Object Oriented Programming in R Part 2: S3 Simplified
In the previous article we made our first steps in Object Oriented Programming in R and learned that there are multiple ways of doing it. In this article, we will...continue reading.
Category: R Programming
How to Make Your Shiny App Beautiful
Shiny apps are very often used for quick prototyping and proof of concept. However, if you want to use a Shiny app in production and make it attractive to the...continue reading.
User Tracking in Shiny Apps: Leveraging {shiny.telemetry} for Comprehensive User Distinction
Delving into the realm of Shiny app development, the path to success often proves to be a complex and evolving landscape. Whether you’re a seasoned developer, a data enthusiast, or...continue reading.
6 Benefits of R {targets} for Data Science Workflows
Efficiency is paramount in navigating the intricacies of data science workflows, and multiple challenges can occur. For example: Working with large datasets Data exist in a variety of formats Different...continue reading.
R doParallel: A Brain-Friendly Introduction to Parallelism in R
Implementing parallel execution in your code can be both a blessing and a curse. On the one hand, you’re leveraging more power your CPU has to offer and increasing execution...continue reading.
Object-Oriented Programming in R (Part 1): An Introduction
Object-oriented programming (OOP) is a popular and widely embraced programming paradigm in software development. The concept of object-oriented programming in R has been previously featured in one of our blog...continue reading.
Goodbye Complicated Dropdowns: Welcome to the New Era of Human Readable Filters
Have you ever tried to book a flight and found yourself overwhelmed by the endless dropdown menus? You’re not alone. We’ve all been there, clicking through multiple options, often unsure...continue reading.
Learnings from the First R-Based Submission to FDA by Novo Nordisk
Novo Nordisk stands as a trailblazer in R-based submissions to the FDA, having recently completed the inaugural submission in this statistical programming language to regulatory authorities. This milestone was achieved...continue reading.
R Docker: How to Run Your R Scripts in a Docker Container
So, you’ve written this amazing R script, but your coworkers can’t run it? It works on your machine, so they have to be doing something wrong, right? Wrong. It’s all...continue reading.
Renv with Docker: How to Dockerize a Shiny Application with an Reproducible Environment
You might have seen our previous articles on Dockerizing R scripts and R Shiny applications and were left wondering: Are all of my dependency versions really fixed right now? It’s...continue reading.
Introducing Autocomplete Search to shiny.fluent’s Dropdown Component
The introduction of shiny.react has been a significant milestone in R Shiny’s evolution, acting as a bridge to React.js and enabling the incorporation of React components within Shiny applications. shiny.fluent,...continue reading.
Unlocking Efficiency in Computational Biology: How Nextflow Streamlines Workflow Management
Efficiently handling complex workflows is crucial in computational biology, going beyond necessity to become a competitive differentiator. As professionals in this dynamic field, you’re likely familiar with the challenges: integrating...continue reading.
Unlocking the Power of Functional Programming in R (Part 4): Enhancing Reproducibility and Operational Value in Pharma
Welcome to the final part of our “Unlocking the Power of Functional Programming in R” series. In this article, we’ll explore how functional programming enhances reproducibility and testing in data...continue reading.
Posit x Databricks: A Game-Changing Synergy for Data Teams
On Thursday, December 5th, 2023, Posit and Databricks held a joint event, revealing several key developments in their ongoing collaboration. These updates, building on announcements from July 2023, showcase tangible...continue reading.
R Data Processing Frameworks: How To Speed Up Your Data Processing Pipelines up to 20 Times
Picture this – the data science team you manage primarily uses R and heavily relies on dplyr for implementing data processing pipelines. All is good, but then out of the...continue reading.
Beyond SAS: How R is Revolutionizing Pharma and Life Sciences
Statistical analysis and data handling play a pivotal role in the life sciences and pharmaceutical industries. The need for accurate and robust data analysis cannot be overstated, as it underpins...continue reading.
Maximizing Efficiency: A Guide to Benchmarking Memory Usage in Shiny Apps
R/Shiny allows you to prototype a working web application quickly and easily. However, with increasing amounts of data, your app may become slow and, in extreme cases, crash due to...continue reading.
Shiny Gatherings #8: Teal’s Role in Pharma Innovation with Paweł Rucki
In the fast-paced world of pharmaceutical software development, open-source tools play a pivotal role. Among these, Teal stands out as a groundbreaking framework, developed under the aegis of Roche, for...continue reading.
R Shiny Docker: How To Run Shiny Apps in a Docker Container
It doesn’t matter if you’ve created the world’s best R Shiny application if you can’t share it with others. Reproducibility and portability are two major key points in software development,...continue reading.
{rhino} vs {golem} vs {leprechaun}: Which R/Shiny Library is Right for You?
Shiny dashboards created using R have become a staple for data professionals due to their flexibility, power, ease of use, and community support when carrying out data visualization and analytics....continue reading.
