tag: python

Vélib' Open Data

2013-05-05

Vélib', the public bicycle sharing system in Paris. I've written a short IPython notebook to play with some of the data, and to illustrate how easy it is to use Python for browsing and analyzing public data sets. Here is an image representing the stations in Paris, with the marker size proportional to the number of bike stands in each station, and the color indicating how many available stands there are. The Seine is easily recognizable, and the fact that most stations near the river are full might be linked to the fact that this data has been obtained on a sunny Sunday of May...

IPython mini-book: Learning IPython for Interactive Computing and Data Visualization

2013-04-27

I'm glad to present my new book, Learning IPython for Interactive Computing and Data Visualization, Packt Publishing.

This book is a beginner-level introduction to IPython for interactive Python programming, high-performance numerical computing, and data visualization. It assumes nothing more than familiarity with Python. It targets developers, students, teachers, hobbyists who know Python a bit, and who want to learn IPython for the extended console, the Notebook, and for more advanced scientific applications.

Hardware-accelerated interactive data visualization in Python

2013-04-04

There have been several interesting discussions recently about the future of visualization in Python. Jake Vanderplas wrote a detailled post about the current state-of-the-art of visualization software in Python. Michael Droettboom, one of the Matplotlib's core developers, consequently wrote about the future challenges Matplotlib will need to tackle. Matplotlib has been designed more than ten years ago, and now needs to embrace modern trends including web frontends, high-level R-style plotting interfaces, hardware-accelerated visualization, etc.

Playing with Ruzzle in Python

2013-02-12

Ruzzle is becoming a popular game on smartphones and tablets. Inspired by Boggle, it consists in finding as many words as possible in a grid of 4x4 letters. Here I'll show how one can easily generate and resolve grids automatically in Python.

NumPy performance tricks

2013-01-27

I've been using NumPy for nearly five years, but I'm still learning performance tricks. The reason is that I currently need to deal with very large arrays (hundreds of millions of elements) and the performance of my code started to be disappointing. Then, through extensive line-by-line profiling, I discovered some subtleties that explain why some seemingly harmless lines of code can actually lead to major bottlenecks. Very often, a small trick allows to significantly improve the performance. Here is what I've learnt. These tips are intended to regular Numpy users rather than pure beginners.