I'm a data scientist working at the intersection of technology and design. Reformed astrophysicist & former e-Research/data consultant.

Swinburne Hacker Within – Week 9

SHW Week 9 website: Getting the most out of IPython Notebook

What we talked about…

Getting the most out of IPython Notebooks was this weeks topic. After a bit of a rocky start (room booking/ITS issues) we launched straight into a somewhat haphazard discussion about who currently uses IPython Notebooks, why you might want to use the, the emerging culture of open data and reproducible science, and current issues faced by new users. We looked at a couple of examples of simple notebooks on the web. the first was an IPython Notebook I started on the Crisis Mapping in Nepal project (very much work in progress). The second example was this Evolution of Swarming notebook which you can downloaded along with data files. If you have new to IPython I recommend downloading this, launching and editing all the different cells.

Another great example is this Notebook that uses Plotly and CartoDB to visualise earthquake data.

A temporal map of earthquakes as reported by the USGS.


Moving existing code/projects to IPython Notebook may be more effort than it’s worth, especially if you use multiple scripts in multiple languages (e.g. IDL + shell scripts + python), or if your datasets/analysis are really complex. IPython Notebook seems to be great for: describing how you analysed data or wrote your pipeline and sharing this with your collaborators, creating tutorials/teaching materials, supplementing public code with a comprehensive description, creating webpages that include html, text and code, or writing how-to-guides etc.

nbviewer is a really useful site for sharing notebooks and I’ve found some good tutorials on web-scraping (e.g. Mining the Social Web, 2nd Edition) and other programming languages.

Neil gave a short presentation with examples of his own Notebooks and talked about why he uses them, how they are organised, and showed us some really useful features including the ability to mix-and-match markdown, HTML and Latex math in essentially text paragraphs, sharing Notebooks using Gist (rather than nbviewer) and converting Notebooks to latex and HTML and PDF from the command line.



Swinburne Hacker Within – Week 10

Mozilla Science Lab's Australasia community call