code: def find(self, df):
      df_shap = pd.DataFrame()
      classes = list(df["y_prediction"].unique())
  
      for c in classes:
          df_f = df[df["y_prediction"] == c]
          df_shap0 = self.average_shap(df_f)
          df_shap0["class_name"] = str(c)
  
          df_shap = df_shap.append(df_shap0)
  
      return df_shap
  
imports: from imports import *
label_desc: Use image node_id 2 for calling the feature_impact_classification obj's underlying member method code with example usage: obj.find(df) and returns: df_shap