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NumPy: Get the number of items, array dimensions, number of array dimensions and the memory size of each element of a given array

Get array metadata (dimensions, size, etc.).

Write a NumPy program to get the number of items, array dimensions, number of array dimensions and the memory size of each element of a given array.

Sample Solution:

Python Code:

# Importing NumPy library
import numpy as np

# Creating a 2D NumPy array
array_nums = np.array([[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12]])

# Printing the original array
print("Original array:")
print(array_nums)

# Finding the number of items in the array
print("\nNumber of items of the said array:")
print(array_nums.size)

# Retrieving the shape of the array (number of rows and columns)
print("\nArray dimensions:")
print(array_nums.shape)

# Finding the number of dimensions of the array
print("\nNumber of array dimensions:")
print(array_nums.ndim)

# Determining the memory size (in bytes) of each array element
print("\nMemory size of each element of the said array")
print(array_nums.itemsize)

Sample Output:

Original array:
[[ 1  2  3  4]
 [ 5  6  7  8]
 [ 9 10 11 12]]

Number of items of the said array:
12

Array dimensions:
(3, 4)

Number of array dimensions:
2

Memory size of each element of the said array
8

Explanation:

In the above code -

  • array_nums = np.array([[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12]]) creates a 2-dimensional NumPy array with 3 rows and 4 columns.
  • print(array_nums) prints the array.
  • print(array_nums.size) prints the total number of elements in the array (3 rows * 4 columns = 12).
  • print(array_nums.shape) prints the shape of the array as a tuple, in this case (3, 4), indicating 3 rows and 4 columns.
  • print(array_nums.ndim) prints the number of dimensions (axes) of the array, which is 2 for a 2-dimensional array.
  • print(array_nums.itemsize) prints the size (in bytes) of each element in the array.

Python-Numpy Code Editor: