code: def _get_boots(arr, nboots):
      
      ## hold results (nboots, [dstat, ])
      boots = np.zeros((nboots,))
      
      ## iterate to fill boots
      for bidx in xrange(nboots):
          ## sample with replacement
          lidx = np.random.randint(0, arr.shape[0], arr.shape[0])
          tarr = arr[lidx]
          _, _, dst = _prop_dstat(tarr)
          boots[bidx] = dst
      
      ## return bootarr
      return boots
docs: return array of bootstrap D-stats