1) strcapture If you want to extract a string of digits and dots from "release 1.2.3" using base then
x <- "release 1.2.3"
strcapture("([0-9.]+)", x, data.frame(version = character(0)))
## version
## 1 1.2.3
2) regexec/regmatches There is also regmatches and regexec but that has already been covered in another answer.
3) sub Also it is often possible to use sub:
sub(".* ([0-9.]+).*", "\1", x)
## [1] "1.2.3"
3a) If you know the match is at the beginning or end then delete everything after or before it:
sub(".* ", "", x)
## [1] "1.2.3"
4) gsub Sometimes we know that the field to be extracted has certain characters and they do not appear elsewhere. In that case simply delete every occurrence of every character that cannot be in the string:
gsub("[^0-9.]", "", x)
## [1] "1.2.3"
5) read.table One can often decompose the input into fields and then pick off the desired one by number or via grep. strsplit, read.table or scan can be used:
read.table(text = x, as.is = TRUE)[[2]]
## [1] "1.2.3"
5a) grep/scan
grep("^[0-9.]+$", scan(textConnection(x), what = "", quiet = TRUE), value = TRUE)
## [1] "1.2.3"
5b) grep/strsplit
grep("^[0-9.]+$", strsplit(x, " ")[[1]], value = TRUE)
## [1] "1.2.3"
6) substring If we know the character position of the field we can use substring like this:
substring(x, 9)
## [1] "1.2.3"
6a) substring/regexpr or we may be able to use regexpr to locate the character position for us:
substring(x, regexpr("\d", x))
## [1] "1.2.3"
7) read.dcf Sometimes it is possible to convert the input to dcf form in which case it can be read with read.dcf. Such data is of the form name: value
read.dcf(textConnection(sub(" ", ": ", x)))
## release
## [1,] "1.2.3"
