I have a matrix such as:
> mt <- matrix(1:9, nrow=3, ncol=3)
> dimnames(mt) <- list( c('a','b','c'), c('x','y','z') )
> mt
x y z
a 1 4 7
b 2 5 8
c 3 6 9
I can convert it into a tabular format with:
> as.data.frame(as.table(mt))
Var1 Var2 Freq
1 a x 1
2 b x 2
3 c x 3
4 a y 4
5 b y 5
6 c y 6
7 a z 7
8 b z 8
9 c z 9
My question is - Is there a clean way to do the reverse?
You can use: ?xtabs :Create a contingency table (optionally a sparse matrix) from cross-classifying factors, usually contained in a data frame, using a formula interface.
xtabs(Freq~Var1+Var2,Data)
Var2
Var1 x y z
a 1 4 7
b 2 5 8
c 3 6 9
You can also use this : ?acsat:Use acast or dcast depending on whether you want vector/matrix/array output or data frame output. Data frames can have at most two dimensions.
library(reshape2)
zz <- "Var1 Var2 Freq
1 a x 1
2 b x 2
3 c x 3
4 a y 4
5 b y 5
6 c y 6
7 a z 7
8 b z 8
9 c z 9"
Data <- read.table(text=zz, header = TRUE)
acast(Data, Var1 ~ Var2)
Using Freq as value column: use value.var to override.
x y z
a 1 4 7
b 2 5 8
c 3 6 9
How about reshape2::acast:
require(reshape2)
acast(m,Var1~Var2)
# x y z
#a 1 4 7
#b 2 5 8
#c 3 6 9
ps: you can use reshape2::melt() to go the other way
