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How to Display Average Line for Y Variable Using ggplot2 in R

Last Updated : 11 Sep, 2024
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In this article, we will explore how to display the average line for a Y variable using ggplot2. Adding an average line is useful in understanding the central tendency of data and making comparisons across different groups.

Introduction to ggplot2 in R

The ggplot2 package is one of the most widely used packages for data visualization in R. It provides a powerful and flexible framework for creating a variety of plots. One of the most common tasks in data analysis is to visualize the relationship between variables and highlight key statistics, such as the average (mean) of a variable using R Programming Language.

Step 1: Setting Up Your R Environment

Before we begin, make sure to install and load the ggplot2 package if it is not already installed in your R environment.

R
# Install ggplot2 if not already installed
install.packages("ggplot2")

# Load the ggplot2 package
library(ggplot2)

Step 2: Understanding the Dataset

For demonstration purposes, we will use the built-in mtcars dataset, which contains data about various car models, including variables like mpg (miles per gallon), hp (horsepower), wt (weight), and others.

R
# Load the mtcars dataset
data("mtcars")

# Display the first few rows of the dataset
head(mtcars)

Output:

                   mpg cyl disp  hp drat    wt  qsec vs am gear carb
Mazda RX4 21.0 6 160 110 3.90 2.620 16.46 0 1 4 4
Mazda RX4 Wag 21.0 6 160 110 3.90 2.875 17.02 0 1 4 4
Datsun 710 22.8 4 108 93 3.85 2.320 18.61 1 1 4 1
Hornet 4 Drive 21.4 6 258 110 3.08 3.215 19.44 1 0 3 1
Hornet Sportabout 18.7 8 360 175 3.15 3.440 17.02 0 0 3 2
Valiant 18.1 6 225 105 2.76 3.460 20.22 1 0 3 1

Step 3: Plotting the Data with ggplot2

Let’s create a basic scatter plot of mpg (miles per gallon) versus hp (horsepower). This plot will show the relationship between fuel efficiency and engine power.

R
# Basic scatter plot of mpg vs hp
ggplot(mtcars, aes(x = hp, y = mpg)) +
  geom_point(color = "blue", size = 3) +
  labs(title = "Scatter Plot of MPG vs Horsepower",
       x = "Horsepower (hp)",
       y = "Miles per Gallon (mpg)") +
  theme_minimal()

Output:

gh
Plotting the Data with ggplot2

This will generate a scatter plot with hp on the x-axis and mpg on the y-axis. The next step is to add an average line for the y-variable (mpg).

Step 4: Adding an Average Line to the Plot

To add an average (mean) line for the y-variable, we can use the geom_hline() function. This function draws a horizontal line on the plot, which in this case will represent the mean value of mpg.

R
# Add a horizontal line representing the average (mean) mpg
mean_mpg <- mean(mtcars$mpg)

ggplot(mtcars, aes(x = hp, y = mpg)) +
  geom_point(color = "blue", size = 3) +
  geom_hline(yintercept = mean_mpg, color = "red", linetype = "dashed", size = 1) +
  labs(title = "Scatter Plot of MPG vs Horsepower with Average MPG Line",
       x = "Horsepower (hp)",
       y = "Miles per Gallon (mpg)",
       subtitle = paste("Average MPG =", round(mean_mpg, 2))) +
  theme_minimal()

Output:

gh
Adding an Average Line to the Plot
  • geom_hline(yintercept = mean_mpg, ...) adds a horizontal line at the y-value equal to the mean of mpg.
  • The color, linetype, and size parameters customize the appearance of the average line. We set the line color to red, make it dashed, and slightly thicker.
  • The subtitle in labs() adds a text label showing the calculated mean mpg on the plot.

Conclusion

The Central Limit Theorem and other statistical methods provide powerful insights into the behavior of data, and ggplot2 in R allows us to visualize these statistics clearly. In this article, we demonstrated how to add an average line to a scatter plot using ggplot2. This can be an essential tool for understanding central tendencies in data, making it easier to identify deviations and compare different groups.


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