RStudio Desktop Erfahrungen

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.

Many functionalities but large learning curve

Kommentare: Overall it seems like a very worthwhile platform, but extremely time consuming learn the basics. This can be frustrating and discouraging.

Vorteile:

There are a ton of packages that can be loaded into R for many purposes (e.g. tables, graphs). For example, GGPlot makes very professional looking graphs that are great for publications. Once you have a basic understanding of the code processes, R can be very useful for a variety of statistics, from simple to quite complex (e.g. MLM, HLM). Also, R is free, which is so amazing considering some of its competitors cost thousands of dollars.

Nachteile:

This is very very difficult to learn as a beginning. It takes quite some time to feel remotely comfortable with the syntax. There are free tutorials on youtube, etc, but it can still be very discouraging as a beginning with coding experience to get started on this platform.

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.

The sophisticated features and tools of R make it a fantastic choice for researchers.

Kommentare: In terms of statistical modeling and analysis, R is one of the most used programming languages.

Vorteile:

Programming in R is available for free and without restrictions. So, there are no requirements for employment, including fees or licenses. R is a state-of-the-art program that gets updates whenever new features are published. R has a renowned set of graphics libraries. These libraries provide assistance and improve the R development environment. The libraries that R provides are numerous and have many different uses. Being able to open the code editor in a separate window is a wonderful feature. With R, creating impressive graphs and charts is simple.

Nachteile:

R is not able to be used in online applications, for example, which is just one of many restrictions it has. R lacks sufficient security. MATLAB and Python are both considerably faster than R as a programming language.

Great way to start coding.

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

Vorteile:

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

Nachteile:

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

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.

Excellent tool for modelling!

Vorteile:

Really great tool and the execution time is quite low!

Nachteile:

There is nothing that I did't like about R-Studio.

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.

Code with simple insights to what you do

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

Vorteile:

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.

Nachteile:

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.

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.

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.

R & Python Developer with RStudio

Kommentare: I am using RStudio over 2 years and I used Python and R languages to programme. It is handy IDE to write code and understand error.

Vorteile:

RStudio is helpful tool for developers who is developing R and Python languages. It helps you understand your code and find the right solution.

Nachteile:

There are other good option respect to the RStudio to use, but you can use it for your progrraming, it works well.

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.

Excellent IDE for R.

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

Vorteile:

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.

Nachteile:

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.

Statistics with R

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

Vorteile:

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.

Nachteile:

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

RStudio Desktop review as a student

Kommentare: 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.

Vorteile:

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.

Nachteile:

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.

Best IDE for R

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

Vorteile:

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).

Nachteile:

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

Review about using RStudio

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

Vorteile:

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

Nachteile:

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

Great solution for data analysis

Vorteile:

They provide open source tools for doing data management, analysis, and visualization. Vast library packages are available to perform statistical analysis as well as machine learning techniques. Highly recommended to the researchers who are handling large data set

Nachteile:

It requires basic knowledge in programming language/ coding. It would be great if the error messages are more informative.

RStudio IDE

Kommentare: I am very pleased with RSudio as it is the best IDE for data analysis

Vorteile:

Rstudio has many interesting features, including easy integration with GitHub and RStudio cloud, and output reports in multiple formats, such as PDF, HTML. In addition, it provides a graphical user interface (GUI) as well as a command-line interface (CLI) to manage R packages. It also supports in-line code execution and in-line plotting.

Nachteile:

Debugging is inefficient in Rstudio, and the software sometimes freezes, especially when working with large datasets.

My experience using R Studio

Kommentare: I use R-Studio regularly at the office for data and statistical analysis and also data visualization.

Vorteile:

The layout and ease of use is superb, there are functions for just about any statistical operation you need to carry out in R Studio. The autocomplete feature on the R-Studio IDE is remarkable, it completes the function for you and also gives you tips on what arguments should be keyed into the functions.

Nachteile:

I have not discovered any feature I don't like yet in R, for now, its just remarkable for statistical analysis and visualization.

Making coding simpler

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

Vorteile:

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!

Nachteile:

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

RStudio is Fantastic! Easy to use

Kommentare: I typically use RStudio to solve research issues such as data analysis of growth mindset. I would highly recommend it for free, convenient data analyses.

Vorteile:

It is super easy to use and convenient. Cheap compared to competitors.

Nachteile:

I think that it is less intuitive than the competitors, such as SPSS. SPSS is much more expensive but definitely easier to use.

Great Data Analysis Software With a Learning Curve

Kommentare: My overall experience with R-Studio has been positive and I have been able to effectively analyze a large amount of data and write papers on it .

Vorteile:

I use R to analyze data for writing papers. What I like about R is that it allows researchers to great insights on their data by using the tools that are in R.

Nachteile:

There is a big learning curve when trying to use R. The software itself does not look inviting to new users and can be daunting.