code: def chart(
      symbols=("AAPL", "GLD", "GOOG", "$SPX", "XOM", "msft"),
      start=datetime.datetime(2008, 1, 1),
      end=datetime.datetime(2009, 12, 31),  # data stops at 2013/1/1
      normalize=True,
      ):
      
  
      start = util.normalize_date(start or datetime.date(2008, 1, 1))
      end = util.normalize_date(end or datetime.date(2009, 12, 31))
      symbols = [s.upper() for s in symbols]
      timeofday = datetime.timedelta(hours=16)
      timestamps = du.getNYSEdays(start, end, timeofday)
  
      ls_keys = ['open', 'high', 'low', 'close', 'volume', 'actual_close']
      ldf_data = da.get_data(timestamps, symbols, ls_keys)
      d_data = dict(zip(ls_keys, ldf_data))
  
      na_price = d_data['close'].values
      if normalize:
          na_price /= na_price[0, :]
      plt.clf()
      plt.plot(timestamps, na_price)
      plt.legend(symbols)
      plt.ylabel('Adjusted Close')
      plt.xlabel('Date')
      plt.savefig('chart.pdf', format='pdf')
      plt.grid(True)
      plt.show()
      return na_price
docs: Display a graph of the price history for the list of ticker symbols provided
  
  
      Arguments:
        symbols (list of str): Ticker symbols like "GOOG", "AAPL", etc
        start (datetime): The date at the start of the period being analyzed.
        end (datetime): The date at the end of the period being analyzed.
        normalize (bool): Whether to normalize prices to 1 at the start of the time series.