Edge list to adjacency matrix converter

Turn a compact graph edge list into a clear adjacency matrix without building the table by hand. Enter one connection per line, choose whether the graph is directed and whether each edge has a weight, and receive a square matrix with an explicit node order. The converter accepts comma-separated or whitespace-separated lines, can retain isolated nodes through an optional node list, and uses stable first-seen ordering for every other vertex. It is designed for algorithm visualization, classroom demonstrations, worked exercises, and quick checks of graph data before coding.

Write the edge list and choose the graph model

Begin with one edge on each line. For an unweighted graph, write two node names such as A B or A,B; the first value is the source and the second is the target. Node names are kept as labels, so letters, numbers, and short identifiers all work, provided a name contains no spaces or commas.

Select directed mode when A to B should mark only row A, column B. Leave directed mode off when the same edge should also mark row B, column A. For a weighted graph, enable weighted mode and add a finite, non-zero number as the third value on every line, for example A B 2.5.

Mixing weighted and unweighted rows is rejected because it would make the meaning of the matrix inconsistent. Blank lines are ignored, while incomplete rows, extra values, and duplicate edges produce a specific input error instead of a silently altered graph. This strictness makes the result suitable for lessons and automated examples where every entry needs a clear explanation.

Read the node order, rows, and columns

An adjacency matrix only makes sense when its node order is known, so the result always returns the node labels beside the matrix. Unless you provide a node list, vertices appear in the order they are first encountered while reading edges from top to bottom. Matrix row i describes edges leaving node i, and column j represents the destination node j.

In an unweighted matrix, a connection is marked with 1 and no connection is marked with 0. In weighted mode, the edge weight replaces 1, while 0 still means that no edge was supplied. Undirected graphs produce a symmetric matrix because each edge is written in both mirrored cells.

Directed graphs may be asymmetric, which makes incoming and outgoing relationships immediately visible. Self-loops are supported and appear on the main diagonal. The response also reports the selected directed and weighted settings and the number of input edges, making it easier to label a visualization or verify that a classroom transcription included every intended connection.

Include isolated nodes and avoid ambiguous data

An edge list cannot reveal a vertex that has no edges. To preserve isolated vertices, supply the optional nodes array in the exact order you want displayed. The converter rejects repeated names in that array because duplicate row labels would make the matrix ambiguous.

It also rejects duplicate edge declarations rather than adding weights or letting the last line win. For an undirected graph, A B and B A count as the same edge; for a directed graph, they are separate edges and occupy different cells. Zero weights are rejected because this matrix reserves zero to mean no connection, so accepting a zero-weight edge would hide its existence.

These rules are useful when teaching graph traversal, degree calculations, shortest-path inputs, or matrix representations: students can trace each edge to one predictable cell or mirrored pair.