Analysis

Data-driven styles Style nodes and edges automatically based on their data values

Shortest path Find and highlight the shortest path between two nodes

Cycle detection Detect and highlight all cycles in a graph

Weakly connected components Color nodes by their connected component

Data Lineage Trace which datasets produced a given report in a pipeline

Minimum Spanning Tree Highlight the minimum spanning tree of a graph (efficient way to link nodes)

BFS and DFS graph traversals Traverse a graph using breadth-first or depth-first search

Betweenness Color and scale nodes by their betweenness centrality score

Other centrality measures Compare degree, closeness, betweenness, and PageRank measures

Community detection newThis example demonstrates the Leiden community detection algorithm — an improvement over the Louvain algorithm that guarantees well-connected communities. A…