Skip to content

Commit 8732ef2

Browse files
DOC/CLN: remove outdated warnings in enhancingperf.rst (pandas-dev#33831)
1 parent 21d75fb commit 8732ef2

File tree

1 file changed

+2
-14
lines changed

1 file changed

+2
-14
lines changed

doc/source/user_guide/enhancingperf.rst

+2-14
Original file line numberDiff line numberDiff line change
@@ -396,7 +396,7 @@ Consider the following toy example of doubling each observation:
396396
1000 loops, best of 3: 233 us per loop
397397
398398
# Custom function with numba
399-
In [7]: %timeit (df['col1_doubled'] = double_every_value_withnumba(df['a'].to_numpy())
399+
In [7]: %timeit df['col1_doubled'] = double_every_value_withnumba(df['a'].to_numpy())
400400
1000 loops, best of 3: 145 us per loop
401401
402402
Caveats
@@ -599,13 +599,6 @@ identifier.
599599
The ``inplace`` keyword determines whether this assignment will performed
600600
on the original ``DataFrame`` or return a copy with the new column.
601601

602-
.. warning::
603-
604-
For backwards compatibility, ``inplace`` defaults to ``True`` if not
605-
specified. This will change in a future version of pandas - if your
606-
code depends on an inplace assignment you should update to explicitly
607-
set ``inplace=True``.
608-
609602
.. ipython:: python
610603
611604
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.
614607
df.eval('a = 1', inplace=True)
615608
df
616609
617-
When ``inplace`` is set to ``False``, a copy of the ``DataFrame`` with the
610+
When ``inplace`` is set to ``False``, the default, a copy of the ``DataFrame`` with the
618611
new or modified columns is returned and the original frame is unchanged.
619612

620613
.. ipython:: python
@@ -653,11 +646,6 @@ whether the query modifies the original frame.
653646
df.query('a > 2', inplace=True)
654647
df
655648
656-
.. warning::
657-
658-
Unlike with ``eval``, the default value for ``inplace`` for ``query``
659-
is ``False``. This is consistent with prior versions of pandas.
660-
661649
Local variables
662650
~~~~~~~~~~~~~~~
663651

0 commit comments

Comments
 (0)