§ \ qiiãó—dZdZdZdS)aA value is being set on a copy of a DataFrame or Series through chained assignment. Such chained assignment never works to update the original DataFrame or Series, because the intermediate object on which we are setting values always behaves as a copy (due to Copy-on-Write). Try using '.loc[row_indexer, col_indexer] = value' instead, to perform the assignment in a single step. See the documentation for a more detailed explanation: https://pandas.pydata.org/pandas-docs/stable/user_guide/copy_on_write.html#chained-assignmenta¬A value is being set on a copy of a DataFrame or Series through chained assignment using an inplace method. Such inplace method never works to update the original DataFrame or Series, because the intermediate object on which we are setting values always behaves as a copy (due to Copy-on-Write). For example, when doing 'df[col].method(value, inplace=True)', try using 'df.method({col: value}, inplace=True)' instead, to perform the operation inplace on the original object, or try to avoid an inplace operation using 'df[col] = df[col].method(value)'. See the documentation for a more detailed explanation: https://pandas.pydata.org/pandas-docs/stable/user_guide/copy_on_write.htmlaBA value is being set on a copy of a DataFrame or Series through chained assignment using an inplace method. Such inplace method never works to update the original DataFrame or Series, because the intermediate object on which we are setting values always behaves as a copy (due to Copy-on-Write). For example, when doing 'df[col].update(other)', try using 'df.update({col: other})' instead, to perform the operation inplace on the original object. See the documentation for a more detailed explanation: https://pandas.pydata.org/pandas-docs/stable/user_guide/copy_on_write.htmlN)Ú_chained_assignment_msgÚ_chained_assignment_method_msgÚ%_chained_assignment_method_update_msg©óúq/var/www/html/bestrading.cuttalo.com/services/ml-inference/venv/lib/python3.11/site-packages/pandas/errors/cow.pyúrs)ðð ,ðð ðð" ð&Ð%Ð%r