ggplot2（ggplot2 命令行）

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 <NULL>, <integer>, or <double>, not <character>

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")

element_geom() and from_theme()

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:

# 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") <- "Bill depth (mm)"
ggplot(df, aes(bill_dep, bill_len)) + geom_point()

Dictionary Labels

dict <- c(species = "Species", bill_dep = "Bill depth (mm)")
ggplot(penguins, aes(bill_dep, bill_len, colour = species)) +
  geom_point() +
  labs(dictionary = dict)

Function Labels

scale_colour_discrete(name = toupper)
guides(x = guide_axis(title = tools::toTitleCase))
labs(y = \(x) paste0(x, " variable"))

Label hierarchy (lowest to highest): aes() < labs(dictionary) < column attribute < labs() < scale_*(name) < guide_*(title)

Named Breaks

scale_colour_discrete(breaks = c(
  "Pygoscelis adeliae" = "Adelie",
  "Pygoscelis papua" = "Gentoo"
))

Discrete Scale Improvements

# Palette for spacing
scale_x_discrete(palette = scales::pal_manual(c(1:3, 5:7)))

# Consistent limits across facets
scale_x_discrete(continuous.limits = c(1, 5))

# Minor breaks
scale_x_discrete(
  minor_breaks = scales::breaks_width(1, offset = 0.5),
  guide = guide_axis(minor.ticks = TRUE)
)

# Secondary axis
scale_x_discrete(sec.axis = dup_axis(
  name = "Counts",
  breaks = seq_len(7),
  labels = paste0("n = ", table(mpg$class))
))

Position Aesthetics

Nudge Aesthetics

geom_text(aes(nudge_x = sign(value) * 3, label = value))

Dodge Order

ggplot(data, aes(x, y, fill = group)) +
  geom_boxplot(position = position_dodge(preserve = "single")) +
  aes(order = group)

Facets

Wrapping Directions

8 direction options for facet_wrap(dir):

Free Space

facet_wrap(~ island, scales = "free_x", space = "free_x")

Layer Layout

geom_point(colour = "grey", layout = "fixed_rows")  # repeat in rows
geom_point(layout = NULL)                            # use facet vars
annotate("text", label = "X", layout = 6)            # specific panel

Options: NULL, "fixed", <integer>, "fixed_cols", "fixed_rows"

Styling

Boxplot Parts

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