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I have code like this:

import numpy as np area = np.zeros([2,2]) f = area print(area) f[0][0]=1 print(area) print(f)

Which produces the following arrays

[[0. 0.] [0. 0.]] [[1. 0.] [0. 0.]] [[1. 0.] [0. 0.]]

How do I get it so that the `area`

array is not 'linked' to the `f`

array i.e. after the calculation the `f`

array changes but the `area`

array does not?

You need to make a copy of `area`

:

f = area.copy()

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They're not just "linked"; they are 2 names for *the same array*.

If you want them to be distinct, make a *copy* of `area`

to assign to `f`

.

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You should copy your first array:

`f = area.copy()`

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You can prevent this by making a copy:

1.

A=B

Assignment of list is happened , so that's why change in one place creates change another list.

2.

B[:] = A

This only works if B is already existing.

3.

B = A.copy()

Both 2 and 3 copies the list into another but they don't get linked to each other.

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##### Comments

- These aren't two arrays that are "linked",
**it is the same array**.`x = y`

says "let the name`x`

now refer to the object currently being referenced by the name`y`

", it doesn't say, "copy the object being referred to by`y`

and assign it to the name`x`

" - Does this answer your question? Python numpy create copy and not reference
- which one? A.copy()?
- The OP is working with a numpy array, not a list, as you have written in your question
- Yes but you are using the word list in you answer, that is what I'm saying, and the op is a out numpy arrays