Looping through dates in python

Question

I have previously only worked in Stata but am now trying to switch to python. I want to conduct an event study. More specifically, I have 4 fixed dates a year. Every first day of every quarter, e.g. 1st January, 1st April...., and an event window +- 10 days around the event date. In order to partition my sample to the desired window I am using the following command:

smpl = merged.ix[datetime.date(year=2013,month=12,day=21):datetime.date(year=2014,month=1,day=10)]

I want to write a loop that automatically shifts the choosen sample period 90 days forward in every run of the loop so that I can subsequently run the required analysis in that step. I know how to run the analysis, but I do not know how to shift the sample 90 days forward for every step in the loop. For example, the next sample in the loop should be:

smpl = merged.ix[datetime.date(year=2014,month=3,day=21):datetime.date(year=2014,month=4,day=10)]

Its probably pretty simple, something like month=I and then shift by +3 every month. I am just to much of a noob in python to get the syntax done. Any help is greatly appreciated.

MaxU - stand with Ukraine · Accepted Answer · 2017-05-17 15:07:11Z

1

I'd use this:

for beg in pd.date_range('2013-12-21', '2017-05-17', freq='90D'):
    smpl = merged.loc[beg:beg + pd.Timedelta('20D')]
    ...

Demo:

    In [158]: for beg in pd.date_range('2013-12-21', '2017-05-17', freq='90D'):
     ...:     print(beg, beg + pd.Timedelta('20D'))
     ...:
2013-12-21 00:00:00 2014-01-10 00:00:00
2014-03-21 00:00:00 2014-04-10 00:00:00
2014-06-19 00:00:00 2014-07-09 00:00:00
2014-09-17 00:00:00 2014-10-07 00:00:00
2014-12-16 00:00:00 2015-01-05 00:00:00
2015-03-16 00:00:00 2015-04-05 00:00:00
2015-06-14 00:00:00 2015-07-04 00:00:00
2015-09-12 00:00:00 2015-10-02 00:00:00
2015-12-11 00:00:00 2015-12-31 00:00:00
2016-03-10 00:00:00 2016-03-30 00:00:00
2016-06-08 00:00:00 2016-06-28 00:00:00
2016-09-06 00:00:00 2016-09-26 00:00:00
2016-12-05 00:00:00 2016-12-25 00:00:00
2017-03-05 00:00:00 2017-03-25 00:00:00

answered May 17, 2017 at 15:07

MaxU - stand with Ukraine

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