RStudio application is free to download and offers easy-to-install, easy-to-use, secure, and reliable Developer Tools applications. RStudio is a very fast, small, compact and innovative Open Source Developer Tools for Windows PC. The R tool is a code editor for users of R, an open-source code base used for statistical and predictive analysis. Proficiency in R scripting is recommended before using this tool. R-Tools R-Drive Image R-Drive Image is a potent utility providing disk image files creation for backup or duplication purposes. A disk image file contains the exact, byte-by-byte copy of a hard drive, partition or logical disk and can be created with various compression levels on the fly without stopping Windows OS and therefore without.

Inspired by R and its community

The RStudio team contributes code to many R packages and projects. R users are doing some of the most innovative and important work in science, education, and industry. It’s a daily inspiration and challenge to keep up with the community and all it is accomplishing.

Managing Packages

If keeping up with the growing number of packages you use is challenging, consider RStudio Package Manager.

Analyse & Explore

The tidyverse is an opinionated collection of R packages designed for data science. All packages share an underlying philosophy and common APIs.

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ggplot 2 is an enhanced data visualization package for R. Create stunning multi-layered graphics with ease.

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dplyr is the next iteration of plyr, focussing on only data frames. dplyr is faster and has a more consistent API.

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tidyr makes it easy to “tidy” your data. Tidy data is data that’s easy to work with: it’s easy to munge (with dplyr), visualise (with ggplot2 or ggvis) and model (with R’s hundreds of modelling packages).

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purrr enhances R’s functional programming (FP) toolkit by providing a complete and consistent set of tools for working with functions and vectors.

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A consistent, simple and easy-to-use set of wrappers around the fantastic 'stringi' package. Camtasia studio 8 free. download full version.

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Communicate & Interact

Shiny makes it incredibly easy to build interactive web applications with R. Shiny has automatic “reactive” binding between inputs and outputs and extensive pre-built widgets.

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rmarkdown lets you insert R code into a markdown document. R then generates a final document, in a wide variety of formats, that replaces the R code with its results.

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Use flexdashboard to publish groups of related data visualizations as a dashboard.

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Model & Predict

TensorFlow™ is an open-source software library for Machine Intelligence. The R interface to TensorFlow lets you work productively using the high-level Keras and Estimator APIs and the core TensorFlow API.

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The tidymodels framework is a collection of packages for modeling and machine learning using tidyverse principles.

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Sparklyr provides bindings to Spark’s distributed machine learning library. Together with sparklyr’s dplyr interface, you can easily create and tune machine learning workflows on Spark, orchestrated entirely within R.

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Connect & Integrate

Sparklyr is an R interface to Apache Spark, a fast and general engine for big data processing. This package connects to local and remote Apache Spark clusters, a ‘dplyr’ compatible back-end, and an interface to Spark’s ML algorithms.

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Plumber enables you to convert your existing R code into web APIs by merely adding a couple of special comments.

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The reticulate package provides a comprehensive set of tools for interoperability between Python and R.

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Additional Resources

Ursa Labs is an industry-funded development group specializing in open source data science tools. It is dedicated to advancing the state of the art in high-productivity, high-performance, cross-language software for data scientists.

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Databases using R

Download R Tools Mac

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Download R Tools

I just posted an issue on stan-dev/rstan. It relates to the devtools-rstudio interface, specifically to the way in which RStudio installs Rtools once activated by a call to pkgbuild::has_build_tools(). The automated install is doing something I am not able to replicate with a manual install, and the manual install is causing rstan to fail. A good starting point would be to know precisely what this install script does. I'm hoping someone in the RStudio community can point me in the right direction. Perhaps the script is open code and I can just inspect it?