knitr::opts_chunk$set( collapse = TRUE, comment = "#>", fig.path = "man/figures/README-" )
/dʒiː.dʒɪˈrɑːf/ (or g-giraffe)
ggraph is an extension of ggplot2
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) library(tidygraph) # 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 = after_stat(index)), show.legend = FALSE) + geom_node_point(aes(size = Popularity)) + facet_edges(~year) + theme_graph(foreground = 'steelblue', fg_text_colour = 'white')
ggraph
builds upon three core concepts that are quite easy to understand:
ggraph
has access to all layout functions available in igraph
and
furthermore provides a large selection of its own, such as hive plots, treemaps,
and circle packing.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. geom_node_point()
.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.
There are many different ways to store and work with relational data in R.
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 devtools
# install.packages("pak") pak::pak('thomasp85/ggraph')
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 most ambitious.
ggdendro
provides support for
dendrogram
and hclust
objects through conversion of the structures into
line segments that can then be plotted with geom_segment()
.
ggtree
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 network plots
ggnetwork
,
geomnet
, and
GGally
all provide some
functionality though none of them are as extensive in scope as ggraph
.
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.
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