title: Plotting datetimeindex on x-axis with matplotlib creates wrong ticks in pandas 0.15 in contrast to 0.14
body: <p>I create a simple pandas dataframe with some random values and a DatetimeIndex like so:</p>
  
  <pre><code>import pandas as pd
  from numpy.random import randint
  import datetime as dt
  import matplotlib.pyplot as plt
  
  # create a random dataframe with datetimeindex
  dateRange = pd.date_range('1/1/2011', '3/30/2011', freq='D')
  randomInts = randint(1, 50, len(dateRange))
  df = pd.DataFrame({'RandomValues' : randomInts}, index=dateRange)
  </code></pre>
  
  <p>Then I plot it in two different ways:</p>
  
  <pre><code># plot with pandas own matplotlib wrapper
  df.plot()
  
  # plot directly with matplotlib pyplot
  plt.plot(df.index, df.RandomValues)
  
  plt.show()
  </code></pre>
  
  <p>(Do not use both statements at the same time as they plot on the same figure.)</p>
  
  <p>I use <strong>Python 3.4 64bit</strong> and <strong>matplotlib 1.4</strong>. With <strong>pandas 0.14</strong>, both statements give me the expected plot (they use slightly different formatting of the x-axis which is okay; note that data is random so the plots do not look the same):
  <img src="https://i.stack.imgur.com/XhIQF.png" alt="pandas 0.14: pandas plot"></p>
  
  <p><img src="https://i.stack.imgur.com/9TOQ1.png" alt="pandas 0.14: matplotlib plot"></p>
  
  <p>However, when using <strong>pandas 0.15</strong>, the pandas plot looks alright but the matplotlib plot has some strange tick format on the x-axis:</p>
  
  <p><img src="https://i.stack.imgur.com/jm5c5.png" alt="pandas 0.15: pandas plot"></p>
  
  <p><img src="https://i.stack.imgur.com/l9zUe.png" alt="pandas 0.15: matplotlib plot"></p>
  
  <p>Is there any good reason for this behaviour and why it has changed from pandas 0.14 to 0.15?</p>