I want to aggregate one column in a data frame according to two grouping variables, and separate the individual values by a comma.
Here is some data:
data <- data.frame(A = c(rep(111, 3), rep(222, 3)), B = rep(1:2, 3), C = c(5:10))
data
# A B C
# 1 111 1 5
# 2 111 2 6
# 3 111 1 7
# 4 222 2 8
# 5 222 1 9
# 6 222 2 10
"A" and "B" are grouping variables, and "C" is the variable that I want to collapse into a comma separated character string. I have tried:
library(plyr)
ddply(data, .(A,B), summarise, test = list(C))
A B test
1 111 1 5, 7
2 111 2 6
3 222 1 9
4 222 2 8, 10
but when I tried to convert test column to character it becomes like this:
ddply(data, .(A,B), summarise, test = as.character(list(C)))
# A B test
# 1 111 1 c(5, 7)
# 2 111 2 6
# 3 222 1 9
# 4 222 2 c(8, 10)
How can I keep the character format and separate them by a comma? For example, row 1 should be only "5,7", and not as c(5,7).
Here are some options using toString, a function that concatenates a vector of strings using comma and space to separate components. If you don't want commas, you can use paste() with the collapse argument instead.
data.table
# alternative using data.table
library(data.table)
as.data.table(data)[, toString(C), by = list(A, B)]
aggregate This uses no packages:
# alternative using aggregate from the stats package in the core of R
aggregate(C ~., data, toString)
sqldf
And here is an alternative using the SQL function group_concat using the sqldf package :
library(sqldf)
sqldf("select A, B, group_concat(C) C from data group by A, B", method = "raw")
dplyr A dplyr alternative:
library(dplyr)
data %>%
group_by(A, B) %>%
summarise(test = toString(C)) %>%
ungroup()
or with more recent versions of dplyr
data %>% summarise(test = toString(C), .by = c(A, B))
plyr
# plyr
library(plyr)
ddply(data, .(A,B), summarize, C = toString(C))