give proper message for Dataframe with renaming keys

Author: jreback

pandas/core/base.py

@@ -447,7 +447,6 @@ def _aggregate(self, arg, *args, **kwargs):
         how can be a string describe the required post-processing, or
         None if not required
         """
-
         is_aggregator = lambda x: isinstance(x, (list, tuple, dict))
         is_nested_renamer = False
 
@@ -482,7 +481,7 @@ def _aggregate(self, arg, *args, **kwargs):
                     # the keys must be in the columns
                     # for ndim=2, or renamers for ndim=1
 
-                    # ok
+                    # ok for now, but deprecated
                     # {'A': { 'ra': 'mean' }}
                     # {'A': { 'ra': ['mean'] }}
                     # {'ra': ['mean']}
@@ -497,8 +496,26 @@ def _aggregate(self, arg, *args, **kwargs):
                                                      'for {0} with a nested '
                                                      'dictionary'.format(k))
 
+                        # deprecation of nested renaming
+                        warnings.warn(
+                            ("using a dict with renaming "
+                             "is deprecated and will be removed in a future "
+                             "version"),
+                            FutureWarning, stacklevel=3)
+
                 arg = new_arg
 
+            else:
+                # we may have renaming keys
+                keys = list(compat.iterkeys(arg))
+                if (isinstance(obj, ABCDataFrame) and
+                        len(obj.columns.intersection(keys)) != len(keys)):
+                    warnings.warn(
+                        ("using a dict with renaming "
+                         "is deprecated and will be removed in a future "
+                         "version"),
+                        FutureWarning, stacklevel=3)
+
             from pandas.tools.concat import concat
 
             def _agg_1dim(name, how, subset=None):
@@ -533,16 +550,6 @@ def _agg(arg, func):
             keys = list(compat.iterkeys(arg))
             result = compat.OrderedDict()
 
-            # renaming keys
-            if isinstance(self._selected_obj, ABCDataFrame):
-                if len(self._selected_obj.columns.intersection(
-                        keys)) != len(keys):
-                    warnings.warn(
-                        ("using a dict with renaming"
-                         "is deprecated and will be removed in a future "
-                         "version"),
-                        FutureWarning, stacklevel=3)
-
             # nested renamer
             if is_nested_renamer:
                 result = list(_agg(arg, _agg_1dim).values())

pandas/core/groupby.py

@@ -2835,9 +2835,11 @@ def aggregate(self, func_or_funcs, *args, **kwargs):
     def _aggregate_multiple_funcs(self, arg, _level):
         if isinstance(arg, dict):
 
-            if isinstance(self._selected_obj, Series):
+            # show the deprecation, but only if we
+            # have not shown a higher level one
+            if isinstance(self._selected_obj, Series) and _level <= 1:
                 warnings.warn(
-                    ("using a dictionary on a Series for aggregation\n"
+                    ("using a dict on a Series for aggregation\n"
                      "is deprecated and will be removed in a future "
                      "version"),
                     FutureWarning, stacklevel=7)

pandas/tests/groupby/test_aggregate.py

@@ -304,6 +304,24 @@ def test_aggregate_api_consistency(self):
                                                     ['D', 'C']])
         assert_frame_equal(result, expected, check_like=True)
 
+    def test_agg_dict_renaming_deprecation(self):
+        # 15931
+        df = pd.DataFrame({'A': [1, 1, 1, 2, 2],
+                           'B': range(5),
+                           'C': range(5)})
+
+        with tm.assert_produces_warning(FutureWarning,
+                                        check_stacklevel=False) as w:
+            df.groupby('A').agg({'B': {'foo': ['sum', 'max']},
+                                 'C': {'bar': ['count', 'min']}})
+            assert "using a dict with renaming" in str(w[0].message)
+
+        with tm.assert_produces_warning(FutureWarning,
+                                        check_stacklevel=False) as w:
+            df.groupby('A').B.agg({'foo': 'count'})
+            assert "using a dict on a Series for aggregation" in str(
+                w[0].message)
+
     def test_agg_compat(self):
 
         # GH 12334