def asTable(self):
        data = []
        data.append(['N',self.n])
        data.append(['Mean',self.mean])
        if self.alpha == 0.01:
            data.append(['Mean 99% CI LB',self.mean_ci[0]])
            data.append(['Mean 99% CI UB',self.mean_ci[1]])
        elif self.alpha == 0.05:
            data.append(['Mean 95% CI LB',self.mean_ci[0]])
            data.append(['Mean 95% CI UB',self.mean_ci[1]])
        elif self.alpha == 0.1:
            data.append(['Mean 90% CI LB',self.mean_ci[0]])
            data.append(['Mean 90% CI UB',self.mean_ci[1]])
        elif self.alpha == 0.25:
            data.append(['Mean 75% CI LB',self.mean_ci[0]])
            data.append(['Mean 75% CI UB',self.mean_ci[1]])
        else:
            data.append(['Mean %0.4f CI LB'%(1.-self.alpha,),self.mean_ci[0]])
            data.append([(1.-self.alpha,)%'Mean %0.4f CI UB',self.mean_ci[1]])
        data.append(['Var',self.var])
        data.append(['Std Dev',self.std])
        data.append(['Std Error',self.ste])
        if self.alpha == 0.01:
            data.append(['99% CI LB',self.ci[0]])
            data.append(['99% CI UB',self.ci[1]])
        elif self.alpha == 0.05:
            data.append(['95% CI LB',self.ci[0]])
            data.append(['95% CI UB',self.ci[1]])
        elif self.alpha == 0.1:
            data.append(['90% CI LB',self.ci[0]])
            data.append(['90% CI UB',self.ci[1]])
        elif self.alpha == 0.25:
            data.append(['75% CI LB',self.ci[0]])
            data.append(['75% CI UB',self.ci[1]])
        else:
            data.append(['%0.4f CI LB'%(1.-self.alpha,),self.ci[0]])
            data.append(['%0.4f CI UB'%(1.-self.alpha,),self.ci[1]])
        #data.append(['DF',self.df])
        data.append(['Median',self.median])
        
        return data
dataset/ETHPy150Open bolme/pyvision/src/pyvision/analysis/stats.py/SummaryStats.asTable/swapped operands of `%`