Dataviz Universe

👋 Hi! This week I launched prtfol.com: a tool that lets data professionals build a strong portfolio in minutes, no code required. You can check what Janina made with it! Working on this made me browse hundreds of homepages. Whether you have one or are planning to build one, here are the most common pitfalls: 1️⃣ Don’t be too verbose Visitors will probably spend less than a minute on your homepage.Paragraphs longer than three sentences likely won’t be read! Keep only what’s essential —...

👋 Hi! My career started as a plant geneticist. I dove into code progressively, and I've always been surrounded by people who were better programmers than I was. There’s a concept they often talked about: low-level vs high-level programming. 🤔 You’ve probably heard about this too! Today I suggest we see what it means and how it applies to dataviz. 🧩 High-level vs Low-level A computer is just hardware that executes instructions. It performs calculations when told to. At its core, it speaks...

Before we dive in, a quick reminder: only 2 days left to join Matplotlib Journey, my course on creating stunning dataviz with Python! 👋 Hi! The goal of this newsletter is to grow your dataviz culture every Saturday with a quick 4-minute read. Today, I suggest we revisit 6 iconic dataviz projects.Just like some movies are classics everyone should know, these visualizations are must-see for anyone working with data. Let’s dive in! 1️⃣ Gapminder What: An interactive bubble chart plotting...

👋 Hi! Yesterday I posted a short piece on LinkedIn that sparked way more discussion than I expected. The topic? Alternatives to the line chart for time series data. We all know the line chart. It’s the default choice to show how something evolves over time. And for good reason: it’s clear, simple, and familiar to almost everyone.But that's not the only option! Line chart alternatives I love exploring chart types. That’s why I built Data To Viz, a decision tree that helps you pick the right...

👋 Hi! There are many tools to build charts out there. I like to think of their organization like this: As you can see, D3.js sits on the far right: it’s the most powerful tool—but also the hardest to learn! Since you’re reading this, you’re probably interested in data visualization. So I believe it’s worth understanding at least a little bit about what D3.js actually is! Homepage of d3.js D3.js = a JavaScript library D3.js is a JavaScript library. It's open source and its code lives on GitHub...

👋 Hi! I’ve been working in dataviz for quite a while now, and one thing has always amazed me: R > Python for dataviz 😳 There are far more Python users worldwide. Yet when it comes to visualization, R still leads the way. Why? Partly because ggplot2 changed everything. Its syntax is so powerful and flexible. And partly because the community keeps pushing it further. Every week you see jaw-dropping charts made with ggplot2 and a new extension.With matplotlib? Not so much. It’s not Matplotlib’s...

👋 Hi there, It’s been a while! Like many in the northern hemisphere, I took a summer break. Now I’m back with hundreds of new ideas, and full of energy for the new dataviz season. 😀 This time of year makes me think of everyone starting a new data analyst role. Or deciding to level up their skills after the holidays. Twelve years ago I was there, beginning my career as a data analyst in academia, studying the wheat genome. If I had to start again, there are so many things I would do...

👋 Hi there! It’s July 5th, and it’s officially time for me… to take a break! 🎉 I started writing this newsletter last September, and wrote 45 issues since then. It does not sound much, but that's actually a big amount of my Saturday time invested to write those little dataviz tips and tricks. ☺️If you liked them, why not sharing them with a friend? Or even better, write me a little testimonial in 10 seconds. See all past issues What a Year! Alongside my consulting work, I built a few tools...

👋 Hey there! I've been writing this newsletter solo for almost a year now, mostly sharing thoughts on dataviz. 😳 Along the way, people often ask me how I got into this field, and if I have any advice for a career in data. So today’s issue is a bit different. I’m sharing 10 career tips, and telling you my story along the way. It’s more personal than usual. A little cliché, a little cheesy… but hey 🤷♂️ 1️⃣ Time adds up (quickly) Twelve years ago, I started working in academia as a...

👋 Hi! This week, a student of my ggplot2 course asked how I go from a dataset to a polished graph. It's a common (and important!) question. So here’s a quick overview of my process: 1️⃣ Explore first I start by making lots of quick, messy plots. No styling, just raw exploration to understand what’s in the data and what story might be hiding. I love using ggplot2 here: easy to filter, tweak, and switch chart types just by changing the geom. Pro tip: The gt_plt_summary() function from gtExtras...