On Jan 30, 2010, at 2:11 PM, Juliet Hannah wrote:
Hi Group,
Consider a data frame like this:
mylabel1 <- rep(c("A","B","C"),each=3)
mylabel2 <- rep(c("A","B","C"),3)
corrs <- c(1,.8,.7,.8,1,.7,.7,.7,1)
myData <- data.frame(mylabel1,mylabel2,corrs)
myData
mylabel1 mylabel2 corrs
1 A A 1.0
2 A B 0.8
3 A C 0.7
4 B A 0.8
5 B B 1.0
6 B C 0.7
7 C A 0.7
8 C B 0.7
9 C C 1.0
I would like to find a general way to get this matrix from the above
dataframe.
corrmat <- matrix(corrs,nrow=3,byrow=TRUE)
row.names(corrmat) <- c("A","B","C")
colnames(corrmat) <- c("A","B","C")
corrmat
A B C
A 1.0 0.8 0.7
B 0.8 1.0 0.7
C 0.7 0.7 1.0
The solution I have is the one above where I rearrange the data so
that I can just use matrix() on one
of the columns. I am looking for a solution in which I don't have to
do this.
Possibilities:
>> reshape(myData, timevar="mylabel2", direction="wide",
v.names="corrs", idvar="mylabel1")[,2:4]
corrs.A corrs.B corrs.C
1 1.0 0.8 0.7
4 0.8 1.0 0.7
7 0.7 0.7 1.0
#---------
> unstack(myData, corrs ~ mylabel2 )
A B C
1 1.0 0.8 0.7
2 0.8 1.0 0.7
3 0.7 0.7 1.0
#-------
library(reshape)
mdat <- melt(myData)
cast(mdat, mylabel1 ~ mylabel2 )
mylabel1 A B C
1 A 1.0 0.8 0.7
2 B 0.8 1.0 0.7
3 C 0.7 0.7 1.0
-- .
David Winsemius, MD
Heritage Laboratories
West Hartford, CT
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