The way to get the previous is using the shift method:
In [11]: df1.change.shift(1)Out[11]:0 NaT1 2014-03-082 2014-04-083 2014-05-084 2014-06-08Name: change, dtype: datetime64[ns]
Now you can subtract these columns. Note: This is with 0.13.1 (datetime stuff
has had a lot of work recently, so YMMV with older versions).
In [12]: df1.change.shift(1) - df1.changeOut[12]:0 NaT1 -31 days2 -30 days3 -31 days4 0 daysName: change, dtype: timedelta64[ns]
You can just apply this to each case/group:
In [13]: df.groupby('case')['change'].apply(lambda x: x.shift(1) - x)Out[13]:0 NaT1 -31 days2 -30 days3 -31 days4 NaTdtype: timedelta64[ns]
