问题
I've got 81,000 records in my test frame, and duplicated is showing me that 2039 are identical matches. One answer to Find duplicated rows (based on 2 columns) in Data Frame in R suggests a method for creating a smaller frame of just the duplicate records. This works for me, too:
dup <- data.frame(as.numeric(duplicated(df$var))) #creates df with binary var for duplicated rows
colnames(dup) <- c("dup") #renames column for simplicity
df2 <- cbind(df, dup) #bind to original df
df3 <- subset(df2, dup == 1) #subsets df using binary var for duplicated`
But it seems, as the poster noted, inelegant. Is there a cleaner way to get the same result: a view of just those records that are duplicates?
In my case I'm working with scraped data and I need to figure out whether the duplicates exist in the original or were introduced by me scraping.
回答1:
duplicated(df) will give you a logical vector (all values consisting of either T/F), which you can then use as an index to your dataframe rows.
# indx will contain TRUE values wherever in df$var there is a duplicate
indx <- duplicated(df$var)
df[indx, ] #note the comma
You can put it all together in one line
df[duplicated(df$var), ] # again, the comma, to indicate we are selected rows
回答2:
doops <- which(duplicated(df$var)==TRUE)
uniques <- df[-doops,]
duplicates <- df[doops,]
Is the logic I generally use when I am trying to remove the duplicate entrys from a data frame.
来源：https://stackoverflow.com/questions/13594968/is-there-a-more-elegant-way-to-find-duplicated-records