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.>comAnanimals 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))> comAnanimals 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:> comAnanimals 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 https://sites.google.com/site/curtisburkhalter/ [[alternative HTML version deleted]]
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
<curtisburkhalter at 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
The key to your problem may be that x<-apply(missing,1,genRows) converts 'missing' to a matrix, with the same type for all columns then makes x either a list or a matrix but never a data.frame. Those features of apply may mess up the rest of your calculations. Don't use apply(). Bill Dunlap TIBCO Software wdunlap tibco.com On Tue, Mar 10, 2015 at 12:43 PM, Curtis Burkhalter < curtisburkhalter at 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 > > https://sites.google.com/site/curtisburkhalter/ > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help at 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. >[[alternative HTML version deleted]]
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.goslee at 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 > <curtisburkhalter at 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]]
William, You say not to use apply here, but what would you use in its place? Thanks On Tue, Mar 10, 2015 at 2:13 PM, William Dunlap <wdunlap at tibco.com> wrote:> The key to your problem may be that > x<-apply(missing,1,genRows) > converts 'missing' to a matrix, with the same type for all columns > then makes x either a list or a matrix but never a data.frame. > Those features of apply may mess up the rest of your calculations. > > Don't use apply(). > > > Bill Dunlap > TIBCO Software > wdunlap tibco.com > > On Tue, Mar 10, 2015 at 12:43 PM, Curtis Burkhalter < > curtisburkhalter at 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 >> >> https://sites.google.com/site/curtisburkhalter/ >> >> [[alternative HTML version deleted]] >> >> ______________________________________________ >> R-help at 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. >> > >-- Curtis Burkhalter https://sites.google.com/site/curtisburkhalter/ [[alternative HTML version deleted]]