Aggregate by factor levels, keeping other variables in the resulting data frame

Question

I'm trying to calculate the minimum values of a numeric column for each level of a factor, while keeping values of another factor in the resulting data frame.

# dummy data
dat <- data.frame(
    code = c("HH11", "HH45", "JL03", "JL03", "JL03", "HH11"), 
    index = c("023434", "3377477", "3388595", "3377477", "1177777", "023434"), 
    value = c(24.1, 37.2, 78.9, 45.9, 20.0, 34.6)
    )

The result I want is the minimum of value for each level of code, keeping index in the resulting data frame.

# result I want:
#   code value    index
# 1 HH11  24.1   023434
# 2 HH45  37.2  3377477
# 3 JL03  20.0  1177777


# ddply attempt
library(plyr)
ddply(dat, ~ code, summarise, val = min(value))
#   code   val
# 1 HH11  24.1
# 2 HH45  37.2
# 3 JL03  20.0


# base R attempt
aggregate(value ~ code, dat, min)
#   code value
# 1 HH11  24.1
# 2 HH45  37.2
# 3 JL03  20.0

Answer 1

You need to use merge on result of aggregate and original data.frame

merge(aggregate(value ~ code, dat, min), dat, by = c("code", "value"))
##   code value   index
## 1 HH11  24.1  023434
## 2 HH45  37.2 3377477
## 3 JL03  20.0 1177777

Answer 2

Just to show that there's always multiple ways to skin a cat:

Using ave to get the indexes of the minimum rows in each group:

dat[which(ave(dat$value,dat$code,FUN=function(x) x==min(x))==1),]

#  code   index value
#1 HH11  023434  24.1
#2 HH45 3377477  37.2
#5 JL03 1177777  20.0

This method also has the potential benefit of returning multiple rows per code group in the instance of multiple values being the minimum.

And another method using by:

do.call(rbind,
  by(dat, dat$code, function(x) cbind(x[1,c("code","index")],value=min(x$value)))
)
#      code   index value
# HH11 HH11  023434  24.1
# HH45 HH45 3377477  37.2
# JL03 JL03 3388595  20.0