From a Pandas newbie: I have data that looks essentially like this -

```
 data1=pd.DataFrame({'Dir':['E','E','W','W','E','W','W','E'], 'Bool':['Y','N','Y','N','Y','N','Y','N'], 'Data':[4,5,6,7,8,9,10,11]}, index=pd.DatetimeIndex(['12/30/2000','12/30/2000','12/30/2000','1/2/2001','1/3/2001','1/3/2001','12/30/2000','12/30/2000']))
data1
Out[1]: 
           Bool  Data Dir
2000-12-30    Y     4   E
2000-12-30    N     5   E
2000-12-30    Y     6   W
2001-01-02    N     7   W
2001-01-03    Y     8   E
2001-01-03    N     9   W
2000-12-30    Y    10   W
2000-12-30    N    11   E

```

And I want to group it by multiple levels, then do a cumsum():

E.g., like `running_sum=data1.groupby(['Bool','Dir']).cumsum()` <-(Doesn't work)

with output that would look something like:

```
Bool Dir Date        running_sum
N    E   2000-12-30           16
     W   2001-01-02            7
         2001-01-03           16
Y    E   2000-12-30            4
         2001-01-03           12
     W   2000-12-30           16

```

My "like" code is clearly not even close. I have made a number of attempts and learned many new things about how not to do this. 

Thanks for any help you can give.