code: def _get_error_scatter(
      trial_numbers: list[int],
      errors: list[float] | None,
  ) -> "go.Scatter":
      if errors is None:
          return go.Scatter()
  
      plotly_red = "rgb(239, 85, 59)"
      return go.Scatter(
          x=trial_numbers,
          y=errors,
          mode="markers+lines",
          name="Error",
          marker=dict(color=plotly_red),
          line=dict(color=plotly_red),
      )
  
imports: from __future__ import annotations
  from typing import NamedTuple
  import tqdm
  import optuna
  from optuna._experimental import experimental_func
  from optuna.logging import get_logger
  from optuna.study.study import Study
  from optuna.terminator import BaseErrorEvaluator
  from optuna.terminator import BaseImprovementEvaluator
  from optuna.terminator import CrossValidationErrorEvaluator
  from optuna.terminator import RegretBoundEvaluator
  from optuna.terminator.improvement.evaluator import DEFAULT_MIN_N_TRIALS
  from optuna.visualization._plotly_imports import _imports
label_desc: Use image node_id 4 for calling a global function with example usage: _get_error_scatter(trial_numbers, errors) and returns: go, go