tag: python

IPython Cookbook released


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.

Why you should move to Python 3 – now


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.

Open Data Hackathon: road accidents


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.

Road accidents

Scientific Python in the Browser: it's coming!


There is currently a manifest trend in the scientific Python ecosystem: Python is slowly but surely coming to the browser. It's a real challenge, but we're getting there. In this post, I want to give an overview of where we are, and where we're headed.

Back from our first Vispy code camp at ESRF


We had our first official Vispy Code Camp this week. I and the other core developers of Vispy were kindly invited by the European Synchrotron Radiation Facility. We presented our young library to software engineers from the ESRF and other European synchrotron facilities. It was also the occasion for us to make a gentle introduction to modern OpenGL, as many attendees didn't have experience in real-time GPU rendering. We discovered various scientific use cases in need of high-bandwidth, low-latency real-time visualization of big data.