code: def time_series_split(ts_df):
      """
      This utility splits any dataframe sent as a time series split using the sklearn function.
      """
      tscv = TimeSeriesSplit(n_splits=2)
      train_index, test_index = (
          list(tscv.split(ts_df))[1][0],
          list(tscv.split(ts_df))[1][1],
      )
      ts_train, ts_test = (
          ts_df[ts_df.index.isin(train_index)],
          ts_df[ts_df.index.isin(test_index)],
      )
      print(ts_train.shape, ts_test.shape)
      return ts_train, ts_test
  
imports: from typing import List
  import numpy
  import pandas
  import copy
  import pdb
  from sklearn.model_selection import TimeSeriesSplit
  import dask
  import dask.dataframe
  import datetime
  from datetime import datetime, date, time
label_desc: Use image node_id 6 for calling a global function with example usage: time_series_split(ts_df) and returns: ts_train,  ts_test