What is a good way to get the independent frequency counts of multiple columns using dplyr? I want to go from a table of values:
# A tibble: 7 x 4
a b c d
<int> <int> <int> <int>
1 1 2 1 3
2 1 2 1 3
3 2 2 5 3
4 3 2 4 3
5 3 3 2 3
6 5 3 4 3
7 5 4 2 1
to a frequency table like so:
# A tibble: 5 x 5
x a_n b_n c_n d_n
<int> <int> <int> <int> <int>
1 1 2 0 2 1
2 2 1 4 2 0
3 3 2 2 0 6
4 4 0 1 2 0
5 5 2 0 1 0
I'm still trying to get my head around dplyr, but it seems like this is something it could do. If it is easier to do with an add-on library, that is fine too.
library(dplyr)
library(reshape2)
df %>%
melt() %>%
dcast(value ~ variable, fun.aggregate=length)
# value a b c d
# 1 1 2 0 2 1
# 2 2 1 4 2 0
# 3 3 2 2 0 6
# 4 4 0 1 2 0
# 5 5 2 0 1 0
df <- structure(list(a = c(1L, 1L, 2L, 3L, 3L, 5L, 5L), b = c(2L, 2L,
2L, 2L, 3L, 3L, 4L), c = c(1L, 1L, 5L, 4L, 2L, 4L, 2L), d = c(3L,
3L, 3L, 3L, 3L, 3L, 1L)), .Names = c("a", "b", "c", "d"), class = "data.frame", row.names = c("1",
"2", "3", "4", "5", "6", "7"))