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

Last Updated : 03 Mar, 2021

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 numpy package.
Use ndim attribute available with numpy array as numpy_array_name.ndim to get the number of dimensions.
Alternatively, we can use 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 numpy array and use one of the above two ways to get the number of dimensions.

Example 1:

Python3

import numpy as np
  
x = np.arange(12).reshape((3, 4))
    
print(x.ndim)

Output:

Example 2:

Python3

import numpy as np
  
  
# create numpy arrays
# 1-d numpy array
_1darr = np.arange(4)      
  
# 2-d numpy array
_2darr = np.arange(15).reshape((5, 3))     
  
# 3-d numpy array
_3darr = np.arange(18).reshape((3, 2, 3))  
  
# printing the type of value obtained using 
# attribute 'ndim'
print("Type of value obtained: ", type(_1darr.ndim))
  
# printing the dimensions of each numpy array
print("Dimensions in _1darr are: ", _1darr.ndim)
print("Dimensions in _2darr are: ", _2darr.ndim)
print("Dimensions in _3darr are: ", _3darr.ndim)
  
# numpy_arr.shape is the number of elements in
# each dimension numpy_arr.shape returns a tuple
# len() of the returned tuple is also gives number
# of dimensions
print("Dimensions in _3darr are: ", len(_3darr.shape))
  
# Use numpy.array() function to convert a list to
# numpy array
__1darr = np.array([5, 4, 1, 3, 2])
__2darr = np.array([[5, 4],[1,2], [4,5]])
print("Dimensions in __1darr are: ", __1darr.ndim)
print("Dimensions in __2darr are: ", __2darr.ndim)

Output:

Type of value obtained:  <class 'int'>
Dimensions in _1darr are:  1
Dimensions in _2darr are:  2
Dimensions in _3darr are:  3
Dimensions in _3darr are:  3
Dimensions in __1darr are:  1
Dimensions in __2darr are:  2

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