Pandas create a new df based on column in current df

Need to create a new df with a column based on couple of formula. I could create multiple df with group and merge. But is there an efficient way for achieve?

df_1 is as below,

  df_1 = pd.DataFrame([['A', '1/1/2021','SKU_1','Customer Backhaul','34,848','$-51,100'],
              ['A', '1/1/2021','SKU_1','FOB','75,357','$12,407,112'],
              ['A', '1/1/2021','SKU_1','Price','75,357','$12,407,112'],
              ['A', '1/1/2021','SKU_1','Vendor Freight - Delivered','40,511','$65,470'],
              ['B', '1/1/2021','SKU_1','Customer Backhaul','197,904','$-157,487'],
              ['B', '1/1/2021','SKU_1','FOB','931,866','$50,059,515'],
              ['B', '1/1/2021','SKU_1','Price','931,866','$62,333,500'],
              ['B', '1/1/2021','SKU_1','Vendor Freight - Delivered','740,355','$1,220,927']], 
              columns=['Group', 'Month','ID','Cost Type','Volume','Order Cost'])

Formulae for 'Value' column,

• Freight = Absolute value of (Customer Backhaul) + Vendor Delivered
• FOB = FOB
• Price = Price - Backhaul
• Volume = Volume of FOB

Out[df_2]

   Group   Month     ID      Cost Type   Volume    Cost
0   A   1/1/2021    SKU_1   Freight     75,357  $116,570
1   A   1/1/2021    SKU_1   FOB         75,357  $12,407,112
2   A   1/1/2021    SKU_1   Price       75,357  $12,434,063
3   B   1/1/2021    SKU_1   Freight     931,866 $1,378,414
4   B   1/1/2021    SKU_1   FOB         931,866 $50,059,515
5   B   1/1/2021    SKU_1   Price       931,866 $62,490,988

from Pandas create a new df based on column in current df