我有一个多天的日内日志返回系列,我想将其缩减为每日 ohlc.我可以做类似的事情
I have an intra day series of log returns over multiple days that I would like to downsample to daily ohlc. I can do something like
hi = series.resample('B', how=lambda x: np.max(np.cumsum()))
low = series.resample('B', how=lambda x: np.min(np.cumsum()))
但每次调用计算 cumsum 似乎效率低下.有没有办法先计算 cumsums 然后将 'ohcl' 应用于数据?
But it seems inefficient to compute cumsum on each call. Is there a way to first compute the cumsums and then apply 'ohcl' to the data?
1999-08-09 12:30:00-04:00 -0.000486
1999-08-09 12:31:00-04:00 -0.000606
1999-08-09 12:32:00-04:00 -0.000120
1999-08-09 12:33:00-04:00 -0.000037
1999-08-09 12:34:00-04:00 -0.000337
1999-08-09 12:35:00-04:00 0.000100
1999-08-09 12:36:00-04:00 0.000219
1999-08-09 12:37:00-04:00 0.000285
1999-08-09 12:38:00-04:00 -0.000981
1999-08-09 12:39:00-04:00 -0.000487
1999-08-09 12:40:00-04:00 0.000476
1999-08-09 12:41:00-04:00 0.000362
1999-08-09 12:42:00-04:00 -0.000038
1999-08-09 12:43:00-04:00 -0.000310
1999-08-09 12:44:00-04:00 -0.000337
...
1999-09-28 06:45:00-04:00 0.000000
1999-09-28 06:46:00-04:00 0.000000
1999-09-28 06:47:00-04:00 0.000000
1999-09-28 06:48:00-04:00 0.000102
1999-09-28 06:49:00-04:00 -0.000068
1999-09-28 06:50:00-04:00 0.000136
1999-09-28 06:51:00-04:00 0.000566
1999-09-28 06:52:00-04:00 0.000469
1999-09-28 06:53:00-04:00 0.000000
1999-09-28 06:54:00-04:00 0.000000
1999-09-28 06:55:00-04:00 0.000000
1999-09-28 06:56:00-04:00 0.000000
1999-09-28 06:57:00-04:00 0.000000
1999-09-28 06:58:00-04:00 0.000000
1999-09-28 06:59:00-04:00 0.000000
df.groupby([df.index.year, df.index.month, df.index.day]).transform(np.cumsum).resample('B', how='ohlc')
我认为这可能是我想要的,但我必须测试.
I think this might be what I want but I have to test.
zelazny7回复后:
After zelazny7's repsonse:
df.groupby(pd.TimeGrouper('D')).transform(np.cumsum).resample('D', how='ohlc')
有效,而且比我以前的解决方案更有效.
works and is also more efficient than my previous solution.
更新:
pd.TimeGrouper('D') 已被弃用,因为 pandas v0.21.0.
pd.TimeGrouper('D') is deprecated since pandas v0.21.0.
使用 pd.Grouper() 改为:
Use pd.Grouper() instead:
df.groupby(pd.Grouper(freq='D')).transform(np.cumsum).resample('D', how='ohlc')
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