code: def pandas_rolling_method(
      df,
      rolling_kwargs,
      name,
      *args,
      groupby_kwargs=None,
      groupby_slice=None,
      **kwargs,
  ):
      groupby = df.groupby(**groupby_kwargs)
      if groupby_slice:
          groupby = groupby[groupby_slice]
      rolling = groupby.rolling(**rolling_kwargs)
      return getattr(rolling, name)(*args, **kwargs).sort_index(
          level=-1
      )
  
imports: from __future__ import annotations
  import datetime
  import warnings
  from numbers import Integral
  import pandas
  from pandas.api.types import is_datetime64_any_dtype
  from pandas.core.window import Rolling
  from dask.array.core import normalize_arg
  from dask.base import tokenize
  from dask.blockwise import BlockwiseDepDict
  from dask.dataframe import methods
  from dask.dataframe._compat import check_axis_keyword_deprecation
  from dask.dataframe.core import Scalar, _Frame, _get_divisions_map_partitions, _get_meta_map_partitions, _maybe_from_pandas, apply_and_enforce, new_dd_object, partitionwise_graph
  from dask.dataframe.io import from_pandas
  from dask.dataframe.multi import _maybe_align_partitions
  from dask.dataframe.utils import insert_meta_param_description, is_dask_collection, is_dataframe_like, is_series_like
  from dask.delayed import unpack_collections
  from dask.highlevelgraph import HighLevelGraph
  from dask.typing import no_default
  from dask.utils import M, apply, derived_from, funcname, has_keyword
label_desc: Use image node_id 3 for calling the RollingGroupby obj's underlying member method code with example usage: obj.pandas_rolling_method(df, rolling_kwargs, name) and returns: getattr