基于CustomBusinessHour start创建pandas多索引

Question

我有一个数据帧，看起来像这样：

             datetime    price  tickvol      bid      ask
0 2016-10-11 12:24:03  2130.25        1  2130.00  2130.25
1 2016-10-11 13:31:03  2130.25        1  2130.00  2130.25
...

我有一个看起来像这样的CustomBusinessHour：

cbh = CustomBusinessHour(start='13:30', end='13:15', weekmask='Sun Mon Tue Wed Thu')

我希望我可以使用自定义营业时间的开始时间戳创建一个新的索引级别，但我在运行时遇到了问题。

我希望得到的结果是：

                cbh            datetime    price  tickvol      bid      ask
2016-10-10 13:30:00 2016-10-11 12:24:03  2130.25        1  2130.00  2130.25
2016-10-11 13:30:00 2016-10-11 13:31:03  2130.25        1  2130.00  2130.25

Answer 1

这就是我最终要做的。它是有效的，但可能还可以改进。看起来CustomBusinessHour并没有直接公开任何方法来确定时间是到了还是到了。

def session_start(ts, cbh):
    """Given a timestamp and a CustomBusinessHour, return the session start
    timestamp"""
    assert type(ts) == pd.Timestamp
    spans = spans_midnight(cbh)
    t = ts.time()
    if spans:
        if cbh.end <= t < cbh.start:
            return pd.NaT
        elif t < cbh.start:
            # this timestamp is part of the previous calendar day session
            ts = ts.replace(day=ts.day - 1)
    else:
        if cbh.end <= t or t < cbh.start:
            return pd.NaT

    return ts.replace(hour=cbh.start.hour, minute=cbh.start.minute,
                      second=cbh.start.second,
                      microsecond=cbh.start.microsecond)


# assuming df looks similar to the one in the problem statement...
cbh = CustomBusinessHour(start='06:30', end='13:15',
                         weekmask='Mon Tue Wed Thu Fri')
df['session_start'] = df.index.map(lambda x: session_start(x, cbh))
df.dropna(how='all', subset=['session_start'], inplace=True)
df.set_index(['session_start', df.index], drop=True, inplace=True)