Note: This package has been maintained by @terrytangyuan since 2017. Please consider sponsoring!

autoplotly

This R package provides functionalities to automatically generate interactive visualizations for many popular statistical results supported by ggfortify package with plotly.js and ggplot2 style. The generated visualizations can also be easily extended using ggplot2 syntax while staying interactive.

You can play the examples interactively here.

Installation

To install the current version from CRAN, use:

install.packages("autoplotly")

To install from development version on Github, use:

devtools::install_github("terrytangyuan/autoplotly")

Example

# Automatically generate interactive plot for results produced by `stats::prcomp`
p <- autoplotly(prcomp(iris[c(1, 2, 3, 4)]), data = iris,
  colour = 'Species', label = TRUE, label.size = 3, frame = TRUE)

# Include additional data columns in the tooltip
autoplotly(prcomp(iris[c(1, 2, 3, 4)]), data = iris,
  colour = "Species",
  tooltip = c("x", "y", "colour", "Sepal.Length", "Petal.Length"))

# You can apply additional ggplot2 elements to the generated interactive plot
p +
  ggplot2::ggtitle("Principal Components Analysis") +
  ggplot2::labs(y = "Second Principal Components", x = "First Principal Components")

# Or apply additional plotly elements to the generated interactive plot
p %>% plotly::layout(annotations = list(
  text = "Example Text",
  font = list(
    family = "Courier New, monospace",
    size = 18,
    color = "black"),
  x = 0,
  y = 0,
  showarrow = TRUE))

Compatibility with ggplot2 4.0

Direct composition with ggplot2 elements, such as p + ggplot2::labs(...), is supported with ggplot2 4.0 on R 4.3 and later. On R 4.1 and R 4.2, pass the elements in a list to avoid the operator dispatch conflict:

p + list(
  ggplot2::ggtitle("Principal Components Analysis"),
  ggplot2::labs(y = "Second Principal Components", x = "First Principal Components")
)

Compatibility with ggplot2 3.x is unchanged.

You can autoplotly many other statistical results automatically with the help of ggfortify. A complete list can be found here.

Reference/Citation

To cite autoplotly in publications, please use the following (available via citation("autoplotly")):

Yuan Tang (2018). autoplotly: An R package for automatic generation of interactive visualizations for statistical results. Journal of Open Source Software, 3(24), 657, https://doi.org/10.21105/joss.00657

Yuan Tang, Masaaki Horikoshi, and Wenxuan Li (2016). ggfortify: Unified Interface to Visualize Statistical Result of Popular R Packages. The R Journal, 8.2, 478-489.