SAS 9.4 Language Reference, 3rd Edition

Testing Your Program

As a final step in preparing your data sets, you should test your program. Create small

temporary SAS data sets that contain a sample of observations that test all of your

program's logic. If your logic is faulty and you get unexpected output, you can use the

DATA step debugger to debug your program. For complete information about the

DATA Step Debugger, see SAS Data Set Options: Reference.

Combining SAS Data Sets: Methods

Concatenating

Definition

Concatenating data sets is the combining of two or more data sets, one after the other,

into a single data set. The number of observations in the new data set is the sum of the

number of observations in the original data sets. The order of observations is sequential.

All observations from the first data set are followed by all observations from the second

data set, and so on.

In the simplest case, all input data sets contain the same variables. If the input data sets

contain different variables, observations from one data set have missing values for

variables defined only in other data sets. In either case, the variables in the new data set

are the same as the variables in the old data sets.

Syntax

Use this form of the SET statement to concatenate data sets:

SET data-set(s);

where

data-set

specifies any valid SAS data set name.

For a complete description of valid SAS data set names, see the SET statement in SAS

Statements: Reference.

DATA Step Processing during Concatenation

Compilation phase

SAS reads the descriptor information of each data set that is named in the SET

statement and then creates a program data vector that contains all the variables from

all data sets as well as variables created by the DATA step.

Execution — Step 1

SAS reads the first observation from the first data set into the program data vector. It

processes the first observation and executes other statements in the DATA step. It

then writes the contents of the program data vector to the new data set.

The SET statement does not reset the values in the program data vector to missing,

except for variables whose value is calculated or assigned during the DATA step.

Variables that are created by the DATA step are set to missing at the beginning of

each iteration of the DATA step. Variables that are read from a data set are not.

Execution — Step 2

SAS continues to read one observation at a time from the first data set until it finds

an end-of-file indicator. The values of the variables in the program data vector are

456 Chapter 21 • Reading, Combining, and Modifying SAS Data Sets

then set to missing, and SAS begins reading observations from the second data set,

and so on, until it reads all observations from all data sets.

Example 1: Concatenation Using the DATA Step

In this example, each data set contains the variables Common and Number, and the

observations are arranged in the order of the values of Common. Generally, you

concatenate SAS data sets that have the same variables. In this case, each data set also

contains a unique variable to show the effects of combining data sets more clearly. The

following shows the Animal and the Plant input data sets in the library that is referenced

by the libref Example:

Animal Plant

OBS Common Animal Number OBS Common Plant Number

1 a Ant 5 1 g Grape 69

2 b Bird 2 h Hazelnut 55

3 c Cat 17 3 i Indigo .

4 d Dog 9 4 j Jicama 14

5 e Eagle 5 k Kale 5

6 f Frog 76 6 l Lentil 77

The following program uses a SET statement to concatenate the data sets and then prints

the results:

data concatenation;

set animal plant;

run;

proc print data=concatenation;

var Common Animal Plant Number;

title 'Data Set CONCATENATION';

run;

Combining SAS Data Sets: Methods 457