Nitter complete color theory

A12. Data Visualization

Five connected studies move data visualization from direct observation and explanation through controlled experiment, application and critique. Five active studies connect evidence, experiment, application and critique.

Observe → Understand → Experiment → Apply → Critique and record

Open any study. Review state, labs, reflections and artifacts stay local to this browser.

• Categorical Palettes

  Begin Data Visualization with categorical palettes: observe directly and record the conditions before interpreting the result.

• Sequential Scales

  Within Data Visualization, build a working explanation of sequential scales, keeping the model distinct from the appearance it describes.

• Diverging Scales

  In Data Visualization, test diverging scales by changing one controlled variable and comparing the evidence.

• Uncertainty and Bivariate Color

  Apply uncertainty and bivariate color within Data Visualization to a practical color decision, preserving both the reasoning and its constraints.

• Redundant Encoding

  In Data Visualization, critique redundant encoding against evidence, exceptions and failure conditions before carrying it forward.