How about
library(reshape2)
mdf.m <- melt(my_df, measure.vars=c("a", "b", "c"))
mdf.m <- mdf.m[mdf.m$value > 0, ]
ddply(mdf.m, "variable", function(x) c("mean"=mean(x$dat), "n"=nrow(x)))
?
Best,
Ista
On Wed, Mar 20, 2013 at 3:57 PM, Alexander Shenkin <ashenkin at ufl.edu> wrote:
Hi folks,
I'm trying to figure out how to get summarized data based on multiple
columns. However, instead of giving summaries for every combination of
categorical columns, I want it for each value of each categorical column
regardless of the other columns. I could do this with three different
commands, but i'm wondering if there's a more elegant way that I'm
missing. Thanks!
allie
my_df = data.frame(a = c(1,1,1,0,0,0), b=c(0,0,0,1,1,1),
c=c(1,0,1,0,1,0), dat=c(10,11,12,13,14,15))
a b c dat
1 1 0 1 10
2 1 0 0 11
3 1 0 1 12
4 0 1 0 13
5 0 1 1 14
6 0 1 0 15
# not what I want
ddply(my_df, .(a,b,c), function(x) c("mean"=mean(x$dat), "n"=nrow(x)))
a b c mean n
1 0 1 0 14 2
2 0 1 1 14 1
3 1 0 0 11 1
4 1 0 1 11 2
What I want:
a b c mean n
1 1 * * 11 3
2 * 1 * 14 3
3 * * 1 12 3
where "*" refers to any value of the other columns.