Fantastic. All of those methods worked, though I did have to first convert my
matrices using the data.matrix command. Thank you for the assistance.
Is there any equally simple way to re-convert the resulting table/matrix to its
original NxN form? I do not see any obvious opposites to the cbind
Hi R-listers,
I'm using R only for a few basic functions but am having difficulty doing
something that *should* be simple. I have an nxn matrix, Q, where Q[i,j] is a
directed value (in this case, oil exports from i to j). Note that
Q[i,j]~=Q[j,i]. I imported column names along with the matrix
There is a slightly surprising way to do this in one step. Here's an
example
tmp - matrix(1:16, 4, 4)
dimnames(tmp) - list(letters[1:4], letters[1:4])
tmp
a b c d
a 1 5 9 13
b 2 6 10 14
c 3 7 11 15
d 4 8 12 16
as.data.frame(as.table(tmp))
Var1 Var2 Freq
1 aa1
2 ba
I think
your.df - as.data.frame( as.table( your.matrix ) )
colnames( your.df ) - c( i, j, Q )
write.table( your.df, file = your.file.name, row.names=FALSE )
will do this.
Chuck
On Thu, 14 Jun 2007, philozine wrote:
Hi R-listers,
I'm using R only for a few basic
