code: def set_single_trial(data: Data) -> Data:
      """Returns a new Data object where we set all rows to have the same
      trial index (i.e. 0). This is meant to be used with our IVW transform,
      which will combine multiple observations of the same outcome.
      """
      df = data._df.copy()
      if "trial_index" in df:
          df["trial_index"] = 0
      return Data(df=df)
  
imports: from __future__ import annotations
  import json
  from abc import abstractmethod
  from functools import reduce
  from hashlib import md5
  from typing import Any, Dict, Iterable, List, Optional, Set, Type, TypeVar, Union
  import numpy
  import pandas
  from ax.core.types import TFidelityTrialEvaluation, TTrialEvaluation
  from ax.utils.common.base import Base
  from ax.utils.common.serialization import extract_init_args, SerializationMixin, serialize_init_args, TClassDecoderRegistry, TDecoderRegistry
  from ax.utils.common.typeutils import checked_cast, not_none
label_desc: Use image node_id 1 for calling a global function with example usage: set_single_trial(data) and returns: Data