🪐 Cosmograph for Python is here! Read more →

Cosmograph: make sense of your graph and machine learning data

Engage with your data,
Right in the browser on your laptop.

What is Cosmograph?

💻 A web-based application that helps you analyze large graph datasets or machine learning embeddings. It runs purely in the browser and doesn't send your data anywhere. All calculations will be done right on your GPU, the faster it is the better.

Read more about the app in our how to use guide.

📚 A JavaScript/React library. You can use it to add blazingly fast network graph and embeddings visualizations to your own web application, and amplify them with extra components like Timeline, Histogram, Search, and more.

Learn more about the library in the documentation.

What can you do with
Cosmograph?

Upload a CSV with your network or machine learning embeddings data and get it visualized

Visualizing network graph data and machine learning embeddings provides intuitive insights into complex relationships and patterns that are often challenging to discern from raw data alone. This makes it easier to spot patterns, explain findings, and make decisions.

Explore the evolution of your data over time

Visualizing the temporal dimension is crucial because it allows to understand how relationships and patterns in your data change over time. This time-based perspective can reveal trends, anomalies, and causal factors that might be missed in static visualizations.

Identify communities and anomalies

Discover patterns and outliers within your data by utilizing a visual search for communities and anomalies. This intuitive method highlights clusters of related data and points of deviation, providing deeper insights. Enhance your data analysis by spotting interconnected groups and unexpected variations effortlessly.

Dive deep with filters and histograms

Analyzing data through filtering and histograms allows for a clearer understanding of data distributions and the frequency of values. Filtering narrows down data to relevant subsets, making targeted analysis more manageable. Histograms visually display patterns, helping to easily spot anomalies and compare different data categories.

Share or embed your graph

Easily share your graph with colleagues or integrate it directly into your website.

Analyze embeddings

Load embedding feature allows loading a file with pre-calculated x and y coordinate columns for points in a two-dimensional space. It harnesses Cosmograph's visualization and analytics capabilities to see semantic relationships and structures within the embedding data.

Organizations use Cosmograph

Web developer?
Try Cosmograph!

Want to add Cosmograph capabilities into your own project?
Check out our React and JavaScript library.

React example

JS/TS example

React
JavaScript
Data

import { Cosmograph } from '@cosmograph/react'

export function GraphVisualization ({ nodes, links }) {
  return (<Cosmograph
    nodes={nodes}
    links={links}
    nodeColor={d => d.color}
    nodeSize={20}
    linkWidth={2}
  />)
}

import { Cosmograph } from '@cosmograph/cosmograph'

// Create an HTML element
const targetElement = document.createElement('div')
document.body.appendChild(targetElement)
  
// Define the configuration
const config = {
  nodeColor: d => d.color,
  nodeSize: 20,
  linkWidth: 2,
  // ... 
}
  
// Create a Cosmograph instance inside the targetElement 
const cosmograph = new Cosmograph(targetElement, config)
  
// Set the data
cosmograph.setData(nodes, links)

export const nodes = [
  { id: '1', color: '#88C6FF' },
  { id: '2', color: '#FF99D2' },
  { id: '3', color: [227, 17, 108, 1] },
]

export const links = [
  { source: '1', target: '2' },
  { source: '1', target: '3' },
  { source: '2', target: '3' },
]

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