Last Update: July 3, 2018

Basically, R language you can use in six ways.You can use the built-in console, you can process your projects through the integrated development environment (IDE), you can use a number of graphical user interfaces (GUI), you can use R features from other applications or services. R terminal you can attach on your computer or you can use it via several online services (data science platforms). Another option is to use R from other languages, such as from Python or F#. In the following chapters are briefly presented various options and R use cases that you can utilize.

R Distributions IDEs GUIs R From Other Apps R Online R From Other Languages

R Distributions r-project.org Microsoft R Open Oracle R Enterprice R4Stagraph In the case of R distributions, we mean the core R runtime - the console interface for running your R scripts. We know the main distribution from r-project.org site. All other distributions I know are based on this distribution. If you are using R in whatever form, it is 99.9 % certain that you are using this distribution. This distribution is multiplatform and distributed entirely under open-source licenses (mostly GPL). The second well-known distribution of R maintains and develops Mistrosoft (MRO). Formerly Revolution Analytics. MRO is an enhanced distribution for improved performance, reproducibility and platform support. The third distribution is offered by Oracle (ORE). This company has also enriched the basic R distribution by packages that facilitate the integration with Oracle databases. Finally, the last distribution is R4Stagraph. This distribution have pre-installed all R packages used by Stagraph software and does not contain any modifications to the basic R distribution.

R GUIs R Commander Rattle Deducer Stagraph Jamovi JASP Red R R AnalyticFlow BlueSky Statistics Exploratory ggraptR Radiant Latticist RClusterGUI As R GUI (graphical user interface) we consider applications that provides a visual interface which allows you to use R features without the need of manual scripts writing (point-and-click or drag-and-drop). There is no sharp border between IDE and GUI applications. Very often R GUI apps allows you to write custom scripts. This makes it possible to extend these applications. An example can be data import from specific sources (e.g. web services). R GUI apps can be divided into general-purpose and specific. General-purpose applications make available general R functions, such as functions for data wrangling, data visualization or statistical analysis. Conversely, specific-purpose applications provides only a selected set of features that targets selected area of data analysis (e.g. spatial data analysis or clustering functions). In the following text are listed the most widely used R GUI applications. R Commander

The program enables analysts to access a selection of commonly-used R commands using a simple interface that should be familiar to most computer users. It also serves the important role of helping users to implement R commands and develop their knowledge and expertise in using the command line, an important skill for those wishing to exploit the full power of the program. Rattle

Rattle is a popular GUI for data mining in R. It presents statistical and visual summaries of data, transforms data so that it can be readily modeled, builds both unsupervised and supervised machine learning models from the data, presents the performance of models graphically, and scores new datasets for deployment into production. A key features is that all of your interactions through the graphical user interface are captured as an R script that can be readily executed in R independently of the Rattle interface. Deducer

Deducer is designed to be a free, easy to use alternative to proprietary data analysis software such as SPSS, JMP, and Minitab. It has a menu system to do common data manipulation and analysis tasks, and an excel-like spreadsheet to view and edit data frames. Stagraph

Simple and powerful "point-and-click" GUI for data import, data wrangling and data visualization. This tool uses dominantly R packages from the Tidyverse group. Jamovi

Jamovi is a relatively new "statistical spreadsheet", designed from the ground up to be easy to use. Jamovi is an alternative GUI based on R to costly statistical products such as SPSS and SAS. JASP

JASP is an open-source project that provides intuitive interface for standard statistical analysis (e.g. ANOVA, correlation, descriptive statistics, regression analysis, T-Test, ...). Red R

Red R is a gui that provides work-flow style of showing and setting up data analysis. R AnalyticFlow

R AnalyticFlow is a general purpose GUI that organizes data analysis processes in a workflow. Visualized processes can be reproduced easily and accurately by simply using a mouse. BlueSky Statistics

Statistics application and development framework built on R. This tool provides familiar powerful user interface available in mainstream statistical applications like SPSS or SAS. Released under Free and Commercial Edition. Exploratory

Very interesting Online / Desktop interface for data import, data wrangling, data visualization, machine learning, dashboarding and results sharing based on R. ggraptR

Simple web based GUI that allows you to create an interactive data visualizations. Radiant

Radiant is an open-source, platform-independent, browser-based interface for business analytics in R. The application is based on the Shiny package and can be run locally or on a server. Latticist

A graphical user interface for exploratory visualization using the lattice R package. Released as an R package. RClusterGUI

The purpose of this tool is to integrate cluster methods, exploration via metadata-based data subsets, and visualization of data and clusters in a user friendly interface.

R From Other Apps A popular way to extend the existing functionality of any program that works with data (in any form) is to integrate it with the R language. You can use features that are not directly supported in the existing interface. This integration allows you to write the R script that process your data from the main application in R terminal. After execution, the result is imported back into the program. This feature has many programs and platforms. As an example, we can state the following: ArcGIS

Excel

Matlab

PostgreSQL

Power BI Desktop

RapidMiner

SAS

SPSS

Stata

SQL Server

R From Other Languages R language is very good tool for data analysis. Other languages are focused on desktop applications or web services development. By combining them, you can quickly and efficiently create complex and robust solutions. Therefore, R is often used from other languages. On the Internet, you can find many use cases. As an example, the following languages may be mentioned: Python

Perl

Ruby

F#

VB.NET, C#

Julia

SQL

Conclusions

The R language is today a well known, widely supported and mature technology. If you know programming in that language, it can help you to solve a number of problems.

In the article, we looked where and how you can benefit from the R platform. If you know this language, you can use it mostly through IDE tools. For less sophisticated users, there are many GUI applications that make R features accessible via the visual interface, without the need of manual coding. You can use R language in desktop applications or using different types of web services.

This article contains only a part of the R language use cases. If you know about other that are not mentioned in article, do not hesitate to contact me via mail or discussion. I’d like to learn about new option and I will add it to the list.