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Top 20 R Libraries for Data Science in 2018 [Infographic]

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.


Of course, this list of libraries is far from complete, but here we have collected the most generic and time-tested tools in our opinion. There are many other specific libraries that might be more efficient while solving particular tasks, so do not hesitate and share your thoughts and experience in the comment section.

Thank you for your attention!

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Comment by Justin McBride on May 29, 2018 at 10:52am

Nice list. I will say that h2o is MUCH faster than gbm and the latter has been orphaned.

Comment by Macgilchrist on May 24, 2018 at 9:35am

Very useful. Thank you!

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