The Comparison Between Python list and NumPy. ndarry slice is described in detail,

The Comparison Between Python list and NumPy. ndarry slice is described in detail,

Differences between Python list and NumPy. ndarry slices

Instance code:

# List slices return non-original data. Modifications to new data will not affect the original data 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 # original data is not changed In [50]: list1Out [50]: [1, 2, 3, 4, 5] In [51]: list2Out [51]: [1, 1999, 3] # And NumPy. the ndarry slice returns the original data 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]) # modify the original data In [58]: arrOut [58]: array ([989, 2, 3, 4, 5]) # to obtain a copy of the original data, you can use copy () In [59]: arr2 = arr [: 3]. copy () In [60]: arr2Out [60]: array ([989, 2, 3]) In [61]: arr2 [1] = 99282In [62]: arr2Out [62]: array ([989,992 82, 3]) # The original data is not modified In [63]: arrOut [63]: array ([989, 2, 3, 4, 5])

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