code: def _tile_subset_tree(cls, op: "DuplicateOperand", inp):
      # subset is available for DataFrame only
      inp = asdataframe(inp)
      out = op.outputs[0]
      subset = op.subset
      if subset is None:
          subset = inp.dtypes.index.tolist()
      # select subset first
      subset_df = yield from recursive_tile(inp[subset])
      # tree aggregate subset
      subset_chunk = cls._gen_tree_chunks(op, subset_df, "subset_tree")[
          0
      ]
  
      out_chunks = []
      for c in inp.chunks:
          chunk_op = op.copy().reset_key()
          chunk_op._method = "subset_tree"
          chunk_op._subset_chunk = subset_chunk
          chunk_params = cls._gen_chunk_params(chunk_op, c)
          out_chunks.append(
              chunk_op.new_chunk([c, subset_chunk], kws=[chunk_params])
          )
  
      new_op = op.copy()
      params = out.params
      params["chunks"] = out_chunks
      splits = tuple(c.shape[0] for c in out_chunks)
      if out.ndim == 2:
          params["nsplits"] = (splits, inp.nsplits[1])
      else:
          params["nsplits"] = (splits,)
      return new_op.new_tileables([inp], kws=[params])
  
imports: import inspect
  import numpy
  import pandas
  from pandas.api.types import is_list_like
  from ...config import options
  from ...core import OutputType, recursive_tile
  from ...core.operand import OperandStage, MapReduceOperand
  from ...serialization.serializables import AnyField, Int32Field, StringField, KeyField
  from ...utils import ceildiv, has_unknown_shape, lazy_import
  from ..initializer import DataFrame
  from ..operands import DataFrameOperandMixin, DataFrameShuffleProxy
label_desc: Use image node_id 16 for calling the DuplicateOperand obj's underlying member method code with example usage: obj._tile_subset_tree(cls, op, inp) and returns: new_op