input: Write a python function to load stock data from a CSV file and split it into training and testing sets.
  assert len(split_data('stock_price_data.csv')[0]) > 0
  assert len(split_data('stock_price_data.csv')[1]) > 0
output: import pandas as pd
  from sklearn.model_selection import train_test_split
  
  def split_data(file_path):
      # Load the CSV file
      data = pd.read_csv(file_path)
      
      # Split the data into training and testing sets
      train_set, test_set = train_test_split(data, test_size=0.2, random_state=42)
      
      return train_set, test_set