How can I use functions returning vectors (like fivenum) with ddply or aggregate?

Question

I would like to split my data frame using a couple of columns and call let\'s say fivenum on each group.

aggregate(Petal.Width ~ Species, iris,          


        

Answer 1

Here is a solution using data.table (while not specifically requested, it is an obvious compliment or replacement for aggregate or ddply. As well as being slightly long to code, repeatedly calling quantile will be inefficient, as for each call you will be sorting the data

library(data.table)
Tukeys_five <- c("Min","Q1","Med","Q3","Max") 

IRIS <- data.table(iris)
# this will create the wide data.table
lengthBySpecies <- IRIS[,as.list(fivenum(Sepal.Length)), by = Species]

# and you can rename the columns from V1, ..., V5 to something nicer

setnames(lengthBySpecies, paste0('V',1:5), Tukeys_five)


lengthBySpecies



      Species Min  Q1 Med  Q3 Max
1:     setosa 4.3 4.8 5.0 5.2 5.8
2: versicolor 4.9 5.6 5.9 6.3 7.0
3:  virginica 4.9 6.2 6.5 6.9 7.9

Or, using a single call to quantile using the appropriate prob argument.

IRIS[,as.list(quantile(Sepal.Length, prob = seq(0,1, by = 0.25))), by = Species]


       Species  0%   25% 50% 75% 100%
1:     setosa 4.3 4.800 5.0 5.2  5.8
2: versicolor 4.9 5.600 5.9 6.3  7.0
3:  virginica 4.9 6.225 6.5 6.9  7.9  

Note that the names of the created columns are not syntactically valid, although you could go through a similar renaming using setnames

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EDIT

Interestingly, quantile will set the names of the resulting vector if you set names = TRUE, and this will copy (slow down the number crunching and consume memory - it even warns you in the help, fancy that!)

Thus, you should probably use

 IRIS[,as.list(quantile(Sepal.Length, prob = seq(0,1, by = 0.25), names = FALSE)), by = Species]

Or, if you wanted to return the named list, without R copying internally

IRIS[,{quant <- as.list(quantile(Sepal.Length, prob = seq(0,1, by = 0.25), names = FALSE))
       setattr(quant, 'names', Tukeys_five)
       quant}, by = Species]