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 ______________________________________________ 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.