code: def pcc_pos(self, row1, row2):
          
          mean1 = np.mean(row1)
          mean2 = np.mean(row2)
  
          a = 0
          x = 0
          y = 0
          for n1, n2 in zip(row1, row2):
              a += (n1 - mean1) * (n2 - mean2)
              x += (n1 - mean1) ** 2
              y += (n2 - mean2) ** 2
          
          if a == 0:
              return 0
          else:
              return a / sqrt(x * y)
docs: Calculate the Pearson correlation coefficient of one position
          compared to another position.
  
          Returns
          -------
          score : float
              Pearson correlation coefficient.