Visualize data with ggplot2

# Visualize data<br>with ggplot2

.class-info[
<figure>
  <img src="img/04/ggplot-logo-min.png" alt="ggplot" title="ggplot" width="15%">
</figure>
]

---

# Cars and displacement

.box-inv-1.medium[What is the relationship between a car's<br>engine weight (displacement) and its mileage (miles per gallon)?]

---

# Your turn #1

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

---

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

---

???

Source: [Wikipedia](https://en.wikipedia.org/wiki/File:National_Museum_in_Poznan_-_Przej%C5%9Bcie_przez_Berezyn%C4%99.JPG)

---

---

# Long distance!

.center[
<figure>
  <img src="img/04/napoleon-google-maps-min.png" alt="Moscow to Vilnius" title="Moscow to Vilnius" width="80%">
  <figcaption>Moscow to Vilnius</figcaption>
</figure>
]

---

# Very cold!

---

# Lots of people died!

---

???

Source: [Wikimedia Commons](https://upload.wikimedia.org/wikipedia/commons/2/29/Minard-min.png)

---

---

# Mapping data to aesthetics

.pull-left.center[

]

.box-inv-1.medium[Aesthetic]

.box-1.sp-after[Position, shape, color, etc.]

.box-inv-1.medium[Data]

]

---

# Mapping data to aesthetics

<table>
  <tr>
    <th class="cell-left">Data</th>
    <th class="cell-left">Aesthetic</th>
    <th class="cell-left">Graphic/Geometry</th>
  </tr>
  <tr>
    <td class="cell-left">Longitude</td>
    <td class="cell-left">Position (x-axis)&emsp;</td>
    <td class="cell-left">Point</td>
  </tr>
  <tr>
    <td class="cell-left">Latitude</td>
    <td class="cell-left">Position (y-axis)</td>
    <td class="cell-left">Point</td>
  </tr>
  <tr>
    <td class="cell-left">Army size</td>
    <td class="cell-left">Size</td>
    <td class="cell-left">Path</td>
  </tr>
  <tr>
    <td class="cell-left">Army direction&emsp;</td>
    <td class="cell-left">Color</td>
    <td class="cell-left">Path</td>
  </tr>
  <tr>
    <td class="cell-left">Date</td>
    <td class="cell-left">Position (x-axis)</td>
    <td class="cell-left">Line + text</td>
  </tr>
  <tr>
    <td class="cell-left">Temperature</td>
    <td class="cell-left">Position (y-axis)</td>
    <td class="cell-left">Line + text</td>
  </tr>
</table>

---

# Mapping data to aesthetics

<table>
  <tr>
    <th class="cell-left">Data</th>
    <th class="cell-left"><code class="remark-inline-code">aes()</code></th>
    <th class="cell-left"><code class="remark-inline-code">geom</code></th>
  </tr>
  <tr>
    <td class="cell-left">Longitude</td>
    <td class="cell-left"><code class="remark-inline-code">x</code></td>
    <td class="cell-left"><code class="remark-inline-code">geom_point()</code></td>
  </tr>
  <tr>
    <td class="cell-left">Latitude</td>
    <td class="cell-left"><code class="remark-inline-code">y</code></td>
    <td class="cell-left"><code class="remark-inline-code">geom_point()</code></td>
  </tr>
  <tr>
    <td class="cell-left">Army size</td>
    <td class="cell-left"><code class="remark-inline-code">size</code></td>
    <td class="cell-left"><code class="remark-inline-code">geom_path()</code></td>
  </tr>
  <tr>
    <td class="cell-left">Army direction&emsp;</td>
    <td class="cell-left"><code class="remark-inline-code">color</code>&emsp;</td>
    <td class="cell-left"><code class="remark-inline-code">geom_path()</code></td>
  </tr>
  <tr>
    <td class="cell-left">Date</td>
    <td class="cell-left"><code class="remark-inline-code">x</code></td>
    <td class="cell-left"><code class="remark-inline-code">geom_line() + geom_text()</code></td>
  </tr>
  <tr>
    <td class="cell-left">Temperature</td>
    <td class="cell-left"><code class="remark-inline-code">y</code></td>
    <td class="cell-left"><code class="remark-inline-code">geom_line() + geom_text()</code></td>
  </tr>
</table>

---

# `ggplot()` template

<code class ='r hljs remark-code'>ggplot(data = <b><span style="background-color:#CBB5FF">DATA</span></b>) +<br>&nbsp;&nbsp;<b><span style="background-color:#FFDFD1">GEOM_FUNCTION</span></b>(mapping = aes(<b><span style="background-color:#FFD0CF">AESTHETIC MAPPINGS</span></b>))</code>

<code class ='r hljs remark-code'>ggplot(data = <b><span style="background-color:#CBB5FF">troops</span></b>) +<br>&nbsp;&nbsp;<b><span style="background-color:#FFDFD1">geom_path</span></b>(mapping = aes(<b><span style="background-color:#FFD0CF">x = longitude</span></b>,<br>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<b><span style="background-color:#FFD0CF">y = latitude</span></b>,<br>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<b><span style="background-color:#FFD0CF">color = direction</span></b>,<br>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<b><span style="background-color:#FFD0CF">size = survivors</span></b>))</code>

---

<table>
 <thead>
  <tr>
   <th style="text-align:left;"> longitude </th>
   <th style="text-align:left;"> latitude </th>
   <th style="text-align:left;"> direction </th>
   <th style="text-align:left;"> survivors </th>
  </tr>
 </thead>
<tbody>
  <tr>
   <td style="text-align:left;"> 24 </td>
   <td style="text-align:left;"> 54.9 </td>
   <td style="text-align:left;"> A </td>
   <td style="text-align:left;"> 340000 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> 24.5 </td>
   <td style="text-align:left;"> 55 </td>
   <td style="text-align:left;"> A </td>
   <td style="text-align:left;"> 340000 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> … </td>
   <td style="text-align:left;"> … </td>
   <td style="text-align:left;"> … </td>
   <td style="text-align:left;"> … </td>
  </tr>
</tbody>
</table>

]

---

---

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

---

---

# Heavy cars with better mileage?

---

# Aesthetics

.box-inv-1.small[`color` (discrete)]

.box-inv-1.small[`color` (continuous)]

<img src="04_visualize-data_files/figure-html/aes-color-continuous-1.png" width="100%" style="display: block; margin: auto;" />
]

.box-inv-1.small[`size`]

.box-inv-1.small[`fill`]

<img src="04_visualize-data_files/figure-html/aes-fill-1.png" width="100%" style="display: block; margin: auto;" />
]

.box-inv-1.small[`shape`]

.box-inv-1.small[`alpha`]

<img src="04_visualize-data_files/figure-html/aes-alpha-1.png" width="100%" style="display: block; margin: auto;" />
]

---

# Mapping columns to aesthetics

```r
ggplot(mpg) + geom_point(aes(x = displ, y = hwy, color = class))
ggplot(mpg) + geom_point(aes(x = displ, y = hwy, size = class))
ggplot(mpg) + geom_point(aes(x = displ, y = hwy, shape = class))
ggplot(mpg) + geom_point(aes(x = displ, y = hwy, alpha = class))
```
]

---

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

---

# Your turn #2

---

# How would you make this plot?

---

```r
ggplot(mpg) +
  geom_point(aes(x = displ, y = hwy, 
                 color = class))
```
]

---

```r
ggplot(mpg) +
  geom_point(aes(x = displ, y = hwy), 
             color = "blue")
```
]

---

```r
ggplot(mpg) +
  geom_point(aes(x = displ, y = hwy, 
                 color = "blue"))
```

<img src="04_visualize-data_files/figure-html/unnamed-chunk-9-1.png" width="100%" style="display: block; margin: auto;" />
]
]

```r
ggplot(mpg) +
  geom_point(aes(x = displ, y = hwy), 
             color = "blue")
```

<img src="04_visualize-data_files/figure-html/unnamed-chunk-10-1.png" width="100%" style="display: block; margin: auto;" />
]
]

---

---

# What's the same? What's different?

.pull-left[
<img src="04_visualize-data_files/figure-html/unnamed-chunk-11-1.png" width="100%" style="display: block; margin: auto;" />
]

.pull-right[
<img src="04_visualize-data_files/figure-html/unnamed-chunk-12-1.png" width="100%" style="display: block; margin: auto;" />
]

---

# Geoms

---

# Possible geoms

<table>
  <tr>
    <th class="cell-left"></th>
    <th class="cell-left">Example geom</th>
    <th class="cell-left">What it makes</th>
  </tr>
  <tr>
    <td class="cell-left"><img src="img/04/geom_bar-min.png"></td>
    <td class="cell-left"><code class="remark-inline-code">geom_col()</code></td>
    <td class="cell-left">Bar charts</td>
  </tr>
  <tr>
    <td class="cell-left"><img src="img/04/geom_text-min.png"></td>
    <td class="cell-left"><code class="remark-inline-code">geom_text()</code></td>
    <td class="cell-left">Text</td>
  </tr>
  <tr>
    <td class="cell-left"><img src="img/04/geom_point-min.png"></td>
    <td class="cell-left"><code class="remark-inline-code">geom_point()</code></td>
    <td class="cell-left">Points</td>
  </tr>
  <tr>
    <td class="cell-left"><img src="img/04/geom_boxplot-min.png"></td>
    <td class="cell-left"><code class="remark-inline-code">geom_boxplot()</code>&emsp;</td>
    <td class="cell-left">Boxplots</td>
  </tr>
  <tr>
    <td class="cell-left"><img src="img/04/geom_sf-min.png"></td>
    <td class="cell-left"><code class="remark-inline-code">geom_sf()</code></td>
    <td class="cell-left">Maps</td>
  </tr>
</table>

---

# Possible geoms

.box-1[See [the **ggplot2** documentation](https://ggplot2.tidyverse.org/reference/index.html#section-layer-geoms) for<br>complete examples of all the different geom layers]

---

# Your turn #3

.pull-left[
<img src="04_visualize-data_files/figure-html/unnamed-chunk-13-1.png" width="100%" style="display: block; margin: auto;" />
]

.pull-right[
<img src="04_visualize-data_files/figure-html/unnamed-chunk-14-1.png" width="100%" style="display: block; margin: auto;" />
]

---

# Your turn #4

---

# Your turn #5

.box-1[Make this density plot of `hwy` colored by `class`.<br>Use the cheatsheet. Hint: don't supply a `y` variable.]

---

# Complex graphs!

---

# Your turn #6

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

---

# Global vs. local

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

<img src="04_visualize-data_files/figure-html/unnamed-chunk-21-1.png" width="60%" style="display: block; margin: auto;" />
]

---

# Global vs. local

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

<img src="04_visualize-data_files/figure-html/unnamed-chunk-22-1.png" width="60%" style="display: block; margin: auto;" />
]

---

---

# So much more!

.box-inv-1[We sequentially add layers onto the foundational `ggplot()` plot to create complex figures]
]

---

# Putting it all together

.box-inv-1.medium[We can build a plot sequentially<br>to see how each grammatical layer<br>changes the appearance]

---

```r
*ggplot(data = mpg,
*      mapping = aes(x = displ,
*                    y = hwy,
*                    color = drv))
```
]

---

```r
ggplot(data = mpg,
       mapping = aes(x = displ,
                     y = hwy,
                     color = drv)) +
* geom_point()
```
]

---

```r
ggplot(data = mpg,
       mapping = aes(x = displ,
                     y = hwy,
                     color = drv)) +
  geom_point() +
* geom_smooth()
```
]

---

```r
ggplot(data = mpg,
       mapping = aes(x = displ,
                     y = hwy,
                     color = drv)) +
  geom_point() +
* geom_smooth(method = "lm")
```
]

---

```r
ggplot(data = mpg,
       mapping = aes(x = displ,
                     y = hwy,
                     color = drv)) +
  geom_point() +
  geom_smooth(method = "lm") +
* scale_color_viridis_d()
```
]

---

```r
ggplot(data = mpg,
       mapping = aes(x = displ,
                     y = hwy,
                     color = drv)) +
  geom_point() +
  geom_smooth(method = "lm") +
  scale_color_viridis_d() +
* facet_wrap(vars(drv), ncol = 1)
```
]

---

```r
ggplot(data = mpg,
       mapping = aes(x = displ,
                     y = hwy,
                     color = drv)) +
  geom_point() +
  geom_smooth(method = "lm") +
  scale_color_viridis_d() +
  facet_wrap(vars(drv), ncol = 1) +
* labs(x = "Displacement", y = "Highway MPG",
*      color = "Drive",
*      title = "Heavier cars get lower mileage",
*      subtitle = "Displacement indicates weight(?)",
*      caption = "I know nothing about cars")
```
]

---

```r
ggplot(data = mpg,
       mapping = aes(x = displ,
                     y = hwy,
                     color = drv)) +
  geom_point() +
  geom_smooth(method = "lm") +
  scale_color_viridis_d() +
  facet_wrap(vars(drv), ncol = 1) +
  labs(x = "Displacement", y = "Highway MPG",
       color = "Drive", 
       title = "Heavier cars get lower mileage",
       subtitle = "Displacement indicates weight(?)",
       caption = "I know nothing about cars") +
* theme_bw()
```
]

---

```r
ggplot(data = mpg, 
       mapping = aes(x = displ,
                     y = hwy,
                     color = drv)) +
  geom_point() +
  geom_smooth(method = "lm") +
  scale_color_viridis_d() +
  facet_wrap(vars(drv), ncol = 1) +
  labs(x = "Displacement", y = "Highway MPG",
       color = "Drive", 
       title = "Heavier cars get lower mileage",
       subtitle = "Displacement indicates weight(?)",
       caption = "I know nothing about cars") +
  theme_bw() +
* theme(legend.position = "bottom",
*       plot.title = element_text(face = "bold"))
```
]

---

```r
ggplot(data = mpg, 
       mapping = aes(x = displ,
                     y = hwy,
                     color = drv)) +
  geom_point() +
  geom_smooth(method = "lm") + 
  scale_color_viridis_d() +
  facet_wrap(vars(drv), ncol = 1) +
  labs(x = "Displacement", y = "Highway MPG",
       color = "Drive", 
       title = "Heavier cars get lower mileage",
       subtitle = "Displacement indicates weight(?)",
       caption = "I know nothing about cars") +
  theme_bw() +
  theme(legend.position = "bottom",
        plot.title = element_text(face = "bold"))
```
]

---

---

# So many possibilities!

.box-1[See [the **ggplot2** documentation](https://ggplot2.tidyverse.org/reference/index.html) for<br>complete examples of everything you can do]
]

---

# A true grammar

.box-1.small[Hunt through Excel menus for a stacked bar chart and manually reshape your data to work with it]
]

.pull-right[
.center[
<figure>
  <img src="img/04/excel-chart-types-min.png" alt="Excel chart types" title="Excel chart types" width="78%">
</figure>
]
]

---

# A true grammar

.box-1.small[Map a column to the x-axis, fill by a different variable, and `geom_col()` to get stacked bars]

.box-1.small[Geoms can be interchangable<br>(e.g. switch `geom_violin()` to `geom_boxplot()`)]
]

.pull-right[
.center[
<figure>
  <img src="img/04/ggplot-layers@4x-min.png" alt="Grammar of graphics layers" title="Grammar of graphics layers" width="100%">
</figure>
]
]

---

# Describing graphs with the grammar

.left-code[
.box-1.small[Map wealth to the x-axis, health to the y-axis, add points, color by continent, size by population, scale the y-axis with a log, and facet by year]

```r
ggplot(filter(gapminder, 
              year %in% c(2002, 2007)), 
       aes(x = gdpPercap,
           y = lifeExp,
           color = continent,
           size = pop)) +
  geom_point() +
  scale_x_log10() + 
  facet_wrap(vars(year), ncol = 1)
```
]

---

# Describing graphs with the grammar

.left-code[
.box-1.small[Map health to the x-axis, add a histogram with bins for every 5 years, fill and facet by continent]

```r
ggplot(gapminder_2007, 
       aes(x = lifeExp,
           fill = continent)) +
  geom_histogram(binwidth = 5, 
                 color = "white") +
  guides(fill = FALSE) +  # Turn off legend
  facet_wrap(vars(continent))
```
]

---

# Describing graphs with the grammar

.left-code[
.box-1.small[Map continent to the x-axis, health to the y-axis, add violin plots and semi-transparent boxplots, fill by continent]

```r
ggplot(gapminder, 
       aes(x = continent,
           y = lifeExp,
           fill = continent)) +
  geom_violin() +
  geom_boxplot(alpha = 0.5) +
  guides(fill = FALSE)  # Turn off legend
```
]

---

# Scales

<table>
  <tr>
    <th class="cell-left">Example layer</th>
    <th class="cell-left">What it does</th>
  </tr>
  <tr>
    <td class="cell-left"><code class="remark-inline-code">scale_x_continuous()</code></td>
    <td class="cell-left">Make the x-axis continuous</td>
  </tr>
  <tr>
    <td class="cell-left"><code class="remark-inline-code">scale_x_continuous(breaks = 1:5)&ensp;</code></td>
    <td class="cell-left">Manually specify axis ticks</td>
  </tr>
  <tr>
    <td class="cell-left"><code class="remark-inline-code">scale_x_log10()</code></td>
    <td class="cell-left">Log the x-axis</td>
  </tr>
  <tr>
    <td class="cell-left"><code class="remark-inline-code">scale_color_gradient()</code></td>
    <td class="cell-left">Use a gradient</td>
  </tr>
  <tr>
    <td class="cell-left"><code class="remark-inline-code">scale_fill_viridis_d()</code></td>
    <td class="cell-left">Fill with discrete viridis colors</td>
  </tr>
</table>

---

# Scales

.box-inv-1.small[`scale_x_log10()`]

<img src="04_visualize-data_files/figure-html/scale-example-1-1.png" width="100%" style="display: block; margin: auto;" />
]

.box-inv-1.small[`scale_color_viridis_d()`]

<img src="04_visualize-data_files/figure-html/scale-example-2-1.png" width="100%" style="display: block; margin: auto;" />
]

---

# Your turn #7

.box-1.small[For bonus fun, try a different viridis option like `plasma` or `inferno`.]

---

```r
ggplot(mpg, 
       aes(x = displ, 
           fill = drv)) +
  geom_density(alpha = 0.75) +
  scale_fill_viridis_d(option = "plasma")
```
]

---

---

# Facets

<table>
  <tr>
    <th class="cell-left">Example layer</th>
    <th class="cell-left">What it does</th>
  </tr>
  <tr>
    <td class="cell-left"><code class="remark-inline-code">facet_wrap(vars(continent))</code></td>
    <td class="cell-left">Plot for each continent</td>
  </tr>
  <tr>
    <td class="cell-left"><code class="remark-inline-code">facet_wrap(vars(continent, year))</code>&emsp;</td>
    <td class="cell-left">Plot for each continent/year</td>
  </tr>
  <tr>
    <td class="cell-left"><code class="remark-inline-code">facet_wrap(..., ncol = 1)</code></td>
    <td class="cell-left">Put all facets in one column</td>
  </tr>
  <tr>
    <td class="cell-left"><code class="remark-inline-code">facet_wrap(..., nrow = 1)</code></td>
    <td class="cell-left">Put all facets in one row</td>
  </tr>
</table>

---

# Facets

.box-inv-1.small[`facet_wrap(vars(continent))`]

<img src="04_visualize-data_files/figure-html/facet-example-1-1.png" width="100%" style="display: block; margin: auto;" />
]

.box-inv-1.small[`facet_wrap(vars(continent, year))`]

<img src="04_visualize-data_files/figure-html/facet-example-2-1.png" width="100%" style="display: block; margin: auto;" />
]

---

# Your turn #8

---

```r
ggplot(mpg, 
       aes(x = displ, 
           y = hwy, 
           color = class)) +
  geom_point() +
  facet_wrap(vars(drv))
```
]

---

---

# Coordinates

<table>
  <tr>
    <th class="cell-left">Example layer</th>
    <th class="cell-left">What it does</th>
  </tr>
  <tr>
    <td class="cell-left"><code class="remark-inline-code">coord_cartesian()</code></td>
    <td class="cell-left">Standard x-y coordinate system</td>
  </tr>
  <tr>
    <td class="cell-left"><code class="remark-inline-code">coord_cartesian(ylim = c(1, 10))</code>&emsp;</td>
    <td class="cell-left">Zoom in where y is 1–10</td>
  </tr>
  <tr>
    <td class="cell-left"><code class="remark-inline-code">coord_flip()</code></td>
    <td class="cell-left">Switch x and y</td>
  </tr>
  <tr>
    <td class="cell-left"><code class="remark-inline-code">coord_polar()</code></td>
    <td class="cell-left">Use circular polar system</td>
  </tr>
</table>

---

# Coordinates

.box-inv-1.small[`coord_cartesian(ylim = c(70, 80), xlim = c(10000, 30000))`]

<img src="04_visualize-data_files/figure-html/coord-example-1-1.png" width="100%" style="display: block; margin: auto;" />
]

.box-inv-1.small[`coord_flip()`]

<img src="04_visualize-data_files/figure-html/coord-example-2-1.png" width="100%" style="display: block; margin: auto;" />
]

---

# Labels

<table>
  <tr>
    <th class="cell-left">Example layer</th>
    <th class="cell-left">What it does</th>
  </tr>
  <tr>
    <td class="cell-left"><code class="remark-inline-code">labs(title = "Neat title")</code></td>
    <td class="cell-left">Title</td>
  </tr>
  <tr>
    <td class="cell-left"><code class="remark-inline-code">labs(caption = "Something")</td>
    <td class="cell-left">Caption</td>
  </tr>
  <tr>
    <td class="cell-left"><code class="remark-inline-code">labs(y = "Something")</td>
    <td class="cell-left">y-axis</td>
  </tr>
  <tr>
    <td class="cell-left"><code class="remark-inline-code">labs(size = "Population")</code></td>
    <td class="cell-left">Title of size legend</td>
  </tr>
</table>

---

# Labels

```r
ggplot(gapminder_2007, 
       aes(x = gdpPercap, y = lifeExp, 
           color = continent, size = pop)) +
  geom_point() +
  scale_x_log10() +
  labs(title = "Health and wealth grow together",
       subtitle = "Data from 2007",
       x = "Wealth (GDP per capita)",
       y = "Health (life expectancy)",
       color = "Continent",
       size = "Population",
       caption = "Source: The Gapminder Project")
```
]

---

# Theme

<table>
  <tr>
    <th class="cell-left">Example layer</th>
    <th class="cell-left">What it does</th>
  </tr>
  <tr>
    <td class="cell-left"><code class="remark-inline-code">theme_grey()</code></td>
    <td class="cell-left">Default grey background</td>
  </tr>
  <tr>
    <td class="cell-left"><code class="remark-inline-code">theme_bw()</td>
    <td class="cell-left">Black and white</td>
  </tr>
  <tr>
    <td class="cell-left"><code class="remark-inline-code">theme_dark()</td>
    <td class="cell-left">Dark</td>
  </tr>
  <tr>
    <td class="cell-left"><code class="remark-inline-code">theme_minimal()</code></td>
    <td class="cell-left">Minimal</td>
  </tr>
</table>

---

# Theme

.box-inv-1.small[`theme_dark()`]

<img src="04_visualize-data_files/figure-html/theme-example-1-1.png" width="100%" style="display: block; margin: auto;" />
]

.box-inv-1.small[`theme_minimal()`]

<img src="04_visualize-data_files/figure-html/theme-example-2-1.png" width="100%" style="display: block; margin: auto;" />
]

---

# Theme

.box-inv-1[There are collections of pre-built themes online,<br>like [the **ggthemes** package](https://jrnold.github.io/ggthemes/)]

.center[
<figure>
  <img src="img/04/ggthemes-min.png" alt="ggthemes" title="ggthemes" width="45%">
</figure>
]

---

# Theme

.box-inv-1[Organizations often make their own custom themes, [like the BBC](https://bbc.github.io/rcookbook/)]

.center[
<figure>
  <img src="img/04/bbc-cookbook-min.png" alt="BBC ggplot theme" title="BBC ggplot theme" width="80%">
</figure>
]

---

# Theme options

```r
theme_bw() + 
theme(legend.position = "bottom",
      plot.title = element_text(face = "bold"),
      panel.grid = element_blank(),
      axis.title.y = element_text(face = "italic"))
```

---

# Saving graphs

.box-inv-1.medium[Use `ggsave()` to save a plot to your computer]

```r
my_plot <- ggplot(...)

ggsave("plot_name.pdf", my_plot, width = 5, height = 3.5)
ggsave("plot_name.png", my_plot, width = 5, height = 3.5)
```

---

# Next up

.box-inv-1.medium[Transforming and<br>manipulating data with dplyr]