Thanks to all. Very helpful. Steven from iPhone
> On Jan 14, 2023, at 3:08 PM, Andrew Simmons <akwsi...@gmail.com> wrote: > > You'll want to use grep() or grepl(). By default, grep() uses extended > regular expressions to find matches, but you can also use perl regular > expressions and globbing (after converting to a regular expression). > For example: > > grepl("^yr", colnames(mydata)) > > will tell you which 'colnames' start with "yr". If you'd rather you > use globbing: > > grepl(glob2rx("yr*"), colnames(mydata)) > > Then you might write something like this to remove the columns starting with > yr: > > mydata <- mydata[, !grepl("^yr", colnames(mydata)), drop = FALSE] > >> On Sat, Jan 14, 2023 at 1:56 AM Steven T. Yen <st...@ntu.edu.tw> wrote: >> >> I have a data frame containing variables "yr3",...,"yr28". >> >> How do I remove them with a wild card----something similar to "del yr*" >> in Windows/doc? Thank you. >> >>> colnames(mydata) >> [1] "year" "weight" "confeduc" "confothr" "college" >> [6] ... >> [41] "yr3" "yr4" "yr5" "yr6" "yr7" >> [46] "yr8" "yr9" "yr10" "yr11" "yr12" >> [51] "yr13" "yr14" "yr15" "yr16" "yr17" >> [56] "yr18" "yr19" "yr20" "yr21" "yr22" >> [61] "yr23" "yr24" "yr25" "yr26" "yr27" >> [66] "yr28"... >> >> ______________________________________________ >> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see >> 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. [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see 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.