R enumerate duplicates in a dataframe with unique value

Question

I have a dataframe containing a set of parts and test results. The parts are tested on 3 sites (North Centre and South). Sometimes those parts are re-tested. I want to eventually create some charts that compare the results from the first time that a part was tested with the second (or third, etc.) time that it was tested, e.g. to look at tester repeatability.

As an example, I've come up with the below code. I've explicitly removed the "Experiment" column from the morley data set, as this is the column I'm effectively trying to recreate. The code works, however it seems that there must be a more elegant way to approach this problem. Any thoughts?

Edit - I realise that the example given was overly simplistic for my actual needs (I was trying to generate a reproducible example as easily as possible).

New example:

part<-as.factor(c("A","A","A","B","B","B","A","A","A","C","C","C"))
site<-as.factor(c("N","C","S","C","N","S","N","C","S","N","S","C"))
result<-c(17,20,25,51,50,49,43,45,47,52,51,56)

data<-data.frame(part,site,result)
data$index<-1
repeat {
    if(!anyDuplicated(data[,c("part","site","index")]))
    { break }
    data$index<-ifelse(duplicated(data[,1:2]),data$index+1,data$index)
}
data

      part site result index
1     A    N     17     1
2     A    C     20     1
3     A    S     25     1
4     B    C     51     1
5     B    N     50     1
6     B    S     49     1
7     A    N     43     2
8     A    C     45     2
9     A    S     47     2
10    C    N     52     1
11    C    S     51     1
12    C    C     56     1

Old example:

#Generate a trial data frame from the morley dataset
df<-morley[,c(2,3)]

#Set up an iterative variable
#Create the index column and initialise to 1
df$index<-1

# Loop through the dataframe looking for duplicate pairs of
# Runs and Indices and increment the index if it's a duplicate
repeat {
    if(!anyDuplicated(df[,c(1,3)]))
    { break }
    df$index<-ifelse(duplicated(df[,c(1,3)]),df$index+1,df$index)
}

# Check - The below vector should all be true
df$index==morley$Expt

Answer 1

We may use diff and cumsum on the 'Run' column to get the expected output. In this method, we are not creating a column of 1s i.e 'index' and also assuming that the sequence in 'Run' is ordered as showed in the OP's example.

indx <- cumsum(c(TRUE,diff(df$Run)<0))
identical(indx, morley$Expt)
#[1] TRUE

Or we can use ave

indx2 <- with(df, ave(Run, Run, FUN=seq_along))
identical(indx2, morley$Expt)
#[1] TRUE

Update

Using the new example

with(data, ave(seq_along(part), part, site, FUN=seq_along))
#[1] 1 1 1 1 1 1 2 2 2 1 1 1

Or we can use getanID from library(splitstackshape)

library(splitstackshape)
getanID(data, c('part', 'site'))[]