Excluding Variables in PROC COMPARE
Using the DROP
Dataset Option
When comparing two datasets using PROC COMPARE
in SAS, there may be cases where you want to exclude specific variables from the comparison. One efficient way to do this is by using the DROP
dataset option. This option allows you to remove certain variables from consideration during the comparison process.
Using the DROP
Dataset Option in PROC COMPARE
The DROP
dataset option is applied directly to the dataset references in the BASE
and COMPARE
options of PROC COMPARE
. When you use DROP
, the specified variables are excluded from the comparison.
Here is the syntax for using the DROP
option:
proc compare base=dataset1(drop=var_to_exclude)
compare=dataset2(drop=var_to_exclude);
run;
In this example, var_to_exclude
is the name of the variable you want to exclude from both datasets (dataset1
and dataset2
) before the comparison is made.
Example: Excluding a Variable from the Comparison
Let's say you have two datasets, sales_2023
and sales_2024
, and you want to compare them, but you want to exclude a variable called region
from the comparison. Here is how you can do that:
proc compare base=sales_2023(drop=region)
compare=sales_2024(drop=region);
run;
This code ensures that the variable region
will not be included in the comparison, while all other variables in the two datasets will be compared.
Excluding Multiple Variables
You can also exclude multiple variables by listing them inside the DROP
option, separated by spaces:
proc compare base=sales_2023(drop=region quarter)
compare=sales_2024(drop=region quarter);
run;
In this case, both region
and quarter
will be excluded from the comparison.
Conclusion
The DROP
dataset option is a powerful and simple tool for excluding variables from comparison in PROC COMPARE
. It provides flexibility by allowing you to exclude one or more variables without needing to manually specify which variables should be included in the comparison.
By leveraging the DROP
option, you can ensure that only relevant variables are considered when comparing datasets, making your SAS programming more efficient and focused.