code: def tile(cls, op: "DataFrameSetAxis"):
      output = op.outputs[0]
      input_tileables = [op.input]
  
      value = op.value
      if isinstance(value, ENTITY_TYPE):
          input_tileables.append(value)
          if has_unknown_shape(value):
              yield
  
      if any(np.isnan(s) for s in op.input.nsplits[op.axis]):
          yield
  
      if op.input.shape[op.axis] != value.shape[0]:
          raise ValueError(
              f"Length mismatch: Expected axis has {value.shape[0]} elements, "
              f"new values have {op.input.shape[op.axis]} elements"
          )
  
      if isinstance(value, ENTITY_TYPE):
          value = yield from recursive_tile(
              value.rechunk({0: op.input.nsplits[op.axis]})
          )
          input_tileables[-1] = value
  
      slices = np.array((0,) + op.input.nsplits[op.axis]).cumsum()
      slice_left = slices[:-1]
      slice_right = slices[1:]
  
      chunks = []
      param_cache = [None] * len(op.input.nsplits[op.axis])
      for inp_chunk in op.input.chunks:
          input_chunks = [inp_chunk]
          value_index = inp_chunk.index[op.axis]
          params = inp_chunk.params
  
          if isinstance(value, ENTITY_TYPE):
              value_data = value.chunks[value_index]
              input_chunks.append(value_data)
          else:
              value_data = value[
                  slice_left[value_index] : slice_right[value_index]
              ]
  
          if param_cache[value_index] is None:
              cached_params = param_cache[value_index] = dict()
              if isinstance(value, ENTITY_TYPE):
                  if op.axis == 0:
                      cached_params[
                          "index_value"
                      ] = value_data.index_value
                  else:
                      cached_params[
                          "columns_value"
                      ] = value_data.index_value
                      cached_params["dtypes"] = output.dtypes.iloc[
                          slice_left[value_index] : slice_right[
                              value_index
                          ]
                      ]
              else:
                  if op.axis == 0:
                      cached_params["index_value"] = parse_index(
                          value_data
                      )
                  else:
                      cached_params["columns_value"] = parse_index(
                          value_data, store_data=True
                      )
                      cached_params["dtypes"] = params[
                          "dtypes"
                      ].set_axis(value_data)
  
          params.update(param_cache[value_index])
  
          new_op = op.copy().reset_key()
          new_op._value = value_data
          chunks.append(new_op.new_chunk(input_chunks, **params))
  
      params = op.outputs[0].params
      params["chunks"] = chunks
      params["nsplits"] = op.input.nsplits
      new_op = op.copy().reset_key()
      return new_op.new_tileables(input_tileables, **params)
  
imports: import numpy
  import pandas
  from ...None import opcodes
  from ...core import ENTITY_TYPE, get_output_types, recursive_tile
  from ...serialization.serializables import AnyField, Int8Field, KeyField
  from ...utils import has_unknown_shape
  from ..operands import DataFrameOperandMixin, DataFrameOperand
  from ..utils import parse_index, validate_axis
label_desc: Use image node_id 7 for calling the DataFrameSetAxis obj's underlying member method code with example usage: obj.tile(cls, op) and returns: new_op