Inverse diagonal on matrix

Question

So I have 2 dataframes. picture them like so:

 data1 <- data.frame(c(1.2, 1.4, 1.3),
                     c(1.12,1.1, 1.9),
                     c(1.8, 1.1, 1.32))

 data2 <- data.frame(c(0.4, 0.2, 0.3),
                     c(0.1, 0.1, 0.4),
                     c(0.5, 0.7, 0.4))

how can I create a joint matrix that will look like this:

combined.data
> 1.2  1.12  1.80
  1.4 1.10  0.7
  1.3  0.4  0.4

upper left matrix is data1, lower-right is data2. I'm

So far, my code is this and I get what I want but up-side down:

new <- -data1
#new <- new[, rev(colnames(data1))]
# diag(new) <- NA
corel <- data2
#corel <- corel[, rev(colnames(data2))]


new[upper.tri(new)] <-  corel[upper.tri(corel)]

And I need the rows and column order to be intact

Any thoughts?

After using Haboryme's take, I somehow got the results. And I've generated a heatmap to show it. Problem is that in some spaces, the data are overlapping the 2 matrices.

Here's the heatmap

Above the diagonal it needs to be fully red, and below the diagonal, blue.

I've accepted the answer by Haboryme. and the problem was that my data was 32*31. if your matrix is not square it's going to be a mess! I just added 1 dummy column to my dataset and it worked like a charm!

Answer 1

You could do:

data1 <- data.frame(c(1.2, 1.4, 1.3),
                    c(1.12,1.1, 1.9),
                    c(1.8, 1.1, 1.32))

data2 <- data.frame(c(0.4, 0.2, 0.3),
                    c(0.1, 0.1, 0.4),
                    c(0.5, 0.7, 0.4))

combined=as.matrix(data1)
combined[apply(lower.tri( as.matrix(data2)), 1, rev)]  <-as.matrix(data2)[apply(lower.tri( as.matrix(data2)), 1, rev)]

> combined
     c.1.2..1.4..1.3. c.1.12..1.1..1.9. c.1.8..1.1..1.32.
[1,]              1.2              1.12               1.8
[2,]              1.4              1.10               0.7
[3,]              1.3              0.40               0.4