text: class FeatureExtractor():
      def __init__(self, restart_name):
          """
          Parameters
          ----------
          restart_name : str
              The name of the 0/1 column indicating restarts in the time series.
          """
          self.restart_name = restart_name
          pass
  
      def transform(self, X_df_raw):
          """Transform time series into list of states.
          We simply use the observables at time t as the state.
          Be careful not to use any information from the future (X_ds[t + 1:])
          when constructing X_df[t].
          Parameters
          ----------
          X_ds : xarray.Dataset
              The raw time series.
          Return
          ------
          X_df : pandas Dataframe
              The list of states.
          """
  
          X_df = X_df_raw.to_dataframe()
  
          # Since we do not use the restart information in our regressor, we have
          # to remove it
          restart = X_df[self.restart_name].values
          X_df = X_df.drop(columns=self.restart_name)
  
          return X_df
  