Faceting in ggplot2

Introduction to faceting

The ggplot2 package offers several powerful data visualization and analysis features such as geoms, layering, aesthetic mapping, themes, and statistical transformations to enable customization and exploration.

Let’s explore another powerful feature of ggplot2—Faceting.

Faceting allows us to arrange multiple graphs on the same page. This feature is useful when working with large datasets, as it allows us to focus on specific subsets of data without getting overwhelmed by the overall complexity of the data. Moreover, dividing the data into smaller groups makes identifying patterns and trends in the dataset easier.

Types of faceting in ggplot2

The ggplot2 library offers three types of faceting for arranging multiple graphs on a single page:

• facet_null(): This creates a single plot, which is the default.
• facet_wrap(): This type of faceting organizes a one-dimensional ribbon of panels into a two-dimensional format, but only for variable combinations with values.
• facet_grid(): This creates a two-dimensional grid of panels based on specified variables for rows and columns, including plots for all variable combinations, even if a particular variable has no data.

The main difference between the facet_grid() and facet_wrap() functions is that the facet_grid() function makes all possible combinations of plots with different variables, even if some plots are empty. In contrast, the facet_wrap() function only makes plots with the available data.

To understand the use of faceting, we’ll first create an ice cream sales dataset that includes the following information:

• The different flavors of ice cream.
• The price per scoop.
• The outside air temperature during the purchase of ice cream by customers.
• Different shops selling the ice cream.
• Total sales made by the shops, etc.