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Accelerating ggplot2
ggforce
is a package aimed at providing missing functionality to ggplot2
through the extension system introduced with ggplot2
v2.0.0. Broadly speaking ggplot2
has been aimed primarily at explorative data visualization in order to investigate the data at hand, and less at providing utilities for composing custom plots a la D3.js. ggforce
is mainly an attempt to address these “shortcomings” (design choices might be a better description). The goal is to provide a repository of geoms, stats, etc. that are as well documented and implemented as the official ones found in ggplot2
.
You can install the released version of ggforce from CRAN with:
And the development version from GitHub with:
ggforce
is by design a collection of features with the only commonality being their tie to the ggplot2
API. Because of this an overview of all features would get too long for a README. The package has a website where every feature is described and justified with examples and plots. There should be a plot in the README of a visualization package though, so without further ado:
library(ggforce)
#> Loading required package: ggplot2
ggplot(iris, aes(Petal.Length, Petal.Width, colour = Species)) +
geom_point() +
facet_zoom(x = Species == "versicolor")
Please note that the ‘ggforce’ project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.