Hi, You can also use ?merge() dat$ind_dat<-TRUE bad$ind_bad<-TRUE res<-merge(dat,bad,all=TRUE) res1<-res[is.na(res$ind_bad),][,1:3] res1 # id year age #5 2 2 Adult #6 2 2 <NA> #7 2 3 <NA> #8 2 2 <NA> #9 2 2 Adult #10 3 2 <NA> #11 3 3 Adult #12 3 4 <NA> A.K.
----- Original Message ----- From: penguins <cat...@bas.ac.uk> To: r-help@r-project.org Cc: Sent: Monday, October 22, 2012 7:04 AM Subject: [R] Remove records from a large dataframe Hi, I am trying to remove a series of records from a large dataframe. The script I have written works fine but takes a long time to run. Can anyone suggest a quicker way to do this? Here is an example of the code I've written. The end result of this bit of code would be a dataframe with any records relating to ID 1 or ID 4 removed: #dataframe id <- c(1,1,1,1,2,2,2,2,2, 3,3,3, 4,4) year <- c(1,1,1,2, 2,2,3,2,2, 2,3,4, 8,8) age <- c("Adult",NA,NA,NA, "Adult",NA,NA,NA, "Adult", NA,"Adult",NA, NA,"Adult") dat <- data.frame(id, year, age) dat.id<-unique(dat$id) #ID numbers for removal bad<- data.frame(c(1,4)) names(bad)<-"id" remove.value<-bad$id good.id<- dat.id[!dat.id%in%remove.value] #Combine all good ID numbers if(exists("dat.2")){ rm(dat.2)} for(i in good.id){ lala<-dat[which(dat$id==i),] if(!exists("dat.2")) { dat.2 <- lala } else { dat.2 <- rbind(dat.2, lala) } } Many thanks in advance for any suggestions -- View this message in context: http://r.789695.n4.nabble.com/Remove-records-from-a-large-dataframe-tp4646990.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ 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. ______________________________________________ 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.