diff --git a/doc/source/user_guide/enhancingperf.rst b/doc/source/user_guide/enhancingperf.rst
index 1d84d05fda079..2056fe2f754f8 100644
--- a/doc/source/user_guide/enhancingperf.rst
+++ b/doc/source/user_guide/enhancingperf.rst
@@ -396,7 +396,7 @@ Consider the following toy example of doubling each observation:
    1000 loops, best of 3: 233 us per loop
 
    # Custom function with numba
-   In [7]: %timeit (df['col1_doubled'] = double_every_value_withnumba(df['a'].to_numpy())
+   In [7]: %timeit df['col1_doubled'] = double_every_value_withnumba(df['a'].to_numpy())
    1000 loops, best of 3: 145 us per loop
 
 Caveats
@@ -599,13 +599,6 @@ identifier.
 The ``inplace`` keyword determines whether this assignment will performed
 on the original ``DataFrame`` or return a copy with the new column.
 
-.. warning::
-
-   For backwards compatibility, ``inplace`` defaults to ``True`` if not
-   specified. This will change in a future version of pandas - if your
-   code depends on an inplace assignment you should update to explicitly
-   set ``inplace=True``.
-
 .. ipython:: python
 
    df = pd.DataFrame(dict(a=range(5), b=range(5, 10)))
@@ -614,7 +607,7 @@ on the original ``DataFrame`` or return a copy with the new column.
    df.eval('a = 1', inplace=True)
    df
 
-When ``inplace`` is set to ``False``, a copy of the ``DataFrame`` with the
+When ``inplace`` is set to ``False``, the default, a copy of the ``DataFrame`` with the
 new or modified columns is returned and the original frame is unchanged.
 
 .. ipython:: python
@@ -653,11 +646,6 @@ whether the query modifies the original frame.
    df.query('a > 2', inplace=True)
    df
 
-.. warning::
-
-   Unlike with ``eval``, the default value for ``inplace`` for ``query``
-   is ``False``.  This is consistent with prior versions of pandas.
-
 Local variables
 ~~~~~~~~~~~~~~~