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 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:
2
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 arrayprint("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 dimensionsprint("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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