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geom_density¤

Computes and draws kernel density estimates, which is a smoothed version of the histogram. This is a useful alternative to the histogram for continuous data that comes from an underlying smooth distribution. The density estimate provides a smooth curve that shows the shape of the distribution without the binning artifacts that can appear in histograms.

Arguments¤

  • plot::GGPlot (optional): a plot object to add this geom to. This is typically used to facilitate creating your ggplot as part of a @chain.
  • data (DataFrame): Data to use for this geom. If not provided, the geom will inherit the data from ggplot.
  • aes(...): the names of the columns in the DataFrame that will be used in the mapping
  • inherit_aes: should the geom inherit aes from the ggplot?
  • ...: options that are not mapped to a column (passed to Makie.Density)

Density vs Histogram¤

Density plots and histograms both display the distribution of a continuous variable, but they have different characteristics:

  • Density plots show a smooth curve that is easier to interpret and compare across groups
  • Histograms show discrete bins that can reveal fine structure in the data
  • Density plots work best when the underlying distribution is smooth
  • Histograms work better for discrete or multimodal data

Required Aesthetics¤

  • x

Optional Aesthetics (see aes)¤

  • fill (maps to fill color under the curve)
  • color / colour (maps to outline color)
  • strokecolor / strokecolour

Optional Arguments¤

  • color / colour: fill color of the density area
  • colormap / palette: colormap for multiple densities
  • strokecolor / strokecolour: outline color
  • strokewidth / stroke: outline width
  • linestyle / linetype: outline style
  • direction: :x (default) for vertical density, :y for horizontal
  • npoints: number of points used to draw the density curve (default: 200)
  • alpha
using TidierPlots
using DataFrames

penguins = penguins_data();

Create a basic density plot showing the distribution of bill length:

ggplot(penguins, @aes(x = bill_length_mm)) +
    geom_density()

Customize the appearance with fill color and stroke:

ggplot(penguins, @aes(x = bill_length_mm)) +
    geom_density(color = :steelblue, strokecolor = :black, stroke = 2)

Use the fill aesthetic to compare distributions across groups. Each group gets its own density curve:

ggplot(penguins, @aes(x = bill_length_mm, fill = species)) +
    geom_density(alpha = 0.5)

Add stroke color to distinguish overlapping densities more clearly:

ggplot(penguins, @aes(x = bill_length_mm, fill = species)) +
    geom_density(alpha = 0.4, strokecolor = :black, stroke = 1)

Use strokecolor aesthetic to color just the outline:

ggplot(penguins, @aes(x = bill_length_mm, strokecolor = species)) +
    geom_density(stroke = 2)

Combine density with other geoms for richer visualizations:

ggplot(penguins, @aes(x = bill_length_mm)) +
    geom_histogram(normalization = :pdf, alpha = 0.3) +
    geom_density(strokecolor = :red, stroke = 2)

Compare distributions across two categorical variables:

ggplot(penguins, @aes(x = bill_length_mm, fill = sex)) +
    geom_density(alpha = 0.5) +
    facet_wrap(:species)

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