Mastering the Art of Customizing Boxplots: Changing No. Decimal Points Displayed for Quantile Values with ggboxplot()

In the world of data visualization, boxplots are a staple for exploring and showcasing the distribution of data. However, when it comes to customizing these plots to suit our specific needs, things can get a bit tricky. One common challenge is changing the number of decimal points displayed for quantile values on a boxplot. Fear not, dear reader, for we’re about to embark on a journey to tackle this exact issue using the mighty ggboxplot() function from the ggpubr package!

The Problem: Too Many Decimal Points!

Imagine you’re working with a dataset that contains values with many decimal points, like stock prices or scientific measurements. When creating a boxplot, the default behavior of ggboxplot() is to display the quantile values with a whopping six decimal points. This can lead to cluttered and hard-to-read plots. What if you want to limit the decimal points to, say, two or three? That’s where the magic of stat_summary() comes in!

Understanding stat_summary()

stat_summary() is a geom_statistic() function that allows us to customize the summary statistics displayed on a plot. By default, ggboxplot() uses stat_summary() behind the scenes to calculate and display the quantile values. To change the number of decimal points, we need to tap into this functionality.

library(ggpubr)
library(ggplot2)

# Create a sample dataset
set.seed(123)
df <- data.frame(x = rnorm(100, mean = 10, sd = 2))

# Basic boxplot with default quantile values
ggboxplot(df, x = "x", y = "..x..") + 
  stat_summary(fun.data = "mean_sdl", geom = "point", col = "red")

This code generates a basic boxplot with the mean and standard deviation displayed as a red point. But, oh dear, look at all those decimal points!

The Solution: Formatting Quantile Values with %1.1f

To limit the number of decimal points, we’ll use the sprintf() function in conjunction with stat_summary(). Specifically, we’ll employ the %1.1f format specifier to round the quantile values to one decimal point. Let’s see it in action!

library(ggpubr)
library(ggplot2)

# Create a sample dataset
set.seed(123)
df <- data.frame(x = rnorm(100, mean = 10, sd = 2))

# Custom boxplot with one decimal point for quantile values
ggboxplot(df, x = "x", y = "..x..") + 
  stat_summary(fun.data = function(x) {
    data.frame(y = sprintf("%1.1f", x),
               label = c("Min", "Q1", "Median", "Q3", "Max"))
  }, geom = "label", aes(label = label), col = "red")

Voilà! Our boxplot now displays the quantile values with a single decimal point, making it much easier to read and understand. But wait, there’s more!

Changing the Number of Decimal Points

What if you want to display two or three decimal points instead of one? Simple! Just adjust the format specifier accordingly. For two decimal points, use %1.2f, and for three, use %1.3f.

# Two decimal points
ggboxplot(df, x = "x", y = "..x..") + 
  stat_summary(fun.data = function(x) {
    data.frame(y = sprintf("%1.2f", x),
               label = c("Min", "Q1", "Median", "Q3", "Max"))
  }, geom = "label", aes(label = label), col = "red")

# Three decimal points
ggboxplot(df, x = "x", y = "..x..") + 
  stat_summary(fun.data = function(x) {
    data.frame(y = sprintf("%1.3f", x),
               label = c("Min", "Q1", "Median", "Q3", "Max"))
  }, geom = "label", aes(label = label), col = "red")

Additional Customizations

Now that we’ve conquered the decimal point conundrum, let’s explore some additional customizations to take our boxplots to the next level!

Changing the Font and Color

Want to make the quantile values stand out? Try changing the font and color to something that pops!

ggboxplot(df, x = "x", y = "..x..") + 
  stat_summary(fun.data = function(x) {
    data.frame(y = sprintf("%1.2f", x),
               label = c("Min", "Q1", "Median", "Q3", "Max"))
  }, geom = "label", aes(label = label), col = "blue", fontface = "bold")

Adding Custom Labels

Sometimes, we want to add custom labels to our boxplot. No problem! Simply modify the label argument in the data frame within stat_summary().

ggboxplot(df, x = "x", y = "..x..") + 
  stat_summary(fun.data = function(x) {
    data.frame(y = sprintf("%1.2f", x),
               label = c("Minimum", "First Quartile", "Median", "Third Quartile", "Maximum"))
  }, geom = "label", aes(label = label), col = "blue")

Conclusion

In this article, we’ve demystified the process of changing the number of decimal points displayed for quantile values on a boxplot using ggboxplot() and stat_summary(). By leveraging the power of sprintf() and format specifiers, we can customize our plots to meet our specific needs. Whether you’re working with financial data, scientific measurements, or any other type of data, mastering this technique will help you communicate your findings more effectively. So, go ahead, get creative, and take your data visualization skills to the next level!

Format Specifier	Description
%1.1f	One decimal point
%1.2f	Two decimal points
%1.3f	Three decimal points

Remember, the possibilities are endless when it comes to customizing your boxplots. Experiment with different format specifiers, colors, and labels to create visually stunning plots that tell a story!

• ggpubr package documentation
• ggplot2 geom_label() documentation
• sprintf() function documentation

Get out there and start customizing those boxplots!

Frequently Asked Question

Get clarity on changing the number of decimal points displayed for quantile values on a boxplot using ggboxplot() and stat_summary() function in R programming language.