[This article was first published on theBioBucket*, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.
..often needed when preparing data for analysis (and usually forgotten until I need it for the next time).Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.
With the below code I convert a set of variables to factors – it could be that there are slicker ways to do it (if you know one let me know!)
> dat <- data.frame(matrix(sample(1:40), 4, 10, dimnames = list(1:4, LETTERS[1:10]))) > str(dat) 'data.frame': 4 obs. of 10 variables: $ A: int 5 34 3 15 $ B: int 28 25 17 24 $ C: int 2 12 10 32 $ D: int 16 27 29 14 $ E: int 40 7 4 31 $ F: int 22 30 6 18 $ G: int 33 36 35 38 $ H: int 19 21 37 8 $ I: int 20 11 9 26 $ J: int 39 13 1 23 > > id <- which(names(dat)%in%c("A", "F", "I")) > dat[, id] <- lapply(dat[, id], as.factor) > str(dat[, id]) 'data.frame': 4 obs. of 3 variables: $ A: Factor w/ 4 levels "3","5","15","34": 2 4 1 3 $ F: Factor w/ 4 levels "6","18","22",..: 3 4 1 2 $ I: Factor w/ 4 levels "9","11","20",..: 3 2 1 4
To leave a comment for the author, please follow the link and comment on their blog: theBioBucket*.
R-bloggers.com offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.