INPUT - OUTPUT Workshop R & RStudio

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<div class="my-logo-left"> <img src="img/UA-eng-hor-1-RGB.jpg" width="110%"/> </div>
<div class="my-logo-right"> <img src="img/logo_VLHORA.svg" width="110%"/> </div>

# INPUT - OUTPUT Workshop R & RStudio
.font160[
.SW-greenD[Deel 4]
]
.font120[
.SW-greenD[*Krachtige visualisaties met*] .UA-red[*`ggplot2`*]
]
Sven De Maeyer

.font80[
.UA-red[
03/05/2022
]
]

---
class: inverse-green, left

# Overzicht

.center2[
- Eenvoudige plotjes in R --- ([doorklikken](#part1))
- Grammar of graphics --- ([doorklikken](#part2))
- Hoe werkt `ggplot2`? --- ([doorklikken](#part3))
- Categorische variabelen visualiseren --- ([doorklikken](#part4))
- Kwantitatieve variabelen visualiseren --- ([doorklikken](#part5))
- Samenhang visualiseren --- ([doorklikken](#part6))
]

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

# 1. Eenvoudige plotjes in R

---

## Plotjes uit .UA-red[`base`]

De generieke .UA-red[`plot()`] functie

```r
plot(RIASEC$age)
```

<img src="Slides_Deel4_files/figure-html/unnamed-chunk-2-1.png" width="288" />

---

## Plotjes uit .UA-red[`base`]

De generieke .UA-red[`plot()`] functie

```r
plot(table(RIASEC$Geslacht))
```

<img src="Slides_Deel4_files/figure-html/unnamed-chunk-3-1.png" width="288" />

---

## Plotjes uit .UA-red[`base`]

De generieke .UA-red[`plot()`] functie

```r
plot(RIASEC$age, RIASEC$Conventional)
```

<img src="Slides_Deel4_files/figure-html/unnamed-chunk-4-1.png" width="360" />

---

## Plotjes uit .UA-red[`base`]

De .UA-red[`boxplot()`] functie

```r
boxplot(RIASEC$Conventional)
```

<img src="Slides_Deel4_files/figure-html/unnamed-chunk-5-1.png" width="360" />

---

## Plotjes uit .UA-red[`base`]

De .UA-red[`hist()`] functie

```r
hist(RIASEC$Conventional)
```

<img src="Slides_Deel4_files/figure-html/unnamed-chunk-6-1.png" width="360" />

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

# 2. Grammar of Graphics

---

## Een meer theoretische benadering van grafieken

.left-column[
<img src="Grammar_of_Graphics_cover.jpeg" width="70%" height="70%" />
]

.right-colum[
<br>
<br>
<br>
- Theoretisch uiteenrafelen van data visualisaties

- Vormt de basis van verschillende moderne grafische applicaties:
  - ggplot2
  - Tableau (Polaris)
  - Vega-Lite
]

.footnote[*Slide gebaseerd op slides van Thomas Lin Pedersen https://github.com/thomasp85/ggplot2_workshop/blob/master/presentation.pdf*]
---

## Centraal idee achter Grammar of Graphics

<img src="Slides_TP_1.jpg" width="70%" height="70%" />

.footnote[*Slide uit slideshow van Thomas Lin Pedersen https://github.com/thomasp85/ggplot2_workshop/blob/master/presentation.pdf*]

---

## Grammar of Graphics: .SW-greenD[Data]

- Data is niet enkel ruwe dataset (kan ook waarden van schattingen op basis van anlayses zijn)

<br>

<table>
 <thead>
  <tr>
   <th style="text-align:left;"> Group </th>
   <th style="text-align:left;"> Country </th>
   <th style="text-align:left;"> Gender </th>
   <th style="text-align:right;"> Mean_age </th>
   <th style="text-align:right;"> Sd_age </th>
   <th style="text-align:right;"> CI_lower </th>
   <th style="text-align:right;"> CI_upper </th>
  </tr>
 </thead>
<tbody>
  <tr>
   <td style="text-align:left;"> BE Male </td>
   <td style="text-align:left;"> BE </td>
   <td style="text-align:left;"> Male </td>
   <td style="text-align:right;"> 39 </td>
   <td style="text-align:right;"> 11.0 </td>
   <td style="text-align:right;"> 17.44 </td>
   <td style="text-align:right;"> 60.56 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> BE Female </td>
   <td style="text-align:left;"> BE </td>
   <td style="text-align:left;"> Female </td>
   <td style="text-align:right;"> 41 </td>
   <td style="text-align:right;"> 13.2 </td>
   <td style="text-align:right;"> 15.13 </td>
   <td style="text-align:right;"> 66.87 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> BE Other </td>
   <td style="text-align:left;"> BE </td>
   <td style="text-align:left;"> Other </td>
   <td style="text-align:right;"> 36 </td>
   <td style="text-align:right;"> 8.2 </td>
   <td style="text-align:right;"> 19.93 </td>
   <td style="text-align:right;"> 52.07 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> NL Male </td>
   <td style="text-align:left;"> NL </td>
   <td style="text-align:left;"> Male </td>
   <td style="text-align:right;"> 37 </td>
   <td style="text-align:right;"> 12.0 </td>
   <td style="text-align:right;"> 13.48 </td>
   <td style="text-align:right;"> 60.52 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> NL Female </td>
   <td style="text-align:left;"> NL </td>
   <td style="text-align:left;"> Female </td>
   <td style="text-align:right;"> 36 </td>
   <td style="text-align:right;"> 14.0 </td>
   <td style="text-align:right;"> 8.56 </td>
   <td style="text-align:right;"> 63.44 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> NL Other </td>
   <td style="text-align:left;"> NL </td>
   <td style="text-align:left;"> Other </td>
   <td style="text-align:right;"> 31 </td>
   <td style="text-align:right;"> 7.2 </td>
   <td style="text-align:right;"> 16.89 </td>
   <td style="text-align:right;"> 45.11 </td>
  </tr>
</tbody>
</table>

- Data hoort 'tidy' te zijn (enkel rijen en kolommen)

---

## Grammar of Graphics: .SW-greenD[Mapping]

`\(=\)` Verbinden van elementen van een grafiek met de Data

<br>

.SW-greenD[*Aesthetic* mapping]

`\(=\)` de link tussen waarden voor een variabele in de Data en de 'geometry' (bv. hoogte van een balk; x-positie van een punt; kleur van punt; dikte van een punt; vorm van een punt)

<br>

.SW-greenD[*Facet* mapping]

`\(=\)` de link tussen waarden voor een variabele in de Data en de panelen die in een grafiek worden onderscheiden (bv. apart paneel per land)

---

## Grammar of Graphics: .SW-greenD[Statistics]

- Data is misschien wel `tidy`, maar wil niet zeggen dat de data-input van een graphic al meteen de juiste waarden bevatten die dienen te worden weergegeven
  - Bv. eerst beschrijvende statistieken berekenen om een boxplot te kunnen plotten
  - Bv. eerst een lineair (of ander) model schatten om een lijn doorheen puntenwolk te trekken

- Vaak impliciet achter bepaalde types van grafieken

---

## Grammar of Graphics: .SW-greenD[Scales]

- Data dient te worden vertaald naar 'grafische eigenschappen' (= Scales)

- Voorbeelden:
  - Categorieën `\(\rightarrow\)` Kleuren;
  - Categorieën `\(\rightarrow\)` Vorm (driehoekje; bolletje; kruisje; ...);
  - Nummers `\(\rightarrow\)` Plaats (x- en y- coördinaten);
  - Nummers `\(\rightarrow\)` Grootte;
  - ...

- Implicatie is dat waarde moeten op een bepaalde wijze geïnterpreteerd worden: discrete; continuous; ...

---

## Grammar of Graphics: .SW-greenD[Geometries]

- Welke geometrische vormen zijn de basis van de grafische representatie?

- Voorbeelden:
  - punten op een x- en y-assen stelsel;
  - boxplots;
  - polygonen;
  - een lijn;
  - ...

---

## Grammar of Graphics: .SW-greenD[Facets]

- Hoeveel panelen worden weergegeven?

- Hoe de panelen te definiëren?

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

# 3. Hoe werkt `ggplot2`?

---
<div class="my-logo-right"> <img src="palmerpenguins_hex.png" width="100%"/> </div>

## Tijd om de pinguïns erbij te halen...

Leuke data (Bron: https://allisonhorst.github.io/palmerpenguins/articles/intro.html)

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

<img src="lter_penguins.png" width="50%" height="50%" />

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

---
<div class="my-logo-right"> <img src="palmerpenguins_hex.png" width="100%"/> </div>

## Tijd om de pinguïns erbij te halen...

<table>
<caption>Table 1. Random sample of 10 observations from the Palmer Pinguins dataset</caption>
 <thead>
  <tr>
   <th style="text-align:left;"> species </th>
   <th style="text-align:left;"> island </th>
   <th style="text-align:right;"> bill_length_mm </th>
   <th style="text-align:right;"> bill_depth_mm </th>
   <th style="text-align:right;"> flipper_length_mm </th>
   <th style="text-align:right;"> body_mass_g </th>
   <th style="text-align:left;"> sex </th>
   <th style="text-align:right;"> year </th>
  </tr>
 </thead>
<tbody>
  <tr>
   <td style="text-align:left;"> Gentoo </td>
   <td style="text-align:left;"> Biscoe </td>
   <td style="text-align:right;"> 47.4 </td>
   <td style="text-align:right;"> 14.6 </td>
   <td style="text-align:right;"> 212 </td>
   <td style="text-align:right;"> 4725 </td>
   <td style="text-align:left;"> female </td>
   <td style="text-align:right;"> 2009 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Adelie </td>
   <td style="text-align:left;"> Torgersen </td>
   <td style="text-align:right;"> 35.1 </td>
   <td style="text-align:right;"> 19.4 </td>
   <td style="text-align:right;"> 193 </td>
   <td style="text-align:right;"> 4200 </td>
   <td style="text-align:left;"> male </td>
   <td style="text-align:right;"> 2008 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Adelie </td>
   <td style="text-align:left;"> Dream </td>
   <td style="text-align:right;"> 40.2 </td>
   <td style="text-align:right;"> 17.1 </td>
   <td style="text-align:right;"> 193 </td>
   <td style="text-align:right;"> 3400 </td>
   <td style="text-align:left;"> female </td>
   <td style="text-align:right;"> 2009 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Gentoo </td>
   <td style="text-align:left;"> Biscoe </td>
   <td style="text-align:right;"> 45.3 </td>
   <td style="text-align:right;"> 13.7 </td>
   <td style="text-align:right;"> 210 </td>
   <td style="text-align:right;"> 4300 </td>
   <td style="text-align:left;"> female </td>
   <td style="text-align:right;"> 2008 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Adelie </td>
   <td style="text-align:left;"> Biscoe </td>
   <td style="text-align:right;"> 39.7 </td>
   <td style="text-align:right;"> 17.7 </td>
   <td style="text-align:right;"> 193 </td>
   <td style="text-align:right;"> 3200 </td>
   <td style="text-align:left;"> female </td>
   <td style="text-align:right;"> 2009 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Adelie </td>
   <td style="text-align:left;"> Biscoe </td>
   <td style="text-align:right;"> 38.2 </td>
   <td style="text-align:right;"> 18.1 </td>
   <td style="text-align:right;"> 185 </td>
   <td style="text-align:right;"> 3950 </td>
   <td style="text-align:left;"> male </td>
   <td style="text-align:right;"> 2007 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Adelie </td>
   <td style="text-align:left;"> Dream </td>
   <td style="text-align:right;"> 40.2 </td>
   <td style="text-align:right;"> 20.1 </td>
   <td style="text-align:right;"> 200 </td>
   <td style="text-align:right;"> 3975 </td>
   <td style="text-align:left;"> male </td>
   <td style="text-align:right;"> 2009 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Adelie </td>
   <td style="text-align:left;"> Biscoe </td>
   <td style="text-align:right;"> 39.0 </td>
   <td style="text-align:right;"> 17.5 </td>
   <td style="text-align:right;"> 186 </td>
   <td style="text-align:right;"> 3550 </td>
   <td style="text-align:left;"> female </td>
   <td style="text-align:right;"> 2008 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Adelie </td>
   <td style="text-align:left;"> Torgersen </td>
   <td style="text-align:right;"> 38.6 </td>
   <td style="text-align:right;"> 21.2 </td>
   <td style="text-align:right;"> 191 </td>
   <td style="text-align:right;"> 3800 </td>
   <td style="text-align:left;"> male </td>
   <td style="text-align:right;"> 2007 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Adelie </td>
   <td style="text-align:left;"> Torgersen </td>
   <td style="text-align:right;"> 36.2 </td>
   <td style="text-align:right;"> 17.2 </td>
   <td style="text-align:right;"> 187 </td>
   <td style="text-align:right;"> 3150 </td>
   <td style="text-align:left;"> female </td>
   <td style="text-align:right;"> 2009 </td>
  </tr>
</tbody>
</table>

---

## De basis .UA-red[`ggplot2`]

.pull-left[

```r
Plot <- ggplot(

## Stap 1: de Data
  data = penguins,
  
  ## Stap 2: Mapping
  aes(
    x = flipper_length_mm,
    y = body_mass_g)
)

Plot
```
]

.pull-right[
<img src="Slides_Deel4_files/figure-html/unnamed-chunk-14-1.png" width="360" />
]

---

## De basis .UA-red[`ggplot2`]

.pull-left[

```r
Plot <- ggplot(

## Stap 1: de Data
  data = penguins,
  
  ## Stap 2: Mapping
  aes(
    x = flipper_length_mm,
    y = body_mass_g)
) +
  ## Stap 3: Geometries toevoegen
  geom_point()

Plot
```
]

.pull-right[
<img src="Slides_Deel4_files/figure-html/unnamed-chunk-16-1.png" width="360" />
]

Merk op dat we enkel stappen van de *Grammar of Graphics* niet dienden te definiëren omdat ze allen logische *default* waarden hebben

---

## De basis .UA-red[`ggplot2`] met meerdere .UA-red[facets]

.pull-left[

```r
Plot <- ggplot(

## Stap 1: de Data
  data = penguins,
  
  ## Stap 2: Mapping
  aes(
    x = flipper_length_mm,
    y = body_mass_g)
) +
  ## Stap 3: Geometries toevoegen
  geom_point() +
  
  ## Stap 4: Facets definiëren
  facet_wrap(.~species)

Plot
```
]

.pull-right[
<img src="Slides_Deel4_files/figure-html/unnamed-chunk-18-1.png" width="360" />
]

---

## Een visualisatie laten 'groeien' door laagjes toe te voegen ...

<img src="Slides_Deel4_files/figure-html/unnamed-chunk-19-1.png" width="1152" style="display: block; margin: auto;" />

---

## De verschillende .UA-red[`geom_*`] opties

<img src="ggplot2_cheatsheet.jpg" width="50%" height="50%" />

De *cheatsheet*:
https://github.com/rstudio/cheatsheets/blob/main/data-visualization-2.1.pdf

---
class: inverse-green, center, middle
name: part4

# 4. Categorische variabele visueel samenvatten met .UA-red[`ggplot2`]

.white[*"de bar is open" *]

---

## Barplot maken met .UA-red[`geom_bar()`]

.pull-left[
- `species` op de x-as zetten
- `geom_bar()` 
- op de achtergrond worden aantallen automatisch geteld (= `stat_count()`)

.footnotesize[

```r
ggplot(penguins,
       aes(
         x = species
       )) +
  geom_bar()
```
]
]
.pull-right[
<img src="Slides_Deel4_files/figure-html/unnamed-chunk-22-1.png" width="360" />
]

---

## Barplot maken met .UA-red[ `geom_col()`]

.pull-left[

- Heb je reeds samengevatte data, dan kan je `geom_col()` hanteren.

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

ggplot(Teldata,
       aes(
         x = species,
         y = Aantal
       )) +
  geom_col()
```

```
## # A tibble: 3 × 2
##   species   Aantal
##   <fct>      <int>
## 1 Adelie       152
## 2 Chinstrap     68
## 3 Gentoo       124
```

]

.pull-right[
<img src="Slides_Deel4_files/figure-html/unnamed-chunk-25-1.png" width="360" />
]

---

## Barplot maken met .UA-red[ `geom_bar()`]

.pull-left[

- Kleur toevoegen door een extra *schaal* te definiëren: de .SW-greenD[`fill`]

.footnotesize[

```r
ggplot(penguins,
       aes(
         x = species
       )) +
  geom_bar(
    ## Extra mapping: de "fill" schaal
    aes(fill = species)
    )
```
]
]

.pull-right[
<img src="Slides_Deel4_files/figure-html/unnamed-chunk-27-1.png" width="360" />
]

---

## Barplot maken met .UA-red[ `geom_bar()`]

.pull-left[

- Kleurenpallette manueel bepalen adhv extra laag met .SW-greenD[`scale_fill_manual()`]

.footnotesize[

```r
ggplot(penguins,
       aes(
         x = species
       )) +
  geom_bar(
    aes(fill = species)
    ) +
  # Zelf kleuren kiezen
  scale_fill_manual(
    values = c("darkorange","purple","cyan4")
    )
```
]
]

.pull-right[
<img src="Slides_Deel4_files/figure-html/unnamed-chunk-29-1.png" width="360" />
]

---

## Barplot maken met .UA-red[ `geom_bar()`]

.pull-left[

- titels toevoegen/veranderen met extra laag .SW-greenD[`labs()`]

.footnotesize[

```r
ggplot(penguins,
       aes(
         x = species
       )) +
  geom_bar(
    aes(fill = species)
    ) +
  scale_fill_manual(
    values = c("darkorange","purple","cyan4")
    ) +
  # Labs laag voor titels en x-as label
  labs(
    title = "Palmer penguins",
    subtitle = "n observations for species",
    x = ""
  )
```
]
]

.pull-right[
<img src="Slides_Deel4_files/figure-html/unnamed-chunk-31-1.png" width="360" />
]

---

## Barplot maken met .UA-red[ `geom_bar()`]

.pull-left[

- ander *theme* hanteren .SW-greenD[`theme_minimal()`]

.footnotesize[

```r
ggplot(penguins,
       aes(
         x = species
       )) +
  geom_bar(
    aes(fill = species)
    ) +
  scale_fill_manual(
    values = c("darkorange","purple","cyan4")
    ) +
  labs(
    title = "Palmer penguins",
    subtitle = "n observations for species",
    x = ""
  ) +
  # Ander thema kiezen
  theme_minimal()
```
]
]

.pull-right[
<img src="Slides_Deel4_files/figure-html/unnamed-chunk-33-1.png" width="360" />
]

---
## Barplot maken met .UA-red[ `geom_bar()`]

.pull-left[

- de richting omdraaien .SW-greenD[`coord_flip()`]
- legende verwijderen .SW-greenD[`theme(legend.position = "none")`]

.footnotesize[

```r
ggplot(penguins,
       aes(
         x = species
       )) +
  geom_bar(
    aes(fill = species)
    ) +
  scale_fill_manual(
    values = c("darkorange","purple","cyan4")
    ) +
  labs(
    title = "Palmer penguins",
    subtitle = "n observations for species",
    x = ""
  ) +  
  coord_flip( ) +
  theme_minimal( ) +
  theme(
    legend.position = "none"
  )
```
]
]

.pull-right[
<img src="Slides_Deel4_files/figure-html/unnamed-chunk-35-1.png" width="360" />
]

---
## Kleuren kiezen ...

<img src="colours_ggplot.jpg" width="70%" height="70%" />

http://www.cookbook-r.com/Graphs/Colors_(ggplot2)/
---

class: inverse-blue

# <i class="fas fa-laptop-code" style="color: #FF0035;"></i> Oefeningen `[ggplot2]` : deel 1

.left-column[
![](https://media.giphy.com/media/A9grgCQ0Dm012/giphy.gif)
]
.right-column[
- Op Dropbox vind je een document .SW-greenD[ `Oefening_ggplot2.Rmd`]

- Plaats dit document op je pc

- Open vervolgens het bestand in `R Studio`

- Het document bevat een set van opdrachten met telkens lege code blokken

- Bedoeling is dat je de juiste code schrijft (en test door te laten lopen) om deze opdrachten uit te voeren

- Zit je vast? No Worries! 
  - Ik ben er
  - Je hebt elkaar 
  - Er is een oplossingssleutel .SW-greenD[`Oefening_ggplot2_oplossing.Rmd`] 
]

---
class: inverse-green, center, middle
name: part5

# 5. Kwantitatieve variabelen visualiseren met .UA-red[`ggplot2`]

---

## Histogram met .UA-red[`geom_histogram()`]

.pull-left[
.footnotesize[

```r
ggplot(penguins,
       aes(
         x = flipper_length_mm,
       )) +
  geom_histogram()
```
]
]

.pull-right[
<img src="Slides_Deel4_files/figure-html/unnamed-chunk-38-1.png" width="360" />
]

---

## Histogram met .UA-red[`geom_histogram()`]

.pull-left[

+ gepimpte versie

.footnotesize[

```r
ggplot(penguins,
       aes(
         x = flipper_length_mm,
         fill = species
       )) +
  geom_histogram(
    alpha = .7
  ) +
  scale_fill_manual(
    values = c("darkorange","purple","cyan4")
    ) +
  labs(
    title = "Palmer penguins",
    subtitle = "Histogram voor flipper lengte",
    x = "Flipper lengte"
  ) +
  theme_minimal()
```
]
]

.pull-right[
<img src="Slides_Deel4_files/figure-html/unnamed-chunk-40-1.png" width="360" />
]

---

## Density plot met .UA-red[`geom_density()`]

.pull-left[

+ density plot (oppervlakte onder de curve = 100%)

.footnotesize[

```r
ggplot(penguins,
       aes(
         x = flipper_length_mm,
         fill = species
       )) +
  geom_density(
    alpha = .7
  ) +
  scale_fill_manual(
    values = c("darkorange","purple","cyan4")
    ) +
  labs(
    title = "Palmer penguins",
    subtitle = "Density plot voor flipper lengte",
    x = "Flipper lengte"
  ) + theme_minimal()
```
]
]

.pull-right[
<img src="Slides_Deel4_files/figure-html/unnamed-chunk-42-1.png" width="360" />
]

---

## Of beter nog .UA-red[`geom_violin()` + `geom_jitter()`]

.pull-left[
.footnotesize[

```r
ggplot(penguins,
       aes(
         x = species,
         y = flipper_length_mm,
         fill = species,
         color = species
       )) +
  geom_violin(
    alpha = .65
  ) +
  geom_jitter(
    alpha = .7
  ) +
  scale_fill_manual(
    values = c("darkorange","purple","cyan4")
    ) +
  scale_color_manual(
    values = c("darkorange","purple","cyan4")
    ) +
  labs(
    title = "Palmer penguins",
    subtitle = "Density plot voor flipper lengte",
    y = "Flipper lengte",
    x = "",
  ) + theme_minimal() + theme(legend.position = "none")
```
]
]

.pull-right[
<img src="Slides_Deel4_files/figure-html/unnamed-chunk-44-1.png" width="360" />
]

---

## Of een *raincloud plot*

<img src="Slides_Deel4_files/figure-html/unnamed-chunk-45-1.png" width="432" style="display: block; margin: auto;" />

.footnote[*Gebaseerd op de tutorial van Cédric Scherer: https://www.cedricscherer.com/*]

---
name: raincloud
## Of een *raincloud plot*  ([Appendix 1: regenwolken laten groeien](#appendix1))

Extra pakket nodig: .UA-red[`ggdist`]

.footnotesize[

```r
library(ggdist)
ggplot(penguins, aes(x = species, y = flipper_length_mm)) + 
  stat_halfeye(
    adjust = .5, 
    width = .6, 
    .width = 0, 
    justification = -.2, 
    point_colour = NA
  ) + 
  geom_boxplot(
    width = .15, 
    outlier.shape = NA
  ) +
  geom_point(
    size = 1.3,
    alpha = .3,
    position = position_jitter(
      seed = 1, width = .1
  )) +
  labs(
    title = "Palmer penguins",
    subtitle = "Verdeling van flipper lengte per soort",
    x = "",
    y = "flipper lengte"
  ) +
  coord_cartesian(xlim = c(1.2, NA), clip = "off") +
  coord_flip() +
  theme_minimal()
```
]
---
class: inverse-blue

# <i class="fas fa-laptop-code" style="color: #FF0035;"></i> Oefeningen `[ggplot2]` : deel 2

.left-column[
![](https://media.giphy.com/media/A9grgCQ0Dm012/giphy.gif)
]
.right-column[
- Op Dropbox vind je een document .SW-greenD[ `Oefening_ggplot2.Rmd`]

- Plaats dit document op je pc

- Open vervolgens het bestand in `R Studio`

- Het document bevat een set van opdrachten met telkens lege code blokken

- Bedoeling is dat je de juiste code schrijft (en test door te laten lopen) om deze opdrachten uit te voeren

- Zit je vast? No Worries! 
  - Ik ben er
  - Je hebt elkaar 
  - Er is een oplossingssleutel .SW-greenD[`Oefening_ggplot2_oplossing.Rmd`] 
]

---
class: inverse-green, center, middle
name: part6

# 6. Samenhang visualiseren met .UA-red[`ggplot2`]

---

## De puntenwolk met .UA-red[`geom_point()`]

.pull-left[
.footnotesize[

```r
ggplot(penguins,
       aes(
         x = body_mass_g,
         y = flipper_length_mm
       )) +
  geom_point( ) +
  labs(
    title = "Palmer penguins",
    subtitle = "Samenhang tussen flipper lengte en body mass",
    y = "Flipper lengte",
    x = "Body mass",
  ) + theme_minimal() + theme(legend.position = "none")
```
]
]

.pull-right[
<img src="Slides_Deel4_files/figure-html/unnamed-chunk-48-1.png" width="360" />
]

---
## De puntenwolk met .UA-red[`geom_point()`] en .UA-red[`geom_smooth()`]

.pull-left[
.footnotesize[

```r
ggplot(penguins,
       aes(
         x = body_mass_g,
         y = flipper_length_mm
       )) +
  geom_point( ) +
  geom_smooth( ) +
  labs(
    title = "Palmer penguins",
    subtitle = "Samenhang tussen flipper lengte en body mass",
    y = "Flipper lengte",
    x = "Body mass",
  ) + theme_minimal() + theme(legend.position = "none")
```
]
]

.pull-right[
<img src="Slides_Deel4_files/figure-html/unnamed-chunk-50-1.png" width="360" />
]

---
## De puntenwolk met .UA-red[`geom_point()`] en .UA-red[`geom_smooth()`]

.pull-left[

- zonder confidentie interval
- lineair model

.footnotesize[

```r
ggplot(penguins,
       aes(
         x = body_mass_g,
         y = flipper_length_mm
       )) +
  geom_point( ) +
  geom_smooth(
    method = "lm",
    se = FALSE
  ) +
  labs(
    title = "Palmer penguins",
    subtitle = "Samenhang tussen flipper lengte en body mass",
    y = "Flipper lengte",
    x = "Body mass",
  ) + theme_minimal() + theme(legend.position = "none")
```
]
]

.pull-right[
<img src="Slides_Deel4_files/figure-html/unnamed-chunk-52-1.png" width="360" />
]

---
## De puntenwolk met .UA-red[`geom_point()`] en .UA-red[`geom_smooth()`]

.pull-left[

- een facet per soort dankzij .UA-red[`facet_wrap()`]

.footnotesize[

```r
ggplot(penguins,
       aes(
         x = body_mass_g,
         y = flipper_length_mm
       )) +
  geom_point( ) +
  geom_smooth(
    method = "lm",
    se = FALSE
  ) +
  facet_wrap(.~species) +
  labs(
    title = "Palmer penguins",
    subtitle = "Samenhang tussen flipper lengte en body mass",
    y = "Flipper lengte",
    x = "Body mass",
  ) + theme_minimal() + theme(legend.position = "none")
```
]
]

.pull-right[
<img src="Slides_Deel4_files/figure-html/unnamed-chunk-54-1.png" width="360" />
]
---
## De puntenwolk met .UA-red[`geom_point()`] en .UA-red[`geom_smooth()`]

.pull-left[

.footnotesize[

```r
ggplot(data = penguins,
       aes(x = flipper_length_mm,
           y = body_mass_g)) +
  geom_point(aes(color = species,
                 shape = species),
             size = 3,
             alpha = 0.8) +
  geom_smooth(
    aes(color = species),
    se = F, method = "lm"
    ) +
  theme_minimal() +
  scale_color_manual(
    values = c("darkorange","purple","cyan4")) +
  labs(title = "Penguin size, Palmer Station LTER",
       subtitle = "Flipper lengte en body mass voor Adelie, Chinstrap en Gentoo Pinguïns",
       x = "Flipper lengte (mm)",
       y = "Body mass (g)",
       color = "Penguin soort",
       shape = "Penguin soort") +
  theme(legend.position = c(0.2, 0.7),
        legend.background = element_rect(fill = "white", color = NA),
        plot.title.position = "plot",
        plot.caption = element_text(hjust = 0, face= "italic"),
        plot.caption.position = "plot")
```
]
]

.pull-right[

<img src="Slides_Deel4_files/figure-html/unnamed-chunk-56-1.png" width="360" />

]

---
class: inverse-blue

# <i class="fas fa-laptop-code" style="color: #FF0035;"></i> Oefeningen `[ggplot2]` : deel 3

.left-column[
![](https://media.giphy.com/media/A9grgCQ0Dm012/giphy.gif)
]
.right-column[
-- Op Dropbox vind je een document .SW-greenD[ `Oefening_ggplot2.Rmd`]

- Plaats dit document op je pc

- Open vervolgens het bestand in `R Studio`

- Het document bevat een set van opdrachten met telkens lege code blokken

- Bedoeling is dat je de juiste code schrijft (en test door te laten lopen) om deze opdrachten uit te voeren

- Zit je vast? No Worries! 
  - Ik ben er
  - Je hebt elkaar 
  - Er is een oplossingssleutel .SW-greenD[`Oefening_ggplot2_oplossing.Rmd`] 
]

---
class: inverse-green, center, middle
name: appendix1

# Appendix 1

*Regenwolken laten groeien*

<br> <br><br>

[Terug naar slideshow...](#raincloud)

---

## Stap 1
.pull-left[

.footnotesize[

```r
library(ggdist)

P1 <- 
  ggplot(penguins, aes(x = species, y = flipper_length_mm)) + 
  stat_halfeye(
  )

P1
```
]

]

.pull-right[
<img src="Slides_Deel4_files/figure-html/unnamed-chunk-58-1.png" width="504" style="display: block; margin: auto;" />
]

---

## Stap 2
.pull-left[

.footnotesize[

```r
P1 <- 
  ggplot(penguins, aes(x = species, y = flipper_length_mm)) + 
  stat_halfeye(
    adjust = .5, 
    width = .6, 
    .width = 0, 
    justification = -.2, 
    point_colour = NA
  )

P1
```
]

]

.pull-right[
<img src="Slides_Deel4_files/figure-html/unnamed-chunk-60-1.png" width="504" style="display: block; margin: auto;" />
]

---

## Stap 3

.pull-left[

.footnotesize[

```r
P2 <- P1 + 
  geom_boxplot(
    width = .15, 
    outlier.shape = NA
  )

P2
```
]

]

.pull-right[
<img src="Slides_Deel4_files/figure-html/unnamed-chunk-62-1.png" width="504" style="display: block; margin: auto;" />
]

---

## Stap 4

.pull-left[

.footnotesize[

```r
P3 <- P2 + 
  geom_point(
    size = 1.3,
    alpha = .3,
    position = position_jitter(
      seed = 1, width = .1
  ))

P3
```
]

]

.pull-right[
<img src="Slides_Deel4_files/figure-html/unnamed-chunk-64-1.png" width="504" style="display: block; margin: auto;" />
]

---

## Stap 5

.pull-left[

.footnotesize[

```r
P4 <- P3 + 
  labs(
    title = "Palmer penguins",
    subtitle = "Verdeling van flipper lengte per soort",
    x = "",
    y = "flipper lengte"
  )

P4
```
]

]

.pull-right[
<img src="Slides_Deel4_files/figure-html/unnamed-chunk-66-1.png" width="504" style="display: block; margin: auto;" />
]

---

## Stap 6

.pull-left[

.footnotesize[

```r
P5 <- P4 +
  coord_cartesian(xlim = c(1.2, NA), clip = "off") +
  coord_flip() +
  theme_minimal() +
  theme(plot.title.position = "plot")

P5
```
]

]

.pull-right[
<img src="Slides_Deel4_files/figure-html/unnamed-chunk-68-1.png" width="504" style="display: block; margin: auto;" />
]
---
class: inverse-green, center, middle

## AANSCHOUW DE REGENWOLKEN / [Terug naar slideshow...](#raincloud)

<img src="Slides_Deel4_files/figure-html/unnamed-chunk-69-1.png" width="504" style="display: block; margin: auto;" />