Remove duplicate column pairs, sort rows based on 2 columns [duplicate]

in the following dataframe I want to keep rows only once if they have duplicate pairs (1 4 and 4 1 are considered the same pair) of Var1 and Var2. I thought of sorting Var1 and Var2 within the row and then remove duplicate rows based on both Var1 and Var2. However, I don't get to my desired result.

This is what my data looks like:

Var1 <- c(1,2,3,4,5,5)
Var2 <- c(4,3,2,1,5,5)
f <- c("blue","green","yellow","red","orange2","grey")
g <- c("blue","green","yellow","red","orange1","grey")
testdata <- data.frame(Var1,Var2,f,g)

I can sort within the rows, however the values of columns f and g should remain untouched, how do I do this?

testdata <- t(apply(testdata, 1, function(x) x[order(x)]))
testdata <- as.data.table(testdata)

Then, I want to remove duplicate rows based on Var1 and Var2

I want to get this as a result:

Var1 Var2 f       g
1    4    blue    blue
2    3    green   green
5    5    orange2 orange1

Thanks for your help!

Solution 1:

In case people are interested in solving this using dplyr:

library(dplyr)
testdata %>% 
   rowwise() %>%
   mutate(key = paste(sort(c(Var1, Var2)), collapse="")) %>%
   distinct(key, .keep_all=T) %>%
   select(-key)

# Source: local data frame [3 x 4]
# Groups: <by row>
# 
# # A tibble: 3 × 4
#    Var1  Var2       f       g
#   <dbl> <dbl>  <fctr>  <fctr>
# 1     1     4    blue    blue
# 2     2     3   green   green
# 3     5     5 orange2 orange1

Solution 2:

Instead of sorting for the whole dataset, sort the 'Var1', 'Var2', and then use duplicated to remove the duplicate rows

testdata[1:2] <- t( apply(testdata[1:2], 1, sort) )
testdata[!duplicated(testdata[1:2]),]
#   Var1 Var2       f       g
#1    1    4    blue    blue
#2    2    3   green   green
#5    5    5 orange2 orange1