Rstudio Addin for Network Analysis and Visualization
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = "100%"
)
snahelper
provides a set RStudio Addin for social network analysis.
The main addin is the SNAhelper
which provides a simple GUI to do common network analytic tasks
and visualize a network with ggraph.
The second addin, called Netbuilder
allows you to quickly build small networks with a small
“canvas” to draw on. The network can be exported as an igraph object at the end of the session by clicking on “Done”.
The third addin Netreader
is meant to facilitated the import of raw network data. It provides a GUI to easily
read network and attribute data and combine them to an igraph object. The underlying code of the import procedure
is shown at the end. This should help users to learn importing data themselves.
The fourth addin Componentlayouter
allows to layout networks with several components manually by placing them on an empty
canvas. Components can also be rotated and resized. After finishing the session, the layout is saved as x and y vertex attributes.
Code to reproduce the used network.
library(tidyverse)
library(igraph)
url <- "https://raw.githubusercontent.com/evelinag/StarWars-social-network/master/networks/starwars-full-interactions-allCharacters.json"
df <- jsonlite::fromJSON(url)
df$nodes$id <- 1:nrow(df$nodes)
df$nodes$display <- df$nodes$name
df$nodes$name <- df$nodes$id-1
g <- graph_from_data_frame(df$links,directed = F,vertices = df$nodes)
V(g)$name <- V(g)$display
g <- remove.vertex.attribute(g,"id")
g <- remove.vertex.attribute(g,"display")
g <- delete.vertices(g,which(degree(g)==0))
V(g)$display <- ifelse(V(g)$value>75,V(g)$name,"")
V(g)$colour <- ifelse(V(g)$display=="",NA,V(g)$display)
g
Netreader
should be pretty selfexplanatory. The first two tabs allow you to import
raw data (edges and attributes). Make sure to specify file delimiters, etc. according to the shown preview.
Using the Netreader
should comes with a learning effect (hopefully). The last tab shows the R code
to produce the network with the chosen data without using the Addin.
The network will be saved in your global environment once you click “Done”.
Highlight an igraph object in your script and selcet the Componentlayouter
from the RStudio addin menu.
Components are added by clicking on the canvas and can be resized/rotated and re-positioned using the buttons at the
bottom. The final layout is stored as x and y coordinates in the igraph object.
# developer version
#install.packages(remotes)
remotes::install_github("schochastics/snahelper")
#CRAN version
install.packages("snahelper")
To work properly, you also need graphlayouts, which adds new
layout algorithms.
install.packages("graphlayouts")
To use the main addin, simply highlight a network in your script and select
SNAhelper
from the Addin dropdown menu.
The layout tab allows you to choose from all implemented algorithms in igraph
and
some layouts from graphlayouts
. The default is a stress based layout and also the recommended choice.
See my blog for an
explanation. In the tweak section you can move individual nodes around. Choose the node from
the dropdown menu and click on its new position in the plot.
The Node Attribute Manager shows all existing node attributes in a sortable table.
In addition, you can calculate some new ones (centrality and clustering).
The functions automatically choose the right version of indices, depending if
the network is directed/weighted/undirected/unweighted.
This is where you can style your nodes. You can either do it manually, by choosing a
color/size for all nodes together, or based on an attribute.
Same as Node Attribute Manager but for edges. So far only shows existing edge attributes.
You can style your edges here. snahelper
automatically detects if your network
is directed and adds arrows if the network is directed. The other options are similar to the nodes tab.
The snahelper automatically chooses the appropriate edge geom. If multiple edges are present, it uses
geom_edge_parallel0()
. Otherwise geom_edge_link0()
.
The result tab shows the network in its full size. If you are satisfied with the results, hit
the Done button and the R code to produce the plot is automatically inserted in your script.
Or you can directly save the result as a png file.