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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def is_nondominated_continuous(self, obs_df):
 """identify which candidate solutions are pareto non-dominated continuously updated, but still slow Parameters obs_df : pandas.DataFrame dataframe with columns of observation names and rows of realizations Returns ------- is_dominated : pandas.Series series with index of obs_df and bool series """


        obj_df = obs_df.loc[:,self.obs_obj_names]
        P = list(obj_df.index)
        PP = set()
        PP.add(P[0])

        #iidx = 1
        #while iidx < len(P):
        for iidx in P:
            jidx = 0
            drop = []
            keep = True
            for jidx in PP:
                # if dominates(iidx,jidx):
                #     drop.append(jidx)
                # elif dominates(jidx,iidx):
                #     keep = False
                #     break
                if jidx == iidx:
                    continue
                if self.dominates(obj_df.loc[iidx, :], obj_df.loc[jidx, :]):
                    drop.append(jidx)
                elif self.dominates(obj_df.loc[jidx, :], obj_df.loc[iidx, :]):
                    keep = False
                    break
            for d in drop:
                PP.remove(d)
            if keep:
                PP.add(iidx)
            #iidx += 1




        is_nondom = pd.Series(data=False,index=obs_df.index,dtype=bool)
        is_nondom.loc[PP] = True
        return is_nondom