Therefore, you often, if not always, have to take intermediate steps to logically relate and process data before you can analyze it or create reports from it.Application requirements vary, but there are common factors for all applications that access, combine, and process data.By renaming one variable, you make the values of both of them available for processing, such as comparing.creates and names a temporary variable that contains an end-of-file indicator. Usually, the master data set and the transaction data set contain the same variables.The output data set contains one observation for each observation in the master data set.If any transaction observations do not match master observations, they become new observations in the output data set.Another data set could contain numeric sequence numbers whose partial values logically relate it to a separate data set by observation number.
The general format is like an equation, with the name of the new variable on the left, and the "formula" for creating that new variable on the right.
Dropping, keeping, and renaming variables is often useful when you update a data set.
Renaming like-named variables prevents the second value that is read from over-writing the first one.
This "formula" approach to creating variables gives you some flexibility.
For example, all of the following are valid ways of computing new variables in SAS: It can sometimes be useful to have a variable with a "constant" value; that is, the value of that variable is identical for every row in the dataset.