Week 9

  • Presentation: Avishi on Amanda Cox
  • Book Club: Yeojin and Anna on Tufte’s Visual Explanations
  • P5 Mini-tutorials:
    • Open a new Terminal in the di-2019 folder and type make update to get the newest files
    • SVG Export: You can save your p5 sketches to SVG files that can then be opened and tweaked in Illustrator. Look in the svg-export folder for an example of what you need to add to your code to make it work.
    • Table objects: See the table-from-cvs example and follow its nested for-loop structure to step through each row and column in turn. Also look at the sequential-palette sketch to see how to calculate value ranges and map them to color ranges.
  • Small group meetings and in-class work session


  • Reading #2: The Subtleties of Color
    • Post your response with the tag ‘R2’ before the start of class
  • A Thousand Suns
    • Clean up whatever spreadsheet manipulation you did to the testing data via pivot tables and the like into a csv-friendly format that has a single header row, 1 set of data per row, and is purely rectangular (i.e., no skipped lines or multi-row/column regions). Save this to a csv in your project/data folder where your p5 code can access it.
    • Find the external data source you’ll be using for your ‘so what’ and ‘compared to what’ variables and convert it to spreadsheet form. This should probably live on Google Sheets but you should also download a csv to project/data.
    • Start a code-based sketch that minimally does the following:
      • loads the testing data you’ll be using via the preload() and loadTable() functions
      • loads the external ‘context’ data you’ve collected and added to the data folder
      • graphically renders the testing data in accordance with one of your pencil sketches
    • Bring in three additional pencil sketches that show different options for merging the testing data with your external data source. As before, save these images to the process directory and explain their logic within the README.md file.
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