Hi, I'm a R beginner. I have data of this form:
user_id, brand_id1, brand_id2, ..... for example: 1 , 45 , 32, 45, 23 2 , 34 4, 11, 43, 45 I'm looking for the right procedure to be able to cluster users. I am especially interested to know which functions to use at each step. I am currently able to load the data in a data frame, each row's name being the user id. #extract user brands, ie all collumn except the first user_brands <- userclustering[,-1] # extract user ids, ie the first column user_ids <- userclustering[,1] # set user ids as row name row.names(user_brands) <- user_ids But now I'm stuck replacing the brand ids by a count for each brand the user ordered, all other brand counters being implicitely 0 for that user. Then I'll need to be sure I can use it for clustering (normalising, correct handling of brands absent from a user's list, etc). thanks in advance for your help! Raph [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.