BUG: not converting scalars properly to M8/m8 on assignment (GH6079)

Author: jreback

pandas/core/common.py

@@ -8,6 +8,7 @@
 import codecs
 import csv
 import types
+from datetime import datetime, timedelta
 
 from numpy.lib.format import read_array, write_array
 import numpy as np
@@ -867,11 +868,14 @@ def _infer_dtype_from_scalar(val):
 
         dtype = np.object_
 
-    elif isinstance(val, np.datetime64):
-        # ugly hacklet
+    elif isinstance(val, (np.datetime64, datetime)) and getattr(val,'tz',None) is None:
         val = lib.Timestamp(val).value
         dtype = np.dtype('M8[ns]')
 
+    elif isinstance(val, (np.timedelta64, timedelta)):
+        val = tslib.convert_to_timedelta(val,'ns')
+        dtype = np.dtype('m8[ns]')
+
     elif is_bool(val):
         dtype = np.bool_
 

pandas/tests/test_frame.py

@@ -10495,7 +10495,17 @@ def test_rank2(self):
         assert_frame_equal(result, expected)
 
         # mixed-type frames
-        self.mixed_frame['foo'] = datetime.now()
+        self.mixed_frame['datetime'] = datetime.now()
+        self.mixed_frame['timedelta'] = timedelta(days=1,seconds=1)
+        self.assert_(self.mixed_frame['datetime'].dtype == 'M8[ns]')
+        self.assert_(self.mixed_frame['timedelta'].dtype == 'm8[ns]')
+        result = self.mixed_frame.get_dtype_counts().order()
+        expected = Series({ 'float64' : 4,
+                            'object' : 1,
+                            'datetime64[ns]' : 1,
+                            'timedelta64[ns]' : 1}).order()
+        assert_series_equal(result,expected)
+
         result = self.mixed_frame.rank(1)
         expected = self.mixed_frame.rank(1, numeric_only=True)
         assert_frame_equal(result, expected)