Hi, everyone! I've got an ill-organized raw dataset and I met some troubles while trying to clean it. 1. There are multiple rows for one person and I'd like to combine them into one. It's like     ID       Gender        Age         Var1         Var2         Var3     1            F               .             .                5            10     1            .               25           .                 .              .     1            .                .             6                .              . And the problem is that the missing pattern is not consistent across individuals. That is, for another individual, the data may look like     ID       Gender        Age         Var1         Var2         Var3     1            F              25           6                .               .     1            .                .              .                5              .     1            .                .             .                .             10 So by far what I can do with it is subsetting the data into many small non-missing datasets including ID and another variable, then remerging them by ID. Since there are many variables in the dataset, it is too time-consuming. Is there any simple way or command that can combine the data into one row for one individual? 2. The other scenario is that there are partly duplicated observations, which look like    ID       Gender        Age         Var1         Var2         Var3     1            F               .             .                5            10     1            F              25          6                5            10 I hope to retain the observation with the most complete information and delete the duplicates. The only way I know about eliminating duplicates is using PROC SORT with NODUP options, but it seems that it does not work here. I feel that it can be solved in a similar way as for problem 1, but I don't know how. Thank you! ... View more