Ggplot2

TL;DR

• Creates customized, high-quality graphics in R for data exploration and communication.
• Builds plots by composing distinct components (aesthetics, geoms) and layering visual elements like points, lines, and bars.
• Supports easy addition of statistical transformations (e.g., adding a linear trend line with geom_smooth(method=“lm”)).

Definition

ggplot2 is a data visualization package for the R programming language. It is based on the grammar of graphics, a framework that separates the construction of a plot into distinct components.

Explanation

ggplot2 enables users to create customized, high-quality graphics by mapping data to aesthetic attributes and adding graphical layers. Typical elements include geoms such as points, lines, and bars; these elements can be layered to form complex graphics. The package also provides functions to apply statistical transformations to the data and visualize those results (for example, fitting and displaying a regression line).

Examples

Scatterplot of temperature vs. ozone

ggplot(data=city_data, aes(x=temperature, y=ozone)) + geom_point()

This creates a scatterplot using the city_data dataset where the x-axis is temperature and the y-axis is ozone; geom_point() adds the individual observations as points.

Scatterplot with linear trend line

ggplot(data=city_data, aes(x=temperature, y=ozone)) + geom_point() + geom_smooth(method="lm")

This adds a linear regression line to the scatterplot; the argument method="lm" specifies that a linear model should be fit to the data.

Use cases

• Data exploration and communication through visual summaries.
• Visualizing relationships in data, such as scatterplots with trend lines.

Related terms

• Grammar of graphics
• R (programming language)
• geom_point
• geom_smooth
• method=“lm”