Jigme Tenzin - Fab Futures - Data Science

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Example 1: Quadratic dataset

import matplotlib.pyplot as plt

# Example: Quadratic dataset
x = [-5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5]
y = [66, 41, 22, 9, 2, 1, 0, 5, 16, 33, 56]

plt.plot(x, y, marker='o')
plt.xlabel("x")
plt.ylabel("y")
plt.title("Quadratic Function Plot")
plt.grid(True)
plt.show()

Example 2: Polynomial Fitting With Noise

What the data represents

import matplotlib.pyplot as plt

x = [-5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5]
y = [-113, -50, -19, -2, 5, 2, -1, 6, 23, 50, 97]

plt.plot(x, y, marker='o')
plt.xlabel("x")
plt.ylabel("y")
plt.title("Cubic Function: y = x³ - 4x + 2")
plt.grid(True)
plt.show()

This graph demonstrates how we can use a polynomial to model real-world data that contains noise (random variation).