Printing only certain panels in R lattice - r

Question

I am plotting a quantile-quantile plot for a certain data that I have. I would like to print only certain panels that satisfy a condition that I put in for panel.qq(x,y,...).
Let me give you an example. The following is my code,
qq(y ~ x|cond,data=test.df,panel=function(x,y,subscripts,...){
if(length(unique(test.df[subscripts,2])) > 3 ){panel.qq(x,y,subscripts,...})})
Here y is the factor and x is the variable that will be plotted on X and y axis. Cond is the conditioning variable. What I would like is, only those panels be printed that pass the condition in the panel function, which is
if(length(unique(test.df[subscripts,2])) > 3).
I hope this information helps. Thanks in advance.
Added Sample data,
y x cond
1 1 6 125
2 2 5 125
3 1 5 125
4 2 6 125
5 1 3 125
6 2 8 125
7 1 8 125
8 2 3 125
9 1 5 125
10 2 6 125
11 1 5 124
12 2 6 124
13 1 6 124
14 2 5 124
15 1 5 124
16 2 6 124
17 1 4 124
18 2 7 124
19 1 0 123
20 2 11 123
21 1 0 123
22 2 11 123
23 1 0 123
24 2 11 123
25 1 0 123
26 2 11 123
27 1 0 123
28 2 2 123
So this is the sample data. What I would like is to not have a panel for 123 as the number of unique values for 123 is 3, while for others its 4. Thanks again.

Answer 1

Yeah, I think it is a subset problem, not a lattice one. You don't include an example, but it looks like you want to keep only rows where there are more than 3 rows for each value of whatever is in column 2 of your data frame. If so, here is a data.table solution.
library(data.table)
test.dt <- as.data.table(test.df)
test.dt.subset <- test.dt[,N:=.N,by=c2][N>3]
Where c2 is that variable in the second column. The last line of code first adds a variable, N, for the count of rows (.N) for each value of c2, then subsets for N>3.
UPDATE: And since a data table is also a data frame, you can use test.dt.subset directly as the data source in the call to qq (or other lattice function).
UPDATE 2: Here is one way to do the same thing without data.table:
d <- data.frame(x=1:15,y=1:15%%2, # example data frame
c2=c(1,2,2,3,3,3,4,4,4,4,5,5,5,5,5))
d$N <- 1 # create a column for count
split(d$N,d$c2) <- lapply(split(d$x,d$c2),length) # populate with count
d
d[d$N>3,] # subset

Answer 2

I did something very similar to DaveTurek.
My sample dataframe above is test.df
test.df.list <- split(test.df,test.df$cond,drop=F)
final.test.df <- do.call("rbind",lapply(test.df.list,function(r){
if(length(unique(r$x)) > 3){r}})
So, here I am breaking the test.df as a list of data.frames by the conditioning variable. Next, in the lapply I am checking the number of unique values in each of subset dataframe. If this number is greater than 3 then the dataframe is given /taken back if not it is ignored. Next, a do.call to bind all the dfs back to one big df to run the quantile quantile plot on it.
In case anyone wants to know the qq function call after getting the specific data. then it is,
trellis.device(postscript,file="test.ps",color=F,horizontal=T,paper='legal')
qq(y ~ x|cond,data=final.test.df,layout=c(1,1),pch=".",cex=3)
dev.off()
Hope this helps.