Plot design

Day 04

Prof Amanda Luby

Carleton College
Stat 220 - Winter 2026

Today

ggplot2 review
customizations in ggplot2
Some guidelines for plot design

What we know:

A basic set of geometries

geom_point()
geom_histogram()
geom_boxplot()
geom_violin()
geom_bar()

How to map variables to aesthetics

x and y axis
color
shape
alpha
size

How to change axis labels and titles

labs()

What next?

Setting aesthetics
Using facets
Changing scales
Changing coordinates
Changing themes
Adding annotations

Survivor

From Season02 to Season 20, Survivor aired on Thursdays. After Season 20, it switched to airing on Wednesdays. Thursday is better for my schedule, so I’d like to make an argument for switching back to Thursdays.

Warm Up

Log into maize
- If you have to type your PAT in everytime you push to GitHub, follow the directions at Getting Set up with Git and GitHub #4 to tell RStudio to save your credentials
Find the .qmd template for today at the course website
Open it up in maize/Rstudio
Work with a neighbor to recreate this graph → (use 15 bins)

08:00

Polishing plots

We’re not quite satisfied….

I want the bars to have a border that stands out
I find stacked histograms hard to read
I don’t like the default color scheme
I don’t like the gray background

Setting aesthetics

Setting = choosing a certain value for an aesthetic

ggplot(season_summary) + 
  geom_histogram(
    aes(x = imdb_mean, fill = day_of_week), 
    bins = 15,
    color = "white"
    )

Changing scales

scale_<aes>_<method>()

Examples:

scale_fill_manual()
scale_fill_brewer()
scale_color_viridis()
scale_shape_manual()

Example (built-in scale)

ggplot(season_summary) + 
  geom_histogram(
    aes(x = imdb_mean, fill = day_of_week), 
    bins = 15,
    color = "white"
    ) + 
  scale_fill_brewer(palette = "Greens")

Example (built-in scale)

RColorBrewer::display.brewer.all()

Aside: types of color scales

Example (manual color palette)

Let’s make Wednesdays navyblue and Thursdays gold2

ggplot(season_summary) + 
  geom_histogram(
    aes(x = imdb_mean, fill = day_of_week), 
    bins = 15,
    color = "white"
    ) + 
  scale_fill_manual(values = c("gold2", "navyblue"))

Can also change non-color scales

ggplot(season_summary) + 
  geom_histogram(
    aes(x = imdb_mean, fill = day_of_week), 
    bins = 15,
    color = "white"
    ) + 
  scale_fill_manual(values = c("gold2", "navyblue")) + 
  scale_x_continuous(limits = c(1,10))

Can also change non-color scales

ggplot(season_summary) + 
  geom_histogram(
    aes(x = imdb_mean, fill = day_of_week), 
    bins = 15,
    color = "white"
    ) + 
  scale_fill_manual(values = c("gold2", "navyblue")) + 
  scale_x_log10(limits = c(1,10))

Can also change non-color scales

ggplot(season_summary) + 
  geom_histogram(
    aes(x = imdb_mean, fill = day_of_week), 
    bins = 15,
    color = "white"
    ) + 
  scale_fill_manual(values = c("gold2", "navyblue")) + 
  scale_x_reverse()

Changing Themes

Theme: The non-data ink on your plots

background
tick marks
grid lines
font
legend position
legend appearance

Prepackaged themes

ggplot2 themes

theme_grey()
theme_bw()
theme_linedraw()
theme_light()
theme_dark()
theme_minimal()
theme_classic()
theme_void()
theme_test()

ggthemes themes

theme_clean()
theme_economist()
theme_excel()
theme_fivethirtyeight()
theme_gdocs()
theme_solarized()
theme_stata()
theme_tufte()
theme_wsj()
And more!

Using a prepackaged theme

ggplot(data = <DATA>) + 
  <GEOM_FUNCTION>(
     mapping = aes(<MAPPINGS>)
  ) +
  <FACET_FUNCTION> +
  theme_<name>()

Try it

Apply theme_light() to the histogram

00:30

Even more customizations

Move legend
Clean up labels and title
Get rid of .5’s in x-axis
Annotations

`?theme`

theme(line, rect, text, title, aspect.ratio, axis.title, axis.title.x,
  axis.title.x.top, axis.title.x.bottom, axis.title.y, axis.title.y.left,
  axis.title.y.right, axis.text, axis.text.x, axis.text.x.top,
  axis.text.x.bottom, axis.text.y, axis.text.y.left, axis.text.y.right,
  axis.ticks, axis.ticks.x, axis.ticks.x.top, axis.ticks.x.bottom,
  axis.ticks.y, axis.ticks.y.left, axis.ticks.y.right, axis.ticks.length,
  axis.line, axis.line.x, axis.line.x.top, axis.line.x.bottom, axis.line.y,
  axis.line.y.left, axis.line.y.right, legend.background, legend.margin,
  legend.spacing, legend.spacing.x, legend.spacing.y, legend.key,
  legend.key.size, legend.key.height, legend.key.width, legend.text,
  legend.text.align, legend.title, legend.title.align, legend.position,
  legend.direction, legend.justification, legend.box, legend.box.just,
  legend.box.margin, legend.box.background, legend.box.spacing,
  panel.background, panel.border, panel.spacing, panel.spacing.x,
  panel.spacing.y, panel.grid, panel.grid.major, panel.grid.minor,
  panel.grid.major.x, panel.grid.major.y, panel.grid.minor.x,
  panel.grid.minor.y, panel.ontop, plot.background, plot.title,
  plot.subtitle, plot.caption, plot.tag, plot.tag.position, plot.margin,
  strip.background, strip.background.x, strip.background.y,
  strip.placement, strip.text, strip.text.x, strip.text.y,
  strip.switch.pad.grid, strip.switch.pad.wrap, ..., complete = FALSE,
  validate = TRUE)

Move legend and make the background transparent

ggplot(season_summary) + 
  geom_histogram(
    aes(x = imdb_mean, fill = day_of_week), 
    bins = 15,
    color = "white"
    ) + 
  scale_fill_manual(values = c("gold2", "navyblue")) + 
  theme_minimal() + 
  theme(
    legend.position = c(.15, .85),
    legend.background = element_blank()
  )

Clean up labels and title

ggplot(season_summary) + 
  geom_histogram(
    aes(x = imdb_mean, fill = day_of_week), 
    bins = 15,
    color = "white"
    ) + 
  scale_fill_manual(values = c("gold2", "navyblue")) + 
  theme_minimal() + 
  theme(
    legend.position = c(.15, .85),
    legend.background = element_blank()
  ) + 
  labs(
    x = "Season Average IMDB Rating",
    y = "",
    fill = "",
    title = "Survivor is better on Thursdays"
  )

Remove minor gridlines

ggplot(season_summary) + 
  geom_histogram(
    aes(x = imdb_mean, fill = day_of_week), 
    bins = 15,
    color = "white"
    ) + 
  scale_fill_manual(values = c("gold2", "navyblue")) + 
  theme_minimal() + 
  theme(
    legend.position = c(.15, .85),
    legend.background = element_blank(),
    panel.grid.minor = element_blank()
  ) + 
  labs(
    x = "Season Average IMDB Rating",
    y = "",
    fill = "",
    title = "Survivor is better on Thursdays"
  )

Get rid of .5’s

ggplot(season_summary) + 
  geom_histogram(
    aes(x = imdb_mean, fill = day_of_week), 
    bins = 15,
    color = "white"
    ) + 
  scale_fill_manual(values = c("gold2", "navyblue")) + 
  scale_x_continuous(breaks = c(6, 7, 8, 9)) +
  theme_minimal() + 
  theme(
    legend.position = c(.15, .85),
    legend.background = element_blank(),
    panel.grid.minor = element_blank()
  ) + 
  labs(
    x = "Season Average IMDB Rating",
    y = "",
    fill = "",
    title = "Survivor is better on Thursdays"
  )

Add an annotation

ggplot(season_summary) + 
  geom_histogram(
    aes(x = imdb_mean, fill = day_of_week), 
    bins = 15,
    color = "white"
    ) + 
  scale_fill_manual(values = c("gold2", "navyblue")) + 
  scale_x_continuous(breaks = c(6, 7, 8, 9)) +
  theme_minimal() + 
  theme(
    legend.position = c(.15, .85),
    legend.background = element_blank(),
    panel.grid.minor = element_blank()
  ) + 
  labs(
    x = "Season Average IMDB Rating",
    y = "",
    fill = "",
    title = "Survivor is better on Thursdays"
  ) +
  annotate("text", 
           x = 6, 
           y = 3, 
           label = "Lowest ratings \n occur on \n Wednesdays",
           col = "navyblue")

Increase text size

ggplot(season_summary) + 
  geom_histogram(
    aes(x = imdb_mean, fill = day_of_week), 
    bins = 15,
    color = "white"
    ) + 
  scale_fill_manual(values = c("gold2", "navyblue")) + 
  scale_x_continuous(breaks = c(6, 7, 8, 9)) +
  theme_minimal(base_size = 20) + 
  theme(
    legend.position = c(.15, .85),
    legend.background = element_blank(),
    panel.grid.minor = element_blank()
  ) + 
  labs(
    x = "Season Average IMDB Rating",
    y = "",
    fill = "",
    title = "Survivor is better on Thursdays"
  ) +
  annotate("text", 
           x = 6, 
           y = 3, 
           label = "Lowest ratings \n occur on \n Wednesdays",
           col = "navyblue")

Plot Design

General guidelines

Show the data, don’t distort it
Choose the right plot
Use color meaningfully and with restraint
Tell a story
Leave out non-story details

1. Show the data, don’t distort it

What a huge effect!

But it isn’t the whole story

2. Choose the right plot: Which slice is the biggest/smallest?

00:30

2. Choose the right plot

Wilke has good suggestions in chapters 5-16
Always stop and think about how easy it is to see the story
Try a few different options

3. Use color meaningfully and with restraint

3. Use color meaningfully and with restraint

4. Tell a story

4. Tell a story

One way to do this is by highlighting the important parts

5. Leave out non-story details

Is this train schedule easy to read?

5. Leave out non-story details

Does removing gridlines make it somewhat easier?

Data visualizations have an aura of objectivity

“We focus on four conventions which imbue visualisations with a sense of objectivity, transparency and facticity. These include: a) two-dimensional viewpoints; b) clean layouts; c) geometric shapes and lines; d) the inclusion of data sources.”

Good graphs can also break these guidelines

Your turn

Now that we have the toolkit to make customizations to our plots, and some “rules” for good graphs, let’s break them!

Choose a graph (the one from class today, one from last class, one from homework, etc.)
Make it ugly

Change the color scale
Choose a complete theme
Make at least 3 custom tweaks to the theme options

Explain why it’s ugly (what “rules” are you breaking? what makes it an ineffective graph?)
Post to our slack #social channel when you’re done (you don’t have to post your explanation)

Plot design

Today

What we know:

What next?

Survivor

Warm Up

Polishing plots

Setting aesthetics

Facets

Changing scales

Example (built-in scale)

Example (built-in scale)

Aside: types of color scales

Example (manual color palette)

Can also change non-color scales

Can also change non-color scales

Can also change non-color scales

Changing Themes

Prepackaged themes

Using a prepackaged theme

Try it

Even more customizations

?theme

Move legend and make the background transparent

Clean up labels and title

Remove minor gridlines

Get rid of .5’s

Add an annotation

Increase text size

Plot Design

Which do you prefer?

General guidelines

1. Show the data, don’t distort it

1. Show the data, don’t distort it

2. Choose the right plot: Which slice is the biggest/smallest?

2. Choose the right plot

3. Use color meaningfully and with restraint

3. Use color meaningfully and with restraint

4. Tell a story

4. Tell a story

5. Leave out non-story details

5. Leave out non-story details

Data visualizations have an aura of objectivity

Good graphs can also break these guidelines

Good graphs can also break these guidelines

Your turn

`?theme`