Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
---|---|---|---|---|---|---|---|---|---|---|
Voicebook | 325 | 7 months ago | 19 | apache-2.0 | Python | |||||
🗣️ A book and repo to get you started programming voice computing applications in Python (10 chapters and 200+ scripts). | ||||||||||
Flowmaker | 109 | 5 years ago | 2 | mit | TypeScript | |||||
flowmaker: JS to SVG flowchart generation extension for Vscode in realtime written in typescript and also download the SVG through local node server. Extension: | ||||||||||
Autoplotly | 76 | 2 years ago | 5 | April 18, 2021 | 1 | R | ||||
Automatic Generation of Interactive Visualizations for Statistical Results | ||||||||||
Microstructpy | 50 | 2 months ago | 32 | April 17, 2022 | 6 | mit | Python | |||
Microstructure modeling, mesh generation, analysis, and visualization. | ||||||||||
Icomesh | 37 | 4 years ago | 4 | isc | JavaScript | |||||
Fast JavaScript icosphere mesh generation library for WebGL visualizations | ||||||||||
Webtrees Pedigree Chart | 34 | 3 months ago | 15 | January 26, 2023 | 7 | gpl-3.0 | JavaScript | |||
SVG based pedigree chart module for webtrees genealogy application. | ||||||||||
Cpcstoryvisualization Pytorch | 33 | 2 years ago | Python | |||||||
Character-Preserving Coherent Story Visualization, ECCV 2020 | ||||||||||
Dungeonizer.js | 30 | 6 years ago | mit | JavaScript | ||||||
Dungeon generation + visualization. | ||||||||||
Gavrog | 27 | a year ago | apache-2.0 | Java | ||||||
Generation, analysis and visualization of reticular ornaments using Gavrog. | ||||||||||
Bluesense | 25 | a year ago | 8 | mit | Vue | |||||
🌈 BlueSense is a long-term project for monitoring Shanghai environment data. |
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.
To install the current version from CRAN, use:
install.packages("autoplotly")
To install from development version on Github, use:
devtools::install_github("terrytangyuan/autoplotly")
# 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)
# 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))
You can autoplotly
many other statistical results automatically with the help of ggfortify. A complete list can be found here.
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.