how to move dataframe's one column names(hierarchical) to index?

I am sorry this seems a basic manipulation but I can't figure it out after searching. The title is probably not accurate.

I have this dataframe

Bunker Port   Rotterdam   Singapore  ...   Rotterdam   Singapore
bunker             HSFO        HSFO  ...       VLSFO       VLSFO
period                               ...                        
Jul 23       453.318000  461.028000  ...  518.098000  553.426000
Aug 23       448.266000  454.016000  ...  513.596000  549.716000

There are 2 levels for the column names: 'Bunker Port' and 'bunker'

and I wish to convert the df to below(the 0-4 index is unecessary):

                   bunker     HSFO        MGO    VLSFO
0     period  Bunker Port      NaN        NaN      NaN
1     Jul 23    Rotterdam  453.318  723.83300  518.098
2     Aug 23    Rotterdam  448.266  735.00000  513.596
3     Jul 23    Singapore  461.028  734.04850  553.426
4     Aug 23    Singapore  454.016  738.74945  549.716

Thanks a lot

You should use the stack() function to move the Bunker Port column index as a row index and then you can use reset_index() function to reset the index and convert the MultiIndex levels into separate columns.

df.stack().reset_index()

You can also specify the level inside the stack() function:

df.stack(level=[0, 1]).reset_index()