When you use a SAS
data set as input into a DATA step, the description of the data set
is available to SAS. In your DATA step, use a SET, MERGE, MODIFY,
or UPDATE statement to read the SAS data set. Use SAS programming
statements to process the data and create an output SAS data set.
In a DATA step, you
can create a new data set that is a subset of the original data set.
For example, if you have a large data set of personnel data, you might
want to look at a subset of observations that meet certain conditions,
such as observations for employees hired after a certain date. Alternatively,
you might want to see all observations but only a few variables, such
as the number of years of education or years of service to the company.
When you use existing
SAS data sets, as well as with subsets created from SAS data sets,
you can make more efficient use of computer resources than if you
use raw data or if you are working with large data sets. Reading fewer
variables means that SAS creates a smaller program data vector, and
reading fewer observations means that fewer iterations of the DATA
step occur. Reading data directly from a SAS data set is more efficient
than reading the raw data again, because the work of describing and
converting the data has already been done.
One way of looking at
a SAS data set is to produce a listing of the data in a SAS data set
by using the PRINT procedure. Another way to look at a SAS data set
is to display information that describes its structure rather than
its data values. To display information about the structure of a data
set, use the DATASETS procedure with the CONTENTS statement. If you
need to work with a SAS data set that is unfamiliar to you, the CONTENTS
statement in the DATASETS procedure displays information such as the
name, type, and length of all the variables in the data set.
An example that shows
the CONTENTS statement in the DATASETS procedure is shown in Input SAS Data Set for Examples.