How to Format Mouse Over Labels Using ggplotly in R

In this article, we will explain how to create a basic plot using ggplot2, convert it to an interactive plot using plotly, and customize the mouse-over labels according to our choice.

What is Mouse Over Labels?

Mouse-over labels are also known as tooltips, are interactive labels that appear when you hover your cursor over a specific element in a plot or chart. These labels display additional information about the data point being hovered on, such as its exact value or other relevant details. One of the key features in plotly is the ability to format tooltips (mouse-over labels) to display detailed information about data points.

However, ggplotly offers flexibility to customize these tooltips, allowing you to include specific information or format the labels as desired.

library(ggplot2)
library(plotly)

Now we will discuss Step-by-Step Guide to Format Mouse Over Labels Using ggplotly in R Programming Language.

Step 1: Create a Basic Plot Using ggplot2

Let's start by creating a simple scatter plot using the ggplot2 package. We will use the mtcars dataset, which contains various attributes of cars like miles per gallon (mpg), weight (wt), and horsepower (hp).

# Basic scatter plot using ggplot2
p <- ggplot(mtcars, aes(x = wt, y = mpg, color = as.factor(cyl))) +
  geom_point(size = 3) +
  labs(title = "Miles Per Gallon vs Weight",
       x = "Weight (1000 lbs)",
       y = "Miles per Gallon (mpg)",
       color = "Cylinders")
p

Output:

• wt is plotted on the x-axis (car weight).
• mpg is plotted on the y-axis (miles per gallon).
• Points are colored based on the number of cylinders (cyl).

Step 2: Convert the Plot to ggplotly

To make this plot interactive, we convert it to a plotly object using the ggplotly() function:

# Convert ggplot to plotly
ggplotly(p)

Output:

This command converts the static ggplot2 plot into an interactive plotly plot. By default, hovering over any point will display the x and y values, and the color group (cylinders).

Step 3: Customizing Mouse Over Labels (Tooltips)

By default, the tooltip displays values for wt, mpg, and cyl. However, you can customize these tooltips to display other information or format them differently using the text aesthetic within ggplot2.

# Add custom tooltip information using the text aesthetic
p <- ggplot(mtcars, aes(x = wt, y = mpg, color = as.factor(cyl), 
                        text = paste("Weight:", wt, "MPG:", mpg, "HP:", hp))) +
  geom_point(size = 3) +
  labs(title = "Miles Per Gallon vs Weight",
       x = "Weight (1000 lbs)",
       y = "Miles per Gallon (mpg)",
       color = "Cylinders")

# Convert to plotly with customized tooltips
ggplotly(p, tooltip = "text")

Output:

• Used the text aesthetic to create a custom label that includes weight, miles per gallon, and horsepower.
• Passed the tooltip = "text" argument to ggplotly() to tell it to use our custom text for the tooltips.

Step 4: Formatting Numbers

To format numbers (e.g., to display only two decimal places), you can use sprintf() or formatC():

# Load required libraries
library(ggplot2)
library(plotly)

# Create ggplot with custom tooltip information using the text aesthetic
p <- ggplot(mtcars, aes(x = wt, y = mpg, color = as.factor(cyl), 
                        text = paste0("<b>Weight:</b> ", wt, "<br>",
                                      "<b>MPG:</b> ", mpg, "<br>",
                                      "<b>HP:</b> ", hp, "<br>",
                                      "<b>Cylinders:</b> ", cyl))) +
  geom_point(size = 3) +
  labs(title = "Miles Per Gallon vs Weight",
       x = "Weight (1000 lbs)",
       y = "Miles per Gallon (mpg)",
       color = "Cylinders") +
  theme_minimal()

# Convert ggplot to plotly with customized tooltips
ggplotly(p, tooltip = "text")

Output:

Conclusion

plotly provides a powerful way to make your ggplot2 visualizations interactive by adding features such as tooltips (mouse-over labels). With a few lines of code, you can customize these tooltips to display relevant information in a format that is most useful for your analysis. By using the text aesthetic in ggplot2 and passing the tooltip argument to ggplotly(), you can take full control of what appears when users hover over your data points. Whether you're working with scientific data, business analytics, or exploratory visualizations, customized tooltips can enhance the clarity and usability of your plots.