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Quick start with Garphield

This page walks through three ways to get started with Garphield: on the main site, from Python or from R.

Start in the workbench

Section titled “Start in the workbench”

Garphield is available to anyone.

  1. Choose a network

    Start with a pre-bundled network, choose one from the library, or bring your own files.

  2. Let the network load

    Garphield loads the network as soon as possible. New graphs use Degree for node size and Louvain for colour up to 10,000 nodes and 100,000 edges. Larger graphs start with neutral colours; choose a source in Color to analyse them. The right panel shows the top five degree nodes and the matching community groups.

  3. Find a node

    Press /, type a node label, then press Enter.

  4. Run network analytics

    Analytics run in your browser. Click Degree and change it to Betweenness to compare the result. Open Explore for the full list, then drag a source into a visual channel to update the network.

  5. Use History

    Open History in the sidebar. Every change can be reversed.

  6. Inspect the node and link tables

    Toggle the table from the top right. Switch between Nodes and Links, sort a column by clicking its header, or edit details inline.

  7. Export your work

    Export the current view as a PNG or .gph project.

Continue with the workspace tour or open your own data.

Start from Python

Section titled “Start from Python”
Terminal window
pip install 'garphield[networkx]'

Then display a graph in a notebook:

import garphield as gph
import networkx as nx


graph = nx.karate_club_graph()
view = gph.show(
    graph,
    node_color="club",
    node_size=graph.degree,
    node_label=str,
)

show() returns a GraphView. Later cells can select nodes, change visual bindings, or read the edited graph back to NetworkX. Use Open in Garphield for the full workbench; Return to notebook sends the result back.

Read the Python guide for pandas, NetworkX, Raphtory, project files, and the notebook handoff.

Start from R

Section titled “Start from R”

Install garphieldr, then open an igraph network:

install.packages("garphieldr")


library(garphieldr)
library(igraph)


project <- garphield_project(make_ring(12))
garphield(project)

The same .gph project moves between R, Python, and the browser workbench. Read the R guide for data frames, RStudio, Quarto, and Shiny.

Embed Garphield

Section titled “Embed Garphield”

Embed Garphield networks in another page with an iframe or the JavaScript driver. The host page can keep its own navigation, filters, and detail views.

Terminal window
pnpm add garphield
import { createGarphield } from "garphield";


const frame = document.querySelector<HTMLIFrameElement>("#network");
if (!frame) throw new Error("Missing graph iframe");


const graph = createGarphield(frame);
await graph.ready();
await graph.setDocument(project);

Start with the embed guide for both embed options, events, and host configuration.

Section titled “Read next”