code: def _t1_summary(self,x):
          
          # set decimal places
          if isinstance(self._decimals,int):
              n = self._decimals
          elif isinstance(self._decimals,dict):
              try:
                  n = self._decimals[x.name]
              except:
                  n = 1
          else:
              n = 1
              warnings.warn('The decimals arg must be an int or dict. Defaulting to {} d.p.'.format(n))
  
          if x.name in self._nonnormal:
              f = '{{:.{}f}} [{{:.{}f}},{{:.{}f}}]'.format(n,n,n)
              return f.format(np.nanmedian(x.values),
                  np.nanpercentile(x.values,25), np.nanpercentile(x.values,75))
          else:
              f = '{{:.{}f}} ({{:.{}f}})'.format(n,n)
              return f.format(np.nanmean(x.values),
                  np.nanstd(x.values,ddof=self._ddof))
docs: Compute median [IQR] or mean (Std) for the input series.
  
          Parameters
          ----------
              x : pandas Series
                  Series of values to be summarised.