von R-Tools Technology4.6 / 5 68 Bewertungen
Bewertet am 13.3.2019
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.
Bewertet am 8.1.2019
For all statistics and data analysis needs
Vorteile: R studio - IDE is has made coding in R easier. This software stands out from other such IDEs for different programming platforms because of its ease of installation (Won't face problems related to environment variable/path as often as faced by other tools) and features - the notepad/console/library etc are available in others but this tool lets you look at the variables/dataset - sort and filter interactively without having to code every step. R studio is available in the cloud version as well - so we need not install it in every computer in case we want to use on the go.
Nachteile: I like everything about this tool, I would definitely recommend this to all R programmers
Bewertet am 29.10.2019
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.
Bewertet am 18.12.2018
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.
Bewertet am 21.5.2019
Best tool to use when working in R
Kommentare: Overall, this software is great and makes my day to day life much easier. There aren't many issues to complain about.
Vorteile: 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.
Nachteile: 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.
Bewertet am 4.6.2019
Excellent Data Analysis Tool
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.
Nachteile: I really feel there are no cons to using R and R-Studio.
Bewertet am 3.5.2019
Experience using R-Studio
Kommentare: With R-Studio, my data analysis tasks at work have been made easier. Its probably the best IDE for R available.
Vorteile: Great interface/layout, its open source, has the auto-complete feature why working with functions (this helps as you know which argument to pass into the function). Another great catch is that you can customise the interface to suit your preference. The ability to see your console, and global environment on the same screen is a big plus.
Nachteile: I haven't yet discovered a feature I don't like in R-Studio
Bewertet am 24.10.2019
A great tool for statistics.
Kommentare: It is a very fast and straightforward tool to analyze data without using Excel or ArcGIS. If you know how to code, R-Studio is a convenient tool compared to R or Python if you focus on the analysis. The program is very light.
Vorteile: A very fast tool that you can manipulate and utilize the data without using tools like ArcGIS or Excel. It is free to use and it can analyze the data with coding, and the speed of analysis is faster than other tools like Python as R-studio is more focused on data analysis. Compared to R, it is more straightforward and easier to use for new users.
The help menu is somewhat difficult to understand even though you go into the help menu. As for the most coding programs, it is better to use Stack Overflow.
When you use a version control project, sometimes there is an error when you open other files than R project and you might need to download from the respiratory again.
Bewertet am 18.4.2019
The best IDE for data analysis, and not just R
Vorteile: 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.
Nachteile: 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.
Bewertet am 29.12.2018
Kommentare: I use R Studio on a daily basis to interact with data. It's my go-to software anytime I need to do something too big for Excel or something that might need to be repeated.
Vorteile: Such a user-friendly IDE. It makes managing all of my active data objects, visualizations, and packages extremely easy.
Nachteile: Nobody will ever accuse R or R Studio in being the fastest or most memory-efficient software.
Bewertet am 15.9.2019
Excellent Statistical Software
Kommentare: My overall experience with R-Studio has been positive. I really have the invention of R-Studio Cloud.
Vorteile: The software performs statistical analysis at a robust level and the invent of R Studio Cloud has made generating reports quick and easy.
Nachteile: What I like the least about this software is the way packages are typically installed and how long it takes to install a package.
Bewertet am 15.5.2019
The best interface to use R
Kommentare: I always enjoy working on R-studio; it's reliable, efficient, and very helpful!
Vorteile: It's the best interface out there to use R, specially for stats. It simplifies a lot of the things you would have to do with commands in plain R.
Nachteile: The 'help' section is the same as in R, so that could be improved.
Bewertet am 20.12.2018
Kommentare: Overall its an A+ product, I highly recommend.
Vorteile: Almost everything about this is good, the documentation, syntax, github integration, the packages for ML applications and more.
Nachteile: It can be little slow and glitchy at sometimes but most of the time its does not disappoint.
Bewertet am 2.8.2018
Losing files is an unfortunate situation solved (in most cases) by R-Studio
Kommentare: A very good experience that is uncommon but if it happens, it needs to be done. It is a corrective type of maintenance in a way.
Vorteile: It is a very simple data recovery tool which can perform well for data deletion or damaged disks. I only used it once some while back to recover important data that was stored in an iPod Classic (in disk mode) which started failing. The process was flawless and fast.
Nachteile: Given the nature of the disk drives and as the data tends to be rewritten after a while in the spaces freed by the table of contents (TOC), it is mostly useful when the recovery happens almost immediately after the event, which limits the recovering power of real old data.
Bewertet am 28.4.2019
Hieu t. P.
Kommentare: R-studio is perfect.
It has traceback that can help find where the error is.
It has a very good tool for customizing it.
It is flexible in changing windows.
Nachteile: Sometimes when updating, the packages are gone!
Bewertet am 28.10.2019
RStudio is the Best Way to Use R
Kommentare: 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.
Vorteile: 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.
Nachteile: 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.
Bewertet am 22.7.2019
R-Studio is a definite go to in the data recovery industry!!
Kommentare: With R-Studio being an option for our business, we are not only able to use our DDI Disk Imager for data recovery but also R-Studio. Sometimes the drive is not failed but files have just been deleted and R-Studio is the man for that job getting the deleted files back.
Vorteile: R-Studio is reliable, can recover deleted files, easy to use. We use R-Studio at our data recovery business "Total Access Data Recovery" so often.
Nachteile: The only con is the cost of the program but the cost of data recovery is much higher so it paid for itself.
Bewertet am 25.9.2019
Powerful tool to analyze data statistically
Kommentare: Analyzing media data statistically to predict future sales
Vorteile: 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
Nachteile: 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
Bewertet am 13.6.2019
Do anything you want (with Statistical analysis)
Fan xuan C.
Vorteile: R is known for super high flexibility - allowing you to customize calculation, write codes that fit your analysis goals, etc. No restrictions whatsoever - what you can think you can make it happen in R.
Nachteile: One may need to learn about R language to start with, which might be painful at the beginning, but it is worth the time!
Bewertet am 13.2.2019
Excellent for analytics and data manipulation!
Kommentare: 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.
Vorteile: 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.
Nachteile: 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.
Bewertet am 29.8.2019
An amazing coding interface
Vorteile: Great tool for coding and has amazing packages including the ggplot library
Nachteile: For automation this tool lacks some of the features present in python.
Bewertet am 14.3.2019
Kommentare: With R I have actually used some of the predictive modeling to help make some financial decisions where I work and it has been very valuable for what our needs are.
Vorteile: I really like being able to make predictive models through R. Ive been using this software for about 8 months now and I feel like I am staring to get the hang of it. it requires just a good background in coding but the applications that you can use it for are great! Ive learned how to calculate discrete probability functions on R and its very accurate. oh and its free!
Nachteile: My biggest complaint about R is the huge learning curve that comes along with trying to learn it. I have to say that I was very frustrated at times. I had no previous experience in small amounts of coding or statistics but I must say that this software is good when you get the hang of it
Bewertet am 21.11.2018
On of the best data analysis and visualization tool
Kommentare: Great tool !! Definitely recommended.
1. Open source
2. Numerous packages available to support various functionalities
3. Great support offered
1. In-built functionalities could be added to offer in-house features
2. Need to install package each time using a new functionality
Bewertet am 31.5.2019
R-Studio is the only IDE that should be used for R
Vorteile: I spent a lot of time trying not to use R-Studio because I like to fight against the norm. I found that there are not other competitive IDE's for R. If time is spent to learn the hot keys and enhancements in R-Studio (such as the markdown and GitHub enhancements), one will not want to use other IDEs for R.
Nachteile: At first the product seems clunky until the shortcuts are learned. I should have watched a video for it when I was first using it.
Bewertet am 29.8.2019
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.