# Lession - #298 NumPy Copy vs View

#### The Difference Between Copy and View

The fundamental contrast between a copy and a view on an array is that the copy is another array, and the view is only a view on the first array.
The copy claims the data and any progressions made to the copy won't influence unique array, and any progressions made to the first array won't influence the copy.
The view doesn't claim the data and any progressions made to the view will influence the first array, and any progressions made to the first array will influence the view.

#### COPY:

Example
Make a copy, change the original array, and display both arrays:
``````import numpy as np

arr = np.array([1, 2, 3, 4, 5]>
x = arr.copy(>
arr = 42

print(arr>
print(x>``````

#### VIEW:

Example
Make a view, change the original array, and display both arrays:
``````import numpy as np

arr = np.array([1, 2, 3, 4, 5]>
x = arr.view(>
arr = 42

print(arr>
print(x>``````

#### Make Changes in the VIEW:

Example
Make a view, change the view, and display both arrays:
``````import numpy as np

arr = np.array([1, 2, 3, 4, 5]>
x = arr.view(>
x = 31

print(arr>
print(x>``````

numpy tile ... Construct an array by repeating A the number of times given by reps.
Numpy min(>
function is used to get a minimum value along a specified axis.
Learn how to create Numpy array, from one dimension to any dimension you want in this series of Numpy tutorials.
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