Split rows and assign values pandas

Question

I have four a data frame as follows:

Proxyid	A	B	C	D
123	1	0	0	0
456	1	1	1	1
789	0	0	0	0

This is the idea of the data frame. now I want to duplicate the rows where there are more than one 1. and assign values as follows.

Proxyid	A	B	C	D
123	1	0	0	0
456	1	0	0	0
456	0	1	0	0
456	0	0	1	0
456	0	0	0	1
789	0	0	0	0

I would really appreciate any input. Thank you.

Answer 1

One option via pd.get_dumies:

df1 = (
    pd.get_dummies(
        df.set_index('Proxyid')
        .mul(df.columns[1:])
        .replace('', np.NAN)
        .stack()
    )
    .reset_index().drop('level_1', 1)
) 
result = df1.append(df[~df.Proxyid.isin(df1.Proxyid)])

OUTPUT:

	Proxyid	A	B	C	D
0	123	1	0	0	0
1	456	1	0	0	0
2	456	0	1	0	0
3	456	0	0	1	0
4	456	0	0	0	1
2	789	0	0	0	0

If you've extra columns just add them in set_index and use:

df1 = df.set_index(['Proxyid', 'test'])
df1 = pd.get_dummies(df1.mul(df1.columns).replace('', np.NAN).stack()).reset_index()
result = df1.append(df[~df.Proxyid.isin(df1.Proxyid)])