code: def _execute_series_map(cls, ctx, op):
      a, pivots = [ctx[c.key] for c in op.inputs]
      out = op.outputs[0]
  
      if len(a) == 0:
          # when the chunk is empty, no slices can be produced
          for i in range(op.n_partition):
              ctx[out.key, (i,)] = a
          return
  
      if isinstance(a, pd.Series):
          try:
              poses = cls._calc_series_poses(
                  a, pivots, ascending=op.ascending
              )
          except TypeError:
              filled_a = a.fillna(_largest)
              filled_pivots = pivots.fillna(_largest)
              poses = cls._calc_series_poses(
                  filled_a, filled_pivots, ascending=op.ascending
              )
          poses = (None,) + tuple(poses) + (None,)
          for i in range(op.n_partition):
              values = a.iloc[poses[i] : poses[i + 1]]
              ctx[out.key, (i,)] = values
  
imports: import os
  import numpy
  import pandas
  from ...None import opcodes
  from ...core.operand import OperandStage, MapReduceOperand
  from ...utils import lazy_import, calc_nsplits
  from ...serialization.serializables import AnyField, Int32Field, ListField, StringField, BoolField
  from ...tensor.base.psrs import PSRSOperandMixin
  from ..core import IndexValue, OutputType
  from ..utils import standardize_range_index, parse_index, is_cudf
  from ..operands import DataFrameOperandMixin, DataFrameOperand, DataFrameShuffleProxy
label_desc: Use image node_id 6 for calling the DataFramePSRSShuffle obj's underlying member method code with example usage: obj._execute_series_map(cls, ctx, op) without return types