Counting 1,865 Big Data & Machine Learning Frameworks, Toolsets, and Examples...
Suggestion? Feedback? Tweet @stkim1

Last Commit
Oct. 17, 2017
Feb. 3, 2013

Vega: A Visualization Grammar

Vega is a visualization grammar, a declarative format for creating, saving, and sharing interactive visualization designs. With Vega you can describe data visualizations in a JSON format, and generate interactive views using either HTML5 Canvas or SVG.

For documentation, tutorials, and examples, see the Vega website. For a description of changes between Vega 2 and Vega 3, please refer to the Vega 3 Porting Guide. Additional API documentation for Vega 3 can be found in the associated modules listed below.

Basic Setup

For a basic setup allowing you to build Vega and run examples, clone and run npm install.

Once installation is complete, use npm run test to run tests and npm run build to build output files.

This repo (vega) includes web-based demos within the test folder. To run these, launch a local webserver in the top-level directory for the repo (e.g., python -m SimpleHTTPServer 8000 for Python 2, python -m http.server 8000 for Python 3) and then point your browser to the right place (e.g., http://localhost:8000/test/).

Development Setup

For a more advanced development setup in which you will be working on multiple modules simultaneously, first clone the relevant Vega 3 modules. Here is a list of all Vega 3 repositories:

Though not strictly required, we recommend using npm link to connect each local copy of a repo with its 'vega-' dependencies. That way, any edits you make in one repo will be immediately reflected within dependent repos, accelerating testing.

For example, to link vega-dataflow for use by other repos, do the following:

# register a link to vega-dataflow
cd vega-dataflow; npm link
# update vega-runtime to use the linked version of vega-dataflow
cd ../vega-runtime; npm link vega-dataflow
# update vega to use the linked version of vega-dataflow
cd ../vega; npm link vega-dataflow

Once links have been setup, you can use npm install as usual to gather all remaining dependencies.

Latest Releases
 Sep. 30 2017
 Sep. 30 2017
 Sep. 29 2017
 Aug. 17 2017
 Aug. 11 2017