code: def modify(df, cols):
      for col in cols:
          series = df[col].values
          df[col + "_magnify"], _ = magnify(series, series)
          df[col + "_affine"], _ = affine(series, series)
          df[col + "_crop"], _ = crop(series, series)
          df[col + "_cross_sum"], _ = cross_sum(series, series)
          df[col + "_resample"], _ = resample(series, series)
          df[col + "_trend"], _ = trend(series, series)
  
          df[col + "_random_affine"], _ = random_time_warp(
              series, series
          )
          df[col + "_random_crop"], _ = random_crop(series, series)
          df[col + "_random_cross_sum"], _ = random_cross_sum(
              series, series
          )
          df[col + "_random_sidetrack"], _ = random_sidetrack(
              series, series
          )
          df[col + "_random_time_warp"], _ = random_time_warp(
              series, series
          )
          df[col + "_random_magnify"], _ = random_magnify(
              series, series
          )
          df[col + "_random_jitter"], _ = random_jitter(series, series)
          df[col + "_random_trend"], _ = random_trend(series, series)
      return df
  
imports: import pandas
  import numpy
  import statsmodels.api
  from scipy import signal, integrate
  from pykalman import UnscentedKalmanFilter
  from tsaug import *
  from fbprophet import Prophet
  import pylab
  from seasonal.periodogram import periodogram
label_desc: Use image node_id 21 for calling a global function with example usage: modify(df, cols) and returns: df