I was doing some Googling to look for a way to solve a

    > problem controlling sharex, and came across an example
    > using axprops. This solved my problem, but now I wonder
    > what other aspects I can control with axprops, or other
    > similar methods. Where is axprops documented? I've looked
    > via pydoc, and in the pdf documentation, but no dice.

axprops is simply a dictionary holding key/value pairs. It is not
part of the matplotlib API. Any function that takes keyword
arguments, such as the Axes constructor, can take a dictionary with
keyword/value pairs using the following syntax

  a = Axes(fig, rect, **d)

where d is a dictionary. This is part of python, not matplotlib
proper, but because matplotlib makes extensive use of keyword
arguments, it is a handy trick to remember. When I am creating
several axes with shared properties, I often use it to have a single
customization point

axprops = dict(axisbg='yellow', xlim=(0,1))

for i in range(N):
   fig.add_subplot(N,1,i+1, **axprops)

or something like that.

But I don't think this solves your problem: you can use this to turn
on the sharex feature but not to turn it off once it is already on.

As for your question about where to find the aspects of the Axes that
can be controlled this way, you can do it by consulting the class
documentation at and
looking for methods that start with "set_" or by firing up an
interactive shell (see and
using setp introspection

In [2]: ax = subplot(111)

In [3]: setp(ax)
    adjustable: ['box' | 'datalim']
    alpha: float
    anchor: ['C', 'SW', 'S', 'SE', 'E', 'NE', 'N', 'NW', 'W']
    animated: [True | False]
    aspect: ['auto' | 'equal' | aspect_ratio]
    autoscale_on: True|False
    axis_bgcolor: any matplotlib color - see help(colors)
    axis_off: void
    axis_on: void
    axisbelow: True|False
    clip_box: a matplotlib.transform.Bbox instance
    clip_on: [True | False]
    cursor_props: a (float, color) tuple
    figure: a Figure instance
    frame_on: True|False
    label: any string
    lod: [True | False]
    navigate: True|False
    navigate_mode: unknown
    position: len(4) sequence of floats
    title: str
    transform: a matplotlib.transform transformation instance
    visible: [True | False]
    xlabel: str
    xlim: len(2) sequence of floats
    xscale: ['log' | 'linear' ]
    xticklabels: sequence of strings
    xticks: sequence of floats
    ylabel: str
    ylim: len(2) sequence of floats
    yscale: ['log' | 'linear']
    yticklabels: sequence of strings
    yticks: sequence of floats
    zorder: any number