code: def __init__(
      self,
      groupby,
      window=None,
      min_periods=None,
      center=False,
      win_type=None,
      axis=0,
  ):
      self._groupby_kwargs = groupby._groupby_kwargs
      self._groupby_slice = groupby._slice
  
      obj = groupby.obj
      if self._groupby_slice is not None:
          if isinstance(self._groupby_slice, str):
              sliced_plus = [self._groupby_slice]
          else:
              sliced_plus = list(self._groupby_slice)
          if isinstance(groupby.by, str):
              sliced_plus.append(groupby.by)
          else:
              sliced_plus.extend(groupby.by)
          obj = obj[sliced_plus]
  
      super().__init__(
          obj,
          window=window,
          min_periods=min_periods,
          center=center,
          win_type=win_type,
          axis=axis,
      )
  
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 1 to create a new RollingGroupby object from inherited base classes: Rolling with example: obj = RollingGroupby(groupby, window, min_periods, center, win_type, axis)