/dʒiː.dʒɪˈrɑːf/ (or g-giraffe)
A grammar of graphics for relational data
ggraph is an extension of
aimed at supporting relational data structures such as networks, graphs,
and trees. While it builds upon the foundation of
ggplot2 and its API
it comes with its own self-contained set of geoms, facets, etc., as well
as adding the concept of layouts to the grammar.
library(ggraph) #> Loading required package: ggplot2 library(tidygraph) #> #> Attaching package: 'tidygraph' #> The following object is masked from 'package:stats': #> #> filter # Create graph of highschool friendships graph <- as_tbl_graph(highschool) %>% mutate(Popularity = centrality_degree(mode = 'in')) # plot using ggraph ggraph(graph, layout = 'kk') + geom_edge_fan(aes(alpha = stat(index)), show.legend = FALSE) + geom_node_point(aes(size = Popularity)) + facet_edges(~year) + theme_graph(foreground = 'steelblue', fg_text_colour = 'white')
The core concepts
ggraph builds upon three core concepts that are quite easy to
defines how nodes are placed on the plot, that is, it is a
conversion of the relational structure into an x and y value for
each node in the graph.
ggraphhas access to all layout functions available in
igraphand furthermore provides a large selection of its own, such as hive plots, treemaps, and circle packing.
are the connected entities in the relational structure. These can be
plotted using the
geom_node_*()family of geoms. Some node geoms make more sense for certain layouts, e.g.
geom_node_tile()for treemaps and icicle plots, while others are more general purpose, e.g.
are the connections between the entities in the relational
structure. These can be visualized using the
geom_edge_*()family of geoms that contain a lot of different edge types for different scenarios. Sometimes the edges are implied by the layout (e.g. with treemaps) and need not be plotted, but often some sort of line is warranted.
All of the tree concepts have been discussed in detail in dedicated blog posts that are also available as vignettes in the package. Please refer to these for more information.
Note: The linked blog posts are based on ggraph v1. After ggraph v1.1 the underlying implementation was moved to tidygraph and cleaned up, but this resulted in some breaking changes in the process. Therefore the vignette versions are generally recommended as they have been updated.
Supported data types
There are many different ways to store and work with relational data in
ggraph is built upon
tidygraph and the large swath of data
structures it supports are thus natively supported in
ggraph. In order
to get a data type supported by
ggraph, simply provide an
as_tbl_graph method for it.
ggraph is available through CRAN and can be installed with
install.packages('ggraph'). The package is under active development
though and the latest set of features can be obtained by installing from
this repository using
ggraph is not the only package to provide some sort of support for
relational data in
ggplot2, though I’m fairly certain that it is the
hclust objects through conversion of the
structures into line segments that can then be plotted with
provides more extensive support for all things tree-related, though it
lacks some of the layouts and edge types that
ggraph offers (it has
other features that
ggraph lacks though). For more standard hairball
GGally all provide some
functionality though none of them are as extensive in scope as
Code of Conduct
Please note that the ‘ggraph’ project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.