Resources

Useful Links

• R for Data Science (Functions): r4ds.hadley.nz/functions.html

• Quarto documentation (parameters): quarto.org/docs/computations/parameters.html

• Quarto documentation (conditional content): quarto.org/docs/authoring/conditional.html

• Ah, Ha, Ha, Ha, Parameterise!: www.cararthompson.com/talks/ah-ha-ha-ha-parameterise

• Parameterized presentations: www.jumpingrivers.com/blog/r-parameterised-presentations-quarto

• Dynamic tabsets: josh.quarto.pub/posts/2022-11-10-quarto-tabsets-update

• Data science resources: nrennie.rbind.io/data-science-resources

Collaborative editing

A frequently asked question from those thinking about switching to Quarto, is how do they collaborate with (non-technical) colleagues who prefer to use tools like Word/Gooogle Docs with track changes? Here are a few options you may find useful:

• trackdown: R package for collaborative writing and editing of R Markdown or Quarto documents in Google Docs.

• Quartorium: a collaborative WYSIWYG editor for Quarto

• Quarto 2: although not yet available, the developers of Quarto are working on a developing a new version of Quarto which will have an in-built collaborative editor to solve this problem!

Questions

When rendering multiple reports, can I map over multiple (dependent) parameters where only some combinations of the parameters are desired?

Yes, you can! As long as you have a way of defining what those combinations of parameters are. For example, this selects some different combinations of years and continents from the gapminder dataset:

params_df <- gapminder |>
  filter(
    year %in% c(2002, 2007) & continent %in% c("Europe") |
      year %in% c(1952, 1957) & continent %in% c("Asia", "Americas")
  ) |>
  select(continent, year) |>
  distinct()

You can then use walk() from {purrr} in a similar way to the examples, but mapping over each row of your parameter data:

walk(
  .x = 1:nrow(params_df),
  .f = ~ quarto_render(
    input = "example.qmd",
    output_file = glue("{params_df$continent[.x]}_{params_df$year[.x]}.html"),
    execute_params = list(
      choose_continent = params_df$continent[.x],
      choose_year = params_df$year[.x]
    )
  )
)

If my list of parameters is long, is there a nice way to see how long my code has left to run when generating multiple reports?

Yes, within walk(), set .progress = TRUE and this will create a progress bar in the console showing how far through your code is, and an approximate amount of time left. You can also use the {beepr} package to get your laptop to beep when the code is finished!