title: Matplotlib style not working in pandas bar plot
body: <p>The code I used to produce the bar plot as per <a href="https://pandas-docs.github.io/pandas-docs-travis/visualization.html" rel="nofollow noreferrer">pandas Visualization  tutorial</a>.</p>
  
  <pre><code>import pandas as pd
  import matplotlib.pyplot as plt
  import numpy as np
  
  plt.style.use('ggplot')
  
  np.random.seed(123456)
  ts = pd.Series(np.random.randn(1000), index=pd.date_range('1/1/2000', periods=1000))
  ts = ts.cumsum()
  df = pd.DataFrame(np.random.randn(1000, 4), index=ts.index, columns=list('ABCD'))
  df = df.cumsum()
  
  plt.figure()
  df.ix[5].plot(kind='bar'); plt.axhline(0, color='k')
  plt.show()
  </code></pre>
  
  <p>I get:</p>
  
  <p><img src="https://i.stack.imgur.com/TJKp0.png" alt="bar plot with matplotlib default colours when ggplot colours expected"></p>
  
  <p>I was expecting to get the bar colours as in the tutorial (vermilion), instead the bars are the default matplotlib blue colour.</p>
  
  <p>I suspect the problem is in pandas. Colours are correct when pandas is not used.</p>
  
  <pre><code>import matplotlib.pyplot as plt
  import numpy as np
  
  plt.style.use('ggplot')
  
  fig, ax = plt.subplots()
  x = np.arange(5)
  y1, y2 = np.random.randint(1, 25, size=(2, 5))
  width = 0.25
  ax.bar(x, y1, width)
  ax.bar(x + width, y2, width)
  ax.set_xticks(x + width)
  ax.set_xticklabels(['a', 'b', 'c', 'd', 'e'])
  
  plt.show()
  </code></pre>
  
  <p>I created my environment using conda.</p>
  
  <pre><code>In [22]: pd.__version__
  Out[22]: u'0.17.1'
  </code></pre>
  
  <p>How can I get pandas plot the right colours?</p>