Use `pd.Timestamp` for parsing and representing points in time.

[eike-welk]

Currently times are represented by datetime.datetime objects; while parsing string representations of times is done with the library dateutil. However Pandas converts datetime.datetime to pd.Timestamp, and represents times internally as integers. Furthermore pd.Timestamp can automatically and comfortably parse string representations of times.

Therefore port all date computations to pd.Timestamp.

Empty series should be filled with NaN or numpy.datetime64('NaT'), not with None.

http://pandas.pydata.org/pandas-docs/dev/missing_data.html#datetimes

http://docs.scipy.org/doc/numpy-dev/reference/arrays.datetime.html

and discussion at end:

https://github.com/pydata/pandas/issues/3593#issuecomment-17850876

[eike-welk]

Done. Times are now repesented as series of Datetime64 objects. Dates from Ebay are parsed by pd.Timestamp.