Apply different functions to different items in group object: Python pandas

Question

Suppose I have a dataframe as follows:

In [1]: test_dup_df

Out[1]:
                  exe_price exe_vol flag 
2008-03-13 14:41:07  84.5    200     yes
2008-03-13         


        

Answer 1

Apply your own function:

In [12]: def func(x):
             exe_price = (x['exe_price']*x['exe_vol']).sum() / x['exe_vol'].sum()
             exe_vol = x['exe_vol'].sum()
             flag = True        
             return Series([exe_price, exe_vol, flag], index=['exe_price', 'exe_vol', 'flag'])


In [13]: test_dup_df.groupby(test_dup_df.index).apply(func)
Out[13]:
                    exe_price exe_vol  flag
date_time                                  
2008-03-13 14:41:07      84.5     200  True 
2008-03-13 14:41:37        85   10000  True
2008-03-13 14:41:38      84.5   69700  True
2008-03-13 14:41:39      84.5    1200  True
2008-03-13 14:42:00      84.5    1000  True
2008-03-13 14:42:08      84.5     300  True
2008-03-13 14:42:10     20.71  100000  True
2008-03-13 14:42:15      84.5    5000  True
2008-03-13 14:42:16      84.5    3200  True