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Damián Avila

Bokeh 0.5.1 Released!

We are excited to announce the release of version 0.5.1 of Bokeh, an interactive web plotting library for Python!

This release includes many bug fixes and improvements over our last recent 0.5 release:

  • Hover activated by default
  • Boxplot in bokeh.charts
  • Better messages when you forget to start the bokeh-server
  • Fixed some packaging bugs
  • Fixed NBviewer rendering
  • Fixed some Unicodeencodeerror

Get It Now!

If you are using Anaconda, you can install with conda:

    conda install bokeh

Alternatively, you can install with pip:

    pip install bokeh

In order to push features to users even faster there are also now periodic dev builds made available. See the Developer’s Guide for more details.

BokehJS is also available by CDN for use in standalone Javascript applications:

    http://cdn.pydata.org/bokeh-0.5.1.min.js
    http://cdn.pydata.org/bokeh-0.5.1.min.css

Additionally, BokehJS is also now installable with the Node Package Manager.

What’s Next?

The release of Bokeh 0.6 is planned for August. Some notable features we intend to work on are:

  • Dynamic and data-driven layout using the Kiwi.js constraint solver (work underway)
  • More chart types (boxplot, violin, contour, etc.) and auto-faceting for bokeh.charts
  • R and/or Matlab language bindings
  • Polar coordinate systems

How to get involved

Issues, enhancement requests, and pull requests can be made on the Bokeh Github page: https://github.com/continuumio/bokeh

Questions can be directed to the Bokeh mailing list: bokeh@continuum.io

If you would like some help incorporating Bokeh into your Notebooks, apps, or dashboards, please send an email to info@continuum.io to inquire about Continuum’s training and consulting services - not just for Bokeh, but for anything in the full NumPy/SciPy/PyData stack.

Tags: Python Bokeh Visualization Big Data
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