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.
Python3
import numpy as np
_1darr = np.arange( 4 )
print (_1darr)
print ( "Dimensions in _1darr are: " , _1darr.ndim)
|
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.
Python3
import numpy as np
x = np.arange( 12 ).reshape(( 3 , 4 ))
print ( "Matrix: \n" , x)
print ( "Dim: " , x.ndim)
|
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().
Python3
import numpy as np
_3darr = np.arange( 18 ).reshape(( 3 , 2 , 3 ))
print ( "Dimensions in _3darr are: " , _3darr.ndim)
print (_3darr)
print ( "Dimensions in _3darr are: " , len (_3darr.shape))
|
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.
Python3
import numpy as np
__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:
Dimensions in __1darr are: 1
Dimensions in __2darr are: 2