Question

Hi I want to avoid using loops and so want to use something from plyr to help solve my problem.

I would like to create a function that gets the sum of a specifically chosen column for each factor from a dataframe.

So if we have the following example data…

df <- data.frame(cbind(x=rnorm(100),y=rnorm(100),z=rnorm(100),f=sample(1:10,100, replace=TRUE))) 
df$f <- as.factor(df$f)

i.e. I would like something like:

foo <- function(df.obj,colname){
     some code
}

where the df.obj would be the df variable above and the colname argument could be any of x,y or z.

and I would like the output/result of the function to have a column of the unique factors (in the above case 1:10) and the sums of the values in column x for each factor.

I expect that the solution to be quite simple and would probably be using ddply or summarise somehow but can’t work out how to do it so that i can have the column name as an argument.

Thanks

Answer 1

Is this what you’re after?

> ddply(df, .(f), colwise(sum))
    f          x           y          z
1   1 -0.4190284  2.61101681  1.2280026
2   2  1.1063977  2.40006922  4.9550079
3   3  0.4498366 -4.00610558  0.9964754
4   4  1.9325488 -2.81241212 -3.1185574
5   5 -4.1077670 -1.01232884 -3.9852388
6   6 -1.0488003 -2.42924689  3.5273636
7   7  2.2999306  0.85930085 -0.6245167
8   8 -4.8105311 -6.81352238 -2.1223436
9   9 -2.8187083  5.03391770  1.6433896
10 10  5.1323666 -0.06192382  1.8978994

Edit: correct answer as supplied by TS:

foo <- function(df.obj,colname){ddply(df, .(f), colwise(sum))[,c("f",colname)]}