A gallery of interesting IPython Notebooks

This page is a curated collection of IPython notebooks that are notable for some reason. Feel free to add new content here, but please try to only include links to notebooks that include interesting visual or technical content; this should not simply be a dump of a Google search on every ipynb file out there.

Note that Matt Davis has conveniently written a set of bookmarklets and extensions to make it a one-click affair to load a Notebook URL into your browser of choice, directly opening into nbviewer.

Entire books or other large collections of notebooks on a topic

• An introduction to Compressed Sensing, part of Python for Signal Processing: an entire book (and blog) on the subject by Jose Unpingco.

• A beautiful matplotlib tutorial, that includes animations and 3d plots. This is part of a complete set of Lectures on scientific computing with Python. By J.R. Johansson.

• A single-atom laser model. This is one of a complete (and amazing) set of lectures on quantum mechanics and quantum optics using QuTiP by J. R. Johansson.

• An introduction to Bayesian inference, this is just chapter 1 in an ongoing book titled Probabilistic Programming and Bayesian Methods for Hackers Using Python and PyMC, by Cameron Davidson-Pilon.

• Logistic models of well switching in Bangladesh, part of the "Will it Python" blog series (repo) on Machine Learning and data analysis in Python. By Carl Vogel.

Scientific computing and data analysis with the SciPy Stack

General topics in scientific computing

• First few lectures of the UW/Coursera course on Data Analysis. (Repo) by Chris Fonnesbeck.

• CythonGSL: a Cython interface for the GNU Scientific Library (GSL) (Project repo, by Thomas Wiecki.

• Exploring seafloor habitats: geographic analysis using IPython Notebook with GRASS & R. This embeds a slideshow and google Earth in the notebook. By Massimo Di Stefano.

• Exploring how smooth-looking functions can have very surprising derivatives even at low orders, combining sympy and matplotlib.

• Using Numba to speed up numerical codes. Another Numba example, this time with self-organizing maps.

• IPython Parallel Push/Execute/Pull Demo by Justin Riley.

• Understanding the design of the R "formula" objects. By Matthew Brett.

Pandas for data analysis

• A 10-minute whirlwind tour of pandas, this is the notebook accompanying a video presentation by Wes McKinney, author of Pandas and the Python for Data Analysis book.

• Time-series analysis with Pandas.

• Financial data analysis with Pandas.

• Data clustering, using pandas, scipy and the R magic.

• Log analysis with Pandas, part of a group presented at PyConCa 2012 by Taavi Burns.

Social data

• A reconstruction of Nate Silver's 538 model for the 2012 US Presidential Election, by Skipper Seabold (complete repo).

• A detailed analysis of the Sandy Hook massacre in Newtown, Conneticut, which accompanies a more detailed blog post on the subject. Here are the notebook and accompanying data. By Brian Keegan.

• More on gun violence analysis with Wikipedia data.

• An analysis of the Gaza-Israel 2012 crisis.

• Ranking NFL Teams. The full repo also includes an explanatory slideshow. By Sean Taylor.

• Automated processing of news media and generation of associated imagery.

• An analysis of national school standardized test data in Colombia using Pandas (in Spanish).

Miscellaneous topics about doing various things with the Notebook itself

• Blogging With IPython in Blogger, also available in blog post form, full repo here. By Fernando Perez.

• Blogging With IPython in Octopress, by Jake van der Plas and available as a blog post. Other notebooks by Jake contain many more great examples of doing interesting work with the scientific Python stack.

• Custom CSS control of the notebook, this is part of a blog repo by Matthias Bussionier.

Whimscal notebooks

• XKCD-styled plots created with Matplotlib. Here is the blog post version with discussion. By Jake van der Plas.

• Van Gogh's Starry Night with ipythonblocks, part of Matt Davis' ipythonblocks. This is a teaching tool for use with the IPython notebook that provides visual elements to understand programming concepts.

• Conway's Game of Life

• "People plots", whimsical stick figures generated with matplotlib.