A reProducible woRkflow with Quarto

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# A reProducible woRkflow with Quarto
.font160[
.SW-greenD[Data visualisations]
]
.font120[
.SW-greenD[*Powerful visualisations with*] .UA-red[*`ggplot2`*]
]
Sven De Maeyer & Tine van Daal

---
class: inverse-green, left

# Overview

.center2[
1. The Grammar of Graphics --- ([click here](#part1))
2. How `ggplot2` works (in a nutshell) --- ([click here](#part2))
3. Visualising a categorical variable --- ([click here](#part3))
4. Visualising a quantitative variable --- ([click here](#part4))
5. Visualising more than one variable --- ([click here](#part5))
]

---
class: inverse-green, center, middle
name: part1

# 1. The Grammar of Graphics

---

## A theoretical approach to visualisation

One system (grammar) of building blocks to create (any) visualisation

At the heart of several modern graphical applications:
  - **ggplot2**
  - Tableau
  - Vega-Lite
  - Observable Plot
  
]

---

## Key idea behind the Grammar of Graphics

.data-theme[.bold[data]]  
  .aes-theme[.bold[aesthetics]]  
  .geom-theme[.bold[geometries]]  
  .facet-theme[.bold[facets]]  
  .stat-theme[.bold[statistics]]  
  .coord-theme[.bold[coordinates]]  
  .theme-theme[.bold[themes]]  
]

.pull-right[
![](https://miro.medium.com/max/1400/1*w1RnmuE7VRK9aCAbtW9KAQ.gif)
.footnote[
_Animation by [Thomas de Beus](https://medium.com/tdebeus/think-about-the-grammar-of-graphics-when-improving-your-graphs-18e3744d8d18)_]
]
<br>  
<br>  
<br>

---
<div class="my-logo-right"> <img src="img/layers of ggplot.png" width="60%"/> </div>

## Grammar of Graphics: .data-theme[data]

Data is not only raw data, but can also be the results from an analysis

|group     |country |gender | mean_age| SD_age| CI_lower| CI_upper|
|:---------|:-------|:------|--------:|------:|--------:|--------:|
|BE Male   |BE      |Male   |       39|   11.0|    17.44|    60.56|
|BE Female |BE      |Female |       41|   13.2|    15.13|    66.87|
|BE Other  |BE      |Other  |       36|    8.2|    19.93|    52.07|
|NL Male   |NL      |Male   |       37|   12.0|    13.48|    60.52|
|NL Female |NL      |Female |       36|   14.0|     8.56|    63.44|
|NL Other  |NL      |Other  |       31|    7.2|    16.89|    45.11|

<br>

Data has to be 'tidy'

---
<div class="my-logo-right"> <img src="img/layers of ggplot.png" width="60%"/> </div>

## Grammar of Graphics: .aes-theme[aesthetics]

.pull-left[
- Describe how variables in data are *mapped* to visual properties. For example: 
  - variables mapped on x- and y-axis
  - variable that defines color or size of points
  - ...
  
- Change appearances of aesthetics using `scales`  
]
.pull-right[
<img src="slides_part-4_files/figure-html/unnamed-chunk-4-1.png" alt="" width="720" style="display: block; margin: auto;" />
]

---
<div class="my-logo-right"> <img src="img/layers of ggplot.png" width="60%"/> </div>

## Grammar of Graphics: .geom-theme[geometries]

.pull-left[
- Geometrical shapes at the heart of visualisation. For example:
  - boxplot
  - line
  - ...
]

.pull-right[
<img src="slides_part-4_files/figure-html/unnamed-chunk-5-1.png" alt="" width="720" style="display: block; margin: auto;" />
]
---
<div class="my-logo-right"> <img src="img/layers of ggplot.png" width="60%"/> </div>

## Grammar of Graphics: .facet-theme[facets]

- Define how much panels are shown and how they are arranged
]
.pull-right[
<img src="slides_part-4_files/figure-html/unnamed-chunk-6-1.png" alt="" width="720" style="display: block; margin: auto;" />

]

---
<div class="my-logo-right"> <img src="img/layers of ggplot.png" width="60%"/> </div>

## Grammar of Graphics: .stat-theme[statistics]

.pull-left[
- Data is `tidy`, but still in need of some statistical calculations. For example: 
  - Calculate descriptive statistics to create a boxplot
  - Estimate a linear (or other) model to draw a regression line in a scatter plot

- Often implicit done by `ggplot2`
]
.pull-right[
<img src="slides_part-4_files/figure-html/unnamed-chunk-7-1.png" alt="" width="720" style="display: block; margin: auto;" />
]

---

## Grammar of Graphics 'works' a bit like *a cake* 
.pull-left[
<br>   
<br>    
1. Start by setting up the *foundation* with **`ggplot()`**

2. Specify *ingredients* (variables) with **`aes()`** and a *flavour* with  **`scales`**

3. Create *layers* to plot with **`geoms`**

4. *Style* the cake with **`theme`**  
]

.pull-right[
<img src="img/like_cake.png" alt="" width="70%" height="70%" />
]
.footnote[
_Slide by [Tanya Shapiro](https://www.tanyashapiro.com/)_
]

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class: inverse-green, center, middle
name: part2

# 2. How `ggplot2` works (in a nutshell)

---
<div class="my-logo-right"> <img src="img/palmerpenguins_hex.png" width="80%"/> </div>

## Time to get the penguins in...

Nice data set that can be used in R 
.font60[(Source: https://allisonhorst.github.io/palmerpenguins/articles/intro.html)]

``` r
install.packages("palmerpenguins")
library(palmerpenguins)
data("penguins")
```

<p align="right">.footnotesize[.SW-greenD[*Artwork by @allison_horst*]] </p>

---
<div class="my-logo-right"> <img src="img/palmerpenguins_hex.png" width="80%"/> </div>

## Time to get the penguins in...

Table: Random sample of 10 observations from the Palmer Pinguins dataset

|species   |island | bill_length_mm| bill_depth_mm| flipper_length_mm| body_mass_g|sex    | year|
|:---------|:------|--------------:|-------------:|-----------------:|-----------:|:------|----:|
|Gentoo    |Biscoe |           47.5|          14.2|               209|        4600|female | 2008|
|Chinstrap |Dream  |           50.5|          19.6|               201|        4050|male   | 2007|
|Gentoo    |Biscoe |           46.9|          14.6|               222|        4875|female | 2009|
|Adelie    |Biscoe |           42.2|          19.5|               197|        4275|male   | 2009|
|Adelie    |Biscoe |           40.6|          18.6|               183|        3550|male   | 2007|
|Gentoo    |Biscoe |           46.2|          14.4|               214|        4650|NA     | 2008|
|Gentoo    |Biscoe |           45.5|          13.9|               210|        4200|female | 2008|
|Adelie    |Biscoe |           40.1|          18.9|               188|        4300|male   | 2008|
|Chinstrap |Dream  |           52.7|          19.8|               197|        3725|male   | 2007|
|Adelie    |Biscoe |           37.7|          18.7|               180|        3600|male   | 2007|

---

## The basics of .UA-red[`ggplot2`]: *data & aesthetics*

``` r
Plot <- ggplot(

## Step 1: data
  data = penguins,
  
  ## Step 2: specify aesthetics (mapping)
  aes(
    x = flipper_length_mm,
    y = body_mass_g)
)

Plot
```
]

.pull-right[
<img src="slides_part-4_files/figure-html/unnamed-chunk-13-1.png" alt="" width="360" style="display: block; margin: auto;" />
]

---

## The basics of .UA-red[`ggplot2`]: *geometry*

``` r
Plot <- ggplot(

## Step 1: data
  data = penguins,
  
  ## Step 2: specify aesthetics (mapping)
  aes(
    x = flipper_length_mm,
    y = body_mass_g)
) +
  ## Step 3: add geometry
  geom_point()

Plot
```
]

.pull-right[
<img src="slides_part-4_files/figure-html/unnamed-chunk-15-1.png" alt="" width="360" style="display: block; margin: auto;" />
]

Not every component of the *Grammar of Graphics* needs to be defined. Several components have *default* values that are applied automatically.

---

## The basics of .UA-red[`ggplot2`]: *facets*

``` r
Plot <- ggplot(

## Step 1: data
  data = penguins,
  
  ## Step 2: specify aesthetics (mapping)
  aes(
    x = flipper_length_mm,
    y = body_mass_g)
) +
  ## Step 3: add geometry
  geom_point() +
  
  ## Step 4: define facets
  facet_wrap(~species)

Plot
```
]

.pull-right[
<img src="slides_part-4_files/figure-html/unnamed-chunk-17-1.png" alt="" width="360" style="display: block; margin: auto;" />
]

---

## The basics of .UA-red[`ggplot2`]: *theme*

``` r
Plot <- ggplot(

Plot
```
]

.pull-right[
<img src="slides_part-4_files/figure-html/unnamed-chunk-19-1.png" alt="" width="360" style="display: block; margin: auto;" />
]

---

## Building a visualisation by adding layers ...

---

## Several .UA-red[`geom_*`] options...

.center[The *cheatsheet*:
https://github.com/rstudio/cheatsheets/blob/main/data-visualization-2.1.pdf]

---
class: inverse-green, center, middle
name: part3

# 3. Visualising a categorical variable

---

## Visualising a categorical variable?

Can you think of some?]

--
.right-column[
<img src="img/data_to_viz.png" alt="" width="70%" height="70%" style="display: block; margin: auto;" />
<br>   
<br>  
.center[.font100[
*Have a look at [data to viz.com](https://www.data-to-viz.com)*
]
]
]

---

## Creating a barplot with .UA-red[`geom_bar()`] or .UA-red[`geom_col()`]

.pull-left[
**`geom_bar()`**
<img src="slides_part-4_files/figure-html/unnamed-chunk-23-1.png" alt="" width="216" style="display: block; margin: auto auto auto 0;" />
]
.pull-right[
**`geom_col()`**
<img src="slides_part-4_files/figure-html/unnamed-chunk-24-1.png" alt="" width="216" style="display: block; margin: auto auto auto 0;" />
]

--
.pull-left[.footnotesize[

``` r
ggplot(
  data = penguins,
  aes(
    x = species
    )
  ) +
  geom_bar()

# stat_count() does the counting automatically 
```
]
]
.pull-right[.footnotesize[

``` r
count_data <- 
  penguins %>%
  count(species, name = 'count')

ggplot(
  data = count_data,
  aes(
    x = species,
    y = count
    )
  ) +
  geom_col()
```
]
]

---