Pandas Add rows for each column

I apologise for the title, I know it isn’t the most helpful. What I’m attempting to do is restructure my data so that each of a given column is given it’s own row with certain values carried over from the previous dataframe.

My Data in its current form is something like this:

ColA | ColB | ColC | val1 | val2 | val3
   1 |    2 |    3 | A    | B    | C
   4 |    5 |    6 | D    | E    | F

And I want to restructure it so I get a result like this:

 ColA | ColB | ColC | val
    1 |    2 |    3 | A
    1 |    2 |    3 | B
    1 |    2 |    3 | C
    4 |    5 |    6 | D 
    4 |    5 |    6 | E 
    4 |    5 |    6 | F 

How would I do this?

I know I could go through each row, grab the relevant data and concat a dataframe but I was hoping for a much better alternative

Answer

Given:

   ColA  ColB  ColC val1 val2 val3
0     1     2     3    A    B    C
1     4     5     6    D    E    F

Doing:

df.melt(['ColA', 'ColB', 'ColC'])

Output:

   ColA  ColB  ColC variable value
0     1     2     3     val1     A
1     4     5     6     val1     D
2     1     2     3     val2     B
3     4     5     6     val2     E
4     1     2     3     val3     C
5     4     5     6     val3     F