DOC: update the GroupBy.apply docstring

pandas/core/groupby.py

@@ -99,9 +99,11 @@
     func : function
         A callable that takes a {input} as its first argument, and
         returns a dataframe, a series or a scalar. In addition the
-        callable may take positional and keyword arguments
-    args, kwargs : tuple and dict
-        Optional positional and keyword arguments to pass to ``func``
+        callable may take positional and keyword arguments.
+    args : tuple
+        Optional positional and keyword arguments to pass to ``func``.
+    kwargs : dict
+        Optional positional and keyword arguments to pass to ``func``.
 
     Returns
     -------
@@ -118,12 +120,12 @@
     Examples
     --------
     {examples}
-
     See also
     --------
     pipe : Apply function to the full GroupBy object instead of to each
         group.
-    aggregate, transform
+    aggregate : Apply aggregate function to the GroupBy object.
+    transform : Apply function column-by-column to the GroupBy object.
     """,
     dataframe_examples="""
     >>> df = pd.DataFrame({'A': 'a a b'.split(), 'B': [1,2,3], 'C': [4,6, 5]})
@@ -136,7 +138,7 @@
     its argument and returns a dataframe. ``apply`` combines the result for
     each group together into a new dataframe:
 
-    >>> g.apply(lambda x: x / x.sum())
+    >>> g[['B','C']].apply(lambda x: x / x.sum())
               B    C
     0  0.333333  0.4
     1  0.666667  0.6
@@ -146,7 +148,7 @@
     its argument and returns a series.  ``apply`` combines the result for
     each group together into a new dataframe:
 
-    >>> g.apply(lambda x: x.max() - x.min())
+    >>> g[['B','C']].apply(lambda x: x.max() - x.min())
        B  C
     A
     a  1  2