The GitHub rendering engine for Ipython notebooks does not support mobile devices (oddly) and it does not support custom CSS/plugins, although this notebook does not utilize any of the latter.
The native GitHub IPython Notebook viewer also doesn't support within-notebook linking, which can be fairly annoying when you spend an hour putting together a nice table of contents system.
Hey Randy, just wanted to say thanks for doing so much to help others extend their knowledge of data science. I don't know where you get your energy but it's been fun watching your rising profile in the data scientist community.
This is great! I have been using iPython notebook (as a biologist) for some months now and "getting a feel for the data" is very important. This notebook is littered with handy Python one liners to quickly gain insight into the data.
I love iPython notebook, I can run the entire back-end on our cluster while working with terabytes of data on my laptop tethered to my phone from a moving train (as we speak ;)).
Edit: Now using your code directly on my own data, I'm learning a lot, a big thanks to Randal S. Olson!!
Definitely, to me the whole cleaning up of data while leaving the code as a trace of that you did is an eye opener (I'm a real noob). iPython notebook is ideal for this. I just started using markdown field to write in a detailed way what I'm exactly doing. I bet it will be helpful to other currently Python unaware colleagues.
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[ 4.9 ms ] story [ 45.4 ms ] thread[1] https://github.com/minrk/ipython_extensions
I love iPython notebook, I can run the entire back-end on our cluster while working with terabytes of data on my laptop tethered to my phone from a moving train (as we speak ;)).
Edit: Now using your code directly on my own data, I'm learning a lot, a big thanks to Randal S. Olson!!