Day 4 was about using an observations dataset scraped by their website api. The dataset was huge ( 6 M  rows), but was fairly clean. It contained data concerning observations by the users of the app from nature of all sorts of kingdoms and species in almost every country in the world.  There were two main approaches to visualize and extract insights from this data; either using their rich dataset to represent different animal, plant, and bacteria genus, or profile users of the app. I went for the latter, which involved dealing with the granularity of the data.

Due to the massive number of users and how frequently they used the app, I went with representing the top 10 users by number of contributions, the type of organisms they shared, their activity over time, and their latest 5 posts. I really like how the seismogram represents spikes in activity over time.

Tableau Quick Tip


  • Add your (+ Measure)/2 and (-Measure)/2 to Measure Values
  • Change Mark type to line
  • Put Measure Types on line
  • Put a discrete date on the shelf

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