Plotting data

<div>
<style type="text/css">.xaringan-extra-logo {
width: 110px;
height: 30px;
z-index: 0;
background-image: url(img/00/logo_uni_elixir.png);
background-size: contain;
background-repeat: no-repeat;
position: absolute;
bottom:1em;left:1em;
}
</style>
<script>(function () {
  let tries = 0
  function addLogo () {
    if (typeof slideshow === 'undefined') {
      tries += 1
      if (tries < 10) {
        setTimeout(addLogo, 100)
      }
    } else {
      document.querySelectorAll('.remark-slide-content:not(.title-slide):not(.inverse):not(.hide_logo)')
        .forEach(function (slide) {
          const logo = document.createElement('a')
          logo.classList = 'xaringan-extra-logo'
          logo.href = 'https://rworkshop.uni.lu/'
          slide.appendChild(logo)
        })
    }
  }
  document.addEventListener('DOMContentLoaded', addLogo)
})()</script>
</div>

# Plotting data

## with `ggplot2`

### A. Ginolhac | rworkshop | 2021-09-09

---
background-image: url(img/plot_ggplot2_overview.png)
background-position: center
background-size: contains

# ggplot2

---

# About this lecture

.flex[
  .w-10[
  ]
  .w-70.bg-washed-green.b--green.ba.bw2.br3.shadow-5.ph3.mt3.mr1[
  .large[.gbox[Learning objectives]

- Learn the basic grammar of graphics
- Understand how it is implemented in `ggplot2`
    + Input data structures as `data.frame/tibble`
    + Mapping columns to display features (*aesthetics*)
    + Types of graphics (*geometries*)
    + Multiple and repeating graphics (*facets*)
    + Transforming plots (*scales*)
    + Using different coordinate systems
    + Customizing graphs with *themes*
- Make quick exploratory plots of your multidimensional data.]
]]

---

# Introduction

.flex.justify-around[
.w-50.bg-washed-green.b--green.ba.bw2.br3.shadow-5.ph3.mt3.mr1[
.large[.gbox[`ggplot2`]]

- stands for **g**rammar of **graphics** plot v2
- Inspired by Leland Wilkinson work on the [grammar of graphics](https://www.amazon.com/Grammar-Graphics-Statistics-Computing/dp/0387245448) in 2005.
]
.w-50.bg-washed-yellow.b--gold.ba.bw2.br3.shadow-5.ph3.mt3.mr1[
.large[.bbox[Idea: split a graph into layers]]

- such as axis, curve(s), labels.
- **3** elements are required: **data**, **aesthetics**,  **geometry** `\(\geqslant 1\)`
]]

.footnote[[Wickham H. 2007. _J. Comp. Graph. Stat._ **19**:3–28](http://www.tandfonline.com/doi/abs/10.1198/jcgs.2009.07098)]

---
background-image: url(img/plot_gglayers.png)
background-position: center
background-size: contains
class: hide_logo

# ggplot2 layers

.footnote[Adapted from this [article](https://www.thinkr.fr/guide-survie-ggplot2-datajournalistes/) by [Colin Fay](https://thinkr.fr/equipe/colin-fay/) ([thinkR]((https://www.thinkr.fr))]

---
background-image: url(img/plot_gglayers_example.png)
background-position: center
background-size: contains
class: hide_logo

# ggplot2 layers

.footnote[Adapted from this [article](https://www.thinkr.fr/guide-survie-ggplot2-datajournalistes/) by [Colin Fay](https://thinkr.fr/equipe/colin-fay/) ([thinkR]((https://www.thinkr.fr))]

---

# Basic example

.flex[
.w-33.bg-washed-yellow.b--yellow.ba.bw2.br3.shadow-5.ph3.mt3.mr2[
.large.gbox[data]
.large[
x  |  y  | shape
---|-----|-------
25 |  11 | circle
0  |  0  | circle
75 |  53 | square
200|  300| square
]]
.w-33.bg-washed-green.b--green.ba.bw2.br3.shadow-5.ph3.mt3.mr2[
.large.gbox[aesthetics]
.center[.Large[
- `x = x`
- `y = y`
- `shape = shape`]]
]
.w-33.bg-washed-blue.b--blue.ba.bw2.br3.shadow-5.ph3.mt3.mr1[
.large.bbox[geometry]
.center[.Large[
- **dot / point**
]]
]
]

.footnote[Wickham: [A Layered Grammar of Graphics](https://www.tandfonline.com/doi/abs/10.1198/jcgs.2009.07098) (2007)]

---

# Result

.center.huge[What if we want to split into panels _circles_ and _squares_?]

---

# Faceting

### Split by **shape**, _aka_ trellis or lattice plots

.flex[
  .w-50.ph3.mt3.mr2[ 
  ![](img/plot_simple_facet.png)
]
.w-50.bg-washed-yellow.b--yellow.ba.bw2.br3.shadow-5.ph3.mt3.mr2[
.large.gbox[Redundancy 💡]
.large[

- **shape** and **facets** provide the same information.
- The `shape` aesthetic is free for another variable.

]
]
.footnote[Wickham: [A Layered Grammar of Graphics](https://www.tandfonline.com/doi/abs/10.1198/jcgs.2009.07098) (2007)
]]

---
background-image: url(img/plot_geofacet.png)
background-position: center

# Faceting can also carry a message

---
class: hide_logo

# Layers

]

.w-50.bg-washed-yellow.b--yellow.ba.bw2.br3.shadow-5.ph5.pb2.mt3.mr2[
.large.gbox[data]
.large[
x  |  y  | shape
---|-----|-------
25 |  11 | circle
0  |  0  | circle
75 |  53 | square
200|  300| square
]]]

.flex[
.w-60.bg-washed-yellow.b--yellow.ba.bw2.br3.shadow-5.ph4.pb1.mt2.ml6.mr2[
.large.bbox[Motivation for this layered system]

.Large[
> *Data visualisation* is not meant just to be seen but to be .bold[read], like written text

]]

---
class: hide_logo

# Combine layers but not with pipes!

`ggplot2` layers are combined with .huge[`+`], .bold[not] .Large[`%>%`, `|>`].

This introduces .bold[a break] in the .bolder[workflow]. (`ggplot1` would have been fine)
]]

.flex[
.w-50.bg-washed-green.b--green.ba.bw2.br3.shadow-5.ph2.pb4.mt2.ml0.mr1[
.large.gbox[`ggplot` lines combined with .Large[`+`]]

```r
library(ggplot2)
swiss %>%
  ggplot(aes(x = Education, 
             y = Examination)) +
  geom_point() +
  scale_colour_brewer()
```

]
.w-50.bg-washed-red.b--red.ba.bw2.br3.shadow-5.ph2.pb2.mt2.ml0.mr2[
.large.rbox[if not, the error is explicit]

```r
swiss %>%
  ggplot(aes(x = Education, 
             y = Examination)) %>%
  geom_point() +
  scale_colour_brewer()
```

```
Error: `mapping` must be created by `aes()`
Did you use %>% instead of +?
```

]]

---

```r
*swiss
```
]
 
.panel2-first_plot-auto[

```
             Fertility Agriculture Examination Education Catholic
Courtelary        80.2        17.0          15        12     9.96
Delemont          83.1        45.1           6         9    84.84
Franches-Mnt      92.5        39.7           5         5    93.40
Moutier           85.8        36.5          12         7    33.77
Neuveville        76.9        43.5          17        15     5.16
Porrentruy        76.1        35.3           9         7    90.57
Broye             83.8        70.2          16         7    92.85
Glane             92.4        67.8          14         8    97.16
Gruyere           82.4        53.3          12         7    97.67
Sarine            82.9        45.2          16        13    91.38
Veveyse           87.1        64.5          14         6    98.61
Aigle             64.1        62.0          21        12     8.52
Aubonne           66.9        67.5          14         7     2.27
Avenches          68.9        60.7          19        12     4.43
Cossonay          61.7        69.3          22         5     2.82
Echallens         68.3        72.6          18         2    24.20
Grandson          71.7        34.0          17         8     3.30
Lausanne          55.7        19.4          26        28    12.11
La Vallee         54.3        15.2          31        20     2.15
Lavaux            65.1        73.0          19         9     2.84
Morges            65.5        59.8          22        10     5.23
Moudon            65.0        55.1          14         3     4.52
Nyone             56.6        50.9          22        12    15.14
Orbe              57.4        54.1          20         6     4.20
Oron              72.5        71.2          12         1     2.40
Payerne           74.2        58.1          14         8     5.23
Paysd'enhaut      72.0        63.5           6         3     2.56
Rolle             60.5        60.8          16        10     7.72
Vevey             58.3        26.8          25        19    18.46
Yverdon           65.4        49.5          15         8     6.10
Conthey           75.5        85.9           3         2    99.71
Entremont         69.3        84.9           7         6    99.68
Herens            77.3        89.7           5         2   100.00
Martigwy          70.5        78.2          12         6    98.96
Monthey           79.4        64.9           7         3    98.22
St Maurice        65.0        75.9           9         9    99.06
Sierre            92.2        84.6           3         3    99.46
Sion              79.3        63.1          13        13    96.83
Boudry            70.4        38.4          26        12     5.62
La Chauxdfnd      65.7         7.7          29        11    13.79
Le Locle          72.7        16.7          22        13    11.22
Neuchatel         64.4        17.6          35        32    16.92
Val de Ruz        77.6        37.6          15         7     4.97
ValdeTravers      67.6        18.7          25         7     8.65
V. De Geneve      35.0         1.2          37        53    42.34
Rive Droite       44.7        46.6          16        29    50.43
Rive Gauche       42.8        27.7          22        29    58.33
             Infant.Mortality
Courtelary               22.2
Delemont                 22.2
Franches-Mnt             20.2
Moutier                  20.3
Neuveville               20.6
Porrentruy               26.6
Broye                    23.6
Glane                    24.9
Gruyere                  21.0
Sarine                   24.4
Veveyse                  24.5
Aigle                    16.5
Aubonne                  19.1
Avenches                 22.7
Cossonay                 18.7
Echallens                21.2
Grandson                 20.0
Lausanne                 20.2
La Vallee                10.8
Lavaux                   20.0
Morges                   18.0
Moudon                   22.4
Nyone                    16.7
Orbe                     15.3
Oron                     21.0
Payerne                  23.8
Paysd'enhaut             18.0
Rolle                    16.3
Vevey                    20.9
Yverdon                  22.5
Conthey                  15.1
Entremont                19.8
Herens                   18.3
Martigwy                 19.4
Monthey                  20.2
St Maurice               17.8
Sierre                   16.3
Sion                     18.1
Boudry                   20.3
La Chauxdfnd             20.5
Le Locle                 18.9
Neuchatel                23.0
Val de Ruz               20.0
ValdeTravers             19.5
V. De Geneve             18.0
Rive Droite              18.2
Rive Gauche              19.3
```
]

---
count: false
 
# Build a plot by layers
.panel1-first_plot-auto[

```r
swiss %>%
* ggplot()
```
]
 
.panel2-first_plot-auto[
<img src="lecture06_plotting_files/figure-html/first_plot_auto_02_output-1.png" width="504" />
]

---
count: false
 
# Build a plot by layers
.panel1-first_plot-auto[

```r
swiss %>%
  ggplot() +
* aes(x = Education)
```
]
 
.panel2-first_plot-auto[
<img src="lecture06_plotting_files/figure-html/first_plot_auto_03_output-1.png" width="504" />
]

---
count: false
 
# Build a plot by layers
.panel1-first_plot-auto[

```r
swiss %>%
  ggplot() +
  aes(x = Education) +
* aes(y = Examination)
```
]
 
.panel2-first_plot-auto[
<img src="lecture06_plotting_files/figure-html/first_plot_auto_04_output-1.png" width="504" />
]

---
count: false
 
# Build a plot by layers
.panel1-first_plot-auto[

```r
swiss %>%
  ggplot() +
  aes(x = Education) +
  aes(y = Examination) +
* geom_point()
```
]
 
.panel2-first_plot-auto[
<img src="lecture06_plotting_files/figure-html/first_plot_auto_05_output-1.png" width="504" />
]

---
count: false
 
# Build a plot by layers
.panel1-first_plot-auto[

```r
swiss %>%
  ggplot() +
  aes(x = Education) +
  aes(y = Examination) +
  geom_point() +
* theme_bw(18)
```
]
 
.panel2-first_plot-auto[
<img src="lecture06_plotting_files/figure-html/first_plot_auto_06_output-1.png" width="504" />
]

.left.footnote[.bold[[`flipbookr`](https://evamaerey.github.io/flipbooks/about)] by [Gina Reynolds](https://github.com/EvaMaeRey)]

---
background-image: url("img/plot_lter_penguins.png")
background-size: cover
class: nvs1

# .small[Palmer penguins]

.footnote[
.flex[
.w100.bg-light-gray.shadow-5.pt1.mh1[
.center[install with .large[`install.packages("palmerpenguins")`]]

![](https://licensebuttons.net/p/zero/1.0/88x31.png) Horst AM, Hill AP, Gorman KB (2020). [palmerpenguins: Palmer Archipelago (Antarctica) penguin data](https://github.com/allisonhorst/palmerpenguins). R package `v0.1.0`
]]]

---

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

]