Why do we carry out research? Well, obviously to test hypotheses, and how do we do that? Again, the answer is simple by getting hold of data. Hopefully, if our experiments are planned and carried out correctly, we can get hold of good data that can tell us something unique about our beautiful planet.
While the first part of any experiment (the planning and execution) is pretty important, the battle does not end here. The other half of the battle is how the data is treated, and analyzing good data in the right way can lead to groundbreaking findings and insights.
Considered to be the scariest aspect of completing research, data analysis is not as much a nightmare as it’s made out to be. While you’ll need to understand what to do with the data, and how to interpret the results, there are softwares out there that are specifically designed for statistical analysis that’ll make this process as easy and smooth as it can be.
Founded in 2009 by J.J. Allaire, RStudio is a company that develops open source and enterprise-ready software for the R statistical computing environment. Its offering allows data specialists to perform their analysis and share them as interactive web apps; enabling clients to scale and share work and make an efficient analysis.
One of its promises is to create free and open-source data science software to enhance the production and consumption of knowledge by everyone, regardless of economic means, and to facilitate collaboration and reproducible research, both of which are critical to the integrity and efficacy of work in science, education, government, and industry.
RStudio currently spends over 50% of its engineering resources on open-source software and leads contributions to over 250 open-source projects, targeting a broad range of areas.
Before, we move on further let’s first get a quick overview of R.
Well, it’s a programming language and environment for statistical computing and graphics. Mainly, utilized for developing statistical software and data analysis, it was created by Ross Ihaka and Robert Gentleman. It was named so, based on the first letter of first name of its two authors, and partly a play on the name of the Bell Labs Language S.
As mentioned above, RStudio develops both open source and enterprise-ready software; here we’ll go through both.
The company’s flagship product, it is an IDE for R. if you don’t know what an IDE is, well, typically IDE provides a rich set tools developing in some target language which in this case is R. It comes with a plethora of features such as console, syntax-highlighting editor, as well as tools for plotting, publishing and distributing data products across your organization, history, and debugging. It provides many features that are lacking in the standard R GUI, and improves on features that do not work properly in the basic R environment.
A user interface for R, it is available in both open source and commercial editions and runs on the desktop (all three major OSs; Windows, Mac, and Linux). It also runs on any system that can communicate with the server RStudio Server or RStudio Server Pro. All you need is a web browser to access it.
It enables you to provide a web browser based interface (the RStudio IDE) to a version of R running on a remote Linux server (Debian/Ubuntu, Red Hat/CentOS, and SUSE Linux), bringing the power and productivity of the RStudio IDE to server-based deployments of R.
Now you can access your work on any system that can communicate with the server. The interface will always look the same, and all you need is a web browser to access it. Its other benefits include:
- Easy sharing of code, data, and other files with teammates
- Allowing multiple users to share access to the more powerful compute resources (memory, processors, etc.) available on a well-equipped server
- Centralized installation and configuration of R, R packages, TeX, and other supporting libraries
All of these are products by RStudio used to share content created by R users.
Open Source Shiny Server provides a platform on which you can host multiple Shiny (an R package that makes it easy to build interactive web apps straight from R) apps and interactive documents on a single server, each with their own URL or port. A commercial version called Shiny Server Pro also exists. Since, it lacks push button publishing and a UI so you’ll need an IT administration for publishing and maintaining apps.
Shinyapps.io is SaaS hosted in the cloud. It has both free and paid plans. It comes with push button publishing. You don’t need to own a server or have knowledge of configuring a firewall to deploy and manage your apps in the cloud. No hardware, installation, or annual purchase contract required.
RStudio Connect is a commercial new publishing platform that can be used for sharing Shiny apps, plots, R Markdown reports, APIs, among many others in one convenient place. Anyone can publish their work in the RStudio IDE to RStudio Connect with the push of a button. That along with scheduled execution of reports, and flexible security policies enables you to bring the power of data science to your entire enterprise.
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.
RStudio Package Manager is a repository management server to organize and centralize R packages across your team, department, or entire organization. Get offline access to CRAN, automate CRAN syncs, share local packages, restrict package access, find packages across repositories, and more. Experience reliable and consistent package management, optimized for teams who use R.
RStudio Team is a bundle of RStudio’s popular professional software for statistical data-analysis, package management, and sharing data products. RStudio Team includes RStudio Server Pro, RStudio Package Manager, and RStudio Connect. RStudio Team offers convenience, simplicity, and savings to organizations using R and RStudio at scale.
Well, that’s it; these were all the essential RStudio products. Hope you liked the article, thanks for reading.