Chapter 51: The TRANSPOSE Procedure
Overview: TRANSPOSE Procedure
What Does the TRANSPOSE Procedure Do?
The TRANSPOSE procedure creates an output data set by restructuring the values in a SAS data set, transposing selected variables into observations. The TRANSPOSE procedure can often eliminate the need to write a lengthy DATA step to achieve the same result. Further, the output data set can be used in subsequent DATA or PROC steps for analysis, reporting, or further data manipulation.
PROC TRANSPOSE does not produce printed output. To print the output data set from the PROC TRANSPOSE step, use PROC PRINT, PROC REPORT, or another SAS reporting tool.
A transposed variable is a variable that the procedure creates by transposing the values of an observation in the input data set into values of a variable in the output data set.
What Types of Transpositions Can PROC TRANSPOSE Perform?
Simple Transposition
The following example illustrates a simple transposition. In the input data set, each variable represents the scores from one tester. In the output data set, each observation now represents the scores from one tester. Each value of _NAME_ is the name of a variable in the input data set that the procedure transposed. Thus, the value of _NAME_ identifies the source of each observation in the output data set. For example, the values in the first observation in the output data set come from the values of the variable Tester1 in the input data set. The statements that produce the output follow.
proc print data=proclib.product noobs; title 'The Input Data Set'; run; proc transpose data=proclib.product out=proclib.product_transposed; run; proc print data=proclib.product_transposed noobs; title 'The Output Data Set'; run;
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The Input Data Set 1 Tester1 Tester2 Tester3 Tester4 22 25 21 21 15 19 18 17 17 19 19 19 20 19 16 19 14 15 13 13 15 17 18 19 10 11 9 10 22 24 23 21
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The Output Data Set 2 _NAME_ COL1 COL2 COL3 COL4 COL5 COL6 COL7 COL8 Tester1 22 15 17 20 14 15 10 22 Tester2 25 19 19 19 15 17 11 24 Tester3 21 18 19 16 13 18 9 23 Tester4 21 17 19 19 13 19 10 21
Complex Transposition Using BY Groups
The next example, which uses BY groups, is more complex. The input data set represents measurements of the weight and length of fish at two lakes. The statements that create the output data set do the following:
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transpose only the variables that contain the length measurements
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create six BY groups, one for each lake and date
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use a data set option to name the transposed variable.
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Input Data Set 1 L o L W L W L W L W c e e e e e e e e a n i n i n i n i t D g g g g g g g g i a t h t h t h t h o t h t h t h t h t n e 1 1 2 2 3 3 4 4 Cole Pond 02JUN95 31 0.25 32 0.30 32 0.25 33 0.30 Cole Pond 03JUL95 33 0.32 34 0.41 37 0.48 32 0.28 Cole Pond 04AUG95 29 0.23 30 0.25 34 0.47 32 0.30 Eagle Lake 02JUN95 32 0.35 32 0.25 33 0.30 . . Eagle Lake 03JUL95 30 0.20 36 0.45 . . . . Eagle Lake 04AUG95 33 0.30 33 0.28 34 0.42 . .
Fish Length Data for Each Location and Date 2 Location Date _NAME_ Measurement Cole Pond 02JUN95 Length1 31 Cole Pond 02JUN95 Length2 32 Cole Pond 02JUN95 Length3 32 Cole Pond 02JUN95 Length4 33 Cole Pond 03JUL95 Length1 33 Cole Pond 03JUL95 Length2 34 Cole Pond 03JUL95 Length3 37 Cole Pond 03JUL95 Length4 32 Cole Pond 04AUG95 Length1 29 Cole Pond 04AUG95 Length2 30 Cole Pond 04AUG95 Length3 34 Cole Pond 04AUG95 Length4 32 Eagle Lake 02JUN95 Length1 32 Eagle Lake 02JUN95 Length2 32 Eagle Lake 02JUN95 Length3 33 Eagle Lake 02JUN95 Length4 . Eagle Lake 03JUL95 Length1 30 Eagle Lake 03JUL95 Length2 36 Eagle Lake 03JUL95 Length3 . Eagle Lake 03JUL95 Length4 . Eagle Lake 04AUG95 Length1 33 Eagle Lake 04AUG95 Length2 33 Eagle Lake 04AUG95 Length3 34 Eagle Lake 04AUG95 Length4 .
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For a complete explanation of the SAS program that produces these results, see Example 4 on page 1340.
EAN: 2147483647
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