- Presentations
- Neil on Lev Manovich & Qinglu on Nicholas Felton
- Reading #2: Subtleties of Color
Assignment
- 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()
andloadTable()
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
- loads the testing data you’ll be using via the
- 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 theREADME.md
file.
- 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