The stat_summary() function in R “allows for tremendous flexibility in the specification of summary functions”.
The stat_summary() function calculates various summary statistics for data points, such as the mean, median, maximum, minimum, or standard deviation. It takes a summary function as an argument, such as mean, median, max, min, sd, q1, or q3, to name a few.
Syntax
stat_summary(mapping = NULL, data = NULL,
geom = "pointrange", position = "identity")Parameters
- mapping: Aesthetic mapping, usually constructed with aes or aes_string.
- data: A layer-specific dataset – is only needed if you want to override the plot defaults.
- geom: The geometric object to use to display the data.
- position: The position adjustment to use for overlapping points on this layer.
Example 1: R program of stat_summary() function
The stat_summary() function is used in combination with the geom_point() or geom_line() functions to add a summary point or line to a graph. It is useful for quickly visualizing summary statistics across different groups or categories in the data.
library(ggplot2)
ggplot(mpg, aes(x = displ, y = hwy, color = factor(cyl))) +
geom_point() +
stat_summary(fun = mean, geom = "line", aes(group = cyl))Output
Example 2: The stat_summary() function from ggplot()
library(ggplot2)
ggplot(mpg, aes(class, hwy)) +
geom_boxplot() +
stat_summary(fun = "mean", geom = "point", shape = 20, size = 3, color = "red")Output
That’s it.
Krunal Lathiya is a seasoned Computer Science expert with over eight years in the tech industry. He boasts deep knowledge in Data Science and Machine Learning. Versed in Python, JavaScript, PHP, R, and Golang. Skilled in frameworks like Angular and React and platforms such as Node.js. His expertise spans both front-end and back-end development. His proficiency in the Python language stands as a testament to his versatility and commitment to the craft.