Plotting with Gadfly.jl

Imports


In [1]:
using Gadfly
using DataFrames, RDatasets


WARNING: Method definition describe(AbstractArray) in module StatsBase at /Users/mrestrep/.julia/v0.5/StatsBase/src/scalarstats.jl:573 overwritten in module DataFrames at /Users/mrestrep/.julia/v0.5/DataFrames/src/abstractdataframe/abstractdataframe.jl:407.

Basics

Simple line scatter

  • Pass data keyword arguments inputs

In [2]:
function linescatter()
    x = [1, 2, 3, 4]
    y = [10, 15, 13, 17]
    plot(x=x,y=y, Geom.line)
end
linescatter()


Out[2]:
x -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7 8 9 -4.0 -3.8 -3.6 -3.4 -3.2 -3.0 -2.8 -2.6 -2.4 -2.2 -2.0 -1.8 -1.6 -1.4 -1.2 -1.0 -0.8 -0.6 -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 2.2 2.4 2.6 2.8 3.0 3.2 3.4 3.6 3.8 4.0 4.2 4.4 4.6 4.8 5.0 5.2 5.4 5.6 5.8 6.0 6.2 6.4 6.6 6.8 7.0 7.2 7.4 7.6 7.8 8.0 -5 0 5 10 -4.0 -3.5 -3.0 -2.5 -2.0 -1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5 6.0 6.5 7.0 7.5 8.0 0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5 6.0 6.5 7.0 7.5 8.0 8.5 9.0 9.5 10.0 10.5 11.0 11.5 12.0 12.5 13.0 13.5 14.0 14.5 15.0 15.5 16.0 16.5 17.0 17.5 18.0 18.5 19.0 19.5 20.0 20.5 21.0 21.5 22.0 22.5 23.0 23.5 24.0 24.5 25.0 25.5 26.0 0 10 20 30 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 y

Customize and add multiple traces to one plot

  • Each trace is a layer with its own aesthetics

Challenge: How to plot dashes?


In [3]:
function multiple_scatter_traces()
    x=1:4
    l1 = layer(x = x, y = [10, 15, 13, 17],  Geom.point)
    l2 = layer(x = x, y = [16, 5, 11, 9], Geom.line)
    l3 = layer(x = x, y = [12, 9, 15, 12], Geom.point, Geom.line)
    l4 = layer(x = x, y = [5, 10, 8, 12], Geom.line)
    plot(l1, l2, l3, l4)
end
multiple_scatter_traces()


Out[3]:
x -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7 8 9 -4.0 -3.8 -3.6 -3.4 -3.2 -3.0 -2.8 -2.6 -2.4 -2.2 -2.0 -1.8 -1.6 -1.4 -1.2 -1.0 -0.8 -0.6 -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 2.2 2.4 2.6 2.8 3.0 3.2 3.4 3.6 3.8 4.0 4.2 4.4 4.6 4.8 5.0 5.2 5.4 5.6 5.8 6.0 6.2 6.4 6.6 6.8 7.0 7.2 7.4 7.6 7.8 8.0 -5 0 5 10 -4.0 -3.5 -3.0 -2.5 -2.0 -1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5 6.0 6.5 7.0 7.5 8.0 -25 -20 -15 -10 -5 0 5 10 15 20 25 30 35 40 45 -20 -19 -18 -17 -16 -15 -14 -13 -12 -11 -10 -9 -8 -7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 -20 0 20 40 -20 -18 -16 -14 -12 -10 -8 -6 -4 -2 0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 y

Data labels and Figure Layout

  • Add the array of labels as an attribute to each trace
  • Layout modifies the "Figure Pane Attributes"

In [4]:
function data_labels()
    x = 1:5
    y1 = [1, 6, 3, 6, 1]
    y2 = [4, 1, 7, 1, 4]
    y1_labels = ["A-1", "A-2", "A-3", "A-4", "A-5"]
    y2_labels = ["B-a", "B-b", "B-c", "B-d", "B-e"]

    l1 = layer(x = x, y = y1, label=y1_labels, Geom.label, Geom.point)
    l2 = layer(x = x, y = y2, label=y2_labels, Geom.label, Geom.point) 
    plot(l1,l2)
end
data_labels()


Out[4]:
x -6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7 8 9 10 11 -5.0 -4.8 -4.6 -4.4 -4.2 -4.0 -3.8 -3.6 -3.4 -3.2 -3.0 -2.8 -2.6 -2.4 -2.2 -2.0 -1.8 -1.6 -1.4 -1.2 -1.0 -0.8 -0.6 -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 2.2 2.4 2.6 2.8 3.0 3.2 3.4 3.6 3.8 4.0 4.2 4.4 4.6 4.8 5.0 5.2 5.4 5.6 5.8 6.0 6.2 6.4 6.6 6.8 7.0 7.2 7.4 7.6 7.8 8.0 8.2 8.4 8.6 8.8 9.0 9.2 9.4 9.6 9.8 10.0 -5 0 5 10 -5.0 -4.5 -4.0 -3.5 -3.0 -2.5 -2.0 -1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5 6.0 6.5 7.0 7.5 8.0 8.5 9.0 9.5 10.0 B-a B-b B-c B-d B-e A-1 A-2 A-3 A-4 A-5 -10 -8 -6 -4 -2 0 2 4 6 8 10 12 14 16 18 -8.0 -7.5 -7.0 -6.5 -6.0 -5.5 -5.0 -4.5 -4.0 -3.5 -3.0 -2.5 -2.0 -1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5 6.0 6.5 7.0 7.5 8.0 8.5 9.0 9.5 10.0 10.5 11.0 11.5 12.0 12.5 13.0 13.5 14.0 14.5 15.0 15.5 16.0 -10 0 10 20 -8.0 -7.5 -7.0 -6.5 -6.0 -5.5 -5.0 -4.5 -4.0 -3.5 -3.0 -2.5 -2.0 -1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5 6.0 6.5 7.0 7.5 8.0 8.5 9.0 9.5 10.0 10.5 11.0 11.5 12.0 12.5 13.0 13.5 14.0 14.5 15.0 15.5 16.0 y

Area


In [5]:
function area1()
end
area1()

Other visual interpretations of Matrix Data and Subplots


In [6]:
function matrix_subplots()

end

matrix_subplots()

Advanced Layouts


In [7]:
function advanced_layouts()

end
advanced_layouts()

Stats Plots


In [8]:
function grouped_bar_example()

end

grouped_bar_example()

In [9]:
function stacked_bar_example()
    
end
stacked_bar_example()

In [10]:
function two_hists()

end

two_hists()

Box (Whisker) Plots


In [11]:
function box_plot()
   
end
box_plot()

Using DataFrames


In [12]:
function data_frame_scatter()
    iris = dataset("datasets", "iris");
    display(head(iris))
end

data_frame_scatter()


SepalLengthSepalWidthPetalLengthPetalWidthSpecies
15.13.51.40.2setosa
24.93.01.40.2setosa
34.73.21.30.2setosa
44.63.11.50.2setosa
55.03.61.40.2setosa
65.43.91.70.4setosa