code: def execute(cls, ctx, op):
      inputs = [ctx[c.key] for c in op.inputs if len(ctx[c.key]) > 0]
      if len(inputs) == 0:
          # corner case: nothing sampled, we need to do nothing
          ctx[op.outputs[-1].key] = ctx[op.inputs[0].key]
          return
  
      xdf = (
          pd
          if isinstance(inputs[0], (pd.DataFrame, pd.Series))
          else cudf
      )
  
      a = xdf.concat(inputs, axis=op.axis)
      p = len(inputs)
      assert a.shape[op.axis] == p * len(op.inputs)
  
      slc = np.linspace(
          p - 1,
          a.shape[op.axis] - 1,
          num=len(op.inputs) - 1,
          endpoint=False,
      ).astype(int)
      if op.axis == 1:
          slc = (slice(None), slc)
      if op.sort_type == "sort_values":
          a = execute_sort_values(a, op, inplace=False)
          ctx[op.outputs[-1].key] = a.iloc[slc]
      else:
          a = execute_sort_index(a, op, inplace=False)
          ctx[op.outputs[-1].key] = a.index[slc]
  
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 2 for calling the DataFramePSRSConcatPivot obj's underlying member method code with example usage: obj.execute(cls, ctx, op) without return types