featurette

class: inverse, left, bottom
background-image: url(https://images.unsplash.com/photo-1603779702200-95b2785f2083?q=80&w=1587&auto=format&fit=crop&ixlib=rb-4.0.3&ixid=M3wxMjA3fDB8MHxwaG90by1wYWdlfHx8fGVufDB8fHx8fA%3D%3D)
background-size: cover
# .Large[# Making pies with ggplot2]
## .small[featuring `coord_polar(theta = "y")`, `geom_bar(position = "fill")`, `stage()`, and {ggtrace}]
#### .tiny[Gina Reynolds | 2023-10-25 |Image credit: 
Nathan Dumlao, Upsplash]
???
Title

---

count: false

.panel1-feature-auto[

```r
*library(tidyverse)
```
]
 
.panel2-feature-auto[

]

---
count: false

.panel1-feature-auto[

```r
library(tidyverse)

*diamonds
```
]
 
.panel2-feature-auto[

```
## # A tibble: 53,940 × 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  0.29 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
## # ℹ 53,930 more rows
```
]

---
count: false

.panel1-feature-auto[

```r
library(tidyverse)

diamonds %>%
*ggplot()
```
]
 
.panel2-feature-auto[
![](ggplot-pie-charts_files/figure-html/feature_auto_03_output-1.png)
]

---
count: false

.panel1-feature-auto[

```r
library(tidyverse)

diamonds %>%
ggplot() +
* aes(x = 0)
```
]
 
.panel2-feature-auto[
![](ggplot-pie-charts_files/figure-html/feature_auto_04_output-1.png)
]

---
count: false

.panel1-feature-auto[

```r
library(tidyverse)

diamonds %>%
ggplot() +
  aes(x = 0) +
* geom_bar(position = "fill")
```
]
 
.panel2-feature-auto[
![](ggplot-pie-charts_files/figure-html/feature_auto_05_output-1.png)
]

---
count: false

.panel1-feature-auto[

```r
library(tidyverse)

diamonds %>%
ggplot() +
  aes(x = 0) +
  geom_bar(position = "fill") +
* aes(fill = cut)
```
]
 
.panel2-feature-auto[
![](ggplot-pie-charts_files/figure-html/feature_auto_06_output-1.png)
]

---
count: false

.panel1-feature-auto[

```r
library(tidyverse)

diamonds %>%
ggplot() +
  aes(x = 0) +
  geom_bar(position = "fill") +
  aes(fill = cut) +
* stat_count(
*   geom = "text", position = "fill",
*   color = "white", size = 8,
*   aes(x = .25,
*       label = after_stat(
*         count*100/sum(count)) |>
*         round(1) |>
*         paste0("%")))
```
]
 
.panel2-feature-auto[
![](ggplot-pie-charts_files/figure-html/feature_auto_07_output-1.png)
]

---
count: false

.panel1-feature-auto[

```r
library(tidyverse)

diamonds %>%
ggplot() +
  aes(x = 0) +
  geom_bar(position = "fill") +
  aes(fill = cut) +
  stat_count(
    geom = "text", position = "fill",
    color = "white", size = 8,
    aes(x = .25,
        label = after_stat(
          count*100/sum(count)) |>
          round(1) |>
          paste0("%"))) +
# usually would include this in above function
* aes(y = stage(start = NULL,
*                 after_stat = count,
*                 after_scale = (ymin +
*                                  ymax)/2))
```
]
 
.panel2-feature-auto[
![](ggplot-pie-charts_files/figure-html/feature_auto_08_output-1.png)
]

---
count: false

.panel1-feature-auto[

```r
library(tidyverse)

diamonds %>%
ggplot() +
  aes(x = 0) +
  geom_bar(position = "fill") +
  aes(fill = cut) +
  stat_count(
    geom = "text", position = "fill",
    color = "white", size = 8,
    aes(x = .25,
        label = after_stat(
          count*100/sum(count)) |>
          round(1) |>
          paste0("%"))) +
# usually would include this in above function
  aes(y = stage(start = NULL,
                  after_stat = count,
                  after_scale = (ymin +
                                   ymax)/2)) +
* coord_polar(theta = "y")
```
]
 
.panel2-feature-auto[
![](ggplot-pie-charts_files/figure-html/feature_auto_09_output-1.png)
]

---
count: false

.panel1-feature-auto[

```r
library(tidyverse)

diamonds %>%
ggplot() +
  aes(x = 0) +
  geom_bar(position = "fill") +
  aes(fill = cut) +
  stat_count(
    geom = "text", position = "fill",
    color = "white", size = 8,
    aes(x = .25,
        label = after_stat(
          count*100/sum(count)) |>
          round(1) |>
          paste0("%"))) +
# usually would include this in above function
  aes(y = stage(start = NULL,
                  after_stat = count,
                  after_scale = (ymin +
                                   ymax)/2)) +
  coord_polar(theta = "y") +
* theme_void()
```
]
 
.panel2-feature-auto[
![](ggplot-pie-charts_files/figure-html/feature_auto_10_output-1.png)
]

---
count: false

.panel1-feature-auto[

```r
library(tidyverse)

diamonds %>%
ggplot() +
  aes(x = 0) +
  geom_bar(position = "fill") +
  aes(fill = cut) +
  stat_count(
    geom = "text", position = "fill",
    color = "white", size = 8,
    aes(x = .25,
        label = after_stat(
          count*100/sum(count)) |>
          round(1) |>
          paste0("%"))) +
# usually would include this in above function
  aes(y = stage(start = NULL,
                  after_stat = count,
                  after_scale = (ymin +
                                   ymax)/2)) +
  coord_polar(theta = "y") +
  theme_void() ->
*classic_pie
```
]
 
.panel2-feature-auto[

]

---

# ggtrace may help clarify strategy?

```r
ggtrace::layer_before_stat(classic_pie, i = 2)
```

```
## # A tibble: 53,940 × 4
##        x fill      PANEL group
##    <dbl> <ord>     <fct> <int>
##  1  0.25 Ideal     1         5
##  2  0.25 Premium   1         4
##  3  0.25 Good      1         2
##  4  0.25 Premium   1         4
##  5  0.25 Good      1         2
##  6  0.25 Very Good 1         3
##  7  0.25 Very Good 1         3
##  8  0.25 Very Good 1         3
##  9  0.25 Fair      1         1
## 10  0.25 Very Good 1         3
## # ℹ 53,930 more rows
```

---

# ggtrace may help clarify strategy?

```r
ggtrace::layer_after_stat(classic_pie,i = 2)
```

```
## # A tibble: 5 × 8
##   count  prop     x width flipped_aes fill      PANEL group
##   <dbl> <dbl> <dbl> <dbl> <lgl>       <ord>     <fct> <int>
## 1  1610     1  0.25   0.9 FALSE       Fair      1         1
## 2  4906     1  0.25   0.9 FALSE       Good      1         2
## 3 12082     1  0.25   0.9 FALSE       Very Good 1         3
## 4 13791     1  0.25   0.9 FALSE       Premium   1         4
## 5 21551     1  0.25   0.9 FALSE       Ideal     1         5
```

---

# ggtrace may help clarify strategy?

```r
ggtrace::layer_after_scale(classic_pie, i = 2) %>% data.frame()
```

```
##           y      fill label count prop    x width flipped_aes PANEL group
## 1 0.9850760 #440154FF    3%  1610    1 0.25   0.9       FALSE     1     1
## 2 0.9246756 #3B528BFF  9.1%  4906    1 0.25   0.9       FALSE     1     2
## 3 0.7672043 #21908CFF 22.4% 12082    1 0.25   0.9       FALSE     1     3
## 4 0.5273730 #5DC863FF 25.6% 13791    1 0.25   0.9       FALSE     1     4
## 5 0.1997683 #FDE725FF   40% 21551    1 0.25   0.9       FALSE     1     5
##        ymax xmin xmax      ymin colour size angle hjust vjust alpha family
## 1 1.0000000 0.25 0.25 0.9701520  white    8     0   0.5   0.5    NA       
## 2 0.9701520 0.25 0.25 0.8791991  white    8     0   0.5   0.5    NA       
## 3 0.8791991 0.25 0.25 0.6552095  white    8     0   0.5   0.5    NA       
## 4 0.6552095 0.25 0.25 0.3995365  white    8     0   0.5   0.5    NA       
## 5 0.3995365 0.25 0.25 0.0000000  white    8     0   0.5   0.5    NA       
##   fontface lineheight
## 1        1        1.2
## 2        1        1.2
## 3        1        1.2
## 4        1        1.2
## 5        1        1.2
```

---

### Contribute

- https://yjunechoe.github.io/ggtrace/

---

### Check out flipbookr, used to build this featurette

- https://github.com/EvaMaeRey/flipbookr
- discussion: https://github.com/EvaMaeRey/flipbookr/blob/master/docs/draft_jasa_submission.pdf

---

### Check out more featurettes

- https://EvaMaeRey.github.io/featurette