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RStudio - the biggest analytics platformRStudio is being used by analysts and managers in both marketing and IT departments. In some cases we do ad-hoc analysis, in other cases, we try to streamline data process with R. The IT department comes in when we need more complex analysis and integration with Python. The marketing department uses for basic data analysis (exploratory, regression, and we are planning to use it for segmentation as well).,1: RStudio is a great tool for organizing your R code - coding, executing and seeing the results on the same page! 2: RStudio (and R in general) is great because it is an open source tool! So it receives new packages and updates constantly. It's also one of the most used analytics tools, so you are likely to find all of the models you need here! 3: Did I mention it is free? This is great if your IT department (or company) has budget constraints.,1: Coding background! Even though I think coding with R is much easier than any other tool (C++, Python, VBA...), you still need to know how to code to get an analysis done. Other tools (like Azure ML or JMP), you don't need a coding background. 2: User interface: There are some better user interfaces out there. RStudio is not bad, but it's not the greatest. 3: Saving files: It always confuses me when I need to save a file or a project. I never know when or how to save which.,10,1 - RStudio helped my organization to find opportunities in the business. Those opportunities gave us a strategic advantage with our customers. 2 - Since it's free, the ROI will always be positive! Unless you spend a lot of time building an analysis and end up not using it. 3 - Overall, RStudio helped my organization to be more analytics-driven! Not just data-driven, but finding the right insights inside the data!,Microsoft Azure Machine Learning Workbench, JMP Statistical Discovery Software from SAS, MATLAB, Adobe Analytics, Domo, Microsoft Power BI, Tableau Desktop, Tableau Online and Tableau Server,Tableau Desktop, Tableau Online, Tableau Public, Microsoft Power BI, Microsoft Azure Machine Learning Workbench, Adobe Analytics, Domo, JMP Statistical Discovery Software from SAS, MATLABRStudio the best for statistical dataBasically, I can simplify the steps when updating a database, and reduce working time. Once it is scheduled as a statistical platform, it offers me all the techniques of data analysis. In addition to programming new methods and routines in an easy and robust way, I can do any database immediately. I can perform all the data analysis and even read files of different formats.,In the first place, because it is a language with a complex learning curve, but very robust and effective for the handling of statistical data, for developers, specialized in these languages, it can be simple. R is a programming language in constant evolution and has extensive documentation, ease in data preparation, with this technique is very simple, largely because it automates many processes by programming sequences. R works with any type of file, R is a language that allows the implementation of additional packages that provide a great capacity of data management, it is open source and free.,RStudio facilitates the work when entering RStudio, we see the screen divided into four windows, that multiplatform R, works on Mac, Windows and UNIX Numbers. This means that you can work with your data, figures, analysis and, most importantly, with your instructions. It is free software, there is a large community of volunteers working to update it. Allowing you to face specific problems. Programs like R-studio, Java GUI for R, R-commander, RKWard, among others, and with more than 6000 packages indexed in CRAN, Biocoductor, GitHub and R-Forge.,10,R has a vast [amonut] help documentation, description of packages and functions. It is difficult to find specific information at any given time. R is an online programming language of command, which does not involve the use of menus like other statistical programs, this makes many people who are not familiar with programming It is very difficult to migrate to R. But this is more than a disadvantage, because programming will better understand the basis of statistics and data analysis, compared to other people who do not use R.,CakePHP, Google Data Studio, CloudDRIVEBest all-in-one IDE for RRStudio is used by several working groups within a larger project for the University of Vermont. It is used mainly for statistical analyses, manipulating spatial data, spatial analyses, and other programming/statistical tasks. I use my personal version of Rstudio as well as Rstudio server for analyses for this project. Rstudio is one of the best IDEs I have come across for R. I can keep track of variables within my workspace, view the files in my working directory, run the code and inspect output, and look at plots on different panels of the Rstudio interface. This helps keep my work organized and efficient. Rstudio has helped increase the overall productivity of the working group in which I work. Also, Rstudio interfaces with Github, which has been used for collaborative coding efforts.,Rstudio is very customizable. You can easily change font colors, sizes, and screen layout. I am particular about how I like my IDE setup, so this is a big plus for me. Rstudio allows you to look at datasets in your workspace with the click of a button. I do a lot of data manipulation, so I am constantly having to look at datasets after operations to make sure they look correct. The view option in Rstudio makes checking datasets very fast. Finally, I love the way Rstudio manages plotting. Your plots can be viewed in one of the panels. Those plots can easily be copy/pasted or exported into a variety of file types. You can also magnify the plots and scroll between plots to look at previous plots.,Sometimes Rstudio crashes when you work with big datasets. I've had some issues installing packages, which is very annoying. Sometimes I can install packages on my PC but not on my Mac, and vice versa. Rstudio is not exactly a lightweight IDE, so it is not ideal for computationally intensive tasks.,10,Increases rate of publishing in research journals. Specific packages in R (not available elsewhere) have allowed me to progress on a new climate downscaling technique I am working on. On the negative side, it is not very unusual to spend 2+ hours figuring package install errors.,PyCharm,PyCharm, Anaconda, GitHub,50,1,analyzing data plotting data and results data processing/formatting,geospatial analysis implementing new techniques (Bayesian spatial analysis via the spBayes package) on research data process large amounts of data easily,writing up research results with Rmarkdown/Latex make use of the 'project' feature in Rstudio which integrates with github integrate other languages into R code (python, C++),10An Essential Tool in Your Data Science ToolkitRStudio is used in our organization for advanced statistical analysis and visualization of data. It also helps us to implement and use advanced forecasting and application modeling for our online and e-commerce data points. For the most part, RStudio is able to meet our needs. While there are other options and opportunities, the open-source community driven nature of the R Community and RStudio helps to greatly enhance the base capabilities available to the initial program.,Easy to Deploy Inexpensive Powerful analysis,Open-Source (Can lend itself to vulnerability) Data Ownership Terms Python quickly overtaking the R language as the data science programming language of choice,8,Faster and more custom data analysis and insights Better visualization than provided by most default visualization platforms Quick, functional democratization of data.,Google Analytics Premium, Adobe Analytics, Adobe TargetRStudio goes a long way for open-source programsRStudio was used by my organization to "clean" big-data projects while working in a private consulting setting. RStudio made the process of importing multiple datasets, creating arrays, and combining data extremely efficient due to the easy to understand the visual layout of the program. The added dictionary feature built into the interface was also very useful. Using the programs interface with others who are not familiar with the R language is more effective as each item defined will be visually identifiable.,Able to handle large amounts of data without storage issues All-in-one user interface Tabs for different worksheets is useful to stay organized Codes can be saved as a project,Sometimes RStudio creates a problem in viewing data; does not show all the fields Dictionary/package finder could be more intuitive Large computational tasks will take longer than running them in command line,10,It is open source so that goes a long way for usage across the company Compatibility with other programs has made it useful in cross-platform data projects A lot of companies and municipalities utilize RStudio, and visualizations that can be created with RStudio helps to promote internal business objectives,rkward, rcommander and JGR,ArcGIS, Microsoft Access, QGIS
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RStudio
40 Ratings
Score 8.8 out of 101
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RStudio Reviews

RStudio
40 Ratings
Score 8.8 out of 101
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Gabriel Chiararia profile photo
June 05, 2018

Review: "RStudio - the biggest analytics platform"

Score 10 out of 10
Vetted Review
Verified User
Review Source
RStudio is being used by analysts and managers in both marketing and IT departments. In some cases we do ad-hoc analysis, in other cases, we try to streamline data process with R. The IT department comes in when we need more complex analysis and integration with Python. The marketing department uses for basic data analysis (exploratory, regression, and we are planning to use it for segmentation as well).
  • 1: RStudio is a great tool for organizing your R code - coding, executing and seeing the results on the same page!
  • 2: RStudio (and R in general) is great because it is an open source tool! So it receives new packages and updates constantly. It's also one of the most used analytics tools, so you are likely to find all of the models you need here!
  • 3: Did I mention it is free? This is great if your IT department (or company) has budget constraints.
  • 1: Coding background! Even though I think coding with R is much easier than any other tool (C++, Python, VBA...), you still need to know how to code to get an analysis done. Other tools (like Azure ML or JMP), you don't need a coding background.
  • 2: User interface: There are some better user interfaces out there. RStudio is not bad, but it's not the greatest.
  • 3: Saving files: It always confuses me when I need to save a file or a project. I never know when or how to save which.
Well suited: For anyone interested in data analysis. R can help you do a simple exploratory analysis to increase your R Square with a boosted decision tree! It's probably one of the most comprehensive analytics tools.

Less appropriate: Maybe if you have a team more focused on business and less on data analysis (marketers, salespeople, for instance), RStudio might not be the best, since the learning curve is complicated.
Read Gabriel Chiararia's full review
Jennifer Lamas profile photo
June 04, 2018

User Review: "RStudio the best for statistical data"

Score 10 out of 10
Vetted Review
Verified User
Review Source
Basically, I can simplify the steps when updating a database, and reduce working time. Once it is scheduled as a statistical platform, it offers me all the techniques of data analysis. In addition to programming new methods and routines in an easy and robust way, I can do any database immediately. I can perform all the data analysis and even read files of different formats.

  • In the first place, because it is a language with a complex learning curve, but very robust and effective for the handling of statistical data, for developers, specialized in these languages, it can be simple.
  • R is a programming language in constant evolution and has extensive documentation, ease in data preparation, with this technique is very simple, largely because it automates many processes by programming sequences.
  • R works with any type of file, R is a language that allows the implementation of additional packages that provide a great capacity of data management, it is open source and free.
  • RStudio facilitates the work when entering RStudio, we see the screen divided into four windows, that multiplatform R, works on Mac, Windows and UNIX Numbers.
  • This means that you can work with your data, figures, analysis and, most importantly, with your instructions. It is free software, there is a large community of volunteers working to update it.
  • Allowing you to face specific problems. Programs like R-studio, Java GUI for R, R-commander, RKWard, among others, and with more than 6000 packages indexed in CRAN, Biocoductor, GitHub and R-Forge.
With RStudio you can review statistical databases in a quick way to help simplify work. If working with certain numbers is cumbersome, RStudio helps to improve the process.
Read Jennifer Lamas's full review
Maike Holthuijzen profile photo
April 25, 2018

RStudio Review: "Best all-in-one IDE for R"

Score 10 out of 10
Vetted Review
Verified User
Review Source
RStudio is used by several working groups within a larger project for the University of Vermont. It is used mainly for statistical analyses, manipulating spatial data, spatial analyses, and other programming/statistical tasks. I use my personal version of Rstudio as well as Rstudio server for analyses for this project. Rstudio is one of the best IDEs I have come across for R. I can keep track of variables within my workspace, view the files in my working directory, run the code and inspect output, and look at plots on different panels of the Rstudio interface. This helps keep my work organized and efficient. Rstudio has helped increase the overall productivity of the working group in which I work. Also, Rstudio interfaces with GitHub, which has been used for collaborative coding efforts.
  • Rstudio is very customizable. You can easily change font colors, sizes, and screen layout. I am particular about how I like my IDE setup, so this is a big plus for me.
  • Rstudio allows you to look at datasets in your workspace with the click of a button. I do a lot of data manipulation, so I am constantly having to look at datasets after operations to make sure they look correct. The view option in Rstudio makes checking datasets very fast.
  • Finally, I love the way Rstudio manages plotting. Your plots can be viewed in one of the panels. Those plots can easily be copy/pasted or exported into a variety of file types. You can also magnify the plots and scroll between plots to look at previous plots.
  • Sometimes Rstudio crashes when you work with big datasets.
  • I've had some issues installing packages, which is very annoying. Sometimes I can install packages on my PC but not on my Mac, and vice versa.
  • Rstudio is not exactly a lightweight IDE, so it is not ideal for computationally intensive tasks.
Well suited for spatial data analysis, statistical analyses, plotting and working with collaborators through GitHub. It can also compile Latex files and supports Rmarkdown, a markup language similar to Latex. Packages are constantly being added, so it's great for using novel analytical techniques that may not be available elsewhere.

Not as well suited for any big data tasks or deep learning or image processing.
Read Maike Holthuijzen's full review
Eric Myers profile photo
May 07, 2018

RStudio Review: "An Essential Tool in Your Data Science Toolkit"

Score 8 out of 10
Vetted Review
Verified User
Review Source
RStudio is used in our organization for advanced statistical analysis and visualization of data. It also helps us to implement and use advanced forecasting and application modeling for our online and e-commerce data points. For the most part, RStudio is able to meet our needs. While there are other options and opportunities, the open-source community driven nature of the R Community and RStudio helps to greatly enhance the base capabilities available to the initial program.
  • Easy to Deploy
  • Inexpensive
  • Powerful analysis
  • Open-Source (Can lend itself to vulnerability)
  • Data Ownership Terms
  • Python quickly overtaking the R language as the data science programming language of choice
To get your feet wet in data science, you definitely should start with RStudio. It allows a low barrier to entry in terms of the learning and knowledge required to set it up and interact. As your analyses get larger, however, RStudio may not be your most efficient choice. It can quickly get bogged down when you begin breaching into extensive data sets that are larger (100000000+ rows of data) and will be dependent on the box you install it on (unless you can cloud-deploy and use Shiny). Be careful before you invest too heavily into this platform that you have truly considered the full costs.
Read Eric Myers's full review
Bronson Bullivant profile photo
April 25, 2018

Review: "RStudio goes a long way for open-source programs"

Score 10 out of 10
Vetted Review
Verified User
Review Source
RStudio was used by my organization to "clean" big-data projects while working in a private consulting setting. RStudio made the process of importing multiple datasets, creating arrays, and combining data extremely efficient due to the easy to understand the visual layout of the program. The added dictionary feature built into the interface was also very useful. Using the programs interface with others who are not familiar with the R language is more effective as each item defined will be visually identifiable.
  • Able to handle large amounts of data without storage issues
  • All-in-one user interface
  • Tabs for different worksheets is useful to stay organized
  • Codes can be saved as a project
  • Sometimes RStudio creates a problem in viewing data; does not show all the fields
  • Dictionary/package finder could be more intuitive
  • Large computational tasks will take longer than running them in command line
It is best for use in large data projects, or small ones with a lot of specific code which has to be saved in a common place. I would say it is less than ideal for tasks that are simple which are best saved for programs that can be replicated among many users, such as Excel/VBA.
Read Bronson Bullivant's full review
Jake Tolbert profile photo
April 24, 2018

User Review: "RStudio is the only IDE you need for R"

Score 10 out of 10
Vetted Review
Verified User
Review Source
I used RStudio to do the overwhelming majority of my data analysis, which includes general direct mail-style campaign selection, statistical analysis, predictive modeling, and reporting. It gives me a single environment to work in where I can do SQL-style work, statistical work and reporting--in essence, if it involves data, I'll do it in RStudio.
  • RStudio ticks most of the IDE boxes for R users: autocompletion, an overview of your current environment, an interface for files in the working directory and a way to interact with plots in the GUI.
  • Combined with the tidyverse set of packages, you can do most of your database work, plus work faster and smarter, in both the interactive environment and in scripts.
  • RStudio's snippets functionality allows you to quickly access the bits of boilerplate code you find yourself typing over and over and to paste them in with just a few keypresses.
  • Though they're currently developing ways to extend RStudio, ie. add-ons, the environment and hooks needed are still fairly limited.
  • Package management is available, but could be simplified even further.
  • Git integration is great and provides are really useful way to view diffs. However, I still run into a few bugs here and there that force me to drop back to the terminal.
RStudio is a must if you've doing any work at all in R--there's simply not a better tool. I've looked into other IDEs including Rodeo--they're just not nearly as polished or effective. RStudio is a mediocre SQL client, but can function as such if need be. The terminal support added recently is useful, but again, the heart of RStudio is semi-interactive work in R.
Read Jake Tolbert's full review
Jevgenijs Steinbuks profile photo
April 24, 2018

RStudio Review: "Open Source Statistical Software ideal for Big Data Work"

Score 8 out of 10
Vetted Review
Verified User
Review Source
Our department extensively uses RStudio to conduct econometric analysis for development research. It is the second popular software after STATA. Rstudio is also occasionally used in other Departments in their knowledge products.
  • Open source and massively parallelizable makes it an ideal vehicle to work with Big data
  • There are many extensive libraries, which makes it easy to implement complex routines in R
  • RStudio is especially helpful to work with geospatial data, such as satellite nightlights or road traffic data.
  • The numerical libraries in R rely on open source solvers, which leads to stability issues for solving complex nonlinear problems
  • Many open source packages are unstable and poor quality
  • Less user-friendly than STATA
RStudio is very well suited for manipulating and organizing large scale geospatial data. It is less appropriate for a complex nonlinear econometric estimation.
Read Jevgenijs Steinbuks's full review
Mounika Chirasani profile photo
April 24, 2018

RStudio Review: "IDE to use with R programming"

Score 8 out of 10
Vetted Review
Verified User
Review Source
RStudio has been used by myself for my Research on machine learning algorithms support vector machines, neural networks, and singular spectrum analysis. It is used mainly for data cleaning and for predictive analysis.
  • Mainly used for data wrangling. Statistical knowledge of software coding skills can do wonders
  • It is used to analyze, process and manipulate data
  • Easy to use for a new learners
  • There are still missing packages for machine learning and deep learning. It has to be improved as python has many.
  • Processing large documents might struck the system while using this IDE.
  • Plotting and showing the graphs has to be improved.
It is best for analyzing large data and predicting and regressions of data.
Read Mounika Chirasani's full review
Robin Mattern profile photo
February 12, 2018

Review: "RStudio as a documentation tool for software development"

Score 9 out of 10
Vetted Review
Verified User
Review Source
We are software developers, not data scientists. We use RStudio for documentation. The .RMD pages allow us to document operational and development tasks with repeatable commands and/or scripts intermixed with explanations.
  • Document BASH and build scripts written in various languages.
  • Run Ad Hoc and initial SQL statements against our databases.
  • Easily publish the .RMD documents as HTML or PDF files.
  • Support for NodeJS and Javascript.
  • Better examples and documentation regarding PanDoc.
Read Robin Mattern's full review
No photo available
April 25, 2018

RStudio Review: "Most underappreciated IDE"

Score 10 out of 10
Vetted Review
Verified User
Review Source
Our entire team uses RStudio both for statistical analysis and application development purposes.
  • RStudio is probably one of the most underrated IDEs. The environment panel is probably the most useful one.
  • The help tab is also very useful, saves a lot of random Google search time.
  • It is also probably the only IDE I never had issues with while installing/upgrading.
  • The debugging feature is probably not the best designed one.
  • I would love to see a live shiny debugging feature in the future, maybe something similar to the environment panel for reactive values.
  • Big computational tasks are sometimes slower in RStudio.
Rstudio is a very well designed IDE. Especially in cases where the user is a beginner and needs to have a very clear view of his/her variables, Rstudio is very useful.
Read this authenticated review
Juan Francisco Tavira profile photo
November 03, 2017

Review: "Rstudio, all-you-can-imagine algorithms for your data"

Score 6 out of 10
Vetted Review
Verified User
Review Source
RStudio is used just in a couple of departments, mostly data analyst working with huge amounts of data and complex algorithms on statistics, trend prediction, and big data projects. All those process are directly impacting business opening new market oportunities
  • Complex mathematical/statistical algorithms on large amount of data
  • Pattern detection, trend prediction, market analysis
  • User interface feels a bit old and too technical for business people
  • It relies on R installation, that means a lot of the libraries are near "hobbist" work and difficult to install and operate
  • Documentation requires some improvements
RStudio is very well suited when your algorithms are very complex and / or your datasets are huge.
But the visualization tools require a bit more building than alternatives and bear in mind that huge amounts of data require that much memory and network transfer, newer big data tools based on Map-Reduce solve the transfer problem.
Read Juan Francisco Tavira's full review

About RStudio

RStudio is a free and open-source integrated development environment for R, a programming language for statistical computing and graphics.
Categories:  Predictive Analytics

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