Data Science, Fundamentals


  • October 25, 2022

How do we choose between Python and R?

This article will help you to understand how we choose between Python and R for data science. We know that R and Python both are open-source programming languages. Both of these languages are having a large community. Both of these languages are having continuous development. That’s the reason these languages add new libraries and tools to their catalog. The major purpose of using R is for statistical analysis; on the other hand, Python provides a more general approach to data science. Both of the languages are state-of-the-art programming languages for data science.

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Python is a high-level general-purpose language. As it helps them increase their code efficiency. Python is a general-purpose language that is used for the deployment and development of various projects. Python has all the tools required to bring a project into the production environment.

Python is better suitable for machine learning, deep learning, and large-scale web applications. Python can be used for various purposes like building a graphical user interface, developing games, etc., despite being an object-oriented language.

There are many python IDEs available to choose from; a few of them are Jupyter Notebook, Spyder, Pycharm, etc.


R is primarily a programming language for statistical computing and graphics. R is a statistical language used for the analysis and visual representation of data. R is suitable for statistical learning having powerful libraries for data experiment and exploration.

Along with object-oriented programming, R can also be used to develop music. R is less popular among users. Its users include scientists and Research & Development who frequently rely on data analysis.

A few IDE’s for the R language are RStudio, StatET, etc.


Both are in-demand skills and will allow you to perform just about any data analytics task you’ll encounter. But based on the factors we can say that Python is picking up and may have an edge over R in years to come. R and Python do not have customer service support which you are on your own in your face any trouble but both the languages have online communities for help and python has greater community support when compared to R. Now we are done with all the parameters of comparison we can say that it was a tough fight between the two but python emerges to the winner due to its immense popularity and simplicity when compared to R. Yet I would suggest that learning both R and Python Which one is better for you will ultimately come down to your background, interests, and career goals.

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Author:John Gabriel TJ

Managing Director || Sr. Data Science Trainer || Consultant || Made 150+ Career Transitions || Helping people to Make Career Transition with a Customized RoadMap based on their past experience into Data Science

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