If there a function that will give me both counts and column/overall percents in the same table? I can looked at both tables and reshape2 and don't see an option for doing it. I'll give a little example:
n <- 100
x <- sample(letters[1:3], n, T)
y <- sample(letters[1:3], n, T)
d <- data.frame(x=x, y=y)
This is very clunky as it requires me to unlist and recombine.
> library(tables)
> (t1 <- tabular(x~y*(n=length), d))
a b c
x n n n
a 13 14 11
b 8 11 13
c 10 12 8
> prop.table(matrix(unlist(t1),3,3), 1)
[,1] [,2] [,3]
[1,] 0.3421053 0.3684211 0.2894737
[2,] 0.2500000 0.3437500 0.4062500
[3,] 0.3333333 0.4000000 0.2666667
This is a little easier, but still not in one.
> library(reshape2)
> (t2 <- acast(d, x~y, length))
Using y as value column: use value_var to override.
a b c
a 13 14 11
b 8 11 13
c 10 12 8
> (t3 <- prop.table(t2,1))
a b c
a 0.3421053 0.3684211 0.2894737
b 0.2500000 0.3437500 0.4062500
c 0.3333333 0.4000000 0.2666667
What I really want is output that looks something like this:
> structure(list(
+ a = data.frame(n=t2[,1], pct=t3[,1]),
+ b = data.frame(n=t2[,2], pct=t3[,2]),
+ c = data.frame(n=t2[,3], pct=t3[,3])),
+ class = 'data.frame',
+ row.names = letters[1:3])
a.n a.pct b.n b.pct c.n c.pct
a 13 0.3421053 14 0.3684211 11 0.2894737
b 8 0.2500000 11 0.3437500 13 0.4062500
c 10 0.3333333 12 0.4000000 8 0.2666667
Is there a way to do this easily with R?
Here is one approach, you still need a second step, but it comes before the tabular
command so the result is still a tabular
object.
n <- 100
x <- sample(letters[1:3], n, T)
y <- sample(letters[1:3], n, T)
d <- data.frame(x=x, y=y)
d$z <- 1/ave( rep(1,n), d$x, FUN=sum )
(t1 <- tabular(x~y*Heading()*z*((n=length) + (p=sum)), d))
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