How to select the row with the maximum value in each group

Question

In a dataset with multiple observations for each subject I want to take a subset with only the maximum data value for each record. For example, with a following dataset:

Answer 1

In base you can use ave to get max per group and compare this with pt and get a logical vector to subset the data.frame.

group[group$pt == ave(group$pt, group$Subject, FUN=max),]
#  Subject pt Event
#3       1  5     2
#7       2 17     2
#9       3  5     2

Or compare it already in the function.

group[as.logical(ave(group$pt, group$Subject, FUN=function(x) x==max(x))),]
#group[ave(group$pt, group$Subject, FUN=function(x) x==max(x))==1,] #Variant
#  Subject pt Event
#3       1  5     2
#7       2 17     2
#9       3  5     2

Answer 2

A dplyr solution:

library(dplyr)
ID <- c(1,1,1,2,2,2,2,3,3)
Value <- c(2,3,5,2,5,8,17,3,5)
Event <- c(1,1,2,1,2,1,2,2,2)
group <- data.frame(Subject=ID, pt=Value, Event=Event)

group %>%
    group_by(Subject) %>%
    summarize(max.pt = max(pt))

This yields the following data frame:

  Subject max.pt
1       1      5
2       2     17
3       3      5

Answer 3

I wasn't sure what you wanted to do about the Event column, but if you want to keep that as well, how about

isIDmax <- with(dd, ave(Value, ID, FUN=function(x) seq_along(x)==which.max(x)))==1
group[isIDmax, ]

#   ID Value Event
# 3  1     5     2
# 7  2    17     2
# 9  3     5     2

Here we use ave to look at the "Value" column for each "ID". Then we determine which value is the maximal and then turn that into a logical vector we can use to subset the original data.frame.

Answer 4

If you want the biggest pt value for a subject, you could simply use:

   pt_max = as.data.frame(aggregate(pt~Subject, group, max))