code: def append_shap_values_to_df(self, input_sv, in_data, scope):
      df_shap = pd.DataFrame(input_sv)
  
      features = list(self.input_data.columns)
      shap_columns = []
      for i in features:
          shap_columns.append(i + "_impact")
  
      try:
          df_shap.columns = shap_columns
      except:
          df_shap = df_shap.T
          df_shap.columns = shap_columns
  
      input_data = in_data
  
      if scope == "global":
          for i in shap_columns:
              input_data[i] = list(df_shap[i])
          return input_data
      else:
          for i in shap_columns:
              input_data[i] = list(df_shap[i])[0]
          return input_data
  
file_path: explainx/lib/frameworks/shapley_values.py
imports: from operator import is_
  import shap
  from explainx.lib.utils import is_classification
  import pandas
  import numpy
label_desc: Use image node_id 6 for calling the ShapleyValues obj's underlying member method code with example usage: obj.append_shap_values_to_df(input_sv, in_data, scope) and returns: input_data, input_data