Python vs R: What to choose for Data Science in 2021?

What do the following have in common?

Coca-Cola vs Pepsi
BMW vs Mercedes
Python vs R

Yes, these are competitors. And the pair of Python vs R is not accidental here, because these are the two main languages that are used in data science – one of the most popular areas of work today.

What are the benefits of Python and R? What language should you choose?

Why Choose Python?

The first language that most data scientists think of, because Python is close to the heart of programmers. It is object oriented, easy to learn, flexible and open source. Python has several tools specially designed for data science like Python, NumPy, Matplotlib.

There is a huge community of Python developers where you can ask a question of any complexity. This language has been trending for a long time and is highly expected to remain the first choice of data scientists and engineers.

Why choose R?

This language is very unique in terms of its features that cannot be found in other languages. With R, you can solve tasks like vector manipulation. This language is specially designed for data scientists and statisticians. It is an interpreted language that supports matrix arithmetic, procedural programming with function, and OOPs (object-oriented programming) with generic functions. Data Science R has hundreds of packages and methods to accomplish the necessary tasks, which allows you to achieve the desired perfection in the task at hand.

As you can see, R and Python are equally good at data science.

Therefore, before choosing a language, you should study each of them in more detail and decide which one you would like to stay on.

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