How to Find Shape of Array in NumPy: Simple Guide

To find the shape of a NumPy array, use the .shape attribute. It returns a tuple showing the size of the array along each dimension.

Syntax

The syntax to find the shape of a NumPy array is simple. Use array.shape, where array is your NumPy array.

• array: Your NumPy array variable.
• .shape: Attribute that returns a tuple with the size of each dimension.

python

array.shape

Example

This example shows how to create a NumPy array and find its shape. The output is a tuple representing the number of rows and columns.

python

import numpy as np

# Create a 2D array with 3 rows and 4 columns
array = np.array([[1, 2, 3, 4],
                  [5, 6, 7, 8],
                  [9, 10, 11, 12]])

# Find the shape of the array
shape = array.shape
print(shape)

Output

(3, 4)

Common Pitfalls

One common mistake is trying to call shape as a function like array.shape(). Remember, shape is an attribute, not a method, so do not use parentheses.

Another pitfall is confusing the shape with the size. shape gives dimensions, while size gives total elements.

python

import numpy as np

array = np.array([1, 2, 3])

# Wrong: calling shape as a function
# print(array.shape())  # This will cause an error

# Right: access shape as attribute
print(array.shape)  # Output: (3,)

Output

(3,)

Quick Reference

Attribute	Description	Example Output
array.shape	Returns tuple of array dimensions	(3, 4)
array.size	Returns total number of elements	12
array.ndim	Returns number of dimensions	2

Key Takeaways

Use the .shape attribute to get the dimensions of a NumPy array.

Do not use parentheses with .shape because it is not a function.

The shape is a tuple showing size along each dimension.

For total elements, use .size instead of .shape.

Check .ndim to know how many dimensions the array has.