In my opinion, Rstudio provides the best environment to be used by statisticians and data scientists. The software is great and its supporting website provides a lot of tutorials.

As 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. Then I started to use RStudio and It was really a big step that makes me more productive. RStudio is an advanced Integrated Development Environment (IDE) for the R language. It has a very nice user interface with advanced code highlighting, viewing data environment, help, and graphs in the same window. Moreover, It is integrated with GIT for easy version controlling inside of the Rstudio. Furthermore, It facilitates creating R shiny apps and developing R packages. 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. So it is a complete R environment for both Statisticians and Data scientists.

Rstudio does not provide menu-driven support for data analysis. 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.

Is great! You start to reduce your fear and anxiety using this software, it is very intuitive and user friendly.

It is great that it has a interfase that helps you to be familiar with the terminal, variables and libraries.

It can be helpful a tutorial for each feature, helping to understand all the things that you can do.

R studio works well, but it could be better. It's an open source software so I do not know if I should expect it to be better, though. You get more than what you pay for (nothing), but the expensive options are worth the price if you can afford it.

I love the price of R/Rstudio - free! Competitors such as SPSS/IBM are expensive for one year licenses. I love how Rstudio is open source.

I dislike how it's more similar to traditional python coding. Competitors such as SPSS have point and click options that are more comprehensive and straightforward.

Overall, I could write my desired code and do my job using powerful packages which were available.

R studio provides a user-friendly environment for R-coder, especially for beginners. The environment provides easy access to variables and their values which is more critical to beginners who need to know what is happening in each part of the code.

This might be a pain point for R overall and not specifically for R studio. However, there are different syntaxes for doing one task when working with some data types, which might get confusing. I prefer simplicity with only one solution.

Using libraries like ddR or multiDplyr, R can process huge amounts of data in parallel or through distributed computing for our research project.

R makes it easy to create beautiful graphs and charts. We can do a wide variety of machine learning tasks with R for our research project. R is an open-source programming language that is free to use. Because of this, anyone can work without getting a license or paying a fee. R is cutting-edge software that gets updated as new features become available.

Other languages for programming, like MATLAB and Python, are much slower than R. R has some limits, such as not being able to be used in a web application. R is not secure enough.

I love the features that allow you to write free open source code to create beautiful output in minutes to be placed in projects and make presentations right in the application. R is a very expandable language and there a many packages that are available to use.

There is a learning curve at first, and do to the amount of information available and packages that can be used, it can be hard to narrow down at first what functions to use when. I wish that RStudio made it easier for people to collaborate with people on their team by allowing web access to make the R files like Google Docs - multiple people can edit the same R file at the same time.

Is worth ad it to make more comfortable to create your new codes.

The interfase is amazing! You can look at the different results from your scripts at the same time. Is intuitive and helps to gain confidence.

At the beginning the organization of the tabs can be tricky, but once you made it, all goes well.

Excellent tool to start and continue coding in a very user-friendly enviroment.

I started coding with the terminal alone. Rstudio interfase helps to be more comfortable while creating new codes. Is a great tool to beginners and veterans.

You can not customize colors and themes on the interfase.

I have been using RStudio Desktop as a Biomedical Science student as part of my courses Applied Biostatistics and Bioinformatics. It is a powerful tool that provides an IDE for data analysis and visualization with R. RStudio Desktop has a user-friendly and intuitive interface which makes it easy to write and execute code, manage packages and libraries, and visualize data all in one place. In addition, one important aspect is its collaboration features and its ability to share projects, code, and data with classmates via GitHub or RStudio Cloud, which has been helpful during team projects. Additionally, the software comes with an excellent integration with the ggplot2 library that allows the creation of attractive plots in no time, perfect for school reports. Overall, I would highly recommend RStudio Desktop to any science student for data analysis and visualization.

What I like the most about RStudio Desktop is its intuitive and user-friendly interface, which allows people with non to limited knowledge of data science or coding, to perform statistic analysis with very little issues.

The software can be quite resource-intensive, which can slow down the computer, especially when working on large projects. I have also encounter some bugs when installing packages.

The best IDE for R programmers. Overall great functionality and easy of use.

Great functionality. Easy to write/edit/modify code. Easy to use and navigate. Great range of options from just writing code to create Reports (RMarkdown) and dashboards (RShiny).

Integration with Git might be a bit complex. The Plot Panel is quite limited.

I have RStudio to handle multiple data sources to ingest huge volumes of data. Next, the data is transformed to meet pre-defined conditions. The data is cleansed and standardised before it is stored in a staging layer. Following this, we analyse patterns and insights available in the data using multiple libraries available in RStudio. We plot graphs to convey insights to shareholders and recommend data-driven actions. This process increases the efficiency of the entire process and adds business value to the organisation.

Handle large datasets efficiently Automation - a number of time-intensive tasks could be automated Flexibility in code design, a number of plotting libraries available, customised plots, multiple data sources supported Intuitive interface with easy installation and set up of libraries Excellent community support Supports statistical, predictive, and numerical analysis

Install more libraries at start-up to reduce the time required to install multiple external libraries Improve the ease of debugging code

It has almost everything an R developer will ever need + some features that are particularly appealing for data scientists (using R) that other generic IDEs are lacking, such as the integration with knitr, pandoc, and markdown, bibliographies and visual editor, that make them particularly appropriate for writing papers or other types of reports.

* Features: it has almost every feature a developer may need + some specific ones for R developers (such as the integration with Knitr and Rmd files) * Objects' explorer is a must in data science, and Rstudio's is particularly good for exploring and giving lot of information about every object in a glimpse. * Multi-platform: GNU/Linux, Windows, Mac * FLOSS * It is used extensively within the R Community * Can be used with python, too

* Lacks refactoring capabilities * Not as appealing as other more modern IDES (such as VSCode) * Not so good for languages other than R * Not extensible

I used r-studio to clean/visualize data and run analyses for a psychology study I worked on. It helped me build on my basic statistical knowledge and gain confidence in my querying.

R-studio is one of the easiest to use statistical tools. It's clean, sleek interface is very intuitive and user friendly. It can handle large amounts of data and it suggests functions as you type, making it very beginner friendly. R-studio was a life saver for me in graduate school and is now a convenient tool I use in my work as an analyst.

R-studio automatically updates periodically which can be a pain. Also, it cannot run multiple queries at the same time.

Overall, an excellent IDE for the R language. Not as smooth and bug-free as could be.

An excellent R IDE for beginner and expert alike. A ton of useful features that makes using R extremely easy, such auto-completion, documentation browser, R Notebooks functionality, data viewer, debugging and build tools, GitHub integration, and more. Doesn't hurt that it looks good too, with the available themes.

Can be a little slow and sometimes glitchy. For example, the data viewer often cannot hand large data samples. Will sometimes crash for no particular reason. The R Notebooks functionality, though still very useful, is currently buggy and missing obvious features - could be much better! Furthermore, there are some features that are lacking compared to a customisable text editor such as Atom.

Working as a freelance epidemiologist and research consultant it is essential that I have access to a program within which I can analyze large amounts of data and share the results easily. R-Studio lets me do this. One the interface of R-Studio is understood it is easy to navigate and allows for numerous analytical procedures to be performed.

R-Studio is free to use and allows users to analyze large datasets easily and quickly. Code for R is available from a variety of sources which enables complicated analysis to be undertaken more easily than writing the code oneself.

I really feel there are no cons to using R and R-Studio.

Research and working with collaborators across labs and at other institutions are made easy.

RStudio is simple and easy to use. Love the integration with Git & Git Hub. Being able to create Rmarkdown documents and html webpages with data and code is made simple and easy. Creating interactive documents with Shiny applications are also made very easy with RStudio.

I don't think there is anything specific that I would change about this software other than I think more people should use it and be taught it in school.