Examples: Interleaving Data

Interleaving SAS^© datasets is a technique that allows combining observations from multiple datasets into a single one, respecting the order defined by one or more common variables specified in the BY statement. To ensure correct interleaving, it is imperative that all input datasets are pre-sorted (using PROC SORT) or indexed according to the same BY variable or variables. The process copies observations from the original datasets into the output dataset, maintaining the sequential order of the BY variable values. If BY variable values are duplicated between input datasets, the order in which the datasets are listed in the SET statement will determine the order of the corresponding observations in the output. If an input dataset contains variables not present in the others, the corresponding values in the output dataset will be null. The total number of observations in the output dataset corresponds to the sum of observations from all input datasets.

Data Analysis

Type : CREATION_INTERNE

The examples use generated data (datalines) to create the SAS datasets necessary to demonstrate interleaving.

1 Code Block

DATA STEP / PROC SORT Data

Explanation :
This example creates two datasets, 'animal' and 'plant', and sorts them by the common variable 'common'. Then, the DATA step interleaves these datasets using the BY statement. The output dataset 'interleave' contains observations from both datasets, ordered by 'common'.

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1	DATA animal;
2	INPUT common $ animal $;
3	DATALINES;
4	a Ant
5	b Bird
6	c Cat
7	d Dog
8	e Eagle
9	f Frog
10	;
11	RUN;
12
13	DATA plant;
14	INPUT common $ plant $;
15	DATALINES;
16	a Apple
17	b Banana
18	c Coconut
19	d Dewberry
20	e Eggplant
21	f Fig
22	;
23	RUN;
24
25	PROC SORT DATA=animal; BY common; RUN;
26	PROC SORT DATA=plant; BY common; RUN;
27
28	DATA interleave;
29	SET animal plant;
30	BY common;
31	RUN;
32	PROC PRINT DATA=interleave; RUN;

2 Code Block

DATA STEP / PROC SORT Data

Explanation :
This example demonstrates interleaving datasets ('animalDupes' and 'plantDupes') that contain duplicate values for the BY variable 'common'. The datasets are sorted before interleaving. The order of the datasets in the SET statement influences the order of observations with the same 'common' values in the output dataset. An additional example with the order 'plantDupes animalDupes' is provided to illustrate this impact.

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1	DATA animalDupes;
2	INPUT common $ animal $;
3	DATALINES;
4	a Ant
5	a Ape
6	b Bird
7	c Cat
8	d Dog
9	e Eagle
10	;
11	RUN;
12
13	DATA plantDupes;
14	INPUT common $ plant $;
15	DATALINES;
16	a Apple
17	b Banana
18	c Coconut
19	c Celery
20	d Dewberry
21	e Eggplant
22	;
23	RUN;
24
25	PROC SORT DATA=animalDupes; BY common; RUN;
26	PROC SORT DATA=plantDupes; BY common; RUN;
27
28	DATA interleave;
29	SET animalDupes plantDupes;
30	BY common;
31	RUN;
32
33	PROC PRINT DATA=interleave; RUN;

3 Code Block

DATA STEP / PROC SORT Data

Explanation :
This example illustrates interleaving datasets ('animalDupes' and 'plantMissing2') where the BY variable 'common' contains values present in one dataset but not in the other (e.g., 'd' in 'animalDupes' and 'f' in 'plantMissing2'). After sorting, the DATA step interleaves the datasets. Variables not present in a specific observation of an input dataset receive missing values in the output dataset.

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1	DATA animalDupes;
2	INPUT common $ animal $;
3	DATALINES;
4	a Ant
5	a Ape
6	b Bird
7	c Cat
8	d Dog
9	e Eagle
10	;
11	RUN;
12
13	DATA plantMissing2;
14	INPUT common $ plant $;
15	DATALINES;
16	a Apple
17	b Banana
18	c Coconut
19	e Eggplant
20	f Fig
21	;
22	RUN;
23
24	PROC SORT DATA=animalDupes; BY common; RUN;
25	PROC SORT DATA=plantMissing2; BY common; RUN;
26
27	DATA interleave;
28	SET animalDupes plantMissing2;
29	BY common;
30	RUN;
31
32	PROC PRINT DATA=interleave; RUN;

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