I am trying to find a solution to pivot data in Pandas in the same manner with which I pivot it in Spotfire but am coming up short with respect to how to accomplish this.
Here is the basis for the dataframe
lot_id run wafer x y test_number test_name value
RBC45627 304102 550000 -120 -2 4 Test1 1.0
RBC45627 304102 550000 -120 -2 11 Test2 1.0
RBC45627 304102 550000 -120 -2 200 Test3 9.35e-07
RBC45627 304102 550000 -120 -2 204 Test4 1.16e-06
RBC45627 304102 550000 -120 -2 206 Test5 -2.83e-09
RBC45627 304102 550000 -120 -2 210 Test6 -1.32e-09
RBC45627 304102 550000 -120 -2 700 Test7 1.21e-11
it then gets pivoted to a single row based on the uniqueness of the columns (lot_id, run, wafer, x, y) and 7 new columns were created based on the concatenation of test_number + test_name
lot_id wafer x y 11.Test2 200.Test3 204.Test4 206.Test5 210.Test6 4.Test1 700.Test7
RBC45627, 304102, 550000, -120, -2, 1, 9.35E-07, 1.16E-06, -2.83E-09, -1.32E-09, 1, 1.21E-11
My attempts have lead to nowhere with the closest being using the following but this leaves me without the original columns that are desired.
fromCSV.pivot(columns=['test_number'],values='value',index=['x','y'])
