code: def parse_dataframe(
      x: ArrayLike | None, name: str | list[str]
  ) -> (
      tuple[Index, Index]
      | tuple[list[Hashable | None], Index]
      | tuple[list[str], NDArray]
  ):
      if x is None:
          assert isinstance(name, str)
          return [name], np.empty(0)
      if isinstance(x, DataFrame):
          return x.columns, x.index
      elif isinstance(x, Series):
          return [x.name], x.index
      else:
          if not isinstance(name, list):
              name = [name]
          return name, np.arange(np.squeeze(x).shape[0])
  
imports: from __future__ import annotations
  from arch.compat.pandas import is_datetime64_any_dtype
  from abc import ABCMeta
  from collections.abc import Hashable, Sequence
  import datetime
  from functools import cached_property
  from typing import Any, Literal, overload
  import numpy
  from pandas import DataFrame, DatetimeIndex, Index, NaT, Series, Timestamp, to_datetime
  from arch.typing import AnyPandas, ArrayLike, DateLike, NDArray
label_desc: Use image node_id 5 for calling a global function with example usage: parse_dataframe(x, name) and returns: list,  np, x,  x, list,  x, name,  np