Aggregate multiple columns according to some others

0
votes

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.

2
raggregate
this has been asked a gazillion times, see here stackoverflow.com/questions/18799901/data-frame-group-by-column and here stackoverflow.com/questions/6289538/… and here stats.stackexchange.com/questions/8225/… - grrgrrbla
@grrgrrbla Please vote to close as a duplicate in this case. - Tim Biegeleisen
possible duplicate of Using aggregate for multiple aggregations - Colonel Beauvel
@tim biegeleisen, already did so - grrgrrbla
I have seen all the above and they all refer to aggregating only one column, which can be easily done with different syntax. - gented

2 Answers

2
votes

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]
1
votes

like this?

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