Dynamically update plot in iPython notebook

As referred in this question, I am trying to update a plot dynamically in an iPython notebook (in one cell). The difference is that I don't want to plot new lines, but that my x_data and y_data are growing at each iteration of some loop.

What I'd like to do is:

import numpy as np
import time
plt.axis([0, 10, 0, 100]) # supoose I know what the limits are going to be
plt.ion()
plt.show()
x = []
y = []
for i in range(10):
     x = np.append(x, i)
     y = np.append(y, i**2)
     # update the plot so that it shows y as a function of x
     time.sleep(0.5)

but I want the plot to have a legend, and if I do

from IPython import display
import time
import numpy as np
plt.axis([0, 10, 0, 100]) # supoose I know what the limits are going to be
plt.ion()
plt.show()
x = []
y = []
for i in range(10):
    x = np.append(x, i)
    y = np.append(y, i**2)
    plt.plot(x, y, label="test")
    display.clear_output(wait=True)
    display.display(plt.gcf())
    time.sleep(0.3)
plt.legend()

I end up with a legend which contains 10 items. If I put the plt.legend() inside the loop, the legend grows at each iteration... Any solution?

Currently, you are creating a new Axes object for every time you plt.plot in the loop.

So, if you clear the current axis (plt.gca().cla()) before you use plt.plot, and put the legend inside the loop, it works without the legend growing each time:

import numpy as np
import time
from IPython import display

x = []
y = []
for i in range(10):
    x = np.append(x, i)
    y = np.append(y, i**2)
    plt.gca().cla() 
    plt.plot(x,y,label='test')
    plt.legend()
    display.clear_output(wait=True)
    display.display(plt.gcf()) 
    time.sleep(0.5)

EDIT: As @tcaswell pointed out in comments, using the %matplotlib notebook magic command gives you a live figure which can update and redraw.