Suppose you have multiple lines in the same plot, each of a different color, and
you wish to make a legend to tell what each line represents. You can do this
by passing on a label to each of the lines when you call
plot(), e.g., the
following line will be labelled "My Line 1".
ax.plot(x, y1, color="red", label="My Line 1")
This specifies the text that will appear in the legend for that line. Now to
make the actual legend visible, we can call
By default it will create a legend inside a box on the upper right hand corner
of the plot. You can pass arguments to
legend() to customize it. For instance
we can position it on the lower right hand corner, with out a frame box
surrounding it, and creating a title for the legend by calling the following:
ax.legend(loc="lower right", title="Legend Title", frameon=False)
Below is an example:
import matplotlib.pyplot as plt # The data x = [1, 2, 3] y1 = [2, 15, 27] y2 = [10, 40, 45] y3 = [5, 25, 40] # Initialize the figure and axes fig, ax = plt.subplots(1, figsize=(8, 6)) # Set the title for the figure fig.suptitle('Simple Legend Example ', fontsize=15) # Draw all the lines in the same plot, assigning a label for each one to be # shown in the legend ax.plot(x, y1, color="red", label="My Line 1") ax.plot(x, y2, color="green", label="My Line 2") ax.plot(x, y3, color="blue", label="My Line 3") # Add a legend with title, position it on the lower right (loc) with no box framing (frameon) ax.legend(loc="lower right", title="Legend Title", frameon=False) # Show the plot plt.show()
Sometimes it is necessary or desirable to place the legend outside the plot. The following code shows how to do it.
import matplotlib.pylab as plt fig, ax = plt.subplots(1, 1, figsize=(10,6)) # make the figure with the size 10 x 6 inches fig.suptitle('Example of a Legend Being Placed Outside of Plot') # The data x = [1, 2, 3] y1 = [1, 2, 4] y2 = [2, 4, 8] y3 = [3, 5, 14] # Labels to use for each line line_labels = ["Item A", "Item B", "Item C"] # Create the lines, assigning different colors for each one. # Also store the created line objects l1 = ax.plot(x, y1, color="red") l2 = ax.plot(x, y2, color="green") l3 = ax.plot(x, y3, color="blue") fig.legend([l1, l2, l3], # List of the line objects labels= line_labels, # The labels for each line loc="center right", # Position of the legend borderaxespad=0.1, # Add little spacing around the legend box title="Legend Title") # Title for the legend # Adjust the scaling factor to fit your legend text completely outside the plot # (smaller value results in more space being made for the legend) plt.subplots_adjust(right=0.85) plt.show()
Another way to place the legend outside the plot is to use
bbox_inches='tight', as shown in the example below:
import matplotlib.pyplot as plt # Data all_x = [10,20,30] all_y = [[1,3], [1.5,2.9],[3,2]] # Plot fig = plt.figure(1) ax = fig.add_subplot(111) ax.plot(all_x, all_y) # Add legend, title and axis labels lgd = ax.legend([ 'Lag ' + str(lag) for lag in all_x], loc='center right', bbox_to_anchor=(1.3, 0.5)) ax.set_title('Title') ax.set_xlabel('x label') ax.set_ylabel('y label') fig.savefig('image_output.png', dpi=300, format='png', bbox_extra_artists=(lgd,), bbox_inches='tight')
Sometimes you will have a grid of subplots, and you want to have a single legend that describes all the lines for each of the subplots as in the following image.
In order to do this, you will need to create a global legend for the figure
instead of creating a legend at the axes level (which will create a separate
legend for each subplot). This is achieved by calling
fig.legend() as can be
seen in the code for the following code.
fig, (ax1, ax2, ax3) = plt.subplots(1, 3, figsize=(10,4)) fig.suptitle('Example of a Single Legend Shared Across Multiple Subplots') # The data x = [1, 2, 3] y1 = [1, 2, 3] y2 = [3, 1, 3] y3 = [1, 3, 1] y4 = [2, 2, 3] # Labels to use in the legend for each line line_labels = ["Line A", "Line B", "Line C", "Line D"] # Create the sub-plots, assigning a different color for each line. # Also store the line objects created l1 = ax1.plot(x, y1, color="red") l2 = ax2.plot(x, y2, color="green") l3 = ax3.plot(x, y3, color="blue") l4 = ax3.plot(x, y4, color="orange") # A second line in the third subplot # Create the legend fig.legend([l1, l2, l3, l4], # The line objects labels=line_labels, # The labels for each line loc="center right", # Position of legend borderaxespad=0.1, # Small spacing around legend box title="Legend Title" # Title for the legend ) # Adjust the scaling factor to fit your legend text completely outside the plot # (smaller value results in more space being made for the legend) plt.subplots_adjust(right=0.85) plt.show()
Something to note about the above example is the following:
l1 = ax1.plot(x, y1, color="red")
plot() is called, it returns a list of line2D objects. In this case it
just returns a list with one single line2D object, which is extracted with the
 indexing, and stored in
A list of all the line2D objects that we are interested in including in the
legend need to be passed on as the first argument to
fig.legend(). The second
fig.legend() is also necessary. It is supposed to be a list of
strings to use as the labels for each line in the legend.
The other arguments passed on to
fig.legend() are purely optional, and just
help with fine-tuning the aesthetics of the legend.
If you call
ax.legend() more than once, the first legend is removed and a new one is drawn. According the official documentation:
This has been done so that it is possible to call legend() repeatedly to update the legend to the latest handles on the Axes
Fear not, though: It is still quite simple to add a second legend (or third, or fourth...) to an axes. In the example here, we plot two lines, then plot markers on their respective maxima and minima. One legend is for the lines, and the other is for the markers.
import matplotlib.pyplot as plt import numpy as np # Generate data for plotting: x = np.linspace(0,2*np.pi,100) y0 = np.sin(x) y1 = .9*np.sin(.9*x) # Find their maxima and minima and store maxes = np.empty((2,2)) mins = np.empty((2,2)) for k,y in enumerate([y0,y1]): maxloc = y.argmax() maxes[k] = x[maxloc], y[maxloc] minloc = y.argmin() mins[k] = x[minloc], y[minloc] # Instantiate figure and plot fig = plt.figure() ax = fig.add_subplot(111) ax.plot(x,y0, label='y0') ax.plot(x,y1, label='y1') # Plot maxima and minima, and keep references to the lines maxline, = ax.plot(maxes[:,0], maxes[:,1], 'r^') minline, = ax.plot(mins[:,0], mins[:,1], 'ko') # Add first legend: only labeled data is included leg1 = ax.legend(loc='lower left') # Add second legend for the maxes and mins. # leg1 will be removed from figure leg2 = ax.legend([maxline,minline],['max','min'], loc='upper right') # Manually add the first legend back ax.add_artist(leg1)
The key is to make sure you have references to the legend objects. The first one you instantiate (
leg1) is removed from the figure when you add the second one, but the
leg1 object still exists and can be added back with
The really great thing is that you can can still manipulate both legends. For example, add the following to the bottom of the above code:
Finally, it's worth mentioning that in the example only the lines were given labels when plotted, meaning that
ax.legend() adds only those lines to the
leg1. The legend for the markers (
leg2) therefore required the lines and labels as arguments when it was instantiated. We could have, alternatively, given labels to the markers when they were plotted too. But then both calls to
ax.legend would have required some extra arguments so that each legend contained only the items we wanted.