TrustRadius
RStudioRStudio - the biggest analytics platform2018-06-05T15:54:17.396ZRStudio 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, MATLABGabriel ChiarariaRStudio the best for statistical data2018-06-04T15:06:02.138ZBasically, 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, CloudDRIVEJennifer LamasBest all-in-one IDE for R2018-04-20T20:20:22.070ZRStudio 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++),10Maike HolthuijzenAn Essential Tool in Your Data Science Toolkit2018-05-07T16:02:01.224ZRStudio 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 TargetEric MyersRStudio goes a long way for open-source programs2018-04-25T15:30:27.725ZRStudio 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, QGISBronson Bullivant
Unspecified
RStudio
40 Ratings
