Practicing data scientists require a great number and diversity of tools to get the job done. Data practitioners scrape, clean, visualize, model, and perform a million different tasks with a wide array of tools. If you ask most people working with data, you will learn that the foremost component in this toolset is the language used to perform the analysis and modeling of the data. Identifying the best programming language for a particular task is akin to asking which world religion is correct, just with slightly less bloodshed.