[R] Weighted Average on More than One Variable in Data Frame

[StellathePug]

Dear R Users,
I have looked for a solution to the following problem and I have not been
able to find it on the archive, through Google or in the R documentation.

I have a data frame, say df, which has 4 variables, one of which I would
like to use as a grouping variable (g), another one that I would like to use
for my weights (w) The other two variables are variables (x1 and x2) for
which I would like to compute the weighted average by group.

df <- data.frame(x1 = c(15, 12,  3, 10, 10, 14, 12), 
                       x2 = c(10, 11, 16,  9,   7, 17, 18),
                        g = c(  1,   1,  1,  2,   2,   3,  3), 
                        w = c( 2,   3,  1,  5,   5,   2,  5)) 

wx1 <- sapply(split(df, df$g), function(x){weighted.mean(x$x1, x$w)}) 
wx2 <- sapply(split(df, df$g), function(x){weighted.mean(x$x2, x$w)})

The above code works, the result is:
> wx1
       1        2        3 
11.50000 10.00000 12.57143 
> wx2
       1        2        3 
11.50000  8.00000 17.71429

But is there not a more elegant way of acting on x1 and x2 simultaneously?
Something along the lines of

wdf <- sapply(split(df, df$g), function(x){weighted.mean(df, x$w)})

which is wrong since df has two columns, while w only has one. I suppose,
one could write a loop but that strikes me as being highly inefficient.

Thank you very much for your help!
Rita

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