Re: [R] Order sapply
Good Afternoon, I get it, my question was really how the data were organized, I thought I was doing something wrong. Thanks -- View this message in context: http://r.789695.n4.nabble.com/Order-sapply-tp4537496p4542518.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.
Re: [R] Order sapply
Hello, 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 I believe that code was mine, from an answer to a post of yours. 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. Maybe that's not possible. The order is given by 'split'. But you can make it near the original, if you put comm1000 last in the split list. # This line should be changed # result - split(df1[!inx, ], list(comm1000[!inx], df1$v_source[!inx], df1$v_destine[!inx])) # to this one. result - split(df1[!inx, ], list(df1$v_source[!inx], df1$v_destine[!inx], comm1000[!inx])) You can also use Sarah's suggestion and have the entire results data frame ordered inx_ord - with(results_user, order(user, v_source, v_destine)) results_user[inx_ord, ] Hope this helps, Rui Barradas -- View this message in context: http://r.789695.n4.nabble.com/Order-sapply-tp4537496p4539748.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.
Re: [R] Order sapply
On Fri, Apr 6, 2012 at 10:27 AM, MSousa ricardosousa2...@clix.pt wrote: Good Afternoon, I have the following code, but it seems that something must be doing wrong, because it is giving the results I want. Didn't someone else have that problem just a few weeks ago? :-P Michael 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 0.000 3 126 126 1 197 197 197.000 3 35 56 1 31 31 31.000 …. 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. __ 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.
Re: [R] Order sapply
On Fri, Apr 6, 2012 at 10:27 AM, MSousa ricardosousa2...@clix.pt wrote: Good Afternoon, I have the following code, but it seems that something must be doing wrong, because it is giving the results I want. Assuming you don't really mean that, you can use order() and/or sort() to put it back into order by val_user and pos. If you provide reproducible data with dput(), someone might be inspired to write you the code to do so. Sarah 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 0.000 3 126 126 1 197 197 197.000 3 35 56 1 31 31 31.000 …. 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 -- Sarah Goslee http://www.functionaldiversity.org __ 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.
