You’ve just finished the hard work of collecting a large amount of rich, clean data; you're now faced with the task of teasing out and presenting the most important takeaways.

Done right, data tells a story that takes the audience on a journey toward your most important conclusions. Nothing helps move them quite like visual elements such as charts, graphs, and maps. But you can’t sacrifice data integrity to visual interest; you have to know not only what makes people stand up and take notice, but also which visual elements best present your key points.

In this session, you’ll discover how to make those choices using basic principles of human attention and perception, along with a simple option to create unique visualizations. That option is Python, a flexible way to programmatically generate graphics that doesn’t require you to be a programming expert. Instead, Python has many libraries and tools made specifically for this purpose. With guidance from this session, you’ll be able to pick up Python tools quickly and make your hard-working data shine with very little setup.
  • Strategies for planning your story to frame the key points in your data
  • How principles of human attention and perception can guide you in creating effective visuals to illustrate key insights in a data set
  • The different design considerations for narrating data in live settings versus for professional reports
  • Ways that Python’s libraries and tools can be used to elevate the quality of a visual narrative

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