BUG: Regression from 0.13 in the treatment of numpy datetime64 non-ns dtypes in Series creation (GH6429)

doc/source/release.rst

@@ -195,6 +195,7 @@ Bug Fixes
   fail (:issue:`6445`).
 - Bug in multi-axis indexing using ``.loc`` on non-unique indices (:issue:`6504`)
 - Bug that caused _ref_locs corruption when slice indexing across columns axis of a DataFrame (:issue:`6525`)
+- Regression from 0.13 in the treatmenet of numpy ``datetime64`` non-ns dtypes in Series creation (:issue:`6529`)
 
 pandas 0.13.1
 -------------

pandas/core/common.py

@@ -124,7 +124,7 @@ def isnull(obj):
 
     See also
     --------
-    pandas.notnull: boolean inverse of pandas.isnull    
+    pandas.notnull: boolean inverse of pandas.isnull
     """
     return _isnull(obj)
 
@@ -272,7 +272,7 @@ def notnull(obj):
     isnulled : array-like of bool or bool
         Array or bool indicating whether an object is *not* null or if an array
         is given which of the element is *not* null.
-    
+
     See also
     --------
     pandas.isnull : boolean inverse of pandas.notnull
@@ -1727,10 +1727,7 @@ def _possibly_cast_to_datetime(value, dtype, coerce=False):
             dtype = value.dtype
 
             if dtype.kind == 'M' and dtype != _NS_DTYPE:
-                try:
-                    value = tslib.array_to_datetime(value)
-                except:
-                    raise
+                value = value.astype(_NS_DTYPE)
 
             elif dtype.kind == 'm' and dtype != _TD_DTYPE:
                 from pandas.tseries.timedeltas import \

pandas/tests/test_series.py

@@ -600,6 +600,25 @@ def test_constructor_dtype_datetime64(self):
         self.assertEqual(result['a'], Timestamp('20130101'))
         self.assertEqual(result['b'], 1)
 
+        # GH6529
+        # coerce datetime64 non-ns properly
+        dates = date_range('01-Jan-2015', '01-Dec-2015', freq='M')
+        values2 = dates.view(np.ndarray).astype('datetime64[ns]')
+        expected = Series(values2, dates)
+
+        # numpy < 1.7 is very odd about astyping
+        if not _np_version_under1p7:
+            for dtype in ['s','D','ms','us','ns']:
+                values1 = dates.view(np.ndarray).astype('M8[{0}]'.format(dtype))
+                result = Series(values1, dates)
+                assert_series_equal(result,expected)
+
+        # leave datetime.date alone
+        dates2 = np.array([ d.date() for d in dates.to_pydatetime() ],dtype=object)
+        series1 = Series(dates2, dates)
+        self.assert_numpy_array_equal(series1.values,dates2)
+        self.assertEqual(series1.dtype,object)
+
     def test_constructor_dict(self):
         d = {'a': 0., 'b': 1., 'c': 2.}
         result = Series(d, index=['b', 'c', 'd', 'a'])