Calculating and placing values ​​in second level column in MultiIndex Pandas DataFrame

I have a multi-indexed DataFrame in which I want to place a second level column named AB. The values ​​of this level two columns should equal AD [1] / DP for each sample, for example. Sample1 AB = 60/180

import pandas as pd
import numpy as np

genotype_data = [
                    ['0/1', '120,60', 180, 5, '0/1', '200,2', 202, 99],
                    ['0/1', '200,20', 60, 99, '0/1', '200,50', 250, 99],
                    ['0/1', '200,2', 202, 99, '0/1', '200,2', 202, 99] 
]


genotype_columns = [['Sample1', 'Sample2'], ['GT', 'AD', 'DP', 'GQ']]
cols = pd.MultiIndex.from_product(genotype_columns)
df = pd.DataFrame(data=genotype_data, columns=cols)

      

        
        
        
      

    

This code creates the following input file / df:

   Sample1                        Sample2                       
GT      AD   DP  GQ      GT      AD   DP  GQ
0/1  120,60  180   5     0/1   200,2  202  99
0/1  200,20   60   3     0/1  200,50  250  99
0/1   200,2  202  99     0/1   200,2  202  99

      

        
        
        
      

    

The desired output should be:

      Sample1                        Sample2                       
GT      AD   DP  GQ    AB      GT      AD   DP  GQ    AB
0/1  120,60  180   5  0.33     0/1   200,2  202  99  0.01
0/1  200,20   60   3  0.33     0/1  200,50  250  99  0.20
0/1   200,2  202  99  0.01     0/1   200,2  202  99  0.01

      

        
        
        
      

    

I have come up with a solution for this, but it is rather slow, inefficient and relies on loops. I need a much more efficient solution as I will be doing this on very large files.

def calc_AB(df):

    sam = df.columns.levels[0][0]
    AD = df.xs('AD', level=1, axis=1).unstack().str.split(",", n=2)
    DP = df.xs('DP', level=1, axis=1).unstack()
    AB = round(pd.to_numeric(AD.str[1]) / pd.to_numeric(DP), 2)
    df[sam, 'AB'] = AB.tolist()

    return df 


dfs = [calc_AB(df[[sam]].astype(str)) for sam in df.columns.levels[0].tolist()]

pd.concat(dfs, axis=1) 

      

        
        
        
      

    

Any help with this would be much appreciated.