Python Coding challenge - Day 423| What is the output of the following Python Code?

 

Step-by-Step Breakdown:

1. Importing NumPy

import numpy as np

NumPy is imported as np to use its numerical functions.

2. Defining the Data Points

x = np.array([1, 2, 3, 4, 5])  

y = np.array([2, 4, 6, 8, 10])  

x and y are NumPy arrays representing a set of data points.

The relationship between x and y follows a linear pattern:

y=2x

This means y is exactly twice the value of x.

3. Performing Linear Regression with np.polyfit

slope, intercept = np.polyfit(x, y, 1)

np.polyfit(x, y, 1) fits a polynomial of degree 1 (a straight line) to the data.

The function finds the best-fit slope (m) and intercept (c) for the equation:

y=mx+c

In this case, since the data follows y = 2x, the computed values will be:

slope = 2.0

intercept = 0.0

4. Printing the Slope

print(slope)

This prints 2.0 since the best-fit line is y = 2x + 0.

Final Output:

2