根据第二列条件删除重复项

Question

I am trying to remove duplicate rows from a data frame based on the max value on a different column

So, for the data frame:

df<-data.frame (rbind(c("a",2,3),c("a",3,4),c("a",3,5),c("b",1,3),c("b",2,6),c("r",4,5))
  colnames(df)<-c("id","val1","val2")

id val1 val2

  a    2    3

  a    3    4

  a    3    5

  b    1    3

  b    2    6

  r    4    5

I would like to keep remove all duplicates by id with the condition that for the corresponding rows they do not have the maximum value for val2.

Thus the data frame should become:

  a    3    5

  b    2    6

  r    4    5

-> remove all a duplicates but keep row with the max value for df$val2 for subset(df, df$id=="a")

Answer 1

Using base R . Here, the columns are factors . Make sure to convert it to numeric

 df$val2 <- as.numeric(as.character(df$val2))
 df[with(df, ave(val2, id, FUN=max)==val2),]
 #  id val1 val2
 #3  a    3    5
 #5  b    2    6
 #6  r    4    5

Or using dplyr

 library(dplyr)
 df %>% 
    group_by(id) %>% 
    filter(val2==max(val2))
 #   id val1 val2
 #1  a    3    5
 #2  b    2    6
 #3  r    4    5

Answer 2

One possible way is to use data.table

library(data.table)
setDT(df)[, .SD[which.max(val2)], by = id]
##    id val1 val2
## 1:  a    3    5
## 2:  b    2    6
## 3:  r    4    5

Answer 3

Here's how I hope your data is really set up

df <- data.frame (id = c(rep("a", 3), rep("b", 2), "r"),
                  val1 = c(2, 3, 3, 1, 2, 4), val2 = c(3, 4, 5, 3, 6, 5))

You could do a split - unsplit

> unsplit(lapply(split(df, df$id), function(x) {
      if(nrow(x) > 1) {
          x[duplicated(x$id) & x$val2 == max(x$val2),]
      } else {
          x
      }
  }), levels(df$id))
#   id val1 val2
# 3  a    3    5
# 5  b    2    6
# 6  r    4    5

You can also use Reduce(rbind, ...) or do.call(rbind, ...) in place of unsplit

Answer 4

Another one

df %>% group_by(id) %>%
         slice(which.max(val2))

  id   val1  val2
   a    3     5
   b    2     6
   r    4     5