Our Experience at posit::conf 2024
posit::conf 2024 was nothing short of amazing! While Posit has already shared their top highlights, we wanted to offer our own take on the experience—what really stood out to us,...continue reading.
Category: R Programming
Simplifying Clinical Data Dashboards with {teal} and {pharmaverseadam}
Every developer must solve two difficult problems when creating a Shiny application (in fact, any application) from the ground up: software architecture and data design. In the world of clinical...continue reading.
Unveiling Bottlenecks (Part 2): A Deep Dive into Profiling Tools
In our previous blog post, we introduced the concept of profiling for optimizing Shiny app performance. Today, we’ll take a deep dive into three powerful tools in this arsenal: reactlog,...continue reading.
Exploring the Top 5 pharmaverse Packages
The pharmaverse is a collaborative project where leading pharmaceutical companies and passionate individuals come together to create helpful tools for clinical reporting. By using R programming and the open-source community, the pharmaverse makes it easier to...continue reading.
A Day in the Life of a Delivery Manager
Ever wondered what it really takes to keep complex tech projects on track? Who even is a Delivery Manager? Meet Aga Rasińska, one of our Delivery Managers at Appsilon, who...continue reading.
Best Practices for Building Blazing-Fast Shiny Apps
Imagine your Shiny app – users are interacting seamlessly, data is processing swiftly, and visualizations update effortlessly. This dream becomes reality with a focus on performance optimization. We created a...continue reading.
R tidymodels: A tidyverse Like Ecosystem for Efficient Machine Learning in R
Have you ever thought R’s approach to machine learning is outdated? Like, data analysis and visualization tools are superb. Everything feels intuitive and every following step of your workflow integrates...continue reading.
Unveiling Bottlenecks: A Guide to Profiling R and R Shiny Code
Shiny applications are fantastic for turning data into interactive dashboards and web apps, making data exploration and visualization more engaging. But even the most visually appealing Shiny app can hit...continue reading.
Object Oriented Programming in R (Part 4): Reference Classes & R6 Classes
In our last article, we explored the S4 OOP system in R. Up until this point, we had only discussed functional OOP systems in R. Today, we are going to...continue reading.
How to Write Tests with shiny::testServer Similar to shinytest2
When developing R Shiny apps, making sure they work well and are reliable is important. Rigorous testing isn’t just about finding bugs; it’s about preventing them, saving time, and ensuring...continue reading.
All You Need to Know About Rhino 1.8 and 1.9 Updates: A Fireside Chat
Rhino, the R package development framework created by Appsilon, has recently released two updates – versions 1.8 and 1.9. In this fireside chat, Kamil Żyła (one of the core developers...continue reading.
{Shiny.Telemetry} 0.3.0: Track User Behavior In Your Shiny Applications
Understanding how users interact with your application in data analytics is crucial for continuous improvement and user satisfaction. {shiny.telemetry} is a groundbreaking tool that lets you do just that. shiny.telemetry...continue reading.
R Microbenchmark: How To Measure And Compare The Execution Of R Expressions
Are you still conducting runtime benchmarks in R through manual calls to `Sys.time()`? We don’t judge, but there’s a way more powerful and automated way to do the same –...continue reading.
The Power Of Transitioning To A ‘-Verse’ Approach In R Package Development
The word “universe” can mean many different things. In modern-day entertainment, we are conditioned to think of it as related movies or media tied together by the tried-and-true formula of...continue reading.
Rhino 1.9.0 Update On CRAN: New Formatting Tools And Cleaner {Bslib} Integration
We’re excited to announce the release of Rhino 1.9, bringing with it some powerful new features for developers. This update focuses on enhancing your coding experience with new formatting tools...continue reading.
Time Series Forecasting In R: From Moving Averages To Seasonal ARIMA
When it comes to time series forecasting in R, one thing you don’t lack is options. There are dozens of algorithms and their variations you can choose from, and doing...continue reading.
ShinyProxy 3.1.1: What’s New And How It Improves Scalability And Performance Of Your Shiny Applications
ShinyProxy has emerged as a powerful solution for deploying Shiny applications, empowering organizations to share interactive data visualizations and analyses. With its robust feature set, ShinyProxy has simplified the process...continue reading.
Introducing Positron: A New, Yet Familiar IDE For R And Python
Nowadays, most data professionals choose either R or Python when it comes to a programming language of choice. But what if you need both? Do you have to constantly switch...continue reading.
Recap: Exploring Clinical Submissions With Admiral: An R-Based ADaM Solution With Ben Straub
Have you been looking for a more efficient way to create ADaM (Analysis Data Model) datasets for your clinical trial submissions? Look no further than Admiral, an open-source R package....continue reading.
R Dygraphs: How To Visualize Time Series Data In R And R Shiny
When it comes to finding an R package capable of making interactive visualizations out of the box while also working flawlessly with R Shiny, you don’t have that many options....continue reading.
