NumPy: Divide each row by a vector element

Last update on March 24 2025 13:36:45 (UTC/GMT +8 hours)

Divide Each Row by Vector

Write a NumPy program to divide each row by a vector element.

Pictorial Presentation:

Sample Solution:

Python Code:

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

# Creating a 2D NumPy array 'x' with repeated rows
x = np.array([[20, 20, 20], [30, 30, 30], [40, 40, 40]])

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

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

# Creating a 1D NumPy array 'v' representing a vector
v = np.array([20, 30, 40])

# Printing a message indicating the vector will be displayed
print("Vector:")

# Printing the vector 'v' with its elements
print(v)

# Performing element-wise division of array 'x' by vector 'v' using broadcasting
# Dividing each row of 'x' by each element of 'v' using 'None' to introduce a new axis for vector 'v'
result = x / v[:, None]

# Printing the result of element-wise division
print(result)

Sample Output:

Original array:                                                        
[[20 20 20]                                                            
 [30 30 30]                                                            
 [40 40 40]]                                                           
Vector:                                                                
[20 30 40]                                                             
[[ 1.  1.  1.]                                                         
 [ 1.  1.  1.]                                                         
 [ 1.  1.  1.]]

Explanation:

In the above exercise –

x = np.array([[20,20,20],[30,30,30],[40,40,40]]): This line creates a 3x3 NumPy array 'x' with rows containing repeated values.

v = np.array([20,30,40]): This line creates a 1D NumPy array 'v' with three elements.

v[:, None]: Reshape the 1D array 'v' to a 2D array with shape (3, 1) by introducing a new axis using 'None' or 'np.newaxis'. The resulting array has dimensions that allow broadcasting with 'x'.

print(x / v[:, None]): Perform element-wise division of 'x' by the reshaped 'v' using broadcasting. Each row of 'x' is divided by the corresponding element of 'v'. The result is a 3x3 array with each row containing ones (since the elements of 'x' are multiples of the corresponding elements in 'v').

For more Practice: Solve these Related Problems:

• Write a NumPy program to divide each row of a 2D array by corresponding elements of a 1D vector using broadcasting.
• Create a function that normalizes each row of a matrix by a provided vector and verifies the output shape.
• Test row-wise division on an array and compare the results with manual element-wise division.
• Implement the division using np.divide and check for correct broadcasting behavior when dimensions differ.

Python-Numpy Code Editor: