes pandas-dev#24752

pandas/core/nanops.py

@@ -437,6 +437,7 @@ def nansum(values, axis=None, skipna=True, min_count=0, mask=None):
     return _wrap_results(the_sum, dtype)
 
 
+@disallow('M8')
 @bottleneck_switch()
 def nanmean(values, axis=None, skipna=True, mask=None):
     """

pandas/tests/frame/test_analytics.py

@@ -794,6 +794,22 @@ def test_mean(self, float_frame_with_na, float_frame, float_string_frame):
                             check_dates=True)
         assert_stat_op_api('mean', float_frame, float_string_frame)
 
+    def test_mean_mixed_datetime_numeric(self):
+        # https://github.com/pandas-dev/pandas/issues/24752
+        df = pd.DataFrame({"A": [1, 1], "B": [pd.Timestamp('2000')] * 2})
+        result = df.mean()
+        expected = pd.Series([1.0], index=['A'])
+        tm.assert_series_equal(result, expected)
+
+    def test_mean_excludeds_datetimes(self):
+        # https://github.com/pandas-dev/pandas/issues/24752
+        # Our long-term desired behavior is unclear, but the behavior in
+        # 0.24.0rc1 was buggy.
+        df = pd.DataFrame({"A": [pd.Timestamp('2000')] * 2})
+        result = df.mean()
+        expected = pd.Series()
+        tm.assert_series_equal(result, expected)
+
     def test_product(self, float_frame_with_na, float_frame,
                      float_string_frame):
         assert_stat_op_calc('product', np.prod, float_frame_with_na)

pandas/tests/test_nanops.py

@@ -971,6 +971,9 @@ def prng(self):
 
 class TestDatetime64NaNOps(object):
     @pytest.mark.parametrize('tz', [None, 'UTC'])
+    @pytest.mark.xfail(reason="disabled")
+    # Enabling mean changes the behavior of DataFrame.mean
+    # See https://github.com/pandas-dev/pandas/issues/24752
     def test_nanmean(self, tz):
         dti = pd.date_range('2016-01-01', periods=3, tz=tz)
         expected = dti[1]