code: def execute(cls, ctx, op):
      out = op.outputs[0]
      if op.stage is None:  # 1 chunk
          df_or_series = ctx[op.input.key]
  
          ctx[out.key] = df_or_series.describe(
              percentiles=op.percentiles,
              include=op.include,
              exclude=op.exclude,
          )
      else:
          assert op.stage == OperandStage.agg
  
          inputs = [ctx[inp.key] for inp in op.inputs]
          xdf = (
              pd
              if isinstance(
                  inputs[0], (pd.DataFrame, pd.Series, pd.Index)
              )
              or cudf is None
              else cudf
          )
  
          if len(inputs) == 1:
              df = inputs[0]
          else:
              assert len(inputs) > 1
              aggregations = inputs[0]
              percentiles = xdf.concat(inputs[1:], axis=0)
              df = xdf.concat(
                  [
                      aggregations.iloc[:-1],
                      percentiles,
                      aggregations.iloc[-1:],
                  ],
                  axis=0,
              )
          # ['count', 'mean', 'std', 'min', {percentiles}, 'max']
          df.index = out.index_value.to_pandas()
          ctx[out.key] = df
  
imports: import numpy
  import pandas
  from ...None import opcodes
  from ...None import tensor
  from ...core import recursive_tile
  from ...core.operand import OperandStage
  from ...serialization.serializables import FieldTypes, KeyField, ListField, AnyField
  from ...utils import lazy_import, has_unknown_shape
  from ..core import SERIES_TYPE
  from ..initializer import DataFrame, Series
  from ..operands import DataFrameOperand, DataFrameOperandMixin
  from ..utils import parse_index, build_empty_df
label_desc: Use image node_id 12 for calling the DataFrameDescribe obj's underlying member method code with example usage: obj.execute(cls, ctx, op) without return types