This is a detailed tutorial of the NumPy Array Copy and View. Find out the difference between both of these with the help of illustrative examples.

Copy

When we try to duplicate some data in the NumPy we usually have to manipulate data in every way possible. During this manipulation of data, we usually use this method of copying things. When we try to copy we make a new file with the same data so that we can make changes in the new copy. With the help of this, no change will occur in the original copy of the data.

A copy of the data owns the data present in that copy and has no link to the original copy of the data. As a result, we can make any number of changes in the original copy it will have no effect on the version of copies of similar data.

When we copy arrays the new copy of the array is present at some other location in the memory. We need some extra space in order to create the copies of the arrays.

Let us go through an example of a copy:

Output:

[9 3 7 6 5]
[9 8 7 6 5]

Now we see that first, we create a copy and then we make changes to the original copy. And also no changes will occur in the copy of the array as we make changes in the original array.

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