Network Visualization Examples with the ggplot2 Package

Samantha Tyner, François Briatte, and Heike Hofmann

2016-12-30

Intro

This vignette is intended to provide several examples of different network visualization methods in the ggplot2 / “tidyverse” framework. The methods, the geomnet package, the ggnetwork package, and the function GGally::ggnet2, are detailed in the paper Network Visualization with ggplot2 by the authors of this vignette.

Required Packages

library(dplyr)
library(tidyr)
library(ggplot2) # needs to be version ≥ 2.1.0
library(scales)

## ggnet2
if (!require(GGally, quietly = TRUE)) {
  getFromNamespace("install_github", asNamespace("devtools"))("ggobi/ggally")
}
## 
## Attaching package: 'GGally'
## The following object is masked from 'package:dplyr':
## 
##     nasa
## geom_net
if (!require(geomnet, quietly = TRUE) ||
    packageVersion("geomnet") < "0.2.0") {
  getFromNamespace("install_github", asNamespace("devtools"))("sctyner/geomnet")
}

## ggnetwork
if (!require(ggnetwork, quietly = TRUE) ||
    packageVersion("ggnetwork") < "0.5.1") {
  getFromNamespace("install_github", asNamespace("devtools"))("briatte/ggnetwork")
}

## pre-load
library(network)
## network: Classes for Relational Data
## Version 1.13.0 created on 2015-08-31.
## copyright (c) 2005, Carter T. Butts, University of California-Irvine
##                     Mark S. Handcock, University of California -- Los Angeles
##                     David R. Hunter, Penn State University
##                     Martina Morris, University of Washington
##                     Skye Bender-deMoll, University of Washington
##  For citation information, type citation("network").
##  Type help("network-package") to get started.
library(sna)
## Loading required package: statnet.common
## sna: Tools for Social Network Analysis
## Version 2.4 created on 2016-07-23.
## copyright (c) 2005, Carter T. Butts, University of California-Irvine
##  For citation information, type citation("sna").
##  Type help(package="sna") to get started.
library(GGally)
library(geomnet)
library(ggnetwork)
library(igraph)
## 
## Attaching package: 'igraph'
## The following objects are masked from 'package:sna':
## 
##     betweenness, bonpow, closeness, components, degree,
##     dyad.census, evcent, hierarchy, is.connected, neighborhood,
##     triad.census
## The following objects are masked from 'package:network':
## 
##     %c%, %s%, add.edges, add.vertices, delete.edges,
##     delete.vertices, get.edge.attribute, get.edges,
##     get.vertex.attribute, is.bipartite, is.directed,
##     list.edge.attributes, list.vertex.attributes,
##     set.edge.attribute, set.vertex.attribute
## The following objects are masked from 'package:tidyr':
## 
##     %>%, crossing
## The following objects are masked from 'package:dplyr':
## 
##     %>%, as_data_frame, groups, union
## The following objects are masked from 'package:stats':
## 
##     decompose, spectrum
## The following object is masked from 'package:base':
## 
##     union

Mad Men Relationship Network Example

geomnet

# make data accessible 
data(madmen, package = "geomnet")

# code for geom_net
# data step: merge edges and nodes by the "from" column

MMnet <- fortify(as.edgedf(madmen$edges), madmen$vertices)
## Using Name1 as the from node column and Name2 as the to node column.
## If this is not correct, rewrite dat so that the first 2 columns are from and to node, respectively.
## Joining edge and node information by from_id and label respectively.
# create plot
set.seed(10052016)
ggplot(data = MMnet, aes(from_id = from_id, to_id = to_id)) +
  geom_net(aes(colour = Gender), layout.alg = "kamadakawai", 
           size = 2, labelon = TRUE, vjust = -0.6, ecolour = "grey60",
           directed =FALSE, fontsize = 3, ealpha = 0.5) +
  scale_colour_manual(values = c("#FF69B4", "#0099ff")) +
  xlim(c(-0.05, 1.05)) +
  theme_net() +
  theme(legend.position = "bottom")
Mad Men relationship network included in the gcookbook package by Winston Chang visualized using geomnet.

Mad Men relationship network included in the gcookbook package by Winston Chang visualized using geomnet.

ggnet2

 library(GGally)
 library(network)
 # make the data available
 data(madmen, package = 'geomnet')
 # data step for both ggnet2 and ggnetwork
 # create undirected network
 mm.net <- network::network(madmen$edges[, 1:2], directed = FALSE)
 # create node attribute (gender)
 rownames(madmen$vertices) <- madmen$vertices$label
 mm.net %v% "gender" <- as.character(
   madmen$vertices[ network.vertex.names(mm.net), "Gender"]
 )
 # gender color palette
 mm.col <- c("female" = "#ff69b4", "male" = "#0099ff")
 # create plot for ggnet2
 set.seed(10052016)
 ggnet2(mm.net, color = mm.col[ mm.net %v% "gender" ],
        label = TRUE, label.color = mm.col[ mm.net %v% "gender" ],
        size = 2, vjust = -0.6, mode = "kamadakawai", label.size = 3)
Mad Men example using the ggnet2 function in the GGally package.

Mad Men example using the ggnet2 function in the GGally package.

ggnetwork

# create plot for ggnetwork. uses same data created for ggnet2 function
 library(ggnetwork)
 set.seed(10052016)
 ggplot(data = ggnetwork(mm.net, layout = "kamadakawai"),
        aes(x, y, xend = xend, yend = yend)) +
   geom_edges(color = "grey50") +
   geom_nodes(aes(colour = gender), size = 2) +
   geom_nodetext(aes(colour = gender, label = vertex.names),
                 size = 3, vjust = -0.6) +
   scale_colour_manual(values = mm.col) +
   xlim(c(-0.05, 1.05)) +
   theme_blank() +
   theme(legend.position = "bottom")
Mad Men example using the ggnetwork package.

Mad Men example using the ggnetwork package.

Blood Donation Example

Blood donation “network”: which blood types can give and receive?

ggnet2

# make data accessible
data(blood, package = "geomnet")

# plot with ggnet2 (Figure 2a)
set.seed(12252016)
ggnet2(network::network(blood$edges[, 1:2], directed=TRUE), 
       mode = "circle", size = 15, label = TRUE, 
       arrow.size = 10, arrow.gap = 0.05, vjust = 0.5,
       node.color = "darkred", label.color = "grey80")
ggnet implementation

ggnet implementation

geomnet

# plot with geomnet (Figure 2b)
set.seed(12252016)
ggplot(data = blood$edges, aes(from_id = from, to_id = to)) +
  geom_net(colour = "darkred", layout.alg = "circle", labelon = TRUE, size = 15,
           directed = TRUE, vjust = 0.5, labelcolour = "grey80",
           arrowsize = 1.5, linewidth = 0.5, arrowgap = 0.05,
           selfloops = TRUE, ecolour = "grey40") + 
  theme_net()
geom_net implementation

geom_net implementation

ggnetwork

# plot with ggnetwork (Figure 2c)
set.seed(12252016)
ggplot(ggnetwork(network::network(blood$edges[, 1:2]),
                 layout = "circle", arrow.gap = 0.05),
       aes(x, y, xend = xend, yend = yend)) +
  geom_edges(color = "grey50",
             arrow = arrow(length = unit(10, "pt"), type = "closed")) +
  geom_nodes(size = 15, color = "darkred") +
  geom_nodetext(aes(label = vertex.names), color = "grey80") +
  theme_blank()
ggnetwork implementation

ggnetwork implementation

Email Network Example

A faux company’s email network provided by the 2014 VAST Challenge.

ggnet2

# make data accessible
data(email, package = 'geomnet')

# create node attribute data
em.cet <- as.character(
  email$nodes$CurrentEmploymentType)
names(em.cet) = email$nodes$label

# remove the emails sent to all employees
edges <- subset(email$edges, nrecipients < 54)
# create network
em.net <- edges[, c("From", "to") ]
em.net <- network::network(em.net, directed = TRUE)
# create employee type node attribute
em.net %v% "curr_empl_type" <-
  em.cet[ network.vertex.names(em.net) ]
set.seed(10312016)
ggnet2(em.net, color = "curr_empl_type",
       size = 4, palette = "Set1",
       arrow.size = 5, arrow.gap = 0.02,
       edge.alpha = 0.25, mode = "fruchtermanreingold",
       edge.color = c("color", "grey50"),
       color.legend = "Employment Type") +
  theme(legend.position = "bottom")
## Warning: Removed 727 rows containing missing values (geom_segment).
The company’s email network visualized with ggnet2.

The company’s email network visualized with ggnet2.

geomnet

# data step for the geomnet plot
email$edges <- email$edges[, c(1,5,2:4,6:9)]
emailnet <- fortify(
  as.edgedf(subset(email$edges, nrecipients < 54)),
  email$nodes)
## Using From as the from node column and to as the to node column.
## If this is not correct, rewrite dat so that the first 2 columns are from and to node, respectively.
## Joining edge and node information by from_id and label respectively.
set.seed(10312016)
ggplot(data = emailnet,
       aes(from_id = from_id, to_id = to_id)) +
  geom_net(layout.alg = "fruchtermanreingold",
    aes(colour = CurrentEmploymentType,
        group = CurrentEmploymentType,
        linewidth = 3 * (...samegroup.. / 8 + .125)),
    ealpha = 0.25,
    size = 4, curvature = 0.05,
    directed = TRUE, arrowsize = 0.5) +
  scale_colour_brewer("Employment Type", palette = "Set1") +
  theme_net() +
  theme(legend.position = "bottom")