Weekly Data Viz Decomp: Your City’s Kickstarter Scene Visualized

Starting off with these weekly to keep a look out for technique and learning.

This week’s viz: Your City’s Kickstarter Scene Visualized

Decomposition of a Visualization:

  • What are the:
    • Variables (Data points, where they are, and how they’re represented):
      • Cities and founding for Kickstarter projected, shown in packed bubbles
      • Barchart breakout breakout with heat using color hue categorized in a data table
    • Data Types (Quantitative, Qualitative, Categorical, Continuous, etc.):
      • Quantitative
    • Encodings (Shape, Color, Position, etc.):
      • Shape, position, size, color hue
  • What works well here?
    • Showing size of funding relative to each other in a large scope, used with the size of the bubbles for individual projects in each city and the packed bubble sizes comparing city to city
  • What does not work well and what would I improve?
    • Would want to be able to filter more, by number of backers for instance to improve explorability and hide the bubbles
  • What is the data source?  Do I see any problems with how it’s cited/used?
    • Kickstarter data, straight from the source
  • Any other comments about what I learned?
    • Good example of a lot of data put into one place to be compared with relative ease
    • The analysis the goes with it is critical because most viewers will not spend enough time to do the analysis themselves to glean the ton of insight here



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