In fact, a user can make it him/herself by using Shiny apps but the nature of the Rstudio is code-driven and the software graphical user interface is intended to help programmers and data scientists and not ordinary pople that like a menu-driven data analysis framework. Rstudio does not provide menu-driven support for data analysis. While it might be the case that you wont have any issues with older versions, as packages are updated. So it is a complete R environment for both Statisticians and Data scientists. It is important to keep R and RStudio up-to-date. Last but not least, it let to easily develop an R notebook to integrate code, graph, table, and documentation with the ability to export it to HTML, PDF, and Word formats. Furthermore, It facilitates creating R shiny apps and developing R packages. Moreover, It is integrated with GIT for easy version controlling inside of the Rstudio. It has a very nice user interface with advanced code highlighting, viewing data environment, help, and graphs in the same window. RStudio is an advanced Integrated Development Environment (IDE) for the R language. Then I started to use RStudio and It was really a big step that makes me more productive. PROSĪs a statistician, I have been an active user of the R statistical programming language since 2007, and I had insisted to use the legacy R GUI all these years until about two years ago. The software is great and its supporting website provides a lot of tutorials. In my opinion, Rstudio provides the best environment to be used by statisticians and data scientists. RStudio Server is the premier integrated development environment for R that allows to move computation close to the data and scale compute and RAM centrally. RStudio is a flexible and multifunctional open-source IDE (integrated development environment) that is extensively used as a graphical front-end to work with R.
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