We shall learn about visualizing the data in a later chapter. For now, let's try loading two sample datasets and building a basic plot. First, install the sklearn library from which we shall load the data using the following command:

$ pip3 install scikit-learn 

Import the datasets using the following command:

from sklearn.datasets import load_iris 
from sklearn.datasets import load_boston 

Import the Matplotlib plotting module:

from matplotlib import pyplot as plt 
%matplotlib inline 

Load the iris dataset, print the description of the dataset, and plot column 1 (sepal length) as x and column 2 (sepal width) as y:

iris = load_iris() 
print(iris.DESCR) 
data=iris.data 
plt.plot(data[:,0],data[:,1],".") 

The resulting plot will look like the following image:

Load the boston dataset, print the description of the dataset and plot column 3 (proportion of non-retail business) as x and column 5 (nitric oxide concentration) as y, each point on the plot marked with a + sign:

boston = load_boston()
print(boston.DESCR)
data=boston.data
plt.plot(data[:,2],data[:,4],"+")

The resulting plot will look like the following image: