Pandas Pivot Table Without Aggregating

I have a dataframe df as: Acct_Id Acct_Nm Srvc_Id Phone_Nm Phone_plan_value Srvc_Num 51 Roger 789 Pixel 30 1 51 Roger 800

Solution 1:

More like a pivot problem , but need swaplevel and sort_index

df.set_index(['Acct_Id','Acct_Nm','Srvc_Num']).\
   unstack().\
   swaplevel(1,0,axis=1).\
   sort_index(level=0,axis=1).add_prefix('Srvc_Num_')


Out[289]: 

Srvc_Num               Srvc_Num_1                                             \
                Srvc_Num_Phone_Nm Srvc_Num_Phone_plan_value Srvc_Num_Srvc_Id   
Acct_Id Acct_Nm                                                                
32      Rafa                  HTC                      35.0456.051      Roger               Pixel                      30.0789.078      Anjay               Nokia                      50.0100.0   
Srvc_Num               Srvc_Num_2                                             \
                Srvc_Num_Phone_Nm Srvc_Num_Phone_plan_value Srvc_Num_Srvc_Id   
Acct_Id Acct_Nm                                                                
32      Rafa                 None                       NaN              NaN   
51      Roger              iPhone                      25.0800.078      Anjay                Oppo                      30.0120.0   
Srvc_Num               Srvc_Num_3                                             
                Srvc_Num_Phone_Nm Srvc_Num_Phone_plan_value Srvc_Num_Srvc_Id  
Acct_Id Acct_Nm                                                               
32      Rafa                 None                       NaN              NaN  
51      Roger              Galaxy                      40.0945.078      Anjay                None                       NaN              NaN  

And here is pivot_table

pd.pivot_table(df,index=['Acct_Id','Acct_Nm'],columns=['Srvc_Num'],values=['Phone_Nm','Phone_plan_value','Srvc_Id'],aggfunc='first')

Solution 2:

How about:

df.set_index(['Acct_Id', 'Acct_Nm', 'Srvc_Num']).unstack().swaplevel(0, 1, axis = 1).sort_index(axis = 1)