All the graph things

We work on visualiation throughout the course. Here are the bits in rough order of presentation.

R graphics landscape slides
- why we prefer ggplot2 (or lattice) over base R graphics
- the underappreciated importance of data.frames, tidy data, and factor management to graphics
- basic jargon of ggplot2
Learning ggplot2 by using it
- my 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
- mostly from Naomi Robbins’ book “Creating More Effective Graphs”
- see figure and the exact ggplot2 code to produce it, side-by-side
- code for all figures and app itself is on GitHub
Colors
- Using colors in R
- Taking control of qualitative colors in ggplot2
Practical pro tips, i.e. a return to mechanics
- Secrets of a happy graphing life: data.frames! tidy data! factors!
- Writing figures to file
- Multiple plots on a page