Matplotlib Cyclers are Great

Posted on Wed 04 January 2017 in visualization • Tagged with python, open science, visualizations

Every now and then I come across a nifty feature in Matplotlib that I wish I'd known about earlier. The MPL documentation can be a beast to get through, and as a result you miss some cool stuff sometimes.

This is a quick demo of one such feature: the cycler.

Have you ever had to loop through a number of plotting parameters in matplotlib? Say you have two datasets and you'd like to compare them to one another. Maybe something like this:


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Brainy Jingle Bells

Posted on Fri 23 December 2016 in neuroscience • Tagged with python, open science, visualizations, brains, holidays

This is a quick demo of how I created this video. Check it out below, or read on to see the code that made it!

The bleeding edge of publishing: a quick biorxiv scrape

Posted on Mon 19 December 2016 in open science • Tagged with python, open science, visualizations, web scraping, preprints

Scraping publication amounts at biorxivΒΆ

Per a recent request somebody posted on Twitter, I thought it'd be fun to write a quick scraper for the biorxiv, an excellent new tool for posting pre-prints of articles before they're locked down with a publisher embargo.

A big benefit of open science is the ability to use modern technologies (like web scraping) to make new use of data that would originally be unavailable to the public. One simple example of this is information and metadata about published articles. While we're not going to dive too deeply here, maybe this will serve as inspiration for somebody else interested in scraping the web.


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Visualizing publication bias: the case of funnel plots

Posted on Wed 30 November 2016 in open science • Tagged with python, funnel plots, open science, visualizations, simulations

This article is now interactive! Check out a live Binder instance here

In the next few months, I'll try to take some time to talk about the things I learn as I make my way through this literature. While it's easy to make one-off complaints to one another about how "science is broken" without really diving into the details, it's important learn about how
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