prepare_data#
- protopipe.mva.prepare_data(ds, derived_features, cuts, select_data=True, label=None)[source]#
Add custom variables to the input data and optionally select it.
- Parameters
- dspandas.DataFrame
Input data not yet selected.
- derived_features: dict
Dictionary of more complex featuresread from the configuration file.
- cuts: str
Fiducial cuts from protopipe.mva.utils.make_cut_list
- select_data: bool
If True apply cuts to the final dataframe.
- label: str
Name of the classifier target label if any.
- Returns
- dspandas.DataFrame
Input data integrated with new variables and optionally selected for the fiducial cuts.