109
I have the following data frame
x <- read.table(text = " id1 id2 val1 val2
1 a x 1 9
2 a x 2 4
3 a y 3 5
4 a y 4 9
5 b x 1 7
6 b y 4 4
7 b x 3 9
8 b y 2 8", header = TRUE)
I want to calculate the mean of val1 and val2 grouped by id1 and id2, and simultaneously count the number of rows for each id1-id2 combination. I can perform each calculation separately:
# calculate mean
aggregate(. ~ id1 + id2, data = x, FUN = mean)
# count rows
aggregate(. ~ id1 + id2, data = x, FUN = length)
In order to do both calculations in one call, I tried
do.call("rbind", aggregate(. ~ id1 + id2, data = x, FUN = function(x) data.frame(m = mean(x), n = length(x))))
However, I get a garbled output along with a warning:
# m n
# id1 1 2
# id2 1 1
# 1.5 2
# 2 2
# 3.5 2
# 3 2
# 6.5 2
# 8 2
# 7 2
# 6 2
# Warning message:
# In rbind(id1 = c(1L, 2L, 1L, 2L), id2 = c(1L, 1L, 2L, 2L), val1 = list( :
# number of columns of result is not a multiple of vector length (arg 1)
I could use the plyr package, but my data set is quite large and plyr is very slow (almost unusable) when the size of the dataset grows.
How can I use aggregate or other functions to perform several calculations in one call?