Vega-Lite – A Grammar of Interactive Graphics

Vega-Lite is a high-level grammar of interactive graphics. It provides a concise, declarative JSON syntax to create an expressive range of visualizations for data analysis and presentation.

Vega-Lite specifications describe visualizations as encoding mappings from data to properties of graphical marks (e.g., points or bars). The Vega-Lite compiler automatically produces visualization components including axes, legends, and scales. It determines default properties of these components based on a set of carefully designed rules. This approach allows Vega-Lite specifications to be concise for quick visualization authoring, while giving user control to override defaults and customize various parts of a visualization. As we also designed Vega-Lite to support data analysis, Vega-Lite supports both data transformations (e.g., aggregation, binning, filtering, sorting) and visual transformations (e.g., stacking and faceting). Moreover, Vega-Lite specifications can be composed into layered and multi-view displays, and made interactive with selections. Get started
Latest Version: 5.17.0
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Compared to Vega, Vega-Lite provides a more concise and convenient form to author common visualizations. As Vega-Lite can compile its specifications to Vega specifications, users may use Vega-Lite as the primary visualization tool and, if needed, transition to use the lower-level Vega for advanced use cases.

For more information, read our introduction article to Vega-Lite v2 on Medium, watch our OpenVis Conf talk about the new features in Vega-Lite v2, see the documentation and take a look at our example gallery. Follow us on Twitter at @vega_vis to stay informed about updates.

Example

Users

Vega-Lite is used by thousands of data enthusiasts, developers, journalists, data scientists, teachers, and researchers across many organizations. Here are some of them. Learn about integrations on our ecosystem page.

  • Airbnb
  • Apple
  • Databricks
  • Google
  • Microsoft
  • Tableau
  • Berkeley
  • Carnegie Mellon University
  • CERN
  • JupyterLab
  • LA Times
  • Massachusetts Institute of Technology
  • University of Washington

Team

The development of Vega-Lite is led by the alumni and members of the University of Washington Interactive Data Lab (UW IDL), including Kanit “Ham” Wongsuphasawat (now at Databricks), Dominik Moritz (now at CMU / Apple), Arvind Satyanarayan (now at MIT), and Jeffrey Heer (UW IDL).

Vega-Lite gets significant contributions from its community. Please see the contributors page for the full list of contributors.