stacked_filled_density_graphs.qmd

# Stacked densities {#sec-stacked-filled-density-graphs}

```{r}
#| label: setup
#| message: false
#| warning: false
#| include: false
library(tidyverse)
library(lubridate)
library(scales)
library(knitr)
library(kableExtra)
library(colorblindr)
library(downlit)
# fonts ----
library(extrafont)
library(sysfonts)
source("_common.R")
# use font
showtext::showtext_auto()
# set theme
ggplot2::theme_set(theme_ggp2g(
    base_size = 15))
```

```{r}
#| label: status
#| results: "asis"
#| echo: false
# status ----
# polish, dev, draft, complete
status("complete")
```


:::: {.callout-note collapse="false" icon=false}

<br>

```{r}
#| label: full_code_display
#| eval: true
#| echo: false
#| warning: false
#| message: false
#| out-height: '60%'
#| out-width: '60%'
#| fig-align: right
library(palmerpenguins) 
library(ggplot2)
peng_density <- filter(palmerpenguins::penguins, !is.na(sex))
labs_fill_density <- labs(
  title = "Adult foraging penguins",
  x = "Flipper length (mm)",
  fill = "Sex")
ggp2_fill_density <- ggplot(data = peng_density, 
       aes(x = flipper_length_mm, 
           after_stat(count),
          fill = sex)) +
      geom_density(position = "fill") 
ggp2_fill_density + 
  labs_fill_density
```

::: {style="font-size: 1.10em; color: #02577A;"}
**This graph requires:**
:::

::: {style="font-size: 1.05em; color: #282b2d;"}
**`r emo::ji("check")` a categorical variable**      
:::

::::

## Description 

Density graphs are typically used to visualize the distribution of a single variable, but stacked density graphs are great for visualizing how proportions vary across numeric (continuous) variables.

## Set up

::: {style="font-size: 1.15em; color: #1e83c8;"}
**PACKAGES:**
:::

Install packages.


::: {style="font-size: 0.85em;"}
```{r}
#| label: pkg_code_fill_density
#| code-fold: show
#| eval: true
#| echo: true
#| warning: false
#| message: false
#| results: hide
install.packages("palmerpenguins")
library(palmerpenguins)
library(ggplot2)
```
:::



::: {style="font-size: 1.15em; color: #1e83c8;"}
**DATA:**
:::

::: {.column-margin}
![Artwork by Allison Horst](../www/lter_penguins.png){fig-align="right" width="100%" height="100%"}
:::


Remove missing `sex` from the `penguins` data.

::: {style="font-size: 0.85em;"}
```{r}
#| label: data_code_fill_density
#| code-fold: show
#| eval: true
#| echo: true
peng_density <- dplyr::filter(palmerpenguins::penguins, !is.na(sex))
dplyr::glimpse(peng_density)
```
:::


## Grammar

::: {style="font-size: 1.15em; color: #1e83c8;"}
**CODE:**
:::

::: {style="font-size: 0.95rem;"}

  -   Create labels with `labs()`

  -   Initialize the graph with `ggplot()` and provide `data`

  -   Map the `flipper_length_mm` to the `x` and add  `after_stat(count)` 

  -   Map `sex` to `fill`  

  -   *Inside* the `geom_density()` function, set `position` to `"fill"`

:::

::: {style="font-size: 0.85em;"}
```{r}
#| label: code_graph_fill_density
#| code-fold: show
#| eval: false
#| echo: true 
#| warning: false
#| message: false
#| out-height: '100%'
#| out-width: '100%'
labs_fill_density <- labs(
  title = "Adult foraging penguins",
  x = "Flipper length (mm)",
  fill = "Sex")
ggp2_fill_density <- ggplot(data = peng_density, 
       aes(x = flipper_length_mm, 
           after_stat(count),
          fill = sex)) +
      geom_density(position = "fill") 
ggp2_fill_density + 
  labs_fill_density
```
:::



::: {style="font-size: 1.15em; color: #1e83c8;"}
**GRAPH:**
:::

```{r}
#| label: create_graph_fill_density
#| eval: true
#| echo: false
#| warning: false
#| message: false
#| out-height: '100%'
#| out-width: '100%'
labs_fill_density <- labs(
  title = "Adult foraging penguins",
  x = "Flipper length (mm)",
  fill = "Sex")
ggp2_fill_density <- ggplot(data = peng_density, 
       aes(x = flipper_length_mm, 
           after_stat(count),
          fill = sex)) +
      geom_density(position = "fill") 
ggp2_fill_density + 
  labs_fill_density
```