Legends and annotations

Legends are an important element that is used to identify the plot elements in a figure. The easiest way to show a legend inside a figure is to use the label argument of the plot function, and show the labels by calling the plt.legend() method:

>>> x = np.linspace(0, 1, 20) 
>>> y1 = np.sin(x)
>>> y2 = np.cos(x)
>>> y3 = np.tan(x)
>>> plt.plot(x, y1, 'c', label='y=sin(x)')
>>> plt.plot(x, y2, 'y', label='y=cos(x)')
>>> plt.plot(x, y3, 'r', label='y=tan(x)')
>>> plt.lengend(loc='upper left')
>>> plt.show()

The output for the preceding command as follows:

The loc argument in the legend command is used to figure out the position of the label box. There are several valid location options: lower left, right, upper left, lower center, upper right, center, lower right, upper right, center right, best, upper center, and center left. The default position setting is upper right. However, when we set an invalid location option that does not exist in the above list, the function automatically falls back to the best option.

If we want to split the legend into multiple boxes in a figure, we can manually set our expected labels for plot lines, as shown in the following image:

The output for the preceding command is as follows:

>>> p1 = plt.plot(x, y1, 'c', label='y=sin(x)')
>>> p2 = plt.plot(x, y2, 'y', label='y=cos(x)')
>>> p3 = plt.plot(x, y3, 'r', label='y=tan(x)')
>>> lsin = plt.legend(handles=p1, loc='lower right')
>>> lcos = plt.legend(handles=p2, loc='upper left')
>>> ltan = plt.legend(handles=p3, loc='upper right')
>>> # with above code, only 'y=tan(x)' legend appears in the figure
>>> # fix: add lsin, lcos as separate artists to the axes
>>> plt.gca().add_artist(lsin)
>>> plt.gca().add_artist(lcos)
>>> # automatically adjust subplot parameters to specified padding
>>> plt.tight_layout()
>>> plt.show()

The other element in a figure that we want to introduce is the annotations which can consist of text, arrows, or other shapes to explain parts of the figure in detail, or to emphasize some special data points. There are different methods for showing annotations, such as text, arrow, and annotation.

• The text method draws text at the given coordinates (x, y) on the plot; optionally with custom properties. There are some common arguments in the function: x, y, label text, and font-related properties that can be passed in via fontdict, such as family, fontsize, and style.
• The annotate method can draw both text and arrows arranged appropriately. Arguments of this function are s (label text), xy (the position of element to annotation), xytext (the position of the label s), xycoords (the string that indicates what type of coordinate xy is), and arrowprops (the dictionary of line properties for the arrow that connects the annotation).

Here is a simple example to illustrate the annotate and text functions:

>>> x = np.linspace(-2.4, 0.4, 20)
>>> y = x*x + 2*x + 1
>>> plt.plot(x, y, 'c', linewidth=2.0)
>>> plt.text(-1.5, 1.8, 'y=x^2 + 2*x + 1',
 fontsize=14, style='italic')
>>> plt.annotate('minima point', xy=(-1, 0),
 xytext=(-1, 0.3),
 horizontalalignment='center', 
 verticalalignment='top', 
 arrowprops=dict(arrowstyle='->', 
 connectionstyle='arc3'))
>>> plt.show()

The output for the preceding command is as follows: