将列折叠/连接/聚合到每个组中的单个逗号分隔字符串

I want to aggregate one column in a data frame according to two grouping variables, and separate the individual values by a comma.

我想根据两个分组变量在数据框架中聚合一列，并用逗号分隔各个值。

Here is some data:

这里有一些数据:

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:

“A”和“B”是分组变量，“C”是我要折叠成逗号分隔的字符串的变量。我有尝试:

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:

但当我试图将测试列转换为字符时，结果是这样的:

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).

如何保持字符格式并使用逗号分隔?例如，第1行应该只有“5,7”，而不是c(5,7)。

2 个解决方案

#1

plyr Try using toString :

尝试使用toString:

# plyr
library(plyr)
ddply(data, .(A,B), summarize, C = toString(C))

Here are some additional alternatives also using toString:

下面是一些使用toString的其他选项:

data.table

data.table

# alternative using data.table
library(data.table)
as.data.table(data)[, toString(C), by = list(A, B)]

aggregate This uses no packages:

合计这个使用没有包:

# alternative using aggregate from the stats package in the core of R
aggregate(C ~., data, toString)

sqldf

sqldf

And here is an alternative using the SQL function group_concat using the sqldf package :

下面是使用sqldf包的SQL函数group_concat的一种替代方法:

library(sqldf)
sqldf("select A, B, group_concat(C) C from data group by A, B", method = "raw")

dplyr A dplyr alternative:

dplyr dplyr替代:

library(dplyr)
data %>%
  group_by(A, B) %>%
  summarise(test = toString(C)) %>%
  ungroup()

#2

Change where you put as.character:

改变你放置的位置。

> 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, however, 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.

但是，请注意，每个条目实际上仍然是一个单独的字符，而不是单个字符串。也就是说，这不是一个实际的字符串，看起来像“5,7”，而是两个字符，“5”和“7”，在它们之间有一个逗号。

Compare with the following:

与以下:

> 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:

以R为基础的可比较的解，当然是集合:

> 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"

#1