Introduction For beginners venturing into the world of Linux, understanding shell expansion is a crucial step towards mastering the command line. Shell expansion is a powerful feature that allows users to generate complex commands and manipulat...

In this post I describe a useful programming pattern that I implemented, and hopefully provide a gentle introduction to the idea of monads. The motivation for all of this was that I had a {dplyr} pipeline as part of a {shiny} app that queries a database and I wanted to “...

Hot on the heels of Shiny in Production 2022 & 2023, we were excited to dive back into all things Shiny for a third consecutive year. In this post we recap the highlights from the two days of talks and workshops. Workshops As with previous it...

Nearly ten years ago, Chrisophe Dutang and I launched a curated collection of datasets featured in Computational Actuarial Science with R, bundled in the CASdatasets R package. Now, this package offers an extensive range of actuarial datasets, serving as a vital resource for students, educators, and researchers alike. We’re ...

Have you ever looked at a headline or a graph and thought, “Well, the numbers don’t lie, right?” It’s tempting to trust the stats we see around us — whether it’s a political poll, a study about coffee’s health benefits, or a chart showing the rise of ...

Looping through column names in R is a fundamental skill for data manipulation and analysis, especially for beginners in R programming. This guide will walk you through various methods to loop through column names in R, providing examples and ex...

One element of the NSF POSE grant for data.table is to create benchmarks which can inform users about when data.table could be more performant than similar software. Two examples of similar software are duckdb and polars, which each provide in-m...

Introduction For beginner C programmers, understanding how to interact with users through input is crucial. The scanf() function is a fundamental tool in C programming that allows you to read user input and store it in variables. This article w...

Note: This blog post is a re-published version from the Global Health Engineering website. For attribution, please see the citation information at the end of this post. About one year ago, I joined the Chair of Global Health Engineering (GHE) ...

Picture this: a crucial clinical trial is underway, and every data point matters. The pharma industry is increasingly turning to open-source tools like R to handle complex data analysis, drawn by their flexibility, innovation, added value and cost-effectiveness. But with these benefits come new challenges — particularly when it comes to ...

A website or application’s performance and loading speed play a crucial role in determining its user experience (UX) and success. Slow performance is the main reason why users lose interest in an application. Thus it is crucial to keep an eye on your Shiny app performance from the early ...

#225–226PuzzlesAuthor: ExcelBIAll files (xlsx with puzzle and R with solution) for each and every puzzle are available on my Github. Enjoy.Puzzle #225Sometimes we have nice tables with so called tidy data, where each observation mean one row. But this ...

Introduction As a beginner R programmer, you may often find yourself needing to manipulate data frames. One common task is adding prefixes to column names, which can be useful for organizing variables, improving readability, or avoiding naming ...

R and Python consoles + JupyterLite in www.techtonique.net

Puzzles no. 559–563PuzzlesAuthor: ExcelBIAll files (xlsx with puzzle and R with solution) for each and every puzzle are available on my Github. Enjoy.Puzzle #559Sometimes we need to make work on columns. It technically just like working on lists, and l...

Think of Shiny for Python custom modules as reusable components. You write the logic once, make it as tweakable as possible, and then reuse it throughout your application. As it turns out, creating custom modules in Shiny for Python is simple enough, but there are some new concepts you need ...

You can read the original post in its original format on Rtask website by ThinkR here: Beyond Functions: How to Enrich an R Package with Data As package developers, we often focus on custom functions, their documentation, and unit testing. To provide a more complete user experience, it can be ...

Adding a suffix to column names in R is a common task that can help in organizing and managing data frames, especially when dealing with multiple datasets. This guide will walk you through the process using base R functions, making it accessible...