code: def _combine_var(pred_results, local_results, axis=0):
      local_sum_data, local_count_data, local_var_data = local_results
      if pred_results is None:
          return (
              local_var_data * local_count_data / (local_count_data - 1)
          )
  
      pred_sum_data, pred_count_data, pred_var_data = pred_results
  
      local_sum_square = (
          local_count_data * local_var_data
          + local_sum_data**2 / local_count_data
      )
      pred_sum_square = (
          pred_count_data * pred_var_data
          + pred_sum_data**2 / pred_count_data
      )
  
      (
          local_sum_square,
          local_sum_data,
          local_count_data,
      ) = _add_pred_results(
          [pred_sum_square, pred_sum_data, pred_count_data],
          [local_sum_square, local_sum_data, local_count_data],
          axis=axis,
      )
  
      return (
          local_sum_square - local_sum_data**2 / local_count_data
      ) / (local_count_data - 1)
  
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 5 for calling a global function with example usage: _combine_var(pred_results, local_results, axis) and returns: unknown, unknown