A guide to using the Unix command-line for efficient data science workflows, including data processing, exploration, and modeling.
A guide to seven essential command-line tools (jq, csvkit, Rio, etc.) for data scientists to obtain, scrub, explore, and model data.
Argues for the importance of statistical theory in data science, using examples from medical research to show where abstract theory solved practical problems.
A review of the book 'NumPy 1.5 Beginner's Guide', covering its content, style, and suitability for learning numerical computing with Python.
A recap of EuroSciPy 2010, highlighting the growth of the Python in science conference, key topics, and the community atmosphere.
Announcing EuroScipy 2010, a European conference on Python for scientific computing, featuring tutorials and keynote speakers in Paris.
