Day 39 of 180 Days of Data Viz Learning #JFDI

I’m doing some form of data visualization learning for 180 days because I need to #JFDI.  See post explaining how and why I’m doing this.

Decomposition of a Visualization:

Note to self:  Haven’t been doing these as much lately, but incredibly helpful for learning how to communicate and to get ideas.  Try to get at least three of these a week so you put in the extra thought to what you see and read.

Infographic: Fewer Americans Are Seeing the Benefits of Higher Education

  • What are the:
    • Variables (Data points, where they are, and how they’re represented):
      • Students enrolled in degree problem denoted by size and color
      • Students dropping out denoted by angle
      • Time on x-axis, debt and funding y-axis in area “mountain” view with different colors
      • Time on x-axis, number of students foreign and American on y-axis in “mountain” view with different colors
    • Data Types (Quantitative, Qualitative, Categorical, Continuous, etc.):
      • Quantitative
      • Categorical (students)
      • Continuous (time)
    • Encodings (Shape, Color, Position, etc.):
  • What works well here?
    • Use of size angle and flowing shapes very compelling in showing proportions of students and what happens
  • What does not work well and what would I improve?
    • Two bottom mountains graphs appear to be connected because of size and color but are not.  I would change the the color scheme more to denote the difference.
    • Color schemes in general are too similar for different types of data, making a compelling story a little less so because of extra processing time needed to understand the visual.
  • What is the data source?  Do I see any problems with how it’s cited/used?
    • Not clearly cited.  Not good.
  • Any other comments about what I learned?
    • Interesting use of combining size, angle, and position to position a psuedo-linear story.

Code/Technical Learning:

Hodgepodge of tasks:

Three Takeways

  • Javascript Review on Treehouse
  • Integrating D3 with Tableau
  • Getting better at SQL queries to create efficient tables to work with

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