Input Data

Part of the power of Plots lies is in the many combinations of allowed input data. You shouldn't spend your time transforming and massaging your data into a specific format. Let Plots do that for you.

There are a few rules to remember, and you'll be a power user in no time.

Inputs are arguments, not keywords

While plot(x = 1:10, y = rand(10)) will work as expected, it is not the preferred method. In fact, this method will simply call plot(1:10, rand(10)). Instead, use plot(rand(10)). In this case, a single input will be mapped to the :y keyword, and a missing value for :x will impute a unit range 1:10.

The reason lies in the flexibility of Julia's multiple dispatch, where every combination of input types can have unique behavior, when desired.

Columns are series

In most cases, passing a (n x m) matrix of values (numbers, etc) will create m series, each with n data points. This follows a consistent rule... vectors apply to a series, matrices apply to many series. This rule carries into keyword arguments. plot(rand(10,4), color = [:red, :blue]) will create 4 series, each assigned the color vector [:red,:blue]. However, plot(rand(10,4), color = [:red :blue]) will create 4 series, with series 1 and 3 taking the color :red and series 2 and 4 taking the color :blue. The difference is that in the first example, it is a length-2 column vector, and in the second example it is a (1 x 2) row vector (a Matrix).

DataFrames support

If you have DataFrames installed, some convenience functionality is turned on. (Those coming from R will appreciate it.) The first argument should be the DataFrame, and subsequent Symbol arguments will be mapped to the corresponding column in that DataFrame. Example:

using DataFrames, Plots; gadfly()
using RDatasets; iris = dataset("datasets", "iris")

scatter(iris, :SepalLength, :SepalWidth, group=:Species,
        title = "My awesome plot", xlabel = "Length", ylabel = "Width",
        m=(0.5, [:+ :h :star7], 12), bg=RGB(.2,.2,.2))

Functions

Functions can typically be used in place of input data, and they will be mapped as needed. 2D and 3D parametric plots can also be created, and ranges can be given as vectors or min/max. For example, here are alternative methods to create the same plot:

using Plots
tmin = 0
tmax = 4π
tvec = linspace(tmin, tmax, 100)

plot(sin(tvec), cos(tvec))
plot(sin, cos, tvec)
plot(sin, cos, tmin, tmax)

Vectors of functions are allowed as well (one series per function).

Shapes

Check out this tutorial to save Gotham: