# list 切片返回的是不原數(shù)據(jù)，對新數(shù)據(jù)的修改不會影響原數(shù)據(jù)In [45]: list1 = [1, 2, 3, 4, 5] In [46]: list2 = list1[:3]In [47]: list2Out[47]: [1, 2, 3]In [49]: list2[1] = 1999# 原數(shù)據(jù)沒變In [50]: list1Out[50]: [1, 2, 3, 4, 5]In [51]: list2Out[51]: [1, 1999, 3]# 而 NumPy.ndarry 的切片返回的是原數(shù)據(jù)In [52]: arr = np.array([1, 2, 3, 4, 5])In [53]: arrOut[53]: array([1, 2, 3, 4, 5])In [54]: arr1 = arr[:3]In [55]: arr1Out[55]: array([1, 2, 3])In [56]: arr1[0] = 989In [57]: arr1Out[57]: array([989,  2,  3])# 修改了原數(shù)據(jù)In [58]: arrOut[58]: array([989,  2,  3,  4,  5])# 若希望得到原數(shù)據(jù)的副本， 可以用 copy()In [59]: arr2 = arr[:3].copy()In [60]: arr2Out[60]: array([989,  2,  3])In [61]: arr2[1] = 99282In [62]: arr2Out[62]: array([ 989, 99282,   3])# 原數(shù)據(jù)沒被修改In [63]: arrOut[63]: array([989,  2,  3,  4,  5])