Dear SAS community, I got stuck with the following question, and unfortunately I was not able to find any kind of solution up to now: I have two datasets. The first one contains a unique ID and a date variable of the day when an event happened (=an accident). E.g.; ID ACCIDENT_DATE 1 2020/11/05 2 2018/01/20 3 2022/07/10 Dataset two contains multiple rows of the ID variable (many of them not in dataset one), a financial transaction date, and the amount of money spend for a medical service, e.g.: ID TRANSACTION_DATE MONEY_VALUE 1 2020/11/08 100 1 2020/11/20 500 1 2020/12/08 250 1 2021/01/08 600 1 2021/11/02 400 2 2018/01/22 500 2 2018/04/01 100 2 2018/08/11 900 3 2022/07/14 1000 3 2022/08/23 300 3 2022/10/10 200 3 2022/11/02 800 3 2023/01/11 500 3 2022/02/22 200 Now, the task would be to join dataset two on dataset one, by summing up the amount of money for different time intervals, meaning e.g. money spend up to 30 days after the accident date, 60 days after the accident, and so on... then saving the results into new variables. Therefore, the output should look like this: ID ACCIDENT_DATE COSTS_UNTIL_30_DAYS COSTS_UNTIL_90_DAYS COSTS_UNTIL_180_MONTHS COSTS_UNTIL_360_MONTHS 1 2020/11/05 ??? ??? ??? ??? 2 2018/01/20 ??? ??? ??? ??? 3 2022/07/10 ??? ??? ??? ??? This is the "easy" example. It would be perfectly, if it would be also possible to take additionally different types of transactions into account, while summing up the costs, e.g.: Dataset two: ID TRANSACTION_DATE MONEY_VALUE TRANSACTION_TYPE 1 2020/11/08 100 A 1 2020/11/20 500 B 1 2020/12/08 250 A 1 2021/01/08 600 C 1 2021/11/02 400 A [...] with the result ID ACCIDENT_DATE A_COSTS_UNTIL_30_DAYS A_COSTS_UNTIL_90_DAYS [...] B_COSTS_UNTIL_30_DAYS B_COSTS_UNTIL_90_DAYS 1 2020/11/05 ??? ??? [...] ??? ??? 2 2018/01/20 ??? ??? [...] ??? ??? 3 2022/07/10 ??? ??? [...] ??? ??? Can anyone help? I would be very happy and grateful for any kind of hint or solution 😊 Best regrads Lars
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