R is incredibly simple and allows for easy manipulation and analyzation of data. It is a tool that handles anything from basic data manipulation to complex machine learning applications.

R-Studio is great for doing any form of statistical analysis. R is very easy to learn and everything seems to flow once you get the basics down. There are countless number of packages that you can use to make your analytics and data manipulation easier. There are even packages to allow you to use python libraries and tools.

No major complaints. Sometimes it's difficult to find the packages (and their documentation) easily. I often find myself googling things instead of using the built in help function.

Overall, R is an excellent data analysis platform, that allows for the creation of polished graphs, and includes a large number of packages that make data analysis easy and intuitive. It very rarely if ever crashes and allows for pulling data from different datasets. Some commands are more complicated than comparable code lines in other programs but usually any issues can be solved by a search engine inquiry.

I use R to analyze data for academic papers. Most recently, I used it to analyze a large dataset of survey responses, and what I like the most is that it can manage using data from different datasets all at once, which is great for large projects. I also think that R is very intuitive when it bounces back with an error to the user, because it explains what the issue is in more detail than other comparable data analysis programs. Lastly, I really like the fact that R very rarely, if ever crashes and that the data analysis code is saved whenever there is a package that requires the program to restart. The packages are also great and allow you to solve more complex data issues than other programs, and it R is particularly adequate for polished graphs, using the ggplot package.

My least favorite part about R is that it is sometimes surprisingly complicated in terms of the code required to complete simple tasks like rename a variable, but there are a lot of forums online for R support, so usually any issues are a search away. I also think R is not quite as good as other programs at giving detailed information on the results of data matching or reshaping data, but this is only a true issue for very specific research projects.

Not available, I just tried this software to see if it could recover my files.

The software doesn't work, it recovers nothing from a deleted harddisk. Comment of R-Studio:"Unfortunately we would not be able to help you to recover the data in this case. You may try to contact professional services data recovery company and see if they be able to help you."

Working with R Studio is great, it is easy to pick up for beginners as well as is a powerful IDE for advanced users. Code written in RStudio can be published and shared with ease.

Using RStudio allows a user to get the most out of R. It is very easy to install and use packages. New packages can be learned and understood very quickly with the help function and the examples that they provide. Images and graphics can be displayed, resized, exported as the user needs them to be.

Some of the defaults can be difficult to work with. Depending on what a user is planning on using R for certain defaults can be poor ways of displaying information, such as when to use scientific notation. Additionally, it is possible to perform actions that either cause infinite loops or could run for days if uninterrupted.

Excellent for data analysis for large data files.

Free, open-source, incredibly rich community of online users, there is seemingly a package for any type of work you are trying to do.

Somewhat steep learning curve, some packages don't work on government servers, overall straightforward syntax but some challenges.