R vs. Python, a comprehensive guide for data professionals

I started using R back in university and carried on using it in my professional life, it wasn’t until 2015 that I took on using Python as it was the standard in the company I worked for. I now, often get asked which of R or Python, one should use or learn as analytics or data science professional.

These days, my recommendation is usually Python for its’ breadth, better tie out with engineering and for offering an easier path to deploying in production. There is however a lot of variables at play.

Educational background and programming paradigms

Some of the complexity lies from the type of educational background you have. The following quote is taken from the #datascience channel on the measure’s slack.

If you are an analyst first and a programmer second, then choose R. If you are a programmer first and an analyst second, choose Python.

A lot of it has to do with the way users are introduced to these programming language. Functional languages tend to be more familiar to use for those with a baggage in mathematics than object oriented language. The functional approach of R, has even some advocate R to be used as a unix tool…