Hi folks,
I was very excited by the varied and amazing projects you pulled off for Byte 3. Nice job, folks! Here are some highlights:
- Some of you experimented with advanced visualization techniques. By linking age distribution to outcome type, it is possible to explore how outcomes vary with age. By supporting selection of different subvalues it is possible to filter the data in different ways. By animating outcomes over time on a map, it becomes clear that certain locations tend to have better outcomes than others.
- Some of your work helped me see the data in a new light. For example, one view of the data shows the percentage outcomes by dog size: Surprisingly, small dogs are adopted as commonly as puppies. Another view shows that of all intake types, strays are most ofter returned to owner while owner surrender are often euthanized. However, a small critique: notice that it is harder to draw these sorts of conclusions from the second chart primarily because the author chose to use number of animals rather than percentages (I find myself doing more work to handle that visual query).
- Your work also helped to highlight how different visualization choices (and data cleaning choices) can have a big impact on the viewer. For example, compare these pairs of visualizations:
- Animal by outcome type v1 and v2 (both allow the viewer to explore different breeds dynamically)
- Age by outcome v1 and v2 (which focuses on telling a story and leading the reader through discoveries)
- Dogs vs cats v1 and v2
- Size vs outcome v1 (includes breed too, check the 2nd chart) and v2
I hope you enjoy all of these as much as I did!