code: def add(self, X):
          
          for each in X:
              self.dpp_vector[each] = X[each]
          self.fit(self.dpp_vector.reshape(1, -1))
docs: Add data about known pipeline and scores.
  
          Updates ``dpp_vector`` and refits model with all data.
  
          Args:
              X (dict): mapping of pipeline indices to scores. Keys must correspond to the index of a
                  column in ``dpp_matrix`` and values are the corresponding score for pipeline on
                  the dataset.