We work on visualiation throughout the course. Here are the bits in rough order of presentation.
- R graphics landscape slides
- why we prefer
lattice) over base R graphics
- the underappreciated importance of data.frames, tidy data, and factor management to graphics
- basic jargon of
ggplot2 by using it
ggplot2 tutorial gives indicative code and all resulting figures
- scatterplots, stripplots, distributions, bars, themes, managing a color scheme, bubble and line plots
- Do’s and don’ts of making effective graphs
- Effective = easy for audience to decode numerical info
- Our ability to decode position along common axis >> area, angle, color, etc.
- The R Graph Catalog presents a visual, clickable index of 100+ figures
- Practical pro tips, i.e. a return to mechanics