Not OP, but I've also been look for a way to leave ggplot2 behind and make the jump to 100% python for data analysis. These look neat.

Seaborn - http://web.stanford.edu/~mwaskom/software/seaborn/

Blaze - http://blaze.pydata.org/docs/v_0_6_5/index.html

Bokeh - http://bokeh.pydata.org/

There's also the confusingly named ggplot (for python): https://github.com/yhat/ggplot

I've used that library, and I really don't like it at all. They tried to bring the R syntax to python, which ends up looking awful and is missing the point of the Graphical Grammar. In the same way that every language has it's own way of expressing control flow, every language should have it's own way to express the Graphical Grammar. We don't need R's GGplot2 in python, we need a pythonic way to express the Graphical Grammar.

If I had stronger python-fu I would love to build "GGPy".

Isn't GGPy seaborn?

Maybe. The plots look a lot like GGplot2 plots, any the syntax looks like python, but I haven't dug in to it to see if it builds plots using the Graphical Grammar under the hood.

we've shifted to plot.ly for visualization and moved away from expensive BI tools. We set up python/pandas scripts on CRON to output realtime data to our local plot.ly web server, which makes a local copy of the data and updates the chart. You simply embed the chart as an iframe where ever want internally, and BOOM, you've got a real time chart (beautiful I may add).

www.plot.ly

$60 per user per month is a bit steep...

Considering enterprise BI software/platforms these days can costs upwards of 4k per month, this is roundoff error.

I agree, just doesn't fit the projects I wish to use it for.