Optimize R chains (magrittr)

Question

I would like to pipe (chain) magrittr object into loop. How can I do this?
I will use dummy operations/data as an example:

library(data.table)
library(magrittr)

# Dummy data modification
d <- mtcars %>%
    setDT() %>%
    .[, cylSQ := sqrt(cyl)] %>%
    .[, carb3 := carb^3]
# Dummy loop
res <- list()
for(i in unique(d$gear)) {
    res[[i]] <- d[gear == i] %>%
        .[, lm(cylSQ ~ mpg + carb3 * wt)] %>%
        .$fitted.values
}

Is it possible not to create object d and to pipe it directly to loop? For example:

for(i in unique(.$gear)) {
    res[[i]] <- .[gear == i] %>%
    ...
}

Edit: I don't want to replace loop with data.table or dplyr , just curious about piping.

Answer 1

Don't you mind using dplyr instead of data.table here? If not, try this:

library(dplyr)
d <- mtcars %>% 
    mutate(cylSQ = sqrt(cyl), carb3 = carb^3) %>% 
    group_by(gear) %>% 
    do(fitted.values = lm(cylSQ ~ mpg + carb3 * wt, data = .)[["fitted.values"]])

Answer 2

This is a bit of sketchy work around, but you can use the exposition operator in the magrittr package %$% .

Ie:

mtcars %>% 
  filter(hp > 1) %$%
  for(i in 1:ncol(.)) {
    print(.[1,i])
  }

[1] 21
[1] 6
[1] 160
[1] 110
[1] 3.9
[1] 2.62
[1] 16.46
[1] 0
[1] 1
[1] 4
[1] 4

Answer 3

I'm not magrittr practitioner so it could probably be improved, but at least works, and should be efficient.

as.data.table(mtcars
              )[, cylSQ := sqrt(cyl)
                ][, carb3 := carb^3
                  ][, lm(cylSQ ~ mpg + carb3 * wt)$fitted.values, by=gear
                    ] %>% 
    split(by = "gear", keep.by = FALSE) %>% 
    lapply(unlist) %>% 
    lapply(unname) -> res

Due to new split.data.table it requires data.table in 1.9.7, see installation wiki for details how to install on various platforms.