How to merge two rows of a pandas dataframe depending on a condition in Python?

I have a dataframe :

           order_creationdate orderid productid  quantity             prod_name  price  Amount
0  2021-01-18 22:27:03.341260       1     SnyTV       3.0           Sony LED TV  412.0  1236.0
1  2021-01-18 17:28:03.343089       1     AMDR5       1.0           AMD Ryzen 5  313.0   313.0
2  2021-01-18 13:19:03.343842       1     INTI0       8.0             Intel I10  146.0  1168.0
3  2021-01-18 10:24:03.344399       1     INTI0       5.0             Intel I10  146.0   730.0
4  2021-01-18 12:29:03.344880       1     CMCFN       4.0  coolermaster CPU FAN  675.0  2700.0

Index 2 and 3 have the same product id’s, hence its the same order, so i am trying to combine the rows into one single row, to get :

INTI0        13 .0       146.0       1898.0

the final df being :

           order_creationdate orderid productid  quantity             prod_name  price  Amount
0  2021-01-18 22:27:03.341260       1     SnyTV       3.0           Sony LED TV  412.0  1236.0
1  2021-01-18 17:28:03.343089       1     AMDR5       1.0           AMD Ryzen 5  313.0   313.0
2  2021-01-18 13:19:03.343842       1     INTI0       13.0         Intel I10    146.0  1898.0
3  2021-01-18 12:29:03.344880       1     CMCFN       4.0  coolermaster CPU FAN  675.0  2700.0

I have tried using df.groupby function :

df2['productid'] =df2['productid'].astype('str')

arr = np.sort(df2[['productid','quantity']], axis=1)

df2 = (df2.groupby([arr[:, 0],arr[:, 1]])
       .agg({'price':'sum', 'Amount':'sum'})
       .rename_axis(('X','Y'))
       .reset_index())
print(df2)

But it throws datatype error

File "/home/anti/Documents/db/create_rec.py", line 65, in <module>
    arr = np.sort(df2[['productid','quantity']], axis=1)
  File "<__array_function__ internals>", line 5, in sort
  File "/home/anti/.local/lib/python3.8/site-packages/numpy/core/fromnumeric.py", line 991, in sort
    a.sort(axis=axis, kind=kind, order=order)
TypeError: '<' not supported between instances of 'float' and 'str'

Answer

df2.groupby(['productid', 'orderid'], as_index=False).agg(
    {'quantity': sum, 'Amount': sum, 'order_creationdate': min, 'prod_name': min, 'price': min}
)

The output is:

  productid  orderid  quantity  Amount         order_creationdate             prod_name  price
0     AMDR5        1       1.0   313.0 2021-01-18 17:28:03.343089           AMD Ryzen 5  313.0
1     CMCFN        1       4.0  2700.0 2021-01-18 12:29:03.344880  coolermaster CPU FAN  675.0
2     INTI0        1      13.0  1898.0 2021-01-18 10:24:03.344399             Intel I10  146.0
3     SnyTV        1       3.0  1236.0 2021-01-18 22:27:03.341260           Sony LED TV  412.0