Emacs and Data Science

Robert Vesco has an interesting post on why he uses Emacs in his data science work. Vesco is a data scientist for Bloomberg so he’s a serious practitioner of the art. Working in data science means he uses a variety of languages such as Python, R, SQL, Stata, and SAS. He notes that most of those languages have an associated IDE that simplifies working with them but that that means learning multiple editors and probably mastering none. He also notes that those specialized IDEs may fall out of favor and not be supported in the future, that they are not portable across platforms, and that they are hard to customize.

Happily, those defects do not apply to Emacs. It runs on essentially every (serious) platform, is open source, will be supported for as long as there are a few programmers still interested in using it, and, of course, is famously customizable. One consequence of that customizability is it can become a reasonable IDE for almost any language. That means that a single tool can be used for all those languages and that it’s worthwhile mastering that tool because it’s the only (editing) tool you need to learn.

The bulk of Vesco’s post covers those features of Emacs that he finds most useful in his work. One of those features is Org mode that allows him to use reproducible research methods in his research and publishing. It’s an interesting read even if you’re not a data scientist.

This entry was posted in General and tagged , , . Bookmark the permalink.