My very personal RStudio R&D journey
April 23, 2022
My very personal RStudio R&D journey
Professional in Research & DevelopmentHospital & Health Care Company, 10,001+ employees
Score 10 out of 10
Overall Satisfaction with RStudio
I have used the R language since around 2010 and before (along with S-Plus). RStudio as soon as it was available, also around 2010. Example use cases: 1. bionanoengineering - descriptive statistics (describing biological motility or nano surfaces), in parallel with image analysis in ImageJ and MATLAB; 2. bioinformatics - producing descriptive statistics for the motility of Neurospora crassa (filamentous fungus) to prove that how one use statistics matters and how it impacts business decisions; 3. pharma - benefit-risk analysis and data visualizations along with Spotfire 4. healthcare - clinical programming along with Stata and Python (one suggestion: it would be nice to have R interface in Stata and improved R interface in Spotfire); 5 - in product development for creating data monitoring & evaluation apps in RShiny. RStudio has been with me since the very beginning of my professional career. I could easily write up a Ph.D. on the use cases of R in life sciences, pharma, healthcare, and computer science. I would highly recommend RStudio for those who need to deliver fast tailored, customized applications, attractive visualizations or need to use Bayesian statistics, for example, to validate pharmacovigilance scores.
- RShiny applications that are intuitive and help to communicate in the multidisciplinary teams
- d3.js based visualizations
- Bayesian statistics
- calculating confidence intervals
- merging tables by using SQL commands
- using regular expressions
- some of the machine learning implementations are best in R
- way more hassle-free than SAS, in my opinion
- open-source - RStudio does not discriminate against people & businesses based on their financial status, many small businesses cannot afford SAS, in many developing countries young people are willing to learn to program, and SAS platforms or other paid software is absolutely out of the question, those people/young programmers will be not able to afford even free cloud SAS due to the internet infrastructure...some of the best ideas come from those who face serious challenges in life and can speak several languages as their minds are often more creative ("necessity is the mother of invention"). I feel that platforms like RStudio or Jupyter connect me with the World, with other creative minds, and contribute to making the World a fairer, better place.
- something like IronPython in Spotfire, but R equivalent would be great; the existing R interface is not fully functioning
- something like Pyhon interface in Stata, but R equivalent would be awesome
- in the pharma World deadlines are tight, pressure is very high - Stata lets manipulate data super fast compared to R
- brining R and Python community together
- in my opinion, Natural Language Processing pipelines are better than in R
- catching up with some of the machine learning implementations - visualization aids in this field are better in Python, at least that is my intuition
- I landed a good job every single time I showed my RStudio implementations during my interviews
- every single time I developed RShiny app, it has been a success business-wise
- R helps to validate some of the other commercial systems, thus helping to make more informed business decisions, for example when choosing a commercial supplier or making an investment decision or planning R&D strategies...also simply because R helps to bring stakeholders together regarding communication of the scientific results
- good for advertising: a funny story - at some point in my career I was prevented to show my app to more customers as they started asking whether this is a product and whether they can buy it together with another product (perhaps R could create some type of fast-track legal pipeline for commercialization of the R-based apps)
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well suited: creating and delivering apps for multi-disciplinary teams, for example, http://drugis.org/index or https://shiny.rstudio.com/gallery/covid19-tracker.html less appropriate: Kaggle competitions, multi-community collaborations, Google collab...scenarios when the whole communities decide to work on a specific problem in Python and R is left behind, e.g. in 2015 my colleague delivered better results with Bayesian statistics simply cause he decided to go for Python to visualize joint distributions (priors and posteriors) ...even if I had way more knowledge on the algorithmic side, I was simply slower because I chose R; what I have learned over the years is that when it comes to the stakeholders, a good visualization (==communicating the results and effectively advertising) is everything as without it there is no funding and without funding no science, no R&D
Posit Feature Ratings
Connect to Multiple Data Sources
Extend Existing Data Sources
Automatic Data Format Detection
Interactive Data Analysis
Interactive Data Cleaning and Enrichment
Multiple Model Development Languages and Tools
Single platform for multiple model development
Self-Service Model Delivery
Flexible Model Publishing Options
Security, Governance, and Cost Controls