Not really. You can use widgets and redraw when the user changes something, but this gets clumsy quickly.
Bokeh allows for interactive visualization though. Vispy[1] does to, by using webgl (but this require a running ipython kernel - so the plot will be static when exported to HTML).
This[2] is an interesting blog post about the future of python plotting/visualization.
Is there any documentation for the plotting library? I would love to explore it, but couldn't find many examples / documentation for different kinds of plot.
Looks like the main advantage is bqplot allows you to create interactive data visualizations. Bokeh and Plotly (commercial product) are the existing libraries that do this, but leave a lot to be desired.
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[ 2.9 ms ] story [ 58.3 ms ] threadBokeh allows for interactive visualization though. Vispy[1] does to, by using webgl (but this require a running ipython kernel - so the plot will be static when exported to HTML).
This[2] is an interesting blog post about the future of python plotting/visualization.
[1] http://vispy.org/
[2] http://www.almarklein.org/future_vis.html
[1] http://matplotlib.org/users/whats_new.html#the-nbagg-backend
I think that a lot of companies used to have internal tools like IPython, but now IPython/Jupyter has surpassed them all. Hooray for OSS.
Julia, Python and Jupyter is awesome toolkit for research, presentation and collaboration.
Hooray indeed to the awesome IPython team!