WebSAS® DATA Step Statements: Reference documentation.sas.com. SAS® Help Center. Customer Support SAS Documentation. SAS® Viya® Programming Documentation ... SAS Data Quality . SAS Job Execution Web Application. Accessibility in SAS Viya. SAS Visual Analytics. SAS Viya: Administration. SAS Viya Operations. SAS Studio. WebSAS programs are comprised of two distinct steps: data steps and proc steps. Data steps are written by you, while procedures are pre-written programs that are built-in. In general, Data steps are used to read, modify and create data files …
SAS Tutorials: The Data Step - Kent State University
WebJun 20, 2016 · Useful tip to prepare data for analysis! I find the SELECT statement useful when writing data dependent code using SAS macro and look ups. Instead of hard-coding the possible values, you can write SAS macro code to create them and if the category values change or new categories are added, the SAS code is automatically updated with … WebSAS® 9.4 DATA Step Statements: Reference documentation.sas.com. SAS® Help Center. Customer Support SAS Documentation. SAS® 9.4 and SAS® Viya® 3.5 Programming Documentation ... SAS Data Quality . Learning SAS Programming . Accessibility for Base. SAS Visual Analytics. SAS Studio. SAS Enterprise Guide. SAS 9.4 Administration. dutch elm disease in minnesota
Debugging the difference between WHERE and IF in SAS
WebDec 8, 2024 · Properly using the SET statement in SAS is one of the key techniques for improving the efficiency of SAS programs. The SET statement has options that can be used to control how the data are to be read. SET statement options. Using the NOBS= and POINT= options. Using the INDSNAME= Option. WebJul 6, 2024 · In SAS, there are four ways to perform WHERE processing: The WHERE= data set option: This option is places after the name of the data set when you use the SET statement the DATA step or the DATA= option in a procedure. The WHERE= option reads only the observations that satisfy the criteria. WebOr, we might want to select only a subset of variables to keep in a working analysis data set. Options illustrated in this lesson include: FIRSTOBS= and OBS=, to reduce the number of observations in the dataset. DROP= and KEEP=, to reduce the number of variables in the dataset. IN =, to create an indicator variable (0,1) which indicates whether ... dutch elm inoculation