We’re going to PLOT!!!!
There are lots of ways to make your matplotlib experience better (especially looking better):
Then, there are numerous approaches using JavaScript (via python):
And lastly, plotly doesn’t quit fit into the above. It’s a true web API for plotting.
Actual discussion
Mark talked about matplotlib basics. The defaults for bar plots are poor, but you can fix them up. Scatterplots are great.
Veusz is a neat package to manually fix up your plot, but you can save them manually.
Bokeh can plot matplotlib objects in javascript. It also does awesome interactive plots and mapping. It can plot in the notbook directly, but you need to run a bokeh-server. Jake Vanderplas (author of mpld3) said he was excited about Bokeh too.
Plotly requires you to be online, but looks nice and is interactive / easy to share.
Vincent is an easy way to get from pandas to D3 (but provides a strong abstraction layer around D3 - Vega).
If you’re interested in digging into javascript, dimple.js comes recommended as a well-documented, lightweight approach that allows full access to D3 underneath. It doesn’t do maps, so if you want that, leaflet and tilemill seem to be the go-to tech these days, with a lot of investment by the folks at Mapbox. This post will probably make you say “whoa, holy map-diffs, GitHub!”