I have a pandas datable as (showing only 2 lines as example, sorted by DATE_1 after some processing)
| DATE_1 | DATE _ 2 | DIFF | |
|---|---|---|---|
| 1175 | 2010-01-01 | 2010-11-16 | 320 |
| 1170 | 2010-05-19 | 2010-11-06 | 171 |
| .... | ... | ... | ... |
so the first date is 2010-01-01.
I want to resample on a 3 months period and sum the DIFF values. I do this by: df[['DIFF']].resample('3M').sum()
what I get is a sum, 3 months after 3 months, as expected. But the dates are not starting where I would expected/wanted them to.
| 2010-01-31 | 320 |
| 2010-04-30 | NaN |
| 2020-07-31 | 171 |
How can I make it so that the 3M matches JAN-MAR, APR-JUN, JUL-SEP, OCT-DIC?
| 2010-03-31 | 320 |
| 2010-06-30 | 171 |
| 2010-09-30 | value.. |
| 2010-12-31 | value ... |
| 2011-03-31 | value ... |
ps: can't get the last table to format correctly (it does on the preview...)
Closing the left interval on M frequencies has the effect of intervals "going up" from first date of series:
df['diff'].resample('3M', closed='left').sum()
date1
2010-03-31 320
2010-06-30 171