def _combine_individual_stats(self, operator_count, cv_score, individual_stats):
        """Combine the stats with operator count and cv score and preprare to be written to _evaluated_individuals

        Parameters
        ----------
        operator_count: int
            number of components in the pipeline
        cv_score: float
            internal cross validation score
        individual_stats: dictionary
            dict containing statistics about the individual. currently:
            'generation': generation in which the individual was evaluated
            'mutation_count': number of mutation operations applied to the individual and its predecessor cumulatively
            'crossover_count': number of crossover operations applied to the individual and its predecessor cumulatively
            'predecessor': string representation of the individual

        Returns
        -------
        stats: dictionary
            dict containing the combined statistics:
            'operator_count': number of operators in the pipeline
            'internal_cv_score': internal cross validation score
            and all the statistics contained in the 'individual_stats' parameter
        """
        stats = deepcopy(individual_stats)  # Deepcopy, since the string reference to predecessor should be cloned
        stats['operator_count'] = operator_count
        stats['internal_cv_score'] = cv_score
        return stats