input: Write a python function to load data from a CSV file and split it into train and test sets using sklearn's train_test_split.
  assert len(train_test_split_data('data.csv')) == 4
  assert train_test_split_data('data.csv')[0].shape[0] > 0
  assert train_test_split_data('data.csv')[2].shape[0] > 0
output: import pandas as pd
  from sklearn.model_selection import train_test_split
  
  def train_test_split_data(file_path):
      data = pd.read_csv(file_path)
      X = data.iloc[:, :-1]
      y = data.iloc[:, -1]
      X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)
      return X_train, X_test, y_train, y_test