[FIXED] Group data together and retain groupings in dataframe

Issue

I have a dataframe:

ID   Deal  Party  Commodity       startdate  enddate  price    quantity  mtmvalue
---- ----- -----  ---------       ---------  -------  ------   --------  ---------
J1   Sell   J   (stock1, stock2)   01Jan23   01Feb23   10.00      10      100.00
J4   Buy    J   (stock1, stock2)   01Jan23   01Feb23   5.00       5       25.00
J2   Sell   J   (stock1, stock2)   01Jan23   01Feb23   10.00      10      100.00
J3   Buy    J   (stock1, stock2)   01Jan23   01Feb23   5.00       10      50.00

I need to group data together by Deal,Commodity, and startdate so that my dataframe looks like this:

ID   Deal  Party  Commodity       startdate  enddate  price    quantity  mtmvalue
---- ----- -----  ---------       ---------  -------  ------   --------  ---------
J1   Sell   J   (stock1, stock2)   01Jan23   01Feb23   10.00      10      100.00
J2   Sell   J   (stock1, stock2)   01Jan23   01Feb23   10.00      10      100.00
J3   Buy    J   (stock1, stock2)   01Jan23   01Feb23   5.00       10      50.00
J4   Buy    J   (stock1, stock2)   01Jan23   01Feb23   5.00       5       25.00

I am doing this which will create two groups, but I want it in one dataframe:

df.groupby(['Deal', 'Commodity', StartDate'])

How would I retain the groupings in the original dataframe?

Solution

Are you looking for sort_values?

>>> df.sort_values(['Deal', 'Commodity', 'startdate'], ascending=False)

   ID  Deal Party         Commodity startdate  enddate  price  quantity  mtmvalue
0  J1  Sell     J  (stock1, stock2)   01Jan23  01Feb23   10.0        10     100.0
2  J2  Sell     J  (stock1, stock2)   01Jan23  01Feb23   10.0        10     100.0
1  J4   Buy     J  (stock1, stock2)   01Jan23  01Feb23    5.0         5      25.0
3  J3   Buy     J  (stock1, stock2)   01Jan23  01Feb23    5.0        10      50.0

Note: There is not enough information here to correctly rank J3 ahead of J4.

Answered By - Corralien