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I'm a newbie for python. I used this below code to make array, and I checked the memory location. It showed different results. I don't know why. I thought both would show same results. Do you know why? If so please, let me know the reason. thanks in advance.

a = np.array([[0,1,2],[3,4,5],[6,7,8]]) 
id(a[0][0]) #1301373082608
id(a[0][0]) #1301373082704
chepner
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4cket
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    Does this answer your question? [Numpy arrays changing id](https://stackoverflow.com/questions/40196986/numpy-arrays-changing-id) – Tudor Ioan Sep 20 '21 at 12:42

1 Answers1

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a is more than just a simple wrapper around the nested list you passed as an argument. a[0] constructs a new 3x1 array from a each time it is used, and a[0][0] constructs a new int64 value from that 3x1 array. Beyond that, you can't predict if each object will have different id numbers, or if (since their lifetimes do not overlap) Python will reuse the same id for each.

chepner
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