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Notes

Lectures

  • possible threads throughout

    • anything is possible
    • what am i trying to show?
      • problem set where they need to figure out the answer to a sci ? with the plot

  • Lecture 1.4

    • go over some plots from link
    • a difficult decision with real uncertainty about what is best
    • no dynamite plots (with few exceptions)

  • Lecture 3.1

    • show where we are going - several high information plots
      • e.g. TT plot with DEseq & RNAi

  • Lecture 5.1

    • add eps as option

  • Lecture 5.4

    • show them how to source a file with ggplot functions & themes

recording mistakes

  • Lecture 1.3

    • go back to end of slide 15 to pick up again

  • Lecture 2.1

    • cuts in third section

  • Lecture 3.1

    • cut on last slide

Problem sets

Week 1

  • Find a plot that you think is terrible
    • Explain why
  • Read Midway SR. 2020. Principles of Effective Data Visualization. Patterns 1:100141.

Week 2

  • Experience working inside and outside aes()

  • changing axis limits - when you get warning about dropping points

  • didnt make it - add later: gradient with challenging scale (pvals), coloring just a few pts

Week 3

  • size plots in a quarto file

Week 4

  • show them how to source a file with ggplot functions & themes

Week 5

Final project

  • 4-6 publication quality images
    • Paper/manuscript/dissertation: multipanel labeled
    • Powerpoint slide: appropriate font and geometry sizes
      • Appropriate alt text

Gallery

Plots to cover

Univariate

  • Histogram
  • Density
  • Box
  • Violin
  • Ridgeline

Bivariate

  • Scatter
  • Lines / paths

Customization