code: def _execute_shuffle_map(cls, ctx, op):
      out = op.outputs[0]
      shuffle_size = op.shuffle_size
      subset = op.subset
  
      inp = ctx[op.input.key]
      dropped = cls._drop_duplicates(inp, op)
      if dropped.ndim == 1:
          dropped = dropped.to_frame()
          subset = dropped.columns.tolist()
      else:
          if subset is None:
              subset = dropped.columns.tolist()
      dropped["_chunk_index_"] = out.index[0]
      dropped["_i_"] = np.arange(dropped.shape[0])
      hashed = hash_dataframe_on(dropped, subset, shuffle_size)
      for i, data in enumerate(hashed):
          reducer_idx = (i,) + out.index[1:]
          ctx[out.key, reducer_idx] = dropped.iloc[data]
  
imports: import numpy
  import pandas
  from ...None import opcodes
  from ...core.operand import OperandStage
  from ...serialization.serializables import BoolField
  from ...utils import lazy_import, calc_nsplits
  from ..operands import OutputType
  from ..utils import parse_index, hash_dataframe_on, gen_unknown_index_value, standardize_range_index
  from ._duplicate import DuplicateOperand, validate_subset
label_desc: Use image node_id 11 for calling the DataFrameDropDuplicates obj's underlying member method code with example usage: obj._execute_shuffle_map(cls, ctx, op) without return types