code: def execute(cls, ctx, op):
      axis = op.axis
      periods = op.periods
  
      obj = ctx[op.input.key]
      out = op.outputs[0]
  
      if (
          _need_consolidate
          and isinstance(obj, (pd.Series, pd.DataFrame))
          and len(obj._data.blocks) > 1
      ):
          # if #internal blocks > 1, shift will create wrong result in pandas 1.1.0
          # see https://github.com/pandas-dev/pandas/issues/35488
          # if shifting merged dataframe slices, shift will raise TypeError in pandas 1.3.0
          # see https://github.com/pandas-dev/pandas/issues/42401
          # thus we force to do consolidate
          obj._data._consolidate_inplace()
  
      result = obj.shift(
          periods=periods,
          freq=op.freq,
          axis=axis,
          fill_value=op.fill_value,
      )
      if result.shape != out.shape:
          slc = [slice(None)] * obj.ndim
          if periods > 0:
              slc[axis] = slice(-out.shape[axis], None)
          else:
              slc[axis] = slice(out.shape[axis])
  
          result = result.iloc[tuple(slc)]
          assert result.shape == out.shape, (result.shape, out.shape)
  
      ctx[out.key] = result
  
imports: import numpy
  import pandas
  from ...None import opcodes
  from ...core import OutputType
  from ...serialization.serializables import KeyField, AnyField, Int8Field, Int64Field
  from ...utils import has_unknown_shape, no_default, pd_release_version
  from ..operands import DataFrameOperand, DataFrameOperandMixin
  from ..utils import parse_index, build_df, build_series, validate_axis
label_desc: Use image node_id 15 for calling the DataFrameShift obj's underlying member method code with example usage: obj.execute(cls, ctx, op) without return types