We’re pleased to announced the release of version 0.2 of the Bokeh plotting library. We’ve made lots of progress since our v0.1 release: over 1,500 commits across two repositories. There is a ton of new functionality, improved and refactored architecture, and hopefully a much easier installation process for users. We’ve built Bokeh from the ground-up to be interactive in the browser, with many live examples in the gallery. You can click on the following thumbnails to see some of the interactive examples:
Bokeh is an interactive web plotting system for visualizing large data. It uses HTML5 Canvas and Python, and has both a high-level interface to allow easy plotting, as well as a powerful low-level interface which is highly configurable.
For more information, visit the Bokeh website.
We’re actively working on adding more to the user and developer guides, but we didn’t want to hold up the release just to flesh those out.
More blog posts
Be sure to follow us on Twitter! We’ll be tweeting more tips and examples and blog posts as we produce them. For instance, we have two more blog posts in the pipeline: an end-to-end example of how to build a simple web dashboard with interactive plotting of streaming data from a web service, and an interactive Google Map viewer of geo data, embedded in an IPython Notebook. Stay tuned!
See our Roadmap for more details.
Get Involved!Bokeh comments powered by Disqus
Back to Blog→
- Anaconda Server
- Bayesian Data Analysis
- Big Data
- Boolean satisfiability problem
- IPython Notebook
- Open Source
- Practical Python
- Product Release
- Product Update
- Python 3
- Raspberry Pi
- SAT solver
- Social Media
- Thomson Reuters