python - Unpivot multiple columns with same name in pandas dataframe

Question

I have the following dataframe:

pp  b          pp   b
5   0.001464    6   0.001853
5   0.001459    6   0.001843

Is there a way to unpivot columns with the same name into multiple rows?

This is the required output:

pp  b         
5   0.001464    
5   0.001459    
6   0.001853
6   0.001843

Answer 1

Try groupby with axis=1

df.groupby(df.columns.values, axis=1).agg(lambda x: x.values.tolist()).sum().apply(pd.Series).T.sort_values('pp')
Out[320]: 
          b   pp
0  0.001464  5.0
2  0.001459  5.0
1  0.001853  6.0
3  0.001843  6.0

A fun way with wide_to_long

s=pd.Series(df.columns)
df.columns=df.columns+s.groupby(s).cumcount().astype(str)

pd.wide_to_long(df.reset_index(),stubnames=['pp','b'],i='index',j='drop',suffix='d+')
Out[342]: 
            pp         b
index drop              
0     0      5  0.001464
1     0      5  0.001459
0     1      6  0.001853
1     1      6  0.001843