Using aggregate with variable names for column names

Question

I have the following data frame: ``` a <- c(1,1,4) b <- c(1,0,2) c <- data.frame(a=a,b=b) str(c) # a b #1 1 1 #2 1 0 #3 4 2 ``` I would like to aggregate the data frame c in the following way: ``` aggregate(b~a,FUN=mean,data=c) # a b #1 1 0.5 #2 4 2.0 ``` However, my main problem is that I will be using a variable for the name of the column So: ``` d <- 'a' ``` If I try to aggregate using this variable d that contains the name of the column, I will obviously get an error: ``` aggregate(b~d,FUN=mean,data=c) #Error in model.frame.default(formula = b ~ d, data = c) : variable lengths differ (found for 'd') ``` This works but I then get silly column names. I would like to avoid the extra step of renaming columns: ``` aggregate(c[,'b']~c[,d],FUN=mean,data=c) # c[, d] c[, "b"] #1 1 0.5 #2 4 2.0 ``` How to I aggregate and also get the right column names the first try? (Maybe there is no way to do this)

Accepted Answer

You could try

```
aggregate(c['b'], c[d], FUN=mean)
#   a   b
# 1 1 0.5
# 2 4 2.0
```

Another option if you are using the `formula` method would be to use `setNames`

```
 setNames(aggregate(b~get(d), FUN=mean, data=c), colnames(c))
 #  a   b
 #1 1 0.5
 #2 4 2.0
```

Using aggregate with variable names for column names

Solution

Problem