This week I gave a presentation to my research group about best practices in scientific computing. It can be hard to know what’s out there, so I thought it would be good to give a brief introduction to some tools as a starting point. My main objective was to show how easy version control is with git, and how it could improve the quality of our science. I also wanted to introduce the magic of interactive data analysis using IPython and the IPython Notebook, along with pandas and other scientific libraries. Historically our primary language has been MATLAB, along with Origin for generating figures, but I think these open source alternatives offer a lot of advantages. I’ve posted the files from the presentation here on github (look in the code directory for example IPython notebooks).