CODEWITHSUNDEEP
pythonlistnumpy
Lifei
Lifei

Reputation: 23

Why do the same operations on numpy and python list get different results?

I try to replace the value of the first element with the value of the second element on a numpy array and a list whose elements are exactly the same, but the result I get is different.

1) test on a numpy array:

test=np.array([2,1])
left=test[:1]
right=test[1:]
test[0]=right[0]
print('left=:',left)

I get: left=: [1]

2) test on a python list:

 test=[2,1]
 left=test[:1]
 right=test[1:]
 test[0]=right[0]
 print('left=:',left)

I get: left=: [2]

Could anyone explain why the results are different? Thanks in advance.

Upvotes: 2

Views: 766

Answers (2)

kcw78
kcw78

Reputation: 7996

To expand on James Down explanation of numpy arrays, you can use .copy() if you really want a COPY and not a VIEW of your array slice. However, when you make a copy, you would have to do the copy of left again after reassigning test[0]=right[0] to get the new value.

Also, regarding the list method, you set test[0]=right[0], so if you print (list) after the assignment, you will get [1 1] instead of the original [2, 1]. As James pointed out, left is a copy of the list item, so not updated with the change to the list.

Upvotes: 1

James Downs
James Downs

Reputation: 168

Slicing (indexing with colons) a numpy array returns a view into the numpy array so when you later update the value of test[0] it updates the value of left as left is just a view into the array.

When you slice into a python list it just returns a copy so when you update the value of test[0], the value of left doesn't change.

This is done because numpy arrays are often very large and creating lots of copies of arrays could be quite taxing.

Upvotes: 3

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