How to Easily Rename Variables in SAS Using the RENAME Statement

You can use the rename option directly within the SET statement of a DATA Step to rename one or more variables as the dataset is being read and copied. This is the preferred method when creating a new dataset based on an existing one, ensuring that the original source data remains untouched, which is a key best practice in data hygiene.

This function uses the following basic syntax structure within the SET statement parentheses:

data new_data;
    set original_data (rename=(old_name=new_name));
run;

This approach is highly efficient because the renaming occurs during the input phase of the new dataset creation. Before diving into the specific renaming techniques, we must establish a working dataset. The following code demonstrates the creation and initial viewing of the example dataset that will be used throughout this tutorial:

/*create dataset for demonstration*/
data original_data;
    input x y z;
    datalines;
1 4 76
2 3 49
2 3 85
4 5 88
2 2 90
;
run;

/*view the initial dataset structure*/
proc print data=original_data;

Example 1: Renaming a Single Variable in a DATA Step

The most common renaming task involves changing the name of just one variable. This is typically done when a variable name is non-descriptive or conflicts with a reserved keyword. When using the SET statement, the renaming happens only in the context of the dataset being created (new_data), leaving the original source dataset (original_data) completely intact.

In this example, we aim to rename the variable labeled x to new_x. This simple modification immediately improves clarity, especially if ‘x’ represented a critical measurement like ‘temperature’ or ‘score’. We apply the rename=(x=new_x) syntax directly inside the parentheses following the source dataset name in the SET statement.

The following code shows how to rename just the x variable in the dataset:

/*rename one variable using the SET option*/
data new_data;
    set original_data (rename=(x=new_x));
run;

/*view new dataset to confirm change*/
proc print data=new_data;

Upon viewing the output, notice that x has been successfully renamed to new_x, while every other variable name (y and z) remained precisely the same. This method is straightforward and highly recommended for selective, precise renaming operations within the DATA Step flow.

Example 2: Renaming Multiple Variables Simultaneously

When cleaning or preparing large datasets, it is often necessary to rename several variables at once. Fortunately, the syntax for renaming multiple variables is a simple extension of the single-variable method. You continue listing the old_name=new_name pairs within the parentheses of the RENAME option inside the SET statement.

A key syntactical detail to remember is that you do not need to include commas, semicolons, or any other separators between the renaming pairs; a space is sufficient. This clean structure contributes to concise and easily readable SAS code, even when dealing with dozens of variable changes.

The following code demonstrates how to rename both the x variable to new_x and the y variable to new_y in the dataset:

/*rename multiple variables concurrently*/
data new_data_multi;
    set original_data (rename=(x=new_x y=new_y));
run;

/*view the resulting dataset*/
proc print data=new_data_multi;

The resulting dataset, new_data_multi, now reflects the updated names for both variables, illustrating the scalability of the RENAME option within the SET statement. This method is highly flexible and should be utilized whenever two or more variables require explicit renaming within a single DATA Step.

Advanced Renaming: Using PROC SQL and PROC DATASETS

While the SET statement method in the DATA Step is ideal for small, explicit changes, it becomes impractical when you need to rename a large number of variables systematically—for instance, adding a standard prefix or suffix to every variable in the dataset. For these complex, automated tasks, a two-step approach involving PROC SQL and PROC DATASETS is far more efficient.

This advanced technique utilizes PROC SQL to query the SAS metadata dictionary (specifically dictionary.columns) and dynamically generate a string of renaming pairs (e.g., x=_NEWx y=_NEWy z=_NEWz). This string is stored in a macro variable, which is then passed to the RENAME statement within PROC DATASETS. The PROC DATASETS procedure is crucial here because it allows modification of an existing dataset in place (using the MODIFY statement) without the need to recreate the entire dataset, offering significant performance benefits for large files.

Example 3: Add Prefix to All Variables

Suppose you have merged several datasets and need to distinguish the origin of the variables from the original_data source. Adding a common prefix, such as _NEW, to every variable provides immediate clarity. This process involves concatenating the variable name with the desired prefix using the CATS function inside PROC SQL. The result is saved into the macro variable &list.

The WHERE clause in the SQL query ensures we only target variables within our specific dataset (WORK.ORIGINAL_DATA). The subsequent PROC DATASETS block then executes the generated RENAME statement using the macro variable. Note that unlike previous examples, this method alters the original_data dataset directly.

/*define prefix to append to each variable using PROC SQL*/
proc sql noprint;
   select cats(name, '=', '_NEW', name)
          into :list
          separated by ' '
          from dictionary.columns
          where libname = 'WORK' and memname = 'ORIGINAL_DATA';
quit;

/*add prefix to each variable in dataset using PROC DATASETS*/
proc datasets library = work;
   modify original_data;
   rename &list;
quit;

/*view updated dataset*/
proc print data=original_data;

Example 4: Add Suffix to All Variables

Adding a suffix is frequently used when performing transformations or standardizations on existing variables (e.g., transforming score into score_std). By appending a suffix like _NEW to all variables, we quickly denote that these are the modified versions of the data. The logic here is nearly identical to the prefix example, with a slight adjustment to the CATS function call to place the suffix after the original variable name.

The following code shows how to add a suffix of _NEW to all variables in the dataset:

/*define suffix to append to each variable using PROC SQL*/
proc sql noprint;
   select cats(name, '=', name, '_NEW')
          into :list
          separated by ' '
          from dictionary.columns
          where libname = 'WORK' and memname = 'ORIGINAL_DATA';
quit;

/*add suffix to each variable in dataset using PROC DATASETS*/
proc datasets library = work;
   modify original_data;
   rename &list;
quit;

/*view updated dataset*/
proc print data=original_data;

Summary of Renaming Methods

Choosing the appropriate method for renaming variables in SAS depends entirely on the scope and complexity of the task. For renaming one or a few variables while creating a new dataset, utilizing the RENAME option within the SET statement in a DATA Step is the most efficient and safest approach, preserving the original data integrity.

For scenarios requiring bulk renaming, such as applying standardized prefixes or suffixes across numerous variables, the combination of PROC SQL (for dynamic name generation) and PROC DATASETS (for in-place modification) provides the necessary automation and performance benefits. Mastering both techniques ensures that you can handle any variable naming requirement efficiently within the SAS environment.

Related SAS Data Management Tutorials

The following tutorials explain how to perform other common tasks in SAS: