make a crosstable dataframe symetric-CodePudding

I have a dataframe that looks like this:

         Cluster.y
Cluster.x  1  2  3  4  5  7
        1  0  1  0 12  0  2
        2  4  1  0  6  1  5
        3  0  0  0  2  0  0
        4  6  9  0 23 10  9
        5  1  0  0 15  5  3
        7  5  4  1 18  4  6

It seems easy, but I couldn't find the solution to make it symmetric. My goal is to for example have all occurrences of Cluster 1 and Cluster 7 (= 7 occurrences), appear in both cells they are meeting in. I want to be able to read the dataframe as rows or columns with the same result. Can anyone point me in the right direction?

EDIT: the dput looks like this:

structure(c(0L, 4L, 0L, 6L, 1L, 5L, 1L, 1L, 0L, 9L, 0L, 4L, 0L, 
0L, 0L, 0L, 0L, 1L, 12L, 6L, 2L, 23L, 15L, 18L, 0L, 1L, 0L, 10L, 
5L, 4L, 2L, 5L, 0L, 9L, 3L, 6L), dim = c(6L, 6L), dimnames = list(
    Cluster.x = c("1", "2", "3", "4", "5", "7"), Cluster.y = c("1", 
    "2", "3", "4", "5", "7")), class = c("xtabs", "table"), call = xtabs(formula = ~Cluster.x   
    Cluster.y, data = Example_cluster_7_20XX))

EDIT: the desired output looks like this (only showing [1:3,1:3]):

         Cluster.y
Cluster.x  1  2  3  
        1  0  5  0 
        2  5  1  0 
        3  0  0  0

Notice that clusters 2 and 1 have 5 occurrences together. Before, they had 4 and 1. When I View(df) it looks like this:

    
Cluster.x   Cluster.y   Freq
1            1            0             
2            2            1
1            2            1
2            1            4
etc..

CodePudding user response：

Perhaps this helps i.e. take the sum of the transpose and the matrix

`diag<-`(m1   t(m1), diag(m1))

-output

      Cluster.y
Cluster.x  1  2  3  4  5  7
        1  0  5  0 18  1  7
        2  5  1  0 15  1  9
        3  0  0  0  2  0  1
        4 18 15  2 23 25 27
        5  1  1  0 25  5  7
        7  7  9  1 27  7  6