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 analysis, particularly in industries like pharmaceutical research. We’ll also address the challenges of transitioning to functional programming in ...

The introduction of innovative tools like Shiny and Quarto has empowered researchers and data scientists to transform complex data into interactive and insightful reports. This progress is not just an improvement in data visualization but a significant leap towards a new paradigm in clinical research. In this article, we’ll ...

As the reliance on data intensifies, the need for efficient and effective data analysis methods has never been greater. This article delves into the world of functional programming in R, a paradigm that offers a refreshing and powerful way to handle data analysis tasks. We will compare functional programming techniques ...

Functional Programming‘s relevance in the R programming language, a language primarily known for its prowess in data analysis and statistical computing, is particularly noteworthy. By leveraging functional programming, organizations can improve operational efficiency and gain a competitive edge.  R’s ecosystem is enriched by functional programming paradigms, which enable ...

In the ever-evolving landscape of software development, there exists a paradigm that has been gaining momentum and reshaping the way we approach coding challenges: functional programming. In this article, we delve deep into the world of functional programming, exploring its advantages, core principles, origin, and reasons behind its growing traction. ...

Visualizing genomics data is not as straightforward as you would think. The whole industry is extremely complex and suffers from a major problem – specialization creep. There are so many niches in genomics, meaning one library or service can’t cover the entire spectrum of genomics data visualization needs. That is, ...

RStudio recently announced the renaming of RStudio Server Pro to RStudio Workbench. Along with the relabel, some updates and new features were added. In this blog, we will discuss our 5 favorite tips for more efficient use of RStudio Workbench (also applicable for RStudio Desktop). R RStudio 1) Shortcuts 2) Multi-Column View 3) Finding ...

Why Data Validation Data validation is a crucial step in any data science project. It ensures clean and well-formatted data that is ready for input pipelines to ML models and dashboards. Cleaned data also minimizes errors further down the line. Often, functions and model training pipelines throw errors when presented ...

5 Great Shiny Dashboards – Appsilon’s Top Picks This article will cover a few of the best Shiny Dashboards created by the Appsilon team. R/Shiny is an R package that makes it easy to build interactive dashboards that look great in R. Additionally, we can build Machine Learning or AI ...