code: def symbols_bollinger(symbols='sp5002012',
      start=datetime.datetime(2008, 1, 1), end=datetime.datetime(2009, 12, 31), price_type='adjusted_close', cleaner=clean_dataframe,
      window=20, sigma=1.):
      
      symbols = normalize_symbols(symbols)
      prices = price_dataframe(symbols, start=start, end=end, price_type=price_type, cleaner=cleaner)
      return frame_bollinger(prices, window=window, sigma=sigma, plot=False)
docs: Calculate the Bolinger for a list or set of symbols
  
      Example:
      >>> symbols_bollinger(["AAPL", "GOOG", "IBM", "MSFT"], '10-12-01', '10-12-30')[-5:]  # doctest: +NORMALIZE_WHITESPACE
                               GOOG      AAPL       IBM      MSFT
      2010-12-23 16:00:00  1.298178  1.185009  1.177220  1.237684
      2010-12-27 16:00:00  1.073603  1.371298  0.590403  0.932911
      2010-12-28 16:00:00  0.745548  1.436278  0.863406  0.812844
      2010-12-29 16:00:00  0.874885  1.464894  2.096242  0.752602
      2010-12-30 16:00:00  0.634661  0.793493  1.959324  0.498395