The R Markdown a11y theme

Theme used

rmarkdown::metadata$output %>% 
  pluck(1, "highlight")
[1] "themes/arrow-pandoc.theme"

Downlit used?

rmarkdown::metadata$output %>% 
  pluck(1, "highlight_downlit")
[1] FALSE

Testing colors here

gitbook(fig_caption = TRUE, number_sections = TRUE,
  self_contained = FALSE, lib_dir = "libs",
  pandoc_args = NULL, ..., template = "default",
  split_by = c("chapter", "chapter+number", "section", "section+number", "rmd", "none"),
  split_bib = TRUE, config = list(), table_css = TRUE)

ui <- fluidPage(
  fileInput("upload", NULL, buttonLabel = "Upload...", multiple = TRUE),
  tableOutput("files")
)
server <- function(input, output, session) {
  output$files <- renderTable(input$upload)
}

server <- function(input, output, session) {
  t <- reactive(seq(0, input$length, length = input$length * 100))
  x <- reactive(sin(input$omega * t() + input$delta) * input$damping ^ t())
  y <- reactive(sin(t()) * input$damping ^ t())

  output$fig <- renderPlot({
    plot(x(), y(), axes = FALSE, xlab = "", ylab = "", type = "l", lwd = 2)
  }, res = 96)
  
  observe({
    reactiveValuesToList(input)
    session$doBookmark()
  })
  onBookmarked(updateQueryString)
}

---
title: "Distill for R Markdown"
description: | 
  Scientific and technical writing, native to the web
output:
  distill::distill_article:
    toc: true
    toc_depth: 2
---

library(palmerpenguins)
library(tidyverse)
penguins %>% 
  dplyr::filter(year == 2007 & species == "Gentoo") %>% 
  dplyr::summarise(mean_fl = mean(flipper_length_mm, na.rm = TRUE))
# A tibble: 1 x 1
  mean_fl
    <dbl>
1    215.

glimpse(penguins)
Rows: 344
Columns: 8
$ species           <fct> Adelie, Adelie, Adelie, Adelie, Adelie, Ad…
$ island            <fct> Torgersen, Torgersen, Torgersen, Torgersen…
$ bill_length_mm    <dbl> 39.1, 39.5, 40.3, NA, 36.7, 39.3, 38.9, 39…
$ bill_depth_mm     <dbl> 18.7, 17.4, 18.0, NA, 19.3, 20.6, 17.8, 19…
$ flipper_length_mm <int> 181, 186, 195, NA, 193, 190, 181, 195, 193…
$ body_mass_g       <int> 3750, 3800, 3250, NA, 3450, 3650, 3625, 46…
$ sex               <fct> male, female, female, NA, female, male, fe…
$ year              <int> 2007, 2007, 2007, 2007, 2007, 2007, 2007, …

# Histogram example: flipper length by species
ggplot(data = penguins, aes(x = flipper_length_mm)) +
  geom_histogram(aes(fill = species), alpha = 0.5, position = "identity") +
  scale_fill_manual(values = c("darkorange","darkorchid","cyan4"))

Figure 1: some cool penguins

mass_flipper <- ggplot(data = penguins,
                       aes(x = flipper_length_mm,
                           y = body_mass_g)) +
  geom_point(aes(color = species,
                 shape = species),
             size = 3,
             alpha = 0.8) +
  theme_minimal() +
  scale_color_manual(values = c("darkorange","purple","cyan4")) +
  labs(title = "Penguin size, Palmer Station LTER",
       subtitle = "Flipper length and body mass for Adelie, Chinstrap and Gentoo Penguins",
       x = "Flipper length (mm)",
       y = "Body mass (g)",
       color = "Penguin species",
       shape = "Penguin species") +
  theme(legend.position = c(0.2, 0.7),
        legend.background = element_rect(fill = "white", color = NA),
        plot.title.position = "plot",
        plot.caption = element_text(hjust = 0, face= "italic"),
        plot.caption.position = "plot")

mass_flipper