Resample Daily Pandas Timeseries With Start At Time Other Than Midnight

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

Solution 1:

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

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

Eg:

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]: 
2011-12-3105:00:0029.52012-01-0105:00:00203.52012-01-0205:00:00491.52012-01-0305:00:00749.5
Freq: 24H, dtype: float64

Solution 2:

I've just spotted an answered question which didn't come up on Google or Stack Overflow previously:

Resample hourly TimeSeries with certain starting hour

This uses the base parameter, which looks like an addition subsequent to Wes McKinney's Python for Data Analysis. I've given the parameter a go and it seems to do the trick.