Gadfly is an implementation of a "grammar of graphics" style statistical graphics system for Julia. This tutorial will outline general usage patterns and will give you a feel for the overall system.
To begin, we need some data. Gadfly can work with data supplied as either a DataFrame or as plain AbstractArrays. In this tutorial, we'll pick and choose some examples from the RDatasets package.
Let us use Fisher's iris dataset as a starting point.
using Gadfly, RDatasets
iris = dataset("datasets", "iris")
Row SepalLength SepalWidth PetalLength PetalWidth Species 1 5.1 3.5 1.4 0.2 setosa 2 4.9 3.0 1.4 0.2 setosa 3 4.7 3.2 1.3 0.2 setosa 4 4.6 3.1 1.5 0.2 setosa 5 5.0 3.6 1.4 0.2 setosa 6 5.4 3.9 1.7 0.4 setosa ... ... ... ... ... ...
When used with a DataFrame, the plot
function in Gadfly is of the form:
plot(data::AbstractDataFrame, elements::Element...; mapping...)
The first argument is the data to be plotted and the keyword arguments at the end map "aesthetics" to columns in the data frame. All input arguments between data
and mapping
are some number of "elements", which are the nouns and verbs, so to speak, that form the grammar.
Let's get to it.
p = plot(iris, x=:SepalLength, y=:SepalWidth, Geom.point);
First note that we've taken advantage of the flexibility of Julia's handling of function signatures and put the keyword arguments in the midst of the positional arguments. This is purely for ease of reading.
The example above produces a Plot
object. It can be saved to a file by drawing to one or more backends using draw
.
img = SVG("iris_plot.svg", 14cm, 8cm)
draw(img, p)
Now we have the following charming little SVG image.
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7.7,3.0
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6.3,2.8
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7.2,3.0
6.4,2.8
6.1,3.0
6.2,2.8
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6.7,3.3
6.3,2.7
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5.6,2.8
6.9,3.2
6.0,2.2
7.7,2.6
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6.5,3.0
6.4,3.2
5.8,2.8
5.7,2.5
6.8,3.0
6.4,2.7
6.5,3.2
7.2,3.6
6.7,2.5
7.3,2.9
4.9,2.5
7.6,3.0
6.5,3.0
6.3,2.9
7.1,3.0
5.8,2.7
6.3,3.3
5.7,2.8
5.1,2.5
6.2,2.9
5.7,2.9
5.7,3.0
5.6,2.7
5.0,2.3
5.8,2.6
6.1,3.0
5.5,2.6
5.5,2.5
5.6,3.0
6.3,2.3
6.7,3.1
6.0,3.4
5.4,3.0
6.0,2.7
5.8,2.7
5.5,2.4
5.5,2.4
5.7,2.6
6.0,2.9
6.7,3.0
6.8,2.8
6.6,3.0
6.4,2.9
6.1,2.8
6.3,2.5
6.1,2.8
5.9,3.2
5.6,2.5
6.2,2.2
5.8,2.7
5.6,3.0
6.7,3.1
5.6,2.9
6.1,2.9
6.0,2.2
5.9,3.0
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5.2,2.7
6.6,2.9
4.9,2.4
6.3,3.3
5.7,2.8
6.5,2.8
5.5,2.3
6.9,3.1
6.4,3.2
7.0,3.2
5.0,3.3
5.3,3.7
4.6,3.2
5.1,3.8
4.8,3.0
5.1,3.8
5.0,3.5
4.4,3.2
4.5,2.3
5.0,3.5
5.1,3.4
4.4,3.0
4.9,3.6
5.5,3.5
5.0,3.2
4.9,3.1
5.5,4.2
5.2,4.1
5.4,3.4
4.8,3.1
4.7,3.2
5.2,3.4
5.2,3.5
5.0,3.4
5.0,3.0
4.8,3.4
5.1,3.3
4.6,3.6
5.1,3.7
5.4,3.4
5.1,3.8
5.7,3.8
5.1,3.5
5.4,3.9
5.7,4.4
5.8,4.0
4.3,3.0
4.8,3.0
4.8,3.4
5.4,3.7
4.9,3.1
4.4,2.9
5.0,3.4
4.6,3.4
5.4,3.9
5.0,3.6
4.6,3.1
4.7,3.2
4.9,3.0
5.1,3.5
h,j,k,l,arrows,drag to pan
i,o,+,-,scroll,shift-drag to zoom
r,dbl-click to reset
c for coordinates
? for help
?
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SepalWidth
If some of the text in this image is overlapping other text, your browser likely has a minimum font size set. You will need to unset this option for the plots to render correctly in your web browser.
If you are working at the REPL, a quicker way to see the image is to omit the semi-colon trailing plot
. This automatically renders the image to your default multimedia display, typically an internet browser. No need to capture the output argument in this case.
plot(iris, x=:SepalLength, y=:SepalWidth)
Note that Geom.point
will be automatically supplied if no other geometries are given.
Alternatively one can manually call display
on a Plot
object. This workflow is necessary when display
would not otherwise be called automatically.
function get_to_it(d)
ppoint = plot(d, x=:SepalLength, y=:SepalWidth, Geom.point)
pline = plot(d, x=:SepalLength, y=:SepalWidth, Geom.line)
ppoint, pline
end
ps = get_to_it(iris)
map(display, ps)
For the rest of the demonstrations, we'll simply omit the trailing semi-colon for brevity.
In this plot we've mapped the x aesthetic to the SepalLength
column and the y aesthetic to the SepalWidth
. The last argument, Geom.point
, is a geometry element which takes bound aesthetics and renders delightful figures. Adding other geometries produces layers, which may or may not result in a coherent plot.
plot(iris, x=:SepalLength, y=:SepalWidth, Geom.point, Geom.line)
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5.8,2.7
6.9,3.1
6.7,3.1
6.9,3.1
6.0,3.0
6.4,3.1
6.3,3.4
7.7,3.0
6.1,2.6
6.3,2.8
6.4,2.8
7.9,3.8
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7.2,3.0
6.4,2.8
6.1,3.0
6.2,2.8
7.2,3.2
6.7,3.3
6.3,2.7
7.7,2.8
5.6,2.8
6.9,3.2
6.0,2.2
7.7,2.6
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6.5,3.0
6.4,3.2
5.8,2.8
5.7,2.5
6.8,3.0
6.4,2.7
6.5,3.2
7.2,3.6
6.7,2.5
7.3,2.9
4.9,2.5
7.6,3.0
6.5,3.0
6.3,2.9
7.1,3.0
5.8,2.7
6.3,3.3
5.7,2.8
5.1,2.5
6.2,2.9
5.7,2.9
5.7,3.0
5.6,2.7
5.0,2.3
5.8,2.6
6.1,3.0
5.5,2.6
5.5,2.5
5.6,3.0
6.3,2.3
6.7,3.1
6.0,3.4
5.4,3.0
6.0,2.7
5.8,2.7
5.5,2.4
5.5,2.4
5.7,2.6
6.0,2.9
6.7,3.0
6.8,2.8
6.6,3.0
6.4,2.9
6.1,2.8
6.3,2.5
6.1,2.8
5.9,3.2
5.6,2.5
6.2,2.2
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6.1,2.9
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4.8,3.0
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4.5,2.3
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5.0,3.2
4.9,3.1
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5.2,4.1
5.4,3.4
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5.1,3.5
5.4,3.9
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5.8,4.0
4.3,3.0
4.8,3.0
4.8,3.4
5.4,3.7
4.9,3.1
4.4,2.9
5.0,3.4
4.6,3.4
5.4,3.9
5.0,3.6
4.6,3.1
4.7,3.2
4.9,3.0
5.1,3.5
h,j,k,l,arrows,drag to pan
i,o,+,-,scroll,shift-drag to zoom
r,dbl-click to reset
c for coordinates
? for help
?
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3.20
3.21
3.22
3.23
3.24
3.25
3.26
3.27
3.28
3.29
3.30
3.31
3.32
3.33
3.34
3.35
3.36
3.37
3.38
3.39
3.40
3.41
3.42
3.43
3.44
3.45
3.46
3.47
3.48
3.49
3.50
3.51
3.52
3.53
3.54
3.55
3.56
3.57
3.58
3.59
3.60
3.61
3.62
3.63
3.64
3.65
3.66
3.67
3.68
3.69
3.70
3.71
3.72
3.73
3.74
3.75
3.76
3.77
3.78
3.79
3.80
3.81
3.82
3.83
3.84
3.85
3.86
3.87
3.88
3.89
3.90
3.91
3.92
3.93
3.94
3.95
3.96
3.97
3.98
3.99
4.00
4.01
4.02
4.03
4.04
4.05
4.06
4.07
4.08
4.09
4.10
4.11
4.12
4.13
4.14
4.15
4.16
4.17
4.18
4.19
4.20
4.21
4.22
4.23
4.24
4.25
4.26
4.27
4.28
4.29
4.30
4.31
4.32
4.33
4.34
4.35
4.36
4.37
4.38
4.39
4.40
4.41
4.42
4.43
4.44
4.45
4.46
4.47
4.48
4.49
4.50
2
3
4
5
SepalWidth
This is the grammar of graphics equivalent of "colorless green ideas sleep furiously". It is valid grammar, but not particularly meaningful.
If by chance your data are stored in Arrays instead of a DataFrame, fear not, identical plots can be created using an alternate plot
signature:
plot(elements::Element...; aesthetics...)
Here, the keyword arguments directly supply the data to be plotted, instead of using them to indicate which columns of a DataFrame to use.
SepalLength = iris.SepalLength
SepalWidth = iris.SepalWidth
plot(x=SepalLength, y=SepalWidth, Geom.point,
Guide.xlabel("SepalLength"), Guide.ylabel("SepalWidth"))
Note that with the Array interface, extra elements must be included to specify the axis labels, whereas with a DataFrame they default to the column names.
Let's do add something meaningful by mapping the color aesthetic.
plot(iris, x=:SepalLength, y=:SepalWidth, color=:Species, Geom.point);
# or equivalently for Arrays:
Color = iris.Species
plot(x=SepalLength, y=SepalWidth, color=Color, Geom.point,
Guide.xlabel("SepalLength"), Guide.ylabel("SepalWidth"),
Guide.colorkey(title="Species"))
SepalLength
4
5
6
7
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
3.98
4.00
4.02
4.04
4.06
4.08
4.10
4.12
4.14
4.16
4.18
4.20
4.22
4.24
4.26
4.28
4.30
4.32
4.34
4.36
4.38
4.40
4.42
4.44
4.46
4.48
4.50
4.52
4.54
4.56
4.58
4.60
4.62
4.64
4.66
4.68
4.70
4.72
4.74
4.76
4.78
4.80
4.82
4.84
4.86
4.88
4.90
4.92
4.94
4.96
4.98
5.00
5.02
5.04
5.06
5.08
5.10
5.12
5.14
5.16
5.18
5.20
5.22
5.24
5.26
5.28
5.30
5.32
5.34
5.36
5.38
5.40
5.42
5.44
5.46
5.48
5.50
5.52
5.54
5.56
5.58
5.60
5.62
5.64
5.66
5.68
5.70
5.72
5.74
5.76
5.78
5.80
5.82
5.84
5.86
5.88
5.90
5.92
5.94
5.96
5.98
6.00
6.02
6.04
6.06
6.08
6.10
6.12
6.14
6.16
6.18
6.20
6.22
6.24
6.26
6.28
6.30
6.32
6.34
6.36
6.38
6.40
6.42
6.44
6.46
6.48
6.50
6.52
6.54
6.56
6.58
6.60
6.62
6.64
6.66
6.68
6.70
6.72
6.74
6.76
6.78
6.80
6.82
6.84
6.86
6.88
6.90
6.92
6.94
6.96
6.98
7.00
7.02
7.04
7.06
7.08
7.10
7.12
7.14
7.16
7.18
7.20
7.22
7.24
7.26
7.28
7.30
7.32
7.34
7.36
7.38
7.40
7.42
7.44
7.46
7.48
7.50
7.52
7.54
7.56
7.58
7.60
7.62
7.64
7.66
7.68
7.70
7.72
7.74
7.76
7.78
7.80
7.82
7.84
7.86
7.88
7.90
7.92
7.94
7.96
7.98
8.00
4
6
8
setosa
versicolor
virginica
Species
5.9,3.0
6.2,3.4
6.5,3.0
6.3,2.5
6.7,3.0
6.7,3.3
6.8,3.2
5.8,2.7
6.9,3.1
6.7,3.1
6.9,3.1
6.0,3.0
6.4,3.1
6.3,3.4
7.7,3.0
6.1,2.6
6.3,2.8
6.4,2.8
7.9,3.8
7.4,2.8
7.2,3.0
6.4,2.8
6.1,3.0
6.2,2.8
7.2,3.2
6.7,3.3
6.3,2.7
7.7,2.8
5.6,2.8
6.9,3.2
6.0,2.2
7.7,2.6
7.7,3.8
6.5,3.0
6.4,3.2
5.8,2.8
5.7,2.5
6.8,3.0
6.4,2.7
6.5,3.2
7.2,3.6
6.7,2.5
7.3,2.9
4.9,2.5
7.6,3.0
6.5,3.0
6.3,2.9
7.1,3.0
5.8,2.7
6.3,3.3
5.7,2.8
5.1,2.5
6.2,2.9
5.7,2.9
5.7,3.0
5.6,2.7
5.0,2.3
5.8,2.6
6.1,3.0
5.5,2.6
5.5,2.5
5.6,3.0
6.3,2.3
6.7,3.1
6.0,3.4
5.4,3.0
6.0,2.7
5.8,2.7
5.5,2.4
5.5,2.4
5.7,2.6
6.0,2.9
6.7,3.0
6.8,2.8
6.6,3.0
6.4,2.9
6.1,2.8
6.3,2.5
6.1,2.8
5.9,3.2
5.6,2.5
6.2,2.2
5.8,2.7
5.6,3.0
6.7,3.1
5.6,2.9
6.1,2.9
6.0,2.2
5.9,3.0
5.0,2.0
5.2,2.7
6.6,2.9
4.9,2.4
6.3,3.3
5.7,2.8
6.5,2.8
5.5,2.3
6.9,3.1
6.4,3.2
7.0,3.2
5.0,3.3
5.3,3.7
4.6,3.2
5.1,3.8
4.8,3.0
5.1,3.8
5.0,3.5
4.4,3.2
4.5,2.3
5.0,3.5
5.1,3.4
4.4,3.0
4.9,3.6
5.5,3.5
5.0,3.2
4.9,3.1
5.5,4.2
5.2,4.1
5.4,3.4
4.8,3.1
4.7,3.2
5.2,3.4
5.2,3.5
5.0,3.4
5.0,3.0
4.8,3.4
5.1,3.3
4.6,3.6
5.1,3.7
5.4,3.4
5.1,3.8
5.7,3.8
5.1,3.5
5.4,3.9
5.7,4.4
5.8,4.0
4.3,3.0
4.8,3.0
4.8,3.4
5.4,3.7
4.9,3.1
4.4,2.9
5.0,3.4
4.6,3.4
5.4,3.9
5.0,3.6
4.6,3.1
4.7,3.2
4.9,3.0
5.1,3.5
h,j,k,l,arrows,drag to pan
i,o,+,-,scroll,shift-drag to zoom
r,dbl-click to reset
c for coordinates
? for help
?
2.0
2.5
3.0
3.5
4.0
4.5
2.0
2.1
2.2
2.3
2.4
2.5
2.6
2.7
2.8
2.9
3.0
3.1
3.2
3.3
3.4
3.5
3.6
3.7
3.8
3.9
4.0
4.1
4.2
4.3
4.4
4.5
1.99
2.00
2.01
2.02
2.03
2.04
2.05
2.06
2.07
2.08
2.09
2.10
2.11
2.12
2.13
2.14
2.15
2.16
2.17
2.18
2.19
2.20
2.21
2.22
2.23
2.24
2.25
2.26
2.27
2.28
2.29
2.30
2.31
2.32
2.33
2.34
2.35
2.36
2.37
2.38
2.39
2.40
2.41
2.42
2.43
2.44
2.45
2.46
2.47
2.48
2.49
2.50
2.51
2.52
2.53
2.54
2.55
2.56
2.57
2.58
2.59
2.60
2.61
2.62
2.63
2.64
2.65
2.66
2.67
2.68
2.69
2.70
2.71
2.72
2.73
2.74
2.75
2.76
2.77
2.78
2.79
2.80
2.81
2.82
2.83
2.84
2.85
2.86
2.87
2.88
2.89
2.90
2.91
2.92
2.93
2.94
2.95
2.96
2.97
2.98
2.99
3.00
3.01
3.02
3.03
3.04
3.05
3.06
3.07
3.08
3.09
3.10
3.11
3.12
3.13
3.14
3.15
3.16
3.17
3.18
3.19
3.20
3.21
3.22
3.23
3.24
3.25
3.26
3.27
3.28
3.29
3.30
3.31
3.32
3.33
3.34
3.35
3.36
3.37
3.38
3.39
3.40
3.41
3.42
3.43
3.44
3.45
3.46
3.47
3.48
3.49
3.50
3.51
3.52
3.53
3.54
3.55
3.56
3.57
3.58
3.59
3.60
3.61
3.62
3.63
3.64
3.65
3.66
3.67
3.68
3.69
3.70
3.71
3.72
3.73
3.74
3.75
3.76
3.77
3.78
3.79
3.80
3.81
3.82
3.83
3.84
3.85
3.86
3.87
3.88
3.89
3.90
3.91
3.92
3.93
3.94
3.95
3.96
3.97
3.98
3.99
4.00
4.01
4.02
4.03
4.04
4.05
4.06
4.07
4.08
4.09
4.10
4.11
4.12
4.13
4.14
4.15
4.16
4.17
4.18
4.19
4.20
4.21
4.22
4.23
4.24
4.25
4.26
4.27
4.28
4.29
4.30
4.31
4.32
4.33
4.34
4.35
4.36
4.37
4.38
4.39
4.40
4.41
4.42
4.43
4.44
4.45
4.46
4.47
4.48
4.49
4.50
2
3
4
5
SepalWidth
Ah, a scientific discovery: Setosa has short but wide sepals!
Color scales in Gadfly by default are produced from perceptually uniform colorspaces (LUV/LCHuv or LAB/LCHab), though it supports RGB, HSV, HLS, XYZ, and converts arbitrarily between these. Color values can also be specified by most names common to CSS or X11, e.g. "oldlace"
or "aliceblue"
. The full list of valid color names is defined in the Colors.jl library .
Color, and other aesthetics, can also be mapped by using arrays with group labels or functional types e.g. ["group label"]
or [colorant"red"]
. ["Group labels"]
are added to the key.
y1 = [0.1, 0.26, NaN, 0.5, 0.4, NaN, 0.48, 0.58, 0.83]
plot(x=1:9, y=y1, Geom.line, Geom.point,
color=["Item 1"], linestyle=[:dash], size=[3pt],
layer(x=1:10, y=rand(10), Geom.line, Geom.point,
color=["Item 2"], size=[5pt], shape=[Shape.square]),
layer(x=1:10, y=rand(10), color=[colorant"hotpink"],
linestyle=[[8pt, 3pt, 2pt, 3pt]], Geom.line))
x
0.0
2.5
5.0
7.5
10.0
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
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
0.40
0.45
0.50
0.55
0.60
0.65
0.70
0.75
0.80
0.85
0.90
0.95
1.00
1.05
1.10
1.15
1.20
1.25
1.30
1.35
1.40
1.45
1.50
1.55
1.60
1.65
1.70
1.75
1.80
1.85
1.90
1.95
2.00
2.05
2.10
2.15
2.20
2.25
2.30
2.35
2.40
2.45
2.50
2.55
2.60
2.65
2.70
2.75
2.80
2.85
2.90
2.95
3.00
3.05
3.10
3.15
3.20
3.25
3.30
3.35
3.40
3.45
3.50
3.55
3.60
3.65
3.70
3.75
3.80
3.85
3.90
3.95
4.00
4.05
4.10
4.15
4.20
4.25
4.30
4.35
4.40
4.45
4.50
4.55
4.60
4.65
4.70
4.75
4.80
4.85
4.90
4.95
5.00
5.05
5.10
5.15
5.20
5.25
5.30
5.35
5.40
5.45
5.50
5.55
5.60
5.65
5.70
5.75
5.80
5.85
5.90
5.95
6.00
6.05
6.10
6.15
6.20
6.25
6.30
6.35
6.40
6.45
6.50
6.55
6.60
6.65
6.70
6.75
6.80
6.85
6.90
6.95
7.00
7.05
7.10
7.15
7.20
7.25
7.30
7.35
7.40
7.45
7.50
7.55
7.60
7.65
7.70
7.75
7.80
7.85
7.90
7.95
8.00
8.05
8.10
8.15
8.20
8.25
8.30
8.35
8.40
8.45
8.50
8.55
8.60
8.65
8.70
8.75
8.80
8.85
8.90
8.95
9.00
9.05
9.10
9.15
9.20
9.25
9.30
9.35
9.40
9.45
9.50
9.55
9.60
9.65
9.70
9.75
9.80
9.85
9.90
9.95
10.00
0
10
Item 1
Item 2
Color
100.04182509610383045
90.3328129509234997
80.5603972086851433
70.9377612026540267
60.8694499414235881
50.9760142153257741
40.8005481597758632
30.019622181022206142
20.9564332314556059
10.24822076502525248
9,0.83
8,0.58
7,0.48
6,NaN
5,0.4
4,0.5
3,NaN
2,0.26
1,0.1
h,j,k,l,arrows,drag to pan
i,o,+,-,scroll,shift-drag to zoom
r,dbl-click to reset
c for coordinates
? for help
?
0.0
0.5
1.0
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
0.40
0.45
0.50
0.55
0.60
0.65
0.70
0.75
0.80
0.85
0.90
0.95
1.00
0.000
0.005
0.010
0.015
0.020
0.025
0.030
0.035
0.040
0.045
0.050
0.055
0.060
0.065
0.070
0.075
0.080
0.085
0.090
0.095
0.100
0.105
0.110
0.115
0.120
0.125
0.130
0.135
0.140
0.145
0.150
0.155
0.160
0.165
0.170
0.175
0.180
0.185
0.190
0.195
0.200
0.205
0.210
0.215
0.220
0.225
0.230
0.235
0.240
0.245
0.250
0.255
0.260
0.265
0.270
0.275
0.280
0.285
0.290
0.295
0.300
0.305
0.310
0.315
0.320
0.325
0.330
0.335
0.340
0.345
0.350
0.355
0.360
0.365
0.370
0.375
0.380
0.385
0.390
0.395
0.400
0.405
0.410
0.415
0.420
0.425
0.430
0.435
0.440
0.445
0.450
0.455
0.460
0.465
0.470
0.475
0.480
0.485
0.490
0.495
0.500
0.505
0.510
0.515
0.520
0.525
0.530
0.535
0.540
0.545
0.550
0.555
0.560
0.565
0.570
0.575
0.580
0.585
0.590
0.595
0.600
0.605
0.610
0.615
0.620
0.625
0.630
0.635
0.640
0.645
0.650
0.655
0.660
0.665
0.670
0.675
0.680
0.685
0.690
0.695
0.700
0.705
0.710
0.715
0.720
0.725
0.730
0.735
0.740
0.745
0.750
0.755
0.760
0.765
0.770
0.775
0.780
0.785
0.790
0.795
0.800
0.805
0.810
0.815
0.820
0.825
0.830
0.835
0.840
0.845
0.850
0.855
0.860
0.865
0.870
0.875
0.880
0.885
0.890
0.895
0.900
0.905
0.910
0.915
0.920
0.925
0.930
0.935
0.940
0.945
0.950
0.955
0.960
0.965
0.970
0.975
0.980
0.985
0.990
0.995
1.000
0
1
y
All aesthetics have a Scale e.g. Scale.x_continuous()
and some have a Guide e.g. Guide.xticks()
. Scales can be continuous or discrete. Some Scales also have a corresponding palette in Theme()
.
Aesthetic Scale. Guide. Theme palette x
x_continuous
xticks
y
y_continuous
yticks
color
color_continuous
colorkey
(tbd) size
size_continuous
–- point_size_min
, point_size_max
size_radius
sizekey
continuous_sizemap
alpha
alpha_continuous
alphakey (tbd)
e.g. Scale.x_continuous(format= , minvalue= , maxvalue= )
format
can be: :plain
, :scientific
, :engineering
, or :auto
.
Continuous scales can be transformed. In the next plot, the large animals are ruining things for us. Putting both axes on a log-scale clears things up.
set_default_plot_size(21cm ,8cm)
mammals = dataset("MASS", "mammals")
p1 = plot(mammals, x=:Body, y=:Brain, label=:Mammal, Geom.point, Geom.label)
p2 = plot(mammals, x=:Body, y=:Brain, label=:Mammal, Geom.point, Geom.label,
Scale.x_log10, Scale.y_log10)
hstack(p1, p2)
Body
10-4
10-2
100
102
104
10-4.0
10-3.5
10-3.0
10-2.5
10-2.0
10-1.5
10-1.0
10-0.5
100.0
100.5
101.0
101.5
102.0
102.5
103.0
103.5
104.0
10-4.00
10-3.95
10-3.90
10-3.85
10-3.80
10-3.75
10-3.70
10-3.65
10-3.60
10-3.55
10-3.50
10-3.45
10-3.40
10-3.35
10-3.30
10-3.25
10-3.20
10-3.15
10-3.10
10-3.05
10-3.00
10-2.95
10-2.90
10-2.85
10-2.80
10-2.75
10-2.70
10-2.65
10-2.60
10-2.55
10-2.50
10-2.45
10-2.40
10-2.35
10-2.30
10-2.25
10-2.20
10-2.15
10-2.10
10-2.05
10-2.00
10-1.95
10-1.90
10-1.85
10-1.80
10-1.75
10-1.70
10-1.65
10-1.60
10-1.55
10-1.50
10-1.45
10-1.40
10-1.35
10-1.30
10-1.25
10-1.20
10-1.15
10-1.10
10-1.05
10-1.00
10-0.95
10-0.90
10-0.85
10-0.80
10-0.75
10-0.70
10-0.65
10-0.60
10-0.55
10-0.50
10-0.45
10-0.40
10-0.35
10-0.30
10-0.25
10-0.20
10-0.15
10-0.10
10-0.05
100.00
100.05
100.10
100.15
100.20
100.25
100.30
100.35
100.40
100.45
100.50
100.55
100.60
100.65
100.70
100.75
100.80
100.85
100.90
100.95
101.00
101.05
101.10
101.15
101.20
101.25
101.30
101.35
101.40
101.45
101.50
101.55
101.60
101.65
101.70
101.75
101.80
101.85
101.90
101.95
102.00
102.05
102.10
102.15
102.20
102.25
102.30
102.35
102.40
102.45
102.50
102.55
102.60
102.65
102.70
102.75
102.80
102.85
102.90
102.95
103.00
103.05
103.10
103.15
103.20
103.25
103.30
103.35
103.40
103.45
103.50
103.55
103.60
103.65
103.70
103.75
103.80
103.85
103.90
103.95
104.00
10-5
100
105
Arctic fox
Owl monkey
Mountain beaver
Cow
Grey wolf
Goat
Roe deer
Guinea pig
Verbet
Chinchilla
Ground squirrel
Arctic ground squirrel
African giant pouched rat
Lesser short-tailed shrew
Star-nosed mole
Nine-banded armadillo
Tree hyrax
N.A. opossum
Asian elephant
Big brown bat
Donkey
Horse
European hedgehog
Patas monkey
Cat
Galago
Genet
Giraffe
Gorilla
Grey seal
Rock hyrax-a
Human
African elephant
Water opossum
Rhesus monkey
Kangaroo
Yellow-bellied marmot
Golden hamster
Mouse
Little brown bat
Slow loris
Okapi
Rabbit
Sheep
Jaguar
Chimpanzee
Baboon
Desert hedgehog
Giant armadillo
Rock hyrax-b
Raccoon
Rat
E. American mole
Mole rat
Musk shrew
Pig
Echidna
Brazilian tapir
Tenrec
Phalanger
Tree shrew
Red fox
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-0.0457574905606751150.414973347970818
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1.77815125038364361.9084850188786497
-0.25963731050575610.38021124171160603
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1.71733758272386372.6434526764861874
2.02.1958996524092336
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0.39794000867203761.08278537031645
2.39794000867203752.690196080028514
0.1461280356782381.0969100130080565
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-1.6382721639824072-0.3979400086720376
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0.60745502321466851.2304489213782739
1.54406804435027571.7481880270062005
0.83250891270623632.2528530309798933
0.54406804435027570.5910646070264992
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1.7923916894982543.12057393120585
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1.92941892571429262.5118833609788744
2.3159703454569182.6085260335771943
2.72345567203518572.832508912706236
0.149219112655379881.2430380486862944
-0.69897000433601870.6989700043360189
0.51851393987788741.4082399653118496
1.02.060697840353612
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2.71683772329952472.816241299991783
2.272073787500012.622214022966295
-1.6382721639824072-0.5228787452803376
3.4060289449636153.663040974893974
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0.30102999566398121.089905111439398
0.54406804435027571.0334237554869496
-1.22184874961635640.0
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0.00.8195439355418687
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0.62221402296629541.7634279935629373
0.017033339298780370.7403626894942439
1.1711411510283821.9921114877869497
1.44185217577329182.060697840353612
1.56026539786271462.0773679052841563
2.6674529528899542.6263403673750423
0.130333768495006140.9084850188786497
-0.31875876262441281.1903316981702914
0.52955867302116311.6483600109809315
h,j,k,l,arrows,drag to pan
i,o,+,-,scroll,shift-drag to zoom
r,dbl-click to reset
c for coordinates
? for help
?
10-1
100
101
102
103
104
10-1.0
10-0.8
10-0.6
10-0.4
10-0.2
100.0
100.2
100.4
100.6
100.8
101.0
101.2
101.4
101.6
101.8
102.0
102.2
102.4
102.6
102.8
103.0
103.2
103.4
103.6
103.8
104.0
10-1.00
10-0.98
10-0.96
10-0.94
10-0.92
10-0.90
10-0.88
10-0.86
10-0.84
10-0.82
10-0.80
10-0.78
10-0.76
10-0.74
10-0.72
10-0.70
10-0.68
10-0.66
10-0.64
10-0.62
10-0.60
10-0.58
10-0.56
10-0.54
10-0.52
10-0.50
10-0.48
10-0.46
10-0.44
10-0.42
10-0.40
10-0.38
10-0.36
10-0.34
10-0.32
10-0.30
10-0.28
10-0.26
10-0.24
10-0.22
10-0.20
10-0.18
10-0.16
10-0.14
10-0.12
10-0.10
10-0.08
10-0.06
10-0.04
10-0.02
100.00
100.02
100.04
100.06
100.08
100.10
100.12
100.14
100.16
100.18
100.20
100.22
100.24
100.26
100.28
100.30
100.32
100.34
100.36
100.38
100.40
100.42
100.44
100.46
100.48
100.50
100.52
100.54
100.56
100.58
100.60
100.62
100.64
100.66
100.68
100.70
100.72
100.74
100.76
100.78
100.80
100.82
100.84
100.86
100.88
100.90
100.92
100.94
100.96
100.98
101.00
101.02
101.04
101.06
101.08
101.10
101.12
101.14
101.16
101.18
101.20
101.22
101.24
101.26
101.28
101.30
101.32
101.34
101.36
101.38
101.40
101.42
101.44
101.46
101.48
101.50
101.52
101.54
101.56
101.58
101.60
101.62
101.64
101.66
101.68
101.70
101.72
101.74
101.76
101.78
101.80
101.82
101.84
101.86
101.88
101.90
101.92
101.94
101.96
101.98
102.00
102.02
102.04
102.06
102.08
102.10
102.12
102.14
102.16
102.18
102.20
102.22
102.24
102.26
102.28
102.30
102.32
102.34
102.36
102.38
102.40
102.42
102.44
102.46
102.48
102.50
102.52
102.54
102.56
102.58
102.60
102.62
102.64
102.66
102.68
102.70
102.72
102.74
102.76
102.78
102.80
102.82
102.84
102.86
102.88
102.90
102.92
102.94
102.96
102.98
103.00
103.02
103.04
103.06
103.08
103.10
103.12
103.14
103.16
103.18
103.20
103.22
103.24
103.26
103.28
103.30
103.32
103.34
103.36
103.38
103.40
103.42
103.44
103.46
103.48
103.50
103.52
103.54
103.56
103.58
103.60
103.62
103.64
103.66
103.68
103.70
103.72
103.74
103.76
103.78
103.80
103.82
103.84
103.86
103.88
103.90
103.92
103.94
103.96
103.98
104.00
10-2
100
102
104
Brain
Body
0
2000
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8000
0
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6000
6500
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4850
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5000
5050
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5150
5200
5250
5300
5350
5400
5450
5500
5550
5600
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5750
5800
5850
5900
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6000
6050
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6200
6250
6300
6350
6400
6450
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6550
6600
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6700
6750
6800
6850
6900
6950
7000
7050
7100
7150
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7250
7300
7350
7400
7450
7500
7550
7600
7650
7700
7750
7800
7850
7900
7950
8000
0
10000
Arctic fox
Owl monkey
Mountain beaver
Cow
Grey wolf
Goat
Roe deer
Guinea pig
Verbet
Chinchilla
Ground squirrel
Arctic ground squirrel
African giant pouched rat
Lesser short-tailed shrew
Star-nosed mole
Nine-banded armadillo
Tree hyrax
N.A. opossum
Asian elephant
Big brown bat
Donkey
Horse
European hedgehog
Patas monkey
Cat
Galago
Genet
Giraffe
Gorilla
Grey seal
Rock hyrax-a
Human
African elephant
Water opossum
Rhesus monkey
Kangaroo
Yellow-bellied marmot
Golden hamster
Mouse
Little brown bat
Slow loris
Okapi
Rabbit
Sheep
Jaguar
Chimpanzee
Baboon
Desert hedgehog
Giant armadillo
Rock hyrax-b
Raccoon
Rat
E. American mole
Mole rat
Musk shrew
Pig
Echidna
Brazilian tapir
Tenrec
Phalanger
Tree shrew
Red fox
4.235,50.4
0.104,2.5
1.62,11.4
0.9,2.6
160.0169.0
3.0,25.0
192.0180.0
0.048,0.33
0.122,3.0
0.075,1.2
0.28,1.9
4.288,39.2
3.6,21.0
60.0,81.0
0.55,2.4
10.55179.5
52.16440.0
100.0157.0
55.5,175.0
2.5,12.1
250.0490.0
1.4,12.5
0.01,0.25
0.023,0.4
0.12,1.0
4.05,17.0
35.0,56.0
6.8,179.0
3.5,3.9
6654.05712.0
62.01320.0
0.75,12.3
85.0,325.0
207.0406.0
529.0680.0
1.41,17.5
0.2,5.0
3.3,25.6
10.0,115.0
0.785,3.5
521.0655.0
187.1419.0
0.023,0.3
2547.04603.0
1.7,6.3
2.0,12.3
3.5,10.8
0.06,1.0
0.005,0.14
1.0,6.6
0.92,5.7
0.101,4.0
0.425,6.4
4.19,58.0
1.04,5.5
14.83,98.2
27.66115.0
36.33119.5
465.0423.0
1.35,8.1
0.48,15.5
3.385,44.5
h,j,k,l,arrows,drag to pan
i,o,+,-,scroll,shift-drag to zoom
r,dbl-click to reset
c for coordinates
? for help
?
0
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10000
Brain
Scale transformations include: _sqrt
, _log
, _log2
, _log10
, _asinh
for the x
, y
, color
aesthetics, and _area
for the size
aesthetic.
using Printf
Diamonds = dataset("ggplot2","diamonds")
p3= plot(Diamonds, x=:Price, y=:Carat, Geom.histogram2d(xbincount=25, ybincount=25),
Scale.x_continuous(format=:engineering) )
p4= plot(Diamonds, x=:Price, y=:Carat, Geom.histogram2d(xbincount=25, ybincount=25),
Scale.x_continuous(format=:plain),
Scale.y_sqrt(labels=y->@sprintf("%i", y^2)),
Scale.color_log10(minvalue=1.0, maxvalue=10^4),
Guide.yticks(ticks=sqrt.(0:5)) )
hstack(p3, p4)
Price
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16900
17000
17100
17200
17300
17400
17500
17600
17700
17800
17900
18000
18100
18200
18300
18400
18500
18600
18700
18800
18900
19000
19100
19200
19300
19400
19500
19600
19700
19800
19900
20000
0
20000
104
100
101
102
103
Count
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r,dbl-click to reset
c for coordinates
? for help
?
0
1
2
3
4
5
Carat
Price
0
5.00×10³
10.0×10³
15.0×10³
20.0×10³
0
1.00×10³
2.00×10³
3.00×10³
4.00×10³
5.00×10³
6.00×10³
7.00×10³
8.00×10³
9.00×10³
10.0×10³
11.0×10³
12.0×10³
13.0×10³
14.0×10³
15.0×10³
16.0×10³
17.0×10³
18.0×10³
19.0×10³
20.0×10³
0
100.0×10⁰
200.0×10⁰
300.0×10⁰
400.0×10⁰
500.0×10⁰
600.0×10⁰
700.0×10⁰
800.0×10⁰
900.0×10⁰
1.000×10³
1.100×10³
1.200×10³
1.300×10³
1.400×10³
1.500×10³
1.600×10³
1.700×10³
1.800×10³
1.900×10³
2.000×10³
2.100×10³
2.200×10³
2.300×10³
2.400×10³
2.500×10³
2.600×10³
2.700×10³
2.800×10³
2.900×10³
3.000×10³
3.100×10³
3.200×10³
3.300×10³
3.400×10³
3.500×10³
3.600×10³
3.700×10³
3.800×10³
3.900×10³
4.000×10³
4.100×10³
4.200×10³
4.300×10³
4.400×10³
4.500×10³
4.600×10³
4.700×10³
4.800×10³
4.900×10³
5.000×10³
5.100×10³
5.200×10³
5.300×10³
5.400×10³
5.500×10³
5.600×10³
5.700×10³
5.800×10³
5.900×10³
6.000×10³
6.100×10³
6.200×10³
6.300×10³
6.400×10³
6.500×10³
6.600×10³
6.700×10³
6.800×10³
6.900×10³
7.000×10³
7.100×10³
7.200×10³
7.300×10³
7.400×10³
7.500×10³
7.600×10³
7.700×10³
7.800×10³
7.900×10³
8.000×10³
8.100×10³
8.200×10³
8.300×10³
8.400×10³
8.500×10³
8.600×10³
8.700×10³
8.800×10³
8.900×10³
9.000×10³
9.100×10³
9.200×10³
9.300×10³
9.400×10³
9.500×10³
9.600×10³
9.700×10³
9.800×10³
9.900×10³
10.00×10³
10.10×10³
10.20×10³
10.30×10³
10.40×10³
10.50×10³
10.60×10³
10.70×10³
10.80×10³
10.90×10³
11.00×10³
11.10×10³
11.20×10³
11.30×10³
11.40×10³
11.50×10³
11.60×10³
11.70×10³
11.80×10³
11.90×10³
12.00×10³
12.10×10³
12.20×10³
12.30×10³
12.40×10³
12.50×10³
12.60×10³
12.70×10³
12.80×10³
12.90×10³
13.00×10³
13.10×10³
13.20×10³
13.30×10³
13.40×10³
13.50×10³
13.60×10³
13.70×10³
13.80×10³
13.90×10³
14.00×10³
14.10×10³
14.20×10³
14.30×10³
14.40×10³
14.50×10³
14.60×10³
14.70×10³
14.80×10³
14.90×10³
15.00×10³
15.10×10³
15.20×10³
15.30×10³
15.40×10³
15.50×10³
15.60×10³
15.70×10³
15.80×10³
15.90×10³
16.00×10³
16.10×10³
16.20×10³
16.30×10³
16.40×10³
16.50×10³
16.60×10³
16.70×10³
16.80×10³
16.90×10³
17.00×10³
17.10×10³
17.20×10³
17.30×10³
17.40×10³
17.50×10³
17.60×10³
17.70×10³
17.80×10³
17.90×10³
18.00×10³
18.10×10³
18.20×10³
18.30×10³
18.40×10³
18.50×10³
18.60×10³
18.70×10³
18.80×10³
18.90×10³
19.00×10³
19.10×10³
19.20×10³
19.30×10³
19.40×10³
19.50×10³
19.60×10³
19.70×10³
19.80×10³
19.90×10³
20.00×10³
0
20.×10³
1.00×10⁴
1.50×10⁴
1.00×10⁰
5.00×10³
Count
h,j,k,l,arrows,drag to pan
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c for coordinates
? for help
?
0
1
2
3
4
5
6
0.00
0.25
0.50
0.75
1.00
1.25
1.50
1.75
2.00
2.25
2.50
2.75
3.00
3.25
3.50
3.75
4.00
4.25
4.50
4.75
5.00
5.25
5.50
5.75
6.00
0.00
0.02
0.04
0.06
0.08
0.10
0.12
0.14
0.16
0.18
0.20
0.22
0.24
0.26
0.28
0.30
0.32
0.34
0.36
0.38
0.40
0.42
0.44
0.46
0.48
0.50
0.52
0.54
0.56
0.58
0.60
0.62
0.64
0.66
0.68
0.70
0.72
0.74
0.76
0.78
0.80
0.82
0.84
0.86
0.88
0.90
0.92
0.94
0.96
0.98
1.00
1.02
1.04
1.06
1.08
1.10
1.12
1.14
1.16
1.18
1.20
1.22
1.24
1.26
1.28
1.30
1.32
1.34
1.36
1.38
1.40
1.42
1.44
1.46
1.48
1.50
1.52
1.54
1.56
1.58
1.60
1.62
1.64
1.66
1.68
1.70
1.72
1.74
1.76
1.78
1.80
1.82
1.84
1.86
1.88
1.90
1.92
1.94
1.96
1.98
2.00
2.02
2.04
2.06
2.08
2.10
2.12
2.14
2.16
2.18
2.20
2.22
2.24
2.26
2.28
2.30
2.32
2.34
2.36
2.38
2.40
2.42
2.44
2.46
2.48
2.50
2.52
2.54
2.56
2.58
2.60
2.62
2.64
2.66
2.68
2.70
2.72
2.74
2.76
2.78
2.80
2.82
2.84
2.86
2.88
2.90
2.92
2.94
2.96
2.98
3.00
3.02
3.04
3.06
3.08
3.10
3.12
3.14
3.16
3.18
3.20
3.22
3.24
3.26
3.28
3.30
3.32
3.34
3.36
3.38
3.40
3.42
3.44
3.46
3.48
3.50
3.52
3.54
3.56
3.58
3.60
3.62
3.64
3.66
3.68
3.70
3.72
3.74
3.76
3.78
3.80
3.82
3.84
3.86
3.88
3.90
3.92
3.94
3.96
3.98
4.00
4.02
4.04
4.06
4.08
4.10
4.12
4.14
4.16
4.18
4.20
4.22
4.24
4.26
4.28
4.30
4.32
4.34
4.36
4.38
4.40
4.42
4.44
4.46
4.48
4.50
4.52
4.54
4.56
4.58
4.60
4.62
4.64
4.66
4.68
4.70
4.72
4.74
4.76
4.78
4.80
4.82
4.84
4.86
4.88
4.90
4.92
4.94
4.96
4.98
5.00
5.02
5.04
5.06
5.08
5.10
5.12
5.14
5.16
5.18
5.20
5.22
5.24
5.26
5.28
5.30
5.32
5.34
5.36
5.38
5.40
5.42
5.44
5.46
5.48
5.50
5.52
5.54
5.56
5.58
5.60
5.62
5.64
5.66
5.68
5.70
5.72
5.74
5.76
5.78
5.80
5.82
5.84
5.86
5.88
5.90
5.92
5.94
5.96
5.98
6.00
0
10
Carat
Aesthetic Scale. Guide. Theme palette x
x_discrete
xticks
y
y_discrete
yticks
color
color_discrete
colorkey
(tbd) shape
shape_discrete
shapekey
point_shapes
size
size_discrete
–- point_size_min
, point_size_max
size_discrete2
sizekey
discrete_sizemap
linestyle
linestyle_discrete
linekey (tbd) line_style
alpha
alpha_discrete
alphakey (tbd) alphas
group
group_discrete
xgroup
xgroup
ygroup
ygroup
e.g. Scale.shape_discrete(labels= , levels= , order= )
mtcars = dataset("datasets","mtcars")
labeldict = Dict(4=>"four", 6=>"six", 8=>"eight")
p5 = plot(mtcars, x=:Cyl, color=:Cyl, Geom.histogram,
Scale.x_discrete(levels=[4,6,8]), Scale.color_discrete(levels=[4,6,8]) )
p6 = plot(mtcars, x=:Cyl, color=:Cyl, Geom.histogram,
Scale.x_discrete(labels=i->labeldict[i], levels=[8,6,4]),
Scale.color_discrete(levels=[8,6,4]) )
hstack(p5, p6)
Cyl
eight
six
four
8
6
4
Cyl
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c for coordinates
? for help
?
0
5
10
15
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
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
0.40
0.45
0.50
0.55
0.60
0.65
0.70
0.75
0.80
0.85
0.90
0.95
1.00
1.05
1.10
1.15
1.20
1.25
1.30
1.35
1.40
1.45
1.50
1.55
1.60
1.65
1.70
1.75
1.80
1.85
1.90
1.95
2.00
2.05
2.10
2.15
2.20
2.25
2.30
2.35
2.40
2.45
2.50
2.55
2.60
2.65
2.70
2.75
2.80
2.85
2.90
2.95
3.00
3.05
3.10
3.15
3.20
3.25
3.30
3.35
3.40
3.45
3.50
3.55
3.60
3.65
3.70
3.75
3.80
3.85
3.90
3.95
4.00
4.05
4.10
4.15
4.20
4.25
4.30
4.35
4.40
4.45
4.50
4.55
4.60
4.65
4.70
4.75
4.80
4.85
4.90
4.95
5.00
5.05
5.10
5.15
5.20
5.25
5.30
5.35
5.40
5.45
5.50
5.55
5.60
5.65
5.70
5.75
5.80
5.85
5.90
5.95
6.00
6.05
6.10
6.15
6.20
6.25
6.30
6.35
6.40
6.45
6.50
6.55
6.60
6.65
6.70
6.75
6.80
6.85
6.90
6.95
7.00
7.05
7.10
7.15
7.20
7.25
7.30
7.35
7.40
7.45
7.50
7.55
7.60
7.65
7.70
7.75
7.80
7.85
7.90
7.95
8.00
8.05
8.10
8.15
8.20
8.25
8.30
8.35
8.40
8.45
8.50
8.55
8.60
8.65
8.70
8.75
8.80
8.85
8.90
8.95
9.00
9.05
9.10
9.15
9.20
9.25
9.30
9.35
9.40
9.45
9.50
9.55
9.60
9.65
9.70
9.75
9.80
9.85
9.90
9.95
10.00
10.05
10.10
10.15
10.20
10.25
10.30
10.35
10.40
10.45
10.50
10.55
10.60
10.65
10.70
10.75
10.80
10.85
10.90
10.95
11.00
11.05
11.10
11.15
11.20
11.25
11.30
11.35
11.40
11.45
11.50
11.55
11.60
11.65
11.70
11.75
11.80
11.85
11.90
11.95
12.00
12.05
12.10
12.15
12.20
12.25
12.30
12.35
12.40
12.45
12.50
12.55
12.60
12.65
12.70
12.75
12.80
12.85
12.90
12.95
13.00
13.05
13.10
13.15
13.20
13.25
13.30
13.35
13.40
13.45
13.50
13.55
13.60
13.65
13.70
13.75
13.80
13.85
13.90
13.95
14.00
14.05
14.10
14.15
14.20
14.25
14.30
14.35
14.40
14.45
14.50
14.55
14.60
14.65
14.70
14.75
14.80
14.85
14.90
14.95
15.00
0
20
Cyl
4
6
8
4
6
8
Cyl
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r,dbl-click to reset
c for coordinates
? for help
?
0
5
10
15
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
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
0.40
0.45
0.50
0.55
0.60
0.65
0.70
0.75
0.80
0.85
0.90
0.95
1.00
1.05
1.10
1.15
1.20
1.25
1.30
1.35
1.40
1.45
1.50
1.55
1.60
1.65
1.70
1.75
1.80
1.85
1.90
1.95
2.00
2.05
2.10
2.15
2.20
2.25
2.30
2.35
2.40
2.45
2.50
2.55
2.60
2.65
2.70
2.75
2.80
2.85
2.90
2.95
3.00
3.05
3.10
3.15
3.20
3.25
3.30
3.35
3.40
3.45
3.50
3.55
3.60
3.65
3.70
3.75
3.80
3.85
3.90
3.95
4.00
4.05
4.10
4.15
4.20
4.25
4.30
4.35
4.40
4.45
4.50
4.55
4.60
4.65
4.70
4.75
4.80
4.85
4.90
4.95
5.00
5.05
5.10
5.15
5.20
5.25
5.30
5.35
5.40
5.45
5.50
5.55
5.60
5.65
5.70
5.75
5.80
5.85
5.90
5.95
6.00
6.05
6.10
6.15
6.20
6.25
6.30
6.35
6.40
6.45
6.50
6.55
6.60
6.65
6.70
6.75
6.80
6.85
6.90
6.95
7.00
7.05
7.10
7.15
7.20
7.25
7.30
7.35
7.40
7.45
7.50
7.55
7.60
7.65
7.70
7.75
7.80
7.85
7.90
7.95
8.00
8.05
8.10
8.15
8.20
8.25
8.30
8.35
8.40
8.45
8.50
8.55
8.60
8.65
8.70
8.75
8.80
8.85
8.90
8.95
9.00
9.05
9.10
9.15
9.20
9.25
9.30
9.35
9.40
9.45
9.50
9.55
9.60
9.65
9.70
9.75
9.80
9.85
9.90
9.95
10.00
10.05
10.10
10.15
10.20
10.25
10.30
10.35
10.40
10.45
10.50
10.55
10.60
10.65
10.70
10.75
10.80
10.85
10.90
10.95
11.00
11.05
11.10
11.15
11.20
11.25
11.30
11.35
11.40
11.45
11.50
11.55
11.60
11.65
11.70
11.75
11.80
11.85
11.90
11.95
12.00
12.05
12.10
12.15
12.20
12.25
12.30
12.35
12.40
12.45
12.50
12.55
12.60
12.65
12.70
12.75
12.80
12.85
12.90
12.95
13.00
13.05
13.10
13.15
13.20
13.25
13.30
13.35
13.40
13.45
13.50
13.55
13.60
13.65
13.70
13.75
13.80
13.85
13.90
13.95
14.00
14.05
14.10
14.15
14.20
14.25
14.30
14.35
14.40
14.45
14.50
14.55
14.60
14.65
14.70
14.75
14.80
14.85
14.90
14.95
15.00
0
20
For discrete scales with a Theme palette, the order of levels
and the order of the Theme palette match.
x, y = 0.55*rand(4), 0.55*rand(4)
plot( Coord.cartesian(xmin=0, ymin=0, xmax=1.0, ymax=1.0),
layer(x=x, y=y, shape=["A"], alpha=["day","day","day","night"]),
layer(x=1.0.-y[1:3], y=1.0.-x[1:3], shape=["B", "C","C"], alpha=["night"]),
Scale.shape_discrete(levels=["A","B","C"]),
Scale.alpha_discrete(levels=["day","night"]),
Theme(discrete_highlight_color=identity, point_size=12pt,
point_shapes=[Shape.circle, Shape.star1, Shape.star2], alphas=[0, 1.0],
default_color="midnightblue" )
)
x
0.0
0.5
1.0
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
0.40
0.45
0.50
0.55
0.60
0.65
0.70
0.75
0.80
0.85
0.90
0.95
1.00
0.000
0.005
0.010
0.015
0.020
0.025
0.030
0.035
0.040
0.045
0.050
0.055
0.060
0.065
0.070
0.075
0.080
0.085
0.090
0.095
0.100
0.105
0.110
0.115
0.120
0.125
0.130
0.135
0.140
0.145
0.150
0.155
0.160
0.165
0.170
0.175
0.180
0.185
0.190
0.195
0.200
0.205
0.210
0.215
0.220
0.225
0.230
0.235
0.240
0.245
0.250
0.255
0.260
0.265
0.270
0.275
0.280
0.285
0.290
0.295
0.300
0.305
0.310
0.315
0.320
0.325
0.330
0.335
0.340
0.345
0.350
0.355
0.360
0.365
0.370
0.375
0.380
0.385
0.390
0.395
0.400
0.405
0.410
0.415
0.420
0.425
0.430
0.435
0.440
0.445
0.450
0.455
0.460
0.465
0.470
0.475
0.480
0.485
0.490
0.495
0.500
0.505
0.510
0.515
0.520
0.525
0.530
0.535
0.540
0.545
0.550
0.555
0.560
0.565
0.570
0.575
0.580
0.585
0.590
0.595
0.600
0.605
0.610
0.615
0.620
0.625
0.630
0.635
0.640
0.645
0.650
0.655
0.660
0.665
0.670
0.675
0.680
0.685
0.690
0.695
0.700
0.705
0.710
0.715
0.720
0.725
0.730
0.735
0.740
0.745
0.750
0.755
0.760
0.765
0.770
0.775
0.780
0.785
0.790
0.795
0.800
0.805
0.810
0.815
0.820
0.825
0.830
0.835
0.840
0.845
0.850
0.855
0.860
0.865
0.870
0.875
0.880
0.885
0.890
0.895
0.900
0.905
0.910
0.915
0.920
0.925
0.930
0.935
0.940
0.945
0.950
0.955
0.960
0.965
0.970
0.975
0.980
0.985
0.990
0.995
1.000
0
1
A
B
C
Shape
0.51883050913022680.9028530710044848
0.95108209770197850.73479094629243
0.80259067013494090.8694405319468117
0.0193460903144308250.2972390696978554
0.097146928995515290.48116949086977323
0.26520905370756990.0489179022980215
0.13055946805318830.19740932986505907
h,j,k,l,arrows,drag to pan
i,o,+,-,scroll,shift-drag to zoom
r,dbl-click to reset
c for coordinates
? for help
?
0.0
0.5
1.0
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
0.40
0.45
0.50
0.55
0.60
0.65
0.70
0.75
0.80
0.85
0.90
0.95
1.00
0.000
0.005
0.010
0.015
0.020
0.025
0.030
0.035
0.040
0.045
0.050
0.055
0.060
0.065
0.070
0.075
0.080
0.085
0.090
0.095
0.100
0.105
0.110
0.115
0.120
0.125
0.130
0.135
0.140
0.145
0.150
0.155
0.160
0.165
0.170
0.175
0.180
0.185
0.190
0.195
0.200
0.205
0.210
0.215
0.220
0.225
0.230
0.235
0.240
0.245
0.250
0.255
0.260
0.265
0.270
0.275
0.280
0.285
0.290
0.295
0.300
0.305
0.310
0.315
0.320
0.325
0.330
0.335
0.340
0.345
0.350
0.355
0.360
0.365
0.370
0.375
0.380
0.385
0.390
0.395
0.400
0.405
0.410
0.415
0.420
0.425
0.430
0.435
0.440
0.445
0.450
0.455
0.460
0.465
0.470
0.475
0.480
0.485
0.490
0.495
0.500
0.505
0.510
0.515
0.520
0.525
0.530
0.535
0.540
0.545
0.550
0.555
0.560
0.565
0.570
0.575
0.580
0.585
0.590
0.595
0.600
0.605
0.610
0.615
0.620
0.625
0.630
0.635
0.640
0.645
0.650
0.655
0.660
0.665
0.670
0.675
0.680
0.685
0.690
0.695
0.700
0.705
0.710
0.715
0.720
0.725
0.730
0.735
0.740
0.745
0.750
0.755
0.760
0.765
0.770
0.775
0.780
0.785
0.790
0.795
0.800
0.805
0.810
0.815
0.820
0.825
0.830
0.835
0.840
0.845
0.850
0.855
0.860
0.865
0.870
0.875
0.880
0.885
0.890
0.895
0.900
0.905
0.910
0.915
0.920
0.925
0.930
0.935
0.940
0.945
0.950
0.955
0.960
0.965
0.970
0.975
0.980
0.985
0.990
0.995
1.000
0
1
y
If you don't supply Scales or Guides, Gadfly will make an educated guess.
gasoline = dataset("Ecdat", "Gasoline")
plot(gasoline, x=:Year, y=:LGasPCar, color=:Country, Geom.point, Geom.line)
Year
1960
1965
1970
1975
1980
1960
1961
1962
1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1960.0
1960.1
1960.2
1960.3
1960.4
1960.5
1960.6
1960.7
1960.8
1960.9
1961.0
1961.1
1961.2
1961.3
1961.4
1961.5
1961.6
1961.7
1961.8
1961.9
1962.0
1962.1
1962.2
1962.3
1962.4
1962.5
1962.6
1962.7
1962.8
1962.9
1963.0
1963.1
1963.2
1963.3
1963.4
1963.5
1963.6
1963.7
1963.8
1963.9
1964.0
1964.1
1964.2
1964.3
1964.4
1964.5
1964.6
1964.7
1964.8
1964.9
1965.0
1965.1
1965.2
1965.3
1965.4
1965.5
1965.6
1965.7
1965.8
1965.9
1966.0
1966.1
1966.2
1966.3
1966.4
1966.5
1966.6
1966.7
1966.8
1966.9
1967.0
1967.1
1967.2
1967.3
1967.4
1967.5
1967.6
1967.7
1967.8
1967.9
1968.0
1968.1
1968.2
1968.3
1968.4
1968.5
1968.6
1968.7
1968.8
1968.9
1969.0
1969.1
1969.2
1969.3
1969.4
1969.5
1969.6
1969.7
1969.8
1969.9
1970.0
1970.1
1970.2
1970.3
1970.4
1970.5
1970.6
1970.7
1970.8
1970.9
1971.0
1971.1
1971.2
1971.3
1971.4
1971.5
1971.6
1971.7
1971.8
1971.9
1972.0
1972.1
1972.2
1972.3
1972.4
1972.5
1972.6
1972.7
1972.8
1972.9
1973.0
1973.1
1973.2
1973.3
1973.4
1973.5
1973.6
1973.7
1973.8
1973.9
1974.0
1974.1
1974.2
1974.3
1974.4
1974.5
1974.6
1974.7
1974.8
1974.9
1975.0
1975.1
1975.2
1975.3
1975.4
1975.5
1975.6
1975.7
1975.8
1975.9
1976.0
1976.1
1976.2
1976.3
1976.4
1976.5
1976.6
1976.7
1976.8
1976.9
1977.0
1977.1
1977.2
1977.3
1977.4
1977.5
1977.6
1977.7
1977.8
1977.9
1978.0
1978.1
1978.2
1978.3
1978.4
1978.5
1978.6
1978.7
1978.8
1978.9
1979.0
1979.1
1979.2
1979.3
1979.4
1979.5
1979.6
1979.7
1979.8
1979.9
1980.0
1960
1980
JAPAN
NETHERLA
NORWAY
SPAIN
SWEDEN
SWITZERL
TURKEY
U.K.
U.S.A.
AUSTRIA
BELGIUM
CANADA
DENMARK
FRANCE
GERMANY
GREECE
IRELAND
ITALY
Country
19784.8184539683
19774.811032467
19764.8148907167
19754.8049322352
19744.7986259444
19734.8463745073
19724.8540732646
19714.8602864749
19704.8484842122
19694.841382713
19684.8341417653
19674.8008834761
19664.8075305603
19654.8059545113
19644.8082735727
19634.7878951522
19624.7989365652
19614.7963170698
19604.8239645123
19784.0003742149
19773.945553345
19763.962305336
19753.9125838579
19743.966961453
19733.995364122
19723.992756786
19713.9836534009
19703.9797051949
19693.948058368
19683.9532027179
19673.9436308491
19663.957212164
19653.968675694
19643.976781186
19633.9852710359
19624.0480509119
19614.0886358
19604.1002442839
19785.1412554768
19775.313462422
19765.312929193
19755.4267771741
19745.42772844
19735.68647036
19725.5788213319
19715.6696463189
19705.72210507
19695.7207051419
19686.0765946269
19676.044478582
19666.156644407
19655.8230458949
19646.064600869
19636.0751291349
19626.0845870211
19616.106212679
19606.1295528491
19784.050047696
19774.100533339
19764.0795721801
19754.120567757
19744.166363739
19734.2298161621
19724.2591593359
19714.280697003
19704.22529671
19694.211290089
19684.2177878429
19674.265918883
19664.2663516041
19654.288713915
19644.3134274369
19634.312484529
19624.2871473959
19614.441329648
19604.397621493
19784.067373445
19774.0310109309
19763.983996505
19753.9738404359
19743.913159154
19734.0305604061
19723.9800657581
19713.982061858
19703.989372472
19693.9917150449
19683.997584757
19673.9973460479
19664.0025573741
19654.015463106
19644.024858515
19634.00276563
19624.0064390159
19614.061869959
19604.063010036
19783.6204438709
19773.6507346971
19763.7108746111
19753.7524488659
19743.768565146
19733.912811545
19723.8912244911
19713.9073442129
19703.96604596
19693.9941031169
19684.0442530621
19674.086322459
19664.113780911
19654.217208979
19644.300577007
19634.346497214
19624.429087629
19614.589239364
19604.7494091723
19784.0024867129
19773.988515537
19763.978209728
19753.9960249669
19743.9603309711
19734.0613489569
19724.077257431
19714.078931746
19704.0888057159
19694.0868228049
19684.103864323
19674.0643140609
19664.0846073869
19654.131633441
19644.164351876
19634.216189342
19624.2342411029
19614.33271925
19604.43504067
19783.8825941949
19773.7766816581
19763.7836345681
19753.718466264
19743.7113837231
19733.8804785129
19723.915296331
19713.9478037431
19703.956407876
19693.987689339
19684.0707346969
19674.119154995
19664.168016513
19654.233001576
19644.31956339
19634.377686978
19624.471717068
19614.559839938
19604.6462680045
19783.9487463871
19773.9646719111
19763.9881620001
19753.995984493
19744.007963901
19734.0938837331
19724.2229757
19714.305623621
19704.401596952
19694.518289907
19684.6846663526
19674.8548612373
19665.0008214407
19655.125850803
19645.275327848
19635.5080817012
19625.6419150489
19615.7584836101
19605.9952865559
19783.3945044428
19773.3802089569
19763.4276288189
19753.5156795149
19743.4994699
19733.6522633939
19723.629243426
19713.6482050719
19703.706871673
19693.737389284
19683.7639029799
19673.7858083619
19663.8227352401
19653.8749851811
19643.936324254
19633.963086271
19624.0289989679
19614.0452481041
19604.050728238
19784.198610729
19774.2415507701
19764.2211462271
19754.248218349
19744.3255853241
19734.253827008
19724.270767878
19714.267117754
19704.2499445181
19694.208612656
19684.18111984
19674.188989564
19664.1682144109
19654.164895673
19644.186242773
19634.176695597
19624.2084346371
19614.2552393669
19604.270420603
19784.546399614
19774.484616757
19764.47995576
19754.580961511
19744.6278067713
19734.7685820877
19724.7957087158
19714.8118147383
19704.8518237449
19694.8947734887
19684.9441602588
19674.9757754289
19665.048395696
19655.0151124361
19645.1786270248
19635.083411848
19625.1880716432
19615.3814948731
19605.0374055349
19783.8838785591
19773.8956900509
19763.8964692669
19753.922028648
19743.8882123569
19733.924155679
19723.9324021681
19713.932104258
19703.9025204189
19693.8991846811
19683.8893615239
19673.875031869
19663.8807406531
19653.861049164
19643.868992975
19633.848782399
19623.8714840411
19613.885345397
19603.916953172
19783.7888825619
19773.812500373
19763.9081160121
19753.8085488721
19743.807994935
19733.8849943329
19723.8466772421
19713.8259622251
19703.801582653
19693.773460001
19683.7782304139
19673.7686207529
19663.7495348571
19653.760583648
19643.7670843699
19633.788996565
19623.823666088
19613.8856225131
19603.9077042329
19784.0366010839
19774.005290418
19764.0077389471
19754.0330145629
19744.000460803
19734.137437795
19724.082807844
19714.1031462929
19704.128807176
19694.173561413
19684.161687403
19674.2034662751
19664.2336434839
19654.249453555
19644.326435619
19634.3539971901
19624.385448561
19614.4828459381
19604.50198595
19784.855845841
19774.810991519
19764.8373587579
19754.888471343
19744.8915906557
19734.89969379
19724.8893020193
19714.8950745608
19704.8995700246
19694.8644326333
19684.868782423
19674.8524989572
19664.871024855
19654.850827846
19644.8397604783
19634.8380800488
19624.8505325093
19614.8265553731
19604.8552384411
19783.842741783
19773.854311239
19763.8641455001
19753.877778414
19743.8182304581
19733.8959956699
19723.905401926
19713.8722450341
19703.870391622
19693.8546012139
19683.8286653779
19673.9068782151
19663.8205378359
19653.9515307039
19643.994375414
19634.001266072
19624.075961692
19614.124355641
19604.16401597
19783.922749583
19773.9316759431
19763.985411744
19754.0290180751
19744.018495372
19734.199380561
19724.128017777
19714.106720494
19704.0808876731
19694.0463547891
19684.045507048
19674.0529106939
19664.0475365589
19654.033983285
19644.037688787
19634.0595091239
19624.0731765511
19614.1009891049
19604.173244195
h,j,k,l,arrows,drag to pan
i,o,+,-,scroll,shift-drag to zoom
r,dbl-click to reset
c for coordinates
? for help
?
3
4
5
6
7
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
2.98
3.00
3.02
3.04
3.06
3.08
3.10
3.12
3.14
3.16
3.18
3.20
3.22
3.24
3.26
3.28
3.30
3.32
3.34
3.36
3.38
3.40
3.42
3.44
3.46
3.48
3.50
3.52
3.54
3.56
3.58
3.60
3.62
3.64
3.66
3.68
3.70
3.72
3.74
3.76
3.78
3.80
3.82
3.84
3.86
3.88
3.90
3.92
3.94
3.96
3.98
4.00
4.02
4.04
4.06
4.08
4.10
4.12
4.14
4.16
4.18
4.20
4.22
4.24
4.26
4.28
4.30
4.32
4.34
4.36
4.38
4.40
4.42
4.44
4.46
4.48
4.50
4.52
4.54
4.56
4.58
4.60
4.62
4.64
4.66
4.68
4.70
4.72
4.74
4.76
4.78
4.80
4.82
4.84
4.86
4.88
4.90
4.92
4.94
4.96
4.98
5.00
5.02
5.04
5.06
5.08
5.10
5.12
5.14
5.16
5.18
5.20
5.22
5.24
5.26
5.28
5.30
5.32
5.34
5.36
5.38
5.40
5.42
5.44
5.46
5.48
5.50
5.52
5.54
5.56
5.58
5.60
5.62
5.64
5.66
5.68
5.70
5.72
5.74
5.76
5.78
5.80
5.82
5.84
5.86
5.88
5.90
5.92
5.94
5.96
5.98
6.00
6.02
6.04
6.06
6.08
6.10
6.12
6.14
6.16
6.18
6.20
6.22
6.24
6.26
6.28
6.30
6.32
6.34
6.36
6.38
6.40
6.42
6.44
6.46
6.48
6.50
6.52
6.54
6.56
6.58
6.60
6.62
6.64
6.66
6.68
6.70
6.72
6.74
6.76
6.78
6.80
6.82
6.84
6.86
6.88
6.90
6.92
6.94
6.96
6.98
7.00
3
4
5
6
7
LGasPCar
We could have added Scale.x_discrete
explicitly, but this is detected and the right default is chosen. This is the case with most of the elements in the grammar. When we've omitted Scale.x_continuous
and Scale.y_continuous
in the plots above, as well as Coord.cartesian
, and guide elements such as Guide.xticks
, Guide.xlabel
and so on, Gadfly tries to fill in the gaps with reasonable defaults.
Gadfly uses a custom graphics library called Compose , which is an attempt at a more elegant, purely functional take on the R grid package. It allows mixing of absolute and relative units and complex coordinate transforms. The primary backend is a native SVG generator (almost native: it uses pango to precompute text extents), though there is also a Cairo backend for PDF and PNG. See Backends for more details.
Building graphics declaratively let's you do some fun things. Like stick two plots together:
fig1a = plot(iris, x=:SepalLength, y=:SepalWidth, Geom.point)
fig1b = plot(iris, x=:SepalWidth, Geom.bar)
fig1 = hstack(fig1a, fig1b)
SepalWidth
1
2
3
4
5
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
0.00
0.02
0.04
0.06
0.08
0.10
0.12
0.14
0.16
0.18
0.20
0.22
0.24
0.26
0.28
0.30
0.32
0.34
0.36
0.38
0.40
0.42
0.44
0.46
0.48
0.50
0.52
0.54
0.56
0.58
0.60
0.62
0.64
0.66
0.68
0.70
0.72
0.74
0.76
0.78
0.80
0.82
0.84
0.86
0.88
0.90
0.92
0.94
0.96
0.98
1.00
1.02
1.04
1.06
1.08
1.10
1.12
1.14
1.16
1.18
1.20
1.22
1.24
1.26
1.28
1.30
1.32
1.34
1.36
1.38
1.40
1.42
1.44
1.46
1.48
1.50
1.52
1.54
1.56
1.58
1.60
1.62
1.64
1.66
1.68
1.70
1.72
1.74
1.76
1.78
1.80
1.82
1.84
1.86
1.88
1.90
1.92
1.94
1.96
1.98
2.00
2.02
2.04
2.06
2.08
2.10
2.12
2.14
2.16
2.18
2.20
2.22
2.24
2.26
2.28
2.30
2.32
2.34
2.36
2.38
2.40
2.42
2.44
2.46
2.48
2.50
2.52
2.54
2.56
2.58
2.60
2.62
2.64
2.66
2.68
2.70
2.72
2.74
2.76
2.78
2.80
2.82
2.84
2.86
2.88
2.90
2.92
2.94
2.96
2.98
3.00
3.02
3.04
3.06
3.08
3.10
3.12
3.14
3.16
3.18
3.20
3.22
3.24
3.26
3.28
3.30
3.32
3.34
3.36
3.38
3.40
3.42
3.44
3.46
3.48
3.50
3.52
3.54
3.56
3.58
3.60
3.62
3.64
3.66
3.68
3.70
3.72
3.74
3.76
3.78
3.80
3.82
3.84
3.86
3.88
3.90
3.92
3.94
3.96
3.98
4.00
4.02
4.04
4.06
4.08
4.10
4.12
4.14
4.16
4.18
4.20
4.22
4.24
4.26
4.28
4.30
4.32
4.34
4.36
4.38
4.40
4.42
4.44
4.46
4.48
4.50
4.52
4.54
4.56
4.58
4.60
4.62
4.64
4.66
4.68
4.70
4.72
4.74
4.76
4.78
4.80
4.82
4.84
4.86
4.88
4.90
4.92
4.94
4.96
4.98
5.00
0
5
h,j,k,l,arrows,drag to pan
i,o,+,-,scroll,shift-drag to zoom
r,dbl-click to reset
c for coordinates
? for help
?
0
50
100
150
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
100
105
110
115
120
125
130
135
140
145
150
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
26.5
27.0
27.5
28.0
28.5
29.0
29.5
30.0
30.5
31.0
31.5
32.0
32.5
33.0
33.5
34.0
34.5
35.0
35.5
36.0
36.5
37.0
37.5
38.0
38.5
39.0
39.5
40.0
40.5
41.0
41.5
42.0
42.5
43.0
43.5
44.0
44.5
45.0
45.5
46.0
46.5
47.0
47.5
48.0
48.5
49.0
49.5
50.0
50.5
51.0
51.5
52.0
52.5
53.0
53.5
54.0
54.5
55.0
55.5
56.0
56.5
57.0
57.5
58.0
58.5
59.0
59.5
60.0
60.5
61.0
61.5
62.0
62.5
63.0
63.5
64.0
64.5
65.0
65.5
66.0
66.5
67.0
67.5
68.0
68.5
69.0
69.5
70.0
70.5
71.0
71.5
72.0
72.5
73.0
73.5
74.0
74.5
75.0
75.5
76.0
76.5
77.0
77.5
78.0
78.5
79.0
79.5
80.0
80.5
81.0
81.5
82.0
82.5
83.0
83.5
84.0
84.5
85.0
85.5
86.0
86.5
87.0
87.5
88.0
88.5
89.0
89.5
90.0
90.5
91.0
91.5
92.0
92.5
93.0
93.5
94.0
94.5
95.0
95.5
96.0
96.5
97.0
97.5
98.0
98.5
99.0
99.5
100.0
100.5
101.0
101.5
102.0
102.5
103.0
103.5
104.0
104.5
105.0
105.5
106.0
106.5
107.0
107.5
108.0
108.5
109.0
109.5
110.0
110.5
111.0
111.5
112.0
112.5
113.0
113.5
114.0
114.5
115.0
115.5
116.0
116.5
117.0
117.5
118.0
118.5
119.0
119.5
120.0
120.5
121.0
121.5
122.0
122.5
123.0
123.5
124.0
124.5
125.0
125.5
126.0
126.5
127.0
127.5
128.0
128.5
129.0
129.5
130.0
130.5
131.0
131.5
132.0
132.5
133.0
133.5
134.0
134.5
135.0
135.5
136.0
136.5
137.0
137.5
138.0
138.5
139.0
139.5
140.0
140.5
141.0
141.5
142.0
142.5
143.0
143.5
144.0
144.5
145.0
145.5
146.0
146.5
147.0
147.5
148.0
148.5
149.0
149.5
150.0
0
200
SepalLength
4
5
6
7
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
3.98
4.00
4.02
4.04
4.06
4.08
4.10
4.12
4.14
4.16
4.18
4.20
4.22
4.24
4.26
4.28
4.30
4.32
4.34
4.36
4.38
4.40
4.42
4.44
4.46
4.48
4.50
4.52
4.54
4.56
4.58
4.60
4.62
4.64
4.66
4.68
4.70
4.72
4.74
4.76
4.78
4.80
4.82
4.84
4.86
4.88
4.90
4.92
4.94
4.96
4.98
5.00
5.02
5.04
5.06
5.08
5.10
5.12
5.14
5.16
5.18
5.20
5.22
5.24
5.26
5.28
5.30
5.32
5.34
5.36
5.38
5.40
5.42
5.44
5.46
5.48
5.50
5.52
5.54
5.56
5.58
5.60
5.62
5.64
5.66
5.68
5.70
5.72
5.74
5.76
5.78
5.80
5.82
5.84
5.86
5.88
5.90
5.92
5.94
5.96
5.98
6.00
6.02
6.04
6.06
6.08
6.10
6.12
6.14
6.16
6.18
6.20
6.22
6.24
6.26
6.28
6.30
6.32
6.34
6.36
6.38
6.40
6.42
6.44
6.46
6.48
6.50
6.52
6.54
6.56
6.58
6.60
6.62
6.64
6.66
6.68
6.70
6.72
6.74
6.76
6.78
6.80
6.82
6.84
6.86
6.88
6.90
6.92
6.94
6.96
6.98
7.00
7.02
7.04
7.06
7.08
7.10
7.12
7.14
7.16
7.18
7.20
7.22
7.24
7.26
7.28
7.30
7.32
7.34
7.36
7.38
7.40
7.42
7.44
7.46
7.48
7.50
7.52
7.54
7.56
7.58
7.60
7.62
7.64
7.66
7.68
7.70
7.72
7.74
7.76
7.78
7.80
7.82
7.84
7.86
7.88
7.90
7.92
7.94
7.96
7.98
8.00
4
6
8
5.9,3.0
6.2,3.4
6.5,3.0
6.3,2.5
6.7,3.0
6.7,3.3
6.8,3.2
5.8,2.7
6.9,3.1
6.7,3.1
6.9,3.1
6.0,3.0
6.4,3.1
6.3,3.4
7.7,3.0
6.1,2.6
6.3,2.8
6.4,2.8
7.9,3.8
7.4,2.8
7.2,3.0
6.4,2.8
6.1,3.0
6.2,2.8
7.2,3.2
6.7,3.3
6.3,2.7
7.7,2.8
5.6,2.8
6.9,3.2
6.0,2.2
7.7,2.6
7.7,3.8
6.5,3.0
6.4,3.2
5.8,2.8
5.7,2.5
6.8,3.0
6.4,2.7
6.5,3.2
7.2,3.6
6.7,2.5
7.3,2.9
4.9,2.5
7.6,3.0
6.5,3.0
6.3,2.9
7.1,3.0
5.8,2.7
6.3,3.3
5.7,2.8
5.1,2.5
6.2,2.9
5.7,2.9
5.7,3.0
5.6,2.7
5.0,2.3
5.8,2.6
6.1,3.0
5.5,2.6
5.5,2.5
5.6,3.0
6.3,2.3
6.7,3.1
6.0,3.4
5.4,3.0
6.0,2.7
5.8,2.7
5.5,2.4
5.5,2.4
5.7,2.6
6.0,2.9
6.7,3.0
6.8,2.8
6.6,3.0
6.4,2.9
6.1,2.8
6.3,2.5
6.1,2.8
5.9,3.2
5.6,2.5
6.2,2.2
5.8,2.7
5.6,3.0
6.7,3.1
5.6,2.9
6.1,2.9
6.0,2.2
5.9,3.0
5.0,2.0
5.2,2.7
6.6,2.9
4.9,2.4
6.3,3.3
5.7,2.8
6.5,2.8
5.5,2.3
6.9,3.1
6.4,3.2
7.0,3.2
5.0,3.3
5.3,3.7
4.6,3.2
5.1,3.8
4.8,3.0
5.1,3.8
5.0,3.5
4.4,3.2
4.5,2.3
5.0,3.5
5.1,3.4
4.4,3.0
4.9,3.6
5.5,3.5
5.0,3.2
4.9,3.1
5.5,4.2
5.2,4.1
5.4,3.4
4.8,3.1
4.7,3.2
5.2,3.4
5.2,3.5
5.0,3.4
5.0,3.0
4.8,3.4
5.1,3.3
4.6,3.6
5.1,3.7
5.4,3.4
5.1,3.8
5.7,3.8
5.1,3.5
5.4,3.9
5.7,4.4
5.8,4.0
4.3,3.0
4.8,3.0
4.8,3.4
5.4,3.7
4.9,3.1
4.4,2.9
5.0,3.4
4.6,3.4
5.4,3.9
5.0,3.6
4.6,3.1
4.7,3.2
4.9,3.0
5.1,3.5
h,j,k,l,arrows,drag to pan
i,o,+,-,scroll,shift-drag to zoom
r,dbl-click to reset
c for coordinates
? for help
?
2.0
2.5
3.0
3.5
4.0
4.5
2.0
2.1
2.2
2.3
2.4
2.5
2.6
2.7
2.8
2.9
3.0
3.1
3.2
3.3
3.4
3.5
3.6
3.7
3.8
3.9
4.0
4.1
4.2
4.3
4.4
4.5
1.99
2.00
2.01
2.02
2.03
2.04
2.05
2.06
2.07
2.08
2.09
2.10
2.11
2.12
2.13
2.14
2.15
2.16
2.17
2.18
2.19
2.20
2.21
2.22
2.23
2.24
2.25
2.26
2.27
2.28
2.29
2.30
2.31
2.32
2.33
2.34
2.35
2.36
2.37
2.38
2.39
2.40
2.41
2.42
2.43
2.44
2.45
2.46
2.47
2.48
2.49
2.50
2.51
2.52
2.53
2.54
2.55
2.56
2.57
2.58
2.59
2.60
2.61
2.62
2.63
2.64
2.65
2.66
2.67
2.68
2.69
2.70
2.71
2.72
2.73
2.74
2.75
2.76
2.77
2.78
2.79
2.80
2.81
2.82
2.83
2.84
2.85
2.86
2.87
2.88
2.89
2.90
2.91
2.92
2.93
2.94
2.95
2.96
2.97
2.98
2.99
3.00
3.01
3.02
3.03
3.04
3.05
3.06
3.07
3.08
3.09
3.10
3.11
3.12
3.13
3.14
3.15
3.16
3.17
3.18
3.19
3.20
3.21
3.22
3.23
3.24
3.25
3.26
3.27
3.28
3.29
3.30
3.31
3.32
3.33
3.34
3.35
3.36
3.37
3.38
3.39
3.40
3.41
3.42
3.43
3.44
3.45
3.46
3.47
3.48
3.49
3.50
3.51
3.52
3.53
3.54
3.55
3.56
3.57
3.58
3.59
3.60
3.61
3.62
3.63
3.64
3.65
3.66
3.67
3.68
3.69
3.70
3.71
3.72
3.73
3.74
3.75
3.76
3.77
3.78
3.79
3.80
3.81
3.82
3.83
3.84
3.85
3.86
3.87
3.88
3.89
3.90
3.91
3.92
3.93
3.94
3.95
3.96
3.97
3.98
3.99
4.00
4.01
4.02
4.03
4.04
4.05
4.06
4.07
4.08
4.09
4.10
4.11
4.12
4.13
4.14
4.15
4.16
4.17
4.18
4.19
4.20
4.21
4.22
4.23
4.24
4.25
4.26
4.27
4.28
4.29
4.30
4.31
4.32
4.33
4.34
4.35
4.36
4.37
4.38
4.39
4.40
4.41
4.42
4.43
4.44
4.45
4.46
4.47
4.48
4.49
4.50
2
3
4
5
SepalWidth
Ultimately this will make more complex visualizations easier to build. For example, facets, plots within plots, and so on. See Compositing for more details.
One advantage of generating our own SVG is that we can annotate our SVG output and embed Javascript code to provide some level of dynamism. Though not a replacement for full-fledged custom interactive visualizations of the sort produced by D3 , this sort of mild interactivity can improve a lot of standard plots.
The fuel efficiency plot is made more clear by toggling off some of the countries, for example. To do so, first render the plot using the SVGJS backend, which was not used to generate this webpage but is the default at the REPL, then simply click or shift-click in the colored squares in the table of keys to the right.
One can also zoom in and out by pressing the shift key while either scrolling the mouse wheel or clicking and dragging a box. Should your mouse not work, try the plus, minus, I, and O, keys. Panning is similarly easy: click and drag without depressing the shift key, or use the arrow keys. For Vim enthusiasts, the H, J, K, and L keys pan as expected. To reset the plot to it's initial state, double click it or hit R. Lastly, press C to toggle on and off a numerical display of the cursor coordinates.