Passing a dictionary is deprecated and will raise in a future version
        of pandas. Pass a list of aggregations instead.
*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 over the specified axis.

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}a