code: def _intersperse_insertion_rows_and_columns(self, pairwise_pvals):
          
          for i in self._insertion_indices:
              pairwise_pvals = np.insert(pairwise_pvals, i, np.nan, axis=0)
              pairwise_pvals = np.insert(pairwise_pvals, i, np.nan, axis=1)
          return pairwise_pvals
docs: Return pvals matrix with inserted NaN rows and columns, as numpy.ndarray.
  
          Each insertion (a header or a subtotal) creates an offset in the calculated
          pvals. These need to be taken into account when converting each pval to a
          corresponding column letter. For this reason, we need to insert an all-NaN
          row and a column at the right indices. These are the inserted indices of each
          insertion, along respective dimensions.