Page 267 - Robotics and AI class 10
P. 267
years = [2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010]
temperatures = [15.2, 15.5, 15.7, 16.0, 16.2, 16.5, 16.8, 17.0, 17.2, 17.5,
17.8]
plt.figure(figsize=(10, 6))
plt.scatter(years, temperatures, color='blue')
plt.title('Year vs Average Temperature')
plt.xlabel('Year')
plt.ylabel('Average Temperature (°C)')
plt.grid(True)
plt.show()
Output:
Next, let's perform linear regression on the data to predict average temperatures for future years:
from sklearn.linear_model import LinearRegression
import numpy as np
X = np.array(years).reshape(-1, 1)
y = np.array(temperatures)
# Create and fit the linear regression model
model = LinearRegression()
model.fit(X, y)
# Predict temperatures for future years
future_years = np.array([2021, 2022, 2023, 2024, 2025]).reshape(-1, 1) predicted_
temperatures = model.predict(future_years)
print("Predicted Temperatures for Future Years:")
for year, temp in zip(future_years, predicted_temperatures):
print(f"Year: {year[0]}, Predicted Temperature: {temp:.2f} °C")
Assignment 265

