matplotlib also provides a specific function to generate scatter plots. It basically works in
the same way, but provides some additional features. Figure 5-14 shows the corresponding
scatter plot to Figure 5-13, this time generated using the scatter function:
In [ 18 ]: plt.figure(figsize=( 7 , 5 ))
plt.scatter(y[:, 0 ], y[:, 1 ], marker=‘o’)
plt.grid(True)
plt.xlabel(‘1st’)
plt.ylabel(‘2nd’)
plt.title(‘Scatter Plot’)
Figure 5-14. Scatter plot via scatter function
The scatter plotting function, for example, allows the addition of a third dimension,
which can be visualized through different colors and be described by the use of a color
bar. To this end, we generate a third data set with random data, this time with integers
between 0 and 10:
In [ 19 ]: c = np.random.randint( 0 , 10 , len(y))
Figure 5-15 shows a scatter plot where there is a third dimension illustrated by different
colors of the single dots and with a color bar as a legend for the colors:
In [ 20 ]: plt.figure(figsize=( 7 , 5 ))
plt.scatter(y[:, 0 ], y[:, 1 ], c=c, marker=‘o’)
plt.colorbar()
plt.grid(True)
plt.xlabel(‘1st’)
plt.ylabel(‘2nd’)
plt.title(‘Scatter Plot’)
