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(SAS) Random Sample Selection - sarathannapareddy

Tue, 11 May 2010 10:40:28 GMT

Last week my manager asked me to randomly pick 10%observations from a large data set and then create a listing so that the Data management programmers can QC the data. I want to share some thoughts here … how easy and simple to do random sampling. Approach 1: Data step Approach: In this approach, the observations are shuffled using the RANUNI function which assigns a random number to each observation.

(SAS) CALL EXECUTE: Easy way to print or sort multiple files. - sarathannapareddy

Mon, 26 Apr 2010 19:42:48 GMT

When printing multiple files, or sorting multiple datasets, the traditional method is to write multiple steps as below. Proc print data=libref.ae; var _all_; run; Proc print data=libref.conmed; var _all_; run; Proc print data=libref.demog; var _all_; run; Proc print data=libref.lab; var _all_; run; Proc print data=libref.medhist; var _all_; run; If you are like me who likes to simplify the traditional SAS code here is the tip. CALL EXECUTE comes to rescue here.

(SAS) How to delete previously assigned formats and informats of variables in the dataset - sarathannapareddy

Tue, 11 Aug 2009 16:26:20 GMT

How to delete previously assigned formats and informats completely from the SAS dataset: PROC DATASETS lib=work; MODIFY dsn; FORMAT _all_; INFORMAT _all_; RUN; QUIT;

(SAS) Renaming All variables in the SAS dataset using SASHELP VIEWS/DICTIONARY.tables - sarathannapareddy

Thu, 30 Jul 2009 13:12:57 GMT

We can rename all the variables in the dataset using the SASHELP views or Dictionary.Tables... I.e SAS metadata... here is how....

(SAS) Renaming All Variables in a SAS Data Set Using the SASHELP VIEWS - sarathannapareddy

Thu, 23 Jul 2009 09:29:51 GMT

*Create a temporary dataset... DSN; data dsn; a=1; b=2; c=3; d=4; e=5; f=6; run; %macro test(lib,dsn); */1)*/ data _null_; set sashelp.vtable(where=(libname="&LIB" and memname="&DSN")); call symput('nvars',nvar); run; */2)*/ data dsn; set sashelp.vcolumn(where=(libname="&LIB" and memname="&DSN")); call symput(cats("var",_n_),name); run; */3)*/ proc datasets library=&LIB; modify &DSN; rename %do i = 1 %to &nvars; &&var&i=Rename_&&var&i. %end; ; quit; run; %mend; %test(WORK,DSN); After submitting the above program... the output looks like this.... Output: Rename_a Rename_b Rename_c Rename_d Rename_e Rename_f 1 2 3 4 5 6

(SAS) Clean-up: Delete temporary Datasets in work directory - sarathannapareddy

Sun, 14 Jun 2009 12:28:58 GMT

It is better always to clean-up/empty the work directory before we run the next set of SAS code. This is VERY helpful in situations where the “working” files created tend to use up a large amount of memory, once the logic of the program has been checked, KILLing the working files will result in a more efficient program. Another important reason to issue the above statement at the end of a program is when programs are run in batch, this will clean up the working library to be sure any “old” files are not left around to be erroneously used1.

(SAS) How to delete or remove previously assigned formats and informats completely from the SAS dataset: - sarathannapareddy

Sun, 07 Jun 2009 22:20:18 GMT

(SAS) Clean-Up: Delete datasets in the work library: - sarathannapareddy

Sun, 07 Jun 2009 22:17:55 GMT