Learning data viz by looking outside of data viz
data / curious
2019.09.30
Hello.
Today is the last day of September. Where I live, the leaves are starting to slowly give way to shades of yellow, orange, red. It happens every year. But every year it still surprises me in a small way.
If you work in data viz, you probably spend a lot of time looking at charts: your own, your colleagues, and the random ones you find on Twitter. We surround ourselves with other people's pixels hoping that new ideas and creativity will soak in through digital osmosis.
But sometimes, the best inspiration is found in something totally unrelated. Something that has nothing to do with data, or with visualization.
Something like the changing color of leaves.
This week I'm trying to step away from my screen and gather inspiration in the colors, shapes, sounds and patterns around me. You'll find a few links in this edition that try to follow this principle as well.
Let's get started.
Read_
Where can I find inspiration to diversify my data viz?
Try looking outside of the field. Sometimes you need to look beyond other people's charts to get the creative juices flowing. Say something like, mid-century nature books, for example.
What will the qualifying time be for the 2020 Boston marathon?
Strava data engineer Dave Hoch crawls through the world's largest running dataset to find out.
Explore_
How does a black hole move?
NASA created this mind-bending animation of a black hole to find out.
What has Congress been tweeting about?
The Pudding created a new interactive essay in partnership with Salesforce. The story uses machine learning and NLP to group categories and topics most referenced by politicians on Twitter.
Analyze_
How can I quickly create random datasets for experimenting?
You could write a quick Python script...OR, if you're craving a GUI, check out this website for pseudo-random dataset generation.
Learn_
What can we learn from generative art?
It's a question I've been asking myself a lot lately. If you program your data viz, you'll notice a lot of overlap between creative coding, generative art and interactive data visualization. The website/podcast generative artistry seems like a really interesting resource to learn more about this intersection.
How do I use Chart.js?
I've praised Chart.js as a Javascript charting library here before as lightweight, simple, and clean. This walkthrough is an approachable introduction to getting started making your first graph.
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