Instead of the default "boxed" axis style I want to have only the left and bottom axis, i.e.:
+------+ | | | | | | ---> | | | | +------+ +------- This should be easy, but I can't find the necessary options in the docs.
This is the suggested Matplotlib 2.0 solution from the official website HERE:
import numpy as np import matplotlib.pyplot as plt x = np.linspace(0, 2*np.pi, 100) y = np.sin(x) ax = plt.subplot(111) ax.plot(x, y) # Hide the right and top spines ax.spines['right'].set_visible(False) ax.spines['top'].set_visible(False) # Only show ticks on the left and bottom spines ax.yaxis.set_ticks_position('left') ax.xaxis.set_ticks_position('bottom') plt.show() 
Alternatively, this
def simpleaxis(ax): ax.spines['top'].set_visible(False) ax.spines['right'].set_visible(False) ax.get_xaxis().tick_bottom() ax.get_yaxis().tick_left() seems to achieve the same effect on an axis without losing rotated label support.
(Matplotlib 1.0.1; solution inspired by this).
[edit] matplotlib in now (2013-10) on version 1.3.0 which includes this
That ability was actually just added, and you need the Subversion version for it. You can see the example code here.
I am just updating to say that there's a better example online now. Still need the Subversion version though, there hasn't been a release with this yet.
[edit] Matplotlib 0.99.0 RC1 was just released, and includes this capability.
If you don't need ticks and such (e.g. for plotting qualitative illustrations) you could also use this quick workaround:
Make the axis invisible (e.g. with plt.gca().axison = False) and then draw them manually with plt.arrow.
(This is more of an extension comment, in addition to the comprehensive answers here.)
Note that we can hide each of these three elements independently of each other:
To hide the border (aka "spine"): ax.set_frame_on(False) or ax.spines['top'].set_visible(False)
To hide the ticks: ax.tick_params(top=False)
To hide the labels: ax.tick_params(labeltop=False)
This is much more rudimentary, but might do the trick:
remove_border()