diff --git a/pandas/core/groupby/base.py b/pandas/core/groupby/base.py
index 7dc0db35bf8fe..99426c55da29b 100644
--- a/pandas/core/groupby/base.py
+++ b/pandas/core/groupby/base.py
@@ -6,6 +6,8 @@
 import collections
 from typing import List
 
+from pandas._typing import final
+
 from pandas.core.dtypes.common import is_list_like, is_scalar
 
 from pandas.core.base import PandasObject
@@ -16,6 +18,7 @@
 class ShallowMixin(PandasObject):
     _attributes: List[str] = []
 
+    @final
     def _shallow_copy(self, obj, **kwargs):
         """
         return a new object with the replacement attributes
@@ -35,6 +38,7 @@ class GotItemMixin(PandasObject):
 
     _attributes: List[str]
 
+    @final
     def _gotitem(self, key, ndim, subset=None):
         """
         Sub-classes to define. Return a sliced object.
diff --git a/pandas/core/groupby/groupby.py b/pandas/core/groupby/groupby.py
index 8f1b99e929f59..23f0e178130be 100644
--- a/pandas/core/groupby/groupby.py
+++ b/pandas/core/groupby/groupby.py
@@ -11,6 +11,7 @@ class providing the base-class of operations.
 import datetime
 from functools import partial, wraps
 import inspect
+from textwrap import dedent
 import types
 from typing import (
     Callable,
@@ -44,6 +45,7 @@ class providing the base-class of operations.
     IndexLabel,
     Label,
     Scalar,
+    final,
 )
 from pandas.compat.numpy import function as nv
 from pandas.errors import AbstractMethodError
@@ -447,6 +449,7 @@ class providing the base-class of operations.
 """
 
 
+@final
 class GroupByPlot(PandasObject):
     """
     Class implementing the .plot attribute for groupby objects.
@@ -570,9 +573,11 @@ def __init__(
         self.grouper = grouper
         self.exclusions = exclusions or set()
 
+    @final
     def __len__(self) -> int:
         return len(self.groups)
 
+    @final
     def __repr__(self) -> str:
         # TODO: Better repr for GroupBy object
         return object.__repr__(self)
@@ -584,6 +589,7 @@ def _assure_grouper(self) -> None:
         """
         pass
 
+    @final
     @property
     def groups(self) -> Dict[Hashable, np.ndarray]:
         """
@@ -592,11 +598,13 @@ def groups(self) -> Dict[Hashable, np.ndarray]:
         self._assure_grouper()
         return self.grouper.groups
 
+    @final
     @property
     def ngroups(self) -> int:
         self._assure_grouper()
         return self.grouper.ngroups
 
+    @final
     @property
     def indices(self):
         """
@@ -605,6 +613,7 @@ def indices(self):
         self._assure_grouper()
         return self.grouper.indices
 
+    @final
     def _get_indices(self, names):
         """
         Safe get multiple indices, translate keys for
@@ -655,12 +664,14 @@ def get_converter(s):
 
         return [self.indices.get(name, []) for name in names]
 
+    @final
     def _get_index(self, name):
         """
         Safe get index, translate keys for datelike to underlying repr.
         """
         return self._get_indices([name])[0]
 
+    @final
     @cache_readonly
     def _selected_obj(self):
         # Note: _selected_obj is always just `self.obj` for SeriesGroupBy
@@ -672,6 +683,7 @@ def _selected_obj(self):
         else:
             return self.obj[self._selection]
 
+    @final
     def _reset_group_selection(self) -> None:
         """
         Clear group based selection.
@@ -684,6 +696,7 @@ def _reset_group_selection(self) -> None:
             self._group_selection = None
             self._reset_cache("_selected_obj")
 
+    @final
     def _set_group_selection(self) -> None:
         """
         Create group based selection.
@@ -709,6 +722,7 @@ def _set_group_selection(self) -> None:
             self._group_selection = ax.difference(Index(groupers), sort=False).tolist()
             self._reset_cache("_selected_obj")
 
+    @final
     def _set_result_index_ordered(
         self, result: "OutputFrameOrSeries"
     ) -> "OutputFrameOrSeries":
@@ -725,6 +739,7 @@ def _set_result_index_ordered(
         result.set_axis(self.obj._get_axis(self.axis), axis=self.axis, inplace=True)
         return result
 
+    @final
     def _dir_additions(self) -> Set[str]:
         return self.obj._dir_additions() | self._apply_allowlist
 
@@ -740,23 +755,25 @@ def __getattr__(self, attr: str):
 
     @Substitution(
         klass="GroupBy",
-        examples="""\
->>> df = pd.DataFrame({'A': 'a b a b'.split(), 'B': [1, 2, 3, 4]})
->>> df
-   A  B
-0  a  1
-1  b  2
-2  a  3
-3  b  4
-
-To get the difference between each groups maximum and minimum value in one
-pass, you can do
-
->>> df.groupby('A').pipe(lambda x: x.max() - x.min())
-   B
-A
-a  2
-b  2""",
+        examples=dedent(
+            """\
+        >>> df = pd.DataFrame({'A': 'a b a b'.split(), 'B': [1, 2, 3, 4]})
+        >>> df
+           A  B
+        0  a  1
+        1  b  2
+        2  a  3
+        3  b  4
+
+        To get the difference between each groups maximum and minimum value in one
+        pass, you can do
+
+        >>> df.groupby('A').pipe(lambda x: x.max() - x.min())
+           B
+        A
+        a  2
+        b  2"""
+        ),
     )
     @Appender(_pipe_template)
     def pipe(self, func, *args, **kwargs):
@@ -764,6 +781,7 @@ def pipe(self, func, *args, **kwargs):
 
     plot = property(GroupByPlot)
 
+    @final
     def _make_wrapper(self, name: str) -> Callable:
         assert name in self._apply_allowlist
 
@@ -801,6 +819,7 @@ def curried(x):
         wrapper.__name__ = name
         return wrapper
 
+    @final
     def get_group(self, name, obj=None):
         """
         Construct DataFrame from group with provided name.
@@ -887,6 +906,7 @@ def f(g):
 
         return result
 
+    @final
     def _python_apply_general(
         self, f: F, data: FrameOrSeriesUnion
     ) -> FrameOrSeriesUnion:
@@ -917,6 +937,7 @@ def _iterate_slices(self) -> Iterable[Series]:
     def transform(self, func, *args, **kwargs):
         raise AbstractMethodError(self)
 
+    @final
     def _cumcount_array(self, ascending: bool = True):
         """
         Parameters
@@ -949,6 +970,7 @@ def _cumcount_array(self, ascending: bool = True):
         rev[sorter] = np.arange(count, dtype=np.intp)
         return out[rev].astype(np.int64, copy=False)
 
+    @final
     def _cython_transform(
         self, how: str, numeric_only: bool = True, axis: int = 0, **kwargs
     ):
@@ -986,6 +1008,7 @@ def _wrap_transformed_output(self, output: Mapping[base.OutputKey, np.ndarray]):
     def _wrap_applied_output(self, keys, values, not_indexed_same: bool = False):
         raise AbstractMethodError(self)
 
+    @final
     def _agg_general(
         self,
         numeric_only: bool = True,
@@ -1059,6 +1082,7 @@ def _cython_agg_general(
 
         return self._wrap_aggregated_output(output, index=self.grouper.result_index)
 
+    @final
     def _transform_with_numba(self, data, func, *args, engine_kwargs=None, **kwargs):
         """
         Perform groupby transform routine with the numba engine.
@@ -1093,6 +1117,7 @@ def _transform_with_numba(self, data, func, *args, engine_kwargs=None, **kwargs)
         # evaluated the data sorted by group
         return result.take(np.argsort(sorted_index), axis=0)
 
+    @final
     def _aggregate_with_numba(self, data, func, *args, engine_kwargs=None, **kwargs):
         """
         Perform groupby aggregation routine with the numba engine.
@@ -1129,6 +1154,7 @@ def _aggregate_with_numba(self, data, func, *args, engine_kwargs=None, **kwargs)
             index = Index(group_keys, name=self.grouper.names[0])
         return result, index
 
+    @final
     def _python_agg_general(self, func, *args, **kwargs):
         func = self._is_builtin_func(func)
         f = lambda x: func(x, *args, **kwargs)
@@ -1171,6 +1197,7 @@ def _python_agg_general(self, func, *args, **kwargs):
 
         return self._wrap_aggregated_output(output, index=self.grouper.result_index)
 
+    @final
     def _concat_objects(self, keys, values, not_indexed_same: bool = False):
         from pandas.core.reshape.concat import concat
 
@@ -1232,6 +1259,7 @@ def reset_identity(values):
 
         return result
 
+    @final
     def _apply_filter(self, indices, dropna):
         if len(indices) == 0:
             indices = np.array([], dtype="int64")
@@ -1321,6 +1349,7 @@ class GroupBy(BaseGroupBy[FrameOrSeries]):
     more
     """
 
+    @final
     @property
     def _obj_1d_constructor(self) -> Type["Series"]:
         # GH28330 preserve subclassed Series/DataFrames
@@ -1329,6 +1358,7 @@ def _obj_1d_constructor(self) -> Type["Series"]:
         assert isinstance(self.obj, Series)
         return self.obj._constructor
 
+    @final
     def _bool_agg(self, val_test, skipna):
         """
         Shared func to call any / all Cython GroupBy implementations.
@@ -1358,6 +1388,7 @@ def result_to_bool(result: np.ndarray, inference: Type) -> np.ndarray:
             skipna=skipna,
         )
 
+    @final
     @Substitution(name="groupby")
     @Appender(_common_see_also)
     def any(self, skipna: bool = True):
@@ -1377,6 +1408,7 @@ def any(self, skipna: bool = True):
         """
         return self._bool_agg("any", skipna)
 
+    @final
     @Substitution(name="groupby")
     @Appender(_common_see_also)
     def all(self, skipna: bool = True):
@@ -1410,6 +1442,7 @@ def count(self):
         # defined here for API doc
         raise NotImplementedError
 
+    @final
     @Substitution(name="groupby")
     @Substitution(see_also=_common_see_also)
     def mean(self, numeric_only: bool = True):
@@ -1466,6 +1499,7 @@ def mean(self, numeric_only: bool = True):
             numeric_only=numeric_only,
         )
 
+    @final
     @Substitution(name="groupby")
     @Appender(_common_see_also)
     def median(self, numeric_only=True):
@@ -1491,6 +1525,7 @@ def median(self, numeric_only=True):
             numeric_only=numeric_only,
         )
 
+    @final
     @Substitution(name="groupby")
     @Appender(_common_see_also)
     def std(self, ddof: int = 1):
@@ -1520,6 +1555,7 @@ def std(self, ddof: int = 1):
             ddof=ddof,
         )
 
+    @final
     @Substitution(name="groupby")
     @Appender(_common_see_also)
     def var(self, ddof: int = 1):
@@ -1547,6 +1583,7 @@ def var(self, ddof: int = 1):
             with group_selection_context(self):
                 return self._python_agg_general(func)
 
+    @final
     @Substitution(name="groupby")
     @Appender(_common_see_also)
     def sem(self, ddof: int = 1):
@@ -1577,6 +1614,7 @@ def sem(self, ddof: int = 1):
             )
         return result
 
+    @final
     @Substitution(name="groupby")
     @Appender(_common_see_also)
     def size(self) -> FrameOrSeriesUnion:
@@ -1602,6 +1640,7 @@ def size(self) -> FrameOrSeriesUnion:
 
         return self._reindex_output(result, fill_value=0)
 
+    @final
     @doc(_groupby_agg_method_template, fname="sum", no=True, mc=0)
     def sum(self, numeric_only: bool = True, min_count: int = 0):
 
@@ -1618,24 +1657,28 @@ def sum(self, numeric_only: bool = True, min_count: int = 0):
 
         return self._reindex_output(result, fill_value=0)
 
+    @final
     @doc(_groupby_agg_method_template, fname="prod", no=True, mc=0)
     def prod(self, numeric_only: bool = True, min_count: int = 0):
         return self._agg_general(
             numeric_only=numeric_only, min_count=min_count, alias="prod", npfunc=np.prod
         )
 
+    @final
     @doc(_groupby_agg_method_template, fname="min", no=False, mc=-1)
     def min(self, numeric_only: bool = False, min_count: int = -1):
         return self._agg_general(
             numeric_only=numeric_only, min_count=min_count, alias="min", npfunc=np.min
         )
 
+    @final
     @doc(_groupby_agg_method_template, fname="max", no=False, mc=-1)
     def max(self, numeric_only: bool = False, min_count: int = -1):
         return self._agg_general(
             numeric_only=numeric_only, min_count=min_count, alias="max", npfunc=np.max
         )
 
+    @final
     @doc(_groupby_agg_method_template, fname="first", no=False, mc=-1)
     def first(self, numeric_only: bool = False, min_count: int = -1):
         def first_compat(obj: FrameOrSeries, axis: int = 0):
@@ -1660,6 +1703,7 @@ def first(x: Series):
             npfunc=first_compat,
         )
 
+    @final
     @doc(_groupby_agg_method_template, fname="last", no=False, mc=-1)
     def last(self, numeric_only: bool = False, min_count: int = -1):
         def last_compat(obj: FrameOrSeries, axis: int = 0):
@@ -1684,6 +1728,7 @@ def last(x: Series):
             npfunc=last_compat,
         )
 
+    @final
     @Substitution(name="groupby")
     @Appender(_common_see_also)
     def ohlc(self) -> DataFrame:
@@ -1699,6 +1744,7 @@ def ohlc(self) -> DataFrame:
         """
         return self._apply_to_column_groupbys(lambda x: x._cython_agg_general("ohlc"))
 
+    @final
     @doc(DataFrame.describe)
     def describe(self, **kwargs):
         with group_selection_context(self):
@@ -1707,6 +1753,7 @@ def describe(self, **kwargs):
                 return result.T
             return result.unstack()
 
+    @final
     def resample(self, rule, *args, **kwargs):
         """
         Provide resampling when using a TimeGrouper.
@@ -1808,6 +1855,7 @@ def resample(self, rule, *args, **kwargs):
 
         return get_resampler_for_grouping(self, rule, *args, **kwargs)
 
+    @final
     @Substitution(name="groupby")
     @Appender(_common_see_also)
     def rolling(self, *args, **kwargs):
@@ -1818,6 +1866,7 @@ def rolling(self, *args, **kwargs):
 
         return RollingGroupby(self, *args, **kwargs)
 
+    @final
     @Substitution(name="groupby")
     @Appender(_common_see_also)
     def expanding(self, *args, **kwargs):
@@ -1829,6 +1878,7 @@ def expanding(self, *args, **kwargs):
 
         return ExpandingGroupby(self, *args, **kwargs)
 
+    @final
     @Substitution(name="groupby")
     @Appender(_common_see_also)
     def ewm(self, *args, **kwargs):
@@ -1839,6 +1889,7 @@ def ewm(self, *args, **kwargs):
 
         return ExponentialMovingWindowGroupby(self, *args, **kwargs)
 
+    @final
     def _fill(self, direction, limit=None):
         """
         Shared function for `pad` and `backfill` to call Cython method.
@@ -1877,6 +1928,7 @@ def _fill(self, direction, limit=None):
             dropna=self.dropna,
         )
 
+    @final
     @Substitution(name="groupby")
     def pad(self, limit=None):
         """
@@ -1903,6 +1955,7 @@ def pad(self, limit=None):
 
     ffill = pad
 
+    @final
     @Substitution(name="groupby")
     def backfill(self, limit=None):
         """
@@ -1929,6 +1982,7 @@ def backfill(self, limit=None):
 
     bfill = backfill
 
+    @final
     @Substitution(name="groupby")
     @Substitution(see_also=_common_see_also)
     def nth(self, n: Union[int, List[int]], dropna: Optional[str] = None) -> DataFrame:
@@ -2102,6 +2156,7 @@ def nth(self, n: Union[int, List[int]], dropna: Optional[str] = None) -> DataFra
 
         return result
 
+    @final
     def quantile(self, q=0.5, interpolation: str = "linear"):
         """
         Return group values at the given quantile, a la numpy.percentile.
@@ -2230,6 +2285,7 @@ def post_processor(vals: np.ndarray, inference: Optional[Type]) -> np.ndarray:
             )
             return result.take(indices, axis=self.axis)
 
+    @final
     @Substitution(name="groupby")
     def ngroup(self, ascending: bool = True):
         """
@@ -2297,6 +2353,7 @@ def ngroup(self, ascending: bool = True):
                 result = self.ngroups - 1 - result
             return result
 
+    @final
     @Substitution(name="groupby")
     def cumcount(self, ascending: bool = True):
         """
@@ -2356,6 +2413,7 @@ def cumcount(self, ascending: bool = True):
             cumcounts = self._cumcount_array(ascending=ascending)
             return self._obj_1d_constructor(cumcounts, index)
 
+    @final
     @Substitution(name="groupby")
     @Appender(_common_see_also)
     def rank(
@@ -2405,6 +2463,7 @@ def rank(
             axis=axis,
         )
 
+    @final
     @Substitution(name="groupby")
     @Appender(_common_see_also)
     def cumprod(self, axis=0, *args, **kwargs):
@@ -2421,6 +2480,7 @@ def cumprod(self, axis=0, *args, **kwargs):
 
         return self._cython_transform("cumprod", **kwargs)
 
+    @final
     @Substitution(name="groupby")
     @Appender(_common_see_also)
     def cumsum(self, axis=0, *args, **kwargs):
@@ -2437,6 +2497,7 @@ def cumsum(self, axis=0, *args, **kwargs):
 
         return self._cython_transform("cumsum", **kwargs)
 
+    @final
     @Substitution(name="groupby")
     @Appender(_common_see_also)
     def cummin(self, axis=0, **kwargs):
@@ -2452,6 +2513,7 @@ def cummin(self, axis=0, **kwargs):
 
         return self._cython_transform("cummin", numeric_only=False)
 
+    @final
     @Substitution(name="groupby")
     @Appender(_common_see_also)
     def cummax(self, axis=0, **kwargs):
@@ -2467,6 +2529,7 @@ def cummax(self, axis=0, **kwargs):
 
         return self._cython_transform("cummax", numeric_only=False)
 
+    @final
     def _get_cythonized_result(
         self,
         how: str,
@@ -2625,6 +2688,7 @@ def _get_cythonized_result(
         else:
             return self._wrap_transformed_output(output)
 
+    @final
     @Substitution(name="groupby")
     def shift(self, periods=1, freq=None, axis=0, fill_value=None):
         """
@@ -2668,6 +2732,7 @@ def shift(self, periods=1, freq=None, axis=0, fill_value=None):
             periods=periods,
         )
 
+    @final
     @Substitution(name="groupby")
     @Appender(_common_see_also)
     def pct_change(self, periods=1, fill_method="pad", limit=None, freq=None, axis=0):
@@ -2697,6 +2762,7 @@ def pct_change(self, periods=1, fill_method="pad", limit=None, freq=None, axis=0
         shifted = fill_grp.shift(periods=periods, freq=freq, axis=self.axis)
         return (filled / shifted) - 1
 
+    @final
     @Substitution(name="groupby")
     @Substitution(see_also=_common_see_also)
     def head(self, n=5):
@@ -2734,6 +2800,7 @@ def head(self, n=5):
         else:
             return self._selected_obj.iloc[:, mask]
 
+    @final
     @Substitution(name="groupby")
     @Substitution(see_also=_common_see_also)
     def tail(self, n=5):
@@ -2771,6 +2838,7 @@ def tail(self, n=5):
         else:
             return self._selected_obj.iloc[:, mask]
 
+    @final
     def _reindex_output(
         self, output: OutputFrameOrSeries, fill_value: Scalar = np.NaN
     ) -> OutputFrameOrSeries:
@@ -2857,6 +2925,7 @@ def _reindex_output(
 
         return output.reset_index(drop=True)
 
+    @final
     def sample(
         self,
         n: Optional[int] = None,
diff --git a/pandas/core/groupby/grouper.py b/pandas/core/groupby/grouper.py
index 8b79ea2242258..d814a7cee436e 100644
--- a/pandas/core/groupby/grouper.py
+++ b/pandas/core/groupby/grouper.py
@@ -7,7 +7,7 @@
 
 import numpy as np
 
-from pandas._typing import FrameOrSeries, Label
+from pandas._typing import FrameOrSeries, Label, final
 from pandas.errors import InvalidIndexError
 from pandas.util._decorators import cache_readonly
 
@@ -289,6 +289,7 @@ def __init__(
         self._grouper = None
         self.dropna = dropna
 
+    @final
     @property
     def ax(self):
         return self.grouper
@@ -320,6 +321,7 @@ def _get_grouper(self, obj, validate: bool = True):
         )
         return self.binner, self.grouper, self.obj
 
+    @final
     def _set_grouper(self, obj: FrameOrSeries, sort: bool = False):
         """
         given an object and the specifications, setup the internal grouper
@@ -379,12 +381,14 @@ def _set_grouper(self, obj: FrameOrSeries, sort: bool = False):
         self.grouper = ax
         return self.grouper
 
+    @final
     @property
     def groups(self):
         # pandas\core\groupby\grouper.py:382: error: Item "None" of
         # "Optional[Any]" has no attribute "groups"  [union-attr]
         return self.grouper.groups  # type: ignore[union-attr]
 
+    @final
     def __repr__(self) -> str:
         attrs_list = (
             f"{attr_name}={repr(getattr(self, attr_name))}"
@@ -396,6 +400,7 @@ def __repr__(self) -> str:
         return f"{cls_name}({attrs})"
 
 
+@final
 class Grouping:
     """
     Holds the grouping information for a single key
diff --git a/pandas/core/groupby/ops.py b/pandas/core/groupby/ops.py
index d98c55755042e..c60a59916affc 100644
--- a/pandas/core/groupby/ops.py
+++ b/pandas/core/groupby/ops.py
@@ -24,7 +24,7 @@
 from pandas._libs import NaT, iNaT, lib
 import pandas._libs.groupby as libgroupby
 import pandas._libs.reduction as libreduction
-from pandas._typing import ArrayLike, F, FrameOrSeries, Label, Shape
+from pandas._typing import ArrayLike, F, FrameOrSeries, Label, Shape, final
 from pandas.errors import AbstractMethodError
 from pandas.util._decorators import cache_readonly
 
@@ -146,6 +146,7 @@ def get_iterator(
         for key, (i, group) in zip(keys, splitter):
             yield key, group.__finalize__(data, method="groupby")
 
+    @final
     def _get_splitter(self, data: FrameOrSeries, axis: int = 0) -> "DataSplitter":
         """
         Returns
@@ -166,6 +167,7 @@ def _get_grouper(self):
         """
         return self.groupings[0].grouper
 
+    @final
     def _get_group_keys(self):
         if len(self.groupings) == 1:
             return self.levels[0]
@@ -175,6 +177,7 @@ def _get_group_keys(self):
             # provide "flattened" iterator for multi-group setting
             return get_flattened_list(comp_ids, ngroups, self.levels, self.codes)
 
+    @final
     def apply(self, f: F, data: FrameOrSeries, axis: int = 0):
         mutated = self.mutated
         splitter = self._get_splitter(data, axis=axis)
@@ -256,6 +259,7 @@ def levels(self) -> List[Index]:
     def names(self) -> List[Label]:
         return [ping.name for ping in self.groupings]
 
+    @final
     def size(self) -> Series:
         """
         Compute group sizes.
@@ -278,6 +282,7 @@ def groups(self) -> Dict[Hashable, np.ndarray]:
             to_groupby = Index(to_groupby)
             return self.axis.groupby(to_groupby)
 
+    @final
     @cache_readonly
     def is_monotonic(self) -> bool:
         # return if my group orderings are monotonic
@@ -291,6 +296,7 @@ def group_info(self):
         comp_ids = ensure_int64(comp_ids)
         return comp_ids, obs_group_ids, ngroups
 
+    @final
     @cache_readonly
     def codes_info(self) -> np.ndarray:
         # return the codes of items in original grouped axis
@@ -300,6 +306,7 @@ def codes_info(self) -> np.ndarray:
             codes = codes[sorter]
         return codes
 
+    @final
     def _get_compressed_codes(self) -> Tuple[np.ndarray, np.ndarray]:
         all_codes = self.codes
         if len(all_codes) > 1:
@@ -309,6 +316,7 @@ def _get_compressed_codes(self) -> Tuple[np.ndarray, np.ndarray]:
         ping = self.groupings[0]
         return ping.codes, np.arange(len(ping.group_index))
 
+    @final
     @cache_readonly
     def ngroups(self) -> int:
         return len(self.result_index)
@@ -330,6 +338,7 @@ def result_index(self) -> Index:
             levels=levels, codes=codes, verify_integrity=False, names=self.names
         )
 
+    @final
     def get_group_levels(self) -> List[Index]:
         if not self.compressed and len(self.groupings) == 1:
             return [self.groupings[0].result_index]
@@ -370,6 +379,7 @@ def get_group_levels(self) -> List[Index]:
 
     _cython_arity = {"ohlc": 4}  # OHLC
 
+    @final
     def _is_builtin_func(self, arg):
         """
         if we define a builtin function for this argument, return it,
@@ -377,6 +387,7 @@ def _is_builtin_func(self, arg):
         """
         return SelectionMixin._builtin_table.get(arg, arg)
 
+    @final
     def _get_cython_function(
         self, kind: str, how: str, values: np.ndarray, is_numeric: bool
     ):
@@ -413,6 +424,7 @@ def _get_cython_function(
 
         return func
 
+    @final
     def _get_cython_func_and_vals(
         self, kind: str, how: str, values: np.ndarray, is_numeric: bool
     ):
@@ -447,6 +459,7 @@ def _get_cython_func_and_vals(
                 raise
         return func, values
 
+    @final
     def _disallow_invalid_ops(self, values: ArrayLike, how: str):
         """
         Check if we can do this operation with our cython functions.
@@ -476,6 +489,7 @@ def _disallow_invalid_ops(self, values: ArrayLike, how: str):
                     f"timedelta64 type does not support {how} operations"
                 )
 
+    @final
     def _ea_wrap_cython_operation(
         self, kind: str, values, how: str, axis: int, min_count: int = -1, **kwargs
     ) -> Tuple[np.ndarray, Optional[List[str]]]:
@@ -512,6 +526,7 @@ def _ea_wrap_cython_operation(
 
         raise NotImplementedError(values.dtype)
 
+    @final
     def _cython_operation(
         self, kind: str, values, how: str, axis: int, min_count: int = -1, **kwargs
     ) -> np.ndarray:
@@ -625,6 +640,7 @@ def _cython_operation(
 
         return result
 
+    @final
     def _aggregate(
         self, result, counts, values, comp_ids, agg_func, min_count: int = -1
     ):
@@ -636,6 +652,7 @@ def _aggregate(
 
         return result
 
+    @final
     def _transform(
         self, result, values, comp_ids, transform_func, is_datetimelike: bool, **kwargs
     ):
@@ -674,6 +691,7 @@ def agg_series(self, obj: Series, func: F):
                 raise
         return self._aggregate_series_pure_python(obj, func)
 
+    @final
     def _aggregate_series_fast(self, obj: Series, func: F):
         # At this point we have already checked that
         #  - obj.index is not a MultiIndex
@@ -693,6 +711,7 @@ def _aggregate_series_fast(self, obj: Series, func: F):
         result, counts = grouper.get_result()
         return result, counts
 
+    @final
     def _aggregate_series_pure_python(self, obj: Series, func: F):
         group_index, _, ngroups = self.group_info