Comparing Two Methods for Removing Formats and Informats in SAS: DATA Step vs. PROC DATASETS

Comparing Two Approaches to Removing Formats and Informats in SAS

When working with SAS datasets, there are times when you need to remove formats and informats that have been previously assigned to variables. Two primary approaches can be used for this task:

• Using the DATA Step
• Using the PROC DATASETS Procedure

This article compares and contrasts these two approaches to help you determine which method is most appropriate for your needs.

Approach 1: Using the DATA Step

The DATA step is a versatile and commonly used method for removing formats and informats. By assigning variables to a null format or informat, you can effectively remove these attributes from your dataset.

Example:

data mydata_clean;
    set mydata;
    format _all_;
    informat _all_;
run;

In this example, the mydata dataset is processed in the DATA step, and all formats and informats are removed. The resulting dataset mydata_clean is a new dataset without any formats or informats.

Advantages:

• Flexibility: The DATA step allows you to remove formats and informats from specific variables or all variables in the dataset.
• Control: You can perform additional data manipulation or transformation while removing formats, all within the same DATA step.
• Simplicity: The syntax is straightforward and familiar to most SAS users.

Disadvantages:

• Data Duplication: The DATA step creates a new dataset, which can be inefficient when working with large datasets, as it requires additional storage space.
• Processing Time: For very large datasets, the process of creating a new dataset can be time-consuming.

Approach 2: Using the PROC DATASETS Procedure

The PROC DATASETS procedure provides another method for removing formats and informats. Unlike the DATA step, this procedure can modify the dataset in place, avoiding the need to create a new dataset.

Example:

proc datasets library=work nolist;
    modify mydata;
    format _all_;
    informat _all_;
    quit;

In this example, the dataset mydata is modified directly in the WORK library. All formats and informats are removed from the dataset without creating a new dataset.

Advantages:

• Efficiency: Since the dataset is modified in place, this approach can be more efficient in terms of both processing time and storage space.
• Scalability: PROC DATASETS is well-suited for handling large datasets because it avoids data duplication.
• Batch Processing: The procedure can be easily integrated into larger batch processes where multiple datasets need to be modified.

Disadvantages:

• Limited Control: Unlike the DATA step, PROC DATASETS does not allow for additional data transformations or manipulations during the removal of formats.
• Less Familiarity: Some SAS users may be less familiar with PROC DATASETS, making it slightly less intuitive than the DATA step.

Comparison Summary

Both approaches have their strengths and weaknesses, and the choice between them depends on the specific needs of your task:

• Use the DATA Step if you need to perform additional data manipulation while removing formats, or if you prefer a method that is simple and easy to understand.
• Use PROC DATASETS if you are working with large datasets and want to avoid data duplication, or if you need to modify datasets in place for efficiency.

Conclusion

Removing formats and informats is a common task in SAS, and understanding the advantages and limitations of both the DATA step and PROC DATASETS will help you choose the most appropriate method for your specific situation. By mastering both techniques, you can ensure that your data processing tasks are both efficient and effective.