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Mark duplicates recursively in data.frame

Given the test dataset,

dat=data.frame(name=c('A','A','B','C','C','C'),val=c(1,1,2,2,3,2)) 

name val
A   1
A   1
B   2
C   2
C   3
C   2

What would be the most efficient way to get this conclusion

name val
A   1
A-1   1
B   2
C   2
C-1   3
C-2   2

So, just mark the duplicates with a custom id. I could think of marking them with a common id with paste(dat[which(duplicated(dat$name)),1],"-1",sep='')

, but that would just put "-1" in front of all duplicates. I want if the item appears a third time, mark it with "-2" etc.

Greetings

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3 answers


Usage make.unique

:



transform(dat,name=make.unique(as.character(name),sep="-"))
  name val
1    A   1
2  A-1   1
3    B   2
4    C   2
5  C-1   3
6  C-2   2
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library(plyr)

ddply( dat, .(name), function(d) {
    d$newname <- paste( d$name, cumsum(duplicated(d$name)), sep="-" )
    d
  })

Result:



  name val newname
1    A   1     A-0
2    A   1     A-1
3    B   2     B-0
4    C   2     C-0
5    C   3     C-1
6    C   2     C-2
+3


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This is not exactly what you asked, but you can try this:

within(dat, {
  Name <- paste(name, as.numeric(ave(as.character(name), 
                                     name, FUN = seq_along)) - 1,
                sep = "-")
  rm(name)
})
#   val Name
# 1   1  A-0
# 2   1  A-1
# 3   2  B-0
# 4   2  C-0
# 5   3  C-1
# 6   2  C-2

Or with a slight modification:

within(dat, {
  name <- as.character(name)
  Name <- as.numeric(ave(name, name, FUN = seq_along)) - 1
  Name <- ifelse(Name == 0, name, paste(name, Name, sep = "-"))
  rm(name)
})
#   val Name
# 1   1    A
# 2   1  A-1
# 3   2    B
# 4   2    C
# 5   3  C-1
# 6   2  C-2
+3


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