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
使用stringr包的str_split_fixed函数
library(stringr)
str_split_fixed(before$type, "_and_", 2)
使用do.call函数 （do.call(what, args, quote = FALSE, envir = parent.frame())）
before <- data.frame(attr = c(1,30,4,6), type=c('foo_and_bar','foo_and_bar_2'))  
out <- strsplit(as.character(before$type),'_and_') 
do.call(rbind, out)
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_")
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)
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 = "_")
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")