Pandas version checks

• I have checked that this issue has not already been reported.

• I have confirmed this bug exists on the latest version of pandas.

• I have confirmed this bug exists on the main branch of pandas.

Reproducible Example

import pandas as pd with pd.option_context("mode.copy_on_write", False): df = pd.DataFrame({"a": [1,2,3], "b": [2,4,6]}) df2 = df.loc[0:1,:] df2.iloc[0,0] = 9999

Issue Description

Under both Python 3.12 and 3.14, with the main branch of Pandas (see details below), the reproducible example does not show the SettingWithCopyWarning.

Possibly related to #61368 (closed), since it probably also has to do with refcounts. This bug happens on multiple versions of Python, though, instead of only with Python 3.14.

Expected Behavior

To show the SettingWithCopyWarning. Under Pandas 2.3.3 it works fine and does show the warning:

SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy df2.iloc[0,0] = 9999 

As in the example, users may choose to disable copy-on-write (pd.options.mode.copy_on_write = False) in order to use the view of a data frame with working assignment on the original data frame, as is the default in Pandas < 3.0. However, if they choose to disable copy-on-write, they still should be warned that they are modifying the original data frame, just like in Pandas < 3.0.

Installed Versions