折叠/连接/聚集一列为每个组中的单个逗号分隔的字符串


77

我想根据两个分组变量在数据框中汇总一列,并用逗号分隔各个值。

这是一些数据:

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”和“ B”是分组变量,“ C”是我要折叠成逗号分隔的character字符串的变量。我试过了:

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

但是当我尝试将测试列转换为character这样时:

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)

如何保留character格式并用逗号分隔?例如,第1行应仅为"5,7",而不应为c(5,7)。

Answers:


89

这是使用的一些选项toString,该函数使用逗号和空格将字符串向量连接起来以分隔各个组成部分。如果你不希望逗号,你可以使用paste()collapse参数来代替。

数据表

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

汇总这不使用任何软件包:

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

sqldf

这是group_concat使用sqldf包的SQL函数的替代方法:

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

dplyrdplyr替代:

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

皮尔

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

要仅保留唯一值:as.data.table(data)[,toString(unique(C)),by = list(A,B)]
ddunn801

20

这是stringr/tidyverse解决方案:

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 test 
  <dbl> <int> <chr>
1   111     1 5, 7 
2   111     2 6    
3   222     1 9    
4   222     2 8, 10

2
一个也可以替代stringr::str_cpaste从基R.
富Pauloo

14

更改放置位置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

请注意,在这种情况下,每个项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,这不是一个看起来像“ 5,7”的实际字符串,而是两个字符“ 5”和“ 7”,R用两个字符之间的逗号显示。

与以下内容进行比较:

> 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

当然,R中的可比解决方案是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"

2

这里有一个小的改进,以避免重复

# 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

希望它会有用。

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