这是关于python中的一个简单代码

Question

I have two tables here

 Reg_No     Name  Marks Grade  Sub1  Sub2
     1  Sanjana    100    A1  60.0   NaN
     2    Alfaz     70     A   NaN  65.0
     3     Ritu     50     B  30.0   NaN
     4    Priya     60     A   NaN  40.0

        Sub1  Sub2
IA      0.50  0.40
OA      0.50  0.60
Others  0.25  0.25

The first table contains marks , sub1 and sub2 and the second table contains IA , OA , Others as rows based on the subjects.

I need to split the column Marks of the first table based on the second table into 3 new columns. The first column is the IA column, if its sub1 in the first table, it should split based on the sub1 column of second table

example:

IA = table1.marks*table2(IA)(sub1) 

ie 100*0.50

This should be my output

Reg_No  Name    Marks   Grade   Sub 1   Sub 2   IA_ OA_ Others_
1   Sanjana       100    A1     60              50  50  25
2   Alfaz         100    A              65      40  60  25
3   Ritu          100    B      30              50  50  25
4   Priya         100    A              40      40  60  25

Please tell me how to code for this

Answer 1

I get every row from second DataFrame and use it with apply() to create new column in first DataFrame

import pandas as pd
import io

text = '''Marks  Sub1  Sub2
100    60.0  NaN
70     NaN   65.0
50     30.0  NaN
60     NaN   40.0'''
df1 = pd.read_csv(io.StringIO(text), sep='\s+')

text = '''Sub1  Sub2
IA      0.50  0.40
OA      0.50  0.60
Others  0.25  0.25'''
df2 = pd.read_csv(io.StringIO(text), sep='\s+')

for row in df2.itertuples():
    name, sub1, sub2 = row  
    df1[name] = df1.apply(lambda x: (x['Marks']*sub2) if pd.isna(x['Sub1']) else (x['Marks']*sub1), axis=1)

print(df1)

Result:

   Marks  Sub1  Sub2    IA    OA  Others
0    100  60.0   NaN  50.0  50.0    25.0
1     70   NaN  65.0  28.0  42.0    17.5
2     50  30.0   NaN  25.0  25.0    12.5
3     60   NaN  40.0  24.0  36.0    15.0