title: Losing timezone-awareness when saving hyerarchical pandas DatetimeIndex to hdf5 in Python
body: <p>I'm on pandas 0.14.1. Assume I need to index data by two timestamps in a hierarchical index using timezones. When saving the resulted DataFrame to hdf5 I seem to lose timezone-awareness:</p>
  
  <pre><code>import pandas as pd
  dti1 = pd.DatetimeIndex(start=pd.Timestamp('20000101'), end=pd.Timestamp('20000102'), freq='D', tz='EST5EDT')
  dti2 = pd.DatetimeIndex(start=pd.Timestamp('20000102'), end=pd.Timestamp('20000103'), freq='D', tz='EST5EDT')
  mux = pd.MultiIndex.from_arrays([dti1, dti2])
  df = pd.DataFrame(0, index=mux, columns=['a'])
  </code></pre>
  
  <p>Here <code>df</code> has timezones:</p>
  
  <pre><code>                                                     a
  2000-01-01 00:00:00-05:00 2000-01-02 00:00:00-05:00  0
  2000-01-02 00:00:00-05:00 2000-01-03 00:00:00-05:00  0
  </code></pre>
  
  <p>After saving and loading to hdf5, timezone information seems to disappear:</p>
  
  <pre><code>df.to_hdf('/tmp/my.h5', 'data')
  pd.read_hdf('/tmp/my.h5', 'data')
  </code></pre>
  
  <p>results in:</p>
  
  <pre><code>                                         a
  2000-01-01 05:00:00 2000-01-02 05:00:00  0
  2000-01-02 05:00:00 2000-01-03 05:00:00  0
  </code></pre>
  
  <p>I wonder if there is a good workaround and whether this is a know bug.</p>