Example usage of Charty¶

Read Iris dataset as an Arrow::Table object.

In [1]:

require "datasets-daru"

iris = Datasets::Iris.new.to_daru

Out[1]:

Daru::DataFrame(150x5)

	sepal_length	sepal_width	petal_length	petal_width	label
0	5.1	3.5	1.4	0.2	Iris-setosa
1	4.9	3.0	1.4	0.2	Iris-setosa
2	4.7	3.2	1.3	0.2	Iris-setosa
3	4.6	3.1	1.5	0.2	Iris-setosa
4	5.0	3.6	1.4	0.2	Iris-setosa
5	5.4	3.9	1.7	0.4	Iris-setosa
6	4.6	3.4	1.4	0.3	Iris-setosa
7	5.0	3.4	1.5	0.2	Iris-setosa
8	4.4	2.9	1.4	0.2	Iris-setosa
9	4.9	3.1	1.5	0.1	Iris-setosa
10	5.4	3.7	1.5	0.2	Iris-setosa
11	4.8	3.4	1.6	0.2	Iris-setosa
12	4.8	3.0	1.4	0.1	Iris-setosa
13	4.3	3.0	1.1	0.1	Iris-setosa
14	5.8	4.0	1.2	0.2	Iris-setosa
15	5.7	4.4	1.5	0.4	Iris-setosa
16	5.4	3.9	1.3	0.4	Iris-setosa
17	5.1	3.5	1.4	0.3	Iris-setosa
18	5.7	3.8	1.7	0.3	Iris-setosa
19	5.1	3.8	1.5	0.3	Iris-setosa
20	5.4	3.4	1.7	0.2	Iris-setosa
21	5.1	3.7	1.5	0.4	Iris-setosa
22	4.6	3.6	1.0	0.2	Iris-setosa
23	5.1	3.3	1.7	0.5	Iris-setosa
24	4.8	3.4	1.9	0.2	Iris-setosa
25	5.0	3.0	1.6	0.2	Iris-setosa
26	5.0	3.4	1.6	0.4	Iris-setosa
27	5.2	3.5	1.5	0.2	Iris-setosa
28	5.2	3.4	1.4	0.2	Iris-setosa
29	4.7	3.2	1.6	0.2	Iris-setosa
...	...	...	...	...	...
149	5.9	3.0	5.1	1.8	Iris-virginica

Setting up Charty with Matplotlib backend.

In [3]:

require 'charty'

charty = Charty::Plotter.new(:pyplot)
Charty::Backends::Pyplot.activate_iruby_integration

Out[3]:

[:inline, "module://ruby.matplotlib.backend_inline"]

Show scatterplot of the relationship between Petal Length and Petal Width.

In [4]:

plot = charty.scatter do
  iris.group_by(:label).groups.each do |label, index|
    records = iris.row[*index]
    series records[:petal_length].to_a, records[:petal_width].to_a, label: label[0]
  end
  xlabel "Petal Length"
  ylabel "Petal Width"
end
plot.render

Out[4]:

You can find the other examples in here.

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