Geom point

Scatter plots are commonly used to display the relationship between two continuous variables.

In this page we will create scatter plots with ggplot2::geom_point(). Through examples we will demonstrate creating:

A default scatter plot to plot two continuos variables against each other.
A scatter plot with the points coloured by a categorical variable.
A scatter plot with the colour and shapes of points determined by 2 categorical variables.
A scatter plot with the size of the points representing a third continuous variable.

Dataset

For demonstration we’ll load the mushroom_tbl data from the mgrtibbles package (hyperlink includes install instructions). We will extract a random sample of 150 rows with slice_sample().

mushroom_tbl details

#Load package
library("mgrtibbles")
#Set seed for random sampling
set.seed("483")
#mushroom_tbl tibble for demonstration
mushroom_tbl <- mgrtibbles::mushroom_tbl |>
    #Random sample of 150 rows
    dplyr::slice_sample(n = 150, replace=FALSE)
#Reset random seed to normal operation
set.seed(NULL)

Default scatter plot

Create a scatter plot of stem_height (y) against stem_width (x).

mushroom_tbl |>
    ggplot2::ggplot(aes(x = stem_width, y = stem_height)) +
        ggplot2::geom_point()

Colour groups

When displaying a single categorical variable it is normally best practice to use the colour aesthetic.

Create a scatter plot of stem_height (y) against stem_width (x). In aes() set colour=class so each point is coloured by whether its is edible or poisonous.

mushroom_tbl |>
    ggplot2::ggplot(aes(x = stem_width, y = stem_height, colour = class)) +
        ggplot2::geom_point()

Colour & shape groups

When displaying 2 different categorical variables in a scatter plot it is common to use colour and shape. I advise using colour for the variable with more groupings.

Create a scatter plot of stem_height (y) against stem_width (x). In aes() set colour=cap_shape and shape=class. Additionally, make the point sizes larger with size=2 in the ggplot2::geom_point() function.

mushroom_tbl |>
    ggplot2::ggplot(aes(x = stem_width, y = stem_height, shape = class, colour = cap_shape)) +
        ggplot2::geom_point(size = 2)

Size by continuous variable

To display a third continuous variable on a scatter plot the size of the points can be used. This can cause issues where it is more likely points will overlap due to large values producing large points.

Create a scatter plot of stem_height (y) against stem_width (x). In aes() set size=cap_diameter so the size of the points represents the cap diameter size.

mushroom_tbl |>
    ggplot2::ggplot(aes(x = stem_width, y = stem_height, size = cap_diameter)) +
        ggplot2::geom_point()

Other considerations

You may want to use a different plot or add other layers on top of a scatter plot depending on you and your data’s needs.

A smooth lin to display patters (i.e. a linear model) can be added with geom_smooth()
If there are too many values to effectively plot with a scatter plot you may want to use a 2D bin count plot
Dashes can be added to the axes margins to display the distributions along with the 2d plot, this is called a rug plot