{ggiraph} makes ‘ggplot’ graphics interactive.

Overview

{ggiraph} is a tool that allows you to create dynamic ggplot graphs. This allows you to add tooltips, hover effects and JavaScript actions to the graphics. The package also allows the selection of graphical elements when used in shiny applications.

Interactivity is added to ggplot geometries, legends and theme elements, via the following aesthetics:

• tooltip: tooltips to be displayed when mouse is over elements.
• onclick: JavaScript function to be executed when elements are clicked.
• data_id: id to be associated with elements (used for hover and click actions)

Why use {ggiraph}

• You want to provide your readers with more information than the basic information available; you can display a tooltip when the user’s mouse is on a graphical element, you can also visually animate elements with the same attribute when the mouse passes over a graphical element, and finally you can link a JavaScript action to the click, such as opening a hypertext link.
• You want to allow users of a Shiny application to select graphical elements; for example, you can make the points of a scatter plot selectable and available as a reactive value from the server part of your application. With Shiny, {ggiraph} allows interaction with graph elements, legends elements, titles and ggplot theme elements from the server part; each selection is available as a reactive value.

Under the hood, {ggiraph} is an htmlwidget and a ggplot2 extension. It allows graphics to be interactive, by exporting them as SVG documents and using special attributes on the various elements.

Usage

With R and R Markdown

The things you need to know to create an interactive graphic :

• Instead of using geom_point, use geom_point_interactive, instead of using geom_sf, use geom_sf_interactive… Provide at least one of the aesthetics tooltip, data_id and onclick to create interactive elements.
• Call function girafe with the ggplot object so that the graphic is translated as a web interactive graphics.

library(ggplot2)
library(ggiraph)
data <- mtcars
data$carname <- row.names(data)

gg_point = ggplot(data = data) +
    geom_point_interactive(aes(x = wt, y = qsec, color = disp,
    tooltip = carname, data_id = carname)) + 
  theme_minimal()

girafe(ggobj = gg_point)

With Shiny

• If used within a shiny application, elements associated with an id (data_id) can be selected and manipulated on client and server sides. The list of selected values will be stored in in a reactive value named [shiny_id]_selected.

Available interactive layers

They are several available interactive geometries, scales and other ggplot elements. Almost all ggplot2 elements can be made interactive with {ggiraph}. They are all based on their ggplot version, same goes for scales and the few guides: geom_point_interactive(), geom_col_interactive(), geom_tile_interactive(), scale_fill_manual_interactive(), scale_discrete_manual_interactive(), guide_legend_interactive(), …

You can also make interactive annotations, titles and facets (see help(interactive_parameters)).

Installation

Get development version on github

# devtools::install_github('davidgohel/ggiraph')
install.packages("ggiraph", repos = c('https://davidgohel.r-universe.dev', 'https://cloud.r-project.org'))

Get CRAN version

install.packages("ggiraph")

Resources

Online documentation

The help pages are located at https://davidgohel.github.io/ggiraph/.

Getting help

If you have questions about how to use the package, visit Stackoverflow and use tags ggiraph and r Stackoverflow link! We usually read them and answer when possible.

Contributing to the package

Bug reports

Bugs are reported through GitHub issues. The issue form requires a reproducible example (a reprex) and the output of sessionInfo(); reports missing these elements are closed without further response. The more reproducible your report, the more time can go into investigating the bug rather than reconstructing it.

For usage questions (“how do I do X with ggiraph”), please read https://ardata.fr/ggiraph-book/ or ask on Stack Overflow with the [r] tag instead.

Pull requests

Before writing any code, please open an issue describing the change you have in mind and the reason for it. The proposal needs to be discussed and explicitly validated by the maintainer before work starts; pull requests for features that have not gone through this step will not be considered, no matter how well crafted. This isn’t meant to discourage contributions, only to make sure the time you invest goes into a change that will actually land.

Pull requests are accepted on a case-by-case basis: once a proposal has been agreed in an issue, the maintainer will invite you to open a PR for that specific change. Unsolicited PRs that bypass this step will be closed.

When invited to open a PR, please include:

• the new function(s) with code and roxygen tags, including runnable examples
• documentation updates where relevant
• corresponding tests in directory inst/tinytest.

Install from sources on macOS

Please read carefully the official R for macOS instructions: https://mac.r-project.org/

To compile {ggiraph} from source, you need libpng. Using Homebrew is recommended:

brew install libpng

Then configure your ~/.R/Makevars file with the appropriate paths. For Apple Silicon Macs (M1/M2/M3), the typical configuration is:

CFLAGS=-I/opt/homebrew/include
CPPFLAGS=-I/opt/homebrew/include
CXXFLAGS=-I/opt/homebrew/include
CXX11FLAGS=-I/opt/homebrew/include
LDFLAGS=-L/opt/homebrew/lib

For Intel Macs, paths are usually /usr/local/include and /usr/local/lib instead.

CFLAGS=-I/usr/local/include
CPPFLAGS=-I/usr/local/include
CXXFLAGS=-I/usr/local/include
CXX11FLAGS=-I/usr/local/include
LDFLAGS=-L/usr/local/lib

Note: Paths may vary depending on your system configuration. We are unable to provide support for installation issues related to macOS compilation setup.