code: def cols_to_multilabel(self):
      """Utility function for correlation and other reducers
      that require transforming hyperparameter values into
      multilabel values before applying the reduction strategy."""
  
      import wrangle
      import pandas as pd
  
      # read in the experiment log
      data = pd.read_csv(self._experiment_log)
  
      # apply recuction window
      data = data.tail(self.reduction_window)
  
      # drop all other metric columns except reduction_metric
      data = data[[self.reduction_metric] + self._param_dict_keys]
  
      # convert all hyperparameter columns to multi label columns
      for col in data.iloc[:, 1:].columns:
          # get the dtype of the column data
          col_dtype = data[col].dtype
  
          # parse column name to contain label, value and dtype
          data = wrangle.col_to_multilabel(
              data,
              col,
              extended_colname=True,
              extended_separator="~" + str(col_dtype) + "~",
          )
  
      return data
  
label_desc: Use image node_id 1 for calling a global function with example usage: cols_to_multilabel() and returns: data