How do I find equal columns in R?

Question

Given the following:

a <- c(1,2,3)
b <- c(1,2,3)
c <- c(4,5,6)
A <- cbind(a,b,c)

I want to find which columns in A are equal to for example my vector a.

My first attempt would be:

> which(a==A)
[1] 1 2 3 4 5 6

Which did not do that. (Too be honest I don't even understand what that did) Second attempt was:

a==A
        a    b     c
[1,] TRUE TRUE FALSE
[2,] TRUE TRUE FALSE
[3,] TRUE TRUE FALSE

which definitely is a step in the right direction but it seems extended into a matrix. What I would have preferred is something like just one of the rows. How do I compare a vector to columns and how do I find columns in a matrix that are equal to a vector?

Answer 1

Use identical. That is R's "scalar" comparison operator; it returns a single logical value, not a vector.

apply(A, 2, identical, a)
#    a     b     c 
# TRUE  TRUE FALSE 

If A is a data frame in your real case, you're better off using sapply or vapply because apply coerces it's input to a matrix.

d <- c("a", "b", "c")
B <- data.frame(a, b, c, d)

apply(B, 2, identical, a) # incorrect!
#     a     b     c     d 
# FALSE FALSE FALSE FALSE 

sapply(B, identical, a) # correct
#    a     b     c     d 
# TRUE  TRUE FALSE FALSE

But note that data.frame coerces character inputs to factors unless you ask otherwise:

sapply(B, identical, d) # incorrect
#     a     b     c     d 
# FALSE FALSE FALSE FALSE 

C <- data.frame(a, b, c, d, stringsAsFactors = FALSE)
sapply(C, identical, d) # correct
#     a     b     c     d 
# FALSE FALSE FALSE  TRUE 

Identical is also considerably faster than using all + ==:

library(microbenchmark)

a <- 1:1000
b <- c(1:999, 1001)

microbenchmark(
  all(a == b), 
  identical(a, b))
# Unit: microseconds
#              expr   min    lq median     uq    max
# 1     all(a == b) 8.053 8.149 8.2195 8.3295 17.355
# 2 identical(a, b) 1.082 1.182 1.2675 1.3435  3.635