Plotting II

# Plotting II
### Intro to Data Science with R <a href='https://therbootcamp.github.io'> The R Bootcamp @ Unibe </a> <a href='https://dwulff.github.io/Intro2R_Unibe_2021/'> </a>  <a href='https://therbootcamp.github.io'> </a>  <a href='mailto:therbootcamp@gmail.com'> </a>  <a href='https://www.linkedin.com/company/basel-r-bootcamp/'> </a>
### September 2021

---

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 </a>
 <a href="https://therbootcamp.github.io/">
 
 The R Bootcamp | September 2021
 
 </a>
 
 </div>

---

# Customizing plots

.pull-left45[
<br2>

1 <high>Store</high> and customize plot as a <high><mono>gg</mono> object</high>.
 
2 Create multiple plots using <high>facetting</high>.
 
3 Use <high>themes</high> to control every <high>detail</high> of the plot.
 
4 Create your <high>own themes</high>.
 
5 Combine <high>multiple plots</high>.
 
6 Create <high>image files</high> in <mono>.pdf</mono>, <mono>.png</mono>, etc.

]

]

---

# The <mono>gg</mono> object

1 ggplot returns an object of the class `gg`. 
2 You can assign the result of `ggplot` to an <high>object</high>. 
3 Evaluating the object will show the plot. 
4 You can even edit existing <high>`ggplot` objects</high>.

```r
# Create my_plot
my_plot <- ggplot(data = mpg,
 aes(x = displ,
 y = hwy)) + 
 geom_point() + 
 theme_bw()
class(my_plot)
```

```
[1] "gg"     "ggplot"
```

]

```r
my_plot # Evaluate my_plot
```

]

---

# The <mono>gg</mono> object

```r
# Create my_plot
my_plot <- ggplot(data = mpg,
 aes(x = displ,
 y = hwy)) + 
 geom_point() + 
 theme_bw()
class(my_plot)
```

```
[1] "gg"     "ggplot"
```

]

```r
my_plot + 
  geom_smooth() # add geom
```

]

---

# `facet_wrap()`

Faceting = <high>same plot for different groups</high>.

To facet plots, use, e.g., `facet_wrap()`.

```r
# Without faceting
ggplot(data = mpg, 
       mapping = aes(x = displ, 
                     y = hwy)) + 
  geom_point() + theme_bw()
```

]

]

---

# `facet_wrap()`

Faceting = <high>same plot for different groups</high>.

To facet plots, use, e.g., `facet_wrap()`.

```r
# With faceting
ggplot(data = mpg, 
       mapping = aes(x = displ, 
                     y = hwy)) + 
  geom_point() + theme_bw() +
  facet_wrap(~ class)  # Tilde first
```

]

]

---

# `facet_grid()`

Faceting = <high>same plot for different groups</high>.

Use `facet_grid()` to create plots of one (set of) variable against those another.

```r
# With faceting
ggplot(data = mpg, 
       mapping = aes(x = displ, 
                     y = hwy)) + 
  geom_point() + theme_bw() +
  facet_grid(drv ~ class) 
```

]

]

---

# `theme()`

To <high>customize the appearance of your plot use `theme()`.

`theme()` has <high>94 arguments</high> allowing to fine-tune, e.g., the background, the axes, the legend, etc.

Arguments are specified via `element_*()` helper functions, mostly `element_rect()` or `element_line()`.

```r
# use theme to change appearance
my_plot + 
  theme(argument = element_*(), 
        argument = element_*(),
        etc.)
```

]

<img src="image/theme.png">

]

---

# Background color: `theme()`

Address the <high>panel background</high> using `panel.background` and that of the <high>plot background</high> using `plot.background` and change the color using `element_rect(fill = color)`.

```r
# change panel and plot color
my_plot + 
  theme(
    panel.background = 
      element_rect(fill = 'tomato'), 
    plot.background = 
      element_rect(fill = 'burlywood'))
```

]

]

---

# Background grid: `theme()`

Address the <high>grid line colors</high> using `panel.grid.major` (large grid lines) and `panel.grid.minor` (small grid lines) and change the color using `element_line(colour = color)`.

```r
# change grid line color
my_plot + 
  theme(
    panel.grid.major = 
      element_line(colour = "salmon"),
    panel.grid.minor = 
      element_line(colour = "seagreen")
    )
```

]

]

---

# Background grid: `theme()`

Change the <high>grid line sizes</high> using `element_line(size = number)`.

```r
# change grid line color
my_plot + 
  theme(
    panel.grid.major = 
      element_line(colour = "salmon",
                   size = 3),
    panel.grid.minor = 
      element_line(colour = "seagreen",
                   size = 1.5)
    )
```

]

]

---

# Axes: `theme()`

Change the <high>axes</high> using the ` axis.line.x` and ` axis.line.y` arguments and `element_line(colour, size, lineend, ...)`.

```r
# change grid line color
my_plot + 
  theme(
    axis.line.x = 
      element_line(colour = "deeppink", 
                   size = 3.5, 
                   lineend = "butt"),
    axis.line.y = 
      element_line(colour = "deeppink", 
                   size = 3.5)
    )
```

]

]

---

# Axes: `theme()`

Change the <high>axes labels</high> using the ` axis.title.x` and ` axis.title.y` arguments and `element_text(family, face, ...)`.

```r
# change grid line color
my_plot + 
  theme(
    axis.title.x = 
      element_text(
                   family = "Comic Sans MS", 
                   size = 30),
    axis.title.y = 
      element_text(family = "Comic Sans MS", 
                   size = 30)
    )
```

]

]

---

# Further arguments (incomplete)

<mono>theme()</mono>

<table style="width:100%">
 <tr>
 <td> Argument </td>
 <td> Description </td>
 </tr>
 <tr>
 <td> <mono>axis.title.*</mono> </td>
 <td> Everything about the axis labels </td>
 </tr>
 <tr>
 <td> <mono>axis.ticks.*</mono> </td>
 <td> Everything about the axis tick marks </td>
 </tr>
 <tr>
 <td> <mono>axis.line.*</mono> </td>
 <td> Everything about the axis line </td>
 </tr>
 <tr>
 <td> <mono>legend.*</mono> </td>
 <td> Everything about the legend </td>
 </tr>
 <tr>
 <td> <mono>panel.*</mono> </td>
 <td> Everything about the panel (inner plot region) </td>
 </tr>
 <tr>
 <td> <mono>plot.*</mono> </td>
 <td> Everything about the plot (outer plot region) </td>
 </tr>
 <tr>
 <td> <mono>strip.*</mono> </td>
 <td> Everything about facet headers </td>
 </tr>
</table>

]

<mono>element_rect()</mono>

<table style="width:100%">
 <tr>
 <td> Argument </td>
 <td> Description </td>
 </tr>
 <tr>
 <td> <mono>fill</mono> </td>
 <td> Fill color </td>
 </tr>
 <tr>
 <td> <mono>colour</mono> </td>
 <td> Border color </td>
 </tr>
</table>

<mono>element_line()</mono>

<table style="width:100%">
 <tr>
 <td> Argument </td>
 <td> Description </td>
 </tr>
 <tr>
 <td> <mono>size</mono> </td>
 <td> Line size </td>
 </tr>
 <tr>
 <td> <mono>linetype</mono> </td>
 <td> Type of line (solid, dashed, etc.) </td>
 </tr>
</table>

<mono>element_text()</mono>

<table style="width:100%">
 <tr>
 <td> Argument </td>
 <td> Description </td>
 </tr>
 <tr>
 <td> <mono>face</mono> </td>
 <td> Font face </td>
 </tr>
 <tr>
 <td> <mono>colour</mono> </td>
 <td> Font colour </td>
 </tr>
</table>

]

---

# Create themes

```r
# define my theme
my_theme <- theme(
 panel.background = 
 element_rect(fill = 'tomato'), 
 plot.background = 
 element_rect(fill = 'burlywood'),
 panel.grid.major = element_line(
 colour = "salmon", size = 3),
 panel.grid.minor = element_line(
 colour = "seagreen", size = 1.5),
 axis.line.x = element_line(
 colour = "deeppink", size = 3.5, 
 lineend = "butt"),
 axis.line.y = element_line(
 colour = "deeppink", size = 3.5),
 axis.title.x = element_text(
 family = "Comic Sans MS", size = 30),
 axis.title.y = element_text(
 family = "Comic Sans MS", size = 30)
 )
```

]

```r
my_plot
```

]

---

# Create themes

]

```r
my_plot + my_theme
```

]

---

# Scales

<high>`Scales` control</high> many automatic aspects of the plot such as the axis limits or the color scale.

Scale functions

<table style="width:100%">
 <tr>
 <td> Function </td>
 <td> Description </td>
 </tr>
 <tr>
 <td> <mono>scale_color_*</mono>, <mono>scale_fill_*</mono> </td>
 <td> Control coloring </td>
 </tr>
 <tr>
 <td> <mono>scale_scale_xy*</mono> </td>
 <td> Control axis dimensions </td>
 </tr>
 <tr>
 <td> <mono>scale_size_*</mono> </td>
 <td> Control geom sizes </td>
 </tr>
 <tr>
 <td> <mono>scale_alpha_*</mono> </td>
 <td> Control transparency </td>
 </tr>
 <tr>
 <td> ... </td>
 <td> ... </td>
 </tr>
</table>

]

```r
# Original plot
my_plot
```

]

---

# Scales

<high>`Scales` control</high> many automatic aspects of the plot such as the axis limits or the color scale.

Scale functions

]

```r
my_plot + 
  scale_x_continuous(limits = c(1, 30))
```

]

---

# Scales

<high>`Scales` control</high> many automatic aspects of the plot such as the axis limits or the color scale.

Scale functions

]

```r
my_plot + 
  scale_x_reverse()
```

]

---

# Scales

<high>`Scales` control</high> many automatic aspects of the plot such as the axis limits or the color scale.

Scale functions

]

```r
my_plot + 
  scale_colour_hue(h = c(160, 260))
```

]

---

# Scales

<high>`Scales` control</high> many automatic aspects of the plot such as the axis limits or the color scale.

Scale functions

<table style="width:100%">
 <tr>
 <td> Function </td>
 <td> Description </td>
 </tr>
 <tr>
 <td> <mono>scale_color_*</mono>, <mono>scale_fill_*</mono> </td>
 <td> Control coloring </td>
 </tr>
 <tr>
 <td> <mono>scale_scale_xy_*</mono> </td>
 <td> Control axis dimensions </td>
 </tr>
 <tr>
 <td> <mono>scale_size_*</mono> </td>
 <td> Control geom sizes </td>
 </tr>
 <tr>
 <td> <mono>scale_alpha_*</mono> </td>
 <td> Control transparency </td>
 </tr>
 <tr>
 <td> ... </td>
 <td> ... </td>
 </tr>
</table>

]

```r
my_plot + 
  scale_size(range = c(1, 15))
```

]

---

# Multiple Plots

<ul>
 <li class="m1">The <mono>patchwork</mono> package provide a simple syntax to combine multiple plots.</li>
 <li class="m2"><mono>patchwork</mono> Syntax:</li>
 <ul class="level">
 <li><mono>+</mono> | generic add</li>
 <li><mono>|</mono> | show next to each other</li>
 <li><mono>/</mono> | show below each other</li>
 <li><mono>()</mono> | combine</li>
 <li><mono>&</mono> | apply to all</li>
 </ul>
</ul>

```r
# Save plots
pretty <- my_plot
ugly <- my_plot + my_theme
```

]

```r
pretty + ugly
```

]

---

# Multiple Plots

```r
# add themes
pretty <- my_plot
ugly <- my_plot + my_theme
```

]

```r
pretty | ugly + pretty
```

]

---

# Multiple Plots

```r
# add themes
pretty <- my_plot
ugly <- my_plot + my_theme
```

]

```r
(pretty+pretty) / (pretty+pretty)
```

]

---

# Multiple Plots

```r
# add themes
pretty <- my_plot
ugly <- my_plot + my_theme
```

]

```r
(pretty+pretty) / (pretty+pretty) &
  my_theme
```

]

---

# Multiple Plots

```r
# add themes
pretty <- my_plot
ugly <- my_plot + my_theme
```

]

```r
(pretty+pretty) / (pretty+pretty) +
  plot_annotation(tag_levels = "A") & 
  theme(legend.position = "none") 
```

]

---

# `ggsave()`

To create an <high>image file</high> of a plot (e.g., `.jpg`, `.pdf`, `.png`), use the `ggsave()` function.

Arguments

<table style="width:100%">
 <tr>
 <td> Argument </td>
 <td> Description </td>
 </tr>
 <tr>
 <td> <mono>filename</mono> </td>
 <td> Name of the to-be-created file </td>
 </tr>
 <tr>
 <td> <mono>device</mono> </td>
 <td> File type (e.g.; "pdf", "jpeg", "png") </td>
 </tr>
 <tr>
 <td> <mono>path</mono> </td>
 <td> Folder to store image in </td>
 </tr>
 <tr>
 <td> <mono>width</mono>, <mono>height</mono> </td>
 <td> Plot width, height (e.g., inches) </td>
 </tr>
</table>

]

```r
# Create my_plot object
my_plot <- ggplot(data = mpg,
 aes(x = displ, y = hwy)) + 
 geom_point() + 
 my_theme

# Create "my_plot.pdf", from my_plot
ggsave(filename = "my_plot.pdf",
       plot = my_plot,
       device = "pdf",
       path = "figures",
       width = 6, 
       height = 4)
```

]

---

# `ggsave()`

To create an <high>image file</high> of a plot (e.g., `.jpg`, `.pdf`, `.png`), use the `ggsave()` function.

Arguments

]

```r
# Create my_plot object
my_plot <- ggplot(data = mpg,
 aes(x = displ, y = hwy)) + 
 geom_point() + 
 my_theme

# Create "my_plot.png", from my_plot
ggsave(filename = "my_plot.png",
       plot = my_plot,
       device = "png",
       path = "figures",
       width = 6, 
       height = 4)
```

]

---

<h1><a href="https://dwulff.github.io/Intro2R_Unibe_2021/_sessions/PlottingII/PlottingII_practical.html">Practical</a></h1>