code: def _combine_minmax(
      pred_results, local_results, axis=0, fun_name=None
  ):
      if pred_results is None:
          return local_results[0]
  
      pred_size = len(pred_results[0])
      con = pd.concat([pred_results[0], local_results[0]], axis=axis)
      result = con.expanding(axis=axis).agg(fun_name)
      if result.ndim == 2:
          return (
              result.iloc[pred_size:, :]
              if axis == 0
              else result.iloc[:, pred_size:]
          )
      else:
          return result.iloc[pred_size:]
  
imports: from collections import namedtuple
  from functools import partial
  import numpy
  import pandas
  from ....None import opcodes
  from ....serialization.serializables import BoolField
  from ..aggregation import BaseDataFrameExpandingAgg
label_desc: Use image node_id 3 for calling a global function with example usage: _combine_minmax(pred_results, local_results, axis, fun_name) and returns: local_results, unknown, result