Gadfly is a system for plotting and visualization based largely on Hadley Wickhams's ggplot2 for R, and Leland Wilkinson's book The Grammar of Graphics.

Getting Started

From the Julia REPL a reasonably up to date version can be installed with


This will likely result in half a dozen or so other packages also being installed.

Gadfly is then loaded with.

using Gadfly

Optional: cairo, pango, and fontconfig

Gadfly works best with the C libraries cairo, pango, and fontconfig installed. The PNG, PS, and PDF backends require cairo, but without it the SVG and Javascript/D3 backends are still available.

Complex layouts involving text are also somewhat more accurate when pango and fontconfig are available.

Julia's Cairo bindings can be installed with


Plot invocations

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.

{.julia hide="true") srand(12345)

# E.g.
plot(x=rand(10), y=rand(10))

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)

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"))

To generate an image file from a plot, use the draw function. Gadfly supports a number of drawing backends. Each is used similarly.

# define a plot
myplot = plot(..)

# draw on every available backend
draw(SVG("myplot.svg", 4inch, 3inch), myplot)
draw(PNG("myplot.png", 4inch, 3inch), myplot)
draw(PDF("myplot.pdf", 4inch, 3inch), myplot)
draw(PS("", 4inch, 3inch), myplot)
draw(D3("myplot.js", 4inch, 3inch), myplot)

If used from IJulia, the output of plot will be shown automatically.

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 usinge the data function.

using RDatasets
# E.g.
plot(dataset("datasets", "iris"), x="SepalLength", y="SepalWidth", Geom.point)
# E.g.
plot(dataset("car", "SLID"), x="Wages", color="Language", Geom.histogram)

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...)

@plot(expr, a, b)

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

# E.g.
plot([sin, cos], 0, 25)
# E.g.
@plot(cos(x)/x, 5, 25)


Gadfly can draw multiple layers to the same plot:

plot(layer(x=rand(10), y=rand(10), Geom.point),
     layer(x=rand(10), y=rand(10), Geom.line))

Or if your data is in a DataFrame:

plot(my_data, layer(x="some_column1", y="some_column2", Geom.point),
              layer(x="some_column3", y="some_column4", Geom.line))

You can also pass different data frames to each layers:

layer(another_dataframe, x="col1", y="col2", Geom.point)

Drawing to backends

Gadfly plots can be rendered to number of formats. Without cairo, or any non-julia libraries, it can produce SVG and d3-powered javascript. Installing cairo gives you access to the PNG, PDF, and PS backends. Rendering to a backend works the same for any of these.

p = plot(x=[1,2,3], y=[4,5,6])
draw(PNG("myplot.png", 12cm, 6cm), p)

Using the d3 backend

The D3 backend writes javascript. Making use of its output is slightly more involved than with the image backends.

Rendering to Javascript is easy enough:

draw(D3("plot.js", 6inch, 6inch), p)

Before the output can be included, you must include the d3 and gadfly javascript libraries. The necessary include for Gadfly is "gadfly.js" which lives in the src directory (which you can find by running joinpath(Pkg.dir("Gadfly"), "src", "gadfly.js") in julia).

D3 can be downloaded from here.

Now the output can be included in an HTML page like:

<script src="d3.min.js"></script>
<script src="gadfly.js"></script>

<!-- Placed whereever you want the graphic to be rendered. -->
<div id="my_chart"></div>
<script src="mammals.js"></script>

A div element must be placed, and the draw function defined in mammals.js must be passed the id of this element, so it knows where in the document to place the plot.


The IJulia project adds Julia support to IPython. This includes a browser based notebook that can inline graphics and plots. Gadfly works out of the box with IJulia, with or without drawing explicity to a backend.

Without a specific call to draw (i.e. just calling plot), the D3 backend is used with a default plot size. The default plot size can be changed with set_default_plot_size.

# E.g.
set_default_plot_size(12cm, 8cm)

Reporting Bugs

This is a new and fairly complex piece of software. Filing an issue to report a bug, counterintuitive behavior, or even to request a feature is extremely valuable in helping me prioritize what to work on, so don't hestitate.