Simplified theming of ggplot2, lattice, and {base} R graphics. In addition to providing a centralized approach to styling R graphics, thematic also enables automatic styling of R plots in Shiny, R Markdown, and RStudio.

Installation

Install the stable release of thematic on CRAN with:

install.packages("thematic")

Auto theming in Shiny requires shiny 1.5.0 or higher:

Auto theming in R Markdown requires rmarkdown 2.7 or higher:

install.packages("rmarkdown")

Using themes with custom fonts works best if you have showtext and/or ragg installed.

Overview

thematic’s auto theming gives R plots the ability to style themselves inside Shiny (via CSS), RStudio (via RStudio themes), and R Markdown (via {bslib}).

Shiny

Call thematic_shiny() before launching a Shiny app to enable thematic for every plotOutput() inside the app. If no values are provided to thematic_shiny(), each plotOutput() uses the app’s CSS colors to inform new R plotting defaults. If the app uses Google Fonts (and you have showtext and/or ragg installed), you may safely provide font = "auto" to thematic_shiny(), which also translates CSS fonts to R. Here’s an example with the Pacifico font:

library(shiny)
library(ggplot2)
library(thematic)

# Call thematic_shiny() prior to launching the app, to change 
# R plot theming defaults for all the plots generated in the app
thematic_shiny(font = "auto")

ui <- fluidPage(
  # bslib makes it easy to customize CSS styles for things 
  # rendered by the browser, like tabsetPanel()
  # https://rstudio.github.io/bslib
  theme = bslib::bs_theme(
    bg = "#002B36", fg = "#EEE8D5", primary = "#2AA198",
    # bslib also makes it easy to import CSS fonts
    base_font = bslib::font_google("Pacifico")
  ),
  tabsetPanel(
    type = "pills",
    tabPanel("ggplot", plotOutput("ggplot")),
    tabPanel("lattice", plotOutput("lattice")),
    tabPanel("base", plotOutput("base"))
  )
)

server <- function(input, output) {
  output$ggplot <- renderPlot({
    ggplot(mtcars, aes(wt, mpg, label = rownames(mtcars), color = factor(cyl))) +
      geom_point() +
      ggrepel::geom_text_repel()
  })
  output$lattice <- renderPlot({
    lattice::show.settings()
  })
  output$base <- renderPlot({
    image(volcano, col = thematic_get_option("sequential"))
  })
}

shinyApp(ui, server)

RStudio

Call thematic_on() before generating plots inside RStudio to have all subsequent plots shown in the “Plots” viewing pane to reflect your RStudio theme. Note that thematic_on() enables thematic for the remainder of the R session, but you can use thematic_off() to disable (or thematic_theme() for one-off use of {thematic}). Here’s an example of how thematic can intelligently adapt each plot to the current RStudio theme:

R Markdown

Call thematic_rmd() before generating plots inside R Markdown to have all subsequent plots within the document reflect the relevant theme. In a static (i.e., non-runtime: shiny) R Markdown context, auto-theming only works with {bslib}-powered rmarkdown::html_document() (as in the example below), but in other situations you may also provide colors and fonts explicitly to thematic_rmd().

Custom theming

By default, thematic attempts to detect the relevant background, foreground, and accent colors. However, you may also specify these settings more directly by providing relevant color and fonts directly to thematic_on() (or thematic_shiny()/thematic_rmd()).

library(ggplot2)
thematic::thematic_on(bg = "#222222", fg = "white", accent = "#0CE3AC", font = "Oxanium")

ggp <- ggplot(mtcars, aes(wt, mpg, label = rownames(mtcars), color = factor(cyl))) +
  geom_point() +
  ggrepel::geom_text_repel()
ggp

thematic works by setting new global defaults that can always be overridden with plot-specific theme()-ing code:

ggp + theme(text = element_text(colour = "purple"))

To use a “complete” ggplot2 theme with thematic (e.g., theme_bw(), theme_minimal(), etc), use theme_set() to set the theme globally. This way thematic has the opportunity to preserve the complete theme’s styling semantics when changing global defaults (e.g., theme_bw() uses the same fill color for the panel and plot background, which is semantically different from the theme_gray() default):

In addition to setting new defaults for main colors and fonts, thematic also sets defaults for qualitative (and sequential) colorscales. See the custom themes article to learn more about how to customize those defaults.

Learn more

Run some examples

Below is a link to an RStudio Cloud instance with some ready to run thematic examples:

Code of Conduct

thematic is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.