In this post series, I'll talk about the big data visualization platform I'm currently developing with WebGL. I'll give in this first post the main motivations for this project. The next posts will contain the technical details.
My new book, IPython Interactive Computing and Visualization Cookbook, has just been released! A sequel to my previous beginner-level book on Python for data analysis, this new 500-page book is a complete advanced-level guide to Python for data science. The 100+ recipes cover not only interactive and high-performance computing topics, but also data science methods in statistics, data mining, machine learning, signal processing, image processing, network analysis, and mathematical modeling.
I finally took the time to update my Wordpress blog and make it static. Having a PHP-based website in 2014 felt archaic. The new site is generated with Pelican, a great Python-based static blog generator.
I started to learn Python in 2008. The same year, Python 3 was released. Yet, almost six years later, I'm still using Python 2. Like the vast majority of scientific Python programmers, apparently.
But now is the time for me to move to Python 3. You should too. Here's why.
I've participated at an Open Data hackathon organized by the French Minister of the Interior and several open data institutions. Together with Rue89 journalists and an OCTO Web developer, we created in two days an interactive map of all 62,000 road accidents in France in 2012. We used a very rich dataset released by the Minister of the Interior and Etalab.