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.

R was my first love when it comes to coding/data analysis. The ability to easily access the terminal, console, and script all at once is great, but the tool really shines in the ability to easily work with data and graphs. No other IDE does such a great job at making it easy to explore files, data frames, and graphs.

RStudio is probably the most sensible and approachable IDE in existence. Super beginner friendly, and it's used by basically anyone who uses R so help, tips, resources, and examples are much easier to find than other tools/languages. The ability to easily explore data frames, file structures, and visualizations is unparalleled across competitors, and basically sets the standard for how an environment should look and feel.

I'd love to see native python support. It's not really a negative since it's not what the tool is designed for, but the python integration via R is a little clunky for those who kind of know both languages, but don't have time to learn the intricacies of how to run python via r packages. If the creators of RStudio came out with a PyStudio I'd drop all other IDEs in a heartbeat. Package/library management can be a little clunky, but it's something you get used to.

Overall, this software is great and makes my day to day life much easier. There aren't many issues to complain about.

I like pretty much everything about this software. It makes my code writing tasks so much easier and more enjoyable. I really like the integration with Bash and Python. It's nice being able to write code in various languages in the same document. I like being able to see my code, console, global environment, and other windows all at the same time which is done with finesse in this software. Having a easy-access, searchable "help" window is a huge time saver.

There are some bugs I come across every now and again. For example, I had code that would not work like expected. The function I was using was giving a weird output. After troubleshooting for an hour, I closed out of R-Studio, went back in and the function was working as it should. I've encountered other similar issues as well where a simple, "close" and "reopen" fixes problems.

I've been using RStudio for almost a decade now, and it keeps getting better every year. There are new features, new conveniences, and it's simply the best environment for writing and executing R code.

RStudio is feature rich, relatively easy to get around, and incredibly extensible. Combined with R packages of your choice, you can do literally anything in the environment. Code completion, colored highlighting, and easy project management make it a delight.

Nothing comes to mind; it's free and open source, so you get what you pay for.

Very positive.

I love that I can run code line by line. I work a lot with developing functions and stuff and the ability to see how my data are changing throughout the process is amazing

In my mind, R and RStudio are synonymous. I would never use anything else to write R code. So, the only things I dislike are reasons to not use R. If you are going to use R, you should use RStudio

For the low price of free, one can get top of the line statistical analysis. Of course, the learning curve is much higher than commercial statistical software. R requires some knowledge in programming concepts like data structures. One may also very well learn algorithms used in Computer Science and Numerical Analysis to make full use of R. However, this preparation pays much in using the software.

R-Studio could improve its functionality by adding convenient menus and buttons for basic statistics like Stata does.

Amazing matematical programming language. I use it often in my job to perform data analysis.

R is an amazing programming language designed to perform statistical analysis and calculations. It is the swiss army tool of a data-scientist. Thanks to its huge community any doubt you may have can be replied easily by a simple search on internet, or by asking in forums. It's easy to use and thanks to R studio its IDE environment is even easier to check what data is loaded / plot graphs / consult the documentation. Very reccomended.

The software is free and this is amazing since it offers so much. As every programming language it may a bit difficult at the start to learn.

In my eyes, RStudio really gives R a clear edge over Python since Python has nothing that is as good as RStudio to offer in terms of IDE, not even close.

Multi faceted display, flexibility, aesthetics, ease of use and performance

Nothing major, a very minor that I couldn't see a way to add the arrows to the scroll bar for the black background versions (this is an extremely minor thing though!)

It helps me to analized, organized and get explanatory and understandable graphics of my time serie data. I work with a great amount of numeral data that could make me go mad but RStudio helps a lot. It is not that scary once you understand how to use the program, in fact it has become one of the most important tools in my research.

RStudio becomes my best friend. It is so practical to use when you get used to. I work with great amounts of data, time series data of phytoplankton, and having the right packages and codes make my work so simpler. I can analyze and get beautiful and explanatory graphics in a few minutes. The coding part is very handy and it can be editing and saved so you do not lose any code or project for the future. Last but not least, it has an universe of graphic design (colours, shapes,...) that adapts to whatever you need.

I have been using the 1.4.1106 version of RStudio and I have a big problem, every once in a while the program crashed and get closed. I could not find any solution to that problem and it keeps happening. Apart from that, it is a very handy program but you need to learn how to use it and, at first, it is not easy at all. So many steps and packages that you have to be very careful or you are gonna end up very frustrating and angry. It could help a lot to bundle functions from different packages (that are statistically related) into one and the program could provide a "first approach" tutorial when you install it for the first time.

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

My overall experience with RStudio has been very positive. My prior experience in code writing was mainly in SAS, STATA and Matlab. RStudio seems to be a much better IDE than those used by these commercial software applications.

RStudio is easy to install and use for programming. It has all the features one expects an IDE to have and the display makes accessing features clear and simple. The popularity of R and RStudio means there is an abundance of information, free tutorials and support from programming websites like DataCamp. For python users you can link RStudio to python for an IDE. Finally, RStudio is superior for code preparation and testing than to other freely available IDEs such as Microsoft's Visual Studio Code.

I have no significant complaints about RStudio. The problem of backwards compatibility of different versions of R and R packages is not an RStudio problem, and RStudio works with all versions of R and R packages. RStudio might look into ways to make the creation of projects that maintain R compatibility via the packrat package more prominent.

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 developed statistical models on the application, took the results as output, visualized my data and presented them.

The application is very easy to use. The interface is user-friendly and simple. You can write the application with python base. A programming language for statisticians is nice.

There is nothing wrong with the application. Beginners may find it difficult to load libraries.

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.

RStudio is still one of the best softwares for statistics and data science, it is very visual and has a lot of content and packages which were produced along the years. Even thought, with R not being popular right now and RStudio being built mostly for it, it still feels good to be home.

The RStudio software is easy to get in, making it the perfect choice for data science beginners or statisticians. It has tons of visual support, so you have a better idea of what you are doing and better chance to know when you have messed up. The amount of packages it has makes it viable even when having to use another languages since there are a lot of packages that integrates the other languages to the RStudio interface.

The fact that it is built primarily on R, which right now is becoming a dead language, makes it unattractive for most customers.

Rstudio is basically the go-to IDE for R code. Period. What I like the most is the way it can handle R scripts, markdown, notebooks, other languages as well (python, sql, etc.) and even latex syntax if you need it.

The only downsides I've always experienced are: memory efficiency and the fact that it is quite slower than "console R". Also, sudden crashes are quite annoying.

It's a great software which generate outputs very easily using a coding system.And also it includes thousands of useful packages.

We can generate coding out put to a word,html or pdf using knit function

Installation of packages depend on the version of the software.so it's difficult to install packages easily

The version for personal use is free, making it a great starting point if you’re learning how to use R. All help files are at your fingertip. Also, I can print out my source codes together with the output that are already beautifully in the LaTex format.

The plot window can look a bit funny at first (the plots are still produced, but you may need to adjust the plot window size for bigger plots to display properly). Also, if your output is rather large, RStudio might freeze without warning after a very long compilation period.

Analyzing media data statistically to predict future sales

There are many sources to find the codes you need like GitHub so you do not need to be a master code to use R-Studio. Statistical analysis is unparalleled and you get insights for your data easily. You can run complex regressions, and statistical tests easily with a few lines of codes

Not easy for beginners, lots of terminologies to get used to. But there are numerous tutorials on YouTube and a large community to help you whenever you get stuck

R studio is my go-to for writing code and sharing work with others

The user interface offers some point and click functionality, which makes it easier to ease others into the software who don’t have a coding background. It’s really nice to be able to access the console, graphics viewers, raw data and help files from a single screen!

Sometimes users can get overwhelmed by the number of available packages, some of which have functions that are masked by earlier downloads

With R-studio, it has been very easy for me to analyse my lab and field data using the codes. The graphs and other visualization obtained using this software are very informative even without explanation. Its also very easy to export the results. Overall, its a very handy and useful tool for students and researchers.

There’s nothing I dislike about this software, but to mention one I would say its availability and cost.

Overall, I have used R studio extensively and it has helped me automate portions of my work as it easily integrates with Excel

R Studio is an easy to use interface for programming in R, which allows me to easily write/edit my code and check the results in the console. Its easy to use for non programmers and has extensive libraries for statistics.

R is an upcoming language, and it still needs more packages for machine learning, AI etc.