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