This feature combines observations from two or more datasets by associating them positionally. The SET statement reads one observation from each listed dataset at each DATA step iteration. Variables common to the datasets are overwritten by the values of the dataset specified last in the SET statement. The process stops once the dataset containing the fewest observations has been fully read, which determines the final number of observations in the resulting dataset. This method does not rely on a key variable for matching and can produce unexpected results if datasets have common variables with unsynchronized values.
Data Analysis
Type : CREATION_INTERNE
Examples use generated data (datalines) or SASHELP. The 'animal' and 'plantG' datasets are created internally for illustration.
1 Code Block
DATA STEP / PROC PRINT Data
Explanation :
This SAS code creates two datasets, 'animal' and 'plantG', then combines them using two consecutive SET statements. The DATA step reads one observation from 'animal' then one observation from 'plantG' for each iteration. The values of the 'common' variable from the 'plantG' dataset (specified last) overwrite those from the 'animal' dataset. The resulting 'combine' dataset will have a number of observations equal to that of the smallest input dataset. The PROC PRINT output shows the combined dataset, illustrating how 'common' values from 'plantG' were retained, even when diverging at the sixth observation (where 'animal' had 'f' and 'plantG' had 'g', 'g' from 'plantG' is kept).
This SAS code creates two datasets, 'animal' and 'plantG', then combines them using two consecutive SET statements. The DATA step reads one observation from 'animal' then one observation from 'plantG' for each iteration. The values of the 'common' variable from the 'plantG' dataset (specified last) overwrite those from the 'animal' dataset. The resulting 'combine' dataset will have a number of observations equal to that of the smallest input dataset. The PROC PRINT output shows the combined dataset, illustrating how 'common' values from 'plantG' were retained, even when diverging at the sixth observation (where 'animal' had 'f' and 'plantG' had 'g', 'g' from 'plantG' is kept).
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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 plantG; |
| 14 | INPUT common $ plant $; |
| 15 | DATALINES; |
| 16 | a Apple |
| 17 | b Banana |
| 18 | c Coconut |
| 19 | d Dewberry |
| 20 | e Eggplant |
| 21 | g Fig |
| 22 | ; |
| 23 | RUN; |
| 24 | |
| 25 | DATA combine; |
| 26 | SET animal; |
| 27 | SET plantG; |
| 28 | RUN; |
| 29 | |
| 30 | PROC PRINT DATA=combine; RUN; |
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