How to check if a NumPy Array is multidimensional or 1D

# How to check if a NumPy Array is multidimensional or 1D

Use the ndim attribute on the NumPy array to check if it is multidimensional or one-dimensional.

The ndim attribute returns the number of array dimensions:

greater than 1 if the array is multidimensional.
equal to 1 if the array is one-dimensional.

main.py

Copied!
import numpy as np

arr1 = np.array([2, 4, 6, 8])
print(arr1.ndim)  # 👉️ 1

print('-' * 50)

if arr1.ndim == 1:
    # 👇️ this runs
    print('The array is one-dimensional')
else:
    print('The array is multidimensional')

print('-' * 50)

arr2 = np.array([[1, 2, 3], [4, 5, 6]])
print(arr2.ndim)  # 👉️ 2

check if numpy array is multidimensional or one dimensional

The code for this article is available on GitHub

The ndarray.ndim attribute returns the number of array dimensions.

main.py

Copied!
import numpy as np

arr1 = np.array([2, 4, 6, 8])
print(arr1.ndim)  # 👉️ 1

arr2 = np.array([[1, 2, 3], [4, 5, 6]])
print(arr2.ndim)  # 👉️ 2

If you need to check if the array is one-dimensional, check if the ndim attribute returns 1.

main.py

Copied!
import numpy as np

arr1 = np.array([2, 4, 6, 8])
print(arr1.ndim)  # 👉️ 1

print('-' * 50)

if arr1.ndim == 1:
    # 👇️ this runs
    print('The array is one-dimensional')
else:
    print('The array is multidimensional')

If the attribute returns 1, then the array is one-dimensional.

Otherwise, it is at least two-dimensional.

If you need to check if the array is multidimensional, check if the ndim attribute returns a value greater than 1.

main.py

Copied!
import numpy as np

arr = np.array([[1, 2, 3], [4, 5, 6]])
print(arr.ndim)  # 👉️ 2

if arr.ndim > 1:
    # 👇️ this runs
    print('The array is multidimensional')
else:
    print('The array is one-dimensional')

The code for this article is available on GitHub

You can use the same approach to check if the NumPy array is two-dimensional.

main.py

Copied!
import numpy as np

arr = np.array([[1, 2, 3], [4, 5, 6]])
print(arr.ndim)  # 👉️ 2

if arr.ndim == 2:
    # 👇️ this runs
    print('The array is two-dimensional')
else:
    print('The array is NOT two-dimensional')

# Checking for empty dimensions with `numpy.squeeze()`

If your array might have empty dimensions, use the numpy.squeeze() method before accessing the ndim attribute.

main.py

Copied!
import numpy as np

arr = np.array([[1, 2, 3]])
print(arr.ndim)  # 👉️ 2

arr = np.squeeze(arr)
print(arr.ndim)  # 👉️ 1

checking for empty dimensions before ndim

The code for this article is available on GitHub

The array in the example has an empty dimension.

main.py

Copied!
import numpy as np

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

print(arr) # 👉️ [[1 2 3]]

print(arr.ndim)  # 👉️ 2

The numpy.squeeze method removes the axes of length one from the supplied array.

main.py

Copied!
import numpy as np

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

print(arr)  # 👉️ [[1 2 3]]

print(arr.squeeze()) # 👉️ [1 2 3]

Accessing the ndim attribute after calling squeeze() produces a different result.

main.py

Copied!
import numpy as np

arr = np.array([[1, 2, 3]])
print(arr.ndim)  # 👉️ 2

arr = np.squeeze(arr)
print(arr.ndim)  # 👉️ 1

checking for empty dimensions before ndim

The code for this article is available on GitHub

# Additional Resources

You can learn more about the related topics by checking out the following tutorials:

I wrote a book in which I share everything I know about how to become a better, more efficient programmer.

You can use the search field on my Home Page to filter through all of my articles.

How to check if a NumPy Array is multidimensional or 1D