##I have also tried the reshape package
library(reshape)
mm <- melt(df, id=c("date_", "id"))
mm1 <- cast(mm, date_~id)
aba <- mm1[,-1]
final <- as.matrix(aba)
colnames(final) <- df$id
rownames(final) <- mm1$date_
final
##Again it works perfectly here, but when I get to my real dataset, I get a
"Cannot allocate vector of size 27.4 MB" error
It seems that the main problem is memory size. Is there an efficient way to
do this?
colnames(df)<-c("date_","id","totret")
library(reshape)
mm <- melt(df, id=c("date_", "id"))
mm1 <- cast(mm, date_~id)
aba <- mm1[,2:2365]
final <- as.matrix(aba)
colnames(final) <- Returns.nodup$id
rownames(final) <- mm1$date_
Jeff08 wrote:
>
> df<-data.frame()
> df[1:8,1]<-c("1","2","5","3","1","4","3","5") ##identifier 1
> df[1:8,2]<-c("c","a","b","c","a","b","b","a") ##identifier 2
> df[1:8,3]<-c(1,2,3,4,5,6,7,8) ##value
>
> ##Each unique combination of identifiers identifies a datapoint
>
>
> ##What I am trying to do is create a matrix with values of the third
> column
> ## and rows/column names of the 1st and 2nd column. As you can see, a lot
> of
> ## combinations of identifier1 and identifier 2, for example (1,b), do not
> ## have a value attached to them, and I would like those values in the
> matrix
> ## to be NA.
>
> ##From the ecodist, I have tried crosstab(df[,1],df[,2],df[,3])
> ##It works perfectly in this case, but when I use it on my actual
> data.frame
> ##It ALWAYS crashes..differences between my real data.frame
> ## 1)Actual df is 3 million rows, 2)df[,1] and df[,2] are
> ## of class "factor" rather than class "character"
> ## knowing this I have tried as.character(df[,1]) & same for df2
> ##but to no avail
>
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