calculate vwap of entire time series
    (input can be pandas series or numpy array)
    bars are usually mid [ (h+l)/2 ] or typical [ (h+l+c)/3 ]

def vwap(bars):
    """
    calculate vwap of entire time series
    (input can be pandas series or numpy array)
    bars are usually mid [ (h+l)/2 ] or typical [ (h+l+c)/3 ]
    """
    typical = ((bars['high'] + bars['low'] + bars['close']) / 3).values
    volume = bars['volume'].values

    return pd.Series(index=bars.index,
                     data=np.cumsum(volume * typical) / np.cumsum(volume))