CODEWITHSUNDEEP
raggregate
gented
gented

Reputation: 1707

Aggregate multiple columns according to some others

Having data in a data.frame, I would like to aggregate some columns (using any general function) grouping by some others, keeping the remaining ones as they are (or even omitting them). The fashion is to recall the group by function in SQL. As an example let us assume we have

df <- data.frame(a=rnorm(4), b=rnorm(4), c=c("A", "B", "C", "A"))

and I want to sum (say) the values in column a and average (say) the values in column b, grouping by the symbols in column c. I am aware it is possible to achieve such using apply, cbind or similars, specifying the functions you want to use, but I was wondering if there were a smarter (one line) way (especially using the aggregate function) to do so.

Upvotes: 0

Views: 641

Answers (2)

Federico Rotolo
Federico Rotolo

Reputation: 57

like this?

    mapply(Vectorize(function(x, y) aggregate(
      df[, x], by=list(df[, 3]), FUN=y), SIMPLIFY = F), 
      1:2, c('sum', 'mean'))

Upvotes: 1

HywelMJ
HywelMJ

Reputation: 332

Sorry but I don't follow how dealing with more than one column complicates things.

library(data.table)
dt <- data.table(df)
dt[,.(sum_a = sum(a),mean_b= mean(b)),by = c]

Upvotes: 2

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