Revised the doc-string for _app_template to bring in line with curren… (#48613)

* Revised the doc-string for _app_template to bring in line with current aggregate() code, in particular with regard to Named Aggregation.

Also fixed text in "See Also" section, where the entries for groupby.transform and aggregate had their text swapped.

* Update pandas/core/groupby/groupby.py

Co-authored-by: Matthew Roeschke <[email protected]>

* fixup

* Language tweaks

Co-authored-by: Matthew Roeschke <[email protected]>
Co-authored-by: MarcoGorelli <>
Co-authored-by: Richard Shadrach <[email protected]>

Author: 3 people

pandas/core/groupby/groupby.py

@@ -494,7 +494,7 @@ class providing the base-class of operations.
 
 Parameters
 ----------
-func : function, str, list or dict
+func : function, str, list, dict or None
     Function to use for aggregating the data. If a function, must either
     work when passed a {klass} or when passed to {klass}.apply.
 
@@ -504,6 +504,10 @@ class providing the base-class of operations.
     - string function name
     - list of functions and/or function names, e.g. ``[np.sum, 'mean']``
     - dict of axis labels -> functions, function names or list of such.
+    - None, in which case ``**kwargs`` are used with Named Aggregation. Here the
+      output has one column for each element in ``**kwargs``. The name of the
+      column is keyword, whereas the value determines the aggregation used to compute
+      the values in the column.
 
     Can also accept a Numba JIT function with
     ``engine='numba'`` specified. Only passing a single function is supported
@@ -534,7 +538,9 @@ class providing the base-class of operations.
 
     .. versionadded:: 1.1.0
 **kwargs
-    Keyword arguments to be passed into func.
+    * If ``func`` is None, ``**kwargs`` are used to define the output names and
+      aggregations via Named Aggregation. See ``func`` entry.
+    * Otherwise, keyword arguments to be passed into func.
 
 Returns
 -------
@@ -544,10 +550,10 @@ class providing the base-class of operations.
 --------
 {klass}.groupby.apply : Apply function func group-wise
     and combine the results together.
-{klass}.groupby.transform : Aggregate using one or more
-    operations over the specified axis.
-{klass}.aggregate : Transforms the Series on each group
+{klass}.groupby.transform : Transforms the Series on each group
     based on the given function.
+{klass}.aggregate : Aggregate using one or more
+    operations over the specified axis.
 
 Notes
 -----