从data.frames列表中删除data.frames中特定的重复观测值

Question

I have a list of data.frames that looks like this:

  $`42`
     Val     Replicate Index     
   26.92        R2    42
   26.92        R3    42
   28.68        R1    42
   28.68        R4    42

 $`43`
    Val      Replicate Index
  28.92        R3    43
  29.28        R2    43
  30.11        R1    43
  30.11        R4    43

 $`44`
    Val  Replicate Index
   24.67       R3    44
   24.70       R2    44
   25.70       R1    44
   25.70       R4    44   

 $`45`
    Val  Replicate Index
  30.57       R1    45
  30.57       R4    45
  32.39       R2    45
  32.81       R3    45

What I would like to do is the following: if in the column "Val" there's a duplicated element with respect to R4 in column "Replicate", they both will be removed from column "Val".

For example, in the data.frame named 45 , since 30.57 (R1) is equal to 30.57 (R4), they both will be removed retaining only 32.39 (R2) and 32.81 (R3). So the desired output for data.frame 45 would be:

 $`45`
    Val  Replicate Index
  32.39       R2    45
  32.81       R3    45      

I tried to use:

lapply(mydf, function(x) x[!duplicated(x[c("Val")]), ])    

but unfortunately it removes all duplicated elements in the column "Val", not with respect to the comparison with R4 in column "Replicate".

Answer 1

If this is only related to "R4" values, then

df[!((duplicated(df$Val) |  duplicated(df$Val, fromLast=TRUE)) &
   df$Val[df$Replicate == "R4"]), ]

will keep the non-duplicate observations as well as all non-R4 observations for some data.frame df. Then, to put this into lapply

mynonDupeList <- lapply(myList,
                    function(i) i[!((duplicated(df$Val) | duplicated(i$Val, fromLast=TRUE))
                                  & i$Val[i$Replicate == "R4"]), ]))

should do the trick.