Removing the unordered pairs repeated twice in a file in R

Question

I have a file like this in R.

**0 1** 
0   2
**0 3**
0   4
0   5
0   6
0   7
0   8
0   9
0   10
**1 0**
1   11
1   12
1   13  
1   14
1   15
1   16
1   17
1   18         


        

Answer 1

Here's one approach:

First, create a vector of the columns sorted and then pasted together.

x <- apply(mydf, 1, function(x) paste(sort(x), collapse = " "))

Then, use ave to create the counts you are looking for.

mydf$count <- ave(x, x, FUN = length)

Finally, you can use the "x" vector again, this time to detect and remove duplicated values.

mydf[!duplicated(x), ]
#    V1 V2 count
# 1   0  1     2
# 2   0  2     1
# 3   0  3     2
# 4   0  4     1
# 5   0  5     1
# 6   0  6     1
# 7   0  7     1
# 8   0  8     1
# 9   0  9     1
# 10  0 10     1
# 12  1 11     1
# 13  1 12     1
# 14  1 13     1
# 15  1 14     1
# 16  1 15     1
# 17  1 16     1
# 18  1 17     1
# 19  1 18     1
# 20  1 19     1

Answer 2

Here is a way using transform, pmin and pmax to reorder the data by row, and then aggregate to provide a count:

# data
x <- data.frame(a=c(rep(0,10),rep(1,10),3),b=c(1:10,0,11:19,0))

#logic
aggregate(count~a+b,transform(x,a=pmin(a,b), b=pmax(a,b), count=1),sum)
   a  b count
1  0  1     2
2  0  2     1
3  0  3     2
4  0  4     1
5  0  5     1
6  0  6     1
7  0  7     1
8  0  8     1
9  0  9     1
10 0 10     1
11 1 11     1
12 1 12     1
13 1 13     1
14 1 14     1
15 1 15     1
16 1 16     1
17 1 17     1
18 1 18     1
19 1 19     1