DEPR: Passing a dictionary to SeriesGroupBy.agg

doc/source/whatsnew/v2.1.0.rst

@@ -115,6 +115,7 @@ Deprecations
 - Deprecated 'method', 'limit', and 'fill_axis' keywords in :meth:`DataFrame.align` and :meth:`Series.align`, explicitly call ``fillna`` on the alignment results instead (:issue:`51856`)
 - Deprecated 'broadcast_axis' keyword in :meth:`Series.align` and :meth:`DataFrame.align`, upcast before calling ``align`` with ``left = DataFrame({col: left for col in right.columns}, index=right.index)`` (:issue:`51856`)
 - Deprecated the 'axis' keyword in :meth:`.GroupBy.idxmax`, :meth:`.GroupBy.idxmin`, :meth:`.GroupBy.fillna`, :meth:`.GroupBy.take`, :meth:`.GroupBy.skew`, :meth:`.GroupBy.rank`, :meth:`.GroupBy.cumprod`, :meth:`.GroupBy.cumsum`, :meth:`.GroupBy.cummax`, :meth:`.GroupBy.cummin`, :meth:`.GroupBy.pct_change`, :meth:`GroupBy.diff`, :meth:`.GroupBy.shift`, and :meth:`DataFrameGroupBy.corrwith`; for ``axis=1`` operate on the underlying :class:`DataFrame` instead (:issue:`50405`, :issue:`51046`)
+- Deprecated passing a dictionary to :meth:`.SeriesGroupBy.agg`; pass a list of aggregations instead (:issue:`50684`)
 - Deprecated :meth:`DataFrame.swapaxes` and :meth:`Series.swapaxes`, use :meth:`DataFrame.transpose` or :meth:`Series.transpose` instead (:issue:`51946`)
 -
 

pandas/core/groupby/generic.py

@@ -68,7 +68,8 @@
 from pandas.core.groupby.groupby import (
     GroupBy,
     GroupByPlot,
-    _agg_template,
+    _agg_template_frame,
+    _agg_template_series,
     _apply_docs,
     _transform_template,
 )
@@ -214,7 +215,7 @@ def _get_data_to_aggregate(
     def apply(self, func, *args, **kwargs) -> Series:
         return super().apply(func, *args, **kwargs)
 
-    @doc(_agg_template, examples=_agg_examples_doc, klass="Series")
+    @doc(_agg_template_series, examples=_agg_examples_doc, klass="Series")
     def aggregate(self, func=None, *args, engine=None, engine_kwargs=None, **kwargs):
         if maybe_use_numba(engine):
             return self._aggregate_with_numba(
@@ -306,6 +307,16 @@ def _aggregate_multiple_funcs(self, arg, *args, **kwargs) -> DataFrame:
                 raise SpecificationError("nested renamer is not supported")
             else:
                 # GH#50684 - This accidentally worked in 1.x
+                msg = (
+                    "Passing a dictionary to SeriesGroupBy.agg is deprecated "
+                    "and will raise in a future version of pandas. Pass a list "
+                    "of aggregations instead."
+                )
+                warnings.warn(
+                    message=msg,
+                    category=FutureWarning,
+                    stacklevel=find_stack_level(),
+                )
                 arg = list(arg.items())
         elif any(isinstance(x, (tuple, list)) for x in arg):
             arg = [(x, x) if not isinstance(x, (tuple, list)) else x for x in arg]
@@ -1291,7 +1302,7 @@ class DataFrameGroupBy(GroupBy[DataFrame]):
     """
     )
 
-    @doc(_agg_template, examples=_agg_examples_doc, klass="DataFrame")
+    @doc(_agg_template_frame, examples=_agg_examples_doc, klass="DataFrame")
     def aggregate(self, func=None, *args, engine=None, engine_kwargs=None, **kwargs):
         if maybe_use_numba(engine):
             return self._aggregate_with_numba(

pandas/core/groupby/groupby.py

@@ -489,7 +489,94 @@ class providing the base-class of operations.
 --------
 %(example)s"""
 
-_agg_template = """
+_agg_template_series = """
+Aggregate using one or more operations over the specified axis.
+
+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 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
+    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.
+
+    .. versionchanged:: 1.1.0
+
+    .. deprecated:: 2.1.0
+
+        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``
+
+    .. versionadded:: 1.1.0
+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
+
+    .. versionadded:: 1.1.0
+**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}"""
+
+_agg_template_frame = """
 Aggregate using one or more operations over the specified axis.
 
 Parameters

pandas/tests/groupby/test_groupby.py

@@ -727,7 +727,9 @@ def test_groupby_as_index_agg(df):
 
     expected3 = grouped["C"].sum()
     expected3 = DataFrame(expected3).rename(columns={"C": "Q"})
-    result3 = grouped["C"].agg({"Q": np.sum})
+    msg = "Passing a dictionary to SeriesGroupBy.agg is deprecated"
+    with tm.assert_produces_warning(FutureWarning, match=msg):
+        result3 = grouped["C"].agg({"Q": np.sum})
     tm.assert_frame_equal(result3, expected3)
 
     # GH7115 & GH8112 & GH8582

pandas/tests/groupby/test_grouping.py

@@ -486,7 +486,9 @@ def test_multifunc_select_col_integer_cols(self, df):
         df.columns = np.arange(len(df.columns))
 
         # it works!
-        df.groupby(1, as_index=False)[2].agg({"Q": np.mean})
+        msg = "Passing a dictionary to SeriesGroupBy.agg is deprecated"
+        with tm.assert_produces_warning(FutureWarning, match=msg):
+            df.groupby(1, as_index=False)[2].agg({"Q": np.mean})
 
     def test_multiindex_columns_empty_level(self):
         lst = [["count", "values"], ["to filter", ""]]

scripts/validate_unwanted_patterns.py

@@ -34,7 +34,8 @@
     "_new_Index",
     "_new_PeriodIndex",
     "_doc_template",
-    "_agg_template",
+    "_agg_template_series",
+    "_agg_template_frame",
     "_pipe_template",
     "__main__",
     "_transform_template",