Future warning from Anaconda about chained assignment

[rppunr]

Hi Bart team,
Specifics about my environment:

1. Microsoft Windows 11 Home-Version 10.0.22631 Build 22631

2. Anaconda - conda 25.5.1

3. Python 3.13.5

   I received a future warning when running bart2 sims in Anaconda. This is the warning:

stat.loc[i]['zscore'] = (stat.loc[i]['score']-tf_stats.loc[i,'mean'])/tf_stats.loc[i,'std']
c:\users\xxx\bart2\bart2-master\bart2-master\bart2\StatTest.py:75: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0!
You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy.
A typical example is when you are setting values in a column of a DataFrame, like:

df["col"][row_indexer] = value

Use df.loc[row_indexer, "col"] = values instead, to perform the assignment in a single step and ensure this keeps updating the original df.

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy

stat.loc[i]['max_auc'] = max(tfs[i])
c:\users\xxx\bart2\bart2-master\bart2-master\bart2\StatTest.py:84: FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0!
You are setting values through chained assignment. Currently this works in certain cases, but when using Copy-on-Write (which will become the default behaviour in pandas 3.0) this will never work to update the original DataFrame or Series, because the intermediate object on which we are setting values will behave as a copy.
A typical example is when you are setting values in a column of a DataFrame, like:

df["col"][row_indexer] = value

Use df.loc[row_indexer, "col"] = values instead, to perform the assignment in a single step and ensure this keeps updating the original df.

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy

Please consider reviewing this warning. Thank you.