Find Graph
Find Graph is an open-source software for creating interactive node-link diagrams and network graphs. It allows users to easily visualize connections in data, build charts and maps, and create interactive presentations.
Find Graph: Open-Source Network Visualization Software
Create interactive node-link diagrams and network graphs with Find Graph, an open-source software for data visualization and presentation purposes
What is Find Graph?
Find Graph is an open-source, cross-platform software application for creating interactive node-link diagrams, charts, maps, and network visualizations. Developed by Apptenance, Find Graph enables users to easily visualize connections and patterns in their data by building interactive presentations and reports.
Key features of Find Graph include:
- Intuitive drag-and-drop interface for quickly building node-link diagrams
- Dynamic filtering, searching, and clustering for exploring large graphs
- Support for importing data from CSV, JSON, SQL, and other sources
- Customizable node and link appearance, labels, icons, colors, and more
- Collaboration tools for sharing, editing, commenting on graphs
- Exporting images, PDFs, and interactive HTML files
- Plugin ecosystem for extending functionality
- Available for Windows, Mac, and Linux
With its emphasis on usability and customization, Find Graph is popular among data analysts, researchers, engineers, and business professionals for data visualization and interactive reporting. The software aims to make network graphing accessible for novices while also providing advanced functionality for power users.
Find Graph Features
Features
- Interactive node-link diagrams and network graphs
- Visualize connections in data
- Build charts and maps
- Create interactive presentations
- Open-source software
Pricing
- Open Source
Pros
Free and open-source
Versatile data visualization capabilities
Interactive and customizable graphs
Suitable for a wide range of use cases
Cons
Steep learning curve for beginners
Limited advanced features compared to commercial tools
Potential performance issues with large datasets
Official Links
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