Faceting for subplots in R Programming - Step-by-Step Execution

Concept Flow - Faceting for subplots

Start with data frame

↓

Choose variable to facet by

↓

Split data into groups

↓

Create subplot for each group

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Arrange subplots in grid

↓

Display combined plot

Faceting splits data by a variable and makes a small plot for each group, arranging them in a grid.

Execution Sample

R Programming

library(ggplot2)

p <- ggplot(mpg, aes(displ, hwy)) +
  geom_point() +
  facet_wrap(~ class)

print(p)

This code creates scatterplots of engine displacement vs highway mpg, one subplot per car class.

Execution Table

Step	Action	Data State	Plot State	Output
1	Load ggplot2 and mpg data	mpg data frame loaded	No plot yet	No output
2	Create base plot with displ vs hwy	mpg data frame	Base scatterplot created	No output
3	Apply facet_wrap(~ class)	mpg split into groups by class	Subplots created for each class	No output
4	Arrange subplots in grid	Groups ready	Subplots arranged in grid layout	No output
5	Print plot	Data unchanged	Plot displayed with multiple subplots	Scatterplots shown, one per class
6	End	No change	Plot displayed	Execution stops

💡 All steps complete, plot with faceted subplots displayed

Variable Tracker

Variable	Start	After Step 2	After Step 3	After Step 4	Final
mpg	Loaded data frame	Unchanged	Unchanged	Unchanged	Unchanged
p	Not defined	Base plot object created	Faceted plot object created	Subplots arranged	Ready to print

Key Moments - 3 Insights

Why does the plot show multiple small plots instead of one big plot?

Because facet_wrap(~ class) splits the data by the 'class' variable and creates one subplot per group, as shown in execution_table step 3.

Does the original data change when faceting is applied?

No, the data remains the same; faceting only changes how the plot is displayed by grouping data visually, as seen in variable_tracker where 'mpg' stays unchanged.

What controls how the subplots are arranged on the page?

facet_wrap arranges subplots in a grid automatically, as described in execution_table step 4.

Visual Quiz - 3 Questions

Look at the execution_table, at which step is the data split into groups for faceting?

A Step 2

B Step 4

C Step 3

D Step 5

💡 Hint

Check the 'Data State' column in execution_table rows to see when data is split.

According to variable_tracker, what is the state of variable 'p' after Step 3?

A Base plot object created

B Faceted plot object created

C Not defined

D Subplots arranged

💡 Hint

Look at the 'p' row and 'After Step 3' column in variable_tracker.

If we remove facet_wrap, how would the output change at Step 5?

A Only one plot without subplots would be shown

B Multiple subplots would still appear

C No plot would be shown

D Plot would show different variables

💡 Hint

Refer to execution_table step 3 and 5 about faceting effect on plot output.

Concept Snapshot

Faceting splits data by a variable to create multiple small plots.
Use facet_wrap(~ variable) or facet_grid(rows ~ cols).
Each subplot shows data for one group.
Subplots are arranged in a grid automatically.
Original data stays unchanged.
Great for comparing groups visually.

Full Transcript

Faceting in R with ggplot2 means splitting your data by a variable and making a small plot for each group. The code starts by loading the data and creating a base plot. Then, facet_wrap(~ class) splits the data by the 'class' variable and creates one subplot per group. These subplots are arranged in a grid automatically. The original data does not change; only the plot display changes. Finally, printing the plot shows all subplots together. This helps compare groups side by side easily.