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R: The R Project for Statistical Computing R is a free software environment for statistical computing and graphics It compiles and runs on a wide variety of UNIX platforms, Windows and MacOS To download R, please choose your preferred CRAN mirror
R Tutorial - W3Schools R is a programming language R is often used for statistical computing and graphical presentation to analyze and visualize data With our "Try it Yourself" editor, you can edit R code and view the result How to output some text, and how to do a simple calculation in R: "Hello World!" Result: [1] "Hello World!"
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R Tutorial | Learn R Programming Language - GeeksforGeeks 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 a
R for Windows Tools to build R and R packages This is what you want to build your own packages on Windows, or to build R itself Please do not submit binaries to CRAN Package developers might want to contact Uwe Ligges directly in case of questions suggestions related to Windows binaries You may also want to read the R FAQ and R for Windows FAQ
R: What is R? - The R Project for Statistical Computing R is a language and environment for statistical computing and graphics It is a GNU project which is similar to the S language and environment which was developed at Bell Laboratories (formerly AT T, now Lucent Technologies) by John Chambers and colleagues
How to Create Interactive Dashboards in R with Shiny and ggplot2 Creating interactive dashboards in R with Shiny and ggplot2 is a great way to explore and present data By combining Shiny’s interactive features with ggplot2’s visualizations, you can build dynamic apps You can add several elements like sliders and checkboxes to make the dashboard more engaging and customizable
The Comprehensive R Archive Network R is ‘GNU S’, a freely available language and environment for statistical computing and graphics which provides a wide variety of statistical and graphical techniques: linear and nonlinear modelling, statistical tests, time series analysis, classification, clustering, etc Please consult the R project homepage for further information