code: def test_split_1(self):
      labeled_path = os.path.join(
          test_dir_path, "test_datasets", "sample_table_large.csv"
      )
      labeled_table = pd.read_csv(labeled_path)
      ori_cols = list(labeled_table.columns)
      out_path = os.path.join(test_dir_path, "test_datasets")
      train_prefix = "train.csv"
      valid_prefix = "valid.csv"
      test_prefix = "test.csv"
      split(
          labeled_table,
          out_path,
          train_prefix,
          valid_prefix,
          test_prefix,
      )
  
      train_path = os.path.join(out_path, train_prefix)
      valid_path = os.path.join(out_path, valid_prefix)
      test_path = os.path.join(out_path, test_prefix)
  
      train = pd.read_csv(train_path)
      valid = pd.read_csv(valid_path)
      test = pd.read_csv(test_path)
  
      self.assertEqual(list(train.columns), ori_cols)
      self.assertEqual(list(valid.columns), ori_cols)
      self.assertEqual(list(test.columns), ori_cols)
  
      if os.path.exists(train_path):
          os.remove(train_path)
      if os.path.exists(valid_path):
          os.remove(valid_path)
      if os.path.exists(test_path):
          os.remove(test_path)
  
imports: import io
  import os
  import shutil
  import unittest
  from test import test_dir_path
  import pandas
  from nose.tools import *
  import torch
  from deepmatcher.data.dataset import *
  from deepmatcher.data.field import FastText, MatchingField
  from deepmatcher.data.process import _make_fields, process
  from torchtext.utils import unicode_csv_reader
  from urllib.parse import urljoin
  from urllib.request import pathname2url
label_desc: Use image node_id 1 for calling the DataframeSplitTestCases obj's underlying member method code with example usage: obj.test_split_1() without return types