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# Checking if a NumPy array is a view or copy

NumPy

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**interactive map of data science**To check if a NumPy array is a view or not use the `base`

property. To check if a NumPy array is a copy, we can use `np.shares_memory(~)`

to check whether the two objects share memory or not.

# Examples

## View or not

Consider the following arrays `a`

and `b`

:

```
a = np.array([1,2])
```

To check if `b`

is a view of `a`

:

```
b.base is a
True
```

Here, array `b`

shares the same memory address as `a`

, so `b.base`

is `a`

evaluates to `True`

.

## Share memory or not

Consider the following arrays `a`

and `b`

:

```
a = np.array([1,2])b = a.copy()
```

To check if `b`

shares memory with `a`

:

```
np.shares_memory(b, a)
False
```

Given the two arrays do not share memory, we can say that `b`

is a copy of `a`

.

Published by Arthur Yanagisawa

Edited by 0 others

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