Merge branch 'cummin-NaT' of https://github.com/unutbu/pandas into unutbu-cummin-NaT

Conflicts:
	doc/source/whatsnew/v0.15.2.txt

Author: jreback

doc/source/whatsnew/v0.15.2.txt

@@ -172,5 +172,8 @@ Bug Fixes
 
 
 
+
 - Bug in `StataWriter` the produces writes strings with 244 characters irrespective of actual size (:issue:`8969`)
 
+
+- Fixed ValueError raised by cummin/cummax when datetime64 Series contains NaT. (:issue:`8965`)

pandas/core/generic.py

@@ -4114,13 +4114,17 @@ def func(self, axis=None, dtype=None, out=None, skipna=True,
                     axis = self._get_axis_number(axis)
 
                 y = _values_from_object(self).copy()
-                if not issubclass(y.dtype.type, (np.integer, np.bool_)):
+
+                if skipna and issubclass(y.dtype.type, 
+                                         (np.datetime64, np.timedelta64)):
+                    result = accum_func(y, axis)
+                    mask = isnull(self)
+                    np.putmask(result, mask, pd.tslib.iNaT)
+                elif skipna and not issubclass(y.dtype.type, (np.integer, np.bool_)):
                     mask = isnull(self)
-                    if skipna:
-                        np.putmask(y, mask, mask_a)
+                    np.putmask(y, mask, mask_a)
                     result = accum_func(y, axis)
-                    if skipna:
-                        np.putmask(result, mask, mask_b)
+                    np.putmask(result, mask, mask_b)
                 else:
                     result = accum_func(y, axis)
 

pandas/tests/test_series.py

@@ -2309,6 +2309,62 @@ def test_cummax(self):
 
         self.assert_numpy_array_equal(result, expected)
 
+    def test_cummin_datetime64(self):
+        s = pd.Series(pd.to_datetime(
+            ['NaT', '2000-1-2', 'NaT', '2000-1-1', 'NaT', '2000-1-3']))
+
+        expected = pd.Series(pd.to_datetime(
+            ['NaT', '2000-1-2', 'NaT', '2000-1-1', 'NaT', '2000-1-1']))
+        result = s.cummin(skipna=True)
+        self.assert_series_equal(expected, result)
+
+        expected = pd.Series(pd.to_datetime(
+            ['NaT', '2000-1-2', '2000-1-2', '2000-1-1', '2000-1-1', '2000-1-1']))
+        result = s.cummin(skipna=False)
+        self.assert_series_equal(expected, result)
+
+    def test_cummax_datetime64(self):
+        s = pd.Series(pd.to_datetime(
+            ['NaT', '2000-1-2', 'NaT', '2000-1-1', 'NaT', '2000-1-3']))
+
+        expected = pd.Series(pd.to_datetime(
+            ['NaT', '2000-1-2', 'NaT', '2000-1-2', 'NaT', '2000-1-3']))
+        result = s.cummax(skipna=True)
+        self.assert_series_equal(expected, result)
+
+        expected = pd.Series(pd.to_datetime(
+            ['NaT', '2000-1-2', '2000-1-2', '2000-1-2', '2000-1-2', '2000-1-3']))
+        result = s.cummax(skipna=False)
+        self.assert_series_equal(expected, result)
+
+    def test_cummin_timedelta64(self):
+        s = pd.Series(pd.to_timedelta(
+            ['NaT', '2 min', 'NaT', '1 min', 'NaT', '3 min', ]))
+
+        expected = pd.Series(pd.to_timedelta(
+            ['NaT', '2 min', 'NaT', '1 min', 'NaT', '1 min', ]))
+        result = s.cummin(skipna=True)
+        self.assert_series_equal(expected, result)
+
+        expected = pd.Series(pd.to_timedelta(
+            ['NaT', '2 min', '2 min', '1 min', '1 min', '1 min', ]))
+        result = s.cummin(skipna=False)
+        self.assert_series_equal(expected, result)
+
+    def test_cummax_timedelta64(self):
+        s = pd.Series(pd.to_timedelta(
+            ['NaT', '2 min', 'NaT', '1 min', 'NaT', '3 min', ]))
+
+        expected = pd.Series(pd.to_timedelta(
+            ['NaT', '2 min', 'NaT', '2 min', 'NaT', '3 min', ]))
+        result = s.cummax(skipna=True)
+        self.assert_series_equal(expected, result)
+
+        expected = pd.Series(pd.to_timedelta(
+            ['NaT', '2 min', '2 min', '2 min', '2 min', '3 min', ]))
+        result = s.cummax(skipna=False)
+        self.assert_series_equal(expected, result)
+
     def test_npdiff(self):
         raise nose.SkipTest("skipping due to Series no longer being an "
                             "ndarray")