The National Longitudinal Surveys from the Bureau of Labor Statistics are unique in that they run long-term to survey the lives of individuals for decades. For The Pudding, Alvin Chang visualized survey responses to show how adversity as a teenager carries into adulthood.

Each person icon represents a respondent and the collective bar chart stacks track through the years. The icons run across the screen on each time segment and demographic shift.

There’s a video version, shown below, and while I enjoy Alvin’s dulcet voice, I prefer the scrolling version.

A decade and a half ago, I wrote the first edition of Visualize This as a how-to guide to my past self. It was for someone who was familiar with visualization but was stuck on the part where it’s time to make and design charts with your own data.

What tools should you use? How do you use them? How do you get from rough sketch to finished graphic? How do you get the visualization idea in your imagination on to a screen where others can see?

It turns out that you can read and learn a lot about visualization — the chart types, the best visual encodings, design considerations, and purpose — without actually knowing how to follow through with the advice. There’s a technical side to visualizing data that couples with the thinking side. I wrote Visualize This for the person who wants to make the coupling and follow through.

The challenge of writing a book with concrete, how-to examples that rely on software is that some of the software fades. The technology and applications shift.

Flash dies. People consume data through different screen sizes. New tools make it easier to visualize data. Tastes change. The field develops.

Visualize This, Second Edition is an update for the tools, chart types, and overall process that changed over the years. The examples are better balanced and more focused.

The new book is still a practical, easy-to-read guide intended for my past self who wanted to make all the charts for all the data. But this time around, I had a decade and a half more experience analyzing data, making charts, and thinking about process.

Visualize This, Second Edition is out in June, but you can pre-order a copy now. I hope it helps you have fun with data.

NatureQuant processes and analyzes satellite imagery to quantify people’s access to nature. They call it a NatureScore. For the Washington Post, Harry Stevens mapped and charted the scores across the United States. At first glance, the map looks a lot like population density, but the better comparison is in how cities with similar population densities look next to each other.

People need a sense of how distributions work before they can make sense of a histogram. Here’s how I (try to) make these misunderstood charts easier to read.

As you might expect, the path of totality brought increased activities as people tried to get in the right spots. For the New York Times, Charlie Smart mapped the movements based on activity data from Mapbox and traffic data from TomTom.

From xkcd, a Rube Goldberg machine that keeps on going. Edit a cell by adding xkcd-esque objects and watch the balls fall and bounce to neighboring cells.

Maybe you heard there’s a total eclipse happening today. AirDNA mapped Airbnb occupancy rates over the week. There might be a pattern.

The anticipation of the solar eclipse has transformed an otherwise ordinary Monday into a lucrative opportunity for STR hosts located within the path of totality. As of March 25th, occupancy rates for April 7th have soared to an impressive 88% across all listings. This represents a massive surge in demand for accommodations on the night before the big celestial event.

The easystats R package in on my to-try list.

easystats is a collection of R packages, which aims to provide a unifying and consistent framework to tame, discipline, and harness the scary R statistics and their pesky models.

Apparently it’s been around since 2022, but it’s new to me.

Show all the data at once so that you can see a full trend efficiently, but show a bit at a time and show how the data builds.

Joanie Lemercier used a grid of spinning paddles that turn with the wind. Collectively, they show the flows through the air in real-time.

It reminds me of a digital map that used a similar geometry to show wind patterns across the United States.

Alexander Miller wrote a “fable of emergence” that combines Conway’s Game of Life with Pandora’s Box.

Conway’s game grew on Pandora the more she played. Although the rules of the game were relatively straightforward, it was surprisingly difficult to predict the next generation from the previous. Something was hidden within this deceptively simple format. The rules formed a subterranean structure of which she could only see the surface.

It’s animated with a sprinkle of interaction to make sure you’re paying attention.

It continues to get easier to take someone’s face and put that person in compromising situations. For The Markup, Mariel Padilla reports on states trying to catch up with the fast-developing technology.

Carrie Goldberg, a lawyer who has been representing victims of nonconsensual porn—commonly referred to as revenge porn—for more than a decade, said she only started hearing from victims of computer-generated images more recently.

“My firm has been seeing victims of deepfakes for probably about five years now, and it’s mostly been celebrities,” Goldberg said. “Now, it’s becoming children doing it to children to be mean. It’s probably really underreported because victims might not know that there’s legal recourse, and it’s not entirely clear in all cases whether there is.”

The internet is going to get very weird and very confusing, especially for those who can’t fathom how a photo, a video, or audio could be fake when it seems so real. Scammers’ imaginations must be running wild these days.

OpenAI previewed Voice Engine, a model to generate voices that mimic, using just a 15-second audio sample:

We first developed Voice Engine in late 2022, and have used it to power the preset voices available in the text-to-speech API as well as ChatGPT Voice and Read Aloud. At the same time, we are taking a cautious and informed approach to a broader release due to the potential for synthetic voice misuse. We hope to start a dialogue on the responsible deployment of synthetic voices, and how society can adapt to these new capabilities. Based on these conversations and the results of these small scale tests, we will make a more informed decision about whether and how to deploy this technology at scale.

They provide worthwhile use cases, such as language translation and providing a voice to those who are non-verbal, but oh boy, the authenticity of online things is going to get tricky very soon.

For Knowing Machines, an ongoing research project that examines the innards of machine learning systems, Christo Buschek and Jer Thorp turn attention to LAION-5B. The large image dataset is used to train various systems, so it’s worth figuring out where the dataset comes from and what it represents.

As artists, academics, practitioners, or as journalists, dataset investigation is one of the few tools we have available to gain insight and understanding into the most complex systems ever conceived by humans.

This is why advocating for dataset transparency is so important if AI systems are ever going to be accountable for their impacts in the world.

If articles covering similar themes have confused you or were too handwavy, this one might clear that up. It describes the system and steps more concretely, so you finish with a better idea of how systems can end up with weird output.

Alasdair Rae outlines the basics of visualizing basketball shot data with QGIS, an open-source software package typically used for geographic maps. Even if you’re not into basketball, sports data can be fun to poke at because it’s comprehensive and usually covers a good range of time and categories.

I collect visualization tools and learning resources and then round them up at the end of each month. Here’s the good stuff for March.

Satellite imagery on its own can be limited in what it can say without context. It’s photos from the sky, which is neat and technical, but then what? For Nightingale, Robert Simmon describes the many ways that journalists use satellite imagery to tell stories and layer meaning.

This is a fun project by Jan Willem Tulp. Based on data from a cross-verified database of notable people, Tulp scrolls through history to show when these people enter and leave the world based on their age. Start in 3500 BC and scroll from there.

To gain a better understanding of how ChatGPT works under the hood, Santiago Ortiz repeatedly passed the prompt “Intelligence is” to the chatbot. Then he visualized the statistical paths to get to a response using a 3-D network. If you squint, the network kind of looks like a computer’s brain.