code: def _zero_many(self, i, j):
      
      i, j, M, N = self._prepare_indices(i, j)
  
      n_samples = len(i)
      offsets = np.empty(n_samples, dtype=self.indices.dtype)
      ret = _sparsetools.csr_sample_offsets(M, N, self.indptr, self.indices,
                                            n_samples, i, j, offsets)
      if ret == 1:
          # rinse and repeat
          self.sum_duplicates()
          _sparsetools.csr_sample_offsets(M, N, self.indptr,
                                          self.indices, n_samples, i, j,
                                          offsets)
  
      # only assign zeros to the existing sparsity structure
      self.data[list(offsets[offsets > -1])] = 0
docs: Sets value at each (i, j) to zero, preserving sparsity structure.
  
      Here (i,j) index major and minor respectively.