ANN: Bokeh 0.5.1 released

[Damian Avila]

On behalf of the Bokeh team, I am very happy to announce the release of
Bokeh version 0.5.1! (http://continuum.io/blog/bokeh-0.
<http://continuum.io/blog/bokeh-0.5>5.1)

Bokeh is a Python library for visualizing large and realtime datasets on
the web.

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

See the CHANGELOG for full details.

In upcoming releases, you should expect to see dynamic, data-driven layouts
(including ggplot-style auto-faceting), as well as R language bindings,
more statistical plot types in bokeh.charts, and cloud hosting for Bokeh
 apps.

Don't forget to check out the full documentation, interactive gallery, and
tutorial at

    http://bokeh.pydata.org

as well as the new Bokeh IPython notebook nbviewer index (including all the
tutorials) at:

    http://nbviewer.ipython.org/github/ContinuumIO/bokeh
-notebooks/blob/master/index.ipynb

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

    conda install bokeh

Alternatively, you can install with pip:

    pip install bokeh

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.min.js>
    http://cdn.pydata.org/bokeh-0.5.1.min.css
<http://cdn.pydata.org/bokeh-0.5.min.css>

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 at continuum.io

If you have interest in helping to develop Bokeh, please get involved!

Damián.