Number of Connected Components in an Undirected Graph
Given n nodes (labeled 0 to n-1) and a list of undirected edges, return the number of connected components in the graph.
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Problem
You have a graph of n nodes. Given an integer n and an array edges where edges[i] = [ai, bi] indicates that there is an edge between ai and bi, return the number of connected components in the graph.
Input
An integer `n` and a list of `edges` where `edges[i] = [a, b]`.
Output
The number of connected components.
Examples
Input: n = 5, edges = [[0,1],[1,2],[3,4]]
Output: 2
Components: {0,1,2} and {3,4}.
Input: n = 5, edges = [[0,1],[1,2],[2,3],[3,4]]
Output: 1
All 5 nodes are connected.
The brute-force approach
Build an adjacency list and BFS/DFS from each unvisited node. Each new BFS/DFS that starts marks one connected component.
adj = defaultdict(list)
for a, b in edges:
adj[a].append(b); adj[b].append(a)
visited = set()
components = 0
for node in range(n):
if node not in visited:
bfs(node, visited, adj)
components += 1
return componentsO(V + E) — actually optimal. Union-Find is often preferred for dynamic connectivity or when edges are added incrementally.
Spotting the pattern
This is a Union-Find problem. The key question to ask yourself:
Each node starts in its own "group." When you process edge [a, b], how do you check whether a and b are already in the same group?
Answering that is where it clicks, and it's exactly what the guided walkthrough below builds with you: the pattern reasoning, a progressive hint ladder that never spoils the answer, a row-by-row dry run, the optimized solution, and an in-browser editor to run your code against real test cases.
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