Good Afternoon, I have the following code, but it seems that something must be doing wrong, because it is giving the results I want. The idea is to create segments while the value of Commutation is less than 1000. for example, from the small set of data below
text=" val_user pos v v_star v_end commutation v_source v_destine 1 1 96-96 1173438391 1173438391 0 96 96 3 2 126-126 1172501729 1172501532 197 126 126 3 3 126-35 1174404177 1172501909 1902268 126 35 3 4 35-56 1174404252 1174404221 31 35 56 3 5 56-99 1174404295 1174404295 0 56 99 3 6 99-92 1174404536 1174404535 1 99 92 3 7 92-99 1174404660 1174404658 2 92 99 3 8 99-43 1174405442 1174405442 0 99 43 3 9 43-99 1174405545 1174405544 1 43 99 3 10 99-43 1174405581 1174405581 0 99 43 3 11 43-99 1174405836 1174405836 0 43 99 3 12 99-43 1174405861 1174405861 0 99 43 3 13 43-99 1174405875 1174405875 0 43 99 3 18 101-113 1174410215 1174410214 1 101 113 3 19 113-36 1174410261 1174410261 0 113 36 3 20 36-60 1174410268 1174410268 0 36 60 3 21 60-101 1174660357 1174411020 249337 60 101 3 22 101-191 1174666205 1174662119 4086 101 191 3 23 191-196 1174666278 1174666265 13 191 196 3 24 196-9 1174666398 1174666366 32 196 9 3 25 9-101 1175154139 1174667144 486995 9 101 3 26 101-37 1175160182 1175159734 448 101 37 3 27 37-55 1175160256 1175160257 -1 37 55 4 1 11-11 1216304836 1216304127 709 11 11 4 2 11-11 1216370154 1216312995 57159 11 11 4 3 11-11 1216373234 1216372799 435 11 11 4 4 11-11 1216373974 1216373373 601 11 11 4 5 11-11 1216382659 1216379277 3382 11 11 4 6 11-11 1216397081 1216395201 1880 11 11 4 7 11-11 1216397339 1216397131 208 11 11 4 8 11-11 1216630649 1216399235 231414 11 11 4 9 11-11 1216637080 1216631541 5539 11 11 4 10 11-11 1216646563 1216640763 5800 11 11 4 11 11-11 1216656338 1216651635 4703 11 11 " df1 <-read.table(textConnection(text), header=TRUE) inx <- df1$commutation > 1000 comm1000 <- cumsum(inx) result <- split(df1[!inx, ], list(comm1000[!inx], df1$v_source[!inx], df1$v_destine[!inx])) result <- sapply(result, function(x) c(x$val_user[1], x$v_source[1], x$v_destine[1], nrow(x), mean(x$comm))) result <- na.exclude(t(result)) rownames(result) <- 1:nrow(result) colnames(result) <- c("user", "v_source", "v_destine", "count", "average") attr(result, "na.action") <- NULL attr(result, "class") <- NULL results_user<-data.frame(result) View(results_user) This give: user v_source v_destine count Min Max average but the results I want: user v_source v_destine count Min Max average 1 96 96 1 0 0 0.0000000 3 126 126 1 197 197 197.0000000 3 35 56 1 31 31 31.0000000 …. I think there is a problem in the order of the different blocks, I don’t understand, how is that data are organized. The idea is to keep the organization of the file near the original. Thanks -- View this message in context: http://r.789695.n4.nabble.com/Order-sapply-tp4537496p4537496.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ 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.