Split data frame string column into multiple columns

Use stringr::str_split_fixed

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

Another option is to use the new tidyr package.

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_")

##   attr foo   bar
## 1    1 foo   bar
## 2   30 foo bar_2
## 3    4 foo   bar
## 4    6 foo bar_2

5 years later adding the obligatory data.table solution

library(data.table) ## v 1.9.6+ 
setDT(before)[, paste0("type", 1:2) := tstrsplit(type, "_and_")]
before
#    attr          type type1 type2
# 1:    1   foo_and_bar   foo   bar
# 2:   30 foo_and_bar_2   foo bar_2
# 3:    4   foo_and_bar   foo   bar
# 4:    6 foo_and_bar_2   foo bar_2

We could also both make sure that the resulting columns will have correct types and improve performance by adding type.convert and fixed arguments (since "_and_" isn't really a regex)

setDT(before)[, paste0("type", 1:2) := tstrsplit(type, "_and_", type.convert = TRUE, fixed = TRUE)]

Yet another approach: use rbind on out:

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]  [,2]   
[1,] "foo" "bar"  
[2,] "foo" "bar_2"
[3,] "foo" "bar"  
[4,] "foo" "bar_2"

And to combine:

data.frame(before$attr, do.call(rbind, out))

Notice that sapply with "[" can be used to extract either the first or second items in those lists so:

before$type_1 <- sapply(strsplit(as.character(before$type),'_and_'), "[", 1)
before$type_2 <- sapply(strsplit(as.character(before$type),'_and_'), "[", 2)
before$type <- NULL

And here's a gsub method:

before$type_1 <- gsub("_and_.+$", "", before$type)
before$type_2 <- gsub("^.+_and_", "", before$type)
before$type <- NULL