RStudio Desktop

RStudio, your Python buddy IDE

Kommentare: I was a user migrated from Eclipse to RStudio, and the change of coding language and environment was rough at the start, but once it gets going, it's amazing how fast you can solve every day problems like it's nothing.

Vorteile:

I think the best thing about RStudio Desktop are the scheduler for Python scripts, personally these have saved hours of tedious work making it a must-use tool for our team.

Nachteile:

Maybe the first time configuration could be a little more intuitive or assisted, once you set up the initial config it's really simple to follow along tutorials or videos to make work.

R for Data Analysts

Kommentare: R was created keeping the data science community in mind, and till date it has lived up to their standards. It is a tool purely focused on analytics and creation of machine learning models. Its libraries allows users to tweak every possible parameters to get the desired results.

Vorteile:

It has always been a tool for statisticians. It provides very specific ML libraries for very specific tasks. The libraries are strategically developed to cater to every minute hyperparameter tuning to achieve optimum results. RStudio allows the codes to be converted to markdowns which can be converted to HTML pages and published as websites effortlessly.

Nachteile:

As mentioned, the R language is quite challenging for naïve users and hence its documentation is also very technical. Its requires some time to gain hands-on experience to get used to this tool. The customer support is also not quite established as compared to python.

R Studio - larger learning curve than SPSS but will save you money

Kommentare: 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.

Vorteile:

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.

Nachteile:

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.

Great tool for coding in R

Kommentare: I've used RStudio to build out code that can help run simple systems that help save a lot of time. Our most important need is that we had to do calculations using data from different sources that can manually take hours but RStudio allows us to get it done within minutes! And the best thing is that you can customize the output better than some other software out there. So overall, I like it a lot but I can understand why some may need something even more powerful.

Vorteile:

This is the best way to code in R and run code that could be helpful for all tasks from the mundane (like renaming or moving files) to the more advanced (like calculations across multiple excel sheets and creating a new master excel sheet with all of the data). Variables are clearly defined in the workspace at the top right, console at the bottom left - your typical work layout which helps with consistency. Overall, I love how powerful it is and like how many different packages are available.

Nachteile:

It's not as fast as some other software, but even for being free, this is more than enough. There isn't a lot of help for using this program either and I feel like I only knew about it because we've used it in school. Overall, the UI could get an update in looks to be more updated with the current times.

Exceptional IDE for Working with Data

Kommentare: I have found using RStudio intuitive, easy, and fun to use. I continue to marvel at the big and little things the developers have implemented that makes this a world class IDE and an indispensable tool for data analysis, data visualization, and general purpose coding.

Vorteile:

RStudio is a delightful IDE for working with Rlang and data. The ability to view tables instantly as you write each line of code allows for deeper insights and better coding. The table viewer even has sort and filtering functions to assist with the coding. The IDE functions make finding the right code commands and their arguments as simple as can be hoped. The layout of the screen and the ability to break out separate windows is really great and makes using the software on a single screen or multiple screens very friendly.

Nachteile:

Missing since of the third party add-ons of IDEs like PyCharm or Visual Studio that enable greater customisation.

The best IDE out there for R programming

Kommentare: Overall, I think RStudio is one of the best and most complete IDEs out there. For R programming specifically, it gives me a lot of flexibility and productivity boosts which is hard to do with any other R IDE.

Vorteile:

I like the completeness of RStudio as an IDE. It has lots of useful features and integrations with R packages that just boosts my productivity.

Nachteile:

I'd like more theme options to choose from. Other than that, I don't really have anything I dislike about RStudio.

A simple IDE with great power

Kommentare: When developing scripts in R, this IDE is the one that should everyone one choose due to its wide range of functionalities.

Vorteile:

Being able to manipulate large datasets and perform complex calculations with ease has greatly improved efficiency in the company. What I find most beneficial is the ability to create reproducible research and reports using R Markdown

Nachteile:

For new developers in R, UI may have some learning curve in comparison to other IDEs.

RStudio user for data analysis, visualisation and modelling

Kommentare: 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.

Vorteile:

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

Nachteile:

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!)

RYouWithMe

Vorteile:

It is very convenient to use for all kinds of data analysis with the inbuilt libraries.

Nachteile:

Some time there is a problem in viewing data. It does not show all the fields.

RStudio Desktop is the best IDE for R

Vorteile:

RStudio makes coding in R easy, helpful, and powerful, with a friendly interface and plenty of tools

Nachteile:

RStudio might slow down your computer, sometimes has trouble with big outputs, and doesn't have a menu for data analysis

Avi's review

Vorteile:

The "strongest" software to analyse big Data

Nachteile:

It's not friendly and very complicating to use

Start to code!

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

Vorteile:

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.

Nachteile:

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

Best IDE for R

Kommentare: The user interface is friendly enough and easy to navigate through for beginners and the tools and capabilities are very satisfactory for advanced users. So R-Studio is a great product for a wide range of users.

Vorteile:

I have enjoyed sing R studio in my machine learning project. R-Studio provides great visual representations of data which I found tremendously helpful. If you are doing heavy R coding, R Studio is a must. The variables are defined in the environment and you can see them by simply clicking on them. There are lots of great libraries to experience with once yo get a hang of it. R-Studio can slow down with large data, but the great integration with cloud computing technologies make up for it. I used the Azure Cloud for cloud computing with R-Studio and I liked that the integration was seamless and the process was so easy. I set the cloud in R-Studio under five minutes.

Nachteile:

Some libraries are not optimized for performance. So you might need to try a few libraries before finding an implementation that will run the algorithm smoothly for a large data set. Also, the program might freeze and you might not be able to recover your work. It's always a good idea to save your work.

The best R suite for statistical analysis

Kommentare: My overall experience has been great, I used RStudio during my PhD program and continue to use for statistical analysis as well as developing new functions, running data analysis and data visualization.

Vorteile:

RStudio integrates the programming language of R into a suite where the user can download packages, visualize their code and run it as well as debug it. Its a must have for R programmers.

Nachteile:

There are no major dislikes about R studio, being a free software it does depend on the open source community for continuing development, which can be arguably not beneficial to the software.

Excellent Integrated development environment solution

Kommentare: 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.

Vorteile:

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

Nachteile:

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

As a researcher, I use R for our project, because it has a lot of advanced features and tools.

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

Vorteile:

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.

Nachteile:

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.

A de facto standard for R Developers

Kommentare: 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.

Vorteile:

* 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

Nachteile:

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

RStudio is a versatile independent development environment

Kommentare: 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.

Vorteile:

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.

Nachteile:

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.

Probably the most beginner-friendly IDE out there

Vorteile:

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.

Nachteile:

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.

Excellent software for data analysis of agricultural research

Vorteile:

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.

Nachteile:

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

R Studio For Data Mining

Kommentare: Basically, I have good memories with this software. When I was learning as a graduate, I used to use this R studio to solve some statistical and mathematical problems which are given by my lectures. There are many aspects of this R studio. If you are a Student, Statisticians or Mathematician, still you may able to use this in order to make things easy.
It has given many options to get some quality graphs that are not available in other software. You have so many ways to present your output. You have a bunch of options to do some analysis in different techniques.
But this is highly recommended for those who are familiar with statistics or Mathematics.

Vorteile:

When we want to take the analysis output, there are so many options available according to that scenario such as R notebook, R markdown, R shiny etc. The very best second thing is this is open-source software( you do not need to buy it)

Nachteile:

When I am dealing with some data mining process, I need to install some packages and I should have a great awareness about those packages in order to get the best output.

A Good Tool For R Programmers

Kommentare: Overall, this is my to-go tool for R programming even though there are other options such as Jupyter that offer many different kernels such as Python and Julia other than R.

Vorteile:

The ability to install missing R packages instantly, creating R Markdown documents, and integration with Shiny Web App are the most appealing features for me as a machine learning researcher. I use RStudio almost everyday and have found it be one of the best interfaces to the R programming language for large scale data science projects.

Nachteile:

Memory management, in particular, with regards to installed packages is not intuitive and the user has to rely on command line options for a clearer picture.

Awesome free analytical software

Kommentare: 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.

Vorteile:

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.

Nachteile:

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

The Best Data Software

Kommentare: Thanks for Providing R-Studio.

Vorteile:

I'm using R software for about a year now. It is one of the best programming languages. Everyone who wants to work as a data engineer, data analyzer, or data scientist should know R. It provides efficient packages to solve various problems. It is user-friendly and easy to learn. When I started to learn R, I thought that it should take a lot of time. But after a while, I mastered using R. It has several features that make it easier to use R instead of utilizing other software.

Nachteile:

It is a reliable and efficient software. I cannot say too much about its Cons. Just as a personal experience, I do not like the graphics and environment of the software. I think it can be improved.

Great tool to code

Kommentare: As a new person in coding, Studio helpme to feel more confident to explore all the possibilities to process our data.

Vorteile:

It is a great improvement to R, the interfase is good and the new tools are great for someone new in the coding world.

Nachteile:

It can help a tutorial for the customization of the features tha Studio presents.