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R Download 2.0: A Free Software for Statistical Computing and Graphics

R Download 2.0: How to Install and Use the Latest Version of R for Windows

If you are looking for a free software environment for statistical computing and graphics, you might want to check out R. R is a popular and widely used tool that can help you perform data analysis, visualization, and modeling with ease and efficiency. In this article, we will show you how to download and install the latest version of R for Windows, which is R 2.10.0, and how to use its features and functions.

r download 2.0

What is R and why do you need it?

R is a free software environment for statistical computing and graphics

R is an open source software that was created by Ross Ihaka and Robert Gentleman at the University of Auckland in New Zealand in the early 1990s. It is based on the S language, which was developed by John Chambers at Bell Labs in the 1970s. R is designed to be a flexible and extensible platform that allows users to manipulate data, perform calculations, create graphs, and develop applications.

R can help you perform data analysis, visualization, and modeling

R has many features that make it a powerful tool for data science. Some of these features are:

  • R can handle various types of data, such as vectors, matrices, lists, data frames, factors, arrays, tables, etc.

  • R can perform various operations on data, such as sorting, filtering, aggregating, transforming, merging, reshaping, etc.

  • R can apply various statistical methods on data, such as descriptive statistics, hypothesis testing, regression analysis, ANOVA, cluster analysis, etc.

  • R can create various types of graphs, such as histograms, boxplots, scatterplots, bar charts, pie charts, etc.

  • R can fit various types of models on data, such as linear models, generalized linear models, nonlinear models, mixed effects models, etc.

  • R can use various packages that extend its functionality and provide specialized tools for different domains, such as bioinformatics, machine learning, spatial analysis, etc.

R has a large and active community of users and developers

R is not only a software, but also a culture. R has a vibrant and diverse community of people who use, develop, and share R. Some of the ways that the R community interacts are:

  • R has an official website ( that provides information, documentation, and downloads for R.

  • R has a comprehensive network of mirrors ( that host the R software and packages.

  • R has a mailing list ( that provides help and support for R users.

  • R has a forum ( that facilitates discussions and collaborations among R users.

  • R has a blog aggregator ( that showcases the latest posts from R bloggers.

  • R has a social media presence ( that shares news and updates about R.

  • R has a conference ( that brings together R users and developers from around the world.

What is new in R 2.10.0?

R 2.10.0 was released in October 2009 and introduced several improvements and features

R 2.10.0 was the latest version of R for Windows at the time of writing this article. It was released on October 26, 2009, and marked the tenth anniversary of the first release of R 1.0.0. R 2.10.0 included many bug fixes, performance enhancements, and new features that made R more robust and user-friendly.

Some of the highlights of R 2.10.0 are:

Enhanced support for Unicode characters and internationalization

R 2.10.0 improved the support for Unicode characters and internationalization in several ways:

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  • R 2.10.0 allowed users to specify the encoding of source files and scripts using a special comment line at the beginning of the file. This enabled users to write and run code in different languages and alphabets.

  • R 2.10.0 enabled users to use Unicode characters in variable names, function names, and package names. This gave users more flexibility and creativity in naming their objects.

  • R 2.10.0 added support for right-to-left languages, such as Arabic and Hebrew, in the R console and the R GUI. This made R more accessible and inclusive for users from different cultures and backgrounds.

  • R 2.10.0 included translations of the R messages and documentation into several languages, such as Chinese, French, German, Italian, Japanese, Korean, Polish, Portuguese, Russian, Spanish, etc. This made R more understandable and helpful for non-English speakers.

New functions and packages for parallel computing and web services

R 2.10.0 added new functions and packages that enabled users to perform parallel computing and web services with R:

  • R 2.10.0 introduced the snow package, which provided a simple and portable way to create and manage clusters of R processes for parallel computing. The snow package supported several types of clusters, such as socket, MPI, PVM, NWS, etc.

  • R 2.10.0 included the parallel package, which was a merger of the multicore and snow packages. The parallel package offered both low-level and high-level functions for parallel computing, such as mclapply, parLapply, parSapply, etc.

  • R 2.10.0 added the Rcurl package, which provided an interface to the libcurl library for accessing web resources. The Rcurl package supported various protocols, such as HTTP, FTP, SFTP, etc., and various features, such as authentication, cookies, proxies, etc.

  • R 2.10.0 included the XML package, which provided tools for parsing and generating XML documents. The XML package also supported XML schemas, namespaces, XPath, XSLT, etc.

  • R 2.10.0 introduced the soap package, which provided an interface to the SOAP protocol for web services. The soap package allowed users to create and consume SOAP messages and services with R.

Improved graphics and plotting capabilities

R 2.10.0 improved the graphics and plotting capabilities of R in several ways:

  • R 2.10.0 added support for alpha blending and transparency in graphics devices and functions. This allowed users to create more realistic and appealing visual effects with R.

  • R 2.10.0 included the latticeExtra package, which provided some extensions and enhancements to the lattice package for creating trellis plots. The latticeExtra package offered some new panel functions, such as panel.smoother, panel.quantile, etc., and some new themes, such as LatticeThemes, TheEconomist.theme, etc.

  • R 2.10.0 introduced the ggplot2 package, which provided a powerful and elegant system for creating plots based on the grammar of graphics. The ggplot2 package allowed users to create complex and customized plots with minimal code and maximum flexibility.

  • R 2.10.0 added the rasterImage function, which enabled users to draw raster images on graphics devices. The rasterImage function supported various formats, such as PNG, JPEG, TIFF, etc., and various options, such as interpolation, rotation, clipping, etc.

  • R 2.10.0 included the tikzDevice package, which provided a graphics device that produced output in the TikZ format for LaTeX documents. The tikzDevice package allowed users to create high-quality graphics that were compatible with LaTeX fonts and symbols.

More options for debugging and testing code

R 2.10.0 added more options for debugging and testing code in R:

  • R 2.10.0 introduced the browseVignettes function, which allowed users to browse the vignettes of installed packages in a web browser. Vignettes are documents that provide examples and explanations of how to use a package.

  • R 2.10.0 included the covr package, which provided tools for measuring and reporting the code coverage of R packages. Code coverage is a metric that indicates how much of the code is executed by a set of tests.

R 2.10.0 added the rbenchmark function, which provided a simple and convenient way to benchmark the execution time of R expressions. The rbenchmark function supported


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