I am attempting to find/discard rows based on their similarity in column values and have the following example code:
vec1 <- c("B","D","E","NA")
vec2 <- c("B","D","E","NA")
vec3 <- c("B","C","E","NA")
vec4 <- c("B","D","E","NA")
vec5 <- c("B","NA","E","E")
vec6 <- c("B","NA","NA","NA")
mat1 <- cbind(vec1,vec2,vec3,vec4,vec5,vec6)
mat1
vec1 vec2 vec3 vec4 vec5 vec6
[1,] "B" "B" "B" "B" "B" "B"
[2,] "D" "D" "C" "D" "NA" "NA"
[3,] "E" "E" "E" "E" "E" "NA"
[4,] "NA" "NA" "NA" "NA" "E" "NA"
rows = apply(mat1, 1, function(i) length(unique(i)) > 1 )
mat2 <- mat1[rows, ]
vec1 vec2 vec3 vec4 vec5 vec6
[1,] "D" "D" "C" "D" "NA" "NA"
[2,] "E" "E" "E" "E" "E" "NA
[3,] "NA" "NA" "NA" "NA" "E" "NA"
How may I change the code above to achieve this? In the help file for unique it suggests there is an incomparables argument, is this implemented and can it be used? I don't necessarily wish to remove the NA's just ignore them.
From comment above
rows = apply(mat1, 1, function(i) length(unique(i[!(i=="NA")]))>1)