Dealing with issues of overplotting

class: center, middle, title-slide

# Dealing with issues of overplotting
### Claus O. Wilke
### last updated: 2022-04-25

---

## Be aware of points plotted exactly on top of one another

.center[
![](overplotting_files/figure-html/mpg-cty-displ-solid-1.svg)
]

???

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

Technical term for this problem: overplotting

---

## Partial transparency helps highlight overlapping points

.center[
![](overplotting_files/figure-html/mpg-cty-displ-transp-1.svg)
]

???

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

---

## A little jitter shows overlaps even more clearly

.center[
![](overplotting_files/figure-html/mpg-cty-displ-jitter-1.svg)
]

???

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

---

## But don't jitter too much

.center[
![](overplotting_files/figure-html/mpg-cty-displ-jitter-extreme-1.svg)
]

???

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

---
class: center middle

## 2D density plots: Contour lines and contour bands

---

## Contour lines are the 2D version of density plots

.center[
![](overplotting_files/figure-html/blue-jays-contour-1.svg)
]

???

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

---

## We can vary shading for added effect

.center[
![](overplotting_files/figure-html/blue-jays-contour-filled-1.svg)
]

???

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

---

## What do we do when there are multiple groups?

.center[
![](overplotting_files/figure-html/blue-jays-no-contour-by-sex-1.svg)
]

???

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

---

## Colored contour lines can work for 2 to 3 groups

.center[
![](overplotting_files/figure-html/blue-jays-contour-by-sex-1.svg)
]

???

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

---

## What if there are multiple groups intermingled?

.center[
![](overplotting_files/figure-html/diamonds-points-1.svg)
]

???

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

---

## Don't make plots that look like spaghetti

.center[
![](overplotting_files/figure-html/diamonds-contours-1.svg)
]

???

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

---

## Contour lines work well with small multiples (facets)

.center[
![](overplotting_files/figure-html/diamonds-contour-facets-1.svg)
]

???

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

---
class: center middle

## 2D histograms: Rectangular and hex bins

---

## 2D histograms: rectangular bins

.center[
![](overplotting_files/figure-html/diamonds-bin2d-facets-1.svg)
]

.absolute-bottom-left[
We need to choose a bin size as in regular histograms
]

---

## 2D histograms: rectangular bins

.center[
![](overplotting_files/figure-html/diamonds-bin2d-facets2-1.svg)
]

.absolute-bottom-left[
We need to choose a bin size as in regular histograms
]

---

## 2D histograms: hex bins

.center[
![](overplotting_files/figure-html/diamonds-hexbin-facets-1.svg)
]

---

## 2D histograms: hex bins

.center[
![](overplotting_files/figure-html/diamonds-hexbin2-facets-1.svg)
]

---

## Choosing the right color scale

.center[
![](overplotting_files/figure-html/diamonds-hexbin2-facets-1.svg)
]

.absolute-bottom-left[
palette: SunsetDark
]

---

## Choosing the right color scale

.center[
![](overplotting_files/figure-html/diamonds-hexbin3-facets-1.svg)
]

.absolute-bottom-left[
palette: Batlow
]

---

## Choosing the right color scale

.center[
![](overplotting_files/figure-html/diamonds-hexbin4-facets-1.svg)
]

.absolute-bottom-left[
palette: YlOrRd
]

---

## Choosing the right color scale

.center[
![](overplotting_files/figure-html/diamonds-hexbin5-facets-1.svg)
]

.absolute-bottom-left[
palette: BluYl
]

---

## Choosing the right color scale

.center[
![](overplotting_files/figure-html/diamonds-hexbin6-facets-1.svg)
]

.absolute-bottom-left[
palette: Heat
]

---

## Choosing the right color scale

.center[
![](overplotting_files/figure-html/diamonds-hexbin7-facets-1.svg)
]

.absolute-bottom-left[
palette: ag_GrnYl
]

---

## Choosing the right color scale

.center[
![](overplotting_files/figure-html/diamonds-hexbin2-facets-1.svg)
]

.absolute-bottom-left[
palette: SunsetDark
]

[//]: # "segment ends here"

---
class: center middle

## Creating 2D density plots and histograms in R

---

## Contour lines

Data preparation:

.tiny-font[

```r
blue_jays <- read_csv("https://wilkelab.org/SDS375/datasets/blue_jays.csv")
```

```

── Column specification ────────────────────────────────────────────────────────
cols(
  bird_id = col_character(),
  sex = col_character(),
  bill_depth_mm = col_double(),
  bill_width_mm = col_double(),
  bill_length_mm = col_double(),
  head_length_mm = col_double(),
  body_mass_g = col_double(),
  skull_size_mm = col_double()
)
```
]

---

## Contour lines

.tiny-font.pull-left[

```r
blue_jays %>%
  ggplot(aes(body_mass_g, head_length_mm)) +
  geom_point() +
  theme_bw(14)
```
]

.pull-right[
![](overplotting_files/figure-html/scatter-demo-out-1.svg)
]

---

## Contour lines

.tiny-font.pull-left[

```r
blue_jays %>%
  ggplot(aes(body_mass_g, head_length_mm)) +
* geom_density_2d() +
  geom_point() +
  theme_bw(14)
```
]

.pull-right[
![](overplotting_files/figure-html/contour-lines-demo-out-1.svg)
]

---

## Contour lines

.tiny-font.pull-left[

```r
blue_jays %>%
  ggplot(aes(body_mass_g, head_length_mm)) +
* geom_density_2d(bins = 5) +
  geom_point() +
  theme_bw(14)
```
]

.pull-right[
![](overplotting_files/figure-html/contour-lines-demo2-out-1.svg)
]

---

## Contour bands

.tiny-font.width-70.move-up-1em[

```r
ggplot(blue_jays, aes(body_mass_g, head_length_mm)) +
* geom_density_2d_filled(bins = 5) +
  #
  geom_point() +
  theme_bw(14)
```
]

.center[
![](overplotting_files/figure-html/contour-bands-demo-out-1.svg)
]

---

## Contour bands

.tiny-font.width-70.move-up-1em[

```r
ggplot(blue_jays, aes(body_mass_g, head_length_mm)) +
* geom_density_2d_filled(bins = 5, alpha = 0.5) +
  #
  geom_point() +
  theme_bw(14)
```
]

.center[
![](overplotting_files/figure-html/contour-bands-demo2-out-1.svg)
]

---

## Contour bands

.tiny-font.width-70.move-up-1em[

```r
ggplot(blue_jays, aes(body_mass_g, head_length_mm)) +
  geom_density_2d_filled(bins = 5, alpha = 0.5) +
* geom_density_2d(bins = 5, color = "black", size = 0.2) +
  geom_point() +
  theme_bw(14)
```
]

.center[
![](overplotting_files/figure-html/contour-bands-demo3-out-1.svg)
]

---

## 2D histograms

.tiny-font.width-70.move-up-1em[

```r
ggplot(blue_jays, aes(body_mass_g, head_length_mm)) +
* geom_bin2d() +
  theme_bw(14)
```
]

.center[
![](overplotting_files/figure-html/bins2d-demo-out-1.svg)
]

---

## 2D histograms

.tiny-font.width-70.move-up-1em[

```r
ggplot(blue_jays, aes(body_mass_g, head_length_mm)) +
* geom_bin2d(binwidth = c(3, 3)) +
  theme_bw(14)
```
]

.center[
![](overplotting_files/figure-html/bins2d-demo2-out-1.svg)
]

---

## 2D histograms

.tiny-font.width-70.move-up-1em[

```r
ggplot(blue_jays, aes(body_mass_g, head_length_mm)) +
* geom_bin2d(binwidth = c(1, 5)) +
  theme_bw(14)
```
]

.center[
![](overplotting_files/figure-html/bins2d-demo3-out-1.svg)
]

---

## 2D histograms

.tiny-font.width-70.move-up-1em[

```r
ggplot(blue_jays, aes(body_mass_g, head_length_mm)) +
* geom_bin2d(binwidth = c(5, 1)) +
  theme_bw(14)
```
]

.center[
![](overplotting_files/figure-html/bins2d-demo4-out-1.svg)
]

---

## Hex bins

.tiny-font.width-70.move-up-1em[

```r
ggplot(blue_jays, aes(body_mass_g, head_length_mm)) +
* geom_hex() +
  theme_bw(14)
```
]

.center[
![](overplotting_files/figure-html/hex-demo-out-1.svg)
]

---

## Hex bins

.tiny-font.width-70.move-up-1em[

```r
ggplot(blue_jays, aes(body_mass_g, head_length_mm)) +
* geom_hex(bins = 15) +
  theme_bw(14)
```
]

.center[
![](overplotting_files/figure-html/hex-demo2-out-1.svg)
]

---

## Hex bins

.tiny-font.width-70.move-up-1em[

```r
ggplot(blue_jays, aes(body_mass_g, head_length_mm)) +
* geom_hex(bins = 10) +
  theme_bw(14)
```
]

.center[
![](overplotting_files/figure-html/hex-demo3-out-1.svg)
]

[//]: # "segment ends here"

---

## Further reading

- Fundamentals of Data Visualization: [Chapter 18: Handling overlapping points](https://clauswilke.com/dataviz/overlapping-points.html)
- **ggplot2** reference documentation: [`geom_density_2d()`](https://ggplot2.tidyverse.org/reference/geom_density_2d.html)
- **ggplot2** reference documentation: [`geom_bin2d()`](https://ggplot2.tidyverse.org/reference/geom_bin2d.html)
- **ggplot2** reference documentation: [`geom_hex()`](https://ggplot2.tidyverse.org/reference/geom_hex.html)