remove duplicate row based only of previous row - r

Question

I'm trying to remove duplicate rows from a data frame, based only on the previous row. The duplicate and unique functions will remove all duplicates, leaving you only with unique rows, which is not what I want.
I've illustrated the problem here with a loop. I need to vectorize this because my actual data set is much to large to use a loop on.
x <- c(1,1,1,1,3,3,3,4)
y <- c(1,1,1,1,3,3,3,4)
z <- c(1,2,1,1,3,2,2,4)
xy <- data.frame(x,y,z)
xy
x y z
1 1 1 1
2 1 1 2
3 1 1 1
4 1 1 1 #this should be removed
5 3 3 3
6 3 3 2
7 3 3 2 #this should be removed
8 4 4 4
# loop that produces desired output
toRemove <- NULL
for (i in 2:nrow(xy)){
test <- as.vector(xy[i,] == xy[i-1,])
if (!(FALSE %in% test)){
toRemove <- c(toRemove, i) #build a vector of rows to remove
}
}
xy[-toRemove,] #exclude rows
x y z
1 1 1 1
2 1 1 2
3 1 1 1
5 3 3 3
6 3 3 2
8 4 4 4
I've tried using dplyr's lag function, but it only works on single columns, when I try to run it over all 3 columns it doesn't work.
ifelse(xy[,1:3] == lag(xy[,1:3],1), NA, xy[,1:3])
Any advice on how to accomplish this?

Answer 1

Looks like we want to remove if the row is same as above:
# make an index, if cols not same as above
ix <- c(TRUE, rowSums(tail(xy, -1) == head(xy, -1)) != ncol(xy))
# filter
xy[ix, ]

Answer 2

Why don't you just iterate the list while keeping track of the previous row to compare it to the next row?
If this is true at some point: remember that row position and remove it from the list then start iterating from the beginning of the list.
Don't delete row while iterating because you will get concurrent modification error.