" class="reference-link">ggraph

/dʒiː.dʒɪˈrɑːf/ (or g-giraffe)

A grammar of graphics for relational data

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.

An example

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 = after_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
understand:

1. The
   Layout
   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. 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.
2. The
   Nodes
   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. geom_node_point().
3. The
   Edges
   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
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.

Installation

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')

Related work

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.

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.