ENH: exclude nuisance columns in GroupBy.transform, close #1364

RELEASE.rst

@@ -112,7 +112,7 @@ pandas 0.8.0
   - Enable storage of sparse data structures in HDFStore (#85)
   - Enable Series.asof to work with arrays of timestamp inputs
   - Cython implementation of DataFrame.corr speeds up by > 100x (#1349, #1354)
-
+  - Exclude "nuisance" columns automatically in GroupBy.transform (#1364)
 
 **API Changes**
 

pandas/core/groupby.py

@@ -1626,14 +1626,17 @@ def transform(self, func, *args, **kwargs):
         obj = self._obj_with_exclusions
         gen = self.grouper.get_iterator(obj, axis=self.axis)
 
+        wrapper = lambda x: func(x, *args, **kwargs)
+
         for name, group in gen:
             object.__setattr__(group, 'name', name)
 
             try:
-                wrapper = lambda x: func(x, *args, **kwargs)
                 res = group.apply(wrapper, axis=self.axis)
+            except TypeError:
+                return self._transform_item_by_item(obj, wrapper)
             except Exception: # pragma: no cover
-                res = func(group, *args, **kwargs)
+                res = wrapper(group)
 
             # broadcasting
             if isinstance(res, Series):
@@ -1651,6 +1654,25 @@ def transform(self, func, *args, **kwargs):
                               axis=self.axis, verify_integrity=False)
         return concatenated.reindex_like(obj)
 
+    def _transform_item_by_item(self, obj, wrapper):
+        # iterate through columns
+        output = {}
+        inds = []
+        for i, col in enumerate(obj):
+            try:
+                output[col] = self[col].transform(wrapper)
+                inds.append(i)
+            except Exception:
+                pass
+
+        if len(output) == 0:
+            raise TypeError('Transform function invalid for data types')
+
+        columns = obj.columns
+        if len(output) < len(obj.columns):
+            columns = columns.take(inds)
+
+        return DataFrame(output, index=obj.index, columns=columns)
 
 
 class DataFrameGroupBy(NDFrameGroupBy):

pandas/tests/test_groupby.py

@@ -419,6 +419,16 @@ def test_transform_select_columns(self):
 
         assert_frame_equal(result, expected)
 
+    def test_transform_exclude_nuisance(self):
+        expected = {}
+        grouped = self.df.groupby('A')
+        expected['C'] = grouped['C'].transform(np.mean)
+        expected['D'] = grouped['D'].transform(np.mean)
+        expected = DataFrame(expected)
+
+        result = self.df.groupby('A').transform(np.mean)
+
+        assert_frame_equal(result, expected)
 
     def test_with_na(self):
         index = Index(np.arange(10))