Maxim 19
Long beats wide.
(Don't keep data in structure)
In the world of spreadsheets, people tend to line up data side-by-side, and put data items (dates, categories, …) into column headers. This runs counter to all the methods available in SAS for group processing, and makes programming difficult, as one has variable column names and has to resort to creating dynamic code (with macros and/or call execute) where such is not necessary at all if categories were represented in their own column and data aligned vertically. There are times where a wide format is needed, eg when preparing data for regression analysis. But for the processing and storing of data, long formats are always to be preferred.
Dynamic variable names force unnecessary dynamic code.
from https://communities.sas.com/t5/SAS-Communities-Library/Maxims-of-Maximally-Efficient-SAS-Programmers/ta-p/352068
In this case you don't need data step at all:
proc transpose data= have out= trance(drop= _name_ rename=(col1 = f));
by id;
var f:;
run;
proc freq data= trance noprint;
table f / out= want;
run;
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