Aggregate data based on a categorical variable

Question

I am trying to calculate mean salary for every job title from a data set which has 2159 job titles and convert into a list. My code

> for (i in 1:length(unique(sfs$JobTitle))) {
  a<-print(paste((sfs$JobTitle[[i]])))
  b<-print(paste((mean(sfs$BasePay[[i]]))))
  ms<-list(a,b)
}

Also tried

for (i in 1:length(unique(sfs$JobTitle))) {   ms<-matrix((sfs$JobTitle[[i]]),(mean(sfs$BasePay[[i]]))) }

The output I am getting is a list of 2 elements only. Can you guys help. Thanks

and that output you are getting is for the last two only. If you are looking for mean salary of all job titles, show us your data `head(dput(dataframename)`, there are faster ways out there — CuriousBeing, Feb 20 '16 at 22:35
Seems like you need `aggregate(sfs$BasePay, list(sfs$JobTitle), mean)`.. but other than that, there are a lot of mistakes in your code. You don't have to use `paste` or `print` or `[[`. — slamballais, Feb 20 '16 at 22:41

score 0 · Accepted Answer · answered Feb 20 '16 at 22:41

Perhaps you don't need a for loop. There are other ways to do it. If you have a data.frame try this:

agg = aggregate(BasePay ~ JobTitle, data=sfs, mean)

This would work also:

sapply(split(sfs$BasePay, sfs$JobTitle), mean)

If you insist on having a list, use lapply:

lapply(split(sfs$BasePay, sfs$JobTitle), mean)

1 Answers1