GGplot cheatsheet

ggplot2 Beginner Cheat Sheet (R)

This quick reference focuses on the essentials you listed and a few logical additions for beginners. All examples use built‑in datasets so you can copy–paste and run immediately.

install.packages("ggplot2")   # once
library(ggplot2)

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Building a plot

ggplot()

Creates a plotting object. Combine with + to add layers.

ggplot(data = mtcars)  # creates an empty canvas using mtcars

aes() (aesthetics)

Maps variables to visual properties such as x, y, color, fill, size, shape.

ggplot(mtcars, aes(x = wt, y = mpg, color = factor(cyl)))

Tip: Put mappings that apply to many layers in the top-level aes(). Put layer-specific mappings inside that layer.

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Geoms (layers that draw things)

geom_point() – scatterplot

ggplot(mtcars, aes(wt, mpg, color = factor(cyl))) +
  geom_point(size = 2)

geom_smooth() – trend/fit lines

Adds model-based smooths (default: LOESS for n < 1000, otherwise GAM). Use se = FALSE to hide the ribbon.

ggplot(mtcars, aes(wt, mpg, color = factor(cyl))) +
  geom_point() +
  geom_smooth(se = TRUE, method = "loess")

Common options: method = "lm" for a straight regression line, formula = y ~ x for custom formulas.

geom_histogram() – distributions of a numeric variable

ggplot(mtcars, aes(x = mpg)) +
  geom_histogram(binwidth = 2, color = "white", fill = "steelblue")

Tip: Control binning with binwidth or bins.

geom_jitter() – jittered points to reduce overplotting

ggplot(iris, aes(Species, Sepal.Length, color = Species)) +
  geom_jitter(width = 0.15 ,height = 0)

Often used instead of (or alongside) geom_point() when x is categorical. Note that you have to 0, otherwise it also jitters in height!

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Faceting (separating plots over a variable)

facet_wrap() – wrap a single faceting variable into multiple rows/cols

ggplot(mtcars, aes(wt, mpg)) +
  geom_point() +
  facet_wrap(~ cyl)

facet_grid() – 2D grid by rows and columns

ggplot(mtcars, aes(wt, mpg)) +
  geom_point() +
  facet_grid(gear ~ cyl)

Tip: Use scales = "free" to allow axes to vary per panel when ranges differ.

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Labels, themes, and polishing

labs() – titles and axis labels

ggplot(mtcars, aes(wt, mpg)) +
  geom_point() +
  labs(
    title = "Fuel efficiency vs. weight",
    subtitle = "mtcars dataset",
    x = "Weight (1000 lbs)", y = "Miles per gallon",
    color = "Cylinders"
  )

theme_bw() – black-and-white theme

ggplot(mtcars, aes(wt, mpg)) +
  geom_point() +
  theme_bw()

Other useful themes: theme_minimal(), theme_classic(). Modify elements with theme().

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Some basic additions to plots

Scales (scale_*) – control colors, fills, axes, legends

ggplot(mtcars, aes(wt, mpg, color = factor(cyl))) +
  geom_point() +
  scale_color_brewer(palette = "Dark2", name = "Cyl") +
  scale_x_continuous(breaks = seq(1.5, 5.5, 0.5))

Why: Scales are how you fine-tune appearance and legends.

Position adjustments – dodge/stack/jitter

ggplot(iris, aes(Species, Sepal.Length, color = Species)) +
  geom_point(position = position_jitter(width = 0.15), alpha = 0.7)

Why: Helps manage overlapping points and grouped geoms (e.g., bars with position = "dodge").

Coordinate systems (coord_*)

ggplot(mtcars, aes(wt, mpg)) +
  geom_point() +
  coord_cartesian(xlim = c(2, 5), ylim = c(10, 35))

Why: Zoom without dropping data (contrast with xlim/ylim).

A minimal template to reuse

library(ggplot2)
p <- ggplot(mtcars, aes(wt, mpg, color = factor(cyl))) +
  geom_point(size = 2, alpha = 0.8) +
  geom_smooth(se = FALSE, method = "lm") +
  facet_wrap(~ gear) +
  labs(title = "MPG vs Weight by Gears", x = "Weight (1000 lbs)", y = "MPG", color = "Cyl") +
  theme_bw()
print(p)

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Quick summary

Function	Purpose
ggplot()	Create a plot object and define data.
aes()	Map variables to aesthetics (x, y, color, fill, size, shape).
geom_point()	Scatterplot points.
geom_smooth()	Trend lines (LOESS/LM) with optional SE ribbon.
geom_histogram()	Histogram for numeric variables.
geom_jitter()	Jittered points for categorical x.
geom_boxplot()	boxplot for numeric variables.
facet_wrap()	Facet by one variable (wrapped layout).
facet_grid()	Facet by row and column variables.
labs()	Titles, subtitles, captions, axis labels, legend titles.
theme_bw()	Black-and-white theme.
scale_*()	Control color/fill palettes, axes, legends.
coord_*()	Coordinate systems and zooming.
ggsave()	Save plots to files.