Compare elements in dataframe columns for each row - Python

Question

I have a really huge dataframe (thousends of rows), but let's assume it is like this:

   A  B  C  D  E  F
0  2  5  2  2  2  2
1  5  2  5  5  5  5
2  5  2  5  2  5  5
3  2  2  2  2  2  2
4  5  5  5  5  5  5

I need to see which value appears most frequently in a group of columns for each row. For instance, the value that appears most frequently in columns ABC and in columns DEF in each row, and put them in another column. In this example, my expected output is

ABC  DEF  
 2    2     
 5    5     
 5    5     
 2    2     
 5    5     

我该如何在Python中做呢？？？谢谢！！

Answer 1

这是使用列的一种方法 groupby

mapperd={'A':'ABC','B':'ABC','C':'ABC','D':'DEF','E':'DEF','F':'DEF'}
df.groupby(mapperd,axis=1).agg(lambda x : x.mode()[0])
Out[826]: 
   ABC  DEF
0    2    2
1    5    5
2    5    5
3    2    2
4    5    5