How to do it...

1. The main command in matplotlib, in pseudo code, is as follows:

plt.plot(numpy array, numpy array of same length)

1. Plot a straight line by placing two NumPy arrays of the same length:

plt.plot(np.arange(10), np.arange(10))

1. Plot an exponential:

plt.plot(np.arange(10), np.exp(np.arange(10)))

1. Place the two graphs side by side:

plt.figure()
plt.subplot(121)
plt.plot(np.arange(10), np.exp(np.arange(10)))
plt.subplot(122)
plt.scatter(np.arange(10), np.exp(np.arange(10)))

Or top to bottom:

plt.figure()
plt.subplot(211)
plt.plot(np.arange(10), np.exp(np.arange(10)))
plt.subplot(212)
plt.scatter(np.arange(10), np.exp(np.arange(10)))

The first two numbers in the subplot command refer to the grid size in the figure instantiated by plt.figure(). The grid size referred to in plt.subplot(221) is 2 x 2, the first two digits. The last digit refers to traversing the grid in reading order: left to right and then up to down.

1. Plot in a 2 x 2 grid traversing in reading order from one to four:

plt.figure()
plt.subplot(221)
plt.plot(np.arange(10), np.exp(np.arange(10)))
plt.subplot(222)
plt.scatter(np.arange(10), np.exp(np.arange(10)))
plt.subplot(223)
plt.scatter(np.arange(10), np.exp(np.arange(10)))
plt.subplot(224)
plt.scatter(np.arange(10), np.exp(np.arange(10)))

1. Finally, with real data:

from sklearn.datasets import load_iris

iris = load_iris()
data = iris.data
target = iris.target

# Resize the figure for better viewing
plt.figure(figsize=(12,5))

# First subplot
plt.subplot(121)

# Visualize the first two columns of data:
plt.scatter(data[:,0], data[:,1], c=target)

# Second subplot
plt.subplot(122)

# Visualize the last two columns of data:
plt.scatter(data[:,2], data[:,3], c=target)

The c parameter takes an array of colors—in this case, the colors 0, 1, and 2 in the iris target: