def display(self, show_only_changes=False, show_outcome=False):
        """Display the generatedcounterfactual explanations.

        Parameters
        ----------
        show_only_changes : boolean (default=False)
            Whether to show only changes on feature values.

        show_outcome : boolean (default=False)
            Whether to add a column with the scorecard outcome. If
            ``outcome_type`` is "binary" or "probability", the estimated
            probability of the counterfactual is added.

        Returns
        -------
        counterfactuals : pandas.DataFrame
            Counterfactual explanations.
        """
        self._check_is_generated()
        self._check_counterfactual_is_found()

        if not isinstance(show_only_changes, bool):
            raise TypeError("show_only_changes must be a boolean; got {}."
                            .format(show_only_changes))

        if not isinstance(show_outcome, bool):
            raise TypeError("show_outcome must be a boolean; got {}."
                            .format(show_outcome))

        cf_queries = []
        for cf in self._cfs:
            cf_query = cf["query"].copy()

            if show_only_changes:
                cf_features = cf["features"]
                for v in cf_query.columns:
                    if v not in cf_features:
                        cf_query[v] = "-"

            if show_outcome:
                outcome_type = cf["outcome_type"]

                if outcome_type == "continuous":
                    cf_query["outcome"] = cf["score"]
                else:
                    cf_score = cf["score"]
                    cf_query["outcome"] = 1.0 / (1.0 + np.exp(-cf_score))

            cf_queries.append(cf_query)

        return pd.concat(cf_queries)
Display the generatedcounterfactual explanations.

        Parameters
        ----------
        show_only_changes : boolean (default=False)
            Whether to show only changes on feature values.

        show_outcome : boolean (default=False)
            Whether to add a column with the scorecard outcome. If
            ``outcome_type`` is "binary" or "probability", the estimated
            probability of the counterfactual is added.

        Returns
        -------
        counterfactuals : pandas.DataFrame
            Counterfactual explanations.
        
optbinning/scorecard/counterfactual/counterfactual.py