Most interaction with Gadfly is through the plot function. Plots are described by binding data to aesthetics, and specifying a number of plot elements including Scales, Coordinates, Guides, and Geometries. Aesthetics are a set of special named variables that are mapped to plot geometry. How this mapping occurs is defined by the plot elements.

This "grammar of graphics" approach tries to avoid arcane incantations and special cases, instead approaching the problem as if one were drawing a wiring diagram: data is connected to aesthetics, which act as input leads, and elements, each self-contained with well-defined inputs and outputs, are connected and combined to produce the desired result.

Plotting arrays

If no plot elements are defined, point geometry is added by default. The point geometry takes as input the x and y aesthetics. So all that's needed to draw a scatterplot is to bind x and y.

# E.g.
plot(x=rand(10), y=rand(10))
x 0.00 0.25 0.50 0.75 1.00 0.0 0.5 1.0 y

Multiple elements can use the same aesthetics to produce different output. Here the point and line geometries act on the same data and their results are layered.

# E.g.
plot(x=rand(10), y=rand(10), Geom.point, Geom.line)
x 0.0 0.5 1.0 0.0 0.2 0.4 0.6 0.8 1.0 y

More complex plots can be produced by combining elements.

# E.g.
plot(x=1:10, y=2.^rand(10),
     Scale.y_sqrt, Geom.point, Geom.smooth,
     Guide.xlabel("Stimulus"), Guide.ylabel("Response"), Guide.title("Dog Training"))
Stimulus 0.0 2.5 5.0 7.5 10.0 1.02 1.12 1.22 1.32 1.42 Response Dog Training

To generate an image file from a plot, use the draw function. Gadfly supports a number of drawing Backends.

Plotting data frames

The DataFrames package provides a powerful means of representing and manipulating tabular data. They can be used directly in Gadfly to make more complex plots simpler and easier to generate.

In this form of plot, a data frame is passed to as the first argument, and columns of the data frame are bound to aesthetics by name or index.

# Signature for the plot applied to a data frames.
plot(data::AbstractDataFrame, elements::Element...; mapping...)

The RDatasets package collects example data sets from R packages. We'll use that here to generate some example plots on realistic data sets. An example data set is loaded into a data frame using the dataset function.

using RDatasets
# E.g.
plot(dataset("datasets", "iris"), x="SepalLength", y="SepalWidth", Geom.point)
SepalLength 4 5 6 7 8 2.0 2.5 3.0 3.5 4.0 4.5 SepalWidth
# E.g.
plot(dataset("car", "SLID"), x="Wages", color="Language", Geom.histogram)
Wages 0 10 20 30 40 50 English Other French Language 0 50 100 150 200

Along with less typing, using data frames to generate plots allows the axis and guide labels to be set automatically.

Functions and Expressions

Along with the standard plot function, Gadfly has some special forms to make plotting functions and expressions more convenient.

plot(f::Function, a, b, elements::Element...)

plot(fs::Array, a, b, elements::Element...)

Some special forms of plot exist for quickly generating 2d plots of functions.

# E.g.
plot([sin, cos], 0, 25)
x 0 5 10 15 20 25 f1 f2 Color -1.0 -0.5 0.0 0.5 1.0 f(x)