PROC TRANSPOSE is a powerful SAS procedure used to reshape data by converting rows into columns or columns into rows. Whether you're preparing datasets for reporting or statistical analysis, PROC TRANSPOSE
can simplify your task with just a few lines of code.
In this blog, you'll learn:
-
What is
PROC TRANSPOSE
? - When and why to use it
- Syntax and options
- Multiple real-world examples
- Tips and tricks for efficient use
🔍 What is PROC TRANSPOSE in SAS?
PROC TRANSPOSE
is used to pivot data—turning variables (columns) into observations (rows), or vice versa. It's especially useful for:
- Summarizing repeated measures
- Restructuring long or wide datasets
- Preparing data for visualizations or modeling
📚 Basic Syntax of PROC TRANSPOSE
📌 Key Options Explained
Option | Description |
---|
BY | Groups data before transposing |
VAR | Specifies variables to transpose |
ID | Uses values of a variable as new column names |
NAME= | Renames the default _NAME_ column |
LABEL= | Renames the default _LABEL_ column |
✅ Example 1: Transposing Without BY or ID
🔹 Input Data
🔹 Transpose Code
🔹 Output
NAME | COL1 | COL2 | COL3 | COL4 |
---|
Sales | 100 | 120 | 140 | 160 |
✅ Example 2: Transposing with ID to Use Column Names
🔹 Output
NAME | Q1 | Q2 | Q3 | Q4 |
---|
Sales | 100 | 120 | 140 | 160 |
✅ Example 3: Transpose with BY Grouping
🔹 Input Data
🔹 Transpose Code
🔹 Output
Student | English | Math | Science |
---|
John | 78 | 85 | 92 |
Anna | 91 | 88 | 84 |
✅ Example 4: Transposing Multiple Variables
🔹 Code
🔹 Output
ID | Height_Visit1 | Height_Visit2 | Weight_Visit1 | Weight_Visit2 |
---|
P1 | 170 | 171 | 65 | 66 |
P2 | 160 | 161 | 60 | 61 |
🧠 Tips for Using PROC TRANSPOSE
- Always
SORT
your data before using BY
. - Use the
PREFIX=
option to create meaningful column names. - Combine multiple transpositions for complex reshaping.
- Use
NAME=
and LABEL=
to rename the default variables _NAME_
and _LABEL_
.
🔎 When to Use PROC TRANSPOSE
Use Case | PROC TRANSPOSE? |
---|
Convert long to wide format | ✅ Yes |
Convert wide to long format | ✅ Yes (reverse) |
Reshape repeated measures | ✅ Yes |
Change actual data values | ❌ No |
Merge multiple reshaped tables | ✅ Yes |
📈 Conclusion
PROC TRANSPOSE
is an essential tool in any SAS programmer’s toolkit. It simplifies the process of reshaping data for reporting, analysis, and modeling. With a good understanding of BY
, ID
, and VAR
options, you can handle almost any data transformation challenge.
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