visualize a dataset using seaborn

we will use this example iris_visualization.py

seaborn is a python data visualization library based on matplotlib

we will load the iris dataset
The iris dataset consists of measurements of three types of Iris flowers: Iris Setosa, Iris Versicolor, and Iris Virginica.
Four features were measured from each sample: the length and the width of the sepals and petals, in centimeters.
We will visualize the relationship between the 4 features for each of three species of Iris

>>> import seaborn as sns
>>> import matplotlib.pyplot as plt
>>> # load the iris dataset
>>> iris = sns.load_dataset("iris")
>>> # return the first 10 rows
>>> iris.head(10)
   sepal_length  sepal_width  petal_length  petal_width species
0           5.1          3.5           1.4          0.2  setosa
1           4.9          3.0           1.4          0.2  setosa
2           4.7          3.2           1.3          0.2  setosa
3           4.6          3.1           1.5          0.2  setosa
4           5.0          3.6           1.4          0.2  setosa
5           5.4          3.9           1.7          0.4  setosa
6           4.6          3.4           1.4          0.3  setosa
7           5.0          3.4           1.5          0.2  setosa
8           4.4          2.9           1.4          0.2  setosa
9           4.9          3.1           1.5          0.1  setosa
>>> # visualize the relationship between the 4 features for each of three species of Iris
>>> sns.pairplot(iris, hue='species', height=1.5)
<seaborn.axisgrid.PairGrid object at 0x7fb899ed15f8>
>>> plt.show()

$ ls seaborn-data/
iris.csv
$ head -10 seaborn-data/iris.csv
sepal_length,sepal_width,petal_length,petal_width,species
5.1,3.5,1.4,0.2,setosa
4.9,3.0,1.4,0.2,setosa
4.7,3.2,1.3,0.2,setosa
4.6,3.1,1.5,0.2,setosa
5.0,3.6,1.4,0.2,setosa
5.4,3.9,1.7,0.4,setosa
4.6,3.4,1.4,0.3,setosa
5.0,3.4,1.5,0.2,setosa
4.4,2.9,1.4,0.2,setosa