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Intuitive User Interface: Users have found RStudio to have an intuitive user interface that allows them to quickly test and debug code. …
Overview
What is Posit?
Posit, formerly RStudio, is a modular data science platform, combining open source and commercial products.
Recent Reviews
Awards
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Popular Features
- Visualization (26)8.484%
- Connect to Multiple Data Sources (25)8.181%
- Extend Existing Data Sources (26)7.474%
- Automatic Data Format Detection (25)6.363%
Reviewer Pros & Cons
Video Reviews
2 videos
RStudio Review: It Proves To Be A Reliable Statistical Tool W/ Support Avenues In Place If Needed
02:53
RStudio Review: Works As An Useful Tool But User Finds Free Version Could Be More Competitive
02:13
Pricing
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What is Posit?
Posit, formerly RStudio, is a modular data science platform, combining open source and commercial products.
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- Setup fee optional
For the latest information on pricing, visithttps://posit.co/pricing
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- Free Trial
- Free/Freemium Version
- Premium Consulting/Integration Services
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Product Demos
What is Posit Workbench? Build Data Products in R & Python using Jupyter, VSCode, and RStudio.
YouTube
Posit Connect | Host all of the data products you create
YouTube
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Product Details
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- FAQs
What is Posit?
Posit, formerly RStudio, provides a modular data science platform that combines open-source and commercial products.
their open source offerings, such as the RStudio IDE, Shiny Server, rmarkdown and the many packages in the tidyverse, boast users among data scientists around the world to enhance the production and consumption of knowledge by everyone, regardless of economic means.
Their commercial software products, including Posit Workbench, Posit Connect, and Posit Package Manager, are available as a bundle in Posit Team. These products aim to give organizations the confidence to adopt R, Python and other open-source data science software at scale. This enables data science teams using R and Python to deliver interactive reports and applications to decision-makers, leverage large amounts of data, integrate with existing enterprise systems, platforms, and processes, and be compliant with security practices and standards.
The platform is complemented by online services, including Posit Cloud and shinyapps.io, to make it easier to do, teach and learn data science, and share data science insights with others, over the web.
Posit’s open-source software and commercial software form what the vendor describes as a virtuous cycle: The adoption of open-source data science software at scale in organizations creates demand for Posit’s commercial software; and the revenue from commercial software, in turn, enables deeper investment in the open-source software that benefits everyone.
Posit Features
Platform Connectivity Features
- Supported: Connect to Multiple Data Sources
- Supported: Extend Existing Data Sources
- Supported: Automatic Data Format Detection
Data Exploration Features
- Supported: Visualization
- Supported: Interactive Data Analysis
Data Preparation Features
- Supported: Interactive Data Cleaning and Enrichment
- Supported: Data Transformations
Platform Data Modeling Features
- Supported: Multiple Model Development Languages and Tools
- Supported: Single platform for multiple model development
- Supported: Self-Service Model Delivery
Model Deployment Features
- Supported: Flexible Model Publishing Options
- Supported: Security, Governance, and Cost Controls
Additional Features
- Supported: Share Data Science insights in the form of Shiny applications, Quarto content, R Markdown reports, Plumber APIs, dashboards, Jupyter Notebooks, and interactive Python content.
Posit Screenshots
Posit Videos
Open Source Software for Data Science - CEO J.J. Allaire provides an overview of Posit's mission, and why Posit has become a Public Benefits Corporation.
Posit Integrations
- Amazon SageMaker
- Kubernetes
- Apache Spark
- Jupyter Notebook
- Streamlit
- Tableau Desktop
- Azure Machine Learning
- Databricks Lakehouse Platform
- Microsoft Visual Studio Code
- Bokeh
- Slurm
- Dash applications
- SAML Marketplaces
Posit Competitors
Posit Technical Details
| Deployment Types | On-premise, Software as a Service (SaaS), Cloud, or Web-Based |
|---|---|
| Operating Systems | Windows, Linux, Mac |
| Mobile Application | No |
Frequently Asked Questions
Posit, formerly RStudio, is a modular data science platform, combining open source and commercial products.
Reviewers rate Security, Governance, and Cost Controls highest, with a score of 9.
The most common users of Posit are from Enterprises (1,001+ employees).
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Community Insights
TrustRadius Insights are summaries of user sentiment data from TrustRadius reviews and, when necessary, 3rd-party data sources. Have feedback on this content? Let us know!
- Pros
- Cons
- Recommendations
Intuitive User Interface: Users have found RStudio to have an intuitive user interface that allows them to quickly test and debug code. This has been mentioned by numerous reviewers, highlighting the ease of use and convenience it offers in coding tasks.
Seamless Integration with Git: The seamless integration of RStudio with Git has been praised by users, making it easy for them to manage version control. Several reviewers have specifically mentioned this as a major advantage of using RStudio for their coding projects.
Powerful Statistical Analysis Tool: Many users appreciate RStudio's capabilities as a powerful tool for statistical analysis and data exploration. They mention its ability to import data from multiple sources, apply machine learning models easily, and export data into various channels.
Confusing and Outdated User Interface: Several users have expressed dissatisfaction with the user interface of RStudio, finding it confusing, unattractive, and outdated compared to other tools. They feel that the interface is too technical for business people.
Frequent Crashes with Large Datasets: Some users have mentioned that RStudio frequently crashes when loading large amounts of data. This can be frustrating and disrupt their workflow.
Lack of Integration with Other Applications: Users have pointed out that RStudio is not as integrated with other applications as Python. This limitation makes it less convenient for users who rely on seamless integration between different software tools.
Users commonly recommend RStudio for beginners in R programming and data analytics. They believe that RStudio is a good tool for learning machine learning and recommend using it for data work, programming R code for machine learning, implementing R software, data analysis, and data science. Users consider RStudio to be a great resource for analyzing data and necessary for anyone who wants to get into R programming. While considering other suites and languages like Python, they still recommend taking a look at RStudio for data analysis. Additionally, users find RStudio to be useful for doing statistics and creating professional plots and figures. They suggest familiarizing oneself with common libraries in the field and doing online tutorials before starting to use RStudio. Users warn about the steep learning curve but believe it is worth investing the time to learn it. Moreover, they recommend using RStudio for big data and epidemiological research.
Attribute Ratings
Reviews
(26-50 of 122)Companies can't remove reviews or game the system. Here's why
January 13, 2022
RStudio Is the Best R GUI for any price, let alone free!
I currently use RStudio to create and develop 3D maps for ground-mounted solar arrays to better account for the terrain where they will be placed. It is also used for statistical analysis within the company to determine where the best placement for the solar arrays will be within the topography.
- Troubleshooting of Code.
- Color Coding of different elements of code.
- Adding new packages.
- Infinitely customizable.
- Better Resource Analysis.
- Better progress bars.
- Debugging could use a little improvement.
December 23, 2021
RStudio is Very Useful but Needs Improvements
I use RStudio to manipulate, munge, analyze data for ad hoc projects, and create visualizations. [My main use for the platform] is for projects that are too big or slow for Excel.
- good visual design environment
- Allows you to quickly see your data set in tabular form
- Manages package list/download well
- When rendering a plot, there are several issues bringing it more smoothly to copy/paste it to a slide deck, etc. It is very frustrating that the aspect ratio, etc. visual quality is not consistent from when you originally render to when copy/paste or downloading as a file to later be put in a slide.
- My resolution changes between laptop mode and desktop mode (plugging into external monitors). In desktop mode I literally have to shut RStudio down and restart/reload/rerun to continue my project. HOW DO I fix this? Is there a way. I've seen a toggle that says it can bounce back and forth depending on device type but it doesn't seem to work!
- When a program hangs, there is a red stop sign ( I think) in console corner to end the process. This requires, however that I need to complete restart RStudio and restart/reload/rerun etc. Can't it just start but keep all packages, datasets, variables in memory?
December 05, 2021
An almost one-stop shop for your analytics needs
RStudio is the only way in which I interact with R. We're primarily a SQL-driven team but sometimes you need a tool that's a little more powerful; enter R. When I need this added firepower, RStudio is where I always go. There aren't any second thoughts. I'm primarily a fan of the UI shortcuts that make interacting with my local directory and managing my packages a breeze.
- Keyboard shortcuts
- Integrating multiple programming languages
- Providing creators with the resources to develop gold-standard packages
- I have never been able to successfully replace my SQL editor with RStudio since the SQL drivers are so hard to set up. I would eventually love to be able to use RStudio as a one-stop-shop.
September 11, 2021
RStudio for R!
RStudio is the go to tool in our team for data analytics workflow, from pulling and wrangling data, modeling and visualization.
Through the products - e.g., web app, API, reports - that were built using the publishing platform (RStudio Connect), every users in the company were able to access analytics applications designed specifically for individual use cases.
Through the products - e.g., web app, API, reports - that were built using the publishing platform (RStudio Connect), every users in the company were able to access analytics applications designed specifically for individual use cases.
- Integration with databases.
- User community.
- Integration with other software/languages.
- Lacks stability.
- Memory management.
September 10, 2021
RStudio: Difficult Learning Curve with Matching Pay Off
RStudio is being implemented by our analytics department to help solve complex client problems by utilizing the data and statistical packages available through RStudio. The ability to perform far more accurate multi-linear regression models and time-series forecasts has helped our clients not only see where they are going in terms of sales but also what affects their sales.
- Data Organization
- Multi-Linear Regression
- Data Visualization
- Time-Series Forecasting
- As a scripting language, it is not a pick up and go platform. You need to spend the time to learning the program.
- Platform versions and Package versions often do not align.
- Would love to see standard templates that would generate a basic code for statistical models. This could save time and help newer users learn how to operate the program.
September 10, 2021
The R-Studio suite is a well thought out solution to development, control and publishing r apps and services.
RStudio is a great way to allow teams to develop r-shiny apps without needing to go and install lots of software on each developer's individual machine. It helps people to get ideas together much faster that you can traditionally. And by pairing it with other products in the suite you can then deploy them to non-devs too for quick feedback.
- Centralised admin
- Ability to manage allocations of CPU / RAM per user
- SSO
- Set up can be complex
- Automated updates via the admin screens
September 06, 2021
RStudio for quick prediction prototyping
Very few of us are getting into predictions using Machine Learning and Data Science. We use Rstudio to program our algorithms. There are only a handful of people in the whole organization who use Rstudio right now. We use it in pockets, and do the proof of concepts with Machine Learning using R.
- We use it for a quick visual representation of data
- We do exploratory data analysis to understand data
- We do predictions using RStudio
- When we have to run 100 iterations using more than 10000 records, RStudio gets stuck or takes a very very long time to respond
- Generating a pdf report from an RMD file is very difficult from RStudio.
- Generating a pdf report in RStudio cloud is straightforward and inbuilt.
September 05, 2021
RStudio - Dire wolf of "Game of Data Science"
Most of the DNA teams within our organization are using RStudio right from data pulls to visualization & reporting. UI/UX for shiny applications has been phenomenal and has been utilized in broader initiatives that enabled huge dollar savings. 'RMarkdown' has eased report generation to a great extent and 'odbc' drivers have made connecting to databases an easy task.
- Abundant development on statistical and data science libraries.
- Interaction with other programming languages and BI tools.
- Customized application building and reporting framework through shiny and markdown.
- Simple IDE with competent and robust functionalities.
- Strong and active community.
- Highly approachable core members and teams @Rstudio.
- Integration with Google Cloud Platform.
- Flexibility of choosing a remote R-interpreter (as is present in IntelliJ/PyCharm).
- Memory issues and slowdowns when it comes to working with large datasets.
- Orchestration of production workflows with Airflow.
- Production pipelines for RStudio Connect content.
September 04, 2021
RStudio is the Swiss Army knife of R Solutions
RStudio provides a number of products and services, from their best-in-class IDE for R to their collaboration and publication platform, RStudio Connect. Our Data Scientists leverage RStudio Server on a daily basis to do analysis, develop dashboards and Shiny applications. They deploy these to either our Shiny Server Pro environment or, more commonly, our RStudio Connect environment. Others at the company use the RStudio IDE to do analysis on their local machines. R, as a statistical programming language, is mostly commonly used by our data scientists who support the whole organization, often in a paired environment. By using RStudio Server we can ensure consistent environments for deployment of assets and ease of managing security. There are pockets of other scientists, marketing and logistics analysts who use R to amplify their work and they use the desktop IDE because they have no need for collaboration.
- Excellent integration of both R and Python IDEs in one.
- Simple publishing of dashboards and applications from RStudio IDE to RStudio Connect.
- Integration of package management with projects to support collaboration.
- Excellent contributors to the R Open Source community, really invested in its health.
- Support integration with Enterprise AD environments for security.
- Python integration is newer and still can be rough, especially with when using virtual environments.
- RStudio Connect pricing feels very department focused, not quite an enterprise perspective.
- Some of the RStudio packages don't follow conventional development guidelines (API breaking changes with minor version numbers) which can make supporting larger projects over longer timeframes difficult.
September 04, 2021
RStudio helps data scientists get things done faster
RStudio is being used in the Underwriting and Analytics Department. We publish our analytics artifacts through RStudio Connect, then users from other department can consume with ease.
We help our colleagues to better understand the financial health of the company through profit and loss evaluation, risk underwriting and portfolio review. RStudio helps us bridge the gap between Data and Solution, we tell story through data visualization and reproducible analytical documents that are easy to grasp by our colleagues.
We help our colleagues to better understand the financial health of the company through profit and loss evaluation, risk underwriting and portfolio review. RStudio helps us bridge the gap between Data and Solution, we tell story through data visualization and reproducible analytical documents that are easy to grasp by our colleagues.
- Great selection of libraries to do statistics, machine learning, data visualization, interactive dashboards
- RStudio Connect makes sharing your work with your colleague a breeze using one-click publishing.
- The ability to connect R with other languages like Julia and Python all within the same working session helps generate more creative ways to solve problems. We can use Julia in R to speed up intensive calculation, or we can use Python Tensorflow or Pytorch in R to do deep learning.
- R has a great community on social media and stackoverflow so it's very easy to learn from the other users.
- The learning curve may be a little steep for new R users
- There are multiple ways to solve a problem. For example, there are mlr3 and tidymodels to build predictive models, and there are tidyverse and data.table to perform data cleaning. It could be confusing and overwhelming for new users to decide which libraries to learn and use.
September 03, 2021
RStudio is the only IDE you need for R
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.
We use RStudio for development within bioinformatics group. The product (R Shiny) from our group is used across the whole organization, it is used for data integration, both clinical and pre-clinical biomarker data and other types of data integration.
- Best IDE for R programming.
- Good ecosystem for R Markdown and R Shiny.
- RStudio Connect is very useful for publishing and user authentication.
- It could have its own consulting team to support company to build R related products instead of partnering.
- It could also offer tailored paid training for small and large companies.
September 02, 2021
Well Suited for Data Visualization and Modeling
We use RStudio as an GUI interface for R, which we use to visualize and model data. For modeling data, we use lots of machine learning techniques like Regression, and R provides an excellent package to implement various flavors of regression like lasso and ridge regression. For data visualization we also use Shiny apps.
- Debugging
- Front-end interface to R
- Provide shortcuts to some R commands
- RStudio connect experience was not very smooth
- Web service configuration for the RStudio server is not very intuitive
- Some Visual DataGrid GUI would be beneficial
September 01, 2021
RStudio is amazing, the future of Data Science
Score 10 out of 10
Vetted Review
Verified User
I use RStudio for research & teaching purposes (I'm a professor in a business school). I know 5-6 of my colleagues also use it. All of my courses are entirely focused on coding and I use RStudio all the time in class. Additionally, all of my research revolves around uses of R code, thus I spend 5-6h/day working with RStudio.
- Amazing user interface
- Great package development
- Incredible simple to use
- Joyful team & community
- NLP, a package (wrapper) for major models (ex: GPT3), just as for Keras-Tensorflow
September 01, 2021
RStudio provides stable and trusted open source tools in a market frequently flooded by trendy and soon-to-be abandoned software
We use RStudio Connect as a publishing platform for R and Python documents, apps, and APIs. It provides us with a professional, clean looking interface to share our work with internal clients and stakeholders. Our usage began within a relatively small team, but the popularity of RStudio Connect and its features saw that usage grow to a broader group of users that spans multiple departments and business units.
- Excellent Documentation
- Well-designed Features
- RStudio Connect could really benefit from containerized environments to enable isolated, reproducible content.
- RStudio Connect's pricing model is a little frustrating at times. Infrequent consumers of content cost the same as heavy users who publish content regularly. This limits our ability to share the work of our data scientists at a reasonable cost. We would much rather pay more for each "publisher" seat and have much cheaper or free "viewer" seats. This would also likely lead to a greater investment in RStudio Connect on our part, as we would be able to expose the platform to more team members and key funding decision makers.
August 31, 2021
RStudio--Standing on the shoulders of giants
We model economic indicators for cities in Mexico. Traffic congestion and other demographics.
- Coordinate data wrangling with visualizations
- Interactions with other software
- Project management
- Function name autofill
- Speed
- More and clearer detail on dashboard bugs
Score 10 out of 10
Vetted Review
Verified User
All courses in the statistics degree, the data science certificate, and quantitative courses in other sciences, such as biology, ecology, and economics that use the programming language R do so using the RStudio IDE. This potentially reaches 1,000 students annually. We use R/RStudio to teach students how to do modern statistics and data analysis.
- Seamless integration with professional quality reporting packages (R Markdown, xaringan, Sweave), other coding languages (Markdown, SQL, Python, C++), version control, and the terminal
- Environment management (using Rprojects)
- Pop-up tool tips for function arguments
- Tab completion!
- Change the default global options to not save Rdata sets between instances; this is very unfriendly for beginner users
- Better GUI support for exporting images out of the viewer pane
July 14, 2021
RStudio for data maturity
It is used to deliver data focused clinical research covering a wide range of clinical areas. It is also being used to develop automated documents and analytics using r markdown documents. This is covering areas of interest within both the university and also our clinical collaborators including hospital, primary care and other healthcare stakeholders.
- User friendly.
- Good customer support.
- Integration of more than R.
- Good documentation.
- Automatically advising of updates.
- The pricing model for RStudio Connect makes it an unfeasible prospect for large public sector organisations.
- The sales yes can sometimes feel quite pushy.
July 14, 2021
RStudio Review
We use RStudio Team for data science related tasks with research and development. We have a smaller user base, but our experience with the tool is fantastic, and we are actively recruiting new internal users. The primary challenge it addresses is empowering researcher to use apply their subject matter expertise to data analysis in a transparent, reproducible way.
- RStudio is a great partner that listens to our needs with a creative mind focused on improving our work, not just on increasing sales. They were extremely accommodating of the stresses COVID-19 placed on our work and our budgets.
- RStudio provides fantastic access to technical experts to address your needs. This close working relationship was key to implementing a capability researchers are excited to use.
- Language interoperability is a focus of theirs but I look forward to additional improvements. Specifically, I'd like to see more tooling to allow python users to use R code.
- A community plugin ecosystem (like VS Code) could be a compelling feature. I'd love to see what the community might come up with.
As an analytics organization embedded within the marketing team, we support roughly 90-100 marketing professionals. While we have an extensive BI and analytics stack, RStudio Connect really helps us with serving insights to these stakeholders at the right moment. We utilize parameterized reporting to cut down time it takes to report, schedule processes that previously relied on cumbersome crontab processes, and host bespoke, highly customized dashboards that allow non-technical users to interact with data better than they would in a BI environment.
- The CSMs are fantastic - they solve our problems with the platform rather than being salespeople in disguise.
- Ease of use - The entire environment is very easy to understand and use, both for developers and non-technical end users.
- Scheduling - We replaced our entire crontab based scheduling system, saving us time through efficiency.
- Git-backed deployment - if you're working with version control already, RStudio Connect works flawlessly with it.
- Python support is still new, though we haven't run into large issues.
- To get Python support, we had to sign up for the mid-pricing tier that comes with 100 users, while we really only needed 10-15 developer seats, so I think some more flexibility in the pricing model would be nice. That said, overall the product seems very(!) reasonably priced.
July 06, 2021
Makes life easier for analytics developers
We employ dozens of R users and install RStudio on our machines so that everyone has a familiar integrated development environment (IDE). We also purchase the commercial product RStudio Connect for our analytics teams to develop and share interactive tools with non-technical users. It allows our more experienced R users to create more advanced tools than on our other intelligence platforms.
- Being a complete IDE
- Integration with RStudio Connect
- Easy to install and administrate
- Could have better integration with free hosting solutions
June 04, 2021
RStudio Cloud recommendation for teaching
Score 10 out of 10
Vetted Review
Verified User
Even though we go back to in-person teaching next academic year, we have taken the decision to continue using RStudio Cloud because of its other benefits, like avoiding the wasted first day of debugging student installations and letting me ID students that are putting in low numbers of hours outside of class, which I can use to intervene early with students who might be having trouble. Also, it's nicer for everybody that I and the demonstrators can just sign into a student's RStudio instance to debug code instead of having to do the shoulder-to-shoulder dance when in class. Finally, RSC gives every student a powerful instance of R, including students who only have a Chromebook, which lets me assign large datasets and RAM+CPU-intensive exercises.
May 24, 2021
Best all-in-one IDE for R
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.
March 17, 2021
RStudio Review
RStudio is being used by our finance department. We have close 20 developers. R is the main language used for development. We use RStudio Connect for running the reports. Our RStudio enterprise edition gives us the best value for our investment. We are planning to upgrade to the latest version soon.
- Provides a great interface for our R language
- Easy to implement multiple packages
- Connect feature for viewing the reports.
- SAML integration has been little pain
- Provide support for latest R versions
- Phone support
March 16, 2021
Using RStudio to solve the pandemic
I have been using RStudio for almost a decade now for the analytic use of systems biology datasets. As a team leader, I made RStudio professional available for multiple data analysts and also used multiple programs offered by RStudio such as package manager and Shiny app. It has definitely improved over the years with use cases and has been widely used by scientists for top-notch research. We now have been using Rstudio for a COVID project and it has been a great experience especially with the functionality of python and other programming languages built into reticulate system. So far so good and I am very satisfied.
- Ease of use for Python users to be all in one platform
- Package manager for version control
- Shiny app functionality
- Interaction with AWS system
- Easier access login for multiple institution users
- Secure cognito access for users