Plotting

# Plotting
### <a href='https://cdsbasel.github.io/dataanalytics/'> Data Analytics for Psychology and Business </a> <a href='https://cdsbasel.github.io/dataanalytics/menu/materials.html'> </a>  <a href='https://cdsbasel.github.io/dataanalytics/'> </a>  <a href='mailto:rui.mata@unibas.ch'> 
### February 2019

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 Data Analytics for Psychology and Business | February 2019
 
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<img src="image/plots.png" height="540px">
 
from <a href="http://r-statistics.co/Top50-Ggplot2-Visualizations-MasterList-R-Code.html">r-statistics.co</a>

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# `base` Plotting

<ul>
 <li class="m1">The <high>traditional</high> approach for plotting.</li>
 <li class="m2"><high>Separate functons</high> for different plots</li>
</ul>

```r
# Histogram in base R
hist(x = basel$alter,
     xlab = "Alter",
     ylab = "Häufigkeit",
     main = "Histogramm Alter")
```

]

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<img src="Plotting_files/figure-html/unnamed-chunk-4-1.png" style="display: block; margin: auto;" />

]

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# `base` Plotting

<ul>
 <li class="m1">The <high>traditional</high> approach for plotting.</li>
 <li class="m2"><high>Separate functons</high> for different plots</li>
</ul>

```r
# Boxplot in base R
boxplot(formula = groesse ~ geschlecht,
        data = basel,
        xlab = "Geschlecht",
        ylab = "Groesse",
        main = "Box plot Groesse")
```

]

.pull-right5[
 
<img src="Plotting_files/figure-html/unnamed-chunk-6-1.png" style="display: block; margin: auto;" />

]

---

# `base` Plotting

<ul>
 <li class="m1">The <high>traditional</high> approach for plotting.</li>
 <li class="m2"><high>Separate functons</high> for different plots</li>
</ul>

```r
# Scatterplot in base R
plot(x = basel$groesse,
     y = basel$einkommen,
     xlab = "Height",
     ylab = "Einkommen",
     main = "Scatterplot Groesse x Einkommen")
```

]

.pull-right5[
 
<img src="Plotting_files/figure-html/unnamed-chunk-8-1.png" style="display: block; margin: auto;" />

]

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# Probleme mit Base R plotting

<ul>
 <li class="m1"><high>Aesthetics</high> are outdated.</li>
 <li class="m2">Pretty plots = <high>lots of code.</high></li>
 <li class="m3">Relatively <high>inflexible</high>.</li>
</ul>
]

<img src="image/outdated.jpeg">
 
from <a href="https://www.healthhosts.com/4-signs-your-website-is-outdated/">healthhosts.com</a>

]

---

# The mighty `tidyverse`

The [`tidyverse`](https://www.tidyverse.org/) is a collection of high-performing, user-friendly R packages, created explicitly for efficient data analytics. 
1. <high><mono>`ggplot2`</mono> for graphics</high>.
2. dplyr for data wrangling.
3. tidyr for data wrangling.
4. `readr` for data I/O.
5. `purrr` for function programming.
6. `tibble` for modern `data.frame`s.

---

# Modular graphics in <mono>ggplot2</mono>

<ul>
 <li class="m1"><high>data</high>: The dataset</li>
 <li class="m2"><high>mapping</high>: The structure of the plot</li>
 <ul class="level">
 <li>What should axes represent?</li>
 <li>What should color/size represent?</li>
 </ul>
 <li class="m3"><high>geoms</high>: Objects drawn within plot</high></li>
 <li class="m4"><high>labs</high>: Plot annotation</high></li>
 <li class="m5"><high>themes</high>: Aesthetic design</high></li>
 <li class="m6"><high>facets</high>: Plot facets </high></li>
 <li class="m7"><high>scales</high>: Scaling of axes</high></li>
</ul>

]

]

---

# Part 1: Wir kreieren diesen Plot

<ul>
 <li class="m1"><high>data</high></li>
 <ul class="level">
 <li>The <mono>mpg</mono> dataset</li>
 </ul>
 <li class="m2"><high>mapping</high></li>
 <ul class="level">
 <li>Engine displacement onto x-axis</li>
 <li>Miles per gallon onto y-axis</li>
 <li>Color according to vehicle class</li>
 </ul>
 <li class="m3"><high>geoms</high></li>
 <ul class="level">
 <li>Plot data as points</li>
 <li>Add regression line</li>
 </ul>
 <li class="m4"><high>labs</high></li>
 <ul class="level">
 <li>Annotation of axes and titles</li>
 </ul>
 <li class="m5"><high>themes</high></li>
 <ul class="level">
 <li>black-white aesthetics</li>
 </ul>
 
</ul>

]

]

---

# `ggplot()`

<ul>
 <li class="m1">All plots start with <highm>ggplot()</highm></li>
 <li class="m2">2 central arguments</li>
 <ul class="level">
 <li><mono>data</mono> | The dataset (<mono>tibble</mono>)</li>
 <li><mono>mapping</mono> | The plot structure defined using <mono>aes()</mono>
 </ul>
 </li>
</ul>
]

```r
ggplot(data = mpg)
```

]

---

# `aes()`

<ul>
 <li class="m1"><highm>aes()</highm> defines the structure for the <mono>mapping</mono> argument</li>
 <li class="m2">Central arguments:</li>
 <ul class="level">
 <li><mono>x,y</mono> | Defines axes</li>
 <li><mono>color,fill</mono> | Defines colors</li>
 <li><mono>alpha</mono> | Defines transparency</li>
 <li><mono>size</mono> | Defines size</li>
 <li><mono>shape</mono> | Defines object sbapes (e.g. circles or squares)</li>
 </ul>
</ul>

]

```r
ggplot(data = mpg,
       mapping = aes(x = displ, y = hwy))
```

]

---

# <mono>+</mono>

<ul>
 <li class="m1">The <highm>+</highm> operator extents plots with additional modules.</li>
</ul>

```r
ggplot(data = mpg,
       mapping = aes(x = displ,
                     y = hwy)) + 
  
  # Plotte Daten als Punkte
  geom_point() 
```

]

]

---

# `geom_*()`

<ul>
 <li class="m1"><highm>geom_*()</highm> functions define the geometric objects used to represent the data.</li>
 <li class="m2">Some common <mono>geoms</mono>:</li>
 <ul class="level">
 <li><mono>geom_point()</mono> | for points</li>
 <li><mono>geom_bar()</mono> | for bars</li>
 <li><mono>geom_boxplot()</mono> | for box-plots </li>
 <li><mono>geom_count()</mono> | for points scaled according to frequency</li>
 <li><mono>geom_smooth()</mono> | for curves</li>
 </ul>
</ul>

]

]

---

## `geom_count()`

```r
ggplot(data = mpg,
  mapping = aes(x = displ, y = hwy)) + 
  geom_count()
```

]

## `geom_bar()`

```r
ggplot(data = mpg,
  mapping = aes(x = class)) + 
  geom_bar()
```

]

---

## `geom_boxplot()`

```r
ggplot(data = mpg,
  mapping = aes(x = class,
                y = hwy)) + 
  geom_boxplot()
```

]

## `geom_violin()`

```r
ggplot(data = mpg,
  mapping = aes(x = class,
                y = hwy)) + 
  geom_violin()
```

]

---

# What's missing?

]

]

---

# `aes()`

<ul>
 <li class="m1"><highm>aes()</highm> defines the structure for the <mono>mapping</mono> argument</li>
 <li class="m2">2 arguments:</li>
 <ul class="level">
 <li><mono>x,y</mono> | Defines axes</li>
 <li><mono>color,fill</mono> | Defines colors</li>
 </ul>
</ul>

```r
ggplot(data = mpg,
       mapping = aes(x = displ, 
                     y = hwy,
                     
                     # Farbe gemäss Klasse
                     color = class)) +
  geom_point()
```

]

]

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# What's missing?

]

]

---

# `geom_smooth()`

<ul>
 <li class="m1"><highm>geom_smooth()</highm> fits curves to the data and adds them to the plot.</li>
 <li class="m2">Central arguments:</li>
 <ul class="level">
 <li><mono>method</mono> | Type of model fitted to data</li>
 <li><mono>color</mono> | Color</high></li>
 </ul>
</ul>

```r
ggplot(data = mpg, 
       mapping = aes(x = displ, y = hwy,
                     col = class)) +
  geom_point() + 
  
  # Add curve
  geom_smooth(col = "blue")
```

]

]

---

# `geom_smooth()`

```r
ggplot(data = mpg, 
       mapping = aes(x = displ, y = hwy,
                     col = class)) +
  geom_point() + 
  
  # Add curve
  geom_smooth(col = "blue",
              method = "lm")
```

]

]

---

# Inheritance

<ul>
 <li class="m1"><highm>geom</highm>s inherit their settings from <mono>mapping</mono>.</li>
 <li class="m2">Vererbte Settings can be <high>overruled</high> using the <mono>geom</mono>s own arguments.</li>
</ul>

```r
ggplot(data = mpg, 
       mapping = aes(x = displ, y = hwy,
                     col = class)) +
  geom_point() + 
  geom_smooth() 
```

]

<img src="image/question.png" height=280px>
 
from <a href="http://catchingfire.ca/the-power-of-a-question-mark/">catchingfire.ca</a>

]

---

# Inheritance

```r
ggplot(data = mpg, 
       mapping = aes(x = displ, y = hwy,
                     col = class)) +
  geom_point() + 
  geom_smooth() 
```

]

]

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# What's missing?

]

]

---

# `labs()`

<ul>
 <li class="m1"><highm>labs()</highm> defines all annotation of the plot.</li>
 <li class="m2">Central arguments:</li>
 <ul class="level">
 <li><mono>x,y</mono> | annotation of axes</li>
 <li><mono>title, subtitle</mono> | title and subtitle</high></li>
 <li><mono>caption</mono> | caption</high></li>
 </ul>
</ul>

```r
ggplot(...) +
  labs(x = "Engine displacement in liters",
       y = "Highway miles per gallon",
       title = "MPG dataset",
       subtitle = "Cars with higher Eng...",
       caption = "Source: MPG dataset...")
```

]

]

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# What's missing?

]

]

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