box_plots.qmd

# Box plots {#sec-box-plots}

```{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 ----
# polishing, restructuring, drafting, complete
status("complete")
```

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

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

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

<br>

```{r}
#| label: full_code_display
#| eval: true
#| echo: false
#| warning: false
#| message: false
#| out-height: '60%'
#| out-width: '60%'
#| fig-align: right
library(ggplot2movies)
library(ggplot2)
penguins <- palmerpenguins::penguins 
labs_boxplot <- labs(
  title = "Adult foraging penguins",
  subtitle = "Distribution of flipper length",
  x = NULL,
  y = "Flipper length (millimeters)")
ggp2_boxplot <- ggplot(data = penguins,
           aes(x = "", 
               y = flipper_length_mm)) +
        geom_boxplot() 
ggp2_boxplot + 
  labs_boxplot
```

::::

## Description

Box plots use five values to summarize data: minimum, first quartile, median, third quartile, and maximum. The plot looks like a box with a line in the middle. Whiskers go from the box to the minimum and maximum values. Unusual points are shown as dots outside the whiskers. Box plots help identify unusual points and compare different groups of data.

## Set up

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**PACKAGES:**
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::: {style="font-size: 0.95rem;"}
Install packages.
:::


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


::: {style="font-size: 1.10em; color: #1e83c8;"}
**DATA:**
:::

::: {.column-margin}
![Artwork by Allison Horst](www/lter_penguins.png){fig-align="right" width="100%" height="100%"}
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::: {style="font-size: 0.95rem;"}
We'll be using the `penguins` data from `palmerpenguins`.
:::

::: {style="font-size: 0.85em;"}
```{r}
#| label: data_code_box
#| code-fold: show
#| eval: true
#| echo: true
penguins <- palmerpenguins::penguins 
glimpse(penguins)
```
:::

## Grammar


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**CODE:**
:::

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

Create labels with `labs()`

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

  - Assign a blank character string (`""`) to the `x` axis in `labs()`

Map `flipper_length_mm` to the `y` axis and an empty string (`""`) to the `x` axis

Add the `geom_boxplot()` layer

:::

::: {style="font-size: 0.85em;"}
```{r}
#| label: code_graph_box
#| code-fold: show
#| eval: false
#| echo: true 
#| warning: false
#| message: false
labs_boxplot <- labs(
  title = "Adult foraging penguins",
  subtitle = "Distribution of flipper length",
  x = "",
  y = "Flipper length (millimeters)")
ggp2_boxplot <- ggplot(data = penguins,
           aes(x = "", 
               y = flipper_length_mm)) +
        geom_boxplot() 
ggp2_boxplot + 
  labs_boxplot
```
:::



::: {style="font-size: 1.10em; color: #1e83c8;"}
**GRAPH:**
:::

```{r}
#| label: create_graph_box
#| eval: true
#| echo: false
#| warning: false
#| message: false
#| layout-nrow: 1
#| column: page-inset-right
labs_boxplot <- labs(
  title = "Adult foraging penguins",
  subtitle = "Distribution of flipper length",
  x = "",
  y = "Flipper length (millimeters)")
ggp2_boxplot <- ggplot(data = penguins,
           aes(x = "", 
               y = flipper_length_mm)) +
        geom_boxplot() 
ggp2_boxplot + 
  labs_boxplot
```



### More Info

Below is more information on interpreting Box plots. 

### `movies` data 

::: {style="font-size: 0.95rem;"}
We'll use the `ggplot2movies::movies` data to create a box plot for movie `length`
:::

::: {style="font-size: 0.85em;"}
```{r}
#| label: more_box_pkgs
#| eval: false
#| echo: true
#| warning: false
#| message: false
install.packages("ggplot2movies")
library(ggplot2movies) 
library(ggplot2)
```
:::

::: {style="font-size: 0.95rem;"}
Filter `ggplot2movies::movies` to only include films after the made after `2000`, and remove missing values from `mpaa` and `budget`
:::

::: {style="font-size: 0.85em;"}
```{r}
#| label: more_box_data
#| eval: true
#| echo: true
#| warning: false
#| message: false
movies_box <- ggplot2movies::movies |> 
                dplyr::filter(year > 2000 & 
                                mpaa != "" & 
                                    !is.na(budget))
head(movies_box)
```
:::



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

Below we create a box plot of the `length` variable using the methods described above: 

:::

::: {style="font-size: 0.85em;"}
```{r}
#| label: more_create_graph_box
#| eval: true
#| echo: true
#| warning: false
#| message: false
#| layout-nrow: 1
#| column: page-inset-right
labs_boxplot <- labs(
  title = "IMDB Movie information and user ratings",
  y = "Movie length (min)", x = "")
ggp2_boxplot <- ggplot(data = movies_box, 
           aes(x = " ", 
               y = length)) +
        geom_boxplot() 

ggp2_boxplot + 
  labs_boxplot
```
:::

### Interpret

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The table below shows the 25th percentile, the median, the 75th percentile, the IQR, and a histogram of the `length` variable from the `movies_box` dataset.
:::

::: {style="font-size: 0.85em;"}
```{r}
#| label: box_table_stats
#| eval: true
#| echo: false 
lgnth_skim <- skimr::skim(movies_box$length)
LengthBoxStats <- select(lgnth_skim,
     `25th` = numeric.p25, Median = numeric.p50,
     `75th` = numeric.p75, Histogram = numeric.hist) %>%
     mutate(IQR = IQR(movies_box$length, na.rm = TRUE)) %>%
     select(`25th`, Median, `75th`, IQR, Histogram)
kableExtra::kable_paper(
  kable_input = knitr::kable(LengthBoxStats), 
  font_size = 14)
```
:::

::: {style="font-size: 0.95rem;"}
The figure below displays how each element in the box plot represents each of the statistics using lines and points.
:::

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::: {style="font-size: 0.95rem;"}
In `ggplot2`, values that fall more than 1.5 times the IQR are displayed as individual points (aka outliers). The lines extending from the bottom and top of the main box represent the last non-outlier value in the distribution.
:::
::::

![](www/boxplot-diagram.png){fig-align="center" width="80%" height="80%"}


### Compare

::: {style="font-size: 0.95rem;"}
Compare the `geom_point()`, `geom_freqpoly()`, `geom_histogram()`, and `geom_density()` graphs of `length` from `movie_box` below to the `geom_boxplot()`:
:::

![](www/boxplot-comparisons.png){fig-align="center" width="85%" height="85%"}