How to extract values from the two matrix dataframe

Question

I have a pandas dataframes as below.

import pandas as pd
df1=pd.DataFrame({'Group1':['a','b','c','d','e'],'Group2':["f","g","h","i","j"],'Group3':['k','L','m','n',"0"]})
print(df1)

df2=pd.DataFrame({'Group1':[0,0,2,1,0],'Group2':[1,2,0,0,0],'Group3':[0,0,0,1,1]})
print(df2)

df1 is a dataframe of students' name. df2 is a dataframe of their test score.

For example, if I compare df1 and df2, g and c have test score 2.

n,o,f,d have value 1.

Rest of them have value 0.

I want to compare df1 and df2, and then extract students' name and score.

The expected output dataframe is like below.

df3=pd.DataFrame({'2':["g","c","NaN","NaN","NaN","NaN","NaN","NaN","NaN"],'1':["n","o","f","d","NaN","NaN","NaN","NaN","NaN"],'0':["k","L","m","h","i","j","a","b","e"]})
print(df3)

My actual dataframe is much larger than above samples and wonder there is any good way of extraction without specifying cells. Your help will be greatly appreciated. Thank you.

Answer 1

This is pivot problem after melt , I am using crosstab , If you want to know more , please check this

i=df2.melt().groupby('value').cumcount()    
c=df2.melt().value
v=df1.melt().value

pd.crosstab(index=i,columns=c,values=v,aggfunc='sum')

value  0     1     2
row_0               
0      a     d     c
1      b     f     g
2      e     n  None
3      h     0  None
4      i  None  None
5      j  None  None
6      k  None  None
7      L  None  None
8      m  None  None