Split column at delimiter in data frame [duplicate]

@Taesung Shin is right, but then just some more magic to make it into a data.frame. I added a "x|y" line to avoid ambiguities:

df <- data.frame(ID=11:13, FOO=c('a|b','b|c','x|y'))
foo <- data.frame(do.call('rbind', strsplit(as.character(df$FOO),'|',fixed=TRUE)))

Or, if you want to replace the columns in the existing data.frame:

within(df, FOO<-data.frame(do.call('rbind', strsplit(as.character(FOO), '|', fixed=TRUE))))

Which produces:

  ID FOO.X1 FOO.X2
1 11      a      b
2 12      b      c
3 13      x      y

The newly popular tidyr package does this with separate. It uses regular expressions so you'll have to escape the |

df <- data.frame(ID=11:13, FOO=c('a|b', 'b|c', 'x|y'))
separate(data = df, col = FOO, into = c("left", "right"), sep = "\\|")

#   ID left right
# 1 11    a     b
# 2 12    b     c
# 3 13    x     y

though in this case the defaults are smart enough to work (it looks for non-alphanumeric characters to split on).

separate(data = df, col = FOO, into = c("left", "right"))

Hadley has a very elegant solution to do this inside data frames in his reshape package, using the function colsplit.

require(reshape)
> df <- data.frame(ID=11:13, FOO=c('a|b','b|c','x|y'))
> df
  ID FOO
1 11 a|b
2 12 b|c
3 13 x|y
> df = transform(df, FOO = colsplit(FOO, split = "\\|", names = c('a', 'b')))
> df
  ID FOO.a FOO.b
1 11     a     b
2 12     b     c
3 13     x     y