Reshaping Multi Indexed DF

Question

I have a dataframe that is structured like so (similar to a pivot table):

A	B	December 2022	January 2023
A1	B1	100	200
A1	B2	101	201

I'd like to and transpose my dataframe in a way so it reads:

Month	A	B	Value
December 2022	A1	B1	100
December 2022	A1	B2	101
January 2023	A1	B1	200
January 2023	A1	B2	201

etc. I've attempted

df.T

But it gives me:

A	A1	A1
B	B1	B2
December 2022	100	101
January 2023	200	201

Answer 1

You should use pd.melt:

>>> df.melt(id_vars=['A', 'B'], var_name='Month', value_name='Value')
    A   B          Month  Value
0  A1  B1  December 2022    100
1  A1  B2  December 2022    101
2  A1  B1   January 2023    200
3  A1  B2   January 2023    201

then to reorder columns, you can use this hack:

>>> df.melt(id_vars=['A', 'B'], var_name='Month', value_name='Value') \
      .set_index('Month').reset_index()

           Month   A   B  Value
0  December 2022  A1  B1    100
1  December 2022  A1  B2    101
2   January 2023  A1  B1    200
3   January 2023  A1  B2    201

Update: according to @sammywemmy's comment:

var_cols = ['A', 'B']
out = df.melt(id_vars=var_cols, var_name='Month', value_name='Value') \
        [['Month'] + var_cols + ['Value']]
print(out)

# Output
           Month   A   B  Value
0  December 2022  A1  B1    100
1  December 2022  A1  B2    101
2   January 2023  A1  B1    200
3   January 2023  A1  B2    201