Thanks Patrick. The first option is probably more helpful because in the actual data, month ranges from 10-20 so the second method may be more complicated. This is the final output that I am looking for so that there's only one observation for each unique id.   id months sales_1 sales_2 1 2 100 120 2 1 60 3 2 200 180 4 2 250 220 ... View more

Below are my sample codes. I changed value for the second observation in the base dataset for simplicity. data dataset; input id months; datalines; 1 2 2 1 3 2 4 2 ; run; data sales1; input id sales; datalines; 1 100 2 60 3 200 4 250 ; run; data sales2; input id sales; datalines; 1 120 2 90 3 180 4 220 ; run; data merge; merge dataset (in=a) sales1 (rename=(sales=sales_1) sales2 (rename=(sales=sales_2); by id; If a; run; Data merge doesn’t work. Since id =2 has months (promo period) =1, I don’t want to read sales from sales2. The idea that I have is to create a variable based on value of “months” from the base data and merge sales data based on it (i.e. merge sales1-sales2 for months = 2) ... View more

The main dataset that I share contains promotion information. The months variable refers to the length of the promotion. I want to read merge the main data with sales data. For example, since the length of the promotion for the first record is 2 months, I want to merge that against sales data 1 (sales data in month 1) and sales data 2 (sales data in month 2) with variable obs being the unique id. This would be a simple task if all promotions have the same length. However, the third record has a promotion that lasts 6 months, so I want to read sales data 1, 2, 3, 4, 5, and 6. Is there a way to do it systematically? ... View more