BUG: HDF5 not reading or writing datetime64 correctly (Panel)
I'm trying to pin down where this is happening still, maybe you'll be able to tell by looking at the values:

``` python
In [10]: a['timestamp'].head()
Out[10]: 
                                               1                   2  \
HRHHID      HUHHNUM PULINENO                                           
45004066531 1       1        1996-12-01 00:00:00 1997-01-01 00:00:00   
                    2        1996-12-01 00:00:00 1997-01-01 00:00:00   
                    3        1996-12-01 00:00:00 1997-01-01 00:00:00   
                    4        1996-12-01 00:00:00 1997-01-01 00:00:00   
                    5        1996-12-01 00:00:00 1997-01-01 00:00:00   


In [13]: a.to_hdf(tst, '/m1996_12', append=False)
/Users/tom/Envs/statsmodels/lib/python2.7/site-packages/pandas-0.12.0_1098_g705b677-py2.7-macosx-10.8-x86_64.egg/pandas/io/pytables.py:2339: PerformanceWarning: 
your performance may suffer as PyTables will pickle object types that it cannot
map directly to c-types [inferred_type->mixed,key->axis0] [items->None]

  warnings.warn(ws, PerformanceWarning)
/Users/tom/Envs/statsmodels/lib/python2.7/site-packages/pandas-0.12.0_1098_g705b677-py2.7-macosx-10.8-x86_64.egg/pandas/io/pytables.py:2339: PerformanceWarning: 
your performance may suffer as PyTables will pickle object types that it cannot
map directly to c-types [inferred_type->mixed,key->block1_items] [items->None]

  warnings.warn(ws, PerformanceWarning)
/Users/tom/Envs/statsmodels/lib/python2.7/site-packages/pandas-0.12.0_1098_g705b677-py2.7-macosx-10.8-x86_64.egg/pandas/io/pytables.py:2339: PerformanceWarning: 
your performance may suffer as PyTables will pickle object types that it cannot
map directly to c-types [inferred_type->mixed,key->block2_values] [items->['flow', 'unemployed_history', 'nonemployed_history', 'either_history']]

  warnings.warn(ws, PerformanceWarning)

In [14]: tst.select('/m1996_12')['timestamp'].head()
Out[14]: 
                                               1                   2  \
HRHHID      HUHHNUM PULINENO                                           
45004066531 1       1        2086-12-01 00:00:00 2087-01-01 00:00:00   
                    2        2086-12-01 00:00:00 2087-01-01 00:00:00   
                    3        2086-12-01 00:00:00 2087-01-01 00:00:00   
                    4        2086-12-01 00:00:00 2087-01-01 00:00:00   
                    5        2086-12-01 00:00:00 2087-01-01 00:00:00   

```

I was thinking it was the `NaT`s (and it may still be) by I wasn't able to reproduce with a simple Panel.

[link](https://www.dropbox.com/s/o0qmwhh2rsy1b18/tst_comp.h5) (90 MB) to the file.

To get the correct dates, I'm using the following:

https://gist.github.com/TomAugspurger/7458121

just call `fix_timestamp` on the Panel and it modifies it in place.
In [29]: pd.**version**
Out[29]: '0.12.0-1098-g705b677'

In [30]: np.**version**
Out[30]: '1.7.1'
