NodeXL allows users to gather vertices into named collections called “Groups”. This is handy whenever the entities in the network are made up of different types or an algorithm has divided the network into sub-regions based on how densely some vertices connect to one another. The Groups menu is found in the NodeXL>Analysis menu:
Since version v.132 of NodeXL it has been possible to Collapse a group of vertices (See: Expand and Collapse Groups of Vertices with NodeXL v.132). When a group is collapsed all of the vertices within that group are removed from the network graph and replaced with a single vertex with a size proportionate to the number of vertices in the group. A small “+” plus sign indicates that the vertex is a placeholder for a group of vertices.
If the user expands a collapsed group all of the vertices that had been hidden return to positions in the network visualization. The Groups menu has commands for creating, collapsing, and expanding groups.
NodeXL (v.166) now has the ability to automatically collapse or expand any group of vertices conditionally based on any attribute in the workbook using the Autofill Columns feature.
The NodeXL Autofill columns feature allows users to map data elements to display elements. At the bottom of this list (you may need to scroll down to see it) you will now find a new row: Group Collapsed?
There are several network metric attributes for each group that are created when the Find Groups and then the Graph Metrics command has been run on a network in NodeXL:
Selecting one of the data items in the drop down allows you to automatically decide if a group with those attributes will be presented in a collapsed or (default) expanded state. The data about each group include the number of vertices within the group, the number of connections between those vertices, the number of non-unique connections, the number of unique connections among the vertices, the number of self-connections, the number of unique connected components, the number of isolated vertices, the number of vertices in the largest component, the number of edges in the largest component, the maximum and average width of the largest component, and the density of the group.
These metrics allow for the automated processing of the graph to measure each group and apply a test to decide if a group is too dense or populous to be seen in an expanded state.