Hi, I recently asked a question about SAS sum of next N rows for every row here .
This is exactly the answer to the question and works well (by one column).
data want(drop = i n);
set have curobs = c nobs = nobs;
Sum_Next_6Numbers = 0;
do p = c + 1 to 6 + c;
if p > nobs then do;
Sum_Next_6Numbers = .; leave;
end;
set have(keep = Number ID rename = (Number = n id = i)) point = p;
if id ne i then do;
Sum_Next_6Numbers = .; leave;
end;
Sum_Next_6Numbers + n;
end;
run;
So basically, I want to sum up next 6 row's values(number column) by 2 columns(id and id2). If there is no 6 months left then this values should be Nan.
I have a dataset like this for each ID and ID2;
data have;
input Months ID ID2 Number;
2018-07-01 1 1 0
2018-08-01 1 1 0
2018-09-01 1 1 0
2018-10-01 1 1 1
2018-11-01 1 1 0
2018-12-01 1 1 1
2019-01-01 1 1 0
2019-02-01 1 1 0
2019-03-01 1 1 0
2019-04-01 1 1 0
2019-05-01 1 1 0
2019-06-01 1 1 0
2019-07-01 1 1 0
2019-08-01 1 1 0
2019-09-01 1 1 0
2019-10-01 1 1 0
2019-11-01 1 1 0
2019-12-01 1 1 0
2020-01-01 1 1 0
2020-02-01 1 1 0
2020-03-01 1 1 0
2020-04-01 1 1 0
2020-05-01 1 1 0
2020-06-01 1 1 0
2020-07-01 1 1 0
2020-08-01 1 1 0
2020-09-01 1 1 0
2020-10-01 1 1 0
2020-11-01 1 1 1
2020-12-01 1 1 0
2021-01-01 1 1 0
2021-02-01 1 1 0
2021-03-01 1 1 0
2021-04-01 1 1 0
2018-07-01 1 2 0
2018-08-01 1 2 0
2018-09-01 1 2 0
2018-10-01 1 2 0
2018-11-01 1 2 0
2018-12-01 1 2 0
2019-01-01 1 2 0
2019-02-01 1 2 0
2019-03-01 1 2 0
2019-04-01 1 2 0
2019-05-01 1 2 0
2019-06-01 1 2 0
2019-07-01 1 2 0
2019-08-01 1 2 0
2019-09-01 1 2 0
2019-10-01 1 2 0
2019-11-01 1 2 0
2019-12-01 1 2 0
2020-01-01 1 2 0
2020-02-01 1 2 0
2020-03-01 1 2 0
2020-04-01 1 2 0
2020-05-01 1 2 0
2020-06-01 1 2 0
2020-07-01 1 2 0
2020-08-01 1 2 0
2020-09-01 1 2 0
2020-10-01 1 2 0
2020-11-01 1 2 0
2020-12-01 1 2 0
2021-01-01 1 2 0
2021-02-01 1 2 0
2021-03-01 1 2 0
2021-04-01 1 2 0
2018-07-01 2 1 0
2018-08-01 2 1 0
2018-09-01 2 1 0
2018-10-01 2 1 0
2018-11-01 2 1 0
2018-12-01 2 1 0
2019-01-01 2 1 0
2019-02-01 2 1 0
2019-03-01 2 1 0
2019-04-01 2 1 0
2019-05-01 2 1 0
2019-06-01 2 1 0
2019-07-01 2 1 0
2019-08-01 2 1 0
2019-09-01 2 1 0
2019-10-01 2 1 0
2019-11-01 2 1 0
2019-12-01 2 1 0
2020-01-01 2 1 0
2020-02-01 2 1 0
2020-03-01 2 1 0
2020-04-01 2 1 0
2020-05-01 2 1 0
2020-06-01 2 1 0
2020-07-01 2 1 0
2020-08-01 2 1 1
2020-09-01 2 1 0
2020-10-01 2 1 0
2020-11-01 2 1 0
2020-12-01 2 1 0
2021-01-01 2 1 0
2021-02-01 2 1 0
2021-03-01 2 1 0
2021-04-01 2 1 0
....... ....... .......
I want a dataset like this;
data want;
input Months ID ID2 Number Sum_Next_6Numbers;
2018-07-01 1 1 0 2
2018-08-01 1 1 0 2
2018-09-01 1 1 0 2
2018-10-01 1 1 1 1
2018-11-01 1 1 0 1
2018-12-01 1 1 1 0
2019-01-01 1 1 0 0
2019-02-01 1 1 0 0
2019-03-01 1 1 0 0
2019-04-01 1 1 0 0
2019-05-01 1 1 0 0
2019-06-01 1 1 0 0
2019-07-01 1 1 0 0
2019-08-01 1 1 0 0
2019-09-01 1 1 0 0
2019-10-01 1 1 0 0
2019-11-01 1 1 0 0
2019-12-01 1 1 0 0
2020-01-01 1 1 0 0
2020-02-01 1 1 0 0
2020-03-01 1 1 0 0
2020-04-01 1 1 0 0
2020-05-01 1 1 0 1
2020-06-01 1 1 0 1
2020-07-01 1 1 0 1
2020-08-01 1 1 0 1
2020-09-01 1 1 0 1
2020-10-01 1 1 0 1
2020-11-01 1 1 1 NaN
2020-12-01 1 1 0 NaN
2021-01-01 1 1 0 NaN
2021-02-01 1 1 0 NaN
2021-03-01 1 1 0 NaN
2021-04-01 1 1 0 NaN
2018-07-01 1 2 0 0
2018-08-01 1 2 0 0
2018-09-01 1 2 0 0
2018-10-01 1 2 0 0
2018-11-01 1 2 0 0
2018-12-01 1 2 0 0
2019-01-01 1 2 0 0
2019-02-01 1 2 0 0
2019-03-01 1 2 0 0
2019-04-01 1 2 0 0
2019-05-01 1 2 0 0
2019-06-01 1 2 0 0
2019-07-01 1 2 0 0
2019-08-01 1 2 0 0
2019-09-01 1 2 0 0
2019-10-01 1 2 0 0
2019-11-01 1 2 0 0
2019-12-01 1 2 0 0
2020-01-01 1 2 0 0
2020-02-01 1 2 0 0
2020-03-01 1 2 0 0
2020-04-01 1 2 0 0
2020-05-01 1 2 0 0
2020-06-01 1 2 0 0
2020-07-01 1 2 0 0
2020-08-01 1 2 0 0
2020-09-01 1 2 0 0
2020-10-01 1 2 0 0
2020-11-01 1 2 0 NaN
2020-12-01 1 2 0 NaN
2021-01-01 1 2 0 NaN
2021-02-01 1 2 0 NaN
2021-03-01 1 2 0 NaN
2021-04-01 1 2 0 NaN
2018-07-01 2 1 0 0
2018-08-01 2 1 0 0
2018-09-01 2 1 0 0
2018-10-01 2 1 0 0
2018-11-01 2 1 0 0
2018-12-01 2 1 0 0
2019-01-01 2 1 0 0
2019-02-01 2 1 0 0
2019-03-01 2 1 0 0
2019-04-01 2 1 0 0
2019-05-01 2 1 0 0
2019-06-01 2 1 0 0
2019-07-01 2 1 0 0
2019-08-01 2 1 0 0
2019-09-01 2 1 0 0
2019-10-01 2 1 0 0
2019-11-01 2 1 0 0
2019-12-01 2 1 0 0
2020-01-01 2 1 0 0
2020-02-01 2 1 0 1
2020-03-01 2 1 0 1
2020-04-01 2 1 0 1
2020-05-01 2 1 0 1
2020-06-01 2 1 0 1
2020-07-01 2 1 0 1
2020-08-01 2 1 1 0
2020-09-01 2 1 0 0
2020-10-01 2 1 0 0
2020-11-01 2 1 0 NaN
2020-12-01 2 1 0 NaN
2021-01-01 2 1 0 NaN
2021-02-01 2 1 0 NaN
2021-03-01 2 1 0 NaN
2021-04-01 2 1 0 NaN
....... ....... .......I did it with a nested for loop in python. I'm new to sas and I'm confused. Is there a way to do this in SAS? Thanks in advance.
Do you have SAS/ETS? This is incredibly trivial with PROC EXPAND - sort of like using the right package in Python.
title;
data test;
input year qtr x;
date = yyq( year, qtr );
format date yyqc.;
datalines;
1989 3 5238
1989 4 5289
1990 1 5375
1990 2 5443
1990 3 5514
1990 4 5527
1991 1 5557
1991 2 5615
;
proc expand data=test out=out method=none;
id date;
convert x = x_lag2 / transformout=(lag 2);
convert x = x_lag1 / transformout=(lag 1);
convert x;
convert x = x_lead1 / transformout=(lead 1);
convert x = x_lead2 / transformout=(lead 2);
convert x = x_movave / transformout=(movave 3);
run;
title "Transformed Series";
proc print data=out;
run;
April 27 – 30 | Gaylord Texan | Grapevine, Texas
Walk in ready to learn. Walk out ready to deliver. This is the data and AI conference you can't afford to miss.
Register now and lock in 2025 pricing—just $495!
Still thinking about your presentation idea? The submission deadline has been extended to Friday, Nov. 14, at 11:59 p.m. ET.
Learn how use the CAT functions in SAS to join values from multiple variables into a single value.
Find more tutorials on the SAS Users YouTube channel.
Ready to level-up your skills? Choose your own adventure.