Mapping Data to Graphics

Dr. Nathaniel Cline

Agenda

1

Grammar of Graphics

2

Grammatical Layers

3

Review and to do

Exploratory Project

Stories about the Census

1. Factoid

2. Interaction

3. Comparison

Warm-up

Data Story Critique

Make your own mobility animation

Grammar of Graphics

History

Before walking through the modern grammar of graphics, let’s look at some historical examples of creative ways people have mapped data to aesthetics to tell a story.

W.E.B. Dubois at the Paris Exhibition

Nice project using Dubois’ style

Famed sociologist, writer, and Black rights activist W. E. B. Du Bois fundamentally changed the representation of Black Americans with his exhibition of data visualizations at the 1900 Paris Exposition. Beautiful in design and powerful in content, these data portraits make visible a wide spectrum of African American culture, from advances in education to the lingering effects of slavery. They convey a literal and figurative representation of what he famously referred to as the color line, collected here in full color for the first time.

Mapping data to aesthetics

Aesthetic

Visual property of a graph

Position, shape, color, etc.

Data

A column in a dataset

Describing Minard

Data	Aesthetic	Graphic/Geometry
Longitude	Position (x-axis)	Point
Latitude	Position (y-axis)	Point
Army size	Size	Path
Army direction	Color	Path
Date	Position (x-axis)	Line+text
Temperature	Position (y-axis)	Line+text

Describing Minard in R

Data	aes()	geom
Longitude	x	geom_point()
Latitude	y	geom_point()
Army size	Size	geom_path()
Army direction	color	geom_path()
Date	x	geom_line() + geom_text
Temperature	y	geom_line() + geom_text

Recall the basic ggplot framework

ggplot(data = DATA) +
  GEOM_FUNCTION(mapping = aes(AESTHETIC MAPPINGS))

Minard

ggplot(data = troops) +
  geom_path(mapping = aes(x = longitude,
                          y = latitude,
                          color = direction,
                          size = survivors))

This is a dataset named troops:

# A tibble: 3 × 4
  longitude latitude direction survivors
  <chr>     <chr>    <chr>     <chr>    
1 24        54.9     A         340000   
2 24.5      55       A         340000   
3 …         …        …         …        

ggplot(data = troops) +
  geom_path(mapping = aes(x = longitude,
                          y = latitude,
                          color = direction,
                          size = survivors))

Code

ggplot(data = troops,
       mapping = aes(x = longitude,
                     y = latitude,
                     color = direction,
                     size = survivors)) +
  geom_path(lineend = "round", linejoin = "mitre") + 
  scale_size_continuous(range = c(1, 20),
                        labels = scales::comma) +
  theme_gray(base_size = 20)

Remember this?

Data	aes()	geom
Wealth (GDP/capita)	x	geom_point()
Health (Life expectancy)	y	geom_point()
Continent	color	geom_point()
Population	size	geom_point()

This is a dataset named gapminder_2007

# A tibble: 3 × 5
  country     continent gdpPercap   lifeExp pop     
  <chr>       <chr>     <chr>       <chr>   <chr>   
1 Afghanistan Asia      974.5803384 43.828  31889923
2 Albania     Europe    5937.029526 76.423  3600523 
3 …           …         …           …       …       

ggplot(data = gapminder_2007,
       mapping = aes(x = gdpPercap,
                     y = lifeExp,
                     color = continent,
                     size = pop)) +
  geom_point() +
  scale_x_log10()

Code

ggplot(data = gapminder_2007,
       mapping = aes(x = gdpPercap,
                     y = lifeExp,
                     color = continent,
                     size = pop)) +
  geom_point() +
  scale_x_log10() +
  scale_size_continuous(range = c(1, 15),
                        labels = scales::comma) +
  theme_gray(base_size = 20)

Grammatical Layers

Layers

We can layer data, aesthetics, and mappings on to the base ggplot() with the ggplot specific pipe operator: +

Aesthetics: color(discrete)

Aesthetics: color(continuous)

Aesthetics: size

Aesthetics: fill

Aesthetics: shape

Aesthetics: alpha

	Example geom	What it makes
	geom_col()	Bar charts
	geom_text()	Text
	geom_point()	Points
	geom_boxplot()	Boxplots
	geom_sf()	Maps

Scales

Scales change the properties of the variable mapping

Example layer	What it does
scale_x_continuous()	Make the x-axis continuous
scale_x_continuous(breaks = 1:5)	Manually specify axis ticks
scale_x_log10()	Log the x-axis
scale_color_gradient()	Use a gradient
scale_fill_viridis_d()	Fill with discrete viridis colors

scale_x_log10()

Code

ggplot(gapminder_2007, aes(x = gdpPercap, y = lifeExp, color = continent, size = pop)) +
  geom_point() +
  scale_x_log10()

scale_color_viridis_d()

Code

ggplot(gapminder_2007, aes(x = gdpPercap, y = lifeExp, color = continent, size = pop)) +
  geom_point() +
  scale_x_log10() +
  scale_color_viridis_d()

Data Viz Catalog

Review and To-do

Review

• We explored the translation of a visual graphic to a grammar (ggplot)

• We will keep practicing this translation process, and the process of adding layers to a ggplot graphic

• Next time we will talk about some other dimensions (like time) and we will explore some more creative approaches to data story telling

Code

ggplot(gapminder, aes(x = gdpPercap, y = lifeExp, 
                      size = pop, color = country)) +
  geom_point(alpha = 0.7) +
  scale_size(range = c(2, 12)) +
  scale_x_log10(labels = scales::dollar) +
  guides(size = "none", color = "none") +
  facet_wrap(~continent) +
  # Special gganimate stuff
  labs(title = 'Year: {frame_time}', x = 'GDP per capita', y = 'life expectancy') +
  transition_time(year) +
  ease_aes('linear')

To-Do

Before next class:

• Make a graph using the county census data set. You can use any geom you like, but you must map a variable to color.

  • note pay attention to whether you are mapping color to a discrete variable or a continuous variable

  • Use ggsave("yourfilename.png") after your ggplot code and post it to our Teams site

• Pick a data viz from Data Viz Catalog and be ready to summarize what it is, and when it might be useful in class.