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PGStats · ‎11-16-2022

Note, if you need to know which of many possible substrings was matched, (using PRXPOSN) you should list the longer substrings first if _n_=1 then do; re_i + prxparse('/\b(myocardial infarction|infarct|MI)\b/i'); re_n + prxparse('/\bno\b|\bnegative\b/i'); end; pos_i = prxmatch(re_i,string); pos_n = prxmatch(re_n,string); infarct = pos_i & not (0<pos_n<pos_i); if infarct then word = prxposn(re_i, 1, string);

PGStats · ‎11-11-2022

If variable RANK is reliable: data have; length name $32; input Name & year mcap code RANK ESG; datalines; Oil & Natural Gas Corpn. Ltd. 2010 2349765 610 1 1 Oil India Ltd. 2010 277160 610 2 0 Selan Exploration Technology Ltd. 2010 6604 610 3 0 Bharat Heavy Electricals Ltd. 2010 1168998 2513 1 1 Godrej Consumer Products Ltd. 2011 118256 34 1 0 Tata Chemicals Ltd. 2011 86662 34 2 0 Piramal Enterprises Ltd. 2011 69996 34 3 1 H M T Ltd. 2011 45032 34 4 0 K S K Energy Ventures Ltd. 2011 37636 34 5 0 B A S F India Ltd. 2011 25692 34 6 0 Peninsula Land Ltd. 2011 16550 34 7 0 Texmaco Rail & Engg. Ltd. 2011 12729 34 8 0 Alembic Ltd. 2011 9760 34 9 0 ; proc sql; create table want as select a.name, a.year, a.code, b.name as low1, c.name as high1, d.name as low2, e.name as high2 from have as a left join have as b on a.code=b.code and a.year=b.year and a.rank=b.rank-1 left join have as c on a.code=c.code and a.year=c.year and a.rank=c.rank+1 left join have as d on a.code=d.code and a.year=d.year and a.rank=d.rank-2 left join have as e on a.code=e.code and a.year=e.year and a.rank=e.rank+2 where a.ESG=1; select * from want; quit;

PGStats · ‎11-09-2022

SG procs do not provide arrows on axes. But you could use SG annotation to achieve this: data have; call streaminit(86585); do x=1 to 10; y+rannor(1); output; end; run; data annoset; function = "ARROW"; shape = "FILLED"; drawspace = "WALLPERCENT"; y1 = 0; y2 = 0; x1 = 0; x2 = 100; output; function = "ARROW"; shape = "FILLED"; drawspace = "WALLPERCENT"; y1 = 0; y2 = 100; x1 = 0; x2 = 0; output; run; proc sgplot data=have noautolegend sganno=annoset; series x=x y=y/ARROWHEADPOS=both ARROWHEADSHAPE=filled ; run;

PGStats · ‎11-05-2022

Try this: %let goodPrefix=stringA|stringB; %let badPrefix=stringC|stringD; /* Or perhaps */ %let goodPrefix=string[AB]; %let badPrefix=string[^AB]; data want; set have; if prxmatch("/^(\s*\b(&goodPrefix.))+/io", variableList) and not prxmatch("/\b(&badPrefix.)/io", variableList); run;

PGStats · ‎11-04-2022

This may serve as a starting point for anyone wishing to tackle this question: data have; infile datalines truncover; input ID Position $ Time Resistance Force y; datalines; 1 Ant 3.82 -23 37 1 1 Ant 4.94 -24 4.4 0 1 Ant 3.49 -41.5 15.8 1 1 Ant 3.07 -39.5 21.15 1 1 Post 3.43 -39 29 1 1 Post 3.53 -45.5 14.15 1 1 Post 4.44 -46 9.55 1 1 Post 3.37 -19 12.9 1 1 Ant 3.35 -46.5 7.2 1 1 Ant 3.19 -43 14.2 1 1 Ant 3.61 -41 24.55 1 1 Ant 4.24 -48 23.15 1 1 Post 2.09 -33 27.25 1 1 Post 2.83 -32 21.2 1 1 Post 3.26 -28 29.7 0 1 Post 3.34 -41.5 10.15 1 2 Ant 5.29 -30 10.9 1 2 Ant 4.22 -29 11.3 1 2 Ant 2.40 -15 10.2 1 2 Ant 3.32 -18.5 8.75 1 2 Post 1.85 -27 9.3 1 2 Post 4.31 -37 8.75 1 2 Post 1.82 -29.5 13.95 1 2 Post 3.98 -24.5 9.8 0 2 Ant 4.06 -39.5 21.45 1 2 Ant 2.90 -35.5 16.5 1 2 Ant 3.23 -35.5 18.2 1 2 Ant 4.24 -31 14.3 1 2 Post 2.45 -31 9.6 1 2 Post 3.51 -20 6 1 2 Post 4.27 -17.5 8.4 1 2 Post 2.67 -25.5 25 0 3 Ant 3.065092996 -40 10.7 1 3 Ant 3.74 -38 17.8 . 3 Ant 3.61 -27 10.1 0 3 Ant 2.08 -26.5 6.45 . 3 Post 2.12 -35 20.4 1 3 Post 3.244 -39 27.5 1 3 Post 4.02 -42 19.9 1 3 Post 1.94 -19 16.6 1 3 Ant 4.37 -14 4.2 0 3 Ant 4.68 -33 6.9 0 3 Ant 3.35 -30.5 8.65 1 3 Ant 1.72 -33 14.1 1 3 Post 0.81 -27 12.2 1 3 Post 3.90 -26 18.35 1 3 Post 4.19 -29 9.4 1 3 Post 4.46 -19 10.2 1 4 Ant 2.89 -42 11.3 1 4 Ant 2.20 -28 12.45 1 4 Ant 2.97 -31 19.5 1 4 Ant 2.06 -31 22.3 1 4 Post 3.35 -44.5 32.9 1 4 Post 2.10 -35 15.3 1 4 Post 3.42 -35 8.35 1 4 Post 4.16 -33 20.9 1 4 Ant 4.06 -15.5 6 1 4 Ant 5.00 -25 21.5 1 4 Ant 4.13 -33.5 24.25 1 4 Ant 5.56 -34 16.7 1 4 Post 4.14 -35 31.75 1 4 Post 4.49 -33.5 25.4 1 4 Post 4.17 -29 41.9 1 4 Post 3.85 -28 28.8 1 5 Ant 2.67 -23 28.2 0 5 Ant 1.68 -23 10.3 1 5 Ant 2.07 -19.5 9.85 1 5 Ant 1.06 -25 12.7 1 5 Post 5.02 -31 10.4 0 5 Post 2.53 -23 11.7 1 5 Post 3.40 -71.5 27.15 1 5 Post 4.78 -41.5 31.85 1 5 Ant 2.15 -42 15.95 1 5 Ant 2.89 -26.5 16.9 1 5 Ant 2.25 -33 9.8 1 5 Ant 2.76 -28 12.1 0 5 Post 3.04 -22 9 1 5 Post 4.45 -37.5 9.25 1 5 Post 4.10 -20.5 15.3 1 5 Post 4.41 -31.5 18.05 1 6 Ant 1.61 -26 18.7 1 6 Ant 1.68 -26 7.4 0 6 Ant 3.93 -29 7.4 0 6 Ant 4.45 -21.5 9.15 . 6 Post 5.48 -28 25.05 1 6 Post 4.11 -48 30.7 1 6 Post 3.20 -23 22.3 1 6 Post 2.77 -28 15.3 1 6 Ant 2.34 -22 10.95 1 6 Ant 2.25 -30 6.2 1 6 Ant 4.16 -24.5 6.6 6 Ant 4.62 -33 12 0 6 Post 2.32 -31 16.65 1 6 Post 4.03 -31 19 1 6 Post 3.43 -17 12 . 6 Post 3.51 -14 11.1 0 7 Ant 2.99 -30 7.65 1 7 Ant 1.80517419 -25 15.95 1 7 Ant 2.106053494 -32 13.8 1 7 Ant 3.096114016 -29 17.55 1 7 Post 3.167542074 -24 11.45 1 7 Post 3.338268984 -24 22.7 1 7 Post 2.659685183 -32.5 21.95 1 7 Post 3.751749917 -17 8.25 1 7 Ant 2.197529839 -25 8.8 0 7 Ant 3.664137015 -35 10.1 0 7 Ant 3.545702335 -39 9.4 0 7 Ant 2.023625001 -35 10.1 1 7 Post 2.372086883 -33 24.25 1 7 Post 3.582104056 -37.5 17.3 1 7 Post 3.45055168 -38 12.6 1 7 Post 3.841677068 -23 9.8 1 8 Ant 3.432008272 -25 18.6 0 8 Ant 2.136605495 -32.5 14.1 1 8 Ant 1.841190586 -18 7 0 8 Ant 2.15865836 -25.5 6.8 0 8 Post 3.359805409 -30 15.5 1 8 Post 3.631259765 -31 28 1 8 Post 4.674356585 -32.5 20.9 1 8 Post 4.044977037 -25 12.9 0 8 Ant 3.346860731 -28 14.6 1 8 Ant 3.850582629 -46 24.5 1 8 Ant 5.340021635 -31.5 8.5 1 8 Ant 3.980653721 -26 11.6 1 8 Post 3.704121331 -26 14.8 1 8 Post 3.848852913 -31.5 15.8 1 8 Post 4.939191479 -18 9.8 1 8 Post 3.134066196 -15 9.1 1 9 Ant 1.309024248 -25 9 1 9 Ant 3.369404446 -27 11.55 1 9 Ant 1.841284373 -26 13.15 1 9 Ant 3.675231524 -21 12.4 1 9 Post 3.06826061 -22 24.2 1 9 Post 3.59966626 -19 17.3 1 9 Post 4.466268907 -16.5 15.7 1 9 Post 1.882204503 -27 11.3 . 9 Ant 3.89896461 -25 21.1 1 9 Ant 2.295202494 -26 9 1 9 Ant 3.272687389 -24.5 4.95 0 9 Ant 4.201883396 -13 2.7 0 9 Post 4.374845784 -25 10.8 0 9 Post 4.459715564 -15.5 11.8 1 9 Post 3.227763303 -19.5 21.05 0 9 Post 2.517233031 -20.5 31.6 1 ; proc sort data=have; by position id; run; proc sgscatter data=have; where resistance gt -50; /* remove outlier */ by position; matrix force time resistance / group=y; run;

PGStats · ‎11-03-2022

Well for one thing, the "o" pattern suffix instructs the matching function that the pattern is a constant, i.e. that it doesn't need to be recompiled at every invocation. Which is clearly not the case here. BTW, the "i" suffix makes the matching case insensitive. So, no need for the lowcase() function call.

PGStats · ‎11-03-2022

With SAS/SQL you have to use the inefficient syntax: proc sql; UPDATE dest_tab tt SET Name = (SELECT Name FROM source_tab WHERE id = tt.id) , Sex = (SELECT Sex FROM source_tab WHERE id = tt.id) , Age = (SELECT Age FROM source_tab WHERE id = tt.id) , Height = (SELECT Height FROM source_tab WHERE id = tt.id) , Weight = (SELECT Weight FROM source_tab WHERE id = tt.id) WHERE EXISTS (SELECT * FROM source_tab WHERE id = tt.id); quit;

PGStats · ‎10-29-2022

No it doesn't. As long as it runs before PRXMATCH. In any case, you should make sure that the datastep variable names are not the same as the input dataset variable names.

PGStats · ‎10-29-2022

It's always a tradeoff between validation strength and complexity, This should filter out many anomalies: data want; if not id then id + prxparse( "/([12][90]\d\d-[01]\d-[0123]\d|[12][90]\d\d-[01]\d|[12][90]\d\d)[ T]([012]\d:[012345]\d|[012]\d:)?/io"); set have; length adtmc $16; if prxmatch(id, ecdtc) then do; d = prxposn(id, 1, ecdtc); t = prxposn(id, 2, ecdtc); adtmc = catx(" ", catx("-", scan(d,1), coalescec(scan(d,2), "XX"), coalescec(scan(d,3), "XX")), catx(":", coalescec(scan(t,1,":"), "XX"), coalescec(scan(t,2,":"), "XX")) ); end; else adtmc = ecdtc; drop id d t; run;

PGStats · ‎10-24-2022

Very neat @Ksharp , but you might want to use do DTCONT = DTCONT + 1 to coalesce(_DTCONT, DTCONT) - 1; instead, to avoid getting note in the LOG and to refer to zero as a date. Cheers

PGStats · ‎10-23-2022

I added two features to the data to make this example more general 1) an empty condition in dataset B (which should be ignored) 2) I made Customer_Id numeric in both datasets data A; input User_ID $ Customer_ID Email_add :$20. Invoice_no $ Invoice_account; datalines; u1 1 example1@gmail.com v1 100 u2 2 example2@gmail.com v2 120 u2 2 example2b@gmail.com v3 130 u3 3 example3@gmail.com v4 150 u4 4 example4@gmail.com v5 165 u5 5 example5@gmail.com v6 180 ; data B; input User_ID $ Customer_ID Email_add :$20.; infile datalines missover dlm = '|'; datalines; | 1 |example1@gmail.com | |example2@gmail.com u3 | | | | ; proc sql; select * from A; select * from B; delete from A where exists ( select * from B where cmiss(User_Id, Customer_Id, Email_Add) < 3 and ((User_Id=A.User_Id) + (Customer_Id=A.Customer_Id) + (Email_Add=A.Email_Add)) = (3 - cmiss(User_Id, Customer_Id, Email_Add)) ); select * from A; quit;

PGStats · ‎10-13-2022

My best guess: Proc sql; create table test1 as (select a.ser_date, m1, f, 1 as aNumber, l1, np1 from table k.claimtable as a inner join k.tab2 as b on a.m1 = b.m1 where a.pc in ('1234') and a.ser_date between '01jan2022'd and 31aug2022'd) union all (select a.ser_date, m1, f, 1 as aNumber, l1, np1 from table k.claimtable as a inner join k.tab3 as b on a.m1 = b.m1 where a.pc in ('99999') and a.ser_date between '01jan2022'd and 31aug2022'd) order by ser_date; quit;

PGStats · ‎10-01-2022

The 0.1500 level mentioned in the message refers to the SLSTAY= option. "the stepwise method looks at all the variables already included in the model and deletes any variable that does not produce an F statistic significant at the SLSTAY= level. Only after this check is made and the necessary deletions are accomplished can another variable be added to the model. The stepwise process ends when none of the variables outside the model has an F statistic significant at the SLENTRY= level and every variable in the model is significant at the SLSTAY= level, or when the variable to be added to the model is the one just deleted from it." The ALPHA= option sets the significance value for confidence and prediction intervals and tests (on the final model).

PGStats · ‎09-29-2022

You didn't show us the expected result, but maybe this? data temp; length var $16; do i = 1 by 1 until(last.id); do n = 1 by 1 until(last.tt); set have; by id tt notsorted; end; var = cats("N_series_", i); value = n; output; var = cats("value_series_", i); value = tt; output; end; keep id var value; run; proc transpose data=temp out=want(drop=_name_); var value; id var; by id; run;

PGStats · ‎09-24-2022

Maybe you imported the dates from somewhere where they are not represented quite the same as in SAS (e.g. Excel)? Happened to me once. The date numbers were not integers. Try: left join EPU_Data as B on round(R.sas_date) = round(B.sas_date)

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