| Basic Concepts |
| SAS Data
Sets |
| Data
Portion
The data portion of a SAS data set is a collection of data values arranged in a rectangular table. In the example below, the name Jones is a data value, the weight 158.3 is a data value, and so on. |
| Data portion |
|
| Observations (Rows)
Rows (called observations) in the data set correspond to records or data lines in a raw data file or external database. An observation is the information about each entity in a SAS data set. The values Jones, M, 48, and 128.6 make up a single observation. |
| Observation |
|
| The data set shown above has four observations, each containing information about an individual. A SAS data set can store any number of observations. |
| Variables (Columns)
Columns (called variables) in the data set correspond to
fields in a raw data file or external database. A variable is the set of
data values that describes a given characteristic. The values Jones,
Laverne, Jaffe, and Wilson make up the variable
|
| Variable |
|
The data set above contains four variables, or categories
of information, about each person: Name, Sex,
Age, and Weight. A SAS data set can store thousands
of variables. Only the capacity of your storage device limits the number
of variables in your SAS data sets. |
| Missing Values
The rectangular arrangement of rows and columns in a SAS data set implies that every variable must exist for each observation. If a data value is unknown for a particular observation, a missing value is recorded in the SAS data set. |
| Missing
value |
|
|
|
Copyright © 2002 SAS Institute Inc., Cary, NC, USA. All rights reserved.