R Loop with conditions - r

Question

I have a series of repeated IDs that I would like to assign to groups with fix size. The subject IDs repeat with different frequencies for example:
# Example Data
ID = c(101,102,103,104)
Repeats = c(2,3,1,3)
Data = data.frame(ID,Repeats)
> head(Data)
ID Repeats
1 101 2
2 102 3
3 103 1
4 104 3
I would like the same repeated ID to stay within the same group. However, each group has a fixed capacity (say 3 only). For example, in my desired output matrix each group can only accommodate 3 IDs:
# Create empty data frame for group annotation
# Add 3 rows in order to have more space for IDs
# Some groups will have NAs due to keeping IDs together (I'm OK with that)
Target = data.frame(matrix(NA,nrow=(sum(Data$Repeats)+3),
ncol=dim(Data)[2]))
names(Target)<-c("ID","Group")
Target$Group<-rep(1:3)
Target$Group<-sort(Target$Group)
> head(Target)
ID Group
1 NA 1
2 NA 1
3 NA 1
4 NA 1
5 NA 2
6 NA 2
I can loop each ID to my Target data frame but this does not guarantee that repeated IDs will stay together in the same group:
# Loop repeated IDs the groups
IDs.repeat = rep(Data$ID, times=Data$Repeats)
# loop IDs to Targets to assign IDs to groups
for (i in 1:length(IDs.repeat))
{
Target$ID[i]<-IDs.repeat[i]
}
In my example in the loop above I get the same ID (102) across two different groups (1 and 2), I would like to avoid this!:
> head(Target)
ID Group
1 101 1
2 101 1
3 102 1
4 102 1
5 102 2
6 103 2
Instead I want the output to look the code to put NA if there is no space for that ID in that group.
> head(Target)
ID Group
1 101 1
2 101 1
3 NA 1
4 NA 1
5 102 2
6 102 2
Anyone has a solution for IDs to stay within the same group if there is sufficient space after assigning ID i?
I think that I need a loop and count NAs within that group and see if the NAs>= to the length of that unique ID. However, I don't know how to implement this simultaneously. Maybe nesting another loop for the j group?
Any help with the loop will be appreciated immensely!

Answer 1

Here's one solution,
## This is the data.frame I'll try to match
target <- data.frame(
ID = c(
rep(101, 2),
rep(102, 3),
rep(103, 1),
rep(104, 3)),
Group = c(
rep(1L, 6), # "L", like 1L makes it an int type rather than numeric
rep(2L, 3)
)
)
print(target)
## Your example data
ID = c(101,102,103,104)
Repeats = c(2,3,1,3)
Data = data.frame(ID,Repeats)
head(Data)
ids_to_group <- 3 # the number of ids per group is specified here.
Data$Group <- sort(
rep(1:ceiling(length(Data$ID) / ids_to_group),
ids_to_group))[1:length(Data$ID)]
# The do.call(rbind, lapply(x = a series, FUN = function(x) { }))
# pattern is a really useful way to stack data.frames
# lapply is basically a fancy for-loop check it out by sending
# ?lapply to the console (to view the help page).
output <- do.call(
rbind,
lapply(unique(Data$ID), FUN = function(ids) {
print(paste(ids, "done.")) # I like to put print statements to follow along
obs <- Data[Data$ID == ids, ]
data.frame(ID = rep(obs$ID, obs$Repeats))
})
)
output <- merge(output, Data[,c("ID", "Group")], by = "ID")
identical(target, output) # returns true if they're equivalent
# For example inspect each with:
str(target)
str(output)