Hello
I need to use the below data to count the number of non-missing IDs. The goal is to reach the percentage completion for each region:
Location | Store | Case_ID |
East | A | Case1 |
East | A | Case1 |
West | B | . |
South | X | Case2 |
South | X | . |
South | Y | Case3 |
South | Y | Case3 |
South | Z | Case4 |
West | A | Case5 |
Requested results:
Location | Number UNIQUE Stores | Non-Missing IDs for these stores | % completion IDs |
East | 1 | 1 | 100% |
West | 2 | 1 | 50% |
South | 3 | 3 | 100% |
Thank you everyone.
You can obtain that with a proc sql:
proc sql;
create table want as
select Location,
count(distinct Store) as unique_stores,
count(distinct Case_ID) as not_missing_id,
count(distinct Case_ID)/count(distinct Store) as cmplt_id format=percent7.
from have
group by Location;
quit;
Hi. Thanks, but this code does not provide the results I am looking for. It provides instead this results as 1, 1, 1
I am looking for
1. the total number of stores in each region
2. For those stores, how many of them have completed (non missing) IDs?
i ran that code and this is the output table
in the Case_id column do you have dots or missing values (i.e. space blank)?
Yes. Many.
could you try this code and share the output:
data have;
set have;
if case_id="." then case_id="";
run;
proc sql;create table want as
select Location,
count(distinct Store) as unique_stores,
count(distinct Case_ID) as not_missing_id,
count(distinct Case_ID)/count(distinct Store) as cmplt_id format=percent7.
from have
group by Location;
quit;
Are you ready for the spotlight? We're accepting content ideas for SAS Innovate 2025 to be held May 6-9 in Orlando, FL. The call is open until September 25. Read more here about why you should contribute and what is in it for you!
Learn how use the CAT functions in SAS to join values from multiple variables into a single value.
Find more tutorials on the SAS Users YouTube channel.