Remove duplicates based on 2nd column condition

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

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

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