Visualizing distributions of data

Really loving these ipython visualisation articles!

There was one about detecting bubbles in liquid for the purposes of reducing spilling that was very interesting

http://nbviewer.ipython.org/github/soft-matter/trackpy-examp...

This may be in the notebook or on Seaborn's homepage (http://stanford.edu/~mwaskom/software/seaborn/), but someone compared seaborn to pandas in that it provides a terse API to a great base package (matplotlib and numpy, respectively). I'm looking forward to using this more.

I find it nicer than bare-bone matplotlib for plotting (one line of code per standard plot + very pleasant graphically).

I knew that it exists for some time (and I had it already installed) but only today I rediscovered it as a really useful tool for default plots in my data analysis / data exploration.

The violin plots are cool and look like a great alternative to box plots, I had not seen those before. Sweet!

Very cool. I suspect many of these port to R as well, and it would be interesting to compare the code and approach.

scatter matrix is my goto high dimensional visualization.