diff --git a/doc/source/user_guide/categorical.rst b/doc/source/user_guide/categorical.rst
index b5cb1d83a9f52..f3d68f4c471c1 100644
--- a/doc/source/user_guide/categorical.rst
+++ b/doc/source/user_guide/categorical.rst
@@ -353,11 +353,6 @@ Renaming categories is done by using the
 
     In contrast to R's ``factor``, categorical data can have categories of other types than string.
 
-.. note::
-
-    Be aware that assigning new categories is an inplace operation, while most other operations
-    under ``Series.cat`` per default return a new ``Series`` of dtype ``category``.
-
 Categories must be unique or a ``ValueError`` is raised:
 
 .. ipython:: python
@@ -952,7 +947,6 @@ categorical (categories and ordering). So if you read back the CSV file you have
 relevant columns back to ``category`` and assign the right categories and categories ordering.
 
 .. ipython:: python
-    :okwarning:
 
     import io
 
@@ -969,8 +963,8 @@ relevant columns back to ``category`` and assign the right categories and catego
     df2["cats"]
     # Redo the category
     df2["cats"] = df2["cats"].astype("category")
-    df2["cats"].cat.set_categories(
-        ["very bad", "bad", "medium", "good", "very good"], inplace=True
+    df2["cats"] = df2["cats"].cat.set_categories(
+        ["very bad", "bad", "medium", "good", "very good"]
     )
     df2.dtypes
     df2["cats"]
@@ -1162,16 +1156,12 @@ Constructing a ``Series`` from a ``Categorical`` will not copy the input
 change the original ``Categorical``:
 
 .. ipython:: python
-    :okwarning:
 
     cat = pd.Categorical([1, 2, 3, 10], categories=[1, 2, 3, 4, 10])
     s = pd.Series(cat, name="cat")
     cat
     s.iloc[0:2] = 10
     cat
-    df = pd.DataFrame(s)
-    df["cat"].cat.categories = [1, 2, 3, 4, 5]
-    cat
 
 Use ``copy=True`` to prevent such a behaviour or simply don't reuse ``Categoricals``:
 
diff --git a/doc/source/whatsnew/v0.15.0.rst b/doc/source/whatsnew/v0.15.0.rst
index 04506f1655c7d..f52253687ecfd 100644
--- a/doc/source/whatsnew/v0.15.0.rst
+++ b/doc/source/whatsnew/v0.15.0.rst
@@ -70,7 +70,6 @@ For full docs, see the :ref:`categorical introduction <categorical>` and the
 :ref:`API documentation <api.arrays.categorical>`.
 
 .. ipython:: python
-    :okwarning:
 
     df = pd.DataFrame({"id": [1, 2, 3, 4, 5, 6],
                        "raw_grade": ['a', 'b', 'b', 'a', 'a', 'e']})
@@ -79,7 +78,7 @@ For full docs, see the :ref:`categorical introduction <categorical>` and the
     df["grade"]
 
     # Rename the categories
-    df["grade"].cat.categories = ["very good", "good", "very bad"]
+    df["grade"] = df["grade"].cat.rename_categories(["very good", "good", "very bad"])
 
     # Reorder the categories and simultaneously add the missing categories
     df["grade"] = df["grade"].cat.set_categories(["very bad", "bad",
diff --git a/doc/source/whatsnew/v0.19.0.rst b/doc/source/whatsnew/v0.19.0.rst
index 0c992cf3cc462..feeb7b5ee30ce 100644
--- a/doc/source/whatsnew/v0.19.0.rst
+++ b/doc/source/whatsnew/v0.19.0.rst
@@ -271,12 +271,12 @@ Individual columns can be parsed as a ``Categorical`` using a dict specification
    such as :func:`to_datetime`.
 
    .. ipython:: python
-      :okwarning:
 
       df = pd.read_csv(StringIO(data), dtype="category")
       df.dtypes
       df["col3"]
-      df["col3"].cat.categories = pd.to_numeric(df["col3"].cat.categories)
+      new_categories = pd.to_numeric(df["col3"].cat.categories)
+      df["col3"] = df["col3"].cat.rename_categories(new_categories)
       df["col3"]
 
 .. _whatsnew_0190.enhancements.union_categoricals:
diff --git a/pandas/core/arrays/categorical.py b/pandas/core/arrays/categorical.py
index 91bdc106ad0b8..becca2b668290 100644
--- a/pandas/core/arrays/categorical.py
+++ b/pandas/core/arrays/categorical.py
@@ -15,11 +15,7 @@
     cast,
     overload,
 )
-from warnings import (
-    catch_warnings,
-    simplefilter,
-    warn,
-)
+from warnings import warn
 
 import numpy as np
 
@@ -31,10 +27,6 @@
     lib,
 )
 from pandas._libs.arrays import NDArrayBacked
-from pandas._libs.lib import (
-    NoDefault,
-    no_default,
-)
 from pandas._typing import (
     ArrayLike,
     AstypeArg,
@@ -48,7 +40,6 @@
     type_t,
 )
 from pandas.compat.numpy import function as nv
-from pandas.util._decorators import deprecate_nonkeyword_arguments
 from pandas.util._exceptions import find_stack_level
 from pandas.util._validators import validate_bool_kwarg
 
@@ -729,8 +720,6 @@ def categories(self) -> Index:
         unique and the number of items in the new categories must be the same
         as the number of items in the old categories.
 
-        Assigning to `categories` is a inplace operation!
-
         Raises
         ------
         ValueError
@@ -748,17 +737,6 @@ def categories(self) -> Index:
         """
         return self.dtype.categories
 
-    @categories.setter
-    def categories(self, categories) -> None:
-        warn(
-            "Setting categories in-place is deprecated and will raise in a "
-            "future version. Use rename_categories instead.",
-            FutureWarning,
-            stacklevel=find_stack_level(),
-        )
-
-        self._set_categories(categories)
-
     @property
     def ordered(self) -> Ordered:
         """
@@ -839,24 +817,7 @@ def _set_dtype(self, dtype: CategoricalDtype) -> Categorical:
         codes = recode_for_categories(self.codes, self.categories, dtype.categories)
         return type(self)(codes, dtype=dtype, fastpath=True)
 
-    @overload
-    def set_ordered(
-        self, value, *, inplace: NoDefault | Literal[False] = ...
-    ) -> Categorical:
-        ...
-
-    @overload
-    def set_ordered(self, value, *, inplace: Literal[True]) -> None:
-        ...
-
-    @overload
-    def set_ordered(self, value, *, inplace: bool) -> Categorical | None:
-        ...
-
-    @deprecate_nonkeyword_arguments(version=None, allowed_args=["self", "value"])
-    def set_ordered(
-        self, value, inplace: bool | NoDefault = no_default
-    ) -> Categorical | None:
+    def set_ordered(self, value: bool) -> Categorical:
         """
         Set the ordered attribute to the boolean value.
 
@@ -864,98 +825,35 @@ def set_ordered(
         ----------
         value : bool
            Set whether this categorical is ordered (True) or not (False).
-        inplace : bool, default False
-           Whether or not to set the ordered attribute in-place or return
-           a copy of this categorical with ordered set to the value.
-
-           .. deprecated:: 1.5.0
-
         """
-        if inplace is not no_default:
-            warn(
-                "The `inplace` parameter in pandas.Categorical."
-                "set_ordered is deprecated and will be removed in "
-                "a future version. setting ordered-ness on categories will always "
-                "return a new Categorical object.",
-                FutureWarning,
-                stacklevel=find_stack_level(),
-            )
-        else:
-            inplace = False
-
-        inplace = validate_bool_kwarg(inplace, "inplace")
         new_dtype = CategoricalDtype(self.categories, ordered=value)
-        cat = self if inplace else self.copy()
+        cat = self.copy()
         NDArrayBacked.__init__(cat, cat._ndarray, new_dtype)
-        if not inplace:
-            return cat
-        return None
-
-    @overload
-    def as_ordered(self, *, inplace: NoDefault | Literal[False] = ...) -> Categorical:
-        ...
-
-    @overload
-    def as_ordered(self, *, inplace: Literal[True]) -> None:
-        ...
+        return cat
 
-    @deprecate_nonkeyword_arguments(version=None, allowed_args=["self"])
-    def as_ordered(self, inplace: bool | NoDefault = no_default) -> Categorical | None:
+    def as_ordered(self) -> Categorical:
         """
         Set the Categorical to be ordered.
 
-        Parameters
-        ----------
-        inplace : bool, default False
-           Whether or not to set the ordered attribute in-place or return
-           a copy of this categorical with ordered set to True.
-
-           .. deprecated:: 1.5.0
-
         Returns
         -------
-        Categorical or None
-            Ordered Categorical or None if ``inplace=True``.
+        Categorical
+            Ordered Categorical.
         """
-        if inplace is not no_default:
-            inplace = validate_bool_kwarg(inplace, "inplace")
-        return self.set_ordered(True, inplace=inplace)
-
-    @overload
-    def as_unordered(self, *, inplace: NoDefault | Literal[False] = ...) -> Categorical:
-        ...
-
-    @overload
-    def as_unordered(self, *, inplace: Literal[True]) -> None:
-        ...
+        return self.set_ordered(True)
 
-    @deprecate_nonkeyword_arguments(version=None, allowed_args=["self"])
-    def as_unordered(
-        self, inplace: bool | NoDefault = no_default
-    ) -> Categorical | None:
+    def as_unordered(self) -> Categorical:
         """
         Set the Categorical to be unordered.
 
-        Parameters
-        ----------
-        inplace : bool, default False
-           Whether or not to set the ordered attribute in-place or return
-           a copy of this categorical with ordered set to False.
-
-           .. deprecated:: 1.5.0
-
         Returns
         -------
-        Categorical or None
-            Unordered Categorical or None if ``inplace=True``.
+        Categorical
+            Unordered Categorical.
         """
-        if inplace is not no_default:
-            inplace = validate_bool_kwarg(inplace, "inplace")
-        return self.set_ordered(False, inplace=inplace)
+        return self.set_ordered(False)
 
-    def set_categories(
-        self, new_categories, ordered=None, rename: bool = False, inplace=no_default
-    ):
+    def set_categories(self, new_categories, ordered=None, rename: bool = False):
         """
         Set the categories to the specified new_categories.
 
@@ -985,15 +883,10 @@ def set_categories(
         rename : bool, default False
            Whether or not the new_categories should be considered as a rename
            of the old categories or as reordered categories.
-        inplace : bool, default False
-           Whether or not to reorder the categories in-place or return a copy
-           of this categorical with reordered categories.
-
-           .. deprecated:: 1.3.0
 
         Returns
         -------
-        Categorical with reordered categories or None if inplace.
+        Categorical with reordered categories.
 
         Raises
         ------
@@ -1008,24 +901,12 @@ def set_categories(
         remove_categories : Remove the specified categories.
         remove_unused_categories : Remove categories which are not used.
         """
-        if inplace is not no_default:
-            warn(
-                "The `inplace` parameter in pandas.Categorical."
-                "set_categories is deprecated and will be removed in "
-                "a future version. Removing unused categories will always "
-                "return a new Categorical object.",
-                FutureWarning,
-                stacklevel=find_stack_level(),
-            )
-        else:
-            inplace = False
 
-        inplace = validate_bool_kwarg(inplace, "inplace")
         if ordered is None:
             ordered = self.dtype.ordered
         new_dtype = CategoricalDtype(new_categories, ordered=ordered)
 
-        cat = self if inplace else self.copy()
+        cat = self.copy()
         if rename:
             if cat.dtype.categories is not None and len(new_dtype.categories) < len(
                 cat.dtype.categories
@@ -1038,26 +919,9 @@ def set_categories(
                 cat.codes, cat.categories, new_dtype.categories
             )
         NDArrayBacked.__init__(cat, codes, new_dtype)
+        return cat
 
-        if not inplace:
-            return cat
-
-    @overload
-    def rename_categories(
-        self, new_categories, *, inplace: Literal[False] | NoDefault = ...
-    ) -> Categorical:
-        ...
-
-    @overload
-    def rename_categories(self, new_categories, *, inplace: Literal[True]) -> None:
-        ...
-
-    @deprecate_nonkeyword_arguments(
-        version=None, allowed_args=["self", "new_categories"]
-    )
-    def rename_categories(
-        self, new_categories, inplace: bool | NoDefault = no_default
-    ) -> Categorical | None:
+    def rename_categories(self, new_categories) -> Categorical:
         """
         Rename categories.
 
@@ -1078,16 +942,10 @@ def rename_categories(
             * callable : a callable that is called on all items in the old
               categories and whose return values comprise the new categories.
 
-        inplace : bool, default False
-            Whether or not to rename the categories inplace or return a copy of
-            this categorical with renamed categories.
-
-            .. deprecated:: 1.3.0
-
         Returns
         -------
-        cat : Categorical or None
-            Categorical with removed categories or None if ``inplace=True``.
+        cat : Categorical
+            Categorical with renamed categories.
 
         Raises
         ------
@@ -1123,32 +981,19 @@ def rename_categories(
         ['A', 'A', 'B']
         Categories (2, object): ['A', 'B']
         """
-        if inplace is not no_default:
-            warn(
-                "The `inplace` parameter in pandas.Categorical."
-                "rename_categories is deprecated and will be removed in "
-                "a future version. Removing unused categories will always "
-                "return a new Categorical object.",
-                FutureWarning,
-                stacklevel=find_stack_level(),
-            )
-        else:
-            inplace = False
-
-        inplace = validate_bool_kwarg(inplace, "inplace")
-        cat = self if inplace else self.copy()
 
         if is_dict_like(new_categories):
-            new_categories = [new_categories.get(item, item) for item in cat.categories]
+            new_categories = [
+                new_categories.get(item, item) for item in self.categories
+            ]
         elif callable(new_categories):
-            new_categories = [new_categories(item) for item in cat.categories]
+            new_categories = [new_categories(item) for item in self.categories]
 
+        cat = self.copy()
         cat._set_categories(new_categories)
-        if not inplace:
-            return cat
-        return None
+        return cat
 
-    def reorder_categories(self, new_categories, ordered=None, inplace=no_default):
+    def reorder_categories(self, new_categories, ordered=None):
         """
         Reorder categories as specified in new_categories.
 
@@ -1162,16 +1007,11 @@ def reorder_categories(self, new_categories, ordered=None, inplace=no_default):
         ordered : bool, optional
            Whether or not the categorical is treated as a ordered categorical.
            If not given, do not change the ordered information.
-        inplace : bool, default False
-           Whether or not to reorder the categories inplace or return a copy of
-           this categorical with reordered categories.
-
-           .. deprecated:: 1.3.0
 
         Returns
         -------
-        cat : Categorical or None
-            Categorical with removed categories or None if ``inplace=True``.
+        cat : Categorical
+            Categorical with reordered categories.
 
         Raises
         ------
@@ -1187,44 +1027,13 @@ def reorder_categories(self, new_categories, ordered=None, inplace=no_default):
         remove_unused_categories : Remove categories which are not used.
         set_categories : Set the categories to the specified ones.
         """
-        if inplace is not no_default:
-            warn(
-                "The `inplace` parameter in pandas.Categorical."
-                "reorder_categories is deprecated and will be removed in "
-                "a future version. Reordering categories will always "
-                "return a new Categorical object.",
-                FutureWarning,
-                stacklevel=find_stack_level(),
-            )
-        else:
-            inplace = False
-
-        inplace = validate_bool_kwarg(inplace, "inplace")
         if set(self.dtype.categories) != set(new_categories):
             raise ValueError(
                 "items in new_categories are not the same as in old categories"
             )
+        return self.set_categories(new_categories, ordered=ordered)
 
-        with catch_warnings():
-            simplefilter("ignore")
-            return self.set_categories(new_categories, ordered=ordered, inplace=inplace)
-
-    @overload
-    def add_categories(
-        self, new_categories, *, inplace: Literal[False] | NoDefault = ...
-    ) -> Categorical:
-        ...
-
-    @overload
-    def add_categories(self, new_categories, *, inplace: Literal[True]) -> None:
-        ...
-
-    @deprecate_nonkeyword_arguments(
-        version=None, allowed_args=["self", "new_categories"]
-    )
-    def add_categories(
-        self, new_categories, inplace: bool | NoDefault = no_default
-    ) -> Categorical | None:
+    def add_categories(self, new_categories) -> Categorical:
         """
         Add new categories.
 
@@ -1235,16 +1044,11 @@ def add_categories(
         ----------
         new_categories : category or list-like of category
            The new categories to be included.
-        inplace : bool, default False
-           Whether or not to add the categories inplace or return a copy of
-           this categorical with added categories.
-
-           .. deprecated:: 1.3.0
 
         Returns
         -------
-        cat : Categorical or None
-            Categorical with new categories added or None if ``inplace=True``.
+        cat : Categorical
+            Categorical with new categories added.
 
         Raises
         ------
@@ -1271,19 +1075,7 @@ def add_categories(
         ['c', 'b', 'c']
         Categories (4, object): ['b', 'c', 'd', 'a']
         """
-        if inplace is not no_default:
-            warn(
-                "The `inplace` parameter in pandas.Categorical."
-                "add_categories is deprecated and will be removed in "
-                "a future version. Removing unused categories will always "
-                "return a new Categorical object.",
-                FutureWarning,
-                stacklevel=find_stack_level(),
-            )
-        else:
-            inplace = False
 
-        inplace = validate_bool_kwarg(inplace, "inplace")
         if not is_list_like(new_categories):
             new_categories = [new_categories]
         already_included = set(new_categories) & set(self.dtype.categories)
@@ -1305,15 +1097,12 @@ def add_categories(
             new_categories = list(self.dtype.categories) + list(new_categories)
 
         new_dtype = CategoricalDtype(new_categories, self.ordered)
-
-        cat = self if inplace else self.copy()
+        cat = self.copy()
         codes = coerce_indexer_dtype(cat._ndarray, new_dtype.categories)
         NDArrayBacked.__init__(cat, codes, new_dtype)
-        if not inplace:
-            return cat
-        return None
+        return cat
 
-    def remove_categories(self, removals, inplace=no_default):
+    def remove_categories(self, removals):
         """
         Remove the specified categories.
 
@@ -1324,16 +1113,11 @@ def remove_categories(self, removals, inplace=no_default):
         ----------
         removals : category or list of categories
            The categories which should be removed.
-        inplace : bool, default False
-           Whether or not to remove the categories inplace or return a copy of
-           this categorical with removed categories.
-
-           .. deprecated:: 1.3.0
 
         Returns
         -------
-        cat : Categorical or None
-            Categorical with removed categories or None if ``inplace=True``.
+        cat : Categorical
+            Categorical with removed categories.
 
         Raises
         ------
@@ -1359,19 +1143,6 @@ def remove_categories(self, removals, inplace=no_default):
         [NaN, 'c', 'b', 'c', NaN]
         Categories (2, object): ['b', 'c']
         """
-        if inplace is not no_default:
-            warn(
-                "The `inplace` parameter in pandas.Categorical."
-                "remove_categories is deprecated and will be removed in "
-                "a future version. Removing unused categories will always "
-                "return a new Categorical object.",
-                FutureWarning,
-                stacklevel=find_stack_level(),
-            )
-        else:
-            inplace = False
-
-        inplace = validate_bool_kwarg(inplace, "inplace")
         if not is_list_like(removals):
             removals = [removals]
 
@@ -1387,11 +1158,7 @@ def remove_categories(self, removals, inplace=no_default):
         if len(not_included) != 0:
             raise ValueError(f"removals must all be in old categories: {not_included}")
 
-        with catch_warnings():
-            simplefilter("ignore")
-            return self.set_categories(
-                new_categories, ordered=self.ordered, rename=False, inplace=inplace
-            )
+        return self.set_categories(new_categories, ordered=self.ordered, rename=False)
 
     def remove_unused_categories(self) -> Categorical:
         """
@@ -2522,40 +2289,40 @@ def _replace(self, *, to_replace, value, inplace: bool = False):
         inplace = validate_bool_kwarg(inplace, "inplace")
         cat = self if inplace else self.copy()
 
-        # build a dict of (to replace -> value) pairs
-        if is_list_like(to_replace):
-            # if to_replace is list-like and value is scalar
-            replace_dict = {replace_value: value for replace_value in to_replace}
-        else:
-            # if both to_replace and value are scalar
-            replace_dict = {to_replace: value}
-
         # other cases, like if both to_replace and value are list-like or if
         # to_replace is a dict, are handled separately in NDFrame
-        for replace_value, new_value in replace_dict.items():
-            if new_value == replace_value:
+        if not is_list_like(to_replace):
+            to_replace = [to_replace]
+
+        categories = cat.categories.tolist()
+        removals = set()
+        for replace_value in to_replace:
+            if value == replace_value:
+                continue
+            if replace_value not in cat.categories:
                 continue
-            if replace_value in cat.categories:
-                if isna(new_value):
-                    with catch_warnings():
-                        simplefilter("ignore")
-                        cat.remove_categories(replace_value, inplace=True)
-                    continue
-
-                categories = cat.categories.tolist()
-                index = categories.index(replace_value)
-
-                if new_value in cat.categories:
-                    value_index = categories.index(new_value)
-                    cat._codes[cat._codes == index] = value_index
-                    with catch_warnings():
-                        simplefilter("ignore")
-                        cat.remove_categories(replace_value, inplace=True)
-                else:
-                    categories[index] = new_value
-                    with catch_warnings():
-                        simplefilter("ignore")
-                        cat.rename_categories(categories, inplace=True)
+            if isna(value):
+                removals.add(replace_value)
+                continue
+
+            index = categories.index(replace_value)
+
+            if value in cat.categories:
+                value_index = categories.index(value)
+                cat._codes[cat._codes == index] = value_index
+                removals.add(replace_value)
+            else:
+                categories[index] = value
+                cat._set_categories(categories)
+
+        if len(removals):
+            new_categories = [c for c in categories if c not in removals]
+            new_dtype = CategoricalDtype(new_categories, ordered=self.dtype.ordered)
+            codes = recode_for_categories(
+                cat.codes, cat.categories, new_dtype.categories
+            )
+            NDArrayBacked.__init__(cat, codes, new_dtype)
+
         if not inplace:
             return cat
 
@@ -2605,10 +2372,6 @@ class CategoricalAccessor(PandasDelegate, PandasObject, NoNewAttributesMixin):
     """
     Accessor object for categorical properties of the Series values.
 
-    Be aware that assigning to `categories` is a inplace operation, while all
-    methods return new categorical data per default (but can be called with
-    `inplace=True`).
-
     Parameters
     ----------
     data : Series or CategoricalIndex
diff --git a/pandas/tests/arrays/categorical/test_analytics.py b/pandas/tests/arrays/categorical/test_analytics.py
index 2723b838c41a2..55d39cf84eb30 100644
--- a/pandas/tests/arrays/categorical/test_analytics.py
+++ b/pandas/tests/arrays/categorical/test_analytics.py
@@ -320,48 +320,6 @@ def test_validate_inplace_raises(self, value):
             'For argument "inplace" expected type bool, '
             f"received type {type(value).__name__}"
         )
-        with pytest.raises(ValueError, match=msg):
-            with tm.assert_produces_warning(
-                FutureWarning, match="Use rename_categories"
-            ):
-                cat.set_ordered(value=True, inplace=value)
-
-        with pytest.raises(ValueError, match=msg):
-            with tm.assert_produces_warning(
-                FutureWarning, match="Use rename_categories"
-            ):
-                cat.as_ordered(inplace=value)
-
-        with pytest.raises(ValueError, match=msg):
-            with tm.assert_produces_warning(
-                FutureWarning, match="Use rename_categories"
-            ):
-                cat.as_unordered(inplace=value)
-
-        with pytest.raises(ValueError, match=msg):
-            with tm.assert_produces_warning(FutureWarning):
-                # issue #37643 inplace kwarg deprecated
-                cat.set_categories(["X", "Y", "Z"], rename=True, inplace=value)
-
-        with pytest.raises(ValueError, match=msg):
-            with tm.assert_produces_warning(FutureWarning):
-                # issue #37643 inplace kwarg deprecated
-                cat.rename_categories(["X", "Y", "Z"], inplace=value)
-
-        with pytest.raises(ValueError, match=msg):
-            with tm.assert_produces_warning(FutureWarning):
-                # issue #37643 inplace kwarg deprecated
-                cat.reorder_categories(["X", "Y", "Z"], ordered=True, inplace=value)
-
-        with pytest.raises(ValueError, match=msg):
-            with tm.assert_produces_warning(FutureWarning):
-                # issue #37643 inplace kwarg deprecated
-                cat.add_categories(new_categories=["D", "E", "F"], inplace=value)
-
-        with pytest.raises(ValueError, match=msg):
-            with tm.assert_produces_warning(FutureWarning):
-                # issue #37643 inplace kwarg deprecated
-                cat.remove_categories(removals=["D", "E", "F"], inplace=value)
 
         with pytest.raises(ValueError, match=msg):
             cat.sort_values(inplace=value)
diff --git a/pandas/tests/arrays/categorical/test_api.py b/pandas/tests/arrays/categorical/test_api.py
index 2f13d4ee0dd40..450581f89d735 100644
--- a/pandas/tests/arrays/categorical/test_api.py
+++ b/pandas/tests/arrays/categorical/test_api.py
@@ -37,31 +37,14 @@ def test_ordered_api(self):
         assert cat4.ordered
 
     def test_set_ordered(self):
-        msg = (
-            "The `inplace` parameter in pandas.Categorical.set_ordered is "
-            "deprecated and will be removed in a future version. setting "
-            "ordered-ness on categories will always return a new Categorical object"
-        )
         cat = Categorical(["a", "b", "c", "a"], ordered=True)
         cat2 = cat.as_unordered()
         assert not cat2.ordered
         cat2 = cat.as_ordered()
         assert cat2.ordered
-        with tm.assert_produces_warning(FutureWarning, match=msg):
-            cat2.as_unordered(inplace=True)
-        assert not cat2.ordered
-        with tm.assert_produces_warning(FutureWarning, match=msg):
-            cat2.as_ordered(inplace=True)
-        assert cat2.ordered
 
         assert cat2.set_ordered(True).ordered
         assert not cat2.set_ordered(False).ordered
-        with tm.assert_produces_warning(FutureWarning, match=msg):
-            cat2.set_ordered(True, inplace=True)
-        assert cat2.ordered
-        with tm.assert_produces_warning(FutureWarning, match=msg):
-            cat2.set_ordered(False, inplace=True)
-        assert not cat2.ordered
 
         # removed in 0.19.0
         msg = (
@@ -95,17 +78,6 @@ def test_rename_categories(self):
         expected = Categorical(["A", "B", "C", "A"])
         tm.assert_categorical_equal(result, expected)
 
-        # and now inplace
-        with tm.assert_produces_warning(FutureWarning):
-            # issue #37643 inplace kwarg deprecated
-            res = cat.rename_categories([1, 2, 3], inplace=True)
-
-        assert res is None
-        tm.assert_numpy_array_equal(
-            cat.__array__(), np.array([1, 2, 3, 1], dtype=np.int64)
-        )
-        tm.assert_index_equal(cat.categories, Index([1, 2, 3]))
-
     @pytest.mark.parametrize("new_categories", [[1, 2, 3, 4], [1, 2]])
     def test_rename_categories_wrong_length_raises(self, new_categories):
         cat = Categorical(["a", "b", "c", "a"])
@@ -130,14 +102,6 @@ def test_rename_categories_dict(self):
         expected = Index([4, 3, 2, 1])
         tm.assert_index_equal(res.categories, expected)
 
-        # Test for inplace
-        with tm.assert_produces_warning(FutureWarning):
-            # issue #37643 inplace kwarg deprecated
-            res = cat.rename_categories({"a": 4, "b": 3, "c": 2, "d": 1}, inplace=True)
-
-        assert res is None
-        tm.assert_index_equal(cat.categories, expected)
-
         # Test for dicts of smaller length
         cat = Categorical(["a", "b", "c", "d"])
         res = cat.rename_categories({"a": 1, "c": 3})
@@ -165,21 +129,12 @@ def test_reorder_categories(self):
             ["a", "b", "c", "a"], categories=["c", "b", "a"], ordered=True
         )
 
-        # first inplace == False
         res = cat.reorder_categories(["c", "b", "a"])
         # cat must be the same as before
         tm.assert_categorical_equal(cat, old)
         # only res is changed
         tm.assert_categorical_equal(res, new)
 
-        # inplace == True
-        with tm.assert_produces_warning(FutureWarning):
-            # issue #37643 inplace kwarg deprecated
-            res = cat.reorder_categories(["c", "b", "a"], inplace=True)
-
-        assert res is None
-        tm.assert_categorical_equal(cat, new)
-
     @pytest.mark.parametrize(
         "new_categories",
         [
@@ -201,7 +156,6 @@ def test_add_categories(self):
             ["a", "b", "c", "a"], categories=["a", "b", "c", "d"], ordered=True
         )
 
-        # first inplace == False
         res = cat.add_categories("d")
         tm.assert_categorical_equal(cat, old)
         tm.assert_categorical_equal(res, new)
@@ -210,14 +164,6 @@ def test_add_categories(self):
         tm.assert_categorical_equal(cat, old)
         tm.assert_categorical_equal(res, new)
 
-        # inplace == True
-        with tm.assert_produces_warning(FutureWarning):
-            # issue #37643 inplace kwarg deprecated
-            res = cat.add_categories("d", inplace=True)
-
-        tm.assert_categorical_equal(cat, new)
-        assert res is None
-
         # GH 9927
         cat = Categorical(list("abc"), ordered=True)
         expected = Categorical(list("abc"), categories=list("abcde"), ordered=True)
@@ -262,14 +208,7 @@ def test_set_categories(self):
         exp_categories = Index(["c", "b", "a"])
         exp_values = np.array(["a", "b", "c", "a"], dtype=np.object_)
 
-        with tm.assert_produces_warning(FutureWarning):
-            # issue #37643 inplace kwarg deprecated
-            res = cat.set_categories(["c", "b", "a"], inplace=True)
-
-        tm.assert_index_equal(cat.categories, exp_categories)
-        tm.assert_numpy_array_equal(cat.__array__(), exp_values)
-        assert res is None
-
+        cat = cat.set_categories(["c", "b", "a"])
         res = cat.set_categories(["a", "b", "c"])
         # cat must be the same as before
         tm.assert_index_equal(cat.categories, exp_categories)
@@ -386,7 +325,6 @@ def test_remove_categories(self):
         old = cat.copy()
         new = Categorical(["a", "b", np.nan, "a"], categories=["a", "b"], ordered=True)
 
-        # first inplace == False
         res = cat.remove_categories("c")
         tm.assert_categorical_equal(cat, old)
         tm.assert_categorical_equal(res, new)
@@ -395,14 +333,6 @@ def test_remove_categories(self):
         tm.assert_categorical_equal(cat, old)
         tm.assert_categorical_equal(res, new)
 
-        # inplace == True
-        with tm.assert_produces_warning(FutureWarning):
-            # issue #37643 inplace kwarg deprecated
-            res = cat.remove_categories("c", inplace=True)
-
-        tm.assert_categorical_equal(cat, new)
-        assert res is None
-
     @pytest.mark.parametrize("removals", [["c"], ["c", np.nan], "c", ["c", "c"]])
     def test_remove_categories_raises(self, removals):
         cat = Categorical(["a", "b", "a"])
@@ -462,11 +392,7 @@ def test_describe(self, factor):
 
         # check unused categories
         cat = factor.copy()
-
-        with tm.assert_produces_warning(FutureWarning):
-            # issue #37643 inplace kwarg deprecated
-            cat.set_categories(["a", "b", "c", "d"], inplace=True)
-
+        cat = cat.set_categories(["a", "b", "c", "d"])
         desc = cat.describe()
 
         exp_index = CategoricalIndex(
@@ -500,15 +426,6 @@ def test_describe(self, factor):
         )
         tm.assert_frame_equal(desc, expected)
 
-    def test_set_categories_inplace(self, factor):
-        cat = factor.copy()
-
-        with tm.assert_produces_warning(FutureWarning):
-            # issue #37643 inplace kwarg deprecated
-            cat.set_categories(["a", "b", "c", "d"], inplace=True)
-
-        tm.assert_index_equal(cat.categories, Index(["a", "b", "c", "d"]))
-
 
 class TestPrivateCategoricalAPI:
     def test_codes_immutable(self):
diff --git a/pandas/tests/arrays/categorical/test_indexing.py b/pandas/tests/arrays/categorical/test_indexing.py
index 94e966642b925..d42b73b7c0020 100644
--- a/pandas/tests/arrays/categorical/test_indexing.py
+++ b/pandas/tests/arrays/categorical/test_indexing.py
@@ -191,14 +191,6 @@ def test_periodindex(self):
         tm.assert_numpy_array_equal(cat3._codes, exp_arr)
         tm.assert_index_equal(cat3.categories, exp_idx)
 
-    def test_categories_assignments(self):
-        cat = Categorical(["a", "b", "c", "a"])
-        exp = np.array([1, 2, 3, 1], dtype=np.int64)
-        with tm.assert_produces_warning(FutureWarning, match="Use rename_categories"):
-            cat.categories = [1, 2, 3]
-        tm.assert_numpy_array_equal(cat.__array__(), exp)
-        tm.assert_index_equal(cat.categories, Index([1, 2, 3]))
-
     @pytest.mark.parametrize(
         "null_val",
         [None, np.nan, NaT, NA, math.nan, "NaT", "nat", "NAT", "nan", "NaN", "NAN"],
@@ -217,9 +209,8 @@ def test_categories_assignments_wrong_length_raises(self, new_categories):
             "new categories need to have the same number of items "
             "as the old categories!"
         )
-        with tm.assert_produces_warning(FutureWarning, match="Use rename_categories"):
-            with pytest.raises(ValueError, match=msg):
-                cat.categories = new_categories
+        with pytest.raises(ValueError, match=msg):
+            cat.rename_categories(new_categories)
 
     # Combinations of sorted/unique:
     @pytest.mark.parametrize(
diff --git a/pandas/tests/frame/indexing/test_setitem.py b/pandas/tests/frame/indexing/test_setitem.py
index 6e7ba57dddf8f..1c08a37c58e4e 100644
--- a/pandas/tests/frame/indexing/test_setitem.py
+++ b/pandas/tests/frame/indexing/test_setitem.py
@@ -1076,12 +1076,7 @@ def test_setitem_mask_categorical(self):
         df = DataFrame({"cats": catsf, "values": valuesf}, index=idxf)
 
         exp_fancy = exp_multi_row.copy()
-        with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
-            # issue #37643 inplace kwarg deprecated
-            return_value = exp_fancy["cats"].cat.set_categories(
-                ["a", "b", "c"], inplace=True
-            )
-        assert return_value is None
+        exp_fancy["cats"] = exp_fancy["cats"].cat.set_categories(["a", "b", "c"])
 
         mask = df["cats"] == "c"
         df[mask] = ["b", 2]
diff --git a/pandas/tests/series/accessors/test_cat_accessor.py b/pandas/tests/series/accessors/test_cat_accessor.py
index 48a01f0018775..54a3ddd24a203 100644
--- a/pandas/tests/series/accessors/test_cat_accessor.py
+++ b/pandas/tests/series/accessors/test_cat_accessor.py
@@ -46,13 +46,6 @@ def test_cat_accessor(self):
 
         exp = Categorical(["a", "b", np.nan, "a"], categories=["b", "a"])
 
-        with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
-            # issue #37643 inplace kwarg deprecated
-            return_value = ser.cat.set_categories(["b", "a"], inplace=True)
-
-        assert return_value is None
-        tm.assert_categorical_equal(ser.values, exp)
-
         res = ser.cat.set_categories(["b", "a"])
         tm.assert_categorical_equal(res.values, exp)
 
@@ -99,8 +92,7 @@ def test_categorical_delegations(self):
         ser = Series(Categorical(["a", "b", "c", "a"], ordered=True))
         exp_categories = Index(["a", "b", "c"])
         tm.assert_index_equal(ser.cat.categories, exp_categories)
-        with tm.assert_produces_warning(FutureWarning, match="Use rename_categories"):
-            ser.cat.categories = [1, 2, 3]
+        ser = ser.cat.rename_categories([1, 2, 3])
         exp_categories = Index([1, 2, 3])
         tm.assert_index_equal(ser.cat.categories, exp_categories)
 
@@ -110,9 +102,8 @@ def test_categorical_delegations(self):
         assert ser.cat.ordered
         ser = ser.cat.as_unordered()
         assert not ser.cat.ordered
-        with tm.assert_produces_warning(FutureWarning, match="The `inplace`"):
-            return_value = ser.cat.as_ordered(inplace=True)
-        assert return_value is None
+
+        ser = ser.cat.as_ordered()
         assert ser.cat.ordered
 
         # reorder
@@ -234,34 +225,13 @@ def test_dt_accessor_api_for_categorical_invalid(self):
             invalid.dt
         assert not hasattr(invalid, "str")
 
-    def test_reorder_categories_updates_dtype(self):
-        # GH#43232
-        ser = Series(["a", "b", "c"], dtype="category")
-        orig_dtype = ser.dtype
-
-        # Need to construct this before calling reorder_categories inplace
-        expected = ser.cat.reorder_categories(["c", "b", "a"])
-
-        with tm.assert_produces_warning(FutureWarning, match="`inplace` parameter"):
-            ser.cat.reorder_categories(["c", "b", "a"], inplace=True)
-
-        assert not orig_dtype.categories.equals(ser.dtype.categories)
-        assert not orig_dtype.categories.equals(expected.dtype.categories)
-        assert ser.dtype == expected.dtype
-        assert ser.dtype.categories.equals(expected.dtype.categories)
-
-        tm.assert_series_equal(ser, expected)
-
     def test_set_categories_setitem(self):
         # GH#43334
 
         df = DataFrame({"Survived": [1, 0, 1], "Sex": [0, 1, 1]}, dtype="category")
 
-        # change the dtype in-place
-        with tm.assert_produces_warning(FutureWarning, match="Use rename_categories"):
-            df["Survived"].cat.categories = ["No", "Yes"]
-        with tm.assert_produces_warning(FutureWarning, match="Use rename_categories"):
-            df["Sex"].cat.categories = ["female", "male"]
+        df["Survived"] = df["Survived"].cat.rename_categories(["No", "Yes"])
+        df["Sex"] = df["Sex"].cat.rename_categories(["female", "male"])
 
         # values should not be coerced to NaN
         assert list(df["Sex"]) == ["female", "male", "male"]
diff --git a/pandas/tests/series/test_constructors.py b/pandas/tests/series/test_constructors.py
index 4a4b5bd3edc6c..11f8544b78e94 100644
--- a/pandas/tests/series/test_constructors.py
+++ b/pandas/tests/series/test_constructors.py
@@ -478,8 +478,7 @@ def test_categorical_sideeffects_free(self):
         cat = Categorical(["a", "b", "c", "a"])
         s = Series(cat, copy=True)
         assert s.cat is not cat
-        with tm.assert_produces_warning(FutureWarning, match="Use rename_categories"):
-            s.cat.categories = [1, 2, 3]
+        s = s.cat.rename_categories([1, 2, 3])
         exp_s = np.array([1, 2, 3, 1], dtype=np.int64)
         exp_cat = np.array(["a", "b", "c", "a"], dtype=np.object_)
         tm.assert_numpy_array_equal(s.__array__(), exp_s)
@@ -496,16 +495,14 @@ def test_categorical_sideeffects_free(self):
         cat = Categorical(["a", "b", "c", "a"])
         s = Series(cat)
         assert s.values is cat
-        with tm.assert_produces_warning(FutureWarning, match="Use rename_categories"):
-            s.cat.categories = [1, 2, 3]
+        s = s.cat.rename_categories([1, 2, 3])
+        assert s.values is not cat
         exp_s = np.array([1, 2, 3, 1], dtype=np.int64)
         tm.assert_numpy_array_equal(s.__array__(), exp_s)
-        tm.assert_numpy_array_equal(cat.__array__(), exp_s)
 
         s[0] = 2
         exp_s2 = np.array([2, 2, 3, 1], dtype=np.int64)
         tm.assert_numpy_array_equal(s.__array__(), exp_s2)
-        tm.assert_numpy_array_equal(cat.__array__(), exp_s2)
 
     def test_unordered_compare_equal(self):
         left = Series(["a", "b", "c"], dtype=CategoricalDtype(["a", "b"]))