An R package for creating interactive web graphics via the open source JavaScript graphing library plotly.js.
Install from CRAN:
install.packages("plotly")Or install the latest development version (on GitHub) via devtools:
devtools::install_github("ropensci/plotly")If you use ggplot2, ggplotly() converts your plots to an interactive, web-based version! It also provides sensible tooltips, which assists decoding of values encoded as visual properties in the plot.
library(plotly)
g <- ggplot(faithful, aes(x = eruptions, y = waiting)) +
stat_density_2d(aes(fill = ..level..), geom = "polygon") +
xlim(1, 6) + ylim(40, 100)
ggplotly(g)
If you'd like to see how ggplotly() does in converting different ggplot2 examples, we host a plotly version of the official ggplot2 documentation. We also have some of our own examples here.
plotly.js supports some chart types that ggplot2 doesn't (our cheatsheet provides a nice summary of the available chart types). You can create any of these charts via plot_ly().
plot_ly(z = ~volcano, type = "surface")
We have a number of vignettes which explain the plot_ly() interface in depth as well as numerous examples on the plotly website and bundled with the package.
plotly.js exposes a number of 'standard' events that work consistently across plot types. It's easy to hook into these events using the event_data() function in shiny apps, as these examples demonstrate:
You can also hook into these events without shiny using htmlwidgets::onRender() (example). This, however, requires JavaScript knowledge and makes it much harder to coordinate views between htmlwidgets.
We have lots of examples on https://plot.ly/r/ and https://plot.ly/ggplot2/, but a more comprehensive review is also available at https://cpsievert.github.io/plotly_book/
Please read through our contributing guidelines. Included are directions for opening issues, asking questions, contributing changes to plotly, and our code of conduct.
