NumPy: Create an array of (3, 4) shape, multiply every element value by 3 and display the new array

NumPy: Array Object Exercise-73 with Solution

Write a NumPy program to create an array of (3, 4) shapes, multiply every element value by 3 and display the result array.

Pictorial Presentation:

Sample Solution:

Python Code:

# Importing the NumPy library and aliasing it as 'np'
import numpy as np

# Creating a 1-dimensional array 'x' with values from 0 to 11 and reshaping it into a 3x4 array
x = np.arange(12).reshape(3, 4)

# Printing a message indicating the original array elements will be shown
print("Original array elements:")

# Printing the original array 'x' with its elements
print(x)

# Using a loop with np.nditer to iterate through each element in the array 'x'
# Setting the elements to 3 times their current value with op_flags set to 'readwrite'
for a in np.nditer(x, op_flags=['readwrite']):
    a[...] = 3 * a  # Multiplying each element by 3

# Printing a message indicating the new array elements after multiplication
print("New array elements:")

# Printing the array 'x' after modifying its elements (each element multiplied by 3)
print(x) 

Sample Output:

Original array elements:                                               
[[ 0  1  2  3]                                                         
 [ 4  5  6  7]                                                         
 [ 8  9 10 11]]                                                        
New array elements:                                                    
[[ 0  3  6  9]                                                         
 [12 15 18 21]                                                         
 [24 27 30 33]]  

Explanation:

In the above code:

• np.arange(12): This function call creates a 1D NumPy array with integers from 0 to 11.
• reshape(3, 4): This method reshapes the 1D array into a 3x4 2D array.
• for a in np.nditer(x, op_flags=['readwrite']):: This part initializes a loop using np.nditer to iterate over each element of the 2D array x. The op_flags=['readwrite'] argument allows the iterator to read and modify the elements in the original array.
• a[...] = 3 * a: Inside the loop, this line multiplies each element of the array by 3 and assigns the result back to the original location in the array.
• Finally print(x) prints the modified 2D array.

Python-Numpy Code Editor:

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