As a general purpose programming language, Python is second to none. And, with libraries such as pandas, matplotlib, and scikit-learn, it has pretty much everything it needs to tackle any data challenge that you might want to throw at it. So, the question that should be on the tip of your tongue is “why would I want to learn R when I already know Python?”

In this talk, you’ll learn why a dedicated Python developer, with over a decade of experience with the language, still chooses to use R for nearly all of his exploratory work. Moreover, we’ll take a look at some of the major differences between R and Python, which tools you need/want to use when working with R, and how the language, and its extensive toolset, can fit into your Python workflow. In addition to its power as an investigative tool, the R language is also quite popular amongst professional data scientists, and so it’s important to understand the language if only to be able to follow along with the plethora of existing resources that use R.

So, if you’ve ever wondered if you’re missing out on anything using Python instead of R, or if you’ve ever found an interesting tutorial that was written in R that you had trouble following, then this talk is for you. By the end of this talk, you should know just enough R to easily follow along with nearly any R analysis or tutorial. And, hopefully, many of the die-hard pythonistas in the audience will be looking forward to giving R a try on their next data analysis task.