Suppose your correlation matrix is called cc. One way
to do what you want is
result = cbind(as.vector(row(cc)),as.vector(col(cc)),as.vector(cc))
result = result[result[,1] != result[,2],]
- Phil Spector
Statistical Computing Facility
Department of Statistics
UC Berkeley
spec...@stat.berkeley.edu
On Fri, 28 Jan 2011, KumaraGuru wrote:
While listing it like that is it possible to remove the rows that has same row
and col numbers?
Like..
1 1 x
2 2 x2
....
Regards,
Kumaraguru
On Jan 28, 2011, at 9:23 AM, Petr PIKAL <petr.pi...@precheza.cz> wrote:
Hi
KumaraGuru <kumaragur...@gmail.com> napsal dne 28.01.2011 17:03:50:
I want to melt the cor matrix and form a 3 col matrix with row# col# and
cor.
Well, in that case it will be probably better to transform it to data
frame and use melt. Or you can drop dimensions of this matrix and generate
proper sequences of row and column numbers. Try it with smaller matrix.
Row names does not matter
x<-matrix(1:12, 4,4)
row.names(x)<-letters[1:4]
colnames(x)<-letters[1:4]
x
a b c d
a 1 5 9 1
b 2 6 10 2
c 3 7 11 3
d 4 8 12 4
dim(x)<-NULL
x
[1] 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4
cbind(rep(1:4, 4), rep(1:4, each=4), x)
x
[1,] 1 1 1
[2,] 2 1 2
[3,] 3 1 3
[4,] 4 1 4
[5,] 1 2 5
[6,] 2 2 6
[7,] 3 2 7
[8,] 4 2 8
[9,] 1 3 9
[10,] 2 3 10
[11,] 3 3 11
[12,] 4 3 12
[13,] 1 4 1
[14,] 2 4 2
[15,] 3 4 3
[16,] 4 4 4
Regards
Petr
This I m using to draw a graph.
Regards,
Kumaraguru
On Jan 28, 2011, at 6:47 AM, Petr PIKAL <petr.pi...@precheza.cz> wrote:
Hi
r-help-boun...@r-project.org napsal dne 28.01.2011 09:52:05:
What makes matrix to print V1, V2 as the row and col indices instead
of
numbers??
cdata = read.table("ramesh.txt") #cdata is read from a file.
c1 = cor(cdata)
I am printing c1 below. I need only numbers. I dont need V1,
V2...what
should I do in this case??
http://r.789695.n4.nabble.com/file/n3243980/ramesh.txt ramesh.txt
V1 V2 V3 V4 V5 V6 V7
V1 1.0000000 0.9471591 0.9191233 0.9403129 0.9689690 0.9621362
0.9529811
V2 0.9471591 1.0000000 0.8888108 0.9108174 0.9703906 0.9425248
0.9294308
V3 0.9191233 0.8888108 1.0000000 0.8788107 0.9077245 0.9078971
0.8965331
V4 0.9403129 0.9108174 0.8788107 1.0000000 0.9477058 0.9017977
0.8646251
V5 0.9689690 0.9703906 0.9077245 0.9477058 1.0000000 0.9531459
0.9162016
V6 0.9621362 0.9425248 0.9078971 0.9017977 0.9531459 1.0000000
0.9447130
V7 0.9529811 0.9294308 0.8965331 0.8646251 0.9162016 0.9447130
1.0000000
V8 0.9167526 0.9395067 0.8491496 0.8942693 0.9460702 0.9304229
0.8505287
V9 0.9512951 0.9598302 0.8666839 0.9465725 0.9645178 0.9486105
0.8979753
V10 0.9551633 0.9040160 0.9180022 0.9429816 0.9448644 0.9220875
0.9075537
Vn are names of columns which R gave to your matrix when you read it
as a
data frame. And cor just makes a matrix of pairwise corelation
coefficients from this data frame conveniently named from this data
frame.
If you do not want those names just unname it.
c1 = unname(cor(cdata))
But I wonder why you dislike those names which are, well, just names.
Regards
Petr
--
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row-col-indices-instead-of-numbers-tp3243980p3243980.html
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