histograms.qmd

# Histograms {#sec-histograms}


```{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))
```

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

::: {style="font-size: 1.25em; color: #02577A;"}
**Histograms require:**
:::

::: {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(palmerpenguins) 
library(ggplot2)
penguins <- palmerpenguins::penguins
labs_histogram <- labs(
  title = "Adult foraging penguins",
  subtitle = "Distribution of flipper length",
  x = "Flipper length (mm)")
ggp2_hist <- ggplot(data = penguins,
     aes(x = flipper_length_mm)) + 
     geom_histogram() 
ggp2_hist + 
  labs_histogram
```

::::

## Description 

A histogram is a graph that displays numerical data spread over a time frame or interval. Each bar shows the frequency of data points within a specific range. Unlike bar graphs, histograms do not have gaps between the bars, indicating that data covers a continuous interval. The x-axis displays the variable range, while the y-axis represents observation frequency.

Unlike a typical bar graph, histograms can be used to visually asses the '[normality](https://en.wikipedia.org/wiki/Normal_distribution)' (i.e. *are the bars symmetrical, with a single peak in the middle of the `x` axis?* Or *do the bars form multiple peaks?*) or '[skewness](https://en.wikipedia.org/wiki/Skewness)' (i.e., *is there a long 'tail' of bars with decreasing length on either end of the `x` axis?*) of a variable's distribution.

## Set up

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

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


::: {style="font-size: 0.85em;"}
```{r}
#| label: pkg_code_histogram
#| 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%"}
:::

::: {style="font-size: 0.95rem;"}
The `penguins` data.
:::

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


## Grammar 

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

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

Create labels with `labs()`

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

Assign `flipper_length_mm` to the `x`

Add the `geom_histogram()`

Adjust the `bins` accordingly 

:::

::: {style="font-size: 0.85em;"}
```{r}
#| label: code_graph_histogram
#| code-fold: show
#| eval: false
#| echo: true 
#| warning: false
#| message: false
labs_histogram <- labs(
  title = "Adult foraging penguins",
  subtitle = "Distribution of flipper length",
  x = "Flipper length (millimeters)")

ggp2_hist <- ggplot(data = penguins,
     aes(x = flipper_length_mm)) + 
     geom_histogram() 

ggp2_hist + 
  labs_histogram
```
:::


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

```{r}
#| label: create_graph_histogram
#| eval: true
#| echo: false
#| warning: false
#| message: false
#| layout-nrow: 1
#| column: page-inset-right
labs_histogram <- labs(
  title = "Adult foraging penguins",
  subtitle = "Distribution of flipper length",
  x = "Flipper length (millimeters)")

ggp2_hist <- ggplot(data = penguins,
     aes(x = flipper_length_mm)) + 
     geom_histogram() 

ggp2_hist + 
  labs_histogram
```


::: {style="font-size: 0.95rem;"}
The standard number of bins is `30`, but ['you should always override this value, exploring multiple widths to find the best to illustrate the stories in your data.'](https://ggplot2.tidyverse.org/reference/geom_histogram.html)
:::