Sarah, This strategy works great for this small dataset, but when I attempt your method with my data set I reach the maximum allowable memory allocation and the operation just stalls and then stops completely before it is finished. Do you know of a way around this?
Thanks On Tue, Mar 10, 2015 at 2:04 PM, Sarah Goslee <sarah.gos...@gmail.com> wrote: > Hi, > > I didn't work through your code, because it looked overly complicated. > Here's a more general approach that does what you appear to want: > > # use dput() to provide reproducible data please! > comAn <- structure(list(animals = c("bird", "bird", "bird", "bird", "bird", > "bird", "dog", "dog", "dog", "dog", "dog", "dog", "cat", "cat", > "cat", "cat"), animalYears = c(1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, > 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L), animalMass = c(29L, 48L, 36L, > 20L, 34L, 34L, 21L, 28L, 25L, 35L, 18L, 11L, 46L, 33L, 48L, 21L > )), .Names = c("animals", "animalYears", "animalMass"), class = > "data.frame", row.names = c("1", > "2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12", "13", > "14", "15", "16")) > > > # add reps to comAn > # assumes comAn is already sorted on animals, animalYears > comAn$reps <- unlist(sapply(rle(do.call("paste", > comAn[,1:2]))$lengths, seq_len)) > > # create full set of combinations > outgrid <- expand.grid(animals=unique(comAn$animals), > animalYears=unique(comAn$animalYears), reps=unique(comAn$reps), > stringsAsFactors=FALSE) > > # combine with comAn > comAn.full <- merge(outgrid, comAn, all.x=TRUE) > > > comAn.full > animals animalYears reps animalMass > 1 bird 1 1 29 > 2 bird 1 2 48 > 3 bird 1 3 36 > 4 bird 2 1 20 > 5 bird 2 2 34 > 6 bird 2 3 34 > 7 cat 1 1 46 > 8 cat 1 2 33 > 9 cat 1 3 48 > 10 cat 2 1 21 > 11 cat 2 2 NA > 12 cat 2 3 NA > 13 dog 1 1 21 > 14 dog 1 2 28 > 15 dog 1 3 25 > 16 dog 2 1 35 > 17 dog 2 2 18 > 18 dog 2 3 11 > > > > On Tue, Mar 10, 2015 at 3:43 PM, Curtis Burkhalter > <curtisburkhal...@gmail.com> wrote: > > Hey everyone, > > > > I've written a function that adds NAs to a dataframe where data is > missing > > and it seems to work great if I only need to run it once, but if I run it > > two times in a row I run into problems. I've created a workable example > to > > explain what I mean and why I would do this. > > > > In my dataframe there are areas where I need to add two rows of NAs (b/c > I > > need to have 3 animal x year combos and for cat in year 2 I only have > one) > > so I thought that I'd just run my code twice using the function in the > code > > below. Everything works great when I run it the first time, but when I > run > > it again it says that the value returned to the list 'x' is of length 0. > I > > don't understand why the function works the first time around and adds an > > NA to the 'animalMass' column, but won't do it again. I've used > > (print(str(dataframe)) to see if there is a change in class or type when > > the function runs through the original dataframe and there is for > > 'animalYears', but I just convert it back before rerunning the function > for > > second time. > > > > Any thoughts on this would be greatly appreciated b/c my actual data > > dataframe I have to input into WinBUGS is 14000x12, so it's not a trivial > > thing to just add in an NA here or there. > > > >>comAn > > animals animalYears animalMass > > 1 bird 1 29 > > 2 bird 1 48 > > 3 bird 1 36 > > 4 bird 2 20 > > 5 bird 2 34 > > 6 bird 2 34 > > 7 dog 1 21 > > 8 dog 1 28 > > 9 dog 1 25 > > 10 dog 2 35 > > 11 dog 2 18 > > 12 dog 2 11 > > 13 cat 1 46 > > 14 cat 1 33 > > 15 cat 1 48 > > 16 cat 2 21 > > > > So every animal has 3 measurements per year, except for the cat in year > two > > which has only 1. I run the code below and get: > > > > #combs defines the different combinations of > > #animals and animalYears > > combs<-paste(comAn$animals,comAn$animalYears,sep=':') > > #counts defines how long the different combinations are > > counts<-ave(1:nrow(comAn),combs,FUN=length) > > #missing defines the combs that have length less than one and puts it in > > #the data frame missing > > missing<-data.frame(vals=combs[counts<2],count=counts[counts<2]) > > > > genRows<-function(dat){ > > vals<-strsplit(dat[1],':')[[1]] > > #not sure why dat[2] is being converted to a string > > newRows<-2-as.numeric(dat[2]) > > newDf<-data.frame(animals=rep(vals[1],newRows), > > animalYears=rep(vals[2],newRows), > > animalMass=rep(NA,newRows)) > > return(newDf) > > } > > > > > > x<-apply(missing,1,genRows) > > comAn=rbind(comAn, > > do.call(rbind,x)) > > > >> comAn > > animals animalYears animalMass > > 1 bird 1 29 > > 2 bird 1 48 > > 3 bird 1 36 > > 4 bird 2 20 > > 5 bird 2 34 > > 6 bird 2 34 > > 7 dog 1 21 > > 8 dog 1 28 > > 9 dog 1 25 > > 10 dog 2 35 > > 11 dog 2 18 > > 12 dog 2 11 > > 13 cat 1 46 > > 14 cat 1 33 > > 15 cat 1 48 > > 16 cat 2 21 > > 17 cat 2 <NA> > > > > So far so good, but then I adjust the code so that it reads (**notice the > > change in the specification in 'missing' to counts<3**): > > > > #combs defines the different combinations of > > #animals and animalYears > > combs<-paste(comAn$animals,comAn$animalYears,sep=':') > > #counts defines how long the different combinations are > > counts<-ave(1:nrow(comAn),combs,FUN=length) > > #missing defines the combs that have length less than one and puts it in > > #the data frame missing > > missing<-data.frame(vals=combs[counts<3],count=counts[counts<3]) > > > > genRows<-function(dat){ > > vals<-strsplit(dat[1],':')[[1]] > > #not sure why dat[2] is being converted to a string > > newRows<-2-as.numeric(dat[2]) > > newDf<-data.frame(animals=rep(vals[1],newRows), > > animalYears=rep(vals[2],newRows), > > animalMass=rep(NA,newRows)) > > return(newDf) > > } > > > > > > x<-apply(missing,1,genRows) > > comAn=rbind(comAn, > > do.call(rbind,x)) > > > > The result for 'x' then reads: > > > >> x > > [[1]] > > [1] animals animalYears animalMass > > <0 rows> (or 0-length row.names) > > > > Any thoughts on why it might be doing this instead of adding an > additional > > row to get the result: > > > >> comAn > > animals animalYears animalMass > > 1 bird 1 29 > > 2 bird 1 48 > > 3 bird 1 36 > > 4 bird 2 20 > > 5 bird 2 34 > > 6 bird 2 34 > > 7 dog 1 21 > > 8 dog 1 28 > > 9 dog 1 25 > > 10 dog 2 35 > > 11 dog 2 18 > > 12 dog 2 11 > > 13 cat 1 46 > > 14 cat 1 33 > > 15 cat 1 48 > > 16 cat 2 21 > > 17 cat 2 <NA> > > 18 cat 2 <NA> > > > > Thanks > > -- > > Curtis Burkhalter > -- Curtis Burkhalter https://sites.google.com/site/curtisburkhalter/ [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see 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.