It's been just over ten years now that I started my bachelor's degree in physics. I remember quite vividly my first semester at the university: timidly meeting new people, keeping up with the exercises, working on complex assignments. Those early days were a whirlwind of learning and adapting. But not just to the academic environment, also to the tools we needed for our studies ...

Ever seen these cool-looking diagrams that show flows of energy, resources, or costs with thick, colorful arrows on the internet? These diagrams are known as Sankey diagrams. They originated in the late 19th century, named after Irish engineer Captain Matthew Henry Phineas Riall Sankey, who first used them in 1898 to illustrate the energy efficiency of steam engines ...

Haikus are now known worldwide. While their structure is becoming widely understood, and probably no longer needs an introduction, I wanted to highlight a few specific features this short Japanese poem format has. Haikus are notably concise, composed of exactly 17 syllables arranged in a 5-7-5 pattern. This ternary rhythm is essential to their form. In terms of language and themes, haikus also rely on two key elements ...

Data should always be carefully and thoughtfully presented. Although this rule seems quite general, it is backed by a very logical rationale. Plots should serve as a direct and clear way to communicate a message. And therefore it is important to select the most effective settings to convey this message. There are right and wrong choices to make when it comes to data representation. And pastamarkers is a delightfully good one ...

If there is one thing that fits in with the Halloween theme, apart from ghosts and vampires, it's neutrinos. Well, one could argue that dark matter would actually fit better, but I needed an excuse to talk about neutrinos and their very interesting history, so neutrinos it is. Positioned among the leptons in the Standard Model (SM), neutrinos are unique. They have an extremely small mass compared to other particles ...

About three months ago, I began coding my own website. Like any beginner, I started reading documentations and following tutorials to get the basics down. Soon, I was learning a whole new set of concepts and languages essential to web development. And I quickly realized that web development has its own Three Musketeers*. First, there’s HTML (Hypertext Markup Language), the foundation, responsible for content and structure ...

My personal data analysis journey started with Pandas dataframes. Being easy to manipulate in Python code, it enables further data analysis while also allowing you to make adjustments should the data change over time. So when I heard about SQL (Structured Query Language), I thought it was yet another similar way of analyzing dataframes. Turns out I was wrong, and it is slightly more complex than that ...

matplotlib is a library that I've been extensively using throughout my PhD. Coming from a place where TCanvas, TLegend and TH1F were the norm, I can tell you that this library is particularly straightforward. Don't get me wrong: it is by no means perfect, but it does contain some features that can be used to make plots more enjoyable to read (though the lack of default LaTeX font will always be a disappointment) ...

Have I ever said that I'm a plant lover? Not the kind of plant lover that would go in a plant shop and buy everything, but more the kind that would let the plants grow starting from seeds. It can be reduced to an input/process/output system. You have seeds. You put them in soil, water them regularly and let them enjoy the warmth of the sun. And a couple of days later or a few months after, you have a plant ...

ROOT is an open-source framework designed for data analysis, particularly in high-energy physics, but it's also used in other fields. While it's a very powerful tool, ROOT can be challenging to work with due to its complexity. A relatively new feature in ROOT has been introduced that combines the efficiency and power of ROOT with the ease and simplicity of Pandas dataframes: RDataFrame...

Recently, I made a cool discovery about Git that changed the way I manage my projects: "push-to-deploy." Before, I had only used Git as a tool to link my projects to remote repositories on platforms like GitHub or GitLab. It was a straightforward process where I would initialize a Git repository on my local machine, connect it to a GitHub repository, and push my code for version control and collaboration ...