Collapse / concatenate / aggregate a column to a single comma separated string within each group
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()
plyr
# plyr
library(plyr)
ddply(data, .(A,B), summarize, C = toString(C))
Here's the stringr
/tidyverse
solution:
library(tidyverse)
library(stringr)
data <- data.frame(A = c(rep(111, 3), rep(222, 3)), B = rep(1:2, 3), C = c(5:10))
data %>%
group_by(A, B) %>%
summarize(text = str_c(C, collapse = ", "))
# A tibble: 4 x 3
# Groups: A [2]
A B text
<dbl> <int> <chr>
1 111 1 5, 7
2 111 2 6
3 222 1 9
4 222 2 8, 10
Change where you put as.character
:
> out <- ddply(data, .(A, B), summarise, test = list(as.character(C)))
> str(out)
'data.frame': 4 obs. of 3 variables:
$ A : num 111 111 222 222
$ B : int 1 2 1 2
$ test:List of 4
..$ : chr "5" "7"
..$ : chr "6"
..$ : chr "9"
..$ : chr "8" "10"
> out
A B test
1 111 1 5, 7
2 111 2 6
3 222 1 9
4 222 2 8, 10
Note in this case that each item is still actually a separate character, not a single character string. That is, this is not an actual string that looks like "5, 7", but rather, two characters, "5" and "7", which R displays with a comma between them.
Compare with the following:
> out2 <- ddply(data, .(A, B), summarise, test = paste(C, collapse = ", "))
> str(out2)
'data.frame': 4 obs. of 3 variables:
$ A : num 111 111 222 222
$ B : int 1 2 1 2
$ test: chr "5, 7" "6" "9" "8, 10"
> out
A B test
1 111 1 5, 7
2 111 2 6
3 222 1 9
4 222 2 8, 10
The comparable solution in base R is, of course, aggregate
:
> A1 <- aggregate(C ~ A + B, data, function(x) c(as.character(x)))
> str(A1)
'data.frame': 4 obs. of 3 variables:
$ A: num 111 222 111 222
$ B: int 1 1 2 2
$ C:List of 4
..$ 0: chr "5" "7"
..$ 1: chr "9"
..$ 2: chr "6"
..$ 3: chr "8" "10"
> A2 <- aggregate(C ~ A + B, data, paste, collapse = ", ")
> str(A2)
'data.frame': 4 obs. of 3 variables:
$ A: num 111 222 111 222
$ B: int 1 1 2 2
$ C: chr "5, 7" "9" "6" "8, 10"
There is a small improvement here to avoid duplicates
# 1. Original data set
data <- data.frame(
A = c(rep(111, 3), rep(222, 3)),
B = rep(1:2, 3),
C = c(5:10))
# 2. Add duplicate row
data <- rbind(data, data.table(
A = 111, B = 1, C = 5
))
# 3. Solution with duplicates
data %>%
group_by(A, B) %>%
summarise(test = toString(C)) %>%
ungroup()
# A B test
# <dbl> <dbl> <chr>
# 1 111 1 5, 7, 5
# 2 111 2 6
# 3 222 1 9
# 4 222 2 8, 10
# 4. Solution without duplicates
data %>%
select(A, B, C) %>% unique() %>%
group_by(A, B) %>%
summarise(test = toString(C)) %>%
ungroup()
# A B test
# <dbl> <dbl> <chr>
# 1 111 1 5, 7
# 2 111 2 6
# 3 222 1 9
# 4 222 2 8, 10
Hope it can be useful.