Here’s a cheat sheet for ggplot2, a popular data visualization package in R:
Basic ggplot Structure
library(ggplot2)
ggplot(data = dataset, aes(x = x_variable, y = y_variable)) +
geom_point() # or other geometry functions like geom_line(), geom_bar(), etc.
Customizing Aesthetics
Color by a Variable:
ggplot(data = dataset, aes(x = x_variable, y = y_variable, color = categorical_variable)) +
geom_point()
Size by a Variable:
ggplot(data = dataset, aes(x = x_variable, y = y_variable, size = numeric_variable)) +
geom_point()
Faceting
Facet by a Variable:
ggplot(data = dataset, aes(x = x_variable, y = y_variable)) +
geom_point() +
facet_wrap(~ categorical_variable)
Themes and Labels
Change Theme:
ggplot(data = dataset, aes(x = x_variable, y = y_variable)) +
geom_point() +
theme_minimal()
Customize Axis Labels and Title:
ggplot(data = dataset, aes(x = x_variable, y = y_variable)) +
geom_point() +
labs(x = "X Axis Label", y = "Y Axis Label", title = "Plot Title")
Statistical Transformations
Add Smooth Line:
ggplot(data = dataset, aes(x = x_variable, y = y_variable)) +
geom_point() +
geom_smooth(method = "lm")
Histogram:
ggplot(data = dataset, aes(x = numeric_variable)) +
geom_histogram(binwidth = 5, fill = "blue", color = "black", alpha = 0.7)
Multiple Layers
ggplot(data = dataset, aes(x = x_variable, y = y_variable)) +
geom_point(color = "blue") +
geom_smooth(method = "lm", color = "red", linetype = "dashed", se = FALSE) +
theme_minimal()
Save Plot
Save as Image:
ggsave("plot.png", plot = last_plot(), width = 6, height = 4)
This cheat sheet provides a starting point for using ggplot2. For more advanced customization and details, refer to the official ggplot2 documentation.