This is the website for Data Science at the Command Line, published by O’Reilly October 2014 First Edition. This hands-on guide demonstrates how the flexibility of the command line can help you become a more efficient and productive data scientist. You’ll learn how to combine small, yet powerful, command-line tools to quickly obtain, scrub, explore, and model your data.
jrnl is a simple journal application for your command line. Journals are stored as human readable plain text files - you can put them into a Dropbox folder for instant syncing and you can be assured that your journal will still be readable in 2050, when all your fancy iPad journal applications will long be forgotten.