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Connected component

A connected component is a maximal subgraph in which every pair of vertices is connected by a path.

How 2 Manning books explain it

Graph Neural Networks in Action

A connected component is a maximal set of graph nodes in which every pair of nodes is connected by a path.

How it is used
Uses component structure to validate graph data, understand topology, and select a modeling subgraph.
How deep it goes
Explains the definition, counts components, compares their metrics, and demonstrates extraction, without deriving connectivity algorithms.
Examples
Uses fraud, candidate social, and Amazon product co-purchaser graphs for component counts, sparse-graph analysis, and connectivity inspection.
What you can do after
Apply it via NetworkX to count components, compare their sizes, isolate the largest subgraph, and support graph EDA.

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Grokking Data Structures

A connected component is a maximal subgraph in which every pair of vertices is connected by a path.

How it is used
Groups vertices into mutually reachable regions when a graph is disconnected.
How deep it goes
Defines connectivity, contrasts weak and strong directed connectivity, and stops short of presenting a component-finding algorithm.
Examples
Uses separate Tiger and Lion clusters, then examines the Chicken’s effect on weak and strong connectivity.
What you can do after
Evaluate whether a graph is connected and identify how its vertices divide into connected regions.

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Related concepts

These guides are generated from the text of Manning books by Manning's knowledge graph and link to the sections they draw on. The full books are available on liveBook and at manning.com.