code: def deploy_ray_func_between_two_axis_partitions(
      axis, func, num_splits, len_of_left, kwargs, *partitions
  ):
      
      lt_table = concat_arrow_table_partitions(axis, partitions[:len_of_left])
      rt_table = concat_arrow_table_partitions(axis, partitions[len_of_left:])
      try:
          result = func(lt_table, rt_table, **kwargs)
      except Exception:
          lt_frame = lt_table.from_pandas()
          rt_frame = rt_table.from_pandas()
          result = pyarrow.Table.from_pandas(func(lt_frame, rt_frame, **kwargs))
      return split_arrow_table_result(
          axis, result, len(result.num_rows), num_splits, result.schema.metadata
      )
docs: Deploy a function along a full axis between two data sets in Ray.
  
      Args:
          axis: The axis to perform the function along.
          func: The function to perform.
          num_splits: The number of splits to return
              (see `split_result_of_axis_func_pandas`).
          len_of_left: The number of values in `partitions` that belong to the
              left data set.
          kwargs: A dictionary of keyword arguments.
          partitions: All partitions that make up the full axis (row or column)
              for both data sets.
  
      Returns:
          A list of Pandas DataFrames.