Basic Plots in R

R provides built-in functions to create various types of plots for data visualization.

Creating a Scatter Plot

Use the plot() function to create scatter plots in R.

plot(mtcars$mpg, mtcars$hp, main='MPG vs Horsepower', xlab='Miles per Gallon', ylab='Horsepower', col='blue')

Creating a Line Plot

Use plot() with type='l' to create a line chart.

x <- 1:10
y <- x^2
plot(x, y, type='l', col='red', main='Line Plot of x^2', xlab='X', ylab='Y')

Creating a Bar Chart

Use barplot() to create bar charts for categorical data.

counts <- table(mtcars$cyl)
barplot(counts, col='green', main='Car Cylinder Count', xlab='Cylinders', ylab='Frequency')

Creating a Histogram

Use hist() to visualize the distribution of a numerical variable.

hist(mtcars$mpg, col='purple', main='Histogram of MPG', xlab='Miles per Gallon')

Creating a Boxplot

Use boxplot() to detect outliers and summarize data distribution.

boxplot(mtcars$mpg, main='Boxplot of MPG', col='orange')

Adding Customizations

You can modify plots by changing colors, labels, and titles.

plot(mtcars$mpg, mtcars$hp, main='MPG vs Horsepower', xlab='MPG', ylab='HP', col='blue', pch=16)

Saving a Plot

Use ggsave() or png() to save plots to a file.

png('plot.png')
plot(mtcars$mpg, mtcars$hp)
dev.off()

Summary

In this lesson, you learned:

• How to create basic plots in R.
• How to customize plots with labels, colors, and titles.
• How to save plots as image files.