Facet

class: center, middle, inverse, title-slide

# Facet
### Gina Reynolds

---

---

name: facets

# Punctuation: Small multiples

Punctuation helps us break up language into digestible pieces. Breaking up visualization can also be helpful.

Creating *small multiples* also known as *faceting* is a powerful way to make data more digestible; we can process the encoding in just one of the plots easily translate those encodings to the remaining plots.   In ggplot, small plots based on a categorical variable can be visualized side-by-side.

---

class: split-40
count: false

.left-panel-facets-rotate[

```r
gapminder %>%  
  filter(year == 2002) %>%  
  ggplot() +  
  aes(x = gdpPercap / 1000) +  
  aes(y = lifeExp) +  
  geom_point() +  
  aes(color = continent) +  
  NULL   
```
]
 
.right-panel-facets-rotate[
<img src="facet_files/figure-html/facets_rotate_1_output-1.png" width="100%" />
]

---
class: split-40
count: false

.left-panel-facets-rotate[

```r
gapminder %>%  
  filter(year == 2002) %>%  
  ggplot() +  
  aes(x = gdpPercap / 1000) +  
  aes(y = lifeExp) +  
  geom_point() +  
  aes(color = continent) +  
* facet_wrap(vars(continent))
```
]
 
.right-panel-facets-rotate[
<img src="facet_files/figure-html/facets_rotate_2_output-1.png" width="100%" />
]

---
class: split-40
count: false

.left-panel-facets-rotate[

```r
gapminder %>%  
  filter(year == 2002) %>%  
  ggplot() +  
  aes(x = gdpPercap / 1000) +  
  aes(y = lifeExp) +  
  geom_point() +  
  aes(color = continent) +  
* facet_wrap(vars(continent), ncol = 2)
```
]
 
.right-panel-facets-rotate[
<img src="facet_files/figure-html/facets_rotate_3_output-1.png" width="100%" />
]

---
class: split-40
count: false

.left-panel-facets-rotate[

```r
gapminder %>%  
  filter(year == 2002) %>%  
  ggplot() +  
  aes(x = gdpPercap / 1000) +  
  aes(y = lifeExp) +  
  geom_point() +  
  aes(color = continent) +  
* facet_wrap(vars(continent), nrow = 1)
```
]
 
.right-panel-facets-rotate[
<img src="facet_files/figure-html/facets_rotate_4_output-1.png" width="100%" />
]

---
class: split-40
count: false

.left-panel-facets-rotate[

```r
gapminder %>%  
  filter(year == 2002) %>%  
  ggplot() +  
  aes(x = gdpPercap / 1000) +  
  aes(y = lifeExp) +  
  geom_point() +  
  aes(color = continent) +  
* facet_wrap(vars(continent), scales = "free_x")
```
]
 
.right-panel-facets-rotate[
<img src="facet_files/figure-html/facets_rotate_5_output-1.png" width="100%" />
]

---
class: split-40
count: false

.left-panel-facets-rotate[

```r
gapminder %>%  
  filter(year == 2002) %>%  
  ggplot() +  
  aes(x = gdpPercap / 1000) +  
  aes(y = lifeExp) +  
  geom_point() +  
  aes(color = continent) +  
* facet_wrap(vars(continent), scales = "free_x")
```
]
 
.right-panel-facets-rotate[
<img src="facet_files/figure-html/facets_rotate_6_output-1.png" width="100%" />
]

---
class: split-40
count: false

.left-panel-facets-rotate[

```r
gapminder %>%  
  filter(year == 2002) %>%  
  ggplot() +  
  aes(x = gdpPercap / 1000) +  
  aes(y = lifeExp) +  
  geom_point() +  
  aes(color = continent) +  
* facet_wrap(vars(continent), scales = "free")
```
]
 
.right-panel-facets-rotate[
<img src="facet_files/figure-html/facets_rotate_7_output-1.png" width="100%" />
]

---
class: split-40
count: false

.left-panel-facets-rotate[

```r
gapminder %>%  
  filter(year == 2002) %>%  
  ggplot() +  
  aes(x = gdpPercap / 1000) +  
  aes(y = lifeExp) +  
  geom_point() +  
  aes(color = continent) +  
* facet_wrap(vars(continent), strip.position = "top")
```
]
 
.right-panel-facets-rotate[
<img src="facet_files/figure-html/facets_rotate_8_output-1.png" width="100%" />
]

---
class: split-40
count: false

.left-panel-facets-rotate[

```r
gapminder %>%  
  filter(year == 2002) %>%  
  ggplot() +  
  aes(x = gdpPercap / 1000) +  
  aes(y = lifeExp) +  
  geom_point() +  
  aes(color = continent) +  
* facet_wrap(vars(continent), strip.position = "bottom")
```
]
 
.right-panel-facets-rotate[
<img src="facet_files/figure-html/facets_rotate_9_output-1.png" width="100%" />
]

---
class: split-40
count: false

.left-panel-facets-rotate[

```r
gapminder %>%  
  filter(year == 2002) %>%  
  ggplot() +  
  aes(x = gdpPercap / 1000) +  
  aes(y = lifeExp) +  
  geom_point() +  
  aes(color = continent) +  
* facet_wrap(vars(continent), strip.position = "left")
```
]
 
.right-panel-facets-rotate[
<img src="facet_files/figure-html/facets_rotate_10_output-1.png" width="100%" />
]

---
class: split-40
count: false

.left-panel-facets-rotate[

```r
gapminder %>%  
  filter(year == 2002) %>%  
  ggplot() +  
  aes(x = gdpPercap / 1000) +  
  aes(y = lifeExp) +  
  geom_point() +  
  aes(color = continent) +  
* facet_wrap(vars(continent), strip.position = "right")
```
]
 
.right-panel-facets-rotate[
<img src="facet_files/figure-html/facets_rotate_11_output-1.png" width="100%" />
]

---
class: split-40
count: false

.left-panel-facets-rotate[

```r
gapminder %>%  
  filter(year == 2002) %>%  
  ggplot() +  
  aes(x = gdpPercap / 1000) +  
  aes(y = lifeExp) +  
  geom_point() +  
  aes(color = continent) +  
* facet_grid(continent ~ pop > 10000000)
```
]
 
.right-panel-facets-rotate[
<img src="facet_files/figure-html/facets_rotate_12_output-1.png" width="100%" />
]

---
class: split-40
count: false

.left-panel-facets-rotate[

```r
gapminder %>%  
  filter(year == 2002) %>%  
  ggplot() +  
  aes(x = gdpPercap / 1000) +  
  aes(y = lifeExp) +  
  geom_point() +  
  aes(color = continent) +  
* facet_grid(continent ~ pop > 10000000, switch = "x")   # y also possible
```
]
 
.right-panel-facets-rotate[
<img src="facet_files/figure-html/facets_rotate_13_output-1.png" width="100%" />
]

---
class: split-40
count: false

.left-panel-facets-rotate[

```r
gapminder %>%  
  filter(year == 2002) %>%  
  ggplot() +  
  aes(x = gdpPercap / 1000) +  
  aes(y = lifeExp) +  
  geom_point() +  
  aes(color = continent) +  
* facet_grid(continent ~ pop > 10000000, switch = "both")
```
]
 
.right-panel-facets-rotate[
<img src="facet_files/figure-html/facets_rotate_14_output-1.png" width="100%" />
]

---
class: split-40
count: false

.left-panel-facets-rotate[

```r
gapminder %>%  
  filter(year == 2002) %>%  
  ggplot() +  
  aes(x = gdpPercap / 1000) +  
  aes(y = lifeExp) +  
  geom_point() +  
  aes(color = continent) +  
* facet_grid(. ~ continent)
```
]
 
.right-panel-facets-rotate[
<img src="facet_files/figure-html/facets_rotate_15_output-1.png" width="100%" />
]

---
class: split-40
count: false

.left-panel-facets-rotate[

```r
gapminder %>%  
  filter(year == 2002) %>%  
  ggplot() +  
  aes(x = gdpPercap / 1000) +  
  aes(y = lifeExp) +  
  geom_point() +  
  aes(color = continent) +  
* ggforce::facet_col(facets = vars(continent), scales = "free_y", space = "free", strip.position = "top")
```
]
 
.right-panel-facets-rotate[
<img src="facet_files/figure-html/facets_rotate_16_output-1.png" width="100%" />
]

---
class: split-40
count: false

.left-panel-facets-rotate[

```r
gapminder %>%  
  filter(year == 2002) %>%  
  ggplot() +  
  aes(x = gdpPercap / 1000) +  
  aes(y = lifeExp) +  
  geom_point() +  
  aes(color = continent) +  
* ggforce::facet_col(facets = vars(continent), scales = "free_y", space = "free", strip.position = "left")
```
]
 
.right-panel-facets-rotate[
<img src="facet_files/figure-html/facets_rotate_17_output-1.png" width="100%" />
]

---
class: split-40
count: false

.left-panel-facets-rotate[

```r
gapminder %>%  
  filter(year == 2002) %>%  
  ggplot() +  
  aes(x = gdpPercap / 1000) +  
  aes(y = lifeExp) +  
  geom_point() +  
  aes(color = continent) +  
* facet_grid(facets = continent ~ .)
```
]
 
.right-panel-facets-rotate[
<img src="facet_files/figure-html/facets_rotate_18_output-1.png" width="100%" />
]

---
class: split-40
count: false

.left-panel-facets-rotate[

```r
gapminder %>%  
  filter(year == 2002) %>%  
  ggplot() +  
  aes(x = gdpPercap / 1000) +  
  aes(y = lifeExp) +  
  geom_point() +  
  aes(color = continent) +  
* facet_grid(rows = vars(continent))
```
]
 
.right-panel-facets-rotate[
<img src="facet_files/figure-html/facets_rotate_19_output-1.png" width="100%" />
]

---
class: split-40
count: false

.left-panel-facets-rotate[

```r
gapminder %>%  
  filter(year == 2002) %>%  
  ggplot() +  
  aes(x = gdpPercap / 1000) +  
  aes(y = lifeExp) +  
  geom_point() +  
  aes(color = continent) +  
* facet_grid(cols = vars(continent))
```
]
 
.right-panel-facets-rotate[
<img src="facet_files/figure-html/facets_rotate_20_output-1.png" width="100%" />
]

---
class: split-40
count: false

.left-panel-facets-rotate[

```r
gapminder %>%  
  filter(year == 2002) %>%  
  ggplot() +  
  aes(x = gdpPercap / 1000) +  
  aes(y = lifeExp) +  
  geom_point() +  
  aes(color = continent) +  
* facet_grid(vars(continent), vars(pop > 10000000))
```
]
 
.right-panel-facets-rotate[
<img src="facet_files/figure-html/facets_rotate_21_output-1.png" width="100%" />
]

---
class: split-40
count: false

.left-panel-facets-rotate[

```r
gapminder %>%  
  filter(year == 2002) %>%  
  ggplot() +  
  aes(x = gdpPercap / 1000) +  
  aes(y = lifeExp) +  
  geom_point() +  
  aes(color = continent) +  
* facet_wrap(vars(continent, pop > 10000000), scales = "free_y")
```
]
 
.right-panel-facets-rotate[
<img src="facet_files/figure-html/facets_rotate_22_output-1.png" width="100%" />
]

---
class: split-40
count: false

.left-panel-facets-rotate[

```r
gapminder %>%  
  filter(year == 2002) %>%  
  ggplot() +  
  aes(x = gdpPercap / 1000) +  
  aes(y = lifeExp) +  
  geom_point() +  
  aes(color = continent) +  
* ggforce::facet_zoom(xlim = c(5,10), horizontal = FALSE)
```
]
 
.right-panel-facets-rotate[
<img src="facet_files/figure-html/facets_rotate_23_output-1.png" width="100%" />
]

---
class: split-40
count: false

.left-panel-facets-rotate[

```r
gapminder %>%  
  filter(year == 2002) %>%  
  ggplot() +  
  aes(x = gdpPercap / 1000) +  
  aes(y = lifeExp) +  
  geom_point() +  
  aes(color = continent) +  
* ggforce::facet_zoom(xlim = c(20, 25), ylim = c(65, 80), horizontal = FALSE)
```
]
 
.right-panel-facets-rotate[
<img src="facet_files/figure-html/facets_rotate_24_output-1.png" width="100%" />
]

---
class: split-40
count: false

.left-panel-facets-rotate[

```r
gapminder %>%  
  filter(year == 2002) %>%  
  ggplot() +  
  aes(x = gdpPercap / 1000) +  
  aes(y = lifeExp) +  
  geom_point() +  
  aes(color = continent) +  
* facet_null()  # overrides any faceting
```
]
 
.right-panel-facets-rotate[
<img src="facet_files/figure-html/facets_rotate_25_output-1.png" width="100%" />
]

<style>
.left-panel-facets-rotate {
  color: #777;
  width: 54%;
  height: 92%;
  float: left;
  font-size: 80%
}
.right-panel-facets-rotate {
  width: 45%;
  float: right;
  padding-left: 1%;
  font-size: 80%
}
.middle-panel-facets-rotate {
  width: NA%;
  float: left;
  padding-left: 1%;
  font-size: 80%
}
</style>

---

class: split-40
count: false

.left-panel-background-auto[

```r
*gapminder
```
]
 
.right-panel-background-auto[

```
  # A tibble: 1,704 x 6
     country     continent  year lifeExp      pop gdpPercap
     <fct>       <fct>     <int>   <dbl>    <int>     <dbl>
   1 Afghanistan Asia       1952    28.8  8425333      779.
   2 Afghanistan Asia       1957    30.3  9240934      821.
   3 Afghanistan Asia       1962    32.0 10267083      853.
   4 Afghanistan Asia       1967    34.0 11537966      836.
   5 Afghanistan Asia       1972    36.1 13079460      740.
   6 Afghanistan Asia       1977    38.4 14880372      786.
   7 Afghanistan Asia       1982    39.9 12881816      978.
   8 Afghanistan Asia       1987    40.8 13867957      852.
   9 Afghanistan Asia       1992    41.7 16317921      649.
  10 Afghanistan Asia       1997    41.8 22227415      635.
  # … with 1,694 more rows
```
]

---
class: split-40
count: false

.left-panel-background-auto[

```r
gapminder %>%  
* filter(year == 2002)
```
]
 
.right-panel-background-auto[

```
  # A tibble: 142 x 6
     country     continent  year lifeExp       pop gdpPercap
     <fct>       <fct>     <int>   <dbl>     <int>     <dbl>
   1 Afghanistan Asia       2002    42.1  25268405      727.
   2 Albania     Europe     2002    75.7   3508512     4604.
   3 Algeria     Africa     2002    71.0  31287142     5288.
   4 Angola      Africa     2002    41.0  10866106     2773.
   5 Argentina   Americas   2002    74.3  38331121     8798.
   6 Australia   Oceania    2002    80.4  19546792    30688.
   7 Austria     Europe     2002    79.0   8148312    32418.
   8 Bahrain     Asia       2002    74.8    656397    23404.
   9 Bangladesh  Asia       2002    62.0 135656790     1136.
  10 Belgium     Europe     2002    78.3  10311970    30486.
  # … with 132 more rows
```
]

---
class: split-40
count: false

.left-panel-background-auto[

```r
gapminder %>%  
  filter(year == 2002) %>%  
* ggplot()
```
]
 
.right-panel-background-auto[
<img src="facet_files/figure-html/background_auto_3_output-1.png" width="100%" />
]

---
class: split-40
count: false

.left-panel-background-auto[

```r
gapminder %>%  
  filter(year == 2002) %>%  
  ggplot() +  
* aes(x = gdpPercap / 1000)
```
]
 
.right-panel-background-auto[
<img src="facet_files/figure-html/background_auto_4_output-1.png" width="100%" />
]

---
class: split-40
count: false

.left-panel-background-auto[

```r
gapminder %>%  
  filter(year == 2002) %>%  
  ggplot() +  
  aes(x = gdpPercap / 1000) +  
* aes(y = lifeExp)
```
]
 
.right-panel-background-auto[
<img src="facet_files/figure-html/background_auto_5_output-1.png" width="100%" />
]

---
class: split-40
count: false

.left-panel-background-auto[

```r
gapminder %>%  
  filter(year == 2002) %>%  
  ggplot() +  
  aes(x = gdpPercap / 1000) +  
  aes(y = lifeExp) +  
* geom_point(data = . %>% select(-continent),
*   color = "darkgrey")
```
]
 
.right-panel-background-auto[
<img src="facet_files/figure-html/background_auto_6_output-1.png" width="100%" />
]

---
class: split-40
count: false

.left-panel-background-auto[

```r
gapminder %>%  
  filter(year == 2002) %>%  
  ggplot() +  
  aes(x = gdpPercap / 1000) +  
  aes(y = lifeExp) +  
  geom_point(data = . %>% select(-continent),  
    color = "darkgrey") +  
* geom_point(color = "magenta")
```
]
 
.right-panel-background-auto[
<img src="facet_files/figure-html/background_auto_7_output-1.png" width="100%" />
]

---
class: split-40
count: false

.left-panel-background-auto[

```r
gapminder %>%  
  filter(year == 2002) %>%  
  ggplot() +  
  aes(x = gdpPercap / 1000) +  
  aes(y = lifeExp) +  
  geom_point(data = . %>% select(-continent),  
    color = "darkgrey") +  
  geom_point(color = "magenta") +  
* facet_wrap(~ continent)
```
]
 
.right-panel-background-auto[
<img src="facet_files/figure-html/background_auto_8_output-1.png" width="100%" />
]

<style>
.left-panel-background-auto {
  color: #777;
  width: 38.6138613861386%;
  height: 92%;
  float: left;
  font-size: 80%
}
.right-panel-background-auto {
  width: 59.4059405940594%;
  float: right;
  padding-left: 1%;
  font-size: 80%
}
.middle-panel-background-auto {
  width: 0%;
  float: left;
  padding-left: 1%;
  font-size: 80%
}
</style>

---

class: split-40
count: false

.left-panel-categorical_free-rotate[

```r
ggplot(mpg, aes(drv, model)) +  
  geom_point() +  
  facet_grid(manufacturer ~ ., scales = "free", space = "free") +  # no strip position argument 
  theme(strip.text.y = element_text(angle = 0))  
```
]
 
.right-panel-categorical_free-rotate[
<img src="facet_files/figure-html/categorical_free_rotate_1_output-1.png" width="100%" />
]

---
class: split-40
count: false

.left-panel-categorical_free-rotate[

```r
ggplot(mpg, aes(drv, model)) +  
  geom_point() +  
* ggforce::facet_col(facets = vars(manufacturer), scales = "free_y", space = "free", strip.position = "top") +
  theme(strip.text.y = element_text(angle = 0))  
```
]
 
.right-panel-categorical_free-rotate[
<img src="facet_files/figure-html/categorical_free_rotate_2_output-1.png" width="100%" />
]

---
class: split-40
count: false

.left-panel-categorical_free-rotate[

```r
ggplot(mpg, aes(drv, model)) +  
  geom_point() +  
* ggforce::facet_col(facets = vars(manufacturer), scales = "free_y", space = "free", strip.position = "left") +
  theme(strip.text.y = element_text(angle = 0))  
```
]
 
.right-panel-categorical_free-rotate[
<img src="facet_files/figure-html/categorical_free_rotate_3_output-1.png" width="100%" />
]

<style>
.left-panel-categorical_free-rotate {
  color: #777;
  width: 38.6138613861386%;
  height: 92%;
  float: left;
  font-size: 80%
}
.right-panel-categorical_free-rotate {
  width: 59.4059405940594%;
  float: right;
  padding-left: 1%;
  font-size: 80%
}
.middle-panel-categorical_free-rotate {
  width: 0%;
  float: left;
  padding-left: 1%;
  font-size: 80%
}
</style>

---

class: split-40
count: false

.left-panel-pyramid-auto[

```r
*gapminder
```
]
 
.right-panel-pyramid-auto[

```
  # A tibble: 1,704 x 6
     country     continent  year lifeExp      pop gdpPercap
     <fct>       <fct>     <int>   <dbl>    <int>     <dbl>
   1 Afghanistan Asia       1952    28.8  8425333      779.
   2 Afghanistan Asia       1957    30.3  9240934      821.
   3 Afghanistan Asia       1962    32.0 10267083      853.
   4 Afghanistan Asia       1967    34.0 11537966      836.
   5 Afghanistan Asia       1972    36.1 13079460      740.
   6 Afghanistan Asia       1977    38.4 14880372      786.
   7 Afghanistan Asia       1982    39.9 12881816      978.
   8 Afghanistan Asia       1987    40.8 13867957      852.
   9 Afghanistan Asia       1992    41.7 16317921      649.
  10 Afghanistan Asia       1997    41.8 22227415      635.
  # … with 1,694 more rows
```
]

---
class: split-40
count: false

.left-panel-pyramid-auto[

```r
gapminder %>%  
* filter(year == 2002 | year == 2007)
```
]
 
.right-panel-pyramid-auto[

```
  # A tibble: 284 x 6
     country     continent  year lifeExp      pop gdpPercap
     <fct>       <fct>     <int>   <dbl>    <int>     <dbl>
   1 Afghanistan Asia       2002    42.1 25268405      727.
   2 Afghanistan Asia       2007    43.8 31889923      975.
   3 Albania     Europe     2002    75.7  3508512     4604.
   4 Albania     Europe     2007    76.4  3600523     5937.
   5 Algeria     Africa     2002    71.0 31287142     5288.
   6 Algeria     Africa     2007    72.3 33333216     6223.
   7 Angola      Africa     2002    41.0 10866106     2773.
   8 Angola      Africa     2007    42.7 12420476     4797.
   9 Argentina   Americas   2002    74.3 38331121     8798.
  10 Argentina   Americas   2007    75.3 40301927    12779.
  # … with 274 more rows
```
]

---
class: split-40
count: false

.left-panel-pyramid-auto[

```r
gapminder %>%  
  filter(year == 2002 | year == 2007) %>%  
* filter(continent == "Americas")
```
]
 
.right-panel-pyramid-auto[

```
  # A tibble: 50 x 6
     country   continent  year lifeExp       pop gdpPercap
     <fct>     <fct>     <int>   <dbl>     <int>     <dbl>
   1 Argentina Americas   2002    74.3  38331121     8798.
   2 Argentina Americas   2007    75.3  40301927    12779.
   3 Bolivia   Americas   2002    63.9   8445134     3413.
   4 Bolivia   Americas   2007    65.6   9119152     3822.
   5 Brazil    Americas   2002    71.0 179914212     8131.
   6 Brazil    Americas   2007    72.4 190010647     9066.
   7 Canada    Americas   2002    79.8  31902268    33329.
   8 Canada    Americas   2007    80.7  33390141    36319.
   9 Chile     Americas   2002    77.9  15497046    10779.
  10 Chile     Americas   2007    78.6  16284741    13172.
  # … with 40 more rows
```
]

---
class: split-40
count: false

.left-panel-pyramid-auto[

```r
gapminder %>%  
  filter(year == 2002 | year == 2007) %>%  
  filter(continent == "Americas") %>%  
* mutate(year = factor(year))   # as categorical
```
]
 
.right-panel-pyramid-auto[

```
  # A tibble: 50 x 6
     country   continent year  lifeExp       pop gdpPercap
     <fct>     <fct>     <fct>   <dbl>     <int>     <dbl>
   1 Argentina Americas  2002     74.3  38331121     8798.
   2 Argentina Americas  2007     75.3  40301927    12779.
   3 Bolivia   Americas  2002     63.9   8445134     3413.
   4 Bolivia   Americas  2007     65.6   9119152     3822.
   5 Brazil    Americas  2002     71.0 179914212     8131.
   6 Brazil    Americas  2007     72.4 190010647     9066.
   7 Canada    Americas  2002     79.8  31902268    33329.
   8 Canada    Americas  2007     80.7  33390141    36319.
   9 Chile     Americas  2002     77.9  15497046    10779.
  10 Chile     Americas  2007     78.6  16284741    13172.
  # … with 40 more rows
```
]

---
class: split-40
count: false

.left-panel-pyramid-auto[

```r
gapminder %>%  
  filter(year == 2002 | year == 2007) %>%  
  filter(continent == "Americas") %>%  
  mutate(year = factor(year)) %>%  # as categorical
# reorder by reverse size of mean life exp
* mutate(country = reorder(country, -lifeExp, mean))
```
]
 
.right-panel-pyramid-auto[

```
  # A tibble: 50 x 6
     country   continent year  lifeExp       pop gdpPercap
     <fct>     <fct>     <fct>   <dbl>     <int>     <dbl>
   1 Argentina Americas  2002     74.3  38331121     8798.
   2 Argentina Americas  2007     75.3  40301927    12779.
   3 Bolivia   Americas  2002     63.9   8445134     3413.
   4 Bolivia   Americas  2007     65.6   9119152     3822.
   5 Brazil    Americas  2002     71.0 179914212     8131.
   6 Brazil    Americas  2007     72.4 190010647     9066.
   7 Canada    Americas  2002     79.8  31902268    33329.
   8 Canada    Americas  2007     80.7  33390141    36319.
   9 Chile     Americas  2002     77.9  15497046    10779.
  10 Chile     Americas  2007     78.6  16284741    13172.
  # … with 40 more rows
```
]

---
class: split-40
count: false

.left-panel-pyramid-auto[

```r
gapminder %>%  
  filter(year == 2002 | year == 2007) %>%  
  filter(continent == "Americas") %>%  
  mutate(year = factor(year)) %>%  # as categorical
# reorder by reverse size of mean life exp
  mutate(country = reorder(country, -lifeExp, mean)) %>%  
# pay attention to this weird prep step
* mutate(life_exp_mod =
*          ifelse(year == 2002, -lifeExp, lifeExp))
```
]
 
.right-panel-pyramid-auto[

```
  # A tibble: 50 x 7
     country   continent year  lifeExp       pop gdpPercap life_exp_mod
     <fct>     <fct>     <fct>   <dbl>     <int>     <dbl>        <dbl>
   1 Argentina Americas  2002     74.3  38331121     8798.        -74.3
   2 Argentina Americas  2007     75.3  40301927    12779.         75.3
   3 Bolivia   Americas  2002     63.9   8445134     3413.        -63.9
   4 Bolivia   Americas  2007     65.6   9119152     3822.         65.6
   5 Brazil    Americas  2002     71.0 179914212     8131.        -71.0
   6 Brazil    Americas  2007     72.4 190010647     9066.         72.4
   7 Canada    Americas  2002     79.8  31902268    33329.        -79.8
   8 Canada    Americas  2007     80.7  33390141    36319.         80.7
   9 Chile     Americas  2002     77.9  15497046    10779.        -77.9
  10 Chile     Americas  2007     78.6  16284741    13172.         78.6
  # … with 40 more rows
```
]

---
class: split-40
count: false

.left-panel-pyramid-auto[

```r
gapminder %>%  
  filter(year == 2002 | year == 2007) %>%  
  filter(continent == "Americas") %>%  
  mutate(year = factor(year)) %>%  # as categorical
# reorder by reverse size of mean life exp
  mutate(country = reorder(country, -lifeExp, mean)) %>%  
# pay attention to this weird prep step
  mutate(life_exp_mod =  
           ifelse(year == 2002, -lifeExp, lifeExp)) %>%  
* ggplot()
```
]
 
.right-panel-pyramid-auto[
<img src="facet_files/figure-html/pyramid_auto_7_output-1.png" width="100%" />
]

---
class: split-40
count: false

.left-panel-pyramid-auto[

```r
gapminder %>%  
  filter(year == 2002 | year == 2007) %>%  
  filter(continent == "Americas") %>%  
  mutate(year = factor(year)) %>%  # as categorical
# reorder by reverse size of mean life exp
  mutate(country = reorder(country, -lifeExp, mean)) %>%  
# pay attention to this weird prep step
  mutate(life_exp_mod =  
           ifelse(year == 2002, -lifeExp, lifeExp)) %>%  
  ggplot() +  
* aes(x = life_exp_mod, y = country, fill = year)
```
]
 
.right-panel-pyramid-auto[
<img src="facet_files/figure-html/pyramid_auto_8_output-1.png" width="100%" />
]

---
class: split-40
count: false

.left-panel-pyramid-auto[

```r
gapminder %>%  
  filter(year == 2002 | year == 2007) %>%  
  filter(continent == "Americas") %>%  
  mutate(year = factor(year)) %>%  # as categorical
# reorder by reverse size of mean life exp
  mutate(country = reorder(country, -lifeExp, mean)) %>%  
# pay attention to this weird prep step
  mutate(life_exp_mod =  
           ifelse(year == 2002, -lifeExp, lifeExp)) %>%  
  ggplot() +  
  aes(x = life_exp_mod, y = country, fill = year) +  
* geom_col()
```
]
 
.right-panel-pyramid-auto[
<img src="facet_files/figure-html/pyramid_auto_9_output-1.png" width="100%" />
]

---
class: split-40
count: false

.left-panel-pyramid-auto[

```r
gapminder %>%  
  filter(year == 2002 | year == 2007) %>%  
  filter(continent == "Americas") %>%  
  mutate(year = factor(year)) %>%  # as categorical
# reorder by reverse size of mean life exp
  mutate(country = reorder(country, -lifeExp, mean)) %>%  
# pay attention to this weird prep step
  mutate(life_exp_mod =  
           ifelse(year == 2002, -lifeExp, lifeExp)) %>%  
  ggplot() +  
  aes(x = life_exp_mod, y = country, fill = year) +  
  geom_col() +  
* ggpol::facet_share(~ year,
*                    reverse_num = TRUE,
*                    scales = "free")
```
]
 
.right-panel-pyramid-auto[
<img src="facet_files/figure-html/pyramid_auto_10_output-1.png" width="100%" />
]

---
class: split-40
count: false

.left-panel-pyramid-auto[

```r
gapminder %>%  
  filter(year == 2002 | year == 2007) %>%  
  filter(continent == "Americas") %>%  
  mutate(year = factor(year)) %>%  # as categorical
# reorder by reverse size of mean life exp
  mutate(country = reorder(country, -lifeExp, mean)) %>%  
# pay attention to this weird prep step
  mutate(life_exp_mod =  
           ifelse(year == 2002, -lifeExp, lifeExp)) %>%  
  ggplot() +  
  aes(x = life_exp_mod, y = country, fill = year) +  
  geom_col() +  
  ggpol::facet_share(~ year,  
                     reverse_num = TRUE,  
                     scales = "free") +  
* theme(legend.position = "none")
```
]
 
.right-panel-pyramid-auto[
<img src="facet_files/figure-html/pyramid_auto_11_output-1.png" width="100%" />
]

---
class: split-40
count: false

.left-panel-pyramid-auto[

```r
gapminder %>%  
  filter(year == 2002 | year == 2007) %>%  
  filter(continent == "Americas") %>%  
  mutate(year = factor(year)) %>%  # as categorical
# reorder by reverse size of mean life exp
  mutate(country = reorder(country, -lifeExp, mean)) %>%  
# pay attention to this weird prep step
  mutate(life_exp_mod =  
           ifelse(year == 2002, -lifeExp, lifeExp)) %>%  
  ggplot() +  
  aes(x = life_exp_mod, y = country, fill = year) +  
  geom_col() +  
  ggpol::facet_share(~ year,  
                     reverse_num = TRUE,  
                     scales = "free") +  
  theme(legend.position = "none") +  
* labs(y = NULL)
```
]
 
.right-panel-pyramid-auto[
<img src="facet_files/figure-html/pyramid_auto_12_output-1.png" width="100%" />
]

---
class: split-40
count: false

.left-panel-pyramid-auto[

```r
gapminder %>%  
  filter(year == 2002 | year == 2007) %>%  
  filter(continent == "Americas") %>%  
  mutate(year = factor(year)) %>%  # as categorical
# reorder by reverse size of mean life exp
  mutate(country = reorder(country, -lifeExp, mean)) %>%  
# pay attention to this weird prep step
  mutate(life_exp_mod =  
           ifelse(year == 2002, -lifeExp, lifeExp)) %>%  
  ggplot() +  
  aes(x = life_exp_mod, y = country, fill = year) +  
  geom_col() +  
  ggpol::facet_share(~ year,  
                     reverse_num = TRUE,  
                     scales = "free") +  
  theme(legend.position = "none") +  
  labs(y = NULL) +  
* scale_y_discrete()
```
]
 
.right-panel-pyramid-auto[
<img src="facet_files/figure-html/pyramid_auto_13_output-1.png" width="100%" />
]

<style>
.left-panel-pyramid-auto {
  color: #777;
  width: 54%;
  height: 92%;
  float: left;
  font-size: 80%
}
.right-panel-pyramid-auto {
  width: 45%;
  float: right;
  padding-left: 1%;
  font-size: 80%
}
.middle-panel-pyramid-auto {
  width: NA%;
  float: left;
  padding-left: 1%;
  font-size: 80%
}
</style>

---

class: split-40
count: false

.left-panel-matrix-auto[

```r
*set.seed(12345)
```
]
 
.right-panel-matrix-auto[

]

---
class: split-40
count: false

.left-panel-matrix-auto[

```r
set.seed(12345)  
*library(ggforce)
```
]
 
.right-panel-matrix-auto[

]

---
class: split-40
count: false

.left-panel-matrix-auto[

```r
set.seed(12345)  
library(ggforce)  
*diamonds
```
]
 
.right-panel-matrix-auto[

```
  # A tibble: 53,940 x 10
     carat cut       color clarity depth table price     x     y     z
     <dbl> <ord>     <ord> <ord>   <dbl> <dbl> <int> <dbl> <dbl> <dbl>
   1 0.23  Ideal     E     SI2      61.5    55   326  3.95  3.98  2.43
   2 0.21  Premium   E     SI1      59.8    61   326  3.89  3.84  2.31
   3 0.23  Good      E     VS1      56.9    65   327  4.05  4.07  2.31
   4 0.290 Premium   I     VS2      62.4    58   334  4.2   4.23  2.63
   5 0.31  Good      J     SI2      63.3    58   335  4.34  4.35  2.75
   6 0.24  Very Good J     VVS2     62.8    57   336  3.94  3.96  2.48
   7 0.24  Very Good I     VVS1     62.3    57   336  3.95  3.98  2.47
   8 0.26  Very Good H     SI1      61.9    55   337  4.07  4.11  2.53
   9 0.22  Fair      E     VS2      65.1    61   337  3.87  3.78  2.49
  10 0.23  Very Good H     VS1      59.4    61   338  4     4.05  2.39
  # … with 53,930 more rows
```
]

---
class: split-40
count: false

.left-panel-matrix-auto[

```r
set.seed(12345)  
library(ggforce)  
diamonds %>%  
* select(carat, table, price, clarity)
```
]
 
.right-panel-matrix-auto[

```
  # A tibble: 53,940 x 4
     carat table price clarity
     <dbl> <dbl> <int> <ord>  
   1 0.23     55   326 SI2    
   2 0.21     61   326 SI1    
   3 0.23     65   327 VS1    
   4 0.290    58   334 VS2    
   5 0.31     58   335 SI2    
   6 0.24     57   336 VVS2   
   7 0.24     57   336 VVS1   
   8 0.26     55   337 SI1    
   9 0.22     61   337 VS2    
  10 0.23     61   338 VS1    
  # … with 53,930 more rows
```
]

---
class: split-40
count: false

.left-panel-matrix-auto[

```r
set.seed(12345)  
library(ggforce)  
diamonds %>%  
  select(carat, table, price, clarity) %>%  
* sample_frac(.1)
```
]
 
.right-panel-matrix-auto[

```
  # A tibble: 5,394 x 4
     carat table price clarity
     <dbl> <dbl> <int> <ord>  
   1  1.01    56  4886 SI1    
   2  0.41    61   827 VS2    
   3  1.26    57  4704 SI2    
   4  0.3     57   554 SI1    
   5  0.34    56   726 VS2    
   6  2       56 15851 SI1    
   7  1.16    57  9526 VVS1   
   8  0.54    56  1760 VS2    
   9  1.51    60 14375 VS1    
  10  0.31    58   907 VVS2   
  # … with 5,384 more rows
```
]

---
class: split-40
count: false

.left-panel-matrix-auto[

```r
set.seed(12345)  
library(ggforce)  
diamonds %>%  
  select(carat, table, price, clarity) %>%  
  sample_frac(.1) %>%  
* ggplot()
```
]
 
.right-panel-matrix-auto[
<img src="facet_files/figure-html/matrix_auto_6_output-1.png" width="100%" />
]

---
class: split-40
count: false

.left-panel-matrix-auto[

```r
set.seed(12345)  
library(ggforce)  
diamonds %>%  
  select(carat, table, price, clarity) %>%  
  sample_frac(.1) %>%  
  ggplot() +  
* ggforce::facet_matrix(
*   rows = vars(everything())
*   )
```
]
 
.right-panel-matrix-auto[
<img src="facet_files/figure-html/matrix_auto_7_output-1.png" width="100%" />
]

---
class: split-40
count: false

.left-panel-matrix-auto[

```r
set.seed(12345)  
library(ggforce)  
diamonds %>%  
  select(carat, table, price, clarity) %>%  
  sample_frac(.1) %>%  
  ggplot() +  
  ggforce::facet_matrix(  
    rows = vars(everything())  
    ) +  
* aes(x = .panel_x)
```
]
 
.right-panel-matrix-auto[
<img src="facet_files/figure-html/matrix_auto_8_output-1.png" width="100%" />
]

---
class: split-40
count: false

.left-panel-matrix-auto[

```r
set.seed(12345)  
library(ggforce)  
diamonds %>%  
  select(carat, table, price, clarity) %>%  
  sample_frac(.1) %>%  
  ggplot() +  
  ggforce::facet_matrix(  
    rows = vars(everything())  
    ) +  
  aes(x = .panel_x) +  
* aes(y = .panel_y)
```
]
 
.right-panel-matrix-auto[
<img src="facet_files/figure-html/matrix_auto_9_output-1.png" width="100%" />
]

---
class: split-40
count: false

.left-panel-matrix-auto[

```r
set.seed(12345)  
library(ggforce)  
diamonds %>%  
  select(carat, table, price, clarity) %>%  
  sample_frac(.1) %>%  
  ggplot() +  
  ggforce::facet_matrix(  
    rows = vars(everything())  
    ) +  
  aes(x = .panel_x) +  
  aes(y = .panel_y) +  
# first geom layer
* geom_point(alpha = 0.2)
```
]
 
.right-panel-matrix-auto[
<img src="facet_files/figure-html/matrix_auto_10_output-1.png" width="100%" />
]

---
class: split-40
count: false

.left-panel-matrix-auto[

```r
set.seed(12345)  
library(ggforce)  
diamonds %>%  
  select(carat, table, price, clarity) %>%  
  sample_frac(.1) %>%  
  ggplot() +  
  ggforce::facet_matrix(  
    rows = vars(everything())  
    ) +  
  aes(x = .panel_x) +  
  aes(y = .panel_y) +  
# first geom layer
  geom_point(alpha = 0.2) +  
# second geom layer
* ggforce::geom_autodensity()
```
]
 
.right-panel-matrix-auto[
<img src="facet_files/figure-html/matrix_auto_11_output-1.png" width="100%" />
]

---
class: split-40
count: false

.left-panel-matrix-auto[

```r
set.seed(12345)  
library(ggforce)  
diamonds %>%  
  select(carat, table, price, clarity) %>%  
  sample_frac(.1) %>%  
  ggplot() +  
  ggforce::facet_matrix(  
    rows = vars(everything())  
    ) +  
  aes(x = .panel_x) +  
  aes(y = .panel_y) +  
# first geom layer
  geom_point(alpha = 0.2) +  
# second geom layer
  ggforce::geom_autodensity() +  
# third geom layer
* geom_density2d()
```
]
 
.right-panel-matrix-auto[
<img src="facet_files/figure-html/matrix_auto_12_output-1.png" width="100%" />
]

---
class: split-40
count: false

.left-panel-matrix-auto[

```r
set.seed(12345)  
library(ggforce)  
diamonds %>%  
  select(carat, table, price, clarity) %>%  
  sample_frac(.1) %>%  
  ggplot() +  
  ggforce::facet_matrix(  
    rows = vars(everything())  
    ) +  
  aes(x = .panel_x) +  
  aes(y = .panel_y) +  
# first geom layer
  geom_point(alpha = 0.2) +  
# second geom layer
  ggforce::geom_autodensity() +  
# third geom layer
  geom_density2d() +  
# overwrites above facet specification with new
* ggforce::facet_matrix(
*   rows = vars(everything()),
*    layer.lower = 1,  # first geom layer
*    layer.diag = c(1,2),  # first, second geom layer
*    layer.upper = 3,  # third geom layer
*    grid.y.diag = FALSE
*   )
```
]
 
.right-panel-matrix-auto[
<img src="facet_files/figure-html/matrix_auto_13_output-1.png" width="100%" />
]

<style>
.left-panel-matrix-auto {
  color: #777;
  width: 59%;
  height: 92%;
  float: left;
  font-size: 80%
}
.right-panel-matrix-auto {
  width: 40%;
  float: right;
  padding-left: 1%;
  font-size: 80%
}
.middle-panel-matrix-auto {
  width: NA%;
  float: left;
  padding-left: 1%;
  font-size: 80%
}
</style>

---

Next up is ['greetings'](themes.html) (themes are what greets the eye).

<style type="text/css">
.remark-code{line-height: 1.5; font-size: 60%}
</style>