In addition to Tom's advice, it might be worth trying to figure out why the log is so large. When I get "log full" type problems, it usually turns out to be because something in my program is generating a very large number of notes/warnings. For instance, if I'm doing something that generates a note at every observation of a 2-million-observation file, that will choke up the log very quickly. One way to identify this is to run the program on a smaller data set so that I can look at the log and see what's taking up the space. If I can identify a step that's spamming the log, I can then fix that problem without needing to shut off logging altogether. ... View more

I'm with PG on this one. The SAS "solution" posted can only be written by somebody who's already guessed that f(x) might be a sum of individual digit scores. But at that point, they've already done 99% of the heavy lifting. Somebody who has that idea in mind doesn't even need SAS; it's easy enough to figure out the digit values and verify the results by eye. ... View more

If you have the data set open, you can also check the length of a character variable by mousing over the column header. After a little while a tooltip will pop up with variable name, length, and other properties. ... View more

Patrick is correct, I was aware of this rather important detail but completely neglected to mention it in my response 😞 In hindsight, my PROC SORT example should have used "by _all_". ... View more

I see you already have solutions, but you might (or might not) find that existing SAS regression options can save you the need to write your own macro. For instance, PROC REG gives you options for stepwise selection (add variables with best explanatory power/remove variables with worst) or by using something like SELECTION=MAXR STOP=&MAXEXPVARS you can force SAS to choose the best n variables. ... View more

You can't delete it from x, because it's not in x to begin with. What you've done here is define &x as the literal string "a1-a10". I assuming you're thinking of this as a list of variables a1, a2, ..., a10, but when you define "%let x=a1-a10" SAS doesn't perform that interpretation. SAS will substitute the characters "a1-a10" in the code where "&x" appears and only then will it interpret it. Demonstration: %let x=a1-a3; data test; a1=5; a2=6; a3=7; diff=&x; sum=sum(of &x); run; When you run this code, the first thing SAS does is to substitute "a1-a3" where "&x" appears: data test; a1=5; a2=6; a3=7; diff=a1-a3; sum=sum(of a1-a3); run; It then interprets based on context. In the first case, it interprets "a1-a3" as a1 minus a3 (= 5-7 = -2); in the second case it interprets it as "a1, a2, a3" (= 5+6+7 = 18). If you can give some more context on what you're looking to do, people might be able to suggest some other solution. ... View more

Assuming you want to remove duplicate observations with the same values? data have; input x y; cards; 1 2 1 4 1 8 2 3 2 4 2 4 2 5 1 7 1 8 ; run; /* PROC SORT method */ proc sort data=have nodup out=want1; by x y; quit; /* PROC SQL method */ proc sql; create table want2 as select distinct * from have; quit; If you want to delete duplicates that are not 100% identical (e.g. all units with the same ID variable regardless of whether they differ in other values) look at the NODUPKEY option in PROC SORT. ... View more

Assumptions: (1) no two records for the same key have overlapping dates (i.e. if birth_da for record 1 < birth_da for record 2 on the same key, then ret_date for record 1 < birth_da for record 2) (2) birth_da is nonmissing (3) missing value for ret_date indicates not yet retired (so can only occur in the last record) So for each key, you want to return the latest birth_da that is not greater than the date? I think the easiest way to do this in simple SAS is to reverse-sort and use LAG to find the next date: %let date='15Jul2001'd; data have; input recordid h_postal $ birth_da ret_date; informat birth_da ret_date ANYDTDTE20.; format birth_da ret_date DATE9.; cards; 1 A 01Jan2000 01Jun2001 2 A 01Jan2002 12Feb2003 3 B 01Jan2000 01Jun2001 4 B 01Jul2001 12Feb2003 5 C 01Jan1999 31Dec1999 6 C 01Jan2001 01Feb2001 7 C 01Jan2003 12feb2003 8 D 01Jan2005 01Jan2007 9 D 01Jan2009 . 10 E 01Jan2001 . ; run; proc sort data=have out=have_reverse; by h_postal descending birth_da; quit; data want; set have_reverse; by h_postal; next_birth_date=lag(birth_da); if first.h_postal then next_birth_date=.; /* because we have sorted in reverse date order, first.h_postal indicates that this is the most recent entry for this unit (highest value of birth_da) */ if (next_birth_date<=ret_date OR missing(ret_date)) AND not missing(next_birth_date) then put "ERROR: dates overlap"; if (birth_da<=&date) AND ((next_birth_date>&date) OR missing(next_birth_date)) then output; drop next_birth_date; run; Edit: before using this you'll need to convert to SAS date variables (which you should be using anyway for this sort of work) and as per Tom's comment, if a date of "190000001" indicates "not yet retired" this should probably be interpreted as missing. Message was edited by: Geoffrey Brent ... View more

The two code examples you provide should give identical results, though WHERE may be faster to run. However there are many cases where WHERE and subsetting IF do not give identical output. Compare: data test; length x $5; input x; cards; One Two Three Four Five ; run; data subset_if; set test; sequence_number=_n_; previous_x=lag(x); if not(x="Three"); run; data subset_where; set test; sequence_number=_n_; previous_x=lag(x); where not(x="Three"); run; In creating SUBSET_IF, we read in and process all lines from TEST before dropping the third observation. Even though the third observation isn't output directly, it still affects what is output: sequence_number goes 1,2,4,5 and previous_x goes " ", "One", "Three", "Four". In creating SUBSET_WHERE, the observation with x="Three" is deleted at an earlier stage, and there's no sign in the output that it ever existed. ... View more