NumPy: Combine a one and a two dimensional array together and display their elements

NumPy: Array Object Exercise-74 with Solution

Write a NumPy program to combine a one and two dimensional array together and display their elements.

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 3
x = np.arange(4)

# Printing a message indicating the array 'x' is one-dimensional
print("One dimensional array:")

# Printing the 1-dimensional array 'x'
print(x)

# Creating a 2-dimensional array 'y' with values from 0 to 7 and reshaping it to a 2x4 array
y = np.arange(8).reshape(2, 4)

# Printing a message indicating the array 'y' is two-dimensional
print("Two dimensional array:")

# Printing the 2-dimensional array 'y'
print(y)

# Using a loop with np.nditer to simultaneously iterate through elements of 'x' and 'y'
# Printing each pair of corresponding elements from 'x' and 'y'
for a, b in np.nditer([x, y]):
    print("%d:%d" % (a, b), end=' ')  # Printing pairs of elements from 'x' and 'y' together

# Printing a newline character to separate the output
print() 

Sample Output:

One dimensional array:                                                 
[0 1 2 3]                                                              
Two dimensional array:                                                 
[[0 1 2 3]                                                             
 [4 5 6 7]]                                                            
0:0                                                                    
1:1                                                                    
2:2                                                                    
3:3                                                                    
0:4                                                                    
1:5                                                                    
2:6                                                                    
3:7

Explanation:

In the above code –

np.arange(4): This function call creates a 1D NumPy array x with integers from 0 to 3.

np.arange(8).reshape(2,4): This line creates a 1D NumPy array with integers from 0 to 7 and then reshapes it into a 2x4 2D array y.

for a, b in np.nditer([x,y]):: This line initializes a loop using np.nditer to iterate over both arrays x and y simultaneously. Since x is a 1D array with shape (4,) and y is a 2D array with shape (2, 4), broadcasting rules make them compatible for iteration.

print("%d:%d" % (a,b),): Inside the loop, print() function prints each pair of corresponding elements from both arrays, separated by a colon.

Python-Numpy Code Editor:

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