BUG/API: df['col'] = value and df.loc[:,'col'] = value are now completely equivalent

doc/source/release.rst

@@ -63,6 +63,8 @@ API Changes
   values. A single indexer that is out-of-bounds and drops the dimensions of the object will still raise
   ``IndexError`` (:issue:`6296`)
 - ``select_as_multiple`` will always raise a ``KeyError``, when a key or the selector is not found (:issue:`6177`)
+- ``df['col'] = value`` and ``df.loc[:,'col'] = value`` are now completely equivalent;
+  previously the ``.loc`` would not necessarily coerce the dtype of the resultant series (:issue:`6149`)
 
 Experimental Features
 ~~~~~~~~~~~~~~~~~~~~~

pandas/core/indexing.py

@@ -394,10 +394,18 @@ def setter(item, v):
                 s = self.obj[item]
                 pi = plane_indexer[0] if lplane_indexer == 1 else plane_indexer
 
-                # set the item, possibly having a dtype change
-                s = s.copy()
-                s._data = s._data.setitem(indexer=pi, value=v)
-                s._maybe_update_cacher(clear=True)
+                # perform the equivalent of a setitem on the info axis
+                # as we have a null slice which means essentially reassign to the columns
+                # of a multi-dim object
+                # GH6149
+                if isinstance(pi, tuple) and all(_is_null_slice(idx) for idx in pi):
+                    s = v
+                else:
+                    # set the item, possibly having a dtype change
+                    s = s.copy()
+                    s._data = s._data.setitem(indexer=pi, value=v)
+                    s._maybe_update_cacher(clear=True)
+
                 self.obj[item] = s
 
             def can_do_equal_len():

pandas/tests/test_indexing.py

@@ -690,6 +690,52 @@ def test_loc_general(self):
         assert_series_equal(result,expected)
         self.assertEqual(result.dtype, object)
 
+    def test_loc_setitem_consistency(self):
+
+        # GH 6149
+        # coerce similary for setitem and loc when rows have a null-slice
+        expected = DataFrame({ 'date': Series(0,index=range(5),dtype=np.int64),
+                               'val' : Series(range(5),dtype=np.int64) })
+
+        df = DataFrame({ 'date': date_range('2000-01-01','2000-01-5'),
+                         'val' : Series(range(5),dtype=np.int64) })
+        df.loc[:,'date'] = 0
+        assert_frame_equal(df,expected)
+
+        df = DataFrame({ 'date': date_range('2000-01-01','2000-01-5'),
+                         'val' : Series(range(5),dtype=np.int64) })
+        df.loc[:,'date'] = np.array(0,dtype=np.int64)
+        assert_frame_equal(df,expected)
+
+        df = DataFrame({ 'date': date_range('2000-01-01','2000-01-5'),
+                         'val' : Series(range(5),dtype=np.int64) })
+        df.loc[:,'date'] = np.array([0,0,0,0,0],dtype=np.int64)
+        assert_frame_equal(df,expected)
+
+        expected = DataFrame({ 'date': Series('foo',index=range(5)),
+                               'val' : Series(range(5),dtype=np.int64) })
+        df = DataFrame({ 'date': date_range('2000-01-01','2000-01-5'),
+                         'val' : Series(range(5),dtype=np.int64) })
+        df.loc[:,'date'] = 'foo'
+        assert_frame_equal(df,expected)
+
+        expected = DataFrame({ 'date': Series(1.0,index=range(5)),
+                               'val' : Series(range(5),dtype=np.int64) })
+        df = DataFrame({ 'date': date_range('2000-01-01','2000-01-5'),
+                         'val' : Series(range(5),dtype=np.int64) })
+        df.loc[:,'date'] = 1.0
+        assert_frame_equal(df,expected)
+
+        # empty (essentially noops)
+        expected = DataFrame(columns=['x', 'y'])
+        df = DataFrame(columns=['x', 'y'])
+        df.loc[:, 'x'] = 1
+        assert_frame_equal(df,expected)
+
+        df = DataFrame(columns=['x', 'y'])
+        df['x'] = 1
+        assert_frame_equal(df,expected)
+
     def test_loc_setitem_frame(self):
         df = self.frame_labels