code: def _execute_combine(cls, ctx, op):
      axis = op.axis
      method = op.method
      limit = op.limit
  
      input_data = ctx[op.inputs[0].key]
      if limit is not None:
          n_summaries = (len(op.inputs) - 1) // 2
          summaries = [
              ctx[inp.key] for inp in op.inputs[1 : 1 + n_summaries]
          ]
      else:
          summaries = [ctx[inp.key] for inp in op.inputs[1:]]
  
      if not summaries:
          ctx[op.outputs[0].key] = input_data.fillna(
              method=method,
              axis=axis,
              limit=limit,
              downcast=op.downcast,
          )
          return
  
      valid_summary = cls._get_first_slice(
          op,
          pd.concat(summaries, axis=axis).fillna(
              method=method, axis=axis
          ),
          1,
      )
  
      if method == "bfill":
          concat_df = pd.concat([input_data, valid_summary], axis=axis)
      else:
          concat_df = pd.concat([valid_summary, input_data], axis=axis)
  
      concat_df.fillna(
          method=method,
          axis=axis,
          inplace=True,
          limit=limit,
          downcast=op.downcast,
      )
      ctx[op.outputs[0].key] = cls._get_first_slice(op, concat_df, -1)
  
imports: import itertools
  import numpy
  import pandas
  from ...None import opcodes
  from ...config import options
  from ...core import ENTITY_TYPE, Entity, OutputType, get_output_types
  from ...core.operand import OperandStage
  from ...serialization.serializables import StringField, AnyField, BoolField, Int64Field
  from ..align import align_dataframe_dataframe, align_dataframe_series, align_series_series
  from ..core import DATAFRAME_TYPE, SERIES_TYPE
  from ..operands import DataFrameOperandMixin, DataFrameOperand
  from ..utils import validate_axis
label_desc: Use image node_id 12 for calling the FillNA obj's underlying member method code with example usage: obj._execute_combine(cls, ctx, op) without return types