title: All the graph things output: html_document: toc: true

toc_depth: 4

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 <!--
  • underappreciated basics: density plots, high-volume scatterplots good stuff here: http://www.ugrad.stat.ubc.ca/~stat540/seminars/seminar03_graphics-ggplot2.html -->