code: def transformDataset(self, df):
      if self.mBestCycleLength is not None:
          lValueCol = df[self.mTimeInfo.mRowNumberColumn].apply(
              lambda x: x % self.mBestCycleLength
          )
          df["cycle_internal"] = lValueCol
          # print("BEST_CYCLE" , self.mBestCycleLength)
          # print(self.mBestCycleValueDict);
          lDict = self.mBestCycleValueDict[self.mBestCycleLength]
          df[self.getCycleName()] = lValueCol.apply(
              lambda x: lDict.get(x, self.mDefaultValue)
          )
      else:
          df[self.getCycleName()] = np.zeros_like(
              df[self.mTimeInfo.mRowNumberColumn]
          )
  
      target = df[self.mTrend_residue_name]
      df[self.getCycleResidueName()] = (
          target - df[self.getCycleName()].values
      )
      if self.mOptions.mDebug:
          self.check_not_nan(
              self.mCycleFrame[self.getCycleName()].values,
              self.getCycleName(),
          )
  
      return df
  
imports: import pandas
  import numpy
  from .None import Time
  from .None import Perf
  from .None import Plots
  from .None import Utils
  import time
label_desc: Use image node_id 7 for calling the cBestCycleForTrend obj's underlying member method code with example usage: obj.transformDataset(df) and returns: df