Ggplot2

ggplot2 Reference

ggplot2 is an R package for producing visualizations using a grammar of graphics. You compose plots from data, mappings, layers, scales, facets, coordinates, and themes.

Core Components

Data and Mapping

ggplot(data = mpg, mapping = aes(x = cty, y = hwy))

• Data: Tidy data frame (rows = observations, columns = variables)
• Mapping: aes() links data columns to visual properties (x, y, colour, size, etc.)

Layers

Layers display data using geometry, statistical transformation, and position adjustment:

ggplot(mpg, aes(cty, hwy)) +
  geom_point() +
  geom_smooth(formula = y ~ x, method = "lm")

Scales

Control how data maps to visual properties and create legends/axes:

ggplot(mpg, aes(cty, hwy, colour = class)) +
  geom_point() +
  scale_colour_viridis_d()

Facets

Split data into panels by variables:

ggplot(mpg, aes(cty, hwy)) +
  geom_point() +
  facet_grid(year ~ drv)

Coordinates

Interpret position aesthetics (Cartesian, polar, map projections):

ggplot(mpg, aes(cty, hwy)) +
  geom_point() +
  coord_fixed()

Theme

Control non-data visual elements:

ggplot(mpg, aes(cty, hwy, colour = class)) +
  geom_point() +
  theme_minimal() +
  theme(legend.position = "top")

---

ggplot2 4.0 Features

ggplot2 4.0.0 (September 2025) introduced S7 classes and major new features.

S7 Migration

Access properties with @ instead of $:

# ggplot2 4.0+
ggplot()@data

# Deprecated (still works temporarily)
ggplot()$data

Stricter type validation:

element_text(hjust = "foo")
#> Error: @hjust must be , , or , not 

Theme-Based Layer Defaults

Ink, Paper, and Accent

Built-in themes accept ink (foreground), paper (background), accent (highlight):

ggplot(mpg, aes(displ, hwy)) +
  geom_point() +
  geom_smooth(method = "lm", formula = y ~ x) +
  theme_gray(paper = "cornsilk", ink = "navy", accent = "tomato")

elementgeom() and fromtheme()

Set layer defaults via theme(geom):

ggplot(mpg, aes(class, displ)) +
  geom_boxplot(aes(colour = from_theme(accent))) +
  theme(geom = element_geom(
    accent = "tomato",
    paper = "cornsilk",
    bordertype = "dashed",
    borderwidth = 0.2,
    linewidth = 2,
    linetype = "solid"
  ))

Theme Palettes

Set default palettes in themes:

theme(
  palette.colour.continuous = c("chartreuse", "forestgreen"),
  palette.shape.discrete = c("triangle", "triangle open")
)

Theme Shortcuts

New theme_sub_*() functions reduce verbosity:

| Shortcut | Prefix replaced | |----------|-----------------| | theme_sub_axis() | axis.* | | theme_sub_axis_x() | axis.*.x | | theme_sub_axis_bottom() | axis.*.x.bottom | | theme_sub_legend() | legend.* | | theme_sub_panel() | panel.* | | theme_sub_plot() | plot.* | | theme_sub_strip() | strip.* |

# Concise
theme_sub_axis_x(
  ticks = element_line(colour = "red"),
  ticks.length = unit(5, "mm")
) +
theme_sub_panel(
  widths = unit(5, "cm"),
  spacing.x = unit(5, "mm")
)

Margin Helpers

margin_auto(1)           # all sides = 1
margin_auto(1, 2)        # t/b=1, l/r=2
margin_auto(1, 2, 3)     # t=1, l/r=2, b=3
margin_part(r = 20)      # partial (NA inherits)

Panel Sizes

theme_sub_panel(widths = unit(c(2, 3, 4), "cm"))  # per-panel
theme_sub_panel(widths = unit(9, "cm"))           # total area

Labels

Label Attributes

Variables with "label" attribute auto-populate axis labels:

attr(df$bill_dep, "label") `, `"fixed_cols"`, `"fixed_rows"`

## Styling

### Boxplot Parts

```r
geom_boxplot(
  whisker.linetype = "dashed",
  box.colour = "black",
  median.linewidth = 2,
  staplewidth = 0.5,
  staple.colour = "grey50"
)

Violin Quantiles

geom_violin(
  quantiles = c(0.1, 0.9),
  quantile.linetype = 1,
  quantile.colour = "red"
)

Labels

geom_label(
  aes(linetype = factor(vs), linewidth = factor(am)),
  text.colour = "black",
  border.colour = "blue"
)

Varying Fill

geom_area(aes(fill = continuous_var))  # gradient (R 4.1+)

New Stats

stat_manual()

make_centroids <- function(df) {
  transform(df, xend = mean(x), yend = mean(y))
}
stat_manual(geom = "segment", fun = make_centroids)

stat_connect()

geom_line(stat = "connect")           # stairstep
geom_ribbon(stat = "connect", alpha = 0.4)

# Custom connection shape
smooth <- cbind(x = seq(0, 1, length.out = 20)[-1],
                y = scales::rescale(plogis(x, 0.5, 0.1)))
stat_connect(connection = smooth)

Coord Reversal

coord_cartesian(reverse = "x")   # "y", "xy", "none"
coord_sf(reverse = "y")
coord_radial(reverse = "theta")  # "r", "thetar", "none"

Deprecations

| Old | New | |-----|-----| | fatten | median.linewidth / middle.linewidth | | draw_quantiles | quantiles | | geom_errorbarh() | geom_errorbar(orientation = "y") | | coord_trans() | coord_transform() | | borders() | annotation_borders() | | facet_wrap(as.table) | facet_wrap(dir) | | theme_get/set/update/replace() | get/set/update/replace_theme() | | last_plot() | get_last_plot() | | layer_data/grob/scales() | get_layer_data/grob(), get_panel_scales() |

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: jsperger
• Source: jsperger/llm-r-skills
• License: MIT

Install and usage instructions live in the source repository linked above.