DataFrame.from_records() converts mx.DateTime to string
python version: 2.7.5
pandas version: 0.12.0
numpy version: 1.7.1
psycopg2 version: 2.5.1

I observe this as I parse the result set from Postgres (my psycopg2 installation is configured to return mx.DateTimes).  The ideal scenario is that these objects are converted to numpy.datetime64 along with appropriate time zone info as this will allow the user to follow all the pandas time series tutorials.   Keeping the mx.DateTime objects as objects rather than string would be a second best option because we can build a wrapper to write out the string representation in a form easily parsable by numpy.datetime64.  Alternatively, we may be able to construct datetime64 using the API bypassing strings altogether.

Converting to strings as it is currently implemented is particularly hellish because the numpy datetime64 object converts to UTC when parsing from the string format extracted by from_records.

For example, the string representation returned by from_records is:
2013-07-29 17:32:53-07

However, when I parse this value in datetime64, what is returned is:
2013-07-30 00:32:53

However, I see from the datetime64 tutorials that with other formats the datetime64 object will represent the time zone.  I see no documentation on how to convert time zones once the datetime64 object is constructed.

Even if I wanted to parse the more stable datetime.datetime module for the purposes of converting over to datetime64 that "-07" is not part of the %z pattern which expects an extra two digits.  

In summary, If the user has access to the original mx.DateTime objects returned by psycopg2 the user can most likely solve their own problems regarding the conversion to datetime64 or other formats.  I wonder how other types returned by psycopg2 might be affected by the current implementation.
