Return multiple columns ( arrays)


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

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 ?