Introduction to ggplot2

Learning Objectives

Understand the code structure for ggplot plots
Understand layers of ggplot objects
Adding labels and captions of ggplot objects
Understand aesthetics of ggplot objects
Know the difference between mapping & setting aesthetics

Let’s load some packages to start with

library(palmerpenguins)
library(tidyverse)
library(knitr)

Let’s load the Palmer Penguins data set and explore some high-level characteristics of the data set.

data(penguins, package = "palmerpenguins")

glimpse(penguins)

## Rows: 344
## Columns: 8
## $ species           <fct> Adelie, Adelie, Adelie, Adelie, Adelie, Adelie, Adel…
## $ island            <fct> Torgersen, Torgersen, Torgersen, Torgersen, Torgerse…
## $ bill_length_mm    <dbl> 39.1, 39.5, 40.3, NA, 36.7, 39.3, 38.9, 39.2, 34.1, …
## $ bill_depth_mm     <dbl> 18.7, 17.4, 18.0, NA, 19.3, 20.6, 17.8, 19.6, 18.1, …
## $ flipper_length_mm <int> 181, 186, 195, NA, 193, 190, 181, 195, 193, 190, 186…
## $ body_mass_g       <int> 3750, 3800, 3250, NA, 3450, 3650, 3625, 4675, 3475, …
## $ sex               <fct> male, female, female, NA, female, male, female, male…
## $ year              <int> 2007, 2007, 2007, 2007, 2007, 2007, 2007, 2007, 2007…

Creating our first `ggplot`

Start by creating a blank canvass by using the penguins data frame.

ggplot(data = penguins)

Map bill depth to the x-axis

ggplot(data = penguins,
       aes(x = bill_depth_mm))

Next, we add y-axis, bill lengths (mm)

ggplot(data = penguins,
       aes(x = bill_depth_mm,
           y = bill_length_mm))

Add a scatter plot using `geom_point()`

Create a scatter plot, representing each two-dimensional observation with a point by adding a geom_point() layer. Additional layers are added to a ggplot using the + operator.

ggplot(data = penguins,
       aes(x = bill_depth_mm,
           y = bill_length_mm)) + 
  geom_point()

Color the points using a variable in the data set

Let’s color the points in our scatter plot based on the species of the penguin being Adelie, Chinstrap, or Gentoo, reproducing the plot below.

ggplot(data = penguins,
       aes(x = bill_depth_mm,
           y = bill_length_mm,
           color = species)) + 
  geom_point()

Add `labs()` to customize the title and subtitle

Next, add another layer to our ggplot to customize the title and subtitle using the labs() function to reproduce the plot below.

ggplot(data = penguins,
       aes(x = bill_depth_mm,
           y = bill_length_mm,
           color = species)) + 
  geom_point() + 
  labs(title = "Penguins bill lengths by bill depths",
       subtitle = "Dimensions for Adelie, Chinstrap and Gentoo penguins")

Also customize the axis labels using the x and y options in the `labs()` function.

ggplot(data = penguins,
       aes(x = bill_depth_mm,
           y = bill_length_mm,
           color = species)) + 
  geom_point() + 
  labs(title = "Penguins bill lengths by bill depths",
       subtitle = "Dimensions for Adelie, Chinstrap and Gentoo penguins",
       x = "Bill depth (mm)",
       y = "Bill length (mm)",
       color = "species")

Legend title

We can also customize the legend title by using the color option and a caption for the overall plot using the caption option in the labs() function. Customize the legend title to be “Species” instead of “species”, and modify the plot caption to match our overall desired plot.

ggplot(data = penguins,
       aes(x = bill_depth_mm,
           y = bill_length_mm,
           color = species)) + 
  geom_point() + 
  labs(title = "Penguins bill lengths by bill depths",
       subtitle = "Dimensions for Adelie, Chinstrap and Gentoo penguins",
       x = "Bill depth (mm)",
       y = "Bill length (mm)",
       color = "species",
       caption = "ggplot by @Anangwe")

Change color to accomodate color blindness

Lastly, use a discrete color scale that is inclusive of viewers with common forms of color blindness by adding a scale_color_viridis_d() layer to the plot, creating the final plot below.

ggplot(data = penguins,
       aes(x = bill_depth_mm,
           y = bill_length_mm,
           color = species)) + 
  geom_point() + 
  labs(title = "Penguins bill lengths by bill depths",
       subtitle = "Dimensions for Adelie, Chinstrap and Gentoo penguins",
       x = "Bill depth (mm)",
       y = "Bill length (mm)",
       color = "species",
       caption = "ggplot by @Anangwe",
       scale_color_viridis_d())

Mapping and scattering aesthetics

ggplot(data = penguins,
       aes(x = bill_depth_mm,
           y = bill_length_mm,
           color = species,
           size = body_mass_g,
           alpha = 0.50)) + 
  geom_point() + 
  labs(title = "Penguins bill lengths by bill depths",
       subtitle = "Dimensions for Adelie, Chinstrap and Gentoo penguins",
       x = "Bill depth (mm)",
       y = "Bill length (mm)",
       color = "species",
       caption = "ggplot by @Anangwe",
       scale_color_viridis_d())

Missing values

To see missing values we can use skim() function from the skimr package. Works best with html.

library(skimr)
skim(penguins)

Data summary
Name	penguins
Number of rows	344
Number of columns	8
_______________________
Column type frequency:
factor	3
numeric	5
________________________
Group variables	None

Variable type: factor

skim_variable	n_missing	complete_rate	ordered	n_unique	top_counts
species	0	1.00	FALSE	3	Ade: 152, Gen: 124, Chi: 68
island	0	1.00	FALSE	3	Bis: 168, Dre: 124, Tor: 52
sex	11	0.97	FALSE	2	mal: 168, fem: 165

Variable type: numeric

skim_variable	n_missing	complete_rate	mean	sd	p0	p25	p50	p75	p100	hist
bill_length_mm	2	0.99	43.92	5.46	32.1	39.23	44.45	48.5	59.6	▃▇▇▆▁
bill_depth_mm	2	0.99	17.15	1.97	13.1	15.60	17.30	18.7	21.5	▅▅▇▇▂
flipper_length_mm	2	0.99	200.92	14.06	172.0	190.00	197.00	213.0	231.0	▂▇▃▅▂
body_mass_g	2	0.99	4201.75	801.95	2700.0	3550.00	4050.00	4750.0	6300.0	▃▇▆▃▂
year	0	1.00	2008.03	0.82	2007.0	2007.00	2008.00	2009.0	2009.0	▇▁▇▁▇

Create a histogram

Reproduce the histogram of the penguin body masses displayed below using ggplot2

ggplot(data = penguins,
       aes(x = body_mass_g)) +
  geom_histogram()

Create a box plot

Reproduce the box plot of the penguin body masses displayed below using ggplot2. Hint: to suppress the y-axis text and ticks, add a theme(axis.text.y = element_blank(), axis.ticks.y = element_blank()) layer to the plot.

ggplot(data = penguins,
       aes(x = body_mass_g,
           y = species,
           color = species)) +
  geom_boxplot() +
  theme(axis.text.y = element_blank(), axis.ticks.y = element_blank())