If your data has anything to do with people or environment, then seasonality matters. Our actions are heavily influenced by our regular hourly, daily, weekly, seasonal, and annual patterns, as well as by typical (e.g. holidays, weather variation, etc.) and one-off (e.g. natural disasters, electrical outages, war, etc.) aberrations to these patterns.
In this talk, Zan will show how seasonality affects data, share visualizations that handle these in effective and interesting ways, and provide guidelines for addressing seasonality in your own work.
About our Speaker:
Zan Armstrong's interest in data visualization originally grew out of her work forecasting and analyzing Google's global search ads revenue. This work led to a collaboration with Martin Wattenberg and Fernanda Viégas to tackle a key analysis problem: Visualizing Statistical Mix Effects and Simpson's Paradox, with the resulting research and "comet chart" presented at InfoVis 2014.
Zan is currently based in San Francisco and freelancing creating interactive data visualization. Zan's favorite projects are those which reveal an unexpected answer or help people see something in a new way. One of these, a project comparing the sizes of countries around the world, was featured on the Flowing Data blog. She also enjoys creating interactive pieces which give others the chance to experience the thrill of making discoveries in data.