class_docstr: Represents a grouped dataset created by calling ``Dataset.groupby()``.
  
  The actual groupby is deferred until an aggregation is applied.
class_docstr_tok: ["Represents","a","grouped","dataset","created","by","calling","``","Dataset.groupby","(",")","``",".","The","actual","groupby","is","deferred","until","an","aggregation","is","applied","."]
code: def __repr__(self) -> str:
      return (
          f"{self.__class__.__name__}(dataset={self._dataset}, "
          f"key={self._key!r})"
      )
  
imports: from typing import Any, Dict, Iterable, List, Optional, Tuple, Union
  from ._internal.table_block import TableBlockAccessor
  from ray.data._internal import sort
  from ray.data._internal.compute import ComputeStrategy
  from ray.data._internal.delegating_block_builder import DelegatingBlockBuilder
  from ray.data._internal.execution.interfaces import TaskContext
  from ray.data._internal.logical.interfaces import LogicalPlan
  from ray.data._internal.logical.operators.all_to_all_operator import Aggregate
  from ray.data._internal.plan import AllToAllStage
  from ray.data._internal.push_based_shuffle import PushBasedShufflePlan
  from ray.data._internal.shuffle import ShuffleOp, SimpleShufflePlan
  from ray.data._internal.sort import SortKey
  from ray.data.aggregate import AggregateFn, Count, Max, Mean, Min, Std, Sum
  from ray.data.aggregate._aggregate import _AggregateOnKeyBase
  from ray.data.block import Block, BlockAccessor, BlockExecStats, BlockMetadata, KeyType, UserDefinedFunction
  from ray.data.context import DataContext
  from ray.data.dataset import DataBatch, Dataset
  from ray.util.annotations import PublicAPI
label_desc: Use image node_id 2 for calling the GroupedData obj's underlying member method code with example usage: obj.__repr__() and returns: self, str, self, str, self, str