feat: Add handling of NaN values to Scaler TableTransformers

[Tarmandan]

Is your feature request related to a problem?

Currently RobustScaler, StandardScaler and possibly RangeScaler will not work on columns containing NaN-values.

Desired solution

The fit and transform methods of the scalers should ignore NaN as they ignore None.

Possible alternatives (optional)

Implementing and raising a ContainsNaNError for the end user might be preferable, as the choice of how to handle rows and columns containing NaN might be relevant to the data science problem.

Screenshots (optional)

No response

Additional Context (optional)

Currently there is no test coverage for NaN and None values in tables for the scalers.

[Tarmandan]

Currently the route chosen is to replace NaN values with None. It is implemented and works on StandardScaler, but needs more test coverage.
Should a warning be added that NaNs have been replaced? It might be unexpected behaviour.
And we have not checked the implications for runtime. It uses the fill_nan from polars, this might not be good for performance.

[Tarmandan]

We discovered that maybe the implementation is not working as intended. We forgot that the with_columns returns a new data_frame (while in the background it only modifies). But then we have some unexplainable error in the robust scaler, see TODO in the test_fit method.