# Print dimensions of numpy array – How to get Numpy Array Dimensions using numpy.ndarray.shape & numpy.ndarray.size() in Python

Print dimensions of numpy array: 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

Get dimensions of numpy array: 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.

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:

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:

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:

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.

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.

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:

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:

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.

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:

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:

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.

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.