docs: def _fit(self, col):
          """Create a map of the empirical probability for each category.
  
          Args:
              col(pandas.DataFrame): Data to transform.
          """
  
          column = col[self.col_name].replace({np.nan: np.inf})
          frequencies = column.groupby(column).count().rename({np.inf: None}).to_dict()
          # next set probability ranges on interval [0,1]
          start = 0
          end = 0
          num_vals = len(col)
  
          for val in frequencies:
              prob = frequencies[val] / num_vals
              end = start + prob
              interval = (start, end)
              mean = np.mean(interval)
              std = prob / 6
              self.probability_map[val] = (interval, mean, std)
              start = end