code: def tile(cls, op: "DataFrameToDatetime"):
      out = op.outputs[0]
      arg = op.arg
  
      if isinstance(arg, DATAFRAME_TYPE):
          if np.isnan(arg.shape[0]) or any(
              np.isnan(s) for s in arg.nsplits[1]
          ):  # pragma: no cover
              yield
  
          arg = yield from recursive_tile(
              arg.rechunk({1: arg.shape[1]})
          )
  
      out_chunks = []
      for chunk in arg.chunks:
          chunk_op = op.copy().reset_key()
          if isinstance(chunk, (TENSOR_CHUNK_TYPE, INDEX_CHUNK_TYPE)):
              chunk_index_value = parse_index(
                  pd.Index([], dtype=out.dtype), op._params, chunk
              )
          else:
              chunk_index_value = chunk.index_value
  
          out_chunk = chunk_op.new_chunk(
              [chunk],
              shape=(chunk.shape[0],),
              dtype=out.dtype,
              index_value=chunk_index_value,
              name=out.name,
              index=(chunk.index[0],),
          )
          out_chunks.append(out_chunk)
  
      params = out.params
      params["nsplits"] = (arg.nsplits[0],)
      params["chunks"] = out_chunks
      new_op = op.copy()
      return new_op.new_tileables(op.inputs, kws=[params])
  
imports: from functools import partial
  from typing import Any
  import numpy
  import pandas
  from pandas.api.types import is_scalar, is_dict_like
  from ...None import opcodes
  from ...core import recursive_tile
  from ...serialization.serializables import KeyField, StringField, BoolField, AnyField
  from ...tensor import tensor
  from ...tensor.core import TENSOR_CHUNK_TYPE
  from ..core import DATAFRAME_TYPE, SERIES_TYPE, INDEX_TYPE, INDEX_CHUNK_TYPE
  from ..initializer import DataFrame, Series, Index
  from ..operands import DataFrameOperand, DataFrameOperandMixin
  from ..utils import parse_index, lazy_import
label_desc: Use image node_id 4 for calling the DataFrameToDatetime obj's underlying member method code with example usage: obj.tile(cls, op) and returns: new_op