Return multiple columns ( arrays)

Hi,

I would like to run groupby and then apply Numba function on top of a pandas.
This is the example :

@nb.jit(nopython=True) 
def my_Numba_function(arr1,arr2):    
	
	arr1[:] =11
	arr2[:] =22

	return arr1,arr2 	


and_df= df_input_imputed.groupby(key_cols_list, as_index = True)[['col_1,'col_2']].\
	apply(lambda x: pd.DataFrame(my_Numba_function(arr1 = x['col_1'].values,arr2 = x['col_2'].values)) )			
	

And instead of getting two columns additional to my index, I am getting the results in a lot of columns ( rows became columns).

How can I fix this ?

Thanks,
Boris