在循环中添加多个列并在 Python 中创建 Dataframe

Question

Here I am trying to create a data frame with multiple columns. I have 760 names and I want to create a column for each name and then altogether they will form a data frame with the names in the top and the product values in the corresponding column of each product name. I get the result as I want. But the problem what occurs is, after running the function and the loop the result which is returned is the column of the last name in the array. Where I am stuck is how to save the name of the product while running the loop in the data frame so that at the end i will have the data frame with all the product information. Thanks in advance!

`dfPN1 = ['BSP752R', 'BTS6143D']
 P = []
 x = []
def f(y):
    P = 0
    P2 = []
    for x in y:
        df_PL_test = df[(df['PL'] == 27)&(df['Diff Load Due Week'] == -1)& (df['Product Name']      == x)]
    
        df_PL_test_sum = df_PL_test.groupby('Delivery_Week_Due' ,as_index =False)['BillingsAndBacklogs'].sum()
    
        df_PL_test_sum_norm = preprocessing.normalize(df_PL_test_sum, axis = 0)
 
        df_test_scaled = pd.DataFrame(df_PL_test_sum_norm, columns = df_PL_test_sum.columns)
    
        P = np.array(df_test_scaled.BillingsAndBacklogs)
    
        a_dataframe = pd.DataFrame({x: P})
    
   return a_dataframe`

Answer 1

Given a df that looks like: dfp =

    Name    Prod
0   Tom     A
1   Bob     B
2   Tom     B
3   Bill    C
4   Sally   B
5   Bob     C  

You can run:

dfp = dfp.pivot(columns= 'Name')  
dfp = dfp.replace(np.nan, '')
dfp = dfp.pivot(columns= 'Name')  

which yields:

    Prod
Name    Bill    Bob Sally   Tom
0                            A
1                B      
2                            B
3        C          
4                      B    
5                 C     

Which seems to be the desired result.