@@ -364,70 +364,6 @@ class providing the base-class of operations.
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--------
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%(example)s"""
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- _agg_template_frame = """
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- Aggregate using one or more operations.
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- Parameters
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- ----------
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- func : function, str, list, dict or None
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- Function to use for aggregating the data. If a function, must either
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- work when passed a {klass} or when passed to {klass}.apply.
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- Accepted combinations are:
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- - function
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- - string function name
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- - list of functions and/or function names, e.g. ``[np.sum, 'mean']``
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- - dict of index labels -> functions, function names or list of such.
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- - None, in which case ``**kwargs`` are used with Named Aggregation. Here the
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- output has one column for each element in ``**kwargs``. The name of the
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- column is keyword, whereas the value determines the aggregation used to compute
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- the values in the column.
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- Can also accept a Numba JIT function with
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- ``engine='numba'`` specified. Only passing a single function is supported
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- with this engine.
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- If the ``'numba'`` engine is chosen, the function must be
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- a user defined function with ``values`` and ``index`` as the
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- first and second arguments respectively in the function signature.
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- Each group's index will be passed to the user defined function
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- and optionally available for use.
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- *args
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- Positional arguments to pass to func.
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- engine : str, default None
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- * ``'cython'`` : Runs the function through C-extensions from cython.
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- * ``'numba'`` : Runs the function through JIT compiled code from numba.
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- * ``None`` : Defaults to ``'cython'`` or globally setting ``compute.use_numba``
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- engine_kwargs : dict, default None
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- * For ``'cython'`` engine, there are no accepted ``engine_kwargs``
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- * For ``'numba'`` engine, the engine can accept ``nopython``, ``nogil``
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- and ``parallel`` dictionary keys. The values must either be ``True`` or
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- ``False``. The default ``engine_kwargs`` for the ``'numba'`` engine is
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- ``{{'nopython': True, 'nogil': False, 'parallel': False}}`` and will be
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- applied to the function
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- **kwargs
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- * If ``func`` is None, ``**kwargs`` are used to define the output names and
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- aggregations via Named Aggregation. See ``func`` entry.
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- * Otherwise, keyword arguments to be passed into func.
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- Returns
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- -------
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- {klass}
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- See Also
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- --------
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- {klass}.groupby.apply : Apply function func group-wise
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- and combine the results together.
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- {klass}.groupby.transform : Transforms the Series on each group
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- based on the given function.
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- {klass}.aggregate : Aggregate using one or more operations.
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- Notes
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- -----
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- When using ``engine='numba'``, there will be no "fall back" behavior internally.
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- The group data and group index will be passed as numpy arrays to the JITed
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- user defined function, and no alternative execution attempts will be tried.
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- Functions that mutate the passed object can produce unexpected
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- behavior or errors and are not supported. See :ref:`gotchas.udf-mutation`
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- for more details.
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- .. versionchanged:: 1.3.0
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- The resulting dtype will reflect the return value of the passed ``func``,
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- see the examples below.
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- {examples}"""
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-
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@final
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class GroupByPlot (PandasObject ):
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