code: def select_row_shap_values(self, shap_values, prediction_col):
      num_of_classes = len(shap_values)
  
      if num_of_classes == len(prediction_col):
          df_final = pd.DataFrame(shap_values)
          return df_final
  
      point_no = 0
      df_array = []
      for p in prediction_col:
          df_array.append(shap_values[p][point_no])
          point_no = point_no + 1
  
      df_final = pd.DataFrame(df_array)
      return df_final
  
file_path: explainx/lib/calculate_shap.py
imports: from imports import *
  from rescale_numeric_feature import *
label_desc: Use image node_id 7 for calling the calculate_shap obj's underlying member method code with example usage: obj.select_row_shap_values(shap_values, prediction_col) and returns: df_final, df_final