18 Aggregate

using CSV, DataFrames, StatsBase

iris = CSV.read("/Users/egenn/icloud/Data/iris.csv", DataFrame)

150×5 DataFrame

125 rows omitted

Row	Sepal.Length	Sepal.Width	Petal.Length	Petal.Width	Species
	Float64	Float64	Float64	Float64	String15
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
7	4.6	3.4	1.4	0.3	setosa
8	5.0	3.4	1.5	0.2	setosa
9	4.4	2.9	1.4	0.2	setosa
10	4.9	3.1	1.5	0.1	setosa
11	5.4	3.7	1.5	0.2	setosa
12	4.8	3.4	1.6	0.2	setosa
13	4.8	3.0	1.4	0.1	setosa
⋮	⋮	⋮	⋮	⋮	⋮
139	6.0	3.0	4.8	1.8	virginica
140	6.9	3.1	5.4	2.1	virginica
141	6.7	3.1	5.6	2.4	virginica
142	6.9	3.1	5.1	2.3	virginica
143	5.8	2.7	5.1	1.9	virginica
144	6.8	3.2	5.9	2.3	virginica
145	6.7	3.3	5.7	2.5	virginica
146	6.7	3.0	5.2	2.3	virginica
147	6.3	2.5	5.0	1.9	virginica
148	6.5	3.0	5.2	2.0	virginica
149	6.2	3.4	5.4	2.3	virginica
150	5.9	3.0	5.1	1.8	virginica

Cleanup column names

rename!(iris, replace.(names(iris), "." => "_"))

150×5 DataFrame

125 rows omitted

Row	Sepal_Length	Sepal_Width	Petal_Length	Petal_Width	Species
	Float64	Float64	Float64	Float64	String15
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
7	4.6	3.4	1.4	0.3	setosa
8	5.0	3.4	1.5	0.2	setosa
9	4.4	2.9	1.4	0.2	setosa
10	4.9	3.1	1.5	0.1	setosa
11	5.4	3.7	1.5	0.2	setosa
12	4.8	3.4	1.6	0.2	setosa
13	4.8	3.0	1.4	0.1	setosa
⋮	⋮	⋮	⋮	⋮	⋮
139	6.0	3.0	4.8	1.8	virginica
140	6.9	3.1	5.4	2.1	virginica
141	6.7	3.1	5.6	2.4	virginica
142	6.9	3.1	5.1	2.3	virginica
143	5.8	2.7	5.1	1.9	virginica
144	6.8	3.2	5.9	2.3	virginica
145	6.7	3.3	5.7	2.5	virginica
146	6.7	3.0	5.2	2.3	virginica
147	6.3	2.5	5.0	1.9	virginica
148	6.5	3.0	5.2	2.0	virginica
149	6.2	3.4	5.4	2.3	virginica
150	5.9	3.0	5.1	1.8	virginica

18.1 Create a grouped DataFrame

groupby(iris, :Species)

GroupedDataFrame with 3 groups based on key: Species

First Group (50 rows): Species = "setosa"

25 rows omitted

Row	Sepal_Length	Sepal_Width	Petal_Length	Petal_Width	Species
	Float64	Float64	Float64	Float64	String15
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
7	4.6	3.4	1.4	0.3	setosa
8	5.0	3.4	1.5	0.2	setosa
9	4.4	2.9	1.4	0.2	setosa
10	4.9	3.1	1.5	0.1	setosa
11	5.4	3.7	1.5	0.2	setosa
12	4.8	3.4	1.6	0.2	setosa
13	4.8	3.0	1.4	0.1	setosa
⋮	⋮	⋮	⋮	⋮	⋮
39	4.4	3.0	1.3	0.2	setosa
40	5.1	3.4	1.5	0.2	setosa
41	5.0	3.5	1.3	0.3	setosa
42	4.5	2.3	1.3	0.3	setosa
43	4.4	3.2	1.3	0.2	setosa
44	5.0	3.5	1.6	0.6	setosa
45	5.1	3.8	1.9	0.4	setosa
46	4.8	3.0	1.4	0.3	setosa
47	5.1	3.8	1.6	0.2	setosa
48	4.6	3.2	1.4	0.2	setosa
49	5.3	3.7	1.5	0.2	setosa
50	5.0	3.3	1.4	0.2	setosa

⋮

Last Group (50 rows): Species = "virginica"

25 rows omitted

Row	Sepal_Length	Sepal_Width	Petal_Length	Petal_Width	Species
	Float64	Float64	Float64	Float64	String15
1	6.3	3.3	6.0	2.5	virginica
2	5.8	2.7	5.1	1.9	virginica
3	7.1	3.0	5.9	2.1	virginica
4	6.3	2.9	5.6	1.8	virginica
5	6.5	3.0	5.8	2.2	virginica
6	7.6	3.0	6.6	2.1	virginica
7	4.9	2.5	4.5	1.7	virginica
8	7.3	2.9	6.3	1.8	virginica
9	6.7	2.5	5.8	1.8	virginica
10	7.2	3.6	6.1	2.5	virginica
11	6.5	3.2	5.1	2.0	virginica
12	6.4	2.7	5.3	1.9	virginica
13	6.8	3.0	5.5	2.1	virginica
⋮	⋮	⋮	⋮	⋮	⋮
39	6.0	3.0	4.8	1.8	virginica
40	6.9	3.1	5.4	2.1	virginica
41	6.7	3.1	5.6	2.4	virginica
42	6.9	3.1	5.1	2.3	virginica
43	5.8	2.7	5.1	1.9	virginica
44	6.8	3.2	5.9	2.3	virginica
45	6.7	3.3	5.7	2.5	virginica
46	6.7	3.0	5.2	2.3	virginica
47	6.3	2.5	5.0	1.9	virginica
48	6.5	3.0	5.2	2.0	virginica
49	6.2	3.4	5.4	2.3	virginica
50	5.9	3.0	5.1	1.8	virginica

combine(groupby(iris, :Species), :Sepal_Length => mean)

3×2 DataFrame