The documentation at : https://numpy.org/doc/stable/user/basics.indexing.html?highlight=slice does say that slicing creates a view into the original, and not a new object.

So it isn't a bug - it is entirely expected behaviour

To Quote :

NumPy slicing creates a view instead of a copy as in the case of built-in Python sequences such as string, tuple and list. Care must be taken when extracting a small portion from a large array which becomes useless after the extraction, because the small portion extracted contains a reference to the large original array whose memory will not be released until all arrays derived from it are garbage-collected. In such cases an explicit copy() is recommended.

------ Original Message ------
From: "Leon fevang-gunn" <leon.fevanggunn@gmail.com>
To: docs@python.org
Sent: Monday, 18 Jul, 22 At 15:59
Subject: [docs] Suspected bug


So I managed to fix it, but I think I had an experience with a bug... It seems that a slice of a numpy array gave me some trouble. Only after redefining the slice as a numpy array would the code run as normal again. In other words:

NOT working:
zk = np.array(list1)
zk2 = zk[a:b]

zk = np.array(list1)
zk2 = np.array(zk[a:b])

I also checked and it does say that a slice of an array should be an array:

in: zk[a:b]
out: arra(list1[a:b])

The problem was that it would link the two variables zk and zk2 together:

zk = array1
zk2 = array1[a:b]

When i changed zk2[0] to a different value, the corresponding element, zk[a], also changes. So for example:

zk = np.array([1,2,3,4,5])
zk2 = np.array(zk[1:4])

in: print(zk)
out: array([1,2,3,4,5])

in: zk_2[0] = 0
out: array([1,0,3,4,5])

Additional information:
- zk is read in from a .csv file using pandas.
- I am using Spyder/Anaconda
- When i change a value of zk_2 in the command window, zk remains the same

Allright, thought I would let someone know. Let me know if you need additional information.

Kind regards,

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-- <br>Anthony Flury<br>anthony.flury@btinternet.com