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R is a statistical programming tool that’s uniquely equipped to handle data, and lots of it Wrangling mass amounts of information and producing publication-ready graphics and visualizations is easy with R So are all sorts of data analysis, mining, and modeling tasks
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R includes extensive facilities for accessing documentation and searching for help There are also specialized search engines for accessing information about R on the internet, and general internet search engines can also prove useful (see below) R Help: help() and ?
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R is an interpreted programming language widely used for statistical computing, data analysis and visualization R language is open-source with large community support R provides structured approach to data manipulation, along with decent libraries and packages like Dplyr, Ggplot2, shiny, Janitor and more
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"R is a language and environment for statistical computing and graphics " "R provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, ) and graphical techniques, and is highly extensible "
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R is a free, open-source programming language built for statistical analysis, data mining, visualization, and machine learning Its strong visualization capabilities make it a favorite among data scientists and analysts who need to share insights with technical and non-technical audiences alike
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R is one of the most comprehensive statistical programming languages available, capable of handling everything from data manipulation and visualization to statistical analysis
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R is a free, open-source programming language, meaning anyone can use, modify, and distribute it It was initially written by Ross Ihaka and Robert Gentleman (also known as R R) of the University of Auckland’s Statistics Department
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