Daniel Roelfs

Since I finished my PhD and started working in industry I have been introduced to a lot of new tools and ways of working that weren’t at all common in academia at least not in any research group I was aware of .

Click on the links below to jump straight to the file format of your interest.

A little while ago I scrolled past a post on BlueSky commenting on a discussion where political scientist Oscar Pocasangre pulled up some figures he created on the topic of discussion a while ago.

Reveal.js is awesome and in this post I’ll explain why.

Throughout my career so far I’ve been lucky to work with many different types of data.

I’ve wandered around the data viz community for a while now, and it tends to be same set of news agencies, organisations, and individuals that are shared and discussed repeatedly for their ingenuity, creativity, or just excellent execution.

Energy production Weather and climate data Length of day Energy storage and prices One of the main reasons I maintain this blog is because I like delving into methods and topics that I don’t get the chance to during my day job.

I’m very about what I share on the internet.

One of the most well-known issues with LLMs is the phenomenon of “hallucinations”, where it makes up facts and presents them confidently as true.

Notebooks are a cornerstone of exploratory data analysis in data science (and sometimes also in production for some godforgiven reason?).

Introduction How Science Works The Article Processing Fee Profit Margins Lobbying What Can Universities Do?

So I’ve recently become the proud owner of a Raspberry Pi 5, a microcomputer that fits in the palm of your hand.

This post is about the 2023 Dutch parliamentary elections, not the 2024 European parliament elections or the 2025 Dutch parliamentary elections So it’s time again for the Netherlands to have another election for the Dutch parliament (Tweede Kamer) The pre…

Using an API (an application programming interface) is a very popular tool for data scientists to pull data from a public source.

Today I want to share a project that deals with data scientist’s favorite kind of data: date- and timedata involving time zones and daylight savings time.

Let’s imagine you’re incredibly lazy and you want to learn R, but you only want to learn one function to do statistics.

The 2022 Winter Olympics started last week.

This is just a very quick blog post outlining some of the commonalities and differences between factor analysis (FA), principal component analysis (PCA), and independent component analysis (ICA).

As of March 2023 {fhimaps} and {splmaps} are no longer supported due to budget cuts at the institution supporting them.

For this post, I decided to hide the code chunks by default to improve legibility.

Introduction If there was a statistics magazine and it were to have ads, the ad for independent component analysis (commonly referred to as the ICA) might read something like this: Do you ever find yourself with a large number of highly related variables?

Introduction Most people in my environment know R as the quintessential tool for statistical analysis and data visualization.

Introduction Whenever I show my colleagues in the genetics group my results, the first things they say are “can you show me the Manhattan plots?”

Introduction A little while ago I was watching a documentary series on Dutch television about one of the most important composers in the Netherlands: Johann Sebastian Bach.

Introduction There are many ways to create a Manhattan plot.

Introduction Plotting ERPs is one of the essential skills in EEG neuroscience.