How to get Numpy Array Dimensions using numpy.ndarray.shape & numpy.ndarray.size() in Python

In this article, we will be discussing how to count several elements in 1D, 2D, and 3D Numpy array. Moreover, we will be discussing the counting of rows and columns in a 2D array and the number of elements per axis in a 3D Numpy array.

Let’s get started!

Get the Dimensions of a Numpy array using ndarray.shape()

NumPy.ndarray.shape

This module is used to get a current shape of an array, but it is also used to reshaping the array in place by assigning a tuple of arrays dimensions to it. The function is:

ndarray.shape

We will use this function for determining the dimensions of the 1D and 2D array.

Get Dimensions of a 2D NumPy array using ndarray.shape:

Let us start with a 2D Numpy array.

2D Numpy Array

Code:
arr2D = np.array([[11 ,12,13,11], [21, 22, 23, 24], [31,32,33,34]])
print(‘2D Numpy Array’)
print(arr2D)
Output:
2D Numpy Array 
[[11 12 13 11] 
[21 22 23 24] 
[31 32 33 34]]

Get the number of rows in this 2D NumPy array:

number of rows in this 2D numpy array

Code:

numOfRows = arr2D.shape[0]
print('Number of Rows : ', numOfRows)
Output:
Number of Rows : 3

Get a number of columns in this 2D NumPy array:

number of columns in this 2D numpy array

Code:

numOfColumns = arr2D.shape[1]
print('Number of Columns : ', numOfColumns)
Output:
Number of Columns: 4

Get the total number of elements in this 2D NumPy array:

total number of elements in this 2D numpy array

Code:

print('Total Number of elements in 2D Numpy array : ', arr2D.shape[0] * arr2D.shape[1])
Output:

Total Number of elements in 2D Numpy array: 12

Get Dimensions of a 1D NumPy array using ndarray.shape

Now, we will work on a 1D NumPy array.

number of elements of this 1D numpy array

Code:

arr = np.array([4, 5, 6, 7, 8, 9, 10, 11])
print(‘Shape of 1D numpy array : ‘, arr.shape)
print(‘length of 1D numpy array : ‘, arr.shape[0])
Output:
Shape of 1D numpy array : (8,)
length of 1D numpy array : 8

Get the Dimensions of a Numpy array using NumPy.shape()

Now, we will see the module which provides a function to get the number of elements in a Numpy array along the axis.

numpy.size(arr, axis=None)

We will use this module for getting the dimensions of a 2D and 1D Numpy array.

Get Dimensions of a 2D numpy array using numpy.size()

We will begin with a 2D Numpy array.

Dimensions of a 2D numpy array using numpy.size

Code:

arr2D = np.array([[11 ,12,13,11], [21, 22, 23, 24], [31,32,33,34]])
print('2D Numpy Array')
print(arr2D)

Output:

2D Numpy Array
[[11 12 13 11]
[21 22 23 24]
[31 32 33 34]]

Get a number of rows and columns of this 2D NumPy array:

number of rows and columns of this 2D numpy array

Code:

numOfRows = np.size(arr2D, 0)
# get number of columns in 2D numpy array
numOfColumns = np.size(arr2D, 1)
print('Number of Rows : ', numOfRows)
print('Number of Columns : ', numOfColumns)
Output:
Number of Rows : 3
Number of Columns: 4

Get a total number of elements in this 2D NumPy array:

 total number of elements in this 2D numpy array

Code:

print('Total Number of elements in 2D Numpy array : ', np.size(arr2D))

Output:

Total Number of elements in 2D Numpy array: 12

Get Dimensions of a 3D NumPy array using numpy.size()

Now, we will be working on the 3D Numpy array.

3D Numpy array

Code:

arr3D = np.array([ [[11, 12, 13, 11], [21, 22, 23, 24], [31, 32, 33, 34]],
[[1, 1, 1, 1], [2, 2, 2, 2], [3, 3, 3, 3]] ])
print(arr3D)
Output:
[[[11 12 13 11]
[21 22 23 24]
[31 32 33 34]]
[[ 1 1 1 1]
[ 2 2 2 2]
[ 3 3 3 3]]]

Get a number of elements per axis in 3D NumPy array:

number of elements per axis in 3D numpy array

Code:

print('Axis 0 size : ', np.size(arr3D, 0))
print('Axis 1 size : ', np.size(arr3D, 1))
print('Axis 2 size : ', np.size(arr3D, 2))

Output:

Axis 0 size : 2
Axis 1 size : 3
Axis 2 size : 4

Get the total number of elements in this 3D NumPy array:

total number of elements in this 3D numpy array

Code:

print(‘Total Number of elements in 3D Numpy array : ‘, np.size(arr3D))

Output:

Total Number of elements in 3D Numpy array : 24

Get Dimensions of a 1D NumPy array using numpy.size()

Let us create a 1D array.

Dimensions of a 1D numpy array using numpy.size()

Code:

arr = np.array([4, 5, 6, 7, 8, 9, 10, 11])
print('Length of 1D numpy array : ', np.size(arr))

Output:

Length of 1D numpy array : 8
A complete example is as follows:
import numpy as np
def main():
print('**** Get Dimensions of a 2D numpy array using ndarray.shape ****')
# Create a 2D Numpy array list of list
 arr2D = np.array([[11 ,12,13,11], [21, 22, 23, 24], [31,32,33,34]])
print('2D Numpy Array')
print(arr2D)
 # get number of rows in 2D numpy array
 numOfRows = arr2D.shape[0]
 # get number of columns in 2D numpy array
 numOfColumns = arr2D.shape[1]
print('Number of Rows : ', numOfRows)
print('Number of Columns : ', numOfColumns)
print('Total Number of elements in 2D Numpy array : ', arr2D.shape[0] * arr2D.shape[1])
print('**** Get Dimensions of a 1D numpy array using ndarray.shape ****')
 # Create a Numpy array from list of numbers
arr = np.array([4, 5, 6, 7, 8, 9, 10, 11])
print('Original Array : ', arr)
print('Shape of 1D numpy array : ', arr.shape)
print('length of 1D numpy array : ', arr.shape[0])
print('**** Get Dimensions of a 2D numpy array using np.size() ****')
 # Create a 2D Numpy array list of list
 arr2D = np.array([[11, 12, 13, 11], [21, 22, 23, 24], [31, 32, 33, 34]])
print('2D Numpy Array')
print(arr2D)
 # get number of rows in 2D numpy array
 numOfRows = np.size(arr2D, 0)
 # get number of columns in 2D numpy array
 numOfColumns = np.size(arr2D, 1)
print('Number of Rows : ', numOfRows)
print('Number of Columns : ', numOfColumns)
print('Total Number of elements in 2D Numpy array : ', np.size(arr2D))
print('**** Get Dimensions of a 3D numpy array using np.size() ****')
 # Create a 3D Numpy array list of list of list
 arr3D = np.array([ [[11, 12, 13, 11], [21, 22, 23, 24], [31, 32, 33, 34]],
[[1, 1, 1, 1], [2, 2, 2, 2], [3, 3, 3, 3]] ])
print('3D Numpy Array')
print(arr3D)
print('Axis 0 size : ', np.size(arr3D, 0))
print('Axis 1 size : ', np.size(arr3D, 1))
print('Axis 2 size : ', np.size(arr3D, 2))
print('Total Number of elements in 3D Numpy array : ', np.size(arr3D))
print('Dimension by axis : ', arr3D.shape)
print('**** Get Dimensions of a 1D numpy array using numpy.size() ****')
 # Create a Numpy array from list of numbers
arr = np.array([4, 5, 6, 7, 8, 9, 10, 11])
print('Original Array : ', arr)
print('Length of 1D numpy array : ', np.size(arr))
if __name__ == '__main__':
main()
Output:
**** Get Dimensions of a 2D numpy array using ndarray.shape ****
2D Numpy Array
[[11 12 13 11]
[21 22 23 24]
[31 32 33 34]]
Number of Rows : 3
Number of Columns : 4
Total Number of elements in 2D Numpy array : 12
**** Get Dimensions of a 1D numpy array using ndarray.shape ****
Original Array : [ 4 5 6 7 8 9 10 11]
Shape of 1D numpy array : (8,)
length of 1D numpy array : 8
**** Get Dimensions of a 2D numpy array using np.size() ****
2D Numpy Array
[[11 12 13 11]
[21 22 23 24]
[31 32 33 34]]
Number of Rows : 3
Number of Columns : 4
Total Number of elements in 2D Numpy array : 12
**** Get Dimensions of a 3D numpy array using np.size() ****
3D Numpy Array
[[[11 12 13 11]
[21 22 23 24]
[31 32 33 34]]
[[ 1 1 1 1]
[ 2 2 2 2]
[ 3 3 3 3]]]
Axis 0 size : 2
Axis 1 size : 3
Axis 2 size : 4
Total Number of elements in 3D Numpy array : 24
Dimension by axis : (2, 3, 4)
**** Get Dimensions of a 1D numpy array using numpy.size() ****
Original Array : [ 4 5 6 7 8 9 10 11]
Length of 1D numpy array : 8

I hope you understood this article well.

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