Hi
above tapply and aggregate, split *apply could be used)
sapply(with(df, split(z, y)), mean)
Cheers
Petr
> -----Original Message-----
> From: R-help <r-help-boun...@r-project.org> On Behalf Of Luigi Marongiu
> Sent: Wednesday, November 17, 2021 2:21 PM
> To: r-help <r-help@r-project.org>
> Subject: [R] vectorization of loops in R
>
> Hello,
> I have a dataframe with 3 variables. I want to loop through it to get
> the mean value of the variable `z`, as follows:
> ```
> df = data.frame(x = c(rep(1,5), rep(2,5), rep(3,5)),
> y = rep(letters[1:5],3),
> z = rnorm(15),
> stringsAsFactors = FALSE)
> m = vector()
> for (i in unique(df$y)) {
> s = df[df$y == i,]
> m = append(m, mean(s$z))
> }
> names(m) = unique(df$y)
> > (m)
> a b c d e
> -0.6355382 -0.4218053 -0.7256680 -0.8320783 -0.2587004
> ```
> The problem is that I have one million `y` values, so the work takes
> almost a day. I understand that vectorization will speed up the
> procedure. But how shall I write the procedure in vectorial terms?
> Thank you
>
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