code: def from_pandas(  # type: ignore
      data: pd.Series,
      npartitions: int | None = None,
      chunksize: int | None = None,
      sort: bool = True,
      name: str | None = None,
  ) -> Series:
      ...
  
imports: from __future__ import annotations
  from collections.abc import Iterable
  from functools import partial
  from math import ceil
  from operator import getitem
  from threading import Lock
  from typing import TYPE_CHECKING, Literal, overload
  import numpy
  import pandas
  import dask.array
  from dask.base import is_dask_collection, tokenize
  from dask.blockwise import BlockwiseDepDict, blockwise
  from dask.dataframe._compat import is_any_real_numeric_dtype
  from dask.dataframe.backends import dataframe_creation_dispatch
  from dask.dataframe.core import DataFrame, Index, Series, _concat, _emulate, _Frame, apply_and_enforce, has_parallel_type, new_dd_object
  from dask.dataframe.dispatch import meta_lib_from_array
  from dask.dataframe.io.utils import DataFrameIOFunction
  from dask.dataframe.utils import check_meta, insert_meta_param_description, is_series_like, make_meta
  from dask.delayed import Delayed, delayed
  from dask.highlevelgraph import HighLevelGraph
  from dask.layers import DataFrameIOLayer
  from dask.utils import M, funcname, is_arraylike
label_desc: Use image node_id 4 for calling a global function with example usage: from_pandas(data, npartitions, chunksize, sort, name) without return types