[r] Unique on a dataframe with only selected columns

I have a dataframe with >100 columns, and I would to find the unique rows, by comparing only two of the columns. I'm hoping this is an easy one, but I can't get it working with unique or duplicated myself.

In the below, I would like to unique only using id and id2:

data.frame(id=c(1,1,3),id2=c(1,1,4),somevalue=c("x","y","z"))

id id2 somevalue
1   1         x
1   1         y
3   4         z

I would like to obtain either:

id id2 somevalue
1   1         x
3   4         z

or:

id id2 somevalue
1   1         y
3   4         z

(I have no preference which of the unique rows is kept)

Here are a couple dplyr options that keep non-duplicate rows based on columns id and id2:

library(dplyr)                                        
df %>% distinct(id, id2, .keep_all = TRUE)
df %>% group_by(id, id2) %>% filter(row_number() == 1)
df %>% group_by(id, id2) %>% slice(1)

Using unique():

dat <- data.frame(id=c(1,1,3),id2=c(1,1,4),somevalue=c("x","y","z"))    
dat[row.names(unique(dat[,c("id", "id2")])),]

Minor update in @Joran's code.
Using the code below, you can avoid the ambiguity and only get the unique of two columns:

dat <- data.frame(id=c(1,1,3), id2=c(1,1,4) ,somevalue=c("x","y","z"))    
dat[row.names(unique(dat[,c("id", "id2")])), c("id", "id2")]