How to Address PROC COMPARE Reporting Same Values as Different in SAS

Working with large datasets in SAS often requires comparing data between two tables. The PROC COMPARE procedure is an essential tool for this task, but sometimes it reports values as different even when they appear to be identical. This issue can arise from various causes, such as numeric precision differences, rounding issues, or formatting inconsistencies. In this post, we will explore common causes of this issue and how to resolve them.

1. Numeric Precision Issues

SAS stores numeric values using floating-point precision, which can lead to small differences that aren't immediately visible. These differences may cause PROC COMPARE to report discrepancies even though the values seem the same.

Solution: Use the CRITERION or FUZZ option to define an acceptable tolerance for differences.

proc compare base=dataset1 compare=dataset2 criterion=0.00001;
run;
    

2. Rounding Differences

If values have been rounded differently in two datasets, PROC COMPARE may detect them as different. For example, one dataset may round to two decimal places, while the other doesn't.

Solution: Apply consistent rounding to both datasets before comparison.

data dataset1_rounded;
    set dataset1;
    value = round(value, 0.01); /* Round to two decimal places */
run;

data dataset2_rounded;
    set dataset2;
    value = round(value, 0.01); /* Same rounding precision */
run;

proc compare base=dataset1_rounded compare=dataset2_rounded;
run;
    

3. Formatting Differences

Sometimes, two values are the same but have different formats applied, leading to a perceived difference by PROC COMPARE.

Solution: Use the NOFORMAT option to ignore formatting in the comparison.

proc compare base=dataset1 compare=dataset2 noformat;
run;
    

4. Character Value Differences (Case Sensitivity and Whitespace)

SAS is case-sensitive when comparing character variables. Extra whitespace at the end of strings can also cause PROC COMPARE to flag a difference.

Solution: Standardize case and remove any unnecessary spaces using the COMPRESS or UPCASE functions.

data dataset1_clean;
    set dataset1;
    char_var = compress(upcase(char_var));
run;

data dataset2_clean;
    set dataset2;
    char_var = compress(upcase(char_var));
run;

proc compare base=dataset1_clean compare=dataset2_clean;
run;
    

5. Handling Different Variable Lengths

Character variables with different lengths may also trigger discrepancies in the comparison.

Solution: Ensure that corresponding variables have the same length in both datasets using LENGTH statements.

Conclusion

By addressing issues related to numeric precision, rounding, formatting, and character data, you can reduce or eliminate discrepancies reported by PROC COMPARE in SAS. These solutions ensure more accurate and meaningful comparisons between datasets.

Feel free to leave a comment if you have additional tips or if you’ve encountered other challenges with PROC COMPARE in SAS!