title: Can pandas plot a time-series without trying to convert the index to Periods?
body: <p>When plotting a time-series, I observe an unusual behavior, which eventually results in not being able to format the xticks of the plot.
  It seems that pandas internally tries to convert the index into a PeriodIndex, but obviously only succeeds if the timestamp values are equally spaced. If they are unevenly spaced (or - strangely - if they are evenly spaced but timezone-aware) the index remains a DatetimeIndex.
  The latter case works as expected. I can set DateFormatter and Locators. If however the index is interally converted to a PeriodIndex before plotting, the x-axis of the resulting plott seems to be messed up.</p>
  
  <p>Here is an Example to reproduce the problem.</p>
  
  <pre><code>from pandas import Series, DataFrame
  import pandas as pd
  from datetime import datetime
  import pytz
  import matplotlib.pyplot as plt
  import matplotlib as mpl
  import numpy as np
  
  idx1 = np.array([datetime(2014, 1, 16, 0),
                   datetime(2014, 1, 16, 5),
                   datetime(2014, 1, 16, 10),
                   datetime(2014, 1, 16, 15), 
                   datetime(2014, 1, 16, 20), 
                   datetime(2014, 1, 17, 1)])
  idx2 = np.array([datetime(2014, 1, 16, 0),
                   datetime(2014, 1, 16, 5),
                   datetime(2014, 1, 16, 10),
                   datetime(2014, 1, 16, 15),
                   datetime(2014, 1, 16, 20),
                   datetime(2014, 1, 16, 23)])
  y = [0, 2, np.nan, 5, 2, 1]
  tz = pytz.timezone('Europe/Berlin')
  
  fig, (ax1, ax2, ax3) = plt.subplots(1,3, figsize=(15,4))
  
  # index convertible to period index
  s1 = Series(y, index=idx1)
  s1.plot(ax=ax1)
  print ax1.get_xticks()
  print ax1.xaxis.get_major_locator()
  print ax1.xaxis.get_major_formatter()
  #ax1.xaxis.set_major_formatter(mpl.dates.DateFormatter('%H'))
  #ax1.xaxis.set_major_locator(mpl.ticker.MultipleLocator(0.25))
  
  # index not convertible to period index
  s2 = Series(y, index=idx2)
  s2.plot(ax=ax2)
  print ax2.get_xticks()
  #ax2.xaxis.set_major_formatter(mpl.dates.DateFormatter('%H'))
  #ax2.xaxis.set_major_locator(mpl.ticker.MultipleLocator(0.25))
  
  # index convertible to period index but tz-aware
  s3 = Series(y, index=idx1)
  s3 = s3.tz_localize(tz)
  s3.plot(ax=ax3)
  print ax3.get_xticks()
  #ax2.xaxis.set_major_formatter(mpl.dates.DateFormatter('%H'))
  #ax2.xaxis.set_major_locator(mpl.ticker.MultipleLocator(0.25))
  
  fig.autofmt_xdate()  # just temporarily
  
  plt.tight_layout()
  plt.show(block=False)
  </code></pre>
  
  <p>Is there a way to tell pandas to keep the index in its original format and not to convert it to Periods? Any ideas how to deal with this are greatly appreciated!</p>
  
  <p>I use pandas 0.13 and matplotlib 1.3.1</p>
  
  <p>As a sidenote:<br> 
  It would of course be great if the timezones were not converted all to UTC. However I realize this problem may still persist for a while. But if anyone has a hint for a workaround I'd be glad to hear (I tried passing a tz directly to the DateFormatter. That works, but the Locators don't seem to like it much).</p>