How to get the number of dimensions of a matrix using NumPy in Python?

In this article, we will discuss how to get the number of dimensions of a matrix using NumPy. It can be found using the ndim parameter of the ndarray() method.

Syntax: no_of_dimensions = numpy.ndarray.ndim

Approach:

• Create an n-dimensional matrix using the NumPy package.
• Use ndim attribute available with the NumPy array as numpy_array_name.ndim to get the number of dimensions.
• Alternatively, we can use the shape attribute to get the size of each dimension and then use len() function for the number of dimensions.
• Use numpy.array() function to convert a list to a NumPy array and use one of the above two ways to get the number of dimensions.

Get the Number of 1-Dimensions of a Matrix

Creating a 1D array using np.arrange and printing the dimension of an array.

Output:

[0 1 2 3]
Dimensions in _1darr are:  1v

Get the Number of 2-Dimensions of a Matrix

Creating a 2D array using np.arrange and printing the dimension of an array.

Output:

Matrix: 
 [[ 0  1  2  3]
 [ 4  5  6  7]
 [ 8  9 10 11]]
Dim:  2

Get the Number of 3-Dimensions of a Matrix

Creating a 3D array using np.arrange and np.reshape. After that, we are printing the dimension of an array using shape and len().

Output:

Dimensions in _3darr are:  3
[[[ 0  1  2]
  [ 3  4  5]]

 [[ 6  7  8]
  [ 9 10 11]]

 [[12 13 14]
  [15 16 17]]]
Dimensions in _3darr are:  3

Convert a list to a Numpy Array and Get a Dimensions of a Matrix

Creating a list of 1D and 2D, using np.arrange we are converting it into a np.array and printing the dimension of an array.

Output:

Dimensions in __1darr are:  1
Dimensions in __2darr are:  2