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https://github.com/davidgohel/ggiraph
make 'ggplot' graphics interactive
https://github.com/davidgohel/ggiraph
Last synced: 28 days ago
JSON representation
make 'ggplot' graphics interactive
- Host: GitHub
- URL: https://github.com/davidgohel/ggiraph
- Owner: davidgohel
- Created: 2015-08-01T22:17:06.000Z (over 9 years ago)
- Default Branch: master
- Last Pushed: 2024-05-17T09:39:13.000Z (7 months ago)
- Last Synced: 2024-11-09T00:54:41.022Z (about 1 month ago)
- Language: R
- Homepage: https://davidgohel.github.io/ggiraph
- Size: 36.1 MB
- Stars: 794
- Watchers: 22
- Forks: 73
- Open Issues: 20
-
Metadata Files:
- Readme: README.Rmd
Awesome Lists containing this project
- awesome-shiny-extensions - ggiraph - HTML widget that makes ggplot2 graphics interactive. Select graphical elements, add tooltips, animations, and JavaScript actions to the graphics. (Visualization / General-Purpose)
- awesome-r-dataviz - ggiraph - Make 'ggplot' graphics interactive. (Interactive plots / Miscellaneous)
README
---
output: github_document
---
```{r, echo = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-"
)
library(ggplot2)
library(ggiraph)
```
> `{ggiraph}` makes 'ggplot' graphics interactive.
[](https://github.com/davidgohel/ggiraph/actions)
[](https://CRAN.R-project.org/package=ggiraph)
[](https://app.codecov.io/gh/davidgohel/ggiraph)
## 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.
```{r eval=FALSE}
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
```{r eval=FALSE}
devtools::install_github('davidgohel/ggiraph')
```
> Get CRAN version
```{r eval=FALSE}
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](https://stackoverflow.com/questions/tagged/ggiraph+r)\! We
usually read them and answer when possible.
## Contributing to the package
### Bug reports
When you file a [bug report](https://github.com/davidgohel/ggiraph/issues), please spend
some time making it easy for me to follow and reproduce. The more time you spend on making
the bug report coherent, the more time I can dedicate to investigate the bug as opposed to
the bug report.
### Contributing to the package development
A great way to start is to contribute an example or improve the documentation.
If you want to submit a Pull Request to integrate functions of yours, provide if possible:
* the new function(s) with code and roxygen tags (with examples)
* a new section in the appropriate vignette that describes how to use the new function
* corresponding tests in directory `inst/tinytest`.
By using rhub (run `rhub::check_for_cran()`), you will see if everything is ok.
When submitted, the PR will be evaluated automatically with Github Action
and you will be able to see if something broke.