How do I assign multiple labels at once in matplotlib?

Question

I have the following dataset:

x = [0, 1, 2, 3, 4] y = [ [0, 1, 2, 3, 4],       [5, 6, 7, 8, 9],       [9, 8, 7, 6, 5] ] 

Now I plot it with:

import matplotlib.pyplot as plt plt.plot(x, y) 

However, I want to label the 3 y-datasets with this command, which raises an error when .legend() is called:

lineObjects = plt.plot(x, y, label=['foo', 'bar', 'baz']) plt.legend()  File "./plot_nmos.py", line 33, in <module>   plt.legend() ... AttributeError: 'list' object has no attribute 'startswith' 

When I inspect the lineObjects:

>>> lineObjects[0].get_label() ['foo', 'bar', 'baz'] >>> lineObjects[1].get_label() ['foo', 'bar', 'baz'] >>> lineObjects[2].get_label() ['foo', 'bar', 'baz'] 

Question

Is there an elegant way to assign multiple labels by just using the .plot() method?

Answer 1

You can iterate over your line objects list, so labels are individually assigned. An example with the built-in python iter function:

lineObjects = plt.plot(x, y) plt.legend(iter(lineObjects), ('foo', 'bar', 'baz'))` 

Edit: after updating to matplotlib 1.1.1, it looks like the plt.plot(x, y), with y as a list of lists (as provided by the author of the question), doesn't work anymore. The one step plotting without iteration over the y arrays is still possible thought after passing y as numpy.array (assuming (numpy)[http://numpy.scipy.org/] as been previously imported).

In this case, use plt.plot(x, y) (if the data in the 2D y array are arranged as columns [axis 1]) or plt.plot(x, y.transpose()) (if the data in the 2D y array are arranged as rows [axis 0])

Edit 2: as pointed by @pelson (see commentary below), the iter function is unnecessary and a simple plt.legend(lineObjects, ('foo', 'bar', 'baz')) works perfectly