Answer : Pandas timestamp differences returns a datetime.timedelta object. This can easily be converted into hours by using the *as_type* method, like so   import pandas df = pandas.DataFrame(columns=['to','fr','ans']) df.to = [pandas.Timestamp('2014-01-24 13:03:12.050000'), pandas.Timestamp('2014-01-27 11:57:18.240000'), pandas.Timestamp('2014-01-23 10:07:47.660000')] df.fr = [pandas.Timestamp('2014-01-26 23:41:21.870000'), pandas.Timestamp('2014-01-27 15:38:22.540000'), pandas.Timestamp('2014-01-23 18:50:41.420000')] (df.fr-df.to).astype('timedelta64[h]')   to yield,   0    58 1     3 2     8 dtype: float64  This was driving me bonkers as the .astype()  solution above didn't work for me.  But I found another way.  Haven't timed it or anything, but might work for others out there:   t1 = pd.to_datetime('1/1/2015 01:00') t2 = pd.to_datetime('1/1/2015 03:30')  print pd.Timedelta(t2...