Efficiently concate character content within one c

2019-09-19 20:22发布

问题:

What is the fastest way to perform concate-like operation over a data.frame in R? Suppose I have the following table:

df <- data.frame(content = c("c1", "c2", "c3", "c4", "c5"),
                 groups = c("g1", "g1", "g1", "g2", "g2"),
                 stringsAsFactors = F)

df$groups <- as.factor(df$groups)

I want to concate the content of cells in content column, by groups, efficiently, to receive the equivalent to:

df2 <- data.frame(content = c("c1 c2 c3", "c4 c5"),
                  groups = c("g1", "g2"),
                  stringsAsFactors = F)

df2 $groups <- as.factor(df2 $groups)

I would prefer some dplyr operation, but have no good idea how to apply it.

回答1:

Here's a method using base's tapply

splat<-with(df, tapply(content, groups, paste, collapse=" "))
df2<-data.frame(groups=names(splat), content=splat, stringsAsFactors=F)
df2$groups <- as.factor(df2$groups)

which gives you

#    groups  content
# g1     g1 c1 c2 c3
# g2     g2    c4 c5

(the extra "g1/g2"s are the rownames of the data.frame)



回答2:

A close relative to tapply is aggregate, which lets you do this:

aggregate(content ~ groups, df, paste, collapse = " ")
#   groups  content
# 1     g1 c1 c2 c3
# 2     g2    c4 c5

Factors are retained:

str(.Last.value)
# 'data.frame':  2 obs. of  2 variables:
#  $ groups : Factor w/ 2 levels "g1","g2": 1 2
#  $ content: chr  "c1 c2 c3" "c4 c5"

Since you mention that you are looking for a dplyr approach, you can try something like this:

library(dplyr)
df %>% group_by(groups) %>% summarise(content = paste(content, collapse = " "))
# Source: local data frame [2 x 2]
# 
#   groups  content
# 1     g1 c1 c2 c3
# 2     g2    c4 c5


回答3:

Using data.table:

library(data.table)
dt = as.data.table(df)

dt[, paste(content, collapse = " "), by = groups]
#   groups       V1
#1:     g1 c1 c2 c3
#2:     g2    c4 c5

Since speed was mentioned in OP, data.table and dplyr are fairly close (the base methods are super slow, no point in testing them):

dt = data.table(content = sample(letters, 26e6, T), groups = LETTERS)
df = as.data.frame(dt)

system.time(dt[, paste(content, collapse = " "), by = groups])
#   user  system elapsed 
#   5.37    0.06    5.65 

system.time(df %>% group_by(groups) %>% summarise(paste(content, collapse = " ")))
#   user  system elapsed 
#   7.10    0.13    7.67