def getstats(self, save=True, filename=None, samples=None, subset=None, ablation_time=False):
        """
        Return pandas dataframe of all sample statistics.
        """
        slst = []

        if samples is not None:
            subset = self.make_subset(samples)

        samples = self._get_samples(subset)

        for s in self.stats_calced:
            for nm in [n for n in samples if self.srm_identifier
                       not in n]:
                if self.stats[nm][s].ndim == 2:
                    # make multi - index
                    reps = np.arange(self.stats[nm][s].shape[-1])
                    ss = np.array([s] * reps.size)
                    nms = np.array([nm] * reps.size)
                    # make sub - dataframe
                    stdf = pd.DataFrame(self.stats[nm][s].T,
                                        columns=self.stats[nm]['analytes'],
                                        index=[ss, nms, reps])
                    stdf.index.set_names(['statistic', 'sample', 'rep'],
                                         inplace=True)
                else:
                    stdf = pd.DataFrame(self.stats[nm][s],
                                        index=self.stats[nm]['analytes'],
                                        columns=[[s], [nm]]).T

                    stdf.index.set_names(['statistic', 'sample'],
                                         inplace=True)
                slst.append(stdf)
        out = pd.concat(slst)

        if ablation_time:
            ats = self.ablation_times(samples=samples, subset=subset)
            ats['statistic'] = 'nanmean'
            ats.set_index('statistic', append=True, inplace=True)
            ats = ats.reorder_levels(['statistic', 'sample', 'rep'])

            out = out.join(ats)

        out.drop(self.internal_standard, 1, inplace=True)

        if save:
            if filename is None:
                filename = 'stat_export.csv'
            out.to_csv(self.export_dir + '/' + filename)

        self.stats_df = out

        return out
Return pandas dataframe of all sample statistics.