Compound figures

class: center, middle, title-slide

.title[
# Compound figures
]
.author[
### Claus O. Wilke
]
.date[
### last updated: 2024-04-22
]

---

## Compound figures

Two common scenarios:

1\. The same type of plot is replicated many times (small multiples)

2\. Several disparate plots are combined into one display

---

background-image: url("https://clauswilke.com/dataviz/multi-panel_figures_files/figure-html/titanic-passenger-breakdown-1.png")
background-position: left 50% top 60%
background-size: 45%

## 1. Small multiples (facets)

???

Figure from [Claus O. Wilke. Fundamentals of Data Visualization. O'Reilly, 2019.](https://clauswilke.com/dataviz)

---

background-image: url("https://clauswilke.com/dataviz/balance_data_context_files/figure-html/titanic-survival-by-gender-class-bad-1.png")
background-position: left 50% top 60%
background-size: 45%

## 1. Small multiples (facets)

.absolute-bottom-left[
Avoid bars or other elements that are floating in space
]

???

Figure from [Claus O. Wilke. Fundamentals of Data Visualization. O'Reilly, 2019.](https://clauswilke.com/dataviz)

---

background-image: url("https://clauswilke.com/dataviz/balance_data_context_files/figure-html/titanic-survival-by-gender-class-1.png")
background-position: left 50% top 60%
background-size: 45%

## 1. Small multiples (facets)

???

Figure from [Claus O. Wilke. Fundamentals of Data Visualization. O'Reilly, 2019.](https://clauswilke.com/dataviz)

---
class: center middle

## Small multiples work even for massive amounts of data

---
background-image: url("https://clauswilke.com/dataviz/multi-panel_figures_files/figure-html/movie-rankings-1.png")
background-position: left 50% top 60%
background-size: 45%

???

Figure from [Claus O. Wilke. Fundamentals of Data Visualization. O'Reilly, 2019.](https://clauswilke.com/dataviz)

---

background-image: url("https://clauswilke.com/dataviz/multi-panel_figures_files/figure-html/BA-degrees-variable-y-lims-1.png")
background-position: left 50% top 70%
background-size: 50%

## y-axis ranges should be consistent among panels

???

Figure from [Claus O. Wilke. Fundamentals of Data Visualization. O'Reilly, 2019.](https://clauswilke.com/dataviz)

---

background-image: url("https://clauswilke.com/dataviz/multi-panel_figures_files/figure-html/BA-degrees-fixed-y-lims-1.png")
background-position: left 50% top 70%
background-size: 50%

## y-axis ranges should be consistent among panels

???

Figure from [Claus O. Wilke. Fundamentals of Data Visualization. O'Reilly, 2019.](https://clauswilke.com/dataviz)

---

background-image: url("https://clauswilke.com/dataviz/multi-panel_figures_files/figure-html/BA-degrees-compound-1.png")
background-position: left 50% top 55%
background-size: 75%

## 2. Combining disparate figures into one display

???

Figure from [Claus O. Wilke. Fundamentals of Data Visualization. O'Reilly, 2019.](https://clauswilke.com/dataviz)

.absolute-bottom-left[
Note: We now need plot labels ("a", "b") to identify sub-plots
]

---

background-image: url("https://clauswilke.com/dataviz/multi-panel_figures_files/figure-html/BA-degrees-compound-bad-1.png")
background-position: left 50% top 55%
background-size: 75%

## Don't use overly large or otherwise prominent labels

.absolute-bottom-left[
Note: Also don't use serif fonts (such as Times) for labels
]

???

Figure from [Claus O. Wilke. Fundamentals of Data Visualization. O'Reilly, 2019.](https://clauswilke.com/dataviz)

---

background-image: url("https://clauswilke.com/dataviz/multi-panel_figures_files/figure-html/athletes-composite-good-1.png")
background-position: left 50% top 65%
background-size: 50%

## Use a consistent color language among sub-plots

???

Figure from [Claus O. Wilke. Fundamentals of Data Visualization. O'Reilly, 2019.](https://clauswilke.com/dataviz)

---

background-image: url("https://clauswilke.com/dataviz/multi-panel_figures_files/figure-html/athletes-composite-inconsistent-1.png")
background-position: left 50% top 65%
background-size: 50%

## Use a consistent color language among sub-plots

???

Figure from [Claus O. Wilke. Fundamentals of Data Visualization. O'Reilly, 2019.](https://clauswilke.com/dataviz)

---

background-image: url("https://clauswilke.com/dataviz/multi-panel_figures_files/figure-html/athletes-composite-good-1.png")
background-position: left 50% top 65%
background-size: 50%

## Pay attention to sub-plot alignment

???

Figure from [Claus O. Wilke. Fundamentals of Data Visualization. O'Reilly, 2019.](https://clauswilke.com/dataviz)

---

background-image: url("https://clauswilke.com/dataviz/multi-panel_figures_files/figure-html/athletes-composite-misaligned-1.png")
background-position: left 50% top 65%
background-size: 50%

## Pay attention to sub-plot alignment

???

Figure from [Claus O. Wilke. Fundamentals of Data Visualization. O'Reilly, 2019.](https://clauswilke.com/dataviz)

---

background-image: url("https://clauswilke.com/dataviz/multi-panel_figures_files/figure-html/athletes-composite-good-1.png")
background-position: left 50% top 65%
background-size: 50%

## Combine plots of different types

.absolute-bottom-left[
This helps your readers to distinguish different parts of the analysis 
]

???

Figure from [Claus O. Wilke. Fundamentals of Data Visualization. O'Reilly, 2019.](https://clauswilke.com/dataviz)

---

background-image: url("https://clauswilke.com/dataviz/telling_a_story_files/figure-html/athletes-composite-repetitive-1.png")
background-position: left 50% top 65%
background-size: 50%

## Combine plots of different types

.absolute-bottom-left[
This helps your readers to distinguish different parts of the analysis 
]

???

Figure from [Claus O. Wilke. Fundamentals of Data Visualization. O'Reilly, 2019.](https://clauswilke.com/dataviz)

---

background-image: url("https://clauswilke.com/dataviz/multi-panel_figures_files/figure-html/athletes-composite-good-1.png")
background-position: left 50% top 65%
background-size: 50%

## Combine plots of different types

.absolute-bottom-left[
This helps your readers to distinguish different parts of the analysis 
]

???

Figure from [Claus O. Wilke. Fundamentals of Data Visualization. O'Reilly, 2019.](https://clauswilke.com/dataviz)

---

## Distinguish infographics from figures in article/book

There are two distinct use cases:

**Infographic:** Standalone, has title/subtitle/caption

**Figure in article/book:** Caption contains title, not part of figure

---

background-image: url("https://clauswilke.com/dataviz/figure_titles_captions_files/figure-html/corruption-development-infographic-1.png")
background-position: left 50% top 45%
background-size: 50%

.absolute-bottom-left[
Example of infographic
]

???

Figure from [Claus O. Wilke. Fundamentals of Data Visualization. O'Reilly, 2019.](https://clauswilke.com/dataviz)

---

background-image: url("https://clauswilke.com/dataviz/figure_titles_captions_files/figure-html/corruption-development-1.png")
background-position: left 15% top 40%
background-size: 50%

.pull-right.width-35.move-down-2em.small-font[
Figure 1. **Corruption and human development.** The most developed countries experience the least corruption. Inspired by a posting in [The Economist online (2011)](https://www.economist.com/graphic-detail/2011/12/02/corrosive-corruption). Data sources: Transparency International & UN Human Development Report.
]

.absolute-bottom-left[
Example of figure in article or book
]

???

Figure from [Claus O. Wilke. Fundamentals of Data Visualization. O'Reilly, 2019.](https://clauswilke.com/dataviz)

[//]: # "segment ends here"

---
class: center middle

## Making compound plots in R

---

## The **patchwork** package

.tiny-font.pull-left.width-40[

```r
library(patchwork)

# make first plot
p1 <- ggplot(mtcars) + 
  geom_point(aes(mpg, disp))

p1
```
]

.pull-right.width-55[
<img src="compound-figures_files/figure-html/patchwork-demo1-out-1.svg" width="100%" />
]

---

## The **patchwork** package

.tiny-font.pull-left.width-40[

```r
library(patchwork)

# make first plot
p1 <- ggplot(mtcars) + 
  geom_point(aes(mpg, disp))

# make second plot
p2 <- ggplot(mtcars) + 
  aes(gear, disp, group = gear) +
  geom_boxplot()

p2
```
]

.pull-right.width-55[
<img src="compound-figures_files/figure-html/patchwork-demo2-out-1.svg" width="100%" />
]

---

## The **patchwork** package

.tiny-font.pull-left.width-40[

```r
library(patchwork)

# make first plot
p1 <- ggplot(mtcars) + 
  geom_point(aes(mpg, disp))

# make second plot
p2 <- ggplot(mtcars) + 
  aes(gear, disp, group = gear) +
  geom_boxplot()

*# place plots side-by-side
*p1 | p2
```
]

.pull-right.width-55[
<img src="compound-figures_files/figure-html/patchwork-demo3-out-1.svg" width="100%" />
]

---

## The **patchwork** package

.tiny-font.pull-left.width-40[

```r
library(patchwork)

# make first plot
p1 <- ggplot(mtcars) + 
  geom_point(aes(mpg, disp))

# make second plot
p2 <- ggplot(mtcars) + 
  aes(gear, disp, group = gear) +
  geom_boxplot()

*# place plots on top of one-another
*p1 / p2
```
]

.pull-right.width-40.move-up-3em[
<img src="compound-figures_files/figure-html/patchwork-demo4-out-1.svg" width="60%" />
]

---

## The **patchwork** package

.tiny-font.pull-left.width-35[

```r
# add a few more plots
p3 <- ggplot(mtcars) + 
  geom_smooth(aes(disp, qsec))

p4 <- ggplot(mtcars) + 
  geom_bar(aes(carb))

*# make complex arrangement
*(p1 | p2 | p3) / p4
```
]

.pull-right.width-60.move-up-1em[
<img src="compound-figures_files/figure-html/patchwork-demo5-out-1.svg" width="90%" />
]

---

## Plot annotations and themes

.tiny-font.pull-left.width-35[

```r
(p1 | p2 | p3) / p4 +
*  plot_annotation(
*    tag_levels = "A"
*  )
```

Automatic labeling of plots
]

.pull-right.width-60.move-up-1em[
<img src="compound-figures_files/figure-html/patchwork-demo6-out-1.svg" width="90%" />
]

---

## Plot annotations and themes

.tiny-font.pull-left.width-35[

```r
(p1 | p2 | p3) / p4 +
*  plot_annotation(
*    tag_levels = "a"
*  )
```

Automatic labeling of plots
]

.pull-right.width-60.move-up-1em[
<img src="compound-figures_files/figure-html/patchwork-demo7-out-1.svg" width="90%" />
]

---

## Plot annotations and themes

.tiny-font.pull-left.width-35[

```r
(p1 | p2 | p3) / p4 +
  plot_annotation(
   tag_levels = "a"
* ) &
* theme_minimal_grid()
```

Applying one theme to all plots
]

.pull-right.width-60.move-up-1em[
<img src="compound-figures_files/figure-html/patchwork-demo8-out-1.svg" width="90%" />
]

---

## Plot annotations and themes

.tiny-font.pull-left.width-35[

```r
(p1 | p2 | p3) / p4 +
  plot_annotation(
   tag_levels = "a",
*  title = "A plot about mtcars",
*  subtitle = "With subtitle...",
*  caption = "...and caption"
  ) &
  theme_minimal_grid()
```

Titles and captions
]

.pull-right.width-60.move-up-1em[
<img src="compound-figures_files/figure-html/patchwork-demo9-out-1.svg" width="90%" />
]

[//]: # "segment ends here"

---

## Further reading

- Fundamentals of Data Visualization: [Chapter 21: Multi-panel figures](https://clauswilke.com/dataviz/multi-panel-figures.html)
- **patchwork** documentation: [Getting started](https://patchwork.data-imaginist.com/articles/patchwork.html)
- **patchwork** documentation: [Plot assembly](https://patchwork.data-imaginist.com/articles/guides/assembly.html)
- **patchwork** documentation: [Adding annotation and style](https://patchwork.data-imaginist.com/articles/guides/annotation.html)