2 Histograms

Histograms require:

✅ a numeric (continuous) variable

2.1 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’ (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’ (i.e., is there a long ‘tail’ of bars with decreasing length on either end of the x axis?) of a variable’s distribution.

2.2 Set up

PACKAGES:

Install packages.

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install.packages("palmerpenguins")
library(palmerpenguins) 
library(ggplot2)

DATA:

The penguins data.

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penguins <- palmerpenguins::penguins
glimpse(penguins)
#> Rows: 344
#> Columns: 8
#> $ species           <fct> Adelie, Adelie, Adelie…
#> $ island            <fct> Torgersen, Torgersen, …
#> $ bill_length_mm    <dbl> 39.1, 39.5, 40.3, NA, …
#> $ bill_depth_mm     <dbl> 18.7, 17.4, 18.0, NA, …
#> $ flipper_length_mm <int> 181, 186, 195, NA, 193…
#> $ body_mass_g       <int> 3750, 3800, 3250, NA, …
#> $ sex               <fct> male, female, female, …
#> $ year              <int> 2007, 2007, 2007, 2007…

2.3 Grammar

CODE:

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

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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

GRAPH:

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.’