Creating and styling boxplots

Key Components of a Boxplot:

• Box: Represents the interquartile range (IQR).

• Whiskers: Extend to the smallest and largest data points within 1.5 times the IQR from Q1 and Q3.

• Median: The line inside the box, representing the middle value of the dataset.

• Outliers: Shown as individual points beyond the whiskers.

Boxplots provide a concise summary, making it easier to understand the distributional properties of a dataset at a glance.

In this tutorial, we demonstrate how to create boxplots using ggplot. We will use a dataset from a nutrition survey of school children 10 years and older from Pakistan. This dataset is available from the Oxford iHealth teaching datasets repository

## link to CSV from GitHub repository ----
1csv_file_url <- "https://raw.githubusercontent.com/OxfordIHTM/teaching_datasets/refs/heads/main/school_nutrition.csv"

## Read CSV file ----
2nut_data <- read.csv(file = csv_file_url)

On inspection of the dataset, we see:

## Show first 5 rows of data ----
head(nut_data)

  region school age_months sex weight height
1      1      1        121   2   20.6  124.6
2      1      1        121   1   27.9  130.7
3      1      1        129   2   25.7  131.4
4      1      1        133   1   27.0  135.7
5      1      1        145   2   28.5  130.5
6      1      1        148   2   35.1  142.1

We have a data.frame with 267 rows and 6 columns.

For this tutorial, we will focus on the weight variable in the dataset for demonstrating how to create and style boxplots in base R.

Creating a boxplot

A boxplot of the weight variable for all children in the dataset can be created as follows:

## Load ggplot2 ----
1library(ggplot2)

## Boxplot of weight of all children ----
2ggplot(data = nut_data, mapping = aes(x = "", y = weight)) +
3  geom_boxplot() +
4  labs(
5    title = "Summary of weight values for all children",
6    subtitle = "School children 10 years and above in Pakistan",
7    y = "Weight (kgs)"
  ) +
8  theme_minimal()

1

Load {ggplot2}. If not yet installed, run install.packages("ggplot2").

2

Set ggplot aesthetic mappings. For boxplot, we just need to set the y axis value aesthetic and provide an empty character x axis value aesthetic so that the x-axis will be treated as a character value. For more information, run ?ggplot.

3

Plot the boxplot using geom_boxplot(). For more information, run ?geom_histogram.

4

Set labels of the plot. For more information, run ?labs.

5

Set the title of the plot.

6

Set the subtitle of the plot.

7

Set the y axis label of the plot.

8

Set a plot theme. For more information, run ?themes.

A boxplot for weight by sex is created as follows:

## Convert sex to factor ----
nut_data$sex <- factor(nut_data$sex, labels = c("Male", "Female"))

## Boxplot of weight by sex of children ----
1ggplot(data = nut_data, mapping = aes(x = sex, y = weight)) +
  geom_boxplot() +
  labs(
    title = "Summary of weight values by sex",
    subtitle = "School children 10 years and above in Pakistan",
    x = "Sex",
    y = "Weight (kgs)"
  ) +
  theme_minimal()

1

Set x-axis variable to sex.