Restructuring pandas dataframe based on number of columns

Kapital :

I have the following pandas dataframe.

ID   Col1   Col2   Col3   Col4   Col5   Col6   Col7   Col8   Col9
1     A      B       C      A     B      C      A      B      C
2     D      E       F      D     E      F      D      E      F 

I would like to get the following table by restructuring every three-column values.

ID   Col_1   Col_2   Col_3
1      A       B       C
       A       B       C
       A       B       C

2      D       E       F
       D       E       F
       D       E       F

OR

ID   Col_1   Col_2   Col_3
1      A       B       C
1      A       B       C
1      A       B       C
2      D       E       F
2      D       E       F
2      D       E       F

Is there any efficient way to do it? I tried to find similar examples here at the StackOverflow community but couldn't. If you have, you can point me.

Any help is appreciated!

anky_91 :

Here is one with apply and np.reshape:

f = lambda x: pd.DataFrame(np.reshape(x.to_numpy(),(-1,3))).add_prefix('Col_')
df.groupby('ID').apply(f).reset_index('ID')

---

   ID Col_0 Col_1 Col_2
0   1     A     B     C
1   1     A     B     C
2   1     A     B     C
3   2     D     E     F
4   2     D     E     F
5   2     D     E     F