Data Visualization

# Data Visualization

## Small multiples and patchwork

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## Setup

* **Option 1**: Download and unzip today's materials into `glhlth562/materials` on YOUR computer
* **Option 2**: Download then upload today's materials into `glhlth562/materials` in the cloud
* **Option 3**: Pull updates from [github](https://github.com/ericpgreen/glhlth562) (assuming you cloned this repo previously)

---

### Your data are probably grouped

]

```r
gapminder %>% 
  select(country, year, gdpPercap) %>% 
  arrange(year)
```

```
## # A tibble: 1,704 × 3
##    country      year gdpPercap
##    <fct>       <int>     <dbl>
##  1 Afghanistan  1952      779.
##  2 Albania      1952     1601.
##  3 Algeria      1952     2449.
##  4 Angola       1952     3521.
##  5 Argentina    1952     5911.
##  6 Australia    1952    10040.
##  7 Austria      1952     6137.
##  8 Bahrain      1952     9867.
##  9 Bangladesh   1952      684.
## 10 Belgium      1952     8343.
## # … with 1,694 more rows
```

]

How do you tell `ggplot()` that your data are grouped?

```r
# see chunk 'grouped'
ggplot(data = gapminder,
       mapping = aes(x = year,
                     y = gdpPercap)) +
  geom_line() 
```

]
]

---

### You probably need more than one plot

```r
# see chunk 'need'
ggplot(data = gapminder,
       mapping = aes(x = year,
                     y = gdpPercap)) +
  geom_line(aes(group = country)) 
```

]

]

]

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background-image: url("data:image/png;base64,#img/smurfs.png")

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### `facet_wrap()`

```r
# see chunk 'wrap'
ggplot(gapminder, aes(x = year, 
                      y = gdpPercap)) + 
  geom_line(color="gray70", aes(group = country)) +
  geom_smooth(size = 1.1, method = "loess", se = FALSE) +
  scale_y_log10(labels=scales::dollar) +
  facet_wrap(~ continent, ncol = 5) + # HERE!!
  labs(x = "Year",
       y = "GDP per capita",
       title = "GDP per capita on Five Continents")
```

]

]

.panel[.panel-name[Your Turn]
* Change `ncol = 5` to `ncol = 4`, run, and then replace it with `nrow = 5`
* Replace `continent` in `facet_wrap(~ continent, ncol = 5)` with `country` 
]

]

---

### `facet_grid()`

```r
# see chunk 'grid'
ggplot(gss_sm,
       aes(x = age, y = childs)) + 
  geom_point(alpha = 0.2) +
  geom_smooth() +
  facet_grid(sex ~ race)
```

]

]

.panel[.panel-name[Your Turn]
* Swap `sex` and `race` in the `facet_grid()` formula
* Change the `alpha` value
* Comment out `geom_smooth()`
* Add `size=5` to `geom_point()`
]

]

---

### Arrange multiple plots with patchwork

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### Patchwork

```r
# see chunk 'patch'
p1 <- ggplot(data = penguins, aes(x = flipper_length_mm)) +
  geom_histogram(aes(fill = species),
                 alpha = 0.5,
                 position = "identity") +
  scale_fill_manual(values = c("darkorange","purple","cyan4")) +
  theme_minimal() +
  labs(x = "Flipper length (mm)",
       y = "Frequency",
       title = "Plot 1")

p2 <- ggplot(data = penguins, aes(x=species, 
                                  y = flipper_length_mm, 
                                  fill=species)) +
  geom_violin() + 
  scale_fill_manual(values = c("darkorange","purple","cyan4")) +
  theme_minimal() +
  labs(y = "Flipper length (mm)",
       x = NULL,
       title = "Plot 2") + 
  theme(legend.position = "none")

p3 <- ggplot(penguins, aes(x = species)) +
  geom_bar(alpha = 0.8) +
  theme_minimal() +
  labs(title = "Plot 3")

p4 <- penguins %>%
  remove_missing() %>% group_by(species) %>% 
  summarise(mean_bmg = mean(body_mass_g)) %>%
  ggplot() +
    geom_segment(aes(x = 0, xend = mean_bmg,
                     y = reorder(species, mean_bmg),
                     yend = reorder(species, mean_bmg)),
                 color = "grey", size = 2) +
    geom_point(aes(y = reorder(species, mean_bmg), x = mean_bmg),
               size = 5, color = "darkorange") +
    labs(x = NULL, y = NULL, title = "Plot 4", 
         subtitle = "Average body mass (g) by species") +
    theme_minimal() +
    theme(plot.title = element_text(face="bold"),
          plot.title.position = "plot")
```

]

```r
(p1 + p2) / (p3 + p4)
```

]

Review the layout options at [https://tinyurl.com/patchopt](https://tinyurl.com/patchopt) and experiment with new configurations and adding annotations
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# Credits

Deck by Eric Green ([@ericpgreen](https://twitter.com/ericpgreen)), licensed under Creative Commons Attribution [CC BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0/)
* {[`xaringan`](https://github.com/yihui/xaringan)} for slides with help from {[`xaringanExtra`](https://github.com/gadenbuie/xaringanExtra)}