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# 3-d numpy array_3darr = np.arange(18).reshape((3, 2, 3)) # printing the dimensions of each numpy arrayprint("Dimensions in _3darr are: ", _3darr.ndim)print(_3darr)# 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 dimensionsprint("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
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.