Assembling Your Dream Theme

.title[
# Assembling Your Dream Theme
]
.subtitle[
## Crafting Custom Designs in ggplot2 for Effortless Visualisation Enhancement
]
.author[
### Long Nguyen & Andreas Neumann
]
.date[
### 2024-05-28
]

---

## Why create ggplot2 themes and colour scales?

- What Andreas said

- Save time

![Meme video "R users explaining why spending 45 minutes customizing a ggplot is better than to accomplish the same result in 2 minutes in Excel". Top post of reddit.com/r/rstats.](img/r-rstats-ggplot2-videomeme.png)

---

## Prerequisites

.pull-left.w33[
- {tidyverse}, which includes (among others):

- {ggplot2}
    
    - [{ragg}](https://www.tidyverse.org/tags/ragg/): high-quality graphic backend for R
    
    - [{systemfonts}](https://www.tidyverse.org/tags/systemfonts/): finds the correct font file for a specific font and style (we'll see it in action later)
]

.pull-right.w67.center[
- In RStudio **Global Options** &rarr; **Graphics**, choose **AGG** as Backend

![](img/rstudio-agg-backend.png)
]

---

```r
*library(ggplot2)
```
]
 
.panel2-penguins-auto[

]

---
count: false

```r
library(ggplot2)
*library(palmerpenguins)
```
]
 
.panel2-penguins-auto[

]

---
count: false

```r
library(ggplot2)
library(palmerpenguins)

*p <- ggplot(
* data = penguins,
* aes(bill_length_mm, bill_depth_mm)
*) 
```
]
 
.panel2-penguins-auto[

]

---
count: false

```r
library(ggplot2)
library(palmerpenguins)

p <- ggplot(
  data = penguins,
  aes(bill_length_mm, bill_depth_mm)
) +
* geom_point(
*   aes(colour = species),
*   size = 2
* )
```
]
 
.panel2-penguins-auto[

]

---
count: false

```r
library(ggplot2)
library(palmerpenguins)

p <- ggplot(
  data = penguins,
  aes(bill_length_mm, bill_depth_mm)
) +
  geom_point(
    aes(colour = species),
    size = 2
  ) +
* labs(
*   title = "Title",
*   subtitle = "Subtitle",
*   caption = "Caption"
* )
```
]
 
.panel2-penguins-auto[

]

---
count: false

```r
library(ggplot2)
library(palmerpenguins)

p <- ggplot(
  data = penguins,
  aes(bill_length_mm, bill_depth_mm)
) +
  geom_point(
    aes(colour = species),
    size = 2
  ) +
  labs(
    title = "Title",
    subtitle = "Subtitle",
    caption = "Caption"
  )

*p 
```
]
 
.panel2-penguins-auto[
<img src="2024-05-28-correlaid-ggplot2-theming_files/figure-html/penguins_auto_06_output-1.png" alt="Scatterplot of bill length by bill depth of 3 penguin species" width="96%" style="display: block; margin: auto;" />
]

---

.pull-left.w42[
<br>
> The easiest way to extend ggplot2 is to make a new theme.
>
> .small[— Thomas Lin Pedersen, [*Extending your ability to extend ggplot2*](https://www.rstudio.com/resources/rstudioconf-2020/extending-your-ability-to-extend-ggplot2/)]
]

.pull-right.w55[
![Screenshot from Thomas Lin Pedersen's talk "Extending your ability to extend ggplot2" at RStudio::conf 2020. Extension points for ggplot2, sorted by increasing complexity. Custom themes and scales are the easiest to write.](img/extending-ggplot2-ss.png)
]

---
class: inverse center middle

# Themes

---
class: inverse center middle

## Arguments of the `theme()` function

---
class: middle

- Familiarise yourself with the [`theme()` function documentation](https://ggplot2.tidyverse.org/reference/theme.html)

```r
?theme
```

---

```r
p
```
]
 
.panel2-theme-interactive-non_seq[
<img src="2024-05-28-correlaid-ggplot2-theming_files/figure-html/theme-interactive_non_seq_01_output-1.png" alt="Modifying the theme of a plot interactively by calling theme_minimal() and theme()" width="96%" style="display: block; margin: auto;" />
]

---
count: false

```r
p +
* theme_minimal(
* )
```
]
 
.panel2-theme-interactive-non_seq[
<img src="2024-05-28-correlaid-ggplot2-theming_files/figure-html/theme-interactive_non_seq_02_output-1.png" alt="Modifying the theme of a plot interactively by calling theme_minimal() and theme()" width="96%" style="display: block; margin: auto;" />
]

---
count: false

```r
p +
  theme_minimal(
*   base_size = 14,
  )
```
]
 
.panel2-theme-interactive-non_seq[
<img src="2024-05-28-correlaid-ggplot2-theming_files/figure-html/theme-interactive_non_seq_03_output-1.png" alt="Modifying the theme of a plot interactively by calling theme_minimal() and theme()" width="96%" style="display: block; margin: auto;" />
]

---
count: false

```r
p +
  theme_minimal(
    base_size = 14,
*   base_family = "Atkinson Hyperlegible"
  )
```
]
 
.panel2-theme-interactive-non_seq[
<img src="2024-05-28-correlaid-ggplot2-theming_files/figure-html/theme-interactive_non_seq_04_output-1.png" alt="Modifying the theme of a plot interactively by calling theme_minimal() and theme()" width="96%" style="display: block; margin: auto;" />
]

---
count: false

```r
p +
  theme_minimal(
    base_size = 14,
    base_family = "Atkinson Hyperlegible"
  ) +
* theme(
*   legend.position = "top",
* )
```
]
 
.panel2-theme-interactive-non_seq[
<img src="2024-05-28-correlaid-ggplot2-theming_files/figure-html/theme-interactive_non_seq_05_output-1.png" alt="Modifying the theme of a plot interactively by calling theme_minimal() and theme()" width="96%" style="display: block; margin: auto;" />
]

---
count: false

```r
p +
  theme_minimal(
    base_size = 14,
    base_family = "Atkinson Hyperlegible"
  ) +
  theme(
    legend.position = "top",
*   plot.title.position = "plot",
  )
```
]
 
.panel2-theme-interactive-non_seq[
<img src="2024-05-28-correlaid-ggplot2-theming_files/figure-html/theme-interactive_non_seq_06_output-1.png" alt="Modifying the theme of a plot interactively by calling theme_minimal() and theme()" width="96%" style="display: block; margin: auto;" />
]

---
count: false

```r
p +
  theme_minimal(
    base_size = 14,
    base_family = "Atkinson Hyperlegible"
  ) +
  theme(
    legend.position = "top",
    plot.title.position = "plot",
*   plot.title = element_text(
*     size = rel(1.5)
*   ),
  )
```
]
 
.panel2-theme-interactive-non_seq[
<img src="2024-05-28-correlaid-ggplot2-theming_files/figure-html/theme-interactive_non_seq_07_output-1.png" alt="Modifying the theme of a plot interactively by calling theme_minimal() and theme()" width="96%" style="display: block; margin: auto;" />
]

---
count: false

```r
p +
  theme_minimal(
    base_size = 14,
    base_family = "Atkinson Hyperlegible"
  ) +
  theme(
    legend.position = "top",
    plot.title.position = "plot",
    plot.title = element_text(
      size = rel(1.5)
    ),
*   panel.grid.minor = element_blank()
  )
```
]
 
.panel2-theme-interactive-non_seq[
<img src="2024-05-28-correlaid-ggplot2-theming_files/figure-html/theme-interactive_non_seq_08_output-1.png" alt="Modifying the theme of a plot interactively by calling theme_minimal() and theme()" width="96%" style="display: block; margin: auto;" />
]

---
class: inverse center middle

## Writing a theme function

---

We can simply pack the regular R code for theming into a function and save ourselves from mindless repeating or copy-pasting!

```r
my_theme <- function(base_size = 14,
                     base_family = "Atkinson Hyperlegible") {

theme_minimal(base_size = base_size, base_family = base_family) +
    theme(
      legend.position = "top",
      plot.title.position = "plot",
      plot.title = element_text(size = rel(1.5)),
      panel.grid.minor = element_blank()
    )

}
```

---

```r
p
```
]
 
.panel2-use-mytheme-non_seq[
<img src="2024-05-28-correlaid-ggplot2-theming_files/figure-html/use-mytheme_non_seq_01_output-1.png" alt="Applying the theme defined in the my_theme() function to a plot" width="96%" style="display: block; margin: auto;" />
]

---
count: false

```r
p +
* my_theme(
* )
```
]
 
.panel2-use-mytheme-non_seq[
<img src="2024-05-28-correlaid-ggplot2-theming_files/figure-html/use-mytheme_non_seq_02_output-1.png" alt="Applying the theme defined in the my_theme() function to a plot" width="96%" style="display: block; margin: auto;" />
]

---
count: false

```r
p +
  my_theme(
*   base_size = 20,
  )
```
]
 
.panel2-use-mytheme-non_seq[
<img src="2024-05-28-correlaid-ggplot2-theming_files/figure-html/use-mytheme_non_seq_03_output-1.png" alt="Applying the theme defined in the my_theme() function to a plot" width="96%" style="display: block; margin: auto;" />
]

---
count: false

```r
p +
  my_theme(
    base_size = 20,
*   base_family = "Menlo"
  )
```
]
 
.panel2-use-mytheme-non_seq[
<img src="2024-05-28-correlaid-ggplot2-theming_files/figure-html/use-mytheme_non_seq_04_output-1.png" alt="Applying the theme defined in the my_theme() function to a plot" width="96%" style="display: block; margin: auto;" />
]

---
count: false

```r
p +
  my_theme(
    base_size = 20,
    base_family = "Menlo"
  ) +
* theme(
*   plot.title = element_text(
*     face = "bold"
*   )
* )
```
]
 
.panel2-use-mytheme-non_seq[
<img src="2024-05-28-correlaid-ggplot2-theming_files/figure-html/use-mytheme_non_seq_05_output-1.png" alt="Applying the theme defined in the my_theme() function to a plot" width="96%" style="display: block; margin: auto;" />
]

---
class: inverse center middle

## More customisations for your theme function<br>(on top of passing arguments to `theme()`)

---

### Example: Showing/hiding gridlines more easily

(Inspired by [hrbrthemes](https://github.com/hrbrmstr/hrbrthemes))

```r
my_theme <- function(base_size = 14,
                     base_family = "Atkinson Hyperlegible",
*                    grid = "XY") {

t <- theme_minimal(base_size = base_size, base_family = base_family) +
    theme(
      legend.position = "top",
      plot.title.position = "plot",
      plot.title = element_text(size = rel(1.5))
    )
  
* if (!grepl("X", grid)) t <- t + theme(panel.grid.major.x = element_blank())
* if (!grepl("Y", grid)) t <- t + theme(panel.grid.major.y = element_blank())
* if (!grepl("x", grid)) t <- t + theme(panel.grid.minor.x = element_blank())
* if (!grepl("y", grid)) t <- t + theme(panel.grid.minor.y = element_blank())
* t

}
```

---

```r
p +
* my_theme()
```
]
 
.panel2-use-mytheme-grid-rotate[
<img src="2024-05-28-correlaid-ggplot2-theming_files/figure-html/use-mytheme-grid_rotate_01_output-1.png" alt="Applying the theme defined in the my_theme() function to a plot – now with the grid argument to show/hide gridlines more easily" width="96%" style="display: block; margin: auto;" />
]

---
count: false

```r
p +
* my_theme(grid = "Y")
```
]
 
.panel2-use-mytheme-grid-rotate[
<img src="2024-05-28-correlaid-ggplot2-theming_files/figure-html/use-mytheme-grid_rotate_02_output-1.png" alt="Applying the theme defined in the my_theme() function to a plot – now with the grid argument to show/hide gridlines more easily" width="96%" style="display: block; margin: auto;" />
]

---
count: false

```r
p +
* my_theme(grid = "Xx")
```
]
 
.panel2-use-mytheme-grid-rotate[
<img src="2024-05-28-correlaid-ggplot2-theming_files/figure-html/use-mytheme-grid_rotate_03_output-1.png" alt="Applying the theme defined in the my_theme() function to a plot – now with the grid argument to show/hide gridlines more easily" width="96%" style="display: block; margin: auto;" />
]

---
count: false

```r
p +
* my_theme(grid = "xy")
```
]
 
.panel2-use-mytheme-grid-rotate[
<img src="2024-05-28-correlaid-ggplot2-theming_files/figure-html/use-mytheme-grid_rotate_04_output-1.png" alt="Applying the theme defined in the my_theme() function to a plot – now with the grid argument to show/hide gridlines more easily" width="96%" style="display: block; margin: auto;" />
]

---
class: inverse center middle

## Making sure that fonts work

---

Applying an unavailable font just quietly falls back to default font (or throws errors depending on your OS and graphics device).

.pull-left.w41[

```r
p +
  my_theme(
    base_family = "Expensive Designer Font"
  )
```
]

.pull-right.w57[
<img src="2024-05-28-correlaid-ggplot2-theming_files/figure-html/unnamed-chunk-1-1.png" alt="Applying an unavailable font just quietly falls back to default font." width="96%" style="display: block; margin: auto;" />
]

---

We can control this behaviour and make it explicit using `systemfonts::system_fonts()`:

```r
my_theme <- function(base_size = 14,
                     base_family = "Atkinson Hyperlegible",
                     grid = "XY") {

if (!(base_family %in% systemfonts::system_fonts()$family)) {
    message("Font '", base_family, "' not installed.\nUsing system's default font.")
    base_family <- ""
  }
  
  [...]

}
```

---

.pull-left.w41[

```r
p +
  my_theme(
    base_family = "Expensive Designer Font"
  )
```
]

.pull-right.w57[

```
#> Font 'Expensive Designer Font' not installed.
#> Using system's default font.
```

<img src="2024-05-28-correlaid-ggplot2-theming_files/figure-html/unnamed-chunk-2-1.png" alt="Applying an unavailable font throws a message and falls back to default font" width="96%" style="display: block; margin: auto;" />
]

---
class: inverse center middle

## Enabling extra font features

---
layout: true

### Example: tabular numbers (or monospaced digits)

---

Tabular numbers are monospaced, which keeps their sizes consistent for display on axes

![](https://blog.datawrapper.de/wp-content/uploads/2022/08/Artboard-1-copy-180-1.png)

---

- Solution 1: choose fonts with tabular numbers enabled by default

---

- Solution 2: use {systemfonts} enable tabular numbers (if your font has this feature and it is not enabled by default)

```r
library(systemfonts)

register_font(
  "Atkinson Hyperlegible tnum",
  "/path/to/Atkinson-Hyperlegible.otf",
  features = font_feature(numbers = "tabular")
)
```

The newly registered font can be found in `registry_fonts()` (instead of `system_fonts`). New fallback condition:

```r
    !(base_family %in% c(
      systemfonts::system_fonts()$family,
      systemfonts::registry_fonts()$family
    ))
```

---

```r
p +
  my_theme(base_family =
*   "Atkinson Hyperlegible",
  )
```
]
 
.panel2-tnum-fonts-rotate[
<img src="2024-05-28-correlaid-ggplot2-theming_files/figure-html/tnum-fonts_rotate_01_output-1.png" alt="Applying the theme defined in the my_theme() function to a plot – now with the grid argument to show/hide gridlines more easily" width="96%" style="display: block; margin: auto;" />
]

---
count: false

```r
p +
  my_theme(base_family =
*   "Menlo",
  )
```
]
 
.panel2-tnum-fonts-rotate[
<img src="2024-05-28-correlaid-ggplot2-theming_files/figure-html/tnum-fonts_rotate_02_output-1.png" alt="Applying the theme defined in the my_theme() function to a plot – now with the grid argument to show/hide gridlines more easily" width="96%" style="display: block; margin: auto;" />
]

---
count: false

```r
p +
  my_theme(base_family =
*   "Atkinson Hyperlegible tnum",
  )
```
]
 
.panel2-tnum-fonts-rotate[
<img src="2024-05-28-correlaid-ggplot2-theming_files/figure-html/tnum-fonts_rotate_03_output-1.png" alt="Applying the theme defined in the my_theme() function to a plot – now with the grid argument to show/hide gridlines more easily" width="96%" style="display: block; margin: auto;" />
]

---
count: false

```r
p +
  my_theme(base_family =
*   "Atkinson Hyperlegible",
  )
```
]
 
.panel2-tnum-fonts-rotate[
<img src="2024-05-28-correlaid-ggplot2-theming_files/figure-html/tnum-fonts_rotate_04_output-1.png" alt="Applying the theme defined in the my_theme() function to a plot – now with the grid argument to show/hide gridlines more easily" width="96%" style="display: block; margin: auto;" />
]

---
class: middle
layout: false

Check out the `theme_correlaid()` function:

https://github.com/CorrelAid/correltools/blob/main/R/ggplot-theme.R

---
class: inverse center middle

## Hands-on session

Create your own theme function! 💻🚀

---
class: inverse center middle

# Colour scales

---

## Colour palettes

#### Sequential palette based on CorrelAid logo

#### Sequential palette based on CorrelAidX logo

#### Qualitative palette

#### Greyscale palette

<span class="color-preview" style="background-color: #3C3C3BFF"></span><code>#3c3c3b</code><span class="color-preview" style="background-color: #727375FF"></span><code>#727375</code><span class="color-preview" style="background-color: #9E9FA3FF"></span><code>#9e9fa3</code><span class="color-preview" style="background-color: #CDCED0FF"></span><code>#cdced0</code>

---

## Steps to create a colour scale function

1. Save the colour palette(s) as charactor vector(s)

1. Create a [function factory](https://adv-r.hadley.nz/function-factories.html) that outputs a palette with the desired number of colours

1. Create a scale function by wrapping a scale constructor (e.g., `ggplot2::continuous_scale()`) around the palette function in step 2

---

### Step 1

```r
correlaid_colours <- list(
  gradient = c("#bcd259", "#6fa07f", "#214f8f"),
  gradient_x = c("#f04451", "#85638c", "#214f8f"),
  qualitative = c("#96c342", "#3863a2", "#f04451"),
  grey = c("#3c3c3b", "#727375", "#9e9fa3", "#cdced0")
)
```

---

### Step 2

```r
correlaid_pal <- function(direction = 1, option = "qualitative") {
  stopifnot(length(option) == 1 && option %in% names(correlaid_colours))

cols <- correlaid_colours[[option]]

function(n) {
    cols <- grDevices::colorRampPalette(cols, space = "Lab", interpolate = "spline")(n)

if (direction < 0) rev(cols) else cols
  }
}
```

- Takes two argument: `option` (which colour palette?) and `direction` (revert or not?)

- Returns a function that takes the desired number of colours (e.g., number of categories) and produces as many colours by interpolation

---

### Step 2

```r
correlaid_pal()(n = 2)
```

```r
correlaid_pal(option = "gradient")(n = 7)
```

```r
correlaid_pal(direction = -1, option = "gradient")(n = 7)
```

---

### Step 3

```r
scale_colour_correlaid_d <- function(direction = 1,
                                     option = "qualitative",
                                     ...) {
  ggplot2::discrete_scale(
    aesthetics = "colour",
    scale_name = "correlaid",
    palette = correlaid_pal(direction, option),
    ...
  )
}
```

- Same for `scale_fill_correlaid_d`

---

### Step 3

```r
scale_colour_correlaid_c <- function(direction = 1,
                                     option = "gradient",
                                     guide = "colourbar",
                                     ...) {
  ggplot2::continuous_scale(
    aesthetics = "colour",
    scale_name = "correlaid",
    palette = scales::gradient_n_pal(correlaid_pal(direction, option)(8)),
    guide = guide,
    ...
  )
}
```

---

.pull-left.w39[

```r
p +
  scale_colour_correlaid_d()
```
]

.pull-right.w59[
<img src="2024-05-28-correlaid-ggplot2-theming_files/figure-html/unnamed-chunk-9-1.png" alt="Applying the defined colour scales functions to a plot" width="96%" style="display: block; margin: auto;" />
]

---

As expected, applying a continuous colour scale to a discrete variable throws an error:

```r
p +
  scale_colour_correlaid_c()
```

```
#> Error in `scale_colour_correlaid_c()`:
#> ! Discrete values supplied to continuous scale.
#> ℹ Example values: Adelie, Adelie, Adelie, Adelie, and Adelie
```

---
class: middle

Check out the `scale_*_correlaid_*()` functions:

https://github.com/CorrelAid/correltools/blob/main/R/ggplot-scales.R

---

## References and further resources

- https://ggplot2-book.org/extensions.html

- https://themockup.blog/posts/2020-12-26-creating-and-using-custom-ggplot2-themes/

- https://www.garrickadenbuie.com/blog/custom-discrete-color-scales-for-ggplot2/

- https://cedricscherer.netlify.app/2019/08/05/a-ggplot2-tutorial-for-beautiful-plotting-in-r/

- https://socviz.co/refineplots.html

---

# Thank you!

.small[
<svg viewBox="0 0 448 512" style="height:1em;position:relative;display:inline-block;top:.1em;" xmlns="http://www.w3.org/2000/svg">  <path d="M400 32H48C21.5 32 0 53.5 0 80v352c0 26.5 21.5 48 48 48h352c26.5 0 48-21.5 48-48V80c0-26.5-21.5-48-48-48zm-48.9 158.8c.2 2.8.2 5.7.2 8.5 0 86.7-66 186.6-186.6 186.6-37.2 0-71.7-10.8-100.7-29.4 5.3.6 10.4.8 15.8.8 30.7 0 58.9-10.4 81.4-28-28.8-.6-53-19.5-61.3-45.5 10.1 1.5 19.2 1.5 29.6-1.2-30-6.1-52.5-32.5-52.5-64.4v-.8c8.7 4.9 18.9 7.9 29.6 8.3a65.447 65.447 0 0 1-29.2-54.6c0-12.2 3.2-23.4 8.9-33.1 32.3 39.8 80.8 65.8 135.2 68.6-9.3-44.5 24-80.6 64-80.6 18.9 0 35.9 7.9 47.9 20.7 14.8-2.8 29-8.3 41.6-15.8-4.9 15.2-15.2 28-28.8 36.1 13.2-1.4 26-5.1 37.8-10.2-8.9 13.1-20.1 24.7-32.9 34z"></path></svg> <svg viewBox="0 0 448 512" style="height:1em;position:relative;display:inline-block;top:.1em;" xmlns="http://www.w3.org/2000/svg">  <path d="M400 32H48C21.5 32 0 53.5 0 80v352c0 26.5 21.5 48 48 48h352c26.5 0 48-21.5 48-48V80c0-26.5-21.5-48-48-48zM277.3 415.7c-8.4 1.5-11.5-3.7-11.5-8 0-5.4.2-33 .2-55.3 0-15.6-5.2-25.5-11.3-30.7 37-4.1 76-9.2 76-73.1 0-18.2-6.5-27.3-17.1-39 1.7-4.3 7.4-22-1.7-45-13.9-4.3-45.7 17.9-45.7 17.9-13.2-3.7-27.5-5.6-41.6-5.6-14.1 0-28.4 1.9-41.6 5.6 0 0-31.8-22.2-45.7-17.9-9.1 22.9-3.5 40.6-1.7 45-10.6 11.7-15.6 20.8-15.6 39 0 63.6 37.3 69 74.3 73.1-4.8 4.3-9.1 11.7-10.6 22.3-9.5 4.3-33.8 11.7-48.3-13.9-9.1-15.8-25.5-17.1-25.5-17.1-16.2-.2-1.1 10.2-1.1 10.2 10.8 5 18.4 24.2 18.4 24.2 9.7 29.7 56.1 19.7 56.1 19.7 0 13.9.2 36.5.2 40.6 0 4.3-3 9.5-11.5 8-66-22.1-112.2-84.9-112.2-158.3 0-91.8 70.2-161.5 162-161.5S388 165.6 388 257.4c.1 73.4-44.7 136.3-110.7 158.3zm-98.1-61.1c-1.9.4-3.7-.4-3.9-1.7-.2-1.5 1.1-2.8 3-3.2 1.9-.2 3.7.6 3.9 1.9.3 1.3-1 2.6-3 3zm-9.5-.9c0 1.3-1.5 2.4-3.5 2.4-2.2.2-3.7-.9-3.7-2.4 0-1.3 1.5-2.4 3.5-2.4 1.9-.2 3.7.9 3.7 2.4zm-13.7-1.1c-.4 1.3-2.4 1.9-4.1 1.3-1.9-.4-3.2-1.9-2.8-3.2.4-1.3 2.4-1.9 4.1-1.5 2 .6 3.3 2.1 2.8 3.4zm-12.3-5.4c-.9 1.1-2.8.9-4.3-.6-1.5-1.3-1.9-3.2-.9-4.1.9-1.1 2.8-.9 4.3.6 1.3 1.3 1.8 3.3.9 4.1zm-9.1-9.1c-.9.6-2.6 0-3.7-1.5s-1.1-3.2 0-3.9c1.1-.9 2.8-.2 3.7 1.3 1.1 1.5 1.1 3.3 0 4.1zm-6.5-9.7c-.9.9-2.4.4-3.5-.6-1.1-1.3-1.3-2.8-.4-3.5.9-.9 2.4-.4 3.5.6 1.1 1.3 1.3 2.8.4 3.5zm-6.7-7.4c-.4.9-1.7 1.1-2.8.4-1.3-.6-1.9-1.7-1.5-2.6.4-.6 1.5-.9 2.8-.4 1.3.7 1.9 1.8 1.5 2.6z"></path></svg> [long39ng](https://github.com/long39ng)  
<svg viewBox="0 0 496 512" style="height:1em;position:relative;display:inline-block;top:.1em;" xmlns="http://www.w3.org/2000/svg">  <path d="M336.5 160C322 70.7 287.8 8 248 8s-74 62.7-88.5 152h177zM152 256c0 22.2 1.2 43.5 3.3 64h185.3c2.1-20.5 3.3-41.8 3.3-64s-1.2-43.5-3.3-64H155.3c-2.1 20.5-3.3 41.8-3.3 64zm324.7-96c-28.6-67.9-86.5-120.4-158-141.6 24.4 33.8 41.2 84.7 50 141.6h108zM177.2 18.4C105.8 39.6 47.8 92.1 19.3 160h108c8.7-56.9 25.5-107.8 49.9-141.6zM487.4 192H372.7c2.1 21 3.3 42.5 3.3 64s-1.2 43-3.3 64h114.6c5.5-20.5 8.6-41.8 8.6-64s-3.1-43.5-8.5-64zM120 256c0-21.5 1.2-43 3.3-64H8.6C3.2 212.5 0 233.8 0 256s3.2 43.5 8.6 64h114.6c-2-21-3.2-42.5-3.2-64zm39.5 96c14.5 89.3 48.7 152 88.5 152s74-62.7 88.5-152h-177zm159.3 141.6c71.4-21.2 129.4-73.7 158-141.6h-108c-8.8 56.9-25.6 107.8-50 141.6zM19.3 352c28.6 67.9 86.5 120.4 158 141.6-24.4-33.8-41.2-84.7-50-141.6h-108z"></path></svg> https://lo-ng.netlify.app/
<svg viewBox="0 0 512 512" style="height:1em;position:relative;display:inline-block;top:.1em;" xmlns="http://www.w3.org/2000/svg">  <path d="M464 64H48C21.49 64 0 85.49 0 112v288c0 26.51 21.49 48 48 48h416c26.51 0 48-21.49 48-48V112c0-26.51-21.49-48-48-48zm0 48v40.805c-22.422 18.259-58.168 46.651-134.587 106.49-16.841 13.247-50.201 45.072-73.413 44.701-23.208.375-56.579-31.459-73.413-44.701C106.18 199.465 70.425 171.067 48 152.805V112h416zM48 400V214.398c22.914 18.251 55.409 43.862 104.938 82.646 21.857 17.205 60.134 55.186 103.062 54.955 42.717.231 80.509-37.199 103.053-54.947 49.528-38.783 82.032-64.401 104.947-82.653V400H48z"></path></svg> nguyen@dezim-institut.de

<br>

.footnote[
.smaller[View the slides at https://lo-ng.netlify.app/slides/2024-05-28-correlaid-ggplot2-theming]
]