How to merge 3 columns into 1 whilst keeping values column separate

I have the following Pivot table:

I want to merge the 3 columns together and have Amount stay separate to form this:

So Far I’ve turned it into a regular DataFrame and did this:

df.melt(id_vars = ['SubClass', 'SubClass2'], value_name = 'CQ')

But that didn’t arrange it right at all. It messed up all the columns.

I’ve thought once I get the melt right, I could just change the NaN values to 0 or blanks.

EDIT

I need to keep Subclass & Subclass2 in the final column as they’re the higher level mapping of Layer, hence why I want the output Col1 to include them before listing Layer with Amount next to it.

Thanks!

>Solution :

here is one way to do it

pd.concat([df,
           df[['Subclass','Subclass2']].stack().reset_index()[0].to_frame().rename(columns={0:'Layer'})
          ]
         )[['Layer','Amount']].sort_values('Layer')

    Layer   Amount
0      A    NaN
1      B    NaN
0      C    5.0
2      E    NaN
3      F    NaN
1      G    100.0