code: def insight_2_global_feature_impact(self, df, expected_values):
      top_positive_variables = []
      average_shap_values_positive = []
  
      top_negative_variables = []
      average_shap_values_negative = []
  
      df_numpy = df.to_numpy()
  
      for i in range(3):
          top_positive_variables.append(df_numpy[-1 * (i + 1)][0])
          average_shap_values_positive.append(df_numpy[-1 * (i + 1)][1])
  
          top_negative_variables.append(df_numpy[i][0])
          average_shap_values_negative.append(df_numpy[i][1])
  
      sentences = []
  
      sentences.append(
          "The average outcome predicted by the model is "
          + str(expected_values)
      )
  
      sentences.append(
          "On average, the variable "
          + top_positive_variables[0]
          + ", "
          + top_positive_variables[1]
          + ",and "
          + top_positive_variables[2]
          + " "
          + "will increase the average model outcome("
          + str(expected_values)
          + ")"
          + " by "
          + str(round(average_shap_values_positive[0], 2))
          + ", "
          + str(round(average_shap_values_positive[1], 2))
          + ", and "
          + str(round(average_shap_values_positive[2], 2))
          + " respectively."
      )
  
      sentences.append(
          "On average, the variable "
          + top_negative_variables[0]
          + ", "
          + top_negative_variables[1]
          + ",and "
          + top_negative_variables[2]
          + " "
          + "will change the average model outcome("
          + str(expected_values)
          + ")"
          + " by "
          + str(round(average_shap_values_negative[0], 2))
          + ", "
          + str(round(average_shap_values_negative[1], 2))
          + ", and"
          + str(round(average_shap_values_negative[2], 2))
          + " respectively."
      )
  
      sentences.append("")
  
      return sentences
  
file_path: explainx/lib/modules/local_explanation/apps/insight_regression.py
imports: from imports import *
label_desc: Use image node_id 3 for calling the insight_regression obj's underlying member method code with example usage: obj.insight_2_global_feature_impact(df, expected_values) and returns: sentences