Top 20 R Libraries for Data Science

All of these programming languages are popular for different data science tasks and projects and have their supporters and opponents. So while we are arranging a comparison of how these programming languages relate to each other, we have prepared some of the most useful R libraries for data scientists and engineers, based on our experience.


R is a well-known and increasingly popular tool in the Data Science field. It is a programming language and a software environment primarily designed for statistical computing, so its interface and structure are very well suited for the scientific tasks. Moreover, R has one of the most developed libraries systems that counts thousands of packages to solve a wide variety of problems.
Although there are many general-purpose packages, we want to focus on those that provide sufficient capabilities for data manipulation, visualization, competitive research, and machine learning. Therefore, we have prepared an infographic of Top 20 R packages for data science, which covers the libraries main features and GitHub activities, as all of the libraries are open-source.

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  1. Ramesh SampangiOctober 30, 2021 at 5:05 AM

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