Products
  • Wolfram|One

    The definitive Wolfram Language and notebook experience

  • Mathematica

    The original technical computing environment

  • Notebook Assistant + LLM Kit

    All-in-one AI assistance for your Wolfram experience

  • Compute Services
  • System Modeler
  • Finance Platform
  • Wolfram|Alpha Notebook Edition
  • Application Server
  • Enterprise Private Cloud
  • Wolfram Engine
  • Wolfram Player
  • Wolfram Cloud App
  • Wolfram Player App

More mobile apps

Core Technologies of Wolfram Products

  • Wolfram Language
  • Computable Data
  • Wolfram Notebooks
  • AI & Linguistic Understanding

Deployment Options

  • Wolfram Cloud
  • wolframscript
  • Wolfram Engine Community Edition
  • Wolfram LLM API
  • WSTPServer
  • Wolfram|Alpha APIs

From the Community

  • Function Repository
  • Community Paclet Repository
  • Example Repository
  • Neural Net Repository
  • Prompt Repository
  • Wolfram Demonstrations
  • Data Repository
  • Group & Organizational Licensing
  • All Products
Consulting & Solutions

We deliver solutions for the AI era—combining symbolic computation, data-driven insights and deep technical expertise

  • Data & Computational Intelligence
  • Model-Based Design
  • Algorithm Development
  • Wolfram|Alpha for Business
  • Blockchain Technology
  • Education Technology
  • Quantum Computation

Wolfram Consulting

Wolfram Solutions

  • Data Science
  • Artificial Intelligence
  • Biosciences
  • Healthcare Intelligence
  • Sustainable Energy
  • Control Systems
  • Enterprise Wolfram|Alpha
  • Blockchain Labs

More Wolfram Solutions

Wolfram Solutions For Education

  • Research Universities
  • Colleges & Teaching Universities
  • Junior & Community Colleges
  • High Schools
  • Educational Technology
  • Computer-Based Math

More Solutions for Education

  • Contact Us
Learning & Support

Get Started

  • Wolfram Language Introduction
  • Fast Intro for Programmers
  • Fast Intro for Math Students
  • Wolfram Language Documentation

More Learning

  • Highlighted Core Areas
  • Demonstrations
  • YouTube
  • Daily Study Groups
  • Wolfram Schools and Programs
  • Books

Grow Your Skills

  • Wolfram U

    Courses in computing, science, life and more

  • Community

    Learn, solve problems and share ideas.

  • Blog

    News, views and insights from Wolfram

  • Resources for

    Software Developers

Tech Support

  • Contact Us
  • Support FAQs
  • Support FAQs
  • Contact Us
Company
  • About Wolfram
  • Career Center
  • All Sites & Resources
  • Connect & Follow
  • Contact Us

Work with Us

  • Student Ambassador Initiative
  • Wolfram for Startups
  • Student Opportunities
  • Jobs Using Wolfram Language

Educational Programs for Adults

  • Summer School
  • Winter School

Educational Programs for Youth

  • Middle School Camp
  • High School Research Program
  • Computational Adventures

Read

  • Stephen Wolfram's Writings
  • Wolfram Blog
  • Wolfram Tech | Books
  • Wolfram Media
  • Complex Systems

Educational Resources

  • Wolfram MathWorld
  • Wolfram in STEM/STEAM
  • Wolfram Challenges
  • Wolfram Problem Generator

Wolfram Initiatives

  • Wolfram Science
  • Wolfram Foundation
  • History of Mathematics Project

Events

  • Stephen Wolfram Livestreams
  • Online & In-Person Events
  • Contact Us
  • Connect & Follow
Wolfram|Alpha
  • Your Account
  • User Portal
  • Wolfram Cloud
  • Products
    • Wolfram|One
    • Mathematica
    • Notebook Assistant + LLM Kit
    • Compute Services
    • System Modeler
    • Finance Platform
    • Wolfram|Alpha Notebook Edition
    • Application Server
    • Enterprise Private Cloud
    • Wolfram Engine
    • Wolfram Player
    • Wolfram Cloud App
    • Wolfram Player App

    More mobile apps

    • Core Technologies
      • Wolfram Language
      • Computable Data
      • Wolfram Notebooks
      • AI & Linguistic Understanding
    • Deployment Options
      • Wolfram Cloud
      • wolframscript
      • Wolfram Engine Community Edition
      • Wolfram LLM API
      • WSTPServer
      • Wolfram|Alpha APIs
    • From the Community
      • Function Repository
      • Community Paclet Repository
      • Example Repository
      • Neural Net Repository
      • Prompt Repository
      • Wolfram Demonstrations
      • Data Repository
    • Group & Organizational Licensing
    • All Products
  • Consulting & Solutions

    We deliver solutions for the AI era—combining symbolic computation, data-driven insights and deep technical expertise

    WolframConsulting.com

    Wolfram Solutions

    • Data Science
    • Artificial Intelligence
    • Biosciences
    • Healthcare Intelligence
    • Sustainable Energy
    • Control Systems
    • Enterprise Wolfram|Alpha
    • Blockchain Labs

    More Wolfram Solutions

    Wolfram Solutions For Education

    • Research Universities
    • Colleges & Teaching Universities
    • Junior & Community Colleges
    • High Schools
    • Educational Technology
    • Computer-Based Math

    More Solutions for Education

    • Contact Us
  • Learning & Support

    Get Started

    • Wolfram Language Introduction
    • Fast Intro for Programmers
    • Fast Intro for Math Students
    • Wolfram Language Documentation

    Grow Your Skills

    • Wolfram U

      Courses in computing, science, life and more

    • Community

      Learn, solve problems and share ideas.

    • Blog

      News, views and insights from Wolfram

    • Resources for

      Software Developers
    • Tech Support
      • Contact Us
      • Support FAQs
    • More Learning
      • Highlighted Core Areas
      • Demonstrations
      • YouTube
      • Daily Study Groups
      • Wolfram Schools and Programs
      • Books
    • Support FAQs
    • Contact Us
  • Company
    • About Wolfram
    • Career Center
    • All Sites & Resources
    • Connect & Follow
    • Contact Us

    Work with Us

    • Student Ambassador Initiative
    • Wolfram for Startups
    • Student Opportunities
    • Jobs Using Wolfram Language

    Educational Programs for Adults

    • Summer School
    • Winter School

    Educational Programs for Youth

    • Middle School Camp
    • High School Research Program
    • Computational Adventures

    Read

    • Stephen Wolfram's Writings
    • Wolfram Blog
    • Wolfram Tech | Books
    • Wolfram Media
    • Complex Systems
    • Educational Resources
      • Wolfram MathWorld
      • Wolfram in STEM/STEAM
      • Wolfram Challenges
      • Wolfram Problem Generator
    • Wolfram Initiatives
      • Wolfram Science
      • Wolfram Foundation
      • History of Mathematics Project
    • Events
      • Stephen Wolfram Livestreams
      • Online & In-Person Events
    • Contact Us
    • Connect & Follow
  • Wolfram|Alpha
  • Wolfram Cloud
  • Your Account
  • User Portal
Wolfram Language & System Documentation Center
GraphPlot
  • See Also
    • Graph
    • GraphPlot3D
    • LayeredGraphPlot
    • TreePlot
    • CommunityGraphPlot
    • GraphLayout
    • GraphEmbedding

    • Entity Types
    • Graph

    • Interpreter Types
    • Graph
    • ComputedGraph

    • Formats
    • Graphlet
    • DOT
    • GraphML
  • Related Guides
    • Graph Visualization
    • Computational Geometry
    • Computational Systems
    • Data Visualization
    • Social Network Analysis
    • Scientific Data Analysis
    • Graph Layouts
    • See Also
      • Graph
      • GraphPlot3D
      • LayeredGraphPlot
      • TreePlot
      • CommunityGraphPlot
      • GraphLayout
      • GraphEmbedding

      • Entity Types
      • Graph

      • Interpreter Types
      • Graph
      • ComputedGraph

      • Formats
      • Graphlet
      • DOT
      • GraphML
    • Related Guides
      • Graph Visualization
      • Computational Geometry
      • Computational Systems
      • Data Visualization
      • Social Network Analysis
      • Scientific Data Analysis
      • Graph Layouts

GraphPlot[g]

generates a plot of the graph g.

GraphPlot[{e1,e2,…}]

generates a plot of the graph with edges ei.

GraphPlot[{…,w[ei],…}]

plots ei with features defined by the symbolic wrapper w.

GraphPlot[{vi 1vj 1,…}]

uses rules vikvjk to specify the graph g.

GraphPlot[m]

uses the adjacency matrix m to specify the graph g.

Details and Options
Details and Options Details and Options
Examples  
Basic Examples  
Scope  
Graph Specification  
Graph Styling  
Options  
DataRange  
DirectedEdges  
GraphLayout  
"BalloonEmbedding"  
"BipartiteEmbedding"  
"CircularEmbedding"  
"CircularMultipartiteEmbedding"  
"DiscreteSpiralEmbedding"  
"GridEmbedding"  
"HighDimensionalEmbedding"  
"LayeredEmbedding"  
"LayeredDigraphEmbedding"  
"LinearEmbedding"  
"MultipartiteEmbedding"  
"PlanarEmbedding"  
"RadialEmbedding"  
"RandomEmbedding"  
"SpectralEmbedding"  
"SpiralEmbedding"  
"SpringElectricalEmbedding"  
"SpringEmbedding"  
"StarEmbedding"  
"TutteEmbedding"  
PlotStyle  
Applications  
Basic Applications  
Graph Theory  
Linguistic or Geographic Data  
Number Properties  
Sparse Test Matrices  
Finite State Diagrams  
Properties & Relations  
See Also
Related Guides
History
Cite this Page
BUILT-IN SYMBOL
  • See Also
    • Graph
    • GraphPlot3D
    • LayeredGraphPlot
    • TreePlot
    • CommunityGraphPlot
    • GraphLayout
    • GraphEmbedding

    • Entity Types
    • Graph

    • Interpreter Types
    • Graph
    • ComputedGraph

    • Formats
    • Graphlet
    • DOT
    • GraphML
  • Related Guides
    • Graph Visualization
    • Computational Geometry
    • Computational Systems
    • Data Visualization
    • Social Network Analysis
    • Scientific Data Analysis
    • Graph Layouts
    • See Also
      • Graph
      • GraphPlot3D
      • LayeredGraphPlot
      • TreePlot
      • CommunityGraphPlot
      • GraphLayout
      • GraphEmbedding

      • Entity Types
      • Graph

      • Interpreter Types
      • Graph
      • ComputedGraph

      • Formats
      • Graphlet
      • DOT
      • GraphML
    • Related Guides
      • Graph Visualization
      • Computational Geometry
      • Computational Systems
      • Data Visualization
      • Social Network Analysis
      • Scientific Data Analysis
      • Graph Layouts

GraphPlot

GraphPlot[g]

generates a plot of the graph g.

GraphPlot[{e1,e2,…}]

generates a plot of the graph with edges ei.

GraphPlot[{…,w[ei],…}]

plots ei with features defined by the symbolic wrapper w.

GraphPlot[{vi 1vj 1,…}]

uses rules vikvjk to specify the graph g.

GraphPlot[m]

uses the adjacency matrix m to specify the graph g.

Details and Options

  • GraphPlot attempts to place vertices to give a well-laid-out version of the graph.
  • GraphPlot supports the same vertices and edges as Graph.
  • The following special wrappers can be used for the edges ei:
  • Annotation[ei,label]provide an annotation
    Button[ei,action]define an action to execute when the element is clicked
    EventHandler[ei,…]define a general event handler for the element
    Hyperlink[ei,uri]make the element act as a hyperlink
    Labeled[ei,…]display the element with labeling
    PopupWindow[ei,cont]attach a popup window to the element
    StatusArea[ei,label]display in the status area when the element is moused over
    Style[ei,opts]show the element using the specified styles
    Tooltip[ei,label]attach an arbitrary tooltip to the element
  • GraphPlot has the same options as Graphics, with the following additions and changes: [List of all options]
  • DataRange Automaticthe range of vertex coordinates to generate
    DirectedEdges Falsewhether to interpret Rule as DirectedEdge
    EdgeLabelsNonelabels and label placements for edges
    EdgeLabelStyleAutomaticstyle to use for edge labels
    EdgeShapeFunctionAutomaticgenerate graphic shapes for edges
    EdgeStyleAutomaticstyles for edges
    GraphLayout Automatichow to lay out vertices and edges
    GraphHighlight{}vertices and edges to highlight
    GraphHighlightStyleAutomaticstyle for highlight
    MethodAutomaticmethod to use
    PerformanceGoalAutomaticaspects of performance to try to optimize
    PlotStyle Automaticgraphics directives to determine styles
    PlotThemeAutomaticoverall theme for the graph
    VertexCoordinatesAutomaticcoordinates for vertices
    VertexLabelsNonelabels and label placements for vertices
    VertexLabelStyleAutomaticstyle to use for vertex labels
    VertexShapeAutomaticgraphic shape for vertices
    VertexShapeFunctionAutomaticgenerate graphic shapes for vertices
    VertexSizeAutomaticsize of vertices
    VertexStyleAutomaticstyles for vertices
  • With the setting VertexCoordinates->Automatic, the embedding of vertices and routing of edges is computed automatically, based on the setting for GraphLayout.
  • Possible special embeddings for GraphLayout include:
  • "BipartiteEmbedding"vertices on two parallel lines
    "CircularEmbedding"vertices on a circle
    "CircularMultipartiteEmbedding"vertices on segments of a circle
    "DiscreteSpiralEmbedding"vertices on a discrete spiral
    "GridEmbedding"vertices on a grid
    "LinearEmbedding"vertices on a line
    "MultipartiteEmbedding"vertices on several parallel lines
    "SpiralEmbedding"vertices on a 3D spiral projected to 2D
    "StarEmbedding"vertices on a circle with a center
  • Possible structured embeddings for layered graphs such as trees and directed acyclic graphs include:
  • "BalloonEmbedding"vertices on a circle with the center at the parent vertex
    "RadialEmbedding"vertices on a circular segment
    "LayeredDigraphEmbedding"vertices on parallel lines for directed acyclic graphs
    "LayeredEmbedding"vertices on parallel lines
  • Possible optimizing embeddings all minimize a quantity and include:
  • "HighDimensionalEmbedding"energy for spring-electrical in high dimension
    "PlanarEmbedding"number of edge crossings
    "SpectralEmbedding"weighted sum of squares distances
    "SpringElectricalEmbedding"energy with edges as springs and vertices as charges
    "SpringEmbedding"energy with edges as springs
    "TutteEmbedding"number of edge crossings and distance to neighbors
  • Possible settings for PlotTheme include common base themes:
  • "Business"a bright, modern look appropriate for business presentations or infographics
    "Detailed"identify data by employing labels and tooltips
    "Marketing"elegant, eye-catching design suitable for marketing needs
    "Minimal"simple graph
    "Monochrome"single-color design
    "Scientific"candid design useful for analyzing detailed data with labels and tooltips
    "Web"clean, bold design suitable for a consumer website or blog
    "Classic"historical design of graph to remain compatible with existing uses
  • Graph features themes affect plot of vertices and edges. Feature themes include:
  • "LargeGraph"large graph
    "ClassicLabeled"classic graph
    "IndexLabeled"index-labeled graph
  • List of all options

    • AlignmentPointCenterthe default point in the graphic to align with
      AspectRatioAutomaticratio of height to width
      AxesFalsewhether to draw axes
      AxesLabelNoneaxes labels
      AxesOriginAutomaticwhere axes should cross
      AxesStyle{}style specifications for the axes
      BackgroundNonebackground color for the plot
      BaselinePositionAutomatichow to align with a surrounding text baseline
      BaseStyle{}base style specifications for the graphic
      ContentSelectableAutomaticwhether to allow contents to be selected
      CoordinatesToolOptionsAutomaticdetailed behavior of the coordinates tool
      DataRangeAutomaticthe range of vertex coordinates to generate
      DirectedEdgesFalsewhether to interpret Rule as DirectedEdge
      EdgeLabelsNonelabels and label placements for edges
      EdgeLabelStyleAutomaticstyle to use for edge labels
      EdgeShapeFunctionAutomaticgenerate graphic shapes for edges
      EdgeStyleAutomaticstyles for edges
      Epilog{}primitives rendered after the main plot
      FormatTypeTraditionalFormthe default format type for text
      FrameFalsewhether to put a frame around the plot
      FrameLabelNoneframe labels
      FrameStyle{}style specifications for the frame
      FrameTicksAutomaticframe ticks
      FrameTicksStyle{}style specifications for frame ticks
      GraphHighlight{}vertices and edges to highlight
      GraphHighlightStyleAutomaticstyle for highlight
      GraphLayoutAutomatichow to lay out vertices and edges
      GridLinesNonegrid lines to draw
      GridLinesStyle{}style specifications for grid lines
      ImageMargins0.the margins to leave around the graphic
      ImagePaddingAllwhat extra padding to allow for labels etc.
      ImageSizeAutomaticthe absolute size at which to render the graphic
      LabelStyle{}style specifications for labels
      MethodAutomaticmethod to use
      PerformanceGoalAutomaticaspects of performance to try to optimize
      PlotLabelNonean overall label for the plot
      PlotRangeAllrange of values to include
      PlotRangeClippingFalsewhether to clip at the plot range
      PlotRangePaddingAutomatichow much to pad the range of values
      PlotRegionAutomaticthe final display region to be filled
      PlotStyleAutomaticgraphics directives to determine styles
      PlotThemeAutomaticoverall theme for the graph
      PreserveImageOptionsAutomaticwhether to preserve image options when displaying new versions of the same graphic
      Prolog{}primitives rendered before the main plot
      RotateLabelTruewhether to rotate y labels on the frame
      TicksAutomaticaxes ticks
      TicksStyle{}style specifications for axes ticks
      VertexCoordinatesAutomaticcoordinates for vertices
      VertexLabelsNonelabels and label placements for vertices
      VertexLabelStyleAutomaticstyle to use for vertex labels
      VertexShapeAutomaticgraphic shape for vertices
      VertexShapeFunctionAutomaticgenerate graphic shapes for vertices
      VertexSizeAutomaticsize of vertices
      VertexStyleAutomaticstyles for vertices

Examples

open all close all

Basic Examples  (3)

Plot a graph:

Plot a graph specified by edge rules:

Plot a graph specified by its adjacency matrix:

Scope  (11)

Graph Specification  (6)

Specify a graph using a graph:

Specify a graph using a rule list:

Specify a graph using a dense adjacency matrix:

Specify a graph using a sparse adjacency matrix:

Use GraphData for collections of graphs:

Use ExampleData for collections of sparse matrices:

Graph Styling  (5)

Give labels for some edges:

Give vertex labels:

Show edges as arrows:

Plot a disconnected graph using different packing methods:

For very large graphs, it is often better not to draw vertices at all:

Options  (71)

DataRange  (1)

Specify the range of vertex coordinates:

DirectedEdges  (1)

Show the direction of edges:

GraphLayout  (66)

"BalloonEmbedding"  (6)

Place each vertex in an enclosing circle centered at its parent vertex:

"BalloonEmbedding" works best for tree graphs:

Use the option "EvenAngle"->True to place vertices evenly in an enclosing circle:

With the setting "OptimalOrder"->True, the vertex ordering optimizes the angular resolution and the aspect ratio:

Use the option "RootVertex"->v to set the root vertex:

Use "SectorAngles"->s to control the size of each sector:

"BipartiteEmbedding"  (1)

Place vertices on two vertical lines based on a bipartite partition:

"CircularEmbedding"  (2)

Place vertices on a circle:

Use the option "Offset"->offset to specify the offset angles:

"CircularMultipartiteEmbedding"  (2)

Place vertices on polygon lines based on a vertex partition:

Use "VertexPartition"->partition to specify a partition of vertices:

"DiscreteSpiralEmbedding"  (3)

Place vertices on a discrete spiral:

"DiscreteSpiralEmbedding" works best for path graphs:

With the setting "OptimalOrder"->True, vertices are reordered so that they lie nicely on a discrete spiral:

"GridEmbedding"  (2)

Place vertices on a grid:

Use "Dimension"->dim to specify a dimension of a grid:

"HighDimensionalEmbedding"  (2)

Place vertices in high dimension according to spring-electrical embedding and project down:

Use "RandomSeed"->int to specify a seed for the random number generator that computes the initial vertex placement:

"LayeredEmbedding"  (6)

Place vertices in several layers in such a way as to minimize edges between nonadjacent layers:

"LayeredEmbedding" works best for tree graphs:

Use the option "LayerSizeFunction"->func to specify the relative height:

Use the option "RootVertex"->v to set the root vertex:

Use the option "LeafDistance"->d to specify the leaf distance:

Use the option "Orientation"->o to draw a tree with different orientations:

"LayeredDigraphEmbedding"  (3)

Place vertices in a series of layers:

Use the option "RootVertex"->v to set the root vertex:

Use the option "Orientation"->o to draw a tree with different orientations:

"LinearEmbedding"  (2)

Place vertices on a line:

Use the option "Method"->m to specify the algorithm:

"MultipartiteEmbedding"  (2)

Place vertices on multiple line grids based on a vertex partition:

Use "VertexPartition"->partition to specify a partition of vertices:

"PlanarEmbedding"  (1)

Place vertices on a plane without an edge crossing:

"RadialEmbedding"  (2)

Place vertices in concentric circles:

Use the option "RootVertex"->v to set the root vertex:

"RandomEmbedding"  (1)

Place vertices randomly:

"SpectralEmbedding"  (2)

Place vertices so the weighted sum of squares of mutual distances is minimized:

Use the option "RelaxationFactor"->r to get the layout based on a relaxed Laplace matrix:

"SpiralEmbedding"  (2)

Place vertices on a spiral:

With the setting "OptimalOrder"->True, vertices are reordered so that they lie on the spiral nicely:

"SpringElectricalEmbedding"  (12)

Place vertices so that they minimize mechanical and electrical energy when each vertex has a charge and each edge corresponds to a spring:

With the setting "EdgeWeighted"->True, edge weights are used:

Use the option "EnergyControl"->e to specify limitations on the total energy of the system during minimization:

Use "InferentialDistance"->d to specify a cutoff distance beyond which the interaction between vertices is assumed to be nonexistent:

Use "MaxIteration"->it to specify a maximum number of iterations to be used in attempting to minimize the energy:

Use "Multilevel"->method to specify a method used during a recursive procedure of coarsening a graph:

With the setting "Octree"->True, an octree data structure (in three dimensions) or a quadtree data structure (in two dimensions) is used in the calculation of repulsive force:

Use "RandomSeed"->int to specify a seed for the random number generator that computes the initial vertex placement:

Use "RepulsiveForcePower"->r to control how fast the repulsive force decays over distance:

Use "StepControl"->method to define how step length is modified during energy minimization:

Use "StepLength"->r to specify the initial step length used in moving the vertices around:

Use "Tolerance"->r to specify the tolerance used in terminating the energy minimization process:

"SpringEmbedding"  (10)

Place vertices so that they minimize mechanical energy when each edge corresponds to a spring:

With the setting "EdgeWeighted"->True, edge weights are used:

Use the option "EnergyControl"->e to specify limitations on the total energy of the system during minimization:

Use "InferentialDistance"->d to specify a cutoff distance beyond which the interaction between vertices is assumed to be nonexistent:

Use "MaxIteration"->it to specify a maximum number of iterations to be used in attempting to minimize the energy:

Use "Multilevel"->method to specify a method used during a recursive procedure of coarsening a graph:

Use "RandomSeed"->int to specify a seed for the random number generator that computes the initial vertex placement:

Use "StepControl"->method to define how step length is modified during energy minimization:

Use "StepLength"->r to specify the initial step length used in moving the vertices around:

Use "Tolerance"->r to specify the tolerance used in terminating the energy minimization process:

"StarEmbedding"  (3)

Place vertices on a star shape:

Use the option "Offset"->offset to specify the offset angles:

Use the option "Center"->center to specify the center:

"TutteEmbedding"  (2)

Place vertices without crossing edges and minimize the sum of distances to neighbors:

"TutteEmbedding" works for 3-connected planar graphs only:

PlotStyle  (3)

Specify an overall style for the graph:

PlotStyle can be combined with VertexShapeFunction, which has higher priority:

PlotStyle can be combined with EdgeShapeFunction, which has higher priority:

Applications  (27)

Basic Applications  (3)

Label vertices and edges:

Plot a graph with "BalloonEmbedding":

Visualize large graphs:

Graph Theory  (5)

Plot a complete graph on 10 nodes:

Plot a random graph on 10 nodes:

A random graph with 1% of possible edges filled in:

A graph describing a simple relation:

Draw the graph of a random permutation:

Linguistic or Geographic Data  (3)

Generate a network of "nearby" words in a dictionary:

A word graph, with edges between adjacent letters in a word:

Show the adjacent countries in South America:

Number Properties  (11)

Numbers that have a common divisor:

Numbers that have no common divisor:

Link a number to another with a 1 bit inserted:

Link a number to another with a 0 bit inserted:

Link a number to another with 1 bit deleted:

Link a number to another that is one bit different:

Link a number to another that is one bit reversed:

Link a number to another that is one bit rotated right:

Link a number to another that is one bit rotated left:

Link a number to itself but with the last bit dropped:

Link a number to itself but with the first bit dropped:

Sparse Test Matrices  (3)

A sparse test matrix related to a structure from NASA's Langley Research Center:

A sparse test matrix related to a finite element model of a geodesic dome:

Use ArrayPlot or MatrixPlot to display sparse matrices:

Finite State Diagrams  (2)

A finite state diagram describing the C preprocessor:

A finite state diagram for string matching:

Properties & Relations  (8)

Use LayeredGraphPlot for hierarchical-style drawing of directed graphs:

Use TreePlot for different types of tree drawing:

Use GraphPlot3D to draw graphs in 3D:

Use GraphData for an extensive collection of predefined graphs and properties:

Get the connectivity and plot it:

Use VertexCoordinates to use the embedding provided by GraphData:

Use PolyhedronData for a large collection of polyhedra and properties:

Compare to a predefined embedding:

Use ExampleData for a large collection of sparse matrices:

Use GeoGraphValuePlot to show the values on geographic networks:

Use GeoGraphPlot to plot relationships between geographic locations on a map:

See Also

Graph  GraphPlot3D  LayeredGraphPlot  TreePlot  CommunityGraphPlot  GraphLayout  GraphEmbedding

Entity Types: Graph

Interpreter Types: Graph  ComputedGraph

Formats: Graphlet  DOT  GraphML

Function Repository: SimpleHypergraphPlot

Related Guides

    ▪
  • Graph Visualization
  • ▪
  • Computational Geometry
  • ▪
  • Computational Systems
  • ▪
  • Data Visualization
  • ▪
  • Social Network Analysis
  • ▪
  • Scientific Data Analysis
  • ▪
  • Graph Layouts

History

Introduced in 2007 (6.0) | Updated in 2019 (12.0)

Wolfram Research (2007), GraphPlot, Wolfram Language function, https://reference.wolfram.com/language/ref/GraphPlot.html (updated 2019).

Text

Wolfram Research (2007), GraphPlot, Wolfram Language function, https://reference.wolfram.com/language/ref/GraphPlot.html (updated 2019).

CMS

Wolfram Language. 2007. "GraphPlot." Wolfram Language & System Documentation Center. Wolfram Research. Last Modified 2019. https://reference.wolfram.com/language/ref/GraphPlot.html.

APA

Wolfram Language. (2007). GraphPlot. Wolfram Language & System Documentation Center. Retrieved from https://reference.wolfram.com/language/ref/GraphPlot.html

BibTeX

@misc{reference.wolfram_2025_graphplot, author="Wolfram Research", title="{GraphPlot}", year="2019", howpublished="\url{https://reference.wolfram.com/language/ref/GraphPlot.html}", note=[Accessed: 01-May-2026]}

BibLaTeX

@online{reference.wolfram_2025_graphplot, organization={Wolfram Research}, title={GraphPlot}, year={2019}, url={https://reference.wolfram.com/language/ref/GraphPlot.html}, note=[Accessed: 01-May-2026]}

Top
Introduction for Programmers
Introductory Book
Wolfram Function Repository | Wolfram Data Repository | Wolfram Data Drop | Wolfram Language Products
Top
  • Products
  • Wolfram|One
  • Mathematica
  • Notebook Assistant + LLM Kit
  • Compute Services
  • System Modeler

  • Wolfram|Alpha Notebook Edition
  • Wolfram|Alpha Pro
  • Mobile Apps

  • Wolfram Engine
  • Wolfram Player

  • Volume & Site Licensing
  • Server Deployment Options
  • Consulting
  • Wolfram Consulting
  • Repositories
  • Data Repository
  • Function Repository
  • Community Paclet Repository
  • Neural Net Repository
  • Prompt Repository

  • Wolfram Language Example Repository
  • Notebook Archive
  • Wolfram GitHub
  • Learning
  • Wolfram U
  • Wolfram Language Documentation
  • Webinars & Training
  • Educational Programs

  • Wolfram Language Introduction
  • Fast Introduction for Programmers
  • Fast Introduction for Math Students
  • Books

  • Wolfram Community
  • Wolfram Blog
  • Public Resources
  • Wolfram|Alpha
  • Wolfram Problem Generator
  • Wolfram Challenges

  • Computer-Based Math
  • Computational Thinking
  • Computational Adventures

  • Demonstrations Project
  • Wolfram Data Drop
  • MathWorld
  • Wolfram Science
  • Wolfram Media Publishing
  • Customer Resources
  • Store
  • Product Downloads
  • User Portal
  • Your Account
  • Organization Access

  • Support FAQ
  • Contact Support
  • Company
  • About Wolfram
  • Careers
  • Contact
  • Events
Wolfram Community Wolfram Blog
Legal & Privacy Policy
WolframAlpha.com | WolframCloud.com
© 2026 Wolfram
© 2026 Wolfram | Legal & Privacy Policy |
English