This is a teenager is an interactive data visualization by Alvin Chang about a group of American teenagers that have been tracked in a longitudinal study since 1997 (they are around 40 years old now). The video version of the visualization is embedded above.
A year from now, in 1998, a researcher named Vincent Felitti will publish a paper that drastically changes the way we think about these kids — and their childhood.
The research will show that these childhood stressors and traumas — called Adverse Childhood Experiences — have a lifelong effect on our health, relationships, happiness, financial security, and pretty much everything else that we value. It will kickstart decades of research that shows that our childhood experiences shape our adulthood far more than we ever thought.
Ok this video from The Pudding is cool for two different reasons. First, you learn about which NBA player had the most unexpectedly great performance since 1985 (e.g. when a guy who is usually good for 6-8 pts inexplicably drops 50). But, you also get a fun little tutorial in how statistical analysis works and the importance of paying attention to the right data in order to get an answer that’s actually meaningful and relevant. How to interpret data in this way is an under-appreciated aspect in the bombardment of data and statistics we see in the media these days and teaching more people about it doesn’t have to be boring or stuffy.
It’s worth noting here that this first stage of data-work can be somewhat vexing: computers are great, but they’re also incredibly frustrating when they don’t do what you’d like them to do. That’s why it’s important to remember that you don’t need to worry — learning to program is exactly as infuriating and as dispiriting for you as it is for everyone else. I know this all too well: some people seem to be terrific at it without putting in all that much effort; then there was me, who first began writing code in 2014, and couldn’t understand the difference between a return statement and a print statement. The reason learning to code is so maddening is because it doesn’t merely involve learning a set number of commands, but a way of thinking. Remember that, and know that the little victories you amass when you finally run your loop correctly or manage to solve a particular data problem all combine to form that deeper understanding.
Before you begin visualizing your data, think through the most important points that you’re trying to communicate. Is the key message the growth of a variable over time? A disparity between quantities? The degree to which a particular value varies? A geographic pattern?
Once you have an idea of the essential takeaways you’d like your readers to understand, you can consider which type of visualization would be most effective at expressing it. During this step, I like to think of the pieces of work that I’ve got in my archive and see if any one of those is especially suitable for the task at hand.
Stay Connected