code: def run_feature_selection(self, df_data, target, idx=0, **kwargs):
          
          list_features = list(df_data.columns.values)
          list_features.remove(target)
          df_target = pd.DataFrame(df_data[target], columns=[target])
          df_features = df_data[list_features]
  
          return self.predict_features(df_features, df_target, idx=idx, **kwargs)
docs: Run feature selection for one node: wrapper around
          ``self.predict_features``.
  
          Args:
              df_data (pandas.DataFrame): All the observational data
              target (str): Name of the target variable
              idx (int): (optional) For printing purposes
  
          Returns:
              list: scores of each feature relatively to the target