例如我们需要将一下数据的第二列从and处拆分为两列：

before = data.frame(attr = c(1,30,4,6), type=c('foo_and_bar','foo_and_bar_2'))

 attr          type

1    1   foo_and_bar

2   30 foo_and_bar_2

3    4   foo_and_bar

4    6 foo_and_bar_2

==>

  attr type_1 type_2

1    1    foo    bar

2   30    foo  bar_2

3    4    foo    bar

4    6    foo  bar_2

1. 使用stringr包的str_split_fixed函数

library(stringr)

str_split_fixed(before$type, "_and_", 2)

1. 使用do.call函数 （do.call(what, args, quote = FALSE, envir = parent.frame())）

before <- data.frame(attr = c(1,30,4,6), type=c('foo_and_bar','foo_and_bar_2'))

out <- strsplit(as.character(before$type),'_and_')

do.call(rbind, out)

1. 使用tidyr包

library(dplyr)

library(tidyr)

before <- data.frame(attr = c(1, 30 ,4 ,6 ), type = c('foo_and_bar', 'foo_and_bar_2'))

before %>% separate(type, c("foo", "bar"), "_and_")

1. 使用sapply 以及 "["

before$type_1 < sapply(strsplit(as.character(before$type),'_and_'), "[", 1)

before$type_2 < sapply(strsplit(as.character(before$type),'_and_'), "[", 2)

或者

before <- data.frame(attr = c(1,30,4,6), type=c('foo_and_bar','foo_and_bar_2'))

after <- with(before, data.frame(attr = attr))

after <- cbind(after, data.frame(t(sapply(out, `[`))))

names(after)[2:3] <- paste("type", 1:2, sep = "_")

1. 使用unlist后重新划分矩阵

before <- data.frame(attr = c(1,30,4,6), type=c('foo_and_bar','foo_and_bar_2'))

tmp <- matrix(unlist(strsplit(as.character(before$type), '_and_')), ncol=2,byrow=TRUE) #you should show how many columns you would get after spliting

after <- cbind(before$attr, as.data.frame(tmp))

names(after) <- c("attr", "type_1", "type_2")