code: def to_train_dataframe(
      self, df: pd.DataFrame, target: str
  ) -> pd.DataFrame:
      columns = list(df.columns.values)
      columns.remove(target)
      columns.insert(self.TARGET_SEQ_INDEX, target)
      return df[columns]
  
imports: from merlion.models.anomaly.forecast_based.prophet import ProphetDetectorConfig, ProphetDetector
  from merlion.models.anomaly.isolation_forest import IsolationForestConfig, IsolationForest
  from merlion.models.anomaly.windstats import WindStatsConfig, WindStats
  from merlion.models.automl.autoprophet import AutoProphetConfig, AutoProphet
  from merlion.models.automl.autosarima import AutoSarimaConfig, AutoSarima
  from merlion.models.forecast.smoother import MSESConfig, MSES
  from merlion.post_process.threshold import AggregateAlarms
  from merlion.transform.moving_average import DifferenceTransform
  from scipy.stats import norm
  from merlion.models.defaults import DefaultDetectorConfig, DefaultDetector, DefaultForecaster, DefaultForecasterConfig
  from merlion.utils import TimeSeries
  from enum import Enum
  import pandas
label_desc: Use image node_id 4 for calling the BaseMerlionForecastAdapter obj's underlying member method code with example usage: obj.to_train_dataframe(df, target) and returns: df