code: def average_shap(self, df):
      variables = [col for col in df.columns if "_impact" in col]
      y = []
      for i in range(len(variables)):
          p = df[variables[i]].mean()
          y.append(p)
      res = {variables[i]: y[i] for i in range(len(y))}
      res2 = {
          k: v for k, v in sorted(res.items(), key=lambda item: item[1])
      }
      res3 = pd.Series(res2, name="Impact_Value")
      res3.index.name = "VariableName"
      fi = res3.reset_index()
      return fi
  
imports: from imports import *
label_desc: Use image node_id 3 for calling the feature_impact_classification obj's underlying member method code with example usage: obj.average_shap(df) and returns: fi