I like Python better as a language, but Python&#x27;s libraries take more work to understand and the APIs aren&#x27;t very unified. R is much more regular and the documentation is better. Even complicated and obscure machine learning tasks have good support in R. <i>BUT</i> the performance for R can be very, very annoying. Assignment is slow as all hell and it can often take work to figure out how to rephrase complicated functions in a way that R can figure out how to do efficiently. I think being much more functional than Python works well for data. I mean the L in LISP stands for list! Visualizations are also easier and more intuitive in R, too, IMO. Especially since half the time you can just wrap some data in &quot;plot&quot; and R will figure our which one it should use.<p>I think the conclusion of the article is correct. R is more pleasant for mathier type stuff, while Python is the better general-purpose language. If your jobs involves showing people powerpoint presentations of the mathematical analysis you&#x27;ve done,you&#x27;d probably want to use R. If, on the other hand, you&#x27;re prototyping data-driven applications, Python would probably be better.<p>That said, I really like Julia, but can&#x27;t justify really diving into it at this point. :\