|
> mtcars |> subset(cyl == 4) |> nrow() # Using the pipe character
[1] 11
</syntaxhighlight>
Another alternative to nested functions is the use of intermediate objects, rather than the pipe operator:
<syntaxhighlight lang="rout">
> mtcars_subset_rows <- subset(mtcars, cyl == 4)
> num_mtcars_subset <- nrow(mtcars_subset_rows)
> print(num_mtcars_subset)
[1] 11
</syntaxhighlight>While the pipe operator can produce code that is easier to read, it is advisable to chain together at most 10-15 lines of code using this operator, as well as to chunk code into [[Task (project management)|sub-tasks]] that are saved into objects having meaningful names.<ref>{{Cite book |last=Wickham |first=Hadley |url=https://r4ds.hadley.nz/ |title=R for data science: import, tidy, transform, visualize, and model data |last2=Çetinkaya-Rundel |first2=Mine |last3=Grolemund |first3=Garrett |date=2023 |publisher=O'Reilly |isbn=978-1-4920-9740-2 |edition=2nd |___location=Beijing; Sebastopol, CA |chapter=4 Workflow: code style |oclc=on1390607935 |chapter-url=https://r4ds.hadley.nz/workflow-style.html}}</ref>
The following is an example having fewer than 10 lines, which some readers may find difficult to grasp in the absence of intermediate named steps:<syntaxhighlight lang="r" line="1">(\(x, n = 42, key = c(letters, LETTERS, " ", ":", ")"))
strsplit(x, "")[[1]] |>
(Vectorize(\(chr) which(chr == key) - 1))() |>
(`+`)(n) |>
(`%%`)(length(key)) |>
(\(i) key[i + 1])() |>
paste(collapse = "")
)("duvFkvFksnvEyLkHAErnqnoyr")</syntaxhighlight>The following is a version of the preceding code that is easier to read:<syntaxhighlight lang="r">
default_key <- c(letters, LETTERS, " ", ":", ")")
f <- function(x, n = 42, key = default_key) {
split_input <- strsplit(x, "")[[1]]
results <- (Vectorize(\(chr) which(chr == key) - 1))(split_input) |>
(`+`)(n) |>
(`%%`)(length(key)) |>
(\(i) key[i + 1])()
combined_results <- paste(results, collapse = "")
return(combined_results)
}
f("duvFkvFksnvEyLkHAErnqnoyr")
</syntaxhighlight>
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