code: def euclidean_dissim(a, b, **_):
      
      if np.isnan(a).any() or np.isnan(b).any():
          raise ValueError("Missing values detected in numerical columns.")
      return np.sum((a - b) ** 2, axis=1)
docs: Euclidean distance dissimilarity function