Pandas resampling data with bigger interval than a whole index range

Question

Situation

I have the folowwing pandas timeseries data:

I need to take into account a case of resampling into bigger interval than a 5 years, for e.g. 10 years:

sample = data.set_index(pd.DatetimeIndex(data['date'])).drop('date', axis=1)['predicted1']
sample.resample('10Y').sum()

I get the following:

date
2000-12-31	0.001396
2010-12-31	1.546418

So resampling function groups data for the first year and separetely for other years.

How to group all data to the 10 year interval? I want to get smth like this:

date
2000-12-31	1.5478132011506138

score 0 · Accepted Answer · answered Oct 05 '22 at 07:43

0

You can change the reference, closing and label in resample:

sample.resample('10Y', origin=sample.index.min(), closed='left', label='left').sum()

Output:

date
1999-12-31    1.547813
Freq: 10A-DEC, Name: predicted1, dtype: float64

answered Oct 05 '22 at 07:43

mozway

And how to make the beginning of the interval 2000-01-01? Maybe there is a way to add some one-day offset – Владислав Черкасов Oct 05 '22 at 07:58
The easiest is probably to post process the index – mozway Oct 05 '22 at 08:00
As I understood, it is possible by adding `loffset='d'` to the params of resample function. @mozway thank you! – Владислав Черкасов Oct 05 '22 at 08:04