code: def load_timeseries_data():
      zipfile = ZipFile(DATASET_ZIP_OCCUPANCY)
      train = pd.read_csv(zipfile.open("datatraining.txt"), sep=",")
      val = pd.read_csv(zipfile.open("datatest.txt"), sep=",")
      test = pd.read_csv(zipfile.open("datatest2.txt"), sep=",")
      return (pd.concat([train, val], sort=False), test, ["Occupancy"])
  
file_path: pytorch_tabular/tests/conftest.py
imports: import os.path
  from zipfile import ZipFile
  import numpy
  import pandas
  import pytest
  from sklearn.datasets import fetch_california_housing, fetch_covtype
label_desc: Use image node_id 3 for calling a global function with example usage: load_timeseries_data() and returns: pd,  test,  list