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$ind_bad),][,1:3]
?res1
#?? id year?? age
#5?? 2??? 2 Adult
#6?? 2??? 2? <NA>
#7?? 2??? 3? <NA>
#8?? 2??? 2? <NA>
#9?? 2??? 2 Adult
#10? 3??? 2? <NA>
#11? 3??? 3 Adult
#12? 3??? 4? <NA>
A.K.
----- Original Message -----
From: penguins <catrsw at bas.ac.uk>
To: r-help at r-project.org
Cc:
Sent: Monday, October 22, 2012 7:04 AM
Subject: [R] Remove records from a large dataframe
Hi, I am trying to remove a series of records from a large dataframe. The
script I have written works fine but takes a long time to run. Can anyone
suggest a quicker way to do this?
Here is an example of the code I've written. The end result of this bit of
code would be a dataframe with any records relating to ID 1 or ID 4 removed:
#dataframe
id <-? ? c(1,1,1,1,2,2,2,2,2, 3,3,3, 4,4)
year <- c(1,1,1,2, 2,2,3,2,2, 2,3,4, 8,8)
age <-? c("Adult",NA,NA,NA, "Adult",NA,NA,NA, "Adult",
? ? ? ? NA,"Adult",NA, NA,"Adult")
dat <- data.frame(id, year, age)
dat.id<-unique(dat$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
--
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