Data Carpentry workshops provide the fundamentals to learning to use scientific computing to facilitate research. In this lesson, we look at some next steps and examples of best practices for organizing a project. We will integrate the data organization ideas from the Spreadsheets lesson with coding in Python and explore how to share code within a lab and as published material.
Data Carpentry Spreadsheets Lesson and a Software or Data Carpentry Python are the minimum requirements. This material will be easier to follow some time after the workshop and you’ve spent some time incorporating those practices into your own work.
This lesson also assumes comfort with the unix command line, but the command line operations could be done through a GUI instead and plain language explanations that accompany command line sections may be enough for a user comfortable creating files and folders and moving them around to do so without use of the command line.