title: Matplotlib showing x-tick labels overlapping
body: <p>Have a look at the graph below:
  <img src="https://i.stack.imgur.com/paHpG.png" alt="enter image description here"></p>
  
  <p>It's a subplot of this larger figure:
  <img src="https://i.stack.imgur.com/q8M8w.png" alt="enter image description here"></p>
  
  <p>I see two problems with it.  First, the x-axis labels overlap with one another (this is my major issue).  Second. the location of the x-axis minor gridlines seems a bit wonky.  On the left of the graph, they look properly spaced.  But on the right, they seem to be crowding the major gridlines...as if the major gridline locations aren't proper multiples of the minor tick locations.</p>
  
  <p>My setup is that I have a DataFrame called <code>df</code> which has a <code>DatetimeIndex</code> on the rows and a column called <code>value</code> which contains floats.  I can provide an example of the <code>df</code> contents in a gist if necessary.  A dozen or so lines of <code>df</code> are at the bottom of this post for reference.</p>
  
  <p>Here's the code that produces the figure:</p>
  
  <pre><code>now = dt.datetime.now()
  
  fig, axes = plt.subplots(2, 2, figsize=(15, 8), dpi=200)
  for i, d in enumerate([360, 30, 7, 1]):
      ax = axes.flatten()[i]
      earlycut = now - relativedelta(days=d)
      data = df.loc[df.index&gt;=earlycut, :]
      ax.plot(data.index, data['value'])
      ax.xaxis_date()
  
      ax.get_xaxis().set_minor_locator(mpl.ticker.AutoMinorLocator())
      ax.get_yaxis().set_minor_locator(mpl.ticker.AutoMinorLocator())
  
      ax.grid(b=True, which='major', color='w', linewidth=1.5)
      ax.grid(b=True, which='minor', color='w', linewidth=0.75)
  </code></pre>
  
  <p>What is my best option here to get the x-axis labels to stop overlapping each other (in each of the four subplots)?  Also, separately (but less urgently), what's up with the minor tick issue in the top-left subplot?</p>
  
  <p>I am on Pandas 0.13.1, numpy 1.8.0, and matplotlib 1.4.x.</p>
  
  <p>Here's a small snippet of <code>df</code> for reference:</p>
  
  <pre><code>                                    id scale  tempseries_id    value
  timestamp                                                           
  2014-11-02 14:45:10.302204+00:00  7564     F              1  68.0000
  2014-11-02 14:25:13.532391+00:00  7563     F              1  68.5616
  2014-11-02 14:15:12.102229+00:00  7562     F              1  68.9000
  2014-11-02 14:05:13.252371+00:00  7561     F              1  69.0116
  2014-11-02 13:55:11.792191+00:00  7560     F              1  68.7866
  2014-11-02 13:45:10.782227+00:00  7559     F              1  68.6750
  2014-11-02 13:35:10.972248+00:00  7558     F              1  68.4500
  2014-11-02 13:25:10.362213+00:00  7557     F              1  68.1116
  2014-11-02 13:15:10.822247+00:00  7556     F              1  68.2250
  2014-11-02 13:05:10.102200+00:00  7555     F              1  68.5616
  2014-11-02 12:55:10.292217+00:00  7554     F              1  69.0116
  2014-11-02 12:45:10.382226+00:00  7553     F              1  69.3500
  2014-11-02 12:35:10.642245+00:00  7552     F              1  69.2366
  2014-11-02 12:25:12.642255+00:00  7551     F              1  69.1250
  2014-11-02 12:15:11.122382+00:00  7550     F              1  68.7866
  2014-11-02 12:05:11.332224+00:00  7549     F              1  68.5616
  2014-11-02 11:55:11.662311+00:00  7548     F              1  68.2250
  2014-11-02 11:45:11.122193+00:00  7547     F              1  68.4500
  2014-11-02 11:35:11.162271+00:00  7546     F              1  68.7866
  2014-11-02 11:25:12.102211+00:00  7545     F              1  69.2366
  2014-11-02 11:15:10.422226+00:00  7544     F              1  69.4616
  2014-11-02 11:05:11.412216+00:00  7543     F              1  69.3500
  2014-11-02 10:55:10.772212+00:00  7542     F              1  69.1250
  2014-11-02 10:45:11.332220+00:00  7541     F              1  68.7866
  2014-11-02 10:35:11.332232+00:00  7540     F              1  68.5616
  2014-11-02 10:25:11.202411+00:00  7539     F              1  68.2250
  2014-11-02 10:15:11.932326+00:00  7538     F              1  68.5616
  2014-11-02 10:05:10.922229+00:00  7537     F              1  68.9000
  2014-11-02 09:55:11.602357+00:00  7536     F              1  69.3500
  </code></pre>
  
  <p>Edit: Trying <code>fig.autofmt_xdate()</code>:
  I don't think this going to do the trick.  This seems to use the same x-tick labels for both graphs on the left and also for both graphs on the right.  Which is not correct given my data.  Please see the problematic output below:</p>
  
  <p><img src="https://i.stack.imgur.com/cY6po.png" alt="enter image description here"></p>