code: def column_correlations(self, X):
          
          utils.validation.check_is_fitted(self, 's_')
  
          # Convert numpy array to pandas DataFrame
          if isinstance(X, np.ndarray):
              X = pd.DataFrame(X)
  
          row_pc = self.row_coordinates(X)
  
          return pd.DataFrame({
              component: {
                  feature: row_pc[component].corr(X[feature])
                  for feature in X.columns
              }
              for component in row_pc.columns
          })
docs: Returns the column correlations with each principal component.