Here is one way: data want (drop=last_sum have last_not_missing_sum); set table1; retain have last_not_missing_sum; by name; last_sum=lag(sum); if first.name then do; have=0; call missing(last_sum); call missing(last_not_missing_sum); end; if not missing(last_sum) then do; have=1; last_not_missing_sum=last_sum; end; if have then adjusted=Intraday/last_not_missing_sum; run; Art, CEO, AnalystFinder.com   ... View more

That is not called four days before,should call fout non-missing value before.   data have; infile cards expandtabs truncover; input name $ date $ time $ Intraday daily; cards; A 12/1/2013 9:30:00 1 A 12/1/2013 10:00:00 2 3 A 12/1/2013 10:30:00 3 A 12/2/2013 11:00:00 2 5 A 12/3/2013 10:00:00 2 A 12/3/2013 10:30:00 1 A 12/3/2013 11:00:00 1 4 A 12/4/2013 11:30:00 1 A 12/4/2013 12:00:00 3 A 12/4/2013 12:30:00 3 7 A 12/7/2013 9:30:00 1 A 12/7/2013 10:00:00 1 2 A 12/8/2013 10:30:00 2 A 12/8/2013 11:00:00 3 5 A 12/17/2013 11:30:00 1 A 12/17/2013 12:00:00 1 2 A 12/18/2013 12:30:00 2 2 A 12/28/2013 9:30:00 1 A 12/28/2013 10:00:00 1 2 B 12/8/2013 10:30:00 2 B 12/8/2013 11:30:00 2 B 12/8/2013 12:30:00 1 5 B 12/14/2013 9:30:00 1 B 12/14/2013 10:30:00 1 2 B 12/15/2013 12:00:00 2 B 12/15/2013 12:30:00 1 3 B 12/24/2013 9:30:00 1 1 B 12/25/2013 10:00:00 2 B 12/25/2013 10:30:00 2 4 B 12/26/2013 12:00:00 2 2 B 12/30/2013 9:30:00 3 B 12/30/2013 10:00:00 2 B 12/30/2013 10:30:00 1 6 B 1/3/2014 11:00:00 1 B 1/3/2014 11:30:00 1 B 1/13/2014 12:00:00 1 3 ; run; data want; set have; by name; array x{0:4} _temporary_; if first.name then do;i=0; call missing(of x{*});end; if not missing(daily) then do; i+1; x{mod(i,5)}= daily; end; if i ge 5 and not missing(daily) then sum=sum(of x{*}); drop i; run; ... View more

Based on Petr's code, I think the better solution is:   proc sql; create table want as select * from have group by name, date having min(time) not between '09:00:01't and '09:05:59't or time ne min(time) ;quit; ... View more

IIRC it's usually a txt file that has the code to create the data set.  Open it as a text file using your favorite text editor (NotePad++  etc).    The code usually doesn't won't translate directly into SAS but the conversion to SAS SQL should be relatively straightforward.    Python can read it directly without converting. You can use Python within SAS Viya so that's another option.     ... View more

That is to say you don't like to use PROC SORT ?   data WORK.TABLEA; infile datalines dsd truncover; input name:$3. date:DATE9.; format date DATE9.; label name="name" date="date"; datalines4; A, 7-May-08 A, 11-Jul-08 A, 3-Jan-09 A, 4-Jan-09 A, 8-Jul-09 A, 24-Jul-09 A, 8-Dec-09 B, 7-May-08 B, 10-May-08 B, 17-May-08 B, 24-May-08 B, 1-Jun-08 B, 18-Jun-08 B, 9-May-09 C, 7-Oct-09 C, 17-Oct-09 C, 25-Oct-09 C, 18-Nov-09 C, 4-Dec-09 C, 19-Dec-09 C, 9-May-10 C, 9-May-10 C, 10-May-10 ;;;; run; data WORK.TABLEB; infile datalines dsd truncover; input name:$3. date:DATE9.; format date DATE9.; label name="name" date="date"; datalines4; A,11-Jul-08 A,3-Jan-09 A,24-Jul-09 B,7-May-08 B,17-May-08 B,18-Jun-08 B,9-Jul-09 C,17-Oct-09 C,4-Dec-09 C,19-Dec-09 ;;;; run; data temp; set tableb(in=inb) tablea; by name date; group+first.date; _inb=inb; run; data key; set temp(where=(_inb=1)); output; group=group+1; output; keep name group; run; proc sql; select * from temp where catx(' ',name,group) not in (select catx(' ',name,group) from key); quit; ... View more

You need to launch SAS with LOCALE=FA_IR, which means you should also use the Arabic encoding. See the blog post https://blogs.sas.com/content/sgf/2014/09/26/encoding-helping-sas-speak-your-language/ which includes links to the SAS NLS documentation.   ... View more