Should you use Python for data science?

It's a key question for many data scientists – especially those that are new to the field: is Python or R better for data science? For those first venturing into the world of data science, it's important to master one language first, rather than looking to be a Jack of all trades from the offset. This is because your processes and techniques are what really matter most, and mastering these in one language before branching out into learning more is what is going to get you a strong footing in the data science world. Once you have a strong set of skills and techniques under your belt, moving into other languages is a great way of skilling up and ensuring that you stay competitive in your field, but your first programming language should allow you to learn as much as you can. And there's no shortage of languages that you can pick as your weapon of choice for doing so – when it comes to data science, there's plenty on offer, including (but not limited to): Java, C, C, Scala, Perl, Clojure, Julia, and more.