从午夜以外的其他时间重新采样每天的 pandas 时间序列 [英] Resample daily pandas timeseries with start at time other than midnight

问题描述

我有一个10分钟频率数据的熊猫时间序列，需要在每个24小时内找到最大值.但是，这24小时需要每天从凌晨5点开始-而不是熊猫假设的默认午夜.

I have a pandas timeseries of 10-min freqency data and need to find the maximum value in each 24-hour period. However, this 24-hour period needs to start each day at 5AM - not the default midnight which pandas assumes.

我一直在检查DateOffset，但是到目前为止我还是在画空白.我可能期望类似于pandas.tseries.offsets.Week(weekday=n)的东西，例如pandas.tseries.offsets.Week(hour=5)，但据我所知，这不受支持.

I've been checking out DateOffset but so far am drawing blanks. I might have expected something akin to pandas.tseries.offsets.Week(weekday=n), e.g. pandas.tseries.offsets.Week(hour=5), but this is not supported as far as I can tell.

我可以先通过shift进行数据处理，但是这很不直观，甚至在一周之后，我仍然无法将头转向移位方向！

I can do a nasty work around by shifting the data first, but it's unintuitive and even coming back to the same code after just a week I have problems wrapping my head around the shift direction!

任何更优雅的想法将不胜感激.

Any more elegant ideas would be much appreciated.

推荐答案

base关键字可以解决问题(请参见

The base keyword can do the trick (see docs):

s.resample('24h', base=5)

例如:

In [35]: idx = pd.date_range('2012-01-01 00:00:00', freq='5min', periods=24*12*3)

In [36]: s = pd.Series(np.arange(len(idx)), index=idx)

In [38]: s.resample('24h', base=5)
Out[38]: 
2011-12-31 05:00:00     29.5
2012-01-01 05:00:00    203.5
2012-01-02 05:00:00    491.5
2012-01-03 05:00:00    749.5
Freq: 24H, dtype: float64

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