prop is hard to use

class: inverse, left, bottom
background-image: url(https://images.unsplash.com/photo-1542204165-65bf26472b9b?auto=format&fit=crop&q=80&w=1548&ixlib=rb-4.0.3&ixid=M3wxMjA3fDB8MHxwaG90by1wYWdlfHx8fGVufDB8fHx8fA%3D%3D)
background-size: cover
# .Large[# [prop is hard to use](https://github.com/tidyverse/ggplot2/issues/5505)]
## .small[featuring [ggplot2/issues/5505]() ...]
#### .tiny[Gina Reynolds | 2023-10-25 |Image credit: Denise Jans, Upsplash]
???
Title

---

count: false

.panel1-feature-auto[

```r
*to_percent = function(x){(100*x) %>% round(1) %>% paste("%")}
```
]
 
.panel2-feature-auto[

]

---
count: false

.panel1-feature-auto[

```r
to_percent = function(x){(100*x) %>% round(1) %>% paste("%")}

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

]

---
count: false

.panel1-feature-auto[

```r
to_percent = function(x){(100*x) %>% round(1) %>% paste("%")}

library(tidyverse)
*theme_set(theme_bw(base_size = 20))
```
]
 
.panel2-feature-auto[

]

---
count: false

.panel1-feature-auto[

```r
to_percent = function(x){(100*x) %>% round(1) %>% paste("%")}

library(tidyverse)
theme_set(theme_bw(base_size = 20))
*Titanic
```
]
 
.panel2-feature-auto[

```
## , , Age = Child, Survived = No
## 
##       Sex
## Class  Male Female
##   1st     0      0
##   2nd     0      0
##   3rd    35     17
##   Crew    0      0
## 
## , , Age = Adult, Survived = No
## 
##       Sex
## Class  Male Female
##   1st   118      4
##   2nd   154     13
##   3rd   387     89
##   Crew  670      3
## 
## , , Age = Child, Survived = Yes
## 
##       Sex
## Class  Male Female
##   1st     5      1
##   2nd    11     13
##   3rd    13     14
##   Crew    0      0
## 
## , , Age = Adult, Survived = Yes
## 
##       Sex
## Class  Male Female
##   1st    57    140
##   2nd    14     80
##   3rd    75     76
##   Crew  192     20
```
]

---
count: false

.panel1-feature-auto[

```r
to_percent = function(x){(100*x) %>% round(1) %>% paste("%")}

library(tidyverse)
theme_set(theme_bw(base_size = 20))
Titanic %>%
* data.frame()
```
]
 
.panel2-feature-auto[

```
##    Class    Sex   Age Survived Freq
## 1    1st   Male Child       No    0
## 2    2nd   Male Child       No    0
## 3    3rd   Male Child       No   35
## 4   Crew   Male Child       No    0
## 5    1st Female Child       No    0
## 6    2nd Female Child       No    0
## 7    3rd Female Child       No   17
## 8   Crew Female Child       No    0
## 9    1st   Male Adult       No  118
## 10   2nd   Male Adult       No  154
## 11   3rd   Male Adult       No  387
## 12  Crew   Male Adult       No  670
## 13   1st Female Adult       No    4
## 14   2nd Female Adult       No   13
## 15   3rd Female Adult       No   89
## 16  Crew Female Adult       No    3
## 17   1st   Male Child      Yes    5
## 18   2nd   Male Child      Yes   11
## 19   3rd   Male Child      Yes   13
## 20  Crew   Male Child      Yes    0
## 21   1st Female Child      Yes    1
## 22   2nd Female Child      Yes   13
## 23   3rd Female Child      Yes   14
## 24  Crew Female Child      Yes    0
## 25   1st   Male Adult      Yes   57
## 26   2nd   Male Adult      Yes   14
## 27   3rd   Male Adult      Yes   75
## 28  Crew   Male Adult      Yes  192
## 29   1st Female Adult      Yes  140
## 30   2nd Female Adult      Yes   80
## 31   3rd Female Adult      Yes   76
## 32  Crew Female Adult      Yes   20
```
]

---
count: false

.panel1-feature-auto[

```r
to_percent = function(x){(100*x) %>% round(1) %>% paste("%")}

library(tidyverse)
theme_set(theme_bw(base_size = 20))
Titanic %>%
  data.frame() %>%
* ggplot(aes(x = Sex, fill = Survived, weight = Freq))
```
]
 
.panel2-feature-auto[
![](prop-is-hard-to-use_files/figure-html/feature_auto_06_output-1.png)
]

---
count: false

.panel1-feature-auto[

```r
to_percent = function(x){(100*x) %>% round(1) %>% paste("%")}

library(tidyverse)
theme_set(theme_bw(base_size = 20))
Titanic %>%
  data.frame() %>%
  ggplot(aes(x = Sex, fill = Survived, weight = Freq)) +
* geom_bar(position = "dodge")
```
]
 
.panel2-feature-auto[
![](prop-is-hard-to-use_files/figure-html/feature_auto_07_output-1.png)
]

---
count: false

.panel1-feature-auto[

```r
to_percent = function(x){(100*x) %>% round(1) %>% paste("%")}

library(tidyverse)
theme_set(theme_bw(base_size = 20))
Titanic %>%
  data.frame() %>%
  ggplot(aes(x = Sex, fill = Survived, weight = Freq)) +
  geom_bar(position = "dodge") +
# Proportion per group
* aes(y     = after_stat(prop), group = Survived)
```
]
 
.panel2-feature-auto[
![](prop-is-hard-to-use_files/figure-html/feature_auto_08_output-1.png)
]

---
count: false

.panel1-feature-auto[

```r
to_percent = function(x){(100*x) %>% round(1) %>% paste("%")}

library(tidyverse)
theme_set(theme_bw(base_size = 20))
Titanic %>%
  data.frame() %>%
  ggplot(aes(x = Sex, fill = Survived, weight = Freq)) +
  geom_bar(position = "dodge") +
# Proportion per group
  aes(y     = after_stat(prop), group = Survived) +
* aes(label = to_percent(after_stat(prop)))
```
]
 
.panel2-feature-auto[
![](prop-is-hard-to-use_files/figure-html/feature_auto_09_output-1.png)
]

---
count: false

.panel1-feature-auto[

```r
to_percent = function(x){(100*x) %>% round(1) %>% paste("%")}

library(tidyverse)
theme_set(theme_bw(base_size = 20))
Titanic %>%
  data.frame() %>%
  ggplot(aes(x = Sex, fill = Survived, weight = Freq)) +
  geom_bar(position = "dodge") +
# Proportion per group
  aes(y     = after_stat(prop), group = Survived) +
  aes(label = to_percent(after_stat(prop))) +
* stat_count(geom = "text", size = 4,
*            position =
*              position_dodge2(width = .9, preserve = "single"))
```
]
 
.panel2-feature-auto[
![](prop-is-hard-to-use_files/figure-html/feature_auto_10_output-1.png)
]

---
count: false

.panel1-feature-auto[

```r
to_percent = function(x){(100*x) %>% round(1) %>% paste("%")}

library(tidyverse)
theme_set(theme_bw(base_size = 20))
Titanic %>%
  data.frame() %>%
  ggplot(aes(x = Sex, fill = Survived, weight = Freq)) +
  geom_bar(position = "dodge") +
# Proportion per group
  aes(y     = after_stat(prop), group = Survived) +
  aes(label = to_percent(after_stat(prop))) +
  stat_count(geom = "text", size = 4,
             position =
               position_dodge2(width = .9, preserve = "single")) +
* scale_y_continuous(labels = scales::percent_format())
```
]
 
.panel2-feature-auto[
![](prop-is-hard-to-use_files/figure-html/feature_auto_11_output-1.png)
]

---
count: false

.panel1-feature-auto[

```r
to_percent = function(x){(100*x) %>% round(1) %>% paste("%")}

library(tidyverse)
theme_set(theme_bw(base_size = 20))
Titanic %>%
  data.frame() %>%
  ggplot(aes(x = Sex, fill = Survived, weight = Freq)) +
  geom_bar(position = "dodge") +
# Proportion per group
  aes(y     = after_stat(prop), group = Survived) +
  aes(label = to_percent(after_stat(prop))) +
  stat_count(geom = "text", size = 4,
             position =
               position_dodge2(width = .9, preserve = "single")) +
  scale_y_continuous(labels = scales::percent_format()) +
# Proportion of total
* aes(y = after_stat(count / sum(count)))
```
]
 
.panel2-feature-auto[
![](prop-is-hard-to-use_files/figure-html/feature_auto_12_output-1.png)
]

---
count: false

.panel1-feature-auto[

```r
to_percent = function(x){(100*x) %>% round(1) %>% paste("%")}

library(tidyverse)
theme_set(theme_bw(base_size = 20))
Titanic %>%
  data.frame() %>%
  ggplot(aes(x = Sex, fill = Survived, weight = Freq)) +
  geom_bar(position = "dodge") +
# Proportion per group
  aes(y     = after_stat(prop), group = Survived) +
  aes(label = to_percent(after_stat(prop))) +
  stat_count(geom = "text", size = 4,
             position =
               position_dodge2(width = .9, preserve = "single")) +
  scale_y_continuous(labels = scales::percent_format()) +
# Proportion of total
  aes(y = after_stat(count / sum(count))) +
* aes(label = to_percent(after_stat(count / sum(count))))
```
]
 
.panel2-feature-auto[
![](prop-is-hard-to-use_files/figure-html/feature_auto_13_output-1.png)
]

---
count: false

.panel1-feature-auto[

```r
to_percent = function(x){(100*x) %>% round(1) %>% paste("%")}

library(tidyverse)
theme_set(theme_bw(base_size = 20))
Titanic %>%
  data.frame() %>%
  ggplot(aes(x = Sex, fill = Survived, weight = Freq)) +
  geom_bar(position = "dodge") +
# Proportion per group
  aes(y     = after_stat(prop), group = Survived) +
  aes(label = to_percent(after_stat(prop))) +
  stat_count(geom = "text", size = 4,
             position =
               position_dodge2(width = .9, preserve = "single")) +
  scale_y_continuous(labels = scales::percent_format()) +
# Proportion of total
  aes(y = after_stat(count / sum(count))) +
  aes(label = to_percent(after_stat(count / sum(count)))) +
# Proportion per x position
* aes(y = after_stat(count / ave(count, x, FUN = sum)))
```
]
 
.panel2-feature-auto[
![](prop-is-hard-to-use_files/figure-html/feature_auto_14_output-1.png)
]

---
count: false

.panel1-feature-auto[

```r
to_percent = function(x){(100*x) %>% round(1) %>% paste("%")}

library(tidyverse)
theme_set(theme_bw(base_size = 20))
Titanic %>%
  data.frame() %>%
  ggplot(aes(x = Sex, fill = Survived, weight = Freq)) +
  geom_bar(position = "dodge") +
# Proportion per group
  aes(y     = after_stat(prop), group = Survived) +
  aes(label = to_percent(after_stat(prop))) +
  stat_count(geom = "text", size = 4,
             position =
               position_dodge2(width = .9, preserve = "single")) +
  scale_y_continuous(labels = scales::percent_format()) +
# Proportion of total
  aes(y = after_stat(count / sum(count))) +
  aes(label = to_percent(after_stat(count / sum(count)))) +
# Proportion per x position
  aes(y = after_stat(count / ave(count, x, FUN = sum))) +
* aes(label = to_percent(after_stat(count / ave(count, x, FUN = sum))))
```
]
 
.panel2-feature-auto[
![](prop-is-hard-to-use_files/figure-html/feature_auto_15_output-1.png)
]

---
count: false

.panel1-feature-auto[

```r
to_percent = function(x){(100*x) %>% round(1) %>% paste("%")}

library(tidyverse)
theme_set(theme_bw(base_size = 20))
Titanic %>%
  data.frame() %>%
  ggplot(aes(x = Sex, fill = Survived, weight = Freq)) +
  geom_bar(position = "dodge") +
# Proportion per group
  aes(y     = after_stat(prop), group = Survived) +
  aes(label = to_percent(after_stat(prop))) +
  stat_count(geom = "text", size = 4,
             position =
               position_dodge2(width = .9, preserve = "single")) +
  scale_y_continuous(labels = scales::percent_format()) +
# Proportion of total
  aes(y = after_stat(count / sum(count))) +
  aes(label = to_percent(after_stat(count / sum(count)))) +
# Proportion per x position
  aes(y = after_stat(count / ave(count, x, FUN = sum))) +
  aes(label = to_percent(after_stat(count / ave(count, x, FUN = sum)))) +
* facet_wrap(~ Class)
```
]
 
.panel2-feature-auto[
![](prop-is-hard-to-use_files/figure-html/feature_auto_16_output-1.png)
]

---
count: false

.panel1-feature-auto[

```r
to_percent = function(x){(100*x) %>% round(1) %>% paste("%")}

library(tidyverse)
theme_set(theme_bw(base_size = 20))
Titanic %>%
  data.frame() %>%
  ggplot(aes(x = Sex, fill = Survived, weight = Freq)) +
  geom_bar(position = "dodge") +
# Proportion per group
  aes(y     = after_stat(prop), group = Survived) +
  aes(label = to_percent(after_stat(prop))) +
  stat_count(geom = "text", size = 4,
             position =
               position_dodge2(width = .9, preserve = "single")) +
  scale_y_continuous(labels = scales::percent_format()) +
# Proportion of total
  aes(y = after_stat(count / sum(count))) +
  aes(label = to_percent(after_stat(count / sum(count)))) +
# Proportion per x position
  aes(y = after_stat(count / ave(count, x, FUN = sum))) +
  aes(label = to_percent(after_stat(count / ave(count, x, FUN = sum)))) +
  facet_wrap(~ Class) +
# Proportion per panel
* aes(y = after_stat(count / ave(count, PANEL, FUN = sum)))
```
]
 
.panel2-feature-auto[
![](prop-is-hard-to-use_files/figure-html/feature_auto_17_output-1.png)
]

---
count: false

.panel1-feature-auto[

```r
to_percent = function(x){(100*x) %>% round(1) %>% paste("%")}

library(tidyverse)
theme_set(theme_bw(base_size = 20))
Titanic %>%
  data.frame() %>%
  ggplot(aes(x = Sex, fill = Survived, weight = Freq)) +
  geom_bar(position = "dodge") +
# Proportion per group
  aes(y     = after_stat(prop), group = Survived) +
  aes(label = to_percent(after_stat(prop))) +
  stat_count(geom = "text", size = 4,
             position =
               position_dodge2(width = .9, preserve = "single")) +
  scale_y_continuous(labels = scales::percent_format()) +
# Proportion of total
  aes(y = after_stat(count / sum(count))) +
  aes(label = to_percent(after_stat(count / sum(count)))) +
# Proportion per x position
  aes(y = after_stat(count / ave(count, x, FUN = sum))) +
  aes(label = to_percent(after_stat(count / ave(count, x, FUN = sum)))) +
  facet_wrap(~ Class) +
# Proportion per panel
  aes(y = after_stat(count / ave(count, PANEL, FUN = sum))) +
* aes(label = to_percent(after_stat(count / ave(count, PANEL, FUN = sum))))
```
]
 
.panel2-feature-auto[
![](prop-is-hard-to-use_files/figure-html/feature_auto_18_output-1.png)
]

---
count: false

.panel1-feature-auto[

```r
to_percent = function(x){(100*x) %>% round(1) %>% paste("%")}

library(tidyverse)
theme_set(theme_bw(base_size = 20))
Titanic %>%
  data.frame() %>%
  ggplot(aes(x = Sex, fill = Survived, weight = Freq)) +
  geom_bar(position = "dodge") +
# Proportion per group
  aes(y     = after_stat(prop), group = Survived) +
  aes(label = to_percent(after_stat(prop))) +
  stat_count(geom = "text", size = 4,
             position =
               position_dodge2(width = .9, preserve = "single")) +
  scale_y_continuous(labels = scales::percent_format()) +
# Proportion of total
  aes(y = after_stat(count / sum(count))) +
  aes(label = to_percent(after_stat(count / sum(count)))) +
# Proportion per x position
  aes(y = after_stat(count / ave(count, x, FUN = sum))) +
  aes(label = to_percent(after_stat(count / ave(count, x, FUN = sum)))) +
  facet_wrap(~ Class) +
# Proportion per panel
  aes(y = after_stat(count / ave(count, PANEL, FUN = sum))) +
  aes(label = to_percent(after_stat(count / ave(count, PANEL, FUN = sum)))) +
# Proportion per panel and x position
* aes(y = after_stat(count / ave(count, x, PANEL, FUN = sum)))
```
]
 
.panel2-feature-auto[
![](prop-is-hard-to-use_files/figure-html/feature_auto_19_output-1.png)
]

---
count: false

.panel1-feature-auto[

```r
to_percent = function(x){(100*x) %>% round(1) %>% paste("%")}

library(tidyverse)
theme_set(theme_bw(base_size = 20))
Titanic %>%
  data.frame() %>%
  ggplot(aes(x = Sex, fill = Survived, weight = Freq)) +
  geom_bar(position = "dodge") +
# Proportion per group
  aes(y     = after_stat(prop), group = Survived) +
  aes(label = to_percent(after_stat(prop))) +
  stat_count(geom = "text", size = 4,
             position =
               position_dodge2(width = .9, preserve = "single")) +
  scale_y_continuous(labels = scales::percent_format()) +
# Proportion of total
  aes(y = after_stat(count / sum(count))) +
  aes(label = to_percent(after_stat(count / sum(count)))) +
# Proportion per x position
  aes(y = after_stat(count / ave(count, x, FUN = sum))) +
  aes(label = to_percent(after_stat(count / ave(count, x, FUN = sum)))) +
  facet_wrap(~ Class) +
# Proportion per panel
  aes(y = after_stat(count / ave(count, PANEL, FUN = sum))) +
  aes(label = to_percent(after_stat(count / ave(count, PANEL, FUN = sum)))) +
# Proportion per panel and x position
  aes(y = after_stat(count / ave(count, x, PANEL, FUN = sum))) +
* aes(label = to_percent(after_stat(count / ave(count, x, PANEL, FUN = sum))))
```
]
 
.panel2-feature-auto[
![](prop-is-hard-to-use_files/figure-html/feature_auto_20_output-1.png)
]

---
count: false

.panel1-feature-auto[

```r
to_percent = function(x){(100*x) %>% round(1) %>% paste("%")}

library(tidyverse)
theme_set(theme_bw(base_size = 20))
Titanic %>%
  data.frame() %>%
  ggplot(aes(x = Sex, fill = Survived, weight = Freq)) +
  geom_bar(position = "dodge") +
# Proportion per group
  aes(y     = after_stat(prop), group = Survived) +
  aes(label = to_percent(after_stat(prop))) +
  stat_count(geom = "text", size = 4,
             position =
               position_dodge2(width = .9, preserve = "single")) +
  scale_y_continuous(labels = scales::percent_format()) +
# Proportion of total
  aes(y = after_stat(count / sum(count))) +
  aes(label = to_percent(after_stat(count / sum(count)))) +
# Proportion per x position
  aes(y = after_stat(count / ave(count, x, FUN = sum))) +
  aes(label = to_percent(after_stat(count / ave(count, x, FUN = sum)))) +
  facet_wrap(~ Class) +
# Proportion per panel
  aes(y = after_stat(count / ave(count, PANEL, FUN = sum))) +
  aes(label = to_percent(after_stat(count / ave(count, PANEL, FUN = sum)))) +
# Proportion per panel and x position
  aes(y = after_stat(count / ave(count, x, PANEL, FUN = sum))) +
  aes(label = to_percent(after_stat(count / ave(count, x, PANEL, FUN = sum)))) +
# Proportion per panel and fill
* aes(y = after_stat(count / ave(count, fill, PANEL, FUN = sum)))
```
]
 
.panel2-feature-auto[
![](prop-is-hard-to-use_files/figure-html/feature_auto_21_output-1.png)
]

---
count: false

.panel1-feature-auto[

```r
to_percent = function(x){(100*x) %>% round(1) %>% paste("%")}

library(tidyverse)
theme_set(theme_bw(base_size = 20))
Titanic %>%
  data.frame() %>%
  ggplot(aes(x = Sex, fill = Survived, weight = Freq)) +
  geom_bar(position = "dodge") +
# Proportion per group
  aes(y     = after_stat(prop), group = Survived) +
  aes(label = to_percent(after_stat(prop))) +
  stat_count(geom = "text", size = 4,
             position =
               position_dodge2(width = .9, preserve = "single")) +
  scale_y_continuous(labels = scales::percent_format()) +
# Proportion of total
  aes(y = after_stat(count / sum(count))) +
  aes(label = to_percent(after_stat(count / sum(count)))) +
# Proportion per x position
  aes(y = after_stat(count / ave(count, x, FUN = sum))) +
  aes(label = to_percent(after_stat(count / ave(count, x, FUN = sum)))) +
  facet_wrap(~ Class) +
# Proportion per panel
  aes(y = after_stat(count / ave(count, PANEL, FUN = sum))) +
  aes(label = to_percent(after_stat(count / ave(count, PANEL, FUN = sum)))) +
# Proportion per panel and x position
  aes(y = after_stat(count / ave(count, x, PANEL, FUN = sum))) +
  aes(label = to_percent(after_stat(count / ave(count, x, PANEL, FUN = sum)))) +
# Proportion per panel and fill
  aes(y = after_stat(count / ave(count, fill, PANEL, FUN = sum))) +
* aes(label = to_percent(after_stat(count / ave(count, fill, PANEL, FUN = sum))))
```
]
 
.panel2-feature-auto[
![](prop-is-hard-to-use_files/figure-html/feature_auto_22_output-1.png)
]

<style>
.panel1-feature-auto {
  color: black;
  width: 49%;
  hight: 32%;
  float: left;
  padding-left: 1%;
  font-size: 80%
}
.panel2-feature-auto {
  color: black;
  width: 49%;
  hight: 32%;
  float: left;
  padding-left: 1%;
  font-size: 80%
}
.panel3-feature-auto {
  color: black;
  width: NA%;
  hight: 33%;
  float: left;
  padding-left: 1%;
  font-size: 80%
}
</style>

---

```r
layer_all_stages <- function(){

a <- ggtrace::layer_before_stat() %>% head(3)
b <- ggtrace::layer_after_stat() %>% head(3)
c <- ggtrace::layer_before_geom() %>% head(3)
d <- ggtrace::layer_after_scale() %>% head(3)

list(before_stat = a, after_stat = b, 
     before_geom = c, after_scale = d)

}

layer_all_stages()
```

```
## $before_stat
## # A tibble: 3 × 5
##   group x          fill  weight PANEL
##   <int> <mppd_dsc> <fct>  <dbl> <fct>
## 1     1 1          No         0 1    
## 2     1 1          No         0 2    
## 3     1 1          No        35 3    
## 
## $after_stat
## # A tibble: 3 × 8
##   count   prop x          width flipped_aes group fill  PANEL
##   <dbl>  <dbl> <mppd_dsc> <dbl> <lgl>       <int> <fct> <fct>
## 1   118 0.967  1            0.9 FALSE           1 No    1    
## 2     4 0.0328 2            0.9 FALSE           1 No    1    
## 3    62 0.305  1            0.9 FALSE           2 Yes   1    
## 
## $before_geom
## # A tibble: 3 × 10
##   label       y count   prop x          width flipped_aes group fill  PANEL
##   <chr>   <dbl> <dbl>  <dbl> <mppd_dsc> <dbl> <lgl>       <int> <fct> <fct>
## 1 96.7 % 0.967    118 0.967  1            0.9 FALSE           1 No    1    
## 2 3.3 %  0.0328     4 0.0328 2            0.9 FALSE           1 No    1    
## 3 30.5 % 0.305     62 0.305  1            0.9 FALSE           2 Yes   1    
## 
## $after_scale
## # A tibble: 3 × 17
##   fill    label       y count   prop x      flipped_aes group PANEL  ymin   ymax
##   <chr>   <chr>   <dbl> <dbl>  <dbl> <mppd> <lgl>       <int> <fct> <dbl>  <dbl>
## 1 #F8766D 96.7 % 0.967    118 0.967  0.775  FALSE           1 1         0 0.967 
## 2 #F8766D 3.3 %  0.0328     4 0.0328 1.775  FALSE           1 1         0 0.0328
## 3 #00BFC4 30.5 % 0.305     62 0.305  1.225  FALSE           2 1         0 0.305 
## # ℹ 6 more variables: xmin <mppd_dsc>, xmax <mppd_dsc>, colour <lgl>,
## #   linewidth <dbl>, linetype <dbl>, alpha <lgl>
```

---

```r
prop_by <- function(...) {
  count <- evalq(count, parent.frame())
  if (length(list(...)) == 0) {
    count / sum(count)
  } else {
    count / ave(count, ..., FUN = function(x) sum(abs(x)))
  }
}

ggplot(diamonds, aes(cut, fill = color)) +
  geom_bar(position = "dodge") + 
  aes(y = after_stat(prop_by()))
```

![](prop-is-hard-to-use_files/figure-html/unnamed-chunk-2-1.png)

---

### Contribute

- https://github.com/EvaMaeRey/ggcirclepack

---

### Check out {packcircles} which does the computation in ggcirclepack

- https://github.com/mbedward/packcircles

---

### 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

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