R Comments

How it works

A # starts a comment outside a quoted string. Comments can explain a unit, a missing-data policy or why a condition is needed. They do not run and cannot enforce the rule they describe. A hash inside quotation marks is ordinary text. Keep useful comments beside the code they qualify.

Run this R example

These examples run locally with R, not PHP, Python or JavaScript. The reviewed baseline is R 4.5.2 on Windows x64/UCRT, using only packages shipped with R. This is a tested version, not a newest-release claim. Install your own R from the official R project; an IDE is optional. Save the complete source as comments.R in a separate learning folder and run Rscript --vanilla comments.R. Keep code and fictional fixtures separate from a real project.

Bhylu has no R browser runner. There is no Try in playground link because the existing Python and JavaScript editors do not execute R. No package installation, account, network dataset, Apache, MySQL or PHP setting is needed to run these base-R sources.

The complete download uses a local scope, restores its temporary options and treats unexpected warnings as errors. Examples that handle an expected warning do so narrowly. Random examples change only their R process’s RNG state. File examples own their temporary output; figure examples leave their named PNG in the current learning folder and refuse to overwrite it. Use a new empty folder to rerun a figure.

Download the complete comments.R · Download all source files with hash checks

For the optional collection downloader, save download-examples.mjs in an empty folder and run node download-examples.mjs. Local preview before publishing uses node download-examples.mjs http://127.0.0.1:8000/examples/r/. It refuses an existing bhylu-r-examples folder and does not install or execute R.

Example

local({
  previous_options <- options(warn = 2, digits = 8, stringsAsFactors = FALSE)
  on.exit(options(previous_options), add = TRUE)
  # Each value describes one fictional session.
  visits <- c(8, 12, 10)
  label <- "Room #2"
  cat(label, "has", length(visits), "sessions\n")
  invisible(NULL)
})

# Each value describes one fictional session.
visits <- c(8, 12, 10)
label <- "Room #2"
cat(label, "has", length(visits), "sessions\n")

Expected result

Room #2 has 3 sessions

The first line is ignored by R. The hash in Room #2 remains in the label because it belongs to a string. The code actually calculates the session count, so the comment cannot drift into an unchecked hard-coded number.