I was reading a very interesting article on R-Bloggers, “Choosing R or Python for Data Analysis? An Infographic”. The Johns Hopkins Data Science Specialization makes a clear choice towards R. Also, this looks a good choice if you have to point jobs in this area. However, python is a generic purpose language and it is very renown for its numerical, scientific and presentation libraries among Data Scientists. The very thorough article concludes that the result is a tie. My point of view is that there is no point in a flame war between Data Scientists. There are enough free resources, tutorials and MOOCs out there to be able to master both with the right amount of effort.
What are you going to do if you are moved to a team where your colleagues have 90% of the work done in the “other” language? Are you going to spend most of the time imposing your view or rather try to concentrate on the 10% of the work left to do? So, my advice is to take a look at this for those who want to learn “R”, : R Programming by the Johns Hopkins University. If you are able to speak French, this other MOOC is also very good to learn Python from the point of view of a Data Scientist: Python pour les scientifiques. On the other end, I have found this one in English, but I cannot recommend it as I am not following it: Practical Numerical Methods with Python.
I have found a way to compare the job offers for the two languages, on one very active market, thanks to the UK site IT Jobs watch UK, in particular the Python jobs data, stats and trends can be found here, while the same statistics for R jobs can be found here.
