Hey Tom,
This solution works great, but if I try to then insert it in my function
that I've displayed above and apply it to my split dataframe I get the
error message:
Error in `[.default`(xj, i) : invalid subscript type 'list'
The reason why I need to try and get this to work within the function is
that I'm trying to apply it to a much larger dataframe
(nrow=12000,ncol=14). The actual data I'm working with consists of a
sampling year, a site, and a bunch of response variables. For each sampling
year by site combination I have 3 within year sampling occasions. For the
sampling year by site combinations that don't have 3 sampling events I need
to fill in the missing occasions with the NAs.
Can you see why I might be getting this error message?
Thanks
On Fri, Mar 6, 2015 at 1:48 PM, Tom Wright <t...@maladmin.com> wrote:
> If all you want is to add a row of na's could you just do something
> like:
>
> nExpectedRows<-length(unique(animals)) * length(unique(animalYears)) * 2
>
> newDf<-data.frame(animals=rep(NA,nExpectedRows-nrow(comAn)),
> animalYears=rep(NA,nExpectedRows-nrow(comAn)),
> animalMass=rep(NA,nExpectedRows-nrow(comAn)))
>
> comAn = rbind(comAn,newDf)
>
>
>
> On Thu, 2015-03-05 at 13:41 -0700, Curtis Burkhalter wrote:
> > Hello everyone,
> >
> > I'm having a problem with a function that I wrote that is supposed to
> add a
> > row to dataframe based upon a conditional statement. To explain I've used
> > an example below:
> >
> > #create data frame
> > animals=c("bird","dog","cat")
> > animals=rep(animals,each=4)
> > animals=animals[1:11]
> > animalYears=c(1,1,2,2,1,1,2,2,1,1,2)
> > animalMass=round(runif(11,min=10,max=50),0)
> >
> > comAn=as.data.frame(cbind(animals,animalYears,animalMass))
> > comAn
> >
> > * animals* *animalYears* *animalMass*
> > 1 bird 1 30
> > 2 bird 1 32
> > 3 bird 2 27
> > 4 bird 2 16
> > 5 dog 1 22
> > 6 dog 1 25
> > 7 dog 2 41
> > 8 dog 2 22
> > 9 cat 1 30
> > 10 cat 1 37
> > 11 cat 2 49
> >
> > We can see here that for every type of animal I have two years of mass
> > measurements, except for the cat in year 2. What I want to do is add an
> > additional row to the end of the dataframe that consists strictly of NAs
> > and then I can substitute those out later.
> >
> > So what I first did was split the 'comAn' dataframe into the different
> > Animal by Year combos.
> >
> > #This line splits 'com_An' into a list ordered by the Animal by Year
> combos
> > comAn_split=split(comAn, paste(comAn$animals,comAn$animalYear))
> >
> > Then I wrote the function that identifies whether a particular Animal by
> > Year combo is less than two rows in length and if so it should add
> another
> > row that consists only of NAs using the vector 'NAs':
> >
> > #This function identifies the length of each Animal by Year combo and
> then
> > #uses the rbind function built in R to add a row
> > #to each animal by year combo if they have less than 2 samples
> >
> > addNA <- function(comAn) {
> > NAs=c(NA,NA,NA)
> > ind <- seq_len(nrow(comAn))
> > comAn[ifelse(length(ind)<2,rbind(NAs),length(ind)),]
> > }
> >
> > #This applies the function addNs to the animals data organized in list
> > format
> > addedNAcomAn <- do.call(rbind, lapply(comAn_split, addNA))
> > addedNAcomAn
> >
> > When I apply the function to the list of the different Animal by Year
> > combos this is what I get:
> > animals animalYears animalMass
> > bird 1 bird 1 23
> > bird 2 bird 2 50
> > cat 1 cat 1 15
> > cat 2 <NA> <NA> <NA>
> > dog 1 dog 1 23
> > dog 2 dog 2 38
> >
> > What I expect is this:
> >
> > animals animalYears animalMass
> > 1 bird 1 41
> > 2 bird 1 23
> > 3 bird 2 23
> > 4 bird 2 50
> > 5 dog 1 49
> > 6 dog 1 23
> > 7 dog 2 13
> > 8 dog 2 38
> > 9 cat 1 42
> > 10 cat 1 15
> > 11 cat 2 33
> > 12 NA NA NA
> >
> > Am I conditioning improperly within the function or am I missing
> something
> > else. Any help would be greatly appreciated.
> >
> > Best
> >
>
>
>
--
Curtis Burkhalter
https://sites.google.com/site/curtisburkhalter/
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