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

May 6, 2019 / Numpy, Python / By

In this article we will discuss how to count number of elements in a 1D, 2D & 3D Numpy array, also how to count number of rows & columns of a 2D numpy array and number of elements per axis in 3D numpy array.

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

numpy.ndarray.shape

Python’s Numpy Module provides a function to get the dimensions of a Numpy array,

ndarray.shape

It returns the dimension of numpy array as tuple.

Let’s use this to get the shape or dimensions of a 2D & 1D numpy array i.e.

Get Dimensions of a 2D numpy array using ndarray.shape

Let’s create a 2D Numpy array i.e.

# 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)

Output:

Frequently Asked:

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

Get number of rows in this 2D numpy array i.e.

# get number of rows in 2D numpy array
numOfRows = arr2D.shape[0]

print('Number of Rows : ', numOfRows)

Output:

Number of Rows :  3

Get number of columns in this 2D numpy array,

# get number of columns in 2D numpy array
numOfColumns = arr2D.shape[1]

print('Number of Columns : ', numOfColumns)

Output:

Number of Columns :  4

Get total number of elements in this 2D numpy array,

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

Let’s create a 1D Numpy array i.e.

# Create a Numpy array from list of numbers
arr = np.array([4, 5, 6, 7, 8, 9, 10, 11])

Get number of elements of this 1D numpy array i.e.

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()

Python’s Numpy module provides a function to get the number of elements in a Numpy array along axis i.e.

numpy.size(arr, axis=None)

Args: It accepts the numpy array and also the axis along which it needs to count the elements.If axis is not passed then returns the total number of arguments.
Returns: The number of elements along the passed axis.

Let’s use this to get the shape or dimensions of a 2D & 1D numpy array i.e.

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

Let’s create a 2D Numpy array i.e.

# 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)

Output:

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

Get number of rows and columns of this 2D numpy array:

# 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)

Output:

Number of Rows :  3
Number of Columns :  4

Get total number of elements in this 2D numpy array:

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()

Let’s create a 3D Numpy array i.e.

# 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(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 number of elements per axis in 3D numpy array i.e.

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 total number of elements in this 3D numpy array i.e.

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’s create a 1D Numpy array i.e.

# Create a Numpy array from list of numbers
arr = np.array([4, 5, 6, 7, 8, 9, 10, 11])

Get number of elements of this 1D numpy array using numpy.size() i.e.

print('Length of 1D numpy array : ', np.size(arr))

Output:

Length of 1D numpy array :  8

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

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