Reverse a get_dummies encoding in pandas

Column names are: ID,1,2,3,4,5,6,7,8,9.

The col values are either 0 or 1

My dataframe looks like this:

 ID     1    2    3    4    5    6   7   8   9 

1002    0    1    0    1    0    0   0   0   0
1003    0    0    0    0    0    0   0   0   0 
1004    1    1    0    0    0    0   0   0   0
1005    0    0    0    0    1    0   0   0   0
1006    0    0    0    0    0    1   0   0   0
1007    1    0    1    0    0    0   0   0   0
1000    0    0    0    0    0    0   0   0   0
1009    0    0    1    0    0    0   1   0   0

I want the column names in front of the ID where the value in a row is 1.

The Dataframe i want should look like this:

 ID      Col2
1002       2    // has 1 at Col(2) and Col(4)
1002       4    
1004       1    // has 1 at col(1) and col(2)
1004       2
1005       5    // has 1 at col(5)
1006       6    // has 1 at col(6)
1007       1    // has 1 at col(1) and col(3)
1007       3
1009       3    // has 1 at col(3) and col(7)
1009       7

Please help me in this, Thanks in advance

Answer

set_index + stack, stack will dropna by default

df.set_index('ID',inplace=True)

df[df==1].stack().reset_index().drop(0, axis=1)
Out[363]: 
     ID level_1
0  1002       2
1  1002       4
2  1004       1
3  1004       2
4  1005       5
5  1006       6
6  1007       1
7  1007       3
8  1009       3
9  1009       7