**NumPy**

319 guides

*chevron_left*

**Cookbooks**

Accessing a value in a 2D arrayAccessing columns of a 2D arrayAccessing rows of a 2D arrayCalculating the determinant of a matrixChecking allowed values for a NumPy data typeChecking if a NumPy array is a view or copyChecking the version of NumPyChecking whether a NumPy array contains a given rowComputing Euclidean distance using NumpyConcatenating 1D arraysConverting array to lowercaseConverting type of NumPy array to stringCreating a copy of an arrayDifference between Python List and Numpy arrayDifference between the methods array_equal and array_equivDifference between the methods mod and fmodDifference between the methods power and float_powerFinding the closest value in an arrayFinding the Index of Largest Value in a Numpy ArrayFinding the Index of Smallest Value in a Numpy ArrayFinding the most frequent value in a NumPy arrayFlattening Numpy arraysGetting constant PiGetting elements from a two dimensional array using two dimensional array of indicesGetting indices of N maximum valuesGetting indices of N minimum valuesGetting the number of columns of a 2D arrayGetting the number of non-zero elements in a NumPy arrayGetting the number of rows of a 2D arrayInitializing an array of onesInitializing an array of zerosInitializing an identity matrixLimiting array values to a certain rangePerforming linear regressionPrinting full or truncated NumPy arrayPrinting large Numpy arrays without truncationRemoving rows containing NaN in a NumPy arrayReversing a NumPy arraySaving NumPy array to a fileShape of Numpy ArraysSorting value of one array according to anotherSuppressing scientific notation

check_circle

Mark as learned thumb_up

0

thumb_down

0

chat_bubble_outline

0

Comment auto_stories Bi-column layout

settings

# Checking if a NumPy array is a view or copy

*schedule*May 20, 2023

local_offer

Tags Python●NumPy

*toc*Table of Contents

*expand_more*

Master the

Start your free 7-days trial now!

**mathematics behind data science**with 100+ top-tier guidesStart your free 7-days trial now!

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

Did you find this page useful?

thumb_up

thumb_down

Comment

Citation

Ask a question or leave a feedback...

thumb_up

0

thumb_down

0

chat_bubble_outline

0

settings

Enjoy our search

Hit / to insta-search docs and recipes!