Data Carpentry’s aim is to teach researchers basic concepts, skills, and tools for working with data so that they can get more done in less time, and with less pain. The lessons below were designed for those interested in working with data in .
Authors:Christie Bahlai, Aleksandra Pawlik, Tracy Teal
Contributors: Jennifer Bryan, Alexander Duryee, Jeffrey Hollister, Daisie Huang, Owen Jones, Clare Sloggett, Harriet Dashnow and Ben Marwick
Data file for the lesson is: phm-collection-messy.xls
Data Carpentry's teaching is hands-on, so participants are encouraged to use their own computers to insure the proper setup of tools for an efficient workflow.