Install from CRAN:
Or install the latest development version (on GitHub) via devtools:
Web-based ggplot2 graphics
If you use ggplot2,
ggplotly() converts your static plots to an interactive web-based version!
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)
ggplotly() tries to replicate the static ggplot2 version exactly (before any interaction occurs), but sometimes you need greater control over the interactive behavior. The
ggplotly() function itself has some convenient “high-level” arguments, such as
dynamicTicks, which tells plotly.js to dynamically recompute axes, when appropriate. The
style() function also comes in handy for modifying the underlying trace attributes (e.g. hoveron) used to generate the plot:
gg <- ggplotly(g, dynamicTicks = "y") style(gg, hoveron = "points", hoverinfo = "x+y+text", hoverlabel = list(bgcolor = "white"))
ggplotly() returns a plotly object, you can apply essentially any function from the R package on that object. Some useful ones include
layout() (for customizing the layout),
add_traces() (and its higher-level
add_*() siblings, for example
add_polygons(), for adding new traces/data),
subplot() (for combining multiple plotly objects), and
plotly_json() (for inspecting the underlying JSON sent to plotly.js).
ggplotly() function will also respect some “unofficial” ggplot2 aesthetics, namely
text (for customizing the tooltip),
frame (for creating animations), and
ids (for ensuring sensible smooth transitions).
Using plotly without ggplot2
plot_ly() function provides a more direct interface to plotly.js so you can leverage more specialized chart types (e.g., parallel coordinates or maps) or even some visualization that the ggplot2 API won’t ever support (e.g., surface, mesh, trisurf, etc).
plot_ly(z = ~volcano, type = "surface")
demo(package = "plotly")) and shiny/rmarkdown examples (list them by running
plotly_example("rmd")). Carson also keeps numerous slide decks with useful examples and concepts.
Please read through our contributing guidelines. Included are directions for opening issues, asking questions, contributing changes to plotly, and our code of conduct.