Bar and column charts with pattern overlays

These are drop-in replacements for ggplot2::geom_col() and ggplot2::geom_bar() that add support for a pattern aesthetic. Map pattern to a discrete variable using scale_pattern_manual() or scale_pattern_discrete().

Usage

geom_col_pattern(
  mapping = NULL,
  data = NULL,
  position = "stack",
  ...,
  width = NULL,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)

geom_bar_pattern(
  mapping = NULL,
  data = NULL,
  position = "stack",
  ...,
  width = NULL,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)

Arguments

mapping

Aesthetic mappings created by ggplot2::aes().

data

Data frame.

position

Position adjustment. Default "stack".

...

Other arguments passed to the layer.

width

Bar width, as a proportion of the bin width.

na.rm

If FALSE (default), missing values are removed with a warning.

show.legend

Logical. Should this layer be included in the legend?

inherit.aes

If FALSE, overrides the default aesthetics.

Value

A ggplot2 layer.

Pattern aesthetics

In addition to all aesthetics accepted by ggplot2::geom_col(), these geoms accept:

pattern

Character name of the pattern. One of "none", "hatch", "crosshatch", "horizontal", "vertical", "dots", "weave", or a custom pattern registered with register_pattern(). Each base pattern (except "none") also has _dense and _sparse variants (e.g. "hatch_dense", "dots_sparse") for pre-set tighter or looser spacing.

pattern_colour

Colour of pattern lines/dots. Default "black".

pattern_linewidth

Line width for line-based patterns. Default 1.

pattern_spacing

Spacing between pattern elements in millimetres. Default 5. Smaller values produce denser patterns; larger values produce sparser patterns. Named density variants (e.g. "hatch_dense") bake in a pre-set spacing multiplier but still respect explicit pattern_spacing values.

pattern_angle

Angle in degrees for hatch patterns. Default 45.

pattern_size

Dot radius in millimetres for the "dots" pattern. Default 0.5.

Examples

library(ggplot2)

# geom_bar_pattern uses stat="count" automatically
ggplot(mpg, aes(class, fill = class, pattern = class)) +
  geom_bar_pattern() +
  scale_pattern_discrete() +
  theme_minimal()


# geom_col_pattern needs x and y (pre-summarised data)
df <- data.frame(
  group = c("A", "B", "C"),
  value = c(3, 5, 4)
)
ggplot(df, aes(group, value, fill = group, pattern = group)) +
  geom_col_pattern() +
  scale_pattern_manual(values = c(A = "hatch", B = "dots", C = "crosshatch")) +
  scale_fill_brewer(palette = "Pastel1")