Data visualization I

Data visualization is one of the most important and difficult skills to master for scientific communication. Each graphic has to tell a story.

Philosophy

"Above all else show the data"

"A large share of ink on a graphic should present
 data-information, the ink changing as the data change.
  Data-ink is the non-erasable core of a graphic, the
   non-redundant ink arranged in response to variation
    in the numbers represented"

Tufte, 1983, The Visual Display of Quantitative Information

A good plot should tell a complete story. For instance, this one tells the story of Napoleon's Grande Armée:

Even something boring can be made to look interesting:

Intro to ggplot2

Notebook here.

Links

• R Cookbook Indespensible reference for how to do things with ggplot2
• ggplot2 cheatsheet Good concise reference
• Intro to ggplot2 Well done lecture using

In-class exercise

• Using the Iris data set, make a plot that clearly separates the three species along two morphological axes.

Homework

1. Using any appropriate data set, create the following types of plots
   • a violin plot
   • a rug plot
   • a scatterplot with groups of points, but without a legend
   • A scatterplot without x-axis ticks
   • annotate a plot with text
2. Take two separate plots in made usig ggplot and arrange them in in columns (not using facet_grid). Hint: you will need to use another library.
3. Draw a histogram of points with a fitted normal distribution (this looks better if your data are roughly normally distributed). E.g., here
4. Implement some plots using the ggplot libary in Python
5. Using Titanic survivor data, make a plot to show whether "women and children first" changed the odds of survival. Was economic class a factor?
6. Make a chord diagram in R, using any library and data set