DOC: add double backticks for sphinx compatibility

Co-authored-by: mroeschke <[email protected]>

Author: tuhinsharma121

pandas/core/groupby/groupby.py

@@ -445,84 +445,6 @@ class providing the base-class of operations.
     see the examples below.
 {examples}"""
 
-_agg_template_frame = """
-Aggregate using one or more operations.
-
-Parameters
-----------
-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.
-
-    Accepted combinations are:
-
-    - function
-    - string function name
-    - list of functions and/or function names, e.g. ``[np.sum, 'mean']``
-    - dict of index 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
-      with this engine.
-
-      If the ``'numba'`` engine is chosen, the function must be
-      a user defined function with ``values`` and ``index`` as the
-      first and second arguments respectively in the function signature.
-      Each group's index will be passed to the user defined function
-      and optionally available for use.
-
-*args
-    Positional arguments to pass to func.
-engine : str, default None
-    * ``'cython'`` : Runs the function through C-extensions from cython.
-    * ``'numba'`` : Runs the function through JIT compiled code from numba.
-    * ``None`` : Defaults to ``'cython'`` or globally setting ``compute.use_numba``
-
-engine_kwargs : dict, default None
-    * For ``'cython'`` engine, there are no accepted ``engine_kwargs``
-    * For ``'numba'`` engine, the engine can accept ``nopython``, ``nogil``
-      and ``parallel`` dictionary keys. The values must either be ``True`` or
-      ``False``. The default ``engine_kwargs`` for the ``'numba'`` engine is
-      ``{{'nopython': True, 'nogil': False, 'parallel': False}}`` and will be
-      applied to the function
-
-**kwargs
-    * 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
--------
-{klass}
-
-See Also
---------
-{klass}.groupby.apply : Apply function func group-wise
-    and combine the results together.
-{klass}.groupby.transform : Transforms the Series on each group
-    based on the given function.
-{klass}.aggregate : Aggregate using one or more operations.
-
-Notes
------
-When using ``engine='numba'``, there will be no "fall back" behavior internally.
-The group data and group index will be passed as numpy arrays to the JITed
-user defined function, and no alternative execution attempts will be tried.
-
-Functions that mutate the passed object can produce unexpected
-behavior or errors and are not supported. See :ref:`gotchas.udf-mutation`
-for more details.
-
-.. versionchanged:: 1.3.0
-
-    The resulting dtype will reflect the return value of the passed ``func``,
-    see the examples below.
-{examples}"""
-
 
 @final
 class GroupByPlot(PandasObject):