Hi Everyone,
I needed to parse some strings recently. The code I've wound up using seems rather clunky, and I was wondering if anyone had any suggestions on a better way? Basically I do the following: 1) Use substr() to do the parsing 2) Use regexpr() to find the location of the string I want to parse on, I then pass this onto substr() 3) Use nchar() as the stop input to substr() where necessary I've got a simple example of the parsing code I used below. It takes questionnaire variable names that includes the question and the brand it was answered for and then parses it so the variable name and the brand are in separate columns. I then use this to restructure the data from unstacked to stacked, but that's another story. > # this is the data set > test [1] "A5.Brands.bought...Dulux" [2] "A5.Brands.bought...Haymes" [3] "A5.Brands.bought...Solver" [4] "A5.Brands.bought...Taubmans.or.Bristol" [5] "A5.Brands.bought...Wattyl" [6] "A5.Brands.bought...Other" > # Where do I want to parse? > break1 <- regexpr('...',test, fixed=TRUE) > break1 [1] 17 17 17 17 17 17 attr(,"match.length") [1] 3 3 3 3 3 3 > # Put Variable name in a variable > str1 <- substr(test,1,break1-1) > str1 [1] "A5.Brands.bought" "A5.Brands.bought" "A5.Brands.bought" "A5.Brands.bought" [5] "A5.Brands.bought" "A5.Brands.bought" > # Put Brand name in a variable > str2 <- substr(test,break1+3, nchar(test)) > str2 [1] "Dulux" "Haymes" "Solver" [4] "Taubmans.or.Bristol" "Wattyl" "Other" Thanks for any and all suggestions Chris Howden Founding Partner Tricky Solutions Tricky Solutions 4 Tricky Problems Evidence Based Strategic Development, IP Commercialisation and Innovation, Data Analysis, Modelling and Training (mobile) 0410 689 945 (fax / office) (+618) 8952 7878 ch...@trickysolutions.com.au ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.