Access n-th element after string splitting

1) data.frame Convert to a data frame and then it is easy to pick off a column or subset of columns:

DF <- read.table(text = string, sep = ",", as.is = TRUE)

DF[[1]]
## [1] "A" "B" "A"

DF[[3]]
## [1] "some text"       "some other text" "yet another one"

DF[-1]
##   V2              V3  V4
## 1  1       some text 200
## 2  2 some other text 300
## 3  3 yet another one 100

DF[2:3]
##   V2              V3
## 1  1       some text
## 2  2 some other text
## 3  3 yet another one

2) data.table::tranpose The data.table package has a function to tranpose lists so that if stringt is the tranposed list then stringt[[3]] is the vector of third fields, say, in a similar way to (1). Even more compact is data.table's tstrsplit mentioned by @Henrik below or the same package's fread mentioned by @akrun below.

library(data.table)

stringt <- transpose(strsplit(string, ","))

# or
stringt <- tstrsplit(string, ",")

stringt[[1]]
## [1] "A" "B" "A"

stringt[[3]]
## [1] "some text"       "some other text" "yet another one"

stringt[-1]
## [[1]]
## [1] "1" "2" "3"
##
## [[2]]
## [1] "some text"       "some other text" "yet another one"
##
## [[3]]
## [1] "200" "300" "100"

stringt[2:3]
## [[1]]
## [1] "1" "2" "3"
##
## [[2]]
## [1] "some text"       "some other text" "yet another one"

purrr also has a transpose function but

library(purrr)
transpose(strsplit(string, ","))

produces a list of lists rather than a list of character vectors.

One option is to use word from stringr with sep argument

library(stringr)
word(string, 1, sep = ",")
#[1] "A" "B" "A"

word(string, 3, sep = ",")
#[1] "some text"       "some other text" "yet another one"

---

Since the performance of word is the worst among all I found out another option using regular expression in base R.

#Get 1st element
sub("(?:[^,],){0}([^,]*).*", "\\1",string)
#[1] "A" "B" "A"

#Get 3rd element
sub("(?:[^,],){2}([^,]*).*", "\\1",string)
#[1] "some text"       "some other text" "yet another one"

There are two groups to match here. First one matches any characters that are not a comma followed by a comma for n times and then again matches another set of characters that are not comma. The first group is not captured (?:) while the second group is captured and returned. Also note that the number in brackets ({}) has to be one less than the word we want. So {0} returns 1st word and {2} returns 3rd word.

Benchmark

string <- c("A,1,some text,200","B,2,some other text,300","A,3,yet another one,100")
string <- rep(string, 1e5)

library(microbenchmark)
microbenchmark(
  tmfmnk_sapply = sapply(strsplit(string, ","), function(x) x[1]),
  tmfmnk_tstrsplit = tstrsplit(string, ",")[[1]],
  avid_useR_sapply = sapply(strsplit(string, ","), '[', 1),
  avid_useR_str_split = str_split(string, ",", simplify = TRUE)[,1],
  Ronak_Shah_word = word(string, 1, sep = ","),
  Ronak_Shah_sub = sub("(?:[^,],){0}([^,]*).*", "\\1",string),
  G_Grothendieck ={DF <- read.table(text = string, sep = ",",as.is = TRUE);DF[[1]]},
  times = 5
)
#Unit: milliseconds
#               expr     min      lq    mean  median      uq     max neval
#      tmfmnk_sapply 1629.69 1641.61 2128.14 1834.99 1893.43 3640.96     5
#   tmfmnk_tstrsplit 1269.94 1283.79 1286.29 1286.68 1290.76 1300.30     5
#   avid_useR_sapply 1445.40 1447.64 1555.76 1498.14 1609.52 1778.13     5
#avid_useR_str_split  324.68  332.28  332.30  333.97  334.01  336.54     5
#    Ronak_Shah_word 6571.29 6810.92 6956.20 6930.86 7217.26 7250.69     5
#     Ronak_Shah_sub  349.76  354.77  356.91  358.91  359.17  361.94     5
#     G_Grothendieck  354.93  358.24  364.43  362.24  367.79  378.94     5

I haven't included Christoph's solution as it is not clear to me how it will work for variable n's. For example for 3rd position , for 4th position etc.

We can simplify OP's code to:

sapply(strsplit(string, ","), '[', 1)
# [1] "A" "B" "A"

sapply(strsplit(string, ","), '[', 3)
# [1] "some text"       "some other text" "yet another one"

Also, with stringr::str_split and simplify = TRUE, we can directly index the column, since the output would be a matrix:

library(stringr)
str_split(string, ",", simplify = TRUE)[,1]
# [1] "A" "B" "A"

str_split(string, ",", simplify = TRUE)[,3]
# [1] "some text"       "some other text" "yet another one"