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Importance of R Language for Data Science

Posted by Doctor Dan on Jul 26, 2016 2:23:04 AM

R is an open-source programming language that was created by Roass Ihaka and Robert Gentleman in 1995. The purpose of developing this language was to focus on delivering a more user-friendly and better way to perform statistics, data analysis, and graphical modules. Initially, R was used for research and academic purposes; however, of late it is being used in enterprises too. In fact, R ranked 6th among the Top Ten Programming Languages of 2015, according to Spectrum Survey conducted by IEEE.

What Makes R Programming Language A Good Choice?

R is the only programming language that allows statisticians to perform the most complicated and intricate analyses without getting into too much of details. With so many benefits for data science, R has gradually mounted heights among professionals of big data. According to a 2014 survey, R is one of the most powerful and popular programming languages used by data scientists today.

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Features of R that makes it popular are:

#1: The Fact That R Is an Open Source Programming Language

R is free for everyone to use because it is an open source programming language. Programming codes of R can be used across all platforms like Linux, Windows, and Mac. There are no limits with respect to subscription costs or license management, which makes it easily available to data geeks. Also, you can have free access to the R programming libraries. Nevertheless, there are some commercial libraries meant for enterprises dealing with data in terabytes. Hadoop is a good example.

#2: The Ultimate Statistical Analysis Kit

R is a programming language having all standard data analysis tools to access data in varied formats, for several data manipulation operations – merges, transformations and aggregations. It includes tools for conventional and modern statistical models including Regression, ANOVA, GLM and Tree, in its object oriented framework, which makes is easier to extract as well as merge the needed information rather than copying it.

#3: Benefits of Charting

R has some great tools to aid data visualization to create graphs, bar charts, multi panel lattice charts, scatter plots and new custom designed graphics. Unparallel charting and graphics offered by R language is highly influenced by data visualization experts. Graphics based on R programming can be seen in blogs like The New York Times, The Economist, and Flowing Data.

#4: R Language Offers Consistent Online Support

R language is the most sophisticated statistics software because of its quick and consistent online support. The language has a loyal user base because statisticians, scientists and engineers, even without proper computer programming knowledge, can easily use it.

#5: The Most Powerful Ecosystem

R has the strongest ecosystem, a package with several functionalities built in for modern statisticians. “dplyr” and “ggplot2” are some examples for data manipulation and plotting, which relieves data scientists from graphic and charting capabilities to be included in applications.

Conclusion

R programming language can do almost everything, for business and otherwise. It is used by leading social networks like Twitter and data scientists find it an indispensible tool.

Topics: Data Science