In [6]:
%%time

filtered_trade = trade[trade['Symbol'] == 'AAPL']
filtered_trade.groupby(by = [filtered_trade.Symbol,vaex.BinnerTime(filtered_trade.Time,'m',every=10)],
                       agg = {'vol': vaex.agg.sum('Trade_Volume')}) \
    .to_pandas_df() \
    .plot('Time','vol',kind='area')
CPU times: user 833 ms, sys: 129 ms, total: 962 ms
Wall time: 509 ms
Out[6]:
<AxesSubplot:xlabel='Time'>