FutureWarning: ChainedAssignmentError: behaviour will change in pandas 3.0!

[Typhus14]

Hello,
Eto code use fonctions of Panda that will become obsolete soon. Do you think to correct this ?
Thank you for the work

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

self.ts_param['e_a'].loc[self.ts_param['e_a'].isnull()] = (self.ts_param['e_min'][self.ts_param['e_a'].isnull()] * self.ts_param.loc[self.ts_param['e_a'].isnull(), 'RH_max']/100 + self.ts_param['e_max'][self.ts_param['e_a'].isnull()] * self.ts_param.loc[self.ts_param['e_a'].isnull(), 'RH_min']/100)/2

[mullenkamp]

Hi @Typhus14 ,

Thank you very much for detailing the issue and how to fix it. As you mentioned, it should be a pretty easy fix. I'll hopefully get to it soon.

[mullenkamp]

Fixed with #8
Use the new version 1.1.1

[Typhus14]

Thank you very much for the fix. It work very well.
best regards